A wireless sensor network (WSN) uses a number of autonomous devices to cooperatively monitor physical or environmental conditions via a wireless network. Since its military beginnings as a means of battlefield surveillance, practical use of this technology has extended to a range of civilian applications including environmental monitoring, natural disaster prediction and relief, health monitoring and fire detection. Technological advancements, coupled with lowering costs, suggest that wireless sensor networks will have a significant impact on 21st century life. The design of wireless sensor networks requires consideration for several disciplines such as distributed signal processing, communications and cross-layer design. Wireless Sensor Networks: Signal Processing and Communications focuses on the theoretical aspects of wireless sensor networks and offers readers signal processing and communication perspectives on the design of large-scale networks. It explains state-of-the-art design theories and techniques to readers and places emphasis on the fundamental properties of large-scale sensor networks. Wireless Sensor Networks: Signal Processing and Communications : Approaches WSNs from a new angle – distributed signal processing, communication algorithms and novel cross-layer design paradigms. Applies ideas and illustrations from classical theory to an emerging field of WSN applications. Presents important analytical tools for use in the design of application-specific WSNs. Wireless Sensor Networks will be of use to signal processing and communications researchers and practitioners in applying classical theory to network design. It identifies research directions for senior undergraduate and graduate students and offers a rich bibliography for further reading and investigation.

This book constitutes the refereed proceedings of the First International Conference on Network-Based Information Systems, NBIS 2007, held in Regensburg, Germany, September 2007 in conjunction with Dexa 2007. It covers recommender systems, business process / design aspects, mobile commerce, security and e-payment, Web services computing / semantic Web, e-negotiation and agent mediated systems, and issues in Web advertising.

Advanced Data Mining Tools and Methods for Social Computing explores advances in the latest data mining tools, methods, algorithms and the architectures being developed specifically for social computing and social network analysis. The book reviews major emerging trends in technology that are supporting current advancements in social networks, including data mining techniques and tools. It also aims to highlight the advancement of conventional approaches in the field of social networking. Chapter coverage includes reviews of novel techniques and state-of-the-art advances in the area of data mining, machine learning, soft computing techniques, and their applications in the field of social network analysis. Provides insights into the latest research trends in social network analysis Covers a broad range of data mining tools and methods for social computing and analysis Includes practical examples and case studies across a range of tools and methods Features coding examples and supplementary data sets in every chapter

The annual Neural Information Processing Systems (NIPS) conference is the flagship meeting on neural computation and machine learning. This volume contains the papers presented at the December 2006 meeting, held in Vancouver.