Mohammad Sh. Daoud, Ph.D

ِِِِAssociate Professor

Abu Dhabi Campus

+971 2 6133591

mohammad.daoud@aau.ac.ae

Biography

MOHAMMAD SH. DAOUD received the Ph.D. degree in computer science from De Montfort University, U.K. He is currently an Associate Professor with the College of Engineering, Al Ain

University, United Arab Emirates. His research interests include Artificial Intelligence, and Secured Systems and Networks.

Education

Ph.D. Computer Science, De Montfort University, UK

Master of Computer Science, University of Jordan, Jordan

BSc of Computer Information System, AL-Zaytoonah University, Jordan

Research Interests

Wireless communications, Artificial Intelligence, and Secured Systems and Networks.

Selected Publications

 

  • Ihnaini, Baha, Khan, M. A., Khan, Tahir Abbas, Abbas, Sagheer Daoud, M.S et al. A Smart Healthcare Recommendation System for Multidisciplinary Diabetes Patients with Data Fusion Based on Deep Ensemble Learning. Computational Intelligence and Neuroscience. Volume 2021.

 

  • Daoud, M. S., Aftab, S., Ahmad, M., Khan, M. A., Iqbal, A. et al. (2022). Machine Learning Empowered Software Defect Prediction System. Intelligent Automation & Soft Computing, 31(2), 1287–1300.

 

  • Daoud, M.Sh., Fatima, A., Khan, W.A., Khan, M.A., Abbas, S., Ihnaini, B., Ahmad, M., Javeid, M.S., Aftab, S. Joint channel and multi-user detection empowered with machine learning (2021) Computers, Materials and Continua, 70 (1), pp. 109-121.

 

  • Abidi, W.U.H., Daoud, M.S., Ihnaini, B., Khan, M.A., Alyas, T., Fatima, A., Ahmad, M. Real-Time Shill Bidding Fraud Detection Empowered with Fussed Machine Learning (2021) IEEE Access, 9, art. ,pp. 113612-113621.

 

  • Ahmad, M., Alfayad, M., Aftab, S., Khan, M.A., Fatima, A., Shoaib, B., Daoud, M.S., Elmitwally, N.S. Data and Machine Learning Fusion Architecture for Cardiovascular Disease Prediction (2021) Computers, Materials and Continua, 69 (2), pp. 2717-2731.

 

  • Shehab, M., Abualigah, L., Jarrah, M.I., Alomari, O.A., Daoud, M.S. Artificial Intelligence in Software Engineering and inverse: Review (2020) International Journal of Computer Integrated Manufacturing, 33 (10-11), pp. 1129-1144.

 

  • Mashal, I., Shuhaiber, A., Daoud, M. Factors influencing the acceptance of smart homes in Jordan(2020) International Journal of Electronic Marketing and Retailing, 11 (2), pp. 113-142.

 

  • Almimi, H.M., Shahin, S.A., Daoud, M.S., Al Fayoumi, M., Ghadi, Y.Enhanced E-voting protocol based on public key cryptography(2019) Proceedings - 2019 International Arab Conference on Information Technology, ACIT 2019, art. no. 8990991, pp. 218-221.

 

  • M Shehab, MS Daoud, HM AlMimi, LM Abualigah, AT Khader. Hybridising cuckoo search algorithm for extracting the ODF maxima in spherical harmonic representation. International Journal of Bio-Inspired Computation, inderscience 14 (3), 190-199, 2019.

 

  • Sh. Daoud, Mohammad & Ghadi, Yazeed & Almimi, Hani. Optimization of the Application Software in Biomechanics and Their Contribution to The Biological Field, Journal of Engineering Science and Technology Review, 178-184, volume 12, issue 1, April 2019.

Conferences

  • M. S. Daoud, T. Elamsy, Y. Ghadi, G. Albrazi and M. Shabou, "Redundancy Avoidance in Entity Resolution Based On Social Networks Paradigm," 2021 Eighth International Conference on Social Network Analysis, Management and Security (SNAMS), 2021, pp. 01-05.

  • L. Alhelli, M. Al-Yafeai, M. S. Daoud and T. Elamsy, "An Intelligent Route Finder For UAE Desert Driver Based On A Algorithm," 2021 8th International Conference on Internet of Things: Systems, Management and Security (IOTSMS), 2021, pp. 1-5.

  • A. Shuhaiber, N. Adam and M. Sh.Daoud, "Towards A Smarter Energy Metering System For A Smarter City: A Regression-Based Model From Users’ Perspective," 2021 22nd International Arab Conference on Information Technology (ACIT), 2021, pp. 1-6.

  • Daoud, M &Hani Mimi. A survey on Location Based-Services over Cellular Network, 8th International Conference on Information Technology ICIT'2017 IEEE International.17- 18,May,20017.

     

Teaching Courses

Introduction to Programming Languages ,Computer Networks, Operating Systems, User Interface, Web Programming , Ethical Hacking and  "Intrusion Analysis and

Incident Management"

Memberships

5th Generation Cellular Communication Group, Manchester Metropolitan / UK.

0

Optimization of the Application Software in Biomechanics and Their Contribution to The Biological Field.

Published in: Journal of Engineering Science & Technology Review

May 01, 2019

Mohammad Sh Daoud Yazeed Ghadi Hani Almimi

Biomechanics refers to study of movement within dynamic biological systems. Advancement of computer software technologies such as JAVA language leads to combine stimuli and signals by biological systems and utilize them for research purposes. The main aim of this research is to analyse various biomechanical software and advancements that have been made in the field of mechanical software. Secondary research analysis has been utilized within this research paper. A Number of computational software such as OpenSim and ABAQUS have been proven to be very beneficial in this aspect. Advancement in biomechanical software has led to better research in cancer and cytoskeletal studies. Thus, Biomechanical software enables us to study kinetics of body without invasive procedures and does not cause any hindrance to ethical issues.


Conference Paper

A new splitting-based displacement prediction approach for location-based services

Published in: 2011 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

Nov 21, 2011

Daoud M.; Ayesh A.; Hopgood A. & Al-Fayoumi

In location-based services (LBSs), the service is provided based on the users' locations through location determination and mobility realization. Several location prediction models have been proposed to enhance and increase the relevance of the information retrieved by users of mobile information systems, but none of them studied the relationship between accuracy rate of prediction and the performance of the model in terms of consuming resources and constraints of mobile devices. Most of the current location prediction research is focused on generalized location models, where the geographic extent is divided into regular-shape cells. These models are not suitable for certain LBSs where the objectives are to compute and present on-road services. One such technique is the Prediction Location Model (PLM), which deals with inner cell structure. The PLM technique suffers from memory usage and poor accuracy. The main goal of this paper is to propose a new path prediction technique for Location-Based Services. The new approach is competitive and more efficient compared to PLM regarding measurements such as accuracy rate of location prediction and memory usage.