Cognitive Computing Using Green Technologies
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Home > Computing and Information Technology > Computer science > Artificial intelligence > Cognitive Computing Using Green Technologies: Modeling Techniques and Applications(Green Engineering and Technology)
Cognitive Computing Using Green Technologies: Modeling Techniques and Applications(Green Engineering and Technology)

Cognitive Computing Using Green Technologies: Modeling Techniques and Applications(Green Engineering and Technology)


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About the Book

Cognitive Computing is a new topic which aims to simulate human thought processes using computers that self-learn through data mining, pattern recognition, and natural language processing. This book focuses on the applications of Cognitive Computing in areas like Robotics, Blockchain, Deep Learning, and Wireless Technologies. This book covers the basics of Green Computing, discusses Cognitive Science methodologies in Robotics, Computer Science, Wireless Networks, and Deep Learning. It goes on to present empirical data and research techniques, modelling techniques and offers a data-driven approach to decision making and problem solving. This book is written for researchers, academicians, undergraduate and graduate students, and industry persons who are working on current applications of Cognitive Computing.

Table of Contents:
Part I: Green Computing Basics. 1. Use of Green Computing. 2. Design of Green Computing. Part II: Cognitive Science and Blockchain Base Distributed Network. 3. Cognitive Wireless Network. 4. Parallel and Distributed Computing in Cognitive Science. 5. Cognitive Analytics After Big Data Analytics and Machine Learning. Part III: Deep learning based Cognitive Robotics and Security. 6. Cognitive Science Based Business Analytics. 7. Security and Privacy for Internet of Things (IoT). 8. Shaping the Wireless Network as Cognitive Robotics. Part IV: Blockchain and Cryptocurrencies. 9. Blockchain and Decentralized Applications. 10. Blockchain in IoT and Edge Computing. Part V: Machine learning Applications. 11. Intelligent Robots with Biometic Neural Learning. 12. Deep Reasoning by Cognitive Robots and Wireless Networks.

About the Author :
Dr. Asis Kumar Tripathy received his Ph.D. in Computer Science and Engineering from National Institute of Technology, Rourkela, India and his M.Tech in Computer Science and Engineering from International Institute of Information Technology, Bhubaneswar, India. Currently, he is working as an Associate Professor in the School of Information Technology and Engineering, VIT Vellore, India. He has authored more than 10 national and international research papers to his credit. He is acting as a reviewer for some prestigious journals like Computers and Electrical Engineering (Elsevier), IET Networks, Wireless Personal Communications (Springer), Health and Technology (Springer), and International Journal of Biometrics (Inderscience). He is associated with many professional bodies OITS, IACSIT, CSTA, and IAENG. His current research interests include Wireless Sensor Networks, IoT and Computational Intelligence. Dr. Chiranji Lal Chowdhary. He have published quality papers/chapters on Deep Learning, Block Chain and Cognitive Computing, and has published books with IGI, AAP and CRC Press. He is also the editor of special issue Journals on these topics. Dr. Mahasweta Sarkar is an Associate Professor in the Department of Electrical and Computer Engineering at San Diego State University (SDSU), California, USA. Dr. Sarkar received her Ph.D in Computer Engineering from University of California at San Diego (UCSD) in 2005. Her research interest lies in the area of wireless data networks. Her work addresses issues like scheduling, routing, optimal resource allocation, power management in wireless networks like WLANs, WMANs, Sensor Networks, Ad Hoc Networks and wireless health. She has over 70 published research articles in technical journals, conference proceedings and book chapters. She is the Director of the Wireless Networks Research Group at SDSU where she leads a team of Ph.D and Masters students along with Post-doctoral Fellows and visiting faculty and PhD students from India, China, Denmark, Iran nad Korea. She is the recipient of the President’s Leadership award at SDSU in 2010 for her excellence in research and the Outstanding Faculty Award in 2014 for her excellence in teaching. Dr. Sanjaya Kumar Panda is working as an Assistant Professor and Head of the Department, CSE at IIITDM Kurnool, Andhra Pradesh, India. He worked as an Assistant Professor in the Department of IT at VSSUT, Burla, Odisha, India. He received Ph. D. degree from IIT (ISM) Dhanbad, Jharkhand, India, M. Tech. degree from NIT, Rourkela, Odisha, India and B. Tech. degree from VSSUT, Burla, Odisha, India in CSE. He received two silver medal awards for best graduate and best post-graduate in CSE. He also received Institution award, IEEE brand ambassador, SGSITS national award for the best research work by young teachers of engineering college for the year 2017, faculty with maximum publishing in CSI publications award, young IT professional award (2017 and 2016), young scientist award, CSI paper presenter award at international conference and CSI distinguished speaker award. He has published more than 60 papers in reputed journals and conferences. He is a member of IEEE, an associate member of IEI, Life member of ISTE, Life member of CSI, IAENG, IACSIT, UACEE, ACEEE and SDIWC. His current research interests include recommender system, cloud computing, big data analytics, grid computing, fault tolerance and load balancing.


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Product Details
  • ISBN-13: 9780367487966
  • Publisher: Taylor & Francis Ltd
  • Publisher Imprint: CRC Press
  • Height: 234 mm
  • No of Pages: 280
  • Sub Title: Modeling Techniques and Applications
  • Width: 156 mm
  • ISBN-10: 0367487969
  • Publisher Date: 27 Apr 2021
  • Binding: Hardback
  • Language: English
  • Series Title: Green Engineering and Technology
  • Weight: 640 gr


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