Nomadic People Optimizer Algorithm and its Applications
Abstract: Many metaheuristic algorithms and their variants have been introduced and implemented to solve several optimization problems. Most of these algorithms were inspired by nature or the behavior of a human or certain animals such as birds, wolves, ants, bees, bats, and etc. These algorithms faced several issues, such as the balancing between the exploration and exploitation capabilities. A novel swarm-based metaheuristic algorithm which depends on the behavior of nomadic people called “Nomadic People Optimizer (NPO)” will be presented. NPO simulates the nature of these people in their movement and searches for sources of life (such as water or grass for grazing), and how they have lived hundreds of years, continuously migrating to the most comfortable and suitable places to live. The NPO algorithm was primarily designed based on the Multi-Swarm approach, consisting of several clans and each clan looking for the best place, in other words, for the best solution depending on the position of their leader. The NPO algorithm has been implemented to solve several optimization problems such as Engineering problems, combinatorial Testing problems, and etc.
Presenter
Associate Prof. Dr. Abdul-Rahman Ahmed Alsewari
Faculty of Computing, Universiti Malaysia Pahang, Malaysia
[email protected]
Profile: Abdul-Rahman A. Alsewari received his Ph.D. degree in Software Engineering from Universiti Sains Malaysia USM, Pinang, Malaysia in 2012. Master of Electronic System Design Engineering from USM in 2009, Bachelor of Computer Engineering from Military Engineering College, Iraq in 2002. He has more than 10 years of Research and Teaching experience in the domain of Computer Engineering and Computer Science. Currently, he is an Associate Professor with the Faculty of Computing, University Malaysia Pahang, where he has conducted Undergraduate and Masters Courses and supervised more than 40 B.Sc., 3 M.Sc., and 5 PhD students. He worked as a Research Fellow with Universiti Sains Malaysia from 2007 until 2012. His research interests include Soft Computing Software Engineering, Artificial Intelligence, Optimization Algorithms, Image Processing, and Machine Learning.
Vehicular Network Security Issues and Challenges
Abstract: Nowadays, vehicle manufacturers are offering increasingly onboard devices, including powerful computers, a large array of sensors, radar devices, cameras, and wireless communications. Vehicles can communicate and interact with its surrounding offering many applications including road safety, traffic efficiency, and passengers’ comfort. Vehicles can communicate and share their movement status so that applications can make the right decisions for the right situation for enabling the full automation of autonomous driving. Besides, vehicles can communicate in an ad hoc manner without the need for infrastructure which makes it promising for many applications to provide safety, internet connectivity, and enable the internet of things (IoT) in rural areas. Unfortunately, there are many security challenges attackers can disturb the fundamental operations of vehicular networks. I am going to highlight the research challenges and the security issues of these emerging vehicular network technology.
Presenter
Assistant Prof. Fuad A. Ghaleb
School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia, Malaysia
[email protected]
Profile: Fuad A. Ghaleb Ph.D. is an assistant professor of cybersecurity at the School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia. Holding Ph.D. and Master’s degrees in computer science (information security) with the best postgraduate student award from University Teknologi Malaysia, Malaysia, and B.Sc degree in computer engineering from Sana’a Universiti, Yemen. Completed a two-year Postdoctoral Fellowship at the School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia. He is the author of 34 articles related to cybersecurity security and computer networks that are published in high ranked journals. Dr. Fuad A. Ghaleb has many international certifications including network security from SAINS Institute, machine learning from Harvard University, and Python for Data Science and AI from IBM. Serve as head of computer engineering at Sana’a Community College for 5 years and lecturer of computer engineering and networking topics for 8 years. He serves as solutions manager of Telecommunication Value-Added Service at Teleinnovation Company in Yemen for 5 years. 4 years of working experience as a Senior Engineer of web development at Yemen Engineering Systems.
AI and Robotics
Abstract: Artificial intelligence describes the work processes of machines that would require intelligence if performed by humans. The term ‘artificial intelligence’ thus means ‘investigating intelligent problem-solving behavior and creating intelligent computer systems. While, a robot is a programmable mechanical device that can perform tasks and interact with its environment, without the aid of human interaction. Artificially intelligent robots are the bridge between robotics and AI. These are robots which are controlled by AI programs.
Presenter
Dr. Goran Abdulrahman Mohammed
Lecturer, Manufacturing Engineering Department, Faculty of Engineering, Koya University, Iraq
[email protected]
Profile: Goran Abdulrahman received his Ph.D. in 2018 from the University of Hull, UK. Also, his M.Sc., and B.Sc. in 2003 and 2000 respectively from the University of Technology (Baghdad). From 2003-2006, he joined the Control and System Engineering Dept., the University of Technology as an assistant lecturer. From 2006-present, he is working as a lecturer at the University of Koya, Faculty of Engineering. The main research interests include Biomechanics (Modelling and Analysis of Human Musculoskeletal System), and Control Systems