Intelligent Systems

Proceedings of ICMIB 2021
1. Auflage 2022
ISBN: 978-981-1909-00-9
Verlag: Springer Nature Singapore

Buch, Englisch, Band 431, 689 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 1077 g

Reihe: Lecture Notes in Networks and Systems

This book features best selected research papers presented at the International Conference on Machine Learning, Internet of Things, and Big Data (ICMIB 2021) held at Indira Gandhi Institute of Technology, Sarang, India, during December 2021. It comprises high-quality research work by academicians and industrial experts in the field of machine learning, mobile computing, natural language processing, fuzzy computing, green computing, human–computer interaction, information retrieval, intelligent control, data mining and knowledge discovery, evolutionary computing, IoT and applications in smart environments, smart health, smart city, wireless networks, big data, cloud computing, business intelligence, Internet security, pattern recognition, predictive analytics applications in healthcare, sensor networks and social sensing, and statistical analysis of search techniques.

Zielgruppe

Research

Autoren/Hrsg.

Udgata, Siba K.

Gao, Xiao-Zhi

Sethi, Srinivas

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Technische Wissenschaften Energietechnik | Elektrotechnik Elektrotechnik
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Big Data
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Ambient Intelligence, RFID, Internet der Dinge
• Mathematik | Informatik EDV | Informatik Angewandte Informatik

Inhaltsverzeichnis

GKEAE-Group Key Exchange and Authentication with ECC in Internet of Things.- PIDA Regulator For Frequency Limitation of Conventional Power Systems.- Synchronization and its use in Communication Network with Frequency Control.- A Comparative Analysis of Weekly Sales Forecasting using Regression Techniques.- Complex Network Visualization using Javascript: A Review.- A Novel Optimized Revenue Scheme in Finite Capacity SLA Aware Service Model in Fog Computing Environment.- Analysis of COVID-19 Data Through Machine Learning Techniques.- Ubiquitous Healthcare System using Recent ICT.- A Parallel Approach to Partition Based Frequent Pattern Mining Algorithm.- A Novel Task Offloading and Resource Allocation Scheme for Mist Assisted Cloud Computing Environment.- Analysis of Performance Characteristics of Social Wireless Sensor Networks.- Finite Element Analysis of an Optimised Sandwiched Spur Gear Set.- Predicting Missing Links in Gene Regulatory Networks using Network Embeddings: A QualitativeAssessment of Selective Embedding Techniques.- Prediction of Heart Diseases Using Soft Computing Technique.- An Architectural Framework to Manage Heterogeneous Emergencies.- Improving Navigational Parameters During Robot Motion Planning using SOMA Technique.- Review on Automated Detection of Covid-19 from X-Ray Images using Machine Learning.- Design and Analysis of a Biconcave DRA by using Machine Learning Algorithms for 5G Application.- An Approach for The Estimation of Rotor Position of PV Fed Switched Reluctance Motor Using ANFIS.

Über Autor(innen)

Prof. Siba Kumar Udgata is Professor in Computer and Information Sciences at University of Hyderabad, India. He has a Ph.D. in Computer Science in the area of mobile computing and wireless communications and also worked as United Nations Fellow and worked in the UNU/IIST, Macau. His research focus is on wireless communication, mobile computing, intelligent sensors, sensor network algorithms, Internet of Things, and applications. He was Volume Editor for several Springer LNAI, AISC International Conference proceedings, and also Associate Editor and Editorial Board Member of IOS Press KES Journal and Elsevier AKCE International Journal of Graphs and Combinatorics. Prof. Udgata has published more than 100 research papers in reputed international journals and conference proceedings. He has worked as Principal Investigator in many Government of India funded research projects mainly for the development of wireless sensor network applications, network security-related applications, and application of swarm intelligence techniques in the cognitive radio network domain.

Dr. Srinivas Sethi is Professor and has been actively involved in teaching and research in Computer Science since 1997. He did his Ph. D., in the area of Mobile Ad hoc Network, and is also continuing his work in wireless communication, sensor network, cognitive radio network, IOT, BCI, and cloud computing. He was Volume Editor for Springer LNNS, International Conference proceedings, Board for different journal and Program Committee Member for different international conferences/ workshop. Now he is working as Faculty in the Department of Computer Science Engineering and Application at Indira Gandhi Institute of Technology Sarang, India, and has published more than 80 research papers in International journals and conference proceedings. He completed 7 research projects funded by different Government of India funding agencies such as DST, AICTE, NPIU, and DRDO.

Prof. Xiao-Zhi Gao is Full Professor at School of Computing, University of Eastern Finland, Finland. He heads the nature-inspired machine learning research group at UEF. His main research interests are bio-inspired computing, nature-inspired computing, machine learning, soft computing, data mining, and communication networks. He has published more than 400 papers in different international journals and conferences of repute. He has been associated with many international conference as Technical Program Co-chair, member and editorial board member also.