Localização e planejamento de caminhos para um robô humanóide e um robô escravo com rodas

This work presents the localization and path planning systems for two robots: a non-instrumented humanoid and a slave wheeled robot. The localization of wheeled robot is made using odometry information and landmark detection. These informations are fused using a Extended Kalman Filter. The relative position of humanoid is acquired fusing (using another Kalman Filter) the wheeled robot pose with the characteristics of the landmark on the back of humanoid. Knowing the wheeled robot position and the humanoid relative position in relation to it, we acquired the absolute position of humanoid. The path planning system was developed to provide the cooperative movement of the two robots,incorporating the visibility restrictions of the robotic system

Morfologia matemática aplicada à detecção de sombras e nuvens em imagens de alta resolução

The spatial resolution improvement of orbital sensors has broadened considerably the applicability of their images in solving urban areas problems. But as the spatial resolution improves, the shadows become even a more serious problem especially when detailed information (under the shadows) is required. Besides those shadows caused by buildings and houses, clouds projected shadows are likely to occur. In this case there is information occlusion by the cloud in association with low illumination and contrast areas caused by the cloud shadow on the ground. Thus, it's important to use efficient methods to detect shadows and clouds areas in digital images taking in count that these areas care for especial processing. This paper proposes the application of Mathematical Morphology (MM) in shadow and clouds detection. Two parts of a panchromatic QuickBird image of Cuiab-MT urban area were used. The proposed method takes advantage of the fact that shadows (low intensity - dark areas) and clouds (high intensity - bright areas) represent the bottom and top, respectively, of the image as it is thought to be a topographic surface. This characteristic allowed MM area opening and closing operations to be applied to reduce or eliminate the bottom and top of the topographic surface.

Orientação indireta de imagens com uso de apoio fotogramétrico extraído a partir da integração de dados derivados do sistema lidar e fotogrametria

In this work a method is proposed to allow the indirect orientation of images using photogrammetric control extracted through integration of data derived from Photogrammetry and Light Detection and Ranging (LiDAR) system. The photogrammetric control is obtained by using an inverse photogrammetric model, which allows the projection of image space straight lines onto the object space. This mathematical model is developed based on the intersection between the collinearity-based straight line and a DSM of region, derived from LiDAR data. The mathematical model used in the indirect orientation of the image is known as the model of equivalent t planes. This mathematical model is based on the equivalence between the vector normal to the projection plane in the image space and to the vector normal to the rotated projection plane in the object space. The goal of this work is to verify the quality, efficiency and potential of photogrammetric control straight lines obtained with proposed method applied to the indirect orientation of images. The quality of generated photogrammetric control was statistically available and the results showed that proposed method is promising and it has potential for the indirect orientation of images.

Comparison of different analysis techniques for the determination of muscle onset in individuals with patellofemoral pain syndrome

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Electrochemical characterization of the paste carbon modified electrode with KSr2Ni0.75Nb4.25O15-delta solid in catalytic oxidation of the dipyrone

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

Use of Poisson spatiotemporal regression models for the Brazilian Amazon Forest: malaria count data

INTRODUÇÃO: A malaria é uma doença endêmica na região da Amazônia Brasileira, e a detecção de possíveis fatores de risco pode ser de grande interesse às autoridades em saúde pública. O objetivo deste artigo é investigar a associação entre variáveis ambientais e os registros anuais de malária na região amazônica usando métodos bayesianos espaço-temporais. MÉTODOS: Utilizaram-se modelos de regressão espaço-temporais de Poisson para analisar os dados anuais de contagem de casos de malária entre os anos de 1999 a 2008, considerando a presença de alguns fatores como a taxa de desflorestamento. em uma abordagem bayesiana, as inferências foram obtidas por métodos Monte Carlo em cadeias de Markov (MCMC) que simularam amostras para a distribuição conjunta a posteriori de interesse. A discriminação de diferentes modelos também foi discutida. RESULTADOS: O modelo aqui proposto sugeriu que a taxa de desflorestamento, o número de habitants por km² e o índice de desenvolvimento humano (IDH) são importantes para a predição de casos de malária. CONCLUSÕES: É possível concluir que o desenvolvimento humano, o crescimento populacional, o desflorestamento e as alterações ecológicas associadas a estes fatores estão associados ao aumento do risco de malária. Pode-se ainda concluir que o uso de modelos de regressão de Poisson que capturam o efeito temporal e espacial em um enfoque bayesiano é uma boa estratégia para modelar dados de contagem de malária.

Methacycline: A Review of Analytical Methods

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Otimização de ELISA empregando a proteína Tc85-11 e planejamento fatorial

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

Structural FRF acquisition via electric impedance measurement applied to damage location

Continuing development of new materials makes systems lighter and stronger permitting more complex systems to provide more functionality and flexibility that demands a more effective evaluation of their structural health. Smart material technology has become an area of increasing interest in this field. The combination of smart materials and artificial neural networks can be used as an excellent tool for pattern recognition, turning their application adequate for monitoring and fault classification of equipment and structures. In order to identify the fault, the neural network must be trained using a set of solutions to its corresponding forward Variational problem. After the training process, the net can successfully solve the inverse variational problem in the context of monitoring and fault detection because of their pattern recognition and interpolation capabilities. The use of structural frequency response function is a fundamental portion of structural dynamic analysis, and it can be extracted from measured electric impedance through the electromechanical interaction of a piezoceramic and a structure. In this paper we use the FRF obtained by a mathematical model (FEM) in order to generate the training data for the neural networks, and the identification of damage can be done by measuring electric impedance, since suitable data normalization correlates FRF and electrical impedance.

Beta: uma ferramenta para geração de testes de unidade a partir de especificações B

Formal methods and software testing are tools to obtain and control software quality. When used together, they provide mechanisms for software specification, verification and error detection. Even though formal methods allow software to be mathematically verified, they are not enough to assure that a system is free of faults, thus, software testing techniques are necessary to complement the process of verification and validation of a system. Model Based Testing techniques allow tests to be generated from other software artifacts such as specifications and abstract models. Using formal specifications as basis for test creation, we can generate better quality tests, because these specifications are usually precise and free of ambiguity. Fernanda Souza (2009) proposed a method to define test cases from B Method specifications. This method used information from the machine s invariant and the operation s precondition to define positive and negative test cases for an operation, using equivalent class partitioning and boundary value analysis based techniques. However, the method proposed in 2009 was not automated and had conceptual deficiencies like, for instance, it did not fit in a well defined coverage criteria classification. We started our work with a case study that applied the method in an example of B specification from the industry. Based in this case study we ve obtained subsidies to improve it. In our work we evolved the proposed method, rewriting it and adding characteristics to make it compatible with a test classification used by the community. We also improved the method to support specifications structured in different components, to use information from the operation s behavior on the test case generation process and to use new coverage criterias. Besides, we have implemented a tool to automate the method and we have submitted it to more complex case studies

Sistema de aquisição de dados para estudos de transiente de pressão e detecção de vazamentos em oleodutos

In February 2011, the National Agency of Petroleum, Natural Gas and Biofuels (ANP) has published a new Technical Rules for Handling Land Pipeline Petroleum and Natural Gas Derivatives (RTDT). Among other things, the RTDT made compulsory the use of monitoring systems and leak detection in all onshore pipelines in the country. This document provides a study on the method for detection of transient pressure. The study was conducted on a industrial duct 16" diameter and 9.8 km long. The pipeline is fully pressurized and carries a multiphase mixture of crude oil, water and natural gas. For the study, was built an infrastructure for data acquisition and validation of detection algorithms. The system was designed with SCADA architecture. Piezoresistive sensors were installed at the ends of the duct and Digital Signal Processors (DSPs) were used for sampling, storage and processing of data. The study was based on simulations of leaks through valves and search for patterns that characterize the occurrence of such phenomena

Feature selection through gravitational search algorithm

In this paper we deal with the problem of feature selection by introducing a new approach based on Gravitational Search Algorithm (GSA). The proposed algorithm combines the optimization behavior of GSA together with the speed of Optimum-Path Forest (OPF) classifier in order to provide a fast and accurate framework for feature selection. Experiments on datasets obtained from a wide range of applications, such as vowel recognition, image classification and fraud detection in power distribution systems are conducted in order to asses the robustness of the proposed technique against Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) and a Particle Swarm Optimization (PSO)-based algorithm for feature selection.

Mineral Trioxide Aggregate-based Endodontic Sealer Stimulates Hydroxyapatite Nucleation in Human Osteoblast-like Cell Culture

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Staining methods applied to glycol methacrylate embedded tissue sections

The use of glycol methacrylate (GMA) avoids some technical artifacts, which are usually observed in paraffin-embedded sections, providing good morphological resolution. on the other hand, weak staining have been mentioned during the use of different methods in plastic sections. In the present study, changes in the histological staining procedures have been assayed during the use of staining and histochemical methods in different GMA-embedded tissues.Samples of tongue, submandibular and sublingual glands, cartilage, portions of respiratory tract and nervous ganglion were fixed in 4% formaldehyde and embedded in glycol methacrylate. The sections of tongue and nervous ganglion were stained by H&E. Picrosirius, Toluidine Blue and Sudan Black B methods were applied, respectively, for identification of collagen fibers in submandibular gland, sulfated glycosaminoglycans in cartilage (metachromasia) and myelin lipids in nervous ganglion. Periodic Acid-Schiff (PAS) method was used for detection of glycoconjugates in submandibular gland and cartilage while AB/PAS combined methods were applied for detection of mucins in the respiratory tract. In addition, a combination of Alcian Blue (AB) and Picrosirius methods was also assayed in the sublingual gland sections.The GMA-embedded tissue sections showed an optimal morphological integrity and were favorable to the staining methods employed in the present study. In the sections of tongue and nervous ganglion, a good contrast of basophilic and acidophilic structures was obtained by H&E. An intense eosinophilia was observed either in the striated muscle fibers or in the myelin sheaths in which the lipids were preserved and revealed by Sudan Black B. In the cartilage matrix, a strong metachromasia was revealed by Toluidine Blue in the negatively-charged glycosaminoglycans. In the chondrocytes, glycogen granules were intensely positive to PAS method. Extracellular glycoproteins were also PAS positive in the basal membrane and in the region occupied by the lamina externa and reticular fibers surrounding each smooth muscle cells of the blood vessels. In the epithelial cells of the respiratory tract, acid and neutral mucins were histochemically detected by AB and PAS methods, respectively. Moreover, granules containing acid and neutral mucins were revealed in purple by AB and PAS concomitantly. In the sublingual gland sections, a distinct affinity of acid mucins by AB (in turquoise-blue) and collagen fibers by Picrosirius (in red) was obtained when these methods were combined. Although some routine dyes used in paraffin sections have showed a weak stain in historesin sections, our results showed that different dyes could be applied in GMA sections if modified staining procedures were assayed. Therefore, appropriate staining contrast and, thus, detection of one or different substances in a same section can be acquired in association to the good morphological resolution provided by GMA. (C) 2003 Elsevier Ltd. All rights reserved.

Giardia duodenalis: protein substrates degradation by trophozoite proteases

The present investigation was undertaken to identify and characterize trophozoite proteases of five axenic strains of Giardia duodenalis isolated in Brazil and the reference strain Portland 1 isolated in the United States. Trophozoite cell lysates of each strain were analysed for the pattern of proteins and for proteolytic activity. Samples were tested in SDS-polyacrylamide gel electrophoresis for the protein profiles, and the detection of proteases in cell lysates was performed using substrate gel electrophoresis [gelatin, collagen, bovine serum albumin (BSA) and haemoglobin] and azocasein assays. Indeed, synthetic inhibitors were included in the assays to characterize the protease classes. Differences on the hydrolysis patterns of protein substrates were observed in relation to the substrate composition as much as the Giardia trophozoite strain. The substrate-containing gels revealed hydrolysis bands with molecular masses ranging from > 97 to 20-15 kDa, and most zones were common to the five strains. However, some pronounced differences could be detected in the BTU-11 pattern. Azocasein was also degraded; however, depending on the lysate assayed, the degree of substrate degradation was variable. It was observed that inhibitory effects are substrate-dependent since the activity was predominantly due to cysteine proteases against gelatin, collagen, BSA and azocasein substrates and due to serine against haemoglobin. The presence of aspartic protease and aminopeptidase activity in the lysates was also indicated.