Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications (Intelligent Data-Centric Systems) - Softcover

Softcover

ISBN 10: 0128133147 ISBN 13: 9780128133149

Publisher: Academic Press, 2018

Synopsis

Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications covers timely topics, including the neural network (NN), particle swarm optimization (PSO), evolutionary algorithm (GA), fuzzy sets (FS) and rough sets (RS), etc. Furthermore, the book highlights recent research on representative techniques to elaborate how a data-centric system formed a powerful platform for the processing of cloud hosted multimedia big data and how it could be analyzed, processed and characterized by CI. The book also provides a view on how techniques in CI can offer solutions in modeling, relationship pattern recognition, clustering and other problems in bioengineering.

It is written for domain experts and developers who want to understand and explore the application of computational intelligence aspects (opportunities and challenges) for design and development of a data-centric system in the context of multimedia cloud, big data era and its related applications, such as smarter healthcare, homeland security, traffic control trading analysis and telecom, etc. Researchers and PhD students exploring the significance of data centric systems in the next paradigm of computing will find this book extremely useful.

About this title

About the Authors

Prof. Arun Kumar Sangaiah received his PhD from the School of Computer Science and Engineering, VIT University, Vellore, India. He is currently a Full Professor with National Yunlin University of Science and Technology, Taiwan. He is also a Professor at the School of Computing Science and Engineering, VIT University, Vellore, India. His areas of research interest include machine learning, Internet of Things, Sustainable Computing. He has published more than 300 research articles in refereed journals, 11 edited books, one patent (held and filed), as well as four projects funded by MOST-TAIWAN, one funded by Ministry of IT of India, and several international projects (CAS, Guangdong Research fund, Australian Research Council). Dr. Sangaiah has received many awards, Yushan Young Scholar, Clarivate Top 1% Highly Cited Researcher (2021,2022, 2023), Top 2% Scientist (Standord Report-2020,2021,2022, 2023), PIFI-CAS fellowship, Top-10 outstanding researcher, CSI significant Contributor etc. He is also serving as Editor-in-Chief and/or Associate Editor of various reputed ISI journals. Dr. Sangaiah is a visiting scientist (2018-2019) with Chinese Academy of Sciences (CAS), China and visiting researcher of Université Paris-Est (UPEC), France (2019-2020) and etc.

Prof. Zhiyong Zhang received his Master, Ph.D. degrees in Computer Science from Dalian University of Technology and Xidian University, respectively. He was a Post-Doctoral Research Fellow at Xi'an Jiaotong University, China. He is currently a full Henan Province Distinguished Professor and Dean with Department of Computer Science, College of Information Engineering, Henan University of Science & Technology. Prof. Zhang is a visiting professor of Computer Science Department, Iowa State University.
He is an ACM Senior Member, IEEE Senior Member, IEEE Systems, Man, Cybernetics Society Technical Committee on Soft Computing, World Federation on Soft Computing Young Researchers Committee, Membership for Digital Rights Management Technical Specialist Workgroup Attached to China National Audio, Video, Multimedia System and Device Standardization Technologies Committee. Prof. Zhang’s research interests include multimedia social networks and digital rights management, applied soft computing, trusted computing, as well as security risk management. He has published over 80 scientific papers and four books on the above research fields, and held 8 granted patents.

Michael Sheng is a full Professor and Head of Department of Computing at Macquarie University, Sydney, Australia. Before moving to Macquarie University, Michael spent 10 years at School of Computer Science, the University of Adelaide (UoA). Prof. Sheng has more than 400 publications as edited books and proceedings, refereed book chapters, and refereed technical papers in journals and conferences. He is ranked by Microsoft Academic as one of the Top Authors in Services Computing (ranked the 5th of All Time worldwide). He is the recipient of the AMiner Most Influential Scholar Award on IoT (2007-2017), ARC Future Fellowship (2014), Chris Wallace Award for Outstanding Research Contribution (2012), and Microsoft Research Fellowship (2003).

From the Back Cover

Arun Kumar Sangaiah

School of Computing Science and Engineering, VIT University, Vellore, Tamil Nadu, India

Michael Sheng

School of Computer Science, The University of Adelaide, Australia

Zhiyong Z. Zhang

Dean, Department of Computer Science, Henan University of Science & Technology, China

As an overwhelming volume of data is being generated rapidly from various sources (e.g., intelligent terminals, multimedia information, cloud services, energy system, bio-engineering and health informatics), the computational intelligence paradigms constitutes a promising role in handling the uncertainty, unpredictability (e.g., data volume, velocity and heterogeneity or variety) and real-world optimization problems. Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications proposes the broad overview of CI paradigms that covers: Neural Network (NN), Particle Swarm Optimization (PSO), Evolutionary Algorithm (GA), Fuzzy Set (FS), and Rough Sets (RS) and etc.

Furthermore, this book highlights the recent research on some representative techniques to elaborate how data centric system formed a powerful platform for processing of cloud hosted multimedia big data could be analyzed, processed and characterized by CI. The CI paradigms not limited to feature selection, optimization approaches for handling high dimensional data, deep learning architectures, hybrid classification and clustering methods in the context of big data infrastructure designs to support big data science centric systems.

Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications also provides a view at how techniques in CI can offer solutions in modelling, relationship pattern recognition, clustering, and other problems particular to the bio-engineering field.

It is written for domain experts and developers, who want to understand and explore the application of computational intelligence aspects (opportunities and challenges) for design and development of data centric system in the context of multi-media cloud, big data era and its related applications such as smarter health care, homeland security, traffic control, trading analysis and telecom etc. The book is well suited for researchers and PhD exploring the significance of data centric systems in the next paradigm of computing.

Edition details

• Publisher: Academic Press
• Publication date: 2018
• Language: English
• ISBN 10: 0128133147
• ISBN 13: 9780128133149
• Binding: Paperback
• Edition number: 1
• Number of pages: 362
• Editor: Sangaiah Arun Kumar