Metodologia para adaptação de microarquiteturas microprogramadas soft-core à uma ISA padrão: estudo do impacto sobre a complexidade de hardware para o padrão MIPS

In academia, it is common to create didactic processors, facing practical disciplines in the area of Hardware Computer and can be used as subjects in software platforms, operating systems and compilers. Often, these processors are described without ISA standard, which requires the creation of compilers and other basic software to provide the hardware / software interface and hinder their integration with other processors and devices. Using reconfigurable devices described in a HDL language allows the creation or modification of any microarchitecture component, leading to alteration of the functional units of data path processor as well as the state machine that implements the control unit even as new needs arise. In particular, processors RISP enable modification of machine instructions, allowing entering or modifying instructions, and may even adapt to a new architecture. This work, as the object of study addressing educational soft-core processors described in VHDL, from a proposed methodology and its application on two processors with different complexity levels, shows that it s possible to tailor processors for a standard ISA without causing an increase in the level hardware complexity, ie without significant increase in chip area, while its level of performance in the application execution remains unchanged or is enhanced. The implementations also allow us to say that besides being possible to replace the architecture of a processor without changing its organization, RISP processor can switch between different instruction sets, which can be expanded to toggle between different ISAs, allowing a single processor become adaptive hybrid architecture, which can be used in embedded systems and heterogeneous multiprocessor environments

Modelagem de máquina de indução trifásica sem mancais com bobinado dividido

This work presents a model of bearingless induction machine with divided winding. The main goal is to obtain a machine model to use a simpler control system as used in conventional induction machine and to know its behavior. The same strategies used in conventional machines were used to reach the bearingless induction machine model, which has made possible an easier treatment of the involved parameters. The studied machine is adapted from the conventional induction machine, the stator windings were divided and all terminals had been available. This method does not need an auxiliary stator winding for the radial position control which results in a more compact machine. Another issue about this machine is the variation of inductances array also present in result of the rotor displacement. The changeable air-gap produces variation in magnetic flux and in inductances consequently. The conventional machine model can be used for the bearingless machine when the rotor is centered, but in rotor displacement condition this model is not applicable. The bearingless machine has two sets of motor-bearing, both sets with four poles. It was constructed in horizontal position and this increases difficulty in implementation. The used rotor has peculiar characteristics; it is projected according to the stator to yield the greatest torque and force possible. It is important to observe that the current unbalance generated by the position control does not modify the machine characteristics, this only occurs due the radial rotor displacement. The obtained results validate the work; the data reached by a supervisory system corresponds the foreseen results of simulation which verify the model veracity

Contribuições aos Processos de Clustering com Base em Métricas não-Euclidianas

In this work we present a new clustering method that groups up points of a data set in classes. The method is based in a algorithm to link auxiliary clusters that are obtained using traditional vector quantization techniques. It is described some approaches during the development of the work that are based in measures of distances or dissimilarities (divergence) between the auxiliary clusters. This new method uses only two a priori information, the number of auxiliary clusters Na and a threshold distance dt that will be used to decide about the linkage or not of the auxiliary clusters. The number os classes could be automatically found by the method, that do it based in the chosen threshold distance dt, or it is given as additional information to help in the choice of the correct threshold. Some analysis are made and the results are compared with traditional clustering methods. In this work different dissimilarities metrics are analyzed and a new one is proposed based on the concept of negentropy. Besides grouping points of a set in classes, it is proposed a method to statistical modeling the classes aiming to obtain a expression to the probability of a point to belong to one of the classes. Experiments with several values of Na e dt are made in tests sets and the results are analyzed aiming to study the robustness of the method and to consider heuristics to the choice of the correct threshold. During this work it is explored the aspects of information theory applied to the calculation of the divergences. It will be explored specifically the different measures of information and divergence using the Rényi entropy. The results using the different metrics are compared and commented. The work also has appendix where are exposed real applications using the proposed method

Aplicação de técnicas de aprendizado de máquina no reconhecimento de classes estruturais de proteínas

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

Classificação de padrões através de um comitê de máquinas aprimorado por aprendizagem por reforço

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

Contribuições a técnicas de agrupamento e visualização de dados multivariados utilizando mapas auto-organizáveis

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

Estudo Comparativo de Métricas de Pontuação para Aprendizagem Estrutural de Redes Bayesianas

Bayesian networks are powerful tools as they represent probability distributions as graphs. They work with uncertainties of real systems. Since last decade there is a special interest in learning network structures from data. However learning the best network structure is a NP-Hard problem, so many heuristics algorithms to generate network structures from data were created. Many of these algorithms use score metrics to generate the network model. This thesis compare three of most used score metrics. The K-2 algorithm and two pattern benchmarks, ASIA and ALARM, were used to carry out the comparison. Results show that score metrics with hyperparameters that strength the tendency to select simpler network structures are better than score metrics with weaker tendency to select simpler network structures for both metrics (Heckerman-Geiger and modified MDL). Heckerman-Geiger Bayesian score metric works better than MDL with large datasets and MDL works better than Heckerman-Geiger with small datasets. The modified MDL gives similar results to Heckerman-Geiger for large datasets and close results to MDL for small datasets with stronger tendency to select simpler network structures

Determinação de dados de equilíbrio de fases para sistemas aquosos com eletrólitos

In the present work are established initially the fundamental relationships of thermodynamics that govern the equilibrium between phases, the models used for the description of the behavior non ideal of the liquid and vapor phases in conditions of low pressures. This work seeks the determination of vapor-liquid equilibrium (VLE) data for a series of multicomponents mixtures of saturated aliphatic hydrocarbons, prepared synthetically starting from substances with analytical degree and the development of a new dynamic cell with circulation of the vapor phase. The apparatus and experimental procedures developed are described and applied for the determination of VLE data. VLE isobarics data were obtained through a Fischer s ebulliometer of circulation of both phases, for the systems pentane + dodecane, heptane + dodecane and decane + dodecane. Using the two new dynamic cells especially projected, of easy operation and low cost, with circulation of the vapor phase, data for the systems heptane + decane + dodecane, acetone + water, tween 20 + dodecane, phenol + water and distillation curves of a gasoline without addictive were measured. Compositions of the equilibrium phases were found by densimetry, chromatography, and total organic carbon analyzer. Calibration curves of density versus composition were prepared from synthetic mixtures and the behavior excess volumes were evaluated. The VLE data obtained experimentally for the hydrocarbon and aqueous systems were submitted to the test of thermodynamic consistency, as well as the obtained from the literature data for another binary systems, mainly in the bank DDB (Dortmund Data Bank), where the Gibbs-Duhem equation is used obtaining a satisfactory data base. The results of the thermodynamic consistency tests for the binary and ternary systems were evaluated in terms of deviations for applications such as model development. Later, those groups of data (tested and approved) were used in the KijPoly program for the determination of the binary kij parameters of the cubic equations of state original Peng-Robinson and with the expanded alpha function. These obtained parameters can be applied for simulation of the reservoirs petroleum conditions and of the several distillation processes found in the petrochemistry industry, through simulators. The two designed dynamic cells used equipments of national technology for the determination of VLE data were well succeed, demonstrating efficiency and low cost. Multicomponents systems, mixtures of components of different molecular weights and also diluted solutions may be studied in these developed VLE cells

Determinação de Dados de Equilíbrio Líquido-Vapor para Sistemas Hidrocarbonetos e Desenvolvimento de uma Nova Célula Dinâmica

In the present work are established initially the fundamental relationships of thermodynamics that govern the equilibrium between phases, the models used for the description of the behavior non ideal of the liquid and vapor phases in conditions of low pressures. This work seeks the determination of vapor-liquid equilibrium (VLE) data for a series of multicomponents mixtures of saturated aliphatic hydrocarbons, prepared synthetically starting from substances with analytical degree and the development of a new dynamic cell with circulation of the vapor phase. The apparatus and experimental procedures developed are described and applied for the determination of VLE data. VLE isobarics data were obtained through a Fischer's ebulliometer of circulation of both phases, for the systems pentane + dodecane, heptane + dodecane and decane + dodecane. Using the two new dynamic cells especially projected, of easy operation and low cost, with circulation of the vapor phase, data for the systems heptane + decane + dodecane, acetone + water, tween 20 + dodecane, phenol + water and distillation curves of a gasoline without addictive were measured. Compositions of the equilibrium phases were found by densimetry, chromatography, and total organic carbon analyzer. Calibration curves of density versus composition were prepared from synthetic mixtures and the behavior excess volumes were evaluated. The VLE data obtained experimentally for the hydrocarbon and aqueous systems were submitted to the test of thermodynamic consistency, as well as the obtained from the literature data for another binary systems, mainly in the bank DDB (Dortmund Data Bank), where the Gibbs-Duhem equation is used obtaining a satisfactory data base. The results of the thermodynamic consistency tests for the binary and ternary systems were evaluated in terms of deviations for applications such as model development. Later, those groups of data (tested and approved) were used in the KijPoly program for the determination of the binary kij parameters of the cubic equations of state original Peng-Robinson and with the expanded alpha function. These obtained parameters can be applied for simulation of the reservoirs petroleum conditions and of the several distillation processes found in the petrochemistry industry, through simulators. The two designed dynamic cells used equipments of national technology for the determination Humberto Neves Maia de Oliveira Tese de Doutorado PPGEQ/PRH-ANP 14/UFRN of VLE data were well succeed, demonstrating efficiency and low cost. Multicomponents systems, mixtures of components of different molecular weights and also diluted solutions may be studied in these developed VLE cells

A implementação do você em cartas pessoais norte-riograndenses do século XX

Considering the theoretical and methodological presuppositions of Variationist Sociolinguistics (cf. WEINREICH; LABOV; HERZOG, 2006; LABOV, [1972] 2008), in this dissertation, we describe and analyze the process of variation/change involving the personal pronouns tu and você, and its extension in the pronominal paradigm in Brazilian Portuguese (BP), in three sets of personal letters written by people from Rio Grande do Norte (RN) along the 20th century. The discursive universe of those letters is news from the cities in which the informers lived and the themes from their everyday life (trade, jobs, trips, family and politics). Part of the analyzed letters integrate the written by hand minimum corpus of the Projeto de História do Português Brasileiro no Rio Grande do Norte (PHPB-RN). We are based on previous studies about the pronominal system in BP Menon (1995), Faraco (1996), Lopes e Machado (2005), Rumeu (2008), Lopes (2009), Lopes, Rumeu e Marcotulio (2011), Lopes e Marcotulio (2011) e Martins e Moura (2012) , which register the form você replaces tu from the end of the first half of 20th century and attest the following situation: while (a) the imperative verbal forms, (b) the explicit subjects and (c) prepositional complement pronouns are favorable contexts for você, the (d) non imperative verbal forms (with null subject), (e) the non prepositional complement pronoun and (f) the possessive pronoun are contexts of resistance of tu. The results got in this dissertation confirm, partially, the statements defended by the previous studies regarding the favorable contexts for the implementation of você in BP: (i) there are, in the letters from the first two decades of 20th century (1916 to 1925), high frequency of the usage of the form você (98%); (ii) in the personal letters of RN especially in the love letters, in which there are higher recurrence of intimate subjects the discursive universe proved to be itself very relevant in the determination/conditions of the forms of tu; (iii) the unique feminine informer of our sample uses, almost categorically, the forms of tu in letters of the period from 1946 to 1972; (iv) the letters corresponding to the period from 1992 to 1994 present a significant usage of the forms associated to the innovating você, letting appear the change is already implemented in the system of BP and there are, in that set of letters, strong evidences that make us state the pronominal forms of non prepositional complement (accusative/ dative) related to tu are also implemented in a system with an almost categorical usage of você

Casal nacional: significações do corpo e do figurino no telejornalismo

The main objective of this study is to investigate the meanings of body and costume as essential components of television journalists aesthetic discourse, as exemplified by the presenters of Jornal Nacional, from Rede Globo. The study is inspired on the paths proposed by semiotics, and combines this approach with other techniques of scientific investigation to identify the meanings of this non-verbal communication form. For that, this work uses the concept of communication proposed by the Palo Alto School s authors, more specifically the concept of Watzlawick et al. (2005), which understands communication like relation and inherent of human beings. The precepts of complex thought and the hologramatic principle of Morin (1990), which value the union and the need to connect the knowledge of elements or parts to that of the systems these parts constitute, is also present in the thinking that guides the work. Throughout the chapters, we elucidate our understanding of body and television as media, and fashion and television journalism as languages. This work approaches a televisual history of Jornal Nacional in order to better understand the aesthetic proposed by television news over time, its presenters and costumes. The elements that are part of the televisual language s expression and content are addressed so that we can better understand the importance of body and presenters costume in this context. Finally, we conduct an analysis of the meanings of television journalism presenters body and costume through their stereotypes, their integration into the fashion cycle and also into the televisual analysis of the most important costume elements of Jornal Nacional s presenter couple: colors, models and accessories. We thus seek to strengthen the understanding of the wardrobe inseparable from the body as communication and detail some of their production understanding processes. The women historical role in brazilian television journalism, as well as masculinization of TV journalism environment are important elements to contextualize televisual language thinking in contemporary society. The investigation covers the origins, concepts, proposals, stereotypes, prejudices, reproductions, naturalizations and reinterpretation of the body and the costume of the presenters through time and the relationship between body, fashion and communication

Formação estelar desencadeada pela colisão entre nuvens moleculares magnetizadas

We use a finite diference eulerian numerical code, called ZEUS 3D, to do simulations involving the collision between two magnetized molecular clouds, aiming to evaluate the rate of star formation triggered by the collision and to analyse how that rate varies depending on the relative orientations between the cloud magnetic fields before the shock. The ZEUS 3D code is not an easy code to handle. We had to create two subroutines, one to study the cloud-cloud collision and the other for the data output. ZEUS is a modular code. Its hierarchical way of working is explained as well as the way our subroutines work. We adopt two sets of different initial values for density, temperature and magnetic field of the clouds and of the external medium in order to study the collision between two molecular clouds. For each set, we analyse in detail six cases with different directions and orientations of the cloud magnetic field relative to direction of motion of the clouds. The analysis of these twelve cases allowed us to conform analytical-theoretical proposals found in the literature, and to obtain several original results. Previous works indicate that, if the cloud magnetic fields before the collision are orthogonal to the direction of motion, then a strong inhibition of star formation will occur during a cloud-cloud shock, whereas if those magnetic fields are parallel to the direction of motion, star formation will be stimulated. Our treatment of the problem confirmed numerically those results, and further allowed us to quantify the relative star forming efficiencies in each case. Moreover, we propose and analyse an intermediate case where the field of one of the clouds is orthogonal to the motion and the field of the other one is parallel to the motion. We conclude that, in this case, the rate at which the star formation occurs has a value also intermediate between the two extreme cases we mentioned above. Besides that we study the case in which the fields are orthogonal to the direction of the motion but, instead of being parallel to each other, they are anti-parallel, and we obtained for this case the corresponding variation of the star formation rate due to this alteration of the field configuration. This last case has not been studied in the literature before. Our study allows us to obtain, from the simulations, the rate of star formation in each case, as well as the temporal dependence of that rate as each collision evolves, what we do in detail for one of the cases in particular. The values we obtain for the rate of star formation are in accordance with those expected from the presently existing observational data

Propriedades magnéticas de multicamadas e filmes finos quasiperiódicos

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Formação estelar desencadeada pela colisão entre nuvens moleculares magnetizadas

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Propriedades magnéticas quase-estáticas de filmes ferromagnéticos amorfos de FeCuNbSiB

Today, one of the topics that attracts interest of the scientific community is the understanding of magnetic properties of magnetic systems with reduced dimensions, in particular, ferromagnetic thin films. In this case, the comprehension and control of these properties, as well as the development of routes to obtain them, are crucial issues in many aspects of current and future technologies for storage and transmission of information in the electro-electronic industry. There are several materials that exhibit soft magnetic properties, and we highlight the amorphous alloys and that ones obtained by partial crystallization, so-called nanocrystalline materials. The production of these alloys as magnetic ribbons is very common in scientific and technological area, but there are just a few works related to the production of these alloys as thin films. In this work, we studied the quasi-static magnetic properties of ferromagnetic thin films based on FeCuNbSiB in a wide range of thicknesses, from 20 to 500 nm, produced by sputtering. In particular, after the structural characterization performed via X-ray diffraction, the magnetic properties of the sets of samples were investigated using experimental magnetization curve, obtained using a vibrating sample magnetometer, as well as through theoretical curves obtained by theoretical modeling and numerical computation. The modeling process is based on the Stoner Wohlfarth model applied to three dimensions, and adds some energy terms, using as reference experimental results of magnetization. In this case, from the comparison between theoretical and experimental results and the analysis of the constant anisotropy behavior as a function of film thickness, we aim to obtain further information on the magnetization process of the samples, to identify routes for the production of thin films and develop a theoretical to films to use it, in the future, in the obtainment of the theoretical curves of some magnetic measurements, such as magnetoimpedance and magnetoresistance