Maracatus Solar e Reis de Paus: tradição e modernidade no carnaval de rua em Fortaleza

This is an ethnographic and comparative study of the Maracatus Solar (2006) and Reis de Paus (1960), whose aim was to verify what is ancient and traditional in the new maracatu practiced by the guild Solar and conversely, what is new or modern in the old maracatu ritualized by guild Reis de Paus. It is worth noting that through this case study it is also intended to ethnographically observe and better understand the processes of ruptures and continuities between modernization and tradition, and the relationship between the global and the local. The communication system, the dancing, the music, the costumes and the loas (letters) were analyzed using the technique of participant observation as well as secondary materials such as newspapers, blogs and magazines. The interviews were open, non-directive, but recorded to facilitate understanding the speech of revelers. The research has shown that all the symbolic elements of aesthetic expression of the maracatu are permeated by clashes of historical contexts and of political representation, which, in another instance, also enunciates a fight of micro-community resistance regarding the renewal process and the social development that plague modern megalopolis. It is In this interim, between modernity and tradition that today it can be spoken about the existence of hybrid identity in the maracatu regarding a context mediated by the overall above mentioned values and customs specific of the new generations. However, one can not deny that the forms of negotiations with modernity also require the establishment of a link with the specific singularity of a popular culture that is not excluded, but also should not get invaded by the idea of authenticity. Therefore, performing this study was above all an opportunity to understand also the community life in the city outskirts, understanding society, culture and everyday social relations maintained between humans that produce and make it all happen. The Solar and Reis de Paus do not join in opposition between themselves nor by their similarity. What is most striking among them is the renewal of a tradition that reinvents itself in the form of popular representation across the street parade

Algoritmo Q-learning como estratégia de exploração e/ou explotação para metaheurísticas GRASP e algoritmo genético

Techniques of optimization known as metaheuristics have achieved success in the resolution of many problems classified as NP-Hard. These methods use non deterministic approaches that reach very good solutions which, however, don t guarantee the determination of the global optimum. Beyond the inherent difficulties related to the complexity that characterizes the optimization problems, the metaheuristics still face the dilemma of xploration/exploitation, which consists of choosing between a greedy search and a wider exploration of the solution space. A way to guide such algorithms during the searching of better solutions is supplying them with more knowledge of the problem through the use of a intelligent agent, able to recognize promising regions and also identify when they should diversify the direction of the search. This way, this work proposes the use of Reinforcement Learning technique - Q-learning Algorithm - as exploration/exploitation strategy for the metaheuristics GRASP (Greedy Randomized Adaptive Search Procedure) and Genetic Algorithm. The GRASP metaheuristic uses Q-learning instead of the traditional greedy-random algorithm in the construction phase. This replacement has the purpose of improving the quality of the initial solutions that are used in the local search phase of the GRASP, and also provides for the metaheuristic an adaptive memory mechanism that allows the reuse of good previous decisions and also avoids the repetition of bad decisions. In the Genetic Algorithm, the Q-learning algorithm was used to generate an initial population of high fitness, and after a determined number of generations, where the rate of diversity of the population is less than a certain limit L, it also was applied to supply one of the parents to be used in the genetic crossover operator. Another significant change in the hybrid genetic algorithm is the proposal of a mutually interactive cooperation process between the genetic operators and the Q-learning algorithm. In this interactive/cooperative process, the Q-learning algorithm receives an additional update in the matrix of Q-values based on the current best solution of the Genetic Algorithm. The computational experiments presented in this thesis compares the results obtained with the implementation of traditional versions of GRASP metaheuristic and Genetic Algorithm, with those obtained using the proposed hybrid methods. Both algorithms had been applied successfully to the symmetrical Traveling Salesman Problem, which was modeled as a Markov decision process

Modelagem de usinas eólicas através de um processo de Markov e técnicas de confiabilidade para a estimativa anual da energia produzida

This study aims to use a computational model that considers the statistical characteristics of the wind and the reliability characteristics of a wind turbine, such as failure rates and repair, representing the wind farm by a Markov process to determine the estimated annual energy generated, and compare it with a real case. This model can also be used in reliability studies, and provides some performance indicators that will help in analyzing the feasibility of setting up a wind farm, once the power curve is known and the availability of wind speed measurements. To validate this model, simulations were done using the database of the wind farm of Macau PETROBRAS. The results were very close to the real, thereby confirming that the model successfully reproduced the behavior of all components involved. Finally, a comparison was made of the results presented by this model, with the result of estimated annual energy considering the modeling of the distribution wind by a statistical distribution of Weibull

Estimação paramétrica e não-paramétrica em modelos de markov ocultos

In this work we study the Hidden Markov Models with finite as well as general state space. In the finite case, the forward and backward algorithms are considered and the probability of a given observed sequence is computed. Next, we use the EM algorithm to estimate the model parameters. In the general case, the kernel estimators are used and to built a sequence of estimators that converge in L1-norm to the density function of the observable process