818 resultados para Linear matrix inequalities (LMI) techniques
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This paper presents the techniques of likelihood prediction for the generalized linear mixed models. Methods of likelihood prediction is explained through a series of examples; from a classical one to more complicated ones. The examples show, in simple cases, that the likelihood prediction (LP) coincides with already known best frequentist practice such as the best linear unbiased predictor. The paper outlines a way to deal with the covariate uncertainty while producing predictive inference. Using a Poisson error-in-variable generalized linear model, it has been shown that in complicated cases LP produces better results than already know methods.
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Apresenta-se uma formulação do tipo incrementaliterativa destinada a análise não linear de pórticos espaciais. Considera-se os efeitos não lineares introduzidos pelas mudanças de configuração geométrica da estrutura e também pela combinação destes efeitos com aqueles inerentes ao comportamento plástico exibido pelo material. As relações cinemáticas empregadas permitem a consideração de deslocamentos arbitrariamente grandes, acompanhadas de pequenas deformações . A modelagem do comportamento plástico do material é efetuada através do conceito de rótula plástica, estabelecido a partir de um critério de plastificação generalizado. Adota-se uma matriz de rigidez geométrica de barra baseada em momentos semitangenciais. Para elementos com extremos plastificados, é deduzida uma matriz de rigidez elasto-plástica. Emprega-se um método numérico do tipo incremental-iterativo, que utiliza como condição básica de controle da análise a constância do trabalho realizado pelos incrementos de cargas, em cada passo incremental (Método de Controle por Trabalho).A formulação permite uma descricão completa do desempenho mecânico da estrutura, inclusive em estágio de deformação pós-crítico em que ocorre regressão do carregamento com aumento de deslocamentos, ou vice-versa. A formulação foi implementada em um programa computacional elaborado em linguagem FORTRAN. Vários exemplos numéricos são apresentados para mostrar a eficiência das procedimentos propostos.
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Em cenas naturais, ocorrem com certa freqüência classes espectralmente muito similares, isto é, os vetores média são muito próximos. Em situações como esta, dados de baixa dimensionalidade (LandSat-TM, Spot) não permitem uma classificação acurada da cena. Por outro lado, sabe-se que dados em alta dimensionalidade [FUK 90] tornam possível a separação destas classes, desde que as matrizes covariância sejam suficientemente distintas. Neste caso, o problema de natureza prática que surge é o da estimação dos parâmetros que caracterizam a distribuição de cada classe. Na medida em que a dimensionalidade dos dados cresce, aumenta o número de parâmetros a serem estimados, especialmente na matriz covariância. Contudo, é sabido que, no mundo real, a quantidade de amostras de treinamento disponíveis, é freqüentemente muito limitada, ocasionando problemas na estimação dos parâmetros necessários ao classificador, degradando portanto a acurácia do processo de classificação, na medida em que a dimensionalidade dos dados aumenta. O Efeito de Hughes, como é chamado este fenômeno, já é bem conhecido no meio científico, e estudos vêm sendo realizados com o objetivo de mitigar este efeito. Entre as alternativas propostas com a finalidade de mitigar o Efeito de Hughes, encontram-se as técnicas de regularização da matriz covariância. Deste modo, técnicas de regularização para a estimação da matriz covariância das classes, tornam-se um tópico interessante de estudo, bem como o comportamento destas técnicas em ambientes de dados de imagens digitais de alta dimensionalidade em sensoriamento remoto, como por exemplo, os dados fornecidos pelo sensor AVIRIS. Neste estudo, é feita uma contextualização em sensoriamento remoto, descrito o sistema sensor AVIRIS, os princípios da análise discriminante linear (LDA), quadrática (QDA) e regularizada (RDA) são apresentados, bem como os experimentos práticos dos métodos, usando dados reais do sensor. Os resultados mostram que, com um número limitado de amostras de treinamento, as técnicas de regularização da matriz covariância foram eficientes em reduzir o Efeito de Hughes. Quanto à acurácia, em alguns casos o modelo quadrático continua sendo o melhor, apesar do Efeito de Hughes, e em outros casos o método de regularização é superior, além de suavizar este efeito. Esta dissertação está organizada da seguinte maneira: No primeiro capítulo é feita uma introdução aos temas: sensoriamento remoto (radiação eletromagnética, espectro eletromagnético, bandas espectrais, assinatura espectral), são também descritos os conceitos, funcionamento do sensor hiperespectral AVIRIS, e os conceitos básicos de reconhecimento de padrões e da abordagem estatística. No segundo capítulo, é feita uma revisão bibliográfica sobre os problemas associados à dimensionalidade dos dados, à descrição das técnicas paramétricas citadas anteriormente, aos métodos de QDA, LDA e RDA, e testes realizados com outros tipos de dados e seus resultados.O terceiro capítulo versa sobre a metodologia que será utilizada nos dados hiperespectrais disponíveis. O quarto capítulo apresenta os testes e experimentos da Análise Discriminante Regularizada (RDA) em imagens hiperespectrais obtidos pelo sensor AVIRIS. No quinto capítulo são apresentados as conclusões e análise final. A contribuição científica deste estudo, relaciona-se à utilização de métodos de regularização da matriz covariância, originalmente propostos por Friedman [FRI 89] para classificação de dados em alta dimensionalidade (dados sintéticos, dados de enologia), para o caso especifico de dados de sensoriamento remoto em alta dimensionalidade (imagens hiperespectrais). A conclusão principal desta dissertação é que o método RDA é útil no processo de classificação de imagens com dados em alta dimensionalidade e classes com características espectrais muito próximas.
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The heteroskedasticity-consistent covariance matrix estimator proposed by White (1980), also known as HC0, is commonly used in practical applications and is implemented into a number of statistical software. Cribari–Neto, Ferrari & Cordeiro (2000) have developed a bias-adjustment scheme that delivers bias-corrected White estimators. There are several variants of the original White estimator that also commonly used by practitioners. These include the HC1, HC2 and HC3 estimators, which have proven to have superior small-sample behavior relative to White’s estimator. This paper defines a general bias-correction mechamism that can be applied not only to White’s estimator, but to variants of this estimator as well, such as HC1, HC2 and HC3. Numerical evidence on the usefulness of the proposed corrections is also presented. Overall, the results favor the sequence of improved HC2 estimators.
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Thirty-six Madeira wine samples from Boal, Malvazia, Sercial and Verdelho white grape varieties were analyzed in order to estimate the free fraction of monoterpenols and C13 norisoprenoids (terpenoid compounds) using dynamic headspace solid phase micro-extraction (HS-SPME) technique coupled with gas chromatography–mass spectrometry (GC–MS). The average values from three vintages (1998–2000) show that these wines have characteristic profiles of terpenoid compounds. Malvazia wines exhibits the highest values of total free monoterpenols, contrary to Verdelho wines which had the lowest levels of terpenoids but produced the highest concentration of farnesol. The use of multivariate analysis techniques allows establishing relations between the compounds and the varieties under investigation. Principal component analysis (PCA) and linear discriminant analysis (LDA) were applied to the obtained matrix data. A good separation and classification power between the four groups as a function of their varietal origin was observed.
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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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One of waste produced on large scale during the well drilling is the gravel drilling. There are techniques for the treatment of the same, but there isn t consensus on what are the best in terms of economic and environmental. One alternative for disposal of this waste and objective of this paper is the incorporation and immobilization of gravel clay matrix to assess their technological properties. The Raw Materials used were characterized by the following techniques: Chemical Analysis by X-ray fluorescence (XRF), mineralogical analysis by X-ray Diffraction (XRD), Grain Size Analysis (FA) and Thermal Analysis by Thermogravimetry (TG) and thermodiferential (DTA). After characterizing, samples were formulated in the following percentages: 0, 5, 10, 15, 25, 50, 75, 100% (weight) of gravel drilling, then the pieces were pressed, dried (110 ° C) and sintered at temperatures of 850, 950 and 1050 ° C. After sintering, samples were tested for water absorption, linear shrinkage, flexural strength, porosity, density, XRD and test color. The results concluded that the incorporation of gravel drilling is a viable possibility for solid masonry bricks and ceramic blocks manufacture at concentrations and firing temperature described here. Residue incorporation reduces an environmental problem, the cost of raw materials for manufacture of ceramic products
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Over recent years the structural ceramics industry in Brazil has found a very favorable market for growth. However, difficulties related to productivity and product quality are partially inhibiting this possible growth. An alternative for trying to solve these problems and, thus, provide the pottery industry the feasibility of full development, is the substitution of firewood used in the burning process by natural gas. In order to contribute to this process of technological innovation, this paper studies the effect of co-use of ceramic phyllite and kaolin waste on the properties of a clay matrix, verifying the possible benefits that these raw materials can give to the final product, as well as the possibility of such materials to reduce the heat load necessary to obtain products with equal or superior quality. The study was divided into two steps: characterization of materials and study of formulations. Two clays, a phyllite and a residue of kaolin were characterized by the following techniques: laser granulometry, plasticity index by Atterberg limits, X-ray fluorescence, X-ray diffraction, mineralogical composition by Rietveld, thermogravimetric and differential thermal analysis. To study the formulations, specifically for evaluation of technological properties of the parts, was performed an experimental model that combined planning involving a mixture of three components (standard mass x phyllite x kaolin waste) and a 23 factorial design with central point associated with thermal processing parameters. The experiment was performed with restricted strip-plot randomization. In total, 13 compositional points were investigated within the following constraints: phyllite ≤ 20% by weight, kaolin waste ≤ 40% by weight, and standard mass ≥ 60% by weight. The thermal parameters were used at the following levels: 750 and 950 °C to the firing temperature, 5 and 15 °C/min at the heating rate, 15 and 45min to the baseline. The results showed that the introduction of phyllite and/or kaolin waste in ceramic body produced a number of benefits in properties of the final product, such as: decreased absorption of water, apparent porosity and linear retraction at burn; besides the increase in apparent specific mass and mechanical properties of parts. The best results were obtained in the compositional points where the sum of the levels of kaolin waste and phyllite was maximal (40% by weight), as well as conditions which were used in firing temperatures of 950 °C. Regarding the prospect of savings in heat energy required to form the desired microstructure, the phyllite and the residue of kaolin, for having small particle sizes and constitutions mineralogical phases with the presence of fluxes, contributed to the optimization of the firing cycle.
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One of the main activities in the petroleum engineering is to estimate the oil production in the existing oil reserves. The calculation of these reserves is crucial to determine the economical feasibility of your explotation. Currently, the petroleum industry is facing problems to analyze production due to the exponentially increasing amount of data provided by the production facilities. Conventional reservoir modeling techniques like numerical reservoir simulation and visualization were well developed and are available. This work proposes intelligent methods, like artificial neural networks, to predict the oil production and compare the results with the ones obtained by the numerical simulation, method quite a lot used in the practice to realization of the oil production prediction behavior. The artificial neural networks will be used due your learning, adaptation and interpolation capabilities
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Maize gluten feed (MGF) is a co-product of wet milling of maize, and is composed of structures that remain after most starch, gluten and germ has been extracted from the grain. Although currently used in dog foods, its digestibility and energy values have not been documented. Two techniques were used to determine nutrient digestibility of MGF for dog foods. Both techniques used extruded diets fed to Beagle dogs, with six replicates per diet. The first study used a difference method in which 300 g/kg of a reference diet was replaced by MGF. Based on the difference method, the coefficient of total tract apparent digestibility (CTTAD) of MGF was 0.53 for dry matter (DM), 0.69 for crude protein (CP), 0.74 for fat, 0.99 for starch, and 0.55 for gross energy (GE). The calculated metabolizable energy (ME) of MGF was 7.99 MJ/kg (as-fed). The second study used a regression method and included a basal diet and a basal diet with 70, 140 and 210 g MGF/kg of diet (as a substitute for maize starch). Maize gluten feed inclusion resulted in a linear reduction of CTTAD of DM (R(2)=0.99; P<0.001), CP (R(2)=0.95; P=0.002), fat (R(2)=0.87; P=0.009). starch (R(2)=0.81; P<0.001), and GE (R(2)=0.99; P<0.001). Faecal production increased linearly from 56 g to 107 g/dog/d (R(2)=0.99; P<0.001), with a linear reduction of faecal DM (R(2)=0.99: P<0.001) and a linear increase in faecal lactic acid concentration (P<0.02). Both urine (R(2)=0.77; P=0.029) and faeces (R(2)=0.92: P=0.019) showed a linear reduction in pH. Results of ingredient MAD obtained by the regression and difference methods were close (6% or less of variation) for CP, fat, and starch, and also for ME content (1.4% higher for the difference method), but the two methods disagreed on calculated CTTAD of DM and organic matter. The high dietary fiber content of MGF (382 g/kg) may explain the low digestibility of this ingredient. Maize gluten feed could be a useful ingredient for formulations designed to have low energy or reduce the urine pH of dogs. (C) 2011 Elsevier B.V. All rights reserved.
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Slugging is a well-known slugging phenomenon in multiphase flow, which may cause problems such as vibration in pipeline and high liquid level in the separator. It can be classified according to the place of its occurrence. The most severe, known as slugging in the riser, occurs in the vertical pipe which feeds the platform. Also known as severe slugging, it is capable of causing severe pressure fluctuations in the flow of the process, excessive vibration, flooding in separator tanks, limited production, nonscheduled stop of production, among other negative aspects that motivated the production of this work . A feasible solution to deal with this problem would be to design an effective method for the removal or reduction of the system, a controller. According to the literature, a conventional PID controller did not produce good results due to the high degree of nonlinearity of the process, fueling the development of advanced control techniques. Among these, the model predictive controller (MPC), where the control action results from the solution of an optimization problem, it is robust, can incorporate physical and /or security constraints. The objective of this work is to apply a non-conventional non-linear model predictive control technique to severe slugging, where the amount of liquid mass in the riser is controlled by the production valve and, indirectly, the oscillation of flow and pressure is suppressed, while looking for environmental and economic benefits. The proposed strategy is based on the use of the model linear approximations and repeatedly solving of a quadratic optimization problem, providing solutions that improve at each iteration. In the event where the convergence of this algorithm is satisfied, the predicted values of the process variables are the same as to those obtained by the original nonlinear model, ensuring that the constraints are satisfied for them along the prediction horizon. A mathematical model recently published in the literature, capable of representing characteristics of severe slugging in a real oil well, is used both for simulation and for the project of the proposed controller, whose performance is compared to a linear MPC
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One of the waste generated during the drilling of oil wells are gravel which are impregnated of drilling fluid. This residue consists of highly toxic chemicals, including toxic metals. This study suggests an alternative process to the treatment of this waste, by incorporating it the form of raw material in the ceramic matrix , and by solidification and stabilize the metals present, Aluminum (Al), Iron (Fe), Manganese (Mn) and Zinc (Zn). The raw materials were characterized by the techniques of X ray fluorescence (FRX), X ray diffraction (DRX), laser granulometry (GL), thermogravimetry (TG) and differential thermal analysis (ADT). To evaluate the percentage of gravel effect the environmental and technological properties were obtained from formulations containing 0, 10 and 20 % by weight of gravel in the ceramic matrix. After sintering at temperatures 1080, 1120 and 1160 °C, the samples were tested for water absorption, the linear shrinkage firing, voltage of rupture and solubility. The results obtained showed that the stabilization by solidification, is a viable alternative to safe disposal of waste drilling. Ceramics products can be used in the manufacture of solid bricks
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This paper presents a pole placement method using both the augmented Jacobian and the corresponding system transfer function matrices. From the manipulation of these matrices a straightforward approach results to get the coefficients of a non-linear system, whose solution gives the parameters of the stabilizers that can provide a pre-specified minimum damping to the system. (C) 2001 Elsevier B.V. Ltd. All rights reserved.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)