This book includes selected peer-reviewed papers presented at the International Conference on Trends in Electronics and Health Informatics (TEHI 2023), held at Institute of Information Technology, Jahangirnagar University, Dhaka, Bangladesh, during December 26-27, 2023. The book is broadly divided into five sections-artificial intelligence and soft computing, healthcare informatics, Internet of things and data analytics, electronics, and communications.
This book includes selected peer-reviewed papers presented at the International Conference on Trends in Electronics and Health Informatics (TEHI 2023), held at Institute of Information Technology, Jahangirnagar University, Dhaka, Bangladesh, during December 26-27, 2023. The book is broadly divided into five sections-artificial intelligence and soft computing, healthcare informatics, Internet of things and data analytics, electronics, and communications.
Mufti Mahmud received his Ph.D. degree in information engineering from the University of Padova, Italy, in 2011. He is currently serving as an associate professor of Cognitive Computation at Nottingham Trent University (NTU), UK. He has been listed among the top 2% cited scientists worldwide in computer science since 2020 and was the recipient of the NTU VC outstanding research award 2021 and the Marie-Curie postdoctoral fellowship. He is the coordinator of the Computer Science and Informatics research excellence framework unit of assessment at NTU and the deputy group leader of the Cognitive Computing & Brain Informatics and the Interactive Systems research groups. With over 18 years of experience in the industry and academia in India, Bangladesh, Italy, Belgium, and the UK, he is an expert in computational intelligence, applied data analysis, and big data technologies with a keen focus on healthcare applications. M. Shamim Kaiser is currently working as Professor at the Institute of Information Technology of Jahangirnagar University, Savar, Dhaka-1342, Bangladesh. He received his Bachelor's and Master's degrees in Applied Physics Electronics and Communication Engineering from the University of Dhaka, Bangladesh in 2002 and 2004, respectively, and the Ph. D. degree in Telecommunication Engineering from the Asian Institute of Technology, Thailand, in 2010. His current research interests include Data Analytics, Machine Learning, Wireless Network & Signal processing, Cognitive Radio Network, Big data and Cyber Security, Renewable Energy. He has authored more than 100 papers in different peer-reviewed journals and conferences. He is Associate Editor of the IEEE Access Journal, Guest Editor of Brain Informatics Journal, and Cognitive Computation Journal. He organized various international conferences such as ICEEICT 2015-2018, IEEE HTC 2017, IEEE ICREST 2018, and BI2020. Anirban Bandyopadhyay is Senior Scientist in the National Institute for Materials Science (NIMS), Tsukuba, Japan. He received Ph.D. from Indian Association for the Cultivation of Science (IACS), Kolkata, 2005, December, on supramolecular electronics. He was ICYS Research Fellow NIMS (2005-2007), Japan, and Permanent Scientist in NIMS (2007-now), Japan. He has 10 patents on building artificial organic brain, big data, molecular bot, cancer & alzheimer drug, fourth circuit element, etc. In 2013-2014, he was Visiting Scientist in MIT, USA, on biorhythms. Kanad Ray (Senior Member, IEEE) received the M.Sc. degree in physics from Calcutta University and the Ph.D. degree in physics from Jadavpur University, West Bengal, India. He has been Professor of Physics and Electronics and Communication and is presently working as Head of the Department of Physics, Amity School of Applied Sciences, Amity University Rajasthan (AUR), Jaipur, India. His current research areas of interest include cognition, communication, electromagnetic field theory, antenna and wave propagation, microwave, computational biology, and applied physics. He has been serving as Editor for various Springer book series. He has been Visiting Professor to UTM & UTeM, Malyasia, and Visiting Scientist to NIMS, Japan. He has established MOU with UTeM Malaysia, NIMS Japan, and University of Montreal, Canada. He has visited several countries such as Netherlands, Turkey, China, Czechoslovakia, Russia, Portugal, Finland, Belgium, South Africa, Japan, Singapore, Thailand, Malaysia, etc., for various academic missions. Shamim Al Mamun is a highly accomplished computer scientist and engineer with a wealth of experience and knowledge in the fields of autonomous systems, artificial intelligence, and software engineering. He received his B.Sc. (Hons.) and M.Sc. (Engg.) degrees in Computer Science and Engineering from Jahangirnagar University (JU) and Bangladesh University of Engineering and Technology (BUET), respectively, and went on to earn his Ph.D. degree from the Graduate School of Science and Engineering at Saitama University in Japan. He is currently working as Professor at the Institute of Information Technology of Jahangirnagar University, Savar, Dhaka-1342, Bangladesh. Throughout his career, he has made significant contributions to the advancement of computer science through his research and publication of more than 60 peer-reviewed articles and papers in international journals and conferences.
Inhaltsangabe
A Deep Learning-based Framework for Detecting Depression from Electroencephalogram Signals.- A Review on Emotion Detection From Text: Opportunities and Challenges.- An Effective Combination of Deep and Machine Learning Models for Monkeypox Detection from dermatographic Image.- A Time-efficient and Effective Image Contrast Enhancement Technique using Fuzzification and Defuzzification.- An Ensemble Machine Learning-based Approach for Detecting Malicious Websites using URL Features.- The Multi-Class Paradigm: How Transformers are Reshaping Language Analysis in NLP.- Deep learning Precision Farming: Identification of Bangladeshi-Grown Fruits Using Transfer Learning-Based Detection.- Deep Learning Solutions for Detecting Bangla Fake News: A CNN-Based Approach.- A Two Stage Stacking Ensemble Learning for Employee Attrition Prediction.- Ensemble Learning Approaches for Alzheimers Disease Classification in Brain Imaging Data.- Pseudo-Knighted Cocktail Shaker Sort.
A Deep Learning-based Framework for Detecting Depression from Electroencephalogram Signals.- A Review on Emotion Detection From Text: Opportunities and Challenges.- An Effective Combination of Deep and Machine Learning Models for Monkeypox Detection from dermatographic Image.- A Time-efficient and Effective Image Contrast Enhancement Technique using Fuzzification and Defuzzification.- An Ensemble Machine Learning-based Approach for Detecting Malicious Websites using URL Features.- The Multi-Class Paradigm: How Transformers are Reshaping Language Analysis in NLP.- Deep learning Precision Farming: Identification of Bangladeshi-Grown Fruits Using Transfer Learning-Based Detection.- Deep Learning Solutions for Detecting Bangla Fake News: A CNN-Based Approach.- A Two Stage Stacking Ensemble Learning for Employee Attrition Prediction.- Ensemble Learning Approaches for Alzheimers Disease Classification in Brain Imaging Data.- Pseudo-Knighted Cocktail Shaker Sort.
A Deep Learning-based Framework for Detecting Depression from Electroencephalogram Signals.- A Review on Emotion Detection From Text: Opportunities and Challenges.- An Effective Combination of Deep and Machine Learning Models for Monkeypox Detection from dermatographic Image.- A Time-efficient and Effective Image Contrast Enhancement Technique using Fuzzification and Defuzzification.- An Ensemble Machine Learning-based Approach for Detecting Malicious Websites using URL Features.- The Multi-Class Paradigm: How Transformers are Reshaping Language Analysis in NLP.- Deep learning Precision Farming: Identification of Bangladeshi-Grown Fruits Using Transfer Learning-Based Detection.- Deep Learning Solutions for Detecting Bangla Fake News: A CNN-Based Approach.- A Two Stage Stacking Ensemble Learning for Employee Attrition Prediction.- Ensemble Learning Approaches for Alzheimers Disease Classification in Brain Imaging Data.- Pseudo-Knighted Cocktail Shaker Sort.
A Deep Learning-based Framework for Detecting Depression from Electroencephalogram Signals.- A Review on Emotion Detection From Text: Opportunities and Challenges.- An Effective Combination of Deep and Machine Learning Models for Monkeypox Detection from dermatographic Image.- A Time-efficient and Effective Image Contrast Enhancement Technique using Fuzzification and Defuzzification.- An Ensemble Machine Learning-based Approach for Detecting Malicious Websites using URL Features.- The Multi-Class Paradigm: How Transformers are Reshaping Language Analysis in NLP.- Deep learning Precision Farming: Identification of Bangladeshi-Grown Fruits Using Transfer Learning-Based Detection.- Deep Learning Solutions for Detecting Bangla Fake News: A CNN-Based Approach.- A Two Stage Stacking Ensemble Learning for Employee Attrition Prediction.- Ensemble Learning Approaches for Alzheimers Disease Classification in Brain Imaging Data.- Pseudo-Knighted Cocktail Shaker Sort.
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