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Dorogovtsev S: The Nature of Complex
Networks

The Nature of Complex Networks

Coding for Erasure Channels

Classical Optics and Electromagnetic Waves

Sustainable Computing and Optimization

Trends and Future Challenges

Managing Sustainable Operations of Logistics and Supply Chain Management

Springer Series in Optical Sciences

This book provides a comprehensive overview of the latest achievements in the field of optical fiber lasers, covering the basics, technology, and numerous applications. Optical fiber lasers are key in a variety of scientific, military, medical, industrial, and commercial spheres, and therefore have undergone rapid innovation. Each chapter highlights a novel development in refining fiber laser features such as the output lasing wavelength, output power, nature of the laser beam, nature of the output laser pulse, design of lasing cavity, and design of fiber structure. These improvements are then applied to a wide variety of lasers, including Raman fiber lasers, gas-filled fiber lasers, rare-earth doped fiber lasers, and more. This book also sheds light on the rise in AI-enabled fiber laser systems in industrial manufacturing. The in-depth coverage of the latest developments in various kinds of optical fiber laser technology ensure this volume will serve as a valuable resource for graduate students, engineers, and scientists both experienced and new to the field.

Recent Advances and Applications

Optical Fiber Lasers

Dynamics and Astrophysics of Galaxies

Studies in National Governance and Emerging Technologies

This book examines how artificial intelligence systems and their applications in security and defence are entangled with governance and policy processes in the EU. Combining concepts and insights from (critical) security studies and science and technology studies, it argues that behind the various AI-related policy initiatives in the EU are particular narratives on security and defence based on European fears of technological innovation and strategic gaps. In this respect, the book casts light on how such beliefs have become increasingly instrumentalized in the European governance dynamics, and subsequently embedded in successive policy initiatives and security and defence research programmes. It challenges conventional understandings of AI technologies as mere security and defence-enabling instruments, by providing a conceptually driven analysis of how certain visions of AI help govern and control one of the most dynamic emergent socio-technical fields. The book will appeal to all those interested in artificial intelligence, security studies, technology and European governance.&nbsp; Raluca Csernatoni is a Research Fellow at Carnegie Europe, where she works on the nexus between European defence and emerging technologies. She is also Guest Professor at the Centre for Security, Diplomacy and Strategy (CSDS), Vrije Universiteit Brussel, Belgium, and Visiting Faculty in the Department of International Relations, Central European University, Austria.

Artificial Security and the Politics of Hype in the EU

Progress In Data Science

Ubiquitous Laplacian: An Introduction To Numerical Pdes With Applications In Data Science

This book analyses Artificial Intelligence (AI) and its impact on sustainability, ethics, security, and society. It provides actionable strategies for eco-friendly AI, navigating legal frameworks, and implementing ethical practices. It examines security challenges from AI misuse, outlining necessary cybersecurity enhancements. Real-world case studies bridge theory and practice. Guidance is provided for aligning AI adoption with societal and environmental goals, promoting responsible AI development for a sustainable future. This comprehensive study of AI begins by looking at AI's role in environmental sustainability, providing actionable strategies for eco-friendly AI development and deployment. This includes understanding the complex relationship between AI and the environment to minimize its footprint and promote AI solutions that contribute to environmental goals. The authors extend into insightful discussion on navigating the intricate legal frameworks and implementing ethical AI practices. This guidance reduces the risk of legal challenges and reputational damage, leading to increased trust and responsible AI development and use. Bridging the gap between theory and practice is another important feature in this book. With real-world case studies, the reader gains practical understanding of how AI is being used in different contexts. This further enhances the accelerated adoption and increased innovation of AI solutions in different fields. This book provides a clear roadmap for responsible and sustainable AI integration, aligning AI initiatives with broader societal objectives.The primary audience for this book includes business leaders, professionals, policymakers, technologists and AI practitioners.

The Blueprint for AI Adoption and Societal Transformation

Oxford Graduate Texts in Mathematics

Graphs and Homomorphisms

This will be the 7th book in the author's 'Lectures on ...' book series, and the first aimed at graduate-level readers(two additional graduate texts are in preparation). Primarily intended for physics graduate students, the book is accessible to advanced undergraduates and will appeal to students with a background in statistics and a keen interest in quantum physics. By the end of this book, readers will be well-prepared for working on research projects that require the drawing of inference from the noisy data collected in quantum experiments, as epitomized by quantum state estimation.The book begins with chapters on the basics of estimation theory and the basics of quantum theory. This includes, in particular, the roles played by the frequentist methods of statistics, which are crucial when planning an experiment, and the Bayesian methods, which are the tools for drawing inference from the actual data gathered. A central concept is that of optimal error regions that supplement the point estimators ('best guesses') with the analogs of error bars in the high-dimensional parameter space; there is, in particular, the plausible region which comprises all point estimators supported by the data.Practical applications require the evaluation of high-dimensional integrals with the aid of Monte Carlo integration. For that, one needs to draw samples of quantum states from the relevant distributions, namely the priors and posteriors of Bayesian methodology. The book discusses the algorithms well-suited for this kind of sampling, which is central to the processing of real-life data.The book illustrates all concepts with pertinent examples and offers numerous exerciseswhich the readers can practice and perfect their skills with. The presentation is detailed and does not skip technical steps, which makes the book particularly valuable for self-studying readers and as textbook adopted by lecturers teaching courses on this or related topics. While the book is based on lecture notes developed for the author's courses on quantum state estimation at NUS and BIT, this book also offers a comprehensive account of the concepts and methods developed in the author's group at CQT and presents this material in textbook form for the first time.

The Nature of Complex Networks

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