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Abstrak :
Mobile context awareness presents work from industrial and academic researchers, focusing on novel methods of context acquisition in the mobile environment – particularly through the use of physical and virtual sensors – along with research into new applications utilising this context. In addition, the book provides insights into the technical and usability challenges involved in mobile context-awareness, as well as observations on current and future trends in the field.

Abstrak :
Context management for distributed and dynamic context-aware computing proposes a novel architecture for context management based on the concept of context domains, allowing applications to keep context interests across distributed context management systems. The authors describe a distributed middleware that implements the aforementioned concepts, without compromising scalability and efficiency of context access.

Abstrak :
With this book, Reichert and Weber address these flexibility needs and provide an overview of PAIS with a strong focus on methods and technologies fostering flexibility for all phases of the process lifecycle (i.e., modeling, configuration, execution and evolution). Their presentation is divided into six parts. Part I starts with an introduction of fundamental PAIS concepts and establishes the context of process flexibility in the light of practical scenarios. Part II focuses on flexibility support for pre-specified processes, the currently predominant paradigm in the field of business process management (BPM). Part III details flexibility support for loosely specified processes, which only partially specify the process model at build-time, while decisions regarding the exact specification of certain model parts are deferred to the run-time. Part IV deals with user- and data-driven processes, which aim at a tight integration of processes and data, and hence enable an increased flexibility compared to traditional PAIS. Part V introduces existing technologies and systems for the realization of a flexible PAIS. Finally, part VI summarizes the main ideas of this book and gives an outlook on advanced flexibility issues.

Abstrak :
This book introduces resource-aware data fusion algorithms to gather and combine data from multiple sources (e.g., sensors) in order to achieve inferences. These techniques can be used in centralized and distributed systems to overcome sensor failure, technological limitation, and spatial and temporal coverage problems. The algorithms described in this book are evaluated with simulation and experimental results to show they will maintain data integrity and make data useful and informative.