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This book provides application of multi criteria decision making techniques for managerial discretion. With this book, a concerted platform has been provided for several peers and other management organizations to understand and implement these tools and deal with the practical problems in a better way so as to provide more robust managerial decision making.
This book provides insights into contemporary issues and challenges concerning operational research and related mathematical modeling fundamentals, such as system reliability, scalability, and adaptability. This collaboration of academia and industry disseminates practical tools and analytics applications of mathematics in engineering and information sciences Optimization techniques have gained popularity among system managers for making crucial decisions while meeting multiple needs. The focus of this book is the evaluation and optimization of critical decisions related to the system betterment. Each chapter presents the recent advancements and research opportunities in system assurance. Operational Perspective of Modeling System Reliability (Research Tools for System Dynamics) is for academicians and those who need to understand the latest developments in the field of System Reliability. Along with these, anyone solving problems within the related application domains will benefit from this compilation.
This book covers advanced reliability and maintainability knowledge as applied to recent engineering problems. It highlights research in the fields of reliability measures of binary and complex engineering systems, cost analysis, simulations, optimizations, risk factors, and sensitivity analysis. The book scrutinizes various advanced tools and techniques, methodology, and concepts to solve the various engineering problems related to reliability and maintainability of the industrial system at minimum cost and maximum profit. It consists of 15 chapters and offers a platform to researchers, academicians, professionals and scientists to enhance their knowledge and understanding the concept of reliability in engineering.
In recent years, mathematical techniques applied to novel disciplines within the science and engineering have experienced extraordinary growth. Advanced Mathematical Techniques in Science and Engineering focusses on a detailed range of mathematics applied within various fields of science and engineering for different tasks. Topics of focus include:- Analysis of Consensus-Building Time in Social Groups- Modeling of intersystem accidents in critical infrastructure systems- Stochastic approaches to analysis and modeling of multi-sources and big data- Performance evaluation of computational DoS attack on access point in Wireless LANs- Ranking methods for decision-making under uncertainty- Unders...
Algorithms are ubiquitous in the contemporary technological world, and they ultimately consist of finite sequences of instructions used to accomplish tasks with necessary input values. This book analyses the top performing algorithms in areas as diverse as Big Data, Artificial Intelligence, Optimization Techniques and Cloud & Cyber Security Systems in order to explore their power and limitations.
This book discusses action-oriented, concise and easy-to-communicate goals and challenges related to quality, reliability, infocomm technology and business operations. It brings together groundbreaking research in the area of software reliability, e-maintenance and big data analytics, highlighting the importance of maintaining the current growth in information technology (IT) adoption in businesses, while at the same time proposing process innovations to ensure sustainable development in the immediate future. In its thirty-seven chapters, it covers various areas of e-maintenance solutions, software architectures, patching problems in software reliability, preventive maintenance, industrial b...
This book shows how machine learning (ML) methods can be used to enhance cyber security operations, including detection, modeling, monitoring as well as defense against threats to sensitive data and security systems. Filling an important gap between ML and cyber security communities, it discusses topics covering a wide range of modern and practical ML techniques, frameworks and tools.
"Digital Blockchain- Big Data, Artificial Intelligence and Virtual Reality in Healthcare Ecosystem" is a book that explores the revolutionary impact of blockchain, big data, and artificial intelligence (AI) on the pharmaceutical and healthcare sectors. The book discusses AI, big data, and their applications in drug research, clinical trials, regulatory compliance, and post-marketing surveillance. The book also discusses education and training in smart pharma, demonstrating the potential of AI, big data, and machine learning to improve workforce capacities. The book discusses intellectual property and data privacy issues, the legislative framework for AI adoption, ethical considerations, and future trends in AI-enabled drug research, manufacturing, and healthcare innovation. It is a valuable resource for healthcare professionals, industrial experts, and academicians, offering theoretical and practical insights.
The distributed transfer function method (DTFM) is an analytical method for modeling, analysis, and control of a class of distributed parameter systems that are governed by partial differential equations and that can be defi ned over multiple interconnected subregions. In this comprehensive reference, the authors show how the DTFM delivers highly accurate analytical solutions in both the frequency domain and the time domain while offering a versatile modeling technique for various problems in mechanical, civil, aerospace, electrical, chemical, biomechanical, and vehicle engineering.