This book provides a panoramic overview on wireless communication network technologies and its evolution, namely cellular mobile networks (especially 5G), Wireless Local Area Network (WLAN) and Narrow Band Internet of Things (NB-IoT).With rich experiences in teaching and scientific research, the renowned authors selectively analyze several key technologies that restrict the performance of wireless communication and computer networks.For easy reading, each chapter is illustrated in somewhat the style of lesson plan.The useful reference text will benefit both undergraduate and graduate students in the fields of wireless communication, computer networks, electronic engineering, automatic control, etc.
This unique textbook intersects traditional library science with data science principles that readers will find useful in implementing or improving data services within their libraries. Data Science for Librarians introduces data science to students and practitioners in library services. Writing for academic, public, and school library managers; library science students; and library and information science educators, authors Yunfei Du and Hammad Rauf Khan provide a thorough overview of conceptual and practical tools for data librarian practice. Partially due to how quickly data science evolves, libraries have yet to recognize core competencies and skills required to perform the job duties of a data librarian. As society transitions from the information age into the era of big data, librarians and information professionals require new knowledge and skills to stay current and take on new job roles, such as data librarianship. Such skills as data curation, research data management, statistical analysis, business analytics, visualization, smart city data, and learning analytics are relevant in library services today and will become increasingly so in the near future. This text serves as a tool for library and information science students and educators working on data science curriculum design.
Provides a systematic overview of a hot research area, examining the principles and theories of energy harvesting communications This book provides a detailed and advanced level introduction to the fundamentals of energy harvesting techniques and their use in state-of-the-art communications systems. It fills the gap in the market by covering both basic techniques in energy harvesting and advanced topics in wireless communications. More importantly, it discusses the application of energy harvesting in communications systems to give readers at different levels a full understanding of these most recent advances in communications technologies. The first half of Energy Harvesting Communications: Principles and Theories focuses on the challenges brought by energy harvesting in communications. The second part of the book looks at different communications applications enhanced by energy harvesting. It offers in-depth chapters that: discuss different energy sources harvested for communications; examine the energy harvesters used for widely used sources; study the physical layer and upper layer of the energy harvesting communications device; and investigate wireless powered communications, energy harvesting cognitive radios, and energy harvesting relaying as applications. Methodically examines the state-of-the-art of energy harvesting techniques Provides comprehensive coverage from basic energy harvesting sources and devices to the end users of these sources and devices Looks at the fundamental principles of energy harvesting communications, and biomedical application and intra-body communications Written in a linear order so that beginners can learn the subject and experienced users can attain a broader view Written by a renowned expert in the field, Energy Harvesting Communications: Principles and Theories is an excellent resource for students, researchers, and others interested in the subject.
This brief introduces a class of problems and models for the prediction of the scalar field of interest from noisy observations collected by mobile sensor networks. It also introduces the problem of optimal coordination of robotic sensors to maximize the prediction quality subject to communication and mobility constraints either in a centralized or distributed manner. To solve such problems, fully Bayesian approaches are adopted, allowing various sources of uncertainties to be integrated into an inferential framework effectively capturing all aspects of variability involved. The fully Bayesian approach also allows the most appropriate values for additional model parameters to be selected automatically by data, and the optimal inference and prediction for the underlying scalar field to be achieved. In particular, spatio-temporal Gaussian process regression is formulated for robotic sensors to fuse multifactorial effects of observations, measurement noise, and prior distributions for obtaining the predictive distribution of a scalar environmental field of interest. New techniques are introduced to avoid computationally prohibitive Markov chain Monte Carlo methods for resource-constrained mobile sensors. Bayesian Prediction and Adaptive Sampling Algorithms for Mobile Sensor Networks starts with a simple spatio-temporal model and increases the level of model flexibility and uncertainty step by step, simultaneously solving increasingly complicated problems and coping with increasing complexity, until it ends with fully Bayesian approaches that take into account a broad spectrum of uncertainties in observations, model parameters, and constraints in mobile sensor networks. The book is timely, being very useful for many researchers in control, robotics, computer science and statistics trying to tackle a variety of tasks such as environmental monitoring and adaptive sampling, surveillance, exploration, and plume tracking which are of increasing currency. Problems are solved creatively by seamless combination of theories and concepts from Bayesian statistics, mobile sensor networks, optimal experiment design, and distributed computation.
China’s new retail revolution will completely transform how the world thinks about retail and digital innovation. But is the world ready yet? In this book, the authors share an insider’s perspective on what is happening in China to reveal the future for global retail, and a clear framework to help you prepare. The book presents a number of real-world cases, based on interviews and first-hand consumer experience, to decode China’s retail revolution so that you can understand what is happening and why, and what it means for the rest of the world. Crucially, the book identifies five critical stages in the development of new retail that global retail executives need to grasp now: lifestyle commerce, Online-Merge-Offline retail, social retail, livestream retail and invisible retail. To help the industry get ready for this new, China-inspired paradigm in retail, the authors present a practical and simple framework – a ten-year strategic roadmap for global retail executives, which we call the “Beyond” the Value Chain Model. China’s new retail is not just about fashion, cosmetics, snacks, data-driven convenient stores and commercial live streaming. At a time when the world of retail is being upended, it offers inspirational lessons in innovation, purpose and agility for global executives across the entire retail spectrum.
This book presents recent advanced techniques in sliding mode control and observer design for industrial power systems, focusing on their applications in polymer electrolyte membrane fuel cells and power converters. Readers will find not only valuable new fault detection and isolation techniques based on sliding mode control and observers, but also a number of robust control and estimation methodologies combined with fuzzy neural networks and extended state observer methods. The book also provides necessary experimental and simulation examples for proton exchange membrane fuel cell systems and power converter systems. Given its scope, it offers a valuable resource for undergraduate and graduate students, academics, scientists and engineers who are working in the field.
This book aims to present some advanced control methodologies for power converters. Power electronic converters have become indispensable devices for plenty of industrial applications over the last decades. Composed by controllable power switches, they can be controlled by effective strategies to achieve desirable transient response and steady-state performance, to ensure the stability, reliability and safety of the system. The most popular control strategy of power converters is the linear proportional–integral–derivative series control which is adopted as industry standard. However, when there exist parameter changes, nonlinearities and load disturbances in the system, the performance of the controller will be significantly degraded. To overcome this problem, many advanced control methodologies and techniques have been developed to improve the converter performance. This book presents the research work on some advanced control methodologies for several types of power converters, including three-phase two-level AC/DC power converter, three-phase NPC AC/DC power converter, and DC/DC buck converter. The effectiveness and advantage of the proposed control strategies are verified via simulations and experiments. The content of this book can be divided into two parts. The first part focuses on disturbance observer-based control methods for power converters under investigation. The second part investigates intelligent control methods. These methodologies provide a framework for controller design, observer design, stability and performance analysis for the considered power converter systems.
In this ambitious volume, Yunfei Bai delves into the creative adaptations of classical Sanskrit, Chinese, and Tibetan literary texts by four renowned nineteenth- and early twentieth-century authors in France and Argentina: Theophile Gautier, Stephane Mallarme, Victor Segalen, and Jorge Luis Borges. Without any knowledge of the source languages, the authors crafted their own French and Spanish retellings based on received translations of these Asian works. Rewriting the Orient not only explores the so far untapped translation-rewriting continuum to trace the pivotal role of Orientalism in the formation of a singular corpus of world literature that goes beyond the Anglophone canon, but also sheds light on a wide range of innovative discursive strategies that readily challenge traditional notions of cultural appropriation.
This SpringerBrief presents a brief introduction to probabilistic risk assessment (PRA), followed by a discussion of abnormal event detection techniques in industrial control systems (ICS). It also provides an introduction to the use of game theory for the development of cyber-attack response models and a discussion on the experimental testbeds used for ICS cyber security research. The probabilistic risk assessment framework used by the nuclear industry provides a valid framework to understand the impacts of cyber-attacks in the physical world. An introduction to the PRA techniques such as fault trees, and event trees is provided along with a discussion on different levels of PRA and the application of PRA techniques in the context of cybersecurity. A discussion on machine learning based fault detection and diagnosis (FDD) methods and cyber-attack detection methods for industrial control systems are introduced in this book as well. A dynamic Bayesian networks based method that can be used to detect an abnormal event and classify it as either a component fault induced safety event or a cyber-attack is discussed. An introduction to the stochastic game formulation of the attacker-defender interaction in the context of cyber-attacks on industrial control systems to compute optimal response strategies is presented. Besides supporting cyber-attack response, the analysis based on the game model also supports the behavioral study of the defender and the attacker during a cyber-attack, and the results can then be used to analyze the risk to the system caused by a cyber-attack. A brief review of the current state of experimental testbeds used in ICS cybersecurity research and a comparison of the structures of various testbeds and the attack scenarios supported by those testbeds is included. A description of a testbed for nuclear power applications, followed by a discussion on the design of experiments that can be carried out on the testbed and the associated results is covered as well. This SpringerBrief is a useful resource tool for researchers working in the areas of cyber security for industrial control systems, energy systems and cyber physical systems. Advanced-level students that study these topics will also find this SpringerBrief useful as a study guide.
This brief introduces a class of problems and models for the prediction of the scalar field of interest from noisy observations collected by mobile sensor networks. It also introduces the problem of optimal coordination of robotic sensors to maximize the prediction quality subject to communication and mobility constraints either in a centralized or distributed manner. To solve such problems, fully Bayesian approaches are adopted, allowing various sources of uncertainties to be integrated into an inferential framework effectively capturing all aspects of variability involved. The fully Bayesian approach also allows the most appropriate values for additional model parameters to be selected automatically by data, and the optimal inference and prediction for the underlying scalar field to be achieved. In particular, spatio-temporal Gaussian process regression is formulated for robotic sensors to fuse multifactorial effects of observations, measurement noise, and prior distributions for obtaining the predictive distribution of a scalar environmental field of interest. New techniques are introduced to avoid computationally prohibitive Markov chain Monte Carlo methods for resource-constrained mobile sensors. Bayesian Prediction and Adaptive Sampling Algorithms for Mobile Sensor Networks starts with a simple spatio-temporal model and increases the level of model flexibility and uncertainty step by step, simultaneously solving increasingly complicated problems and coping with increasing complexity, until it ends with fully Bayesian approaches that take into account a broad spectrum of uncertainties in observations, model parameters, and constraints in mobile sensor networks. The book is timely, being very useful for many researchers in control, robotics, computer science and statistics trying to tackle a variety of tasks such as environmental monitoring and adaptive sampling, surveillance, exploration, and plume tracking which are of increasing currency. Problems are solved creatively by seamless combination of theories and concepts from Bayesian statistics, mobile sensor networks, optimal experiment design, and distributed computation.
This book provides a panoramic overview on wireless communication network technologies and its evolution, namely cellular mobile networks (especially 5G), Wireless Local Area Network (WLAN) and Narrow Band Internet of Things (NB-IoT).With rich experiences in teaching and scientific research, the renowned authors selectively analyze several key technologies that restrict the performance of wireless communication and computer networks.For easy reading, each chapter is illustrated in somewhat the style of lesson plan.The useful reference text will benefit both undergraduate and graduate students in the fields of wireless communication, computer networks, electronic engineering, automatic control, etc.
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