1000 resultados para Sistemas de equações lineares


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Knowledge of the leaf area plant are needed for agronomic and physiological studies involving plant growth. The aim of this study was to obtain a mathematical model using linear measures of leaf dimensions, which will allow the estimation of leaf area of Crotalaria juncea L. Correlation studies were conducted involving real leaf area (Sf) and leaf length (C), maximum leaf width (L) and the product between C and L. All tested models (linear, exponential or geometric) provided good estimation of leaf area (above 87%). The better fit was attained using linear model, passing or not through the origin. From a practical viewpoint, it is suggested to use the linear model involving the C and L product, using a linear coefficient equal to zero. Estimation of leaf area of Crotalaria juncea L. can be obtained using the model Sf = 0.7160 x (C*L) with a determination coefficient of 0.9712.

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Com o objetivo de obter uma equação que, por meio de parâmetros lineares dimensionais das folhas, permitisse a estimativa da área foliar de Ipomoea hederifolia e Ipomoea nil, estudaram-se correlações entre a área foliar real (Sf) e os parâmetros dimensionais do limbo foliar, como o comprimento ao longo da nervura principal (C) e a largura máxima (L), perpendicular à nervura principal. Todas as - equações exponenciais, geométricas ou lineares simples - permitiram boas estimativas da área foliar. do ponto de vista prático, sugere-se optar pela equação linear simples envolvendo o produto C x L, considerando-se o coeficiente linear igual a zero. Desse modo, a estimativa da área foliar de I. hederifolia pode ser feita pela fórmula Sf = 0,7583 x (C x L), ou seja, 75,83% do produto entre o comprimento ao longo da nervura principal e a largura máxima, ao passo que, para I. nil, a estimativa da área foliar pode ser feita pela fórmula Sf = 0,6122 x (C x L), ou seja, 61,22% do produto entre o comprimento ao longo da nervura principal e a largura máxima da folha.

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Esta pesquisa teve como objetivo obter uma equação, por meio de medidas lineares dimensionais das folhas, que permitisse a estimativa da área foliar de Momordica charantia e Pyrostegia venusta. Entre maio e dezembro de 2007, foram estudadas as correlações entre a área folia real (Sf) e as medidas dimensionais do limbo foliar, como o comprimento ao longo da nervura principal (C) e a largura máxima (L) perpendicular à nervura principal. Todas as equações, exponenciais geométricas ou lineares simples, permitiram boas estimativas da área foliar. do ponto de vista prático, sugere-se optar pela equação linear simples envolvendo o produto C x L, considerando-se o coeficiente linear igual a zero. Desse modo, a estimativa da área foliar de Momordica charantia pode ser feita pela fórmula Sf = 0,4963 x (C x L), e a de Pyrostegia venusta, por Sf = 0,6649 x (C x L).

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

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The present research aims at contributing to the area of detection and diagnosis of failure through the proposal of a new system architecture of detection and isolation of failures (FDI, Fault Detection and Isolation). The proposed architecture presents innovations related to the way the physical values monitored are linked to the FDI system and, as a consequence, the way the failures are detected, isolated and classified. A search for mathematical tools able to satisfy the objectives of the proposed architecture has pointed at the use of the Kalman Filter and its derivatives EKF (Extended Kalman Filter) and UKF (Unscented Kalman Filter). The use of the first one is efficient when the monitored process presents a linear relation among its physical values to be monitored and its out-put. The other two are proficient in case this dynamics is no-linear. After that, a short comparative of features and abilities in the context of failure detection concludes that the UFK system is a better alternative than the EKF one to compose the architecture of the FDI system proposed in case of processes of no-linear dynamics. The results shown in the end of the research refer to the linear and no-linear industrial processes. The efficiency of the proposed architecture may be observed since it has been applied to simulated and real processes. To conclude, the contributions of this thesis are found in the end of the text

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The usual programs for load flow calculation were in general developped aiming the simulation of electric energy transmission, subtransmission and distribution systems. However, the mathematical methods and algorithms used by the formulations were based, in majority, just on the characteristics of the transmittion systems, which were the main concern focus of engineers and researchers. Though, the physical characteristics of these systems are quite different from the distribution ones. In the transmission systems, the voltage levels are high and the lines are generally very long. These aspects contribute the capacitive and inductive effects that appear in the system to have a considerable influence in the values of the interest quantities, reason why they should be taken into consideration. Still in the transmission systems, the loads have a macro nature, as for example, cities, neiborhoods, or big industries. These loads are, generally, practically balanced, what reduces the necessity of utilization of three-phase methodology for the load flow calculation. Distribution systems, on the other hand, present different characteristics: the voltage levels are small in comparison to the transmission ones. This almost annul the capacitive effects of the lines. The loads are, in this case, transformers, in whose secondaries are connected small consumers, in a sort of times, mono-phase ones, so that the probability of finding an unbalanced circuit is high. This way, the utilization of three-phase methodologies assumes an important dimension. Besides, equipments like voltage regulators, that use simultaneously the concepts of phase and line voltage in their functioning, need a three-phase methodology, in order to allow the simulation of their real behavior. For the exposed reasons, initially was developped, in the scope of this work, a method for three-phase load flow calculation in order to simulate the steady-state behaviour of distribution systems. Aiming to achieve this goal, the Power Summation Algorithm was used, as a base for developping the three phase method. This algorithm was already widely tested and approved by researchers and engineers in the simulation of radial electric energy distribution systems, mainly for single-phase representation. By our formulation, lines are modeled in three-phase circuits, considering the magnetic coupling between the phases; but the earth effect is considered through the Carson reduction. Its important to point out that, in spite of the loads being normally connected to the transformers secondaries, was considered the hypothesis of existence of star or delta loads connected to the primary circuit. To perform the simulation of voltage regulators, a new model was utilized, allowing the simulation of various types of configurations, according to their real functioning. Finally, was considered the possibility of representation of switches with current measuring in various points of the feeder. The loads are adjusted during the iteractive process, in order to match the current in each switch, converging to the measured value specified by the input data. In a second stage of the work, sensibility parameters were derived taking as base the described load flow, with the objective of suporting further optimization processes. This parameters are found by calculating of the partial derivatives of a variable in respect to another, in general, voltages, losses and reactive powers. After describing the calculation of the sensibility parameters, the Gradient Method was presented, using these parameters to optimize an objective function, that will be defined for each type of study. The first one refers to the reduction of technical losses in a medium voltage feeder, through the installation of capacitor banks; the second one refers to the problem of correction of voltage profile, through the instalation of capacitor banks or voltage regulators. In case of the losses reduction will be considered, as objective function, the sum of the losses in all the parts of the system. To the correction of the voltage profile, the objective function will be the sum of the square voltage deviations in each node, in respect to the rated voltage. In the end of the work, results of application of the described methods in some feeders are presented, aiming to give insight about their performance and acuity

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This work develops a robustness analysis with respect to the modeling errors, being applied to the strategies of indirect control using Artificial Neural Networks - ANN s, belong to the multilayer feedforward perceptron class with on-line training based on gradient method (backpropagation). The presented schemes are called Indirect Hybrid Control and Indirect Neural Control. They are presented two Robustness Theorems, being one for each proposed indirect control scheme, which allow the computation of the maximum steady-state control error that will occur due to the modeling error what is caused by the neural identifier, either for the closed loop configuration having a conventional controller - Indirect Hybrid Control, or for the closed loop configuration having a neural controller - Indirect Neural Control. Considering that the robustness analysis is restrict only to the steady-state plant behavior, this work also includes a stability analysis transcription that is suitable for multilayer perceptron class of ANN s trained with backpropagation algorithm, to assure the convergence and stability of the used neural systems. By other side, the boundness of the initial transient behavior is assured by the assumption that the plant is BIBO (Bounded Input, Bounded Output) stable. The Robustness Theorems were tested on the proposed indirect control strategies, while applied to regulation control of simulated examples using nonlinear plants, and its results are presented

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In recent decades, changes have been occurring in the telecommunications industry, allied to competition driven by the policies of privatization and concessions, have fomented the world market irrefutably causing the emergence of a new reality. The reflections in Brazil have become evident due to the appearance of significant growth rates, getting in 2012 to provide a net operating income of 128 billion dollars, placing the country among the five major powers in the world in mobile communications. In this context, an issue of increasing importance to the financial health of companies is their ability to retain their customers, as well as turn them into loyal customers. The appearance of infidelity from customer operators has been generating monthly rates shutdowns about two to four percent per month accounting for business management one of its biggest challenges, since capturing a new customer has meant an expenditure greater than five times to retention. For this purpose, models have been developed by means of structural equation modeling to identify the relationships between the various determinants of customer loyalty in the context of services. The original contribution of this thesis is to develop a model for loyalty from the identification of relationships between determinants of satisfaction (latent variables) and the inclusion of attributes that determine the perceptions of service quality for the mobile communications industry, such as quality, satisfaction, value, trust, expectation and loyalty. It is a qualitative research which will be conducted with customers of operators through simple random sampling technique, using structured questionnaires. As a result, the proposed model and statistical evaluations should enable operators to conclude that customer loyalty is directly influenced by technical and operational quality of the services offered, as well as provide a satisfaction index for the mobile communication segment

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

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Equipment maintenance is the major cost factor in industrial plants, it is very important the development of fault predict techniques. Three-phase induction motors are key electrical equipments used in industrial applications mainly because presents low cost and large robustness, however, it isn t protected from other fault types such as shorted winding and broken bars. Several acquisition ways, processing and signal analysis are applied to improve its diagnosis. More efficient techniques use current sensors and its signature analysis. In this dissertation, starting of these sensors, it is to make signal analysis through Park s vector that provides a good visualization capability. Faults data acquisition is an arduous task; in this way, it is developed a methodology for data base construction. Park s transformer is applied into stationary reference for machine modeling of the machine s differential equations solution. Faults detection needs a detailed analysis of variables and its influences that becomes the diagnosis more complex. The tasks of pattern recognition allow that systems are automatically generated, based in patterns and data concepts, in the majority cases undetectable for specialists, helping decision tasks. Classifiers algorithms with diverse learning paradigms: k-Neighborhood, Neural Networks, Decision Trees and Naïves Bayes are used to patterns recognition of machines faults. Multi-classifier systems are used to improve classification errors. It inspected the algorithms homogeneous: Bagging and Boosting and heterogeneous: Vote, Stacking and Stacking C. Results present the effectiveness of constructed model to faults modeling, such as the possibility of using multi-classifiers algorithm on faults classification

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This work has as main objective the study of arrays of microstrip antennas with superconductor rectangular patch. The phases and the radiation patterns are analyzed. A study of the main theories is presented that explain the microscopic and macroscopic phenomena of superconductivity. The BCS, London equations and the Two Fluid Model, are theories used in the applications of superconductors, at the microstrip antennas and antennas arrays. Phase Arrangements will be analyzed in linear and planar configurations. The arrangement factors of these configurations are obtained, and the phase criteria and the spacing between the elements, are examined in order to minimize losses in the superconductor, compared with normal conductors. The new rectangular patch antenna, consist of a superconducting material, with the critical temperature of 233 K, whose formula is Tl5Ba4Ca2Cu9Oy, is analyzed by the method of the Transverse nTransmission Line (TTL), developed by H. C. C. Fernandes, applied in the Fourier Transform Domain (FTD). The TTL is a full-wave method, which has committed to obtaining the electromagnetic fields in terms of the transverse components of the structure. The inclusion of superconducting patch is made using the complex resistive boundary condition, using the impedance of the superconductor in the Dyadic Green function, in the structure. Results are obtained from the resonance frequency depending on the parameters of the antenna using superconducting material, radiation patterns in E-Plane and H -Plane, the phased antennas array in linear and planar configurations, for different values of phase angles and different spacing between the elements

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This work has as main objective to study the application of microstrip antennas with patch and use of superconducting arrays of planar and linear phase. Was presented a study of the main theories that explain clearly the superconductivity. The BCS theory, Equations of London and the Two Fluid Model are theories that supported the implementation of the superconducting microstrip antennas. Arrangements phase was analyzed in linear and planar configuration of its antennas are reported factors such arrays to settings and criteria of phase and the spacing between the elements that make the arrayst was reviewed in order to minimize losses due to secondary lobes. The antenna used has a rectangular patch Sn5InCa2Ba4Cu10Oy the superconducting material was analyzed by the method of Transverse Transmission Line (TTL) applied in the field of Fourier transform (FTD). The TTL is a full-wave method, which has committed to obtaining the electromagnetic fields in terms of cross-cutting components of the structure. The inclusion of superconducting patch is made using the boundary condition, complex resistive. Are obtained when the resonant frequency depending on the parameters of the antenna, radiation pattern of E-Plan and H-Plan for the M-phase arrangements of antennas in the linear and planar configurations for different values of phase and spacing between the elements.

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This work deals with an on-line control strategy based on Robust Model Predictive Control (RMPC) technique applied in a real coupled tanks system. This process consists of two coupled tanks and a pump to feed the liquid to the system. The control objective (regulator problem) is to keep the tanks levels in the considered operation point even in the presence of disturbance. The RMPC is a technique that allows explicit incorporation of the plant uncertainty in the problem formulation. The goal is to design, at each time step, a state-feedback control law that minimizes a 'worst-case' infinite horizon objective function, subject to constraint in the control. The existence of a feedback control law satisfying the input constraints is reduced to a convex optimization over linear matrix inequalities (LMIs) problem. It is shown in this work that for the plant uncertainty described by the polytope, the feasible receding horizon state feedback control design is robustly stabilizing. The software implementation of the RMPC is made using Scilab, and its communication with Coupled Tanks Systems is done through the OLE for Process Control (OPC) industrial protocol

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A aplicação mecanizada de herbicidas em ferrovias tem como principal vantagem a grande capacidade operacional, cobrindo trechos extensos em curtos espaços de tempo. Entretanto em função das características dos equipamentos utilizados, quase sempre ocorre grande desperdício de herbicida. A aplicação manual, através de pulverizadores costais, tem como principal vantagem a possibilidade da pulverização dirigida às áreas infestadas, diminuindo a quantidade de herbicida aplicado. Por outro lado, sua reduzida capacidade operacional faz com que a aplicação de longos trechos seja demorada, tornando-a, assim, mais dependente dos problemas climáticos e operacionais da ferrovia. O objetivo do trabalho foi realizar uma análise comparativa das características operacionais e econômicas destes sistemas de aplicação, apontando os fatores mais importantes a serem avaliados para a sua implantação. Para tanto, foram realizadas simulações em computador, baseando-se em diversas equações matemáticas e dados levantados no campo. Os resultados mostraram que a aplicação manual apresentou-se mais econômica apenas para trechos com baixas infestações (até 10%, e média). Na composição de custos, os gastos com herbicidas corresponderam a cerca de 80% do total para a aplicação mecanizada e apenas 8% na manual. Levando-se em conta os fatores operacionais e de mão-de-obra, em apenas um dos trechos avaliados houve vantagem econômica do uso da aplicação manual.

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Conventional methods to solve the problem of blind source separation nonlinear, in general, using series of restrictions to obtain the solution, often leading to an imperfect separation of the original sources and high computational cost. In this paper, we propose an alternative measure of independence based on information theory and uses the tools of artificial intelligence to solve problems of blind source separation linear and nonlinear later. In the linear model applies genetic algorithms and Rényi of negentropy as a measure of independence to find a separation matrix from linear mixtures of signals using linear form of waves, audio and images. A comparison with two types of algorithms for Independent Component Analysis widespread in the literature. Subsequently, we use the same measure of independence, as the cost function in the genetic algorithm to recover source signals were mixed by nonlinear functions from an artificial neural network of radial base type. Genetic algorithms are powerful tools for global search, and therefore well suited for use in problems of blind source separation. Tests and analysis are through computer simulations