32 resultados para Maximum entropy statistical estimate

em Instituto Politécnico do Porto, Portugal


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Catastrophic events, such as wars and terrorist attacks, tornadoes and hurricanes, earthquakes, tsunamis, floods and landslides, are always accompanied by a large number of casualties. The size distribution of these casualties has separately been shown to follow approximate power law (PL) distributions. In this paper, we analyze the statistical distributions of the number of victims of catastrophic phenomena, in particular, terrorism, and find double PL behavior. This means that the data sets are better approximated by two PLs instead of a single one. We plot the PL parameters, corresponding to several events, and observe an interesting pattern in the charts, where the lines that connect each pair of points defining the double PLs are almost parallel to each other. A complementary data analysis is performed by means of the computation of the entropy. The results reveal relationships hidden in the data that may trigger a future comprehensive explanation of this type of phenomena.

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This paper studies the statistical distributions of worldwide earthquakes from year 1963 up to year 2012. A Cartesian grid, dividing Earth into geographic regions, is considered. Entropy and the Jensen–Shannon divergence are used to analyze and compare real-world data. Hierarchical clustering and multi-dimensional scaling techniques are adopted for data visualization. Entropy-based indices have the advantage of leading to a single parameter expressing the relationships between the seismic data. Classical and generalized (fractional) entropy and Jensen–Shannon divergence are tested. The generalized measures lead to a clear identification of patterns embedded in the data and contribute to better understand earthquake distributions.

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In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

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In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

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Deoxyribonucleic acid, or DNA, is the most fundamental aspect of life but present day scientific knowledge has merely scratched the surface of the problem posed by its decoding. While experimental methods provide insightful clues, the adoption of analysis tools supported by the formalism of mathematics will lead to a systematic and solid build-up of knowledge. This paper studies human DNA from the perspective of system dynamics. By associating entropy and the Fourier transform, several global properties of the code are revealed. The fractional order characteristics emerge as a natural consequence of the information content. These properties constitute a small piece of scientific knowledge that will support further efforts towards the final aim of establishing a comprehensive theory of the phenomena involved in life.

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In smart grids context, the distributed generation units based in renewable resources, play an important rule. The photovoltaic solar units are a technology in evolution and their prices decrease significantly in recent years due to the high penetration of this technology in the low voltage and medium voltage networks supported by governmental policies and incentives. This paper proposes a methodology to determine the maximum penetration of photovoltaic units in a distribution network. The paper presents a case study, with four different scenarios, that considers a 32-bus medium voltage distribution network and the inclusion storage units.

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This paper analyzes DNA information using entropy and phase plane concepts. First, the DNA code is converted into a numerical format by means of histograms that capture DNA sequence length ranging from one up to ten bases. This strategy measures dynamical evolutions from 4 up to 410 signal states. The resulting histograms are analyzed using three distinct entropy formulations namely the Shannon, Rényie and Tsallis definitions. Charts of entropy versus sequence length are applied to a set of twenty four species, characterizing 486 chromosomes. The information is synthesized and visualized by adapting phase plane concepts leading to a categorical representation of chromosomes and species.

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Introdução: Os pontos gatilho (PG) do esternocleidomastóideo (ECM) podem ser a causa de dor na face e no crânio. A técnica músculo-energia (TME) pode ser utilizada na presença de PG. Objectivo: Verificar qual o efeito imediato da TME, aplicada no ECM, na sensibilidade dolorosa à pressão (SDP) do PG do ECM e nas amplitudes cervicais em comparação com uma técnica placebo. Metodologia: Uma amostra voluntária de 52 indivíduos foi dividida aleatoriamente por dois grupos. Inicialmente foi medida a SDP e as amplitudes dos movimentos activos da coluna cervical. Após a aplicação da TME, com 20% da força máxima, e da técnica placebo, nos respectivos grupos, a SDP e as amplitudes cervicais foram reavaliadas. Resultados: Não existiram diferenças estatísticas significativas para afirmar que os dados recolhidos antes e depois da aplicação da TME eram significativamente diferentes. Conclusão: Os efeitos imediatos da TME, neste estudo, não foram significativos. No entanto, a bibliografia aponta noutro sentido, tornando-se importante perceber de que forma podemos melhorar a aplicação da TME, de forma a optimizar os seus efeitos.

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This research work has been focused in the study of gallinaceous feathers, a waste that may be valorised as sorbent, to remove the Dark Blue Astrazon 2RN (DBA) from Dystar. This study was focused on the following aspects: optimization of experimental conditions through factorial design methodology, kinetic studies into a continuous stirred tank adsorber (at pH 7 and 20ºC), equilibrium isotherms (at pH 5, 7 and 9 at 20 and 45ºC) and column studies (at 20ºC, at pH 5, 7 and 9). In order to evaluate the influence of the presence of other components in the sorption of the dyestuff, all experiments were performed both for the dyestuff in aqueous solution and in real textile effluent. The pseudo-first and pseudo-second order kinetic models were fitted to the experimental data, being the latter the best fit for the aqueous solution of dyestuff. For the real effluent both models fit the experimental results and there is no statistical difference between them. The Central Composite Design (CCD) was used to evaluate the effects of temperature (15 - 45ºC) and pH (5 - 9) over the sorption in aqueous solution. The influence of pH was more significant than temperature. The optimal conditions selected were 45ºC and pH 9. Both Langmuir and Freundlich models could fit the equilibrium data. In the concentration range studied, the highest sorbent capacity was obtained for the optimal conditions in aqueous solution, which corresponds to a maximum capacity of 47± 4 mg g-1. The Yoon-Nelson, Thomas and Yan’s models fitted well the column experimental data. The highest breakthrough time for 50% removal, 170 min, was obtained at pH 9 in aqueous solution. The presence of the dyeing agents in the real wastewater decreased the sorption of the dyestuff mostly for pH 9, which is the optimal pH. The effect of pH is less pronounced in the real effluent than in aqueous solution. This work shows that feathers can be used as sorbent in the treatment of textile wastewaters containing DBA.

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Hoje em dia, a prevenção dos resíduos de metais é uma questão muito importante para um grande número de empresas, pois necessitam optimizar o seu sistema de tratamento de águas residuais a fim de alcançarem os limites legais dos teores em iões metálicos e poderem efectuar a descarga das águas residuais no domínio hídrico público. Devido a esta problemática foram efectuados estudos inovadores relacionados com a remoção de iões metálicos de águas residuais, verificando-se que as tecnologias de membrana oferecem uma série de vantagens para o efeito. Uma dessas tecnologias, referida como Membrana Líquida de Suporte (SLM), é baseada num mecanismo de extracção. A membrana hidrofóbica, impregnada com uma solução extractora, funciona como barreira entre a água residual e uma solução, geralmente ácida. A diferença de pH entre a água residual e a solução actua como força motriz para o transporte de iões metálicos da água residual para a referida solução. Poderá ocorrer um problema de falta de estabilidade, resultante da possível fuga da solução extractora para fora dos poros das membranas. Estudos anteriores mostraram que os ácidos alquilfosfóricos ou ácidos fosfónicos, como os reagentes D2EHPA e CYANEX e hidroxioximas como o LIX 860-I podem ser muito úteis para a extração de iões metálicos como ferro, cobre, níquel, zinco e outros. A clássica extracção líquido-líquido também tem mostrado que a mistura de diferentes extractores pode ter um efeito sinergético. No entanto, não é claro que haja um efeito óptimo da razão de extractor ou que tipo de complexo é formado durante o processo de extracção. O objectivo deste projecto é investigar este comportamento sinergético e as complexas formações por meio de um método espectrofotométrico, o “Job’s method” e “Mole-ratio method”. Estes métodos são utilizados para estimar a estequiometria dos vários complexos entre dois solutos, a partir da variação de absorvância dos complexos quando comparado com a absorvância do soluto. Com este projecto, o Job’s method e mole-ratio method serão aplicados a um sistema de três componentes, para conseguir mais informações sobre a complexação de níquel (II) e a fim de determinar a razão extractor: metal dos complexos formados durante a aplicação de mistura de extractores D2EHPA e LIX 860-I. Segundo Job’s method a elavada absorvância situa-se na região de 0,015-0,040 M de LIX 860-I e uma baixa concentração de D2EHPA. Quando as diferentes experiências são encontradas num conjunto experimental foram avaliadas de acordo com o método de trabalho, o valor máximo do gráfico foi encontrado para uma baixa fração molar do ião metálico e uma maior concentração de D2EHPA. Esta mudança foi encontrado de 0,50 até 0,30, que poderia apontar para a direção da formação de diferentes complexos. Para o Mole-Ratio method, a estequiometria dos complexos metal pode ser determinada a partir do ponto de intersecção das linhas tangente do gráfico da absorbância versus a concentração do ligante. Em todos os casos, o máximo foi obtido em torno de uma concentração total de 0,010 M. Quando D2EHPA foi aplicado sozinho, absorvâncias muito baixos foram obtidas.

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O desenvolvimento de sistemas de localização pedestre com recurso a técnicas de dead reckoning tem mostrado ser uma área em expansão no mundo académico e não só. Existem algumas soluções criadas, no entanto, nem todas as soluções serão facilmente implementadas no mercado, quer seja pelo hardware caro, ou pelo sistema em si, que é desenvolvido tendo em conta um cenário em particular. INPERLYS é um sistema que visa apresentar uma solução de localização pedestre, independentemente do cenário, utilizando recursos que poderão ser facilmente usados. Trata-se de um sistema que utiliza uma técnica de dead reckonig para dar a localização do utilizador. Em cenários outdoor, um receptor GPS fornece a posição do utilizador, fornecendo uma posição absoluta ao sistema. Quando não é possível utilizar o GPS, recorre-se a um sensor MEMS e a uma bússola para se obter posições relativas à última posição válida do GPS. Para interligar todos os sensores foi utilizado o protocolo de comunicações sem fios ZigBee™. A escolha recaiu neste protocolo devido a factores como os seus baixos consumos e o seu baixo custo. Assim o sistema torna-se de uso fácil e confortável para o utilizador, ao contrário de sistemas similares desenvolvidos, que utilizam cabos para interligarem os diferentes componentes do sistema. O sensor MEMS do tipo acelerómetro tem a função de ler a aceleração horizontal, ao nível do pé. Esta aceleração será usada por um algoritmo de reconhecimento do padrão das acelerações para se detectar os passos dados. Após a detecção do passo, a aceleração máxima registada nesse passo é fornecida ao coordenador, para se obter o deslocamento efectuado. Foram efectuados alguns testes para se perceber a eficiência do INPERLYS. Os testes decorreram num percurso plano, efectuados a uma velocidade normal e com passadas normais. Verificou-se que, neste momento, o desempenho do sistema poderá ser melhorado, quer seja a nível de gestão das comunicações, quer a nível do reconhecimento do padrão da aceleração horizontal, essencial para se detectar os passos. No entanto o sistema é capaz de fornecer a posição através do GPS, quando é possível a sua utilização, e é capaz de fornecer a orientação do movimento.

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The mechanisms of speech production are complex and have been raising attention from researchers of both medical and computer vision fields. In the speech production mechanism, the articulator’s study is a complex issue, since they have a high level of freedom along this process, namely the tongue, which instigates a problem in its control and observation. In this work it is automatically characterized the tongues shape during the articulation of the oral vowels of Portuguese European by using statistical modeling on MR-images. A point distribution model is built from a set of images collected during artificially sustained articulations of Portuguese European sounds, which can extract the main characteristics of the motion of the tongue. The model built in this work allows under standing more clearly the dynamic speech events involved during sustained articulations. The tongue shape model built can also be useful for speech rehabilitation purposes, specifically to recognize the compensatory movements of the articulators during speech production.

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Multi-objective particle swarm optimization (MOPSO) is a search algorithm based on social behavior. Most of the existing multi-objective particle swarm optimization schemes are based on Pareto optimality and aim to obtain a representative non-dominated Pareto front for a given problem. Several approaches have been proposed to study the convergence and performance of the algorithm, particularly by accessing the final results. In the present paper, a different approach is proposed, by using Shannon entropy to analyzethe MOPSO dynamics along the algorithm execution. The results indicate that Shannon entropy can be used as an indicator of diversity and convergence for MOPSO problems.

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We report the results of the growth of Cu-Sn-S ternary chalcogenide compounds by sulfurization of dc magnetron sputtered metallic precursors. Tetragonal Cu2SnS3 forms for a maximum sulfurization temperature of 350 ºC. Cubic Cu2SnS3 is obtained at sulfurization temperatures above 400 ºC. These results are supported by XRD analysis and Raman spectroscopy measurements. The latter analysis shows peaks at 336 cm-1, 351 cm-1 for tetragonal Cu2SnS3, and 303 cm-1, 355 cm-1 for cubic Cu2SnS3. Optical analysis shows that this phase change lowers the band gap from 1.35 eV to 0.98 eV. At higher sulfurization temperatures increased loss of Sn is expected in the sulphide form. As a consequence, higher Cu content ternary compounds like Cu3SnS4 grow. In these conditions, XRD and Raman analysis only detected orthorhombic (Pmn21) phase (petrukite). This compound has Raman peaks at 318 cm-1, 348 cm-1 and 295 cm-1. For a sulfurization temperature of 450 ºC the samples present a multi-phase structure mainly composed by cubic Cu2SnS3 and orthorhombic (Pmn21) Cu3SnS4. For higher temperatures, the samples are single phase and constituted by orthorhombic (Pmn21) Cu3SnS4. Transmittance and reflectance measurements were used to estimate a band gap of 1.60 eV. For comparison we also include the results for Cu2ZnSnS4 obtained using similar growth conditions.

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Modern real-time systems, with a more flexible and adaptive nature, demand approaches for timeliness evaluation based on probabilistic measures of meeting deadlines. In this context, simulation can emerge as an adequate solution to understand and analyze the timing behaviour of actual systems. However, care must be taken with the obtained outputs under the penalty of obtaining results with lack of credibility. Particularly important is to consider that we are more interested in values from the tail of a probability distribution (near worst-case probabilities), instead of deriving confidence on mean values. We approach this subject by considering the random nature of simulation output data. We will start by discussing well known approaches for estimating distributions out of simulation output, and the confidence which can be applied to its mean values. This is the basis for a discussion on the applicability of such approaches to derive confidence on the tail of distributions, where the worst-case is expected to be.