Applied Computational Technologies

Proceedings of ICCET 2022
1. Auflage 2022
ISBN: 978-981-19-2718-8
Verlag: Springer Nature Singapore

Buch, Englisch, Band 303, 765 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 1332 g

Reihe: Smart Innovation, Systems and Technologies

This book is a collection of best selected research papers presented at 7th International Conference on Computing in Engineering and Technology (ICCET 2022), organized by Dr. Babasaheb Ambedkar Technological University, Lonere, India, during February 12 – 13, 2022. Focusing on frontier topics and next-generation technologies, it presents original and innovative research from academics, scientists, students, and engineers alike. The theme of the conference is Applied Information Processing System.

Zielgruppe

Research

Autoren/Hrsg.

Iyer, Brijesh

Peng, Sheng-Lung

Crick, Tom

Fachgebiete

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

Inhaltsverzeichnis

Part 1: Applied Computations using Deep and Machine Learning.- Classification of Traffic Signs Using Deep Learning-based Approach for Smart Cities.- Sentimental analysis of twitter data on online learning during unlock phase of COVID-19.- Bonafide Satellite Landslide Image Detection Using Deep Learning.- Deep Learning Approach for Predicting the Price of Cryptocurrencies.- Deep Learning and Super-hybrid Textual Feature based Multi-category Thematic Classifier for Punjabi Poetry.- Attention based Deep Learning Techniques for Question Classification in Question Answering Systems.- Optimized Fuzzy Hypersphere Neural Network with Online Adaptation capability.- Built-Up Area Extraction on Multispectral Satellite Data using Simple CNN.- Framework of CNN Architecture for Fashion Image Classification.- A novel CNN Framework for Early-Stage Detection of Blindness in Diabetic Patients.- Design and Development of Loan Predictor Using Machine Learning.- An Analysis of document summarization for educational data classification using NLP with machine learning techniques.- Detection of Disease in Plants with Android Integration using Machine Learning.- Analysis of Post-flood Impacts on Sentinel-2 Data Using Non-Parametric Machine Learning Classifiers: A Case Study from Bihar Floods.- Performance Analysis of Quantitative Software Vulnerability Prioritization Techniques.- Accessibility and Performance Evaluation of Healthcare and E-Learning Sites in India: A Comparative Study Using TAW and GTMetrix.- Performance analysis of Cardiovascular diseases using Machine Learning.- A Deep Learning Paradigm for Computer Aided Diagnosis of Emphysema from Lung HRCT Images.- Deep learning Convolution Neural Network for Tomato Leaves Disease Detection by Inception.- Sarcasm Detection in Hindi-English Code-mixed Tweets using Machine Learning Algorithms.- Efficient Automated Disease Diagnosis Using Machine Learning Models.- Plant Disease Classification using Transfer Learning.- Performance Assessmentfor Heart-Disease Prediction using Machine Learning Algorithms.- Human Behavior Analysis: Applications and Machine Learning Algorithms.- Advancement of deep learning and its substantial impact on the diagnosis of COVID-19 cases.- Apple Leaf Disease Detection and Classification using CNN Models.- Part 2: Intelligent systems and Machine vision.- Textural and Statistical Feature Extraction from segmented Hard Exudates for Diabetic Retinopathy Classification.- Detection of Epileptic using Wavelet packetsub-bands from EEG Signals.- A New Paradigm for Healthcare System Using Emerging Technologies.- Brain Tumour Detection Using UNet based Semantic Segmentation Scheme.- Alzheimer Disease Prediction using Learning Algorithms.- Digital Learning in developing Asia in the COVID-19 pandemic: A Statistical Approach.- Real-Time Detection of Face Mask and Social Distancing.- Porn Image Forensics: Image Classification, Forgery Detection and Localization.- Parallel Image Processing for Liquid Level Detection.- Single Image Dehazing Techniques for Different Types of Hazy Images.- Predicting 3D Model of Images for Augmented Reality Applications.- Region of Interest using Viola-Jones Algorithm for Video Steganography.- Face Expression Recognition using SVM and KNN classifier with HOG features.- Computer Vision Analysis of BRIEF and ORB Feature Detection Algorithms.- The state of the art Text Summarization Techniques.- Ensemble Mechanism for Decision Support Information System for Water Source Evaluation and Management in Narava Basin, Visakhapatnam.- Part 3: Applied Information Processing Techniques.- Analysis of Feature Selection Methods for UKM-IDS20 Dataset.- An Intelligent Recommendation System using Market Segmentation.- Development and Implementation of Tweet Stream Summarization Technique for Pernicious Tweet Detection.- State of the art on Twitter Spam Detection.- VM Anti-Forensics: Detecting File Wiping usingFile System Journals.- SelectGoREATech: Selection of Goal-Oriented Requirements Elicitation and Analysis Techniques.- Securing Blood Distribution Systems UsingBlockchain.- Distributed Data Register Technology as the Main Component of Economic Decentralization.- Performance Analysis of Scalable Transactions in Distributed Data Store.- Cyber-attackPrevention based on Modified LVQ in SDN using Neural Networks.- An Optimized Cloud-Based Solution for Small-Scale Non-IT Business Firms: An Experimental Analysis.- Sentiment of Primary Features in Aspect Based Sentiment Analysis of Hindi Reviews.- Part 4: Cloud Computing and Wireless Sensor Networks.- Spatiotemporal based Power Control Scheme for D2D Communication in 5G IoT Networks with QoS Constraints.- Cloud Computing Based Workload Prediction Using Cluster Machine Learning Approach. Sleeping Node Scheduling Method Based Redundant Node Energy Reduction inWireless Sensor Networks.- A Hybrid RSS/ToA Based Situational Awareness Technique for Indoor Massive MIMO Wireless System.- A Perceptive Node Transposition and Network Reformation in Wireless Sensor Network.- Energy Efficient Routing Protocol for Multisink Wireless Sensor Networks.- Secure Data Aggregation Model for People Centric Sensing Networks.- A smart energy optimization and collision avoidance routing strategy for IoT systems in the WSN domain.- State of the art on Cloud-Information Flow Control.- Service Placement in Edge Computing with AI based Techniques: A Systematic Review.- Part 5: ICT in Education and Research.- Empathic Chatbot: Emotional Astuteness for Mental Health Well-being.- ICT in Education: A Comparative Analysis of Pre-Covid and Post-Covid Era.- Credit point based Voluntary work Analysis: An integrated model based on proper waste disposal, fitness contribution and social work index.- The State of the art Techniques in Recommendation Systems.- An Analysis of E-Commerce Identification Using Sentimental Analysis: A Survey.- Remote Employee Monitoring & Management.

Über Autor(innen)

Dr. Brijesh Iyer received his Ph.D. degree in Electronics and Telecommunication Engineering from Indian Institute of Technology, Roorkee, India, in 2015. He is Associate Professor in the University Department of E&TC Engineering at Dr. Babasaheb Ambedkar Technological University, Lonere, Maharashtra-India (A State Technological University). He is a recipient of INAE research fellowship in the field of Engineering. He had 02 patents to his credit and authored over 50 research publications in peer-reviewed reputed journals and conference proceedings. He had authored 05 five books on curricula and 07 edited books on cutting-edge technologies like sensors and healthcare technology. He has served as Program Committee Member for various International Conferences and Reviewer for various international journals. His research interests include RF front-end design for 5G and beyond, IoT and biomedical image/signal processing.

Dr. Tom Crick is Professor of Digital and Policy at Swansea University (UK), with his role split between the £32m Computational Foundry and the School of Education. Alongside his academic work in data science, intelligent systems, software sustainability and smart infrastructure (with 130+ publications and £7.4m of career research income), he has been heavily involved in science, innovation and digital policy in the UK over the past ten years, as well as national curriculum reform. Tom chaired the Welsh Government’s review of the ICT curriculum in 2013 and has recently led the development of the science and technology area in the new Curriculum for Wales, published in January 2020. Tom was also inaugural chair of the National Network for Excellence in Science and Technology (2017-2019), a £4m strategic investment by the Welsh Government; he is also Commissioner of the National Infrastructure Commission for Wales (2018-present) and was a member of the expert panel of the Welsh Government’s Review of Digital Innovation andthe Future of Work (2019). Tom is Editor-in-Chief of the Computer Journal, one of the longest-established journals (since 1958) serving all branches of the academic computer science community, published by Oxford University Press. As part of his wider work with professional bodies and learned societies, he is an elected Member-at-Large of ACM Council (2020-present), as well as Vice-Chair of ACM Europe Council (2017-present), having previously been Vice-President of BCS, the Chartered Institute for IT (2017-2020). He is Distinguished Speaker and Senior Member of the ACM and Chartered Fellow of the BCS and IET. Tom was appointed MBE in the 2017 Queen’s Birthday Honors for “services to computer science and the promotion of computer science education”; in 2020, he was made Fellow of the Learned Society of Wales, the national academy for science and the arts.

Dr. Sheng-Lung Peng is Doctor of Philosophy in Computer Science from National Tsing Hua University, Taiwan, 1999. He also secured Master of Science in Computer Science and information Engineering from National Chung Cheng University, Taiwan, 1992, and Bachelor of Science in Mathematics from National Tsing Hua University, Taiwan, 1988. At present, he is a full professor and the director of the Department of Creative Technologies and Product Design, at National Taipei University of Business, Taiwan. Further, he is Honorary Professor, Beijing Information Science and Technology University, China Visiting Professor, Ningxia Institute of Science and Technology, China and Adjunct Professor, Mandsaur University, India. He had authored several journal and conference papers of international repute. He had served as PC member and Chair of various international conferences of repute. His research interests are designing and analyzing algorithms for bioinformatics, combinatorics, data mining, and networks.