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This book delves into the history of biometrics, the different systems that have been developed to date, problems that have arisen from these systems, the necessity of AI-based biometrics systems, different AI techniques developed to date (including machine learning, deep learning, natural language processing, and pattern recognition), their potential uses and applications, security and privacy issues in AI-based Biometric systems, current trends in AI-based biometrics, and presents case studies of AI-based biometrics.
This book highlights recent research on intelligent systems and nature-inspired computing. It presents 130 selected papers from the 19th International Conference on Intelligent Systems Design and Applications (ISDA 2020), which was held online. The ISDA is a premier conference in the field of computational intelligence, and the latest installment brought together researchers, engineers and practitioners whose work involves intelligent systems and their applications in industry. Including contributions by authors from 40 countries, the book offers a valuable reference guide for all researchers, students and practitioners in the fields of Computer Science and Engineering.
This book presents advances in security assurance for cyber-physical systems (CPS) and report on new machine learning (ML) and artificial intelligence (AI) approaches and technologies developed by the research community and the industry to address the challenges faced by this emerging field. Cyber-physical systems bridge the divide between cyber and physical-mechanical systems by combining seamlessly software systems, sensors, and actuators connected over computer networks. Through these sensors, data about the physical world can be captured and used for smart autonomous decision-making. This book introduces fundamental AI/ML principles and concepts applied in developing secure and trustworthy CPS, disseminates recent research and development efforts in this fascinating area, and presents relevant case studies, examples, and datasets. We believe that it is a valuable reference for students, instructors, researchers, industry practitioners, and related government agencies staff.
Signal Processing and Communications Applications Conference (S U) is one of the most prominent scientific events in Turkey During the conference, researchers share their novel contributions to scientific and technological development
Multi-Criteria Decision-Making (MCDM) includes methods and tools for modeling and solving complex problems. MCDM has become popular in the production and service sectors to improve the quality of service, reduce costs, and make people more prosperous. This book illustrates applications through case studies focused on disaster management. With a presentation of both Multi-Attribute Decision-Making (MADM) and Multi-Objective Decision-Making (MODM) models, this is the first book to merge these methods and tools with disaster management. This book raises awareness for society and decision-makers on how to measure readiness and what necessary preventive measures need to be taken. It offers models and case studies that can be easily adapted to solve complex problems and find solutions in other fields. Multi-Criteria Decision Analysis: Case Studies in Disaster Management will offer new insights to researchers working in the areas of industrial engineering, systems engineering, healthcare systems, operations research, mathematics, business, computer science, and disaster management, and, hopefully, the book will also stimulate further work in MCDM.
This book provides in-depth guidance on how to use multi-criteria decision analysis methods for risk assessment and risk management. The frontiers of engineering operations management methods for identifying the risks, investigating their roles, analyzing the complex cause-effect relationships, and proposing countermeasures for risk mitigation are presented in this book. There is a total of ten chapters, mainly including the indicators and organizational models for risk assessment, the integrated Bayesian Best-Worst method and classifiable TOPSIS model for risk assessment, new risk prioritization model, fuzzy risk assessment under uncertainties, assessment of COVID-19 transmission risk based...
This book presents the latest research perspectives on how the Industry 4.0 paradigm is challenging the process of technological and structural change and how the diversification of the economy affects structural transformation. It also explores the impact of fast-growing technologies on the transformation of socioeconomic and environmental systems, and asks whether structural and technological change can generate sustainable economic growth and employment. Further, the book presents the basic innovations (new technologies, materials, energy, etc) and industrial policies that can lead to such a structural change.
This book provides in-depth guidance on how to use multi-criteria decision analysis methods for risk assessment and risk management. The frontiers of engineering operations management methods for identifying the risks, investigating their roles, analyzing the complex cause-effect relationships, and proposing countermeasures for risk mitigation are presented in this book. There is a total of ten chapters, mainly including the indicators and organizational models for risk assessment, the integrated Bayesian Best-Worst method and classifiable TOPSIS model for risk assessment, new risk prioritization model, fuzzy risk assessment under uncertainties, assessment of COVID-19 transmission risk based...
Take a problem-solving approach to learning all about transformers and get up and running in no time by implementing methodologies that will build the future of NLP Key Features Explore quick prototyping with up-to-date Python libraries to create effective solutions to industrial problems Solve advanced NLP problems such as named-entity recognition, information extraction, language generation, and conversational AI Monitor your model's performance with the help of BertViz, exBERT, and TensorBoard Book DescriptionTransformer-based language models have dominated natural language processing (NLP) studies and have now become a new paradigm. With this book, you'll learn how to build various trans...