Materiais supercondutores HTS para arranjos de antenas e aplicação de PBG para micro-ondas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Aplicações de arranjos de antenas de microfita com patch supercondutor

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

Antenas de microfita com patch supercondutor a 212 K

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.

Controle preditivo robusto baseado em desigualdades matriciais lineares aplicado a um sistema de tanques acoplados

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

Técnicas inteligentes hídridas para o controle de sistemas não lineares

A neuro-fuzzy system consists of two or more control techniques in only one structure. The main characteristic of this structure is joining one or more good aspects from each technique to make a hybrid controller. This controller can be based in Fuzzy systems, artificial Neural Networks, Genetics Algorithms or rein forced learning techniques. Neuro-fuzzy systems have been shown as a promising technique in industrial applications. Two models of neuro-fuzzy systems were developed, an ANFIS model and a NEFCON model. Both models were applied to control a ball and beam system and they had their results and needed changes commented. Choose of inputs to controllers and the algorithms used to learning, among other information about the hybrid systems, were commented. The results show the changes in structure after learning and the conditions to use each one controller based on theirs characteristics

Separação cega de fontes lineares e não lineares usando algoritmo genético, redes neurais artificiais RBF e negentropia de Rényi como medida de independência

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

Estudo e implementação de um controlador preditivo generalizado bilinear compensado adaptativo

The present work presents the study and implementation of an adaptive bilinear compensated generalized predictive controller. This work uses conventional techniques of predictive control and includes techniques of adaptive control for better results. In order to solve control problems frequently found in the chemical industry, bilinear models are considered to represent the dynamics of the studied systems. Bilinear models are simpler than general nonlinear model, however it can to represent the intrinsic not-linearities of industrial processes. The linearization of the model, by the approach to time step quasilinear , is used to allow the application of the equations of the generalized predictive controller (GPC). Such linearization, however, generates an error of prediction, which is minimized through a compensation term. The term in study is implemented in an adaptive form, due to the nonlinear relationship between the input signal and the prediction error.Simulation results show the efficiency of adaptive predictive bilinear controller in comparison with the conventional.

Relações entre a produção de laranjeira 'Westin' e as precipitações em Botucatu, SP

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Algoritmos genéticos aplicados a um comitê de LS-SVM em problemas de classificação

The pattern classification is one of the machine learning subareas that has the most outstanding. Among the various approaches to solve pattern classification problems, the Support Vector Machines (SVM) receive great emphasis, due to its ease of use and good generalization performance. The Least Squares formulation of SVM (LS-SVM) finds the solution by solving a set of linear equations instead of quadratic programming implemented in SVM. The LS-SVMs provide some free parameters that have to be correctly chosen to achieve satisfactory results in a given task. Despite the LS-SVMs having high performance, lots of tools have been developed to improve them, mainly the development of new classifying methods and the employment of ensembles, in other words, a combination of several classifiers. In this work, our proposal is to use an ensemble and a Genetic Algorithm (GA), search algorithm based on the evolution of species, to enhance the LSSVM classification. In the construction of this ensemble, we use a random selection of attributes of the original problem, which it splits the original problem into smaller ones where each classifier will act. So, we apply a genetic algorithm to find effective values of the LS-SVM parameters and also to find a weight vector, measuring the importance of each machine in the final classification. Finally, the final classification is obtained by a linear combination of the decision values of the LS-SVMs with the weight vector. We used several classification problems, taken as benchmarks to evaluate the performance of the algorithm and compared the results with other classifiers

Crescimento aéreo e radicular de arroz de terras altas em função da adubação fosfatada e bioestimulante

The use of plant regulators that stimulate root growth can increase phosphorus uptake by upland rice. The objective of this study was to evaluate shoot and root growth of upland rice fertilized with different phosphorus doses with and without biostimulant. The experiment was carried out in greenhouse in the Faculdade de Ciencias Agronomicas-UNESP, in Botucatu-SP. The treatments consisted of six phosphorus doses applied in sowing (0, 12,5, 25, 50, 100 and 200 mg dm(-3)), with and without Stimulate (R) applied in the seeds (cv. Primavera). The plants were grown for 78 days and then cut at soil level to evaluate leaf area and leaves and collar dry matter. Root samples that were harvested on the same day had their root diameter and dry matter evaluated. The experimental design was the completely randomized, with three replications, arranged as a factorial 2x6. Variance analysis and regression were used to data evaluation. Linear and quadratic equations were adjusted at a probability level of 5%, using those with higher determination coefficient (R(2)). The increase on the phosphorus dose contributed to the lower matter production and leaf area of the plants when the biostimulant was applied. For shoot phosphorus accumulation and root evaluations, the same behavior was observed. It was concluded that the use of Stimulate (R) in seeds, for fitomass production or root system evaluation, was only efficient in low phosphorus doses.

Atividades estruturais de equações polinomiais numa abordagem histórica por meio de e-book

The present study investigates how the inter-relationship of the content of polynomial equations works with structured activities and with the history of mathematics through a sequence of activities presented in an e-book, so that the result of this research will proceed will result in a didactic and pedagogic proposal for the teaching of polynomial equations in a historical approach via the reported e-book. Therefore, we have considered in theoretical and methodological assumptions of the History of Mathematics, in structured activities and new technologies with an emphasis on e-book tool. We used as a methodological approach the qualitative research, as our research object adjusts to the objectives of this research mode. As methodological instruments, we used the e-book as a synthesis tool of the sequence of activities to be evaluated, while the questionnaires, semi-structured interviews and participant observation were designed to register and analyze the evaluation made by the research, participants in the structured activities. The processing and analysis of data collected though the questionnaires were organized, classified and quantified in summary tables to facilitate visualization, interpretation, understanding, and analysis of these data. As for participant observation was used to contribute to the qualitative analysis of the quantified data. The interviews were synthetically transcribed and qualitatively analyzed. The analysis ratified our research objectives and contributed to improve, approve and indicate the use of e-book for the teaching of polynomial equations. Thus, we consider that this educational product will bring significant contributions to the teaching of mathematical content, in Basic Education

Extração automatica de segmentos lineares de rodovias em imagens de resoluções variadas

In this paper a methodology for automatic extraction of road segments from images with different resolutions (low, middle and high resolution) is presented. It is based on a generalized concept of lines in digital images, by which lines can be described by the centerlines of two parallel edges. In the specific case of low resolution images, where roads are manifested as entities of 1 or 2 pixels wide, the proposed methodology combines an automatic image enhancement operation with the following strategies: automatic selection of the hysteresis thresholds and the Gaussian scale factor; line length thresholding; and polygonization. In medium and high resolution images roads manifest as narrow and elongated ribbons and, consequently, the extraction goal becomes the road centerlines. In this case, it is not necessary to apply the previous enhancement step used to enhance roads in low resolution images. The results obtained in the experimental evaluation satisfied all criteria established for the efficient extraction of road segments from different resolution images, providing satisfactory results in a completely automatic way.

Desempenho de diferentes equações antropométricas na predição de gordura corporal excessiva em crianças e adolescentes

OBJETIVO: O objetivo do presente estudo foi analisar a eficiência de diferentes equações antropométricas para a identificação de excesso de gordura corporal entre crianças e adolescentes. MÉTODOS: A amostra foi composta por 1.498 indivíduos (678 meninos e 820 meninas), com idade entre 7 e 17 anos (M=13,7, DP=2,0), da cidade de Presidente Prudente (SP). A massa corporal e a estatura foram mensuradas para o cálculo do Índice de Massa Corporal. Também foi realizada a mensuração da circunferência de cintura e das dobras cutâneas subescapular, tricipital, abdominal e da panturrilha. O percentual de gordura corporal foi calculado por meio de quatro equações: Slaughter et al., Slaughter II et al., Dezenberg et al., e Deurenberg et al.. Para indicar a eficiência das diferentes equações antropométricas na indicação da obesidade, foi utilizada a análise da curva Receiver Operating Characteristic Curve. RESULTADOS: No grupo masculino, foram observados valores de sensibilidade elevados (82,4% a 100,0%) e valores oscilando de baixo a alto, para a especificidade (20,9% a 94,9%). Para o sexo feminino, os valores de sensibilidade variaram entre moderado e alto (72,2% a 99,4%); e os de especificidade apresentaram, também, grande oscilação entre baixo e alto (21,6% a 98,2%). CONCLSÃO: A equação proposta por Deurenberg et al., apresentou o melhor desempenho no diagnóstico tanto da presença como da ausência de obesidade na amostra investigada.

Espectro das ondas de spin lineares e não-lineares em multicamadas magnéticas anisotrópicas

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Processos difusivos generalizados

We investigate several diffusion equations which extend the usual one by considering the presence of nonlinear terms or a memory effect on the diffusive term. We also considered a spatial time dependent diffusion coefficient. For these equations we have obtained a new classes of solutions and studied the connection of them with the anomalous diffusion process. We start by considering a nonlinear diffusion equation with a spatial time dependent diffusion coefficient. The solutions obtained for this case generalize the usual one and can be expressed in terms of the q-exponential and q-logarithm functions present in the generalized thermostatistics context (Tsallis formalism). After, a nonlinear external force is considered. For this case the solutions can be also expressed in terms of the q-exponential and q-logarithm functions. However, by a suitable choice of the nonlinear external force, we may have an exponential behavior, suggesting a connection with standard thermostatistics. This fact reveals that these solutions may present an anomalous relaxation process and then, reach an equilibrium state of the kind Boltzmann- Gibbs. Next, we investigate a nonmarkovian linear diffusion equation that presents a kernel leading to the anomalous diffusive process. Particularly, our first choice leads to both a the usual behavior and anomalous behavior obtained through a fractionalderivative equation. The results obtained, within this context, correspond to a change in the waiting-time distribution for jumps in the formalism of random walks. These modifications had direct influence in the solutions, that turned out to be expressed in terms of the Mittag-Leffler or H of Fox functions. In this way, the second moment associated to these distributions led to an anomalous spread of the distribution, in contrast to the usual situation where one finds a linear increase with time