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Gesamtkatalog

Catalogue complet

Hamada J: Psychophysics and Experimental
Phenomenology of Pattern Cognition

Psychophysics and Experimental Phenomenology of Pattern Cognition

Stories of Mending the Broken Brain

How to Use a Fork

Medical Robots and Devices: New Developments and Advances

AI and Data Science in Medical Research focuses on the integration of AI and data science into medical research, highlighting their impact on drug discovery, medical imaging, diagnostics, and genomic medicine. The book addresses the acceleration of therapeutic compound discovery and optimization of drug development pipelines through AI. The volume also discusses advancements in medical imaging, including early disease detection and neuroimaging. Additionally, it covers the application of AI in genomic medicine, offering insights into personalized treatment strategies. The volume concludes with an examination of AI's role in public health surveillance, particularly in disease detection and epidemiological research.

AI and Data Science in Medical Research

Psychology Library Editions: Aggression

Perspectives on Aggression and Violence

Accounting for Aggression

Creativity in the Age of AI

What Art Is Now

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

This book reviews the potential of natural products in the treatment and management of neurodegenerative disorders. The introductory chapter provides fundamental insights into neurodegenerative disorders. Subsequently, the book covers the therapeutic potential of polyphenols and other agents for Amyotrophic Lateral Sclerosis, the application of natural ingredients for Friedreich ataxia, and the combined effects of natural ingredients in addressing Huntington's disease. The book also explores conventional therapeutic regimens for Lewy body disease and examines the synergistic effects of both natural and synthetic agents. Furthermore, the chapters discuss the utilization of natural extracts in the management of spinal muscular atrophy while examining broader synthetic management approaches. The second section of the book explores nanodelivery systems for managing neurodegenerative disorders. It discusses synergistic treatment approaches, followed by an analysis of advanced techniques such as electron spinning and electron spraying and their application in neurodegenerative disorders. The book also reviews the therapeutic potential of flavonoids in managing neurodegenerative disorders. Towards the end, the book also examines the ethical framework of natural remedies used in the treatment of neurodegenerative disorders. This book is intended for neuroscientists and researchers in the fields of neurology, pharmacology, and nanotechnology. Seasonal blurb This book explores the potential of natural products in the treatment and management of neurodegenerative disorders. It reviews the role of polyphenols for Amyotrophic Lateral Sclerosis, natural ingredients for Friedreich ataxia, and Huntington's disease. The book also examines conventional treatments for Lewy body disease and spinal muscular atrophy and the synergy of natural and synthetic agents. The book presents nanodelivery systems, synergistic treatments, and reviews the ethical framework for the utilization of natural remedies in treating neurodegenerative disorders. This book is a valuable resource for neuroscientists and researchers in neurology, pharmacology, and nanotechnology. Short blurb This book explores the potential of natural products and nanodelivery systems in the treatment and management of neurodegenerative disorders. It also reviews the ethical framework for the utilization of natural remedies in treating neurodegenerative disorders. It is a valuable source for researchers in neurology, pharmacology, and nanotechnology.

Therapeutic Potential of Natural Products in Neurodegenerative Disorders

AI and Data Science in Precision Medicine, Predictive Analytics, and Medical Practice explores the transformative role of AI and data science in enhancing precision medicine, predictive analytics, and medical practice. The book covers diverse topics such as AI-driven personalized medicine, seizure prediction through EEG analysis, and the application of chaos theory in AI-driven healthcare. The volume also delves into medical practice and education, including ethical considerations, AI-driven supply chain management, and clinical documentation using natural language processing. Furthermore, it examines AI's role in telemedicine, patient engagement, and adherence, offering innovative solutions to improve healthcare delivery and outcomes.

AI and Data Science in Precision Medicine, Predictive Analytics, and Medical Practice

Embedded System and GUI Development using MATLAB for Engineering Applications

Enhancing Reflective Teaching in Higher Education

Redefining Teaching and Learning

GenAI in Higher Education

Connected Diagnoses: IoT, Healthcare, and Digital Forensics investigates the complex intersection of IoT, healthcare, and digital forensics. This book explores the intricate relationships between these fields, with a focus on cybersecurity, patient data ethics, and challenges in IoT investigations. This book advances knowledge on leveraging IoT securely to enhance patient care and digital forensic analysis, providing significant insights from experts along with practical guidance for those operating at the crossroads of these critical disciplines. The book helps professionals grasp, adapt to, and capitalize on the interconnected nature of emerging technologies to ensure ethics, security, and safety. It is a comprehensive resource that benefits researchers and practitioners seeking to understand the convergence of medical technology, interconnected devices, and digital forensics.

IoT, Healthcare, and Digital Forensics

Connected Diagnoses

A comprehensive, up-to-date introduction to active inference and the free energy principle for an engineering-focused audience. Active inference, which uses machine learning to model brain function and behavior, emerged from decades of cross-disciplinary research in computational neuroscience, resulting in a vast literature but no unifying treatment. Filling this gap, Sanjeev Namjoshi provides comprehensive coverage of the foundational material needed to understand and navigate this fast-moving field from first principles. Using a simple, conversational style free of proofs, lemmas, and theorems, Namjoshi brings together theory and technical material in one self-contained text. The book begins with an explanation of the general statistical framework used in active inference models that describes the relationship between artificial agents and their environments. It then introduces fundamental concepts in machine learning and statistics and connects them to the active inference perspective. Featuring worked examples, simulations, and detailed walkthroughs of concepts, this user-friendly text aims to expand the readership of active inference to an engineering-focused audience.&nbsp; <ul><li>Provides a one-stop-shop for understanding the foundations and applications of active inference and the free energy principle </li><li>Makes a complex, interdisciplinary subject accessible to students and professionals beyond the neurosciences</li><li>Covers discrete and continuous state-space formulations of active inference as well as state-of-the-art extensions to base active inference methods</li><li>Features extensive appendices and supplemental resources</li></ul>

Principles, Algorithms, and Applications of the Free Energy Principle for Engineers

Fundamentals of Active Inference

Six Dimensions of Business Dark Data

Agentic Hyper-Personalized Dimensions

Psychophysics and Experimental Phenomenology of Pattern Cognition

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