Advancing Cybersecurity In Smart Factories Through Autonomous Robotic Defenses
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Advancing Cybersecurity in Smart Factories Through Autonomous Robotic Defenses
As industrial automation increasingly relies on artificial intelligence (AI) to drive robotic and drone technologies, the need to secure these systems against sophisticated cyber threats has become paramount. By exploring the cybersecurity challenges and solutions for AI-powered industrial systems, AI has become key for advancing real-time threat detection and adversarial machine learning attacks. The implementations of secure AI-driven robotics and drones reach various industrial sectors such as manufacturing, energy, logistics, and agriculture. AI is transforming industrial automation and, at the same time, exposing these systems to new vulnerabilities. Advancing Cybersecurity in Smart Factories Through Autonomous Robotic Defenses bridges the gap between the technical aspects of AI, industrial automation, and the evolving landscape of cybersecurity. This book provides readers with insight into the most recent advancements in AI-powered security tools, explore ethical and regulatory considerations, and learn practical strategies to protect complex systems from cyberattacks. Covering topics such as smart factories, wearable devices, and drone systems, this book is an excellent resource for cybersecurity professionals, computer engineers, industrial engineers, policymakers, policy regulators, professionals, researchers, scholars, academicians, and more.
Applied Linear Algebra
"Applied Linear Algebra: Core Principles" is a comprehensive guide that delves into the principles, methodologies, and practical applications of linear algebra in various fields of science, engineering, and technology. Combining theoretical foundations, computational techniques, and real-world examples, this book offers a holistic approach to understanding and utilizing linear algebra concepts. Covering a wide range of topics, including vector spaces, matrices, eigenvalue problems, singular value decomposition, and numerical techniques, readers will gain a thorough understanding of both fundamental and advanced principles. Real-world applications in data science, machine learning, signal processing, control systems, and image processing are integrated throughout, demonstrating the practical relevance of linear algebra. Complex mathematical concepts are presented in a clear and accessible manner, making the book suitable for students, researchers, and practitioners with varying levels of mathematical background. Detailed explanations, illustrative examples, and step-by-step solutions aid comprehension and retention. An interdisciplinary approach connects theoretical concepts with practical applications, highlighting the versatility of linear algebra in solving real-world problems. Extensive references to literature, research papers, and online resources enable readers to explore topics in greater depth. This book is an invaluable resource for students, researchers, and professionals seeking to apply linear algebra techniques in their work across various domains.
Transactions on Intelligent Welding Manufacturing
The primary aim of this volume is to provide researchers and engineers from both academia and industry with up-to-date coverage of recent advances in the fields of robotic welding, intelligent systems and automation. It gathers selected papers from the 2017 International Workshop on Intelligentized Welding Manufacturing (IWIWM’2017), held June 23-26, 2017 in Shanghai, China. The contributions reveal how intelligentized welding manufacturing (IWM) is becoming an inescapable trend, just as intelligentized robotic welding is becoming a key technology. The volume is divided into four main parts: Intelligent Techniques for Robotic Welding, Sensing in Arc Welding Processing, Modeling and Intelligent Control of Welding Processing, and Intelligent Control and its Applications in Engineering.