Proceedings of International Conference on Advanced Communications and Machine Intelligence

MICA 2023
2024
ISBN: 978-981-97-6221-7
Verlag: Springer Nature Singapore

Buch, Englisch, Band 405, 556 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 1118 g

Reihe: Smart Innovation, Systems and Technologies

This book presents high-quality, peer-reviewed papers from International Conference on Advanced Communications and Machine Intelligence (MICA 2023), hosted by National Institute of Technology Warangal, Telangana, India, during 30–31 October 2023. The book includes all areas of advanced communications and machine intelligence. The book is useful for academicians, scientists, researchers from industry, research scholars, and students working in these areas.

Zielgruppe

Research

Autoren/Hrsg.

Peng, Sheng-Lung

Sarkar, Joy Lal

Mondal, Ayan

Kagita, Venkateswara Rao

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik

Inhaltsverzeichnis

A Novel Approach for Prediction of Liver Disease Using Voting Algorithm Based on Machine Learning Models.- An Empirical Study on Security Methods for Federated Learning Environments and Their Various Applications.- SWIFT Image Registration with ORB Features.-MELP: Multi-Embedding based Link Prediction in Attributed Networks.- A Comprehensive Analysis: Exploring the scope of research on Person recognition from the Body shapes.- Facial Expression Recognition using Ensemble Learning Approach.- Text-Based Language Learning Application.- Identification of Misogynistic Memes Using Transformer Models.- A Hybrid Deep Learning Model for robust deep fake detection.- Hybrid Convolutional Neural Networks for MultiEmotion classification using GAMEEMO.- Machine Learning Based Analysis of Code Smells at Class Level and Method Level. Deep Convolutional Neural Networks for Automated  Road Damage Detection.- Application of Artificial Intelligence in Automatic Cephalometric Landmark Annotations - A Comprehensive Review.- Multi Criteria Decision Making for Hospital Management System Software Selection Using Intuitionistic Fuzzy-MOORA.- Recommender System using Community Detection and Probabilistic Matrix Factorization.- Recommender System using Local Community Detection and Non-Negative Matrix Factorization.- MCDM Problems in an Interval Number for Group Decision- Making.- Sentiment analysis for the football clubs using Twitter Data.- Fresh Fruit Detection Using Yolo and OpenCV.- An investigation of ensemble-based framework for stress detection using multimodal clues.- Enabling Digital Trust for Predictions Made By AI In Heart Disease Prediction.- Predicting Suicidal Ideation on Reddit: A Precise Machine Learning Classifier for Mental Health Support.- Hybrid Deep Neural Network for detection of Myocardial Infarction with Electrocardiogram Signals.- Single Image Super-Resolution Evaluated Using Objective Metrics.- Temporal Intelligence: Recognizing User Activities with Stacked LSTM Network.- Prospective Study of Models for Advanced Persistent Threat Detection: A review.- A Deep learning framework for Crowd Internet of Things(Crowd-IoT).- A conceptual framework for the monitoring of the vehicle using Blockchain Technology.- Circuit that Models Supercapacitor Module Discharge.- Analysis of Inheritance of Criminal Behaviour from the Parents using Genetic Algorithm.- Load Distribution Using Optimized number of Controllers in Software Defined Networks.- Group based Itinerary Recommendation Engine for the Tourist.- Point of Interest using IOT.- Communications using Fog Cloud Systems with Interrupted Network Connectivity in Healthcare Emergency.- A Scalable High Speed Priority Encoder Design.- A Perspective of Mango Pest Classification Using Wrapper-Based Feature Selection Algorithm.- Multi-Criteria Decision-Making Problems Based Anti-Virus Software Selection Using Intuitionistic Fuzzy VIKOR.- Real Time Object Detection Using YOLOv5.- HSO-based K-Means Segmentation for Identification of Disease and Deficiency in Paddy Plant.- Improving Facial Emotion Recognition Through Ensemble Classification Strategies.- Prediction of Traffic Signs avoiding adversarial effects using Convolutional Neural Networks.- Crowd Sourcing Based Online Blood Bank System.- Active Directory and its Security Testing.- mLSTM: A Novel Modified Long Short Term Memory Networks For Melody Synthesis Melody Generation.- Time-slot based POI recommendations using user’s current location.

Über Autor(innen)

Dr. Sheng-Lung Peng is a professor at the Department of Creative Technologies and Product Design and the dean of the College of Innovative Design and Management at National Taipei University of Business in Taiwan. He received his Ph.D. degree from the Computer Science Department of National Tsing Hua University in Taiwan. He is an honorary professor at Beijing Information Science and Technology University and a visiting professor at Ningxia Institute of Science and Technology in China. He is also an adjunct professor at National Dong Hwa University in Taiwan and Mandsaur University and Kazi Nazrul University in India. Dr. Peng has edited several special issues in journals, such as Frontiers in Public Health, Journal of Internet Technology, IEEE Internet of Things Magazine, Computers and Electrical Engineering, Sensors, and so on. His research interests are in the design and analysis of algorithms in the fields of bioinformatics, combinatorics, data mining, and networking.

Dr. Ayan Mondal is an assistant professor in the Department of Computer Science and Engineering at the Indian Institute of Technology (IIT) Indore, India. Prior to this, he worked as a research engineer at Univ Rennes, Inria, CNRS, IRISA, France. He earned his Doctor of Philosophy (Ph.D.) from the Department of Computer Science and Engineering, IIT Kharagpur, India, in 2020. He was a visiting researcher at Inria, Rennes, France, in 2019. He completed his Master of Science (by Research) (M.S.) degree from the Indian Institute of Technology Kharagpur, India, in 2015. He received his Bachelor of Technology (B.Tech.) degree in Electronics and Communication Engineering from West Bengal University of Technology, India, in 2012. Dr. Venkateswara Rao Kagita is an assistant professor at NIT Warangal in the Department of Computer Science and Engineering. He has obtained Ph.D. from the University of Hyderabad. His research interests are data mining and machine learning, with a specific focus on machine learning techniques for recommender systems. His research works have been published in various reputed journals and conference proceedings such as Pattern Recognition, Pattern Recognition Letters, Information Sciences, Expert Systems with Applications, Journal of Approximate Reasoning, AAI, PRICAI. He has also delivered various guest lectures in several international and national workshops at IIT Hyderabad, Central University of Rajasthan, etc.

Dr. Joy Lal Sarkar is an associate professor in the Department of Computer Science and Engineering, Techno College of Engineering, Agartala, Tripura, India. He received M.Tech. in Computer Science and Engineering from Biju Patnaik University of Technology, Odisha, India, and a Doctor of Philosophy (Ph.D.) in Computer Science and Engineering from Tripura University (A Central University), Tripura, India. His research interests include software-defined networks, the Internet of Things, recommendation systems, artificial intelligence, and health informatics. He has published more than 60 research papers in different refereed international journals, conferences, and book chapters. Dr. Sarkar has been awarded the best paper award by several renowned international conferences. He was awarded the best reviewer by the Digital Communication Network, Elsevier.