This SpringerBrief provides a concise guide to applying wireless energy transfer techniques in traditional battery-powered sensor networks. It examines the benefits and challenges of wireless power including efficiency and reliability. The authors build a wireless rechargeable sensor networks from scratch and aim to provide perpetual network operation. Chapters cover a wide range of topics from the collection of energy information and recharge scheduling to joint design with typical sensing applications such as data gathering. Problems are approached using a natural combination of probability theory, optimization, algorithm and protocol designs. All proposed mechanisms are evaluated by extensive simulations. Wireless Rechargeable Sensor Networks targets professionals and researchers working in networks, wireless communications, energy technology and information technology. Advanced-level students studying electrical engineering and computer science will also find this material useful as a study guide.
This comprehensive compendium designs deep neural network models and systems for intelligent analysis of fundus imaging. In response to several blinding fundus diseases such as Retinopathy of Prematurity (ROP), Diabetic Retinopathy (DR) and Macular Edema (ME), different image acquisition devices and fundus image analysis tasks are elaborated.From the actual fundus disease analysis tasks, various deep neural network models and experimental results are constructed and analyzed. For each task, an actual system for clinical application is developed.This useful reference text provides theoretical and experimental reference basis for AI researchers, system engineers of intelligent medicine and ophthalmologists.
This book provides detailed systematic micro-level analysis of the historical development of the Chinese banking industry, focusing in particular on the development of the Bank of China (BOC) in the period 1905 to 1949. Banking reform is a key area of China’s economic transformation, and this book, bringing a vast amount of material to a Western audience for the first time, provides a detailed evidence of the key challenges faced by a major Chinese bank. The book: addresses important issues in its evolution, including corporate governance government intervention, foreign competition and white-collar crime evaluates how the challenges in these areas were met considers the results of its efforts draws lessons for policy making today.
This book reviews the latest advances in the development of silicon nano-biotechnology for biological and biomedical applications, which include biosensing, bioimaging, and cancer therapy. In this book, newly developed silicon nano-biotechnology and its biomedical applications are systematically introduced. For instance, fluorescent silicon nanoparticles, serving as novel high-performance biological nanoprobes, are superbly suited to real-time and long-term bioimaging. Silicon nanowire-based sensing platform is especially capable of sensitive, specific, and multiplexed detection of various biological species. Silicon-based nanocarriers with ultra-high drug-loading capacity are highly efficacious for in vitro and in vivo cancer therapies. This book is intended for readers who are interested in the design of functional silicon nanostructures and their biological and biomedical applications. It uses silicon nanoparticles and silicon nanowires as models and discusses topics ranging from their synthesis to their biological applications, the goal being to highlight these exciting achievements as starting points in the field of silicon nano-biotechnology. Yao He is a Professor at Institute of Functional Nano&Soft Materials (FUNSOM), Soochow University, China. Yuanyuan Su is an Associate Professor at Institute of Functional Nano&Soft Materials (FUNSOM), Soochow University, China.
This book is inspired by the development of distributed model predictive control of networked systems to save computation and communication sources. The significant new contribution is to show how to design efficient DMPCs that can be coordinated asynchronously with the increasing effectiveness of the event-triggering mechanism and how to improve the event-triggered DMPC for different requirements improvement of control performance, extension to interconnected networked systems, etc. The book is likely to be of interest to the persons who are engaged in researching control theory in academic institutes, the persons who go in for developing control systems in R&D institutes or companies, the control engineers who are engaged in the implementation of control algorithms, and people who are interested in the distributed MPC.
There has been a surging interest in developing systems for analyzing big graphs generated by real applications, such as online social networks and knowledge graphs. This book aims to help readers get familiar with the computation models of various graph processing systems with minimal time investment. This book is organized into three parts, addressing three popular computation models for big graph analytics: think-like-a-vertex, think-likea- graph, and think-like-a-matrix. While vertex-centric systems have gained great popularity, the latter two models are currently being actively studied to solve graph problems that cannot be efficiently solved in vertex-centric model, and are the promising next-generation models for big graph analytics. For each part, the authors introduce the state-of-the-art systems, emphasizing on both their technical novelties and hands-on experiences of using them. The systems introduced include Giraph, Pregel+, Blogel, GraphLab, CraphChi, X-Stream, Quegel, SystemML, etc. Readers will learn how to design graph algorithms in various graph analytics systems, and how to choose the most appropriate system for a particular application at hand. The target audience for this book include beginners who are interested in using a big graph analytics system, and students, researchers and practitioners who would like to build their own graph analytics systems with new features.
In recent years China has experienced intense economic development. Previously a rapidly urbanising industrial economy, the country has become a post-industrial economy with a service sector that accounts for almost half the nation’s GDP. This transformation has created many socio-political changes, but key among them is social mobilisation. This book provides a full and systematic analysis of social mobilisation in China, and how its use as part of state capacity has evolved.
Reindeer-herding Ewenki hunters have lived in the forests of China’s Greater Khingan Range for over three hundred years. They have sustained their livelihoods by collecting plants and herbs, hunting animals and herding reindeer. This ethnography details changing Ewenki ways of life brought first by China’s modernization and development policies and more recently by ecological policies that aim to preserve and restore the badly damaged ecologies of western China. Xie reflects on modernization and urbanization in China through this study of ecological migration policies and their effects on relocated Aoluguya Ewenki hunters.
This book focuses on mobile data and its applications in the wireless networks of the future. Several topics form the basis of discussion, from a mobile data mining platform for collecting mobile data, to mobile data processing, and mobile feature discovery. Usage of mobile data mining is addressed in the context of three applications: wireless communication optimization, applications of mobile data mining on the cellular networks of the future, and how mobile data shapes future cities. In the discussion of wireless communication optimization, both licensed and unlicensed spectra are exploited. Advanced topics include mobile offloading, resource sharing, user association, network selection and network coexistence. Mathematical tools, such as traditional convexappl/non-convex, stochastic processing and game theory are used to find objective solutions. Discussion of the applications of mobile data mining to cellular networks of the future includes topics such as green communication networks, 5G networks, and studies of the problems of cell zooming, power control, sleep/wake, and energy saving. The discussion of mobile data mining in the context of smart cities of the future covers applications in urban planning and environmental monitoring: the technologies of deep learning, neural networks, complex networks, and network embedded data mining. Mobile Data Mining and Applications will be of interest to wireless operators, companies, governments as well as interested end users.
This open access book deals with a rich variety of taxis-type cross-diffusive equations. Particularly, it intends to show the key role played by quasi-energy inequality in the derivation of some necessary a priori estimates. This book addresses applied mathematics and all researchers interested in mathematical development of reaction-diffusion theory and its application and can be a basis for a graduate course in applied mathematics.
Anxiety disorder is a broad term used to describe a group of mental disorders characterized by a collection of anxiety symptoms as the primary clinical presentation. These disorders are marked by excessive fear and anxiety, along with associated behavioral disturbances. Fear refers to an anxious reaction when confronted with a specific unfavorable or dangerous situation, while anxiety refers to a state of highly disturbed anticipation, accompanied by nervousness and autonomic dysfunction, even without appropriate ob-jective factors. According to the ICD-11 and DSM-5 classifications of dis-orders, the current anxiety disorder includes: generalized anxiety disorder, panic disorder, agoraphobia, social anxiety disorder, specific phobia disorder, dissociative anxiety disorder, selective mutism and anxiety disorders caused by other medications or physical illnesses. The five most common types of anxiety disorders are generalized anxiety disorder, panic disorder, specific phobia disorder, social anxiety disorder and specific fear disorder.
This SpringerBrief provides a concise guide to applying wireless energy transfer techniques in traditional battery-powered sensor networks. It examines the benefits and challenges of wireless power including efficiency and reliability. The authors build a wireless rechargeable sensor networks from scratch and aim to provide perpetual network operation. Chapters cover a wide range of topics from the collection of energy information and recharge scheduling to joint design with typical sensing applications such as data gathering. Problems are approached using a natural combination of probability theory, optimization, algorithm and protocol designs. All proposed mechanisms are evaluated by extensive simulations. Wireless Rechargeable Sensor Networks targets professionals and researchers working in networks, wireless communications, energy technology and information technology. Advanced-level students studying electrical engineering and computer science will also find this material useful as a study guide.
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