39 resultados para Técnicas Terapêuticas
Resumo:
Nowadays, classifying proteins in structural classes, which concerns the inference of patterns in their 3D conformation, is one of the most important open problems in Molecular Biology. The main reason for this is that the function of a protein is intrinsically related to its spatial conformation. However, such conformations are very difficult to be obtained experimentally in laboratory. Thus, this problem has drawn the attention of many researchers in Bioinformatics. Considering the great difference between the number of protein sequences already known and the number of three-dimensional structures determined experimentally, the demand of automated techniques for structural classification of proteins is very high. In this context, computational tools, especially Machine Learning (ML) techniques, have become essential to deal with this problem. In this work, ML techniques are used in the recognition of protein structural classes: Decision Trees, k-Nearest Neighbor, Naive Bayes, Support Vector Machine and Neural Networks. These methods have been chosen because they represent different paradigms of learning and have been widely used in the Bioinfornmatics literature. Aiming to obtain an improvment in the performance of these techniques (individual classifiers), homogeneous (Bagging and Boosting) and heterogeneous (Voting, Stacking and StackingC) multiclassification systems are used. Moreover, since the protein database used in this work presents the problem of imbalanced classes, artificial techniques for class balance (Undersampling Random, Tomek Links, CNN, NCL and OSS) are used to minimize such a problem. In order to evaluate the ML methods, a cross-validation procedure is applied, where the accuracy of the classifiers is measured using the mean of classification error rate, on independent test sets. These means are compared, two by two, by the hypothesis test aiming to evaluate if there is, statistically, a significant difference between them. With respect to the results obtained with the individual classifiers, Support Vector Machine presented the best accuracy. In terms of the multi-classification systems (homogeneous and heterogeneous), they showed, in general, a superior or similar performance when compared to the one achieved by the individual classifiers used - especially Boosting with Decision Tree and the StackingC with Linear Regression as meta classifier. The Voting method, despite of its simplicity, has shown to be adequate for solving the problem presented in this work. The techniques for class balance, on the other hand, have not produced a significant improvement in the global classification error. Nevertheless, the use of such techniques did improve the classification error for the minority class. In this context, the NCL technique has shown to be more appropriated
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The stability of synchronous generators connected to power grid has been the object of study and research for years. The interest in this matter is justified by the fact that much of the electricity produced worldwide is obtained with the use of synchronous generators. In this respect, studies have been proposed using conventional and unconventional control techniques such as fuzzy logic, neural networks, and adaptive controllers to increase the stabilitymargin of the systemduring sudden failures and transient disturbances. Thismaster thesis presents a robust unconventional control strategy for maintaining the stability of power systems and regulation of output voltage of synchronous generators connected to the grid. The proposed control strategy comprises the integration of a sliding surface with a linear controller. This control structure is designed to prevent the power system losing synchronism after a sudden failure and regulation of the terminal voltage of the generator after the fault. The feasibility of the proposed control strategy was experimentally tested in a salient pole synchronous generator of 5 kVA in a laboratory structure
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Self-organizing maps (SOM) are artificial neural networks widely used in the data mining field, mainly because they constitute a dimensionality reduction technique given the fixed grid of neurons associated with the network. In order to properly the partition and visualize the SOM network, the various methods available in the literature must be applied in a post-processing stage, that consists of inferring, through its neurons, relevant characteristics of the data set. In general, such processing applied to the network neurons, instead of the entire database, reduces the computational costs due to vector quantization. This work proposes a post-processing of the SOM neurons in the input and output spaces, combining visualization techniques with algorithms based on gravitational forces and the search for the shortest path with the greatest reward. Such methods take into account the connection strength between neighbouring neurons and characteristics of pattern density and distances among neurons, both associated with the position that the neurons occupy in the data space after training the network. Thus, the goal consists of defining more clearly the arrangement of the clusters present in the data. Experiments were carried out so as to evaluate the proposed methods using various artificially generated data sets, as well as real world data sets. The results obtained were compared with those from a number of well-known methods existent in the literature
Resumo:
An evaluation project was conducted on the technique of treatment for effluent oil which is the deriving process to improve cashews. During the evaluation the following techniques were developed: advanced processes of humid oxidation, oxidative processes, processes of biological treatment and processes of adsorption. The assays had been carried through in kinetic models, with an evaluation of the quality of the process by means of determining the chemical demand of oxygen (defined as a technique of control by means of comparative study between the available techniques). The results demonstrated that the natural biodegradation of the effluent ones is limited, as result using the present natural flora in the effluent one revealed impracticable for an application in the industrial systems, independent of the evaluation environment (with or without the oxygen presence). The job of specific microorganisms for the oily composite degradation developed the viability technique of this route, the acceptable levels of inclusion in effluent system of treatment of the improvement of the cashew being highly good with reasonable levels of removal of CDO. However, the use combined with other techniques of daily pay-treatment for these effluent ones revealed to still be more efficient for the context of the treatment of effluent and discarding in receiving bodies in acceptable standards for resolution CONAMA 357/2005. While the significant generation of solid residues the process of adsorption with agroindustrial residues (in special the chitosan) is a technical viable alternative, however, when applied only for the treatment of the effluent ones for discarding in bodies of water, the economic viability is harmed and minimized ambient profits. Though, it was proven that if used for ends of I reuse, the viability is equalized and justifies the investments. There was a study of the photochemistry process which have are applicable to the treatment of the effluent ones, having resulted more satisfactory than those gotten for the UV-Peroxide techniques. There was different result on the one waited for the use of catalyses used in the process of Photo. The catalyses contained the mixing oxide base of Cerium and Manganese, incorporated of Potassium promoters this had presented the best results in the decomposition of the involved pollutants. Having itself an agreed form the gotten photochemistry daily paytreatment resulted, then after disinfection with chlorine the characteristics next the portability to the water were guarantee. The job of the humid oxidation presented significant results in the removal of pollutants; however, its high cost alone is made possible for job in projects of reuses, areas of low scarcity and of raised costs with the capitation/acquisition of the water, in special, for use for industrial and potable use. The route with better economic conditions and techniques for the job in the treatment of the effluent ones of the improvement of the cashew possesses the sequence to follow: conventional process of separation water-oil, photochemistry process and finally, the complementary biological treatment
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Water still represents, on its critical properties and phase transitions, a problem of current scientific interest, as a consequence of the countless open questions and of the inadequacy of the existent theoretical models, mainly related to the different solid and liquid phases that this substance possesses. For example, there are 13 known crystalline forms of water, and also amorphous phases. One of them, the amorphous ice of very high density (VHDA), was just recently observed. Other example is the anomalous behavior in the macroscopic density, which presents a maximum at the temperature of 277 K. In order to experimentally investigate the behavior of one of the liquid-solid phase transitions, the anomaly in its density and also the metastability, we used three different cooling techniques and, as comparison systems, we made use of the solvents: acetone and ethyl alcohol. The first studied cooling system employ a Peltier plate, a device recently developed, which makes use of small cubes made up of semiconductors to change heat among two surfaces; the second system is a commercial refrigerator, similar to the residential ones. Finally, the liquid nitrogen technique, which is used to refrigerate the samples in a container, in two ways: a very fast and other one, almost static. In those three systems, three Beckers of aluminum were used (with a volume of 80 ml, each), containing water, alcohol and acetone. They were closed and maintained at atmospheric pressure. Inside of each Becker were installed three thermocouples, disposed along the vertical axis of the Beckers, one close to the inferior surface, other to the medium level and the last one close the superior surface. A system of data acquisition was built via virtual instrumentation using as a central equipment a Data-Acquisition board. The temperature data were collected by the three thermocouples in the three Beckers, simultaneously, in function of freezing time. We will present the behavior of temperature versus freezing time for the three substances. The results show the characterization of the transitions of the liquid
Resumo:
This dissertation briefly presents the random graphs and the main quantities calculated from them. At the same time, basic thermodynamics quantities such as energy and temperature are associated with some of their characteristics. Approaches commonly used in Statistical Mechanics are employed and rules that describe a time evolution for the graphs are proposed in order to study their ergodicity and a possible thermal equilibrium between them
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
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The objective of this work is to identify, to chart and to explain the evolution of the soil occupation and the envirionment vulnerability of the areas of Canto do Amaro and Alto da Pedra, in the city of Mossoró-RN, having as base analyzes it multiweather of images of orbital remote sensors, the accomplishment of extensive integrated works of field to a Geographic Information System (GIS). With the use of inserted techniques of it analyzes space inserted in a (GIS), and related with the interpretation and analyzes of products that comes from the Remote Sensoriamento (RS.), make possible resulted significant to reach the objectives of this works. Having as support for the management of the information, the data set gotten of the most varied sources and stored in digital environment, it comes to constitute the geographic data base of this research. The previous knowledge of the spectral behavior of the natural or artificial targets, and the use of algorithms of Processing of Digital images (DIP), it facilitates the interpretation task sufficiently and searchs of new information on the spectral level. Use as background these data, was generated a varied thematic cartography was: Maps of Geology, Geomorfológicals Units soils, Vegetation and Use and Occupation of the soil. The crossing in environment SIG, of the above-mentioned maps, generated the maps of Natural and Vulnerability envirionmental of the petroliferous fields of I Canto do Amaro and Alto da Pedra-RN, working in an ambient centered in the management of waters and solid residuos, as well as the analysis of the spatial data, making possible then a more complex analysis of the studied area
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The present essay shows strategies of improvement in a well succeded evolutionary metaheuristic to solve the Asymmetric Traveling Salesman Problem. Such steps consist in a Memetic Algorithm projected mainly to this problem. Basically this improvement applied optimizing techniques known as Path-Relinking and Vocabulary Building. Furthermore, this last one has being used in two different ways, in order to evaluate the effects of the improvement on the evolutionary metaheuristic. These methods were implemented in C++ code and the experiments were done under instances at TSPLIB library, being possible to observe that the procedures purposed reached success on the tests done