Relativistic time effects in financial dynamics

Financial time series have a complex dynamic nature. Many techniques were adopted having in mind standard paradigms of time flow. This paper explores an alternative route involving relativistic effects. It is observed that the measuring perspective influences the results and that we can have different time textures.

Analysis of temperature time-series: embedding dynamics into the MDS method

Global warming and the associated climate changes are being the subject of intensive research due to their major impact on social, economic and health aspects of the human life. Surface temperature time-series characterise Earth as a slow dynamics spatiotemporal system, evidencing long memory behaviour, typical of fractional order systems. Such phenomena are difficult to model and analyse, demanding for alternative approaches. This paper studies the complex correlations between global temperature time-series using the Multidimensional scaling (MDS) approach. MDS provides a graphical representation of the pattern of climatic similarities between regions around the globe. The similarities are quantified through two mathematical indices that correlate the monthly average temperatures observed in meteorological stations, over a given period of time. Furthermore, time dynamics is analysed by performing the MDS analysis over slices sampling the time series. MDS generates maps describing the stations’ locus in the perspective that, if they are perceived to be similar to each other, then they are placed on the map forming clusters. We show that MDS provides an intuitive and useful visual representation of the complex relationships that are present among temperature time-series, which are not perceived on traditional geographic maps. Moreover, MDS avoids sensitivity to the irregular distribution density of the meteorological stations.

Symbolic fractional dynamics

Fractional dynamics reveals long range memory properties of systems described by means of signals represented by real numbers. Alternatively, dynamical systems and signals can adopt a representation where states are quantified using a set of symbols. Such signals occur both in nature and in man made processes and have the potential of a aftermath as relevant as the classical counterpart. This paper explores the association of Fractional calculus and symbolic dynamics. The results are visualized by means of the multidimensional technique and reveal the association between the fractal dimension and one definition of fractional derivative.

Enhanced Race-to-halt: a leakage-aware energy management approach for dynamic priority systems

With progressing CMOS technology miniaturization, the leakage power consumption starts to dominate the dynamic power consumption. The recent technology trends have equipped the modern embedded processors with the several sleep states and reduced their overhead (energy/time) of the sleep transition. The dynamic voltage frequency scaling (DVFS) potential to save energy is diminishing due to efficient (low overhead) sleep states and increased static (leakage) power consumption. The state-of-the-art research on static power reduction at system level is based on assumptions that cannot easily be integrated into practical systems. We propose a novel enhanced race-to-halt approach (ERTH) to reduce the overall system energy consumption. The exhaustive simulations demonstrate the effectiveness of our approach showing an improvement of up to 8 % over an existing work.

Dynamic Analysis and Pattern Visualization of Forest Fires

This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.

Modelação Dinâmica de Sistemas de Drenagem Urbana. Aplicação a um caso de estudo

A crescente expansão urbana e o incremento das exigências ambientais e financeiras promovem a implementação de abordagens sustentáveis para a gestão das infraestruturas sanitárias. Assim, o recurso a instrumentos de monitorização e à modelação matemática surge como o caminho para a racionalização do investimento e a otimização dos sistemas existentes. Neste contexto, a modelação dinâmica de sistemas de drenagem urbana assume relevância para o controlo e redução dos caudais em excesso e das descargas de poluentes nos meios recetores, resultantes de um incremento significativo de afluências pluviais indevidas, de problemas de sub-dimensionamento ou falta de operação e manutenção. O objetivo da presente dissertação consiste na modelação, calibração e diagnóstico do sistema intercetor de Lordelo utilizando o software Storm Water Management Model, através dos dados recolhidos a partir do projeto de Reabilitação dos intercetores de Lordelo, elaborado pela Noraqua. A modelação considera a avaliação das afluências de tempo seco e as afluências pluviais pelo software Sanitary Sewer Overflow Analysis and Planning Toolbox. Com efeito, a simulação dinâmica, permitiu um conhecimento mais detalhado do sistema, avaliando a capacidade hidráulica e localizando os pontos propícios a inundações. Assim, foi possível testar soluções de beneficiação do sistema, englobando a problemática das afluências pluviais indevidas calibradas. Apesar das dificuldades sentidas face à qualidade dos dados existentes, verificou-se que o SSOAP e o SWMM são ferramentas úteis na deteção, diagnóstico e redução dos caudais em excesso e que o procedimento utilizado pode ser aplicado a sistemas semelhantes, como forma de definir a melhor solução técnica e económica ao nível do planeamento, operação e reabilitação do sistema.

Reabilitação do Aeroporto de Ondjiva em Angola

Com o progresso da tecnologia aeronáutica, a deslocação de pessoas e bens tornou-se bastante acessível para variados pontos de mundo, com espaço de tempo muito reduzido. Um dos motores essenciais deste avanço, concernente à mobilidade, é o transporte aéreo e a sua evolução. Este tipo de transporte requer a máxima segurança, sendo que um único acidente pode gerar centenas de vítimas. Atendendo a estas condições, a qualidade dos pavimentos aeroportuários é de grande importância para a segurança da movimentação das aeronaves em solo. Mas, por razões económicas e por vezes de espaço, perspetivas de novas construções perdem viabilidade comparativamente a soluções de reabilitação. A posição geográfica do aeroporto de Ondjiva faz com que seja um importante ponto de passagem entre a África do Sul e a Namíbia e, prevê-se que o número de voos que se efetuam no aeroporto cresça, sendo que o país está numa fase de grande evolução. O presente trabalho visa o conhecimento do processo de dimensionamento para pavimentos aeroportuários e soluções de correção para anomalias que possam apresentar, aplicando-os ao aeroporto de Ondjiva, em Angola. Atualmente, o aeroporto revela um grande desgaste das pistas de táxi, inadaptabilidade das cabeceiras face às cargas estáticas a que são submetidas e, largura insuficiente da pista para a aeronave de projeto, ou aeronave crítica, atendendo ao regulamento da ICAO (International Civil Aviation Organization). Para melhorar o conforto, a segurança e eficiência dos serviços aéreos, o dimensionamento do aeroporto deve obedecer aos princípios e regras da ICAO. Pretende-se também a modelação de uma solução de reforço para o pavimento existente, para que não seja necessário construir um aeroporto de raiz, minimizando custos. Após a realização do dimensionamento, foi estudada a sinalização horizontal e luminosa da pista, para que esteja em conformidade com as suas novas medidas.

Dynamic Analysis and Pattern Visualization of Forest Fires

This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.

State Space Analysis of Forest Fires

This paper studies forest fires from the perspective of dynamical systems. Burnt area, precipitation and atmospheric temperatures are interpreted as state variables of a complex system and the correlations between them are investigated by means of different mathematical tools. First, we use mutual information to reveal potential relationships in the data. Second, we adopt the state space portrait to characterize the system’s behavior. Third, we compare the annual state space curves and we apply clustering and visualization tools to unveil long-range patterns. We use forest fire data for Portugal, covering the years 1980–2003. The territory is divided into two regions (North and South), characterized by different climates and vegetation. The adopted methodology represents a new viewpoint in the context of forest fires, shedding light on a complex phenomenon that needs to be better understood in order to mitigate its devastating consequences, at both economical and environmental levels.

Integer and Fractional Order Entropy Analysis of Earthquake Data-series

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.

Entropy Analysis of Industrial Accident Data Series

Complex industrial plants exhibit multiple interactions among smaller parts and with human operators. Failure in one part can propagate across subsystem boundaries causing a serious disaster. This paper analyzes the industrial accident data series in the perspective of dynamical systems. First, we process real world data and show that the statistics of the number of fatalities reveal features that are well described by power law (PL) distributions. For early years, the data reveal double PL behavior, while, for more recent time periods, a single PL fits better into the experimental data. Second, we analyze the entropy of the data series statistics over time. Third, we use the Kullback–Leibler divergence to compare the empirical data and multidimensional scaling (MDS) techniques for data analysis and visualization. Entropy-based analysis is adopted to assess complexity, having the advantage of yielding a single parameter to express relationships between the data. The classical and the generalized (fractional) entropy and Kullback–Leibler divergence are used. The generalized measures allow a clear identification of patterns embedded in the data.

Fractional State Space Analysis of Economy Systems

This paper examines modern economic growth according to the multidimensional scaling (MDS) method and state space portrait (SSP) analysis. Electing GDP per capita as the main indicator for economic growth and prosperity, the long-run perspective from 1870 to 2010 identifies the main similarities among 34 world partners’ modern economic growth and exemplifies the historical waving mechanics of the largest world economy, the USA. MDS reveals two main clusters among the European countries and their old offshore territories, and SSP identifies the Great Depression as a mild challenge to the American global performance, when compared to the Second World War and the 2008 crisis.

Towards a classification scheme for musical sounds

Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA), 2013

Analysis of Natural and Artificial Phenomena Using Signal Processing and Fractional Calculus

In this paper we study several natural and man-made complex phenomena in the perspective of dynamical systems. For each class of phenomena, the system outputs are time-series records obtained in identical conditions. The time-series are viewed as manifestations of the system behavior and are processed for analyzing the system dynamics. First, we use the Fourier transform to process the data and we approximate the amplitude spectra by means of power law functions. We interpret the power law parameters as a phenomenological signature of the system dynamics. Second, we adopt the techniques of non-hierarchical clustering and multidimensional scaling to visualize hidden relationships between the complex phenomena. Third, we propose a vector field based analogy to interpret the patterns unveiled by the PL parameters.

Multidimensional Scalling Analysis of the World Economy During the Period 1972-2012

The last 40 years of the world economy are analyzed by means of computer visualization methods. Multidimensional scaling and the hierarchical clustering tree techniques are used. The current Western downturn in favor of Asian partners may still be reversed in the coming decades.