{"group":{"id":1,"name":"Community","lockable":false,"created_at":"2012-01-18T18:02:15.000Z","updated_at":"2026-05-26T00:16:20.000Z","description":"Problems submitted by members of the MATLAB Central community.","is_default":true,"created_by":161519,"badge_id":null,"featured":false,"trending":false,"solution_count_in_trending_period":0,"trending_last_calculated":"2026-05-26T00:00:00.000Z","image_id":null,"published":true,"community_created":false,"status_id":2,"is_default_group_for_player":false,"deleted_by":null,"deleted_at":null,"restored_by":null,"restored_at":null,"description_opc":null,"description_html":null,"published_at":null},"problems":[{"id":811,"title":"Genome Sequence 004: Long 3rd Generation Segment Correction","description":"The Melopsittacus undulates genome, Parrot Budgerigar, was successfully sequenced in July 2012 using long 3rd Gen sequences provided by \u003chttp://www.pacificbiosciences.com/ PacBio\u003e. The \u003chttp://assemblathon.org/a-parrot-a-fish-and-a-snake-walk-into-a-bar Assemblathon Genome Contest\u003e led the team of Phillippy, Koren and Jarvis to successfully \u003chttp://www.sciencedaily.com/releases/2012/07/120702210229.htm Sequence Parrot DNA\u003e using the PacBio 3rd Generation data and Illumina 2nd Gen data.\r\n\r\nThe 3rd gen PacBio data is very long, 1K-20K, but has 15% error rate. The Illumina data is 100-500 long with \u003c1% error rate. Jarvis and his team combined this data to achieve \u003c 0.1% error rate.\r\n\r\nGenome Challenge 004 is the correction of simplified PacBio simulated reads with high error rate.\r\n\r\n*Input:* \r\n\r\nCall 1: empty array, segment Width, Flag=0\r\n\r\nCall 2: N PacBio DNA vectors (N x width), Segment Width, Flag=1\r\n\r\n*Output:* \r\n\r\nCall 1: empty vector, Number of Requested Vectors\r\n\r\nCall 2: Corrected DNA vector, Number of Requested Vectors\r\n\r\n*Score:* Number of N vectors used to produce correct vector for w=1024 case\r\n\r\nThe first call to the PacBio_fix routine returns the number of vectors requested to produce a final product. This may be a function of w.\r\n\r\nThe second call to PacBio_fix will have a DNA matix (N x width) and flag=1.\r\n\r\nThe response to the second call is the fixed DNA sequence, vector of width w.\r\n\r\n*example:*\r\nFirst call return : N=3\r\n\r\n  01230123111122223333 Truth\r\n  Input example\r\n  01232123112122221332 Injected errors\r\n  01130123111122123323\r\n  11230133121122223333\r\n\r\n  Output: \r\n  01230123111122223333 Truth, hopefully\r\n\r\n\r\nThis data is simplified by only having simple substitutions and the data sets are provided pre-aligned. \r\n\r\nThe real PacBio data is quite a bit more complicated. Values may be added, deleted, substituted, and are of varying lengths. This causes alignment issues.\r\n\r\nFollow-Up Challenges: Sample Data from the PacBio site for \u003chttp://www.cbcb.umd.edu/software/PBcR/ Lambda Phage\u003e will be molded into various Challenges. Possible challenges are correcting individual long segments and assembling multiple long segments into the full Lambda Phage genome. The Parrot genome is too big for Cody to solve in 50 seconds.\r\n","description_html":"\u003cp\u003eThe Melopsittacus undulates genome, Parrot Budgerigar, was successfully sequenced in July 2012 using long 3rd Gen sequences provided by \u003ca href=\"http://www.pacificbiosciences.com/\"\u003ePacBio\u003c/a\u003e. The \u003ca href=\"http://assemblathon.org/a-parrot-a-fish-and-a-snake-walk-into-a-bar\"\u003eAssemblathon Genome Contest\u003c/a\u003e led the team of Phillippy, Koren and Jarvis to successfully \u003ca href=\"http://www.sciencedaily.com/releases/2012/07/120702210229.htm\"\u003eSequence Parrot DNA\u003c/a\u003e using the PacBio 3rd Generation data and Illumina 2nd Gen data.\u003c/p\u003e\u003cp\u003eThe 3rd gen PacBio data is very long, 1K-20K, but has 15% error rate. The Illumina data is 100-500 long with \u0026lt;1% error rate. Jarvis and his team combined this data to achieve \u0026lt; 0.1% error rate.\u003c/p\u003e\u003cp\u003eGenome Challenge 004 is the correction of simplified PacBio simulated reads with high error rate.\u003c/p\u003e\u003cp\u003e\u003cb\u003eInput:\u003c/b\u003e\u003c/p\u003e\u003cp\u003eCall 1: empty array, segment Width, Flag=0\u003c/p\u003e\u003cp\u003eCall 2: N PacBio DNA vectors (N x width), Segment Width, Flag=1\u003c/p\u003e\u003cp\u003e\u003cb\u003eOutput:\u003c/b\u003e\u003c/p\u003e\u003cp\u003eCall 1: empty vector, Number of Requested Vectors\u003c/p\u003e\u003cp\u003eCall 2: Corrected DNA vector, Number of Requested Vectors\u003c/p\u003e\u003cp\u003e\u003cb\u003eScore:\u003c/b\u003e Number of N vectors used to produce correct vector for w=1024 case\u003c/p\u003e\u003cp\u003eThe first call to the PacBio_fix routine returns the number of vectors requested to produce a final product. This may be a function of w.\u003c/p\u003e\u003cp\u003eThe second call to PacBio_fix will have a DNA matix (N x width) and flag=1.\u003c/p\u003e\u003cp\u003eThe response to the second call is the fixed DNA sequence, vector of width w.\u003c/p\u003e\u003cp\u003e\u003cb\u003eexample:\u003c/b\u003e\r\nFirst call return : N=3\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e01230123111122223333 Truth\r\nInput example\r\n01232123112122221332 Injected errors\r\n01130123111122123323\r\n11230133121122223333\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003eOutput: \r\n01230123111122223333 Truth, hopefully\r\n\u003c/pre\u003e\u003cp\u003eThis data is simplified by only having simple substitutions and the data sets are provided pre-aligned.\u003c/p\u003e\u003cp\u003eThe real PacBio data is quite a bit more complicated. Values may be added, deleted, substituted, and are of varying lengths. This causes alignment issues.\u003c/p\u003e\u003cp\u003eFollow-Up Challenges: Sample Data from the PacBio site for \u003ca href=\"http://www.cbcb.umd.edu/software/PBcR/\"\u003eLambda Phage\u003c/a\u003e will be molded into various Challenges. Possible challenges are correcting individual long segments and assembling multiple long segments into the full Lambda Phage genome. The Parrot genome is too big for Cody to solve in 50 seconds.\u003c/p\u003e","function_template":"function [M_fix,N]=PacBio_fix(M,w,flag)\r\n% 1st Call\r\n% M is empty\r\n% w is width of segment\r\n% flag is 0\r\n% Ouput is N, the number of segments requested to fix the segment\r\n% 2nd Call\r\n% M is an Nxw array of values [0:3]\r\n\r\n M_fix=[];\r\n N=1; % needed for 2nd call with flag==1\r\n if flag==0 % Requested number of Segments\r\n  N=1;\r\n  return;\r\n end\r\n\r\nM_fix=M(1,:);\r\n\r\n\r\nend","test_suite":"%%\r\nfeval(@assignin,'caller','score',0);\r\n%%\r\nM=[];\r\nflag=0;\r\nw=100;\r\n[M_fix,N]=PacBio_fix(M,w,flag);\r\n\r\nM_truth=randi(4,1,w,'uint8')-1;\r\nM=repmat(M_truth,N,1);\r\n\r\n% Apply 15% substitution error\r\nqerr=floor(.15*N*w);\r\nerrvec=randi(N*w,qerr,1);\r\nerrval=randi(4,qerr,1)-1;\r\n\r\nM(errvec)=errval;\r\n\r\nflag=1;\r\ntic\r\n[M_fix,N]=PacBio_fix(M,w,flag);\r\ntoc\r\n\r\nassert(isequal(M_fix,M_truth),sprintf('Error Count=%i',sum(M_fix~=M_truth)))\r\n%%\r\nM=[];\r\nflag=0;\r\nw=6144;\r\n[M_fix,N]=PacBio_fix(M,w,flag);\r\n\r\nM_truth=randi(4,1,w,'uint8')-1;\r\nM=repmat(M_truth,N,1);\r\n\r\n% Apply 15% substitution error\r\nqerr=floor(.15*N*w);\r\nerrvec=randi(N*w,qerr,1);\r\nerrval=randi(4,qerr,1)-1;\r\n\r\nM(errvec)=errval;\r\n\r\nflag=1;\r\ntic\r\n[M_fix,N]=PacBio_fix(M,w,flag);\r\ntoc\r\n\r\nassert(isequal(M_fix,M_truth),sprintf('Error Count=%i',sum(M_fix~=M_truth)))\r\n\r\n%%\r\n% Size Performance is based on w=1024 case\r\nM=[];\r\nflag=0;\r\nw=1024;\r\n[M_fix,N]=PacBio_fix(M,w,flag);\r\n\r\nM_truth=randi(4,1,w,'uint8')-1;\r\nM=repmat(M_truth,N,1);\r\n\r\n% Apply 15% substitution error\r\nqerr=floor(.15*N*w);\r\nerrvec=randi(N*w,qerr,1);\r\nerrval=randi(4,qerr,1)-1;\r\n\r\nM(errvec)=errval;\r\n\r\nflag=1;\r\ntic\r\n[M_fix,not_N]=PacBio_fix(M,w,flag);\r\ntoc\r\n\r\nassert(isequal(M_fix,M_truth),sprintf('Error Count=%i',sum(M_fix~=M_truth)))\r\n\r\nfeval(@assignin,'caller','score',min(20,N));\r\n\r\n\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":3,"test_suite_updated_at":"2012-10-08T02:30:34.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-07-01T05:26:57.000Z","updated_at":"2026-05-26T02:20:13.000Z","published_at":"2012-10-08T02:29:50.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Melopsittacus undulates genome, Parrot Budgerigar, was successfully sequenced in July 2012 using long 3rd Gen sequences provided by\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://www.pacificbiosciences.com/\\\"\u003e\u003cw:r\u003e\u003cw:t\u003ePacBio\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e. The\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://assemblathon.org/a-parrot-a-fish-and-a-snake-walk-into-a-bar\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eAssemblathon Genome Contest\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e led the team of Phillippy, Koren and Jarvis to successfully\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://www.sciencedaily.com/releases/2012/07/120702210229.htm\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eSequence Parrot DNA\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e using the PacBio 3rd Generation data and Illumina 2nd Gen data.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe 3rd gen PacBio data is very long, 1K-20K, but has 15% error rate. The Illumina data is 100-500 long with \u0026lt;1% error rate. Jarvis and his team combined this data to achieve \u0026lt; 0.1% error rate.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGenome Challenge 004 is the correction of simplified PacBio simulated reads with high error rate.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInput:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCall 1: empty array, segment Width, Flag=0\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCall 2: N PacBio DNA vectors (N x width), Segment Width, Flag=1\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCall 1: empty vector, Number of Requested Vectors\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCall 2: Corrected DNA vector, Number of Requested Vectors\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eScore:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e Number of N vectors used to produce correct vector for w=1024 case\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe first call to the PacBio_fix routine returns the number of vectors requested to produce a final product. This may be a function of w.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe second call to PacBio_fix will have a DNA matix (N x width) and flag=1.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe response to the second call is the fixed DNA sequence, vector of width w.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eexample:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e First call return : N=3\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[01230123111122223333 Truth\\nInput example\\n01232123112122221332 Injected errors\\n01130123111122123323\\n11230133121122223333\\n\\nOutput: \\n01230123111122223333 Truth, hopefully]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis data is simplified by only having simple substitutions and the data sets are provided pre-aligned.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe real PacBio data is quite a bit more complicated. Values may be added, deleted, substituted, and are of varying lengths. This causes alignment issues.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFollow-Up Challenges: Sample Data from the PacBio site for\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://www.cbcb.umd.edu/software/PBcR/\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eLambda Phage\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e will be molded into various Challenges. Possible challenges are correcting individual long segments and assembling multiple long segments into the full Lambda Phage genome. The Parrot genome is too big for Cody to solve in 50 seconds.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":738,"title":"Criss_Cross_010 : Unique elements, Square array, Words in one array","description":"Criss Cross matrix puzzle - Square matrix, Unique elements, Single Word List\r\n\r\nArrange the \"words\" into a solid square such that all words are used.\r\n\r\nGiven an array of words make the original Square or Square Transpose.\r\n\r\nWords are left to Right or Top to Bottom. No fliplr or flipud.\r\n\r\n*Example:*\r\n\r\nM_orig = [1 2 3; 4 5 6; 7 8 9]\r\n\r\nvr = [1 2 3; 4 5 6; 7 8 9]\r\n\r\nvc = [1 2 3; 4 5 6; 7 8 9]\r\n\r\n*Inputs:*\r\n\r\nw = [1 2 3; 4 5 6; 7 8 9;1 4 7; 2 5 8; 3 6 9]\r\n\r\nsorted w gives\r\n\r\nw = [1 2 3; 1 4 7; 2 5 8; 3 6 9; 4 5 6; 7 8 9]\r\n\r\n\r\n*Output:*\r\n\r\nM_out = [1 2 3; 4 5 6; 7 8 9] or\r\n\r\nM_out=[1 4 7; 2 5 8; 3 6 9]\r\n\r\n\r\nMax size : 256\r\n\r\nThis is the second in the Criss Cross puzzles series.\r\n\r\nFollow up puzzles will have non-unique values and quite a few other variations.\r\n","description_html":"\u003cp\u003eCriss Cross matrix puzzle - Square matrix, Unique elements, Single Word List\u003c/p\u003e\u003cp\u003eArrange the \"words\" into a solid square such that all words are used.\u003c/p\u003e\u003cp\u003eGiven an array of words make the original Square or Square Transpose.\u003c/p\u003e\u003cp\u003eWords are left to Right or Top to Bottom. No fliplr or flipud.\u003c/p\u003e\u003cp\u003e\u003cb\u003eExample:\u003c/b\u003e\u003c/p\u003e\u003cp\u003eM_orig = [1 2 3; 4 5 6; 7 8 9]\u003c/p\u003e\u003cp\u003evr = [1 2 3; 4 5 6; 7 8 9]\u003c/p\u003e\u003cp\u003evc = [1 2 3; 4 5 6; 7 8 9]\u003c/p\u003e\u003cp\u003e\u003cb\u003eInputs:\u003c/b\u003e\u003c/p\u003e\u003cp\u003ew = [1 2 3; 4 5 6; 7 8 9;1 4 7; 2 5 8; 3 6 9]\u003c/p\u003e\u003cp\u003esorted w gives\u003c/p\u003e\u003cp\u003ew = [1 2 3; 1 4 7; 2 5 8; 3 6 9; 4 5 6; 7 8 9]\u003c/p\u003e\u003cp\u003e\u003cb\u003eOutput:\u003c/b\u003e\u003c/p\u003e\u003cp\u003eM_out = [1 2 3; 4 5 6; 7 8 9] or\u003c/p\u003e\u003cp\u003eM_out=[1 4 7; 2 5 8; 3 6 9]\u003c/p\u003e\u003cp\u003eMax size : 256\u003c/p\u003e\u003cp\u003eThis is the second in the Criss Cross puzzles series.\u003c/p\u003e\u003cp\u003eFollow up puzzles will have non-unique values and quite a few other variations.\u003c/p\u003e","function_template":"function M_out = Criss_Cross(w)\r\n\r\n M_out=zeros(size(w,2));\r\n \r\nend","test_suite":"%%\r\nformat long\r\nformat compact\r\nseed=clock;\r\nseed=1000*seed(6);\r\nrng(seed);\r\n\r\nn=4;\r\n% Create a Unique element square array\r\nM=randperm(n*n);\r\nM=reshape(M,n,n)\r\n\r\nvr=M(1:n,:);\r\nvc=M(:,1:n);\r\n\r\nw=[vr;vc'];\r\nw=sortrows(w);\r\n\r\nM_out=Criss_Cross(w)\r\n\r\nassert(isequal(M,M_out)||isequal(M',M_out));\r\n%%\r\nseed=clock;\r\nseed=1000*seed(6);\r\nrng(seed);\r\n\r\nn=8;\r\n% Create a Unique element square array\r\nM=randperm(n*n);\r\nM=reshape(M,n,n)\r\n\r\nvr=M(1:n,:);\r\nvc=M(:,1:n);\r\n\r\nw=[vr;vc'];\r\nw=sortrows(w);\r\n\r\nM_out=Criss_Cross(w)\r\n\r\nassert(isequal(M,M_out)||isequal(M',M_out));\r\n%%\r\nseed=clock;\r\nseed=1000*seed(6);\r\nrng(seed);\r\n\r\nn=16;\r\n% Create a Unique element square array\r\nM=randperm(n*n);\r\nM=reshape(M,n,n);\r\n\r\nvr=M(1:n,:);\r\nvc=M(:,1:n);\r\n\r\nw=[vr;vc'];\r\nw=sortrows(w);\r\n\r\ntic\r\nM_out=Criss_Cross(w);\r\ntoc\r\n\r\nassert(isequal(M,M_out)||isequal(M',M_out));\r\n%%\r\nseed=clock;\r\nseed=1000*seed(6);\r\nrng(seed);\r\n\r\nn=16;\r\n% Create a Unique element square array\r\nM=randperm(n*n);\r\nM=reshape(M,n,n);\r\n\r\nvr=M(1:n,:);\r\nvc=M(:,1:n);\r\n\r\nw=[vr;vc'];\r\nw=sortrows(w);\r\n\r\ntic\r\nM_out=Criss_Cross(w);\r\ntoc\r\n\r\nassert(isequal(M,M_out)||isequal(M',M_out));\r\n%%\r\nn=256;\r\n% Create a Unique element square array\r\nM=randperm(n*n);\r\nM=reshape(M,n,n);\r\n\r\nvr=M(1:n,:);\r\nvc=M(:,1:n);\r\n\r\nw=[vr;vc'];\r\nw=sortrows(w);\r\n\r\ntic\r\nM_out=Criss_Cross(w);\r\ntoc\r\n\r\nassert(isequal(M,M_out)||isequal(M',M_out));","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":9,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2012-06-03T20:11:23.000Z","updated_at":"2026-05-26T04:33:51.000Z","published_at":"2012-06-03T21:38:39.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCriss Cross matrix puzzle - Square matrix, Unique elements, Single Word List\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eArrange the \\\"words\\\" into a solid square such that all words are used.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven an array of words make the original Square or Square Transpose.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWords are left to Right or Top to Bottom. No fliplr or flipud.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eExample:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eM_orig = [1 2 3; 4 5 6; 7 8 9]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003evr = [1 2 3; 4 5 6; 7 8 9]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003evc = [1 2 3; 4 5 6; 7 8 9]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInputs:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ew = [1 2 3; 4 5 6; 7 8 9;1 4 7; 2 5 8; 3 6 9]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003esorted w gives\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ew = [1 2 3; 1 4 7; 2 5 8; 3 6 9; 4 5 6; 7 8 9]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eM_out = [1 2 3; 4 5 6; 7 8 9] or\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eM_out=[1 4 7; 2 5 8; 3 6 9]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eMax size : 256\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis is the second in the Criss Cross puzzles series.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFollow up puzzles will have non-unique values and quite a few other variations.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":61312,"title":"Electric Power Steering (EPS) Motor Torque with Efficiency","description":"In EPS systems, the motor must generate additional torque to compensate for system losses.\r\nGiven Required assist torque at rack Ta and Mechanical efficiency η (0 \u003c η ≤ 1)\r\nCompute required motor torque Tm.\r\n","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 110.906px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 467.484px 55.4531px; transform-origin: 467.496px 55.4531px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIn EPS systems, the motor must generate additional torque to compensate for system losses.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven Required assist torque at rack \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eTa \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eand\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003e \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eMechanical efficiency \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eη (0 \u0026lt; η ≤ 1)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eCompute required motor torque \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eTm\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function Tm = epsMotorTorque(Ta,eta)\r\nTm = 0;\r\nend","test_suite":"%%\r\nTa = 10; eta = 0.9;\r\nTm_expected = Ta / eta;\r\nassert(abs(epsMotorTorque(Ta,eta) - Tm_expected) \u003c 1e-6)\r\n\r\n%%\r\nTa = 15; eta = 0.85;\r\nTm_expected = Ta / eta;\r\nassert(abs(epsMotorTorque(Ta,eta) - Tm_expected) \u003c 1e-6)\r\n\r\n%%\r\nTa = 8; eta = 0.8;\r\nTm_expected = Ta / eta;\r\nassert(abs(epsMotorTorque(Ta,eta) - Tm_expected) \u003c 1e-6)","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":2305225,"edited_by":2305225,"edited_at":"2026-04-28T09:46:20.000Z","deleted_by":null,"deleted_at":null,"solvers_count":27,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-04-28T09:46:15.000Z","updated_at":"2026-05-24T20:53:49.000Z","published_at":"2026-04-28T09:46:20.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIn EPS systems, the motor must generate additional torque to compensate for system losses.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven Required assist torque at rack \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eTa \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr/\u003e\u003cw:t\u003eand\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003eMechanical efficiency \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eη (0 \u0026lt; η ≤ 1)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCompute required motor torque \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eTm\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61331,"title":"Move Array Element by Offset with Optional Ring Mode","description":"Move Element by Offset\r\nWrite a function moveab(x, A, B, option) that moves the element at index A in array x by B positions.\r\nPositive B moves the element to the right \r\nNegative B moves the element to the left \r\nThe relative order of all other elements must be preserved \r\nUse 1-based indexing \r\nPhilosophy:\r\nWhen moving elements in an array, a special case occurs when end elements can either move to the next index in the array or move by its relative postion between other elements. When the end element is moved by one space, it can then wrap and move to the first index in the array, however, the order of the elements has not changed. With the option of ring behavior, end elements will wrap but also move as intended by moving to the second index instead of the first. This is also maintained for reverse move options.\r\nDefault behavior:\r\nRemove the element at index A and reinsert it B positions away in the array \r\nIf the shift goes past either end, wrap around to the other side \r\nLarge values of B must wrap correctly (e.g., use modulo with the array length) \r\nDefault wrapping acts as follows:  x = [1 2 3]; moveab(x, 3, 1) → [3 1 2]        \r\nExamples:\r\nx = [1 2 3 4 5 6 7 8]; moveab(x, 3, 3) → [1 2 4 5 6 3 7 8]\r\nx = [1 2 3]; moveab(x, 3, 1) → [3 1 2]\r\n'ring' option for wrapping:\r\nThe default simply wrapping simply shifts the last element to the first, but when the array to treated as a ring, the element was never moved by 1 space, the order was never changed. The 'ring' option moves the last element by 1 space in a ring, resulting in the following behavior:  x = [1 2 3]; moveab(x, 3, 1,'ring') → [1 3 2]\r\nMoving backwards in 'ring' mode:  x = [1 2 3]; moveab(x, 1, -1,'ring') → [3 1 2]. \r\nMoving backwards in default mode: x = [1 2 3]; moveab(x, 1, -1)        → [2 3 1]. \r\n    \r\nExamples (comparison of ring and default mode):\r\nx = [1 2 3]; moveab(x, 3, 1) → [3 1 2]  \r\nx = [1 2 3]; moveab(x, 3, 1, 'ring') → [1 3 2]\r\nx = [1 2 3]; moveab(x, 1, -1) → [2 1 3] \r\nx = [1 2 3]; moveab(x, 1, -1, 'ring') → [2 1 3]\r\nx = 1:10; moveab(x, 10, 1) → [10 1 2 3 4 5 6 7 8 9]\r\nx = 1:10; moveab(x, 10, 1, 'ring') → [1 10 2 3 4 5 6 7 8 9]\r\nx = 1:10; moveab(x, 1, -1) → [2 3 4 5 6 7 8 9 10 1]\r\nx = 1:10; moveab(x, 1, -1, 'ring') → [2 3 4 5 6 7 8 9 1 10]","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 967.847px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 469.499px 483.919px; transform-origin: 469.499px 483.923px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 20.9961px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 445.5px 10.498px; text-align: left; transform-origin: 445.504px 10.498px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; 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margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWrite a function \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003emoveab(x, A, B, option)\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e that moves the element at index \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eA\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e in array \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ex\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e by \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eB\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e positions.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cul style=\"block-size: 81.7383px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 452.498px 40.8691px; transform-origin: 452.502px 40.8691px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003ePositive \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eB\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e moves the element to the right \u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eNegative \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eB\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e moves the element to the left \u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe relative order of all other elements must be preserved \u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eUse 1-based indexing \u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv style=\"block-size: 20.9961px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 445.5px 10.498px; text-align: left; transform-origin: 445.504px 10.498px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003ePhilosophy:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 83.9844px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 445.5px 41.9922px; text-align: left; transform-origin: 445.504px 41.9922px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWhen moving elements in an array, a special case occurs when end elements can either move to the next index in the array or move by its relative postion between other elements. When the end element is moved by one space, it can then wrap and move to the first index in the array, however, the order of the elements has not changed. With the option of ring behavior, end elements will wrap but also move as intended by moving to the second index instead of the first. This is also maintained for reverse move options.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.9961px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 445.5px 10.498px; text-align: left; transform-origin: 445.504px 10.498px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eDefault behavior:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cul style=\"block-size: 81.7383px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 452.498px 40.8691px; transform-origin: 452.502px 40.8691px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eRemove the element at index \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eA\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e and reinsert it \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eB\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e positions away in the array \u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIf the shift goes past either end, wrap around to the other side \u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eLarge values of \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eB\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e must wrap correctly (e.g., use modulo with the array length) \u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eDefault wrapping acts as follows:  \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ex = [1 2 3]; moveab(x, 3, 1)\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e → \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[3 1 2]\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e        \u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv style=\"block-size: 20.9961px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 445.5px 10.498px; text-align: left; transform-origin: 445.504px 10.498px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eExamples:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cul style=\"block-size: 40.8691px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 452.498px 20.4346px; transform-origin: 452.502px 20.4346px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ex = [1 2 3 4 5 6 7 8]; moveab(x, 3, 3)\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e → \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[1 2 4 5 6 3 7 8]\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ex = [1 2 3]; moveab(x, 3, 1)\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e → \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[3 1 2]\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv style=\"block-size: 20.9961px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 445.5px 10.498px; text-align: left; transform-origin: 445.504px 10.498px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003e'ring' option for wrapping:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cul style=\"block-size: 61.3037px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 452.498px 30.6478px; transform-origin: 452.502px 30.6519px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 30.6478px; text-align: left; transform-origin: 424.504px 30.6519px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe default simply wrapping simply shifts the last element to the first, but when the array to treated as a ring, the element was never moved by 1 space, the order was never changed. The 'ring' option moves the last element by 1 space in a ring, resulting in the following behavior:  \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ex = [1 2 3]; moveab(x, 3, 1,'ring')\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e → \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[1 3 2]\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cul style=\"block-size: 40.8691px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 452.498px 20.4346px; transform-origin: 452.502px 20.4346px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eMoving backwards in 'ring' mode:  x = [1 2 3]; moveab(x, 1, -1,'ring')\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e → \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[3 1 2]. \u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eMoving backwards in default mode: x = [1 2 3]; moveab(x, 1, -1)       \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e → \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[2 3 1]. \u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv style=\"block-size: 20.9961px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 445.5px 10.498px; text-align: left; transform-origin: 445.504px 10.498px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e    \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.9961px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 445.5px 10.498px; text-align: left; transform-origin: 445.504px 10.498px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eExamples (comparison of ring and default mode):\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cul style=\"block-size: 40.8691px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 452.498px 20.4346px; transform-origin: 452.502px 20.4346px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ex = [1 2 3]; moveab(x, 3, 1)\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e → \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[3 1 2]  \u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ex = [1 2 3]; moveab(x, 3, 1, 'ring')\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e → \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[1 3 2]\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cul style=\"block-size: 40.8691px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 452.498px 20.4346px; transform-origin: 452.502px 20.4346px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ex = [1 2 3]; moveab(x, 1, -1)\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e → \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[2 1 3] \u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ex = [1 2 3]; moveab(x, 1, -1, 'ring')\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e → \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[2 1 3]\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cul style=\"block-size: 40.8691px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 452.498px 20.4346px; transform-origin: 452.502px 20.4346px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ex = 1:10; moveab(x, 10, 1)\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e → \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[10 1 2 3 4 5 6 7 8 9]\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ex = 1:10; moveab(x, 10, 1, 'ring')\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e → \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[1 10 2 3 4 5 6 7 8 9]\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cul style=\"block-size: 40.8691px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 452.498px 20.4346px; transform-origin: 452.502px 20.4346px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ex = 1:10; moveab(x, 1, -1)\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e → \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[2 3 4 5 6 7 8 9 10 1]\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ex = 1:10; moveab(x, 1, -1, 'ring')\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e → \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[2 3 4 5 6 7 8 9 1 10]\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function x2 = moveab(x)\r\n  x2 = x;\r\nend","test_suite":"%%\r\n% Basic right move (default)\r\nx = 1:8;\r\ny_correct = [1 2 4 5 6 3 7 8];\r\nassert(isequal(moveab(x,3,3),y_correct))\r\n\r\n%%\r\n% End wrap (default)\r\nx = 1:10;\r\ny_correct = [10 1 2 3 4 5 6 7 8 9];\r\nassert(isequal(moveab(x,10,1),y_correct))\r\n\r\n%%\r\n% End wrap ('ring')\r\nx = 1:10;\r\ny_correct = [1 10 2 3 4 5 6 7 8 9];\r\nassert(isequal(moveab(x,10,1,'ring'),y_correct))\r\n\r\n%%\r\n% Negative move on first element (default)\r\nx = 1:10;\r\ny_correct = [2 3 4 5 6 7 8 9 10 1];\r\nassert(isequal(moveab(x,1,-1),y_correct))\r\n\r\n%%\r\n% Negative move on first element ('ring')\r\nx = 1:10;\r\ny_correct = [2 3 4 5 6 7 8 9 1 10];\r\nassert(isequal(moveab(x,1,-1,'ring'),y_correct))\r\n\r\n%%\r\n% Large positive B (default, modulo behavior)\r\nx = 1:10;\r\ny_correct = moveab(x,3,7);\r\nassert(isequal(moveab(x,3,57),y_correct))\r\n\r\n%%\r\n% Large negative B ('ring', modulo behavior)\r\nx = 1:10;\r\ny_correct = [2 3 4 5 6 7 8 9 1 10]; % same as B = -1\r\nassert(isequal(moveab(x,1,-11,'ring'),y_correct))","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":31885,"edited_by":31885,"edited_at":"2026-05-06T17:12:22.000Z","deleted_by":null,"deleted_at":null,"solvers_count":4,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-05T19:32:54.000Z","updated_at":"2026-05-27T06:45:02.000Z","published_at":"2026-05-05T20:40:10.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eMove Element by Offset\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWrite a function \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003emoveab(x, A, B, option)\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e that moves the element at index \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eA\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e in array \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e by \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eB\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e positions.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ePositive \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eB\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e moves the element to the right \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNegative \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eB\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e moves the element to the left \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe relative order of all other elements must be preserved \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eUse 1-based indexing \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ePhilosophy:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr/\u003e\u003cw:t\u003eWhen moving elements in an array, a special case occurs when end elements can either move to the next index in the array or move by its relative postion between other elements. When the end element is moved by one space, it can then wrap and move to the first index in the array, however, the order of the elements has not changed. With the option of ring behavior, end elements will wrap but also move as intended by moving to the second index instead of the first. This is also maintained for reverse move options.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eDefault behavior:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eRemove the element at index \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eA\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e and reinsert it \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eB\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e positions away in the array \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf the shift goes past either end, wrap around to the other side \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eLarge values of \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eB\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e must wrap correctly (e.g., use modulo with the array length) \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eDefault wrapping acts as follows:  \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex = [1 2 3]; moveab(x, 3, 1)\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e → \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[3 1 2]\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e        \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eExamples:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex = [1 2 3 4 5 6 7 8]; moveab(x, 3, 3)\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e → \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[1 2 4 5 6 3 7 8]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex = [1 2 3]; moveab(x, 3, 1)\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e → \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[3 1 2]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e'ring' option for wrapping:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe default simply wrapping simply shifts the last element to the first, but when the array to treated as a ring, the element was never moved by 1 space, the order was never changed. The 'ring' option moves the last element by 1 space in a ring, resulting in the following behavior:  \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex = [1 2 3]; moveab(x, 3, 1,'ring')\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e → \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[1 3 2]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eMoving backwards in 'ring' mode:  x = [1 2 3]; moveab(x, 1, -1,'ring')\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e → \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[3 1 2]. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eMoving backwards in default mode: x = [1 2 3]; moveab(x, 1, -1)       \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e → \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[2 3 1]. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e    \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eExamples (comparison of ring and default mode):\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex = [1 2 3]; moveab(x, 3, 1)\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e → \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[3 1 2]  \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex = [1 2 3]; moveab(x, 3, 1, 'ring')\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e → \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[1 3 2]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex = [1 2 3]; moveab(x, 1, -1)\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e → \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[2 1 3] \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex = [1 2 3]; moveab(x, 1, -1, 'ring')\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e → \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[2 1 3]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex = 1:10; moveab(x, 10, 1)\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e → \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[10 1 2 3 4 5 6 7 8 9]\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex = 1:10; moveab(x, 10, 1, 'ring')\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e → \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[1 10 2 3 4 5 6 7 8 9]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex = 1:10; moveab(x, 1, -1)\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e → \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[2 3 4 5 6 7 8 9 10 1]\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex = 1:10; moveab(x, 1, -1, 'ring')\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e → \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[2 3 4 5 6 7 8 9 1 10]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61340,"title":"Piston Mean Speed","description":"Mean piston speed is a critical mechanical stress indicator.\r\nIt sets limits on valve timing, bearing loads and material fatigue. \r\nMost production engines keep mean piston speed under 15 m/s; racing engines push this toward 25 m/s.\r\n\r\nGiven stroke S (m) and engine speed n (RPM), compute mean piston speed v_p (m/s).","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 345px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 468.5px 172.5px; transform-origin: 468.5px 172.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eMean piston speed is a critical mechanical stress indicator.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIt sets limits on valve timing, bearing loads and material fatigue. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eMost production engines keep mean piston speed under 15 m/s; racing engines push this toward 25 m/s.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 225px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 112.5px; text-align: left; transform-origin: 444.5px 112.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cimg class=\"imageNode\" style=\"vertical-align: baseline\" src=\"https://marineinbox.com/wp-content/uploads/2019/08/images.png\" data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven stroke S (m) and engine speed n (RPM), compute mean piston speed v_p (m/s).\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function vp = meanPistonSpeed(S, n)\r\nvp = 0;\r\nend","test_suite":"%%Test 1\r\nS=0.086; n=3000;\r\nassert(abs(meanPistonSpeed(S,n) - 2*S*n/60) \u003c 1e-6)\r\n%%Test 2\r\nS=0.092; n=6000;\r\nassert(abs(meanPistonSpeed(S,n) - 2*S*n/60) \u003c 1e-6)\r\n%%Test 3\r\nS=0.105; n=8000;\r\nassert(abs(meanPistonSpeed(S,n) - 2*S*n/60) \u003c 1e-6)\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":2305225,"edited_by":2305225,"edited_at":"2026-05-27T03:50:54.000Z","deleted_by":null,"deleted_at":null,"solvers_count":12,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-21T09:58:25.000Z","updated_at":"2026-05-27T03:50:54.000Z","published_at":"2026-05-21T09:58:25.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eMean piston speed is a critical mechanical stress indicator.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIt sets limits on valve timing, bearing loads and material fatigue. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eMost production engines keep mean piston speed under 15 m/s; racing engines push this toward 25 m/s.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"219\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"230\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven stroke S (m) and engine speed n (RPM), compute mean piston speed v_p (m/s).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/image\",\"target\":\"/media/image1.png\",\"relationshipId\":\"rId1\"}]},{\"partUri\":\"/media/image1.png\",\"contentType\":\"image/png\",\"content\":\"https://marineinbox.com/wp-content/uploads/2019/08/images.png\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61339,"title":"Engine Displacement ","description":"Engine displacement is the total swept volume of all cylinders. \r\nIt is determined by bore (cylinder diameter), stroke (piston travel) and the number of cylinders. \r\nDisplacement is typically quoted in litres or cubic centimetres for consumer engines.\r\n\r\nGiven bore B (m), stroke S (m), and number of cylinders N, compute total displacement V_d (m³).","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 511px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 468.5px 255.5px; transform-origin: 468.5px 255.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eEngine displacement is the total swept volume of all cylinders. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIt is determined by bore (cylinder diameter), stroke (piston travel) and the number of cylinders. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eDisplacement is typically quoted in litres or cubic centimetres for consumer engines.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 391px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 195.5px; text-align: left; transform-origin: 444.5px 195.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cimg class=\"imageNode\" style=\"vertical-align: baseline\" src=\"https://www.aa1car.com/library/engine_displacement.jpg\" data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven bore B (m), stroke S (m), and number of cylinders N, compute total displacement V_d (m³).\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function Vd = engineDisplacement(B, S, N)\r\nVd = 0;\r\nend","test_suite":"%%Test 1\r\nB=0.086; S=0.086; N=4;\r\nassert(abs(engineDisplacement(B,S,N) - (pi/4)*B^2*S*N) \u003c 1e-8)\r\n%%Test 2\r\nB=0.096; S=0.092; N=6;\r\nassert(abs(engineDisplacement(B,S,N) - (pi/4)*B^2*S*N) \u003c 1e-8)\r\n%%Test 3\r\nB=0.110; S=0.105; N=8;\r\nassert(abs(engineDisplacement(B,S,N) - (pi/4)*B^2*S*N) \u003c 1e-8)\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":1,"created_by":2305225,"edited_by":2305225,"edited_at":"2026-05-27T03:47:33.000Z","deleted_by":null,"deleted_at":null,"solvers_count":13,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-21T09:54:47.000Z","updated_at":"2026-05-27T03:50:04.000Z","published_at":"2026-05-21T09:54:47.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eEngine displacement is the total swept volume of all cylinders. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIt is determined by bore (cylinder diameter), stroke (piston travel) and the number of cylinders. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eDisplacement is typically quoted in litres or cubic centimetres for consumer engines.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"385\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"381\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven bore B (m), stroke S (m), and number of cylinders N, compute total displacement V_d (m³).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/image\",\"target\":\"/media/image1.jpg\",\"relationshipId\":\"rId1\"}]},{\"partUri\":\"/media/image1.jpg\",\"contentType\":\"image/jpg\",\"content\":\"https://www.aa1car.com/library/engine_displacement.jpg\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":988,"title":"Convert a substructure reference string into a valid definition structure for subsref and subsasgn","description":"You have a reference to an element in a data structure, which you want to pass to a function. Not the value itself, but the reference. And you don't like to use evil eval constructions. \r\nTherefore, you convert the reference into a structure, like liked by Matlab's built-in subsref and subsasgn functions.\r\n\r\nFor example, to reference the value a(12), you would have to convert '(12)' into \r\n\r\n  def = \r\n    type: '()'\r\n    subs: {[12]}\r\n\r\nAnd to reference a(12).field_b{1,3}{2}((3:4),:).c, you would need to convert '(12).field_b{1,3}{2}((3:4),:).c' into \r\n\r\n  def(1) = \r\n    type: '()'\r\n    subs: {[12]}\r\n\r\n  def(2) = \r\n    type: '.'\r\n    subs: {'field_b'}\r\n\r\n  def(3) = \r\n    type: '{}'\r\n    subs: {[1]  [3]}\r\n\r\n  def(4) = \r\n    type: '{}'\r\n    subs: {2}\r\n\r\n  def(5) = \r\n    type: '()'\r\n    subs: {[3 4]  ':'}\r\n\r\n  def(6) = \r\n    type: '.'\r\n    subs: {'c'}\r\n\r\nThe assignment is correct when any sub-structure reference that is accepted by subsref and subsasgn is correctly converted from a string to a valid structure.\r\n\r\nNote: Solutions wrapped in (f)eval(c), inline, str2func, regexprep (dynamic regular expressions), etc, are not appreciated.","description_html":"\u003cp\u003eYou have a reference to an element in a data structure, which you want to pass to a function. Not the value itself, but the reference. And you don't like to use evil eval constructions. \r\nTherefore, you convert the reference into a structure, like liked by Matlab's built-in subsref and subsasgn functions.\u003c/p\u003e\u003cp\u003eFor example, to reference the value a(12), you would have to convert '(12)' into\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003edef = \r\n  type: '()'\r\n  subs: {[12]}\r\n\u003c/pre\u003e\u003cp\u003eAnd to reference a(12).field_b{1,3}{2}((3:4),:).c, you would need to convert '(12).field_b{1,3}{2}((3:4),:).c' into\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003edef(1) = \r\n  type: '()'\r\n  subs: {[12]}\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003edef(2) = \r\n  type: '.'\r\n  subs: {'field_b'}\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003edef(3) = \r\n  type: '{}'\r\n  subs: {[1]  [3]}\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003edef(4) = \r\n  type: '{}'\r\n  subs: {2}\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003edef(5) = \r\n  type: '()'\r\n  subs: {[3 4]  ':'}\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003edef(6) = \r\n  type: '.'\r\n  subs: {'c'}\r\n\u003c/pre\u003e\u003cp\u003eThe assignment is correct when any sub-structure reference that is accepted by subsref and subsasgn is correctly converted from a string to a valid structure.\u003c/p\u003e\u003cp\u003eNote: Solutions wrapped in (f)eval(c), inline, str2func, regexprep (dynamic regular expressions), etc, are not appreciated.\u003c/p\u003e","function_template":"function def = subsdef(defstr)\r\n  def = substruct('()',{1});\r\nend","test_suite":"%%\r\nnocheat = isempty(regexp(evalc('type subsdef'),'(eval|regexprep|inline|str2func)'));\r\ny_correct = 1i;\r\nb(12) = y_correct;\r\ndefstr = '(12)';\r\nassert(isequal(subsref(b,subsdef(defstr)),y_correct) \u0026\u0026 nocheat)\r\n\r\n%%\r\nnocheat = isempty(regexp(evalc('type subsdef'),'(eval|regexprep|inline|str2func)'));\r\ny_correct = -4i;\r\nc{1,2,3,4,5}.field_b = y_correct;\r\ndefstr = '{1,2,3,4,5}.field_b';\r\nassert(isequal(subsref(c,subsdef(defstr)),y_correct) \u0026\u0026 nocheat)\r\n\r\n%%\r\nnocheat = isempty(regexp(evalc('type subsdef'),'(eval|regexprep|inline|str2func)'));\r\ny_correct = 3i;\r\na(12).field_b{1,3}{2}((3),1).c = y_correct;\r\ndefstr = '(12).field_b{1,3}{2}((3),1).c';\r\nassert(isequal(subsref(a,subsdef(defstr)),y_correct) \u0026\u0026 nocheat)\r\n\r\n%%\r\nnocheat = isempty(regexp(evalc('type subsdef'),'(eval|regexprep|inline|str2func)'));\r\ny_correct = repmat(2i,3,1);\r\nd{2}.a(1:3,:) = y_correct;\r\ndefstr = '{2}.a(1:3,:)';\r\nassert(isequal(subsref(d,subsdef(defstr)),y_correct) \u0026\u0026 nocheat)\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":6556,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":8,"test_suite_updated_at":"2012-10-11T14:58:11.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-10-11T14:55:15.000Z","updated_at":"2026-05-26T06:11:25.000Z","published_at":"2012-10-11T14:55:15.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eYou have a reference to an element in a data structure, which you want to pass to a function. Not the value itself, but the reference. And you don't like to use evil eval constructions. Therefore, you convert the reference into a structure, like liked by Matlab's built-in subsref and subsasgn functions.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor example, to reference the value a(12), you would have to convert '(12)' into\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[def = \\n  type: '()'\\n  subs: {[12]}]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAnd to reference a(12).field_b{1,3}{2}((3:4),:).c, you would need to convert '(12).field_b{1,3}{2}((3:4),:).c' into\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[def(1) = \\n  type: '()'\\n  subs: {[12]}\\n\\ndef(2) = \\n  type: '.'\\n  subs: {'field_b'}\\n\\ndef(3) = \\n  type: '{}'\\n  subs: {[1]  [3]}\\n\\ndef(4) = \\n  type: '{}'\\n  subs: {2}\\n\\ndef(5) = \\n  type: '()'\\n  subs: {[3 4]  ':'}\\n\\ndef(6) = \\n  type: '.'\\n  subs: {'c'}]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe assignment is correct when any sub-structure reference that is accepted by subsref and subsasgn is correctly converted from a string to a valid structure.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNote: Solutions wrapped in (f)eval(c), inline, str2func, regexprep (dynamic regular expressions), etc, are not appreciated.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":61333,"title":"Given the ratio of the two legs (longer / shorter), and the hypotenuse length, find the shorter leg.","description":"Further to the problem 43236, find the length of shorter leg\r\nP.S No built-in functions allowed","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(33, 33, 33); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 51px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 243.5px 25.5px; transform-origin: 243.5px 25.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 219.5px 10.5px; text-align: left; transform-origin: 219.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFurther to the problem 43236, find the length of shorter leg\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 219.5px 10.5px; text-align: left; transform-origin: 219.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eP.S No built-in functions allowed\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = FindShortLeg(x,ratio)\r\n y = x;\r\nend","test_suite":"%%\r\nx = 40;\r\nratio = 16/9;\r\ny_correct = 19.6104;\r\nassert(abs(FindShortLeg(x,ratio)-y_correct)\u003c0.01)\r\n\r\n%%\r\nx = 25;\r\nratio = 16/9;\r\ny_correct = 12.2565;\r\nassert(abs(FindShortLeg(x,ratio)-y_correct)\u003c0.01)\r\n\r\n%%\r\nx = 10;\r\nratio = 16/9;\r\ny_correct =  4.9026;\r\nassert(abs(FindShortLeg(x,ratio)-y_correct)\u003c0.01)\r\n\r\n%%\r\nx = 5;\r\nratio = 4/3;\r\ny_correct = 3;\r\nassert(abs(FindShortLeg(x,ratio)-y_correct)\u003c0.01)\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":584788,"edited_by":584788,"edited_at":"2026-05-21T11:24:29.000Z","deleted_by":null,"deleted_at":null,"solvers_count":10,"test_suite_updated_at":"2026-05-21T05:44:56.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-21T05:28:33.000Z","updated_at":"2026-05-26T12:27:22.000Z","published_at":"2026-05-21T05:28:33.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFurther to the problem 43236, find the length of shorter leg\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eP.S No built-in functions allowed\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61336,"title":"Brake Mean Effective Pressure (BMEP)","description":"BMEP is a normalised measure of engine work output per cycle per unit displacement. It lets you compare engines of different sizes on equal footing.\r\nA higher BMEP indicates a more efficient use of displacement.\r\n\r\nGiven torque T (N·m), displacement V_d (m³), and number of strokes k (2 or 4), compute BMEP.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 599.719px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 468.5px 299.859px; transform-origin: 468.5px 299.859px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 21px; text-align: left; transform-origin: 444.5px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eBMEP is a normalised measure of engine work output per cycle per unit displacement. It lets you compare engines of different sizes on equal footing.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eA higher BMEP indicates a more efficient use of displacement.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 488.719px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 244.359px; text-align: left; transform-origin: 444.5px 244.359px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cimg class=\"imageNode\" style=\"vertical-align: baseline\" src=\"https://static.wixstatic.com/media/1efdb1_5ced4cd83869436cbfd4286a5c83ab9b~mv2.png\" data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven torque T (N·m), displacement V_d (m³), and number of strokes k (2 or 4), compute BMEP.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function bmep = calcBMEP(T, Vd, k)\r\nbmep = 0;\r\nend","test_suite":"%%\r\nT = 200; Vd = 0.002; k = 4;\r\nbmep_expected = (T * 2 * pi * k) / Vd;\r\nassert(abs(calcBMEP(T,Vd,k) - bmep_expected) \u003c 1e-3)\r\n%%\r\nT = 350; Vd = 0.003; k = 4;\r\nbmep_expected = (T * 2 * pi * k) / Vd;\r\nassert(abs(calcBMEP(T,Vd,k) - bmep_expected) \u003c 1e-3)\r\n%%\r\nT = 80; Vd = 0.0005; k = 2;\r\nbmep_expected = (T * 2 * pi * k) / Vd;\r\nassert(abs(calcBMEP(T,Vd,k) - bmep_expected) \u003c 1e-3)\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":2305225,"edited_by":2305225,"edited_at":"2026-05-26T03:50:39.000Z","deleted_by":null,"deleted_at":null,"solvers_count":13,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-21T09:38:18.000Z","updated_at":"2026-05-26T15:09:13.000Z","published_at":"2026-05-21T09:38:18.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eBMEP is a normalised measure of engine work output per cycle per unit displacement. It lets you compare engines of different sizes on equal footing.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA higher BMEP indicates a more efficient use of displacement.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"802\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"1477\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven torque T (N·m), displacement V_d (m³), and number of strokes k (2 or 4), compute BMEP.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/image\",\"target\":\"/media/image1.png\",\"relationshipId\":\"rId1\"}]},{\"partUri\":\"/media/image1.png\",\"contentType\":\"image/png\",\"content\":\"https://static.wixstatic.com/media/1efdb1_5ced4cd83869436cbfd4286a5c83ab9b~mv2.png\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61337,"title":"Volumetric efficiency","description":"Volumetric efficiency measures how well an engine breathes.\r\nThe ratio of the actual air mass drawn in per cycle to the theoretical maximum based on displacement. \r\nNaturally aspirated engines typically achieve 80–95%.\r\n\r\nGiven actual air mass m_actual (kg), air density ρ (kg/m³), and displacement V_d (m³), compute volumetric efficiency η_v.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 634.383px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 467.484px 317.18px; transform-origin: 467.496px 317.191px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eVolumetric efficiency measures how well an engine breathes.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe ratio of the actual air mass drawn in per cycle to the theoretical maximum based on displacement. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eNaturally aspirated engines typically achieve 80–95%.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 514.477px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 257.227px; text-align: left; transform-origin: 443.508px 257.238px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cimg class=\"imageNode\" style=\"vertical-align: baseline\" src=\"https://media.springernature.com/lw685/springer-static/image/chp%3A10.1007%2F978-3-030-89216-6_3/MediaObjects/521933_1_En_3_Fig3_HTML.png\" data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven actual air mass m_actual (kg), air density ρ (kg/m³), and displacement V_d (m³), compute volumetric efficiency η_v.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function eta_v = volEfficiency(m_actual, rho, Vd)\r\neta_v = 0;\r\nend","test_suite":"%%Test 1\r\nm = 0.00180; rho = 1.2; Vd = 0.002;\r\nassert(abs(volEfficiency(m,rho,Vd) - m/(rho*Vd)) \u003c 1e-6)\r\n%%Test 2\r\nm = 0.00252; rho = 1.2; Vd = 0.003;\r\nassert(abs(volEfficiency(m,rho,Vd) - m/(rho*Vd)) \u003c 1e-6)\r\n%%Test 3\r\nm = 0.00096; rho = 1.15; Vd = 0.0012;\r\nassert(abs(volEfficiency(m,rho,Vd) - m/(rho*Vd)) \u003c 1e-6)\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":2305225,"edited_by":2305225,"edited_at":"2026-05-21T09:48:02.000Z","deleted_by":null,"deleted_at":null,"solvers_count":13,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-21T09:45:01.000Z","updated_at":"2026-05-26T15:09:52.000Z","published_at":"2026-05-21T09:48:02.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eVolumetric efficiency measures how well an engine breathes.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe ratio of the actual air mass drawn in per cycle to the theoretical maximum based on displacement. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNaturally aspirated engines typically achieve 80–95%.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven actual air mass m_actual (kg), air density ρ (kg/m³), and displacement V_d (m³), compute volumetric efficiency η_v.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/image\",\"target\":\"/media/image1.png\",\"relationshipId\":\"rId1\"}]},{\"partUri\":\"/media/image1.png\",\"contentType\":\"image/png\",\"content\":\"https://media.springernature.com/lw685/springer-static/image/chp%3A10.1007%2F978-3-030-89216-6_3/MediaObjects/521933_1_En_3_Fig3_HTML.png\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61341,"title":"Specific Fuel Consumption","description":"Brake-specific fuel consumption (BSFC) measures how efficiently an engine converts fuel mass into useful work. \r\nLower is better. Modern petrol engines achieve roughly 250–270 g/kWh at their best efficiency point.\r\n\r\nGiven fuel mass flow rate m_dot (kg/s) and brake power P (W), compute BSFC in g/kWh.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 110.906px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 467.484px 55.4531px; transform-origin: 467.496px 55.4531px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eBrake-specific fuel consumption (BSFC) measures how efficiently an engine converts fuel mass into useful work. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eLower is better. Modern petrol engines achieve roughly 250–270 g/kWh at their best efficiency point.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven fuel mass flow rate m_dot (kg/s) and brake power P (W), compute BSFC in g/kWh.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function bsfc = calcBSFC(m_dot, P)\r\nbsfc = 0;\r\nend","test_suite":"%%Test 1\r\nm_dot=0.0070; P=100000;\r\nassert(abs(calcBSFC(m_dot,P) - (m_dot/P)*3.6e6) \u003c 1e-3)\r\n%%Test 2\r\nm_dot=0.0105; P=150000;\r\nassert(abs(calcBSFC(m_dot,P) - (m_dot/P)*3.6e6) \u003c 1e-3)\r\n%%Test 3\r\nm_dot=0.0040; P=60000;\r\nassert(abs(calcBSFC(m_dot,P) - (m_dot/P)*3.6e6) \u003c 1e-3)","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":2305225,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":12,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-21T10:05:55.000Z","updated_at":"2026-05-26T15:28:57.000Z","published_at":"2026-05-21T10:05:55.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eBrake-specific fuel consumption (BSFC) measures how efficiently an engine converts fuel mass into useful work. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eLower is better. Modern petrol engines achieve roughly 250–270 g/kWh at their best efficiency point.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven fuel mass flow rate m_dot (kg/s) and brake power P (W), compute BSFC in g/kWh.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61342,"title":"Swept Volume and Clearance Volume","description":"The swept volume (V_s) is the volume displaced by the piston as it travels from BDC (Bottom Dead Centre) to TDC (Top Dead Centre). The clearance volume (V_c) is the remaining volume above the piston at TDC — it cannot be swept and defines the compression limit.\r\n\r\nGiven total cylinder volume at BDC V_BDC (m³) and clearance volume at TDC V_TDC (m³), compute the swept volume V_s and confirm it matches the bore-stroke formula using bore B (m) and stroke S (m).","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 616.383px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 467.484px 308.18px; transform-origin: 467.496px 308.191px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 41.9531px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 20.9766px; text-align: left; transform-origin: 443.508px 20.9766px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe swept volume (V_s) is the volume displaced by the piston as it travels from BDC (Bottom Dead Centre) to TDC (Top Dead Centre). The clearance volume (V_c) is the remaining volume above the piston at TDC — it cannot be swept and defines the compression limit.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 514.477px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 257.227px; text-align: left; transform-origin: 443.508px 257.238px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cimg class=\"imageNode\" style=\"vertical-align: baseline\" src=\"https://media.springernature.com/lw685/springer-static/image/chp%3A10.1007%2F978-3-030-89216-6_3/MediaObjects/521933_1_En_3_Fig3_HTML.png\" data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 41.9531px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 20.9766px; text-align: left; transform-origin: 443.508px 20.9766px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven total cylinder volume at BDC V_BDC (m³) and clearance volume at TDC V_TDC (m³), compute the swept volume V_s and confirm it matches the bore-stroke formula using bore B (m) and stroke S (m).\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function [Vs, Vc] = sweptClearanceVolume(V_BDC, V_TDC)\r\nVs = 0;\r\nVc = 0;\r\nend","test_suite":"%%Test 1\r\nV_BDC=550e-6; V_TDC=50e-6;\r\n[Vs,Vc] = sweptClearanceVolume(V_BDC,V_TDC);\r\nassert(abs(Vs - 500e-6) \u003c 1e-9)\r\nassert(abs(Vc - 50e-6) \u003c 1e-9)\r\n%%Test 2\r\nV_BDC=750e-6; V_TDC=62.5e-6;\r\n[Vs,Vc] = sweptClearanceVolume(V_BDC,V_TDC);\r\nassert(abs(Vs - 687.5e-6) \u003c 1e-9)\r\nassert(abs(Vc - 62.5e-6) \u003c 1e-9)\r\n%%Test 3\r\nV_BDC=400e-6; V_TDC=36.36e-6;\r\n[Vs,Vc] = sweptClearanceVolume(V_BDC,V_TDC);\r\nassert(abs(Vs - (V_BDC-V_TDC)) \u003c 1e-9)\r\nassert(abs(Vc - V_TDC) \u003c 1e-9)","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":2305225,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":12,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-21T10:13:10.000Z","updated_at":"2026-05-26T15:31:54.000Z","published_at":"2026-05-21T10:13:10.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe swept volume (V_s) is the volume displaced by the piston as it travels from BDC (Bottom Dead Centre) to TDC (Top Dead Centre). The clearance volume (V_c) is the remaining volume above the piston at TDC — it cannot be swept and defines the compression limit.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"507\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"685\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven total cylinder volume at BDC V_BDC (m³) and clearance volume at TDC V_TDC (m³), compute the swept volume V_s and confirm it matches the bore-stroke formula using bore B (m) and stroke S (m).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/image\",\"target\":\"/media/image1.png\",\"relationshipId\":\"rId1\"}]},{\"partUri\":\"/media/image1.png\",\"contentType\":\"image/png\",\"content\":\"https://media.springernature.com/lw685/springer-static/image/chp%3A10.1007%2F978-3-030-89216-6_3/MediaObjects/521933_1_En_3_Fig3_HTML.png\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61343,"title":"Geometric Compression Ratio","description":"The geometric compression ratio CR is the ratio of the total cylinder volume at BDC to the clearance volume at TDC. It is one of the most fundamental engine design parameters — it governs knock tendency, thermal efficiency, and peak cylinder pressure.\r\n\r\nGiven swept volume V_s (m³) and clearance volume V_c (m³), compute the compression ratio CR. Also verify the result using the TDC/BDC volumes directly.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 996.398px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 467.484px 498.188px; transform-origin: 467.496px 498.199px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 41.9531px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 20.9766px; text-align: left; transform-origin: 443.508px 20.9766px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe geometric compression ratio CR is the ratio of the total cylinder volume at BDC to the clearance volume at TDC. It is one of the most fundamental engine design parameters — it governs knock tendency, thermal efficiency, and peak cylinder pressure.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 894.492px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 447.234px; text-align: left; transform-origin: 443.508px 447.246px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cimg class=\"imageNode\" style=\"vertical-align: baseline\" src=\"https://capstone-x.com/wp-content/uploads/2026/01/Gemini_Generated_Image_12mi8212mi8212mi.png\" data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 41.9531px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 20.9766px; text-align: left; transform-origin: 443.508px 20.9766px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven swept volume V_s (m³) and clearance volume V_c (m³), compute the compression ratio CR. Also verify the result using the TDC/BDC volumes directly.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function CR = compressionRatio(Vs, Vc)\r\nCR = 0;\r\nend","test_suite":"%%Test 1\r\nVs = 500e-6; Vc = 55.56e-6;\r\nCR_expected = (Vs + Vc) / Vc;\r\nassert(abs(compressionRatio(Vs,Vc) - CR_expected) \u003c 1e-4)\r\n%%Test 2\r\nVs = 687.5e-6; Vc = 62.5e-6;\r\nCR_expected = (Vs + Vc) / Vc;\r\nassert(abs(compressionRatio(Vs,Vc) - CR_expected) \u003c 1e-4)\r\n%%Test 3\r\nVs = 363.6e-6; Vc = 36.36e-6;\r\nCR_expected = (Vs + Vc) / Vc;\r\nassert(abs(compressionRatio(Vs,Vc) - CR_expected) \u003c 1e-4)\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":2305225,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":12,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-21T10:16:34.000Z","updated_at":"2026-05-26T15:32:28.000Z","published_at":"2026-05-21T10:16:34.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe geometric compression ratio CR is the ratio of the total cylinder volume at BDC to the clearance volume at TDC. It is one of the most fundamental engine design parameters — it governs knock tendency, thermal efficiency, and peak cylinder pressure.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"1024\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"1024\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven swept volume V_s (m³) and clearance volume V_c (m³), compute the compression ratio CR. Also verify the result using the TDC/BDC volumes directly.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/image\",\"target\":\"/media/image1.png\",\"relationshipId\":\"rId1\"}]},{\"partUri\":\"/media/image1.png\",\"contentType\":\"image/png\",\"content\":\"https://capstone-x.com/wp-content/uploads/2026/01/Gemini_Generated_Image_12mi8212mi8212mi.png\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":843,"title":"Hyperspectral Processing: Determine Material Components given a Hyperspectral vector","description":"Given a hyperspectral data set and Reflectance Spectral Signature Library determine a pixel's component percentages. \r\n\r\n\u003chttp://aviris.jpl.nasa.gov/aviris/index.html NASA AVIRIS\u003e\r\n\r\nA Ground Square is imaged by hundreds of pixels, each at a different wavelength.\r\nThe signal on pixel 1(500nm to 505nm) is a sum of the components (Concrete/Tree/Grass...) by percentage of area covered times the material reflectance.\r\nPixel 2 (510-515nm) is different by the Reflectance deltas between Concrete and a Tree.\r\n\r\nLet S(i,j) be the response of Material i for band j\r\n\r\ng( j )= %(Concrete)*S(1,j)+%(Tree)*S(2,j)+...%(Grass)*S(end,j);\r\n\r\nA 300-Band 9-Material Spectral file is loaded. Comparison between foliage and rocks is quite significant. The materials are Bush, Calcite, Concrete, Conifer, Grass (not that type), Fir tree, Gypsum, Maple, Sage\r\n\r\n*g=S*f*  where f is the percentage of the imaged pixel covered by the\r\nmaterial.\r\n\r\n*Input:* \r\ng spectral sum [301,1]; \r\nS spectral material response [301,9]  Nine materials\r\n\r\n*Output:*\r\nSolve for f  ....( eg f=[0 .5 0 .25 .25 0 0 0 0]' )\r\n\r\n( f should sum to 1, max(f) is 1 and min(f) is 0 )\r\n\r\nThe test Suite will round to 2 decimal places.\r\nCases of \"other materials\" which will induce negative values are not\r\ntested.\r\n\r\nThis is introductory and ignores atmospheric absorption.\r\n\r\nThere is a matrix operation hint in the test suite for a method to solve for f.\r\n\r\n\r\n\u003chttp://aviris.jpl.nasa.gov/data/free_data.html AVARIS Free Data\u003e\r\nThese data files are large with 224 bands x 750 channels x 2000 samples\r\n\r\nTo expand these files may require a tar converter\r\n\u003chttp://aviris.jpl.nasa.gov/alt_locator/111013_AV_Download.readme NASA readme\u003e\r\n...and... \r\n\u003chttp://aviris.jpl.nasa.gov/alt_gulf/ NASA Tools bottom Left\u003e\r\nThere are some possible issues with the NASA tar tool. Two non-standard files can be found at \u003chttp://dll-files.org/7968/index.html libiconv-2.dll\u003e and \u003chttp://dll-files.org/7975/libintl-2.dll.html libintl-2.dll\u003e\r\n\r\nSee the Test Suite for details on opening the AVIRIS Moffett Field file.","description_html":"\u003cp\u003eGiven a hyperspectral data set and Reflectance Spectral Signature Library determine a pixel's component percentages.\u003c/p\u003e\u003cp\u003e\u003ca href=\"http://aviris.jpl.nasa.gov/aviris/index.html\"\u003eNASA AVIRIS\u003c/a\u003e\u003c/p\u003e\u003cp\u003eA Ground Square is imaged by hundreds of pixels, each at a different wavelength.\r\nThe signal on pixel 1(500nm to 505nm) is a sum of the components (Concrete/Tree/Grass...) by percentage of area covered times the material reflectance.\r\nPixel 2 (510-515nm) is different by the Reflectance deltas between Concrete and a Tree.\u003c/p\u003e\u003cp\u003eLet S(i,j) be the response of Material i for band j\u003c/p\u003e\u003cp\u003eg( j )= %(Concrete)*S(1,j)+%(Tree)*S(2,j)+...%(Grass)*S(end,j);\u003c/p\u003e\u003cp\u003eA 300-Band 9-Material Spectral file is loaded. Comparison between foliage and rocks is quite significant. The materials are Bush, Calcite, Concrete, Conifer, Grass (not that type), Fir tree, Gypsum, Maple, Sage\u003c/p\u003e\u003cp\u003e\u003cb\u003eg=S*f\u003c/b\u003e  where f is the percentage of the imaged pixel covered by the\r\nmaterial.\u003c/p\u003e\u003cp\u003e\u003cb\u003eInput:\u003c/b\u003e \r\ng spectral sum [301,1]; \r\nS spectral material response [301,9]  Nine materials\u003c/p\u003e\u003cp\u003e\u003cb\u003eOutput:\u003c/b\u003e\r\nSolve for f  ....( eg f=[0 .5 0 .25 .25 0 0 0 0]' )\u003c/p\u003e\u003cp\u003e( f should sum to 1, max(f) is 1 and min(f) is 0 )\u003c/p\u003e\u003cp\u003eThe test Suite will round to 2 decimal places.\r\nCases of \"other materials\" which will induce negative values are not\r\ntested.\u003c/p\u003e\u003cp\u003eThis is introductory and ignores atmospheric absorption.\u003c/p\u003e\u003cp\u003eThere is a matrix operation hint in the test suite for a method to solve for f.\u003c/p\u003e\u003cp\u003e\u003ca href=\"http://aviris.jpl.nasa.gov/data/free_data.html\"\u003eAVARIS Free Data\u003c/a\u003e\r\nThese data files are large with 224 bands x 750 channels x 2000 samples\u003c/p\u003e\u003cp\u003eTo expand these files may require a tar converter \u003ca href=\"http://aviris.jpl.nasa.gov/alt_locator/111013_AV_Download.readme\"\u003eNASA readme\u003c/a\u003e\r\n...and...  \u003ca href=\"http://aviris.jpl.nasa.gov/alt_gulf/\"\u003eNASA Tools bottom Left\u003c/a\u003e\r\nThere are some possible issues with the NASA tar tool. Two non-standard files can be found at \u003ca href=\"http://dll-files.org/7968/index.html\"\u003elibiconv-2.dll\u003c/a\u003e and \u003ca href=\"http://dll-files.org/7975/libintl-2.dll.html\"\u003elibintl-2.dll\u003c/a\u003e\u003c/p\u003e\u003cp\u003eSee the Test Suite for details on opening the AVIRIS Moffett Field file.\u003c/p\u003e","function_template":"function f = hyperspectral(g,S)\r\n% g is [301,1]\r\n% S is [301,9]\r\n  f = zeros(size(S,2),1);\r\nend","test_suite":"%%\r\n% The AVIRIS fileread info is at the bottom\r\n% Solution Hint:\r\n% The Matrix hint is inv(S'S)(S'S)=I\r\n% With g=Sf multiply both sides by h'\r\n% S'g=S'Sf, now multiply both sides by inv(S'S)\r\n% inv(S'S)(S'g)=inv(S'S)(S'S)f which is I*f\r\n% Now simplify the right side and there is a solution\r\n% Solution Bigger/Better Hint: Search on mldivide\r\n%%\r\nglobal S\r\n%http://tinyurl.com/matlab-hyper-spectra\r\n%http://rmatlabtest.appspot.com/Spectra.mat\r\nurlwrite('http://rmatlabtest.appspot.com/Spectra.mat','Spectra.mat') ;\r\nload('Spectra.mat'); % S is the variable in Spectra.mat\r\nf_exp=[.5 .5 0 0 0 0 0 0 0 ]';\r\ng=S*f_exp;\r\n\r\nf = hyperspectral(g,S);\r\nassert(isequal(round(100*f)/100,f_exp),sprintf('%f\\n',f))\r\n%%\r\nglobal S\r\nf_exp=[0 .5 0.25 0 0 0 0.25 0 0 ]';\r\ng=S*f_exp;\r\nf = hyperspectral(g,S);\r\nassert(isequal(round(100*f)/100,f_exp),sprintf('%f\\n',f))\r\n%%\r\nglobal S\r\nf_exp=[0 .25 0.6 0 0 0 0 0.15 0 ]';\r\ng=S*f_exp;\r\nf = hyperspectral(g,S);\r\nassert(isequal(round(100*f)/100,f_exp),sprintf('%f\\n',f))\r\n%%\r\n%\r\n%Reading of the full Moffett Field file: (8GB RAM recommended)\r\n% The file is 600MB\r\n%cd 'C:\\Users\\???' % Your file location\r\n%fn='f080611t01p00r07rdn_c_sc01_ort_img'\r\n%fid = fopen (fn,'r');\r\n%A = int16(fread(fid, 'int16', 'ieee-be'));\r\n%A2 = reshape (A, 224,753,1924); % Specifics found in text files\r\n%A3 = permute (A2,[3 2 1]); % X Y Band\r\n%figure;imagesc(squeeze(A3(:,:,1))); % To view top layer\r\n","published":true,"deleted":false,"likes_count":3,"comments_count":8,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":11,"test_suite_updated_at":"2013-02-02T19:05:40.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-07-19T02:49:02.000Z","updated_at":"2026-05-26T16:59:53.000Z","published_at":"2012-07-19T03:34:29.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven a hyperspectral data set and Reflectance Spectral Signature Library determine a pixel's component percentages.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:hyperlink w:docLocation=\\\"http://aviris.jpl.nasa.gov/aviris/index.html\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eNASA AVIRIS\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA Ground Square is imaged by hundreds of pixels, each at a different wavelength. The signal on pixel 1(500nm to 505nm) is a sum of the components (Concrete/Tree/Grass...) by percentage of area covered times the material reflectance. Pixel 2 (510-515nm) is different by the Reflectance deltas between Concrete and a Tree.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eLet S(i,j) be the response of Material i for band j\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eg( j )= %(Concrete)*S(1,j)+%(Tree)*S(2,j)+...%(Grass)*S(end,j);\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA 300-Band 9-Material Spectral file is loaded. Comparison between foliage and rocks is quite significant. The materials are Bush, Calcite, Concrete, Conifer, Grass (not that type), Fir tree, Gypsum, Maple, Sage\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eg=S*f\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e where f is the percentage of the imaged pixel covered by the material.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e g spectral sum [301,1]; S spectral material response [301,9] Nine materials\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e Solve for f ....( eg f=[0 .5 0 .25 .25 0 0 0 0]' )\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e( f should sum to 1, max(f) is 1 and min(f) is 0 )\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe test Suite will round to 2 decimal places. Cases of \\\"other materials\\\" which will induce negative values are not tested.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis is introductory and ignores atmospheric absorption.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThere is a matrix operation hint in the test suite for a method to solve for f.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:hyperlink w:docLocation=\\\"http://aviris.jpl.nasa.gov/data/free_data.html\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eAVARIS Free Data\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e These data files are large with 224 bands x 750 channels x 2000 samples\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eTo expand these files may require a tar converter\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://aviris.jpl.nasa.gov/alt_locator/111013_AV_Download.readme\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eNASA readme\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e ...and... \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://aviris.jpl.nasa.gov/alt_gulf/\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eNASA Tools bottom Left\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e There are some possible issues with the NASA tar tool. Two non-standard files can be found at\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://dll-files.org/7968/index.html\\\"\u003e\u003cw:r\u003e\u003cw:t\u003elibiconv-2.dll\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e and\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://dll-files.org/7975/libintl-2.dll.html\\\"\u003e\u003cw:r\u003e\u003cw:t\u003elibintl-2.dll\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSee the Test Suite for details on opening the AVIRIS Moffett Field file.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":61338,"title":"Fuel-Air Equivalence Ratio (Lambda)","description":"Lambda (λ) is the ratio of actual air-fuel ratio to the stoichiometric air-fuel ratio. \r\nλ = 1 is perfect stoichiometry, \r\nλ \u003c 1 is rich, \r\nλ \u003e 1 is lean. \r\nEngine management systems constantly target λ = 1 for optimal catalyst performance.\r\n\r\nGiven actual AFR and stoichiometric AFR (AFR_s), compute lambda.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 572px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 468.5px 286px; transform-origin: 468.5px 286px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eLambda (λ) is the ratio of actual air-fuel ratio to the stoichiometric air-fuel ratio. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eλ = 1 is perfect stoichiometry, \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eλ \u0026lt; 1 is rich, \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eλ \u0026gt; 1 is lean. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eEngine management systems constantly target λ = 1 for optimal catalyst performance.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 392px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 196px; text-align: left; transform-origin: 444.5px 196px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cimg class=\"imageNode\" style=\"vertical-align: baseline\" src=\"https://i.ytimg.com/vi/9uFdrcPkMGE/hq720.jpg?sqp=-oaymwEhCK4FEIIDSFryq4qpAxMIARUAAAAAGAElAADIQj0AgKJD\u0026amp;rs=AOn4CLDLLtOPt4b2zx4L72ztX9tL_4S0vw\" data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven actual AFR and stoichiometric AFR (AFR_s), compute lambda.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function lam = calcLambda(AFR, AFR_s)\r\nlam = 0;\r\nend","test_suite":"%%Test 1\r\nassert(abs(calcLambda(14.7, 14.7) - 1.0) \u003c 1e-6)\r\n%%Test 2\r\nassert(abs(calcLambda(12.5, 14.7) - 12.5/14.7) \u003c 1e-6)\r\n%%Test 3\r\nassert(abs(calcLambda(16.2, 14.7) - 16.2/14.7) \u003c 1e-6)","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":2305225,"edited_by":2305225,"edited_at":"2026-05-27T03:46:08.000Z","deleted_by":null,"deleted_at":null,"solvers_count":13,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-21T09:51:05.000Z","updated_at":"2026-05-27T03:46:42.000Z","published_at":"2026-05-21T09:51:05.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eLambda (λ) is the ratio of actual air-fuel ratio to the stoichiometric air-fuel ratio. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eλ = 1 is perfect stoichiometry, \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eλ \u0026lt; 1 is rich, \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eλ \u0026gt; 1 is lean. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eEngine management systems constantly target λ = 1 for optimal catalyst performance.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"386\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"686\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven actual AFR and stoichiometric AFR (AFR_s), compute lambda.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/image\",\"target\":\"/media/image1.jpg\",\"relationshipId\":\"rId1\"}]},{\"partUri\":\"/media/image1.jpg\",\"contentType\":\"image/jpg\",\"content\":\"https://i.ytimg.com/vi/9uFdrcPkMGE/hq720.jpg?sqp=-oaymwEhCK4FEIIDSFryq4qpAxMIARUAAAAAGAElAADIQj0AgKJD\u0026rs=AOn4CLDLLtOPt4b2zx4L72ztX9tL_4S0vw\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":737,"title":"Criss_Cross_000 : Unique elements in a Square array","description":"Criss Cross matrix puzzle - Easy: Square matrix, Unique elements\r\n\r\nArrange the \"words\" into a solid square such that all words are used.\r\n\r\nGiven an array of row words and an array of column words make the unique Square.\r\n\r\nThere is no flipping or rotating in this simplest case.\r\n\r\nexample:\r\n\r\nM_orig =[1 2 3; 4 5 6; 7 8 9]\r\n\r\n*Inputs:*\r\n\r\nvr = [1 2 3; 4 5 6; 7 8 9]\r\n\r\nscramled gives vr =[7 8 9; 1 2 3; 4 5 6]\r\n\r\nvc =[1 2 3; 4 5 6; 7 8 9]\r\n\r\nscrambled gives vc =[3 1 2;6 4 5; 9 7 8]\r\n\r\n*Output:*\r\n\r\nM_out=[1 2 3; 4 5 6; 7 8 9]\r\n\r\nMax size : 4096\r\n\r\n\r\nThis is the first in a series of Criss Cross puzzles.\r\n\r\nFollow up puzzles will have non-unique values, non-identified row or col, and there are quite a few other variations.","description_html":"\u003cp\u003eCriss Cross matrix puzzle - Easy: Square matrix, Unique elements\u003c/p\u003e\u003cp\u003eArrange the \"words\" into a solid square such that all words are used.\u003c/p\u003e\u003cp\u003eGiven an array of row words and an array of column words make the unique Square.\u003c/p\u003e\u003cp\u003eThere is no flipping or rotating in this simplest case.\u003c/p\u003e\u003cp\u003eexample:\u003c/p\u003e\u003cp\u003eM_orig =[1 2 3; 4 5 6; 7 8 9]\u003c/p\u003e\u003cp\u003e\u003cb\u003eInputs:\u003c/b\u003e\u003c/p\u003e\u003cp\u003evr = [1 2 3; 4 5 6; 7 8 9]\u003c/p\u003e\u003cp\u003escramled gives vr =[7 8 9; 1 2 3; 4 5 6]\u003c/p\u003e\u003cp\u003evc =[1 2 3; 4 5 6; 7 8 9]\u003c/p\u003e\u003cp\u003escrambled gives vc =[3 1 2;6 4 5; 9 7 8]\u003c/p\u003e\u003cp\u003e\u003cb\u003eOutput:\u003c/b\u003e\u003c/p\u003e\u003cp\u003eM_out=[1 2 3; 4 5 6; 7 8 9]\u003c/p\u003e\u003cp\u003eMax size : 4096\u003c/p\u003e\u003cp\u003eThis is the first in a series of Criss Cross puzzles.\u003c/p\u003e\u003cp\u003eFollow up puzzles will have non-unique values, non-identified row or col, and there are quite a few other variations.\u003c/p\u003e","function_template":"function M_out = Criss_Cross(vr,vc)\r\n\r\n M_out=vr*0;\r\n \r\nend","test_suite":"%%\r\nformat long\r\nformat compact\r\nseed=clock;\r\nseed=1000*seed(6);\r\nrng(seed)\r\n\r\nn=4;\r\n% Create a Unique element square array\r\nM=randperm(n*n);\r\nM=reshape(M,n,n)\r\n\r\nvr=M(1:n,:);\r\nvr=sortrows(vr);\r\n\r\nvc=M(:,1:n);\r\nvc=sortrows(vc')';\r\n\r\ntic\r\nM_out=Criss_Cross(vr,vc);\r\ntoc\r\nM_out\r\n\r\nassert(isequal(M,M_out));\r\n%%\r\nseed=clock;\r\nseed=1000*seed(6);\r\nrng(seed)\r\n\r\nn=8;\r\n% Create a Unique element square array\r\nM=randperm(n*n);\r\nM=reshape(M,n,n)\r\n\r\nvr=M(1:n,:);\r\nvr=sortrows(vr);\r\n\r\nvc=M(:,1:n);\r\nvc=sortrows(vc')';\r\n\r\ntic\r\nM_out=Criss_Cross(vr,vc);\r\ntoc\r\nM_out\r\n\r\nassert(isequal(M,M_out));\r\n%%\r\nseed=clock;\r\nseed=1000*seed(6);\r\nrng(seed)\r\n\r\nn=128;\r\n% Create a Unique element square array\r\nM=randperm(n*n);\r\nM=reshape(M,n,n);\r\n\r\nvr=M(1:n,:);\r\nvr=sortrows(vr);\r\n\r\nvc=M(:,1:n);\r\nvc=sortrows(vc')';\r\n\r\ntic\r\nM_out=Criss_Cross(vr,vc);\r\ntoc\r\n\r\nassert(isequal(M,M_out));\r\n%%\r\nseed=clock;\r\nseed=1000*seed(6);\r\nrng(seed)\r\n\r\nn=1024;\r\n% Create a Unique element square array\r\nM=randperm(n*n);\r\nM=reshape(M,n,n);\r\n\r\nvr=M(1:n,:);\r\nvr=sortrows(vr);\r\n\r\nvc=M(:,1:n);\r\nvc=sortrows(vc')';\r\n\r\ntic\r\nM_out=Criss_Cross(vr,vc);\r\ntoc\r\n\r\nassert(isequal(M,M_out));\r\n%%\r\nseed=clock;\r\nseed=1000*seed(6);\r\nrng(seed)\r\n\r\nn=4096;\r\n% Create a Unique element square array\r\nM=randperm(n*n);\r\nM=reshape(M,n,n);\r\n\r\nvr=M(1:n,:);\r\nvr=sortrows(vr);\r\n\r\nvc=M(:,1:n);\r\nvc=sortrows(vc')';\r\n\r\ntic\r\nM_out=Criss_Cross(vr,vc);\r\ntoc\r\n\r\nassert(isequal(M,M_out));","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":9,"test_suite_updated_at":"2012-06-03T20:42:28.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-06-03T18:05:05.000Z","updated_at":"2026-05-27T07:19:16.000Z","published_at":"2012-06-03T19:37:49.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCriss Cross matrix puzzle - Easy: Square matrix, Unique elements\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eArrange the \\\"words\\\" into a solid square such that all words are used.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven an array of row words and an array of column words make the unique Square.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThere is no flipping or rotating in this simplest case.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eexample:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eM_orig =[1 2 3; 4 5 6; 7 8 9]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInputs:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003evr = [1 2 3; 4 5 6; 7 8 9]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003escramled gives vr =[7 8 9; 1 2 3; 4 5 6]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003evc =[1 2 3; 4 5 6; 7 8 9]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003escrambled gives vc =[3 1 2;6 4 5; 9 7 8]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eM_out=[1 2 3; 4 5 6; 7 8 9]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eMax size : 4096\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis is the first in a series of Criss Cross puzzles.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFollow up puzzles will have non-unique values, non-identified row or col, and there are quite a few other variations.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":61304,"title":"Turning radius of a vehicle","description":"The turning radius represents the radius of the circular path followed by a vehicle.\r\nGiven Wheelbase L and Steering angle δ, Compute the turning radius R.\r\nEquation:\r\nR = L / tan(delta)","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 110.906px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 467.484px 55.4531px; transform-origin: 467.496px 55.4531px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe turning radius represents the radius of the circular path followed by a vehicle.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven Wheelbase \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eL and \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eSteering angle \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eδ, \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eCompute the turning radius \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eR\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eEquation:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eR = L / tan(delta)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function R = turningRadius(L,delta)\r\nR = 0;\r\nend","test_suite":"%%\r\nL = 2.5; delta = 30*pi/180;\r\nR_expected = 4.3301;\r\nassert(abs(turningRadius(L,delta) - R_expected) \u003c 1e-3)\r\n\r\n%%\r\nL = 3.0; delta = 20*pi/180;\r\nR_expected = 8.2426;\r\nassert(abs(turningRadius(L,delta) - R_expected) \u003c 1e-3)\r\n\r\n%%\r\nL = 2.8; delta = 10*pi/180;\r\nR_expected = 15.866;\r\nassert(abs(turningRadius(L,delta) - R_expected) \u003c 1e-1)","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":2305225,"edited_by":2305225,"edited_at":"2026-04-28T09:16:45.000Z","deleted_by":null,"deleted_at":null,"solvers_count":41,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-04-28T09:13:54.000Z","updated_at":"2026-05-27T07:21:01.000Z","published_at":"2026-04-28T09:16:45.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe turning radius represents the radius of the circular path followed by a vehicle.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven Wheelbase \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eL and \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003eSteering angle \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eδ, \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003eCompute the turning radius \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eR\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eEquation:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eR = L / tan(delta)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61359,"title":"Count the even numbers in a multiplication table","description":"A multiplication table that has products of numbers from 1 to 10 has 75 even numbers among the products. \r\nWrite a function to count the even numbers in a multiplication table of products  with  and  both running from 1 to .\r\n","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 406.425px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 469px 203.212px; transform-origin: 469px 203.212px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 445px 10.5px; text-align: left; transform-origin: 445px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eA multiplication table that has products of numbers from 1 to 10 has 75 even numbers among the products. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 445px 10.5px; text-align: left; transform-origin: 445px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWrite a function to count the even numbers in a multiplication table of products \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg 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width=\"34.5\" height=\"18\" alt=\"axb\" style=\"width: 34.5px; height: 18px;\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e with \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"font-family: STIXGeneral-webfont, serif; font-style: italic; font-weight: 400; color: rgb(33, 33, 33);\"\u003ea\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e and \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"font-family: STIXGeneral-webfont, serif; font-style: italic; font-weight: 400; color: rgb(33, 33, 33);\"\u003eb\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e both running from 1 to \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"font-family: STIXGeneral-webfont, serif; font-style: italic; font-weight: 400; color: rgb(33, 33, 33);\"\u003en\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 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alt=\"10x10 multiplication table and front cover of Marmaduke Multiply's\" data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = MTevens(n)\r\n   y = 0.75*n^2;\r\nend","test_suite":"%%\r\nn = 10;\r\ny = MTevens(n);\r\ny_correct = 75;\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nn = 24;\r\ny = MTevens(n);\r\ny_correct = 432;\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nn = 36;\r\ny = MTevens(n);\r\ny_correct = 972;\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nn = 121;\r\ny = MTevens(n);\r\ny_correct = 10920;\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nn = 453;\r\ny = MTevens(n);\r\ny_correct = 153680;\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nn = 1843;\r\ny = MTevens(n);\r\ny_correct = 2546565;\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nn = 3048;\r\ny = MTevens(n);\r\ny_correct = 6967728;\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nn = 9132;\r\ny = MTevens(n);\r\ny_correct = 62545068;\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nn = 25467;\r\ny = MTevens(n);\r\ny_correct = 486413333;\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nn = 400531;\r\ny = MTevens(n);\r\ny_correct = 120318611205;\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nn = 8843250;\r\ny = MTevens(n);\r\ny_correct = 58652302921875;\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nn = 94906265;\r\ny = MTevens(n);\r\ny_correct = 6755399304734536;\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nn = 1534;\r\ny = MTevens(MTevens(n));\r\ny_correct = 2336065763333;\r\nassert(isequal(y,y_correct))","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":46909,"edited_by":46909,"edited_at":"2026-05-27T03:22:28.000Z","deleted_by":null,"deleted_at":null,"solvers_count":4,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-27T03:22:21.000Z","updated_at":"2026-05-27T10:25:09.000Z","published_at":"2026-05-27T03:22:28.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc 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\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61345,"title":"Get The Opposite Of The Number Without Negative (-) On It","description":"You must get the opposite of the number X without making -X.\r\nHint: You can make it by Subtraction and Multiplication.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 51px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 401px 25.5px; transform-origin: 401px 25.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eYou must get the opposite of the number X without making -X.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eHint: You can make it by Subtraction and Multiplication.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = getOpposite(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = 1;\r\ny_correct = -1;\r\nassert(isequal(getOpposite(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5122697,"edited_by":5122697,"edited_at":"2026-05-23T17:34:53.000Z","deleted_by":null,"deleted_at":null,"solvers_count":7,"test_suite_updated_at":"2026-05-23T14:51:23.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-23T14:48:38.000Z","updated_at":"2026-05-27T09:26:49.000Z","published_at":"2026-05-23T14:48:38.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eYou must get the opposite of the number X without making -X.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eHint: You can make it by Subtraction and Multiplication.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61346,"title":"Find The Area Of Triangle Using Base \u0026 Height","description":"You should find the area of the Triangle using base and height.\r\nGood Luck!","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 51px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 401px 25.5px; transform-origin: 401px 25.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eYou should find the area of the Triangle using base and height.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eGood Luck!\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function area = triangleArea(base, height)\r\n  area = ;\r\nend","test_suite":"%%\r\nbase = 1;\r\nheight = 1;\r\narea = 0.5;\r\nassert(isequal(triangleArea(base, height),area))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5122697,"edited_by":5122697,"edited_at":"2026-05-23T17:34:26.000Z","deleted_by":null,"deleted_at":null,"solvers_count":10,"test_suite_updated_at":"2026-05-23T16:51:38.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-23T16:46:19.000Z","updated_at":"2026-05-27T09:28:37.000Z","published_at":"2026-05-23T16:49:16.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eYou should find the area of the Triangle using base and height.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eGood Luck!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61347,"title":"Find The Area Of The Circle","description":"Find the area of the Circle using PI.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 401px 10.5px; transform-origin: 401px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eFind the area of the Circle using PI.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function area = circleArea(r)\r\n  area = ;\r\nend","test_suite":"%%\r\nr = 1;\r\narea = pi * r^2;\r\nassert(isequal(circleArea(r),area))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5122697,"edited_by":5122697,"edited_at":"2026-05-23T17:33:44.000Z","deleted_by":null,"deleted_at":null,"solvers_count":10,"test_suite_updated_at":"2026-05-23T17:01:17.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-23T16:57:42.000Z","updated_at":"2026-05-27T09:30:49.000Z","published_at":"2026-05-23T16:59:46.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eFind the area of the Circle using PI.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61349,"title":"Trapezium","description":"Calculate the area of the Trapezium using it's bases and height.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 401px 10.5px; transform-origin: 401px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eCalculate the area of the Trapezium using it's bases and height.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function trapeziumArea = trapeziumArea(base1, base2, height)\r\n  base3 = ;\r\n  trapeziumArea = ;\r\nend","test_suite":"%%\r\nbase1 = 1;\r\nbase2 = 1;\r\nheight = 1;\r\ntrapeziumArea = 0.5*(base1+base2)*height;\r\nassert(isequal(trapeziumArea(base1, base2, height),trapeziumArea))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5122697,"edited_by":5122697,"edited_at":"2026-05-23T18:08:08.000Z","deleted_by":null,"deleted_at":null,"solvers_count":8,"test_suite_updated_at":"2026-05-23T18:08:08.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-23T17:59:40.000Z","updated_at":"2026-05-27T09:33:56.000Z","published_at":"2026-05-23T18:03:46.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eCalculate the area of the Trapezium using it's bases and height.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61348,"title":"Basic Physics I","description":"Calculate the energy by the famous formula of Albert Einstein.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 401px 10.5px; transform-origin: 401px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eCalculate the energy by the famous formula of Albert Einstein.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"c = 300000\r\nfunction E = E(m)\r\n  E = ;\r\nend","test_suite":"%%\r\nm = 1;\r\nE = 90000000000;\r\nassert(isequal(E(m),E))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5122697,"edited_by":5122697,"edited_at":"2026-05-26T12:35:46.000Z","deleted_by":null,"deleted_at":null,"solvers_count":8,"test_suite_updated_at":"2026-05-23T17:28:56.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-23T17:19:37.000Z","updated_at":"2026-05-27T09:32:44.000Z","published_at":"2026-05-23T17:23:28.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eCalculate the energy by the famous formula of Albert Einstein.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61350,"title":"Circle Perimeter","description":"Get the perimeter of the Circle by PI.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 401px 10.5px; transform-origin: 401px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eGet the perimeter of the Circle by PI.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function p = circleP(r)\r\n  p = ;\r\nend","test_suite":"%%\r\nr = 1;\r\np = 2*pi*r;\r\nassert(isequal(circleP(r),p))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5122697,"edited_by":5122697,"edited_at":"2026-05-24T11:52:44.000Z","deleted_by":null,"deleted_at":null,"solvers_count":8,"test_suite_updated_at":"2026-05-24T11:52:11.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-24T11:50:23.000Z","updated_at":"2026-05-27T09:34:58.000Z","published_at":"2026-05-24T11:52:11.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eGet the perimeter of the Circle by PI.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61352,"title":"Basic Algebra I","description":"You should solve the problem 3X - 2 = 7 by finding the value of X.\r\nYou must use this array/vector [2 3 7].\r\nGOOD LUCK!","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 81px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 401px 40.5px; transform-origin: 401px 40.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eYou should solve the problem \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003e3X - 2 = 7 \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eby finding the value of \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eX\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eYou must use this array/vector \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003e[2 3 7].\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGOOD LUCK!\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function X = equation()\r\n  nums = [2 3 7];\r\n  X = ;\r\nend","test_suite":"%%\r\nnums = [2 3 7]\r\nX = (nums(3)+nums(1))/nums(2);\r\nassert(isequal(equation(),X))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5122697,"edited_by":5122697,"edited_at":"2026-05-24T13:26:11.000Z","deleted_by":null,"deleted_at":null,"solvers_count":8,"test_suite_updated_at":"2026-05-24T13:13:31.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-24T13:07:29.000Z","updated_at":"2026-05-27T09:37:42.000Z","published_at":"2026-05-24T13:11:18.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eYou should solve the problem \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e3X - 2 = 7 \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003eby finding the value of \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eX\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eYou must use this array/vector \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[2 3 7].\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGOOD LUCK!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61351,"title":"Get The Square Root Of Number Power (^) Three","description":"Get the Square Root of number Power (^) Three.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 401px 10.5px; transform-origin: 401px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eGet the Square Root of number Power (^) Three.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function num = calc(n)\r\n  num = ;\r\nend","test_suite":"%%\r\nn = 1;\r\nnum = sqrt(n^3);\r\nassert(isequal(calc(n),num))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5122697,"edited_by":5122697,"edited_at":"2026-05-24T12:10:19.000Z","deleted_by":null,"deleted_at":null,"solvers_count":9,"test_suite_updated_at":"2026-05-24T12:06:24.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-24T11:57:15.000Z","updated_at":"2026-05-27T09:35:46.000Z","published_at":"2026-05-24T11:59:07.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eGet the Square Root of number Power (^) Three.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61353,"title":"Basic Algebra II","description":"You have the equation X^2 = n you should find the value of X.\r\nGOOD LUCK!","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 51px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 401px 25.5px; transform-origin: 401px 25.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eYou have the equation \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eX^2 = n \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eyou should find the value of \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eX\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGOOD LUCK!\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function X = equation(n)\r\n  X = ;\r\nend","test_suite":"%%\r\nn = 1;\r\nX = sqrt(n);\r\nassert(isequal(equation(n),X))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5122697,"edited_by":5122697,"edited_at":"2026-05-24T13:23:14.000Z","deleted_by":null,"deleted_at":null,"solvers_count":8,"test_suite_updated_at":"2026-05-24T13:23:14.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-24T13:20:58.000Z","updated_at":"2026-05-27T09:38:31.000Z","published_at":"2026-05-24T13:23:14.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eYou have the equation \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eX^2 = n \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr/\u003e\u003cw:t\u003eyou should find the value of \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eX\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr/\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr/\u003e\u003cw:t\u003eGOOD LUCK!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61354,"title":"Rhombus","description":"Get the area of the Rhombus using it's Diagonals.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 401px 10.5px; transform-origin: 401px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eGet the area of the Rhombus using it's Diagonals.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function area = area(d1,d2)\r\n  area = ;\r\nend","test_suite":"%%\r\nd1 = 1;\r\nd2 = 1;\r\narea = 0.5*(d1*d2);\r\nassert(isequal(area(d1,d2),area))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5122697,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":7,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-24T13:30:18.000Z","updated_at":"2026-05-27T09:39:14.000Z","published_at":"2026-05-24T13:30:18.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eGet the area of the Rhombus using it's Diagonals.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61355,"title":"Basic Algebra III","description":"Get the Cube Root of the number n.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 401px 10.5px; transform-origin: 401px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eGet the Cube Root of the number n.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function ans = cbRt(n)\r\n  ans = ;\r\nend","test_suite":"%%\r\nn = 8;\r\nans = nthroot(n,3);\r\nassert(isequal(cbRt(n),ans))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5122697,"edited_by":5122697,"edited_at":"2026-05-26T12:25:53.000Z","deleted_by":null,"deleted_at":null,"solvers_count":5,"test_suite_updated_at":"2026-05-26T12:25:53.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-26T12:24:06.000Z","updated_at":"2026-05-27T09:40:08.000Z","published_at":"2026-05-26T12:24:06.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eGet the Cube Root of the number n.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61357,"title":"Basic Physics III","description":"Calculate the Potential Energy (PE).","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 401px 10.5px; transform-origin: 401px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eCalculate the Potential Energy (PE).\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function PE = PE(w,h)\r\n  PE = ;\r\nend","test_suite":"%%\r\nw = 1;\r\nh = 1;\r\nPE = w*h;\r\nassert(isequal(PE(w,h),PE))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5122697,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":5,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-26T14:50:35.000Z","updated_at":"2026-05-27T09:41:48.000Z","published_at":"2026-05-26T14:50:35.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eCalculate the Potential Energy (PE).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61356,"title":"Basic Physics II","description":"Get the Kinetic Energy (KE).","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 401px 10.5px; transform-origin: 401px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eGet the Kinetic Energy (KE).\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function KE = KE(m,v)\r\n  KE = ;\r\nend","test_suite":"%%\r\nm = 1;\r\nv = 1;\r\nKE = 0.5*m*v^2;\r\nassert(isequal(KE(m,v),KE))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5122697,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":5,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-26T12:30:40.000Z","updated_at":"2026-05-27T09:41:02.000Z","published_at":"2026-05-26T12:30:40.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eGet the Kinetic Energy (KE).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61358,"title":"Basic Physics IV","description":"Calculate the Mechanical Energy (ME).","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 401px 10.5px; transform-origin: 401px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eCalculate the Mechanical Energy (ME).\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function ME = ME(PE,KE)\r\n  ME = ;\r\nend","test_suite":"%%\r\nPE = 1;\r\nKE = 1;\r\nME = PE+KE;\r\nassert(isequal(ME(PE,KE),ME))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5122697,"edited_by":5122697,"edited_at":"2026-05-26T14:58:18.000Z","deleted_by":null,"deleted_at":null,"solvers_count":5,"test_suite_updated_at":"2026-05-26T14:58:18.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-26T14:56:53.000Z","updated_at":"2026-05-27T09:43:20.000Z","published_at":"2026-05-26T14:56:53.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eCalculate the Mechanical Energy (ME).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":42526,"title":"Initialize a Natural Number matrix.","description":"Given length of matrix initialize a matrix consisting of natural numbers from 1 to n:\r\n\r\nn = 10;\r\nx = [ 1 2 3 4 5 6 7 8 9 10];\r\n\r\nn = 5;\r\nx = [1 2 3 4 5];","description_html":"\u003cp\u003eGiven length of matrix initialize a matrix consisting of natural numbers from 1 to n:\u003c/p\u003e\u003cp\u003en = 10;\r\nx = [ 1 2 3 4 5 6 7 8 9 10];\u003c/p\u003e\u003cp\u003en = 5;\r\nx = [1 2 3 4 5];\u003c/p\u003e","function_template":"function y = naturalNumbers(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = 1;\r\ny_correct = 1;\r\nassert(isequal(naturalNumbers(x),y_correct))\r\n\r\n%%\r\nx = 3;\r\ny_correct = [1 2 3];\r\nassert(isequal(naturalNumbers(x),y_correct))","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":48756,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":142,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2015-08-22T17:20:10.000Z","updated_at":"2026-05-26T13:57:36.000Z","published_at":"2015-08-22T17:24:03.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven length of matrix initialize a matrix consisting of natural numbers from 1 to n:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003en = 10; x = [ 1 2 3 4 5 6 7 8 9 10];\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003en = 5; x = [1 2 3 4 5];\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":58758,"title":"Hemisphere Volume on Top of a Cylinder","description":"This MATLAB function has to calculate the volume of a hemisphere placed on top of a cylinder, given valid inputs. It takes the radius of the cylinder and the height of the cylinder as input, and returns the total volume of the hemisphere and the cylinder combined.\r\n","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.440001px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 93px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 332px 46.5px; transform-origin: 332px 46.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 309px 31.5px; text-align: left; transform-origin: 309px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eThis MATLAB function has to calculate the volume of a hemisphere placed on top of a cylinder, given valid inputs. It takes the radius of the cylinder and the height of the cylinder as input, and returns the total volume of the hemisphere and the cylinder combined.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 309px 10.5px; text-align: left; transform-origin: 309px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function volume = computeHemisphereVolume(radius, height)\r\n\r\n    volume = 0;\r\nend","test_suite":"%%\r\nradius = 3;\r\nheight = 8;\r\nexpectedOutput = 282.743338823081;\r\nvolume = computeHemisphereVolume(radius, height);\r\nassert(abs(expectedOutput - volume) \u003c 1e-4)\r\n%%\r\nradius = 2.5;\r\nheight = 5;\r\nexpectedOutput = 130.899693899575;\r\nvolume = computeHemisphereVolume(radius, height);\r\nassert(abs(expectedOutput - volume) \u003c 1e-4)\r\n%%\r\nradius = 10;\r\nheight = 15;\r\nexpectedOutput = 6806.78408277789;\r\nvolume = computeHemisphereVolume(radius, height);\r\nassert(abs(expectedOutput - volume) \u003c 1e-4)\r\n%%\r\nradius = 0;\r\nheight = 12;\r\nexpectedOutput = 0;\r\nvolume = computeHemisphereVolume(radius, height);\r\nassert(abs(expectedOutput - volume) \u003c 1e-4)\r\n%%\r\nradius = 7.2;\r\nheight = 3.5;\r\nexpectedOutput = 1351.73935424539;\r\nvolume = computeHemisphereVolume(radius, height);\r\nassert(abs(expectedOutput - volume) \u003c 1e-4)\r\n","published":true,"deleted":false,"likes_count":13,"comments_count":4,"created_by":3429354,"edited_by":26769,"edited_at":"2023-12-02T00:24:04.000Z","deleted_by":null,"deleted_at":null,"solvers_count":74,"test_suite_updated_at":"2023-12-02T00:24:04.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2023-07-18T21:20:09.000Z","updated_at":"2026-05-24T20:38:13.000Z","published_at":"2023-07-18T21:20:09.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis MATLAB function has to calculate the volume of a hemisphere placed on top of a cylinder, given valid inputs. It takes the radius of the cylinder and the height of the cylinder as input, and returns the total volume of the hemisphere and the cylinder combined.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":2014,"title":"\"Find out the best cricket\"","description":"This is how I originally read Problem 2013, so let's just go with it.  Give me the first and last name of the best cricket, regardless of your input.","description_html":"\u003cp\u003eThis is how I originally read Problem 2013, so let's just go with it.  Give me the first and last name of the best cricket, regardless of your input.\u003c/p\u003e","function_template":"function y = BestCricket(x)\r\n  y = x;\r\nend","test_suite":"x = 1;\r\nassert(isequal(BestCricket(x),'Jiminy Cricket'))\r\n%%\r\nx = magic(7);\r\nassert(isequal(BestCricket(x),'Jiminy Cricket'))\r\n%%\r\nx='Who is the best cricket?';\r\nassert(isequal(BestCricket(x),'Jiminy Cricket'))\r\n","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":1615,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":131,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2013-11-26T16:35:20.000Z","updated_at":"2026-05-15T02:14:50.000Z","published_at":"2013-11-26T16:35:20.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis is how I originally read Problem 2013, so let's just go with it. Give me the first and last name of the best cricket, regardless of your input.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":44688,"title":"World Cup 2018 Prediction!","description":"Which team will be the winner?\r\n","description_html":"\u003cp\u003eWhich team will be the winner?\u003c/p\u003e","function_template":"function y = Worldcup2018winner()\r\n  y = \"????\"\r\nend","test_suite":"%%\r\nteams={'Russia','Saudi Arabia', 'Egypt', 'Uruguay', 'Portugal', 'Spain','Morocco','Iran',...\r\n    'France','Australia', 'Peru','Denmark', 'Brazil', 'Switzerland', 'Costa Rica', 'Serbia', ...\r\n    'Germany', 'Mexico', 'Sweden', 'STH Korea', 'Belgium', 'Panama', 'Tunisia', 'England' , ...\r\n    'Argentina','Iceland', 'Croatia', 'Nigeria', 'Poland', 'Senegal', 'Colombia', 'Japan'};\r\nd=false;\r\nfor i=1:numel(teams)\r\n    if strcmp(Worldcup2018winner(),teams{i})\r\n        d=true;\r\n        break;\r\n    end\r\nend\r\nassert(d)","published":true,"deleted":false,"likes_count":1,"comments_count":3,"created_by":218677,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":141,"test_suite_updated_at":"2018-06-15T17:39:57.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2018-06-15T17:38:14.000Z","updated_at":"2026-05-15T02:16:34.000Z","published_at":"2018-06-15T17:38:14.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWhich team will be the winner?\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":56230,"title":"compter le nombre de zéros dans une matrice","description":"écrire une fonction count_zeros qui prend en entrée une matrice M et détermine le nombre de zéros dans une matrice","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.440000534057617px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 42px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: left; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; \"\u003e\u003cspan style=\"\"\u003eécrire une fonction count_zeros qui prend en entrée une matrice M et détermine le nombre de zéros dans une matrice\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function N = count_zeros(M)\r\n  %a vous de jouer\r\nend","test_suite":"%%\r\nx = 0;\r\ny_correct = 1;\r\nassert(isequal(count_zeros(x),y_correct))\r\n%%\r\nx = [0 0 1 1 0 0.5];\r\ny_correct = 3;\r\nassert(isequal(count_zeros(x),y_correct))\r\n%%\r\nx = [0 0 1; 1 2 0.5; 0 0 3];\r\ny_correct = 4;\r\nassert(isequal(count_zeros(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":1,"created_by":63915,"edited_by":26769,"edited_at":"2022-11-23T21:23:15.000Z","deleted_by":null,"deleted_at":null,"solvers_count":57,"test_suite_updated_at":"2022-11-23T21:23:15.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2022-10-06T10:19:12.000Z","updated_at":"2026-05-21T15:39:58.000Z","published_at":"2022-10-06T10:19:11.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eécrire une fonction count_zeros qui prend en entrée une matrice M et détermine le nombre de zéros dans une matrice\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":42940,"title":"modulus of a number","description":"find the modulus of a given number","description_html":"\u003cp\u003efind the modulus of a given number\u003c/p\u003e","function_template":"function y = your_fcn_name(x)\r\n  y = abs(x);\r\nend","test_suite":"%%\r\nx = 1;\r\ny_correct = 1;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = -1;\r\ny_correct = 1;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = -3;\r\ny_correct = 3;\r\nassert(isequal(your_fcn_name(x),y_correct))","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":86789,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":240,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2016-09-01T21:06:06.000Z","updated_at":"2026-05-27T07:17:29.000Z","published_at":"2016-09-01T21:06:12.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003efind the modulus of a given number\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":44264,"title":"Calculate feeling temperature before climbing a mountain","description":"I sometimes climb a mountain.\r\nAs is well known, when the altitude becomes 100 (m) higher, the temperature lowers by 0.6 degrees Celsius.\r\nIn addition there is wind.\r\nAt wind velocity 1(m/s), the feeling temperature falls  1 degree Celsius.\r\n\r\ne.g.\r\n\r\n* temperature of the level ground(gT) : 25 degrees Celsius\r\n* wind velocity(v) : 10 m/s\r\n* at altitude(h) : 3000 m\r\n\r\nIn this case, feeling temperature(fT) is calculated as -3 degrees Celsius.\r\n","description_html":"\u003cp\u003eI sometimes climb a mountain.\r\nAs is well known, when the altitude becomes 100 (m) higher, the temperature lowers by 0.6 degrees Celsius.\r\nIn addition there is wind.\r\nAt wind velocity 1(m/s), the feeling temperature falls  1 degree Celsius.\u003c/p\u003e\u003cp\u003ee.g.\u003c/p\u003e\u003cul\u003e\u003cli\u003etemperature of the level ground(gT) : 25 degrees Celsius\u003c/li\u003e\u003cli\u003ewind velocity(v) : 10 m/s\u003c/li\u003e\u003cli\u003eat altitude(h) : 3000 m\u003c/li\u003e\u003c/ul\u003e\u003cp\u003eIn this case, feeling temperature(fT) is calculated as -3 degrees Celsius.\u003c/p\u003e","function_template":"function fT =  feeling_temperature(gT,h,v)\r\n  fT = gT;\r\nend","test_suite":"%%\r\ngT=25;\r\nh=3000;\r\nv=10;\r\n\r\nfT_correct = -3;\r\nassert(isequal(feeling_temperature(gT,h,v),fT_correct))\r\n\r\n%%\r\ngT=30;\r\nh=500;\r\nv=0;\r\n\r\nfT_correct=27;\r\nassert(isequal(feeling_temperature(gT,h,v),fT_correct))\r\n\r\n%%\r\ngT=28;\r\nh=2500;\r\nv=3;\r\n\r\nfT_correct=10;\r\nassert(isequal(feeling_temperature(gT,h,v),fT_correct))","published":true,"deleted":false,"likes_count":3,"comments_count":0,"created_by":102298,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":74,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2017-07-16T14:13:00.000Z","updated_at":"2026-05-22T11:48:16.000Z","published_at":"2017-07-16T14:28:25.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eI sometimes climb a mountain. As is well known, when the altitude becomes 100 (m) higher, the temperature lowers by 0.6 degrees Celsius. In addition there is wind. At wind velocity 1(m/s), the feeling temperature falls 1 degree Celsius.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ee.g.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003etemperature of the level ground(gT) : 25 degrees Celsius\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ewind velocity(v) : 10 m/s\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eat altitude(h) : 3000 m\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIn this case, feeling temperature(fT) is calculated as -3 degrees Celsius.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":54595,"title":"String Logic 18","description":"Examples:\r\n'DIG' --\u003e 'DG'\r\n'IMPORTANT' --\u003e 'IPRAT'\r\n'DEAL' --\u003e 'DA'\r\n'LIMB' --\u003e 'LM'\r\n'MOSTLY' --\u003e 'MSL'","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 171px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 85.5px; transform-origin: 407px 85.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eExamples:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e'DIG' --\u0026gt; 'DG'\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e'IMPORTANT' --\u0026gt; 'IPRAT'\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e'DEAL' --\u0026gt; 'DA'\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e'LIMB' --\u0026gt; 'LM'\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e'MOSTLY' --\u0026gt; 'MSL'\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = StringLogic(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = 'DIG';\r\ny_correct = 'DG';\r\nassert(isequal(StringLogic(x),y_correct))\r\n\r\n%%\r\nx = 'IMPORTANT';\r\ny_correct = 'IPRAT';\r\nassert(isequal(StringLogic(x),y_correct))\r\n\r\n%%\r\nx = 'DEAL';\r\ny_correct = 'DA';\r\nassert(isequal(StringLogic(x),y_correct))\r\n\r\n%%\r\nx = 'LIMB';\r\ny_correct = 'LM';\r\nassert(isequal(StringLogic(x),y_correct))\r\n\r\n%%\r\nx = 'MOSTLY';\r\ny_correct = 'MSL';\r\nassert(isequal(StringLogic(x),y_correct))\r\n\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":232412,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":100,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2022-05-05T07:12:14.000Z","updated_at":"2026-05-15T02:37:09.000Z","published_at":"2022-05-05T07:12:14.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eExamples:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e'DIG' --\u0026gt; 'DG'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e'IMPORTANT' --\u0026gt; 'IPRAT'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e'DEAL' --\u0026gt; 'DA'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e'LIMB' --\u0026gt; 'LM'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e'MOSTLY' --\u0026gt; 'MSL'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":42678,"title":"For a given linear index as input for n sized square matrix, find corresponding row and column.","description":"If input is 1, the row and column will be 1 and 1 respectively.","description_html":"\u003cp\u003eIf input is 1, the row and column will be 1 and 1 respectively.\u003c/p\u003e","function_template":"function rc = your_fcn_name(i,n)\r\n  % i is index and n is length of matrix \r\nend","test_suite":"%%\r\ni = 1;n = 1;\r\ny_correct = [1,1];\r\nassert(isequal(your_fcn_name(i,n),y_correct))\r\n%%\r\ni = 7;n = 3;\r\ny_correct = [1,3];\r\nassert(isequal([your_fcn_name(i,n)],y_correct))\r\n%%\r\ni = 16;n = 7;\r\ny_correct = [2,3];\r\nassert(isequal([your_fcn_name(i,n)],y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":3,"created_by":28123,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":77,"test_suite_updated_at":"2015-10-31T18:52:14.000Z","rescore_all_solutions":true,"group_id":1,"created_at":"2015-10-31T16:23:03.000Z","updated_at":"2026-05-15T03:12:19.000Z","published_at":"2015-10-31T16:38:06.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf input is 1, the row and column will be 1 and 1 respectively.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":45537,"title":"Get the area of ​​the square.","description":"Four circles are inscribed in the square ABCD. The perimeter of each circle is *aπ*.\r\n\r\n\u003c\u003chttp://imgfz.com/i/UzgCJut.png\u003e\u003e\r\n\r\nGiven *a*, obtain the area of ​​the square.\r\n","description_html":"\u003cp\u003eFour circles are inscribed in the square ABCD. The perimeter of each circle is \u003cb\u003eaπ\u003c/b\u003e.\u003c/p\u003e\u003cimg src = \"http://imgfz.com/i/UzgCJut.png\"\u003e\u003cp\u003eGiven \u003cb\u003ea\u003c/b\u003e, obtain the area of ​​the square.\u003c/p\u003e","function_template":"function y = squartArea(a)\r\n     y = a;\r\nend","test_suite":"%%\r\na = 0;\r\ny = 0;\r\nassert(isequal(squartArea(a),y))\r\n%%\r\na = 8;\r\ny = 256;\r\nassert(isequal(squartArea(a),y))\r\n%%\r\na = 1;\r\ny = 4;\r\nassert(isequal(squartArea(a),y))\r\n%%\r\na = 10;\r\ny = 400;\r\nassert(isequal(squartArea(a),y))\r\n%%\r\na = 50;\r\ny = 10000;\r\nassert(isequal(squartArea(a),y))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":446926,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":102,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-05-18T03:09:51.000Z","updated_at":"2026-05-24T15:55:13.000Z","published_at":"2020-05-18T03:09:51.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/image\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/media/image1.JPEG\"}],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFour circles are inscribed in the square ABCD. The perimeter of each circle is\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eaπ\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ea\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, obtain the area of the square.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray 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fb+I9KtjBZeG9CiQsXY/21MzOxxlmY22WY4GSSSfWgBLvTotL1LwnbRFnxqMzvI+C8rtazlnY+pJJOMDngAACuurlmtPEWpa3o8+oafpVra2Nw87tBqEk7tmGSMAKYEHWQHOeg6V1NABRRRQBXu5mt7OeZUDtHGzBS2M4BOM4OPyNQWt1dNcG2vbaOGYpvTypjIrKDg8lVIIJGRjHI5POLF1b/arWa3MjoJUZCyY3AEY4zkZ/CobSyNuzSS3U91KflEswUEL1wAqqAM+2T3PAwAXaKKKACiiigAooooAKKKKACiiigAooooAKKKKAKNtc3F1KWWCMWhyFkMp8xiDj7u3ABwSDu9OKvVRgsDbXJeK8uBASSLY7CgJOTg7dw5yQN2BnAAAAq9QAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQB/9k=\"}]}"},{"id":54109,"title":"Get the n-th rand number with given seed","description":"Given seed s, return the n-th rand number using rand(). Round the answer with 4 digits.\r\nn is a postive integer.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 51px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 25.5px; transform-origin: 407px 25.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 276px 8px; transform-origin: 276px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven seed s, return the n-th rand number using rand(). Round the answer with 4 digits.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 67px 8px; transform-origin: 67px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003en is a postive integer.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function ans = getNthRand(s,n)\r\n","test_suite":"%%\r\ns = 1; n = 3;\r\ny_correct = .0001;\r\nassert(isequal(getNthRand(s,n),y_correct))\r\n%%\r\ns = 2; n = 100;\r\ny_correct = .8817;\r\nassert(isequal(getNthRand(s,n),y_correct))\r\n%%\r\ns = 1.2; n = 7;\r\ny_correct = .1863;\r\nassert(isequal(getNthRand(s,n),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":2044730,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":42,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2022-03-04T18:35:12.000Z","updated_at":"2026-05-15T10:14:06.000Z","published_at":"2022-03-04T18:35:12.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven seed s, return the n-th rand number using rand(). Round the answer with 4 digits.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003en is a postive integer.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":1382,"title":"Schwarzschild radius","description":"Compute the Schwarzschild radius for objects of mass m (kg). Use c = 299,792.458 km/s and G = 6.6738*10^-11 N*(m/kg)^2. Your function should give the result in m.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 42px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 21px; transform-origin: 407px 21px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 40.5px 8px; transform-origin: 40.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eCompute the\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 2px 8px; transform-origin: 2px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"/#null\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eSchwarzschild radius\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 246px 8px; transform-origin: 246px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e for objects of mass m (kg). Use c = 299,792.458 km/s and G = 6.6738*10^-11 N*(m/kg)^2. Your function should give the result in m.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = Schwarzschild_radius(m)\r\n  y = m;\r\nend","test_suite":"%%\r\nm = 5.98e24/81; % Moon\r\ny_correct = 1e-4; % m\r\nassert(isequal(Schwarzschild_radius(m),y_correct))\r\n\r\n%%\r\nm = 5.98e24; % Earth\r\ny_correct = 0.0089; % m\r\nassert(isequal(Schwarzschild_radius(m),y_correct))\r\n\r\n%%\r\nm = 1.89813e27; % Jupiter\r\ny_correct =  2.819; % m\r\nassert(isequal(Schwarzschild_radius(m),y_correct))\r\n\r\n%%\r\nm = 2e30; % Sun\r\ny_correct =  2970.2416; % m\r\nassert(isequal(Schwarzschild_radius(m),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":3,"created_by":810,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":57,"test_suite_updated_at":"2013-03-27T16:02:16.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-03-24T00:27:37.000Z","updated_at":"2026-05-26T21:59:48.000Z","published_at":"2013-03-24T00:30:30.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCompute the\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eSchwarzschild radius\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e for objects of mass m (kg). Use c = 299,792.458 km/s and G = 6.6738*10^-11 N*(m/kg)^2. Your function should give the result in m.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":55915,"title":"Juros Compostos","description":"Faça uma função que receba um capital inicial (C), uma taxa de juros a ser aplicada (i) e um tempo (t) para qual será aplicado o investimento. Retorne o montante final.\r\nTodos os calculos faram baseados em meses. E o valor final deve ser expresso em 2 casas decimais.\r\n\r\nJurosCompostos(2000, 0.03, 4) = 2251.02 ","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 132.438px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 66.2188px; transform-origin: 407px 66.2188px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFaça uma função que receba um capital inicial (C), uma taxa de juros a ser aplicada (i) e um tempo (t) para qual será aplicado o investimento. Retorne o montante final.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eTodos os calculos faram baseados em meses. E o valor final deve ser expresso em 2 casas decimais.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 20.4375px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 10.2188px; transform-origin: 404px 10.2188px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003eJurosCompostos(2000, 0.03, 4) = 2251.02 \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function m = JurosCompostos(c, i, t)\r\n  % faça a sua função\r\nend","test_suite":"%%\r\nc = 2000;\r\ni = 0.03;\r\nt = 4;\r\ny_correct = 2251.02 ;\r\nassert(isequal(JurosCompostos(c, i, t) ,y_correct))\r\n\r\n\r\n%%\r\nc = 8000;\r\ni = 0.012;\r\nt = 6;\r\ny_correct = 8593.56 ;\r\nassert(isequal(JurosCompostos(c, i, t) ,y_correct))\r\n\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":2564100,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":36,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2022-09-17T19:11:27.000Z","updated_at":"2026-05-15T10:36:48.000Z","published_at":"2022-09-17T19:11:27.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFaça uma função que receba um capital inicial (C), uma taxa de juros a ser aplicada (i) e um tempo (t) para qual será aplicado o investimento. Retorne o montante final.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eTodos os calculos faram baseados em meses. E o valor final deve ser expresso em 2 casas decimais.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[JurosCompostos(2000, 0.03, 4) = 2251.02 ]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":51163,"title":"Total price with tax calculation for (m) items and price (p)","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 40.8889px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 406.5px 20.4444px; transform-origin: 406.5px 20.4444px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 20.4444px; text-align: left; transform-origin: 383.5px 20.4444px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eWrite a code that will calculate the total price with tax (T) of (m) items that carry price (p). Consider the tax rate as (r). Round the total price to two decimal places. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function T = Total_price(m,n,r)\r\n\r\nend","test_suite":"%%\r\np = 1;\r\nm=2;\r\nr=0.05;\r\nT_correct = 2.1;\r\nassert(isequal(Total_price(p,m,r),T_correct))\r\n\r\n%%\r\np = 4;\r\nm=5;\r\nr=0.1;\r\nT_correct = 22;\r\nassert(isequal(Total_price(p,m,r),T_correct))\r\n\r\n%%\r\np = 4.85;\r\nm=5;\r\nr=0.1;\r\nT_correct = 26.68;\r\nassert(isequal(Total_price(p,m,r),T_correct))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":995198,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":37,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2021-03-24T06:47:24.000Z","updated_at":"2026-05-15T10:52:02.000Z","published_at":"2021-03-24T06:47:24.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWrite a code that will calculate the total price with tax (T) of (m) items that carry price (p). Consider the tax rate as (r). Round the total price to two decimal places. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":44473,"title":"Let's make puddings !","description":"We will make puddings with eggs, milk and sugar.\r\nTo make one pudding, we need one egg, 140(cc) of milk, 15 (g) of sugar.\r\nNow We have x eggs,  y (cc) of milk, z (g) of sugar.\r\nHow many puddings can we make?\r\n\r\neg. When we have 3 eggs, 300cc milk, 300g sugar...\r\n\r\ninput :  x = 3, y = 300, z = 300\r\n\r\noutput :  Puddings= 2","description_html":"\u003cp\u003eWe will make puddings with eggs, milk and sugar.\r\nTo make one pudding, we need one egg, 140(cc) of milk, 15 (g) of sugar.\r\nNow We have x eggs,  y (cc) of milk, z (g) of sugar.\r\nHow many puddings can we make?\u003c/p\u003e\u003cp\u003eeg. When we have 3 eggs, 300cc milk, 300g sugar...\u003c/p\u003e\u003cp\u003einput :  x = 3, y = 300, z = 300\u003c/p\u003e\u003cp\u003eoutput :  Puddings= 2\u003c/p\u003e","function_template":"function Puddings = Egg_Milk_Sugar(x,y,z)\r\n  Puddings = 100;\r\nend","test_suite":"%% 1\r\nx = 3;\r\ny = 300;\r\nz = 300;\r\nC = 2;\r\nassert(isequal(Egg_Milk_Sugar(x,y,z),C))\r\n%% 2 \r\nx = 0;\r\ny = 999;\r\nz = 999;\r\nC = 0;\r\nassert(isequal(Egg_Milk_Sugar(x,y,z),C))\r\n%% 3\r\nx = 12;\r\ny = 1000;\r\nz = 100;\r\nC = 6;\r\nassert(isequal(Egg_Milk_Sugar(x,y,z),C))","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":137687,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":56,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2017-12-27T02:51:08.000Z","updated_at":"2026-05-25T11:42:47.000Z","published_at":"2017-12-27T03:32:17.000Z","restored_at":"2018-02-06T15:11:49.000Z","restored_by":null,"spam":false,"simulink":false,"admin_reviewed":true,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWe will make puddings with eggs, milk and sugar. To make one pudding, we need one egg, 140(cc) of milk, 15 (g) of sugar. Now We have x eggs, y (cc) of milk, z (g) of sugar. How many puddings can we make?\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eeg. When we have 3 eggs, 300cc milk, 300g sugar...\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003einput : x = 3, y = 300, z = 300\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eoutput : Puddings= 2\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":42976,"title":"iteration of N blank spot","description":"we have N spot which can be blank o filled calculate the number of iteration for these spots. e.g. N=2 1- blank blank 2- blank full 3- full blank 4- full full iteration is 4 e.g. N=3 1- blank blank blank 2- blank blank full 3- blank full blank 4- blank full full 5- full blank blank 6- full blank full 7- full full blank 8- full full full iteration is 8","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 63px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 31.5px; transform-origin: 407px 31.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 372.5px 8px; transform-origin: 372.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003ewe have N spot which can be blank o filled calculate the number of iteration for these spots. e.g. N=2 1- blank blank 2- blank full 3- full blank 4- full full iteration is 4 e.g. N=3 1- blank blank blank 2- blank blank full 3- blank full blank 4- blank full full 5- full blank blank 6- full blank full 7- full full blank 8- full full full iteration is 8\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = your_fcn_name(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = 1;\r\ny_correct = 2;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = 5;\r\ny_correct = 32;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = 8;\r\ny_correct = 256;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = 11;\r\ny_correct = 2048;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = 16;\r\ny_correct = 65536;\r\nassert(isequal(your_fcn_name(x),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":2,"created_by":86389,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":61,"test_suite_updated_at":"2021-06-17T14:24:43.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2016-09-02T16:46:32.000Z","updated_at":"2026-04-22T05:15:27.000Z","published_at":"2016-09-02T16:46:32.000Z","restored_at":"2022-02-16T22:15:33.000Z","restored_by":null,"spam":false,"simulink":false,"admin_reviewed":true,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ewe have N spot which can be blank o filled calculate the number of iteration for these spots. e.g. N=2 1- blank blank 2- blank full 3- full blank 4- full full iteration is 4 e.g. N=3 1- blank blank blank 2- blank blank full 3- blank full blank 4- blank full full 5- full blank blank 6- full blank full 7- full full blank 8- full full full iteration is 8\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":49657,"title":"Determine the area of square if length of the diagonal is given","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 10.5px; transform-origin: 407px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eWe have to find the area of square if the length of the diagonal of a square is given.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = your_fcn_name(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = 4;\r\ny_correct = 8;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":822117,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":75,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-12-29T15:05:52.000Z","updated_at":"2026-05-24T15:57:49.000Z","published_at":"2020-12-29T15:05:52.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWe have to find the area of square if the length of the diagonal of a square is given.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"}],"problem_search":{"errors":[],"problems":[null,{"id":811,"title":"Genome Sequence 004: Long 3rd Generation Segment Correction","description":"The Melopsittacus undulates genome, Parrot Budgerigar, was successfully sequenced in July 2012 using long 3rd Gen sequences provided by \u003chttp://www.pacificbiosciences.com/ PacBio\u003e. The \u003chttp://assemblathon.org/a-parrot-a-fish-and-a-snake-walk-into-a-bar Assemblathon Genome Contest\u003e led the team of Phillippy, Koren and Jarvis to successfully \u003chttp://www.sciencedaily.com/releases/2012/07/120702210229.htm Sequence Parrot DNA\u003e using the PacBio 3rd Generation data and Illumina 2nd Gen data.\r\n\r\nThe 3rd gen PacBio data is very long, 1K-20K, but has 15% error rate. The Illumina data is 100-500 long with \u003c1% error rate. Jarvis and his team combined this data to achieve \u003c 0.1% error rate.\r\n\r\nGenome Challenge 004 is the correction of simplified PacBio simulated reads with high error rate.\r\n\r\n*Input:* \r\n\r\nCall 1: empty array, segment Width, Flag=0\r\n\r\nCall 2: N PacBio DNA vectors (N x width), Segment Width, Flag=1\r\n\r\n*Output:* \r\n\r\nCall 1: empty vector, Number of Requested Vectors\r\n\r\nCall 2: Corrected DNA vector, Number of Requested Vectors\r\n\r\n*Score:* Number of N vectors used to produce correct vector for w=1024 case\r\n\r\nThe first call to the PacBio_fix routine returns the number of vectors requested to produce a final product. This may be a function of w.\r\n\r\nThe second call to PacBio_fix will have a DNA matix (N x width) and flag=1.\r\n\r\nThe response to the second call is the fixed DNA sequence, vector of width w.\r\n\r\n*example:*\r\nFirst call return : N=3\r\n\r\n  01230123111122223333 Truth\r\n  Input example\r\n  01232123112122221332 Injected errors\r\n  01130123111122123323\r\n  11230133121122223333\r\n\r\n  Output: \r\n  01230123111122223333 Truth, hopefully\r\n\r\n\r\nThis data is simplified by only having simple substitutions and the data sets are provided pre-aligned. \r\n\r\nThe real PacBio data is quite a bit more complicated. Values may be added, deleted, substituted, and are of varying lengths. This causes alignment issues.\r\n\r\nFollow-Up Challenges: Sample Data from the PacBio site for \u003chttp://www.cbcb.umd.edu/software/PBcR/ Lambda Phage\u003e will be molded into various Challenges. Possible challenges are correcting individual long segments and assembling multiple long segments into the full Lambda Phage genome. The Parrot genome is too big for Cody to solve in 50 seconds.\r\n","description_html":"\u003cp\u003eThe Melopsittacus undulates genome, Parrot Budgerigar, was successfully sequenced in July 2012 using long 3rd Gen sequences provided by \u003ca href=\"http://www.pacificbiosciences.com/\"\u003ePacBio\u003c/a\u003e. The \u003ca href=\"http://assemblathon.org/a-parrot-a-fish-and-a-snake-walk-into-a-bar\"\u003eAssemblathon Genome Contest\u003c/a\u003e led the team of Phillippy, Koren and Jarvis to successfully \u003ca href=\"http://www.sciencedaily.com/releases/2012/07/120702210229.htm\"\u003eSequence Parrot DNA\u003c/a\u003e using the PacBio 3rd Generation data and Illumina 2nd Gen data.\u003c/p\u003e\u003cp\u003eThe 3rd gen PacBio data is very long, 1K-20K, but has 15% error rate. The Illumina data is 100-500 long with \u0026lt;1% error rate. Jarvis and his team combined this data to achieve \u0026lt; 0.1% error rate.\u003c/p\u003e\u003cp\u003eGenome Challenge 004 is the correction of simplified PacBio simulated reads with high error rate.\u003c/p\u003e\u003cp\u003e\u003cb\u003eInput:\u003c/b\u003e\u003c/p\u003e\u003cp\u003eCall 1: empty array, segment Width, Flag=0\u003c/p\u003e\u003cp\u003eCall 2: N PacBio DNA vectors (N x width), Segment Width, Flag=1\u003c/p\u003e\u003cp\u003e\u003cb\u003eOutput:\u003c/b\u003e\u003c/p\u003e\u003cp\u003eCall 1: empty vector, Number of Requested Vectors\u003c/p\u003e\u003cp\u003eCall 2: Corrected DNA vector, Number of Requested Vectors\u003c/p\u003e\u003cp\u003e\u003cb\u003eScore:\u003c/b\u003e Number of N vectors used to produce correct vector for w=1024 case\u003c/p\u003e\u003cp\u003eThe first call to the PacBio_fix routine returns the number of vectors requested to produce a final product. This may be a function of w.\u003c/p\u003e\u003cp\u003eThe second call to PacBio_fix will have a DNA matix (N x width) and flag=1.\u003c/p\u003e\u003cp\u003eThe response to the second call is the fixed DNA sequence, vector of width w.\u003c/p\u003e\u003cp\u003e\u003cb\u003eexample:\u003c/b\u003e\r\nFirst call return : N=3\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003e01230123111122223333 Truth\r\nInput example\r\n01232123112122221332 Injected errors\r\n01130123111122123323\r\n11230133121122223333\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003eOutput: \r\n01230123111122223333 Truth, hopefully\r\n\u003c/pre\u003e\u003cp\u003eThis data is simplified by only having simple substitutions and the data sets are provided pre-aligned.\u003c/p\u003e\u003cp\u003eThe real PacBio data is quite a bit more complicated. Values may be added, deleted, substituted, and are of varying lengths. This causes alignment issues.\u003c/p\u003e\u003cp\u003eFollow-Up Challenges: Sample Data from the PacBio site for \u003ca href=\"http://www.cbcb.umd.edu/software/PBcR/\"\u003eLambda Phage\u003c/a\u003e will be molded into various Challenges. Possible challenges are correcting individual long segments and assembling multiple long segments into the full Lambda Phage genome. The Parrot genome is too big for Cody to solve in 50 seconds.\u003c/p\u003e","function_template":"function [M_fix,N]=PacBio_fix(M,w,flag)\r\n% 1st Call\r\n% M is empty\r\n% w is width of segment\r\n% flag is 0\r\n% Ouput is N, the number of segments requested to fix the segment\r\n% 2nd Call\r\n% M is an Nxw array of values [0:3]\r\n\r\n M_fix=[];\r\n N=1; % needed for 2nd call with flag==1\r\n if flag==0 % Requested number of Segments\r\n  N=1;\r\n  return;\r\n end\r\n\r\nM_fix=M(1,:);\r\n\r\n\r\nend","test_suite":"%%\r\nfeval(@assignin,'caller','score',0);\r\n%%\r\nM=[];\r\nflag=0;\r\nw=100;\r\n[M_fix,N]=PacBio_fix(M,w,flag);\r\n\r\nM_truth=randi(4,1,w,'uint8')-1;\r\nM=repmat(M_truth,N,1);\r\n\r\n% Apply 15% substitution error\r\nqerr=floor(.15*N*w);\r\nerrvec=randi(N*w,qerr,1);\r\nerrval=randi(4,qerr,1)-1;\r\n\r\nM(errvec)=errval;\r\n\r\nflag=1;\r\ntic\r\n[M_fix,N]=PacBio_fix(M,w,flag);\r\ntoc\r\n\r\nassert(isequal(M_fix,M_truth),sprintf('Error Count=%i',sum(M_fix~=M_truth)))\r\n%%\r\nM=[];\r\nflag=0;\r\nw=6144;\r\n[M_fix,N]=PacBio_fix(M,w,flag);\r\n\r\nM_truth=randi(4,1,w,'uint8')-1;\r\nM=repmat(M_truth,N,1);\r\n\r\n% Apply 15% substitution error\r\nqerr=floor(.15*N*w);\r\nerrvec=randi(N*w,qerr,1);\r\nerrval=randi(4,qerr,1)-1;\r\n\r\nM(errvec)=errval;\r\n\r\nflag=1;\r\ntic\r\n[M_fix,N]=PacBio_fix(M,w,flag);\r\ntoc\r\n\r\nassert(isequal(M_fix,M_truth),sprintf('Error Count=%i',sum(M_fix~=M_truth)))\r\n\r\n%%\r\n% Size Performance is based on w=1024 case\r\nM=[];\r\nflag=0;\r\nw=1024;\r\n[M_fix,N]=PacBio_fix(M,w,flag);\r\n\r\nM_truth=randi(4,1,w,'uint8')-1;\r\nM=repmat(M_truth,N,1);\r\n\r\n% Apply 15% substitution error\r\nqerr=floor(.15*N*w);\r\nerrvec=randi(N*w,qerr,1);\r\nerrval=randi(4,qerr,1)-1;\r\n\r\nM(errvec)=errval;\r\n\r\nflag=1;\r\ntic\r\n[M_fix,not_N]=PacBio_fix(M,w,flag);\r\ntoc\r\n\r\nassert(isequal(M_fix,M_truth),sprintf('Error Count=%i',sum(M_fix~=M_truth)))\r\n\r\nfeval(@assignin,'caller','score',min(20,N));\r\n\r\n\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":3,"test_suite_updated_at":"2012-10-08T02:30:34.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-07-01T05:26:57.000Z","updated_at":"2026-05-26T02:20:13.000Z","published_at":"2012-10-08T02:29:50.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Melopsittacus undulates genome, Parrot Budgerigar, was successfully sequenced in July 2012 using long 3rd Gen sequences provided by\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://www.pacificbiosciences.com/\\\"\u003e\u003cw:r\u003e\u003cw:t\u003ePacBio\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e. The\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://assemblathon.org/a-parrot-a-fish-and-a-snake-walk-into-a-bar\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eAssemblathon Genome Contest\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e led the team of Phillippy, Koren and Jarvis to successfully\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://www.sciencedaily.com/releases/2012/07/120702210229.htm\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eSequence Parrot DNA\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e using the PacBio 3rd Generation data and Illumina 2nd Gen data.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe 3rd gen PacBio data is very long, 1K-20K, but has 15% error rate. The Illumina data is 100-500 long with \u0026lt;1% error rate. Jarvis and his team combined this data to achieve \u0026lt; 0.1% error rate.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGenome Challenge 004 is the correction of simplified PacBio simulated reads with high error rate.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInput:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCall 1: empty array, segment Width, Flag=0\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCall 2: N PacBio DNA vectors (N x width), Segment Width, Flag=1\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCall 1: empty vector, Number of Requested Vectors\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCall 2: Corrected DNA vector, Number of Requested Vectors\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eScore:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e Number of N vectors used to produce correct vector for w=1024 case\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe first call to the PacBio_fix routine returns the number of vectors requested to produce a final product. This may be a function of w.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe second call to PacBio_fix will have a DNA matix (N x width) and flag=1.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe response to the second call is the fixed DNA sequence, vector of width w.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eexample:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e First call return : N=3\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[01230123111122223333 Truth\\nInput example\\n01232123112122221332 Injected errors\\n01130123111122123323\\n11230133121122223333\\n\\nOutput: \\n01230123111122223333 Truth, hopefully]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis data is simplified by only having simple substitutions and the data sets are provided pre-aligned.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe real PacBio data is quite a bit more complicated. Values may be added, deleted, substituted, and are of varying lengths. This causes alignment issues.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFollow-Up Challenges: Sample Data from the PacBio site for\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://www.cbcb.umd.edu/software/PBcR/\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eLambda Phage\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e will be molded into various Challenges. Possible challenges are correcting individual long segments and assembling multiple long segments into the full Lambda Phage genome. The Parrot genome is too big for Cody to solve in 50 seconds.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":738,"title":"Criss_Cross_010 : Unique elements, Square array, Words in one array","description":"Criss Cross matrix puzzle - Square matrix, Unique elements, Single Word List\r\n\r\nArrange the \"words\" into a solid square such that all words are used.\r\n\r\nGiven an array of words make the original Square or Square Transpose.\r\n\r\nWords are left to Right or Top to Bottom. No fliplr or flipud.\r\n\r\n*Example:*\r\n\r\nM_orig = [1 2 3; 4 5 6; 7 8 9]\r\n\r\nvr = [1 2 3; 4 5 6; 7 8 9]\r\n\r\nvc = [1 2 3; 4 5 6; 7 8 9]\r\n\r\n*Inputs:*\r\n\r\nw = [1 2 3; 4 5 6; 7 8 9;1 4 7; 2 5 8; 3 6 9]\r\n\r\nsorted w gives\r\n\r\nw = [1 2 3; 1 4 7; 2 5 8; 3 6 9; 4 5 6; 7 8 9]\r\n\r\n\r\n*Output:*\r\n\r\nM_out = [1 2 3; 4 5 6; 7 8 9] or\r\n\r\nM_out=[1 4 7; 2 5 8; 3 6 9]\r\n\r\n\r\nMax size : 256\r\n\r\nThis is the second in the Criss Cross puzzles series.\r\n\r\nFollow up puzzles will have non-unique values and quite a few other variations.\r\n","description_html":"\u003cp\u003eCriss Cross matrix puzzle - Square matrix, Unique elements, Single Word List\u003c/p\u003e\u003cp\u003eArrange the \"words\" into a solid square such that all words are used.\u003c/p\u003e\u003cp\u003eGiven an array of words make the original Square or Square Transpose.\u003c/p\u003e\u003cp\u003eWords are left to Right or Top to Bottom. No fliplr or flipud.\u003c/p\u003e\u003cp\u003e\u003cb\u003eExample:\u003c/b\u003e\u003c/p\u003e\u003cp\u003eM_orig = [1 2 3; 4 5 6; 7 8 9]\u003c/p\u003e\u003cp\u003evr = [1 2 3; 4 5 6; 7 8 9]\u003c/p\u003e\u003cp\u003evc = [1 2 3; 4 5 6; 7 8 9]\u003c/p\u003e\u003cp\u003e\u003cb\u003eInputs:\u003c/b\u003e\u003c/p\u003e\u003cp\u003ew = [1 2 3; 4 5 6; 7 8 9;1 4 7; 2 5 8; 3 6 9]\u003c/p\u003e\u003cp\u003esorted w gives\u003c/p\u003e\u003cp\u003ew = [1 2 3; 1 4 7; 2 5 8; 3 6 9; 4 5 6; 7 8 9]\u003c/p\u003e\u003cp\u003e\u003cb\u003eOutput:\u003c/b\u003e\u003c/p\u003e\u003cp\u003eM_out = [1 2 3; 4 5 6; 7 8 9] or\u003c/p\u003e\u003cp\u003eM_out=[1 4 7; 2 5 8; 3 6 9]\u003c/p\u003e\u003cp\u003eMax size : 256\u003c/p\u003e\u003cp\u003eThis is the second in the Criss Cross puzzles series.\u003c/p\u003e\u003cp\u003eFollow up puzzles will have non-unique values and quite a few other variations.\u003c/p\u003e","function_template":"function M_out = Criss_Cross(w)\r\n\r\n M_out=zeros(size(w,2));\r\n \r\nend","test_suite":"%%\r\nformat long\r\nformat compact\r\nseed=clock;\r\nseed=1000*seed(6);\r\nrng(seed);\r\n\r\nn=4;\r\n% Create a Unique element square array\r\nM=randperm(n*n);\r\nM=reshape(M,n,n)\r\n\r\nvr=M(1:n,:);\r\nvc=M(:,1:n);\r\n\r\nw=[vr;vc'];\r\nw=sortrows(w);\r\n\r\nM_out=Criss_Cross(w)\r\n\r\nassert(isequal(M,M_out)||isequal(M',M_out));\r\n%%\r\nseed=clock;\r\nseed=1000*seed(6);\r\nrng(seed);\r\n\r\nn=8;\r\n% Create a Unique element square array\r\nM=randperm(n*n);\r\nM=reshape(M,n,n)\r\n\r\nvr=M(1:n,:);\r\nvc=M(:,1:n);\r\n\r\nw=[vr;vc'];\r\nw=sortrows(w);\r\n\r\nM_out=Criss_Cross(w)\r\n\r\nassert(isequal(M,M_out)||isequal(M',M_out));\r\n%%\r\nseed=clock;\r\nseed=1000*seed(6);\r\nrng(seed);\r\n\r\nn=16;\r\n% Create a Unique element square array\r\nM=randperm(n*n);\r\nM=reshape(M,n,n);\r\n\r\nvr=M(1:n,:);\r\nvc=M(:,1:n);\r\n\r\nw=[vr;vc'];\r\nw=sortrows(w);\r\n\r\ntic\r\nM_out=Criss_Cross(w);\r\ntoc\r\n\r\nassert(isequal(M,M_out)||isequal(M',M_out));\r\n%%\r\nseed=clock;\r\nseed=1000*seed(6);\r\nrng(seed);\r\n\r\nn=16;\r\n% Create a Unique element square array\r\nM=randperm(n*n);\r\nM=reshape(M,n,n);\r\n\r\nvr=M(1:n,:);\r\nvc=M(:,1:n);\r\n\r\nw=[vr;vc'];\r\nw=sortrows(w);\r\n\r\ntic\r\nM_out=Criss_Cross(w);\r\ntoc\r\n\r\nassert(isequal(M,M_out)||isequal(M',M_out));\r\n%%\r\nn=256;\r\n% Create a Unique element square array\r\nM=randperm(n*n);\r\nM=reshape(M,n,n);\r\n\r\nvr=M(1:n,:);\r\nvc=M(:,1:n);\r\n\r\nw=[vr;vc'];\r\nw=sortrows(w);\r\n\r\ntic\r\nM_out=Criss_Cross(w);\r\ntoc\r\n\r\nassert(isequal(M,M_out)||isequal(M',M_out));","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":9,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2012-06-03T20:11:23.000Z","updated_at":"2026-05-26T04:33:51.000Z","published_at":"2012-06-03T21:38:39.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCriss Cross matrix puzzle - Square matrix, Unique elements, Single Word List\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eArrange the \\\"words\\\" into a solid square such that all words are used.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven an array of words make the original Square or Square Transpose.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWords are left to Right or Top to Bottom. No fliplr or flipud.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eExample:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eM_orig = [1 2 3; 4 5 6; 7 8 9]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003evr = [1 2 3; 4 5 6; 7 8 9]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003evc = [1 2 3; 4 5 6; 7 8 9]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInputs:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ew = [1 2 3; 4 5 6; 7 8 9;1 4 7; 2 5 8; 3 6 9]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003esorted w gives\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ew = [1 2 3; 1 4 7; 2 5 8; 3 6 9; 4 5 6; 7 8 9]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eM_out = [1 2 3; 4 5 6; 7 8 9] or\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eM_out=[1 4 7; 2 5 8; 3 6 9]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eMax size : 256\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis is the second in the Criss Cross puzzles series.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFollow up puzzles will have non-unique values and quite a few other variations.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":61312,"title":"Electric Power Steering (EPS) Motor Torque with Efficiency","description":"In EPS systems, the motor must generate additional torque to compensate for system losses.\r\nGiven Required assist torque at rack Ta and Mechanical efficiency η (0 \u003c η ≤ 1)\r\nCompute required motor torque Tm.\r\n","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 110.906px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 467.484px 55.4531px; transform-origin: 467.496px 55.4531px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIn EPS systems, the motor must generate additional torque to compensate for system losses.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven Required assist torque at rack \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eTa \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eand\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003e \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eMechanical efficiency \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eη (0 \u0026lt; η ≤ 1)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eCompute required motor torque \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eTm\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function Tm = epsMotorTorque(Ta,eta)\r\nTm = 0;\r\nend","test_suite":"%%\r\nTa = 10; eta = 0.9;\r\nTm_expected = Ta / eta;\r\nassert(abs(epsMotorTorque(Ta,eta) - Tm_expected) \u003c 1e-6)\r\n\r\n%%\r\nTa = 15; eta = 0.85;\r\nTm_expected = Ta / eta;\r\nassert(abs(epsMotorTorque(Ta,eta) - Tm_expected) \u003c 1e-6)\r\n\r\n%%\r\nTa = 8; eta = 0.8;\r\nTm_expected = Ta / eta;\r\nassert(abs(epsMotorTorque(Ta,eta) - Tm_expected) \u003c 1e-6)","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":2305225,"edited_by":2305225,"edited_at":"2026-04-28T09:46:20.000Z","deleted_by":null,"deleted_at":null,"solvers_count":27,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-04-28T09:46:15.000Z","updated_at":"2026-05-24T20:53:49.000Z","published_at":"2026-04-28T09:46:20.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIn EPS systems, the motor must generate additional torque to compensate for system losses.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven Required assist torque at rack \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eTa \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr/\u003e\u003cw:t\u003eand\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003eMechanical efficiency \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eη (0 \u0026lt; η ≤ 1)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCompute required motor torque \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eTm\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61331,"title":"Move Array Element by Offset with Optional Ring Mode","description":"Move Element by Offset\r\nWrite a function moveab(x, A, B, option) that moves the element at index A in array x by B positions.\r\nPositive B moves the element to the right \r\nNegative B moves the element to the left \r\nThe relative order of all other elements must be preserved \r\nUse 1-based indexing \r\nPhilosophy:\r\nWhen moving elements in an array, a special case occurs when end elements can either move to the next index in the array or move by its relative postion between other elements. When the end element is moved by one space, it can then wrap and move to the first index in the array, however, the order of the elements has not changed. With the option of ring behavior, end elements will wrap but also move as intended by moving to the second index instead of the first. This is also maintained for reverse move options.\r\nDefault behavior:\r\nRemove the element at index A and reinsert it B positions away in the array \r\nIf the shift goes past either end, wrap around to the other side \r\nLarge values of B must wrap correctly (e.g., use modulo with the array length) \r\nDefault wrapping acts as follows:  x = [1 2 3]; moveab(x, 3, 1) → [3 1 2]        \r\nExamples:\r\nx = [1 2 3 4 5 6 7 8]; moveab(x, 3, 3) → [1 2 4 5 6 3 7 8]\r\nx = [1 2 3]; moveab(x, 3, 1) → [3 1 2]\r\n'ring' option for wrapping:\r\nThe default simply wrapping simply shifts the last element to the first, but when the array to treated as a ring, the element was never moved by 1 space, the order was never changed. The 'ring' option moves the last element by 1 space in a ring, resulting in the following behavior:  x = [1 2 3]; moveab(x, 3, 1,'ring') → [1 3 2]\r\nMoving backwards in 'ring' mode:  x = [1 2 3]; moveab(x, 1, -1,'ring') → [3 1 2]. \r\nMoving backwards in default mode: x = [1 2 3]; moveab(x, 1, -1)        → [2 3 1]. \r\n    \r\nExamples (comparison of ring and default mode):\r\nx = [1 2 3]; moveab(x, 3, 1) → [3 1 2]  \r\nx = [1 2 3]; moveab(x, 3, 1, 'ring') → [1 3 2]\r\nx = [1 2 3]; moveab(x, 1, -1) → [2 1 3] \r\nx = [1 2 3]; moveab(x, 1, -1, 'ring') → [2 1 3]\r\nx = 1:10; moveab(x, 10, 1) → [10 1 2 3 4 5 6 7 8 9]\r\nx = 1:10; moveab(x, 10, 1, 'ring') → [1 10 2 3 4 5 6 7 8 9]\r\nx = 1:10; moveab(x, 1, -1) → [2 3 4 5 6 7 8 9 10 1]\r\nx = 1:10; moveab(x, 1, -1, 'ring') → [2 3 4 5 6 7 8 9 1 10]","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 967.847px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 469.499px 483.919px; transform-origin: 469.499px 483.923px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 20.9961px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 445.5px 10.498px; text-align: left; transform-origin: 445.504px 10.498px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; 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margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWrite a function \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003emoveab(x, A, B, option)\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e that moves the element at index \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eA\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e in array \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ex\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e by \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eB\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e positions.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cul style=\"block-size: 81.7383px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 452.498px 40.8691px; transform-origin: 452.502px 40.8691px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003ePositive \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eB\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e moves the element to the right \u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eNegative \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eB\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e moves the element to the left \u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe relative order of all other elements must be preserved \u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eUse 1-based indexing \u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv style=\"block-size: 20.9961px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 445.5px 10.498px; text-align: left; transform-origin: 445.504px 10.498px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003ePhilosophy:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 83.9844px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 445.5px 41.9922px; text-align: left; transform-origin: 445.504px 41.9922px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWhen moving elements in an array, a special case occurs when end elements can either move to the next index in the array or move by its relative postion between other elements. When the end element is moved by one space, it can then wrap and move to the first index in the array, however, the order of the elements has not changed. With the option of ring behavior, end elements will wrap but also move as intended by moving to the second index instead of the first. This is also maintained for reverse move options.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.9961px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 445.5px 10.498px; text-align: left; transform-origin: 445.504px 10.498px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eDefault behavior:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cul style=\"block-size: 81.7383px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 452.498px 40.8691px; transform-origin: 452.502px 40.8691px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eRemove the element at index \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eA\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e and reinsert it \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eB\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e positions away in the array \u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIf the shift goes past either end, wrap around to the other side \u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eLarge values of \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eB\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e must wrap correctly (e.g., use modulo with the array length) \u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eDefault wrapping acts as follows:  \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ex = [1 2 3]; moveab(x, 3, 1)\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e → \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[3 1 2]\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e        \u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv style=\"block-size: 20.9961px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 445.5px 10.498px; text-align: left; transform-origin: 445.504px 10.498px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eExamples:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cul style=\"block-size: 40.8691px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 452.498px 20.4346px; transform-origin: 452.502px 20.4346px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ex = [1 2 3 4 5 6 7 8]; moveab(x, 3, 3)\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e → \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[1 2 4 5 6 3 7 8]\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ex = [1 2 3]; moveab(x, 3, 1)\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e → \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[3 1 2]\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv style=\"block-size: 20.9961px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 445.5px 10.498px; text-align: left; transform-origin: 445.504px 10.498px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003e'ring' option for wrapping:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cul style=\"block-size: 61.3037px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 452.498px 30.6478px; transform-origin: 452.502px 30.6519px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 30.6478px; text-align: left; transform-origin: 424.504px 30.6519px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe default simply wrapping simply shifts the last element to the first, but when the array to treated as a ring, the element was never moved by 1 space, the order was never changed. The 'ring' option moves the last element by 1 space in a ring, resulting in the following behavior:  \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ex = [1 2 3]; moveab(x, 3, 1,'ring')\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e → \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[1 3 2]\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cul style=\"block-size: 40.8691px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 452.498px 20.4346px; transform-origin: 452.502px 20.4346px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eMoving backwards in 'ring' mode:  x = [1 2 3]; moveab(x, 1, -1,'ring')\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e → \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[3 1 2]. \u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eMoving backwards in default mode: x = [1 2 3]; moveab(x, 1, -1)       \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e → \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[2 3 1]. \u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv style=\"block-size: 20.9961px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 445.5px 10.498px; text-align: left; transform-origin: 445.504px 10.498px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e    \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.9961px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 445.5px 10.498px; text-align: left; transform-origin: 445.504px 10.498px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eExamples (comparison of ring and default mode):\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cul style=\"block-size: 40.8691px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 452.498px 20.4346px; transform-origin: 452.502px 20.4346px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ex = [1 2 3]; moveab(x, 3, 1)\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e → \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[3 1 2]  \u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ex = [1 2 3]; moveab(x, 3, 1, 'ring')\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e → \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[1 3 2]\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cul style=\"block-size: 40.8691px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 452.498px 20.4346px; transform-origin: 452.502px 20.4346px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ex = [1 2 3]; moveab(x, 1, -1)\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e → \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[2 1 3] \u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ex = [1 2 3]; moveab(x, 1, -1, 'ring')\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e → \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[2 1 3]\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cul style=\"block-size: 40.8691px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 452.498px 20.4346px; transform-origin: 452.502px 20.4346px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ex = 1:10; moveab(x, 10, 1)\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e → \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[10 1 2 3 4 5 6 7 8 9]\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ex = 1:10; moveab(x, 10, 1, 'ring')\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e → \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[1 10 2 3 4 5 6 7 8 9]\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003cul style=\"block-size: 40.8691px; font-family: Helvetica, Arial, sans-serif; list-style-type: square; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 452.498px 20.4346px; transform-origin: 452.502px 20.4346px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ex = 1:10; moveab(x, 1, -1)\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e → \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[2 3 4 5 6 7 8 9 10 1]\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4346px; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 424.504px 10.2132px; text-align: left; transform-origin: 424.504px 10.2173px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ex = 1:10; moveab(x, 1, -1, 'ring')\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e → \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003e[2 3 4 5 6 7 8 9 1 10]\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function x2 = moveab(x)\r\n  x2 = x;\r\nend","test_suite":"%%\r\n% Basic right move (default)\r\nx = 1:8;\r\ny_correct = [1 2 4 5 6 3 7 8];\r\nassert(isequal(moveab(x,3,3),y_correct))\r\n\r\n%%\r\n% End wrap (default)\r\nx = 1:10;\r\ny_correct = [10 1 2 3 4 5 6 7 8 9];\r\nassert(isequal(moveab(x,10,1),y_correct))\r\n\r\n%%\r\n% End wrap ('ring')\r\nx = 1:10;\r\ny_correct = [1 10 2 3 4 5 6 7 8 9];\r\nassert(isequal(moveab(x,10,1,'ring'),y_correct))\r\n\r\n%%\r\n% Negative move on first element (default)\r\nx = 1:10;\r\ny_correct = [2 3 4 5 6 7 8 9 10 1];\r\nassert(isequal(moveab(x,1,-1),y_correct))\r\n\r\n%%\r\n% Negative move on first element ('ring')\r\nx = 1:10;\r\ny_correct = [2 3 4 5 6 7 8 9 1 10];\r\nassert(isequal(moveab(x,1,-1,'ring'),y_correct))\r\n\r\n%%\r\n% Large positive B (default, modulo behavior)\r\nx = 1:10;\r\ny_correct = moveab(x,3,7);\r\nassert(isequal(moveab(x,3,57),y_correct))\r\n\r\n%%\r\n% Large negative B ('ring', modulo behavior)\r\nx = 1:10;\r\ny_correct = [2 3 4 5 6 7 8 9 1 10]; % same as B = -1\r\nassert(isequal(moveab(x,1,-11,'ring'),y_correct))","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":31885,"edited_by":31885,"edited_at":"2026-05-06T17:12:22.000Z","deleted_by":null,"deleted_at":null,"solvers_count":4,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-05T19:32:54.000Z","updated_at":"2026-05-27T06:45:02.000Z","published_at":"2026-05-05T20:40:10.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eMove Element by Offset\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWrite a function \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003emoveab(x, A, B, option)\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e that moves the element at index \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eA\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e in array \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e by \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eB\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e positions.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ePositive \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eB\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e moves the element to the right \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNegative \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eB\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e moves the element to the left \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe relative order of all other elements must be preserved \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eUse 1-based indexing \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ePhilosophy:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr/\u003e\u003cw:t\u003eWhen moving elements in an array, a special case occurs when end elements can either move to the next index in the array or move by its relative postion between other elements. When the end element is moved by one space, it can then wrap and move to the first index in the array, however, the order of the elements has not changed. With the option of ring behavior, end elements will wrap but also move as intended by moving to the second index instead of the first. This is also maintained for reverse move options.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eDefault behavior:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eRemove the element at index \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eA\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e and reinsert it \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eB\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e positions away in the array \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf the shift goes past either end, wrap around to the other side \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eLarge values of \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eB\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e must wrap correctly (e.g., use modulo with the array length) \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eDefault wrapping acts as follows:  \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex = [1 2 3]; moveab(x, 3, 1)\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e → \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[3 1 2]\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e        \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eExamples:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex = [1 2 3 4 5 6 7 8]; moveab(x, 3, 3)\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e → \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[1 2 4 5 6 3 7 8]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex = [1 2 3]; moveab(x, 3, 1)\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e → \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[3 1 2]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e'ring' option for wrapping:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe default simply wrapping simply shifts the last element to the first, but when the array to treated as a ring, the element was never moved by 1 space, the order was never changed. The 'ring' option moves the last element by 1 space in a ring, resulting in the following behavior:  \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex = [1 2 3]; moveab(x, 3, 1,'ring')\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e → \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[1 3 2]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eMoving backwards in 'ring' mode:  x = [1 2 3]; moveab(x, 1, -1,'ring')\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e → \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[3 1 2]. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eMoving backwards in default mode: x = [1 2 3]; moveab(x, 1, -1)       \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e → \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[2 3 1]. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e    \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eExamples (comparison of ring and default mode):\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex = [1 2 3]; moveab(x, 3, 1)\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e → \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[3 1 2]  \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex = [1 2 3]; moveab(x, 3, 1, 'ring')\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e → \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[1 3 2]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex = [1 2 3]; moveab(x, 1, -1)\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e → \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[2 1 3] \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex = [1 2 3]; moveab(x, 1, -1, 'ring')\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e → \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[2 1 3]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex = 1:10; moveab(x, 10, 1)\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e → \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[10 1 2 3 4 5 6 7 8 9]\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex = 1:10; moveab(x, 10, 1, 'ring')\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e → \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[1 10 2 3 4 5 6 7 8 9]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex = 1:10; moveab(x, 1, -1)\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e → \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[2 3 4 5 6 7 8 9 10 1]\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ex = 1:10; moveab(x, 1, -1, 'ring')\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e → \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[2 3 4 5 6 7 8 9 1 10]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61340,"title":"Piston Mean Speed","description":"Mean piston speed is a critical mechanical stress indicator.\r\nIt sets limits on valve timing, bearing loads and material fatigue. \r\nMost production engines keep mean piston speed under 15 m/s; racing engines push this toward 25 m/s.\r\n\r\nGiven stroke S (m) and engine speed n (RPM), compute mean piston speed v_p (m/s).","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 345px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 468.5px 172.5px; transform-origin: 468.5px 172.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eMean piston speed is a critical mechanical stress indicator.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIt sets limits on valve timing, bearing loads and material fatigue. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eMost production engines keep mean piston speed under 15 m/s; racing engines push this toward 25 m/s.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 225px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 112.5px; text-align: left; transform-origin: 444.5px 112.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cimg class=\"imageNode\" style=\"vertical-align: baseline\" src=\"https://marineinbox.com/wp-content/uploads/2019/08/images.png\" data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven stroke S (m) and engine speed n (RPM), compute mean piston speed v_p (m/s).\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function vp = meanPistonSpeed(S, n)\r\nvp = 0;\r\nend","test_suite":"%%Test 1\r\nS=0.086; n=3000;\r\nassert(abs(meanPistonSpeed(S,n) - 2*S*n/60) \u003c 1e-6)\r\n%%Test 2\r\nS=0.092; n=6000;\r\nassert(abs(meanPistonSpeed(S,n) - 2*S*n/60) \u003c 1e-6)\r\n%%Test 3\r\nS=0.105; n=8000;\r\nassert(abs(meanPistonSpeed(S,n) - 2*S*n/60) \u003c 1e-6)\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":2305225,"edited_by":2305225,"edited_at":"2026-05-27T03:50:54.000Z","deleted_by":null,"deleted_at":null,"solvers_count":12,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-21T09:58:25.000Z","updated_at":"2026-05-27T03:50:54.000Z","published_at":"2026-05-21T09:58:25.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eMean piston speed is a critical mechanical stress indicator.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIt sets limits on valve timing, bearing loads and material fatigue. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eMost production engines keep mean piston speed under 15 m/s; racing engines push this toward 25 m/s.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"219\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"230\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven stroke S (m) and engine speed n (RPM), compute mean piston speed v_p (m/s).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/image\",\"target\":\"/media/image1.png\",\"relationshipId\":\"rId1\"}]},{\"partUri\":\"/media/image1.png\",\"contentType\":\"image/png\",\"content\":\"https://marineinbox.com/wp-content/uploads/2019/08/images.png\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61339,"title":"Engine Displacement ","description":"Engine displacement is the total swept volume of all cylinders. \r\nIt is determined by bore (cylinder diameter), stroke (piston travel) and the number of cylinders. \r\nDisplacement is typically quoted in litres or cubic centimetres for consumer engines.\r\n\r\nGiven bore B (m), stroke S (m), and number of cylinders N, compute total displacement V_d (m³).","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 511px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 468.5px 255.5px; transform-origin: 468.5px 255.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eEngine displacement is the total swept volume of all cylinders. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIt is determined by bore (cylinder diameter), stroke (piston travel) and the number of cylinders. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eDisplacement is typically quoted in litres or cubic centimetres for consumer engines.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 391px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 195.5px; text-align: left; transform-origin: 444.5px 195.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cimg class=\"imageNode\" style=\"vertical-align: baseline\" src=\"https://www.aa1car.com/library/engine_displacement.jpg\" data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven bore B (m), stroke S (m), and number of cylinders N, compute total displacement V_d (m³).\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function Vd = engineDisplacement(B, S, N)\r\nVd = 0;\r\nend","test_suite":"%%Test 1\r\nB=0.086; S=0.086; N=4;\r\nassert(abs(engineDisplacement(B,S,N) - (pi/4)*B^2*S*N) \u003c 1e-8)\r\n%%Test 2\r\nB=0.096; S=0.092; N=6;\r\nassert(abs(engineDisplacement(B,S,N) - (pi/4)*B^2*S*N) \u003c 1e-8)\r\n%%Test 3\r\nB=0.110; S=0.105; N=8;\r\nassert(abs(engineDisplacement(B,S,N) - (pi/4)*B^2*S*N) \u003c 1e-8)\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":1,"created_by":2305225,"edited_by":2305225,"edited_at":"2026-05-27T03:47:33.000Z","deleted_by":null,"deleted_at":null,"solvers_count":13,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-21T09:54:47.000Z","updated_at":"2026-05-27T03:50:04.000Z","published_at":"2026-05-21T09:54:47.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eEngine displacement is the total swept volume of all cylinders. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIt is determined by bore (cylinder diameter), stroke (piston travel) and the number of cylinders. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eDisplacement is typically quoted in litres or cubic centimetres for consumer engines.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"385\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"381\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven bore B (m), stroke S (m), and number of cylinders N, compute total displacement V_d (m³).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/image\",\"target\":\"/media/image1.jpg\",\"relationshipId\":\"rId1\"}]},{\"partUri\":\"/media/image1.jpg\",\"contentType\":\"image/jpg\",\"content\":\"https://www.aa1car.com/library/engine_displacement.jpg\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":988,"title":"Convert a substructure reference string into a valid definition structure for subsref and subsasgn","description":"You have a reference to an element in a data structure, which you want to pass to a function. Not the value itself, but the reference. And you don't like to use evil eval constructions. \r\nTherefore, you convert the reference into a structure, like liked by Matlab's built-in subsref and subsasgn functions.\r\n\r\nFor example, to reference the value a(12), you would have to convert '(12)' into \r\n\r\n  def = \r\n    type: '()'\r\n    subs: {[12]}\r\n\r\nAnd to reference a(12).field_b{1,3}{2}((3:4),:).c, you would need to convert '(12).field_b{1,3}{2}((3:4),:).c' into \r\n\r\n  def(1) = \r\n    type: '()'\r\n    subs: {[12]}\r\n\r\n  def(2) = \r\n    type: '.'\r\n    subs: {'field_b'}\r\n\r\n  def(3) = \r\n    type: '{}'\r\n    subs: {[1]  [3]}\r\n\r\n  def(4) = \r\n    type: '{}'\r\n    subs: {2}\r\n\r\n  def(5) = \r\n    type: '()'\r\n    subs: {[3 4]  ':'}\r\n\r\n  def(6) = \r\n    type: '.'\r\n    subs: {'c'}\r\n\r\nThe assignment is correct when any sub-structure reference that is accepted by subsref and subsasgn is correctly converted from a string to a valid structure.\r\n\r\nNote: Solutions wrapped in (f)eval(c), inline, str2func, regexprep (dynamic regular expressions), etc, are not appreciated.","description_html":"\u003cp\u003eYou have a reference to an element in a data structure, which you want to pass to a function. Not the value itself, but the reference. And you don't like to use evil eval constructions. \r\nTherefore, you convert the reference into a structure, like liked by Matlab's built-in subsref and subsasgn functions.\u003c/p\u003e\u003cp\u003eFor example, to reference the value a(12), you would have to convert '(12)' into\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003edef = \r\n  type: '()'\r\n  subs: {[12]}\r\n\u003c/pre\u003e\u003cp\u003eAnd to reference a(12).field_b{1,3}{2}((3:4),:).c, you would need to convert '(12).field_b{1,3}{2}((3:4),:).c' into\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003edef(1) = \r\n  type: '()'\r\n  subs: {[12]}\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003edef(2) = \r\n  type: '.'\r\n  subs: {'field_b'}\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003edef(3) = \r\n  type: '{}'\r\n  subs: {[1]  [3]}\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003edef(4) = \r\n  type: '{}'\r\n  subs: {2}\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003edef(5) = \r\n  type: '()'\r\n  subs: {[3 4]  ':'}\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003edef(6) = \r\n  type: '.'\r\n  subs: {'c'}\r\n\u003c/pre\u003e\u003cp\u003eThe assignment is correct when any sub-structure reference that is accepted by subsref and subsasgn is correctly converted from a string to a valid structure.\u003c/p\u003e\u003cp\u003eNote: Solutions wrapped in (f)eval(c), inline, str2func, regexprep (dynamic regular expressions), etc, are not appreciated.\u003c/p\u003e","function_template":"function def = subsdef(defstr)\r\n  def = substruct('()',{1});\r\nend","test_suite":"%%\r\nnocheat = isempty(regexp(evalc('type subsdef'),'(eval|regexprep|inline|str2func)'));\r\ny_correct = 1i;\r\nb(12) = y_correct;\r\ndefstr = '(12)';\r\nassert(isequal(subsref(b,subsdef(defstr)),y_correct) \u0026\u0026 nocheat)\r\n\r\n%%\r\nnocheat = isempty(regexp(evalc('type subsdef'),'(eval|regexprep|inline|str2func)'));\r\ny_correct = -4i;\r\nc{1,2,3,4,5}.field_b = y_correct;\r\ndefstr = '{1,2,3,4,5}.field_b';\r\nassert(isequal(subsref(c,subsdef(defstr)),y_correct) \u0026\u0026 nocheat)\r\n\r\n%%\r\nnocheat = isempty(regexp(evalc('type subsdef'),'(eval|regexprep|inline|str2func)'));\r\ny_correct = 3i;\r\na(12).field_b{1,3}{2}((3),1).c = y_correct;\r\ndefstr = '(12).field_b{1,3}{2}((3),1).c';\r\nassert(isequal(subsref(a,subsdef(defstr)),y_correct) \u0026\u0026 nocheat)\r\n\r\n%%\r\nnocheat = isempty(regexp(evalc('type subsdef'),'(eval|regexprep|inline|str2func)'));\r\ny_correct = repmat(2i,3,1);\r\nd{2}.a(1:3,:) = y_correct;\r\ndefstr = '{2}.a(1:3,:)';\r\nassert(isequal(subsref(d,subsdef(defstr)),y_correct) \u0026\u0026 nocheat)\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":6556,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":8,"test_suite_updated_at":"2012-10-11T14:58:11.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-10-11T14:55:15.000Z","updated_at":"2026-05-26T06:11:25.000Z","published_at":"2012-10-11T14:55:15.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eYou have a reference to an element in a data structure, which you want to pass to a function. Not the value itself, but the reference. And you don't like to use evil eval constructions. Therefore, you convert the reference into a structure, like liked by Matlab's built-in subsref and subsasgn functions.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor example, to reference the value a(12), you would have to convert '(12)' into\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[def = \\n  type: '()'\\n  subs: {[12]}]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAnd to reference a(12).field_b{1,3}{2}((3:4),:).c, you would need to convert '(12).field_b{1,3}{2}((3:4),:).c' into\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[def(1) = \\n  type: '()'\\n  subs: {[12]}\\n\\ndef(2) = \\n  type: '.'\\n  subs: {'field_b'}\\n\\ndef(3) = \\n  type: '{}'\\n  subs: {[1]  [3]}\\n\\ndef(4) = \\n  type: '{}'\\n  subs: {2}\\n\\ndef(5) = \\n  type: '()'\\n  subs: {[3 4]  ':'}\\n\\ndef(6) = \\n  type: '.'\\n  subs: {'c'}]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe assignment is correct when any sub-structure reference that is accepted by subsref and subsasgn is correctly converted from a string to a valid structure.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNote: Solutions wrapped in (f)eval(c), inline, str2func, regexprep (dynamic regular expressions), etc, are not appreciated.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":61333,"title":"Given the ratio of the two legs (longer / shorter), and the hypotenuse length, find the shorter leg.","description":"Further to the problem 43236, find the length of shorter leg\r\nP.S No built-in functions allowed","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(33, 33, 33); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 51px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 243.5px 25.5px; transform-origin: 243.5px 25.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 219.5px 10.5px; text-align: left; transform-origin: 219.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFurther to the problem 43236, find the length of shorter leg\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 219.5px 10.5px; text-align: left; transform-origin: 219.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eP.S No built-in functions allowed\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = FindShortLeg(x,ratio)\r\n y = x;\r\nend","test_suite":"%%\r\nx = 40;\r\nratio = 16/9;\r\ny_correct = 19.6104;\r\nassert(abs(FindShortLeg(x,ratio)-y_correct)\u003c0.01)\r\n\r\n%%\r\nx = 25;\r\nratio = 16/9;\r\ny_correct = 12.2565;\r\nassert(abs(FindShortLeg(x,ratio)-y_correct)\u003c0.01)\r\n\r\n%%\r\nx = 10;\r\nratio = 16/9;\r\ny_correct =  4.9026;\r\nassert(abs(FindShortLeg(x,ratio)-y_correct)\u003c0.01)\r\n\r\n%%\r\nx = 5;\r\nratio = 4/3;\r\ny_correct = 3;\r\nassert(abs(FindShortLeg(x,ratio)-y_correct)\u003c0.01)\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":584788,"edited_by":584788,"edited_at":"2026-05-21T11:24:29.000Z","deleted_by":null,"deleted_at":null,"solvers_count":10,"test_suite_updated_at":"2026-05-21T05:44:56.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-21T05:28:33.000Z","updated_at":"2026-05-26T12:27:22.000Z","published_at":"2026-05-21T05:28:33.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFurther to the problem 43236, find the length of shorter leg\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eP.S No built-in functions allowed\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61336,"title":"Brake Mean Effective Pressure (BMEP)","description":"BMEP is a normalised measure of engine work output per cycle per unit displacement. It lets you compare engines of different sizes on equal footing.\r\nA higher BMEP indicates a more efficient use of displacement.\r\n\r\nGiven torque T (N·m), displacement V_d (m³), and number of strokes k (2 or 4), compute BMEP.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 599.719px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 468.5px 299.859px; transform-origin: 468.5px 299.859px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 21px; text-align: left; transform-origin: 444.5px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eBMEP is a normalised measure of engine work output per cycle per unit displacement. It lets you compare engines of different sizes on equal footing.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eA higher BMEP indicates a more efficient use of displacement.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 488.719px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 244.359px; text-align: left; transform-origin: 444.5px 244.359px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cimg class=\"imageNode\" style=\"vertical-align: baseline\" src=\"https://static.wixstatic.com/media/1efdb1_5ced4cd83869436cbfd4286a5c83ab9b~mv2.png\" data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven torque T (N·m), displacement V_d (m³), and number of strokes k (2 or 4), compute BMEP.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function bmep = calcBMEP(T, Vd, k)\r\nbmep = 0;\r\nend","test_suite":"%%\r\nT = 200; Vd = 0.002; k = 4;\r\nbmep_expected = (T * 2 * pi * k) / Vd;\r\nassert(abs(calcBMEP(T,Vd,k) - bmep_expected) \u003c 1e-3)\r\n%%\r\nT = 350; Vd = 0.003; k = 4;\r\nbmep_expected = (T * 2 * pi * k) / Vd;\r\nassert(abs(calcBMEP(T,Vd,k) - bmep_expected) \u003c 1e-3)\r\n%%\r\nT = 80; Vd = 0.0005; k = 2;\r\nbmep_expected = (T * 2 * pi * k) / Vd;\r\nassert(abs(calcBMEP(T,Vd,k) - bmep_expected) \u003c 1e-3)\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":2305225,"edited_by":2305225,"edited_at":"2026-05-26T03:50:39.000Z","deleted_by":null,"deleted_at":null,"solvers_count":13,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-21T09:38:18.000Z","updated_at":"2026-05-26T15:09:13.000Z","published_at":"2026-05-21T09:38:18.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eBMEP is a normalised measure of engine work output per cycle per unit displacement. It lets you compare engines of different sizes on equal footing.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA higher BMEP indicates a more efficient use of displacement.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"802\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"1477\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven torque T (N·m), displacement V_d (m³), and number of strokes k (2 or 4), compute BMEP.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/image\",\"target\":\"/media/image1.png\",\"relationshipId\":\"rId1\"}]},{\"partUri\":\"/media/image1.png\",\"contentType\":\"image/png\",\"content\":\"https://static.wixstatic.com/media/1efdb1_5ced4cd83869436cbfd4286a5c83ab9b~mv2.png\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61337,"title":"Volumetric efficiency","description":"Volumetric efficiency measures how well an engine breathes.\r\nThe ratio of the actual air mass drawn in per cycle to the theoretical maximum based on displacement. \r\nNaturally aspirated engines typically achieve 80–95%.\r\n\r\nGiven actual air mass m_actual (kg), air density ρ (kg/m³), and displacement V_d (m³), compute volumetric efficiency η_v.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 634.383px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 467.484px 317.18px; transform-origin: 467.496px 317.191px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eVolumetric efficiency measures how well an engine breathes.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe ratio of the actual air mass drawn in per cycle to the theoretical maximum based on displacement. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eNaturally aspirated engines typically achieve 80–95%.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 514.477px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 257.227px; text-align: left; transform-origin: 443.508px 257.238px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cimg class=\"imageNode\" style=\"vertical-align: baseline\" src=\"https://media.springernature.com/lw685/springer-static/image/chp%3A10.1007%2F978-3-030-89216-6_3/MediaObjects/521933_1_En_3_Fig3_HTML.png\" data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven actual air mass m_actual (kg), air density ρ (kg/m³), and displacement V_d (m³), compute volumetric efficiency η_v.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function eta_v = volEfficiency(m_actual, rho, Vd)\r\neta_v = 0;\r\nend","test_suite":"%%Test 1\r\nm = 0.00180; rho = 1.2; Vd = 0.002;\r\nassert(abs(volEfficiency(m,rho,Vd) - m/(rho*Vd)) \u003c 1e-6)\r\n%%Test 2\r\nm = 0.00252; rho = 1.2; Vd = 0.003;\r\nassert(abs(volEfficiency(m,rho,Vd) - m/(rho*Vd)) \u003c 1e-6)\r\n%%Test 3\r\nm = 0.00096; rho = 1.15; Vd = 0.0012;\r\nassert(abs(volEfficiency(m,rho,Vd) - m/(rho*Vd)) \u003c 1e-6)\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":2305225,"edited_by":2305225,"edited_at":"2026-05-21T09:48:02.000Z","deleted_by":null,"deleted_at":null,"solvers_count":13,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-21T09:45:01.000Z","updated_at":"2026-05-26T15:09:52.000Z","published_at":"2026-05-21T09:48:02.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eVolumetric efficiency measures how well an engine breathes.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe ratio of the actual air mass drawn in per cycle to the theoretical maximum based on displacement. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNaturally aspirated engines typically achieve 80–95%.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven actual air mass m_actual (kg), air density ρ (kg/m³), and displacement V_d (m³), compute volumetric efficiency η_v.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/image\",\"target\":\"/media/image1.png\",\"relationshipId\":\"rId1\"}]},{\"partUri\":\"/media/image1.png\",\"contentType\":\"image/png\",\"content\":\"https://media.springernature.com/lw685/springer-static/image/chp%3A10.1007%2F978-3-030-89216-6_3/MediaObjects/521933_1_En_3_Fig3_HTML.png\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61341,"title":"Specific Fuel Consumption","description":"Brake-specific fuel consumption (BSFC) measures how efficiently an engine converts fuel mass into useful work. \r\nLower is better. Modern petrol engines achieve roughly 250–270 g/kWh at their best efficiency point.\r\n\r\nGiven fuel mass flow rate m_dot (kg/s) and brake power P (W), compute BSFC in g/kWh.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 110.906px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 467.484px 55.4531px; transform-origin: 467.496px 55.4531px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eBrake-specific fuel consumption (BSFC) measures how efficiently an engine converts fuel mass into useful work. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eLower is better. Modern petrol engines achieve roughly 250–270 g/kWh at their best efficiency point.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven fuel mass flow rate m_dot (kg/s) and brake power P (W), compute BSFC in g/kWh.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function bsfc = calcBSFC(m_dot, P)\r\nbsfc = 0;\r\nend","test_suite":"%%Test 1\r\nm_dot=0.0070; P=100000;\r\nassert(abs(calcBSFC(m_dot,P) - (m_dot/P)*3.6e6) \u003c 1e-3)\r\n%%Test 2\r\nm_dot=0.0105; P=150000;\r\nassert(abs(calcBSFC(m_dot,P) - (m_dot/P)*3.6e6) \u003c 1e-3)\r\n%%Test 3\r\nm_dot=0.0040; P=60000;\r\nassert(abs(calcBSFC(m_dot,P) - (m_dot/P)*3.6e6) \u003c 1e-3)","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":2305225,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":12,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-21T10:05:55.000Z","updated_at":"2026-05-26T15:28:57.000Z","published_at":"2026-05-21T10:05:55.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eBrake-specific fuel consumption (BSFC) measures how efficiently an engine converts fuel mass into useful work. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eLower is better. Modern petrol engines achieve roughly 250–270 g/kWh at their best efficiency point.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven fuel mass flow rate m_dot (kg/s) and brake power P (W), compute BSFC in g/kWh.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61342,"title":"Swept Volume and Clearance Volume","description":"The swept volume (V_s) is the volume displaced by the piston as it travels from BDC (Bottom Dead Centre) to TDC (Top Dead Centre). The clearance volume (V_c) is the remaining volume above the piston at TDC — it cannot be swept and defines the compression limit.\r\n\r\nGiven total cylinder volume at BDC V_BDC (m³) and clearance volume at TDC V_TDC (m³), compute the swept volume V_s and confirm it matches the bore-stroke formula using bore B (m) and stroke S (m).","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 616.383px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 467.484px 308.18px; transform-origin: 467.496px 308.191px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 41.9531px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 20.9766px; text-align: left; transform-origin: 443.508px 20.9766px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe swept volume (V_s) is the volume displaced by the piston as it travels from BDC (Bottom Dead Centre) to TDC (Top Dead Centre). The clearance volume (V_c) is the remaining volume above the piston at TDC — it cannot be swept and defines the compression limit.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 514.477px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 257.227px; text-align: left; transform-origin: 443.508px 257.238px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cimg class=\"imageNode\" style=\"vertical-align: baseline\" src=\"https://media.springernature.com/lw685/springer-static/image/chp%3A10.1007%2F978-3-030-89216-6_3/MediaObjects/521933_1_En_3_Fig3_HTML.png\" data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 41.9531px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 20.9766px; text-align: left; transform-origin: 443.508px 20.9766px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven total cylinder volume at BDC V_BDC (m³) and clearance volume at TDC V_TDC (m³), compute the swept volume V_s and confirm it matches the bore-stroke formula using bore B (m) and stroke S (m).\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function [Vs, Vc] = sweptClearanceVolume(V_BDC, V_TDC)\r\nVs = 0;\r\nVc = 0;\r\nend","test_suite":"%%Test 1\r\nV_BDC=550e-6; V_TDC=50e-6;\r\n[Vs,Vc] = sweptClearanceVolume(V_BDC,V_TDC);\r\nassert(abs(Vs - 500e-6) \u003c 1e-9)\r\nassert(abs(Vc - 50e-6) \u003c 1e-9)\r\n%%Test 2\r\nV_BDC=750e-6; V_TDC=62.5e-6;\r\n[Vs,Vc] = sweptClearanceVolume(V_BDC,V_TDC);\r\nassert(abs(Vs - 687.5e-6) \u003c 1e-9)\r\nassert(abs(Vc - 62.5e-6) \u003c 1e-9)\r\n%%Test 3\r\nV_BDC=400e-6; V_TDC=36.36e-6;\r\n[Vs,Vc] = sweptClearanceVolume(V_BDC,V_TDC);\r\nassert(abs(Vs - (V_BDC-V_TDC)) \u003c 1e-9)\r\nassert(abs(Vc - V_TDC) \u003c 1e-9)","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":2305225,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":12,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-21T10:13:10.000Z","updated_at":"2026-05-26T15:31:54.000Z","published_at":"2026-05-21T10:13:10.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe swept volume (V_s) is the volume displaced by the piston as it travels from BDC (Bottom Dead Centre) to TDC (Top Dead Centre). The clearance volume (V_c) is the remaining volume above the piston at TDC — it cannot be swept and defines the compression limit.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"507\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"685\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven total cylinder volume at BDC V_BDC (m³) and clearance volume at TDC V_TDC (m³), compute the swept volume V_s and confirm it matches the bore-stroke formula using bore B (m) and stroke S (m).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/image\",\"target\":\"/media/image1.png\",\"relationshipId\":\"rId1\"}]},{\"partUri\":\"/media/image1.png\",\"contentType\":\"image/png\",\"content\":\"https://media.springernature.com/lw685/springer-static/image/chp%3A10.1007%2F978-3-030-89216-6_3/MediaObjects/521933_1_En_3_Fig3_HTML.png\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61343,"title":"Geometric Compression Ratio","description":"The geometric compression ratio CR is the ratio of the total cylinder volume at BDC to the clearance volume at TDC. It is one of the most fundamental engine design parameters — it governs knock tendency, thermal efficiency, and peak cylinder pressure.\r\n\r\nGiven swept volume V_s (m³) and clearance volume V_c (m³), compute the compression ratio CR. Also verify the result using the TDC/BDC volumes directly.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 996.398px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 467.484px 498.188px; transform-origin: 467.496px 498.199px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 41.9531px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 20.9766px; text-align: left; transform-origin: 443.508px 20.9766px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe geometric compression ratio CR is the ratio of the total cylinder volume at BDC to the clearance volume at TDC. It is one of the most fundamental engine design parameters — it governs knock tendency, thermal efficiency, and peak cylinder pressure.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 894.492px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 447.234px; text-align: left; transform-origin: 443.508px 447.246px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cimg class=\"imageNode\" style=\"vertical-align: baseline\" src=\"https://capstone-x.com/wp-content/uploads/2026/01/Gemini_Generated_Image_12mi8212mi8212mi.png\" data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 41.9531px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 20.9766px; text-align: left; transform-origin: 443.508px 20.9766px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven swept volume V_s (m³) and clearance volume V_c (m³), compute the compression ratio CR. Also verify the result using the TDC/BDC volumes directly.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function CR = compressionRatio(Vs, Vc)\r\nCR = 0;\r\nend","test_suite":"%%Test 1\r\nVs = 500e-6; Vc = 55.56e-6;\r\nCR_expected = (Vs + Vc) / Vc;\r\nassert(abs(compressionRatio(Vs,Vc) - CR_expected) \u003c 1e-4)\r\n%%Test 2\r\nVs = 687.5e-6; Vc = 62.5e-6;\r\nCR_expected = (Vs + Vc) / Vc;\r\nassert(abs(compressionRatio(Vs,Vc) - CR_expected) \u003c 1e-4)\r\n%%Test 3\r\nVs = 363.6e-6; Vc = 36.36e-6;\r\nCR_expected = (Vs + Vc) / Vc;\r\nassert(abs(compressionRatio(Vs,Vc) - CR_expected) \u003c 1e-4)\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":2305225,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":12,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-21T10:16:34.000Z","updated_at":"2026-05-26T15:32:28.000Z","published_at":"2026-05-21T10:16:34.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe geometric compression ratio CR is the ratio of the total cylinder volume at BDC to the clearance volume at TDC. It is one of the most fundamental engine design parameters — it governs knock tendency, thermal efficiency, and peak cylinder pressure.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"1024\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"1024\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven swept volume V_s (m³) and clearance volume V_c (m³), compute the compression ratio CR. Also verify the result using the TDC/BDC volumes directly.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/image\",\"target\":\"/media/image1.png\",\"relationshipId\":\"rId1\"}]},{\"partUri\":\"/media/image1.png\",\"contentType\":\"image/png\",\"content\":\"https://capstone-x.com/wp-content/uploads/2026/01/Gemini_Generated_Image_12mi8212mi8212mi.png\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":843,"title":"Hyperspectral Processing: Determine Material Components given a Hyperspectral vector","description":"Given a hyperspectral data set and Reflectance Spectral Signature Library determine a pixel's component percentages. \r\n\r\n\u003chttp://aviris.jpl.nasa.gov/aviris/index.html NASA AVIRIS\u003e\r\n\r\nA Ground Square is imaged by hundreds of pixels, each at a different wavelength.\r\nThe signal on pixel 1(500nm to 505nm) is a sum of the components (Concrete/Tree/Grass...) by percentage of area covered times the material reflectance.\r\nPixel 2 (510-515nm) is different by the Reflectance deltas between Concrete and a Tree.\r\n\r\nLet S(i,j) be the response of Material i for band j\r\n\r\ng( j )= %(Concrete)*S(1,j)+%(Tree)*S(2,j)+...%(Grass)*S(end,j);\r\n\r\nA 300-Band 9-Material Spectral file is loaded. Comparison between foliage and rocks is quite significant. The materials are Bush, Calcite, Concrete, Conifer, Grass (not that type), Fir tree, Gypsum, Maple, Sage\r\n\r\n*g=S*f*  where f is the percentage of the imaged pixel covered by the\r\nmaterial.\r\n\r\n*Input:* \r\ng spectral sum [301,1]; \r\nS spectral material response [301,9]  Nine materials\r\n\r\n*Output:*\r\nSolve for f  ....( eg f=[0 .5 0 .25 .25 0 0 0 0]' )\r\n\r\n( f should sum to 1, max(f) is 1 and min(f) is 0 )\r\n\r\nThe test Suite will round to 2 decimal places.\r\nCases of \"other materials\" which will induce negative values are not\r\ntested.\r\n\r\nThis is introductory and ignores atmospheric absorption.\r\n\r\nThere is a matrix operation hint in the test suite for a method to solve for f.\r\n\r\n\r\n\u003chttp://aviris.jpl.nasa.gov/data/free_data.html AVARIS Free Data\u003e\r\nThese data files are large with 224 bands x 750 channels x 2000 samples\r\n\r\nTo expand these files may require a tar converter\r\n\u003chttp://aviris.jpl.nasa.gov/alt_locator/111013_AV_Download.readme NASA readme\u003e\r\n...and... \r\n\u003chttp://aviris.jpl.nasa.gov/alt_gulf/ NASA Tools bottom Left\u003e\r\nThere are some possible issues with the NASA tar tool. Two non-standard files can be found at \u003chttp://dll-files.org/7968/index.html libiconv-2.dll\u003e and \u003chttp://dll-files.org/7975/libintl-2.dll.html libintl-2.dll\u003e\r\n\r\nSee the Test Suite for details on opening the AVIRIS Moffett Field file.","description_html":"\u003cp\u003eGiven a hyperspectral data set and Reflectance Spectral Signature Library determine a pixel's component percentages.\u003c/p\u003e\u003cp\u003e\u003ca href=\"http://aviris.jpl.nasa.gov/aviris/index.html\"\u003eNASA AVIRIS\u003c/a\u003e\u003c/p\u003e\u003cp\u003eA Ground Square is imaged by hundreds of pixels, each at a different wavelength.\r\nThe signal on pixel 1(500nm to 505nm) is a sum of the components (Concrete/Tree/Grass...) by percentage of area covered times the material reflectance.\r\nPixel 2 (510-515nm) is different by the Reflectance deltas between Concrete and a Tree.\u003c/p\u003e\u003cp\u003eLet S(i,j) be the response of Material i for band j\u003c/p\u003e\u003cp\u003eg( j )= %(Concrete)*S(1,j)+%(Tree)*S(2,j)+...%(Grass)*S(end,j);\u003c/p\u003e\u003cp\u003eA 300-Band 9-Material Spectral file is loaded. Comparison between foliage and rocks is quite significant. The materials are Bush, Calcite, Concrete, Conifer, Grass (not that type), Fir tree, Gypsum, Maple, Sage\u003c/p\u003e\u003cp\u003e\u003cb\u003eg=S*f\u003c/b\u003e  where f is the percentage of the imaged pixel covered by the\r\nmaterial.\u003c/p\u003e\u003cp\u003e\u003cb\u003eInput:\u003c/b\u003e \r\ng spectral sum [301,1]; \r\nS spectral material response [301,9]  Nine materials\u003c/p\u003e\u003cp\u003e\u003cb\u003eOutput:\u003c/b\u003e\r\nSolve for f  ....( eg f=[0 .5 0 .25 .25 0 0 0 0]' )\u003c/p\u003e\u003cp\u003e( f should sum to 1, max(f) is 1 and min(f) is 0 )\u003c/p\u003e\u003cp\u003eThe test Suite will round to 2 decimal places.\r\nCases of \"other materials\" which will induce negative values are not\r\ntested.\u003c/p\u003e\u003cp\u003eThis is introductory and ignores atmospheric absorption.\u003c/p\u003e\u003cp\u003eThere is a matrix operation hint in the test suite for a method to solve for f.\u003c/p\u003e\u003cp\u003e\u003ca href=\"http://aviris.jpl.nasa.gov/data/free_data.html\"\u003eAVARIS Free Data\u003c/a\u003e\r\nThese data files are large with 224 bands x 750 channels x 2000 samples\u003c/p\u003e\u003cp\u003eTo expand these files may require a tar converter \u003ca href=\"http://aviris.jpl.nasa.gov/alt_locator/111013_AV_Download.readme\"\u003eNASA readme\u003c/a\u003e\r\n...and...  \u003ca href=\"http://aviris.jpl.nasa.gov/alt_gulf/\"\u003eNASA Tools bottom Left\u003c/a\u003e\r\nThere are some possible issues with the NASA tar tool. Two non-standard files can be found at \u003ca href=\"http://dll-files.org/7968/index.html\"\u003elibiconv-2.dll\u003c/a\u003e and \u003ca href=\"http://dll-files.org/7975/libintl-2.dll.html\"\u003elibintl-2.dll\u003c/a\u003e\u003c/p\u003e\u003cp\u003eSee the Test Suite for details on opening the AVIRIS Moffett Field file.\u003c/p\u003e","function_template":"function f = hyperspectral(g,S)\r\n% g is [301,1]\r\n% S is [301,9]\r\n  f = zeros(size(S,2),1);\r\nend","test_suite":"%%\r\n% The AVIRIS fileread info is at the bottom\r\n% Solution Hint:\r\n% The Matrix hint is inv(S'S)(S'S)=I\r\n% With g=Sf multiply both sides by h'\r\n% S'g=S'Sf, now multiply both sides by inv(S'S)\r\n% inv(S'S)(S'g)=inv(S'S)(S'S)f which is I*f\r\n% Now simplify the right side and there is a solution\r\n% Solution Bigger/Better Hint: Search on mldivide\r\n%%\r\nglobal S\r\n%http://tinyurl.com/matlab-hyper-spectra\r\n%http://rmatlabtest.appspot.com/Spectra.mat\r\nurlwrite('http://rmatlabtest.appspot.com/Spectra.mat','Spectra.mat') ;\r\nload('Spectra.mat'); % S is the variable in Spectra.mat\r\nf_exp=[.5 .5 0 0 0 0 0 0 0 ]';\r\ng=S*f_exp;\r\n\r\nf = hyperspectral(g,S);\r\nassert(isequal(round(100*f)/100,f_exp),sprintf('%f\\n',f))\r\n%%\r\nglobal S\r\nf_exp=[0 .5 0.25 0 0 0 0.25 0 0 ]';\r\ng=S*f_exp;\r\nf = hyperspectral(g,S);\r\nassert(isequal(round(100*f)/100,f_exp),sprintf('%f\\n',f))\r\n%%\r\nglobal S\r\nf_exp=[0 .25 0.6 0 0 0 0 0.15 0 ]';\r\ng=S*f_exp;\r\nf = hyperspectral(g,S);\r\nassert(isequal(round(100*f)/100,f_exp),sprintf('%f\\n',f))\r\n%%\r\n%\r\n%Reading of the full Moffett Field file: (8GB RAM recommended)\r\n% The file is 600MB\r\n%cd 'C:\\Users\\???' % Your file location\r\n%fn='f080611t01p00r07rdn_c_sc01_ort_img'\r\n%fid = fopen (fn,'r');\r\n%A = int16(fread(fid, 'int16', 'ieee-be'));\r\n%A2 = reshape (A, 224,753,1924); % Specifics found in text files\r\n%A3 = permute (A2,[3 2 1]); % X Y Band\r\n%figure;imagesc(squeeze(A3(:,:,1))); % To view top layer\r\n","published":true,"deleted":false,"likes_count":3,"comments_count":8,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":11,"test_suite_updated_at":"2013-02-02T19:05:40.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-07-19T02:49:02.000Z","updated_at":"2026-05-26T16:59:53.000Z","published_at":"2012-07-19T03:34:29.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven a hyperspectral data set and Reflectance Spectral Signature Library determine a pixel's component percentages.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:hyperlink w:docLocation=\\\"http://aviris.jpl.nasa.gov/aviris/index.html\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eNASA AVIRIS\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA Ground Square is imaged by hundreds of pixels, each at a different wavelength. The signal on pixel 1(500nm to 505nm) is a sum of the components (Concrete/Tree/Grass...) by percentage of area covered times the material reflectance. Pixel 2 (510-515nm) is different by the Reflectance deltas between Concrete and a Tree.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eLet S(i,j) be the response of Material i for band j\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eg( j )= %(Concrete)*S(1,j)+%(Tree)*S(2,j)+...%(Grass)*S(end,j);\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA 300-Band 9-Material Spectral file is loaded. Comparison between foliage and rocks is quite significant. The materials are Bush, Calcite, Concrete, Conifer, Grass (not that type), Fir tree, Gypsum, Maple, Sage\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eg=S*f\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e where f is the percentage of the imaged pixel covered by the material.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e g spectral sum [301,1]; S spectral material response [301,9] Nine materials\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e Solve for f ....( eg f=[0 .5 0 .25 .25 0 0 0 0]' )\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e( f should sum to 1, max(f) is 1 and min(f) is 0 )\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe test Suite will round to 2 decimal places. Cases of \\\"other materials\\\" which will induce negative values are not tested.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis is introductory and ignores atmospheric absorption.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThere is a matrix operation hint in the test suite for a method to solve for f.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:hyperlink w:docLocation=\\\"http://aviris.jpl.nasa.gov/data/free_data.html\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eAVARIS Free Data\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e These data files are large with 224 bands x 750 channels x 2000 samples\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eTo expand these files may require a tar converter\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://aviris.jpl.nasa.gov/alt_locator/111013_AV_Download.readme\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eNASA readme\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e ...and... \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://aviris.jpl.nasa.gov/alt_gulf/\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eNASA Tools bottom Left\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e There are some possible issues with the NASA tar tool. Two non-standard files can be found at\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://dll-files.org/7968/index.html\\\"\u003e\u003cw:r\u003e\u003cw:t\u003elibiconv-2.dll\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e and\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://dll-files.org/7975/libintl-2.dll.html\\\"\u003e\u003cw:r\u003e\u003cw:t\u003elibintl-2.dll\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSee the Test Suite for details on opening the AVIRIS Moffett Field file.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":61338,"title":"Fuel-Air Equivalence Ratio (Lambda)","description":"Lambda (λ) is the ratio of actual air-fuel ratio to the stoichiometric air-fuel ratio. \r\nλ = 1 is perfect stoichiometry, \r\nλ \u003c 1 is rich, \r\nλ \u003e 1 is lean. \r\nEngine management systems constantly target λ = 1 for optimal catalyst performance.\r\n\r\nGiven actual AFR and stoichiometric AFR (AFR_s), compute lambda.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 572px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 468.5px 286px; transform-origin: 468.5px 286px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eLambda (λ) is the ratio of actual air-fuel ratio to the stoichiometric air-fuel ratio. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eλ = 1 is perfect stoichiometry, \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eλ \u0026lt; 1 is rich, \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eλ \u0026gt; 1 is lean. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eEngine management systems constantly target λ = 1 for optimal catalyst performance.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 392px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 196px; text-align: left; transform-origin: 444.5px 196px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cimg class=\"imageNode\" style=\"vertical-align: baseline\" src=\"https://i.ytimg.com/vi/9uFdrcPkMGE/hq720.jpg?sqp=-oaymwEhCK4FEIIDSFryq4qpAxMIARUAAAAAGAElAADIQj0AgKJD\u0026amp;rs=AOn4CLDLLtOPt4b2zx4L72ztX9tL_4S0vw\" data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 444.5px 10.5px; text-align: left; transform-origin: 444.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven actual AFR and stoichiometric AFR (AFR_s), compute lambda.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function lam = calcLambda(AFR, AFR_s)\r\nlam = 0;\r\nend","test_suite":"%%Test 1\r\nassert(abs(calcLambda(14.7, 14.7) - 1.0) \u003c 1e-6)\r\n%%Test 2\r\nassert(abs(calcLambda(12.5, 14.7) - 12.5/14.7) \u003c 1e-6)\r\n%%Test 3\r\nassert(abs(calcLambda(16.2, 14.7) - 16.2/14.7) \u003c 1e-6)","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":2305225,"edited_by":2305225,"edited_at":"2026-05-27T03:46:08.000Z","deleted_by":null,"deleted_at":null,"solvers_count":13,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-21T09:51:05.000Z","updated_at":"2026-05-27T03:46:42.000Z","published_at":"2026-05-21T09:51:05.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eLambda (λ) is the ratio of actual air-fuel ratio to the stoichiometric air-fuel ratio. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eλ = 1 is perfect stoichiometry, \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eλ \u0026lt; 1 is rich, \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eλ \u0026gt; 1 is lean. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eEngine management systems constantly target λ = 1 for optimal catalyst performance.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"386\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"686\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven actual AFR and stoichiometric AFR (AFR_s), compute lambda.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/image\",\"target\":\"/media/image1.jpg\",\"relationshipId\":\"rId1\"}]},{\"partUri\":\"/media/image1.jpg\",\"contentType\":\"image/jpg\",\"content\":\"https://i.ytimg.com/vi/9uFdrcPkMGE/hq720.jpg?sqp=-oaymwEhCK4FEIIDSFryq4qpAxMIARUAAAAAGAElAADIQj0AgKJD\u0026rs=AOn4CLDLLtOPt4b2zx4L72ztX9tL_4S0vw\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":737,"title":"Criss_Cross_000 : Unique elements in a Square array","description":"Criss Cross matrix puzzle - Easy: Square matrix, Unique elements\r\n\r\nArrange the \"words\" into a solid square such that all words are used.\r\n\r\nGiven an array of row words and an array of column words make the unique Square.\r\n\r\nThere is no flipping or rotating in this simplest case.\r\n\r\nexample:\r\n\r\nM_orig =[1 2 3; 4 5 6; 7 8 9]\r\n\r\n*Inputs:*\r\n\r\nvr = [1 2 3; 4 5 6; 7 8 9]\r\n\r\nscramled gives vr =[7 8 9; 1 2 3; 4 5 6]\r\n\r\nvc =[1 2 3; 4 5 6; 7 8 9]\r\n\r\nscrambled gives vc =[3 1 2;6 4 5; 9 7 8]\r\n\r\n*Output:*\r\n\r\nM_out=[1 2 3; 4 5 6; 7 8 9]\r\n\r\nMax size : 4096\r\n\r\n\r\nThis is the first in a series of Criss Cross puzzles.\r\n\r\nFollow up puzzles will have non-unique values, non-identified row or col, and there are quite a few other variations.","description_html":"\u003cp\u003eCriss Cross matrix puzzle - Easy: Square matrix, Unique elements\u003c/p\u003e\u003cp\u003eArrange the \"words\" into a solid square such that all words are used.\u003c/p\u003e\u003cp\u003eGiven an array of row words and an array of column words make the unique Square.\u003c/p\u003e\u003cp\u003eThere is no flipping or rotating in this simplest case.\u003c/p\u003e\u003cp\u003eexample:\u003c/p\u003e\u003cp\u003eM_orig =[1 2 3; 4 5 6; 7 8 9]\u003c/p\u003e\u003cp\u003e\u003cb\u003eInputs:\u003c/b\u003e\u003c/p\u003e\u003cp\u003evr = [1 2 3; 4 5 6; 7 8 9]\u003c/p\u003e\u003cp\u003escramled gives vr =[7 8 9; 1 2 3; 4 5 6]\u003c/p\u003e\u003cp\u003evc =[1 2 3; 4 5 6; 7 8 9]\u003c/p\u003e\u003cp\u003escrambled gives vc =[3 1 2;6 4 5; 9 7 8]\u003c/p\u003e\u003cp\u003e\u003cb\u003eOutput:\u003c/b\u003e\u003c/p\u003e\u003cp\u003eM_out=[1 2 3; 4 5 6; 7 8 9]\u003c/p\u003e\u003cp\u003eMax size : 4096\u003c/p\u003e\u003cp\u003eThis is the first in a series of Criss Cross puzzles.\u003c/p\u003e\u003cp\u003eFollow up puzzles will have non-unique values, non-identified row or col, and there are quite a few other variations.\u003c/p\u003e","function_template":"function M_out = Criss_Cross(vr,vc)\r\n\r\n M_out=vr*0;\r\n \r\nend","test_suite":"%%\r\nformat long\r\nformat compact\r\nseed=clock;\r\nseed=1000*seed(6);\r\nrng(seed)\r\n\r\nn=4;\r\n% Create a Unique element square array\r\nM=randperm(n*n);\r\nM=reshape(M,n,n)\r\n\r\nvr=M(1:n,:);\r\nvr=sortrows(vr);\r\n\r\nvc=M(:,1:n);\r\nvc=sortrows(vc')';\r\n\r\ntic\r\nM_out=Criss_Cross(vr,vc);\r\ntoc\r\nM_out\r\n\r\nassert(isequal(M,M_out));\r\n%%\r\nseed=clock;\r\nseed=1000*seed(6);\r\nrng(seed)\r\n\r\nn=8;\r\n% Create a Unique element square array\r\nM=randperm(n*n);\r\nM=reshape(M,n,n)\r\n\r\nvr=M(1:n,:);\r\nvr=sortrows(vr);\r\n\r\nvc=M(:,1:n);\r\nvc=sortrows(vc')';\r\n\r\ntic\r\nM_out=Criss_Cross(vr,vc);\r\ntoc\r\nM_out\r\n\r\nassert(isequal(M,M_out));\r\n%%\r\nseed=clock;\r\nseed=1000*seed(6);\r\nrng(seed)\r\n\r\nn=128;\r\n% Create a Unique element square array\r\nM=randperm(n*n);\r\nM=reshape(M,n,n);\r\n\r\nvr=M(1:n,:);\r\nvr=sortrows(vr);\r\n\r\nvc=M(:,1:n);\r\nvc=sortrows(vc')';\r\n\r\ntic\r\nM_out=Criss_Cross(vr,vc);\r\ntoc\r\n\r\nassert(isequal(M,M_out));\r\n%%\r\nseed=clock;\r\nseed=1000*seed(6);\r\nrng(seed)\r\n\r\nn=1024;\r\n% Create a Unique element square array\r\nM=randperm(n*n);\r\nM=reshape(M,n,n);\r\n\r\nvr=M(1:n,:);\r\nvr=sortrows(vr);\r\n\r\nvc=M(:,1:n);\r\nvc=sortrows(vc')';\r\n\r\ntic\r\nM_out=Criss_Cross(vr,vc);\r\ntoc\r\n\r\nassert(isequal(M,M_out));\r\n%%\r\nseed=clock;\r\nseed=1000*seed(6);\r\nrng(seed)\r\n\r\nn=4096;\r\n% Create a Unique element square array\r\nM=randperm(n*n);\r\nM=reshape(M,n,n);\r\n\r\nvr=M(1:n,:);\r\nvr=sortrows(vr);\r\n\r\nvc=M(:,1:n);\r\nvc=sortrows(vc')';\r\n\r\ntic\r\nM_out=Criss_Cross(vr,vc);\r\ntoc\r\n\r\nassert(isequal(M,M_out));","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":3097,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":9,"test_suite_updated_at":"2012-06-03T20:42:28.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-06-03T18:05:05.000Z","updated_at":"2026-05-27T07:19:16.000Z","published_at":"2012-06-03T19:37:49.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCriss Cross matrix puzzle - Easy: Square matrix, Unique elements\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eArrange the \\\"words\\\" into a solid square such that all words are used.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven an array of row words and an array of column words make the unique Square.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThere is no flipping or rotating in this simplest case.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eexample:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eM_orig =[1 2 3; 4 5 6; 7 8 9]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eInputs:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003evr = [1 2 3; 4 5 6; 7 8 9]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003escramled gives vr =[7 8 9; 1 2 3; 4 5 6]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003evc =[1 2 3; 4 5 6; 7 8 9]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003escrambled gives vc =[3 1 2;6 4 5; 9 7 8]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eOutput:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eM_out=[1 2 3; 4 5 6; 7 8 9]\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eMax size : 4096\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis is the first in a series of Criss Cross puzzles.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFollow up puzzles will have non-unique values, non-identified row or col, and there are quite a few other variations.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":61304,"title":"Turning radius of a vehicle","description":"The turning radius represents the radius of the circular path followed by a vehicle.\r\nGiven Wheelbase L and Steering angle δ, Compute the turning radius R.\r\nEquation:\r\nR = L / tan(delta)","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 110.906px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 467.484px 55.4531px; transform-origin: 467.496px 55.4531px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe turning radius represents the radius of the circular path followed by a vehicle.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven Wheelbase \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eL and \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eSteering angle \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eδ, \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eCompute the turning radius \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eR\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eEquation:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 20.9766px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 443.508px 10.4766px; text-align: left; transform-origin: 443.508px 10.4883px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eR = L / tan(delta)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function R = turningRadius(L,delta)\r\nR = 0;\r\nend","test_suite":"%%\r\nL = 2.5; delta = 30*pi/180;\r\nR_expected = 4.3301;\r\nassert(abs(turningRadius(L,delta) - R_expected) \u003c 1e-3)\r\n\r\n%%\r\nL = 3.0; delta = 20*pi/180;\r\nR_expected = 8.2426;\r\nassert(abs(turningRadius(L,delta) - R_expected) \u003c 1e-3)\r\n\r\n%%\r\nL = 2.8; delta = 10*pi/180;\r\nR_expected = 15.866;\r\nassert(abs(turningRadius(L,delta) - R_expected) \u003c 1e-1)","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":2305225,"edited_by":2305225,"edited_at":"2026-04-28T09:16:45.000Z","deleted_by":null,"deleted_at":null,"solvers_count":41,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-04-28T09:13:54.000Z","updated_at":"2026-05-27T07:21:01.000Z","published_at":"2026-04-28T09:16:45.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe turning radius represents the radius of the circular path followed by a vehicle.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven Wheelbase \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eL and \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003eSteering angle \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eδ, \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003eCompute the turning radius \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eR\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eEquation:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eR = L / tan(delta)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61359,"title":"Count the even numbers in a multiplication table","description":"A multiplication table that has products of numbers from 1 to 10 has 75 even numbers among the products. \r\nWrite a function to count the even numbers in a multiplication table of products  with  and  both running from 1 to .\r\n","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 406.425px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 469px 203.212px; transform-origin: 469px 203.212px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 445px 10.5px; text-align: left; transform-origin: 445px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eA multiplication table that has products of numbers from 1 to 10 has 75 even numbers among the products. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 445px 10.5px; text-align: left; transform-origin: 445px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWrite a function to count the even numbers in a multiplication table of products \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg 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width=\"34.5\" height=\"18\" alt=\"axb\" style=\"width: 34.5px; height: 18px;\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e with \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"font-family: STIXGeneral-webfont, serif; font-style: italic; font-weight: 400; color: rgb(33, 33, 33);\"\u003ea\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e and \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"font-family: STIXGeneral-webfont, serif; font-style: italic; font-weight: 400; color: rgb(33, 33, 33);\"\u003eb\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e both running from 1 to \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"font-family: STIXGeneral-webfont, serif; font-style: italic; font-weight: 400; color: rgb(33, 33, 33);\"\u003en\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 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alt=\"10x10 multiplication table and front cover of Marmaduke Multiply's\" data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = MTevens(n)\r\n   y = 0.75*n^2;\r\nend","test_suite":"%%\r\nn = 10;\r\ny = MTevens(n);\r\ny_correct = 75;\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nn = 24;\r\ny = MTevens(n);\r\ny_correct = 432;\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nn = 36;\r\ny = MTevens(n);\r\ny_correct = 972;\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nn = 121;\r\ny = MTevens(n);\r\ny_correct = 10920;\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nn = 453;\r\ny = MTevens(n);\r\ny_correct = 153680;\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nn = 1843;\r\ny = MTevens(n);\r\ny_correct = 2546565;\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nn = 3048;\r\ny = MTevens(n);\r\ny_correct = 6967728;\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nn = 9132;\r\ny = MTevens(n);\r\ny_correct = 62545068;\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nn = 25467;\r\ny = MTevens(n);\r\ny_correct = 486413333;\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nn = 400531;\r\ny = MTevens(n);\r\ny_correct = 120318611205;\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nn = 8843250;\r\ny = MTevens(n);\r\ny_correct = 58652302921875;\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nn = 94906265;\r\ny = MTevens(n);\r\ny_correct = 6755399304734536;\r\nassert(isequal(y,y_correct))\r\n\r\n%%\r\nn = 1534;\r\ny = MTevens(MTevens(n));\r\ny_correct = 2336065763333;\r\nassert(isequal(y,y_correct))","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":46909,"edited_by":46909,"edited_at":"2026-05-27T03:22:28.000Z","deleted_by":null,"deleted_at":null,"solvers_count":4,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-27T03:22:21.000Z","updated_at":"2026-05-27T10:25:09.000Z","published_at":"2026-05-27T03:22:28.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc 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\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61345,"title":"Get The Opposite Of The Number Without Negative (-) On It","description":"You must get the opposite of the number X without making -X.\r\nHint: You can make it by Subtraction and Multiplication.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 51px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 401px 25.5px; transform-origin: 401px 25.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eYou must get the opposite of the number X without making -X.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eHint: You can make it by Subtraction and Multiplication.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = getOpposite(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = 1;\r\ny_correct = -1;\r\nassert(isequal(getOpposite(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5122697,"edited_by":5122697,"edited_at":"2026-05-23T17:34:53.000Z","deleted_by":null,"deleted_at":null,"solvers_count":7,"test_suite_updated_at":"2026-05-23T14:51:23.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-23T14:48:38.000Z","updated_at":"2026-05-27T09:26:49.000Z","published_at":"2026-05-23T14:48:38.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eYou must get the opposite of the number X without making -X.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eHint: You can make it by Subtraction and Multiplication.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61346,"title":"Find The Area Of Triangle Using Base \u0026 Height","description":"You should find the area of the Triangle using base and height.\r\nGood Luck!","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 51px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 401px 25.5px; transform-origin: 401px 25.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eYou should find the area of the Triangle using base and height.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eGood Luck!\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function area = triangleArea(base, height)\r\n  area = ;\r\nend","test_suite":"%%\r\nbase = 1;\r\nheight = 1;\r\narea = 0.5;\r\nassert(isequal(triangleArea(base, height),area))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5122697,"edited_by":5122697,"edited_at":"2026-05-23T17:34:26.000Z","deleted_by":null,"deleted_at":null,"solvers_count":10,"test_suite_updated_at":"2026-05-23T16:51:38.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-23T16:46:19.000Z","updated_at":"2026-05-27T09:28:37.000Z","published_at":"2026-05-23T16:49:16.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eYou should find the area of the Triangle using base and height.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eGood Luck!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61347,"title":"Find The Area Of The Circle","description":"Find the area of the Circle using PI.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 401px 10.5px; transform-origin: 401px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eFind the area of the Circle using PI.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function area = circleArea(r)\r\n  area = ;\r\nend","test_suite":"%%\r\nr = 1;\r\narea = pi * r^2;\r\nassert(isequal(circleArea(r),area))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5122697,"edited_by":5122697,"edited_at":"2026-05-23T17:33:44.000Z","deleted_by":null,"deleted_at":null,"solvers_count":10,"test_suite_updated_at":"2026-05-23T17:01:17.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-23T16:57:42.000Z","updated_at":"2026-05-27T09:30:49.000Z","published_at":"2026-05-23T16:59:46.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eFind the area of the Circle using PI.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61349,"title":"Trapezium","description":"Calculate the area of the Trapezium using it's bases and height.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 401px 10.5px; transform-origin: 401px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eCalculate the area of the Trapezium using it's bases and height.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function trapeziumArea = trapeziumArea(base1, base2, height)\r\n  base3 = ;\r\n  trapeziumArea = ;\r\nend","test_suite":"%%\r\nbase1 = 1;\r\nbase2 = 1;\r\nheight = 1;\r\ntrapeziumArea = 0.5*(base1+base2)*height;\r\nassert(isequal(trapeziumArea(base1, base2, height),trapeziumArea))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5122697,"edited_by":5122697,"edited_at":"2026-05-23T18:08:08.000Z","deleted_by":null,"deleted_at":null,"solvers_count":8,"test_suite_updated_at":"2026-05-23T18:08:08.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-23T17:59:40.000Z","updated_at":"2026-05-27T09:33:56.000Z","published_at":"2026-05-23T18:03:46.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eCalculate the area of the Trapezium using it's bases and height.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61348,"title":"Basic Physics I","description":"Calculate the energy by the famous formula of Albert Einstein.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 401px 10.5px; transform-origin: 401px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eCalculate the energy by the famous formula of Albert Einstein.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"c = 300000\r\nfunction E = E(m)\r\n  E = ;\r\nend","test_suite":"%%\r\nm = 1;\r\nE = 90000000000;\r\nassert(isequal(E(m),E))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5122697,"edited_by":5122697,"edited_at":"2026-05-26T12:35:46.000Z","deleted_by":null,"deleted_at":null,"solvers_count":8,"test_suite_updated_at":"2026-05-23T17:28:56.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-23T17:19:37.000Z","updated_at":"2026-05-27T09:32:44.000Z","published_at":"2026-05-23T17:23:28.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eCalculate the energy by the famous formula of Albert Einstein.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61350,"title":"Circle Perimeter","description":"Get the perimeter of the Circle by PI.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 401px 10.5px; transform-origin: 401px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eGet the perimeter of the Circle by PI.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function p = circleP(r)\r\n  p = ;\r\nend","test_suite":"%%\r\nr = 1;\r\np = 2*pi*r;\r\nassert(isequal(circleP(r),p))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5122697,"edited_by":5122697,"edited_at":"2026-05-24T11:52:44.000Z","deleted_by":null,"deleted_at":null,"solvers_count":8,"test_suite_updated_at":"2026-05-24T11:52:11.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-24T11:50:23.000Z","updated_at":"2026-05-27T09:34:58.000Z","published_at":"2026-05-24T11:52:11.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eGet the perimeter of the Circle by PI.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61352,"title":"Basic Algebra I","description":"You should solve the problem 3X - 2 = 7 by finding the value of X.\r\nYou must use this array/vector [2 3 7].\r\nGOOD LUCK!","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 81px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 401px 40.5px; transform-origin: 401px 40.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eYou should solve the problem \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003e3X - 2 = 7 \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eby finding the value of \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eX\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eYou must use this array/vector \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003e[2 3 7].\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGOOD LUCK!\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function X = equation()\r\n  nums = [2 3 7];\r\n  X = ;\r\nend","test_suite":"%%\r\nnums = [2 3 7]\r\nX = (nums(3)+nums(1))/nums(2);\r\nassert(isequal(equation(),X))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5122697,"edited_by":5122697,"edited_at":"2026-05-24T13:26:11.000Z","deleted_by":null,"deleted_at":null,"solvers_count":8,"test_suite_updated_at":"2026-05-24T13:13:31.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-24T13:07:29.000Z","updated_at":"2026-05-27T09:37:42.000Z","published_at":"2026-05-24T13:11:18.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eYou should solve the problem \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e3X - 2 = 7 \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003eby finding the value of \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eX\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eYou must use this array/vector \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e[2 3 7].\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGOOD LUCK!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61351,"title":"Get The Square Root Of Number Power (^) Three","description":"Get the Square Root of number Power (^) Three.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 401px 10.5px; transform-origin: 401px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eGet the Square Root of number Power (^) Three.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function num = calc(n)\r\n  num = ;\r\nend","test_suite":"%%\r\nn = 1;\r\nnum = sqrt(n^3);\r\nassert(isequal(calc(n),num))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5122697,"edited_by":5122697,"edited_at":"2026-05-24T12:10:19.000Z","deleted_by":null,"deleted_at":null,"solvers_count":9,"test_suite_updated_at":"2026-05-24T12:06:24.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-24T11:57:15.000Z","updated_at":"2026-05-27T09:35:46.000Z","published_at":"2026-05-24T11:59:07.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eGet the Square Root of number Power (^) Three.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61353,"title":"Basic Algebra II","description":"You have the equation X^2 = n you should find the value of X.\r\nGOOD LUCK!","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 51px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 401px 25.5px; transform-origin: 401px 25.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eYou have the equation \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eX^2 = n \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eyou should find the value of \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eX\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGOOD LUCK!\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function X = equation(n)\r\n  X = ;\r\nend","test_suite":"%%\r\nn = 1;\r\nX = sqrt(n);\r\nassert(isequal(equation(n),X))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5122697,"edited_by":5122697,"edited_at":"2026-05-24T13:23:14.000Z","deleted_by":null,"deleted_at":null,"solvers_count":8,"test_suite_updated_at":"2026-05-24T13:23:14.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-24T13:20:58.000Z","updated_at":"2026-05-27T09:38:31.000Z","published_at":"2026-05-24T13:23:14.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eYou have the equation \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eX^2 = n \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr/\u003e\u003cw:t\u003eyou should find the value of \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eX\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr/\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr/\u003e\u003cw:t\u003eGOOD LUCK!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61354,"title":"Rhombus","description":"Get the area of the Rhombus using it's Diagonals.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 401px 10.5px; transform-origin: 401px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eGet the area of the Rhombus using it's Diagonals.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function area = area(d1,d2)\r\n  area = ;\r\nend","test_suite":"%%\r\nd1 = 1;\r\nd2 = 1;\r\narea = 0.5*(d1*d2);\r\nassert(isequal(area(d1,d2),area))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5122697,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":7,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-24T13:30:18.000Z","updated_at":"2026-05-27T09:39:14.000Z","published_at":"2026-05-24T13:30:18.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eGet the area of the Rhombus using it's Diagonals.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61355,"title":"Basic Algebra III","description":"Get the Cube Root of the number n.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 401px 10.5px; transform-origin: 401px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eGet the Cube Root of the number n.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function ans = cbRt(n)\r\n  ans = ;\r\nend","test_suite":"%%\r\nn = 8;\r\nans = nthroot(n,3);\r\nassert(isequal(cbRt(n),ans))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5122697,"edited_by":5122697,"edited_at":"2026-05-26T12:25:53.000Z","deleted_by":null,"deleted_at":null,"solvers_count":5,"test_suite_updated_at":"2026-05-26T12:25:53.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-26T12:24:06.000Z","updated_at":"2026-05-27T09:40:08.000Z","published_at":"2026-05-26T12:24:06.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eGet the Cube Root of the number n.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61357,"title":"Basic Physics III","description":"Calculate the Potential Energy (PE).","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 401px 10.5px; transform-origin: 401px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eCalculate the Potential Energy (PE).\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function PE = PE(w,h)\r\n  PE = ;\r\nend","test_suite":"%%\r\nw = 1;\r\nh = 1;\r\nPE = w*h;\r\nassert(isequal(PE(w,h),PE))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5122697,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":5,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-26T14:50:35.000Z","updated_at":"2026-05-27T09:41:48.000Z","published_at":"2026-05-26T14:50:35.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eCalculate the Potential Energy (PE).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61356,"title":"Basic Physics II","description":"Get the Kinetic Energy (KE).","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 401px 10.5px; transform-origin: 401px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eGet the Kinetic Energy (KE).\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function KE = KE(m,v)\r\n  KE = ;\r\nend","test_suite":"%%\r\nm = 1;\r\nv = 1;\r\nKE = 0.5*m*v^2;\r\nassert(isequal(KE(m,v),KE))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5122697,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":5,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-26T12:30:40.000Z","updated_at":"2026-05-27T09:41:02.000Z","published_at":"2026-05-26T12:30:40.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eGet the Kinetic Energy (KE).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":61358,"title":"Basic Physics IV","description":"Calculate the Mechanical Energy (ME).","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 401px 10.5px; transform-origin: 401px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 377px 10.5px; text-align: left; transform-origin: 377px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; font-weight: 700; \"\u003eCalculate the Mechanical Energy (ME).\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function ME = ME(PE,KE)\r\n  ME = ;\r\nend","test_suite":"%%\r\nPE = 1;\r\nKE = 1;\r\nME = PE+KE;\r\nassert(isequal(ME(PE,KE),ME))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5122697,"edited_by":5122697,"edited_at":"2026-05-26T14:58:18.000Z","deleted_by":null,"deleted_at":null,"solvers_count":5,"test_suite_updated_at":"2026-05-26T14:58:18.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2026-05-26T14:56:53.000Z","updated_at":"2026-05-27T09:43:20.000Z","published_at":"2026-05-26T14:56:53.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eCalculate the Mechanical Energy (ME).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":42526,"title":"Initialize a Natural Number matrix.","description":"Given length of matrix initialize a matrix consisting of natural numbers from 1 to n:\r\n\r\nn = 10;\r\nx = [ 1 2 3 4 5 6 7 8 9 10];\r\n\r\nn = 5;\r\nx = [1 2 3 4 5];","description_html":"\u003cp\u003eGiven length of matrix initialize a matrix consisting of natural numbers from 1 to n:\u003c/p\u003e\u003cp\u003en = 10;\r\nx = [ 1 2 3 4 5 6 7 8 9 10];\u003c/p\u003e\u003cp\u003en = 5;\r\nx = [1 2 3 4 5];\u003c/p\u003e","function_template":"function y = naturalNumbers(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = 1;\r\ny_correct = 1;\r\nassert(isequal(naturalNumbers(x),y_correct))\r\n\r\n%%\r\nx = 3;\r\ny_correct = [1 2 3];\r\nassert(isequal(naturalNumbers(x),y_correct))","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":48756,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":142,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2015-08-22T17:20:10.000Z","updated_at":"2026-05-26T13:57:36.000Z","published_at":"2015-08-22T17:24:03.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven length of matrix initialize a matrix consisting of natural numbers from 1 to n:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003en = 10; x = [ 1 2 3 4 5 6 7 8 9 10];\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003en = 5; x = [1 2 3 4 5];\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":58758,"title":"Hemisphere Volume on Top of a Cylinder","description":"This MATLAB function has to calculate the volume of a hemisphere placed on top of a cylinder, given valid inputs. It takes the radius of the cylinder and the height of the cylinder as input, and returns the total volume of the hemisphere and the cylinder combined.\r\n","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.440001px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 93px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 332px 46.5px; transform-origin: 332px 46.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 309px 31.5px; text-align: left; transform-origin: 309px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eThis MATLAB function has to calculate the volume of a hemisphere placed on top of a cylinder, given valid inputs. It takes the radius of the cylinder and the height of the cylinder as input, and returns the total volume of the hemisphere and the cylinder combined.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 309px 10.5px; text-align: left; transform-origin: 309px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function volume = computeHemisphereVolume(radius, height)\r\n\r\n    volume = 0;\r\nend","test_suite":"%%\r\nradius = 3;\r\nheight = 8;\r\nexpectedOutput = 282.743338823081;\r\nvolume = computeHemisphereVolume(radius, height);\r\nassert(abs(expectedOutput - volume) \u003c 1e-4)\r\n%%\r\nradius = 2.5;\r\nheight = 5;\r\nexpectedOutput = 130.899693899575;\r\nvolume = computeHemisphereVolume(radius, height);\r\nassert(abs(expectedOutput - volume) \u003c 1e-4)\r\n%%\r\nradius = 10;\r\nheight = 15;\r\nexpectedOutput = 6806.78408277789;\r\nvolume = computeHemisphereVolume(radius, height);\r\nassert(abs(expectedOutput - volume) \u003c 1e-4)\r\n%%\r\nradius = 0;\r\nheight = 12;\r\nexpectedOutput = 0;\r\nvolume = computeHemisphereVolume(radius, height);\r\nassert(abs(expectedOutput - volume) \u003c 1e-4)\r\n%%\r\nradius = 7.2;\r\nheight = 3.5;\r\nexpectedOutput = 1351.73935424539;\r\nvolume = computeHemisphereVolume(radius, height);\r\nassert(abs(expectedOutput - volume) \u003c 1e-4)\r\n","published":true,"deleted":false,"likes_count":13,"comments_count":4,"created_by":3429354,"edited_by":26769,"edited_at":"2023-12-02T00:24:04.000Z","deleted_by":null,"deleted_at":null,"solvers_count":74,"test_suite_updated_at":"2023-12-02T00:24:04.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2023-07-18T21:20:09.000Z","updated_at":"2026-05-24T20:38:13.000Z","published_at":"2023-07-18T21:20:09.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis MATLAB function has to calculate the volume of a hemisphere placed on top of a cylinder, given valid inputs. It takes the radius of the cylinder and the height of the cylinder as input, and returns the total volume of the hemisphere and the cylinder combined.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":2014,"title":"\"Find out the best cricket\"","description":"This is how I originally read Problem 2013, so let's just go with it.  Give me the first and last name of the best cricket, regardless of your input.","description_html":"\u003cp\u003eThis is how I originally read Problem 2013, so let's just go with it.  Give me the first and last name of the best cricket, regardless of your input.\u003c/p\u003e","function_template":"function y = BestCricket(x)\r\n  y = x;\r\nend","test_suite":"x = 1;\r\nassert(isequal(BestCricket(x),'Jiminy Cricket'))\r\n%%\r\nx = magic(7);\r\nassert(isequal(BestCricket(x),'Jiminy Cricket'))\r\n%%\r\nx='Who is the best cricket?';\r\nassert(isequal(BestCricket(x),'Jiminy Cricket'))\r\n","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":1615,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":131,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2013-11-26T16:35:20.000Z","updated_at":"2026-05-15T02:14:50.000Z","published_at":"2013-11-26T16:35:20.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis is how I originally read Problem 2013, so let's just go with it. Give me the first and last name of the best cricket, regardless of your input.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":44688,"title":"World Cup 2018 Prediction!","description":"Which team will be the winner?\r\n","description_html":"\u003cp\u003eWhich team will be the winner?\u003c/p\u003e","function_template":"function y = Worldcup2018winner()\r\n  y = \"????\"\r\nend","test_suite":"%%\r\nteams={'Russia','Saudi Arabia', 'Egypt', 'Uruguay', 'Portugal', 'Spain','Morocco','Iran',...\r\n    'France','Australia', 'Peru','Denmark', 'Brazil', 'Switzerland', 'Costa Rica', 'Serbia', ...\r\n    'Germany', 'Mexico', 'Sweden', 'STH Korea', 'Belgium', 'Panama', 'Tunisia', 'England' , ...\r\n    'Argentina','Iceland', 'Croatia', 'Nigeria', 'Poland', 'Senegal', 'Colombia', 'Japan'};\r\nd=false;\r\nfor i=1:numel(teams)\r\n    if strcmp(Worldcup2018winner(),teams{i})\r\n        d=true;\r\n        break;\r\n    end\r\nend\r\nassert(d)","published":true,"deleted":false,"likes_count":1,"comments_count":3,"created_by":218677,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":141,"test_suite_updated_at":"2018-06-15T17:39:57.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2018-06-15T17:38:14.000Z","updated_at":"2026-05-15T02:16:34.000Z","published_at":"2018-06-15T17:38:14.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWhich team will be the winner?\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":56230,"title":"compter le nombre de zéros dans une matrice","description":"écrire une fonction count_zeros qui prend en entrée une matrice M et détermine le nombre de zéros dans une matrice","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.440000534057617px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 42px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: left; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; \"\u003e\u003cspan style=\"\"\u003eécrire une fonction count_zeros qui prend en entrée une matrice M et détermine le nombre de zéros dans une matrice\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function N = count_zeros(M)\r\n  %a vous de jouer\r\nend","test_suite":"%%\r\nx = 0;\r\ny_correct = 1;\r\nassert(isequal(count_zeros(x),y_correct))\r\n%%\r\nx = [0 0 1 1 0 0.5];\r\ny_correct = 3;\r\nassert(isequal(count_zeros(x),y_correct))\r\n%%\r\nx = [0 0 1; 1 2 0.5; 0 0 3];\r\ny_correct = 4;\r\nassert(isequal(count_zeros(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":1,"created_by":63915,"edited_by":26769,"edited_at":"2022-11-23T21:23:15.000Z","deleted_by":null,"deleted_at":null,"solvers_count":57,"test_suite_updated_at":"2022-11-23T21:23:15.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2022-10-06T10:19:12.000Z","updated_at":"2026-05-21T15:39:58.000Z","published_at":"2022-10-06T10:19:11.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eécrire une fonction count_zeros qui prend en entrée une matrice M et détermine le nombre de zéros dans une matrice\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":42940,"title":"modulus of a number","description":"find the modulus of a given number","description_html":"\u003cp\u003efind the modulus of a given number\u003c/p\u003e","function_template":"function y = your_fcn_name(x)\r\n  y = abs(x);\r\nend","test_suite":"%%\r\nx = 1;\r\ny_correct = 1;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = -1;\r\ny_correct = 1;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = -3;\r\ny_correct = 3;\r\nassert(isequal(your_fcn_name(x),y_correct))","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":86789,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":240,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2016-09-01T21:06:06.000Z","updated_at":"2026-05-27T07:17:29.000Z","published_at":"2016-09-01T21:06:12.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003efind the modulus of a given number\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":44264,"title":"Calculate feeling temperature before climbing a mountain","description":"I sometimes climb a mountain.\r\nAs is well known, when the altitude becomes 100 (m) higher, the temperature lowers by 0.6 degrees Celsius.\r\nIn addition there is wind.\r\nAt wind velocity 1(m/s), the feeling temperature falls  1 degree Celsius.\r\n\r\ne.g.\r\n\r\n* temperature of the level ground(gT) : 25 degrees Celsius\r\n* wind velocity(v) : 10 m/s\r\n* at altitude(h) : 3000 m\r\n\r\nIn this case, feeling temperature(fT) is calculated as -3 degrees Celsius.\r\n","description_html":"\u003cp\u003eI sometimes climb a mountain.\r\nAs is well known, when the altitude becomes 100 (m) higher, the temperature lowers by 0.6 degrees Celsius.\r\nIn addition there is wind.\r\nAt wind velocity 1(m/s), the feeling temperature falls  1 degree Celsius.\u003c/p\u003e\u003cp\u003ee.g.\u003c/p\u003e\u003cul\u003e\u003cli\u003etemperature of the level ground(gT) : 25 degrees Celsius\u003c/li\u003e\u003cli\u003ewind velocity(v) : 10 m/s\u003c/li\u003e\u003cli\u003eat altitude(h) : 3000 m\u003c/li\u003e\u003c/ul\u003e\u003cp\u003eIn this case, feeling temperature(fT) is calculated as -3 degrees Celsius.\u003c/p\u003e","function_template":"function fT =  feeling_temperature(gT,h,v)\r\n  fT = gT;\r\nend","test_suite":"%%\r\ngT=25;\r\nh=3000;\r\nv=10;\r\n\r\nfT_correct = -3;\r\nassert(isequal(feeling_temperature(gT,h,v),fT_correct))\r\n\r\n%%\r\ngT=30;\r\nh=500;\r\nv=0;\r\n\r\nfT_correct=27;\r\nassert(isequal(feeling_temperature(gT,h,v),fT_correct))\r\n\r\n%%\r\ngT=28;\r\nh=2500;\r\nv=3;\r\n\r\nfT_correct=10;\r\nassert(isequal(feeling_temperature(gT,h,v),fT_correct))","published":true,"deleted":false,"likes_count":3,"comments_count":0,"created_by":102298,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":74,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2017-07-16T14:13:00.000Z","updated_at":"2026-05-22T11:48:16.000Z","published_at":"2017-07-16T14:28:25.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eI sometimes climb a mountain. As is well known, when the altitude becomes 100 (m) higher, the temperature lowers by 0.6 degrees Celsius. In addition there is wind. At wind velocity 1(m/s), the feeling temperature falls 1 degree Celsius.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ee.g.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003etemperature of the level ground(gT) : 25 degrees Celsius\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ewind velocity(v) : 10 m/s\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eat altitude(h) : 3000 m\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIn this case, feeling temperature(fT) is calculated as -3 degrees Celsius.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":54595,"title":"String Logic 18","description":"Examples:\r\n'DIG' --\u003e 'DG'\r\n'IMPORTANT' --\u003e 'IPRAT'\r\n'DEAL' --\u003e 'DA'\r\n'LIMB' --\u003e 'LM'\r\n'MOSTLY' --\u003e 'MSL'","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 171px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 85.5px; transform-origin: 407px 85.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eExamples:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e'DIG' --\u0026gt; 'DG'\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e'IMPORTANT' --\u0026gt; 'IPRAT'\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e'DEAL' --\u0026gt; 'DA'\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e'LIMB' --\u0026gt; 'LM'\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e'MOSTLY' --\u0026gt; 'MSL'\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = StringLogic(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = 'DIG';\r\ny_correct = 'DG';\r\nassert(isequal(StringLogic(x),y_correct))\r\n\r\n%%\r\nx = 'IMPORTANT';\r\ny_correct = 'IPRAT';\r\nassert(isequal(StringLogic(x),y_correct))\r\n\r\n%%\r\nx = 'DEAL';\r\ny_correct = 'DA';\r\nassert(isequal(StringLogic(x),y_correct))\r\n\r\n%%\r\nx = 'LIMB';\r\ny_correct = 'LM';\r\nassert(isequal(StringLogic(x),y_correct))\r\n\r\n%%\r\nx = 'MOSTLY';\r\ny_correct = 'MSL';\r\nassert(isequal(StringLogic(x),y_correct))\r\n\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":232412,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":100,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2022-05-05T07:12:14.000Z","updated_at":"2026-05-15T02:37:09.000Z","published_at":"2022-05-05T07:12:14.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eExamples:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e'DIG' --\u0026gt; 'DG'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e'IMPORTANT' --\u0026gt; 'IPRAT'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e'DEAL' --\u0026gt; 'DA'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e'LIMB' --\u0026gt; 'LM'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e'MOSTLY' --\u0026gt; 'MSL'\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":42678,"title":"For a given linear index as input for n sized square matrix, find corresponding row and column.","description":"If input is 1, the row and column will be 1 and 1 respectively.","description_html":"\u003cp\u003eIf input is 1, the row and column will be 1 and 1 respectively.\u003c/p\u003e","function_template":"function rc = your_fcn_name(i,n)\r\n  % i is index and n is length of matrix \r\nend","test_suite":"%%\r\ni = 1;n = 1;\r\ny_correct = [1,1];\r\nassert(isequal(your_fcn_name(i,n),y_correct))\r\n%%\r\ni = 7;n = 3;\r\ny_correct = [1,3];\r\nassert(isequal([your_fcn_name(i,n)],y_correct))\r\n%%\r\ni = 16;n = 7;\r\ny_correct = [2,3];\r\nassert(isequal([your_fcn_name(i,n)],y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":3,"created_by":28123,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":77,"test_suite_updated_at":"2015-10-31T18:52:14.000Z","rescore_all_solutions":true,"group_id":1,"created_at":"2015-10-31T16:23:03.000Z","updated_at":"2026-05-15T03:12:19.000Z","published_at":"2015-10-31T16:38:06.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf input is 1, the row and column will be 1 and 1 respectively.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":45537,"title":"Get the area of ​​the square.","description":"Four circles are inscribed in the square ABCD. The perimeter of each circle is *aπ*.\r\n\r\n\u003c\u003chttp://imgfz.com/i/UzgCJut.png\u003e\u003e\r\n\r\nGiven *a*, obtain the area of ​​the square.\r\n","description_html":"\u003cp\u003eFour circles are inscribed in the square ABCD. The perimeter of each circle is \u003cb\u003eaπ\u003c/b\u003e.\u003c/p\u003e\u003cimg src = \"http://imgfz.com/i/UzgCJut.png\"\u003e\u003cp\u003eGiven \u003cb\u003ea\u003c/b\u003e, obtain the area of ​​the square.\u003c/p\u003e","function_template":"function y = squartArea(a)\r\n     y = a;\r\nend","test_suite":"%%\r\na = 0;\r\ny = 0;\r\nassert(isequal(squartArea(a),y))\r\n%%\r\na = 8;\r\ny = 256;\r\nassert(isequal(squartArea(a),y))\r\n%%\r\na = 1;\r\ny = 4;\r\nassert(isequal(squartArea(a),y))\r\n%%\r\na = 10;\r\ny = 400;\r\nassert(isequal(squartArea(a),y))\r\n%%\r\na = 50;\r\ny = 10000;\r\nassert(isequal(squartArea(a),y))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":446926,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":102,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-05-18T03:09:51.000Z","updated_at":"2026-05-24T15:55:13.000Z","published_at":"2020-05-18T03:09:51.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/image\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/media/image1.JPEG\"}],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFour circles are inscribed in the square ABCD. The perimeter of each circle is\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eaπ\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"-1\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ea\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, obtain the area of the square.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray 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fb+I9KtjBZeG9CiQsXY/21MzOxxlmY22WY4GSSSfWgBLvTotL1LwnbRFnxqMzvI+C8rtazlnY+pJJOMDngAACuurlmtPEWpa3o8+oafpVra2Nw87tBqEk7tmGSMAKYEHWQHOeg6V1NABRRRQBXu5mt7OeZUDtHGzBS2M4BOM4OPyNQWt1dNcG2vbaOGYpvTypjIrKDg8lVIIJGRjHI5POLF1b/arWa3MjoJUZCyY3AEY4zkZ/CobSyNuzSS3U91KflEswUEL1wAqqAM+2T3PAwAXaKKKACiiigAooooAKKKKACiiigAooooAKKKKAKNtc3F1KWWCMWhyFkMp8xiDj7u3ABwSDu9OKvVRgsDbXJeK8uBASSLY7CgJOTg7dw5yQN2BnAAAAq9QAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQB/9k=\"}]}"},{"id":54109,"title":"Get the n-th rand number with given seed","description":"Given seed s, return the n-th rand number using rand(). Round the answer with 4 digits.\r\nn is a postive integer.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 51px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 25.5px; transform-origin: 407px 25.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 276px 8px; transform-origin: 276px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven seed s, return the n-th rand number using rand(). Round the answer with 4 digits.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 67px 8px; transform-origin: 67px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003en is a postive integer.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function ans = getNthRand(s,n)\r\n","test_suite":"%%\r\ns = 1; n = 3;\r\ny_correct = .0001;\r\nassert(isequal(getNthRand(s,n),y_correct))\r\n%%\r\ns = 2; n = 100;\r\ny_correct = .8817;\r\nassert(isequal(getNthRand(s,n),y_correct))\r\n%%\r\ns = 1.2; n = 7;\r\ny_correct = .1863;\r\nassert(isequal(getNthRand(s,n),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":2044730,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":42,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2022-03-04T18:35:12.000Z","updated_at":"2026-05-15T10:14:06.000Z","published_at":"2022-03-04T18:35:12.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven seed s, return the n-th rand number using rand(). Round the answer with 4 digits.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003en is a postive integer.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":1382,"title":"Schwarzschild radius","description":"Compute the Schwarzschild radius for objects of mass m (kg). Use c = 299,792.458 km/s and G = 6.6738*10^-11 N*(m/kg)^2. Your function should give the result in m.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 42px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 21px; transform-origin: 407px 21px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 40.5px 8px; transform-origin: 40.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eCompute the\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 2px 8px; transform-origin: 2px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"/#null\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eSchwarzschild radius\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 246px 8px; transform-origin: 246px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e for objects of mass m (kg). Use c = 299,792.458 km/s and G = 6.6738*10^-11 N*(m/kg)^2. Your function should give the result in m.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = Schwarzschild_radius(m)\r\n  y = m;\r\nend","test_suite":"%%\r\nm = 5.98e24/81; % Moon\r\ny_correct = 1e-4; % m\r\nassert(isequal(Schwarzschild_radius(m),y_correct))\r\n\r\n%%\r\nm = 5.98e24; % Earth\r\ny_correct = 0.0089; % m\r\nassert(isequal(Schwarzschild_radius(m),y_correct))\r\n\r\n%%\r\nm = 1.89813e27; % Jupiter\r\ny_correct =  2.819; % m\r\nassert(isequal(Schwarzschild_radius(m),y_correct))\r\n\r\n%%\r\nm = 2e30; % Sun\r\ny_correct =  2970.2416; % m\r\nassert(isequal(Schwarzschild_radius(m),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":3,"created_by":810,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":57,"test_suite_updated_at":"2013-03-27T16:02:16.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-03-24T00:27:37.000Z","updated_at":"2026-05-26T21:59:48.000Z","published_at":"2013-03-24T00:30:30.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eCompute the\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eSchwarzschild radius\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e for objects of mass m (kg). Use c = 299,792.458 km/s and G = 6.6738*10^-11 N*(m/kg)^2. Your function should give the result in m.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":55915,"title":"Juros Compostos","description":"Faça uma função que receba um capital inicial (C), uma taxa de juros a ser aplicada (i) e um tempo (t) para qual será aplicado o investimento. Retorne o montante final.\r\nTodos os calculos faram baseados em meses. E o valor final deve ser expresso em 2 casas decimais.\r\n\r\nJurosCompostos(2000, 0.03, 4) = 2251.02 ","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 132.438px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 66.2188px; transform-origin: 407px 66.2188px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFaça uma função que receba um capital inicial (C), uma taxa de juros a ser aplicada (i) e um tempo (t) para qual será aplicado o investimento. Retorne o montante final.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eTodos os calculos faram baseados em meses. E o valor final deve ser expresso em 2 casas decimais.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 20.4375px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 10.2188px; transform-origin: 404px 10.2188px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003eJurosCompostos(2000, 0.03, 4) = 2251.02 \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function m = JurosCompostos(c, i, t)\r\n  % faça a sua função\r\nend","test_suite":"%%\r\nc = 2000;\r\ni = 0.03;\r\nt = 4;\r\ny_correct = 2251.02 ;\r\nassert(isequal(JurosCompostos(c, i, t) ,y_correct))\r\n\r\n\r\n%%\r\nc = 8000;\r\ni = 0.012;\r\nt = 6;\r\ny_correct = 8593.56 ;\r\nassert(isequal(JurosCompostos(c, i, t) ,y_correct))\r\n\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":2564100,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":36,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2022-09-17T19:11:27.000Z","updated_at":"2026-05-15T10:36:48.000Z","published_at":"2022-09-17T19:11:27.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFaça uma função que receba um capital inicial (C), uma taxa de juros a ser aplicada (i) e um tempo (t) para qual será aplicado o investimento. Retorne o montante final.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eTodos os calculos faram baseados em meses. E o valor final deve ser expresso em 2 casas decimais.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[JurosCompostos(2000, 0.03, 4) = 2251.02 ]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":51163,"title":"Total price with tax calculation for (m) items and price (p)","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 40.8889px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 406.5px 20.4444px; transform-origin: 406.5px 20.4444px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 20.4444px; text-align: left; transform-origin: 383.5px 20.4444px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eWrite a code that will calculate the total price with tax (T) of (m) items that carry price (p). Consider the tax rate as (r). Round the total price to two decimal places. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function T = Total_price(m,n,r)\r\n\r\nend","test_suite":"%%\r\np = 1;\r\nm=2;\r\nr=0.05;\r\nT_correct = 2.1;\r\nassert(isequal(Total_price(p,m,r),T_correct))\r\n\r\n%%\r\np = 4;\r\nm=5;\r\nr=0.1;\r\nT_correct = 22;\r\nassert(isequal(Total_price(p,m,r),T_correct))\r\n\r\n%%\r\np = 4.85;\r\nm=5;\r\nr=0.1;\r\nT_correct = 26.68;\r\nassert(isequal(Total_price(p,m,r),T_correct))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":995198,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":37,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2021-03-24T06:47:24.000Z","updated_at":"2026-05-15T10:52:02.000Z","published_at":"2021-03-24T06:47:24.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWrite a code that will calculate the total price with tax (T) of (m) items that carry price (p). Consider the tax rate as (r). Round the total price to two decimal places. \u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":44473,"title":"Let's make puddings !","description":"We will make puddings with eggs, milk and sugar.\r\nTo make one pudding, we need one egg, 140(cc) of milk, 15 (g) of sugar.\r\nNow We have x eggs,  y (cc) of milk, z (g) of sugar.\r\nHow many puddings can we make?\r\n\r\neg. When we have 3 eggs, 300cc milk, 300g sugar...\r\n\r\ninput :  x = 3, y = 300, z = 300\r\n\r\noutput :  Puddings= 2","description_html":"\u003cp\u003eWe will make puddings with eggs, milk and sugar.\r\nTo make one pudding, we need one egg, 140(cc) of milk, 15 (g) of sugar.\r\nNow We have x eggs,  y (cc) of milk, z (g) of sugar.\r\nHow many puddings can we make?\u003c/p\u003e\u003cp\u003eeg. When we have 3 eggs, 300cc milk, 300g sugar...\u003c/p\u003e\u003cp\u003einput :  x = 3, y = 300, z = 300\u003c/p\u003e\u003cp\u003eoutput :  Puddings= 2\u003c/p\u003e","function_template":"function Puddings = Egg_Milk_Sugar(x,y,z)\r\n  Puddings = 100;\r\nend","test_suite":"%% 1\r\nx = 3;\r\ny = 300;\r\nz = 300;\r\nC = 2;\r\nassert(isequal(Egg_Milk_Sugar(x,y,z),C))\r\n%% 2 \r\nx = 0;\r\ny = 999;\r\nz = 999;\r\nC = 0;\r\nassert(isequal(Egg_Milk_Sugar(x,y,z),C))\r\n%% 3\r\nx = 12;\r\ny = 1000;\r\nz = 100;\r\nC = 6;\r\nassert(isequal(Egg_Milk_Sugar(x,y,z),C))","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":137687,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":56,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2017-12-27T02:51:08.000Z","updated_at":"2026-05-25T11:42:47.000Z","published_at":"2017-12-27T03:32:17.000Z","restored_at":"2018-02-06T15:11:49.000Z","restored_by":null,"spam":false,"simulink":false,"admin_reviewed":true,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWe will make puddings with eggs, milk and sugar. To make one pudding, we need one egg, 140(cc) of milk, 15 (g) of sugar. Now We have x eggs, y (cc) of milk, z (g) of sugar. How many puddings can we make?\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eeg. When we have 3 eggs, 300cc milk, 300g sugar...\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003einput : x = 3, y = 300, z = 300\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eoutput : Puddings= 2\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":42976,"title":"iteration of N blank spot","description":"we have N spot which can be blank o filled calculate the number of iteration for these spots. e.g. N=2 1- blank blank 2- blank full 3- full blank 4- full full iteration is 4 e.g. N=3 1- blank blank blank 2- blank blank full 3- blank full blank 4- blank full full 5- full blank blank 6- full blank full 7- full full blank 8- full full full iteration is 8","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 63px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 31.5px; transform-origin: 407px 31.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 372.5px 8px; transform-origin: 372.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003ewe have N spot which can be blank o filled calculate the number of iteration for these spots. e.g. N=2 1- blank blank 2- blank full 3- full blank 4- full full iteration is 4 e.g. N=3 1- blank blank blank 2- blank blank full 3- blank full blank 4- blank full full 5- full blank blank 6- full blank full 7- full full blank 8- full full full iteration is 8\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = your_fcn_name(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = 1;\r\ny_correct = 2;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = 5;\r\ny_correct = 32;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = 8;\r\ny_correct = 256;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = 11;\r\ny_correct = 2048;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = 16;\r\ny_correct = 65536;\r\nassert(isequal(your_fcn_name(x),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":2,"created_by":86389,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":61,"test_suite_updated_at":"2021-06-17T14:24:43.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2016-09-02T16:46:32.000Z","updated_at":"2026-04-22T05:15:27.000Z","published_at":"2016-09-02T16:46:32.000Z","restored_at":"2022-02-16T22:15:33.000Z","restored_by":null,"spam":false,"simulink":false,"admin_reviewed":true,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ewe have N spot which can be blank o filled calculate the number of iteration for these spots. e.g. N=2 1- blank blank 2- blank full 3- full blank 4- full full iteration is 4 e.g. N=3 1- blank blank blank 2- blank blank full 3- blank full blank 4- blank full full 5- full blank blank 6- full blank full 7- full full blank 8- full full full iteration is 8\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":49657,"title":"Determine the area of square if length of the diagonal is given","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 10.5px; transform-origin: 407px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eWe have to find the area of square if the length of the diagonal of a square is given.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = your_fcn_name(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = 4;\r\ny_correct = 8;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":822117,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":75,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-12-29T15:05:52.000Z","updated_at":"2026-05-24T15:57:49.000Z","published_at":"2020-12-29T15:05:52.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWe have to find the area of square if the length of the diagonal of a square is given.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"}],"term":null,"current_player_id":null,"fields":[{"name":"page","type":"integer","callback":null,"default":1,"directive":null,"facet":null,"facet_method":"and","operator":null,"param":null,"static":null,"prepend":true},{"name":"per_page","type":"integer","callback":null,"default":50,"directive":null,"facet":null,"facet_method":"and","operator":null,"param":null,"static":null,"prepend":true},{"name":"sort","type":"string","callback":null,"default":null,"directive":null,"facet":null,"facet_method":"and","operator":null,"param":null,"static":null,"prepend":true},{"name":"body","type":"text","callback":null,"default":"*:*","directive":null,"facet":null,"facet_method":"and","operator":null,"param":"term","static":null,"prepend":false},{"name":"group","type":"string","callback":null,"default":null,"directive":"group","facet":true,"facet_method":"and","operator":null,"param":"term","static":null,"prepend":true},{"name":"difficulty_rating_bin","type":"string","callback":null,"default":null,"directive":"difficulty_rating_bin","facet":true,"facet_method":"and","operator":null,"param":"term","static":null,"prepend":true},{"name":"id","type":"integer","callback":null,"default":null,"directive":"id","facet":null,"facet_method":"and","operator":null,"param":"term","static":null,"prepend":true},{"name":"tag","type":"string","callback":null,"default":null,"directive":"tag","facet":null,"facet_method":"and","operator":null,"param":"term","static":null,"prepend":true},{"name":"product","type":"string","callback":null,"default":null,"directive":"product","facet":null,"facet_method":"and","operator":null,"param":"term","static":null,"prepend":true},{"name":"created_at","type":"timeframe","callback":{},"default":null,"directive":"created_at","facet":null,"facet_method":"and","operator":null,"param":"term","static":null,"prepend":true},{"name":"profile_id","type":"integer","callback":null,"default":null,"directive":"author_id","facet":null,"facet_method":"and","operator":null,"param":"term","static":null,"prepend":true},{"name":"created_by","type":"string","callback":null,"default":null,"directive":"author","facet":null,"facet_method":"and","operator":null,"param":"term","static":null,"prepend":true},{"name":"player_id","type":"integer","callback":null,"default":null,"directive":"solver_id","facet":null,"facet_method":"and","operator":null,"param":"term","static":null,"prepend":true},{"name":"player","type":"string","callback":null,"default":null,"directive":"solver","facet":null,"facet_method":"and","operator":null,"param":"term","static":null,"prepend":true},{"name":"solvers_count","type":"integer","callback":null,"default":null,"directive":"solvers_count","facet":null,"facet_method":"and","operator":null,"param":"term","static":null,"prepend":true},{"name":"comments_count","type":"integer","callback":null,"default":null,"directive":"comments_count","facet":null,"facet_method":"and","operator":null,"param":"term","static":null,"prepend":true},{"name":"likes_count","type":"integer","callback":null,"default":null,"directive":"likes_count","facet":null,"facet_method":"and","operator":null,"param":"term","static":null,"prepend":true},{"name":"leader_id","type":"integer","callback":null,"default":null,"directive":"leader_id","facet":null,"facet_method":"and","operator":null,"param":"term","static":null,"prepend":true},{"name":"leading_solution","type":"integer","callback":null,"default":null,"directive":"leading_solution","facet":null,"facet_method":"and","operator":null,"param":"term","static":null,"prepend":true}],"filters":[{"name":"asset_type","type":"string","callback":null,"default":null,"directive":null,"facet":null,"facet_method":"and","operator":null,"param":null,"static":"\"cody:problem\"","prepend":true},{"name":"profile_id","type":"integer","callback":{},"default":null,"directive":null,"facet":null,"facet_method":"and","operator":null,"param":"author_id","static":null,"prepend":true}],"query":{"params":{"per_page":50,"current_player":null,"sort":"map(difficulty_value,0,0,999) 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