International Conference on GIScience Short Paper Proceedings, 2016
Wireless Sensor Networks (WSNs) are widely used for monitoring and observation of dynamic phenome... more Wireless Sensor Networks (WSNs) are widely used for monitoring and observation of dynamic phenomena. A sensor in WSNs covers only a limited region, depending on its sensing and communicating ranges, as well as the environment configuration. For efficient deployment of sensors in a WSN the coverage estimation is a critical issue. Probabilistic methods are among the most accurate models proposed for sensor coverage estimation. However, most of these methods are based on raster representation of the environment for coverage estimation which limits their quality. In this paper, we propose a probabilistic method for estimation of the coverage of a sensor network based on 3D vector representation of the environment.
a series of events highlighting the most recent advances in ontology, web services, semantic soci... more a series of events highlighting the most recent advances in ontology, web services, semantic social media, semantic web, deep semantic web, semantic networking and semantic reasoning. The inaugural International Conference on Advances in Semantic Processing, SEMAPRO 2007, was initiated considering the complexity of understanding and processing information. Semantic processing considers contextual dependencies and adds to the individually acquired knowledge emergent properties and understanding. Hardware and software support and platforms were developed for semantically enhanced information retrieval and interpretation. Searching for video, voice and speech [VVS] raises additional problems to specialized engines with respect to text search. Contextual searching and special patterns-based techniques are current solutions. We take here the opportunity to warmly thank all the members of the SEMAPRO 2013 Technical Program Committee, as well as the numerous reviewers. The creation of such...
INDEX: Incremental depth extension approach for protein–protein interaction networks alignment
Biosystems
High-throughput methods have provided us with a large amount of data pertaining to protein-protei... more High-throughput methods have provided us with a large amount of data pertaining to protein-protein interaction networks. The alignment of these networks enables us to better understand biological systems. Given the fact that the alignment of networks is computationally intractable, it is important to introduce a more efficient and accurate algorithm which finds as large as possible similar areas among networks. This paper proposes a new algorithm named INDEX for the global alignment of protein-protein interaction networks. INDEX has multiple phases. First, it computes topological and biological scores of proteins and creates the initial alignment based on the proposed matching score strategy. Using networks topologies and aligned proteins, it then selects a set of high scoring proteins in each phase and extends new alignments around them until final alignment is obtained. Proposing a new alignment strategy, detailed consideration of matching scores, and growth of the alignment core has led INDEX to obtain a larger common connected subgraph with a much greater number of edges compared with previous methods. Regarding other measures such as edge correctness, symmetric substructure score, and runtime, the proposed algorithm performed considerably better than existing popular methods. Our results show that INDEX can be a promising method for identifying functionally conserved interactions. The INDEX executable file is available at https://github.com/a-mir/index/.
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Papers by Abolfazl Mir