Topic
- Computing and Processing
- Components, Circuits, Devices and Systems
- Communication, Networking and Broadcast Technologies
- Power, Energy and Industry Applications
- Signal Processing and Analysis
- Robotics and Control Systems
- General Topics for Engineers
- Fields, Waves and Electromagnetics
- Engineered Materials, Dielectrics and Plasmas
- Bioengineering
- Transportation
- Photonics and Electrooptics
- Engineering Profession
- Aerospace
- Geoscience
- Nuclear Engineering
- Career Development
- Emerging Technologies
- Telecommunications
- English for Technical Professionals
Najmaddin Abo Mosali
Affiliation
Department of Electrical Engineering Technology, Faculty of Engineering Technology, Universiti Tun Hussein Onn Malaysia (UTHM)
Topic
Acceleration Term,Actor-critic,Aerial Vehicles,Angular Rotation,Antenna Design,Antenna Solution,Application Of Reinforcement Learning,Application Of Solution,Autonomic Features,Characteristics For Applications,Compact Antenna,Compact Solution,Conceptual Diagram,Cramer-Rao Lower Bound,Deep Q-network,Deep Reinforcement Learning,Design Process,Divide-and-conquer Approach,Experimental Validation,Exponential Weighting,Flight Test,Inverse Reinforcement Learning,Markov Decision Process,Multi-agent Reinforcement Learning,Multi-stage Training,Q-learning,Reinforcement Learning Framework,Return Loss,Reward Function,Reward Model,Sensor Failure,Simulation Results,Target Tracking,Time Series,Tracking Performance,Trained Agent,Unmanned Aerial Vehicles,Vector Network Analyzer,Velocity Term,
Biography
Najmaddin Abo Mosali received the B.Eng. degree in electronic engineering from Universiti Tun Hussein Onn Malaysia (UTHM), in 2016, and the upgraded master’s degree in mechanical engineering in the area of aeronautical, in 2018. He is currently pursuing the Ph.D. degree in mechanical engineering in the area of aeronautical with UTHM. He has authored or coauthored numbers of journals and proceedings. His current research interests include the aircraft and target tracking, intelligent adaptive control, and reinforcement learning. He has received the Chancellor Award for his bachelor’s degree and number of Gold, Silver, and Bronze medals in international and local competitions.