Sobrevivência e tamanho populacional do Tiê-preto Tachyphonus Rufus (aves: thraupidae) em fragmento de restinga no extremo Norte da Mata Atlântica

For a long time, we believed in the pattern that tropical and south hemisphere species have high survival. Nowadays results began to contradict this pattern, indicating the need for further studies. Despite the advanced state of the study of bird population parameters, little is known about their variation throughout the year and the factors affecting them. Reproduction, for example, is one factor that may alter adult survival rates, because during this process the breeding pair allocates resources to maintain itself to maintain offspring, making itself more susceptible to diseases and predation. The aim of this study was to estimate survival and population size of a Central and South America passerine, Tachyphonus rufus (Boddaert, 1783), testing hypotheses about the factors that define these parameters. We performed data collection between Nov/2010 and ago/2012 in 12 ha plot, in a fragment of Atlantic Forest in northeastern Brazil. We used capture-mark-recapture methods to generate estimates using Closed Design Robust model in the program MARK. We generated Multi-state models to test some assumptions inherent to Closed Robust Design. The influence of co-variables (time, rain and reproductive cycle) and the effect of transient individuals were measured. Capture, recapture and apparent survival parameters were defined by reproductive cycle, while temporary dispersal was influence by rain. The estimates showed a higher apparent survival during the non-breeding period (92% ± 1%) than during breeding (40% ± 9%), revealing a cost of reproduction and suggesting a trade-off between surviving and reproducing. The low annual survival observed (34%) did not corroborate the pattern of high rates expected for a tropical bird. The largest population size was estimated to be 56 individuals in Nov/11, explained by high recruitment of juveniles, while the lowest observed in May/12: 10 individuals, probably as a result of massive influx of competitor species. Results from this study add to the growing literature on life history of Neotropical species. We encourage studies like this especially in Brazil, where there are few information, and suggest that covariates related to habitat quality and environmental changes should be tested, so that we can generate increasingly reliable models

Análise paramétrica da simulação composicional do processo de Drenagem Gravitacional Assistida por Gás (GAGD)

In Brazil and around the world, oil companies are looking for, and expected development of new technologies and processes that can increase the oil recovery factor in mature reservoirs, in a simple and inexpensive way. So, the latest research has developed a new process called Gas Assisted Gravity Drainage (GAGD) which was classified as a gas injection IOR. The process, which is undergoing pilot testing in the field, is being extensively studied through physical scale models and core-floods laboratory, due to high oil recoveries in relation to other gas injection IOR. This process consists of injecting gas at the top of a reservoir through horizontal or vertical injector wells and displacing the oil, taking advantage of natural gravity segregation of fluids, to a horizontal producer well placed at the bottom of the reservoir. To study this process it was modeled a homogeneous reservoir and a model of multi-component fluid with characteristics similar to light oil Brazilian fields through a compositional simulator, to optimize the operational parameters. The model of the process was simulated in GEM (CMG, 2009.10). The operational parameters studied were the gas injection rate, the type of gas injection, the location of the injector and production well. We also studied the presence of water drive in the process. The results showed that the maximum vertical spacing between the two wells, caused the maximum recovery of oil in GAGD. Also, it was found that the largest flow injection, it obtained the largest recovery factors. This parameter controls the speed of the front of the gas injected and determined if the gravitational force dominates or not the process in the recovery of oil. Natural gas had better performance than CO2 and that the presence of aquifer in the reservoir was less influential in the process. In economic analysis found that by injecting natural gas is obtained more economically beneficial than CO2

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

Aprendizado por Reforço com Valores deInfluência em Sistemas Multi-Agente

We propose a new paradigm for collective learning in multi-agent systems (MAS) as a solution to the problem in which several agents acting over the same environment must learn how to perform tasks, simultaneously, based on feedbacks given by each one of the other agents. We introduce the proposed paradigm in the form of a reinforcement learning algorithm, nominating it as reinforcement learning with influence values. While learning by rewards, each agent evaluates the relation between the current state and/or action executed at this state (actual believe) together with the reward obtained after all agents that are interacting perform their actions. The reward is a result of the interference of others. The agent considers the opinions of all its colleagues in order to attempt to change the values of its states and/or actions. The idea is that the system, as a whole, must reach an equilibrium, where all agents get satisfied with the obtained results. This means that the values of the state/actions pairs match the reward obtained by each agent. This dynamical way of setting the values for states and/or actions makes this new reinforcement learning paradigm the first to include, naturally, the fact that the presence of other agents in the environment turns it a dynamical model. As a direct result, we implicitly include the internal state, the actions and the rewards obtained by all the other agents in the internal state of each agent. This makes our proposal the first complete solution to the conceptual problem that rises when applying reinforcement learning in multi-agent systems, which is caused by the difference existent between the environment and agent models. With basis on the proposed model, we create the IVQ-learning algorithm that is exhaustive tested in repetitive games with two, three and four agents and in stochastic games that need cooperation and in games that need collaboration. This algorithm shows to be a good option for obtaining solutions that guarantee convergence to the Nash optimum equilibrium in cooperative problems. Experiments performed clear shows that the proposed paradigm is theoretical and experimentally superior to the traditional approaches. Yet, with the creation of this new paradigm the set of reinforcement learning applications in MAS grows up. That is, besides the possibility of applying the algorithm in traditional learning problems in MAS, as for example coordination of tasks in multi-robot systems, it is possible to apply reinforcement learning in problems that are essentially collaborative

Aplicação de sistemas multi-classificadores no diagnóstico de falhas em motores de indução trifásicos

Equipment maintenance is the major cost factor in industrial plants, it is very important the development of fault predict techniques. Three-phase induction motors are key electrical equipments used in industrial applications mainly because presents low cost and large robustness, however, it isn t protected from other fault types such as shorted winding and broken bars. Several acquisition ways, processing and signal analysis are applied to improve its diagnosis. More efficient techniques use current sensors and its signature analysis. In this dissertation, starting of these sensors, it is to make signal analysis through Park s vector that provides a good visualization capability. Faults data acquisition is an arduous task; in this way, it is developed a methodology for data base construction. Park s transformer is applied into stationary reference for machine modeling of the machine s differential equations solution. Faults detection needs a detailed analysis of variables and its influences that becomes the diagnosis more complex. The tasks of pattern recognition allow that systems are automatically generated, based in patterns and data concepts, in the majority cases undetectable for specialists, helping decision tasks. Classifiers algorithms with diverse learning paradigms: k-Neighborhood, Neural Networks, Decision Trees and Naïves Bayes are used to patterns recognition of machines faults. Multi-classifier systems are used to improve classification errors. It inspected the algorithms homogeneous: Bagging and Boosting and heterogeneous: Vote, Stacking and Stacking C. Results present the effectiveness of constructed model to faults modeling, such as the possibility of using multi-classifiers algorithm on faults classification

Impacto do racionamento nos resultados das empresas concessionárias do serviço público de distribuição de energia elétrica: um estudo nas empresas privadas da Região Nordeste

This work verifies the impact caused by the Emergencial Program of Reduction of Consumption of Electric Energy (energy-rationing program) in the results of the concessionary private companies of the public service of electric energy distribution localized in the Northeast Area. As the rationing invigorated from June 2001 to February 2002, its effects are diluted in the results presented by these companies in the second semester of 2001 and first quarter of 2002, with prominence for the last quarter of 2001, when the revenue of extraordinary tariff restore was instituted by the National Agency of Electric Energy (ANEEL), consequence of the so-called General Agreement of the Electric Sector made between the federal government and the companies of the electric sector. The structure of a generic electric sector and a historical review of the Brazilian electric sector from the time it was controlled by the private enterprises, including the State control period, about 1960, and returning to the control of the private enterprises in 1990, under a new regulation structure are presented. An explanation of the models of economic regulation that Brazil used for the electric sector is made, with prominence for the price cap that is the actual effective model. The process of tariff revision foreseen in the concession contracts signed by the federal government and the concessionary companies is presented, highlighting its two stages: the tariff rebalancing that defines the new price cap and the calculation of the factor X that establishes the efficiency goals for the companies. There is made a presentation of the Emergencial Program of Reduction of Consumption of Electric Energy and of the consequent General Agreement of the Electric Sector, which created the revenue of extraordinary tariff restore. A conceptual revision on reviews is presented, regarding to concepts, accomplishment and recognition. A brief review of the six companies that made part of the worked sample is also presented. Analyzing the quarters historical review and of amount of sold energy, it was possible to conclude that the energy-rationing altered the results of the studied companies significantly and that alteration was masked by the accounting process of the revenue of extraordinary tariff restore