Maximizing Information System Availability Through Bayesian Belief Network Approaches Emerging Research And Opportunities

Technological tools have enhanced the available opportunities and activities in the realm of e-business. In organizations that support real-time business-critical operations, the proper use and maintenance of relevant technology is crucial. Maximizing Information System Availability Through Bayesian Belief Network Approaches: Emerging Research and Opportunities is a pivotal book that features the latest research perspectives on the implementation of effective information systems in business contexts. Highlighting relevant topics such as data security, investment viability, and operational risk management, this book is ideally designed for managers, professionals, academics, practitioners, and students interested in novel techniques for maintaining and measuring information system availability.

This book constitutes the full papers and short monographs developed on the base of the refereed proceedings of the International Conference on Information Technologies: Information and Communication Technologies for Research and Industry (ICIT-2019), held in Saratov, Russia in February 2019. The book brings accepted papers which present new approaches and methods of solving problems in the sphere of control engineering and decision making for the various fields of studies: industry and research, ontology-based data simulation, smart city technologies, theory and use of digital signal processing, cognitive systems, robotics, cybernetics, automation control theory, image recognition technologies, and computer vision. Particular emphasis is laid on modern trends, new approaches, algorithms and methods in selected fields of interest. The presented papers were accepted after careful reviews made by at least three independent reviewers in a double-blind way. The acceptance level was about 60%. The chapters are organized thematically in several areas within the following tracks: • Models, Methods & Approaches in Decision Making Systems • Mathematical Modelling for Industry & Research • Smart City Technologies The conference is focused on development and globalization of information and communication technologies (ICT), methods of control engineering and decision making along with innovations and networking, ICT for sustainable development and technological change, and global challenges. Moreover, the ICIT-2019 served as a discussion area for the actual above-mentioned topics. The editors believe that the readers will find the proceedings interesting and useful for their own research work.

Modern optimization approaches have attracted an increasing number of scientists, decision makers, and researchers. As new issues in this field emerge, different optimization methodologies must be developed and implemented. The Handbook of Research on Emergent Applications of Optimization Algorithms is an authoritative reference source for the latest scholarly research on modern optimization techniques for solving complex problems of global optimization and their applications in economics and engineering. Featuring coverage on a broad range of topics and perspectives such as hybrid systems, non-cooperative games, and cryptography, this publication is ideally designed for students, researchers, and engineers interested in emerging developments in optimization algorithms.

Social technology is quickly becoming a vital tool in our personal, educational, and professional lives. Its use must be further examined in order to determine the role of social media technology in organizational settings to promote business development and growth. Social Network Analytics for Contemporary Business Organizations is a critical scholarly resource that analyzes the application of social media in business applications. Featuring coverage on a broad range of topics, such as business management, dynamic networks, and online interaction, this book is geared towards professionals, researchers, academics, students, managers, and practitioners actively involved in the business industry.

Risk management is a vital concern in any organization. In order to succeed in the competitive modern business environment, the decision-making process must be effectively governed and managed. Research, Practices, and Innovations in Global Risk and Contingency Management is a critical scholarly resource that provides an all-encompassing holistic discussion of risk management and perception, while giving readers innovations on empirical risk-contingency management research and case studies. Featuring coverage on a broad range of topics, such as contingency planning, project management, and risk mitigation, this book is geared towards academicians, practitioners, and researchers seeking current research on risk and contingency management issues.

Business retains a large influence over the progression of society. Thus, shared goals among corporations could lead to a larger positive impact on the resilience of social and economic expansions. Value Sharing for Sustainable and Inclusive Development is a critical academic resource that explores the opportunities through which businesses can contribute to sustainable and inclusive development. Featuring coverage on a broad range of topics such as the value sharing model, corporate social responsibility, and multi-sided markets, this book is geared toward academicians, researchers, policy makers, and students seeking current research on the importance of collaborative efforts on the part of businesses and entities to achieve functional progression.

"In this book researchers have employed different approaches to examine and describe various types of relationships among people in communities by using social capital as a conceptual and theoretical tool"--Provided by publisher.

This book exemplifies the interplay between the general formal framework of graphical models and the exploration of new algorithm and architectures. The selections range from foundational papers of historical importance to results at the cutting edge of research. Graphical models use graphs to represent and manipulate joint probability distributions. They have their roots in artificial intelligence, statistics, and neural networks. The clean mathematical formalism of the graphical models framework makes it possible to understand a wide variety of network-based approaches to computation, and in particular to understand many neural network algorithms and architectures as instances of a broader probabilistic methodology. It also makes it possible to identify novel features of neural network algorithms and architectures and to extend them to more general graphical models.This book exemplifies the interplay between the general formal framework of graphical models and the exploration of new algorithms and architectures. The selections range from foundational papers of historical importance to results at the cutting edge of research. Contributors H. Attias, C. M. Bishop, B. J. Frey, Z. Ghahramani, D. Heckerman, G. E. Hinton, R. Hofmann, R. A. Jacobs, Michael I. Jordan, H. J. Kappen, A. Krogh, R. Neal, S. K. Riis, F. B. Rodríguez, L. K. Saul, Terrence J. Sejnowski, P. Smyth, M. E. Tipping, V. Tresp, Y. Weiss