Modelagem de Superfícies Seletivas de Freqüência e Antenas de Microfita utilizando Redes Neurais Artificiais

This work has as main objective the application of Artificial Neural Networks, ANN, in the resolution of problems of RF /microwaves devices, as for example the prediction of the frequency response of some structures in an interest region. Artificial Neural Networks, are presently a alternative to the current methods of analysis of microwaves structures. Therefore they are capable to learn, and the more important to generalize the acquired knowledge, from any type of available data, keeping the precision of the original technique and adding the low computational cost of the neural models. For this reason, artificial neural networks are being increasily used for modeling microwaves devices. Multilayer Perceptron and Radial Base Functions models are used in this work. The advantages/disadvantages of these models and the referring algorithms of training of each one are described. Microwave planar devices, as Frequency Selective Surfaces and microstrip antennas, are in evidence due the increasing necessities of filtering and separation of eletromagnetic waves and the miniaturization of RF devices. Therefore, it is of fundamental importance the study of the structural parameters of these devices in a fast and accurate way. The presented results, show to the capacities of the neural techniques for modeling both Frequency Selective Surfaces and antennas

Controle inteligente de sistemas eletroidráulicos utilizando redes neurais artificiais

This work describes the development of a nonlinear control strategy for an electro-hydraulic actuated system. The system to be controlled is represented by a third order ordinary differential equation subject to a dead-zone input. The control strategy is based on a nonlinear control scheme, combined with an artificial intelligence algorithm, namely, the method of feedback linearization and an artificial neural network. It is shown that, when such a hard nonlinearity and modeling inaccuracies are considered, the nonlinear technique alone is not enough to ensure a good performance of the controller. Therefore, a compensation strategy based on artificial neural networks, which have been notoriously used in systems that require the simulation of the process of human inference, is used. The multilayer perceptron network and the radial basis functions network as well are adopted and mathematically implemented within the control law. On this basis, the compensation ability considering both networks is compared. Furthermore, the application of new intelligent control strategies for nonlinear and uncertain mechanical systems are proposed, showing that the combination of a nonlinear control methodology and artificial neural networks improves the overall control system performance. Numerical results are presented to demonstrate the efficacy of the proposed control system

Desenvolvimento de perfis aerodinâmicos a partir de suas características utilizando redes neurais artificiais

One of the current major concerns in engineering is the development of aircrafts that have low power consumption and high performance. So, airfoils that have a high value of Lift Coefficient and a low value for the Drag Coefficient, generating a High-Efficiency airfoil are studied and designed. When the value of the Efficiency increases, the aircraft s fuel consumption decreases, thus improving its performance. Therefore, this work aims to develop a tool for designing of airfoils from desired characteristics, as Lift and Drag coefficients and the maximum Efficiency, using an algorithm based on an Artificial Neural Network (ANN). For this, it was initially collected an aerodynamic characteristics database, with a total of 300 airfoils, from the software XFoil. Then, through the software MATLAB, several network architectures were trained, between modular and hierarchical, using the Back-propagation algorithm and the Momentum rule. For data analysis, was used the technique of cross- validation, evaluating the network that has the lowest value of Root Mean Square (RMS). In this case, the best result was obtained for a hierarchical architecture with two modules and one layer of hidden neurons. The airfoils developed for that network, in the regions of lower RMS, were compared with the same airfoils imported into the software XFoil

Consumo e digestibilidade aparente de dietas com níveis crescentes do subproduto do caju em ovinos

The present study was conducted to evaluate the intake and digestibility of diets containing increasing levels of byproduct of cashew in sheep. The animals were distributed in a completely randomized design were evaluated in four levels (0%, 20%, 40%, 60%) by product of cashew with four replicates, making up 16 observations. The indicator used was the Purified Lignin and Enriched - LIPE ®. The scorer was orally administered directly into the mouth of the animals, in the form of capsules 250mg/animal/dia for a period of two days and five days of adaptation samples being the same supplied with the aid of a hose polyethylene and a device allowing the release of the capsule in the esophagus of sheep. With the estimate made by the indicator LIPE was observed a reduction for DM, OM, CP, NDF, EE, NFC and MM along the inclusion of byproduct of cashew. The results of nutrient digestibility were not satisfactory with the inclusion of byproduct of cashew, reducing linearly with the inclusion of the diets. The use of increasing levels of byproduct of cashew in the diets of sheep did not provide satisfactory results, it is not feasible to use the animals studied in this experiment

Estudo da estabilidade térmica de adoçantes naturais e artificiais

Sweeteners provide a pleasant sensation of sweetness that helps the sensory quality of the human diet, can be divided into natural sweeteners such as fructose, galactose, glucose, lactose and sucrose, and articial sweeteners such as aspartame, cyclamate and saccharin. This work aimed to study the thermal stability of natural and artificial sweeteners in atmospheres of nitrogen and syntetic air using thermogravimetry (TG), derivative thermogravimetry (DTG), Differential Thermal Analysis (DTA) and Differential Scanning Calorimetry (DSC). Among the natural sweeteners analyzed showed higher thermal stability for the lactose and sucrose, which showed initial decomposition temperatures near 220 ° C, taking advantage of the lactose has a higher melting point (213 ° C) compared to sucrose (191 ° C). The lower thermal stability was observed for fructose, it has the lowest melting point (122 °C) and the lower initial decomposition temperature (170 °C). Of the artificial sweeteners studied showed higher thermal stability for sodium saccharin, which had the highest melting point (364 ° C) as well as the largest initial decomposition temperature (466 ° C under nitrogen and 435 ° C in air). The lower thermal stability was observed for aspartame, which showed lower initial decomposition temperature (158 ° C under nitrogen and 170 ° C under air). For commercial sweeteners showed higher thermal stability for the sweeteners L and C, which showed initial temperature of thermal decomposition near 220 ° C and melting points near 215 ° C. The lower thermal stability was observed for the sweetener P, which showed initial decomposition temperature at 160 ° C and melting point of 130 °C. Sweeteners B, D, E, I, J, N and O had low thermal stability, with the initial temperature of decomposition starts near 160 °C, probably due to the presence of aspartame, even if they have as the main constituent of the lactose, wich is the most stable of natural sweeteners. According to the results we could also realize that all commercial sweeteners are in its composition by at least a natural sweeteners and are always found in large proportions, and lactose is the main constituent of 60% of the total recorded

Desenvolvimento de metodologia capaz de detectar e quantificar misturas de corantes em sucos artificiais em pó

Foi desenvolvido um método para detectar e quantificar misturas de corantes em sucos artificiais em pó fabricados no Brasil, de diferentes marcas e sabores. Foram estudados 6 corantes artificiais: amarelo tartrazina, amarelo crepúsculo, vermelho ponceau 4R, vermelho bordeaux S, vermelho 40 e azul brilhante presentes de forma unitária ou em misturas nos sucos com sabores laranja, tangerina, maracujá, abacaxi, limão e uva. A identificação dos corantes nas amostras foi feita através da comparação com os espectros dos padrões, utilizando-se a análise por infravermelho médio e pelos respectivos valores de absorção máxima nos comprimentos de onda relativos aos padrões e valores de referência na literatura. Também foram estudados os perfis de decomposição térmica por termogravimetria, termogravimetria derivada e calorimetria diferencial exploratória dos corantes e dos sucos em pó, sendo determinados os teores de umidade, de matéria orgânica e de cinzas. O teor de umidade encontrado não ultrapassou 4% para todas as amostras de suco analisadas. Com relação ao teor de matéria orgânica obteve-se para 57% dos sucos analisados um teor médio de 51,3% e para 43% das outras amostras obteve-se uma média de 67,2 %. Os resultados obtidos para o teor de cinzas indicaram que 29% das amostras apresentaram um teor de 26,7% para esse parâmetro enquanto 71% das amostras apresentaram um teor de cinzas de 46,4%. Os resultados obtidos por análise térmica mostraram-se adequados considerando-se que para obter os resultados pelo método tradicional há um investimento maior de tempo, de pessoal envolvido e de material, além da proteção ao meio ambiente. Para a análise por espectroscopia de absorção molecular foi proposta uma equação simplificada para a determinação de cada corante na mistura utilizando-se a lei de Beer. Para validação, empregou-se a espectroscopia de absorção molecular no visível, onde foi investigada a influência dos interferentes (TiO2 e açúcar) presentes nas amostras de sucos, os testes de fotodegradação e a avaliação do efeito do pH. Para quantificação tomou-se como referência 512 amostras sintéticas contendo um e dois corantes (1,5625 a 25,000 mg L-1) para obtenção das curvas analíticas que foram aplicadas à análise dos sucos em pó. Os resultados indicaram que o teor máximo do amarelo crepúsculo foi encontrado nos sucos com os sabores laranja, tangerina e manga que correspondeu a 25,6% da ingestão diária aceitável (para ser ultrapassada corresponderia a ingestão de 4 copos). O teor máximo encontrado para o amarelo tartrazina nos sucos foi para o sabor maracujá que correspondeu a 8,5% da ingestão diária aceitável, (para ser alcançado corresponderia a ingestão de 12 copos). O método proposto foi testado e validado com sucesso para amostras de sucos em pó sendo de simples execução e de rapidez na obtenção dos resultados

Sistema não-Intrusivo para Estimação da Direção do olhar utilizando redes neurais artificiais

The fundamental senses of the human body are: vision, hearing, touch, taste and smell. These senses are the functions that provide our relationship with the environment. The vision serves as a sensory receptor responsible for obtaining information from the outside world that will be sent to the brain. The gaze reflects its attention, intention and interest. Therefore, the estimation of gaze direction, using computer tools, provides a promising alternative to improve the capacity of human-computer interaction, mainly with respect to those people who suffer from motor deficiencies. Thus, the objective of this work is to present a non-intrusive system that basically uses a personal computer and a low cost webcam, combined with the use of digital image processing techniques, Wavelets transforms and pattern recognition, such as artificial neural network models, resulting in a complete system that performs since the image acquisition (including face detection and eye tracking) to the estimation of gaze direction. The obtained results show the feasibility of the proposed system, as well as several feature advantages.

Modelo comportamental do capacitor ferroelétrico como unidade básica de neurônios artificiais e sua implementação em FPGA

This work proposes the use of the behavioral model of the hysteresis loop of the ferroelectrics capacitor as a new alternative to the usually costly techniques in the computation of nonlinear functions in artificial neurons implemented on reconfigurable hardware platform, in this case, a FPGA device. Initially the proposal has been validated by the implementation of the boolean logic through the digital models of two artificial neurons: the Perceptron and a variation of the model Integrate and Fire Spiking Neuron, both using the model also digital of the hysteresis loop of the ferroelectric capacitor as it’s basic nonlinear unit for the calculations of the neurons outputs. Finally, it has been used the analog model of the ferroelectric capacitor with the goal of verifying it’s effectiveness and possibly the reduction of the number of necessary logic elements in the case of implementing the artificial neurons on integrated circuit. The implementations has been carried out by Simulink models and the synthesizing has been done through the DSP Builder software from Altera Corporation.

Avaliação das características de carcaça e perfil dos ácidos graxos em suínos na fase de terminação, alimentados com dietas contendo farelo de bagaço de caju

Provide healthier meat to consumers of pig farmers has required an adjustment of nutrition and feed management. Nutrition is a primary factor in defining the qualitative aspects of pork, because through it we can modify the fatty acid profile. The objective of this study was to analyze the effects of adding bran bagasse cashew (FBC) in diets for finishing pigs, on carcass traits and meat quality. 20 crossbred barrows with an average initial weight of 57.93 ± 3.67 kg / BW were used Diets were formulated based on corn and soybean meal containing vegetable oil, commercial core and different levels of inclusion of the bran bagasse cashew ( 0.0, 7.5 % , 15.0 % , 22.5 % and 30.0 % ) . The experimental design was a randomized block with 5 treatments and 4 replications. Quantitative, qualitative, fatty acid profile of the longissimus muscle and fat area parameters were evaluated. It was observed that with the inclusion of FBC, the parameters of carcass yield, backfat thickness, fat area had a negative linear effect relationship and meat / fat positive effect. Regarding the profile of fatty acids in fat area, the content of linoleic fatty acid level of 30 % of FBC was 18.2 % higher ( P < 0.05 ) at the level of 0.0 % and the arachidonic level of 22.5 % was higher than 33.3 % and 37.5 % at levels of 0.0 % and 15.0 % ( FBC ) respectively. It is concluded that finishing pigs may be food diets containing up to 30 % of FBC, improving the quality of housing for lower fat deposition and modification in the fatty acid profile.

Cálculo das incertezas climáticas sobre América do Sul utilizando modelos do CMIP5: aferição através das redes neurais artificiais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Evoluções nas modelagens de substratos artificiais (metamateriais) com práticas experimentais em antenas de microfita

Esse trabalho tem como objetivo apresentar configurações de substratos dielétricos inovadores projetados e fabricados a partir de estruturas metamateriais. Para isso, são avaliados diversos fatores que podem influenciar no seu desempenho. A princípio, foi feito um levantamento bibliográfico a respeito dos temas, que estão relacionados com as pesquisas sobre: materiais dielétricos, metamateriais e interferometria óptica. São estudados, pesquisados e desenvolvidos dois projetos experimentais propostos, que comprovam a eficiência de métodos, para se alcançar a permeabilidade magnética negativa na formação de metamateriais. O primeiro projeto é a produção de uma nova estrutura, com u anel ressoador triangular equilateral (Split Equilateral Triangle Resonator - SETR). O segundo projeto: aplica os princípios da interferometria óptica, especialmente, com o interferômetro de Fabry-Perot. Técnicas para obtenção dos dispositivos que complementam a placa metamaterial como substrato foram pesquisadas na literatura e exemplificadas principalmente por meio de simulações e medições. Foram feitas comparações, simulações e medições de estruturas convencionais e especiais. As experiências se concentram nas evoluções e modelagens de substratos metamateriais com aplicações em antenas de microfita. As melhorias de alguns parâmetros de desempenho de antenas também são relatadas. As simulações das antenas foram feitas nos programas computacionais comerciais. Os resultados medidos foram obtidos com um analisador vetorial de redes da Rhode and Schwarz modelo ZVB 14.

Evoluções nas modelagens de substratos artificiais (metamateriais) com práticas experimentais em antenas de microfita

Esse trabalho tem como objetivo apresentar configurações de substratos dielétricos inovadores projetados e fabricados a partir de estruturas metamateriais. Para isso, são avaliados diversos fatores que podem influenciar no seu desempenho. A princípio, foi feito um levantamento bibliográfico a respeito dos temas, que estão relacionados com as pesquisas sobre: materiais dielétricos, metamateriais e interferometria óptica. São estudados, pesquisados e desenvolvidos dois projetos experimentais propostos, que comprovam a eficiência de métodos, para se alcançar a permeabilidade magnética negativa na formação de metamateriais. O primeiro projeto é a produção de uma nova estrutura, com u anel ressoador triangular equilateral (Split Equilateral Triangle Resonator - SETR). O segundo projeto: aplica os princípios da interferometria óptica, especialmente, com o interferômetro de Fabry-Perot. Técnicas para obtenção dos dispositivos que complementam a placa metamaterial como substrato foram pesquisadas na literatura e exemplificadas principalmente por meio de simulações e medições. Foram feitas comparações, simulações e medições de estruturas convencionais e especiais. As experiências se concentram nas evoluções e modelagens de substratos metamateriais com aplicações em antenas de microfita. As melhorias de alguns parâmetros de desempenho de antenas também são relatadas. As simulações das antenas foram feitas nos programas computacionais comerciais. Os resultados medidos foram obtidos com um analisador vetorial de redes da Rhode and Schwarz modelo ZVB 14.

Implementação de uma matriz de neurônios dinamicamente reconfigurável para descrição de topologias de redes neurais artificiais multilayer perceptrons

The Artificial Neural Networks (ANN), which is one of the branches of Artificial Intelligence (AI), are being employed as a solution to many complex problems existing in several areas. To solve these problems, it is essential that its implementation is done in hardware. Among the strategies to be adopted and met during the design phase and implementation of RNAs in hardware, connections between neurons are the ones that need more attention. Recently, are RNAs implemented both in application specific integrated circuits's (Application Specific Integrated Circuits - ASIC) and in integrated circuits configured by the user, like the Field Programmable Gate Array (FPGA), which have the ability to be partially rewritten, at runtime, forming thus a system Partially Reconfigurable (SPR), the use of which provides several advantages, such as flexibility in implementation and cost reduction. It has been noted a considerable increase in the use of FPGAs for implementing ANNs. Given the above, it is proposed to implement an array of reconfigurable neurons for topologies Description of artificial neural network multilayer perceptrons (MLPs) in FPGA, in order to encourage feedback and reuse of neural processors (perceptrons) used in the same area of the circuit. It is further proposed, a communication network capable of performing the reuse of artificial neurons. The architecture of the proposed system will configure various topologies MLPs networks through partial reconfiguration of the FPGA. To allow this flexibility RNAs settings, a set of digital components (datapath), and a controller were developed to execute instructions that define each topology for MLP neural network.

Implementação de uma matriz de neurônios dinamicamente reconfigurável para descrição de topologias de redes neurais artificiais multilayer perceptrons

The Artificial Neural Networks (ANN), which is one of the branches of Artificial Intelligence (AI), are being employed as a solution to many complex problems existing in several areas. To solve these problems, it is essential that its implementation is done in hardware. Among the strategies to be adopted and met during the design phase and implementation of RNAs in hardware, connections between neurons are the ones that need more attention. Recently, are RNAs implemented both in application specific integrated circuits's (Application Specific Integrated Circuits - ASIC) and in integrated circuits configured by the user, like the Field Programmable Gate Array (FPGA), which have the ability to be partially rewritten, at runtime, forming thus a system Partially Reconfigurable (SPR), the use of which provides several advantages, such as flexibility in implementation and cost reduction. It has been noted a considerable increase in the use of FPGAs for implementing ANNs. Given the above, it is proposed to implement an array of reconfigurable neurons for topologies Description of artificial neural network multilayer perceptrons (MLPs) in FPGA, in order to encourage feedback and reuse of neural processors (perceptrons) used in the same area of the circuit. It is further proposed, a communication network capable of performing the reuse of artificial neurons. The architecture of the proposed system will configure various topologies MLPs networks through partial reconfiguration of the FPGA. To allow this flexibility RNAs settings, a set of digital components (datapath), and a controller were developed to execute instructions that define each topology for MLP neural network.

Previsão do índice bovespa por meio de redes neurais artificiais: uma análise comparada aos métodos tradicionais de séries de tempo

Forecast is the basis for making strategic, tactical and operational business decisions. In financial economics, several techniques have been used to predict the behavior of assets over the past decades.Thus, there are several methods to assist in the task of time series forecasting, however, conventional modeling techniques such as statistical models and those based on theoretical mathematical models have produced unsatisfactory predictions, increasing the number of studies in more advanced methods of prediction. Among these, the Artificial Neural Networks (ANN) are a relatively new and promising method for predicting business that shows a technique that has caused much interest in the financial environment and has been used successfully in a wide variety of financial modeling systems applications, in many cases proving its superiority over the statistical models ARIMA-GARCH. In this context, this study aimed to examine whether the ANNs are a more appropriate method for predicting the behavior of Indices in Capital Markets than the traditional methods of time series analysis. For this purpose we developed an quantitative study, from financial economic indices, and developed two models of RNA-type feedfoward supervised learning, whose structures consisted of 20 data in the input layer, 90 neurons in one hidden layer and one given as the output layer (Ibovespa). These models used backpropagation, an input activation function based on the tangent sigmoid and a linear output function. Since the aim of analyzing the adherence of the Method of Artificial Neural Networks to carry out predictions of the Ibovespa, we chose to perform this analysis by comparing results between this and Time Series Predictive Model GARCH, developing a GARCH model (1.1).Once applied both methods (ANN and GARCH) we conducted the results' analysis by comparing the results of the forecast with the historical data and by studying the forecast errors by the MSE, RMSE, MAE, Standard Deviation, the Theil's U and forecasting encompassing tests. It was found that the models developed by means of ANNs had lower MSE, RMSE and MAE than the GARCH (1,1) model and Theil U test indicated that the three models have smaller errors than those of a naïve forecast. Although the ANN based on returns have lower precision indicator values than those of ANN based on prices, the forecast encompassing test rejected the hypothesis that this model is better than that, indicating that the ANN models have a similar level of accuracy . It was concluded that for the data series studied the ANN models show a more appropriate Ibovespa forecasting than the traditional models of time series, represented by the GARCH model