Sistema inteligente para estimar a porosidade em sedimentos a partir da análise de sinais GPR

This Thesis presents the elaboration of a methodological propose for the development of an intelligent system, able to automatically achieve the effective porosity, in sedimentary layers, from a data bank built with information from the Ground Penetrating Radar GPR. The intelligent system was built to model the relation between the porosity (response variable) and the electromagnetic attribute from the GPR (explicative variables). Using it, the porosity was estimated using the artificial neural network (Multilayer Perceptron MLP) and the multiple linear regression. The data from the response variable and from the explicative variables were achieved in laboratory and in GPR surveys outlined in controlled sites, on site and in laboratory. The proposed intelligent system has the capacity of estimating the porosity from any available data bank, which has the same variables used in this Thesis. The architecture of the neural network used can be modified according to the existing necessity, adapting to the available data bank. The use of the multiple linear regression model allowed the identification and quantification of the influence (level of effect) from each explicative variable in the estimation of the porosity. The proposed methodology can revolutionize the use of the GPR, not only for the imaging of the sedimentary geometry and faces, but mainly for the automatically achievement of the porosity one of the most important parameters for the characterization of reservoir rocks (from petroleum or water)

Photosynthetic induction in Eucalyptus urograndis seedlings and cuttings measured by an open photoacoustic cell

Photosynthetic induction in leaves of four-month-old Eucalyptus urograndis seedlings and of cuttings obtained from adult trees that were previously dark-adapted was studied by the in vivo and in situ Open Photoacoustic Cell Technique, Results for the gas exchange component of the photoacoustic (PA) signal were interpreted considering that the gas uptake component would have a phase angle nearly opposite to that of the oxygen evolution component. By subtracting the thermal component from the total PA signal, we studied the competition between gas uptake and oxygen evolution during the photosynthetic induction. Seedlings presented a net oxygen evolution prior to cuttings, but cuttings reached a higher steady-state photosynthetic activity. The chlorophyll (Chl) a/b ratio and the Chl fluorescence induction characteristic F-v/F-m were significantly higher for cuttings, while there was no difference between samples in stomata density and leaf thickness. Thus the differences in PA signals of seedlings and cuttings are associated to differences between the photosystem 2 antenna systems of these samples.

Comparison of logistic and neural network models to fit to the egg production curve of White Leghorn hens

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Emprego de redes neurais artificiais supervisionadas e não supervisionadas no estudo de parâmetros reológicos de excipientes farmacêuticos sólidos

In this paper artificial neural network (ANN) based on supervised and unsupervised algorithms were investigated for use in the study of rheological parameters of solid pharmaceutical excipients, in order to develop computational tools for manufacturing solid dosage forms. Among four supervised neural networks investigated, the best learning performance was achieved by a feedfoward multilayer perceptron whose architectures was composed by eight neurons in the input layer, sixteen neurons in the hidden layer and one neuron in the output layer. Learning and predictive performance relative to repose angle was poor while to Carr index and Hausner ratio (CI and HR, respectively) showed very good fitting capacity and learning, therefore HR and CI were considered suitable descriptors for the next stage of development of supervised ANNs. Clustering capacity was evaluated for five unsupervised strategies. Network based on purely unsupervised competitive strategies, classic "Winner-Take-All", "Frequency-Sensitive Competitive Learning" and "Rival-Penalize Competitive Learning" (WTA, FSCL and RPCL, respectively) were able to perform clustering from database, however this classification was very poor, showing severe classification errors by grouping data with conflicting properties into the same cluster or even the same neuron. On the other hand it could not be established what was the criteria adopted by the neural network for those clustering. Self-Organizing Maps (SOM) and Neural Gas (NG) networks showed better clustering capacity. Both have recognized the two major groupings of data corresponding to lactose (LAC) and cellulose (CEL). However, SOM showed some errors in classify data from minority excipients, magnesium stearate (EMG) , talc (TLC) and attapulgite (ATP). NG network in turn performed a very consistent classification of data and solve the misclassification of SOM, being the most appropriate network for classifying data of the study. The use of NG network in pharmaceutical technology was still unpublished. NG therefore has great potential for use in the development of software for use in automated classification systems of pharmaceutical powders and as a new tool for mining and clustering data in drug development

Descrição das ninfas de Quesada gigas (Olivier) (Hemiptera: Cicadidae) associadas ao cafeeiro

Neste trabalho, as ninfas de Quesada gigas (Olivier) são descritas e ilustradas. Uma chave para o reconhecimento dos cinco ínstares ninfais é também apresentada. Foram analisados exemplares coletados em cafezais dos municípios de São Sebastião do Paraíso, Monte Santo de Minas e Patrimônio (Minas Gerais), Franca e Casa Branca (São Paulo). As amostras encontram-se preservadas em álcool a 80% e depositadas na Coleção Entomológica do Departamento de Fitossanidade da FCAV-UNESP, Câmpus de Jaboticabal. Os caracteres analisados foram: antenas, tecas alares, perna anterior, ápice da tíbia meso e metatorácicas e ápice abdominal do macho/fêmea. Foi adotada uma fórmula para indicar a configuração que é apresentada pelas estruturas presentes no fêmur anterior. Ninfas de Q. gigas de primeiro ínstar apresentam fórmula femoral 2-1-0, de segundo ínstar 2-1-3, de terceiro ínstar 2-1-5, de quarto ínstar 2-1-6 e as de quinto ínstar 2-2-8. O primeiro número refere-se à somatória dos dentes posteriores e dentes acessórios, o segundo ao número de dentes intermediários e o terceiro aos dentes do pente femoral. As estruturas apresentadas pelo fêmur protorácico constituem caracteres morfológicos adequados para a identificação dos ínstares ninfais de cigarras.

Desenvolvimento de substrato cerâmico BiNbO4 para antenas de microfita de sistemas de comunicações sem fio

The main purpose of this work was the development of ceramic dielectric substrates of bismuth niobate (BiNbO4) doped with vanadium pentoxide (V2O5), with high permittivity, used in the construction of microstrip patch antennas with applications in wireless communications systems. The high electrical permittivity of the ceramic substrate provided a reduction of the antenna dimensions. The numerical results obtained in the simulations and the measurements performed with the microstrip patch antennas showed good agreement. These antennas can be used in wireless communication systems in various frequency bands. Results were satisfactory for antennas operating at frequencies in the S band, in the range between 2.5 GHz and 3.0 GHz.

Desenvolvimento de antenas de microfita com Patch em anel utilizando materiais ferrimagnéticos e metamateriais

In general, the materials used as substrates in the project of microstrip antennas are: isotropic, anisotropic dielectrics and ferrimagnetic materials (magnetic anisotropy). The use of ferrimagnetic materials as substrates in microstrip patch antennas has been concentrated on the analysis of antennas with circular and rectangular patches. However, a new class of materials, called metamaterials, has been currently the focus of a great deal of interest. These materials exhibit bianisotropic characteristics, with permittivity and permeability tensors. The main objective of this work is to develop a theoretical and numerical analysis for the radiation characteristics of annular ring microstrip antennas, using ferrites and metamaterials as substrates. The full wave analysis is performed in the Hankel transform domain through the application of the Hertz vector potentials. Considering the definition of the Hertz potentials and imposing the boundary conditions, the dyadic Green s function components are obtained relating the surface current density components at the plane of the patch to the electric field tangential components. Then, Galerkin s method is used to obtain a system of matrix equations, whose solution gives the antenna resonant frequency. From this modeling, it is possible to obtain numerical results for the resonant frequency, radiation pattern, return loss, and antenna bandwidth as a function of the annular ring physical parameters, for different configurations and substrates. The theoretical analysis was developed for annular ring microstrip antennas on a double ferrimagnetic/isotropic dielectric substrate or metamaterial/isotropic dielectric substrate. Also, the analysis for annular ring microstrip antennas on a single ferrimagnetic or metamaterial layer and for suspended antennas can be performed as particular cases

Desenvolvimento de antenas de microfita e antenas DRA Broadband

The search for ever smaller device and without loss of performance has been increasingly investigated by researchers involving applied electromagnetics. Antennas using ceramics materials with a high dielectric constant, whether acting as a substract element of patch radiating or as the radiant element are in evidence in current research, that due to the numerous advantages offered, such as: low profile, ability to reduce the its dimensions when compared to other devices, high efficiency of ratiation, suitability the microwave range and/or millimeter wave, low temperature coefficient and low cost. The reason for this high efficiency is that the dielectric losses of ceramics are very low when compared to commercially materials sold used in printed circuit boards, such as fiberglass and phenolite. These characteristics make ceramic devices suitable for operation in the microwave band. Combining the design of patch antennas and/or dielectric resonator antenna (DRA) to certain materials and the method of synthesis of these powders in the manufacture of devices, it s possible choose a material with a dielectric constant appropriate for the design of an antenna with the desired size. The main aim of this work is the design of patch antennas and DRA antennas on synthesis of ceramic powders (synthesis by combustion and polymeric precursors - Pe- chini method) nanostructured with applications in the microwave band. The conventional method of mix oxides was also used to obtain nanometric powders for the preparation of tablets and dielectric resonators. The devices manufactured and studied on high dielectric constant materials make them good candidates to have their small size compared to other devices operating at the same frequency band. The structures analyzed are excited by three different techniques: i) microstrip line, ii) aperture coupling and iii) inductive coupling. The efficiency of these techniques have been investigated experimentally and compared with simulations by Ansoft HFSS, used in the accurate analysis of the electromagnetic behavior of antennas over the finite element method (FEM). In this thesis a literature study on the theory of microstrip antennas and DRA antenna is performed. The same study is performed about the materials and methods of synthesis of ceramic powders, which are used in the manufacture of tablets and dielectric cylinders that make up the devices investigated. The dielectric media which were used to support the analysis of the DRA and/or patch antennas are analyzed using accurate simulations using the finite difference time domain (FDTD) based on the relative electrical permittivity (er) and loss tangent of these means (tand). This work also presents a study on artificial neural networks, showing the network architecture used and their characteristics, as well as the training algorithms that were used in training and modeling some parameters associated with the devices investigated

Técnicas de inteligência artificial para a geração dinâmica de set points para uma coluna de destilação

Artificial Intelligence techniques are applied to improve performance of a simulated oil distillation system. The chosen system was a debutanizer column. At this process, the feed, which comes to the column, is segmented by heating. The lightest components become steams, by forming the LPG (Liquefied Petroleum Gas). The others components, C5+, continue liquid. In the composition of the LPG, ideally, we have only propane and butanes, but, in practice, there are contaminants, for example, pentanes. The objective of this work is to control pentane amount in LPG, by means of intelligent set points (SP s) determination for PID controllers that are present in original instrumentation (regulatory control) of the column. A fuzzy system will be responsible for adjusting the SP's, driven by the comparison between the molar fraction of the pentane present in the output of the plant (LPG) and the desired amount. However, the molar fraction of pentane is difficult to measure on-line, due to constraints such as: long intervals of measurement, high reliability and low cost. Therefore, an inference system was used, based on a multilayer neural network, to infer the pentane molar fraction through secondary variables of the column. Finally, the results shown that the proposed control system were able to control the value of pentane molar fraction under different operational situations

Análise dos Modos Ressonantes em Antenas de Microfita sobre Substratos Iso/Anisotrópicos por Técnicas da Ressonância Transversa

Neste trabalho, são utilizadas a Técnica da Ressonância Transversa (TRT) e a Técnica da Ressonância Transversa Modificada (MTRT), para a determinação das freqüências dos modos ressonantes de antenas de microfita com patch quadrado, retangular e circular e com substratos isotrópicos e anisotrópicos. Para isso, é proposto um modelo da cavidade equivalente, onde a antena tipo patch retangular é representada como sendo a superposição de duas linhas infinitas em microfita, uma de largura W, representando a dimensão que expressa a largura do patch, e a outra com largura L, representando a dimensão que expressa o comprimento do patch. A avaliação da eficiência e aplicabilidade dos métodos citados é realizada comparando-se com resultados experimentais e obtidos através de outras técnicas. Três situações serão verificadas: estruturas com substrato infinito, estrutura com substrato tipo pedestal e estruturas com substrato truncado além dos limites da fita metálica. Os resultados obtidos demonstram que as técnicas de análise de onda completa utilizadas neste trabalho, por um formalismo matemático mais rigoroso, são eficientes e precisas tanto na aplicação em estruturas com substrato isotrópico como nas que possuem substrato anisotrópico. Inicialmente são consideradas apenas as estruturas com substratos isotrópicos, com diferentes constantes dielétricas, e é avaliada a influência da largura do substrato sobre as freqüências dos modos ressonantes das antenas. Posteriormente, a análise do truncamento do dielétrico é realizada para estruturas com substrato anisotrópico. Em todos os casos, os resultados experimentais, obtidos a partir da construção de protótipos, são confrontados com os obtidos a partir de simulação, utilizando as técnicas TRT e MTRT. No final, as técnicas descritas são utilizadas para antenas tipo patch circular, sendo utilizada uma técnica de equivalência para transformar a antena circular em outra quadrada ou retangular equivalente, dependendo do modo que se queira encontrar. Os resultados obtidos são então analisados, observando-se uma boa concordância e indicando a viabilidade do método. Após isso, são apresentadas as conclusões e sugeridos alguns temas para a continuidade deste trabalho

Contribuições à análise de robustez de sistemas de controle usando redes neurais

This work develops a robustness analysis with respect to the modeling errors, being applied to the strategies of indirect control using Artificial Neural Networks - ANN s, belong to the multilayer feedforward perceptron class with on-line training based on gradient method (backpropagation). The presented schemes are called Indirect Hybrid Control and Indirect Neural Control. They are presented two Robustness Theorems, being one for each proposed indirect control scheme, which allow the computation of the maximum steady-state control error that will occur due to the modeling error what is caused by the neural identifier, either for the closed loop configuration having a conventional controller - Indirect Hybrid Control, or for the closed loop configuration having a neural controller - Indirect Neural Control. Considering that the robustness analysis is restrict only to the steady-state plant behavior, this work also includes a stability analysis transcription that is suitable for multilayer perceptron class of ANN s trained with backpropagation algorithm, to assure the convergence and stability of the used neural systems. By other side, the boundness of the initial transient behavior is assured by the assumption that the plant is BIBO (Bounded Input, Bounded Output) stable. The Robustness Theorems were tested on the proposed indirect control strategies, while applied to regulation control of simulated examples using nonlinear plants, and its results are presented

Detecção e isolamento de falhas em sistemas dinâmicos baseados em redes neurais

This master dissertation presents the development of a fault detection and isolation system based in neural network. The system is composed of two parts: an identification subsystem and a classification subsystem. Both of the subsystems use neural network techniques with multilayer perceptron training algorithm. Two approaches for identifica-tion stage were analyzed. The fault classifier uses only residue signals from the identification subsystem. To validate the proposal we have done simulation and real experiments in a level system with two water reservoirs. Several faults were generated above this plant and the proposed fault detection system presented very acceptable behavior. In the end of this work we highlight the main difficulties found in real tests that do not exist when it works only with simulation environments

Algoritmos inteligentes para auto-correção, auto-verificação e auto-validação de medidas em sensores

This work presents a set of intelligent algorithms with the purpose of correcting calibration errors in sensors and reducting the periodicity of their calibrations. Such algorithms were designed using Artificial Neural Networks due to its great capacity of learning, adaptation and function approximation. Two approaches willbe shown, the firstone uses Multilayer Perceptron Networks to approximate the many shapes of the calibration curve of a sensor which discalibrates in different time points. This approach requires the knowledge of the sensor s functioning time, but this information is not always available. To overcome this need, another approach using Recurrent Neural Networks was proposed. The Recurrent Neural Networks have a great capacity of learning the dynamics of a system to which it was trained, so they can learn the dynamics of a sensor s discalibration. Knowingthe sensor s functioning time or its discalibration dynamics, it is possible to determine how much a sensor is discalibrated and correct its measured value, providing then, a more exact measurement. The algorithms proposed in this work can be implemented in a Foundation Fieldbus industrial network environment, which has a good capacity of device programming through its function blocks, making it possible to have them applied to the measurement process

Dispositivos planares integrados utilizando método dinâmico com metamateriais e PBG

This work presents a theoretical, numerical and computation analysis of parameters of a rectangular microstrip antenna with metamaterial substrate, fin line as a coupler and also integrated devices like integrated filter antenna. It is applied theory to full-wave of Transverse Transmission Line - TTL method, to characterize the magnitude of the substrate and obtain the general equations of the electromagnetic fields. About the metamaterial, they are characterized by permittivity and permeability tensor, reaching to the general equations for the electromagnetic fields of the antenna. It is presented a study about main representation of PBG(Photonic Band Gap) material and its applied for a specific configuration. A few parameters are simulated some structures in order to reduce the physical dimensions and increase the bandwidth. The results are presented through graphs. The theoretical and computational analysis of this work have shown accurate and relatively concise. Conclusions are drawn and suggestions for future work

Análise e síntese de antenas e superfícies seletivas de frequência utilizando computação evolucionária e inteligência de enxames

The frequency selective surfaces, or FSS (Frequency Selective Surfaces), are structures consisting of periodic arrays of conductive elements, called patches, which are usually very thin and they are printed on dielectric layers, or by openings perforated on very thin metallic surfaces, for applications in bands of microwave and millimeter waves. These structures are often used in aircraft, missiles, satellites, radomes, antennae reflector, high gain antennas and microwave ovens, for example. The use of these structures has as main objective filter frequency bands that can be broadcast or rejection, depending on the specificity of the required application. In turn, the modern communication systems such as GSM (Global System for Mobile Communications), RFID (Radio Frequency Identification), Bluetooth, Wi-Fi and WiMAX, whose services are highly demanded by society, have required the development of antennas having, as its main features, and low cost profile, and reduced dimensions and weight. In this context, the microstrip antenna is presented as an excellent choice for communications systems today, because (in addition to meeting the requirements mentioned intrinsically) planar structures are easy to manufacture and integration with other components in microwave circuits. Consequently, the analysis and synthesis of these devices mainly, due to the high possibility of shapes, size and frequency of its elements has been carried out by full-wave models, such as the finite element method, the method of moments and finite difference time domain. However, these methods require an accurate despite great computational effort. In this context, computational intelligence (CI) has been used successfully in the design and optimization of microwave planar structures, as an auxiliary tool and very appropriate, given the complexity of the geometry of the antennas and the FSS considered. The computational intelligence is inspired by natural phenomena such as learning, perception and decision, using techniques such as artificial neural networks, fuzzy logic, fractal geometry and evolutionary computation. This work makes a study of application of computational intelligence using meta-heuristics such as genetic algorithms and swarm intelligence optimization of antennas and frequency selective surfaces. Genetic algorithms are computational search methods based on the theory of natural selection proposed by Darwin and genetics used to solve complex problems, eg, problems where the search space grows with the size of the problem. The particle swarm optimization characteristics including the use of intelligence collectively being applied to optimization problems in many areas of research. The main objective of this work is the use of computational intelligence, the analysis and synthesis of antennas and FSS. We considered the structures of a microstrip planar monopole, ring type, and a cross-dipole FSS. We developed algorithms and optimization results obtained for optimized geometries of antennas and FSS considered. To validate results were designed, constructed and measured several prototypes. The measured results showed excellent agreement with the simulated. Moreover, the results obtained in this study were compared to those simulated using a commercial software has been also observed an excellent agreement. Specifically, the efficiency of techniques used were CI evidenced by simulated and measured, aiming at optimizing the bandwidth of an antenna for wideband operation or UWB (Ultra Wideband), using a genetic algorithm and optimizing the bandwidth, by specifying the length of the air gap between two frequency selective surfaces, using an optimization algorithm particle swarm