Computational Intelligence and Sustainable Systems (eBook, PDF)

Intelligence and Sustainable Computing
Redaktion: Anandakumar, H.; Onn, Chow Chee; Arulmurugan, R.

• Format: PDF

Produktbeschreibung

This book features research related to computational intelligence and energy and thermal aware management of computing resources. The authors publish original and timely research in current areas of power, energy, temperature, and environmental engineering as and advances in computational intelligence that are benefiting the fields. Topics include signal processing architectures, algorithms, and applications; biomedical informatics and computation; artificial intelligence and machine learning; green technologies in information; and more. The book includes contributions from a wide range of researchers, academicians, and industry professionals. The book is made up both of extended papers presented at the International Conference on Intelligent Computing and Sustainable System (ICICSS 2018), September 20-21, 2018, and other accepted papers on R&D and original research work related to the practice and theory of technologies to enable and support Intelligent Computing applications.

• Presents the most recent challenges and developments in computational intelligence for sustainable systems and their best practices for application;
• Includes high quality research contributions from a wide range of scholars, researchers, academicians and professionals;
• Features expanded papers from the International Conference on Intelligent Computing and Sustainable System (ICICSS 2018), September 20-21, 2018.

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Produktdetails

• Verlag: Springer Nature Switzerland
• Seitenzahl: 304
• Erscheinungstermin: 14. Dezember 2018
• Englisch
• ISBN-13: 9783030026745
• Artikelnr.: 54760766

Autorenporträt

Anandakumar Haldorai,  Professor(Associate) and Research Head in Department of Computer Science and Engineering, Sri Eshwar College of Engineering, Coimbatore, Tamilnadu, India He has received his Master's in Software Engineering from PSG College of Technology, Coimbatore. PhD in Information and Communication Engineering from PSG College of Technology under, Anna University, Chennai. His research areas include Cognitive Radio Networks, Mobile Communications and Networking Protocols. He has authored more than 45 research papers in reputed International Journals and IEEE, Springer Conferences. He has authored 5 book and many book chapters with reputed publishers such as Springer and IGI. He is served as a reviewer for IEEE, IET, Springer, Inderscience and Elsevier journals. He is also the guest editor of many journals with Wiley, Springer, Elsevier, Inderscience, etc. He has been the General chair, Session Chair, and Panelist in several conferences. He is senior member of IEEE, MIET, MACM and EAI research group. Arulmurugan Ramu is a Professor in Bannari Amman Institute of Technology, Sathyamangalam, Erode, TamilNadu since 2012. His research focuses on the automatic interpretation of images and related problems in machine learning and optimization. His main research interest is in vision, particularly high-level visual recognition in computer vision. Some of the most recent work in his lab relates to fundamental technological problems related to large-scale data, machine learning and artificial intelligence. He has studied the interaction of attention and natural scene and object recognition. He is author of more than fifteen papers in major computer vision and machine learning conferences and journals. From 2011 to 2015 he was researcher fellow at the Anna University. He is the recipient of the PhD degree in Information and Communication Engineering from the Anna University, Chennai in 2015, M.Tech in Information Technology Anna University of Technology in 2009 respectively and of the B.Tech degree in Information Technology by the Aruani Engineering College in 2007.                        Chee-Onn Chow received his Bachelor of Engineering (Hons) and Master of Engineering Science degrees from University of Malaya, Malaysia in 1999 and 2001, respectively. He received his Doctorate of Engineering from the Tokai University, Japan in 2008. He joined the Department of Electrical Engineering as tutor in 1999, and subsequently been offered a lecturer position in 2001. He is currently an Associate Professor in the same department since 2015. His research interests include various issues related to wireless communications. He is a Chartered Engineer (IET, UK), a Professor Engineer (BEM, Malaysia) and a Senior Members of IEEE.

Inhaltsangabe

Chapter 1. Performance Analysis of Deep Neural Network and Stacked Auto encoder for Image Classification.- Chapter 2. Soft Computing based Void Recovery Protocol for Mobile Wireless Sensor Networks.- Chapter 3. Latest Research Trends And Challenges of Computational Intelligence Using Artificial Intelligence And Augmented Reality.- Chapter 4. Efficient Evolutionary Techniques for Wireless Body Area using Cognitive Radio Networks.- Chapter 5. Artificial Intelligence and Machine Learning for Large-Scale Data.- Chapter 6. Impact of Green Practices on Pakistani Manufacturing Firms' Performance: A Path Analysis Using Structural Equation Modelling.- Chapter 7. Cluster Based Health Monitoring Scheme in Wireless Sensor Networks.- Chapter 8. Design and Implementation of Area and Delay Efficient FXLMS Filter for active Noise Cancellation.- Chapter 9. Aspect based Text Summarization using Map Reduce Optimization.- Chapter 10. A Hill Climbing Approach for Residues Mapping in Protein Structures Alignment.- Chapter 11. Hardcopy Text Recognition and Vocalization for Visually Impaired and Illiterates in Bilingual Language.- Chapter 12. Investigation of Non-Natural Information from Remote Sensing Images: A Case Study Approach.- Chapter 13. Minimization of SCA Attacks by CMOS Based Blurring Gates.- Chapter 14. Linux based Elevator Control System.- Chapter 15. SOS Emergency Ad-Hoc Wireless Network.- Chapter 16. Promoting Greenness with IoT based Plant Growth System.- Chapter 17. Study on the Supply Chain Integration: In the Perspective of Pakistan.- Chapter 18. Multilevel Coding For Multiple Input Multiple Output System.