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.

The use of contextually aware, pervasive, distributed computing, and sensor networks to bridge the gap between the physical and online worlds is the basis of mobile social networking. This book shows how applications can be built to provide mobile social networking, the research issues that need to be solved to enable this vision, and how mobile social networking can be used to provide computational intelligence that will improve daily life. With contributions from the fields of sociology, computer science, human-computer interaction and design, this book demonstrates how mobile social networks can be inferred from users' physical interactions both with the environment and with others, as well as how users behave around them and how their behavior differs on mobile vs. traditional online social networks.

The use of contextually aware, pervasive, distributed computing, and sensor networks to bridge the gap between the physical and online worlds is the basis of mobile social networking. This book shows how applications can be built to provide mobile social networking, the research issues that need to be solved to enable this vision, and how mobile social networking can be used to provide computational intelligence that will improve daily life. With contributions from the fields of sociology, computer science, human-computer interaction and design, this book demonstrates how mobile social networks can be inferred from users' physical interactions both with the environment and with others, as well as how users behave around them and how their behavior differs on mobile vs. traditional online social networks.

This volume contains the proceedings of UIC 2009, the 6th International C- ference on Ubiquitous Intelligence and Computing: Building Smart Worlds in Real and Cyber Spaces. The UIC 2009 conference was technically co-sponsored by the IEEE and the IEEE Computer Society Technical Committee on Scalable Computing. The conference was also sponsored by the Australian Centre of - cellence in Information and Communication Technologies (NICTA). UIC 2009 was accompanied by six workshops on a variety of research challenges within the area of ubiquitous intelligence and computing. The conference was held in Brisbane, Australia, July 7-9, 2009. The event was the sixth meeting of this conference series. USW 2005 (First International Workshop on Ubiquitous Smart World), held in March 2005 in Taiwan, was the ?rst event in the series. This event was followed by UISW 2005 (Second International Symposium on Ubiquitous Intelligence and Smart Worlds) held in December 2005 in Japan. Since 2006, the conference has been held annually under the name UIC (International Conference on Ubiquitous Intelligence and Computing). UIC 2006 was held in September 2006 in Wuhan andThreeGorges, China, followedbyUIC2007heldinJuly2007inHongKong, and UIC 2008 held in June 2008 in Oslo, Norway. Ubiquitous sensors, computers, networksand informationare paving the way towardasmartworldinwhichcomputationalintelligenceisdistributedthrou- out the physical environment to provide reliable and relevant services to peop

This book constitutes the refereed proceedings of the 7th International Conference On Smart Homes and and Health Telematics, ICOST 2009, held in Tours, France, in July 2009. The 27 revised full papers and 20 short papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on cognitive assistance and chronic diseases management; ambient living systems; service continuity and context awareness; user modeling and human-machine interaction; ambient intelligence modeling and privacy issues, human behavior and activities monitoring.

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.

Nobel laureate Tu Youyou won the 2015 prize for Medicine/Physiology for the discovery of artemisinin, a drug therapy for malaria that has saved millions across the globe.This book traces the path of discovery beginning with Chairman Mao's 1964 instruction to Chinese researchers to find a cure for malaria, a disease that plagued the military and civilians alike in endemic regions. It chronicles the years of painstaking research to find effective anti-malarial drugs, and how an entry in a collection of traditional Chinese medicine prescriptions gave Tu Youyou the clue which led her to successfully extract artemisinin from the plant, Artemisia annua.Gathering together information from a variety of sources including first-hand accounts, this book describes the contributions of the many organisations, scientists, doctors and countless others who played a part in the process of discovery and clinical testing. It also provides insights into the challenges of carrying out such an extensive research project with limited resources during the upheavals of the Cultural Revolution. An inspirational read for young scientists.Includes the translation of Professor Tu Youyou's 2015 Nobel Lecture.

Nobel laureate Tu Youyou won the 2015 prize for Medicine/Physiology for the discovery of artemisinin, a drug therapy for malaria that has saved millions across the globe.This book traces the path of discovery beginning with Chairman Mao's 1964 instruction to Chinese researchers to find a cure for malaria, a disease that plagued the military and civilians alike in endemic regions. It chronicles the years of painstaking research to find effective anti-malarial drugs, and how an entry in a collection of traditional Chinese medicine prescriptions gave Tu Youyou the clue which led her to successfully extract artemisinin from the plant, Artemisia annua.Gathering together information from a variety of sources including first-hand accounts, this book describes the contributions of the many organisations, scientists, doctors and countless others who played a part in the process of discovery and clinical testing. It also provides insights into the challenges of carrying out such an extensive research project with limited resources during the upheavals of the Cultural Revolution. An inspirational read for young scientists.Includes the translation of Professor Tu Youyou's 2015 Nobel Lecture.