Proposta de uma ferramenta de visualização e realidade virtual para o monitoramento de tráfego de redes de computadores

Pós-graduação em Ciência da Computação - IBILCE

Estudos de imagens provenientes de membranas de borracha natural com aditivos metálicos utilizando técnicas de Fourier, Gabor e Wavelets

Pós-graduação em Ciência e Tecnologia de Materiais - FC

Classificação de cobertura do solo utilizando árvores de decisão e sensoriamento remoto

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise e extração de características de imagens termográficas utilizando componentes principais

Pós-graduação em Engenharia Mecânica - FEIS

Papel de neutrófilos humanos no direcionamento da resposta imune adaptativa do tipo Th1 contra o Paracoccidioides brasiliensis

Pós-graduação em Doenças Tropicais - FMB

Modulação da proliferação, apoptose e autofagia de linfocitos T por RAGE

Pós-graduação em Odontologia - FOAR

Identification of b-quark jets with the CMS experiment

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Nature-Inspired Framework for Hyperspectral Band Selection

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

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.

Seleção de características utilizando algoritmos evolucionistas e suas aplicações em reconhecimento de padrões

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Static Video Summarization through Optimum-Path Forest Clustering

This paper introduces the Optimum-Path Forest (OPF) classifier for static video summarization, being its results comparable to the ones obtained by some state-of-the-art video summarization techniques. The experimental section has been conducted using several image descriptors in two public datasets, followed by an analysis of OPF robustness regarding one ad-hoc parameter. Future works are guided to improve OPF effectiveness on each distinct video category.

Metabolic profiling by ultra-performance liquid chromatography-mass spectrometry and parallel factor analysis for the determination of disease biomarkers in Eucalyptus

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

Interferon-gamma production by human neutrophils upon stimulation by IL-12, IL-15 and IL-18 and challenge with Paracoccidioides brasiliensis

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

Multi-scale lacunarity as an alternative to quantify and diagnose the behavior of prostate cancer

Prostate cancer is a serious public health problem accounting for up to 30% of clinical tumors in men. The diagnosis of this disease is made with clinical, laboratorial and radiological exams, which may indicate the need for transrectal biopsy. Prostate biopsies are discerningly evaluated by pathologists in an attempt to determine the most appropriate conduct. This paper presents a set of techniques for identifying and quantifying regions of interest in prostatic images. Analyses were performed using multi-scale lacunarity and distinct classification methods: decision tree, support vector machine and polynomial classifier. The performance evaluation measures were based on area under the receiver operating characteristic curve (AUC). The most appropriate region for distinguishing the different tissues (normal, hyperplastic and neoplasic) was defined: the corresponding lacunarity values and a rule's model were obtained considering combinations commonly explored by specialists in clinical practice. The best discriminative values (AUC) were 0.906, 0.891 and 0.859 between neoplasic versus normal, neoplasic versus hyperplastic and hyperplastic versus normal groups, respectively. The proposed protocol offers the advantage of making the findings comprehensible to pathologists. (C) 2014 Elsevier Ltd. All rights reserved.

Description and performance of track and primary-vertex reconstruction with the CMS tracker

A description is provided of the software algorithms developed for the CMS tracker both for reconstructing charged-particle trajectories in proton-proton interactions and for using the resulting tracks to estimate the positions of the LHC luminous region and individual primary-interaction vertices. Despite the very hostile environment at the LHC, the performance obtained with these algorithms is found to be excellent. For t (t) over bar events under typical 2011 pileup conditions, the average track-reconstruction efficiency for promptly-produced charged particles with transverse momenta of p(T) > 0.9GeV is 94% for pseudorapidities of vertical bar eta vertical bar < 0.9 and 85% for 0.9 < vertical bar eta vertical bar < 2.5. The inefficiency is caused mainly by hadrons that undergo nuclear interactions in the tracker material. For isolated muons, the corresponding efficiencies are essentially 100%. For isolated muons of p(T) = 100GeV emitted at vertical bar eta vertical bar < 1.4, the resolutions are approximately 2.8% in p(T), and respectively, 10 m m and 30 mu m in the transverse and longitudinal impact parameters. The position resolution achieved for reconstructed primary vertices that correspond to interesting pp collisions is 10-12 mu m in each of the three spatial dimensions. The tracking and vertexing software is fast and flexible, and easily adaptable to other functions, such as fast tracking for the trigger, or dedicated tracking for electrons that takes into account bremsstrahlung.