987 resultados para architecture evaluation
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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores
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This paper aims to study the best way to express the parasitemia of Trypanosoma cruzi's experimentally infected animals. Individual scores may have a great variability, not emphasized by the majority of the authors. A group of 50 rats infected with 1x10(6) trypomastigotes of T. cruzi Y strain was used and the parasitemia was estimated by BRENER' s method. The results showed that the median can avoid false results due to very high or low parasitemias but it does not have the mathematic properties necessary for analysis of variance. The comparison of the means of the original and transformed data, with their respective coefficients of variability (CV), showed that the logarithmic mean (Mlog) have the minor value of CV. Therefore, the Mlog is the best way to express the parasitemia when the data show great variability. The number of the animal for group did not affect the variability of data when the Mlog and CV were used.
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Apresentação realizada a uma delegação da Administração pública da Bulgária, que visitou o INA em 2 de Dezembro de 2008.
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Sparse matrix-vector multiplication (SMVM) is a fundamental operation in many scientific and engineering applications. In many cases sparse matrices have thousands of rows and columns where most of the entries are zero, while non-zero data is spread over the matrix. This sparsity of data locality reduces the effectiveness of data cache in general-purpose processors quite reducing their performance efficiency when compared to what is achieved with dense matrix multiplication. In this paper, we propose a parallel processing solution for SMVM in a many-core architecture. The architecture is tested with known benchmarks using a ZYNQ-7020 FPGA. The architecture is scalable in the number of core elements and limited only by the available memory bandwidth. It achieves performance efficiencies up to almost 70% and better performances than previous FPGA designs.
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Comunicação apresentada na 32ª conferência anual do European Group of Public Administration (EGPA), em Toulouse.
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In the last decade, local image features have been widely used in robot visual localization. In order to assess image similarity, a strategy exploiting these features compares raw descriptors extracted from the current image with those in the models of places. This paper addresses the ensuing step in this process, where a combining function must be used to aggregate results and assign each place a score. Casting the problem in the multiple classifier systems framework, in this paper we compare several candidate combiners with respect to their performance in the visual localization task. For this evaluation, we selected the most popular methods in the class of non-trained combiners, namely the sum rule and product rule. A deeper insight into the potential of these combiners is provided through a discriminativity analysis involving the algebraic rules and two extensions of these methods: the threshold, as well as the weighted modifications. In addition, a voting method, previously used in robot visual localization, is assessed. Furthermore, we address the process of constructing a model of the environment by describing how the model granularity impacts upon performance. All combiners are tested on a visual localization task, carried out on a public dataset. It is experimentally demonstrated that the sum rule extensions globally achieve the best performance, confirming the general agreement on the robustness of this rule in other classification problems. The voting method, whilst competitive with the product rule in its standard form, is shown to be outperformed by its modified versions.
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Mice transcutaneously infected with about 400 cercariae were submitted to treatment with oxamniquine (400 mg/kg), 24 hours after infection. The recovery of schistosomules, at 4, 24, 48 and 72 hours and 35 days after treatment, showed the activity of the drug on the parasites, thus practically preventing their migration from the skin to the lungs. Worm recovery performed in the lungs (96 hours after treatment) showed recovery means of 0.6 worms/mouse in the treated group and 53.8 in the control group (untreated). The perfusion of the portal system carried out at 35 days after treatment clearly showed the elimination of all the parasites in the treated group, whereas a recovery mean of 144.7 worms/mouse was detected in the control group (untreated). These findings confirm the efficacy of oxamniquine at the skin phase of infection, and also show similarity with the immunization method that uses irradiated cercariae. The practical application of these findings in the medical clinic is discussed too
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The reuse of waste fluid catalytic cracking (FCC) catalyst as partial surrogate for cement can reduce the environmental impact of both the oil-refinery and cement production industries [1,2]. FCC catalysts can be considered as pozzolanic materials since in the presence of water they tend to chemically react with calcium hydroxide to produce compounds possessing cementitious properties [3,4]. In addition, partial replacement of cement with FCC catalysts can enhance the performance of pastes and mortars, namely by improving their compressive strength [5,6]. In the present work the reaction of waste FCC catalyst with Ca(OH)2 has been investigated after a curing time of 28 days by scanning electron microscopy (SEM) with electron backscattered signal (BSE) combined with X-ray energy dispersive spectroscopy (EDS) carried out with a JEOL JSM 7001F instrument operated at 15 kV coupled to an INCA pentaFetx3 Oxford spectrometer. The polished cross-sections of FCC particles embedded in resin have also been evaluated by atomic force microscopy (AFM) in contact mode (CM) using a NanoSurf EasyScan 2 instrument. The SEM/EDS results revealed that an inward migration of Ca occurred during the reaction. A weaker outward migration of Si and Al was also apparent (Fig. 1). The migration of Ca was not homogeneous and tended to follow high-diffusivity paths within the porous waste FCC catalyst particles. The present study suggests that the porosity of waste FCC catalysts is key for the migration/reaction of Ca from the surrounding matrix, playing an important role in the pozzolanic activity of the system. The topography images and surface roughness parameters obtained by atomic force microscopy can be used to infer the local porosity in waste FCC catalyst particles (Fig. 2).
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Dissertação apresentada na Faculdade de Ciências e Tecnologias da Universidade Nova de Lisboa para a obtenção do Grau de Mestre em Engenharia Informática
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This paper proposes an FPGA-based architecture for onboard hyperspectral unmixing. This method based on the Vertex Component Analysis (VCA) has several advantages, namely it is unsupervised, fully automatic, and it works without dimensionality reduction (DR) pre-processing step. The architecture has been designed for a low cost Xilinx Zynq board with a Zynq-7020 SoC FPGA based on the Artix-7 FPGA programmable logic and tested using real hyperspectral datasets. Experimental results indicate that the proposed implementation can achieve real-time processing, while maintaining the methods accuracy, which indicate the potential of the proposed platform to implement high-performance, low cost embedded systems.