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.

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 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.

The Grand Scribe's Records, Volume VI, contains annotated translations of the "hereditary houses" for the Ch'in and Han dynasties. Such "houses" were an invention of Ssu-ma Ch'ien and in early periods treated the history of various states. Here, however, the subjects vary, often containing merely biographies of their main protagonist. The volume begins with an account of the rebel Ch'en She in chapter 48, whose "house" consisted of the other rebel leaders he spawned into action against the Ch'in dynasty, and ends in chapter 60 with the memorials concerning the reigns of the sons of Emperor Wu of the Han born to concubines, men whose reigns ended badly. Besides accounts of the kings from the royal Liu family, included are the stories of the maternal relatives, empresses, and imperial consorts, as well as the major statesmen and military leaders who guided the Han victory.

"An essential source for the study of events in early China, a guide to the moral philosophy of the gentlemen of Han, and a splendid work of literature which may be read for the pleasure of its style and the power of its narrative. . . . This work makes Shi ji and its scholarship accessible to any reader of English, and it is a model for any work in this field and style." -Bulletin of the School of Oriental and African Studies "Through such work as this, the scholarly and literary community of the West will learn more of the splendor and romance of early China, and may better appreciate the lessons in humanity presented by its great historian." -Bulletin of the School of Oriental and African Studies "Nienhauser's new translation is scrupulously scholarly . . . the design of this series is nearly flawless . . . the translation itself is very precise." -Chinese Literature: Essays, Articles, Reviews This project will result in the first complete translation (in nine volumes) of the Shih chi (The Grand Scribe's Records), one of the most important narratives in traditional China. Ssu-ma Ch'ien (145-ca. 86 BC), who compiled the work, is known as the Herodotus of China.

With Part I of the two-part fifth volume of Ssu-ma Ch ien s Shi chi (The Grand Scribe s Records), we enter the world of the shih chia or "hereditary houses." These ten chapters trace the history of China s first states, from their establishment in the 11th century B.C. until their incorporation in the first empire under the Ch in in 221 B.C. Combining myth, anecdote, chronicle, and biography based on early written and oral sources, many no longer extant, the narratives make for compelling reading, as dramatic and readable as any in this grand history."