32 resultados para Semiótica Aplicada


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Systems whose spectra are fractals or multifractals have received a lot of attention in recent years. The complete understanding of the behavior of many physical properties of these systems is still far from being complete because of the complexity of such systems. Thus, new applications and new methods of study of their spectra have been proposed and consequently a light has been thrown on their properties, enabling a better understanding of these systems. We present in this work initially the basic and necessary theoretical framework regarding the calculation of energy spectrum of elementary excitations in some systems, especially in quasiperiodic ones. Later we show, by using the Schr¨odinger equation in tight-binding approximation, the results for the specific heat of electrons within the statistical mechanics of Boltzmann-Gibbs for one-dimensional quasiperiodic systems, growth by following the Fibonacci and Double Period rules. Structures of this type have already been exploited enough, however the use of non-extensive statistical mechanics proposed by Constantino Tsallis is well suited to systems that have a fractal profile, and therefore our main objective was to apply it to the calculation of thermodynamical quantities, by extending a little more the understanding of the properties of these systems. Accordingly, we calculate, analytical and numerically, the generalized specific heat of electrons in one-dimensional quasiperiodic systems (quasicrystals) generated by the Fibonacci and Double Period sequences. The electronic spectra were obtained by solving the Schr¨odinger equation in the tight-binding approach. Numerical results are presented for the two types of systems with different values of the parameter of nonextensivity q

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In the present work we use a Tsallis maximum entropy distribution law to fit the observations of projected rotational velocity measurements of stars in the Pleiades open cluster. This new distribution funtion which generalizes the Ma.xwel1-Boltzmann one is derived from the non-extensivity of the Boltzmann-Gibbs entropy. We also present a oomparison between results from the generalized distribution and the Ma.xwellia.n law, and show that the generalized distribution fits more closely the observational data. In addition, we present a oomparison between the q values of the generalized distribution determined for the V sin i distribution of the main sequence stars (Pleiades) and ones found for the observed distribution of evolved stars (subgiants). We then observe a correlation between the q values and the star evolution stage for a certain range of stel1ar mass

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

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The aiming of this work is linked to chemical education, focusing organic chemistry classes of Chemical Engineering, Pharmacy and Zootechny graduate courses of the Federal University of Rio Grande do Norte. For that, teaching-learning process related to basic chemical subjects which support the understanding of organic chemistry concepts was evaluated in a research period of two years. The education proposal linked to the theoretical content of the cited classes, pointed out the process of knowledge construction, in which educational commitment as well as dedication in the teaching-learning process was also valued. In that approach several didactic tools were applied, among them scientific articles were used as supplementary studies of the basic organic chemistry concepts and related. The acceptability of students, as well as their motivation, performance and learning process was justified by the data collection of the applied teaching methodology. The acceptability and commitment of the students facing this teaching interactive approach, which transversely contributed to the intellectual maturity growth of the students, as well their professional development, were evidenced by satisfactory obtained results that will be herein discussed

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Este trabalho apresenta uma extensão do provador haRVey destinada à verificação de obrigações de prova originadas de acordo com o método B. O método B de desenvolvimento de software abrange as fases de especificação, projeto e implementação do ciclo de vida do software. No contexto da verificação, destacam-se as ferramentas de prova Prioni, Z/EVES e Atelier-B/Click n Prove. Elas descrevem formalismos com suporte à checagem satisfatibilidade de fórmulas da teoria axiomática dos conjuntos, ou seja, podem ser aplicadas ao método B. A checagem de SMT consiste na checagem de satisfatibilidade de fórmulas da lógica de primeira-ordem livre de quantificadores dada uma teoria decidível. A abordagem de checagem de SMT implementada pelo provador automático de teoremas haRVey é apresentada, adotando-se a teoria dos vetores que não permite expressar todas as construções necessárias às especificações baseadas em conjuntos. Assim, para estender a checagem de SMT para teorias dos conjuntos destacam-se as teorias dos conjuntos de Zermelo-Frankel (ZFC) e de von Neumann-Bernays-Gödel (NBG). Tendo em vista que a abordagem de checagem de SMT implementada no haRVey requer uma teoria finita e pode ser estendida para as teorias nãodecidíveis, a teoria NBG apresenta-se como uma opção adequada para a expansão da capacidade dedutiva do haRVey à teoria dos conjuntos. Assim, através do mapeamento dos operadores de conjunto fornecidos pela linguagem B a classes da teoria NBG, obtem-se uma abordagem alternativa para a checagem de SMT aplicada ao método B

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Ce travail a pour but d analyser un corpus de six textes hybrides, que nous classons comme des poèmes-chansons/ poèmes-chantés à cause de leur double présence dans deux systèmes sémiotiques différents. Le premier, la littérature, ou plus spécifiquement la poésie, a comme support le livre As Coisas [Les Choses], d Arnaldo Antunes et l autre, la chanson, est enregistré dans les disques du même auteur. Notre travail lance un regard sur ce corpus, en essayant de vérifier un aspect recourrent dans l oeuvre d Arnaldo Antunes qui est la présence da priméité, catégorie theórique développée par Charles Sanders Peirce. Au-delà de l observation de cet aspect sémiothique, nous ferons une discussion sur la chanson populaire, et ses rapports avec la poésie et par conséquent avec la Litterature. La théorie sémiothique s appuyera sur deux piliers : En ce qui concerne l étude de la priméité, nous travaillerons avec les théories de Peirce, mais en nous servant aussi des ouvrages de Lúcia Santaella, Winfried Nöth, Júlio Plaza et Décio Pignatari ; Dans l autre voie, pour ce qui concerne l analyse des chansons, nous utiliserons la théorie de Luiz Tatit, fondée sur la sémiothique de Algirdas Julien Greimas. Tatit trace une méthode d analyse, où il est possible d analyser une chanson en exploitant et le texte et la mélodie, ce qui permet une meilleure compréhension de l étude des poèmes-chansons et ses variations. Comme support pour la discussion sur la musique, nous nous servirons des théories de José Miguel Wisnik, Claude Lévi-Strauss, Roland Barthes et Jean Fisette

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In this work a study of social networks based on analysis of family names is presented. A basic approach to the mathematical formalism of graphs is developed and then main theoretical models for complex networks are presented aiming to support the analysis of surnames networks models. These, in turn, are worked so as to be drawn leading quantities, such as aggregation coefficient, minimum average path length and connectivity distribution. Based on these quantities, it can be stated that surnames networks are an example of complex network, showing important features such as preferential attachment and small-world character

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In this work we study a new risk model for a firm which is sensitive to its credit quality, proposed by Yang(2003): Are obtained recursive equations for finite time ruin probability and distribution of ruin time and Volterra type integral equation systems for ultimate ruin probability, severity of ruin and distribution of surplus before and after ruin

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This research studies the application of syntagmatic analysis of written texts in the language of Brazilian Portuguese as a methodology for the automatic creation of extractive summaries. The automation of abstracts, while linked to the area of natural language processing (PLN) is studying ways the computer can autonomously construct summaries of texts. For this we use as presupposed the idea that switch to the computer the way a language is structured, in our case the Brazilian Portuguese, it will help in the discovery of the most relevant sentences, and consequently build extractive summaries with higher informativeness. In this study, we propose the definition of a summarization method that automatically perform the syntagmatic analysis of texts and through them, to build an automatic summary. The phrases that make up the syntactic structures are then used to analyze the sentences of the text, so the count of these elements determines whether or not a sentence will compose the summary to be generated

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The Monte Carlo method is accurate and is relatively simple to implement for the solution of problems involving complex geometries and anisotropic scattering of radiation as compared with other numerical techniques. In addition, differently of what happens for most of numerical techniques, for which the associated simulations computational time tends to increase exponentially with the complexity of the problems, in the Monte Carlo the increase of the computational time tends to be linear. Nevertheless, the Monte Carlo solution is highly computer time consuming for most of the interest problems. The Multispectral Energy Bundle model allows the reduction of the computational time associated to the Monte Carlo solution. The referred model is here analyzed for applications in media constituted for nonparticipating species and water vapor, which is an important emitting species formed during the combustion of hydrocarbon fuels. Aspects related to computer time optimization are investigated the model solutions are compared with benchmark line-by-line solutions

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The conventional control schemes applied to Shunt Active Power Filters (SAPF) are Harmonic extractor-based strategies (HEBSs) because their effectiveness depends on how quickly and accurately the harmonic components of the nonlinear loads are identified. The SAPF can be also implemented without the use of the load harmonic extractors. In this case, the harmonic compensating term is obtained from the system active power balance. These systems can be considered as balanced-energy-based schemes (BEBSs) and their performance depends on how fast the system reaches the equilibrium state. In this case, the phase currents of the power grid are indirectly regulated by double sequence controllers with two degrees of freedom, where the internal model principle is employed to avoid reference frame transformation. Additionally the DSC controller presents robustness when the SAPF is operating under unbalanced conditions. Furthermore, SAPF implemented without harmonic detection schemes compensate simultaneously harmonic distortion and reactive power of the load. Their compensation capabilities, however, are limited by the SAPF power converter rating. Such a restriction can be minimized if the level of the reactive power correction is managed. In this work an estimation scheme for determining the filter currents is introduced to manage the compensation of reactive power. Experimental results are shown for demonstrating the performance of the proposed SAPF system.

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Generation systems, using renewable sources, are becoming increasingly popular due to the need for increased use of electricity. Currently, renewables sources have a role to cooperate with conventional generation, due to the system limitation in delivering the required power, the need for reduction of unwanted effects from sources that use fossil fuels (pollution) and the difficulty of building new transmission and/or distribution lines. This cooperation takes place through distributed generation. Therefore, this work proposes a control strategy for the interconnection of a PV (Photovoltaic) system generation distributed with a three-phase power grid through a connection filter the type LCL. The compensation of power quality at point of common coupling (PCC) is performed ensuring that the mains supply or consume only active power and that his currents have low distorcion. Unlike traditional techniques which require schemes for harmonic detection, the technique performs the harmonic compensation without the use of this schemes, controlling the output currents of the system in an indirect way. So that there is effective control of the DC (Direct Current) bus voltage is used the robust controller mode dual DSMPI (Dual-Sliding Mode-Proportional Integral), that behaves as a sliding mode controller SM-PI (Sliding Mode-Proportional Integral) during the transition and like a conventional PI (Proportional Integral) in the steady-state. For control of current is used to repetitive control strategy, which are used double sequence controllers (DSC) tuned to the fundamental component, the fifth and seventh harmonic. The output phase current are aligned with the phase angle of the utility voltage vector obtained from the use of a SRF-PLL (Synchronous Reference Frame Phase-Locked-Loop). In order to obtain the maximum power from the PV array is used a MPPT (Maximum Power Point Tracking) algorithm without the need for adding sensors. Experimental results are presented to demonstrate the effectiveness of the proposed control system.

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The classifier support vector machine is used in several problems in various areas of knowledge. Basically the method used in this classier is to end the hyperplane that maximizes the distance between the groups, to increase the generalization of the classifier. In this work, we treated some problems of binary classification of data obtained by electroencephalography (EEG) and electromyography (EMG) using Support Vector Machine with some complementary techniques, such as: Principal Component Analysis to identify the active regions of the brain, the periodogram method which is obtained by Fourier analysis to help discriminate between groups and Simple Moving Average to eliminate some of the existing noise in the data. It was developed two functions in the software R, for the realization of training tasks and classification. Also, it was proposed two weights systems and a summarized measure to help on deciding in classification of groups. The application of these techniques, weights and the summarized measure in the classier, showed quite satisfactory results, where the best results were an average rate of 95.31% to visual stimuli data, 100% of correct classification for epilepsy data and rates of 91.22% and 96.89% to object motion data for two subjects.

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This work proposes a new autonomous navigation strategy assisted by genetic algorithm with dynamic planning for terrestrial mobile robots, called DPNA-GA (Dynamic Planning Navigation Algorithm optimized with Genetic Algorithm). The strategy was applied in environments - both static and dynamic - in which the location and shape of the obstacles is not known in advance. In each shift event, a control algorithm minimizes the distance between the robot and the object and maximizes the distance from the obstacles, rescheduling the route. Using a spatial location sensor and a set of distance sensors, the proposed navigation strategy is able to dynamically plan optimal collision-free paths. Simulations performed in different environments demonstrated that the technique provides a high degree of flexibility and robustness. For this, there were applied several variations of genetic parameters such as: crossing rate, population size, among others. Finally, the simulation results successfully demonstrate the effectiveness and robustness of DPNA-GA technique, validating it for real applications in terrestrial mobile robots.

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This work proposes a new autonomous navigation strategy assisted by genetic algorithm with dynamic planning for terrestrial mobile robots, called DPNA-GA (Dynamic Planning Navigation Algorithm optimized with Genetic Algorithm). The strategy was applied in environments - both static and dynamic - in which the location and shape of the obstacles is not known in advance. In each shift event, a control algorithm minimizes the distance between the robot and the object and maximizes the distance from the obstacles, rescheduling the route. Using a spatial location sensor and a set of distance sensors, the proposed navigation strategy is able to dynamically plan optimal collision-free paths. Simulations performed in different environments demonstrated that the technique provides a high degree of flexibility and robustness. For this, there were applied several variations of genetic parameters such as: crossing rate, population size, among others. Finally, the simulation results successfully demonstrate the effectiveness and robustness of DPNA-GA technique, validating it for real applications in terrestrial mobile robots.