Wei Liu

Grounded in autoethnographic observations and informed by critical, postmodern, ethnographic, and narrative approaches, this work presents a new framework for intercultural communication education that aims to deconstruct normative intercultural paradigms. Critical scholars in intercultural communication education have advocated a shift from the essentialist approach, which focuses on the Western Centre, to a non-essentialist approach that treats all national cultures as equally complex, rich, and legitimate. However, deconstructing old frameworks is easier than constructing new alternatives. At the heart of this book lies the “Lebowski Shock”, an innovative theoretical construct that bridges the gap between the ideals of non-essentialist and non-stereotypical intercultural learning, and their practical implementation. It can overcome the human cognitive tendency toward essentialism and the entrenched power structures that perpetuate essentialist views. By offering a tangible and actionable framework, the “Lebowski Shock” equips readers with the tools to approach learning, teaching, and collaboration across diverse cultural contexts and foster open-ended, participatory, nuanced, and respectful intercultural engagement. This book will serve as an essential resource for scholars, educators, and students in intercultural communication education, as well as for anyone dedicated to promoting intercultural understanding.

This book shows that the stock market returns of hundreds of anomaly portfolios discovered by researchers in finance over the past three decades can be explained by a recent asset pricing model dubbed the ZCAPM. Anomaly portfolios are long/short portfolio returns on stocks that cannot be explained by asset pricing models, and their number has been steadily increasing into the hundreds. Since asset pricing models cannot explain them, behavioral theories have become popular to account for anomalies. Unlike the efficient market hypothesis that assumes rational investors, these human psychology-based theories emphasize irrational investor behavior. This book collects and analyzes a large database of U.S. stock returns for anomaly portfolios over a long sample period spanning approximately 60 years. The authors overview different asset pricing models that have attempted to explain anomalous portfolio returns in the stock market. They then provide a theoretical and empirical discussion of a new asset pricing model dubbed the ZCAPM and report compelling empirical evidence that reveals the ZCAPM can explain hundreds of anomalies. Implications to the efficient-markets/behavioral-finance controversy are discussed. The book will be of particular interest to researchers, students, and professors of capital markets, asset management, and financial economics alongside professionals.

This book first analyzes the institutional changes and historical value orientations brought about by China's economic reforms and then explores the justice and progressiveness of changes in social production relations, as well as the uniqueness of economic growth and macro control in China's institutional changes. It further delves into the effectiveness and qualitative improvement during the growth process, including the evolution of structural height, the formation of structural benefits, and the improvement of factor productivity and input–output efficiency. Finally, the book dissects the systemic motivation of China's economic growth and development and proposes the requirements for systemic changes to achieve sustainable development. The main innovation of this book lies in revealing the basic driving factors of the debate on the justice of institutional change from the perspective of value theory, deepening the understanding of China's reform and development experience,and emphasizing the importance of economic growth structure efficiency and total factor efficiency.

This book explores acupuncture's remarkable evolution in the United States over the last fifty years as it transitioned from an obscure practice to a pivotal modality in complementary medicine. These pages chronicle acupuncture's transformative journey within the dominant culture of Western scientific medicine, highlighting key milestones from the use of acupuncture in pain management to the NIH-sponsored open-access digital compendium of acupuncture points and related information. Through narratives detailing educational advancements, legislative battles, practical applications, and scientific research, the reader gains a comprehensive view of how acupuncture has navigated controversies and debates to secure its place in modern healthcare. This book traces acupuncture's expanding role in the healthcare system, reflects on its historical significance, and considers its future in global health. Insightful commentary provides acupuncture practitioners, skeptics, and aficionados with a useful overview of acupuncture's past, its current achievements and its promise for the future.

This book chooses four different transmission mechanisms of interest rate, credit, exchange rate, and asset price to study whether China’s monetary policy has an impact on these four transmission mechanisms and then studies whether these four transmission mechanisms have an impact on the macroeconomy, so as to determine the impact of China’s monetary policy on macro-goals.

A critical challenge in deep learning is the vulnerability of deep learning networks to security attacks from intelligent cyber adversaries. Even innocuous perturbations to the training data can be used to manipulate the behaviour of deep networks in unintended ways. In this book, we review the latest developments in adversarial attack technologies in computer vision; natural language processing; and cybersecurity with regard to multidimensional, textual and image data, sequence data, and temporal data. In turn, we assess the robustness properties of deep learning networks to produce a taxonomy of adversarial examples that characterises the security of learning systems using game theoretical adversarial deep learning algorithms. The state-of-the-art in adversarial perturbation-based privacy protection mechanisms is also reviewed. We propose new adversary types for game theoretical objectives in non-stationary computational learning environments. Proper quantificationof the hypothesis set in the decision problems of our research leads to various functional problems, oracular problems, sampling tasks, and optimization problems. We also address the defence mechanisms currently available for deep learning models deployed in real-world environments. The learning theories used in these defence mechanisms concern data representations, feature manipulations, misclassifications costs, sensitivity landscapes, distributional robustness, and complexity classes of the adversarial deep learning algorithms and their applications. In closing, we propose future research directions in adversarial deep learning applications for resilient learning system design and review formalized learning assumptions concerning the attack surfaces and robustness characteristics of artificial intelligence applications so as to deconstruct the contemporary adversarial deep learning designs. Given its scope, the book will be of interest to Adversarial Machine Learning practitioners and Adversarial Artificial Intelligence researchers whose work involves the design and application of Adversarial Deep Learning.

This book chooses four different transmission mechanisms of interest rate, credit, exchange rate, and asset price to study whether China’s monetary policy has an impact on these four transmission mechanisms and then studies whether these four transmission mechanisms have an impact on the macroeconomy, so as to determine the impact of China’s monetary policy on macro-goals.

A critical challenge in deep learning is the vulnerability of deep learning networks to security attacks from intelligent cyber adversaries. Even innocuous perturbations to the training data can be used to manipulate the behaviour of deep networks in unintended ways. In this book, we review the latest developments in adversarial attack technologies in computer vision; natural language processing; and cybersecurity with regard to multidimensional, textual and image data, sequence data, and temporal data. In turn, we assess the robustness properties of deep learning networks to produce a taxonomy of adversarial examples that characterises the security of learning systems using game theoretical adversarial deep learning algorithms. The state-of-the-art in adversarial perturbation-based privacy protection mechanisms is also reviewed. We propose new adversary types for game theoretical objectives in non-stationary computational learning environments. Proper quantificationof the hypothesis set in the decision problems of our research leads to various functional problems, oracular problems, sampling tasks, and optimization problems. We also address the defence mechanisms currently available for deep learning models deployed in real-world environments. The learning theories used in these defence mechanisms concern data representations, feature manipulations, misclassifications costs, sensitivity landscapes, distributional robustness, and complexity classes of the adversarial deep learning algorithms and their applications. In closing, we propose future research directions in adversarial deep learning applications for resilient learning system design and review formalized learning assumptions concerning the attack surfaces and robustness characteristics of artificial intelligence applications so as to deconstruct the contemporary adversarial deep learning designs. Given its scope, the book will be of interest to Adversarial Machine Learning practitioners and Adversarial Artificial Intelligence researchers whose work involves the design and application of Adversarial Deep Learning.

Integrated Human-Machine Intelligence: Beyond Artificial Intelligence focuses on deep situational awareness in human-computer integration, covering the interaction and integration mechanisms of human intelligence, machine intelligence and environmental systems. The book also details the cognitive, philosophical, social, scientific and technological, and military theories and methods of human-computer division, cooperation and collaborative decision-making to provide basic theoretical support for a development strategy in the field of national intelligence. Sections focus on describing a new form of intelligence produced by the interaction of human, machine and environmental systems which will become the next generation of AI. From the perspective of deep situational awareness in human-computer integration, the book studies the interaction and integration mechanisms of human intelligence, machine intelligence and environmental systems. In addition, it details the cognitive, philosophical, social, scientific and technological, and military theories and methods of human-computer division, cooperation and collaborative decision-making, so as to provide basic theoretical support for a development strategy in the field of national intelligence.

This book, for the first time, introduces comprehensively all main topics of lifeline earthquake engineering, including the structure analysis, network evaluation, and network design. The distinctive features involved in this book are the construction of theories and methods for stochastic analysis of structures based the physical idea, probability analytical algorithms for network evaluation by employing Boolean Algebra, functional evaluation of water distribution networks using hydraulic analysis, and network design methods by employing genetic, simulated annealing, and hybrid algorithms.

This book proposes a new capital asset pricing model dubbed the ZCAPM that outperforms other popular models in empirical tests using US stock returns. The ZCAPM is derived from Fischer Black’s well-known zero-beta CAPM, itself a more general form of the famous capital asset pricing model (CAPM) by 1990 Nobel Laureate William Sharpe and others. It is widely accepted that the CAPM has failed in its theoretical relation between market beta risk and average stock returns, as numerous studies have shown that it does not work in the real world with empirical stock return data. The upshot of the CAPM’s failure is that many new factors have been proposed by researchers. However, the number of factors proposed by authors has steadily increased into the hundreds over the past three decades. This new ZCAPM is a path-breaking asset pricing model that is shown to outperform popular models currently in practice in finance across different test assets and time periods.Since asset pricing is central to the field of finance, it can be broadly employed across many areas, including investment analysis, cost of equity analyses, valuation, corporate decision making, pension portfolio management, etc. The ZCAPM represents a revolution in finance that proves the CAPM as conceived by Sharpe and others is alive and well in a new form, and will certainly be of interest to academics, researchers, students, and professionals of finance, investing, and economics.

This book, for the first time, introduces comprehensively all main topics of lifeline earthquake engineering, including the structure analysis, network evaluation, and network design. The distinctive features involved in this book are the construction of theories and methods for stochastic analysis of structures based the physical idea, probability analytical algorithms for network evaluation by employing Boolean Algebra, functional evaluation of water distribution networks using hydraulic analysis, and network design methods by employing genetic, simulated annealing, and hybrid algorithms.

The problem with many machine learning classification algorithms is that their high level of accuracy is achieved at the cost of model comprehensibility, and with a consequent loss of justifiability: their mechanism cannot be shown to be reasonable because it cannot be explained. This has hindered their acceptance in sensitive domains, leading to growing demand for 'explainable AI'. In addition, the EU's recent GDPR legislation has elevated the issue to a legal requirement. If domain knowledge regarding nondecreasing (monotone) relationships could be incorporated into high performance classification algorithms without compromising their performance, the resulting increase in comprehensibility may allow them to surpass 'black box' barriers to acceptance and unlock their high accuracy for wider use. This book aims for 'complete' monotone classification algorithms, that: (a) are partially monotone (allow nonmonotone features); (b) guarantee monotonicity globally; (c) retain high accuracy; and (d) are scalable to large data sets. To achieve these aims, the book contains: - Explanation of the principles of ordinal classification, monotonicity and partial orders.- Extensive review of the literature and available monotone algorithms.- Several techniques for monotone tree-based ensembles (and Random Forest in particular).- Novel constraint generation for monotone Support Vector Machines.- Extension of cone-based dominance relations to partial monotonicity, for classification and pairwise and partial-order based problems.A panel of seventeen partially monotone datasets is used throughout the book to allow comparative empirical accuracy and performance of the many approaches discussed. It is hoped this book encourages and enables practitioners to include knowledge of monotonicity in their models when appropriate, for the sake of accuracy, simplicity, and interpretability.

Seismic Risk Analysis of Nuclear Power Plants addresses the needs of graduate students in engineering, practicing engineers in industry, and regulators in government agencies, presenting the entire process of seismic risk analysis in a clear, logical, and concise manner. It offers a systematic and comprehensive introduction to seismic risk analysis of critical engineering structures focusing on nuclear power plants, with a balance between theory and applications, and includes the latest advances in research. It is suitable as a graduate-level textbook, for self-study, or as a reference book. Various aspects of seismic risk analysis - from seismic hazard, demand, and fragility analyses to seismic risk quantification, are discussed, with detailed step-by-step analysis of specific engineering examples. It presents a wide range of topics essential for understanding and performing seismic risk analysis, including engineering seismology, probability theory and random processes, digital signal processing, structural dynamics, random vibration, and engineering risk and reliability.

Simultaneous confidence bands enable more intuitive and detailed inference of regression analysis than the standard inferential methods of parameter estimation and hypothesis testing. Simultaneous Inference in Regression provides a thorough overview of the construction methods and applications of simultaneous confidence bands for various inferential purposes. It supplies examples and MATLAB® programs that make it easy to apply the methods to your own data analysis. The MATLAB programs, along with color figures, are available for download on www.personal.soton.ac.uk/wl/mybook.htmlMost of the book focuses on normal-error linear regression models. The author presents simultaneous confidence bands for a simple regression line, a multiple linear regression model, and polynomial regression models. He also uses simultaneous confidence bands to assess part of a multiple linear regression model with the zero function, to compare two regression models, and to evaluate more than two regression models. The final chapter demonstrates the use of simultaneous confidence bands in generalized linear regression models, such as logistic regression models. This book shows how to employ simultaneous confidence bands to make useful inferences in regression analysis. The topics discussed can be extended to functions other than parametric regression functions, offering novel opportunities for research beyond linear regression models.

This new edition includes approximately 30% new materials covering the following information that has been added to this important work: extends the contents on Li-ion batteries detailing the positive and negative electrodes and characteristics and other components including binder, electrolyte, separator and foils, and the structure of Li-ion battery cell. Nickel-cadmium batteries are deleted.adds a new section presenting the modelling of multi-mode electrically variable transmission, which gradually became the main structure of the hybrid power-train during the last 5 years.newly added chapter on noise and vibration of hybrid vehicles introduces the basics of vibration and noise issues associated with power-train, driveline and vehicle vibrations, and addresses control solutions to reduce the noise and vibration levels. Chapter 10 (chapter 9 of the first edition) is extended by presenting EPA and UN newly required test drive schedules and test procedures for hybrid electric mileage calculation for window sticker considerations. In addition to the above major changes in this second edition, adaptive charging sustaining point determination method is presented to have a plug-in hybrid electric vehicle with optimum performance.

Fuel cell technology has attracted great interest in recent decades. However, progress in lignocellulosic biomass-energized fuel cells has been slow. This is because that lignocellulosic biomass generally cannot be directly used for electricity generation in a fuel cell with high efficiency. As a renewable resource is available in large quantities in many regions of the world, lignocellulosic biomass can be a promising feedstock for sustainable electricity production using fuel cell technologies. In this monograph, we focus on the electricity generation in fuel cells that are operated at high temperatures with high efficiency using lignocellulosic biomass-derived fuels. More specifically, we discussed biomass conversion coupled solid oxide fuel cell and direct carbon fuel cell. The state of the art in technology development, as well as challenges, is outlined and perspectives on future development are provided.

This book provides an introduction to the theory of stochastic partial differential equations (SPDEs) of evolutionary type. SPDEs are one of the main research directions in probability theory with several wide ranging applications. Many types of dynamics with stochastic influence in nature or man-made complex systems can be modelled by such equations. The theory of SPDEs is based both on the theory of deterministic partial differential equations, as well as on modern stochastic analysis. Whilst this volume mainly follows the ‘variational approach’, it also contains a short account on the ‘semigroup (or mild solution) approach’. In particular, the volume contains a complete presentation of the main existence and uniqueness results in the case of locally monotone coefficients. Various types of generalized coercivity conditions are shown to guarantee non-explosion, but also a systematic approach to treat SPDEs with explosion in finite time is developed. It is, so far, the only book where the latter and the ‘locally monotone case’ is presented in a detailed and complete way for SPDEs. The extension to this more general framework for SPDEs, for example, in comparison to the well-known case of globally monotone coefficients, substantially widens the applicability of the results.