823 resultados para Machine components
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This study presents an approach to combine uncertainties of the hydrological model outputs predicted from a number of machine learning models. The machine learning based uncertainty prediction approach is very useful for estimation of hydrological models' uncertainty in particular hydro-metrological situation in real-time application [1]. In this approach the hydrological model realizations from Monte Carlo simulations are used to build different machine learning uncertainty models to predict uncertainty (quantiles of pdf) of the a deterministic output from hydrological model . Uncertainty models are trained using antecedent precipitation and streamflows as inputs. The trained models are then employed to predict the model output uncertainty which is specific for the new input data. We used three machine learning models namely artificial neural networks, model tree, locally weighted regression to predict output uncertainties. These three models produce similar verification results, which can be improved by merging their outputs dynamically. We propose an approach to form a committee of the three models to combine their outputs. The approach is applied to estimate uncertainty of streamflows simulation from a conceptual hydrological model in the Brue catchment in UK and the Bagmati catchment in Nepal. The verification results show that merged output is better than an individual model output. [1] D. L. Shrestha, N. Kayastha, and D. P. Solomatine, and R. Price. Encapsulation of parameteric uncertainty statistics by various predictive machine learning models: MLUE method, Journal of Hydroinformatic, in press, 2013.
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This thesis presents the study and development of fault-tolerant techniques for programmable architectures, the well-known Field Programmable Gate Arrays (FPGAs), customizable by SRAM. FPGAs are becoming more valuable for space applications because of the high density, high performance, reduced development cost and re-programmability. In particular, SRAM-based FPGAs are very valuable for remote missions because of the possibility of being reprogrammed by the user as many times as necessary in a very short period. SRAM-based FPGA and micro-controllers represent a wide range of components in space applications, and as a result will be the focus of this work, more specifically the Virtex® family from Xilinx and the architecture of the 8051 micro-controller from Intel. The Triple Modular Redundancy (TMR) with voters is a common high-level technique to protect ASICs against single event upset (SEU) and it can also be applied to FPGAs. The TMR technique was first tested in the Virtex® FPGA architecture by using a small design based on counters. Faults were injected in all sensitive parts of the FPGA and a detailed analysis of the effect of a fault in a TMR design synthesized in the Virtex® platform was performed. Results from fault injection and from a radiation ground test facility showed the efficiency of the TMR for the related case study circuit. Although TMR has showed a high reliability, this technique presents some limitations, such as area overhead, three times more input and output pins and, consequently, a significant increase in power dissipation. Aiming to reduce TMR costs and improve reliability, an innovative high-level technique for designing fault-tolerant systems in SRAM-based FPGAs was developed, without modification in the FPGA architecture. This technique combines time and hardware redundancy to reduce overhead and to ensure reliability. It is based on duplication with comparison and concurrent error detection. The new technique proposed in this work was specifically developed for FPGAs to cope with transient faults in the user combinational and sequential logic, while also reducing pin count, area and power dissipation. The methodology was validated by fault injection experiments in an emulation board. The thesis presents comparison results in fault coverage, area and performance between the discussed techniques.
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In this work is reported, in a first step, the effect of different experimental parameters and their relation with polymer properties using the homogeneous binary catalyst system composed by Ni(α-diimine)Cl2 (α-diimine = 1,4-bis(2,6-diisopropylphenyl)- acenaphthenediimine) and {TpMs*}V(Ntbu)Cl2 (TpMs* = hydridobis(3-mesitylpyrazol-1- yl)(5-mesitylpyrazol-1-yl)) activated with MAO. This complexes combination produces, in a single reactor, polyethylene blends with different and controlled properties dependent on the polymerization temperature, solvent and Nickel molar fraction (xNi). In second, the control of linear low density polyethylene (LLDPE) production was possible, using a combination of catalyst precursors {TpMs}NiCl (TpMs = hydridotris(3- mesitylpyrazol-1-yl)) and Cp2ZrCl2, activated with MAO/TMA, as Tandem catalytic system. The catalytic activities as well as the polymer properties are dependent on xNi. Polyethylene with different Mw and controlled branches is produced only with ethylene monomer. Last, the application group 3 metals catalysts based, M(allyl)2Cl(MgCl2)2.4THF (M = Nd, La and Y), in isoprene polymerization with different cocatalysts systems and experimental parameters is reported. High yields and polyisoprene with good and controlled properties were produced. The metal center, cocatalysts and the experimental parameters are determinant for the polymers properties and their control. High conversions in cis-1,4- or trans-1,4-polyisoprene were obtained and the polymer microstructure depending of cocatalyst and metal type. Combinations of Y and La precursors were effective systems for the cis/transpolyisoprene blends production, and the control of cis-trans-1,4-microstructures by Yttrium molar fraction (xY) variation was possible.
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Analisa o modelo de criação de conhecimento da Philips Components Display e confronta-o com um modelo teórico. Aborda as diferenças culturais na aplicação do modelo teórico e que impactos essas diferenças representas na aplicalidade desse modelo na cultura da PCD e brasileira
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A new form of composition of the indicators employed to generate the United Nations Human Development Index (HDI) is presented here. This form of composition is based on the assumption that random errors affect the measurement of each indicator. This assumption allows for replacing the vector of evaluations according to each indicator by vectors of probabilities of being the best or the worst according to such attribute. The probabilistic composition of such probabilities of preference according to each indicator into probabilities of being the best or the worst according to all of them generates indices that may unveil, on one hand, performances to be followed and, on the other hand, extreme conditions that an additive composition would hide. Differences between the results of application of the diverse forms of composition are examined in the case of the HDI and in the case of the districts version of the HDI employed to compare Brazilian municipalities. It is verified that the smallest correlation between the education.
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In present research, headspace solid-phase microextraction (HS-SPME) followed by gas chromatography–mass spectrometry (GC–qMS), was evaluated as a reliable and improved alternative to the commonly used liquid–liquid extraction (LLE) technique for the establishment of the pattern of hydrolytically released components of 7 Vitis vinifera L. grape varieties, commonly used to produce the world-famous Madeira wine. Since there is no data available on their glycosidic fractions, at a first step, two hydrolyse procedures, acid and enzymatic, were carried out using Boal grapes as matrix. Several parameters susceptible of influencing the hydrolytic process were studied. The best results, expressed as GC peak area, number of identified components and reproducibility, were obtained using ProZym M with b-glucosidase activity at 35 °C for 42 h. For the extraction of hydrolytically released components, HS-SPME technique was evaluated as a reliable and improved alternative to the conventional extraction technique, LLE (ethyl acetate). HS-SPME using DVB/CAR/PDMS as coating fiber displayed an extraction capacity two fold higher than LLE (ethyl acetate). The hydrolyzed fraction was mainly characterized by the occurrence of aliphatic and aromatic alcohols, followed by acids, esters, carbonyl compounds, terpenoids, and volatile phenols. Concerning to terpenoids its contribution to the total hydrolyzed fraction is highest for Malvasia Cândida (23%) and Malvasia Roxa (13%), and their presence according previous studies, even at low concentration, is important from a sensorial point of view (can impart floral notes to the wines), due to their low odor threshold (μg/L). According to the obtained data by principal component analysis (PCA), the sensorial properties of Madeira wines produced by Malvasia Cândida and Malvasia Roxa could be improved by hydrolysis procedure, since their hydrolyzed fraction is mainly characterized by terpenoids (e.g. linalool, geraniol) which are responsible for floral notes. Bual and Sercial grapes are characterized by aromatic alcohols (e.g. benzyl alcohol, 2-phenylethyl alcohol), so an improvement in sensorial characteristics (citrus, sweet and floral odors) of the corresponding wines, as result of hydrolytic process, is expected.
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SOARES, Elvira Maria Mafaldo et al. Prevalence of the metabolic syndrome and its components in Brazilian women with polycystic ovary syndrome. Fertility and Sterility, v.89, n.3, p.649-655, mar. 2008
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The spread of the Web boosted the dissemination of Information Systems (IS) based on the Web. In order to support the implementation of these systems, several technologies came up or evolved with this purpose, namely the programming languages. The Technology Acceptance Model TAM (Davis, 1986) was conceived aiming to evaluate the acceptance/use of information technologies by their users. A lot of studies and many applications have used the TAM, however, in the literature it was not found a mention of the use of such model related to the use of programming languages. This study aims to investigate which factors influence the use of programming languages on the development of Web systems by their developers, applying an extension of the TAM, proposed in this work. To do so, a research was done with Web developers in two Yahoo groups: java-br and python-brasil, where 26 Java questionnaires and 39 Python questionnaires were fully answered. The questionnaire had general questions and questions which measured intrinsic and extrinsic factors of the programming languages, the perceived usefulness, the perceived ease of use, the attitude toward the using and the programming language use. Most of the respondents were men, graduate, between 20 and 30 years old, working in the southeast and south regions. The research was descriptive in the sense of its objectives. Statistical tools, descriptive statistics, main components and linear regression analysis were used for the data analysis. The foremost research results were: Java and Python have machine independence, extensibility, generality and reliability; Java and Python are more used by corporations and international organizations than supported by the government or educational institutions; there are more Java programmers than Python programmers; the perceived usefulness is influenced by the perceived ease of use; the generality and the extensibility are intrinsic factors of programming languages which influence the perceived ease of use; the perceived ease of use influences the attitude toward the using of the programming language
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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The determination of the chemical composition of body and carcass is important in nutritional and growth regulation studies. The purpose of this study was to develop equations to predict the chemical composition of body and carcass using chemical composition of body components. Twenty 3/4Boer x 1/4Saanen crossbred male kids, weighing from 20 to 35 kg, were used in this study. The empty body chemical composition was measured by grinding all body components and sampling for chemical analyses. The body components used to estimate body and carcass composition were: neck, fore leg, ribs, loin, hind leg, 9-11 th rib section, non-carcass components (head plus feet, organs plus blood, and hide), visceral fat, and kidney fat. The chemical composition of organs plus blood and 9-11 th rib section had the highest precision to estimate percentage of fat, protein, and water in the body (r(2) of 0.94, 0.82, and 0.90, respectively). For carcass composition, the chemical composition of ribs was the best component to predict all carcass chemical components; however, the equations to estimate the percentages of protein and ash showed a low precision (r(2) = 0.48, 0.44, respectively). The 9-11 th rib section was accurate and precise to estimate carcass fat percentage. We concluded the chemical composition of the body of 3/4Boer x 1/4Saanen crossbred male kids was highly correlated with the composition of body parts, specifically organs plus blood and 9-11 th rib section. Further studies should focus on evaluating these body parts for different breeds and genders under different production scenarios. (C) 2007 Elsevier B.V. All rights reserved.