Proceedings of the 13th National Technical Seminar on Unmanned System Technology 2023—Volume 1

Dr. Zainah Md. Zain is a renowned academic with a distinguished career in control and robotics. She is currently affiliated with the Faculty of Electrical and Electronics Engineering Technology at Universiti Malaysia Pahang Al-Sultan Abdullah, Pahang, Malaysia, where she has accumulated over 20 years of experience in academia and research. Dr. Zain holds the position of Head of Programme for the Bachelor of Electrical Engineering Technology. Her research interests encompass Underactuated Systems, Nonlinear Control, and Underwater Robots. She is recognized as a registered professional technologist by the Malaysian Board of Technologists and is an active member of prestigious organizations such as the Society for Underwater Technology, The Institution of Engineering and Technology, and the Institute of Electrical and Electronics Engineers - Oceanic Engineering Society, among others. Dr. Zain's significant contributions to IEEE have been acknowledged with several grant awards, including the IEEE TryEngineering STEM grant, and she was honored as an IEEE STEM Champion in 2023. Additionally, she has served as a grant reviewer for IEEE EPIC grants. Dr. Zool Hilmi Ismail is an accomplished academic with a distinguished career in engineering and robotics. As an Associate Professor at Universiti Teknologi Malaysia, Kuala Lumpur, he has contributed significantly to the field. His research interests encompass Edge Computing, Model-Predictive Control, Path-Planning, and Task Allocation using Deep-Reinforcement Learning. He holds the title of a registered professional engineer under the Board of Engineers Malaysia and is an active member of prestigious organizations such as the Society for Underwater Technology, The Institution of Engineering and Technology, and the Institute of Electrical and Electronics Engineers - Oceanic Engineering Society, among others. His remarkable contributions have been recognized with several awards from International RoboCup Competitions in the Service Robot Category. In addition, he served as a committee member for International RoboCup@Home Education in 2017. Dr. Huiping Li is the Full Professor with the School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an. Dr Li has published one monograph and more than 90 journal articles and conference papers. He was awarded the National Science Fund for Excellent Young Scholars of China, and Shaanxi Provincial Science Fund for Outstanding Young Scholars. Dr. Li has won the first prize of Natural Science from the Chinese Association of Automation, and the best youth author paper from IFAC 2019 TA. Dr Li is the Chair of IEEE Xi’an IES Chapter and technical committee member of IEEE IES Cyber-physical systems. Dr Li is the General Co-Chair of 2023 IEEE ONCON, was the Technical Program Chair of IEEE ICPS 2021 and the Publicity Co-Chair of IEEE ISIE 2019. Dr Li was a Guest Technical Editor for aSpecial Section in IEEE/ASME Transactions on Mechatronics. He serves as the Associate Editor for IEEE Transactions on Industrial Electronics, IEEE Transactions on Industrial Informatics, and ASME Journal on Dynamic Systems, Measurement and Control. He is a Senior member of IEEE. Dr. Xianbo Xiang attained his B.E. and M.E. degrees in automatic control and marine engineering from the Huazhong University of Science and Technology (HUST), Wuhan, China, in 2000 and 2003, respectively. He further pursued his academic journey and earned his Ph.D. degree in robotics from the University of Montpellier 2, Montpellier, France, in 2011. Presently, he serves as a Professor at the School of Naval Architecture and Ocean Engineering, HUST. Notably, in 2006, he participated as an EU Erasmus Mundus Visiting Scholar in the SpaceMaster Project. Moreover, from 2008 to 2011, he contributed to the European Project FreeSubNet as an EC Marie Curie ESR Fellow with LIRMM/CNRS, France. His research endeavors primarily revolve around robotics and marine vehicle systems. Dr. Rama Rao Karri working in the Faculty of Engineering, Universiti Teknologi Brunei (UTB), Brunei Darussalam and has over 20 years of working experience in Academics, Industry, and Research. He has experience working in multidisciplinary fields and has expertise in various machine-learning techniques and process modelling. As of 6 Feb 2024, he has published 200+ research articles in reputed journals, book chapters, and conference proceedings. He is an editorial board member in 10 renowned journals and has peer-reviewed more than 470+ articles. Further, he handled 195 articles as an editor. He was listed in the top 2% of the world’s most influential scientists for the Years 2021, 2022 & 2023.

• Variant Histogram Equalization based Enhancement to Deep Transfer Learning for Automatic Detection of Photovoltaic Cell Defects in Electroluminescence Images.- Soft Robotic Conveyor Belt.- Auto-tuning of Frequency Sampling Filter Algorithm using Step Response Data Analysis.- Optimal Load Sharing Strategy in a Hybrid Power System Based on PV/Fuel Cell/ Battery.- Real-Time Vision-Based Halal Logo Verification System.- Genetic Algorithm for Mobile Robot Global Path Planning Application.- Empowering Rural Education: A Comprehensive Study on the Implementation and Cost Analysis of Standalone Photovoltaic Systems in Sarawak Schools.- Industrial Fans Health Analytics with Deep Learning.- Comparative Analysis of Wavelet and MFCC Features, and Machine Learning Techniques for the Robust Classification of Seismic Signals.- Cuckoo Search Algorithms for Maximum Power Point Intelligent Tracking of PV Array Under Partial Shading Conditions.- Automatic Plant Water Stress Phenotyping For Genotype Classification Using Lightweight CNN.- Deep or Shallow Networks: Coral Types Classification using Residual Network Models.- Strawberry Ripeness Classification Using Fuzzy Logic Approach.- Analysis Voltage and Frequency Control of Microgrid Systems with Load Demand Response.- A Novel Deep Learning Approach for MRI Segmentation of Brain Tumors.- Waterfall Alarm System for Headwater Phenomena.- Classification of Mango Species and Ripeness Using Feature Extraction with An Artificial Neural Network.