This book explores the critical issue of fairness in human-machine interfaces. It delves into the integration of technology and cognitive science to develop AI systems that are unbiased, reliable, and user-friendly. The book also sheds light on emotional data processing in AI accelerators and federated learning modules. Additionally, it covers machine learning, knowledge representation, and the application of knowledge graphs to understand and optimize the behaviour of AI assistance devices.
* Explains complex issues of Cognitive Fairness Aware Contextual Proactive Federated Protocol collects data and identifies individual emotional issues and resolves them by contextual solitary proactive communication
* Discusses emotional data processing challenges through AI accelerator with federated learning module to generate periodical counselling messages
* Data analysis anomalies are addressed in Graph Data Base Modelling by anomaly prediction and anomaly detection
* Describes anomaly detection techniques in the form of abnormal data records, messages, events, groups, and/or other unexpected observations in graph database modelling
* Outlier detection for data analysis deals with the detection of patterns in Graph Data Base
This book is for researchers, academics, students, AI Practitioners and Developers, Ethics Experts in AI Technology and machine-learning practitioners interested in fairness in human-machine interfaces.
Vithya Ganesan, PhD
She is a professor in the Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India. Currently Principal Investigator to develop a device for visually challenged people by cloud service, Deep learning and IoT. It is funded by Indian organization Directorate of Science and Technology -SERB-Core Research Grant. Dr. Vithya has received her PhD degree from Anna University, Chennai and 24+ years of teaching and research experience, and her current research interests are IoT, AI, deep learning, and data science. She has published more than 45 indexed research papers, patents and book chapters. She is a certified professional in many online certifications. She serves as a reviewer for academic publishers and as an editor for SCI, scopus and web of science journals. She has reviewed more than 150 papers for many reputed publishers and conferences. She is currently working as research guide, reviewer, editor and journal ambassador. She is keynote speaker for FDP, workshops, seminars for many institutions and organizations. Scopus ID: 57222093546, Web of Science Researcher ID AAX-7928-2021
S. Indu Vadhani
She currently works as senior software engineer at Meta Platforms, Inc., which is an American multinational technology company headquartered in Menlo Park, California, USA. Prior to that, she was working as a software Engineer at CISCO, San Jose, CA. Ms S. Indu Vadhani received her master's degree from University of Southern California, Los Angeles, USA. She has worked on automation of traffic monitoring, virtual machine implementation using Python, and has developed complex software modules for VMware Cloud Storage functionality in Enterprise-class SaaS (Software as a Service). She contributed to VMC on AWS (VMware Cloud on Amazon Web Services) built on a micro-services architecture using Java Spring Boot framework. She leads design/architecture review processes and participates in technical discussions with dependent teams to implement features such as Custom Storage Policy support in VM Creation. Scopus ID: 55446048400
Subrata Chowdhury
He is with the Sreenivasa Institute of Technology and Management Studies, Chittoor, Andhra Pradesh, India. He has edited five books in association with the CRC Press and others. He has published more than 50 articles in international and reputed journals. His research interests include data mining, big data, machine learning, quantum computing, fuzzy logic, AI, edge computing, swarm intelligence, and healthcare. He serves as a reviewer for reputed publishers and an editor for Hindawi journals. He has worked with software companies as a consultant and is the external supervisor for many PhD students. Currently, he is associated with the Study Council for Rural Development projects.
Souvik Pal, PhD
Souvik Pal is an Professor in the Department of Computer Science and Engineering at Sister Nivedita University (Techno India Group), Kolkata, India. Prior to that, he was associated with Global Institute of Management and Technology; Brainware University, Kolkata; JIS College of Engineering, Nadia; Elitte College of Engineering, Kolkata; and Nalanda Institute of Technology, Bhubaneswar, India. Dr. Pal received his MTech, and PhD degrees in the field of Computer Science and Engineering from KIIT University, Bhubaneswar, India. With more than a decade of academic experience, he is the author or co-editor of more than 15 books from reputed publishers and he holds three patents. He is serving as a Series Editor for "Advances in Learning Analytics for Intelligent Cloud-IoT Systems", "Internet of Things: Data-Centric Intelligent Computing, Informatics, and Communication", published CRC Press, Taylor & Francis Group, USA; "Conference Proceedings Series on Intelligent Systems, Data Engineering, and Optimization", published CRC Press, Taylor & Francis Group, USA; Dr. Pal has published a number of research papers in Scopus / SCI/SCIE Journals and conferences. He is the organizing chair of RICE 2019, Vietnam; RICE 2020 Vietnam; ICICIT 2019, Tunisia. He has been invited as a keynote speaker at ICICCT 2019, Turkey, and ICTIDS 2019, 2021 Malaysia. He has also served as Proceedings Editor of ICICCT 2019, 2020; ICMMCS 2020, 2021; ICWSNUCA 2021, India. His professional activities include roles as Associate Editor, Guest Editor, and Editorial Board member for more than 100+ international journals and conferences of high impact. His research area includes cloud computing, big data, internet of things, wireless sensor network, and data analytics. He is a member of many professional organizations, including MIEEE; MCSI; MCSTA/ACM, USA; MIAENG, Hong Kong; MIRED, USA; MACEEE, New Delhi; MIACSIT, Singapore; and MAASCIT, USA.
Vishnu Pendyala, PhD
He is a seasoned Technical Leader with over two decades of development, porting, and DevOps experience in the software industry. He received his PhD in Computer Engineering from Santa Clara University. He is a Senior Member of IEEE and has presented and published widely referenced papers for international conferences and publications. He served as a repeat technical paper reviewer for professional journals and conferences. Vishnu received the Ramanujam memorial gold medal at the State Math Olympiad and has been a successful leader during his undergrad years. He also played an active role in Computer Society of India and was the Program Secretary for its annual convention. He is IEEE Computer Society Distinguished Contributor (One of the 22 in the Class of 2022),ACM Distinguished Speaker (2019 - 2022), Senior Member,Senator, SJSU Academic Senate (2023 - date),IEEE Computer Society Election Committee Member (2024), Area 4 Coordinator (2025 - date),Chair (2022 - date), Vice Chair (2019), Secretary (2021), IEEE Computer Society, SCV Chapter Chair (2025 - date), IEEE Computational Intelligence Society, Santa Clara Valley Chapter Board of Directors, Silicon Valley Engineering Council (July 2018 - November 2019) Executive Council Member, SIGBDA, Computer Society of India (May 2016 - Current) Scopus Author ID: 55936784700
Herausgeber*in
Assistant Professor, JIS College of Engineering, WB, India
1. Federated learning by Contextual Model for Advanced AI Assistance 2. Computational Modeling for Personalized Emotion Data and Visual Analytics to Predicting Habits 3. A review on Computational modeling for Personalize demotion and visual analytics to predicting habits 4. An impact of AI-Driven Sentiment Analysis Improves Stock Market Trend Predictions, Risk Management, and Ethics 5. Transformative Strategies for AIED Interaction on the evolution of AI Learning Companions in the Era of Human-Robot Interaction in EFL Settings 6. Comprehensive Overview of Graph Database: Types, Algorithms, Visualization Tools, Applications, and Key Challenges 7. Context-aware Knowledge Base Engineering for Anomaly Detection and Predictive Maintenance in Graph Databases 8. Context Anomaly Identification Algorithm using Dirichlet Graph based mapping in health care analytics 9. Human-Machine Interaction Failure for Indian Companies-An Exploratory Study 10. Practical Solutions for Data Consistency and Query Performance in Graph Database and Search Engine Integration 11. Co-evolution of Human and Machine Intelligence 12. A Novel Graph Machine Learning Pipeline for Anomaly Detection 13. Implementing a Graph Machine Learning Pipeline for Anomaly Detection 14. Proactive Human - Machine Collaboration 15. Proactive Assistance between Human and Machine
