Data-Driven 3D Facial Animation systematically describes the important techniques developed over the last ten years or so. Comprehensive in scope, the book provides an up-to-date reference source for those working in the facial animation field.
Data-Driven 3D Facial Animation systematically describes the important techniques developed over the last ten years or so. Comprehensive in scope, the book provides an up-to-date reference source for those working in the facial animation field.
This SpringerBrief offers a comprehensive review and in-depth discussion of the current research on resource management. The authors explain how to best utilize harvested energy and temporally available licensed spectrum. Throughout the brief, the primary focus is energy and spectrum harvesting sensor networks (ESHNs) including energy harvesting (EH)-powered spectrum sensing and dynamic spectrum access. To efficiently collect data through the available licensed spectrum, this brief examines the joint management of energy and spectrum. An EH-powered spectrum sensing and management scheme for Heterogeneous Spectrum Harvesting Sensor Networks (HSHSNs) is presented in this brief. The scheme dynamically schedules the data sensing and spectrum access of sensors in ESHSNs to optimize the network utility, while considering the stochastic nature of EH process, PU activities and channel conditions. This brief also provides useful insights for the practical resource management scheme design for ESHSNs and motivates a new line of thinking for future sensor networking. Professionals, researchers, and advanced-level students in electrical or computer engineering will find the content valuable.
Understand the energy storage technologies of the future with this groundbreaking guide Magnesium-based materials have revolutionary potential within the field of clean and renewable energy. Their suitability to act as battery and hydrogen storage materials has placed them at the forefront of the world#s most significant research and technological initiatives. It has never been more essential that professionals working in energy storage and energy systems understand these materials and their extraordinary potential applications. Magnesium-Based Energy Storage Materials and Systems provides a thorough introduction to advanced Magnesium (Mg)-based materials, including both Mg-based hydrogen storage and Mg-based batteries. Offering both foundational knowledge and practical applications, including step-by-step device design processes, it also highlights interactions between Mg-based and other materials. The result is an indispensable guide to a groundbreaking set of renewable energy resources. Magnesium-Based Energy Storage Materials and Systems readers will also find: In-depth analysis of the effects of employing catalysts, nano-structuring Magnesium-based materials, and many more subjects Detailed discussion of electrolyte, cathode, and anode materials for Magnesium batteries Snapshots of in-progress areas of research and development Magnesium-Based Energy Storage Materials and Systems is ideal for materials scientists, inorganic chemists, solid state chemists, electrochemists, and chemical engineers.
This book focuses on the deep learning technologies and their applications in the catenary detection of high-speed railways. As the only source of power for high-speed trains, the catenary's service performance directly affects the safe operation of high-speed railways. This book systematically shows the latest research results of catenary detection in high-speed railways, especially the detection of catenary support component defect and fault. Some methods or algorithms have been adopted in practical engineering. These methods or algorithms provide important references and help the researcher, scholar, and engineer on pantograph and catenary technology in high-speed railways. Unlike traditional detection methods of catenary support component based on image processing, some advanced methods in the deep learning field, including convolutional neural network, reinforcement learning, generative adversarial network, etc., are adopted and improved in this book. The main contents include the overview of catenary detection of electrified railways, the introduction of some advance of deep learning theories, catenary support components and their characteristics in high-speed railways, the image reprocessing of catenary support components, the positioning of catenary support components, the detection of defect and fault, the detection based on 3D point cloud, etc.
What are the recent developments in the field of Metrology?" International leading experts answer this question providing both state of the art presentation and a road map to the future of measurement science. The book is organized in six sections according to the areas of expertise, namely: Introduction; Length, Distance and Surface; Voltage, Current and Frequency; Optics; Time and Relativity; Biology and Medicine. Theoretical basis and applications are explained in accurate and comprehensive manner, providing a valuable reference to researchers and professionals.
Mechanism of charge transport in organic solids has been an issue of intensive interests and debates for over 50 years, not only because of the applications in printing electronics, but also because of the great challenges in understanding the electronic processes in complex systems. With the fast developments of both electronic structure theory and the computational technology, the dream of predicting the charge mobility is now gradually becoming a reality. This volume describes recent progresses in Prof. Shuai’s group in developing computational tools to assess the intrinsic carrier mobility for organic and carbon materials at the first-principles level. According to the electron-phonon coupling strength, the charge transport mechanism is classified into three different categories, namely, the localized hopping model, the extended band model, and the polaron model. For each of them, a corresponding theoretical approach is developed and implemented into typical examples.
Special Distillation Processes, Second Edition focuses on the latest developments in the field, such as separation methods that may prove useful for solving problems encountered during research. Topics include extraction, membrane and adsorption distillation involving the separation principle, process design and experimental techniques. The relationship between processes and techniques are also presented. Comprehensive and easy-to-read, this book provides key information needed to understand processes. It will be a valuable reference source for chemical engineers and students wishing to branch out in chemical engineering. Provides the only comprehensive book available on special distillation processes Contains a thorough introduction to recent developments in the field Presents a valuable reference for students, academics and engineers in chemical engineering
Metal Oxide Semiconductors Up-to-date resource highlighting highlights emerging applications of metal oxide semiconductors in various areas and current challenges and directions in commercialization Metal Oxide Semiconductors provides a current understanding of oxide semiconductors, covering fundamentals, synthesizing methods, and applications in diodes, thin-film transistors, gas sensors, solar cells, and more. The text presents state-of-the-art information along with fundamental prerequisites for understanding and discusses the current challenges in pursuing commercialization and future directions of this field. Despite rapid advancements in the materials science and device physics of oxide semiconductors over the past decade, the understanding of science and technology in this field remains incomplete due to its relatively short research history; this book aims to bridge the gap between the rapidly advancing research progress in this field and the demand for relevant materials and devices by researchers, engineers, and students. Written by three highly qualified authors, Metal Oxide Semiconductors discusses sample topics such as: Fabrication techniques and principles, covering vacuum-based methods, including sputtering, atomic layer deposition and evaporation, and solution-based methods Fundamentals, progresses, and potentials of p–n heterojunction diodes, Schottky diodes, metal-insulator-semiconductor diodes, and self-switching diodes Applications in thin-film transistors, detailing the current progresses and challenges towards commercialization for n-type TFTs, p-type TFTs, and circuits Detailed discussions on the working mechanisms and representative devices of oxide-based gas sensors, pressure sensors, and PH sensors Applications in optoelectronics, both in solar cells and ultraviolet photodetectors, covering their parameters, materials, and performance Memory applications, including resistive random-access memory, transistor-structured memory devices, transistor-structured artificial synapse, and optical memory transistors A comprehensive monograph covering all aspects of oxide semiconductors, Metal Oxide Semiconductors is an essential resource for materials scientists, electronics engineers, semiconductor physicists, and professionals in the semiconductor and sensor industries who wish to understand all modern developments that have been made in the field.
With the increasing penetration of renewable energy and distributed energy resources, smart grid is facing great challenges, which could be divided into two categories. On the one hand, the endogenous uncertainties of renewable energy and electricity load lead to great difficulties in smart grid forecast. On the other hand, massive electric devices as well as their complex constraint relationships bring about significant difficulties in smart grid dispatch. Owe to the rapid development of artificial intelligence in recent years, several artificial intelligence enabled computational methods have been successfully applied in the smart grid and achieved good performances. Therefore, this book is concerned with the research on the key issues of artificial intelligence enabled computational methods for smart grid forecast and dispatch, which consist of three main parts. (1) Introduction for smart grid forecast and dispatch, in inclusion of reviewing previous contribution of various research methods as well as their drawbacks to analyze characteristics of smart grid forecast and dispatch. (2) Artificial intelligence enabled computational methods for smart grid forecast problems, which are devoted to present the recent approaches of deep learning and machine learning as well as their successful applications in smart grid forecast. (3) Artificial intelligence enabled computational methods for smart grid dispatch problems, consisting of edge-cutting intelligent decision-making approaches, which help determine the optimal solution of smart grid dispatch. The book is useful for university researchers, engineers, and graduate students in electrical engineering and computer science who wish to learn the core principles, methods, algorithms, and applications of artificial intelligence enabled computational methods.
This textbook focuses on the performance and application of highway engineering composite material. It collects and compiles the data obtained by the authors in numerous recent practical and research projects in the field of technology and application of highway engineering composite materials in China. It provides valuable reference materials for students and engineering technicians taking courses on the selection, design and construction of composite materials for highway engineering. It offers solutions to various practical engineering problems, and also includes in-depth theoretical analyses of related issues in simple language. Some of the concepts and applications, such as the highway pavement functional layer and the application of polymer composite material to protection of soft rocks, have not been previously covered in the literature before, and as such the book provides engineering and technical professionals with a new vision and new methods. Further, it not only explains the basic concepts, principles, and requirements of composite material for highway engineering, but also describes its application, including the related theoretical analyses, design and construction, making it ideal as a reference book for technical personnel, as well as a textbook for undergraduates and postgraduates majoring in highway engineering.
This book highlights the fundamentals and latest progresses in the research and applications of laser shock peening (LSP). As a novel technology for surface treatment, LSP greatly improves the resistance of metallic materials to fatigue and corrosion. The book presents the mechanisms, techniques, and applications of LSP in a systematic way. It discusses a series of new progresses in fatigue performance improvement of metal parts with LSP. It also introduces lasers, equipment, and techniques of newly developed industry LSP, with a detailed description of the novel LSP blisk. The book demonstrates in details numerical analysis and simulation techniques and illustrates process stability control, quality control, and analysis determination techniques. It is a valuable reference for scientists, engineers, and students in the fields of laser science, materials science, astronautics, and aeronautics who seek to understand, develop, and optimize LSP processes.
With its comprehensive coverage of recent progress in metallic biomaterials, this reference focuses on emerging materials and new biofunctions for promising applications. The text is systematically structured, with the information organized according to different material systems, and concentrates on various advanced materials, such as anti-bacterial functionalized stainless steel, biodegradable metals with bioactivity, and novel structured metallic biomaterials. Authors from well-known academic institutes and with many years of clinical experience discuss all important aspects, including design strategies, fabrication and modification techniques, and biocompatibility.
Density Matrix Renormalization Group (DMRG)-based Approaches in Computational Chemistry outlines important theories and algorithms of DMRG-based approaches and explores their use in computational chemistry. Beginning with an introduction to DMRG and DMRG-based approaches, the book goes on to discuss the key theories and applications of DMRG, from DMRG for semi-empirical and ab-initio quantum chemistry, to DMRG in embedded environments, frequency spaces and quantum dynamics. Drawing on the experience of its expert authors, sections detail recent ideas and key developments, providing an up-to-date view of current developments in the field for students and researchers in quantum chemistry. Provides an expertly-curated, consolidated overview of research in the field Includes exercises that support learning and link theory to practice Outlines key theories and algorithms for computational chemistry applications
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