The book is a collection of best selected research papers presented at International Conference on Trends in Sustainable Computing and Machine Intelligence (ICTSM 2023) organized by Stamford International University, Bangkok, Thailand, during October 5-6, 2023. The book includes original research by researchers working in the field of machine learning. The book covers important topics like decision support systems, neural networks and applications, machine learning, natural language processing, automated problem solving, AI and evolutionary algorithms, intelligent information systems, computational intelligence, computer vision and image processing, cognitive and biologically inspired vision, soft computing and applications, hybrid intelligent systems, distributed computing, pattern recognition and analysis, ubiquitous and high-performance computing, security, trust and privacy, big data for sustainable computing, and energy-aware machine learning.
Reihe
Auflage
Sprache
Verlagsort
Zielgruppe
Illustrationen
196
51 s/w Abbildungen, 196 farbige Abbildungen
XIII, 495 p. 247 illus., 196 illus. in color.
Maße
Höhe: 241 mm
Breite: 160 mm
Dicke: 32 mm
Gewicht
ISBN-13
978-981-99-9435-9 (9789819994359)
DOI
10.1007/978-981-99-9436-6
Schweitzer Klassifikation
Dr. Surekha Lanka holds a Doctoral degree in Computer Science with a specialization of Artificial Intelligence from University of Swahili, Panama and a Master's degree of Computer Science from Andhra University, India, Master of Technology of computer science and engineering from Nagarjuna University , India, She also has done Master courses in Wireless communication from University of Athens, Greece. She has more than 13 years' experience in teaching in various countries Thailand, Saudi Arabia, India, Bahrain and also worked as a Research Assistant at the International Institute of Research and Management in India. Currently, she is pursuing her second PhD in the Education Administration and Leadership at Stamford University, Thailand.
Antonio Sarasa Cabezuelo has a Ph.D. in Computer Science from the Complutense University of Madrid. In 1999, he joined the UCM as Professor, where he has been Assistant Professor, Associate Professor at Full time, Collaborating Professor and since July 2013 he is Contracted Doctor professor. From the point of view of research, he has focused mainly on e-learning issues, standardization, digital heritage, and software development using techniques inspired by the design and implementation of computer languages. He is Member of the official Research Group of the UCM in Engineering of Software Languages and Applications (ILSA). He has participated as Researcher in 9 projects of the national plans, and in 10 projects of Educational Innovation, in 5 of them as their Director. The results of his research have been published in more than 70 articles in journals, lectures, and book chapters.
Alexandru Tugui is Full Professor at the Department of Accounting, Business Informatics and Statistics at Alexandru Ioan Cuza University of Iasi (Romania). Currently, his research fields concern the limits of artificial intelligence, societal transformations, smart economy, calm technology, technological singularity, and research methods. His research appeared in Big Data and Cognitive Computing, International Journal of Computers Communications Control, Sustainability, RemoteSensing, Transformations in Business and Economics, Carpathian Journal of Mathematics, Futurist, Encyclopedia of Information Science and Technology, Encyclopedia of Multimedia Technology and Networking. He is Ph.D. Adviser in business informatics and a futurologist in society and technology.
Design of a Boosting-based Similarity Measure for Evaluating Gene Expression using Learning Approaches.- Leveraging Linear Programming for Identification of Peripheral Blood Smear Malarial Parasitic Microscopic Images.- The AI's Ethical Limitations from the Societal Perspective. An AI Algorithms' Limitation?.- Enhancement of Physical Layer Security for Relay Aided Multi-Hop Communication using Deep Transfer Learning Technique.- Marine Vessel Trajectory Forecasting using Long-Short-Term Memory Neural Networks Optimized via Modified Metaheuristic Algorithm.- Application of Artificial Intelligence in Virtual Reality.- An Extension Application of 1D Wavelet Denoising Method for Image Denoising.- Improving Navigation Safety by Utilizing Statistical Method of Target Detection on the Background of Atmospheric Precipitation.- Effects of Exogenous Factors and Bayesian-Bandit Hyperparameter Optimization in Traffic Forecast Analysis.- Development of Autoencoder and Variational Autoencoder for Image Recognition using Convolutional Neural Network.- A Semantic Web based Prototype Exercise - Video Game for Children with Anxiety and Juvenile Myoclonic Epilepsy and its Usability Assessment.
