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Apps and models for teaching numerical sciences and computer science

version 1.2.0.1 (2.72 MB) by Emilie Delaherche
Interactive apps and Simulink models for numerical sciences and computer science

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Updated 01 Sep 2016

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This submission contains a manual and a series of MATLAB Apps and Simulink Models for introducing Numerical Sciences and Computer Science in secondary schools.
It includes the following apps and models :
- Data Type Conversion App. App to convert between boolean, decimal, hexadecimal and character types,
- Simulink model to realize logical operations on booleans,

- JPEG Compression App. This App allows you to change the quality factor of JPEG compression and visualize original, compressed and gray-scale image difference between original and compressed image.

- Watermarking is the process of hiding digital information in a carrier signal, here an image. The Watermarking App allows the user to :
- Load an image
- Enter the message to hide
- Select the bit containing the hidden message
- Select the color component containing the hidden message (R, G, B)
- Visualize original image, code image and watermarked image,

- Audio Acquisition App : Interactive acquisition of audio signals,

- Graph Traverse App. This App allows the user to :
- Load a graph (sparse matrix)
- Visualize the graph
- Run a traverse algorithm (DFS or BFS) or find the shortest Path between two nodes
- Visualize the path, possibly step by step

- Simulink models to communicate an encrypted image between two Raspberry Pi,

- Simulink model for obstacle avoidance on LEGO Mindstorms (using State Machines, stateflow).

Cite As

Emilie Delaherche (2021). Apps and models for teaching numerical sciences and computer science (https://www.mathworks.com/matlabcentral/fileexchange/47854-apps-and-models-for-teaching-numerical-sciences-and-computer-science), MATLAB Central File Exchange. Retrieved .

Comments and Ratings (3)

h hjjhk

i want jpeg image compression code can you help me thank's

Pavel Osipov

Thai Le

MATLAB Release Compatibility
Created with R2014b
Compatible with any release
Platform Compatibility
Windows macOS Linux
Acknowledgements

Inspired by: Data Acquisition

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