Analysis of UV spectral bands using multidimensional scaling

This study describes the change of the ultraviolet spectral bands starting from 0.1 to 5.0 nm slit width in the spectral range of 200–400 nm. The analysis of the spectral bands is carried out by using the multidimensional scaling (MDS) approach to reach the latent spectral background. This approach indicates that 0.1 nm slit width gives higher-order noise together with better spectral details. Thus, 5.0 nm slit width possesses the higher peak amplitude and lower-order noise together with poor spectral details. In the above-mentioned conditions, the main problem is to find the relationship between the spectral band properties and the slit width. For this aim, the MDS tool is to used recognize the hidden information of the ultraviolet spectra of sildenafil citrate by using a Shimadzu UV–VIS 2550, which is in the world the best double monochromator instrument. In this study, the proposed mathematical approach gives the rich findings for the efficient use of the spectrophotometer in the qualitative and quantitative studies.

The Persistence of Memory

This paper analyzes several natural and man-made complex phenomena in the perspective of dynamical systems. Such phenomena are often characterized by the absence of a characteristic length-scale, long range correlations and persistent memory, which are features also associated to fractional order systems. For each system, the output, interpreted as a manifestation of the system dynamics, is analyzed by means of the Fourier transform. The amplitude spectrum is approximated by a power law function and the parameters are interpreted as an underlying signature of the system dynamics. The complex systems under analysis are then compared in a global perspective in order to unveil and visualize hidden relationships among them.

Power Law Behavior and Self-similarity in Modern Industrial Accidents

Advances in technology have produced more and more intricate industrial systems, such as nuclear power plants, chemical centers and petroleum platforms. Such complex plants exhibit multiple interactions among smaller units and human operators, rising potentially disastrous failure, which can propagate across subsystem boundaries. This paper analyzes industrial accident data-series in the perspective of statistical physics and dynamical systems. Global data is collected from the Emergency Events Database (EM-DAT) during the time period from year 1903 up to 2012. The statistical distributions of the number of fatalities caused by industrial accidents reveal Power Law (PL) behavior. We analyze the evolution of the PL parameters over time and observe a remarkable increment in the PL exponent during the last years. PL behavior allows prediction by extrapolation over a wide range of scales. In a complementary line of thought, we compare the data using appropriate indices and use different visualization techniques to correlate and to extract relationships among industrial accident events. This study contributes to better understand the complexity of modern industrial accidents and their ruling principles.

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 Analysis of the DNA Information

Proceedings of the 12th Conference on 'Dynamical Systems -Theory and Applications'

Kinematic Manipulability of Robotic Systems

Many tasks involving manipulation require cooperation between robots. Meanwhile, it is necessary to determine the adequate values for the robot parameters to obtain a good performence. This paper discusses several aspects related with the manipulability of two co-operative robots when handling objects with different lengths and orientations. In this line of thought, a numerical tool is developed for the calculation and the graphical visualization of the manipulability measure.

Probabilistic Stereo Egomotion Transform

In this paper we propose a novel fully probabilistic solution to the stereo egomotion estimation problem. We extend the notion of probabilistic correspondence to the stereo case which allow us to compute the whole 6D motion information in a probabilistic way. We compare the developed approach against other known state-of-the-art methods for stereo egomotion estimation, and the obtained results compare favorably both for the linear and angular velocities estimation.

Simulação de Robôs Quadrúpedes Utilizando o SimMechanics

Desde sempre o Homem procurou automatizar tarefas repetitivas. Tanto na indústria como no sector doméstico ou de comércio estão constantemente a surgir novos equipamentos procurando aumentar o nível de automação de diversas tarefas. A necessidade de empresas criadoras de produtos inovadores se manterem concorrenciais obrigou à adopção de métodos de projecto e planeamento mais estruturados e eficientes que eliminem os desperdícios tanto de material como de tempo. Diversas construções em termos orçamentais e o aumento da procura de produtos de alta qualidade a baixo custo deu origem a um novo tipo de programas, os programas de simulação virtual. Tal como na indústria, também na investigação nas Instituições de Ensino Superior se procuram adoptar os métodos de trabalho mais eficientes possíveis. Uma parte dos programas de simulação robótica utilizados hoje em dia na investigação no Instituto Superior de Engenharia do Porto estão concebidos em linguagem C. Embora esta linguagem seja extremamente capaz, existem métodos mais adequados de simulação que aceleram o processo de modelação permitindo a visualização do movimento e simulação de diversas situações potencialmente criticas sem existir a necessidade de construção de um protótipo funcional do robô. Durante o último ano, este projecto permitiu construir um modelo de um robô quadrúpede num programa de simulação virtual chamado Simmechanics™. Embora haja já algum trabalho desenvolvido nesta área, constatou-se que a informação existente possuía algumas lacunas. Com o trabalho desenvolvido preparou-se esta dissertação que pretende clarificar algumas questões que surgem na modelação de um robô. Neste documento explica-se como modelar um robô de corpo flexível, modelar as pernas e as respectivas juntas da anca e do joelho assim como também se apresenta a modelação de um contacto com o solo recorrendo a um modelo descrito na literatura. Este documento foi escrito a pensar no leitor, procurando-se explicar de forma simples mas concisa os diversos passos necessários para construir um modelo virtual de um robô. O autor espera, desta forma, ajudar futuros colegas que pretendam trabalhar com o Simmechanics™ a mais facilmente se integrarem com o programa aumentando desta forma o declive da curva de aprendizagem e permitindo um maior aproveitamento desta ferramenta.

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.

Identification of Paracoccidioides brasiliensis in adrenal glands biopsies of two patients with paracoccidioidomycosis and adrenal insufficiency

The authors report two cases of adrenal insufficiency secondary to infiltration of the adrenal glands by Paracoccidioides brasiliensis. The first patient had been treated for a chronic multifocal form of paracoccidiodomycosis 11 years ago. The diagnosis of the mycosis was done simultaneous with that of the adrenal insufficiency in the second patient. In both patients the diagnosis was done by direct visualization of fungus in adrenal biopsies. They were treated with hormonal supplements and itraconazol by 12 and six months, without relapses during the follow-up period.

Visualizing control systems performance: A fractional perspective

This article presents a novel method for visualizing the control systems behavior. The proposed scheme uses the tools of fractional calculus and computes the signals propagating within the system structure as a time/frequency-space wave. Linear and nonlinear closed-loop control systems are analyzed, for both the time and frequency responses, under the action of a reference step input signal. Several nonlinearities, namely, Coulomb friction and backlash, are also tested. The numerical experiments demonstrate the feasibility of the proposed methodology as a visualization tool and motivate its extension for other systems and classes of nonlinearities.

Tutor Inteligente para o Ensino em Medicina

O objectivo deste trabalho consistiu no desenvolvimento de um protótipo que possibilita a adaptação do conteúdo disponibilizado de acordo com as características pessoais e psicológicas do aluno, aplicado no ensino da Medicina, nomeadamente na componente de Desenho de Estudos da disciplina de Introdução à Medicina. Para o protótipo desenvolvido foi definida uma arquitectura constituída por três componentes: um Modelo de Aluno que engloba as características pessoais e psicológicas do aluno, um Modelo de Domínio constituído por um grafo de conceitos e um Modelo Pedagógico formado pelas regras de adaptação e mecanismos de interação utilizados para obter uma solução adaptativa. Os diferentes componentes desenvolvidos para este protótipo permitem que este apresente as seguintes funcionalidades: Acesso ao conceito adequado, tendo em consideração o nível de conhecimento do aluno; Visualização de conte udos adequados ao estilo de aprendizagem do aluno; Adaptação do percurso do aluno de acordo com os resultados obtidos; Atualização das preferências de aprendizagem, com base no comportamento demonstrado pelo aluno na interação com o sistema. A primeira versão da ferramenta j a foi implementada. No entanto ainda será realizada a avaliação do protótipo em ambiente de aprendizagem, com a maior brevidade possível.