Universal Threats in Expert Applications and Solutions

Vijay Singh Rathore is presently working as Professor-CSE and Director of Research and International Relations, IES University, Bhopal, and also running his own establishment Shree KKarni Universe College, Jaipur (in partnership). He is Membership Chair, ACM Jaipur Chapter, and Past Chairman, CSI Jaipur Chapter. He is having teaching experience of 22+ years. He is Former Professor—CSE—and Director—Out Reach, JECRC, Jaipur. His core research areas include internet security, cloud computing, big data, and IoT. He has organized and participated 25+ national and international conferences of repute.  His foreign visits for various academic activities (Delegate/Invited/Keynote Speaker/Session Chair/Guest) include USA, UK, Canada, France, Netherlands, Singapore, Egypt, Thailand, Vietnam, Nepal, etc. He had been Member of Indian Higher Education Delegation and visited 20+ leading universities at Canada (May, 2019), UK (July, 2017), and USA (Aug, 2018) supported by AICTE. João Manuel R. S. Tavares graduated in mechanical engineering at the Universidade do Porto, Portugal, in 1992. He also earned his M.Sc. degree and Ph.D. degree in electrical and computer engineering from the Universidade do Porto in 1995 and 2001 and attained his habilitation in mechanical engineering in 2015. He is Senior Researcher at the Instituto de Ciência e InovaçãoemEngenhariaMecânica e Engenharia Industrial (INEGI) and Full Professor at the Department of Mechanical Engineering (DEMec) of the Faculdade de Engenharia da Universidade do Porto (FEUP). João Tavares is Co-Editor of more than 75 books and Co-Author of more than 50 book chapters. He has been Committee Member of several international and national journals and conferences. His main research areas include computational vision, medical imaging, computational mechanics, scientific visualization, human–computer interaction, and new product development.M. Hanumanthappa is working as Professor of Bangalore University and Chairman for the Board of Studies, in computer science and applications, Bengaluru City University, Bengaluru. He has vast teaching for the board of industry experience spreading over two decades at postgraduate level and various IT industries. He has authored more than 120 research papers in reputed international journals and peer-reviewed conference papers at international and national levels. He is Recipient of the Best Paper Publication Award by many organizations. His research interest includes data mining, information retrieval, network security, and natural language processing. He is Chairman for the Board of Studies in Computer Science of Tumkur University, Bangalore North University. He has conducted many Ph.D. viva voce examinations of various universities across the country. He has authored many computer science books by various publishers. He delivered many lectures at various conferences at national and international level. B. Surendiran is working as Associate Professor, Dept. of CSE, NIT Puducherry, Karaikal. He has more than 16 years of teaching and research experience. He had completed his Ph.D. in the year 2012 from NIT Trichy. His research interests are medical image processing, machine learning, dimensionality reduction, etc. He had 50+ international journal and conference publications to his credit. He has delivered 85+ lectures, reviewed 500+ research papers, and guided 12 Ph.D. Scholars. He has received Best reviewer award in 2019 by publons.com, Web of  Science, and also Outstanding Reviewer Award by Biomedical and Pharmacology Journal in the year 2020. He is Active Reviewer for IEEE sensors, IET image processing, and various SCI/Scopus Journals.

• Exploring the impact and applications of data science and big data in promoting sustainability.- Improving Data Mining Reliability through Applied C-B Techniques for Addressing Misplaced Values.- Comparative Analysis of NSAI and Traditional Neural Networks for Visual Question Answering on DAQUAR Datasets.- Comparative Analysis of Deep Learning Models for Cassava Disease on Small and Large Datasets.- Solar Intelligence Predictive Models for Power Generation And Radiation.- Advancing Intrusion Detection with Deep Learning: Techniques, Limitations, and Future Trends.