Xu Chen – författare

INTELLIGENT IOT FOR THE DIGITAL WORLD DISCOVER HOW THE INTELLIGENT INTERNET OF THINGS WILL CHANGE THE INFORMATION AND COMMUNICATION TECHNOLOGY INDUSTRY IN THE NEXT DECADE In the digital world, most data and Internet of Things (IoT) services need to be efficiently processed and executed by intelligent algorithms using local or regional computing resources, thus greatly saving and reducing communication bandwidth, end-to-end service delay, long-distance data transmissions, and potential privacy breaches. This book proposes a pyramid model, where data, computing and algorithm jointly constitute the triangular base to support a variety of user-centric intelligent IoT services at the spire by using different kinds of smart terminals or devices.This book provides a state-of-the-art review of intelligent IoT technologies and applications, discusses the key challenges and opportunities facing the digital world, and answers the following five critical questions:What is the most feasible network architecture to effectively provide sufficient resources anywhere anytime for intelligent IoT application scenarios?How do we efficiently discover, allocate and manage computing, communication and caching resources in heterogeneous networks across multiple domains and operators?How do we agilely achieve adaptive service orchestration and reliable service provisioning to meet dynamic user requirements in real time?How do we effectively protect data privacy in IoT applications, where IoT devices and edge/fog computing nodes only have limited resources and capabilities?How do we continuously guarantee and maintain the synchronization and reliability of wide-area IoT systems and applications?Written for professionals working in 5G/IoT technology development, service management and big data analytics, this book offers an overview of intelligent IoT service architecture, key technologies, important applications and future technological trends.

Explore the benefits and applications of foodborne bioactive peptides Food-Derived Bioactive Peptides: Green Preparation, Activity Mechanisms, and Health Applications explains the uses and benefits of bioactive peptides derived from food sources. Authored by leading researchers at Fuzhou University with extensive expertise in functional foods and biotechnology, this book provides food scientists and industry professionals with detailed insights into these health-promoting compounds. It systematically covers their sources, preparation methods, activity evaluation, functional mechanisms, and practical applications. The book explores nine major peptide classifications including antifreeze, antioxidant, antimicrobial, metal chelate, anti-ageing, anti-fatigue, immune regulatory, flavor, and self-assembling peptides. Each chapter thoroughly covers sources, evaluation methods, mechanisms, security assessment, applications, and limitations. A final chapter examines AI integration in functional peptides research, demonstrating how machine learning revolutionizes peptide discovery and bioactivity prediction. The book includes: Comprehensive coverage of preparation methods including enzymatic hydrolysis, fermentation, and biotechnological approaches for generating bioactive peptides from food sourcesDetailed examination of nine major peptide classifications with consistent coverage of sources, mechanisms, applications, security assessment, and limitationsCutting-edge integration of artificial intelligence and machine learning applications for peptide discovery, bioactivity prediction, and preparation optimizationPractical guidance on activity evaluation methodologies and functional mechanism analysis for each bioactive peptide categoryReal-world applications across food preservation, nutraceutical development, functional materials, and health-promoting food ingredient formulation strategiesThis book serves as an essential resource for food scientists, biotechnologists, nutritional biochemists, and R&D professionals working in functional food and nutraceutical industries. It combines rigorous academic foundations with practical guidance for developing innovative health-promoting products and advancing sustainable food applications.

With the explosive growth of mobile computing and Internet of Things (IoT) applications, as exemplified by AR/VR, smart city, and video/audio surveillance, billions of mobile and IoT devices are being connected to the Internet, generating zillions of bytes of data at the network edge. Driven by this trend, there is an urgent need to push the frontiers of artificial intelligence (AI) to the network edge to fully unleash the potential of IoT big data. Indeed, the marriage of edge computing and AI has resulted in innovative solutions, namely edge intelligence or edge AI. Nevertheless, research and practice on this emerging inter-disciplinary field is still in its infancy stage. To facilitate the dissemination of the recent advances in edge intelligence in both academia and industry, this book conducts a comprehensive and detailed survey of the recent research efforts and also showcases the authors' own research progress on edge intelligence. Specifically, the book first reviewsthe background and present motivation for AI running at the network edge. Next, it provides an overview of the overarching architectures, frameworks, and emerging key technologies for deep learning models toward training/inference at the network edge. To illustrate the research problems for edge intelligence, the book also showcases four of the authors' own research projects on edge intelligence, ranging from rigorous theoretical analysis to studies based on realistic implementation. Finally, it discusses the applications, marketplace, and future research opportunities of edge intelligence. This emerging interdisciplinary field offers many open problems and yet also tremendous opportunities, and this book only touches the tip of iceberg. Hopefully, this book will elicit escalating attention, stimulate fruitful discussions, and open new directions on edge intelligence.

This book conducts a comprehensive and detailed survey of the recent research efforts in edge intelligence. To illustrate the research problems for edge intelligence, the book also showcases four of the authors' own research projects on edge intelligence, ranging from rigorous theoretical analysis to studies based on realistic implementation.

This SpringerBrief explains how to leverage mobile users' social relationships to improve the interactions of mobile devices in mobile networks. It develops a social group utility maximization (SGUM) framework that captures diverse social ties of mobile users and diverse physical coupling of mobile devices. Key topics include random access control, power control, spectrum access, and location privacy.This brief also investigates SGUM-based power control game and random access control game, for which it establishes the socially-aware Nash equilibrium (SNE). It then examines the critical SGUM-based spectrum access game, and pseudonym change game for personalized location privacy. The authors propose future work on extending the SGUM framework to negative social ties, to demonstrate relevance to security applications and span the continuum between zero-sum game (ZSG) and non-cooperative game (NCG).Social Group Utility Maximization targets researchers and professionals working on mobile networks and social networks. Advanced-level students in electrical engineering and computer science will also find this material useful for their related courses.

This brief presents research results on social cognitive radio networks, a transformational and innovative networking paradigm that promotes the nexus between social interactions and cognitive radio networks. Along with a review of the research literature, the text examines the key motivation and challenges of social cognitive radio network design. Three socially inspired distributed spectrum sharing mechanisms are introduced: adaptive channel recommendation mechanism, imitation-based social spectrum sharing mechanism, and evolutionarily stable spectrum access mechanism. The brief concludes with a discussion of future research directions which ascertains that exploiting social interactions for distributed spectrum sharing will advance the state-of-the-art of cognitive radio network design, spur a new line of thinking for future wireless networks, and enable novel wireless service and applications.

This book constitutes the refereed proceedings of the 7th EAI International Conference on Game Theory for Networks, GameNets 2017, held in Knoxville, Tennessee, USA, in May 2017.The 10 conference papers and 5 invited papers presented cover topics such as smart electric grid, Internet of Things (IoT), social networks, networks security, mobile service markets, and epidemic control.

By focusing on deep learning as the most representative technique of AI, this book provides a comprehensive overview of how AI services are being applied to the network edge near the data sources, and demonstrates how AI and edge computing can be mutually beneficial.

By focusing on deep learning as the most representative technique of AI, this book provides a comprehensive overview of how AI services are being applied to the network edge near the data sources, and demonstrates how AI and edge computing can be mutually beneficial.

This two part LNCS 15227 and 15528 volumes constitutes the proceedings of the 20th IFIP WG 10.3 International Conference on Network and Parallel Computing, NPC 2024, which was held in Haikou, China, during December 7–8, 2024. The 76 full papers presented in this volume were carefully reviewed and selected from 200 submissions.

This two part LNCS 15227 and 15528 volumes constitutes the proceedings of the 20th IFIP WG 10.3 International Conference on Network and Parallel Computing, NPC 2024, which was held in Haikou, China, during December 7–8, 2024. The 76 full papers presented in this volume were carefully reviewed and selected from 200 submissions.

This open access book provides a detailed exploration of how dynamic disturbances, such as those caused by blasting or seismic activity, affect the damage and failure mechanisms of rocks. When excavation is carried out under high stress environment, the external disturbance will change the stress field of the rock, which may lead to potential engineering damage such as large deformation and large displacement of the free surfaces of the engineering surrounding rock, and even cause instability damage, rockburst, and other engineering disasters. From 1960s onward, the subject of progressive damage and failure of rock materials has been extensively investigated to prevent and control geological disasters and engineering accidents. However, the existing researches usually did not take the effects of low-frequency dynamic disturbances on the mechanical properties of rock into consideration. Rock mechanics researchers, such as graduate students, doctoral students, or academics, need to understand the complex interactions between dynamic disturbances and rock integrity. They require up-to-date knowledge of the latest research findings and models to predict rock behaviors accurately.

This book presents the accumulated data and current state of geological knowledge on China’s main shale gas fields. It addresses a broad range of topics, including the geological setting, reference sections and published boreholes, lithostratigraphy, biostratigraphy and chronostratigraphy, sedimentology and sequence stratigraphy of the late Ordovician to early Silurian, spatial and temporal distribution patterns and environmental changes in the black shales of the Wufeng and Lungmachi formations, numerical analysis of the Wufengian and Lungmachian Total Organic Carbon (TOC), late Ordovician to early Silurian bentonites of the Yangtze region, and a graptolite atlas of the Wufeng and Lungmachi formations. Given its scope, the book represents a valuable asset for researchers and petroleum engineers alike.