Otimização de superfícies seletivas de frequência com elementos pré-fractais utilizando rede neural MLP e algoritmos de busca populacional

This thesis describes design methodologies for frequency selective surfaces (FSSs) composed of periodic arrays of pre-fractals metallic patches on single-layer dielectrics (FR4, RT/duroid). Shapes presented by Sierpinski island and T fractal geometries are exploited to the simple design of efficient band-stop spatial filters with applications in the range of microwaves. Initial results are discussed in terms of the electromagnetic effect resulting from the variation of parameters such as, fractal iteration number (or fractal level), fractal iteration factor, and periodicity of FSS, depending on the used pre-fractal element (Sierpinski island or T fractal). The transmission properties of these proposed periodic arrays are investigated through simulations performed by Ansoft DesignerTM and Ansoft HFSSTM commercial softwares that run full-wave methods. To validate the employed methodology, FSS prototypes are selected for fabrication and measurement. The obtained results point to interesting features for FSS spatial filters: compactness, with high values of frequency compression factor; as well as stable frequency responses at oblique incidence of plane waves. This thesis also approaches, as it main focus, the application of an alternative electromagnetic (EM) optimization technique for analysis and synthesis of FSSs with fractal motifs. In application examples of this technique, Vicsek and Sierpinski pre-fractal elements are used in the optimal design of FSS structures. Based on computational intelligence tools, the proposed technique overcomes the high computational cost associated to the full-wave parametric analyzes. To this end, fast and accurate multilayer perceptron (MLP) neural network models are developed using different parameters as design input variables. These neural network models aim to calculate the cost function in the iterations of population-based search algorithms. Continuous genetic algorithm (GA), particle swarm optimization (PSO), and bees algorithm (BA) are used for FSSs optimization with specific resonant frequency and bandwidth. The performance of these algorithms is compared in terms of computational cost and numerical convergence. Consistent results can be verified by the excellent agreement obtained between simulations and measurements related to FSS prototypes built with a given fractal iteration

Compressão auto-adaptativa de imagens coloridas

Image compress consists in represent by small amount of data, without loss a visual quality. Data compression is important when large images are used, for example satellite image. Full color digital images typically use 24 bits to specify the color of each pixel of the Images with 8 bits for each of the primary components, red, green and blue (RGB). Compress an image with three or more bands (multispectral) is fundamental to reduce the transmission time, process time and record time. Because many applications need images, that compression image data is important: medical image, satellite image, sensor etc. In this work a new compression color images method is proposed. This method is based in measure of information of each band. This technique is called by Self-Adaptive Compression (S.A.C.) and each band of image is compressed with a different threshold, for preserve information with better result. SAC do a large compression in large redundancy bands, that is, lower information and soft compression to bands with bigger amount of information. Two image transforms are used in this technique: Discrete Cosine Transform (DCT) and Principal Component Analysis (PCA). Primary step is convert data to new bands without relationship, with PCA. Later Apply DCT in each band. Data Loss is doing when a threshold discarding any coefficients. This threshold is calculated with two elements: PCA result and a parameter user. Parameters user define a compression tax. The system produce three different thresholds, one to each band of image, that is proportional of amount information. For image reconstruction is realized DCT and PCA inverse. SAC was compared with JPEG (Joint Photographic Experts Group) standard and YIQ compression and better results are obtain, in MSE (Mean Square Root). Tests shown that SAC has better quality in hard compressions. With two advantages: (a) like is adaptive is sensible to image type, that is, presents good results to divers images kinds (synthetic, landscapes, people etc., and, (b) it need only one parameters user, that is, just letter human intervention is required

Desenvolvimento de um compósito de espuma rígida de poliuretana de mamona e fibras de sisal para isolação térmica

The search for sustainable technologies that can contribute to reduce energy consumption is a great challenge in the field of insulation materials. In this context, composites manufactured from vegetal sources are an alternative technology. The principal objectives of this work are the development and characterization of a composite composed by the rigid polyurethane foam derived from castor oil (commercially available as RESPAN D40) and sisal fibers. The manufacture of the composite was done with expansion controlled inside a closed mold. The sisal fibers where used in the form of needlepunched nonwoven with a mean density of 1150 g/m2 and 1350 g/m2. The composite characterization was performed through the following tests: thermal conductivity, thermal behavior, thermo gravimetric analysis (TG/DTG), mechanical strength in compression and flexural, apparent density, water absorption in percentile, and the samples morphology was analyzed in a MEV. The density and humidity percentage of the sisal fiber were also determined. The thermal conductivity of the composites was higher than the pure polyurethane foam, the addition of nonwoven sisal fibers will become in a higher level of compact foam, reducing empty spaces (cells) of polyurethane, inducing an increase in k value. The apparent density of the composites was higher than pure polyurethane foam. In the results of water absorption tests, was seen a higher absorption percent of the composites, what is related to the presence of sisal fibers which are hygroscopic. From TG/DTG results, with the addition of sisal fibers reduced the strength to thermal degradation of the composites, a higher loss of mass was observed in the temperature band between 200 and 340 °C, related to urethane bonds decomposition and cellulose degradation and its derivatives. About mechanical behavior in compression and flexural, composites presented a better mechanical behavior than the rigid polyurethane foam. An increase in the amount of sisal fibers induces a higher rigidity of the composites. At the thermal behavior tests, the composites were more mechanically and thermally resistant than some materials commonly used for thermal insulation, they present the same or better results. The density of nonwoven sisal fiber had influence over the insulation grade; this means that, an increaser in sisal fiber density helped to retain the heat