Jun Cai - Böcker

Micro- and Nano-Bionic Surfaces: Biomimetics, Interface Energy Field Effects, and Applications synthesizes the latest research in bio-inspired surfaces and devices for tactile and flow field perception. The book provides solutions to common problems related to flow field/tactile perception, intelligent MEMS sensors, smart materials, material removal methods, cell/particle control methods, and micro-nano robot technology. With a heavy emphasis on applications throughout, the book starts by providing insights into biomimetic device design, outlining strategies readers can adopt for various engineering applications. From there, it introduces the controlling methods of smart materials, controlling methods from external energy input, and more.

Sections demonstrate how to solve problems of high efficiency, high quality, and low damage material removal for metals, composites, soft tissues, and other materials by applying bionic wave-motion surface characteristics. The latest theoretical and technical developments in field control methods applied to biological interfaces are also discussed, and the book concludes with a chapter on fabrication strategies to synthesize micro/nano functional particles based on bio-templates.

Provides an overview on the latest research in bio-inspired surfaces and devices for tactile and flow-field perception Introduces techniques for characterizing different bionic surfaces and how to use energy fields analysis to treat different bionic surface and interface problems Discusses the latest theoretical and experimental developments in field control and their applications in the biomedical field Outlines fabrication methods and assembly and alignment processes of micro-/nano-functional particles based on microorganism templates

Digital twin computing is the bridge between the real and virtual worlds, and operates as a mirror that reflects the real world into the virtual world. Digital twin technologies take data from sensor networks in the real world, utilise artificial intelligence and machine learning to analyse the data, and then create a digital representation or simulation that updates as their real world counterpart updates. As such, the model can be used to understand the real world environment, and the digital twin can be used to make informed decisions that will be of benefit in the real world. Foundations of Digital Twins explains the fundamentals of digital twins, how digital twin technologies can gather real world data using the sensor networks that comprise the Internet of Things, and how that data can be sorted, analysed, and utilised to improve services and to increase sustainability. Structured in five sections, the book begins with an introductory overview of each technology, establishing a clear understanding of their individual roles and their potential when combined. The second section delves into data acquisition, featuring advanced sensors, drones, robots and actuators. Part Three considers data exchange and security, focusing on CPS, the internet of things, and blockchain. Part Four looks at how digital twins can impact on data computing, such as video streaming, cloud computing, fog computing and edge-computing. The final section explores the future opportunities and risks of adopting advanced technologies in this evolving field, including artificial intelligence, the ethical issues concerned when collecting and using data, and the security implications. By blending theory with practical insights, Foundations of Digital Twins serves as both an educational resource and a practical guide for researchers, students and professionals seeking to harness the power of these advanced technologies in complex, real world environments.Explains how digital twins gather real world data to create a virtual model of a real world environmentDiscusses how that virtual model can be utilized in the making of informed decisions about the real world environmentConsiders the associated technologies that support digital twins, including blockchain, sensor networks, artificial intelligence and machine learningExplores how digital twins can be used to monitor and improve real world services.

This book constitutes the refereed proceedings of the 10th International Conference on Advances in Brain Inspired Cognitive Systems, BICS 2019, held in Guangzhou, China, in July 2019. The 57 papers presented in this volume were carefully reviewed and selected from 129 submissions.

The three-volume proceedings set LNCS 13655,13656 and 13657 constitutes the refereedproceedings of the 4th International Conference on Machine Learning for Cyber Security, ML4CS 2022, which taking place during December 2–4, 2022, held in Guangzhou, China.The 100 full papers and 46 short papers were included in these proceedings were carefully reviewed and selected from 367 submissions.

The three-volume proceedings set LNCS 13655,13656 and 13657 constitutes the refereedproceedings of the 4th International Conference on Machine Learning for Cyber Security, ML4CS 2022, which taking place during December 2–4, 2022, held in Guangzhou, China.The 100 full papers and 46 short papers were included in these proceedings were carefully reviewed and selected from 367 submissions.

The three-volume proceedings set LNCS 13655,13656 and 13657 constitutes the refereedproceedings of the 4th International Conference on Machine Learning for Cyber Security, ML4CS 2022, which taking place during December 2–4, 2022, held in Guangzhou, China.The 100 full papers and 46 short papers were included in these proceedings were carefully reviewed and selected from 367 submissions.

Human digital twin (HDT) is a transformative technology poised to transform various human-centric systems. With its potential applications in personalized healthcare, HDT promises swift, precise, and efficient healthcare services through the integration of cutting-edge technologies such as artificial intelligence, data analytics, internet of things, cybersecurity as well as virtual and augmented reality. This book addresses the critical gap in the existing literature by offering a comprehensive exploration of connectivity solutions for HDT while prioritizing reliability, security, and privacy. Key topics covered include the foundational concept of HDT, its design requirements and associated challenges, edge-assisted human-to-virtual solutions, blockchain-enabled data-sharing mechanisms, and differentially private federated multi-task learning (DPFML) methodologies tailored for HDT.The discussion on the concept of HDT encompasses an overview of its applications and its specific characteristics when compared to the conventional digital twin models. In addressing the design requirements and challenges of HDT, the text delves into the complexities of securing high-quality data, ensuring ultra-reliable and low-latency communication, data privacy and integrity, while managing storage, computation and analytics. Exploring edge-assisted human-to-virtual solutions, the book also introduces a connectivity framework and details the modeling process for human-to-virtual twin connectivity. The book later presents an in-depth examination of the practical Byzantine fault tolerance framework, followed by a discussion on shard-based Byzantine fault-tolerant schemes tailored for HDT, along with analyses of latency and throughput.Furthermore, the book outlines the framework for DPFML-assisted human-to-virtual twin connectivity, accompanied by a novel consensus algorithm known as the proof of model quality. Finally, it presents future research directions aimed at addressing communication challenges hindering the seamless design and development of HDT. By offering this comprehensive exploration, the book serves as a valuable resource for researchers, practitioners, and policymakers seeking to navigate the evolving landscape of HDT and its transformative potential in various domains.

This book initially delves into its fundamentals to initiate the exploration of online incentive mechanisms in wireless communications.

This book constitutes the refereed proceedings of the 6th International Conference on Security and Privacy in New Computing Environments, SPNCE 2023, held in Guangzhou, China, during November 25-26, 2023.The 29 full papers were selected from 75 submissions and are grouped in these thematical parts: IoT, network security and privacy challenges; multi-party privacy preserving neural networks; security and privacy steganography and forensics.

This book focuses on the integration of self-evolving Digital Twins (DTs) with wireless networks, exploring critical methodologies for dynamic twin construction and real-time service interaction. It addresses challenges posed by wireless environments, which are paramount for maintaining high-fidelity virtual replicas of physical systems. The content provides a comprehensive outline for building and managing DTs that can continuously adapt over wireless networks.The authors dedicated this book to innovative solutions for optimizing resource allocation and intelligent decision-making.  It includes game-theoretic online optimization for federated DT construction and generative artificial intelligence-aided framework for quality-of-experience driven DT service interaction. Furthermore, it shows the practical implementation of these technologies through detailed applications in intelligent vehicular networks.This book is appropriate for advanced-level students in computer science and electrical engineering, who are studying wireless communications, distributed systems, Internet of Things, and cyber-physical systems. Researchers and industry practitioners seeking to leverage DTs for innovation in smart manufacturing, intelligent transportation, and smart cities will find this book invaluable as well.

This brief focuses on the current research on mechanism design for dynamic spectrum sharing in cognitive radio (CR) networks. Along with a review of CR architectures and characteristics, this brief presents the motivations, significances and unique challenges of implementing algorithmic mechanism design for encouraging both primary spectrum owners and secondary spectrum users to participate in dynamic spectrum sharing. The brief then focuses on recent advances in mechanism design in CR networks. With an emphasis on dealing with the uncertain spectrum availabilities, mechanisms based on spectrum recall, two-stage spectrum sharing and online spectrum allocation are introduced with the support of theoretic analyses and numerical illustrations. The brief concludes with a discussion of potential research directions and interests, which will motivate further studies on mechanism design for wireless communications. This brief is concise and approachable for researchers, professionals and advanced-level students in wireless communications and networks.

This two-volume set, CCIS 1453 and CCIS 1454, constitutes refereed proceedings of the 6th International Conference on Data Mining and Big Data, DMBD 2021, held in Guangzhou, China, in October 2021.