Antenas de microfita com patch quase-fractal para aplicações em Redes WPAN/WLAN

The microstrip antennas are in constant evidence in current researches due to several advantages that it presents. Fractal geometry coupled with good performance and convenience of the planar structures are an excellent combination for design and analysis of structures with ever smaller features and multi-resonant and broadband. This geometry has been applied in such patch microstrip antennas to reduce its size and highlight its multi-band behavior. Compared with the conventional microstrip antennas, the quasifractal patch antennas have lower frequencies of resonance, enabling the manufacture of more compact antennas. The aim of this work is the design of quasi-fractal patch antennas through the use of Koch and Minkowski fractal curves applied to radiating and nonradiating antenna s edges of conventional rectangular patch fed by microstrip inset-fed line, initially designed for the frequency of 2.45 GHz. The inset-fed technique is investigated for the impedance matching of fractal antennas, which are fed through lines of microstrip. The efficiency of this technique is investigated experimentally and compared with simulations carried out by commercial software Ansoft Designer used for precise analysis of the electromagnetic behavior of antennas by the method of moments and the neural model proposed. In this dissertation a study of literature on theory of microstrip antennas is done, the same study is performed on the fractal geometry, giving more emphasis to its various forms, techniques for generation of fractals and its applicability. This work also presents a study on artificial neural networks, showing the types/architecture of networks used and their characteristics as well as the training algorithms that were used for their implementation. The equations of settings of the parameters for networks used in this study were derived from the gradient method. It will also be carried out research with emphasis on miniaturization of the proposed new structures, showing how an antenna designed with contours fractals is capable of a miniaturized antenna conventional rectangular patch. The study also consists of a modeling through artificial neural networks of the various parameters of the electromagnetic near-fractal antennas. The presented results demonstrate the excellent capacity of modeling techniques for neural microstrip antennas and all algorithms used in this work in achieving the proposed models were implemented in commercial software simulation of Matlab 7. In order to validate the results, several prototypes of antennas were built, measured on a vector network analyzer and simulated in software for comparison

Síntese de superfícies seletivas de frequência atráves de técnicas de computação natural

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Algoritmos genéticos e processamento paralelo aplicados à definição e treinamento de redes neurais perceptron de múltiplas camadas

ln this work, it was deveIoped a parallel cooperative genetic algorithm with different evolution behaviors to train and to define architectures for MuItiIayer Perceptron neural networks. MuItiIayer Perceptron neural networks are very powerful tools and had their use extended vastIy due to their abiIity of providing great resuIts to a broad range of appIications. The combination of genetic algorithms and parallel processing can be very powerful when applied to the Iearning process of the neural network, as well as to the definition of its architecture since this procedure can be very slow, usually requiring a lot of computational time. AIso, research work combining and appIying evolutionary computation into the design of neural networks is very useful since most of the Iearning algorithms deveIoped to train neural networks only adjust their synaptic weights, not considering the design of the networks architecture. Furthermore, the use of cooperation in the genetic algorithm allows the interaction of different populations, avoiding local minima and helping in the search of a promising solution, acceIerating the evolutionary process. Finally, individuaIs and evolution behavior can be exclusive on each copy of the genetic algorithm running in each task enhancing the diversity of populations

SAMVC sistema de autoria de museus virtuais colaborativos

The use of graphical objects three-dimensional (3D) multimedia applications is gaining more space in the media. Networks with high transmission rates, computers with large processing and graphics boost and popularize such three-dimensional applications. The areas of 3D applications ranging from military applications, entertainment applications geared up for education. Within the applications related to education, we highlight the applications that create virtual copies of cultural spaces such as museums. Through this copy, you can virtually visit a museum, see other users, communicate, exchange information on works, etc. Thereby allowing the visit museums physically distant remote users. A major problem of such virtual environments is its update. By dealing with various media (text, images, sounds, and 3D models), its subsequent handling and update on a virtual environment requires staff with specialized knowledge. Speaking of museums, they hardly have people on your team with this profile. Inside the GT-MV (Grupo de Trabalho de Museus Virtuais), funded by RNP (Rede Nacional de Ensino e Pesquisa) propose a portal for registration, amendment and seen collaborative virtual museums of Brazil. The update, be it related to work or physical space, a system with a national scale like this, would be impossible if done only by the project team. Within this scenario, we propose the modeling and implementation of a tool that allows editing of virtual spaces in an easy and intuitive as compared with available tools. Within the context of GT-MV, we apply the SAMVC (Sistema de Autoria de Museus Virtuais Colaborativos) to museums where curators build the museum from a 3D floor plan (2D). The system, from these twodimensional information, recreates the equivalent in three dimensions. With this, through little or no training, team members from each museum may be responsible for updating the system

Estudos de algumas ferramentas de coleta e visualização de dados e desempenho de aplicações paralelas no ambiente MPI

The last years have presented an increase in the acceptance and adoption of the parallel processing, as much for scientific computation of high performance as for applications of general intention. This acceptance has been favored mainly for the development of environments with massive parallel processing (MPP - Massively Parallel Processing) and of the distributed computation. A common point between distributed systems and MPPs architectures is the notion of message exchange, that allows the communication between processes. An environment of message exchange consists basically of a communication library that, acting as an extension of the programming languages that allow to the elaboration of applications parallel, such as C, C++ and Fortran. In the development of applications parallel, a basic aspect is on to the analysis of performance of the same ones. Several can be the metric ones used in this analysis: time of execution, efficiency in the use of the processing elements, scalability of the application with respect to the increase in the number of processors or to the increase of the instance of the treat problem. The establishment of models or mechanisms that allow this analysis can be a task sufficiently complicated considering parameters and involved degrees of freedom in the implementation of the parallel application. An joined alternative has been the use of collection tools and visualization of performance data, that allow the user to identify to points of strangulation and sources of inefficiency in an application. For an efficient visualization one becomes necessary to identify and to collect given relative to the execution of the application, stage this called instrumentation. In this work it is presented, initially, a study of the main techniques used in the collection of the performance data, and after that a detailed analysis of the main available tools is made that can be used in architectures parallel of the type to cluster Beowulf with Linux on X86 platform being used libraries of communication based in applications MPI - Message Passing Interface, such as LAM and MPICH. This analysis is validated on applications parallel bars that deal with the problems of the training of neural nets of the type perceptrons using retro-propagation. The gotten conclusions show to the potentiality and easinesses of the analyzed tools.

Sistema especialista para detecção de falhas em comandos elétricos

This work consists of the creation of a Specialist System which utilizes production rules to detect inadequacies in the command circuits of an operation system and commands of electric engines known as Direct Start. Jointly, three other modules are developed: one for the simulation of the commands diagram, one for the simulation of faults and another one for the correction of defects in the diagram, with the objective of making it possible to train the professionals aiming a better qualification for the operation and maintenance. The development is carried through in such a way that the structure of the task allows the extending of the system and a succeeding promotion of other bigger and more complex typical systems. The computational environment LabView is employed to enable the system

Análise de desempenho da rede neural artificial do tipo multilayer perceptron na era multicore

Artificial neural networks are usually applied to solve complex problems. In problems with more complexity, by increasing the number of layers and neurons, it is possible to achieve greater functional efficiency. Nevertheless, this leads to a greater computational effort. The response time is an important factor in the decision to use neural networks in some systems. Many argue that the computational cost is higher in the training period. However, this phase is held only once. Once the network trained, it is necessary to use the existing computational resources efficiently. In the multicore era, the problem boils down to efficient use of all available processing cores. However, it is necessary to consider the overhead of parallel computing. In this sense, this paper proposes a modular structure that proved to be more suitable for parallel implementations. It is proposed to parallelize the feedforward process of an RNA-type MLP, implemented with OpenMP on a shared memory computer architecture. The research consistes on testing and analizing execution times. Speedup, efficiency and parallel scalability are analyzed. In the proposed approach, by reducing the number of connections between remote neurons, the response time of the network decreases and, consequently, so does the total execution time. The time required for communication and synchronization is directly linked to the number of remote neurons in the network, and so it is necessary to investigate which one is the best distribution of remote connections

Contribuições a técnicas de agrupamento e visualização de dados multivariados utilizando mapas auto-organizáveis

Self-organizing maps (SOM) are artificial neural networks widely used in the data mining field, mainly because they constitute a dimensionality reduction technique given the fixed grid of neurons associated with the network. In order to properly the partition and visualize the SOM network, the various methods available in the literature must be applied in a post-processing stage, that consists of inferring, through its neurons, relevant characteristics of the data set. In general, such processing applied to the network neurons, instead of the entire database, reduces the computational costs due to vector quantization. This work proposes a post-processing of the SOM neurons in the input and output spaces, combining visualization techniques with algorithms based on gravitational forces and the search for the shortest path with the greatest reward. Such methods take into account the connection strength between neighbouring neurons and characteristics of pattern density and distances among neurons, both associated with the position that the neurons occupy in the data space after training the network. Thus, the goal consists of defining more clearly the arrangement of the clusters present in the data. Experiments were carried out so as to evaluate the proposed methods using various artificially generated data sets, as well as real world data sets. The results obtained were compared with those from a number of well-known methods existent in the literature

Previsão do módulo de elasticidade transversal de compósitos unidirecionais através de redes neurais mistas

The aim of this study is to create an artificial neural network (ANN) capable of modeling the transverse elasticity modulus (E2) of unidirectional composites. To that end, we used a dataset divided into two parts, one for training and the other for ANN testing. Three types of architectures from different networks were developed, one with only two inputs, one with three inputs and the third with mixed architecture combining an ANN with a model developed by Halpin-Tsai. After algorithm training, the results demonstrate that the use of ANNs is quite promising, given that when they were compared with those of the Halpín-Tsai mathematical model, higher correlation coefficient values and lower root mean square values were observed

Recuperação e purificação de quitosanases usando adsorção em leito expandido com streamline DEAE com modelagem e simulação usando redes neurais

Expanded Bed Adsorption (EBA) is an integrative process that combines concepts of chromatography and fluidization of solids. The many parameters involved and their synergistic effects complicate the optimization of the process. Fortunately, some mathematical tools have been developed in order to guide the investigation of the EBA system. In this work the application of experimental design, phenomenological modeling and artificial neural networks (ANN) in understanding chitosanases adsorption on ion exchange resin Streamline® DEAE have been investigated. The strain Paenibacillus ehimensis NRRL B-23118 was used for chitosanase production. EBA experiments were carried out using a column of 2.6 cm inner diameter with 30.0 cm in height that was coupled to a peristaltic pump. At the bottom of the column there was a distributor of glass beads having a height of 3.0 cm. Assays for residence time distribution (RTD) revelead a high degree of mixing, however, the Richardson-Zaki coefficients showed that the column was on the threshold of stability. Isotherm models fitted the adsorption equilibrium data in the presence of lyotropic salts. The results of experiment design indicated that the ionic strength and superficial velocity are important to the recovery and purity of chitosanases. The molecular mass of the two chitosanases were approximately 23 kDa and 52 kDa as estimated by SDS-PAGE. The phenomenological modeling was aimed to describe the operations in batch and column chromatography. The simulations were performed in Microsoft Visual Studio. The kinetic rate constant model set to kinetic curves efficiently under conditions of initial enzyme activity 0.232, 0.142 e 0.079 UA/mL. The simulated breakthrough curves showed some differences with experimental data, especially regarding the slope. Sensitivity tests of the model on the surface velocity, axial dispersion and initial concentration showed agreement with the literature. The neural network was constructed in MATLAB and Neural Network Toolbox. The cross-validation was used to improve the ability of generalization. The parameters of ANN were improved to obtain the settings 6-6 (enzyme activity) and 9-6 (total protein), as well as tansig transfer function and Levenberg-Marquardt training algorithm. The neural Carlos Eduardo de Araújo Padilha dezembro/2013 9 networks simulations, including all the steps of cycle, showed good agreement with experimental data, with a correlation coefficient of approximately 0.974. The effects of input variables on profiles of the stages of loading, washing and elution were consistent with the literature

Conectores sequenciadores e e aí em contos e narrativas de experiência pessoal escritos por alunos de ensino fundamental: uma abordagem sociofuncionalista

In this dissertation, based on two theoretical frameworks, American functionalism and variationist sociolinguistics, I take as subject the sequence connectors E and AÍ, which has the grammatical function of indicating retroactive-propeller sequenciation of information. I analyze the variable use of these connectors in texts written by students from two public schools in the city of Natal, RN, attending at the time of data collection (the year 2012), two distinct levels of basic education: the sixth and the ninth year. The students who contributed to this research wrote, as part of their activities in the classroom, texts of two narrative genres: narrative of personal experience (non-fictional) and short story (fictional). In addition, these students and their Portuguese teachers answered a test of linguistic attitude in which they gave their opinions regarding the appropriateness of the use of connectors E and AÍ in contexts of speech and writing marked by distinct degrees of formality. The results obtained by means of quantitative analysis showed different tendencies of linguistic, social and stylistic distribution of connectors E and AÍ in the narrative texts written by the students. I related these results to the action of two principles: the principle of persistence, linked to the process of change by grammaticalization, and the principle of stylistic markedness. Besides, I took into account the answers provided by students and teachers to the test of linguistic attitude for refine the interpretation of the results

Treinamento resistido reduz inflamação em músculo esquelético e melhora a sensibilidade à insulina periférica em ratos obesos induzidos por dieta hiperlipídica

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

Respostas lactacidêmicas de ratos ao treinamento intermitente de alta intensidade

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

Efeitos do esteróide anabólico nandrolona sobre o músculo sóleo de ratos submetidos a treinamento físico através de natação: estudo histológico, histoquímico e morfométrico

Este estudo teve por objetivo analisar as alterações histológicas, histoquímicas e morfométricas das fibras do músculo sóleo de ratos submetidos a um programa de natação, associado ou não à administração do esteróide anabólico decanoato de nandrolona. Foram utilizados 22 ratos Wistar machos, 12 dos quais receberam injeção intramuscular do esteróide (5mg/kg) e 10, óleo mineral (5mg/kg), duas vezes por semana. Os animais foram submetidos a 42 sessões de natação por nove semanas (de segunda a sexta-feira), com aumento progressivo de carga por meio do tempo de natação. Após o sacrifício, o músculo sóleo esquerdo foi retirado, imerso em n-hexana e acondicionado em nitrogênio líquido. Cortes do terço médio desse músculo foram feitos em micrótomo criostato (-20ºC) e corados pela técnica HE e pelo método histoquímico NADH-TR. Os animais submetidos a treinamento físico e a esteróide (TA) ou óleo mineral (TO) apresentaram fibras musculares com maior diâmetro, quando comparados com os animais-controle (NTA e NTO). Não houve diferença significativa entre as medidas das médias dos diâmetros das fibras dos grupos NTA e NTO e entre TA e TO. Nos grupos TA e NTA notou-se acentuado processo de fagocitose, arredondamento e hialinização das fibras musculares. Já nos grupos TA, TO e NTA observou-se perda da atividade enzimática oxidativa. Os resultados sugerem que a natação produz hipertrofia muscular de forma semelhante, tanto no grupo que recebeu esteróide como no que recebeu óleo mineral. No entanto, o grupo que recebeu esteróide apresentou sinais claros de maior degeneração muscular.

Comportamento da produção de espécies reativas de oxigênio em miocárdio de ratos submetidos a treinamento de baixa intensidade em diferentes temperaturas

INTRODUÇÃO: A prática de exercício físico proporciona aumento da produção de espécies reativas de oxigênio (ERO) resultantes do metabolismo aeróbio e, gera uma quantidade significativa de calor, em conseqüência da produção de energia, resultando em sobrecarga orgânica. A associação entre ERO e exercício, e entre exercício e variações da temperatura ambiente têm sido estudadas, contudo, há escassez de informações que considere a associação entre produção de radicais livres no miocárdio e atividade física em temperatura elevada. OBJETIVO: Comparar a produção de ERO em miocárdio de ratos submetidos ao treinamento de baixa intensidade em diferentes temperaturas. MÉTODOS: Foram utilizados 20 ratos Wistar, machos, jovens, peso (250 a 280g), divididos em quatro grupos: G1 (n = 5) expostos ao treinamento e calor (39º ± 1C); G2 (n = 5) expostos somente ao calor durante o mesmo período de G1, sem treinamento; G3 (n = 5) expostos ao treinamento em temperatura ambiente (22º ± 1C); G4 (n = 5) expostos à temperatura ambiente sem treinamento. O treinamento foi realizado em esteira rolante climatizada por cinco semanas, evoluindo 5 minutos a cada duas sessões finalizando em 60 minutos em baixa intensidade 8m/min. O ambiente foi controlado entre 39 ± 1ºC e 22 ± 1ºC e entre 40 e 60 % de umidade relativa. A lipoperoxidação foi avaliada por Quimiluminescência (QL). A análise dos dados foi realizada a partir do teste Two Way ANOVA para análise da QL e t de student para a Capacidade Antioxidante Total (TRAP). RESULTADOS: A análise da QL revelou uma curva de emissão de luz significantemente mais baixa para o grupo exposto ao exercício em normotermia comparado aos sedentários mantidos no calor. A análise da TRAP mostrou diminuição em todos os grupos experimentais em relação ao G4. CONCLUSÃO: Concluiu-se que houve níveis menores de produção de ERO nos grupos submetidos somente ao calor ou somente ao exercício.