Chinese art has experienced its most profound metamorphosis since the early 1950s, transforming from humble realism to socialist realism, from revolutionary art to critical realism, then avant-garde movement, and globalized Chinese art. With a hybrid mix of Chinese philosophy, imported but revised Marxist ideology, and western humanities, Chinese artists have created an alternative approach – after a great ideological and aesthetic transition in the 1980s – toward its own contemporaneity though interacting and intertwining with the art of rest of the world. This book will investigate, from the perspective of an activist, critic, and historian who grew up prior to and participated in the great transition, and then researched and taught the subject, the evolution of Chinese art in modern and contemporary times. The volume will be a comprehensive and insightful history of the one of the most sophisticated and unparalleled artistic and cultural phenomena in the modern world.
Public–Private Partnerships (PPP or 3Ps) allow the public sector to seek alternative funding and expertise from the private sector during procurement processes. Such partnerships, if executed with due diligence, often benefit the public immensely. Unfortunately, Public–Private Partnerships can be vulnerable to corruption. This book looks at what measures we can put in place to check corruption during procurement and what good governance strategies the public sector can adopt to improve the performance of 3Ps. The book applies mathematical models to analyze 3Ps. It uses game theory to study the interaction and dynamics between the stakeholders and suggests strategies to reduce corruption risks in various 3Ps stages. The authors explain through game theory-based simulation how governments can adopt a evaluating process at the start of each procurement to weed out undesirable private partners and why the government should take a more proactive approach. Using a methodological framework rooted in mathematical models to illustrate how we can combat institutional corruption, this book is a helpful reference for anyone interested in public policymaking and public infrastructure management.
The book examines a relatively unexplored issue in supply chain risk management, which is how long companies specifically take to respond to catastrophic events of low probability but high impact. The book also looks at why such supply chain disruptions are unavoidable, and consequently, all complex supply chains are inherently at risk. The book illustrates how companies can respond to supply chain disruptions with faster responses and in shorter lead-times to reduce impact. In reducing total response time, designing solutions, and deploying a recovery plan sooner after a disruption in anticipation of such events, companies reduce the impact of disruption risk. The book also explores the basics of multiple-criteria decision-making (MCDM) and analytic hierarchy process (AHP), and how they contribute to both the quality of the financial economic decision-making process and the quality of the resulting decisions. The book illustrates through cases in the construction sector how this industry has become more complex and riskier due to the diverse nature of activities among global companies.
Public-Private Partnership (PPP) is a channel through which the public sector can seek alternative funding and expertise from the private sector to procure public infrastructure. Governments around the world are increasingly turning to Public-Private Partnerships to deliver essential goods and services. Unfortunately, PPPs, like any other public procurement, can be at risk of corruption. This book begins by looking at the basics of PPP and the challenges of the PPP process. It then conceptualizes the vulnerability of various stages of Public-Private Partnership models and corruption risk against the backdrop of contract theory, principal-agent theory and transaction cost economics. The book also discusses potential control mechanisms. The book also stresses the importance of good governance for PPP. It outlines principles and procedures of project risk management (PRM) developed by a working party of the Association of Project Managers. Finally, the book concludes by proposing strategies and solutions to overcome the limitations and challenges of the current approach toward PPP.
This book provides a systematic overview of watermarking and steganography methods for triangle meshes related to computer graphics and security. The significance of this research has been well recognized by the growing body of work on watermarking, steganography and steganalysis of 3D meshes. With the evolution of the CAD industry and real-world end-user applications such as virtual reality (VR) and 3D printing, 3D meshes have attracted world-wide attention. Besides, the flexible data structure of 3D geometry provides enough space to embed secret information, making it ideal for applications such as copyright protection and covert communication. Our goal of the book is to allow readers to systematically understand 3D mesh information hiding technology and its applications as a whole. The book outlines comprehensive techniques, including handcrafted and deep learning-based techniques, digital and physical techniques in the literature and provides standard evaluation metrics for triangle meshes. The up-to-date geometrical deep learning and 3D printing-related algorithms are also covered. Offering a rich blend of ideas and algorithms, the book is up-to-date and self-contained. It is an excellent reference resource for users who are seeking 3D mesh watermarking and steganography algorithms, as well as for graduate students and researchers wanting to grasp the frontiers of triangular mesh processing on data hiding.
The manufacturing industry will reap significant benefits from encouraging the development of digital manufacturing science and technology. Digital Manufacturing Science uses theorems, illustrations and tables to introduce the definition, theory architecture, main content, and key technologies of digital manufacturing science. Readers will be able to develop an in-depth understanding of the emergence and the development, the theoretical background, and the techniques and methods of digital manufacturing science. Furthermore, they will also be able to use the basic theories and key technologies described in Digital Manufacturing Science to solve practical engineering problems in modern manufacturing processes. Digital Manufacturing Science is aimed at advanced undergraduate and postgraduate students, academic researchers and researchers in the manufacturing industry. It allows readers to integrate the theories and technologies described with their own research works, and to propose new ideas and new methods to improve the theory and application of digital manufacturing science.
This book provides an in-depth examination of recent research advances in cloud-edge-end computing, covering theory, technologies, architectures, methods, applications, and future research directions. It aims to present state-of-the-art models and optimization methods for fusing and integrating clouds, edges, and devices. Cloud-edge-end computing provides users with low-latency, high-reliability, and cost-effective services through the fusion and integration of clouds, edges, and devices. As a result, it is now widely used in various application scenarios. The book introduces the background and fundamental concepts of clouds, edges, and devices, and details the evolution, concepts, enabling technologies, architectures, and implementations of cloud-edge-end computing. It also examines different types of cloud-edge-end orchestrated systems and applications and discusses advanced performance modeling approaches, as well as the latest research on offloading and scheduling policies. It also covers resource management methods for optimizing application performance on cloud-edge-end orchestrated systems. The intended readers of this book are researchers, undergraduate and graduate students, and engineers interested in cloud computing, edge computing, and the Internet of Things. The knowledge of this book will enrich our readers to be at the forefront of cloud-edge-end computing.
Discover data analytics methodologies for the diagnosis and prognosis of industrial systems under a unified random effects model In Industrial Data Analytics for Diagnosis and Prognosis - A Random Effects Modelling Approach, distinguished engineers Shiyu Zhou and Yong Chen deliver a rigorous and practical introduction to the random effects modeling approach for industrial system diagnosis and prognosis. In the book’s two parts, general statistical concepts and useful theory are described and explained, as are industrial diagnosis and prognosis methods. The accomplished authors describe and model fixed effects, random effects, and variation in univariate and multivariate datasets and cover the application of the random effects approach to diagnosis of variation sources in industrial processes. They offer a detailed performance comparison of different diagnosis methods before moving on to the application of the random effects approach to failure prognosis in industrial processes and systems. In addition to presenting the joint prognosis model, which integrates the survival regression model with the mixed effects regression model, the book also offers readers: A thorough introduction to describing variation of industrial data, including univariate and multivariate random variables and probability distributions Rigorous treatments of the diagnosis of variation sources using PCA pattern matching and the random effects model An exploration of extended mixed effects model, including mixture prior and Kalman filtering approach, for real time prognosis A detailed presentation of Gaussian process model as a flexible approach for the prediction of temporal degradation signals Ideal for senior year undergraduate students and postgraduate students in industrial, manufacturing, mechanical, and electrical engineering, Industrial Data Analytics for Diagnosis and Prognosis is also an indispensable guide for researchers and engineers interested in data analytics methods for system diagnosis and prognosis.
This book examines the connection between central-local government relations and the transition of contemporary China, the urbanization process and social development. Based on empirical investigations and theoretical research, it argues that this is the key to understanding the transition of central-local government relations from the overall fiscal rationing system in the 1980s and the tax distribution system in the 1990s. The former system provided the incentive for local government to “set up a number of enterprises” and resulted in rapid local industrialization, while the latter system enabled the local governments to move from “operating the enterprises” to “operating the land and cities”. The book analyzes two aspects of the profound impact of the change in central-local government relations on the behavior of local governments: land quota acquisition and urbanization, thus providing valuable insights into the economic and social development of contemporary China.
Public–Private Partnerships (PPP or 3Ps) allow the public sector to seek alternative funding and expertise from the private sector during procurement processes. Such partnerships, if executed with due diligence, often benefit the public immensely. Unfortunately, Public–Private Partnerships can be vulnerable to corruption. This book looks at what measures we can put in place to check corruption during procurement and what good governance strategies the public sector can adopt to improve the performance of 3Ps. The book applies mathematical models to analyze 3Ps. It uses game theory to study the interaction and dynamics between the stakeholders and suggests strategies to reduce corruption risks in various 3Ps stages. The authors explain through game theory-based simulation how governments can adopt a evaluating process at the start of each procurement to weed out undesirable private partners and why the government should take a more proactive approach. Using a methodological framework rooted in mathematical models to illustrate how we can combat institutional corruption, this book is a helpful reference for anyone interested in public policymaking and public infrastructure management.
Public-Private Partnership (PPP) is a channel through which the public sector can seek alternative funding and expertise from the private sector to procure public infrastructure. Governments around the world are increasingly turning to Public-Private Partnerships to deliver essential goods and services. Unfortunately, PPPs, like any other public procurement, can be at risk of corruption. This book begins by looking at the basics of PPP and the challenges of the PPP process. It then conceptualizes the vulnerability of various stages of Public-Private Partnership models and corruption risk against the backdrop of contract theory, principal-agent theory and transaction cost economics. The book also discusses potential control mechanisms. The book also stresses the importance of good governance for PPP. It outlines principles and procedures of project risk management (PRM) developed by a working party of the Association of Project Managers. Finally, the book concludes by proposing strategies and solutions to overcome the limitations and challenges of the current approach toward PPP.
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