Classification Performance of Multilayer Perceptrons with Different Risk Functionals

In the present paper we assess the performance of information-theoretic inspired risks functionals in multilayer perceptrons with reference to the two most popular ones, Mean Square Error and Cross-Entropy. The information-theoretic inspired risks, recently proposed, are: HS and HR2 are, respectively, the Shannon and quadratic Rényi entropies of the error; ZED is a risk reflecting the error density at zero errors; EXP is a generalized exponential risk, able to mimic a wide variety of risk functionals, including the information-thoeretic ones. The experiments were carried out with multilayer perceptrons on 35 public real-world datasets. All experiments were performed according to the same protocol. The statistical tests applied to the experimental results showed that the ubiquitous mean square error was the less interesting risk functional to be used by multilayer perceptrons. Namely, mean square error never achieved a significantly better classification performance than competing risks. Cross-entropy and EXP were the risks found by several tests to be significantly better than their competitors. Counts of significantly better and worse risks have also shown the usefulness of HS and HR2 for some datasets.

Prevalência do consumo de drogas ilícitas nas Forças Armadas estudo epidemiológico num dos ramos

RESUMO: Desde 1976 que as Forças Armadas desenvolvem acções de prevenção do consumo de drogas e álcool. Na década de 80 foi criada capacidade laboratorial e deu-se início a um programa de rastreios toxicológicos. No quinquénio 2001 a 2005, as proporções de resultados positivos, associando todos os tipos de rastreio, variaram entre 3,7% e 1,5%. De Outubro de 2006 a Julho de 2007 realizou-se um estudo analítico transversal, para estimar a prevalência do consumo de drogas (canabinóides, opiáceos, cocaína e anfetaminas) num dos Ramos das Forças Armadas, com base nos despistes realizados pelo seu laboratório. Foi utilizada uma amostra aleatória simples de 1039 militares, profissionais (QP) e contratados (RC), no activo e de ambos os sexos. Desde a nomeação dos militares a rastrear, passando pela cadeia de custódia das amostras até à obtenção do resultado foi utilizado apoio informático específico. O processo de pesquisa utilizou duas técnicas de triagem por imunoensaio e tecnologia de confirmação por GC/MS, de acordo com as recomendações europeias, permitindo estabelecer uma metodologia standard para organizações e empresas. A prevalência estimada, de consumidores de droga, foi de 3,8/1.000, para um erro de 0,37%. O número de casos registado (4) não permitiu a utilização de testes estatísticos que conduzissem à identificação de características determinantes da positividade, mas não deixou de revelar aspectos inesperados. A observação de séries de casos e a realização regular de estudos epidemiológicos, que ajudem a redefinir grupos alvo e a perceber a dimensão, as determinantes e as consequências do consumo de drogas é sugerida, em conclusão.--------------------------------------- RÉSUMÉ: Depuis 1976, les Forces Armées mettent au point des mesures visant à prévenir la consommation de drogues et d'alcool. En 1980, fut créé capacité laboratoriel et ont ensuite commencé un programme de dépistage toxicologique. Au cours des cinq années allant de 2001 à 2005, les proportions de consommateurs, impliquant tous les types de dépistage, allaient de 3,7% à 1,5 %. D'octobre 2006 à juillet 2007, une étude analytique transversale a été organisée pour évaluer la prévalence de l’usage de drogues (cannabis, opiacés, cocaïne et amphétamines) dans une branche de les Forces Armées, basée sur les dépistages faites par un laboratoire militaire, à l'aide d'un échantillon aléatoire de 1039 militaires, professionnels (QP) et sous contract (RC), à l’actif et des deux sexes. Tout au long du procès, de la nomination des donneurs, en passant par la chaine de garde des échantillons, jusqu’à obtention du résultat, il fut employé un appui informatique sécurisé. Le processus de recherche employa deux techniques de tri par imunoessay et la technologie de confirmation GC/MS, selon les recommandations européennes, permettant d'établir une méthodologie standard pour les organisations et les entreprises. La prévalence estimée fut de 3,8/1.000 pour une marge d’erreur de 0,37%. Le nombre de cas enregistrés (4) n'autorise pas l'utilisation de testes statistiques de menant à l'identification de caractéristiques déterminant de la positivité, mais il permet à révéler des aspects inattendus. L'observation de séries de cas et la tenue régulière d’études épidémiologiques, qui contribuent à redéfinir les groupes cibles et de comprendre l'ampleur, les déterminants et les conséquences de l'usage de drogues, est suggéré, en fin de compte.--------------------------------------- ABSTRACT: Since 1976, the Armed Forces, have been developing measures to prevent the use of drugs and alcohol. In 1980, was created laboratory facility which then started a program of toxicological screenings. In the five years running from 2001 to 2005, the proportions of consumers, involving all types of screening, ranged from 3,7% to 1,5%. From October 2006 to July 2007, a cross-sectional study was held to estimate the prevalence of drug use (cannabinoids, opiates, cocaine and amphetamines) in one branch of the Portuguese Armed Forces, based on laboratory screenings, using a random sample of 1039 military, professional (QP) and enlisted (RC), active-duty and of both sexes. Specific computer support was used all the way, from the appointment, including the chain of custody of samples, to the obtaining of the result. The process of search used two techniques for sorting by immunoassay and confirmation technology GC/MS, according to European recommendations, allowing to establish a standard methodology for organizations and companies. The estimated prevalence of drug users was 3.8/1.000 for a 0.37% error (95% confidence interval). The number of cases registered (4) does not permit use of statistical testing leading to the identification of characteristics weighing in the establishing to extrapolate for the population, but it allows revealing unexpected aspects. The observation of series of cases and the regular holding of epidemiological studies, which help redefine target groups and to understand the extent, the determinants and consequences of drug use, is suggested, in conclusion.

Otimização de placas compósitas laminadas utilizando redes neuronais e enxames de partículas

Trabalho Final de mestrado para obtenção do grau de Mestre em engenharia Mecância

Dynamical Stability and Predictability of Football Players: The Study of One Match

The game of football demands new computational approaches to measure individual and collective performance. Understanding the phenomena involved in the game may foster the identification of strengths and weaknesses, not only of each player, but also of the whole team. The development of assertive quantitative methodologies constitutes a key element in sports training. In football, the predictability and stability inherent in the motion of a given player may be seen as one of the most important concepts to fully characterise the variability of the whole team. This paper characterises the predictability and stability levels of players during an official football match. A Fractional Calculus (FC) approach to define a player’s trajectory. By applying FC, one can benefit from newly considered modeling perspectives, such as the fractional coefficient, to estimate a player’s predictability and stability. This paper also formulates the concept of attraction domain, related to the tactical region of each player, inspired by stability theory principles. To compare the variability inherent in the player’s process variables (e.g., distance covered) and to assess his predictability and stability, entropy measures are considered. Experimental results suggest that the most predictable player is the goalkeeper while, conversely, the most unpredictable players are the midfielders. We also conclude that, despite his predictability, the goalkeeper is the most unstable player, while lateral defenders are the most stable during the match.

Maximum level and time to peak of dam-break waves on mobile horizontal bed

Journal of Hydraulic Engineering, Vol. 135, No. 11, November 1, 2009

Unmixing hyperspectral data: independent and dependent component analysis

The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.

Nonautonomous Graphs and Topological Entropy of Nonautonomous Lorenz Systems

In this work, we associate a p-periodic nonautonomous graph to each p-periodic nonautonomous Lorenz system with finite critical orbits. We develop Perron-Frobenius theory for nonautonomous graphs and use it to calculate their entropy. Finally, we prove that the topological entropy of a p-periodic nonautonomous Lorenz system is equal to the entropy of its associated nonautonomous graph.

Comparing wind generation profiles: A circular data approach

The importance of wind power energy for energy and environmental policies has been growing in past recent years. However, because of its random nature over time, the wind generation cannot be reliable dispatched and perfectly forecasted, becoming a challenge when integrating this production in power systems. In addition the wind energy has to cope with the diversity of production resulting from alternative wind power profiles located in different regions. In 2012, Portugal presented a cumulative installed capacity distributed over 223 wind farms [1]. In this work the circular data statistical methods are used to analyze and compare alternative spatial wind generation profiles. Variables indicating extreme situations are analyzed. The hour (s) of the day where the farm production attains its maximum daily production is considered. This variable was converted into circular variable, and the use of circular statistics enables to identify the daily hour distribution for different wind production profiles. This methodology was applied to a real case, considering data from the Portuguese power system regarding the year 2012 with a 15-minutes interval. Six geographical locations were considered, representing different wind generation profiles in the Portuguese system.In this work the circular data statistical methods are used to analyze and compare alternative spatial wind generation profiles. Variables indicating extreme situations are analyzed. The hour (s) of the day where the farm production attains its maximum daily production is considered. This variable was converted into circular variable, and the use of circular statistics enables to identify the daily hour distribution for different wind production profiles. This methodology was applied to a real case, considering data from the Portuguese power system regarding the year 2012 with a 15-minutes interval. Six geographical locations were considered, representing different wind generation profiles in the Portuguese system.

Sucesso terapêutico no controlo da tuberculose em Portugal : determinantes do resultado do tratamento e a sua capacidade preditiva

RESUMO - Enquadramento/objectivos: Apesar do elevado nível de comprometimento em estratégias eficazes para o controlo da tuberculose, em todo o mundo, esta constitui ainda um sério problema de Saúde Pública, com uma estimativa global de 9,4milhões de casos novos em 2008 e 1,8milhões de mortes/ano. O reduzido conhecimento das barreiras e facilitadores para o sucesso terapêutico constitui um importante obstáculo na procura de soluções eficazes de melhoramento da qualidade dos programas de controlo da tuberculose. Este estudo procura contribuir para a identificação atempada de doentes com perfis preditivos de insucesso terapêutico, através da identificação inicial de potenciais determinantes do resultado, com base num modelo epidemiológico e estatístico. Métodos: Foi desenvolvido um estudo de caso-controlo para a população de casos notificados ao Programa Nacional de Controlo da Tuberculose (n=24491), entre 2000-2007. Os factores preditivos de insucesso terapêutico foram identificados na análise bivariada e multivariada, com um nível de significância de 5%; a regressão logística foi utilizada para estimar a odds ratio de insucesso terapêutico, em comparação com o sucesso terapêutico, para diversos factores identificados na literatura, e para os quais os dados se encontravam disponíveis. Resultados: A dependência alcoólica (OR=2,889), o país de origem (OR=3,910), a situação sem-abrigo (OR=3.919), a co-infecção pelo VIH (OR=5,173), a interrupção (OR=60.615) ou falha terapêutica no tratamento anterior (OR=67.345) e a duração do tratamento inferior a 165 dias (OR=1930,133) foram identificados como factores preditivos de insucesso terapêutico. A duração do tratamento inferior a 165 dias provou ser o mais importante determinante do resultado terapêutico. Conclusões: Os resultados sugerem que um doente imigrante, em situação de sem-abrigo, dependente alcoólico, com tratamentos anteriores para a tuberculose e co-infectado pelo VIH apresenta uma elevada probabilidade de insucesso terapêutico. Assim, deverão ser definidas estratégias específicas, centradas no doente por forma a impedir este resultado. A base de dados (SVIG-TB), provou ser uma ferramenta de qualidade para a investigação sobre diversos aspectos do controlo da tuberculose. ------------------------------- ABSTRACT - Background/Objective: Despite the high commitment in good strategies for tuberculosis control worldwide, this is still a serious Public Health problem, with global estimates of 9,4million new cases in 2008 and 1,8million deaths/year. The poor understanding of the barriers and facilitators to treatment success is a major obstacle to find effective solutions to improve the quality of tuberculosis programs. This study tries to contribute to the timely identification of patients with predictive profiles of unsuccessful treatment outcomes, through the initial identification of characteristics probably affecting treatment outcome, found on the basis of an epidemiological and statistical model. Methods: A case-control study was conducted for the population of cases notified to the National Program for Tuberculosis Control (n=24 491), between 2000-2007. Predictive factors for unsuccessful outcome were assessed in a bivariate and multivariate analysis, using a significance level of 5%; a logistic regression was used to estimate the odds-ratio of unsuccessful, as compared to successful outcome, for several factors identified in the literature and to which data was available. Results: Alcohol abuse (OR=2,889), patient´s foreign origin (OR=3,910), homelessness (OR=3,919), HIV co-infection (OR=5,173), interruption (OR=60,615) or unsuccessful outcome in the previous treatment (OR=67,345) and treatment duration below 165 days (OR=1930,133) were identified as predictive of unsuccessful outcomes. A low treatment duration proved to be the most powerful factor affecting treatment outcome. Conclusions: Results suggest that a foreign-born patient, alcohol abuser, who has had a previous treatment for tuberculosis and is co-infected with HIV is very likely to have an unsuccessful outcome. Therefore, specific, patient-centered strategies should be taken to prevent an unsuccessful outcome. The database (SVIG-TB), has proved to be a quality tool on research of various aspects of tuberculosis control.

Extremum estimators and stochastic optimization methods

Submitted in partial fulfillment for the Requirements for the Degree of PhD in Mathematics, in the Speciality of Statistics in the Faculdade de Ciências e Tecnologia

IgG recognizing 21-24 kDa and 30-33 kDa tachyzoite antigens show maximum avidity maturation during natural and accidental human toxoplasmosis

We describe the avidity maturation of IgGs in human toxoplasmosis using sequential serum samples from accidental and natural infections. In accidental cases, avidity increased continuously throughout infection while naturally infected patients showed a different profile. Twenty-five percent of sera from chronic patients having specific IgM positive results could be appropriately classified using exclusively the avidity test data. To take advantage of the potentiality of this technique, antigens recognized by IgG showing steeper avidity maturation were identified using immunoblot with KSCN elution. Two clusters of antigens, in the ranges of 21-24 kDa and 30-33 kDa, were identified as the ones that fulfill the aforementioned avidity characteristics.

Trace elements quantification in Portuguese red wines

Dissertation for the Degree of Master in Technology and Food Safety – Food Quality

Quantificação da complexidade do ritmo cardíaco usando o método da Multiscale Entropy

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

New prevalence estimate of TT virus (TTV) infection in low- and high-risk population from São Paulo, Brazil

The prevalence of TT virus (TTV) infection was investigated by Polymerase Chain Reaction (PCR) in low- (blood donors and healthy children/adolescents) and high-risk (hemophiliacs) groups from São Paulo, Brazil. Primers based on the untranslated region (UTR) of the viral genome proved to be much more ubiquitous, leading to much higher frequencies for both groups ( > or = 81%) than the earlier N22-PCR directed to the open reading frame 1 (blood donors, 5.5%, and hemophiliacs, 42.3%). The UTR-PCR also revealed an interesting profile for healthy children/adolescents: very high prevalence at the early years and significant decrease in male teenagers. The N22-PCR, in turn, demonstrated higher frequency in hemophiliacs treated with fresh blood products (58%), than in those treated with virus-inactivated clotting factors (9.4%) and blood donors (5.5%).