Name: Meshaal Mouawad | مشعل معوض
Type: User
Company: SABIC | Innovation & Big Data
Bio: Digital Innovation Engineer at SABIC | Metaverse Innovation | XR/VR Developer | Digital Twin | AI, Deep & Machine Learning | Robotics
Twitter: Meshaal_Mouawad
Location: Saudi Arabia
Blog: https://msstate.academia.edu/Meshaalmouawad
Meshaal Mouawad | مشعل معوض's Projects
https://drive.google.com/drive/folders/1NzA1KPOR-drZ2CZ8CCmfpX_YnsoIHuZV?usp=sharing. This is a 'Super Mario 3D World' Style game created in Unity and C#. I have videos of this project on my youtube channel:https://www.youtube.com/channel/UCEShkg8TVshTmfDlvBZkXjw. The programming and animations are my own work, however, not all modelling is my own
All algorithms implemented in C#.
The project examines design aspects for a U.S. Army radar for learning purpose. Constant false alarm rate (CFAR) detection refers to a common form of adaptive algorithm used in radar systems to detect target returns against a background of noise, clutter and interference.
This is an internship I have completed at General Electric. message from the program (In this program you will combine and visualize data to drive meaningful insights using enterprise-grade technology. You'll have work samples for both data engineering and data visualization to assist the GE Aviation team to make decisions based off real time data. We are excited to have you participate and we hope that you come away from them with a better understanding of how GE Aviation rises to the challenge to invent the future of flight, lift people up, and bring them home safely. )
Three experiments were examined in this technical report for digital signal processing. In experiment 1, we analyzed and examined how the fast Fourier transform (FFT) resolution was affected by adjusting the filter length, the filter type, and the FFT order. An FFT Physical resolution and a Computational Resolution were discussed in experiment 1. In experiment 2, the data was given in MATLAB and we investigated the signals concurrently in time and frequency using the Short-time Fourier transform (STFT). We estimated the sampling rate and briefly discussed the Short-time Fourier transform (STFT) and the FFT in terms of how different they are. The Short-time Fourier transform (STFT) and Support Vector Machine (SVM) were discussed in experiment 3. We implemented an SVM to estimate four walking speeds using features extracted from simulated micro-doppler radar for walking humans. Figures of the STFT magnitude of each class are presented and discussed the basics of Doppler Effect as well as micro-doppler. We examined the results using a confusion matrix for training and testing and the best results are presented. MATLAB and related tools were used in this project and the code is provided in the report.
Improvement of Potential Field Algorithm for Robot Path Planning. The objective of the project is to apply the Artificial Potential Field (APF) algorithm for robot path planning to improve this robot path planning algorithm and resolve some issues such as local minima of an autonomous mobile robot.
Abstract—. MNIST, Modified National Institute of Standards and Technology, is the largest database of handwritten numbers used in deep learning, and machine learning. In this project, a hands-on experience of applying machine learning and pattern recognition techniques is given to a real-world data set such as MNIST. Multiple building blocks have been proposed and analyzed to improve the speed and the accuracy of the Convolutional Neural Networks (CNN). Two networks have been used with the same data. In network I, a three-layer MLP with ReLU and dropout resulting in fast training process with over all accuracy 95% during training and 94% for testing. Network II on the other hand, a stack of CNN, RelU, and Max pooling shows slower training process with better accuracy than network I and overall, 99% accuracy for training, and 98.9% for testing. Another modification on network II improved overall accuracy during the training to 99.82% and accuracy for testing to 99.25%. this modification will be shown in the report. The building blocks for the project will be discussed briefly with the results and figures. Python code is also provided for this project. This project may be used for as a guidance for new students or engineers who aiming to understand pattern recognition.
All Algorithms implemented in Python
Objectives: The objective of the project is to 1- get familiar with Visibility Graph (VG) technique-based robot global path planning. 2- apply the Visibility Graph technique of robot global path planning in workspace with a variety of obstacles. 3- improve this Visibility Graph technique of robot path planning and attempt creation of Reduced Visibility Graph (RVG) algorithm. 4- revise the Visibility Graph learned in the classroom to Tangent Graph-based (TG) path planning (optional).
Rocket-Game-Project
Custom Speckle visuals for PowerBI
This first mission in the Junior Programmer pathway will provide you with the core foundation needed to create a wide range of digital experiences in Unity. You’ll learn about fundamental programming concepts such as variables, functions and basic logic through two practical projects.
Central repository for tools, tutorials, resources, and documentation for robotics simulation in Unity.
🌻🍄 Learn to make Super Mario Bros in Unity.