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Wireless sensor networks (WSNs) can provide real-time information about geospatial environments, and so have the potential to play an important role in the monitoring of geographic phenomena. The research reported in this paper uses WSNs to provide salient information about spatially distributed dynamic fields, such as regional variations in temperature or concentration of a toxic gas. The focus is on topological changes to areas of high-activity that occur during the evolution of the field. Topological changes investigated include region merging and splitting, and hole formation or elimination. Such changes are formally characterized, and an algorithm is developed that detects such changes by means purely of in-network processing. The efficiency of this algorithm is investigated both theoretically and using simulation experiments.

Nowadays, Web applications are very prevalent around the world, and it becomes more and more important to ensure their qualities by testing. However, due to the special characters of Web applications, traditional testing methods are not suitable for Web testing in many aspects. So based on the related work by now, this paper presents our research work in such areas as the Web application modeling, the test case generation, the detailed testing methods and techniques, the testing executing process, and the testing measurements. And based on the rules of software engineering, these processes are the necessary parts of the whole testing. Our methods focus on such specialties as numerous users, distributed structures, dynamic and interactive functions of Web applications and the improvements for the testing efficiency.

The authors present a local stereo matching algorithm whose performance is insensitive to changes in radiometric conditions between the input images. First, a prior on the disparities is built by combining the DAISY descriptor and Census filtering. Then, a Census-based cost aggregation with a self-adaptive window is performed. Finally, the maximum a-posteriori estimation is carried out to compute the disparity. The authors' algorithm is compared with both local and global stereo matching algorithms (NLCA, ELAS, ANCC, AdaptWeight and CSBP) by using Middlebury datasets. The results show that the proposed algorithm achieves high-accuracy dense disparity estimations and is more robust to radiometric differences between input images than other algorithms.

Abstract. Fuzzy ontology mapping is important for handling uncertain knowledge on the semantic web. However, current ontology mapping technologies are not sufficient for fuzzy ontologies. This paper proposes a framework of mapping fuzzy concepts between fuzzy ontologies. It applies the approximate concept mapping approach, extends atom fuzzy concept sets and defines the least upper bounds to reduce the searching space. It resolves the mapping problem of fuzzy concepts into finding the simplified least upper bounds for atom fuzzy concepts, and gives an algorithm for searching the simplified least upper bounds, which is fast and proved correct. The framework is efficient for mapping fuzzy concepts between fuzzy ontologies.