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

Efeito Peltier em estruturas semicondutoras quasiperiódicas

There is nowadays a growing demand for located cooling and stabilization in optical and electronic devices, haul of portable systems of cooling that they allow a larger independence in several activities. The modules of thermoelectrical cooling are bombs of heat that use efect Peltier, that consists of the production of a temperature gradient when an electric current is applied to a thermoelectrical pair formed by two diferent drivers. That efect is part of a class of thermoelectrical efcts that it is typical of junctions among electric drivers. The modules are manufactured with semiconductors. The used is the bismuth telluride Bi2Te3, arranged in a periodic sequence. In this sense the idea appeared of doing an analysis of a system that obeys the sequence of Fibonacci. The sequence of Fibonacci has connections with the golden proportion, could be found in the reproductive study of the bees, in the behavior of the light and of the atoms, as well as in the growth of plants and in the study of galaxies, among many other applications. An apparatus unidimensional was set up with the objective of investigating the thermal behavior of a module that obeys it a rule of growth of the type Fibonacci. The results demonstrate that the modules that possess periodic arrangement are more eficient

Sistema de agentes poligínicos para esteganálise de imagens digitais

In this work, we propose a multi agent system for digital image steganalysis, based on the poliginic bees model. Such approach aims to solve the problem of automatic steganalysis for digital media, with a case study on digital images. The system architecture was designed not only to detect if a file is suspicious of covering a hidden message, as well to extract the hidden message or information regarding it. Several experiments were performed whose results confirm a substantial enhancement (from 67% to 82% success rate) by using the multi-agent approach, fact not observed in traditional systems. An ongoing application using the technique is the detection of anomalies in digital data produced by sensors that capture brain emissions in little animals. The detection of such anomalies can be used to prove theories and evidences of imagery completion during sleep provided by the brain in visual cortex areas