Bøker av Chuan Zhang

This book guides readers into the realm of particle accelerators, which have served as indispensable tools for fundamental research, energy development, medical therapy, industrial applications, national security, etc., since 1924. Towards a new generation of high power proton and ion accelerators, challenges often come from space charge effects, which are most pronounced in low-velocity beams. This book focuses on Radio-Frequency Quadrupole (RFQ) accelerators, one of the most popular front-end structures for accelerator facilities, and their beam physics. Uncovering the limitations of the classic design methods, novel approaches to achieve efficient RFQ accelerators with high beam quality will be presented. In addition, new ideas for possible future developments, such as how to realize long RFQs with high performance and how RFQs can be applied for much higher beam-velocities to shorten large-scale accelerators, will be introduced. To provide a general overview of the research and development of RFQs accelerating particle species from protons to uranium ions, this book uses over 10 real examples developed or proposed in the twenty-first century for various facilities of different dimensions (from large scale e.g. a collider to small scale e.g. university experimental setups). With its rich content and comprehensive scope, this book is an invaluable reference for researchers and graduate students interested in RFQ accelerators and the intricacies of space charge physics in low-velocity beams.

Mobile crowdsensing is a new sensing paradigm that utilizes the intelligence of a crowd of individuals to collect data for mobile purposes by using their portable devices, such as smartphones and wearable devices. Commonly, individuals are incentivized to collect data to fulfill a crowdsensing task released by a data requester. This ¿sensing as a service¿ elaborates our knowledge of the physical world by opening up a new door of data collection and analysis. However, with the expansion of mobile crowdsensing, privacy issues urgently need to be solved.In this book, we discuss the research background and current research process of privacy protection in mobile crowdsensing. In the first chapter, the background, system model, and threat model of mobile crowdsensing are introduced. The second chapter discusses the current techniques to protect user privacy in mobile crowdsensing. Chapter three introduces the privacy-preserving content-based task allocation scheme. Chapter fourfurther introduces the privacy-preserving location-based task scheme. Chapter five presents the scheme of privacy-preserving truth discovery with truth transparency. Chapter six proposes the scheme of privacy-preserving truth discovery with truth hiding. Chapter seven summarizes this monograph and proposes future research directions.In summary, this book introduces the following techniques in mobile crowdsensing: 1) describe a randomizable matrix-based task-matching method to protect task privacy and enable secure content-based task allocation; 2) describe a multi-clouds randomizable matrix-based task-matching method to protect location privacy and enable secure arbitrary range queries; and 3) describe privacy-preserving truth discovery methods to support efficient and secure truth discovery. These techniques are vital to the rapid development of privacy-preserving in mobile crowdsensing.