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This book focuses on a critical discussion of the status and prospects of current approaches in quantum mechanics and quantum field theory, in particular concerning gravity. It contains a carefully selected cross-section of lectures and discussions at the seventh conference ¿Progress and Visions in Quantum Theory in View of Gravity¿ which took place in fall 2018 at the Max Planck Institute for Mathematics in the Sciences in Leipzig.In contrast to usual proceeding volumes, instead of reporting on the most recent technical results, contributors were asked to discuss visions and new ideas in foundational physics, in particular concerning foundations of quantum field theory. A special focus has been put on the question of which physical principles of quantum (field) theory can be considered fundamental in view of gravity.The book is mainly addressed to mathematicians and physicists who are interested in fundamental questions ofmathematical physics. It allows the reader to obtain a broad and up-to-date overview of a fascinating active research area.

This book provides a review of advanced topics relating to the theory, research, analysis and implementation in the context of big data platforms and their applications, with a focus on methods, techniques, and performance evaluation. The explosive growth in the volume, speed, and variety of data being produced every day requires a continuous increase in the processing speeds of servers and of entire network infrastructures, as well as new resource management models. This poses significant challenges (and provides striking development opportunities) for data intensive and high-performance computing, i.e., how to efficiently turn extremely large datasets into valuable information and meaningful knowledge.The task of context data management is further complicated by the variety of sources such data derives from, resulting in different data formats, with varying storage, transformation, delivery, and archiving requirements. At the same time rapid responses are neededfor real-time applications. With the emergence of cloud infrastructures, achieving highly scalable data management in such contexts is a critical problem, as the overall application performance is highly dependent on the properties of the data management service.

There have been extraordinary developments in the field of neuroscience in recent years, sparking a number of discussions within the legal field. This book studies the various interactions between neuroscience and the world of law, and explores how neuroscientific findings could affect some fundamental legal categories and how the law should be implemented in such cases. The book is divided into three main parts. Starting with a general overview of the convergence of neuroscience and law, the first part outlines the importance of their continuous interaction, the challenges that neuroscience poses for the concepts of free will and responsibility, and the peculiar characteristics of a ¿new¿ cognitive liberty. In turn, the second part addresses the phenomenon of cognitive and moral enhancement, as well as the uses of neurotechnology and their impacts on health, self-determination and the concept of being human. The third and last partinvestigates the use of neuroscientific findings in both criminal and civil cases, and seeks to determine whether they can provide valuable evidence and facilitate the assessment of personal responsibility, helping to resolve cases. The book is the result of an interdisciplinary dialogue involving jurists, philosophers, neuroscientists, forensic medicine specialists, and scholars in the humanities; further, it is intended for a broad readership interested in understanding the impacts of scientific and technological developments on people¿s lives and on our social systems.

This book reviews the state of the art in algorithmic approaches addressing the practical challenges that arise with hyperspectral image analysis tasks, with a focus on emerging trends in machine learning and image processing/understanding. It presents advances in deep learning, multiple instance learning, sparse representation based learning, low-dimensional manifold models, anomalous change detection, target recognition, sensor fusion and super-resolution for robust multispectral and hyperspectral image understanding. It presents research from leading international experts who have made foundational contributions in these areas. The book covers a diverse array of applications of multispectral/hyperspectral imagery in the context of these algorithms, including remote sensing, face recognition and biomedicine. This book would be particularly beneficial to graduate students and researchers who are taking advanced courses in (or are working in) the areas ofimage analysis, machine learning and remote sensing with multi-channel optical imagery. Researchers and professionals in academia and industry working in areas such as electrical engineering, civil and environmental engineering, geosciences and biomedical image processing, who work with multi-channel optical data will find this book useful.

This handbook provides comprehensive knowledge and includes an overview of the current state-of-the-art of Big Data Privacy, with chapters written by international world leaders from academia and industry working in this field. The first part of this book offers a review of security challenges in critical infrastructure and offers methods that utilize acritical intelligence (AI) techniques to overcome those issues. It then focuses on big data security and privacy issues in relation to developments in the Industry 4.0. Internet of Things (IoT) devices are becoming a major source of security and privacy concern in big data platforms. Multiple solutions that leverage machine learning for addressing security and privacy issues in IoT environments are also discussed this handbook. The second part of this handbook is focused on privacy and security issues in different layers of big data systems. It discusses about methods for evaluating security and privacy of big data systems on network, application and physical layers. This handbook elaborates on existing methods to use data analytic and AI techniques at different layers of big data platforms to identify privacy and security attacks. The final part of this handbook is focused on analyzing cyber threats applicable to the big data environments. It offers an in-depth review of attacks applicable to big data platforms in smart grids, smart farming, FinTech, and health sectors. Multiple solutions are presented to detect, prevent and analyze cyber-attacks and assess the impact of malicious payloads to those environments. This handbook provides information for security and privacy experts in most areas of big data including; FinTech, Industry 4.0, Internet of Things, Smart Grids, Smart Farming and more. Experts working in big data, privacy, security, forensics, malware analysis, machine learning and data analysts will find this handbook useful as areference. Researchers and advanced-level computer science students focused on computer systems, Internet of Things, Smart Grid, Smart Farming, Industry 4.0 and network analysts will also find this handbook useful as a reference.

This volume analyzes the global challenges of food security, land use changes, and climate change impacts on food production in order to recommend sustainable development policies, anticipate future food services and demands, and identify the economic benefits and trade-offs of meeting food security demands and achieving climate change mitigation objectives. The key points of analysis that form the conclusions of this book are based on measuring the quantity and quality of land and water resources, and the rate of use of sustainable management of these resources in the context of socio-economic factors, including food security, poverty, and climate change impacts. In six parts, readers will learn about these crucial dimensions of the affects of climate change on food security, and will gain a better understanding of how to assess the trade-offs when combating multiple climate change challenges and how to develop sustainable solutions to these problems. The bookpresents multidimensional perspectives from expert contributors, offering holistic and strategic approaches to link knowledge on climate change and food security with action in the form of policy recommendations, with a focus on sociological and socio-economic components of climate change impacts. The intended audience of the book includes students and researchers engaged in climate change and food security issues, NGOs, and policy makers.