Dr. Marwan Kadhim Mohammed AL-shammari
@uob.edu.iq
Computer Engineering
Northeastern University, China
Marwan Kadhim Mohammed was born in Iraq in 1977, PhD, in Northeastern University. He received the B.S. in Computer Engineering from Baghdad University, Iraq in 2000, the M.S. in Computer Engineering from UTeM University, Malaysia, in 2014, CISCO American institute instructor from 2007. He joined Baghdad University in 2006 as a lecturer of Department of computer engineering. He was director for research & developing division and training & continues learning division respectively. He was Core member in advisory office of Baghdad University. He has been a team leader at South Korean and Canada with Coicka and ED companies respectively. He is team leader for many projects in the field of Java, , visuals, IOS, OS, CG, Media, Networking, DB, Embedded Systems, Embedded Software, VR, EEG, Robotic surgery, Networking. He was external lecturer for postgraduate student in Northeastern University. 5 papers published, chapter in Springer book series 2018.
RESEARCH INTERESTS
UAV, Robotics, VR, EEG, cybersecurity, Embedded system, Embedded software, Telemedicine, and robotic surgery, deep-learning, neural network, SWARM, 5G wireless mesh network.
Scopus Publications
Scholar Citations
Scholar h-index
Scopus Publications
Halah Hasan Mahmoud, Marwan Kadhim Mohammed Al-Shammari, Gehad Abdullah Amran, Elsayed Tag eldin, Ala R. Alareqi, Nivin A. Ghamry, Ehaa ALnajjar, and Esmail Almosharea
Computers, Materials and Continua (Tech Science Press)
Halah Hasan Mahmoud, Abed Saif Alghawli, Marwan Kadhim Mohammed Al-shammari, Gehad Abdullah Amran, Khaled H. Mutmbak, Khaled H. Al-harbi, and Mohammed A. A. Al-qaness
MDPI AG
The predilection for 5G telemedicine networks has piqued the interest of industry researchers and academics. The most significant barrier to global telemedicine adoption is to achieve a secure and efficient transport of patients, which has two critical responsibilities. The first is to get the patient to the nearest hospital as quickly as possible, and the second is to keep the connection secure while traveling to the hospital. As a result, a new network scheme has been suggested to expand the medical delivery system, which is an agile network scheme to securely redirect ambulance motorbikes to the nearest hospital in emergency cases. This research provides a secured and efficient telemedicine transport strategy compatible with the vehicle social network (VSN). The proposed telemedicine method should find the best ambulance motorbike route for getting patients to the hospital as quickly as possible. This approach also enables the secure exchange of information between ambulance motorbikes and hospitals. Ant colony optimization (ACO) is utilized as a SWARM technique to expand the capabilities of 5G-wireless mesh networks to determine the best path. To secure communication, the secure socket layer (SSL), which is boosted once by the advanced encryption standard (AES), has achieved a new suggested scheme as a cybersecurity approach. According to the performance evaluation, this approach will determine the optimal route for motorbike ambulances. Additionally, this technique establishes a secure connection between ambulance motorbikes and the hospital. The study enhances telemedicine transportation.
Marwan Kadhim Mohammed Al-shammari, TianHan Gao, Rana Kadhim Mohammed, and Song Zhou
Multimedia Tools and Applications Springer Science and Business Media LLC
Attention Deficit Hyperactivity Disorder (ADHD) is a common and heritable disease that has an environmental influence on brain function. The diseases affects multiple aspects of the lives of college students, not only on their study but also on the relationships with other people. The problem with ADHD attention involves short term memory. The purpose of this paper is to investigate the capability of improving short term working memory for ADHD patients by the aid of technology a proper VR environment is built for ADHD, who are isolated from the real circumference. Electroencephalography (EEG) is taken as biofeedback to read the brain signal from the patient. A deep learning approach and an artificial neural network method, are employed to efficiently and accurately process EEG. The findings of the trial indicate that the virtual reality recommended system will play a greater role in improving the attention to the ADHD patient.
Marwan Kadhim Mohammed Al-shammari and Gao Tian Han
Springer International Publishing
Alzheimer disease is associated with many risks, including the destruction of family morale and the loss of experience of many scientists in different areas. However, little research depending on computer science has been conducted to explore this disease. The purpose of this study is trying to find the possibility of using computer techniques to improve the therapeutic methods of Alzheimer disease. This paper elaborates the approach of using EEG signals on virtual reality environment and introducing them as a patient’s therapeutic program to improve temporary memory. The patient’s memory is rearranging based on a suitable brain signal through the theory of artificial neural network and deep learning technique so that the memory is able to be gradually improved.
Wang Bei Lei, Marwan Kadhim Mohammed Al-shammari, and HuiMing Xiao
ACM
This study examines the secure transition for robotic surgery session. Surgeon sends set of instructions as data. The data is encapsulated with surgeon secure signature to conform surgeon identity. At the same time, patient information sends to the surgeon as a secure row of frames to estimate patient situation dependent on the real medical reports. Elliptic Curve Diffie-Hellman is use as an asymmetric encryption method. Here the session between surgeon console and interactive robot arm was achieved and supported with four secret keys. Two private keys are chosen on each side and two public keys are calculated from these private keys. These results indicate that the level of the security was improved by use asymmetric encryption rather than symmetric encryption. And by contributed four secret keys the patient information must be safer.