907 resultados para power law model
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This paper presents a case-study of a PMU application with PSS support in a real large scale Chinese power system to suppress inter-area oscillations. The paper uses PMU measured feedback signals from a PSS input signal for dynamic torque analysis (DTA). In the paper, a mathematical model of multi-machine power system is described, followed by formation of the residue and DTA indices. Simulations of the model are used with a large-scale power system model to demonstrate the role of PSS and the equivalence of DTA residue indices.
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It is acknowledged that wind power is a stochastic energy source compared to hydroelectric generation which is easily scheduled. In this paper a scheme for coordinating wind power plant and hydroelectric power plant is presented by using PMUs to measure and control the state of wind and hydro power plants. Hydroelectric generation is proposed as a method of energy reserve and compensation in the context of wind power fluctuation in order to avoid full or partial curtailment of wind generation to benefit wind providers. The feasibility of this proposed scheme is investigated by power flow calculation and stability analysis using the IEEE 30-bus power system model.
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We investigate the basic behavior and performance of simulated quantum annealing (QA) in comparison with classical annealing (CA). Three simple one-dimensional case study systems are considered: namely, a parabolic well, a double well, and a curved washboard. The time-dependent Schrodinger evolution in either real or imaginary time describing QA is contrasted with the Fokker-Planck evolution of CA. The asymptotic decrease of excess energy with annealing time is studied in each case, and the reasons for differences are examined and discussed. The Huse-Fisher classical power law of double-well CA is replaced with a different power law in QA. The multiwell washboard problem studied in CA by Shinomoto and Kabashima and leading classically to a logarithmic annealing even in the absence of disorder turns to a power-law behavior when annealed with QA. The crucial role of disorder and localization is briefly discussed.
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In this paper, we investigate secure device-to-device (D2D) communication in energy harvesting large-scale cognitive cellular networks. The energy constrained D2D transmitter harvests energy from multi-antenna equipped power beacons (PBs), and communicates with the corresponding receiver using the spectrum of the cellular base stations (BSs). We introduce a power transfer model and an information signal model to enable wireless energy harvesting and secure information transmission. In the power transfer model, we propose a new power transfer policy, namely, best power beacon (BPB) power transfer. To characterize the power transfer reliability of the proposed policy, we derive new closed-form expressions for the exact power outage probability and the asymptotic power outage probability with large antenna arrays at PBs. In the information signal model, we present a new comparative framework with two receiver selection schemes: 1) best receiver selection (BRS), and 2) nearest receiver selection (NRS). To assess the secrecy performance, we derive new expressions for the secrecy throughput considering the two receiver selection schemes using the BPB power transfer policies. We show that secrecy performance improves with increasing densities of PBs and D2D receivers because of a larger multiuser diversity gain. A pivotal conclusion is reached that BRS achieves better secrecy performance than NRS but demands more instantaneous feedback and overhead.
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Responses by marine species to ocean acidification (OA) have recently been shown to be modulated by external factors including temperature, food supply and salinity. However the role of a fundamental biological parameter relevant to all organisms, that of body size, in governing responses to multiple stressors has been almost entirely overlooked. Recent consensus suggests allometric scaling of metabolism with body size differs between species, the commonly cited 'universal' mass scaling exponent (b) of A3/4 representing an average of exponents that naturally vary. One model, the Metabolic-Level Boundaries hypothesis, provides a testable prediction: that b will decrease within species under increasing temperature. However, no previous studies have examined how metabolic scaling may be directly affected by OA. We acclimated a wide body-mass range of three common NE Atlantic echinoderms (the sea star Asterias rubens, the brittlestars Ophiothrix fragilis and Amphiura filiformis) to two levels of pCO(2) and three temperatures, and metabolic rates were determined using closed-chamber respirometry. The results show that contrary to some models these echinoderm species possess a notable degree of stability in metabolic scaling under different abiotic conditions; the mass scaling exponent (b) varied in value between species, but not within species under different conditions. Additionally, we found no effect of OA on metabolic rates in any species. These data suggest responses to abiotic stressors are not modulated by body size in these species, as reflected in the stability of the metabolic scaling relationship. Such equivalence in response across ontogenetic size ranges has important implications for the stability of ecological food webs.
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This study examines the firm size distribution of US banks and credit unions. A truncated lognormal distribution describes the size distribution, measured using assets data, of a large population of small, community-based commercial banks. The size distribution of a smaller but increasingly dominant cohort of large banks, which operate a high-volume low-cost retail banking model, exhibits power-law behaviour. There is a progressive increase in skewness over time, and Zipf’s Law is rejected as a descriptor of the size distribution in the upper tail. By contrast, the asset size distribution of the population of credit unions conforms closely to the lognormal distribution.
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The dynamics of predator-prey pursuit appears complex, making the development of a framework explaining predator and prey strategies problematic. We develop a model for terrestrial, cursorial predators to examine how animal mass modulates predator and prey trajectories and affects best strategies for both parties. We incorporated the maximum speed-mass relationship with an explanation of why larger animals should have greater turn radii; the forces needed to turn scale linearly with mass whereas the maximum forces an animal can exert scale to a 2/3 power law. This clarifies why in a meta-analysis, we found a preponderance of predator/prey mass ratios that minimized the turn radii of predators compared to their prey. It also explained why acceleration data from wild cheetahs pursuing different prey showed different cornering behaviour with prey type. The outcome of predator prey pursuits thus depends critically on mass effects and the ability of animals to time turns precisely.
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By testing a simple asset pricing model of heterogeneous agents to characterize the power-law behavior of the DAX 30 from 1975 to 2007, we provide supporting evidence on empirical findings that investors and fund managers use combinations of fixed and switching strategies based on fundamental and technical analysis when making investment decisions. By conducting econometric analysis via Monte Carlo simulations, we show that the autocorrelation patterns, the estimates of the power-law decay indices, (FI)GARCH parameters, and tail index of the model match closely the corresponding estimates for the DAX 30. A mechanism analysis based on the calibrated model provides further insights into the explanatory power of heterogeneous agent models.
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Nas últimas décadas, um grande número de processos têm sido descritos em termos de redes complexas. A teoria de redes complexas vem sendo utilizada com sucesso para descrever, modelar e caracterizar sistemas naturais, artificias e sociais, tais como ecossistemas, interações entre proteínas, a Internet, WWW, até mesmo as relações interpessoais na sociedade. Nesta tese de doutoramento apresentamos alguns modelos de agentes interagentes em redes complexas. Inicialmente, apresentamos uma breve introdução histórica (Capítulo 1), seguida de algumas noções básicas sobre redes complexas (Capítulo 2) e de alguns trabalhos e modelos mais relevantes a esta tese de doutoramento (Capítulo 3). Apresentamos, no Capítulo 4, o estudo de um modelo de dinâmica de opiniões, onde busca-se o consenso entre os agentes em uma população, seguido do estudo da evolução de agentes interagentes em um processo de ramificação espacialmente definido (Capítulo 5). No Capítulo 6 apresentamos um modelo de otimização de fluxos em rede e um estudo do surgimento de redes livres de escala a partir de um processo de otimização . Finalmente, no Capítulo 7, apresentamos nossas conclusões e perspectivas futuras.
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O trabalho apresentado tem por objetivo contribuir para a valorização da borracha proveniente de pneus em fim de vida, assente em princípios de sustentabilidade ambiental. A abordagem adotada para a concretização deste objetivo consiste na incorporação de borracha de pneus em formulações de base termoplástica e elastomérica (TPE), adequadas ao processo de moldação por injeção. São desenvolvidos estudos sobre a morfologia, propriedades mecânicas, térmicas e reológicas das ligas poliméricas à base de granulado de borracha de pneu (GTR). A falta de adesão entre o GTR e a matriz polimérica leva à degradação das propriedades mecânicas dos materiais obtidos. A estratégia explorada passa pela utilização de um elastómero para promover o encapsulamento do GTR e, desta forma, procurar obter ligas com propriedades mecânicas características de um TPE. São analisadas ligas ternárias (TPEGTR) compostas por polipropileno (PP) de elevada fluidez, GTR e elastómero virgem. O efeito da presença de diferentes elastómeros nas ligas é analisado neste trabalho: um elastómero de etilenopropileno- dieno (EPDM), e um novo elastómero de etileno-propileno (EPR) obtido por catálise metalocénica. O estudo da morfologia das ligas obtidas mostra haver interação entre os materiais, sendo possível inferir a viabilidade da estratégia adotada para promover a adesão do GTR. A incorporação de elastómero promove o aumento da resistência ao impacto e da extensão na rotura nas ligas, o que é atribuído, fundamentalmente, ao encapsulamento do GTR e ao aumento da tenacidade da matriz termoplástica. Com o objetivo de avaliar a influência da estrutura cristalina das ligas TPEGTR no seu comportamento mecânico, procede-se à análise do processo de cristalização sob condições isotérmicas e não isotérmicas. Neste estudo, é avaliado o efeito da presença dos materiais que constituem a fase elastomérica na cinética de cristalização. Para cada uma das ligas desenvolvidas, recorre-se ao modelo de Avrami para avaliar o efeito da temperatura no mecanismo de nucleação, na morfologia das estruturas cristalinas e na taxa de cristalização. Recorre-se à reometria capilar para estudar, sob condições estacionárias, o comportamento reológico das ligas TPEGTR. O modelo de Cross-WLF é utilizado para avaliar o comportamento reológico de todos os materiais, obtendo-se resultados similares àqueles obtidos experimentalmente. O comportamento reológico dos polímeros PP, EPR e EPDM é do tipo reofluidificante, tendo o EPR um comportamento reológico similar ao do PP e o EPDM um comportamento reo-fluidificante mais pronunciado. Em todas as ligas analisadas o comportamento reológico revela-se do tipo reo-fluidificante, sendo que a presença de GTR promove o aumento da viscosidade. Os parâmetros obtidos do modelo de Cross-WLF são utilizados para realizar a simulação da etapa de injeção recorrendo a um software comercial. Os resultados obtidos são validados experimentalmente pelo processo de moldação por injeção, evidenciando uma boa adequabilidade da aplicação deste modelo a estas ligas. O trabalho desenvolvido sobre ligas TPEGTR, constitui um contributo para a valorização da borracha proveniente de pneus em fim de vida, assente em princípios de sustentabilidade ambiental.
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Tese de doutoramento, Geografia (Geografia Física), Universidade de Lisboa, Instituto de Geografia e Ordenamento do Território, 2015
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Proteins are biochemical entities consisting of one or more blocks typically folded in a 3D pattern. Each block (a polypeptide) is a single linear sequence of amino acids that are biochemically bonded together. The amino acid sequence in a protein is defined by the sequence of a gene or several genes encoded in the DNA-based genetic code. This genetic code typically uses twenty amino acids, but in certain organisms the genetic code can also include two other amino acids. After linking the amino acids during protein synthesis, each amino acid becomes a residue in a protein, which is then chemically modified, ultimately changing and defining the protein function. In this study, the authors analyze the amino acid sequence using alignment-free methods, aiming to identify structural patterns in sets of proteins and in the proteome, without any other previous assumptions. The paper starts by analyzing amino acid sequence data by means of histograms using fixed length amino acid words (tuples). After creating the initial relative frequency histograms, they are transformed and processed in order to generate quantitative results for information extraction and graphical visualization. Selected samples from two reference datasets are used, and results reveal that the proposed method is able to generate relevant outputs in accordance with current scientific knowledge in domains like protein sequence/proteome analysis.
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This manuscript analyses the data generated by a Zero Length Column (ZLC) diffusion experimental set-up, for 1,3 Di-isopropyl benzene in a 100% alumina matrix with variable particle size. The time evolution of the phenomena resembles those of fractional order systems, namely those with a fast initial transient followed by long and slow tails. The experimental measurements are best fitted with the Harris model revealing a power law behavior.
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Power law (PL) distributions have been largely reported in the modeling of distinct real phenomena and have been associated with fractal structures and self-similar systems. In this paper, we analyze real data that follows a PL and a double PL behavior and verify the relation between the PL coefficient and the capacity dimension of known fractals. It is to be proved a method that translates PLs coefficients into capacity dimension of fractals of any real data.
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Power law (PL) distributions have been largely reported in the modeling of distinct real phenomena and have been associated with fractal structures and self-similar systems. In this paper, we analyze real data that follows a PL and a double PL behavior and verify the relation between the PL coefficient and the capacity dimension of known fractals. It is to be proved a method that translates PLs coefficients into capacity dimension of fractals of any real data.