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In the last few years, large-scale experiments have generated genome-wide protein interaction networks for many organisms including Saccharomyces cerevisiae (baker's yeast), Caenorhabditis elegans (worm) and Drosophila melanogaster (fruit fly). In this thesis, we examine the vertex and edge betweenness centrality measures of these graphs. These measures capture how "central" a vertex or an edge is in the graph by considering the fraction of shortest paths that pass through that vertex or edge. Our primary observation is that the distribution of the vertex betweenness centrality follows a power law, but the distribution of the edge betweenness centrality has a Poisson-like distribution with a very sharp spike. To investigate this phenomenon, we generated random networks with degree distribution identical to those of the protein interaction networks. To our surprise, we found out that the random networks and the protein interaction networks had almost identical distribution of edge betweenness. We conjecture that the "Poisson-like" distribution of the edge betweenness centrality is the property of any graph whose degree distribution satisfies power law. / Master of Science

Power Laws são leis estatísticas que permeiam os mais variados campos do conhecimento humano tais como Biologia, Sociologia, Geografia, Linguística, Astronomia, entre outros, e que têm como característica mais importante a disparidade entre os elementos causadores, ou seja, alguns poucos elementos são responsáveis pela grande maioria dos efeitos. Exemplos famosos são o Princípio de Pareto, a Lei de Zipf e o modelo de Incêndios Florestais. O Princípio de Pareto diz que 80% da riqueza de uma nação está nas mãos de apenas 20% da população; em outras palavras, uma relação causa e efeito chamada 80-20. A Lei de Zipf enuncia que o comportamento da frequência versus o ranking de ocorrência é dado por uma curva hiperbólica com um comportamento semelhante a 1/x. O modelo de Incêndios Florestais modela o comportamento do crescimento de árvores em uma floresta entre sucessivas queimadas que causam destruição de agrupamentos de árvores. As Power Laws demonstram que uma porcentagem pequena de uma distribuição tem uma alta frequência de ocorrência, enquanto o restante dos casos que aparecem tem uma frequência baixa, o que levaria a uma reta decrescente em uma escala logarítmica. A partir de simulações utilizando o conjunto de benchmarks SPEC-CPU2000, este estudo procura investigar como essas leis estatísticas podem ser utilizadas para entender e melhorar o desempenho de caches baseados em diferentes políticas de substituição de linhas de cache. O estudo sobre a possibilidade de uma nova política de substituição composta por um cache Pareto, bem como um novo mecanismo de chaveamento do comportamento de algoritmos adaptativos de substituição de linhas de cache, chamado de Forest Fire Switching Mechanism, ambos baseados em Power Laws, são propostos a fim de se obter ganhos de desempenho na execução de aplicações. / Power Laws are statistical laws that permeate the most varied fields of human knowledge such as Biology, Sociology, Geography, Linguistics, Astronomy, among others, and have as most important characteristic the disparity between the cause events, in other words, some few elements are responsible for most of the effects. Famous examples are the Pareto Principle, the Zipfs Law and the Forest Fire model. The Pareto Principle says that 80% of a nations wealth is in the hands of just 20% of the population; in other words, a cause and effect relationship called 80-20. Zipf\'s Law states that the behavior of frequency versus ranking of occurrence is given by a hyperbolic curve with a behavior similar to 1/x. The Forest Fire model represents the behavior of trees growing in a forest between successive fires that cause the destruction of clusters of trees. The Power Laws demonstrate that a small percentage of a distribution has a high frequency of occurrence, while the rest of the cases that appear have a low frequency, which would take to a decreasing line in a logarithmic scale. Based on simulations using the SPEC-CPU2000 benchmarks, this work seeks to investigate how these distributions can be used in order to understand and improve the performance of caches based on different cache line replacement policies. The study about the possibility of a new replacement policy composed by a Pareto cache, and a new switching mechanism of the behavior of cache line replacement adaptive algorithms, called Forest Fire Switching Mechanism, both based on Power Laws, are proposed in order to obtain performance gains on the execution of applications.

Power Laws são leis estatísticas que permeiam os mais variados campos do conhecimento humano tais como Biologia, Sociologia, Geografia, Linguística, Astronomia, entre outros, e que têm como característica mais importante a disparidade entre os elementos causadores, ou seja, alguns poucos elementos são responsáveis pela grande maioria dos efeitos. Exemplos famosos são o Princípio de Pareto, a Lei de Zipf e o modelo de Incêndios Florestais. O Princípio de Pareto diz que 80% da riqueza de uma nação está nas mãos de apenas 20% da população; em outras palavras, uma relação causa e efeito chamada 80-20. A Lei de Zipf enuncia que o comportamento da frequência versus o ranking de ocorrência é dado por uma curva hiperbólica com um comportamento semelhante a 1/x. O modelo de Incêndios Florestais modela o comportamento do crescimento de árvores em uma floresta entre sucessivas queimadas que causam destruição de agrupamentos de árvores. As Power Laws demonstram que uma porcentagem pequena de uma distribuição tem uma alta frequência de ocorrência, enquanto o restante dos casos que aparecem tem uma frequência baixa, o que levaria a uma reta decrescente em uma escala logarítmica. A partir de simulações utilizando o conjunto de benchmarks SPEC-CPU2000, este estudo procura investigar como essas leis estatísticas podem ser utilizadas para entender e melhorar o desempenho de caches baseados em diferentes políticas de substituição de linhas de cache. O estudo sobre a possibilidade de uma nova política de substituição composta por um cache Pareto, bem como um novo mecanismo de chaveamento do comportamento de algoritmos adaptativos de substituição de linhas de cache, chamado de Forest Fire Switching Mechanism, ambos baseados em Power Laws, são propostos a fim de se obter ganhos de desempenho na execução de aplicações. / Power Laws are statistical laws that permeate the most varied fields of human knowledge such as Biology, Sociology, Geography, Linguistics, Astronomy, among others, and have as most important characteristic the disparity between the cause events, in other words, some few elements are responsible for most of the effects. Famous examples are the Pareto Principle, the Zipfs Law and the Forest Fire model. The Pareto Principle says that 80% of a nations wealth is in the hands of just 20% of the population; in other words, a cause and effect relationship called 80-20. Zipf\'s Law states that the behavior of frequency versus ranking of occurrence is given by a hyperbolic curve with a behavior similar to 1/x. The Forest Fire model represents the behavior of trees growing in a forest between successive fires that cause the destruction of clusters of trees. The Power Laws demonstrate that a small percentage of a distribution has a high frequency of occurrence, while the rest of the cases that appear have a low frequency, which would take to a decreasing line in a logarithmic scale. Based on simulations using the SPEC-CPU2000 benchmarks, this work seeks to investigate how these distributions can be used in order to understand and improve the performance of caches based on different cache line replacement policies. The study about the possibility of a new replacement policy composed by a Pareto cache, and a new switching mechanism of the behavior of cache line replacement adaptive algorithms, called Forest Fire Switching Mechanism, both based on Power Laws, are proposed in order to obtain performance gains on the execution of applications.

Earthquakes are amongst the most destructive of natural phenomena and have been the subject of significant research effort over many decades, to predict the onset of seismic events. Electromagnetic emissions detected prior to earthquakes provide a potential data source for seismic predictions and research suggests that specific pre-seismic electromagnetic activity can be directly related to specific earthquakes although it is still an open issue as to the precise links between these electromagnetic emissions and subsequent earthquakes. In this research, findings of the long memory or the self-organization of several pre-earthquake MHz electromagnetic time-series provide significant outcomes regarding the earthquake prediction. It is also recognised that enhanced radon gas emission has an equally long history as being associated with seismic activity. In general, several anomalous soil radon emissions have been observed prior to earthquakes and this has been recorded all over the world. The abnormal soil radon exhalation from the interior of the earth has been associated with earthquakes and is considered as an important field of research. The research reported in this thesis compared and contrasted the merits of combining electromagnetic emission data and radon exhalation data as precursors of earthquakes with the aim of enhancing earthquake prediction methodology. The findings from the long-memory analysis of radon disturbances in the soil indicated a very significant issue: the radon disturbances in the soil prior to earthquakes exhibit similar behaviour as the MHz RF disturbances of general failure. So, the radon precursors and the MHz electromagnetic correspond to the same pre-earthquake phase. Geological explanations were proposed in view of the asperity model. Persistent and anti-persistent MHz anomalies were due to the micro-cracking of the heterogeneous medium of the earth's crust which may have led the system's evolution towards the global failure. Fractal methods have been used on historical data, to investigate MHz electromagnetic time-series spectra on emissions preceding major earthquakes over the period 2007 to 2014 and the characteristics of enhanced radon emissions have been studied over the period 2008 to 2015 for seismic events occurring in the Aegean Region. It has been found that both the electromagnetic emissions and the radon exhalation data exhibit similar fractal behaviour and are associated with impending seismic activity. Hence both phenomena are relevant to earthquake predictions and should both be employed in any systematic approach to this problem as the varying geological and geographic conditions under which earthquakes can occur, might preclude one or other data from being measurable. According to the several techniques applied in this thesis, all should be employed in sequential steps, albeit the power-law spectral fractal analysis is the most significant to trace long-memory patterns of 1/f processes as those of the processes of earthquakes.

Submitted by Maicon Juliano Schmidt (maicons) on 2015-07-13T19:17:40Z No. of bitstreams: 1 Eduardo Schnurr Siqueira.pdf: 1543388 bytes, checksum: 203a2765367b043538126c29889d7be5 (MD5) / Made available in DSpace on 2015-07-13T19:17:40Z (GMT). No. of bitstreams: 1 Eduardo Schnurr Siqueira.pdf: 1543388 bytes, checksum: 203a2765367b043538126c29889d7be5 (MD5) Previous issue date: 2013-01-31 / Nenhuma / Fluidos não-Newtonianos apresentam relação não linear entre a tensão de cisalhamento e a taxa de cisalhamento, ou seja, sua viscosidade não é constante. Eles estão presentes na natureza (sangue, lamas, areia movediça), assim como em muitos produtos industriais classificam-se nesta categoria, tais como produtos alimentícios (iogurtes, queijos cremosos, doces de frutas, chocolate ), tintas, borrachas, polímeros fundidos, soluções poliméricas, adesivos e gomas. Nos casos em que a viscosidade diminui com aumento da taxa de cisalhamento, os fluidos são classificados como pseudoplásticos; os que apresentam comportamento inverso são classificados como dilatantes. O modelo Power-Law é utilizado em engenharia para modelar ambos os comportamentos. Computational Fluid Dynamics - CFD (Dinâmica dos Fluidos Computacional) é uma ferramenta utilizada na simulação numérica de escoamentos de fluidos Newtonianos e não-Newtonianos. Inúmeros códigos comerciais e livres são utilizados atualmente, dentre eles o código livre e aberto Multiphase Flow with Interphase Exchanges (MFIX), o qual foi desenvolvido visando a simulação numérica de escoamentos multifásicos reativos do tipo sólido-gás em leitos fluidizados. O objetivo do presente trabalho é implementar no MFIX o modelo Power-Law, validar a modificação e realizar um estudo de caso utilizando o modelo. Com a implementação de um modelo não-Newtoniano ao código, pretende-se abrir caminho para a simulação de escoamentos multifásicos do tipo sólido-líquido não-Newtoniano, bem como aumentar a potencialidade do código, a fim de se estudar casos monofásicos de escoamentos de fluidos não-Newtonianos sujeitos à transferência de calor. O modelo implementado foi validado através da comparação com resultados da literatura para o escoamento em uma cavidade. Posteriormente, foram realizadas simulações do escoamento não isotérmico e isotérmico em torno de um prisma de seção quadrada imerso em um canal. Foram variados os parâmetros número de Prandtl, índice do modelo Power-Law e razão de bloqueio. Verificou-se que o número de Nusselt tem influência direta e é fortemente influenciado pela razão de bloqueio e inversamente, com pouca intensidade, pelo índice Power-Law. O número de Prandtl também influenciou diretamente no número de Nusselt e demonstrou que, quanto maior o seu valor, mais acentuada fica a variação do número de Nusselt em função da razão de bloqueio. / Non-Newtonian fluids exhibit nonlinear relationship between the shear stress and the shear rate, that is, its viscosity is not constant. They are present in nature (blood, sludge) as well as many industrial products are classified in this category, such as food products (yoghurt, soft cheeses, jams, chocolate), paints, rubber, polymer melts, polymer solutions, adhesives and gums. In cases where viscosity decreases with increasing shear rate, the fluids are classified as shear-thinning, while the opposite behavior is classified as shear-thickening. The Power-Law model is used in engineering to model both behaviors. Computational Fluid Dynamics - CFD is a tool used in the numerical simulation of Newtonian and non-Newtonian fluid flow. Numerous free and commercial codes are used today, including the free and open source Multiphase Flow with Interphase Exchanges (MFIX), which was developed to the numerical simulation of multiphase (fluid-solid) and reactive flows. The goal of this work is to implement the Power-Law model in MFIX, validate the implementation and conduct a case study using the model implemented. With the implementation of a non-Newtonian model to the code, a new possibility for the simulation of multiphase flows of solid-non-Newtonian liquids is opened, as well as there is an increase in the capability of the code regarding the study of single-phase fluid flows of Non-Newtonian fluids subject to heat transfer. The model was implemented and validated by comparison with literature results for the flow in a lid driven cavity. Subsequently, simulations were carried out concerning isothermal and non-isothermal flows around a square cylinder immersed in a channel. Parameters of analyses consisted of Prandtl number, Power-Law index and blockage ratio, for a fixed Reynolds number. It was found that the Nusselt number is strongly influenced by the blockage ratio and decreases with the increase of the Power-Law index. The Prandtl number also directly influences the process. With its increase, the dependence of the Nusselt number with the blockage ratio is more pronounced.

In this thesis we examine the ability of the log-periodic power law model to accurately predict the end of speculative bubbles on financial markets through modeling of asset price dynamics on a selection of historical bubbles. The methods we use are based on a nonlinear least squares estimation which yields predictions of when the bubble will change regime.We find evidence which support the occurrence of LPPL-patterns leading up to the change in regime; asset prices during bubble periods seem to oscillate around a faster-than-exponential growth. In most cases the estimation yields accurate predictions, although we conclude that the predictions are quite dependent on at which point in time the prediction is conducted. We also find that the end of a speculative bubble seems to be influenced by both endogenous speculative growth and exogenous factors. For this reason we propose a new way of interpreting the predictions of the model, where the end dates should be interpreted as the start of a time period where the asset prices are especially sensitive to exogenous events. We propose that negative news during this time period results in a regime shift of the bubble. This study is the first to address both the possibilities and the limitations of the LPPL-model, and should therefore be considered as a contribution to the academia.

In this thesis we consider graph partition of a particular kind of complex networks referred to as power law graphs. In particular, we focus our analysis on the market graph, constructed from time series of price return on the American stock market. Two different methods originating from clustering analysis in social networks and image segmentation are applied to obtain graph partitions and the results are evaluated in terms of the structure and quality of the partition. Along with the market graph, power law graphs from three different theoretical graph models are considered. This study highlights topological features common in many power law graphs as well as their differences and limitations. Our results show that the market graph possess a clear clustered structure only for higher correlation thresholds. By studying the internal structure of the graph clusters we found that they could serve as an alternative to traditional sector classification of the market. Finally, partitions for different time series was considered to study the dynamics and stability in the partition structure. Even though the results from this part were not conclusive we think this could be an interesting topic for future research. / I denna uppsats studeras graf partition av en typ av komplexa nätverk som kallas power law grafer. Specifikt fokuserar vi på marknadengrafen, konstruerad av tidsserier av aktiepriser på den amerikanska aktiemarknaden. Två olika metoder, initialt utvecklade för klusteranalys i sociala nätverk samt för bildanalys appliceras för att få graf-partitioner och resultaten utvärderas utifrån strukturen och kvaliten på partitionen. Utöver marknadsgrafen studeras aven power law grafer från tre olika teoretiska grafmodeller. Denna studie belyser topologiska egenskaper vanligt förekommande i många power law grafer samt modellerns olikheter och begränsningar. Våra resultat visar att marknadsgrafen endast uppvisar en tydlig klustrad struktur för högre korrelation-trösklar. Genom att studera den interna strukturen hos varje kluster fann vi att kluster kan vara ett alternativ till traditionell marknadsindelning med industriella sektorer. Slutligen studerades partitioner för olika tidsserier för att undersöka dynamiken och stabiliteten i partitionsstrukturen. Trots att resultaten från denna del inte var entydiga tror vi att detta kan vara ett intressant spår för framtida studier.

With the high development of economic and demand for city research, an issue of detecting city boundaries plays an extremely important role in urbanization that promotes the progress of human civilization. Some critical applications such as land use, urban planning and city sprawl have been constantly discussed, which rely on the acquisition of city areas. For the better acquisition of city areas, choosing a proper method to capture city boundaries becomes significant where it greatly improves the value of city study. Although conventional data can be used to define the city boundaries, some drawbacks still exist when measuring the city boundaries in a global scale. Remote sensing (RS) data of nightlight imagery (2010) by Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) acquired from National oceanic and atmospheric administration's National Geoscience Data Center (NOAA/NOGA) is applied to extract the city boundaries in fifty countries, of which these countries are chosen followed by the Gross Domestic Product that are ranked in top 50. In this case, the data distribution of nightlight imagery followed by heavy-tailed distribution. Head/tail break algorithm poses a possibility of calculating reasonable threshold and extracting the natural cities with the help of software based on the Geomatics information system (GIS). An extended study of power law is made by using of power law estimator from previous studies to check whether the extracted natural cities can match the power law distribution. Result shows that combination of the nightlight imagery data and the head/tail break is capable of extracting the city boundaries and a set of possible thresholds with visual inspection by using the head/tail break are executed. There is only one country, namely Belgium, cannot be processed due to its data properties. Result also address how well the natural cities of the fifty countries can be extracted in terms of visual inspection, among the chosen cities, 33 of countries boundaries can be better matched and 13 countries can fundamentally match the city boundaries. Meanwhile, an extended study of power law is provided and four countries have to be found that do not follow the power law distribution. From the result obtained, the study expects that integration of support data will efficiently increase the accuracy of extraction and more useful information can be acquired in further study. On the other hand, a comparative study of threshold decision needs to be verified, put it differently, whether using head/tail break with visual inspection on extracted city boundaries is helpful or not.