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Gesamtkatalog

Catalogue complet

Assistive Robotics

Modeling, Computation, and Realization

Chapter 1. Data-Driven Approaches to Real-Time Constrained Tracking Control of Redundant Manipulators. Chapter 2. Mastering Control: A Haptic Robotic Arm with Intuitive Joystick Control and Programmable Sequences. Chapter 3. Visual Saliency under Uncertain Workspace of Assistive Robots. Chapter 4. Engineering a Better Walk: Concepts of Gait Analysis for Development of Rehabilitative Exoskeleton. Chapter 5. Construction and Control of a Cable-Driven Gait Assistance Exosuit Based on Kinematic Synergies. Chapter 6. Assistive Telerobotics and Intuitive Interaction. Chapter 7. An automated Framework based on UAV and Convolutional Neural Networks for the Detection of Xylella Fastidiosa Disease in Olive Trees. Chapter 8. A State-of-the-Art Review on Garbage Collection and Segregation Robot. Chapter 9. Forward and Inverse Problems Relating to an Assistive Robotic Manipulator in an Uncertain Environment. Chapter 10. Development of Intelligent Control Systems for Assistive Robots. Chapter 11. Depth Estimation and 3D Mapping of Navigable Indoor Environments for Assistive Robots. Chapter 12. Positional Control of a 3D Printed Indigenous 6 DoF Feeding Robotic Arm using ANFIS and Fuzzy-PID Controller. Chapter 13. Control Issues in Haptic Robot Navigation and Object/Obstacle Recognition Using a Flexible Sensing Antenna. Chapter 14. Flexible Link Lumped Masses Manipulators: Modeling and Control. Chapter 15. Robotic Grasp Prehension: Novel Design Metrics for Assistive Systems using Compliance. Chapter 16. Modelling and Mapping of an Autonomous Assistive Robot for Material Handling in Dynamic Indoor Environments. Chapter 17. Synthesis of Sensor-Assisted Robotic Grasp using Customized Graphical User Interface

My Journey and the Future of Energy

Inexhaustible

Embedded System and GUI Development using MATLAB for Engineering Applications

This book is a comprehensive guide that immerses you into the world of building and deploying AI-powered solutions. You are introduced to the core architecture of LLMs and equipped with essential Best Data Practices (BDPs) for utilizing Generative AI responsibly, ensuring ethical and efficient AI deployment.The book starts with the foundational aspects of Generative AI application development. You will learn the nuances of data handling in Generative AI apps, from working with embeddings to managing unstructured and structured data, and handling Personally Identifiable Information (PII) data. The exploration extends to understanding the differences between deterministic and LLM-based data synthesis and integrating Generative AI apps with enterprise data, providing you with practical insights into leveraging data effectively for intelligent applications. A chapter on prompt engineering explains the importance of prompts in AI interactions, covering a spectrum of techniques and pitfalls while offering exercises to enhance prompt engineering skills. As you progress through the book, you take a journey from conceptualization to production and deployment of Generative AI applications. You discover the essentials of Generative AI application development, gain insights into the pathway from ideation to production, and explore the intricacies of LLM selection and fine-tuning.The book equips you with the knowledge and tools necessary to navigate the complex terrain of AI development and deployment, making it an indispensable resource for AI enthusiasts, developers, and business leaders alike.What You Will Learn<ul><li>Know the core architecture of LLMs and how these models have revolutionized AI applications</li><li>Handle various data types, including unstructured, structured, and personally identifiable information (PII) data in Generative AI applications</li><li>Understand prompt engineering and its importance in AI interactions and applications</li><li>Understand modular design of Generative AI apps, essential backend and frontend components, and the unique principles guiding Generative AI app design</li></ul>&nbsp;&nbsp;

Building and Deploying Ethical AI-Powered Solutions

Practical Generative AI: From Concept to Deployment

Harnessing the Power of AI for Your Organization—Profitably and Safely

The AI Conundrum

Human Machine Integration in Industry 5.0

Digital Twin and Digital Triplet Technologies

Enhancing Reflective Teaching in Higher Education

Redefining Teaching and Learning

GenAI in Higher Education

Praise for IRREPLACEABLE "If you think AI is just about robots and algorithms, think again. IRREPLACEABLE will shatter your assumptions and challenge you to reimagine what it means to be human in a machine age." -Dr. Marshall Goldsmith, Thinkers50 #1 Executive Coach and New York Times Bestselling Author of The Earned Life, Triggers, and What Got You Here Won't Get You There "IRREPLACEABLE is addressing the most important question of our time: how do we keep our humanity front and center in an AI-dominated world? I challenge you to find a book more timely and relevant!" -Klaus Schwab, Founder and Executive Chairman of the World Economic Forum "IRREPLACEABLE is a vital guide to thinking differently and working confidently in tandem with AI. Pascal Bornet's insights and strategies are essential to succeed with customers and colleagues, in your community and career." -Ron Kaufman, New York Times Bestselling Author of Uplifting Service "In a world obsessed with the power of AI, IRREPLACEABLE dares to ask the question: what makes us human? The answer may surprise you." -Dr. Luc Julia, Co-Founder of Apple Siri "One of the most important books of our times, Pascal Bornet's IRREPLACEABLE is a must-read guide for navigating the AI revolution, empowering readers to excel personally and professionally in a technology-driven world." -Bernard Marr, Futurist, Internationally Bestselling Author "A very practical guide to strengthening our humanity with AI." -Nir Eyal, Bestselling Author of Hooked and Indistractable "Both a wake-up call and a practical guide to rediscover what makes us truly human in the age of AI." -Gerd Leonhard, Futurist and Humanist "I've always believed that AI will enhance human capabilities rather than replace them. This excellent book provides a roadmap for individuals and organizations to become effective partners with smart machines. Follow its advice, and you'll be well-equipped for the present and the future." -Thomas H. Davenport, Distinguished Professor, Babson College; Author of Only Humans Need Apply, Working with AI, and All In on AI "IRREPLACEABLE challenges us to confront the ultimate dilemmas: who are we, and what is our purpose in a world transformed by AI? The answers may just change your life." -Professor Jochen Wirtz, Vice Dean MBA Programmes, National University of Singapore "IRREPLACEABLE forces us to question our future in an increasingly technologically mediated world and learn to take action!" -Leonard A. Schlesinger, Baker Foundation Professor, Harvard Business School

The Art of Standing Out in the Age of Artificial Intelligence

IRREPLACEABLE

A Path to Sustainable Development Goals

AI and ML Techniques in IoT-based Communication

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

Advances in Industrial and Systems Engineering

Advances in Human-AI Collaboration

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

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

Assistive Robotics

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