
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
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Mohamad Kenan Al-Hares
Also published under:Mohamed Kenan Al-Hares, M. Kenan Al-Hares, M. K. Al-Hares
Affiliation
School of Engineering and Digital Arts, University of Kent, Canterbury, U.K.
Topic
Data Rate,Remote Unit,Traffic Sources,Base Station,Cloud Radio Access Network,Frame Size,Medium Access Control,Mobile Network,Priority Queue,Serialized,Traffic Flow,Access Network,Data Rate Requirements,Digital Unit,Fronthaul Network,Hip Joint,Knee Joint,Lower Limb,Lower Limb Exoskeletons,Medium Access Control Layer,Radio Access Network,Simulation Results,Single-mode Fiber,Split Point,Systematic Review,Time-aware Shaping,Traffic Characteristics,Traffic Rate,Virtual Network Functions,Actuation Mechanism,Air Interface,Analog-to-digital Converter,Angular Velocity,Ankle Foot Orthoses,Arbitrary Waveform Generator,Assistive Technology,Back Propagation Neural Network,Bridge Network,Brushless DC,Buffer Management,Buffer Size,Cerebral Palsy,Clinical Characteristics,Clinical Perspective,Clinical Trials,Combined Weight,Complementary Cumulative Distribution Function,Control Architecture,Control Strategy,DC Motor,
Biography
Mohamad Kenan Al-Hares received the B.Eng. degree in computer and communication engineering from Arab International University, Daraa, Syria, the M.Sc. degree in network computing from Coventry University, Coventry, U.K., and the Ph.D. degree in electronic engineering from the University of Kent, Canterbury, U.K. He is currently with the Intelligent Interactions Research Group. He is a member of the Kent Assistive Robotics Laboratory (KAROL), School of Engineering, University of Kent. His research interests include cloud-radio access networks, ethernet fronthaul development for the future mobile networks, and machine and deep learning.