269 resultados para Classificadores nominais


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Este trabalho tem como principais objetivos identificar alguns problemas ambientais, perceber as potencialidades das energias renováveis e as diversas maneiras de aproveitamento solar, estabelecer uma comparação entre o Decreto-Lei n.º 80/2006, que deixou de vigorar, e o Decreto-Lei n.º 118/2013, que veio substituí-lo e dimensionar um sistema solar térmico simples com pré-fabricados de pavimento com função de coletor, recentemente criado e desenvolvido. O conhecimento das técnicas do aproveitamento solar, tanto ao nível do aproveitamento ativo como passivo, aplicadas aos edifícios, são suficientes para uma diminuição significativa na fatura energética dos edifícios, responsáveis pelo consumo de 40% da energia final. No tratamento e análise dos decretos, foi possível estudar um caso de estudo, deste modo estabelecendo mais eficazmente as diferenças entre estes. Para tal foram comparados os valores das soluções adotadas no edifício com os valores limites regulamentares pelo Decreto-Lei com os valores dispostos no Decreto-Lei n.º 118/2013, procedendo a cálculos sempre que necessários. As maiores diferenças sentidas foram ao nível do cálculo das necessidades nominais anuais de energia. No caso de estudo, optou-se pela simplicidade aquando do dimensionamento dos pré-fabricados, pois este projeto está ainda numa fase inicial com muitas melhorias a serem feitas a nível do material a utilizar. A comercialização deste produto ainda não é possível, no entanto, prevê-se que o seu custo venha a ser apelativo. A conjugar com o baixo custo, existe o fator da versatilidade das peças, sendo possível uma instalação com variadas formas ou até mesmo padrões.

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Building design is an effective way to achieve HVAC energy consumption reduction. However, this potentiality is often neglected by architects due to the lack of references to support design decisions. This works intends to propose architectural design guidelines for energy efficiency and thermal performance of Campus/UFRN buildings. These guidelines are based on computer simulations results using the software DesignBuilder. The definition of simulation models has begun with envelope variables, partially done after a field study of thirteen buildings at UFRN/Campus. This field study indicated some basic envelope patterns that were applied in simulation models. Occupation variables were identified with temperature and energy consumption monitoring procedures and a verification of illumination and equipment power, both developed at the Campus/UFRN administration building. Three simulation models were proposed according to different design phases and decisions. The first model represents early design decisions, simulating the combination of different types of geometry with three levels of envelope thermal performance. The second model, still as a part of early design phase, analyses thermal changes between circulation halls lateral and central and office rooms, as well as the heat fluxes and monthly temperatures in each circulation hall. The third model analyses the influence of middle-design and detail design decisions on energy consumption and thermal performance. In this model, different solutions of roofs, shading devices, walls and external colors were simulated. The results of all simulation models suggest a high influence of thermal loads due to the incidence of solar radiation on windows and surfaces, which highlights the importance of window shading devices, office room orientation and absorptance of roof and walls surfaces

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This work presents a diagnosis faults system (rotor, stator, and contamination) of three-phase induction motor through equivalent circuit parameters and using techniques patterns recognition. The technology fault diagnostics in engines are evolving and becoming increasingly important in the field of electrical machinery. The neural networks have the ability to classify non-linear relationships between signals through the patterns identification of signals related. It is carried out induction motor´s simulations through the program Matlab R & Simulink R , and produced some faults from modifications in the equivalent circuit parameters. A system is implemented with multiples classifying neural network two neural networks to receive these results and, after well-trained, to accomplish the identification of fault´s pattern

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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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Reinforcement learning is a machine learning technique that, although finding a large number of applications, maybe is yet to reach its full potential. One of the inadequately tested possibilities is the use of reinforcement learning in combination with other methods for the solution of pattern classification problems. It is well documented in the literature the problems that support vector machine ensembles face in terms of generalization capacity. Algorithms such as Adaboost do not deal appropriately with the imbalances that arise in those situations. Several alternatives have been proposed, with varying degrees of success. This dissertation presents a new approach to building committees of support vector machines. The presented algorithm combines Adaboost algorithm with a layer of reinforcement learning to adjust committee parameters in order to avoid that imbalances on the committee components affect the generalization performance of the final hypothesis. Comparisons were made with ensembles using and not using the reinforcement learning layer, testing benchmark data sets widely known in area of pattern classification

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The pattern classification is one of the machine learning subareas that has the most outstanding. Among the various approaches to solve pattern classification problems, the Support Vector Machines (SVM) receive great emphasis, due to its ease of use and good generalization performance. The Least Squares formulation of SVM (LS-SVM) finds the solution by solving a set of linear equations instead of quadratic programming implemented in SVM. The LS-SVMs provide some free parameters that have to be correctly chosen to achieve satisfactory results in a given task. Despite the LS-SVMs having high performance, lots of tools have been developed to improve them, mainly the development of new classifying methods and the employment of ensembles, in other words, a combination of several classifiers. In this work, our proposal is to use an ensemble and a Genetic Algorithm (GA), search algorithm based on the evolution of species, to enhance the LSSVM classification. In the construction of this ensemble, we use a random selection of attributes of the original problem, which it splits the original problem into smaller ones where each classifier will act. So, we apply a genetic algorithm to find effective values of the LS-SVM parameters and also to find a weight vector, measuring the importance of each machine in the final classification. Finally, the final classification is obtained by a linear combination of the decision values of the LS-SVMs with the weight vector. We used several classification problems, taken as benchmarks to evaluate the performance of the algorithm and compared the results with other classifiers

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The continuous development of instruments and equipment used as tools or torque measurement in the industry is demanding more accurate techniques in the use of this kind instrumentation, including development of metrological characteristics in torque measurement. The same happens with the needs in calibration services. There is a diversity of methods of hand torque tools in the market with different measuring range but without complaining with technical standards in terms of requirements of quality and reliability. However, actually there is no choice of a torque measuring standard that fulfils, with low cost, the needs for the calibration of hand torque tools in a large number of ranges. The objective of this thesis is to show the development and evaluation of a torque measuring standard device with a conception to allow the calibration of hand torque tools with three levels of torque with an single instrument, promoting reduction of costs and time in the calibration, also offering reliability for the evaluation of torque measuring instrument. To attend the demand in the calibration of hand torque tools it is necessary that the calibration laboratories have a big collection of torque measuring standards, to fulfills the needs of the costumer, what is very costly. The development of this type of torque measuring standard revealed a viable technique and economically making possible the calibration of hand torque tools in different nominal ranges through a single measurement system versatile, efficient and of easy operation

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Supported catalysts of CuCl2 on sílica were used in the methane oxychlorination reaction. The materials were synthesized by the ion exchange technique in a basic solution, using a copper-ammonia complex with 3 and 6 % of nominal copper loading. The materials where characterized by thermogravimetry (TG), X-ray Fluorescence Spectroscopy (XRF), Temperature Programmed Reduction (TPR), Scanning Electron Microscopy with X-ray microanalysis (SEM/EDS), BET specific area and pore distribution. The characterization confirms the presence of copper on the support surface, concluding that the ion exchange technique was adequate in the catalyst synthesis. For the reaction test, an oxychlorination bench scale unit was employed. The tests were carried at 673 and 773 K. The results showed the influence of temperature and catalyst copper content on the oxychlorination of methane reaction

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This body of work aims to describe and analyze the behavior of the Aí specificity marker of indefinite Noun Phrases (NP), one of the many functions this linguistic item is developing in contemporary Brazilian Portuguese. From the Functional Linguistic theory perspective, the North American declivity, this project intends to outline the possible grammaticalization trajectory taken by the Aí specificity marker. It will be followed from its function as a spatial deitic up to its integration of indefinite NP, and the action of the fundamental principles of the theory, such as iconicity and informativity, will be observed on the use of this item. Following this, Aí specificity marker behavior will be described in respect to various linguistic and social factors: type of text where the occurrence is encountered, language modality in which the latter is produced, syntactic function developed by the NP specified by Aí , the existence or lack of material intervening between Aí and the NP nuclear noun, informational status of the NP adjugated to Aí , and finally, sex, education and age of the speaker. The occurrence of conversational implicatures will also be verified (GRICE, 1982) within the contexts of Aí specificity marker use. Reflections on the teaching of grammar will be made, as well as on the possibility and validity of working with noun phrase specificity markers in elementary and high school Portuguese language classes. The data used in this research project stem from Corpus Discurso & Gramática A língua falada e escrita na cidade do Natal (FURTADO DA CUNHA, 1998), and from Corpus Discurso & Gramática A língua falada e escrita na cidade do Rio de Janeiro (VOTRE; OLIVEIRA, 1995)

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In the light of the Functional Linguistic Theory, in its North-American version (HOPPER, 1987, 1991, 1998, 2008, 2010; GIVÓN, 2001; LEHMANN, 2002; HOPPER; TRAUGOTT, 2003; FURTADO DA CUNHA; OLIVEIRA; MARTELOTTA, 2003, among others), the general objective of this research is to demonstrate, based on morphosyntactic and semantic-pragmatic properties, that AQUI (HERE), AÍ, ALI and LÁ (THERE) are part of an emerging paradigm in Brazilian Portuguese recently constituted and still developing of forms indicating specificity in indefinite noun phrases (NP). The data that make up the corpus of this research were collected in the following large Brazilian oral corpora: the Corpus Discurso & Gramática: a língua falada e escrita na cidade de Natal (FURTADO DA CUNHA, 1998), the Banco Conversacional de Natal (FURTADO DA CUNHA, 2010), the Projeto Variação Linguística no Estado da Paraíba VALPB (HORA, 2005) and the Projeto Variação Linguística Urbana na Região Sul do Brasil VARSUL (VANDRESEN, 2002). Firstly, the behavior of the specificity markings AQUI, AÍ, ALI and LÁ is described with respect to many factors of morphosyntactic and semantic-pragmatic nature: type of construction in which the markers appeared; existence or not of intervening material between the specificity marker item and the NP s nuclear noun; type of noun to which AQUI, AÍ, ALI and LÁ are linked; syntactic function of the specified SN; informational status of the NP to which the specificity markers AQUI, AÍ, ALI and LÁ are attached; occurrence of conversational implicatures (GRICE, 1982) in the context of use of these specificity markers. Next, a possible grammaticalization trajectory is outlined, according to which AQUI, AÍ, ALI and LÁ would had gone from an early spatial deictic indication to the specificity indication. The results point to the existence of forms with varying degree of emergence in this new paradigm of nominal specification, with AÍ being, probably, the item most grammaticalized, followed by LÁ, then ALI and AQUI, which permanence in the paradigm do not yet appear to be consolidated

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In the last decade, an increasing number of studies focusing on the impact of oral deformities on quality of life have been published. However, the evaluation of patients at different phases of the treatment has not been performed. Therefore, the purpose of this study was to determine the impact that dentofacial deformities have on patients` quality of life, as well as the influence exerted by social, economic, demographic and orthodontic factors, type and severity of malocclusion. A bicentric study - of the cross-sectional type of repeated panels - involving two cities - Natal and Rio de Janeiro - was carried out. A total of 227 patients participated in the study: 71 patients in the initial phase of the treatment (before any orthosurgical procedure), 115 patients in the pre-surgical (with braces) phase and 41 patients in the postoperative phase. The quality of life was measured using the Orthognatic Quality of Life Questionnnaire - OQLQ, translated and validated into Portuguese. The normative and aesthetic need for treatment was assessed with the Index of Orthodontic Treatment Need (IOTN) and the Dental Aesthetic Index (DAI); the social, economic and demographic factors, the type of service and malocclusion were also assessed. The data were analyzed through χ2/ Fisher`s exact test to seek the association between the nominal categorical variables in the three phases of treatment, Mann Whitney and Kruskal-Wallis test for gauging the existence of significant differences between two and three groups regarding each domain of OQLQ, respectively. For all tests, it was adopted a significance level of 5%. There was a statistically significant difference (p <0.001) in the general scores of OQLQ and in the domains of social aspects, facial aesthetics and oral function, when the "postoperative group" was compared to the "initial" and "orthodontic preparation" groups. Women, single, aged between 31 and 59 and living in Natal had the greatest impact on quality of life among patients in the "orthodontic preparation" group. Only the variable "income" (2 to 3 minimum wages), for the "initial" group, and gender (female) for the "postoperative" group, showed significant association with quality of life. The normative variable IOTN (DHC and AC) showed significant association with the OQLQ for the "initial" group, and the IOTN-AC-auto in the group of orthodontic preparation, being less important to women. We conclude that the ortho-surgical therapy has positive effects on quality of life after orthognathic surgery

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The use of intelligent agents in multi-classifier systems appeared in order to making the centralized decision process of a multi-classifier system into a distributed, flexible and incremental one. Based on this, the NeurAge (Neural Agents) system (Abreu et al 2004) was proposed. This system has a superior performance to some combination-centered methods (Abreu, Canuto, and Santana 2005). The negotiation is important to the multiagent system performance, but most of negotiations are defined informaly. A way to formalize the negotiation process is using an ontology. In the context of classification tasks, the ontology provides an approach to formalize the concepts and rules that manage the relations between these concepts. This work aims at using ontologies to make a formal description of the negotiation methods of a multi-agent system for classification tasks, more specifically the NeurAge system. Through ontologies, we intend to make the NeurAge system more formal and open, allowing that new agents can be part of such system during the negotiation. In this sense, the NeurAge System will be studied on the basis of its functioning and reaching, mainly, the negotiation methods used by the same ones. After that, some negotiation ontologies found in literature will be studied, and then those that were chosen for this work will be adapted to the negotiation methods used in the NeurAge.

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Multi-classifier systems, also known as ensembles, have been widely used to solve several problems, because they, often, present better performance than the individual classifiers that form these systems. But, in order to do so, it s necessary that the base classifiers to be as accurate as diverse among themselves this is also known as diversity/accuracy dilemma. Given its importance, some works have investigate the ensembles behavior in context of this dilemma. However, the majority of them address homogenous ensemble, i.e., ensembles composed only of the same type of classifiers. Thus, motivated by this limitation, this thesis, using genetic algorithms, performs a detailed study on the dilemma diversity/accuracy for heterogeneous ensembles

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In the world we are constantly performing everyday actions. Two of these actions are frequent and of great importance: classify (sort by classes) and take decision. When we encounter problems with a relatively high degree of complexity, we tend to seek other opinions, usually from people who have some knowledge or even to the extent possible, are experts in the problem domain in question in order to help us in the decision-making process. Both the classification process as the process of decision making, we are guided by consideration of the characteristics involved in the specific problem. The characterization of a set of objects is part of the decision making process in general. In Machine Learning this classification happens through a learning algorithm and the characterization is applied to databases. The classification algorithms can be employed individually or by machine committees. The choice of the best methods to be used in the construction of a committee is a very arduous task. In this work, it will be investigated meta-learning techniques in selecting the best configuration parameters of homogeneous committees for applications in various classification problems. These parameters are: the base classifier, the architecture and the size of this architecture. We investigated nine types of inductors candidates for based classifier, two methods of generation of architecture and nine medium-sized groups for architecture. Dimensionality reduction techniques have been applied to metabases looking for improvement. Five classifiers methods are investigated as meta-learners in the process of choosing the best parameters of a homogeneous committee.

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Neste trabalho, um controlador adaptativo backstepping a estrutura variável (Variable Structure Adaptive Backstepping Controller, VS-ABC) é apresentado para plantas monovariáveis, lineares e invariantes no tempo com grau relativo unitário. Ao invés das tradicionais leis integrais para estimação dos parâmetros da planta, leis chaveadas são utilizadas com o objetivo de aumentar a robustez em relação a incertezas paramétricas e distúrbios externos, bem como melhorar o desempenho transitório do sistema. Adicionalmente, o projeto do novo controlador é mais intuitivo quando comparado ao controlador backstepping original, uma vez que os relés introduzidos apresentam amplitudes diretamente relacionadas com os parâmetros nominais da planta. Esta nova abordagem, com uso de estrutura variável, também reduz a complexidade das implementações práticas, motivando a utilização de componentes industriais, tais como, FPGAs (Field Programmable Gate Arrays ), MCUs (Microcontrollers) e DSPs (Digital Signal Processors). Simulações preliminares para um sistema instável de primeira e segunda ordem são apresentadas de modo a corroborar os estudos. Um dos exemplos de Rohrs é ainda abordado através de simulações, para os dois cenários adaptativos: o controlador backstepping adaptativo original e o VS-ABC