First uniform treatment of moving objects databases, the technology that supports GPS and RFID data analysis.

We live in an age of rapid technological development. The Internet already affects our lives in many ways. Indeed, we continue to depend more, and more intrinsically, on the Internet, which is increasingly becoming a fundamental piece of societal infrastructure, just as water supply, electricity grids, and transportation networks have been for a long time. But while these other infrastructures are relatively static, the Internet is undergoing swift and fundamental change: Notably, the Internet is going mobile. The world has some 6.7 billion humans, 4 billion mobile phones, and 1.7 billion Internet users. The two most populous continents, Asia and Africa, have relatively low Internet penetration and hold the greatest potentials for growth. Their mobile phone users by far outnumber their Internet users, and the numbers are growing rapidly. China and India are each gaining about half a dozen million new phone users per month. Users across the globe as a whole increasingly embrace mobile Internet devices, with smart phone sales are starting to outnumber PC sales. Indeed, these and other facts suggest that the Internet stands to gain a substantial mobile component. This mega trend towards “mobile” is enabled by rapid and continuing advances in key technology areas such as mobile communication, consumer electronics, g- positioning, and computing. In short, this is the backdrop for this very timely book on moving objects by Xiaofeng Meng and Jidong Chen.

Intelligent technologies have emerged as imperative tools in computer science and information security. However, advanced computing practices have preceded new methods of attacks on the storage and transmission of data. Developing approaches such as image processing and pattern recognition are susceptible to breaches in security. Modern protection methods for these innovative techniques require additional research. The Handbook of Research on Intelligent Data Processing and Information Security Systems provides emerging research exploring the theoretical and practical aspects of cyber protection and applications within computer science and telecommunications. Special attention is paid to data encryption, steganography, image processing, and recognition, and it targets professionals who want to improve their knowledge in order to increase strategic capabilities and organizational effectiveness. As such, this book is ideal for analysts, programmers, computer engineers, software engineers, mathematicians, data scientists, developers, IT specialists, academicians, researchers, and students within fields of information technology, information security, robotics, artificial intelligence, image processing, computer science, and telecommunications.

Monitoring of public and private sites has increasingly become a very sensitive issue resulting in a patchwork of privacy laws varying from country to country -though all aimed at protecting the privacy of the citizen. It is important to remember, however, that monitoring and vi sual surveillance capabilities can also be employed to aid the citizen. The focus of current development is primarily aimed at public and cor porate safety applications including the monitoring of railway stations, airports, and inaccessible or dangerous environments. Future research effort, however, has already targeted citizen-oriented applications such as monitoring assistants for the aged and infirm, route-planning and congestion-avoidance tools, and a range of environment al monitoring applications. The latest generation of surveillance systems has eagerly adopted re cent technological developments to produce a fully digital pipeline of digital image acquisition, digital data transmission and digital record ing. The resultant surveillance products are highly-fiexihle, capahle of generating forensic-quality imagery, and ahle to exploit existing Internet and wide area network services to provide remote monitoring capability.

This Springer Brief presents a comprehensive survey of the existing methodologies of background subtraction methods. It presents a framework for quantitative performance evaluation of different approaches and summarizes the public databases available for research purposes. This well-known methodology has applications in moving object detection from video captured with a stationery camera, separating foreground and background objects and object classification and recognition. The authors identify common challenges faced by researchers including gradual or sudden illumination change, dynamic backgrounds and shadow and ghost regions. This brief concludes with predictions on the future scope of the methods. Clear and concise, this brief equips readers to determine the most effective background subtraction method for a particular project. It is a useful resource for professionals and researchers working in this field.

This book constitutes the thoroughly refereed post-conference proceedings of three workshops of the 12th International Conference on Web-Age Information Management, WAIM 2011, held in Wuhan, China, in September 2011. The 20 revised full papers are organized in topical sections on the three following workshops: the First International Workshop on Web-based Geographic Information Management (WGIM 2011), the Third International Workshop on XML Data Management (XMLDM 2011), and the First International Workshop on Social Network Analysis (SNA 2011).

We are rapidly heading towards a world in which the computing infrastructure will contain billions of devices, which will interact with other computing/communications devices that are carried or worn by users as they go through their daily routines. Such devices will provide data access to mobile users as they move within buildings, cities, or across the globe. This new infrastructure presents tremendous challenges for data management technology, including: huge scale; variable and intermittent connectivity; location and context-aware applications; bandwidth, power, and devi- size limitations; and multimedia data delivery across hybrid networks and systems. Traditional data management technologies such as query processing, transaction management, workflow, business process management, and metadata management must all be reevaluated in this emerging environment. Furthermore, nontraditional issues such as the semantics of mobile data, location-dependent querying, broadcast and multicast delivery, and caching/prefetching techniques must all be addressed. The ability to track people as they move about their daily tasks raises serious issues of security and privacy. This conference is the fourth in the Mobile Data Management series, focusing on the challenges and opportunities for the management of data in mobile, pervasive, and wearable computing. MDM 2000 and 2001 were in Hong Kong and MDM 2002 was in Singapore. Eighty-seven papers were submitted to the conference from 23 countries and were subject to a rigorous review procedure. Every paper had three or four independent reviews. Twenty-one full papers and 15 short papers from both academia and industry were selected for publication in this volume of proceedings.

Deep learning, as a recent AI technique, has proven itself efficient in solving many real-world problems. Deep learning algorithms are efficient, high performing, and an effective standard for solving these problems. In addition, with IoT, deep learning is in many emerging and developing domains of computer technology. Deep learning algorithms have brought a revolution in computer vision applications by introducing an efficient solution to several image processing-related problems that have long remained unresolved or moderately solved. Various significant IoT technologies in various industries, such as education, health, transportation, and security, combine IoT with deep learning for complex problem solving and the supported interaction between human beings and their surroundings. Examining the Impact of Deep Learning and IoT on Multi-Industry Applications provides insights on how deep learning, together with IoT, impacts various sectors such as healthcare, agriculture, cyber security, and social media analysis applications. The chapters present solutions to various real-world problems using these methods from various researchers’ points of view. While highlighting topics such as medical diagnosis, power consumption, livestock management, security, and social media analysis, this book is ideal for IT specialists, technologists, security analysts, medical practitioners, imaging specialists, diagnosticians, academicians, researchers, industrial experts, scientists, and undergraduate and postgraduate students who are working in the field of computer engineering, electronics, and electrical engineering.

This book includes the volume 2 of the proceedings of the 2012 International Conference on Mechanical and Electronic Engineering(ICMEE2012), held at June 23-24,2012 in Hefei, China. The conference provided a rare opportunity to bring together worldwide researchers who are working in the fields. This volume 2 is focusing on Mechatronic Engineering and Technology, Electronic Engineering and Electronic Information Technology .

"Temporal Information Processing Technology and Its Applications" systematically studies temporal information processing technology and its applications. The book covers following subjects: 1) time model, calculus and logic; 2) temporal data models, semantics of temporal variable ‘now’ temporal database concepts; 3) temporal query language, a typical temporal database management system: TempDB; 4) temporal extension on XML, workflow and knowledge base; and, 5) implementation patterns of temporal applications, a typical example of temporal application. The book is intended for researchers, practitioners and graduate students of databases, data/knowledge management and temporal information processing. Dr. Yong Tang is a professor at the Computer School, South China Normal University, China.