Magdy A. Mohamed

§ Fault diagnosis in motoring systems using artificial intelligence techniques.
§ It has been argued that the recommended system will improve fault detection accuracy.
§ Collecting dataset and extracting hybrid signal feature is the reason support the idea.
§ Machine Learning models are used to create the suggested model, and outcomes from
different models are compared.
§ The proposed scheme will be adapted to an efficient Shaped scheme for completely
classification among health and fault cases: • KNN. • SVM. • DT. • Random Forest.
• XGBoost.
§ https://mail.etasr.com/index.php/ETASR/article/view/14015
§ https://cmt3.research.microsoft.com/SSSCEA2026/Submission/Summary/281
§ https://jaes.journals.ekb.eg/author?_action=gl&manu_code=428962
§ Design and Implementation of a fully Interactive Web Server for Monitoring and
Control (WMC) Embedded System Application.
§ The real time measurement of conditioning environmental parameters (Temperature and
Humidity) using HC11 and DHT11 modules connected to Raspberry kit with an
optimized Web Graphical User Interface (GUI).
§ The digital environmental parameters measurement is filled by creating multi- actuator.
§ The proposed system consists of the system reading, monitoring and acting stages to
adapt the targeted environmental parameters.
§ Each place equipped with remotely actuator achieved by using both the wireless module
integrated with the smart database engine to store each timed status.
§ According to the conditioned set point and the measured environmental parameters by
the actuator the parameters are adequate. These states can be used for driving the
appropriate actuators .
§ Intelligent algorithms are used for system data acquisition; if the site state remains
unchanged, no more data is stored.
§ C# code to control the HC-11 module using transfer parameters amount for each site.
§ Visual studio 2008 for web for interface. Microsoft SQL Database is used to store the
environmental parameter status.
§ http://sersc.org/journals/index.php/IJAST/article/view/20103

Technical courses
§ NTI Machine Learning.
§ NTI Deep Learning.
§ NTI Computer Vision.
§ Relational Database Management System (RDBMS).
§ CompTIA A+ (220-901 and 220-902).
§ Developing Microsoft SQL Server 2000/2019 Databases (70-464).
§ Administering Microsoft SQL Server 2000/2019 Databases (70-462).
§ The Microsoft Certified professional (MCP).
§ The Microsoft Certified Applications Developer (MCAD).
§ The Microsoft Certified Solution Developer (MCSD).
§ Oracle development course at planning institution.
§ Microsoft Certified Solution Architecture.
§ Kaspersky Administration and Implementation.
§ Milestone Certified Integration.
§ MATLAB and Simulink Self-Paced Online Courses.
§ Virtual Environment Infrastructures (VMWare - Nutanix).
§ Linux/Unix administration Infrastructure