A path- and label-cost propagation approach to speedup the training of the optimum-path forest classifier

In general, pattern recognition techniques require a high computational burden for learning the discriminating functions that are responsible to separate samples from distinct classes. As such, there are several studies that make effort to employ machine learning algorithms in the context of big data classification problems. The research on this area ranges from Graphics Processing Units-based implementations to mathematical optimizations, being the main drawback of the former approaches to be dependent on the graphic video card. Here, we propose an architecture-independent optimization approach for the optimum-path forest (OPF) classifier, that is designed using a theoretical formulation that relates the minimum spanning tree with the minimum spanning forest generated by the OPF over the training dataset. The experiments have shown that the approach proposed can be faster than the traditional one in five public datasets, being also as accurate as the original OPF. (C) 2014 Elsevier B. V. All rights reserved.

Speeding up optimum-path forest training by path-cost propagation

In this paper we present an optimization of the Optimum-Path Forest classifier training procedure, which is based on a theoretical relationship between minimum spanning forest and optimum-path forest for a specific path-cost function. Experiments on public datasets have shown that the proposed approach can obtain similar accuracy to the traditional one but with faster data training. © 2012 ICPR Org Committee.

Evaluation of ERIC-PCR as Genotyping Method for Corynebacterium pseudotuberculosis Isolates

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

High levels of genetic differentiation and selfing in the Brazilian cerrado fruit tree Dipteryx alata Vog. (Fabaceae)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Reproductive phenology of Atlantic forest tree species in Brazil: An eleven year study

This paper describes the reproductive phenorhythms of tree species in a tropical seasonal lowland forest in Southeastern Brazil. Every two weeks, five individuals of 41 species were observed for the occurrence of flowering and fruiting, from May 1982 to December 1992. All phenophases showed high seasonality, when considering the whole set of species, but the amplitude of the cycles was much more variable between years; only 13 species had regular flowering. Infra-annual flowering and fruiting were found in 11 and four species, respectively, while only one species flowered and fruited continually. Supra-annual cycles were observed in four (flowering) and seven (fruiting) species. An increase was observed in number of species and individuals flowering and fruiting from 1990 to 1992, following mainly an elevation in the absolute minimum air temperature. These data suggest a relationship between reproductive phenology and major climatic phenomena like El Niño events and solar activity cycles. © International Society for Tropical Ecology.

Tree species community spatial structure in a terra firme Amazon forest, Brazil

All trees with diameter at breast height dbh >= 10.0 cm were stem-mapped in a "terra firme" tropical rainforest in the Brazilian Amazon, at the EMBRAPA Experimental Site, Manaus, Brazil. Specifically, the relationships of tree species with soil properties were determined by using canonical correspondence analyses based on nine soil variables and 68 tree species. From the canonical correspondence analyses, the species were grouped into two groups: one where species occur mainly in sandy sites, presenting low organic matter content; and another one where species occur mainly in dry and clayey sites. Hence, we used Ripley's K function to analyze the distribution of species in 32 plots ranging from 2,500 m(2) to 20,000 m(2) to determine whether each group presents some spatial aggregation as a soil variations result. Significant spatial aggregation for the two groups was found only at over 10,000 m(2) sampling units, particularly for those species found in clayey soils and drier environments, where the sampling units investigated seemed to meet the species requirements. Soil variables, mediated by topographic positions had influenced species spatial aggregation, mainly in an intermediate to large distances varied range (>= 20 m). Based on our findings, we conclude that environmental heterogeneity and 10,000 m(2) minimum sample unit sizes should be considered in forest dynamic studies in order to understand the spatial processes structuring the "terra firme" tropical rainforest in Brazilian Amazon.