Displaying similar documents to “A model of regular sparsity map representation.”

Summarizing sensors data in vehicular ad hoc networks

Dorsaf Zekri, Bruno Defude, Thierry Delot (2010)

RAIRO - Operations Research - Recherche Opérationnelle

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This article focuses on data aggregation in vehicular networks. In such networks, sensor data are usually produced and exchanged between vehicles in order to warn or inform the drivers when an event is detected (, ). In the following, we present a solution to aggregate and store these data in order to have a history of past events. We therefore use Flajolet-Martin sketches. Our goal is to generate additional knowledge to assist drivers by providing them useful information even if no...

Selecting differentially expressed genes for colon tumor classification

Krzysztof Fujarewicz, Małgorzata Wiench (2003)

International Journal of Applied Mathematics and Computer Science

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DNA microarrays provide a new technique of measuring gene expression, which has attracted a lot of research interest in recent years. It was suggested that gene expression data from microarrays (biochips) can be employed in many biomedical areas, e.g., in cancer classification. Although several, new and existing, methods of classification were tested, a selection of proper (optimal) set of genes, the expressions of which can serve during classification, is still an open problem. Recently...

An Overview of Modelling Bulgarian Wildland Fire Behaviour by Application of a Mathematical Game Method and WRF-Fire Models

Dobrinkova, Nina (2012)

Serdica Journal of Computing

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This paper presents the main achievements of the author’s PhD dissertation. The work is dedicated to mathematical and semi-empirical approaches applied to the case of Bulgarian wildland fires. After the introductory explanations, short information from every chapter is extracted to cover the main parts of the obtained results. The methods used are described in brief and main outcomes are listed. ACM Computing Classification System (1998): D.1.3, D.2.0, K.5.1.