Análise e otimização de superfícies seletivas de Frequência utilizando redes neurais artificiais e algoritmos de otimização natural

The bidimensional periodic structures called frequency selective surfaces have been well investigated because of their filtering properties. Similar to the filters that work at the traditional radiofrequency band, such structures can behave as band-stop or pass-band filters, depending on the elements of the array (patch or aperture, respectively) and can be used for a variety of applications, such as: radomes, dichroic reflectors, waveguide filters, artificial magnetic conductors, microwave absorbers etc. To provide high-performance filtering properties at microwave bands, electromagnetic engineers have investigated various types of periodic structures: reconfigurable frequency selective screens, multilayered selective filters, as well as periodic arrays printed on anisotropic dielectric substrates and composed by fractal elements. In general, there is no closed form solution directly from a given desired frequency response to a corresponding device; thus, the analysis of its scattering characteristics requires the application of rigorous full-wave techniques. Besides that, due to the computational complexity of using a full-wave simulator to evaluate the frequency selective surface scattering variables, many electromagnetic engineers still use trial-and-error process until to achieve a given design criterion. As this procedure is very laborious and human dependent, optimization techniques are required to design practical periodic structures with desired filter specifications. Some authors have been employed neural networks and natural optimization algorithms, such as the genetic algorithms and the particle swarm optimization for the frequency selective surface design and optimization. This work has as objective the accomplishment of a rigorous study about the electromagnetic behavior of the periodic structures, enabling the design of efficient devices applied to microwave band. For this, artificial neural networks are used together with natural optimization techniques, allowing the accurate and efficient investigation of various types of frequency selective surfaces, in a simple and fast manner, becoming a powerful tool for the design and optimization of such structures

Aplicações de Dispositivos de Microondas utilizando Substrato EBG/PBG para Comunicações Móveis

The modern society depends on an efficient communications system able to of transmitting and receiving information with a higher speed and reliability every time. The need for ever more efficient devices raises optimization techniques of microstrip devices, such as techniques to increase bandwidth: thicker substrates and substrate structures with EBG (Electromagnetic Band Gap) and PBG (Photonic Band Gap). This work has how aims the study of the application of PBG materials on substrates of planar structures in microstrip, more precisely in directional quadrature couplers and in rat-race and impedance of transformers. A study of the planar structures in microstrip and substrates EBG is presented. The PBG substrates can be used to optimize the radiation through the air, thus reducing the occurrence of surface waves and the resulting diffraction edge responsible for degradation of radiation pattern. Through specific programs in FORTRAN Power Station obtained the frequencies and couplings for each structure. Are used the program PACMO - Computer Aided Design in Microwave. Results are obtained of the frequency and coupling devices, ranging the frequency band used (cellular communication and Wimax systems) and the permittivity of the substrate, comparing the results of conventional material and PBG materials in the s and p polarizations.

Estudo das interações polifenol-proteína e das reações de escurecimento não-enzimático para o processamento de cajuína

The cashew, a fruit from Brazilian Northeast is used to produce juice due to its flavor and vitamin C richness. However, its acceptance is limited due to its astringency. Cajuína is a derivate product appreciated by its characteristic flavor, freshness and lack of astringency, due to tannin removal. Cajuína is a light yellow beverage made from clarified cashew juice and sterilized after bottling. It differs from the integral and concentrated juice by the clarification and thermal treatment steps. Many problems such as haze and excessive browning could appear if these steps are not controlled. The objective of this work was divided into two stages with the aim to supply process information in order to obtain a good quality product with uniform characteristics (sensory and nutritional). Polyphenol-protein interaction was studied at the clarification step, which is an empirical process, to provide values on the amount of clarifying solution (gelatin) that must be added to achieve a complete juice clarification. Clarification essays were performed with juice dilutions of 1:2 and 1:10 and the effect of metabissulfite and tannic acid addition was evaluated. It was not possible to establish a clarification point. Metabissulfite did not influenced the clarification process however tannic acid addition displaced the clarification point, showing the difficulty visual monitoring of the process. Thermal treatment of clarified juice was studied at 88, 100, 111 e 121 °C. To evaluate the non-enzymatic browning, vitamin C, 5-hidroximetilfurfural (5-HMF) and sugar variation were correlated with color parameters (reflectance spectra, color difference and CIELAB). Kinetic models were obtained for reflectance spectra, ascorbic acid and 5-HMF. It was observed that 5-HMF introduction followed a first order kinetic rate at the beginning of the thermal treatment and a zero order kinetic at later process stages. An inverse correlation was observed between absorbance at 420 nm and ascorbic acid degradation, which indicates that ascorbic acid might be the principal factor on cajuína non-enzymatic browning. Constant sugar concentration showed that this parameter did not contribute directly to the nonenzymatic browning. Optimization techniques showed showed that to obtain a high vitamin C and a low 5-HMF content, the process must be done at 120 ºC. With the water-bath thermal treatment, the 90 °C temperature promoted a lower ascorbic acid degradation at the expense of a higher 5-HMF level

Análise das medidas de boa e má diversidade na construção de comitês de classificadores através de metaheurísticas de otimização multiobjetivo

Committees of classifiers may be used to improve the accuracy of classification systems, in other words, different classifiers used to solve the same problem can be combined for creating a system of greater accuracy, called committees of classifiers. To that this to succeed is necessary that the classifiers make mistakes on different objects of the problem so that the errors of a classifier are ignored by the others correct classifiers when applying the method of combination of the committee. The characteristic of classifiers of err on different objects is called diversity. However, most measures of diversity could not describe this importance. Recently, were proposed two measures of the diversity (good and bad diversity) with the aim of helping to generate more accurate committees. This paper performs an experimental analysis of these measures applied directly on the building of the committees of classifiers. The method of construction adopted is modeled as a search problem by the set of characteristics of the databases of the problem and the best set of committee members in order to find the committee of classifiers to produce the most accurate classification. This problem is solved by metaheuristic optimization techniques, in their mono and multi-objective versions. Analyzes are performed to verify if use or add the measures of good diversity and bad diversity in the optimization objectives creates more accurate committees. Thus, the contribution of this study is to determine whether the measures of good diversity and bad diversity can be used in mono-objective and multi-objective optimization techniques as optimization objectives for building committees of classifiers more accurate than those built by the same process, but using only the accuracy classification as objective of optimization