The book focuses on low-carbon issues and China's economy, which is analyzed from the perspective of electricity economics. It proposes the novel concept of an "economic gene" to reflect certain characteristics of the economy. The gene mapping of China's economy has been studied based on production functions with electricity. Economic mutations have also been studied with the aim of diagnosing problems in the economy. Two such mutations have occurred in China since 1978, the most recent being in 2012 and no further mutation is expected until 2025. The book describes the inherent quality of China's economy from 2012 to 2025, and how mechanism reforms would greatly improve marginal representative factor productivity in this period. The agents response equilibrium (ARE) approach to simulate national economy, based on multi-agent technology is proposed. Another cornerstone of the model is the input-output table. Simulated input-output tables from 2011 to 2025 are provided in the book.This book provides recommendations for policy makers and advisors, and is a valuable resource for researchers in the fields of economics, public policies, low-carbon development, electricity and energy. It also provides insights into China's economic development.
This brief investigates spectrum efficient and energy efficient strategies, known as cognitive radio networks (CRNs), to ensure secure cooperation between licensed and unlicensed users. The authors address issues of spectrum scarcity, spectrum sensing, transmission performance, trust-aware cooperation, and secure communications.
Two security-aware cooperation based spectrum access schemes are presented. The first is a trust-aware cooperative framework for CRNs to improve the throughput or energy efficiency of licensed users and offer transmission opportunities to unlicensed users, taking into consideration the trustworthiness of unlicensed users. The second scheme is a cooperative framework to enhance secure communications of licensed users. An introduction to CRNs and literature survey enhance the discussion while numerical results are provided to demonstrate the viability of the proposed schemes.
The brief is designed for researchers and professionals working with cognitive radio networks or interested in cooperation based access. Advanced-level students studying computer communication networks and communications engineering will also find this brief useful.
This book provides a comprehensive review and in-depth study on efficient beamforming design and rigorous performance analysis in mmWave networks, covering beam alignment, beamforming training and beamforming-aided caching. Due to significant beam alignment latency between the transmitter and the receiver in existing mmWave systems, this book proposes a machine learning based beam alignment algorithm for mmWave networks to determine the optimal beam pair with a low latency. Then, to analyze and enhance the performance of beamforming training (BFT) protocol in 802.11ad mmWave networks, an analytical model is presented to evaluate the performance of BFT protocol and an enhancement scheme is proposed to improve its performance in high user density scenarios. Furthermore, it investigates the beamforming-aided caching problem in mmWave networks, and proposes a device-to-device assisted cooperative edge caching to alleviate backhaul congestion and reduce content retrieval delay.
This book concludes with future research directions in the related fields of study. The presented beamforming designs and the corresponding research results covered in this book, provides valuable insights for practical mmWave network deployment and motivate new ideas for future mmWave networking.
This book targets researchers working in the fields of mmWave networks, beamforming design, and resource management as well as graduate students studying the areas of electrical engineering, computing engineering and computer science. Professionals in industry who work in this field will find this book useful as a reference.
This book explores multimedia applications that emerged from computer vision and machine learning technologies. These state-of-the-art applications include MPEG-7, interactive multimedia retrieval, multimodal fusion, annotation, and database re-ranking. The application-oriented approach maximizes reader understanding of this complex field. Established researchers explain the latest developments in multimedia database technology and offer a glimpse of future technologies. The authors emphasize the crucial role of innovation, inspiring users to develop new applications in multimedia technologies such as mobile media, large scale image and video databases, news video and film, forensic image databases and gesture databases. With a strong focus on industrial applications along with an overview of research topics, Multimedia Database Retrieval: Technology and Applications is an indispensable guide for computer scientists, engineers and practitioners involved in the development and use ofmultimedia systems. It also serves as a secondary text or reference for advanced-level students interested in multimedia technologies.
This book provides a comprehensive review and in-depth discussion of the state-of-the-art research literature and propose energy-efficient computation offloading and resources management for mobile edge computing (MEC), covering task offloading, channel allocation, frequency scaling and resource scheduling. Since the task arrival process and channel conditions are stochastic and dynamic, the authors first propose an energy efficient dynamic computing offloading scheme to minimize energy consumption and guarantee end devices' delay performance. To further improve energy efficiency combined with tail energy, the authors present a computation offloading and frequency scaling scheme to jointly deal with the stochastic task allocation and CPU-cycle frequency scaling for minimal energy consumption while guaranteeing the system stability. They also investigate delay-aware and energy-efficient computation offloading in a dynamic MEC system with multiple edge servers, and introduce anend-to-end deep reinforcement learning (DRL) approach to select the best edge server for offloading and allocate the optimal computational resource such that the expected long-term utility is maximized. Finally, the authors study the multi-task computation offloading in multi-access MEC via non-orthogonal multiple access (NOMA) and accounting for the time-varying channel conditions. An online algorithm based on DRL is proposed to efficiently learn the near-optimal offloading solutions.
Researchers working in mobile edge computing, task offloading and resource management, as well as advanced level students in electrical and computer engineering, telecommunications, computer science or other related disciplines will find this book useful as a reference. Professionals working within these related fields will also benefit from this book.
This monograph addresses the spectrum-scarcity problem by providing a comprehensive overview of spectrum resource management in Cognitive Radio Sensor Networks (CRSNs). It shows a variety of CRSN applications covering Machine-to-Machine communications, cyber physical systems and Internet-of-Things. The authors explore the benefits of an integrated energy efficient spectrum management solution for CRSNs including spectrum sensing, decision and allocation. Both theoretical and experimental aspects of CRSNs are covered in detail.
Academics, researchers and developers will find this monograph an exceptional resource with valuable knowledge and insights. It also has extensive references from top journals, conference proceedings, books and standards.
Comment le monde occidental est-il perçu et représenté au sein d'un univers éloigné de lui que la Chine ? Comment cet Occident, construit et reconstruit au cours de notre siècle, marque-t-il la recherche, par la Chine, de sa propre identité moderne ? Zhang Ning nous présente une illustration saisissante de ce débat, aussi bien politique que symbolique, en mettant en rapport la question de la modernité chinoise avec l'aspect particulier de la transformation du champ théâtral dans la Chine moderne.
The book offers a focused examination of deep learning-based wireless communication systems and their applications. While both principles and engineering practice are explored, greater emphasis is placed on the latter. The book offers an in-depth exploration of major topics such as cognitive spectrum intelligence, learning resource allocation optimization, transmission intelligence, learning traffic and mobility prediction, and security in wireless communication. Notably, the book provides a comprehensive and systematic treatment of practical issues related to intelligent wireless communication, making it particularly useful for those seeking to learn about practical solutions in AI-based wireless resource management. This book is a valuable resource for researchers, engineers, and graduate students in the fields of wireless communication, telecommunications, and related areas.
This book employs a qualitative analysis of China's publicly financed construction sector, taking the system design as its point of departure and applying comprehensive evaluation techniques to create an index system for this type of construction - which in turn serves as a basis for quantitatively evaluating China's publicly financed construction sector. Given the fact that China's publicly financed construction sector is a very complex field of systems engineering involving multiple subsystems, as an important indicator of China's fiscal innovations since its reform and opening, publicly financed construction is now shifting from theory to practice, demonstrating that China has entered an era of fully publicly financed construction.
This book describes recently developed research methods used to study complex problems in fluid engineering, especially optical flow measurement, flow visualization and numerical methods. It includes a wealth of diagrams and images, and the content is presented in a step-by-step manner from beginning to end, helping readers grasp the central points of the book.The book also presents a number of practical cases, illustrating how the research methods covered can be concretely implemented. Lastly, the book offers a valuable point of departure for pursuing further research.
The IoT topology defines the way various components communicate with each other within a network. Topologies can vary greatly in terms of security, power consumption, cost, and complexity. Optimizing the IoT topology for different applications and requirements can help to boost the network's performance and save costs. More importantly, optimizing the topology robustness can ensure security and prevent network failure at the foundation level. In this context, this book examines the optimization schemes for topology robustness in the IoT, helping readers to construct a robustness optimization framework, from self-organizing to intelligent networking.
The book provides the relevant theoretical framework and the latest empirical research on robustness optimization of IoT topology. Starting with the self-organization of networks, it gradually moves to genetic evolution. It also discusses the application of neural networks and reinforcement learning to endow the node with self-learning ability to allow intelligent networking.
This book is intended for students, practitioners, industry professionals, and researchers who are eager to comprehend the vulnerabilities of IoT topology. It helps them to master the research framework for IoT topology robustness optimization and to build more efficient and reliable IoT topologies in their industry.
