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3rd EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing de Anandakumar Haldorai

3rd EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing: EAI/Springer Innovations in Communication and Computing

Editat de Anandakumar Haldorai, Arulmurugan Ramu, Sudha Mohanram, Joan Lu
en Limba Engleză Hardback – 20 dec 2021
This book features the proceedings of The EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing (BDCC 2020), which took place 18 – 19 December 2020. The papers feature detail on cognitive computing and its self-learning systems that use data mining, pattern recognition and natural language processing (NLP) to mirror the way the human brain works. This international conference focuses on technologies from knowledge representation techniques and natural language processing algorithms to dynamic learning approaches. Topics covered include Data Science for Cognitive Analysis, Real-Time Ubiquitous Data Science, Platform for Privacy Preserving Data Science, and Internet-Based Cognitive Platform.

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Specificații

ISBN-13: 9783030787493
ISBN-10: 3030787494
Pagini: 250
Ilustrații: XII, 250 p. 130 illus., 113 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.54 kg
Ediția:1st ed. 2022
Editura: Springer International Publishing
Colecția Springer
Seria EAI/Springer Innovations in Communication and Computing

Locul publicării:Cham, Switzerland

Cuprins

1 A Hybrid Algorithm for Document Clustering Using Optimized Kernel Matrix and Unsupervised Constraints.- 2 A Multi-Objective Optimal Trajectory Planning for Autonomous Vehicles using Dragonfly Algorithm.- 3 A Novel Coherent Architecture for Traffic Signal Management in Internet of Things.- 4 Color-to-Grayscale conversion for images with non-uniform chromatic distribution using Multiple Regression.- 5 Concurrent Spatial Color Information Processing for Video Based Vehicle Detection Applications.- 6 Efficient Routing Strategies For Energy Management in Wireless Sensor Network.- 7 Emperor Penguin Optimization Algorithm and M-Treebased multi-constraint Mul-ticast Ad hoc On demand Distance Vector Routing Protocol for MANETs.- 8 Fog Assisted Real-Time Coronary Heart Disease Risk Detection in IoT Based Healthcare System.- 9 Food Demand Forecast For Online Food Delivery Service Using CatBoost Model.- 10 GLCM Feature Based Texture image classification using Support vector Machine.- 11 Improved Rider Optimization Algorithm-based Link Aware Fault Detection (IROA-LAFD) scheme for securing Mobile Ad Hoc Networks (MANETs).- 12 Media Access Protocol for Wireless Sensor Network using Active Reception Scheme Based Energy Efficient Technique.- 13 Predictive Crime Analytics Using Linear Regression and K means.- 14 Reorganizing Virtual Machines as Docker Containers for Efficient Data Centers.- 15 Secured On Demand Adaptive Routing protocol for Data Transmission in IoT Environment.- 16 Service Measurement Index based Cloud Service Selection using Order Preference by Similarity to Ideal Solution based on Intuitionistic Fuzzy Values.- 17 Similarity analytics for semantic text using Natural Language Processing.- Author Index.

Notă biografică

Dr. Anandakumar Haldorai, Professor (Associate) and Research Head in Department of Computer Science and Engineering, Sri Eshwar College of Engineering, Coimbatore, Tamil Nadu, India. He has received his Master’s in Software Engineering and PhD in Information and Communication Engineering from PSG College of Technology under, Anna University, Chennai. His research areas include Big Data, Cognitive Radio Networks, Mobile Communications and Networking Protocols. He has authored more than 125 research papers in reputed International Journals and IEEE conferences. He has authored 11 books and many book chapters with reputed publishers such as Springer and IGI. He is Editor in Chief of KeAi – Elsevier IJIN and served as a reviewer for IEEE, IET, Springer, Inderscience and Elsevier journals. He is also the guest editor of many journals with Elsevier, Springer, Inderscience, etc. He has been the General Chair, Session Chair, and Panelist in several conferences. He is senior member ofIEEE, IET, ACM and Fellow member of EAI research group.
Dr. Arulmurugan Ramu, is a Professor, Presidency University, Bangalore, India. 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. He has authored more than 35 papers in major computer vision and machine learning conferences and journals. He is the recipient of Ph.D. degrees in Information and Communication Engineering from the Anna University at Chennai, M.Tech in Information Technology Anna University of Technology and B.Tech degree in Information Technology. He is guided many Ph.D. research scholar under the area of Image Processing using Machine Learning. He is an Associate Editor of Inderscience IJISC journal. He is awarded as Best Young Faculty Award 2018 and nominated for Best Young Researcher Award (Male) by International Academic and Research ExcellenceAwards (IARE-2019).
Dr. Sudha Mohanram, has graduated from Government College of Engineering, Salem and has obtained her Master’s in Engineering from Coimbatore Institute of Technology. She has completed her PhD in Electrical Engineering in Anna University Chennai in the year 2010. She started her teaching profession as a Lecturer in Government College of Technology, Coimbatore. She possesses 20 years of teaching experience. When she was about 13 years into teaching profession, her family founded Sri Eshwar College of Engineering in 2008. She has been playing the role of Secretary till 2011 and became the Principal of the institution in 2011. She has steered the institution to be one of the most sought after institutions in Coimbatore, within a short span of time through its laudable achievement in Academic excellence and Placement. She has published many papers in leading journals. She is a member of IEEE and EAI research group.
Dr. Joan Luis Professor in Informatics at the University of Huddersfield (UK). Her extensive research covers information access, retrieval and visualization, XML and other data technologies, data management systems, security issues, wireless, and Internet computing. She has been an invited speaker for various industrial-oriented events, guest speaker in UK higher education academy (HEA) on Mobile technology in classrooms, 2012, keynote speaker for international conferences (INFOCCOM13, in Portugal and The Scientific Conference 2014, in Kurdistan). She is a research grant reviewer for The Swiss National Science Foundation (SNSF), and an external adviser for a collaboration between Leeds Mat University, UK and Sakarya University in Turkey. She was principal investigator for three EU projects from 2008 to 2012. She published 5 academic research books and over 180 papers. Professor Lu has acted as the founder and a program chair for the International XML Technology workshop and XMLTech (USA) for 11years (2003-2011).

Textul de pe ultima copertă

This book features the proceedings of The EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing (BDCC 2020), which took place 18 – 19 December 2020. The papers feature detail on cognitive computing and its self-learning systems that use data mining, pattern recognition and natural language processing (NLP) to mirror the way the human brain works. This international conference focuses on technologies from knowledge representation techniques and natural language processing algorithms to dynamic learning approaches. Topics covered include Data Science for Cognitive Analysis, Real-Time Ubiquitous Data Science, Platform for Privacy Preserving Data Science, and Internet-Based Cognitive Platform.

Caracteristici

Contains proceedings from EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing (BDCC 2020), 18 – 19 December 2020 Features topics ranging from Data Science for Cognitive Analysis to Internet-Based Cognitive Platforms Relevant for researchers, professionals, academics, and students in Cognitive Computing