Comparative phylogeography of Trypanosoma cruzi TCIIc: New hosts, association with terrestrial ecotopes, and spatial clustering

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Spatial clustering applied to health area

The significant volume of work accidents in the cities causes an expressive loss to society. The development of Spatial Data Mining technologies presents a new perspective for the extraction of knowledge from the correlation between conventional and spatial attributes. One of the most important techniques of the Spatial Data Mining is the Spatial Clustering, which clusters similar spatial objects to find a distribution of patterns, taking into account the geographical position of the objects. Applying this technique to the health area, will provide information that can contribute towards the planning of more adequate strategies for the prevention of work accidents. The original contribution of this work is to present an application of tools developed for Spatial Clustering which supply a set of graphic resources that have helped to discover knowledge and support for management in the work accidents area. © 2011 IEEE.

Geoprocessamento aplicado na identificação de padrões espaciais do perfil de nascimento na região do Vale do Paraíba

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Algoritmo para prospecção multirrelacional de dados espaciais

Pós-graduação em Ciência da Computação - IBILCE

Extração de conhecimento em bases de dados espaciais: algoritmo CHSMST+

Pós-graduação em Ciência da Computação - IBILCE

Detecção de outliers espaciais: refinamento de similaridade e desempenho

Pós-graduação em Ciência da Computação - IBILCE

Estudo da diversidade genética do MycobacteriUm leprae em pacientes com hanseníase no município de Rondonópolis (MT): uma contribuição para o melhor entendimento da sua transmissão

Pós-graduação em Doenças Tropicais - FMB

Spatial patterns or trees in the Picinguara coastal sandy forest (state of Sao-Paulo, Brazil)

The species of the sandy plains forests (forests of the ''restingas'') have not yet had their spatial patterns studied as aids to the understanding of the diversity found in the different physiognomies along the Brazilian coast. In this paper a 10 x 10 m quadrat framework laid in a hectare of a tree dominant forest in the sandy plains of the Picinguaba area of the Serra do Mar State Park (municipality of Ubatuba, state of São Paulo, Brazil) was used to assess the spatial pattern of distribution for the ten most important species : Pera glabrata, Euterpe edulis, Eugenia brasiliensis, Alchornea triplinervea, Guatteria australis, Myrcia racemosa, Jacaranda semiserrata, Guarea macrophylla, Euplassa cantareirae and Nectandra oppositifolia. The spatial patterns were inferred through the calculations of their T-Square Index (C) and Dispersal Distance Index (I). P. glabrata shows a random pattern, E. edulis aggregate, E. brasiliensis, A. triplinervia, G. australis, E. cantareirae and N. oppositifolia with a tendency between aggregate and uniform and, M. racemosa, J. semiserrata and G. macrophylla between aggregate and random. Although the indexes are dependent of the sample size and of the technique adjustments, the relationship of the pattern with the environmental factors is shown by clustering methods. The results give confirmation of how the spatial patterns bring associations between populations and shape of the vegetation physiognomy.

Designing spatial correlation of quantum dots: towards self-assembled three-dimensional structures

Buried two-dimensional arrays of InP dots were used as a template for the lateral ordering of self-assembled quantum dots. The template strain field can laterally organize compressive (InAs) as well as tensile (GaP) self-assembled nanostructures in a highly ordered square lattice. High-resolution transmission electron microscopy measurements show that the InAs dots are vertically correlated to the InP template, while the GaP dots are vertically anti-correlated, nucleating in the position between two buried InP dots. Finite InP dot size effects are observed to originate InAs clustering but do not affect GaP dot nucleation. The possibility of bilayer formation with different vertical correlations suggests a new path for obtaining three-dimensional pseudocrystals.

Determining spatial resolution in spatial load forecasting using a grid-based model

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Community-wide spatial and temporal discordances of seed-seedling shadows in a tropical rainforest

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

OntoSDM: an approach to improve quality on spatial data mining algorithms

The increase in new electronic devices had generated a considerable increase in obtaining spatial data information; hence these data are becoming more and more widely used. As well as for conventional data, spatial data need to be analyzed so interesting information can be retrieved from them. Therefore, data clustering techniques can be used to extract clusters of a set of spatial data. However, current approaches do not consider the implicit semantics that exist between a region and an object’s attributes. This paper presents an approach that enhances spatial data mining process, so they can use the semantic that exists within a region. A framework was developed, OntoSDM, which enables spatial data mining algorithms to communicate with ontologies in order to enhance the algorithm’s result. The experiments demonstrated a semantically improved result, generating more interesting clusters, therefore reducing manual analysis work of an expert.