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Gesamtkatalog

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This book is the first comprehensive study of fault-tolerance and fault-caused deadlock effects in asynchronous on-chip networks, aiming to overcome these drawbacks and ensure greater reliability of applications.

Song Wei: Asynchronous On-Chip Networks
and Fault-Tolerant Techniques

Asynchronous On-Chip Networks and Fault-Tolerant Techniques

1. Introduction, 2. Asynchronous Circuits, 3. Asynchronous Networks-on-Chip, 4. Optimizing Asynchronous On-Chip Networks, 5. Fault-Tolerant Asynchronous Circuits, 6. Fault-Tolerant Coding, 7. Deadlock Detection, 8. Deadlock Recovery, 9. Summary

The Linux Memory Manager

Wendepunkte in der Analogen und Digitalen Welt

Machine Learning For Dummies

Data-Driven Modeling

Advances in Learning Analytics for Intelligent Cloud-IoT Systems

Intrusion Detection Paradigm for Cloud-IoT Environments

Micro & Nano Technologies

The advances in microsystems offer new opportunities and capabilities to develop systems for biomedical applications, such as diagnostics and therapy. In its third edition, Microsystems for Bioelectronics offers a comprehensive treatment of microsystems by thoroughly covering basic physics, chemistry, biology, materials, and engineering concepts, with an emphasis on the performance limits associated with the shrinking scale of microsystems. Microsystems for Bioelectronics: Scaling and Performance Limits considers physical principles and trends in extremely scaled autonomous microsystems such as integrated intelligent sensor systems, with a focus on energy minimization. It explores the implications of energy minimization on device and system architecture. It further details behavior of electronic components and its implications on system-level scaling and performance limits. In particular, fundamental scaling limits for energy sourcing, sensing, memory, computation and communication subsystems are developed and new applications such as optical, magnetic and mechanical sensors are presented. This fully revised and updated edition includes information on DRAM and 3D NAND semiconductor memories, betavoltaic energy conversion, advanced packaging, recent technology trends, and new technology roadmaps. The new edition of this well-proven book with its unique focus and interdisciplinary approach shows the complexities of the next generation of nanoelectronic microsystems in a clear and easy-to-understand manner, and is aimed for a broad audience within several disciplines.

Scaling and Performance Limits

Microsystems for Bioelectronics

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

Powered by Hyperscale Computing and Next Generation Networks

AI-Driven Smart Healthcare

Distributed Computing and Intelligent Data Analytics

Comprehensive insights into value engineering principles tailored for electrical systems in construction with real-world examples included throughout Value Engineering for Electrical Systems in Construction is a comprehensive guide that provides practical tools and methodologies to apply value engineering (VE) principles across the full lifecycle of electrical systems-from early-stage concept design to execution and retrofit. The book features detailed case studies, examples, templates, and checklists that serve both value engineering initiatives and best design practices. Written by a highly qualified author with extensive experience leading diverse international construction projects, Value Engineering for Electrical Systems in Construction covers: <ul> <li>Strategies and techniques for value engineering projects in electrical works, focusing on efficiency and innovation</li> <li>Structured value engineering framework tailored specifically to electrical systems</li> <li>Applications for both new-build and retrofit contexts</li> <li>Guidance across MV/LV power distribution, lighting, ELV, ICT, emergency systems, earthing, external infrastructure, BIM integration, and cross-disciplinary coordination</li> <li>Professional guidance and best practices to implement VE concepts effectively</li> <li>Comprehensive collection of custom-developed VE checklists, decision matrices, and evaluation tools</li> <li>Common challenges in electrical engineering and construction, with actionable solutions</li> <li>Application of VE principles with focus on regulatory compliance, lifecycle costs, and performance optimization</li> </ul> Value Engineering for Electrical Systems in Construction is an essential reference for professionals involved in designing, implementing, and managing electrical systems in construction projects, including electrical engineers, MEP engineers, project managers, architects, construction managers, cost engineers, and estimators/quantity surveyors.

Value Engineering for Electrical Systems in Construction

Up-to-date reference enabling readers to address the full spectrum of AI security challenges while maintaining model utility Generative AI Security: Defense, Threats, and Vulnerabilities delivers a technical framework for securing generative AI systems, building on established standards while focusing specifically on emerging threats to large language models and other generative AI systems. Moving beyond treating AI security as a dual-use technology, this book provides detailed technical analysis of three critical dimensions: implementing AI-powered security tools, defending against AI-enhanced attacks, and protecting AI systems from compromise through attacks like prompt injection, model poisoning, and data extraction. The book provides concrete technical implementations supported by real-world case studies of actual AI system compromises, examining documented cases like the DeepSeek breaches, Llama vulnerabilities, and Google's CaMeL security defenses to demonstrate attack methodologies and defense strategies while emphasizing foundational security principles that remain relevant despite technological shifts. Each chapter progresses from theoreticalfoundations to practical applications. The book also includes an implementation guide and hands-on exercises focusing on specific vulnerabilities in generative AI architectures, security control implementation, and compliance frameworks. Generative AI Security: Defense, Threats, and Vulnerabilities discusses topics including: <ul> <li>Machine learning fundamentals, including supervised, unsupervised, and reinforcement learning and feature engineering and selection</li> <li>Intelligent Security Information and Event Management (SIEM), covering AI-enhanced log analysis, predictive vulnerability assessment, and automated patch generation</li> <li>Deepfakes and synthetic media, covering image and video manipulation, voice cloning, audio deepfakes, and AI's greater impact on information integrity</li> <li>Security attacks on generative AI, including jailbreaking, adversarial, backdoor, and data poisoning attacks</li> <li>Privacy-preserving AI techniques including federated learning and homomorphic encryption</li> </ul> Generative AI Security: Defense, Threats, and Vulnerabilities is an essential resource for cybersecurity professionals and architects, engineers, IT professionals, and organization leaders seeking integrated strategies that address the full spectrum of Generative AI security challenges while maintaining model utility.

Triangulating AI Security

Methods, Applications, and Implications

Adaptive AI in Sensor Informatics

Asynchronous On-Chip Networks and Fault-Tolerant Techniques

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