Next Gen Technologies In Computational Intelligence

The Proceeding includes the research contribution from the International Conference on Next-Gen Technologies in Computational Intelligence (NGTCA 2023) held on March 24th 2023 at Vels Institute of Science, Technology and Advanced Studies. NGCTA 2023 is the flagship conference of the Computer Society of India (Region 7). Computer Society of India (CSI) is the largest association of IT professionals in India. CSI is a non-profit organization established in 1965 and its members are committed to the advancement of theory and practice of Computer Engineering and Technology Systems. The Mission of CSI is to facilitate research, knowledge sharing, learning, and career enhancement for all categories of IT professionals, while simultaneously inspiring and nurturing new entrants into the industry and helping them to integrate into the IT community. At present, CSI has 76chapters across India, over 550 student branches with 1,00,000 plus members. It serves its members through technical events, seminars, workshops, conferences, publications & journals, research projects, competitions, special interest groups, awards & recognitions, etc. Various CSI chapters conduct Research Convention every year.

The 18 full and 13 short papers presented were carefully reviewed and selected from 255 submissions. There were organized in topical sections named: Image Processing, Pattern Analysis and Machine Vision; Information and Data Convergence; Disruptive Technologies for Future; E-Governance and Smart World

This book focuses on next generation data technologies in support of collective and computational intelligence. The book brings various next generation data technologies together to capture, integrate, analyze, mine, annotate and visualize distributed data – made available from various community users – in a meaningful and collaborative for the organization manner. A unique perspective on collective computational intelligence is offered by embracing both theory and strategies fundamentals such as data clustering, graph partitioning, collaborative decision making, self-adaptive ant colony, swarm and evolutionary agents. It also covers emerging and next generation technologies in support of collective computational intelligence such as Web 2.0 social networks, semantic web for data annotation, knowledge representation and inference, data privacy and security, and enabling distributed and collaborative paradigms such as P2P, Grid and Cloud Computing due to the geographically dispersed and distributed nature of the data. The book aims to cover in a comprehensive manner the combinatorial effort of utilizing and integrating various next generations collaborative and distributed data technologies for computational intelligence in various scenarios. The book also distinguishes itself by assessing whether utilization and integration of next generation data technologies can assist in the identification of new opportunities, which may also be strategically fit for purpose.

This book offers an excellent presentation of intelligent engineering and informatics foundations for researchers in this field as well as many examples with industrial application. It contains extended versions of selected papers presented at the inaugural ACASE 2012 Conference dedicated to the Applications of Systems Engineering. This conference was held from the 6th to the 8th of February 2012, at the University of Technology, Sydney, Australia, organized by the University of Technology, Sydney (Australia), Wroclaw University of Technology (Poland) and the University of Applied Sciences in Hagenberg (Austria). The book is organized into three main parts. Part I contains papers devoted to the heuristic approaches that are applicable in situations where the problem cannot be solved by exact methods, due to various characteristics or dimensionality problems. Part II covers essential issues of the network management, presents intelligent models of the next generation of networks and distributed systems as well as discusses applications of modern numerical methods in large intractable systems. Part III covers salient issues of complexity in intelligent system applications. This part also contains papers and articles which discuss concurrency issues that arise when multiple systems attempt to use the same radio space and the inter-connected system applications in the field of medical simulation and training.

The 18 full and 13 short papers presented were carefully reviewed and selected from 255 submissions. There were organized in topical sections named: Image Processing, Pattern Analysis and Machine Vision; Information and Data Convergence; Disruptive Technologies for Future; E-Governance and Smart World

The interaction of database and AI technologies is crucial to such applications as data mining, active databases, and knowledge-based expert systems. This volume collects the primary readings on the interactions, actual and potential, between these two fields. The editors have chosen articles to balance significant early research and the best and most comprehensive articles from the 1980s. An in-depth introduction discusses basic research motivations, giving a survey of the history, concepts, and terminology of the interaction. Major themes, approaches and results, open issues and future directions are all discussed, including the results of a major survey conducted by the editors of current work in industry and research labs. Thirteen sections follow, each with a short introduction. Topics examined include semantic data models with emphasis on conceptual modeling techniques for databases and information systems and the integration of data model concepts in high-level data languages, definition and maintenance of integrity constraints in databases and knowledge bases, natural language front ends, object-oriented database management systems, implementation issues such as concurrency control and error recovery, and representation of time and knowledge incompleteness from the viewpoints of databases, logic programming, and AI.

This book provides a detailed insight into Robotic Process Automation (RPA) technologies linked with AI that will help organizations implement Industry 4.0 procedures. RPA tools enhance their functionality by incorporating AI objectives, such as use of artificial neural network algorithms, text mining techniques, and natural language processing techniques for information extraction and the subsequent process of optimization and forecasting scenarios for the purpose of improving an organization's operational and business processes. The target readers of this book are researchers, professors, graduate students, scientists, policymakers, professionals, and developers working in the IT and ITeS sectors, i.e. people who are working on emerging technologies. This book also provides insights and decision support tools necessary for executives concerned with different industrial and organizational automation-centric jobs, knowledge dissemination, information, and policy development for automation in different educational, government, and non-government organizations. This book is of special interest to college and university educators who teach AI, machine learning, blockchain, business intelligence, cognitive intelligence, and brain intelligence courses in different capacities.

This book covers the applications of computational intelligence techniques in business systems and advocates how these techniques are useful in modern business operations. The book redefines the computational intelligence foundations, the three pillars - neural networks, evolutionary computation, and fuzzy systems. It also discusses emerging areas such as swarm intelligence, artificial immune systems (AIS), support vector machines, rough sets, and chaotic systems. The other areas have also been demystified in the book to strengthen the range of computational intelligence techniques such as expert systems, knowledge-based systems, and genetic algorithms. Therefore, this book will redefine the role of computational intelligence techniques in modern business system operations such as marketing, finance & accounts, operations, personnel management, supply chain management, and logistics. Besides, this book guides the readers through using them to model, discover, and interpret new patterns that cannot be found through statistical methods alone in various business system operations. This book reveals how computational intelligence can inform the design and integration of services, architecture, brand identity, and product portfolio across the entire enterprise. The book will provide insights into research gaps, open challenges, and unsolved computational intelligence problems. The book will act as a premier reference and instant material for all the users who are contributing/practicing the adaptation of computational intelligence modern techniques in business systems.