Desenvolvimento de perfis aerodinâmicos a partir de suas características utilizando redes neurais artificiais

One of the current major concerns in engineering is the development of aircrafts that have low power consumption and high performance. So, airfoils that have a high value of Lift Coefficient and a low value for the Drag Coefficient, generating a High-Efficiency airfoil are studied and designed. When the value of the Efficiency increases, the aircraft s fuel consumption decreases, thus improving its performance. Therefore, this work aims to develop a tool for designing of airfoils from desired characteristics, as Lift and Drag coefficients and the maximum Efficiency, using an algorithm based on an Artificial Neural Network (ANN). For this, it was initially collected an aerodynamic characteristics database, with a total of 300 airfoils, from the software XFoil. Then, through the software MATLAB, several network architectures were trained, between modular and hierarchical, using the Back-propagation algorithm and the Momentum rule. For data analysis, was used the technique of cross- validation, evaluating the network that has the lowest value of Root Mean Square (RMS). In this case, the best result was obtained for a hierarchical architecture with two modules and one layer of hidden neurons. The airfoils developed for that network, in the regions of lower RMS, were compared with the same airfoils imported into the software XFoil

Integração de redes GNSS: uma proposta metodológica de densificação da rede SIRGAS na América do Sul

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Aninhamento em redes bipartidas

We present a nestedness index that measures the nestedness pattern of bipartite networks, a problem that arises in theoretical ecology. Our measure is derived using the sum of distances of the occupied elements in the adjacency matrix of the network. This index quantifies directly the deviation of a given matrix from the nested pattern. In the most simple case the distance of the matrix element ai,j is di,j = i+j, the Manhattan distance. A generic distance is obtained as di,j = (i¬ + j¬)1/¬. The nestedness índex is defined by = 1 − where is the temperature of the matrix. We construct the temperature index using two benchmarks: the distance of the complete nested matrix that corresponds to zero temperature and the distance of the average random matrix that is defined as temperature one. We discuss an important feature of the problem: matrix occupancy. We address this question using a metric index ¬ that adjusts for matrix occupancy

Conexão entre as redes complexas e estatística de Kaniadakis e busca eficiente das propriedades críticas do processo epidêmico difusivo 1D

In this work we study a connection between a non-Gaussian statistics, the Kaniadakis statistics, and Complex Networks. We show that the degree distribution P(k)of a scale free-network, can be calculated using a maximization of information entropy in the context of non-gaussian statistics. As an example, a numerical analysis based on the preferential attachment growth model is discussed, as well as a numerical behavior of the Kaniadakis and Tsallis degree distribution is compared. We also analyze the diffusive epidemic process (DEP) on a regular lattice one-dimensional. The model is composed of A (healthy) and B (sick) species that independently diffusive on lattice with diffusion rates DA and DB for which the probabilistic dynamical rule A + B → 2B and B → A. This model belongs to the category of non-equilibrium systems with an absorbing state and a phase transition between active an inactive states. We investigate the critical behavior of the DEP using an auto-adaptive algorithm to find critical points: the method of automatic searching for critical points (MASCP). We compare our results with the literature and we find that the MASCP successfully finds the critical exponents 1/ѵ and 1/zѵ in all the cases DA =DB, DA DB. The simulations show that the DEP has the same critical exponents as are expected from field-theoretical arguments. Moreover, we find that, contrary to a renormalization group prediction, the system does not show a discontinuous phase transition in the regime o DA >DB.

Estudo de sistemas complexos com interações de longo alcance : percolação, redes e tráfego

In this thesis we investigate physical problems which present a high degree of complexity using tools and models of Statistical Mechanics. We give a special attention to systems with long-range interactions, such as one-dimensional long-range bondpercolation, complex networks without metric and vehicular traffic. The flux in linear chain (percolation) with bond between first neighbor only happens if pc = 1, but when we consider long-range interactions , the situation is completely different, i.e., the transitions between the percolating phase and non-percolating phase happens for pc < 1. This kind of transition happens even when the system is diluted ( dilution of sites ). Some of these effects are investigated in this work, for example, the extensivity of the system, the relation between critical properties and the dilution, etc. In particular we show that the dilution does not change the universality of the system. In another work, we analyze the implications of using a power law quality distribution for vertices in the growth dynamics of a network studied by Bianconi and Barabási. It incorporates in the preferential attachment the different ability (fitness) of the nodes to compete for links. Finally, we study the vehicular traffic on road networks when it is submitted to an increasing flux of cars. In this way, we develop two models which enable the analysis of the total flux on each road as well as the flux leaving the system and the behavior of the total number of congested roads

Propagação de danos no modelo de ising em redes de bravais e em fractais

In this work we have studied, by Monte Carlo computer simulation, several properties that characterize the damage spreading in the Ising model, defined in Bravais lattices (the square and the triangular lattices) and in the Sierpinski Gasket. First, we investigated the antiferromagnetic model in the triangular lattice with uniform magnetic field, by Glauber dynamics; The chaotic-frozen critical frontier that we obtained coincides , within error bars, with the paramegnetic-ferromagnetic frontier of the static transition. Using heat-bath dynamics, we have studied the ferromagnetic model in the Sierpinski Gasket: We have shown that there are two times that characterize the relaxation of the damage: One of them satisfy the generalized scaling theory proposed by Henley (critical exponent z~A/T for low temperatures). On the other hand, the other time does not obey any of the known scaling theories. Finally, we have used methods of time series analysis to study in Glauber dynamics, the damage in the ferromagnetic Ising model on a square lattice. We have obtained a Hurst exponent with value 0.5 in high temperatures and that grows to 1, close to the temperature TD, that separates the chaotic and the frozen phases

Redes sociais e comunidades virtuais para a preservação e transmissão das tradições gaúchas na Internet

Considerando a potencialidade apresentada pelas tecnologias de informação e comunicação na atualidade este estudo aponta as formas pelas quais grupos sociais mobilizados em torno de uma vinculação étnica podem se servir do aparato da Internet, em especial do World Wide Web, para divulgar aspectos de sua cultura e modo de vida. Trata-se de grupos dedicados ao ensino, transmissão, preservação e disseminação da tradição gaúcha vinculados aos Centros de Tradições Gaúchas (CTG). Especificamente, este artigo apresenta como os tradicionalistas gaúchos estabelecem suas redes sociais na Internet, constituindo comunidades virtuais em torno do tema cultura e tradição gaúcha, fazendo uso dos serviços da Web 2.0. Abordam-se neste estudo experiências que indicam que o terreno virtual é fértil e possível de transformar e revolucionar o campo das tradições, sua preservação, disseminação e (re)invenção. No contexto de modernidade tardia esse recurso não pode ser descartado. Independente da análise se situar no campo econômico, político ou cultural, entre tantos outros, o fato é que a Internet se constitui num meio eficaz e abrangente de transmitir, ensinar e preservar conteúdos de todos os tipos.

Uma análise da aplicação do modelo de Rede Neural RePART em Comitês de classificadores

RePART (Reward/Punishment ART) is a neural model that constitutes a variation of the Fuzzy Artmap model. This network was proposed in order to minimize the inherent problems in the Artmap-based model, such as the proliferation of categories and misclassification. RePART makes use of additional mechanisms, such as an instance counting parameter, a reward/punishment process and a variable vigilance parameter. The instance counting parameter, for instance, aims to minimize the misclassification problem, which is a consequence of the sensitivity to the noises, frequently presents in Artmap-based models. On the other hand, the use of the variable vigilance parameter tries to smoouth out the category proliferation problem, which is inherent of Artmap-based models, decreasing the complexity of the net. RePART was originally proposed in order to minimize the aforementioned problems and it was shown to have better performance (higer accuracy and lower complexity) than Artmap-based models. This work proposes an investigation of the performance of the RePART model in classifier ensembles. Different sizes, learning strategies and structures will be used in this investigation. As a result of this investigation, it is aimed to define the main advantages and drawbacks of this model, when used as a component in classifier ensembles. This can provide a broader foundation for the use of RePART in other pattern recognition applications

Excitações elementares em super-redes quasiperiódicas com simetria espelho

In this thesis, we investigated the magnonic and photonic structures that exhibit the so-called deterministic disorder. Speci cally, we studied the effects of the quasiperiodicity, associated with an internal structural symmetry, called mirror symmetry, on the spectra of photonics and magnonics multilayer. The quasiperiodicity is introduced when stacked layers following the so-called substitutional sequences. The three sequences used here were the Fibonacci sequence, Thue-Morse and double-period, all with mirror symmetry. Aiming to study the propagation of light waves in multilayer photonic, and spin waves propagation in multilayer magnonic, we use a theoretical model based on transfer matrix treatment. For the propagation of light waves, we present numerical results that show that the quasiperiodicity associated with a mirror symmetry greatly increases the intensity of transmission and the transmission spectra exhibit a pro le self-similar. The return map plotted for this system show that the presence of internal symmetry does not alter the pattern of Fibonacci maps when compared with the case without symmetry. But when comparing the maps of Thue-Morse and double-time sequences with their case without the symmetry mirror, is evident the change in the pro le of the maps. For magnetic multilayers, we work with two di erent systems, multilayer composed of a metamagnetic material and a non-magnetic material, and multilayers composed of two cubic Heisenberg ferromagnets. In the rst case, our calculations are carried out in the magnetostatic regime and calculate the dispersion relation of spin waves for the metamgnetic material considered FeBr2. We show the e ect of mirror symmetry in the spectra of spin waves, and made the analysis of the location of bulk bands and the scaling laws between the full width of the bands allowed and the number of layers of unit cell. Finally, we calculate the transmission spectra of spin waves in quasiperiodic multilayers consisting of Heisenberg ferromagnets. The transmission spectra exhibit self-similar patterns, with regions of scaling well-de ned in frequency and the return maps indicates only dependence of the particular sequence used in the construction of the multilayer

Conhecimento sobre energia eólica: um estudo exploratório a partir das redes semânticas naturais de estudantes da cidade de Natal

The human being has a fundamental role in issues concerning scarcity of energy resources as well as in the success of technologies which favor the use of renewable sources, such as wind energy. But what does wind energy mean for people? What are the psychological meanings concerning this term? Aiming to answer these questions, the general objective of this dissertation was to identify and to analyze the knowledge about wind energy taking into account a network of psychological meanings. One hundred and ninety one (191) university students from Natal-RN participated in the study, being male the majority (53%); aged between 17 and 51 years old (M=23.3 years; SD=5.7). Participants responded to self reports using the Natural Semantic Networks (NSW) technique, as well as to several sociodemographic questions. The results showed a consistent, positive and useful general semantic network. In this semantic network, knowledge about wind energy was represented by words that correspond to the appeal of (pro) environmental stance (e.g., clean and nature), that evinced both the technological aspect (e.g., force) and the economic aspect (e.g., economy). Results from different groups were also analyzed. The first set of groups (non-environemental and environmental) was divided considering the course (e.g., ecology and economy). The second set of groups(non-caretaker and caretaker) was divided based on the practice of environmental care expressed. Subtle differences were observed in the semantic networks of caretakers, who emphasized environment, an attribute not mentioned by non-caretakes. This indicates a construction of knowledge that is influenced by the presence or absence of the environmental commitment. Such findings may be useful in the construction of instruments for surveys and in the development of public and educational policies. Additionally, they may assist the media towards a more objective performance concerning wind energy

Interpretação sísmica e análise de atributos - área do levantamento sísmico 3D de siririzinho (Bacia Sergipe-Alagoas, NE do Brasil)

The main objective of the present thesis was the seismic interpretation and seismic attribute analysis of the 3D seismic data from the Siririzinho high, located in the Sergipe Sub-basin (southern portion of Sergipe-Alagoas Basin). This study has enabled a better understanding of the stratigraphy and structure that the Siririzinho high experienced during its development. In a first analysis, we used two types of filters: the dip-steered median filter, was used to remove random noise and increase the lateral continuity of reflections, and fault-enhancement filter was applied to enhance the reflection discontinuities. After this filtering step similarity and curvature attributes were applied in order to identify and enhance the distribution of faults and fractures. The use of attributes and filtering greatly contributed to the identification and enhancement of continuity of faults. Besides the application of typical attributes (similarity and curvature) neural network and fingerprint techniques were also used, which generate meta-attributes, also aiming to highlight the faults; however, the results were not satisfactory. In a subsequent step, well log and seismic data analysis were performed, which allowed the understanding of the distribution and arrangement of sequences that occur in the Siririzinho high, as well as an understanding of how these units are affected by main structures in the region. The Siririzinho high comprises an elongated structure elongated in the NS direction, capped by four seismo-sequences (informally named, from bottom to top, the sequences I to IV, plus the top of the basement). It was possible to recognize the main NS-oriented faults, which especially affect the sequences I and II, and faults oriented NE-SW, that reach the younger sequences, III and IV. Finally, with the interpretation of seismic horizons corresponding to each of these sequences, it was possible to define a better understanding of geometry, deposition and structural relations in the area.

Análise da incerteza na representação de classes temáticas resultantes da aplicação de uma rede neural artificial

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Integração de Redes GNSS locais ao SIRGAS

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise de séries temporais de coordenadas estimadas com GPS: uma proposta metodológica para eliminação de efeitos sazonais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Um método para detecção e classificação de curtos-circuitos em redes de distribuição de energia elétrica baseado na transformada de Fourier e em redes neurais artificiais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)