Human Machine Interaction in the Digital Era: Towards Conversational Artificial Intelligence

The Human Machine Interaction in the Digital Era (ICHMIDE) 2023 conference aims to address the main issues of concern in the design issues with a particular emphasis on the design and development of interfaces for autonomous robots. Its main objective is to provide an international forum for the dissemination and exchange of up-to-date scientific information on research related to integrated human/machine systems at multiple scales, and includes areas such as human/machine interaction, engineering mathematical models, assistive technologies, system modelling, design, testing and validation. The organization of ICHMS is based on the following Track types: Smart Applications for Digital Era, Computational Mathematical and Electronics, Intelligent Systems in Security and Communication Technologies, Technological Interventions using AI and Machine Learning, Applied Science, and IoT Techniques for Industries.

Table of Contents:
1. A Performance of Comparative Study on Hate Speech Detection using Deep Learning Algorithms2. A Study on Technology-Related Distraction in College Student’s Academics Using Data Mining Techniques 3. A Study of Various Deep Learning Methods Used for Image Splicing Detection 4. ASO-GRU-NN: Atom Search Optimized Gated Recurrent Units based Neural Network for the Severity Classification of COVID-19 Using Different Feature Extraction Methods 5. Deep Learning Based Brain Tumour Detection Using Image Processing 6. Detection and Notification System in Emergency Vehicles for Unidentified Accident Victims 7. E-Learning Technologies with Interactive Factors and Elements on the Perspective of Knowledge Management8. Expert System in Wearables and Web of Things Using Artificial Neural Network9. Cognitive Based Learning in Feed Forward MLP for Classification of Neurodegenerative Disorders10. Prediction of Lung Cancer Disease in Human Beings from Biomedical Text Dataset Using Transfer Learning 11. An End-to-End Machine Learning Model to Predict the First Innings Score in IPL 12. Real Time Intrusion Detection Network Using Artificial Neural Network 13. Detection of People or Animals Using Deep-learning in Railway Tracks 14. Confronting Floating Plastic Debris as Pollutants in Marine Using Technological Solutions Deep Learning Approach 15. Recommender Model for e-Learning Environment Using Enhanced Support Vector Space Model (ESVM)16. Ripeness Detection in Watermelon Using CNN 17. Heart Disease Prediction and Analysis Using Ensemble Classifier in Machine Learning Techniques 18. Study of Factors associated with Diets and Prevalence of Overweight and Obesity among Adolescent Girls 19. Comparison of Distinct Mel-Frequency Cepstral Co-efficient (MFCC) Selection for Heart Disease Prediction Using Machine Learning Algorithms 20. Artificial Intelligence Based Virtual Health Assistant and Patient Monitoring System 21. A Novel OLPP Based LVQ-LM Network for Health Care Dataset 22. Effectiveness of Chat Bots to Detect Health Insurance Fraudulent Claims23. Polycystic Ovary Syndrome Classification Using Machine Learning Algorithm 24. Deep Predictive Analytics of Online Learning Materials to Customer Clusters with User Intention and Behavior Patterns25. Intelligent Home Automation with Multiple Languages Voice Control 26. Commercial Power Hip Kinfolk Organized Commerce Plus the Basic Aimed at Scientific Office 27. Review on Student Performance Evaluation System for E-Learning 28. Modified LSTM for Prediction of Pollutants Concentration29. An Effective Analysis of Feature Selection Methods for High Dimensional Data—A Survey30. Management Information System for Operation, Planning and Control of Wind Energy Farms31. Deep Learning Procedures to Detect Breast Cancer in Mammogram and MR Images and Relative Exploration of Images 32. Usage and Adoption of Technology Among Christians During Covid-19: Based on UTAUT2 Model33. Artificial Intelligence (AI) Enabled Decision Framework for Supply Chain Resilience (SCRs) 34. Prognosticating Mobile Application Usage Pattern with Modified Genetic Algorithm and Dynamic Density Updated Clustering Approach 35. Differential Privacy for Set Valued Data Publishing to Avoid Illegal Attack 36. Recognition and Classification of Thyroid Nodule with Deep Recurrent Neural Network Using Ultrasound Images 37. Recognizing Spectral Patterns of Phytophthora Infestans on Tomatoes Using Image Processing Techniques 38. Operating Wind Energy Turbine Generator as Smart Factory Using Management Information System Equipped with Industry 4.0 Standards 39. A Review on Machine Learning Techniques to Identify Plant Diseases 40. SPK-A Traffic Violation Detection System41. Hybrid Leach Protocol and Genetic Algorithm to Obtain Route Node in Under Water Sensor Network 42. A Drastic Review on Self-Efficacy of Hard of Hearing and Mutant Students Using Assistive Technologies in Higher Education43. Uncovering the Secrets of Stegware: An In-Depth Analysis of Steganography and its Evolving Threat Landscape 44. Wheelchairs—A Boon in the Rehabilitative Era45. CoV-3DM: COVID-19 Disease Detection Based on Ensemble SMOTE Technique with Routine Blood Test Parameters 46. A Research on Patient Engagement Using Predictive Analytics 47. Healthcare in Your Hands: Sentiment Analysis on Indian Telemedicine in the Era of Global Pandemic 48. Effectiveness of Behavioural and Personality Aspects in Enhancing the Organizational Culture of the Teaching Professionals

About the Author :
Prof. J. Dhilipan Dr. J. Dhilipan is working as a professor and Head in the Department of Computer Science and Applications (MCA), SRM Institute of Science and Technology, Ramapuram, Chennai-89. He received Ph.D degree from Manonmaniam Sundranar University, M. Phil degree from Dravidan University and M. C. A degree from Madurai Kamaraj university. He has 21 years of teaching experience in academic institutions. He is passionate on teaching, imparting, training, motivating and helping of young minds with knowledge and good discipline. He holds 47 publications in reputed journals and 60 conference publications. more than 96 papers in National and International reputed journals with 70 citations and 5 h-index. Serving an Organizing Chair, Program Chair and Program Committees of several national and International technical programs. His main areas of research include Artificial Intelligence, Machine Learning and Data Analytics. Prof. V. Saravanan Prof. V Saravanan has completed his PhD in Computer Science in the Department of Computer Science and Engineering, Bharathiar University during 2004. His research area includes Artificial Intelligence, Machine Learning and Software Agents. In his credit he has 90+ publications in international journals indexed with ISI, Scopus etc., He has presented many research papers in National, International conferences and Journals and also guiding many researchers leading to their PhD degree. He has totally 25 years’ experience in teaching including 3 years as researcher in Bharathiar University. He has guided 18 PhD scholars in Computer Science. As the credit toward funded projects, he had completed with Majmaah University and King Abdulaziz City for Science and Technology, Kingdom of Saudi Arabia with the total project cost of USD $41500. He is a Senior Member of IEEE, life member of Computer Society of India, Indian Society for Technical Education. He worked as Professor & Head of the Department of Computer Applications in Karunya University, Coimbatore and as Director-Computer Applications of Dr. NGP Institute of Technology, Coimbatore, and Dean-Computer Studies, SNS Institutions, Coimbatore. At present he working as Vice-Principal(Academics), Faculty of Science and Humanities, SRM Institute of Science and Technology, Ramapuram, Chennai, Tamilnadu, India. Prof. R. Agusthiyar Prof. R. Agusthiyar is well known academician in the field of Higher Education with 21 years of teaching experience and he started his teaching profession from 2002 to till date and now he is working as a Professor and Head in Department of Computer Applications (BCA), Faculty of Science and Humanities, SRMIST, Ramapuram Campus. He has received his Post Graduate MCA degree from Madurai Kamaraj University, Tamil Nadu, India in 2001, and M. Phil degree from Periyar University, Tamil Nadu, India in 2008 respectively. He has received his Ph.D in Data mining at Anna University in the Year 2017 under the guidance of Prof. Dr. K. Narashiman Anna University. His research interests include Data mining, Artificial Intelligence and Machine Learning. He has published 14 research publications in indexed journals and 25 publications in International and National Conferences. He is guiding 8 research scholars in SRM Institute of Science and Technology. He has two patents in the field of IoT and Machine Learning.