Classificação de imagens de ambientes coralinos: uma abordagem empregando uma combinação de classificadores e máquina de vetor de suporte

The use of the maps obtained from remote sensing orbital images submitted to digital processing became fundamental to optimize conservation and monitoring actions of the coral reefs. However, the accuracy reached in the mapping of submerged areas is limited by variation of the water column that degrades the signal received by the orbital sensor and introduces errors in the final result of the classification. The limited capacity of the traditional methods based on conventional statistical techniques to solve the problems related to the inter-classes took the search of alternative strategies in the area of the Computational Intelligence. In this work an ensemble classifiers was built based on the combination of Support Vector Machines and Minimum Distance Classifier with the objective of classifying remotely sensed images of coral reefs ecosystem. The system is composed by three stages, through which the progressive refinement of the classification process happens. The patterns that received an ambiguous classification in a certain stage of the process were revalued in the subsequent stage. The prediction non ambiguous for all the data happened through the reduction or elimination of the false positive. The images were classified into five bottom-types: deep water; under-water corals; inter-tidal corals; algal and sandy bottom. The highest overall accuracy (89%) was obtained from SVM with polynomial kernel. The accuracy of the classified image was compared through the use of error matrix to the results obtained by the application of other classification methods based on a single classifier (neural network and the k-means algorithm). In the final, the comparison of results achieved demonstrated the potential of the ensemble classifiers as a tool of classification of images from submerged areas subject to the noise caused by atmospheric effects and the water column

Análise e desenvolvimento de controladores preditivos multivariáveis baseados em multi-modelos bilineares

This work addresses issues related to analysis and development of multivariable predictive controllers based on bilinear multi-models. Linear Generalized Predictive Control (GPC) monovariable and multivariable is shown, and highlighted its properties, key features and applications in industry. Bilinear GPC, the basis for the development of this thesis, is presented by the time-step quasilinearization approach. Some results are presented using this controller in order to show its best performance when compared to linear GPC, since the bilinear models represent better the dynamics of certain processes. Time-step quasilinearization, due to the fact that it is an approximation, causes a prediction error, which limits the performance of this controller when prediction horizon increases. Due to its prediction error, Bilinear GPC with iterative compensation is shown in order to minimize this error, seeking a better performance than the classic Bilinear GPC. Results of iterative compensation algorithm are shown. The use of multi-model is discussed in this thesis, in order to correct the deficiency of controllers based on single model, when they are applied in cases with large operation ranges. Methods of measuring the distance between models, also called metrics, are the main contribution of this thesis. Several application results in simulated distillation columns, which are close enough to actual behaviour of them, are made, and the results have shown satisfactory

Sistema inteligente para diagnóstico de patologias na laringe utilizando máquinas de vetor de suporte

The human voice is an important communication tool and any disorder of the voice can have profound implications for social and professional life of an individual. Techniques of digital signal processing have been used by acoustic analysis of vocal disorders caused by pathologies in the larynx, due to its simplicity and noninvasive nature. This work deals with the acoustic analysis of voice signals affected by pathologies in the larynx, specifically, edema, and nodules on the vocal folds. The purpose of this work is to develop a classification system of voices to help pre-diagnosis of pathologies in the larynx, as well as monitoring pharmacological treatments and after surgery. Linear Prediction Coefficients (LPC), Mel Frequency cepstral coefficients (MFCC) and the coefficients obtained through the Wavelet Packet Transform (WPT) are applied to extract relevant characteristics of the voice signal. For the classification task is used the Support Vector Machine (SVM), which aims to build optimal hyperplanes that maximize the margin of separation between the classes involved. The hyperplane generated is determined by the support vectors, which are subsets of points in these classes. According to the database used in this work, the results showed a good performance, with a hit rate of 98.46% for classification of normal and pathological voices in general, and 98.75% in the classification of diseases together: edema and nodules

Modelo para determinar as exigências de proteína para poedeiras

O objetivo do trabalho foi elaborar um modelo para estimar as exigências de proteína bruta (PB) para poedeiras leves, usando o método fatorial. Para determinar as exigências de proteína bruta (PB) para manutenção foi utilizada a técnica do balanço de nitrogênio. A exigência de proteína bruta para o ganho de peso foi determinada em função do conteúdo de nitrogênio na carcaça e a eficiência de utilização do nitrogênio da dieta. A exigência de PB, para produção de ovos, foi determinada considerando o teor de PB determinado nos ovos e a eficiência de deposição do nitrogênio no ovo. A partir dos valores das exigências para manutenção, para o ganho e produção foi elaborada uma equação para predizer as exigências diárias de PB (g/ ave/ dia) para poedeiras: PB = 1,94. P0,75 + 0,48.G + 0,301.O, em que P = peso corporal (kg), G = ganho de peso diário (g/dia) e O = massa de ovos produzida (g/ave/dia).

Exigências de minerais para cabras durante a gestação: Na, K, Mg, S, Fe e Zn

O trabalho foi realizado com o objetivo de estimar a retenção e a exigência líquida dos minerais Na, K, Mg, S, Fe e Zn durante a gestação de cabras com um ou dois fetos. A estimativa de retenção foi baseada na diferença entre o total de cada mineral depositado no feto, útero, membranas, fluídos fetais e glândula mamária dos animais nas diferentes etapas da gestação e o total de cada mineral armazenado nas cabras vazias, utilizando-se o modelo de predição ln=A+Bx+Cx2, em que x=tempo de gestação. Os conteúdos de Na, K, Mg, S, Fe e Zn, durante as gestações de um e dois fetos foram de: 13,2 e 21,4 mg; 13,3 e 21,3 g; 2,1 e 3,7 mg; 5,5 e 9,3 mg; 575,5 e 981,0 mg; 112,6 e 164,7 mg nas gestações, resultando em exigências líquidas diárias de 0,13 e 0,11 g; 0,21 e 0,31 g; 0,06 e 0,11g; 0,17 e 0,21 g; 22,94 e 40,51 mg; 2,63 e 2,78 mg, respectivamente.

Estimação de parâmetros genéticos em caprinos leiteiros por meio de análise de regressão aleatória utilizando-se a Amostragem de Gibbs

Modelos de regressão aleatória foram utilizados neste estudo para estimar parâmetros genéticos da produção de leite no dia do controle (PLDC) em caprinos leiteiros da raça Alpina, por meio da metodologia Bayesiana. As estimativas geradas foram comparadas às obtidas com análise de regressão aleatória, utilizando-se o REML. As herdabilidades encontradas pela análise Bayesiana variaram de 0,18 a 0,37, enquanto, pelo REML, variaram de 0,09 a 0,32. As correlações genéticas entre dias de controle próximos se aproximaram da unidade, decrescendo gradualmente conforme a distância entre os dias de controle aumentou. Os resultados obtidos indicam que: a estrutura de covariâncias da PLDC em caprinos ao longo da lactação pode ser modelada adequadamente por meio da regressão aleatória; a predição de ganhos genéticos e a seleção de animais geneticamente superiores é viável ao longo de toda a trajetória da lactação; os resultados gerados pelas análises de regressão aleatória utilizando-se a Amostragem de Gibbs e o REML foram semelhantes, embora as estimativas das variâncias genéticas e das herdabilidades tenham sido levemente superiores na análise Bayesiana, utilizando-se a Amostragem de Gibbs.

Avaliação econômica do uso da restrição alimentar qualitativa para suínos com elevado peso de abate

O objetivo neste trabalho foi avaliar economicamente o uso da restrição alimentar qualitativa para suínos machos castrados em terminação sobre o desempenho e as características de carcaça de 60 animais. Dez suínos foram abatidos no início da fase experimental (89,0 ± 4,2 kg) e os demais, alimentados com rações contendo cinco níveis de restrição nutricional qualitativa (0, 5, 10, 15 e 20%), obtidas pela inclusão de casca de arroz finamente moída, até o final do experimento (127,8 ± 2,9 kg). Foram calculados os custos com alimentação durante o período experimental (R$alimento) e estimados os valores de receita bruta de cada carcaça de animais abatidos aos 128 kg (RBsuíno128kg) ou no início do experimento (RBmédia_suíno89kg). A partir destes três dados, foi calculado o resultado líquido (RL) do uso das dietas experimentais (RL = RBsuíno128kg - RBmédia_suíno89kg - R$alimento). Também foram analisadas as variações mensais dos preços do milho, do farelo de soja e do suíno, sendo determinado o preço do milho como o fator de maior impacto sobre a lucratividade do uso da restrição qualitativa. A equação de predição da probabilidade de aumento linear do resultado líquido pelo uso da restrição qualitativa foi determinada em função dos diferentes preços do milho - PM (valor de P RL = 0,392 - 0,625PM, R² = 0,73). Efeito significativo foi observado para preços do milho de cerca de quatro vezes ou mais acima do custo da casca de arroz. Assim, conclui-se que a viabilidade do uso da restrição qualitativa, até o nível de 20%, depende do cenário econômico, mas sobretudo do preço do milho, o principal ingrediente substituído nas rações ao empregar-se a restrição qualitativa, e de sua relação com o custo do resíduo utilizado para diluição energética.

Genetic and environmental effects on sexual precocity traits in Nellore cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Avaliação da Farinha de Carne e Ossos na Alimentação de Frangos de Corte

Um mil quatrocentos e quarenta pintos de um dia, machos, foram utilizados com o objetivo de avaliar a utilização da farinha de carne e ossos (FCO) sobre o desempenho e rendimento de carcaça de frangos de corte. Foi utilizado o delineamento inteiramente ao acaso em esquema fatorial 2 x 2 x 2, com os fatores: níveis de inclusão da FCO (3 e 6%), tipos de FCO (37,51 e 41,58% de proteína bruta), valores de energia metabolizável da FCO conforme equações de predição sugerida pelo NRC (1994) ou tabela de Rostagno et al. (1994), mais um tratamento controle sem a inclusão de FCO, com quatro repetições de 40 aves cada. O consumo de ração e ganho de peso (GP) foram influenciados pela inclusão de FCO, sendo verificado maior GP quando a FCO não foi utilizada. As demais características de desempenho não foram afetadas pelos fatores estudados. A gordura abdominal foi reduzida quando a FCO não foi utilizada. Concluiu-se que dietas de frangos de corte contendo até 6% de FCO proporcionam pior desempenho quando comparadas com aquelas a base de milho e farelo de soja.

Desenvolvimento e avaliação de controladores preditivos baseados em modelos biliares

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Predicao de campo em comunicacao sem fio

Even living in the XXI century are still some difficulties in access to broadband Internet in several Brazilian cities, due to the purchasing power of people and lack of government investment. But even with these difficulties, we seek to encourage the use of wireless technology, which is based on the IEEE 802.11b protocol - also known as Wi-Fi (Wireless Fidelity) Wireless Fidelity Communications, having wide range of commercial applications in the world market, nationally and internationally. In Brazil, this technology is in full operation in major cities and has proved attractive in relation to the access point to multipoint and point-to-point. This paper is a comparative analysis of prediction field, using models based on the prediction of propagation loss. To validate the techniques used here, the Okumura-Hata models, modified Okumura-Hata, Walfisch-Ikegami model, were applied to a wireless computer network, located in the neighborhood of Cajupiranga in the city of Melbourn, in Rio Grande do Norte . They are used for networking wireless 802.11b, using the Mobile Radio to measure signal levels, beyond the heights of the antennas and distances from the transmitter. The performance data versus distance are added to the graphs generated and compared with results obtained through calculations of propagation models

Estudo e implementação de um controlador preditivo generalizado bilinear compensado adaptativo

The present work presents the study and implementation of an adaptive bilinear compensated generalized predictive controller. This work uses conventional techniques of predictive control and includes techniques of adaptive control for better results. In order to solve control problems frequently found in the chemical industry, bilinear models are considered to represent the dynamics of the studied systems. Bilinear models are simpler than general nonlinear model, however it can to represent the intrinsic not-linearities of industrial processes. The linearization of the model, by the approach to time step quasilinear , is used to allow the application of the equations of the generalized predictive controller (GPC). Such linearization, however, generates an error of prediction, which is minimized through a compensation term. The term in study is implemented in an adaptive form, due to the nonlinear relationship between the input signal and the prediction error.Simulation results show the efficiency of adaptive predictive bilinear controller in comparison with the conventional.

Controlador preditivo não linear aplicado ao controle de golfadas em processos de produção de petróleo

Slugging is a well-known slugging phenomenon in multiphase flow, which may cause problems such as vibration in pipeline and high liquid level in the separator. It can be classified according to the place of its occurrence. The most severe, known as slugging in the riser, occurs in the vertical pipe which feeds the platform. Also known as severe slugging, it is capable of causing severe pressure fluctuations in the flow of the process, excessive vibration, flooding in separator tanks, limited production, nonscheduled stop of production, among other negative aspects that motivated the production of this work . A feasible solution to deal with this problem would be to design an effective method for the removal or reduction of the system, a controller. According to the literature, a conventional PID controller did not produce good results due to the high degree of nonlinearity of the process, fueling the development of advanced control techniques. Among these, the model predictive controller (MPC), where the control action results from the solution of an optimization problem, it is robust, can incorporate physical and /or security constraints. The objective of this work is to apply a non-conventional non-linear model predictive control technique to severe slugging, where the amount of liquid mass in the riser is controlled by the production valve and, indirectly, the oscillation of flow and pressure is suppressed, while looking for environmental and economic benefits. The proposed strategy is based on the use of the model linear approximations and repeatedly solving of a quadratic optimization problem, providing solutions that improve at each iteration. In the event where the convergence of this algorithm is satisfied, the predicted values of the process variables are the same as to those obtained by the original nonlinear model, ensuring that the constraints are satisfied for them along the prediction horizon. A mathematical model recently published in the literature, capable of representing characteristics of severe slugging in a real oil well, is used both for simulation and for the project of the proposed controller, whose performance is compared to a linear MPC

Modelagem de Superfícies Seletivas de Freqüência e Antenas de Microfita utilizando Redes Neurais Artificiais

This work has as main objective the application of Artificial Neural Networks, ANN, in the resolution of problems of RF /microwaves devices, as for example the prediction of the frequency response of some structures in an interest region. Artificial Neural Networks, are presently a alternative to the current methods of analysis of microwaves structures. Therefore they are capable to learn, and the more important to generalize the acquired knowledge, from any type of available data, keeping the precision of the original technique and adding the low computational cost of the neural models. For this reason, artificial neural networks are being increasily used for modeling microwaves devices. Multilayer Perceptron and Radial Base Functions models are used in this work. The advantages/disadvantages of these models and the referring algorithms of training of each one are described. Microwave planar devices, as Frequency Selective Surfaces and microstrip antennas, are in evidence due the increasing necessities of filtering and separation of eletromagnetic waves and the miniaturization of RF devices. Therefore, it is of fundamental importance the study of the structural parameters of these devices in a fast and accurate way. The presented results, show to the capacities of the neural techniques for modeling both Frequency Selective Surfaces and antennas

Efeitos da radiação uv, temperatura e vapor aquecido nos compósitos poliméricos: monitoramento, instabilidade estrutural e fratura

The application of composite materials and in particular the fiber-reinforced plastics (FRP) has gradually conquered space from the so called conventional materials. However, challenges have arisen when their application occurs in equipment and mechanical structures which will be exposed to harsh environmental conditions, especially when there is the influence of environmental degradation due to temperature, UV radiation and moisture in the mechanical performance of these structures, causing irreversible structural damage such as loss of dimensional stability, interfacial degradation, loss of mass, loss of structural properties and changes in the damage mechanism. In this context, the objective of this thesis is the development of a process for monitoring and modeling structural degradation, and the study of the physical and mechanical properties in FRP when in the presence of adverse environmental conditions (ageing). The mechanism of ageing is characterized by controlled environmental conditions of heated steam and ultraviolet radiation. For the research, it was necessary to develop three polymer composites. The first was a lamina of polyester resin reinforced with a short glass-E fiber mat (representing the layer exposed to ageing), and the other two were laminates, both of seven layers of reinforcement, one being made up only of short fibers of glass-E, and the other a hybrid type reinforced with fibers of glass-E/ fibers of curaua. It should be noted that the two laminates have the lamina of short glass-E fibers as a layer of the ageing process incidence. The specimens were removed from the composites mentioned and submitted to environmental ageing accelerated by an ageing chamber. To study the monitoring and modeling of degradation, the ageing cycles to which the lamina was exposed were: alternating cycles of UV radiation and heated steam, a cycle only of UV radiation and a cycle only of heated steam, for a period defined by norm. The laminates have already undergone only the alternating cycle of UV and heated steam. At the end of the exposure period the specimens were subjected to a structural stability assessment by means of the developed measurement of thickness variation technique (MTVT) and the measurement of mass variation technique (MMVT). Then they were subjected to the mechanical tests of uniaxial tension for the lamina and all the laminates, besides the bending test on three points for the laminates. This study was followed by characterization of the fracture and the surface degradation. Finally, a model was developed for the composites called Ageing Zone Diagram (AZD) for monitoring and predicting the tensile strength after the ageing processes. From the results it was observed that the process of degradation occurs Abstract Raimundo Nonato Barbosa Felipe xiv differently for each composite studied, although all were affected in certain way and that the most aggressive ageing process was that of UV radiation, and that the hybrid laminated fibers of glass-E/curaua composite was most affected in its mechanical properties