Proceedings of Third International Conference on Computing and Communication Networks

ICCCN 2023, Volume 1
Herausgegeben:Fortino, Giancarlo; Kumar, Akshi; Swaroop, Abhishek; Shukla, Pancham

• Broschiertes Buch

Produktbeschreibung

This book includes selected peer-reviewed papers presented at third International Conference on Computing and Communication Networks (ICCCN 2023), held at Manchester Metropolitan University, UK, during 17-18 November 2023. The book covers topics of network and computing technologies, artificial intelligence and machine learning, security and privacy, communication systems, cyber physical systems, data analytics, cyber security for industry 4.0, and smart and sustainable environmental systems.

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Produktdetails

• Lecture Notes in Networks and Systems 917
• Verlag: Springer / Springer Nature Singapore / Springer, Berlin
• Artikelnr. des Verlages: 978-981-97-0891-8
• 2024
• Seitenzahl: 820
• Erscheinungstermin: 21. Juli 2024
• Englisch
• Abmessung: 235mm x 155mm x 41mm
• Gewicht: 1367g
• ISBN-13: 9789819708918
• ISBN-10: 9819708915
• Artikelnr.: 69782173

Autorenporträt

  Giancarlo Fortino (SM'12) is Full Professor of Computer Engineering at the Dept. of Informatics, Modeling, Electronics, and Systems of the University of Calabria (Unical), Italy. He received a Ph.D. in Computer Engineering from Unical in 2000. He is also Distinguished Professor at Wuhan University of Technology and Huazhong Agricultural University (China), High-End Expert at HUST (China), Senior Research Fellow at the Italian ICAR-CNR Institute, CAS PIFI Visiting Scientist at SIAT-Shenzhen, and Distinguished Lecturer for IEEE Sensors Council. He is Web of Science Highly Cited Researcher 2020. His research interests include wearable computing systems, e-Health, Internet of Things, and agent-based computing. He is currently the scientific responsible of the Digital Health group of the Italian CINI National Laboratory at Unical. He is Author of 500+ papers in int'l journals, conferences, and books. Dr. Akshi Kumar is Senior Lecturer-Data Science and AI in the Department of Computing & Mathematics, Faculty of Science & Engineering, Manchester Metropolitan University, UK. She is Post-doc from Federal Institute of Education, Science and Technology of Ceará, Fortaleza, Brazil and a Ph.D. from Faculty of Technology, University of Delhi, India. She has worked as Associate Professor at the Netaji Subhas University of Technology (NSUT), New Delhi, India, and as Assistant Professor at the Delhi Technological University (DTU), New Delhi, India, and has a total teaching and research experience of 16 years. She has published more than 85 peer-reviewed journal papers including 50 SCIE publications, 65+ conference papers with 4 best paper awards and 2 patents with Indian Patent Office. She has successfully guided 7 doctorates, 33 Master thesis candidates. She has been serving as Associate Editor and Guest Editor in various high impact journals with reputed publishers. Prof. (Dr.) Abhishek Swaroop completed his B.Tech. (CSE) from GBP University of Agriculture & Technology, M.Tech. from Punjabi University Patiala, and Ph.D. from NIT Kurukshetra. He has 28 years of teaching and Industrial experience. He has served in reputed educational institutions such as Jaypee Institute of Information Technology, Noida, Sharda University Greater Noida and Galgotias University, Greater Noida. He is actively engaged in research. He has guided 12 M.Tech. Dissertations also. He has authored 3 books and 5 book chapters. His 10 papers are indexed in DBLP and 16 papers are SCI. He had been part of the organizing committee of three IEEE conferences (ICCCA-2015, ICCCA-2016, ICCCA-2017), one Springer conference (ICICC-2018) as Technical Program Chair. He is Member of various professional societies like CSI and ACM and editorial board of various reputed journals. Dr Pancham Shukla is Principal Teaching Fellow in the Faculty of Engineering at Imperial College London. He holds more than 25years of teaching and research experience at various Universities in UK and India. He holds Ph.D. in Electrical and Electronic Engineering from Imperial College London. He has supervised a broad range of projects and published papers in signal/image processing, electronic, and communications systems. He has organized conferences and has served as Technical Session Chair along with reviewing many international conference and journal papers. He received Vice Chancellor's award for outstanding contribution to Learning and Teaching as well as Student Union's award as an outstanding member of academic staff while working at London Metropolitan University.

Inhaltsangabe

Multiscale Feature Pyramid Network-enabled Deep Learning and IoT-based Pest Detection System Using Sound Analytics in Large Agricultural Field.- Detection of Wormhole attacks using DCNNBiLSTM model to secure the MANET.- Enhancing Security in Wireless Sensor Networks: A Broadcast/Multicast Authentication Framework with Identity-Based Signature Schemes.- TSFTO: a Two Stage Fuzzy based Tasks Orchestration Algorithm for Edge and Fog Computing Environments.- Tracking Climatic Variations through Smart IoTdrivenApproach:An Exploratory Analysis.- Design and Manufacturing of an Efficient Low-Cost Fire Alarm System Based on GSM Communications and IoT Technology.- A Comparative Analysis of Optimised Routing Protocols for High-Performance Mobile Ad-Hoc Networks.- Integrating Sandpiper Optimization Algorithm and Secure Aware Routing Protocol for Efficient Cluster Head Selection in Wireless Sensor Networks.- The Effects of Weather Conditions on Data Transmission in Free Space for Wireless Sensor Networks.- Using Wireless Sensor Network Performance and Optimizing in underground Mines with Virtual MIMO antenna.- A Novel Logistic Regression based Fire Detection Model using IoT in Underground Coal Mines.- An MQTT IoT Intrusion Detection System using Deep-Learning.- Multi-Objective Optimal Feature Selection for Cyber Security integrated with Deep Learning.- Application of Gradient Boosting Classifier based ComputationalIntelligence to detect Drug Addiction threat in society.- INSURANCE 4.0: SMART INSURANCE TECHNOLOGIES AND CHALLENGES AHEAD.- Review on Vision Transformer for Satellite Image Classification.- Primitive Roots and Euler Totient Function based Progressive Visual Cryptography.- An Approach for Fire Detection Using Image Processing.- A Review of Various Approaches for Authorship Identification in Digital Forensics.- The change weight of threat in network security communication based on analysis of multisource data.- Machine Learning Model for Traffic Prediction and Pattern Extraction in High Speed Optical Networks.- Improved Markov Decision Process in Wireless Sensor Network for Optimal Energy Consumption.- Design and Implementation of a Hybrid Deep learning Framework for Handwritten Text Recognition.- A LSTM based intelligent framework for Financial Stock Prediction.- Mispronunciation Detection Using Feature Learning.- Annotating social data with speaker/user engagement. Illustration on online hate characterization in French.- Heuristic Learning Models based Stochastic Regularization Technique for Reducing the Overfit of Training Data.- Convolution Neural Network Vs Transfer Learning in Image Classification.- Unveiling Consumer Segmentation: Harnessing K means Clustering using Elbow and Silhouette for Precise Targeting.- Multimodal Sentiment Analysis and Multimodal Emotion Analysis: A Review.- A Deep Dive into Brain Computer Interface.- Climatic Variables Assessment in a Smart SensoryEnabled Setting.- Towards Improved Clustering for Textual Data.- Self-Adaptive Learning Algorithm as a Tool for the Development and Strengthening of the dyslexic Student's Skills in the Study of Musical Composition.- Digital-Game-Based Language Learning: An Exploration of Attitudes among Teacher Aspirants in a Non-Metropolitan Area.- A Unified Approach for Identification and Analysis of the Sources of Uncertainty in Machine Learning Techniques.- Sentiment Analysis of Tweets associated with TurkeySyria Earthquakes 2023.- Ensemble Classification with Lazy Predict on Three Diabetes Datasets: A Comparative Study with Resampling Techniques.- Employee Attrition Prediction using Ensemble Methods.- Measuring Bias in Generated Text using Language Models- GPT-2 and BERT.- A Certain Investigation on Under Sea Water Image Object Detection and Classification Using Artificial Intelligence Algorithms.- DDoS Cyber-Attacks Detection-Based Hybrid CNN-LSTM.- Proposed Multilevel Secret Images Sharing Scheme.- Image Captioning System for Movie Subtitling using Neural Networksand LSTM.- Semantic Application based on the Bhagavad Gita: A Deep Learning Approach.- RMODCNN: A Novel Plant Disease Prediction Framework.- Refined Human-Computer Interaction: Enhancing Efficiency and Collaboration.- The Impact Of Data Valuation On Feature Importance In Classification Models.- Evaluating Machine Learning Algorithms for New Indian Parliament Building Sentiment Analysis.- Track 2: Advances In Artificial Intelligence And Machine Learning Adoption of Artificial Intelligence in Business Operations of Technology Firms.- An Artificial Intelligence Approach to Quantifying Exercise Form for Optimal Performance and Injury Prevention.- Predicting Content Popularity on Social Media: An Analytical Approach using Regression Modeling.- Hybrid Encryption Algorithm: AES and PRESENT lightweight with a chaotic system(PHEPA-AES).- Improving Network Intrusion Detection with Convolutional Neural Networks and Data Balancing Techniques.- MbAbI: A Benchmark Dataset for Malayalam Text Understanding and Reasoning.- A Novel Approach to Image Restoration and Image Enhancement.- Smart Helmet With Crash Detection.- Digital Payment Systems and Financial Inclusion: Examine How Digital Payment Systems, Such As Mobile Wallets and Digital Currencies, Can Improve Financial Inclusion by Providing Access to Banking Services for the Unbanked and Underbanked Population.- Enhanced Prediction of Breast Cancer using Machine Learning Ensemble Models and Techniques.- Enhancing Adaptive E-Learning with Generative AI: Expanding the Horizon Beyond Recommendation Systems.- A Fusion Framework of Pre-Trained Deep Learning Models for Oral Squamous Cell Carcinoma Classification.