The Zhuangzi is one of the great classic Taoist texts. Zhuangzi (or Zhuang Tzu) himself was born during the upheavals and chaos of China' s Warring States period (475&– 221 BC). His outstanding written style, vivid and fantastical imagination and marvelous fables exercised a profound influence on the formation of traditional Chinese culture, whilst he himself occupied a commanding position amongst the thinkers of the day. He disdained worldly fame and profit and lived in transcendent calm and unaffected ease. Amidst the rush, busyness and ever-increasing tempo of life today it is easy to become lost and exhausted. However, Zhuangzi and his wisdom can teach us how to find spiritual comfort in this vast world of ours.This book takes the essence of Zhuangzi' s classic and in a single phrase or topic or even a story in its commentary provides us with a concise and original interpretation in an easily understood form. It combines the philosophy of the classic with modern life and takes the reader through 1,000 years of history. In this dialogue with the sages of Chinese philosophy there is both an exchange and collision of ideas that absorb a life force from their wisdom, provide an understanding of the real meaning of life and place us in the modern world, calm and confident in our conduct.Open this book and then, like the kunpeng, journey at will in the liberated poetic world of Zhuangzi.
This book is suitable for front-line personnel engaged in the design, construction and maintenance of tramway track engineering as a technical reference, and also provides theoretical reference for researchers in related fields.
Inductively Coupled Plasma-Atomic Emission Spectroscopy (ICP-AES) has been widely adopted as a routine analytical technique for elemental analysis in both industry and academia. However, spectral interference can be a major problem, particularly with such line-rich elements as the rare earth elements. An Atlas of High Resolution Spectra of Rare Earth Elements, which comes complete with a CD of spectra in full colour, is a reference source suitable for all analytical spectroscopists. Using some previously unpublished high resolution spectra, this atlas enables users of ICP-AES to select the best lines of any single rare earth element matrix. Clear instructions for the use of the accompanying CD are provided, which allows all adjacent interferent spectral profiles to be displayed and superimposed. Up-to-date and informative, this unique book will be welcomed as a practical and indispensable reference guide by all those who use ICP-AES for the analysis of rare earth elements.
This book covers connectivity and edge computing solutions for representative Internet of Things (IoT) use cases, including industrial IoT, rural IoT, Internet of Vehicles (IoV), and mobile virtual reality (VR). Based on their unique characteristics and requirements, customized solutions are designed with targets such as supporting massive connections or seamless mobility and achieving low latency or high energy efficiency. Meanwhile, the book highlights the role of artificial intelligence (AI) in future IoT networks and showcases AI-based connectivity and edge computing solutions. The solutions presented in this book serve the overall purpose of facilitating an increasingly connected and intelligent world. The potential benefits of the solutions include increased productivity in factories, improved connectivity in rural areas, enhanced safety for vehicles, and enriched entertainment experiences for mobile users. Featuring state-of-the-art research in the IoT field, this book can help answer the question of how to connect billions of diverse devices and enable seamless data collection and processing in future IoT. The content also provides insights regarding the significance of customizing use case-specific solutions as well as approaches of using various AI methods to empower IoT. This book targets researchers and graduate students working in the areas of electrical engineering, computing engineering, and computer science as a secondary textbook or reference. Professionals in industry who work in the field of IoT will also find this book useful.
This thesis reports on the development of a fully integrated and automated microsystem consisting of low-cost, disposable plastic chips for DNA extraction and PCR amplification, combined with a reusable glass capillary array electrophoresis chip, which can be employed in a modular-based format for genetic analysis. In the thesis, DNA extraction is performed by adopting a filter paper-based method, followed by an “in-situ” PCR carried out directly in the same reaction chamber of the chip without elution. PCR products are then co-injected with sizing standards into separation channels for detection using a novel injection electrode. The entire process is automatically carried out by a custom-made compact control and detection instrument. The author thoroughly tests the system’s performance and reliability by conducting rapid genetic screening of mutations on congenital hearing loss and pharmacogenetic typing of multiple warfarin-related single-nucleotide polymorphisms. The successful development and operation of this microsystem establishes the feasibility of rapid “sample-in-answer-out” testing in routine clinical practice.
Robot calibration is the process of enhancing the accuracy of a robot by modifying its control software. This book provides a comprehensive treatment of the theory and implementation of robot calibration using computer vision technology. It is the only book to cover the entire process of vision-based robot calibration, including kinematic modeling, camera calibration, pose measurement, error parameter identification, and compensation. The book starts with an overview of available techniques for robot calibration, with an emphasis on vision-based techniques. It then describes various robot-camera systems. Since cameras are used as major measuring devices, camera calibration techniques are reviewed. Camera-Aided Robot Calibration studies the properties of kinematic modeling techniques that are suitable for robot calibration. It summarizes the well-known Denavit-Hartenberg (D-H) modeling convention and indicates the drawbacks of the D-H model for robot calibration. The book develops the Complete and Parametrically Continuous (CPC) model and the modified CPC model, that overcome the D-H model singularities. The error models based on these robot kinematic modeling conventions are presented. No other book available addresses the important, practical issue of hand/eye calibration. This book summarizes current research developments and demonstrates the pros and cons of various approaches in this area. The book discusses in detail the final stage of robot calibration - accuracy compensation - using the identified kinematic error parameters. It offers accuracy compensation algorithms, including the intuitive task-point redefinition and inverse-Jacobian algorithms and more advanced algorithms based on optimal control theory, which are particularly attractive for highly redundant manipulators. Camera-Aided Robot Calibration defines performance indices that are designed for off-line, optimal selection of measurement configurations. It then describes three approaches: closed-form, gradient-based, and statistical optimization. The included case study presents experimental results that were obtained by calibrating common industrial robots. Different stages of operation are detailed, illustrating the applicability of the suggested techniques for robot calibration. Appendices provide readers with preliminary materials for easier comprehension of the subject matter. Camera-Aided Robot Calibration is a must-have reference for researchers and practicing engineers-the only one with all the information!
China has experienced rapid economic growth over the past two decades and is on the brink of eradicating poverty. However, income inequality increased sharply from the early 1980s and rendered China among the most unequal countries in the world. This trend has started to reverse as China has experienced a modest decline in inequality since 2008. This paper identifies various drivers behind these trends – including structural changes such as urbanization and aging and, more recently, policy initiatives to combat it. It finds that policies will need to play an important role in curbing inequality in the future, as projected structural trends will put further strain on equity considerations. In particular, fiscal policy reforms have the potential to enhance inclusiveness and equity, both on the tax and expenditure side.
This book provides a timely and comprehensive study of dynamic resource management for network slicing in service-oriented fifth-generation (5G) and beyond core networks. This includes the perspective of developing efficient computation resource provisioning and scheduling solutions to guarantee consistent service performance in terms of end-to-end (E2E) data delivery delay. Network slicing is enabled by the software defined networking (SDN) and network function virtualization (NFV) paradigms. For a network slice with a target traffic load, the E2E service delivery is enabled by virtual network function (VNF) placement and traffic routing with static resource allocations. When data traffic enters the network, the traffic load is dynamic and can deviate from the target value, potentially leading to QoS performance degradation and network congestion. Data traffic has dynamics in different time granularities. For example, the traffic statistics (e.g., mean and variance) can be non-stationary and experience significant changes in a coarse time granularity, which are usually predictable. Within a long time duration with stationary traffic statistics, there are traffic dynamics in small timescales, which are usually highly bursty and unpredictable. To provide continuous QoS performance guarantee and ensure efficient and fair operation of the network slices over time, it is essential to develop dynamic resource management schemes for the embedded services in the presence of traffic dynamics during virtual network operation. Queueing theory is used in system modeling, and different techniques including optimization and machine learning are applied to solving the dynamic resource management problems. Based on a simplified M/M/1 queueing model with Poisson traffic arrivals, an optimization model for flow migration is presented to accommodate the large-timescale changes in the average traffic rates with average E2E delay guarantee, while addressing a trade-off between load balancing and flow migration overhead. To overcome the limitations of Poisson traffic model, the authors present a machine learning approach for dynamic VNF resource scaling and migration. The new solution captures the inherent traffic patterns in a real-world traffic trace with non-stationary traffic statistics in large timescale, predicts resource demands for VNF resource scaling, and triggers adaptive VNF migration decision making, to achieve load balancing, migration cost reduction, and resource overloading penalty suppression in the long run. Both supervised and unsupervised machine learning tools are investigated for dynamic resource management. To accommodate the traffic dynamics in small time granularities, the authors present a dynamic VNF scheduling scheme to coordinate the scheduling among VNFs of multiple services, which achieves network utility maximization with delay guarantee for each service. Researchers and graduate students working in the areas of electrical engineering, computing engineering and computer science will find this book useful as a reference or secondary text. Professionals in industry seeking solutions to dynamic resource management for 5G and beyond networks will also want to purchase this book.
Thank you for visiting our website. Would you like to provide feedback on how we could improve your experience?
This site does not use any third party cookies with one exception — it uses cookies from Google to deliver its services and to analyze traffic.Learn More.