With the proliferation of GPS devices in daily life, trajectory data that records where and when people move is now readily available on a large scale. As one of the most typical representatives, it has now become widely recognized that taxi trajectory data provides rich opportunities to enable promising smart urban services. Yet, a considerable gap still exists between the raw data available, and the extraction of actionable intelligence. This gap poses fundamental challenges on how we can achieve such intelligence. These challenges include inaccuracy issues, large data volumes to process, and sparse GPS data, to name but a few. Moreover, the movements of taxis and the leaving trajectory data are the result of a complex interplay between several parties, including drivers, passengers, travellers, urban planners, etc. In this book, we present our latest findings on mining taxi GPS trajectory data to enable a number of smart urban services, and to bring us one step closer to the vision of smart mobility. Firstly, we focus on some fundamental issues in trajectory data mining and analytics, including data map-matching, data compression, and data protection. Secondly, driven by the real needs and the most common concerns of each party involved, we formulate each problem mathematically and propose novel data mining or machine learning methods to solve it. Extensive evaluations with real-world datasets are also provided, to demonstrate the effectiveness and efficiency of using trajectory data. Unlike other books, which deal with people and goods transportation separately, this book also extends smart urban services to goods transportation by introducing the idea of crowdshipping, i.e., recruiting taxis to make package deliveries on the basis of real-time information. Since people and goods are two essential components of smart cities, we feel this extension is bot logical and essential. Lastly, we discuss the most important scientific problems and open issues in mining GPS trajectory data.

This book explores the application of a significant discussion approach, Quality Talk, to English learning in Taiwanese college classrooms. Quality Talk has been found to successfully enhance students' reading comprehension and higher-level thinking in American contexts. It offers an introduction to Quality Talk and demonstrates how it can be implemented in college level English classes. It addresses students' three levels of English proficiency: elementary, intermediate, and advanced. The respective chapters discuss a range of aspects: students' language proficiency levels, students' own viewpoints on the discussion approach, students' academic backgrounds, teaching materials, and culture-based learning. Readers will gain valuable insights into the Quality Talk approach and how it can be implemented in the classroom.

This book explores the application of a significant discussion approach, Quality Talk, to English learning in Taiwanese college classrooms. Quality Talk has been found to successfully enhance students' reading comprehension and higher-level thinking in American contexts. It offers an introduction to Quality Talk and demonstrates how it can be implemented in college level English classes. It addresses students' three levels of English proficiency: elementary, intermediate, and advanced. The respective chapters discuss a range of aspects: students' language proficiency levels, students' own viewpoints on the discussion approach, students' academic backgrounds, teaching materials, and culture-based learning. Readers will gain valuable insights into the Quality Talk approach and how it can be implemented in the classroom.

This book uncovers the mysterious social and political structures of China's "Third Front," the large state-sponsored development of inland China during the late Maoist period. This movement gave birth to a few important industrial bases such as Panzhihua and Liupanshui and had significant impact on megacities such as Lanzhou, Wuhan, and Chongqing. Yet, this is scarcely known to the West and even the younger generation of Chinese. Chen explores the ways that new industrial structures and hierarchies were created and operated, using political and sociological methodologies to understand what is distinctive in the history of the Chinese corporation. This book will be of immense interest to political scientists, sociologists, China scholars, and researchers of alternative economic structures.

This book uncovers the mysterious social and political structures of China's "Third Front," the large state-sponsored development of inland China during the late Maoist period. This movement gave birth to a few important industrial bases such as Panzhihua and Liupanshui and had significant impact on megacities such as Lanzhou, Wuhan, and Chongqing. Yet, this is scarcely known to the West and even the younger generation of Chinese. Chen explores the ways that new industrial structures and hierarchies were created and operated, using political and sociological methodologies to understand what is distinctive in the history of the Chinese corporation. This book will be of immense interest to political scientists, sociologists, China scholars, and researchers of alternative economic structures.

The papers included in this volume were presented at the Symposium on Advances in the Continuum Mechanics and Thermodynamics of Material Behavior, held as part of the 1999 Joint ASME Applied Mechanics and Materials Summer Conference at Virginia Tech on June 27-30, 1999. The Symposium was held in honor of Professor Roger L. Fosdick on his 60th birthday. The papers are written by prominent researchers in the fields of mechanics, thermodynamics, materials modeling, and applied mathematics. They address open questions and present the latest development in these and related areas. This volume is a valuable reference for researchers and graduate students in universities and research laboratories.

The papers included in this volume were presented at the Symposium on Advances in the Continuum Mechanics and Thermodynamics of Material Behavior, held as part of the 1999 Joint ASME Applied Mechanics and Materials Summer Conference at Virginia Tech on June 27-30, 1999. The Symposium was held in honor of Professor Roger L. Fosdick on his 60th birthday. The papers are written by prominent researchers in the fields of mechanics, thermodynamics, materials modeling, and applied mathematics. They address open questions and present the latest development in these and related areas. This volume is a valuable reference for researchers and graduate students in universities and research laboratories.

With the proliferation of GPS devices in daily life, trajectory data that records where and when people move is now readily available on a large scale. As one of the most typical representatives, it has now become widely recognized that taxi trajectory data provides rich opportunities to enable promising smart urban services. Yet, a considerable gap still exists between the raw data available, and the extraction of actionable intelligence. This gap poses fundamental challenges on how we can achieve such intelligence. These challenges include inaccuracy issues, large data volumes to process, and sparse GPS data, to name but a few. Moreover, the movements of taxis and the leaving trajectory data are the result of a complex interplay between several parties, including drivers, passengers, travellers, urban planners, etc. In this book, we present our latest findings on mining taxi GPS trajectory data to enable a number of smart urban services, and to bring us one step closer to the vision of smart mobility. Firstly, we focus on some fundamental issues in trajectory data mining and analytics, including data map-matching, data compression, and data protection. Secondly, driven by the real needs and the most common concerns of each party involved, we formulate each problem mathematically and propose novel data mining or machine learning methods to solve it. Extensive evaluations with real-world datasets are also provided, to demonstrate the effectiveness and efficiency of using trajectory data. Unlike other books, which deal with people and goods transportation separately, this book also extends smart urban services to goods transportation by introducing the idea of crowdshipping, i.e., recruiting taxis to make package deliveries on the basis of real-time information. Since people and goods are two essential components of smart cities, we feel this extension is bot logical and essential. Lastly, we discuss the most important scientific problems and open issues in mining GPS trajectory data.

This book focuses on information literacy in higher education from Asian countries. It explores the changing concepts, philosophies, learning environments, and technological environments of information literacy and discusses how information literacy education in universities should be carried out in the context of the information literacy framework. It also analyses the research focus and trends of information literacy education in universities in the past ten years worldwide and Asia by using the bibliometric method as well as the information literacy education models of universities in Asian countries. In addition, this book also explains the current status of information literacy education and related issues in Taiwan, Japan, Hong Kong, Malaysia, Thailand and Vietnam. The target audience of this book is mainly university librarians, school librarians, the faculty and students of library and information sciences, information education and technology education related departments worldwide.

This book provides insight into domino effects in industrial chemical sites and process industries. It is about the integration of safety and security resources to prevent and mitigate domino effects in the process industries. It explains how chemical industrial areas, comprised of various hazardous installations, are susceptible to a chain of undesired events, or domino effects, triggered by accidental events or intentional attacks and then presents solutions to prevent them. Firstly, the book provides a dynamic graph approach to model the domino effects induced by accidental fire or intentional fire, considering the spatial-temporal evolution of fires. Then, a dynamic risk assessment method based on a discrete dynamic event tree is proposed to assess the likelihood of VCEs and the vulnerability of installations, addressing the time dependencies in vapor cloud dispersion and the uncertainty of delayed ignitions. A dynamic methodology based on dynamic graphs and Monte Carlo is provided to assess the vulnerability of individuals and installations exposed to multi-hazards, such as fire, explosion and toxic release during escalation events. Based on these domino effect models, an economic approach is developed to integrate safe and security resources, obtaining the most cost-benefit protection strategy for preventing domino effects. Finally, a resilience-based approach is provided to find out the most cost-resilient way to protect chemical industrial areas, addressing possible domino effects. This integrated approach will be of interest to researchers, industrial engineers, chemical engineers and safety managers and will help professionals to new solutions in the area of safety and security.

This book investigates compressive sensing techniques to provide a robust and general framework for network data analytics. The goal is to introduce a compressive sensing framework for missing data interpolation, anomaly detection, data segmentation and activity recognition, and to demonstrate its benefits. Chapter 1 introduces compressive sensing, including its definition, limitation, and how it supports different network analysis applications. Chapter 2 demonstrates the feasibility of compressive sensing in network analytics, the authors we apply it to detect anomalies in the customer care call dataset from a Tier 1 ISP in the United States. A regression-based model is applied to find the relationship between calls and events. The authors illustrate that compressive sensing is effective in identifying important factors and can leverage the low-rank structure and temporal stability to improve the detection accuracy. Chapter 3 discusses that there are several challenges in applying compressive sensing to real-world data. Understanding the reasons behind the challenges is important for designing methods and mitigating their impact. The authors analyze a wide range of real-world traces. The analysis demonstrates that there are different factors that contribute to the violation of the low-rank property in real data. In particular, the authors find that (1) noise, errors, and anomalies, and (2) asynchrony in the time and frequency domains lead to network-induced ambiguity and can easily cause low-rank matrices to become higher-ranked. To address the problem of noise, errors and anomalies in Chap. 4, the authors propose a robust compressive sensing technique. It explicitly accounts for anomalies by decomposing real-world data represented in matrix form into a low-rank matrix, a sparse anomaly matrix, an error term and a small noise matrix. Chapter 5 addresses the problem of lack of synchronization, and the authors propose a data-driven synchronization algorithm. It can eliminate misalignment while taking into account the heterogeneity of real-world data in both time and frequency domains. The data-driven synchronization can be applied to any compressive sensing technique and is general to any real-world data. The authors illustrates that the combination of the two techniques can reduce the ranks of real-world data, improve the effectiveness of compressive sensing and have a wide range of applications. The networks are constantly generating a wealth of rich and diverse information. This information creates exciting opportunities for network analysis and provides insight into the complex interactions between network entities. However, network analysis often faces the problems of (1) under-constrained, where there is too little data due to feasibility and cost issues in collecting data, or (2) over-constrained, where there is too much data, so the analysis becomes unscalable. Compressive sensing is an effective technique to solve both problems. It utilizes the underlying data structure for analysis. Specifically, to solve the under-constrained problem, compressive sensing technologies can be applied to reconstruct the missing elements or predict the future data. Also, to solve the over-constraint problem, compressive sensing technologies can be applied to identify significant elements To support compressive sensing in network data analysis, a robust and general framework is needed to support diverse applications. Yet this can be challenging for real-world data where noise, anomalies and lack of synchronization are common. First, the number of unknowns for network analysis can be much larger than the number of measurements. For example, traffic engineering requires knowing the complete traffic matrix between all source and destination pairs, in order to properly configure traffic and avoid congestion. However, measuring the flow between all source and destination pairs is very expensive or even infeasible. Reconstructing data from a small number of measurements is an underconstrained problem. In addition, real-world data is complex and heterogeneous, and often violate the low-level assumptions required by existing compressive sensing techniques. These violations significantly reduce the applicability and effectiveness of existing compressive sensing methods. Third, synchronization of network data reduces the data ranks and increases spatial locality. However, periodic time series exhibit not only misalignment but also different frequencies, which makes it difficult to synchronize data in the time and frequency domains. The primary audience for this book is data engineers, analysts and researchers, who need to deal with big data with missing anomalous and synchronization problems. Advanced level students focused on compressive sensing techniques will also benefit from this book as a reference.

Smart Metro Station Systems: Data Science and Engineering introduces key technologies in data science and engineering for smart metro station systems. The book consists of three main parts, focusing on the environment, people and energy. Each chapter includes practical applications, along with information on metro traffic flow monitoring and passenger guidance, methods for behavior analysis and trajectory projection, clustering and anomaly detection in crowd hotspots, monitoring and prediction for station humidity, monitoring and spatial prediction for air pollutants, time series feature extraction and analysis of metro load, characteristic and correlation analysis of metro load, and prediction and intelligent ventilation control. This volume offers a key reference on the emerging area of smart metro stations and will be useful to those working on smart railways, data science, engineering, artificial intelligence and aligned fields.

This book constitutes the refereed proceedings of the 15th International Conference on Network and System Security, NSS 2021, held in Tianjin, China, on October 23, 2021. The 16 full and 8 short papers presented in this book were carefully reviewed and selected from 62 submissions. They focus on theoretical and practical aspects of network and system security, such as authentication, access control, availability, integrity, privacy, confidentiality, dependability and sustainability of computer networks and systems.

This book provides insight into domino effects in industrial chemical sites and process industries. It is about the integration of safety and security resources to prevent and mitigate domino effects in the process industries. It explains how chemical industrial areas, comprised of various hazardous installations, are susceptible to a chain of undesired events, or domino effects, triggered by accidental events or intentional attacks and then presents solutions to prevent them. Firstly, the book provides a dynamic graph approach to model the domino effects induced by accidental fire or intentional fire, considering the spatial-temporal evolution of fires. Then, a dynamic risk assessment method based on a discrete dynamic event tree is proposed to assess the likelihood of VCEs and the vulnerability of installations, addressing the time dependencies in vapor cloud dispersion and the uncertainty of delayed ignitions. A dynamic methodology based on dynamic graphs and Monte Carlo is provided to assess the vulnerability of individuals and installations exposed to multi-hazards, such as fire, explosion and toxic release during escalation events. Based on these domino effect models, an economic approach is developed to integrate safe and security resources, obtaining the most cost-benefit protection strategy for preventing domino effects. Finally, a resilience-based approach is provided to find out the most cost-resilient way to protect chemical industrial areas, addressing possible domino effects. This integrated approach will be of interest to researchers, industrial engineers, chemical engineers and safety managers and will help professionals to new solutions in the area of safety and security.

This book constitutes the refereed proceedings of the 14th International Conference on Network and System Security, NSS 2020, held in Melbourne, VIC, Australia, in November 2020. The 17 full and 9 short papers were carefully reviewed and selected from 60 submissions. The selected papers are devoted to topics such as secure operating system architectures, applications programming and security testing, intrusion and attack detection, cybersecurity intelligence, access control, cryptographic techniques, cryptocurrencies, ransomware, anonymity, trust, recommendation systems, as well machine learning problems. Due to the Corona pandemic the event was held virtually.

This book constitutes the refereed proceedings of the 13th China Conference on Wireless Sensor Networks, CWSN 2019, held in Chongqing, China, in October 2019. The 27 full papers were carefully reviewed and selected from 158 submissions. The papers are organized in topical sections on fundamentals on Internet of Things; applications on Internet of Things; and IntelliSense, location and tracking.

"A Trip to China" is an intermediate Chinese language textbook designed for students who have studied one year of college Chinese. Offering a strong foundation in grammar and vocabulary, it is written from the perspective of a foreign exchange student who has just arrived in China for the first time. This thoroughly revised edition not only provides students essential lessons for advancing their Chinese language skills, but also introduces important aspects of contemporary Chinese society and culture.

The textbook incorporates suggestions from years of student and teacher feedback, and includes new lessons as well as updated vocabulary glosses, grammar explanations, and exercises. An improved format juxtaposes text and vocabulary on adjacent pages and combines grammar notes and exercises into one easy-to-use volume.Intermediate-level Chinese language textbookRevised edition Single-volume, user-friendly format New lessons and updated vocabulary, grammar explanations, and exercises Introduces students to important aspects of contemporary Chinese society and culture

This article focuses on the research of RTDI policies (research, technology, development and innovation), and the theme of this article is to link the three indicators together: RTDI policy-making process-the contents of RTDI policies-the appropriateness of RTDI policies on the configuration of the national, the sectoral and the technological innovation systems. We define the configuration of the three innovation systems as national, sectoral and technological innovation system (NSTIS). We assume the policy-making process of RTDI policies would shape the contents of RTDI policies. Once the contents of RTDI policies are implemented, the RTDI policies would influence, whether appropriate or inappropriate, on the NSTIS. We use the Taiwanese pharmaceutical biotechnology policies as empirical cases. On the basis of the empirical cases of Taiwan, we find that the consistency and appropriateness of RTDI policies are shaped by four variables: polity, horizontal coordination, vertical coordination and the involvement of external stakeholders. The policy-making process indeed shapes the RTDI policies which further shape the development of NSTIS.