Traffic flow breakdown prediction using feature reduction through Rough-Neuro fuzzy Networks

The prediction of the traffic behavior could help to make decision about the routing process, as well as enables gains on effectiveness and productivity on the physical distribution. This need motivated the search for technological improvements in the Routing performance in metropolitan areas. The purpose of this paper is to present computational evidences that Artificial Neural Network ANN could be use to predict the traffic behavior in a metropolitan area such So Paulo (around 16 million inhabitants). The proposed methodology involves the application of Rough-Fuzzy Sets to define inference morphology for insertion of the behavior of Dynamic Routing into a structured rule basis, without human expert aid. The dynamics of the traffic parameters are described through membership functions. Rough Sets Theory identifies the attributes that are important, and suggest Fuzzy relations to be inserted on a Rough Neuro Fuzzy Network (RNFN) type Multilayer Perceptron (MLP) and type Radial Basis Function (RBF), in order to get an optimal surface response. To measure the performance of the proposed RNFN, the responses of the unreduced rule basis are compared with the reduced rule one. The results show that by making use of the Feature Reduction through RNFN, it is possible to reduce the need for human expert in the construction of the Fuzzy inference mechanism in such flow process like traffic breakdown. © 2011 IEEE.

Land use image classification through optimum-path forest clustering

Land use classification has been paramount in the last years, since we can identify illegal land use and also to monitor deforesting areas. Although one can find several research works in the literature that address this problem, we propose here the land use recognition by means of Optimum-Path Forest Clustering (OPF), which has never been applied to this context up to date. Experiments among Optimum-Path Forest, Mean Shift and K-Means demonstrated the robustness of OPF for automatic land use classification of images obtained by CBERS-2B and Ikonos-2 satellites. © 2011 IEEE.

Electrical consumers data clustering through optimum-path forest

Non-technical losses identification has been paramount in the last decade. Since we have datasets with hundreds of legal and illegal profiles, one may have a method to group data into subprofiles in order to minimize the search for consumers that cause great frauds. In this context, a electric power company may be interested in to go deeper a specific profile of illegal consumer. In this paper, we introduce the Optimum-Path Forest (OPF) clustering technique to this task, and we evaluate the behavior of a dataset provided by a brazilian electric power company with different values of an OPF parameter. © 2011 IEEE.

Automatic visual dictionary generation through Optimum-Path Forest clustering

Image categorization by means of bag of visual words has received increasing attention by the image processing and vision communities in the last years. In these approaches, each image is represented by invariant points of interest which are mapped to a Hilbert Space representing a visual dictionary which aims at comprising the most discriminative features in a set of images. Notwithstanding, the main problem of such approaches is to find a compact and representative dictionary. Finding such representative dictionary automatically with no user intervention is an even more difficult task. In this paper, we propose a method to automatically find such dictionary by employing a recent developed graph-based clustering algorithm called Optimum-Path Forest, which does not make any assumption about the visual dictionary's size and is more efficient and effective than the state-of-the-art techniques used for dictionary generation. © 2012 IEEE.

VEGF-C expression in oral cancer by neurotransmitter-induced activation of beta-adrenergic receptors

The aim of this study was to investigate the expression of vascular endothelial growth factor type C (VEGF-C) in oral squamous cell carcinoma (OSCC) cell lines through norepinephrine-induced activation of beta-adrenergic receptors. Human OSCC cell lines (SCC-9 and SCC-25) expressing beta-adrenergic receptors were stimulated with different concentrations of norepinephrine (0.1, 1, and 10 μM) and 1 μM of propranolol, and analyzed after 1, 6, and 24 h. VEGF-C gene expression and VEGF-C production in the cell supernatant were evaluated by real-time PCR and by ELISA, respectively. The results showed that beta-adrenergic receptor stimulation by different concentrations of norepinephrine or blocking by propranolol did not markedly alter VEGF-C expression by SCC-9 and SCC-25 cells. VEGF-C protein levels produced by oral malignant cell lines after stimulation with different norepinephrine concentrations or blocking with propranolol was statistically similar (p > 0.05) to those of the control group (nonstimulated OSCC cell lines). Our findings suggest that stimulation of beta-adrenergic receptors by means of norepinephrine does not seem to modulate the VEGF-C expression in OSCC cell lines. These findings reinforce the need for further studies in order to understand the responsiveness of oral cancer to beta-adrenergic receptor stimulation or blockage, especially with regard to VEGF-C production. © 2012 International Society of Oncology and BioMarkers (ISOBM).

Genotype×production environment interaction for weaning weight in Angus populations of Brazil and Uruguay

The objective of this study was to define production environments by grouping different environmental factors and, consequently, to assess genotype by production environment interactions on weaning weight (WW) in the Angus populations of Brazil and Uruguay. Climatic conditions were represented by monthly temperature means (°C), minimum and maximum temperatures in winter and summer respectively and accumulated rainfall (mm/year). Mode in month of birth and weaning, and calf weight (kg) and age (days) at weaning were used as indicators of management conditions of 33 and 161 herds in 13 and 34 regions in Uruguay and Brazil, respectively. Two approaches were developed: (a) a bi-character analysis of extreme sub-datasets within each environmental factor (bottom and top 33% of regions), (b) three different production environments (including farms from both countries) were defined in a cluster analysis using standardized environmental factors. To identify the variables that influenced the cluster formation, a discriminant analysis was previously carried out. Management (month, age and weight at weaning) and climatic factors (accumulated rainfalls and winter and summer temperatures) were the most important factors in the clustering of farms. Bi or trivariate analyses were performed to estimate heritability and genetic correlations for WW in extreme sub-datasets within environmental factor or between clusters, using MTDFREML software. Heritability estimates of WW in the first approach ranged from 0.27 to 0.54, and genetic correlations between top and bottom sub-datasets within environmental factors, from -0.29 to 0.70. In the cluster approach, heritabilities were 0.58±0.04 for cluster 1, 0.31±0.01 for Cluster 2 and 0.40±0.02 for Cluster 3. Genetic correlations were 0.27±0.08, 0.32±0.09 and 0.33±0.09, between clusters 1 and 2, 1 and 3, and 2 and 3, respectively. Both approaches suggest the existence of genotype x environment interaction for weaning weight in Angus breed of Brazil and Uruguay. © 2012 Elsevier B.V.

Desenvolvimento de interface amigável de rotina em linguagem c++ para o processamento aritmético e estatístico de dados censitários

A routine was developed in C++ for the processing of social and environmental census data acquired by the Brazilian Institute of Geography and Statistics (IBGE). The routine employs a simple graphical environment. The data generated are presented in a tabular format, which facilitates a broad and objective view of the values, and provides a convenient means of querying the database. The source code used to develop the routine permits updates and changes, as required by the user. Statistical and mathematical analysis enables the generation of social and environmental indicators, together with quantitative and qualitative classification of the socio-environmental quality of the region analyzed. As an example, the routine was applied using census data for the city of Sorocaba (São Paulo State, Brazil), including conditions of household occupation, water supply, sanitation, level of education, income, and other factors. It is envisaged that the proposed analytical model will assist professionals from different fields of research and teaching to develop urban planning and management strategies.

Fuzzy control embedded in microcontroller and applied to an experimental apparatus using magnetorheological fluid damper

This work focuses on applying fuzzy control embedded in microcontrollers in an experimental apparatus using magnetorheological fluid damper. The non-linear behavior of the magnetorheological dampers associated with the parametric variations on vehicle suspension models corroborate the use of the fuzzy controllers. The fundamental formulation of this controller is discussed and its performance is shown through numeric simulations. An experimental apparatus representing a two degree of freedom system containing a magnetorheological damper is used to identify the main parameters and to evaluate the performance of the closed-loop system with the embedded low-cost microcontroller-based fuzzy controller. © 2013 Brazilian Society for Automatics - SBA.

Metrics to support the evaluation of association rule clustering

Many topics related to association mining have received attention in the research community, especially the ones focused on the discovery of interesting knowledge. A promising approach, related to this topic, is the application of clustering in the pre-processing step to aid the user to find the relevant associative patterns of the domain. In this paper, we propose nine metrics to support the evaluation of this kind of approach. The metrics are important since they provide criteria to: (a) analyze the methodologies, (b) identify their positive and negative aspects, (c) carry out comparisons among them and, therefore, (d) help the users to select the most suitable solution for their problems. Some experiments were done in order to present how the metrics can be used and their usefulness. © 2013 Springer-Verlag GmbH.

Classificação fuzzy de vertentes por krigagem e TPS com agregação de regiões via diagrama de Voronoi

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Utilização do controle estatístico de processo na unidade de produção e desenvolvimento de derivados de soja - UNISOJA - F.C.F. - UNESP

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise comparativa da variação entre quasiespecies do Vírus da Hepatite C genótipo 1 em amostras prétratamento de pacientes tratados com Peginterferon

Pós-graduação em Genética - IBILCE

Efeito de tratamentos térmicos na resistência à tração e na dureza Vickers do Ti c.p. e da liga Ti-6Al-4V obtidos por fundição odontológica

Pós-graduação em Reabilitação Oral - FOAR

Ativação da ligação c-h no metano por espécies MOm n+ (M = Nb, Fe; m = 0, 1; n = 0, 1, 2): estrutura eletrônica, mecanismo de reação e reatividade

The need for renewal and a more efficient use of energy resources has provided an increased interest in studies of methane activation processes in the gas phase by transition metal oxides. In this respect, the present work is an effort to assess , by means of a computational standpoint, the reactivity of NbOm n+ and FeOm n+ (m = 1, 2, n = 0, 1, 2) oxides in the activation process of the methane C-H bond, which corresponds to the first rate limiting step in the process of converting methane to methanol. These oxides are chosen, primarily, because the iron oxides are the most experimentally studied, and iron ions are more abundant in biological mediums. The main motive for choosing niobium oxides is the abundance of natural reserves of this mineral in Brazil (98%), especially in Minas Gerais. Initially, a thorough investigation was conducted, using different theoretical methods, to analyze the structural and electronic properties of the investigated oxides. Based on these results, the most reliable methodology was selected to investigate the activation process of the methane C-H bond by the series of iron and niobium oxides, considering all possible reaction mechanisms known to activate the C-H bond of alkanes. It is worth noting that, up to this moment and to our knowledge, there are no papers, in literature , investigating and comparing all the mechanisms considered in this work. I n general, the main results obtained show different catalytic tendencies and behaviors throughout the series of monoxides and dioxides of iron and niobium. An important and common result found in the two studies is that the increase in the load on the metal center and the addition of oxygen atoms to the metal, clearly favor the initial thermodynamics of the reaction, i.e., favor the approach of the metal center to methane, distorting its electron cloud and, thereby, decreasing its inertia. Comparing the two sets of oxides, we conclude that the iron oxides are the most efficient in activating the methane C-H bond. Among the iron oxides investigated, FeO + showed better kinetic and thermodynamic performance in the reaction with methane, while from the niobium oxides and ions NbO 2+ and NbO2 2+, showed better catalytic efficiency in the activation of the methane C-H bond.

Avaliação da atividade dos óleos essenciais de cymbopogon citratus (D.C.) Stapf, Tagetes minuta L. e Curcuma zedoaria roscoe frente aos microrganismos Candida spp., Staphylococcus spp. e Streptococcus mutans

Pós-graduação em Biopatologia Bucal - ICT