Computer Engineering Department at UOT held seminars for postgraduate students (MSc) in the research phase. The session was attended by the head of the department, Assist. Prof. Dr. Hassan Jalil Hassan, the professors, the student supervisors', in addition to the postgraduate students, in conference hall at the department.

Where the initial discussion of the student (Zainab Issam Kanon) for her research tagged:

Multi-Mobile Robots Path Planning Algorithm and Control Methodology Design based on FPGAs.

Under the supervision of Prof. Dr. Ahmed Sabah Al-Araji and Prof. Dr. Muhammad Najm Abdullah.

The objective of this work is trying to improve the performance of a group of mobile robots while planning the required path from the starting point to the target point, following the paths, avoiding collision with stationary obstacles and also avoiding the paths of other mobile robots. So a smart algorithm is proposed to solve these problems. Adaptive control methodology with optimized particle swarming algorithm is also used to control the motion of the non-linear mobile robot system. 

In the same session, MSc student (Bilqis Raad Abdul Latif) was discussed for her research tagged:

An Overlay Bio-inspired Routing Protocol for Ad-hoc Networks.

Under the supervision of Lec. Dabsam Mohamed Saeed.

The work aims reducing the overburden of energy conservation to extend the life of the network.

The research of MSc student (Tariq Mustafa Radwan) was discussed for his tagged research:

Remote Autonomous Proctoring on Multiple Exam Stations by Learning Visual Behaviors

Under the supervision of Lec. Dr. Saif Ghassan Mohamed.

This research aims to monitor the examination halls automatically and without the presence of observers to increase the accuracy of monitoring and reduce the effort and cost on educational institutions.

At the end of the session, MSc student (Rania Roni Aziz) discussed her research tagged:

Heart Disease Diagnosis System In The Internet Of Things Environment Based On Deep Learning Techniques.

Under the supervision of Lec .Dr. Ahmed Musa Dinar.

The goal of this work is to design and implement an Internet of Things-based system for more accurate diagnosis and prediction of heart disease using deep learning techniques. First, multiple sensors sense the patient's physiological data and transmit it to the connected device. Then, the read data is sent to a deep learning algorithm for processing.