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Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

Advanced Technologies in Electronics,
Communications and Signal Processing

Advanced Technologies in Electronics, Communications and Signal Processing

First EAI International Conference, ICATECS 2024, Hyderabad, India, July 26–27, 2024, Proceedings, Part I

Ninth EAI International Conference, SmartGift 2024, Hong Kong, China, December 9–10, 2024, Proceedings

Smart Grid and Innovative Frontiers in Telecommunications

5th EAI International Conference, HealthWear 2024, Isparta, Turkey, December 2–3, 2024, Proceedings

IoT Technologies and Wearables for HealthCare

20th EAI International Conference, SecureComm 2024, Dubai, United Arab Emirates, October 28–30, 2024, Proceedings, Part III

Security and Privacy in Communication Networks

First EAI International Conference, ICATECS 2024, Hyderabad, India, July 26–27, 2024, Proceedings, Part II

Second EAI International Conference, SmartSP 2024, New Orleans, LA, USA, November 7–8, 2024, Proceedings

Security and Privacy in Cyber-Physical Systems and Smart Vehicles

Third Pan-African Conference, PAAISS 2024, Durban, South Africa, December 4–6, 2024, Proceedings, Part II

Pan-African Artificial Intelligence and Smart Systems

20th EAI International Conference, CollaborateCom 2024, Wuzhen, China, November 14–17, 2024, Proceedings, Part I

Collaborative Computing: Networking, Applications and Worksharing

20th EAI International Conference, SecureComm 2024, Dubai, United Arab Emirates, October 28–30, 2024, Proceedings, Part I

8th EAI International Conference, SGIoT 2024, Taichung, Taiwan, November 23–24, 2024, Proceedings

Smart Grid and Internet of Things

20th EAI International Conference, CollaborateCom 2024, Wuzhen, China, November 14–17, 2024, Proceedings, Part II

Third Pan-African Conference, PAAISS 2024, Durban, South Africa, December 4–6, 2024, Proceedings, Part I

7th EAI International Conference, 6GN 2024, Chongqing, China, October 19–20, 2024, Proceedings

6GN for Future Wireless Networks

A no-fluff guide to implementing best security practices for microservices in the cloud written by a team of experienced security engineers at Snapchat. This book takes you through every step of secure software development and deployment for microservices – the discrete functions within a larger application. Readers begin by exploring core security tenets, then dive into developing microservices and securing infrastructure. Along the way, they’ll gain the skills to think like a security engineer at scale and effectively plan secure designs. Each chapter provides step-by-step explanations of vital concepts, practical examples, mistakes to look out for, and quizzes to test the reader’s knowledge. Whether you’re a one-person security team or a larger group, this book equips you with the skills to build a full-fledged microservices security discipline.

Securing Cloud Native Apps

This book is the first one that shows how to accurately and efficiently solve time-varying problems in real-time or online using continuous- or discrete-time zeroing dynamics. The authors provide a comprehensive treatment of the theory of both static and dynamic neural networks. They develop, analyze, model, simulate, and compare zeroing dynamics models for the online solution of numerous time-varying problems, such as root finding, nonlinear equation solving, matrix inversion, matrix square root finding, quadratic optimization, and inequality solving.

Zeroing Dynamics, Gradient Dynamics, and Newton Iterations

Environmental Monitoring Using Artificial Intelligence is a vital resource for anyone looking to leverage cutting-edge technologies in artificial intelligence and sensor systems to effectively address environmental challenges, offering innovative solutions and insights essential for creating a sustainable future. Environmental Monitoring Using Artificial Intelligence provides a comprehensive exploration of the cutting-edge technologies transforming environmental monitoring. This book bridges the gap between artificial intelligence (AI), natural language processing (NLP), and sensor-based systems, highlighting their potential to revolutionize the way we address pressing environmental challenges. Each chapter presents innovative case studies, real-world applications, and the latest research on how these technologies are being utilized to monitor and manage ecosystems, water resources, air quality, and urban sustainability. From advanced sensor networks to machine learning models, this book covers a broad spectrum of topics, including smart water solutions, biodiversity conservation, waste management, and agricultural sustainability. It offers an interdisciplinary approach, making it an essential resource for environmental engineers, data scientists, researchers, and policymakers. Whether you're exploring smart city innovations, renewable energy monitoring, or AI-driven solutions for environmental protection, Environmental Monitoring Using Artificial Intelligence equips readers with the knowledge and tools to leverage technology for a sustainable future.

Environmental Monitoring Using Artificial Intelligence

Analytics and AI for Healthcare

This book centres on the topic of digital twins for superior healthcare decision support, as access is enabled to large volumes of multi-dimensional data such as patient's electronic medical records, medical scans, and data.

For Superior Clinical Decision Making

Digital Twins

Intelligent automation is widely considered to have the greatest potential for Industry 4.0 innovations for corporations. Industrial machinery is increasingly being upgraded to intelligent machines that can perceive, act, evolve, and interact in an industrial environment. The innovative technologies featured in this machinery include the Internet of Things, cyber-physical systems, and artificial intelligence. Artificial intelligence enables computer systems to learn from experience, adapt to new input data, and perform intelligent tasks. The significance of AI is not found in its computational models, but in how humans can use them. Consistently observing equipment to keep it from malfunctioning is the procedure of predictive maintenance. Predictive maintenance includes a periodic maintenance schedule and anticipates equipment failure rather than responding to equipment problems. Currently, the industry is struggling to adopt a viable and trustworthy predictive maintenance plan for machinery. The goal of predictive maintenance is to reduce the amount of unanticipated downtime that a machine experiences due to a failure in a highly automated manufacturing line. In recent years, manufacturing across the globe has increasingly embraced the Industry 4.0 concept. Greater solutions than those offered by conventional maintenance are promised by machine learning, revealing precisely how AI and machine learning-based models are growing more prevalent in numerous industries for intelligent performance and greater productivity. Artificial and Machine Learning for Industry 4.0 emphasizes technological developments that could have great influence on an industrial revolution and introduces the fundamental technologies responsible for directing the development of innovative firms. Decision-making requires a vast intake of data and customization in the manufacturing process, which managers and machines both deal with on a regular basis. One of the biggest issues in this field is the capacity to foresee when maintenance of assets is necessary. Leaders in the sector will have to make careful decisions about how, when, and where to employ these technologies. Artificial and Machine Learning for Industry 4.0 offers contemporary technological advancements in AI and machine learning from an Industry 4.0 perspective, looking at their prospects, obstacles, and potential applications.

Artificial Intelligence and Machine Learning for Industry 4.0

Develop AI solutions and projects that create real and effective business value with this guide to leading a successful enterprise AI program.

Optimize AI Teams for Value Creation

Leading Enterprise AI Programs

Springer Handbooks of Computational Statistics

Handbook of Blockchain Analytics

Integration of Federated Learning and Blockchain f or Smart Cities

Encyclopedia of Optimization

Medical Robots and Devices: New Developments and Advances

Medical Imaging Application in Health Assessment and Disease Management is an all-encompassing book that explores the transformative power of medical imaging in various fields of medicine. It showcases the latest advancements and applications of medical imaging modalities, ranging from neurology and oncology to audiology and osteoporosis. The book highlights the role of medical imaging in understanding and treating neurological conditions, assessing bone health, unraveling hearing disorders, and diagnosing and treating oncological conditions. It also delves into the potential of artificial intelligence and machine learning in improving cancer diagnosis and treatment. The book explores the use of medical imaging in observing mental health conditions such as autism spectrum disorder and stress-related behavioral changes. This comprehensive resource is essential for researchers and professional engineers in the fields of medical image computing/processing, computer science, artificial intelligence, radiology, neuroscience, and biomedical research.

Medical Imaging Application in Health Assessment and Disease Management

Learn how to manage the risks and opportunities of agentic AI with this practical guide to ensuring the safe and beneficial developments of advanced AI systems.

Principles and Responsible Practices

Safer Agentic AI

Use AI to Protect Your Organization

Artificial Intelligence in Cybersecurity

Advanced Technologies in Electronics, Communications and Signal ...

Informations bibliographiques

Mots-clés

Informations bibliographiques

Mots-clés

Autres titres de la collection: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

Autres titres sur ce thème