From filters to features:Scale-space analysis of edge and blur coding in human vision

To make vision possible, the visual nervous system must represent the most informative features in the light pattern captured by the eye. Here we use Gaussian scale-space theory to derive a multiscale model for edge analysis and we test it in perceptual experiments. At all scales there are two stages of spatial filtering. An odd-symmetric, Gaussian first derivative filter provides the input to a Gaussian second derivative filter. Crucially, the output at each stage is half-wave rectified before feeding forward to the next. This creates nonlinear channels selectively responsive to one edge polarity while suppressing spurious or "phantom" edges. The two stages have properties analogous to simple and complex cells in the visual cortex. Edges are found as peaks in a scale-space response map that is the output of the second stage. The position and scale of the peak response identify the location and blur of the edge. The model predicts remarkably accurately our results on human perception of edge location and blur for a wide range of luminance profiles, including the surprising finding that blurred edges look sharper when their length is made shorter. The model enhances our understanding of early vision by integrating computational, physiological, and psychophysical approaches. © ARVO.

Essays on numerically efficient inference in nonlinear and non-Gaussian state space models, and commodity market analysis.

The first two articles build procedures to simulate vector of univariate states and estimate parameters in nonlinear and non Gaussian state space models. We propose state space speci fications that offer more flexibility in modeling dynamic relationship with latent variables. Our procedures are extension of the HESSIAN method of McCausland[2012]. Thus, they use approximation of the posterior density of the vector of states that allow to : simulate directly from the state vector posterior distribution, to simulate the states vector in one bloc and jointly with the vector of parameters, and to not allow data augmentation. These properties allow to build posterior simulators with very high relative numerical efficiency. Generic, they open a new path in nonlinear and non Gaussian state space analysis with limited contribution of the modeler. The third article is an essay in commodity market analysis. Private firms coexist with farmers' cooperatives in commodity markets in subsaharan african countries. The private firms have the biggest market share while some theoretical models predict they disappearance once confronted to farmers cooperatives. Elsewhere, some empirical studies and observations link cooperative incidence in a region with interpersonal trust, and thus to farmers trust toward cooperatives. We propose a model that sustain these empirical facts. A model where the cooperative reputation is a leading factor determining the market equilibrium of a price competition between a cooperative and a private firm

Analysis of small signal stability margins using genetic optimization

Power system small signal stability analysis aims to explore different small signal stability conditions and controls, namely: (1) exploring the power system security domains and boundaries in the space of power system parameters of interest, including load flow feasibility, saddle node and Hopf bifurcation ones; (2) finding the maximum and minimum damping conditions; and (3) determining control actions to provide and increase small signal stability. These problems are presented in this paper as different modifications of a general optimization to a minimum/maximum, depending on the initial guesses of variables and numerical methods used. In the considered problems, all the extreme points are of interest. Additionally, there are difficulties with finding the derivatives of the objective functions with respect to parameters. Numerical computations of derivatives in traditional optimization procedures are time consuming. In this paper, we propose a new black-box genetic optimization technique for comprehensive small signal stability analysis, which can effectively cope with highly nonlinear objective functions with multiple minima and maxima, and derivatives that can not be expressed analytically. The optimization result can then be used to provide such important information such as system optimal control decision making, assessment of the maximum network's transmission capacity, etc. (C) 1998 Elsevier Science S.A. All rights reserved.

Analysis of nonlinear dynamics of vocal folds using high-speed video observation and biomechanical modeling

Primary voice production occurs in the larynx through vibrational movements carried out by vocal folds. However, many problems can affect this complex system resulting in voice disorders. In this context, time-frequency-shape analysis based on embedding phase space plots and nonlinear dynamics methods have been used to evaluate the vocal fold dynamics during phonation. For this purpose, the present work used high-speed video to record the vocal fold movements of three subjects and extract the glottal area time series using an image segmentation algorithm. This signal is used for an optimization method which combines genetic algorithms and a quasi-Newton method to optimize the parameters of a biomechanical model of vocal folds based on lumped elements (masses, springs and dampers). After optimization, this model is capable of simulating the dynamics of recorded vocal folds and their glottal pulse. Bifurcation diagrams and phase space analysis were used to evaluate the behavior of this deterministic system in different circumstances. The results showed that this methodology can be used to extract some physiological parameters of vocal folds and reproduce some complex behaviors of these structures contributing to the scientific and clinical evaluation of voice production. (C) 2010 Elsevier Inc. All rights reserved.

A Phase Space Box-counting based Method for Arrhythmia Prediction from Electrocardiogram Time Series

Arrhythmia is one kind of cardiovascular diseases that give rise to the number of deaths and potentially yields immedicable danger. Arrhythmia is a life threatening condition originating from disorganized propagation of electrical signals in heart resulting in desynchronization among different chambers of the heart. Fundamentally, the synchronization process means that the phase relationship of electrical activities between the chambers remains coherent, maintaining a constant phase difference over time. If desynchronization occurs due to arrhythmia, the coherent phase relationship breaks down resulting in chaotic rhythm affecting the regular pumping mechanism of heart. This phenomenon was explored by using the phase space reconstruction technique which is a standard analysis technique of time series data generated from nonlinear dynamical system. In this project a novel index is presented for predicting the onset of ventricular arrhythmias. Analysis of continuously captured long-term ECG data recordings was conducted up to the onset of arrhythmia by the phase space reconstruction method, obtaining 2-dimensional images, analysed by the box counting method. The method was tested using the ECG data set of three different kinds including normal (NR), Ventricular Tachycardia (VT), Ventricular Fibrillation (VF), extracted from the Physionet ECG database. Statistical measures like mean (μ), standard deviation (σ) and coefficient of variation (σ/μ) for the box-counting in phase space diagrams are derived for a sliding window of 10 beats of ECG signal. From the results of these statistical analyses, a threshold was derived as an upper bound of Coefficient of Variation (CV) for box-counting of ECG phase portraits which is capable of reliably predicting the impeding arrhythmia long before its actual occurrence. As future work of research, it was planned to validate this prediction tool over a wider population of patients affected by different kind of arrhythmia, like atrial fibrillation, bundle and brunch block, and set different thresholds for them, in order to confirm its clinical applicability.

Empirical evidence for ultrametric structure in multi-layer perceptron error surfaces

Combinatorial optimization problems share an interesting property with spin glass systems in that their state spaces can exhibit ultrametric structure. We use sampling methods to analyse the error surfaces of feedforward multi-layer perceptron neural networks learning encoder problems. The third order statistics of these points of attraction are examined and found to be arranged in a highly ultrametric way. This is a unique result for a finite, continuous parameter space. The implications of this result are discussed.

O pátio jesuítico no Palácio Anchieta: narrativas tipomorfológicas e paisagísticas na cidade de Vitória (ES)

A hipótese defendida nesta pesquisa se baseia na possibilidade de a arquitetura jesuítica implantada em terras brasileiras (século XVI) dialogar e agenciar, num mesmo corpo edificado, e de modo inter-relacionado, aspectos relativos à morfologia urbana, tipologia e paisagem. Lama explica que, como disciplina, a morfologia urbana agrega para si não somente o ambiente construído, mas os meios pelos quais este foi construído em sua interação com a forma urbana, ou seja, os “fenômenos sociais, econômicos e outros motores da urbanização” (LAMAS, 1992). Entender a forma urbana é entender seus elementos constituintes, “quer em ordem à leitura ou análise do espaço, quer em ordem à sua concepção ou produção” (LAMAS, 1992). Estudar a forma urbana significa compreender o lugar onde se insere a cidade e seus elementos constituintes, seus espaços e a inter-relação entre eles e seu contexto, em um espectro abrangente do que se denomina cidade, e urbano. A tipologia arquitetônica e a morfologia urbana estão interligadas no cerne de suas análises, considerando que ambas, segundo Pereira, estudam “duas ordens de fatos homogêneos” (PEREIRA, 2012); estudam elementos constituintes da cidade – arquitetônicos e espaciais – que se sobrepõem ou se complementam de acordo com a escala de análise utilizada. A arquitetura jesuítica do Brasil colonial modela de modo determinante a construção de distintos núcleos urbanos originários na costa brasileira no século XVI. Isso, por meio da implantação de tipologia edilícia que acompanha a doutrina jesuítica de localização e escolha do sítio para suas construções, preconizando segurança, visibilidade do entorno e facilidade de acesso por rios ou pelo mar. Essas construções, realizadas em áreas elevadas, marcaram, por conseguinte, no tempo e no espaço, a paisagem dos primeiros núcleos urbanos brasileiros. A pesquisa analisou um dos exemplares históricos da arquitetura jesuítica no Estado do Espírito Santo, especificamente na cidade de Vitória, capital e núcleo urbano original da colonização portuguesa neste Estado. A instalação dos jesuítas na antiga Vila da Vitória, no séc. XVI, através de sua igreja dedicada a São Tiago e de seu colégio anexo, marca a presença tipológica de uma arquitetura religiosa que influencia a própria morfologia da cidade – caracterizando esta arquitetura como um tipomorfológico - e, por reflexo, participa da construção de sua paisagem urbana secular. Entende-se que o antigo complexo jesuítico de São Tiago e atual Palácio Anchieta, sede governamental e prédio cultural capixaba, é uma arquitetura que permeia estas três grandes narrativas arquitetônicas e urbanas: a tipologia, a morfologia e a paisagem.

Modelação do comportamento dinâmico de sistemas barragem-fundação-albufeira: formulação no espaço de estados com amortecimento generalizado

Com este trabalho mostra-se a importância da utilização integrada de modelos numéricos e de resultados da observação do comportamento dinâmico de barragens com vista ao controlo da segurança de sistemas barragem-fundação-albufeira. Neste trabalho utilizou-se o MATLAB para desenvolver um programa de elementos finitos 3D (DySSA 1.0, “Dynamic State Space Analysis”) para análise do comportamento dinâmico de sistemas barragem-fundação-albufeira considerando uma formulação em deslocamentos com a albufeira discretizada em elementos finitos com módulo de distorção nulo. Utiliza-se uma formulação no espaço de estados o que permite considerar amortecimento não proporcional à massa e à rigidez e conduz a modos de vibração complexos. Apresentam-se os fundamentos do método dos elementos finitos na perspetiva da sua implementação computacional para análise dinâmica de estruturas, e apresenta-se sumariamente o programa DySSA 1.0, o qual permite a análise estática e dinâmica de estruturas utilizando elementos finitos tridimensionais isoparamétricos do segundo grau (tipo cubo com 20 pontos nodais), e correspondentes elementos de junta (com 16 pontos nodais, 8 por cada face). O programa foi testado com base na análise dinâmica de uma parede em consola submetida à pressão hidrodinâmica. Os resultados numéricos foram comparados com soluções analíticas e com resultados experimentais obtidos no laboratório de estruturas do ISEL. Descrevem-se os fundamentos da análise dinâmica de estruturas no domínio do tempo, e referem-se os princípios em que se baseiam as metodologias de identificação modal no domínio da frequência. Analisa-se o comportamento dinâmico da barragem do Cabril em termos de frequências naturais e configurações modais, utilizando um modelo 3D representativo do sistema. Os resultados deste modelo numérico são comparados com resultados experimentais obtidos com base no sistema de monitorização dinâmica em contínuo, que foi instalado pelo LNEC em 2008.

Modelação e monitorização do comportamento dinâmico de barragens abóbada: identificação modal automática

Trabalho Final de Mestrado elaborado no Laboratório de Engenharia Civil (LNEC) para obtenção do grau de Mestre em Engenharia Civil pelo Instituto Superior de Engenharia de Lisboa no âmbito do protocolo de cooperação entre o ISEL e o LNEC

Identificação modal e simulação da resposta sísmica de barragens abóbada

Trabalho Final de Mestrado elaborado no Laboratório Nacional de Engenharia Civil (LNEC) para a obtenção do grau de Mestre em Engenharia Civil pelo Instituto Superior de Engenharia de Lisboa no âmbito do protocolo de cooperação ente o ISEL e o LNEC

Characterization approach to modified glassy carbon electrode-nanofilm system within multidimensional scaling

The aim of this work is to characterize the nanofilm consisting of the benzoic acid-modified glassy carbon (GC) electrode system through multidimensional scaling space analysis. The surface modification is based on the electrochemical reaction between the GC electrode and benzoic acid-diazonium salt (BA-DAS). As a result, the nonofilms regarding the benzoic acid-glassy carbon (BA-GC) electrode surface was obtained. For the analysis of the naonfilm of BC-GC electrode system, the IR spectra of the modified BA-GC electrode surface, GC surface and BA-DAS were recorded in the spectral range of 599.84 – 3996.34 [cm–1]. The IR data vectors of the above three forms were processed by the using the multidimensional scaling space approach to demonstrate the existence of a nanofilm on the modified BA-GC electrode system. Two- and three-dimensional MDS profiles obtained by application of multidimensional scaling approach to the data sets {CG1,...,CG10}, {BA-GC1,...,BA-GC10} and {FILM1,...,FILM10} allow a good recognition of the nanofilm on the modified glassy carbon (GC) electrode system.

Printed electronics for ubiquitous computing applications

Dissertação para obtenção do Grau de Doutor em Química

Scheduling dynamic dataflow graphs with model checking

With the shift towards many-core computer architectures, dataflow programming has been proposed as one potential solution for producing software that scales to a varying number of processor cores. Programming for parallel architectures is considered difficult as the current popular programming languages are inherently sequential and introducing parallelism is typically up to the programmer. Dataflow, however, is inherently parallel, describing an application as a directed graph, where nodes represent calculations and edges represent a data dependency in form of a queue. These queues are the only allowed communication between the nodes, making the dependencies between the nodes explicit and thereby also the parallelism. Once a node have the su cient inputs available, the node can, independently of any other node, perform calculations, consume inputs, and produce outputs. Data ow models have existed for several decades and have become popular for describing signal processing applications as the graph representation is a very natural representation within this eld. Digital lters are typically described with boxes and arrows also in textbooks. Data ow is also becoming more interesting in other domains, and in principle, any application working on an information stream ts the dataflow paradigm. Such applications are, among others, network protocols, cryptography, and multimedia applications. As an example, the MPEG group standardized a dataflow language called RVC-CAL to be use within reconfigurable video coding. Describing a video coder as a data ow network instead of with conventional programming languages, makes the coder more readable as it describes how the video dataflows through the different coding tools. While dataflow provides an intuitive representation for many applications, it also introduces some new problems that need to be solved in order for data ow to be more widely used. The explicit parallelism of a dataflow program is descriptive and enables an improved utilization of available processing units, however, the independent nodes also implies that some kind of scheduling is required. The need for efficient scheduling becomes even more evident when the number of nodes is larger than the number of processing units and several nodes are running concurrently on one processor core. There exist several data ow models of computation, with different trade-offs between expressiveness and analyzability. These vary from rather restricted but statically schedulable, with minimal scheduling overhead, to dynamic where each ring requires a ring rule to evaluated. The model used in this work, namely RVC-CAL, is a very expressive language, and in the general case it requires dynamic scheduling, however, the strong encapsulation of dataflow nodes enables analysis and the scheduling overhead can be reduced by using quasi-static, or piecewise static, scheduling techniques. The scheduling problem is concerned with nding the few scheduling decisions that must be run-time, while most decisions are pre-calculated. The result is then an, as small as possible, set of static schedules that are dynamically scheduled. To identify these dynamic decisions and to find the concrete schedules, this thesis shows how quasi-static scheduling can be represented as a model checking problem. This involves identifying the relevant information to generate a minimal but complete model to be used for model checking. The model must describe everything that may affect scheduling of the application while omitting everything else in order to avoid state space explosion. This kind of simplification is necessary to make the state space analysis feasible. For the model checker to nd the actual schedules, a set of scheduling strategies are de ned which are able to produce quasi-static schedulers for a wide range of applications. The results of this work show that actor composition with quasi-static scheduling can be used to transform data ow programs to t many different computer architecture with different type and number of cores. This in turn, enables dataflow to provide a more platform independent representation as one application can be fitted to a specific processor architecture without changing the actual program representation. Instead, the program representation is in the context of design space exploration optimized by the development tools to fit the target platform. This work focuses on representing the dataflow scheduling problem as a model checking problem and is implemented as part of a compiler infrastructure. The thesis also presents experimental results as evidence of the usefulness of the approach.

El cambio de valores para la mejora de las estrategias de aprendizaje y el rendimiento académico.

Analizar la relación entre los valores personales del alumnado de BUP y sus concepciones referidas al aprendizaje, sus conductas de estudio y su rendimiento académico. Aplicar el método de Autoconfrontación de valores para mejorar los hábitos y estrategias de aprendizaje del alumnado de BUP. Estudio 1: 325 alumnos-as, 179 de primero de BUP y 146 de segundo, pertenecientes a institutos de Bachillerato de la zona norte, centro y sus de Madrid. Estudio 2: 301 alomnos-as de segfundo de BUP, 157 del grupo experimental y 144 del de control, pertenecientes a centros de Bachillerato de la zona norte, centro y sur de Madrid. Estudio 1: se realiza un estudio correlacional en el que se analiza la relación entre los valores personales del alumnado y los determinantes del rendimiento académico. Se procede a la aplicación del Cuestionario de Valores de Schwartz (CVS), analizando los datos obtenidos según el procedimiento de análisis multidimensional SSA (Smallest Space Analysis). Se aplica el Cuestionario de Estrategias de Aprendizaje, Hábitos de Estudio y Satisfacción Académica (CEAYS), reduciendo los datos obtenidos, mediante análisis factorial con rotación varimax y un índice de fiabilidad, a un conjunto de variables compuestas. Estudio 2: se aplica un cuestionario inicial a la muestra y se procede a la puesta en práctica, con el grupo experimental, de la intervención educativa Autoconfrontación de valores. Tras dicha aplicación, se realiza un cuestionario al grupo experimental. Cuestionario de Valores de Schwartz (CVS), Cuestionario de Estrategias de Aprendizaje, Hábitos de Estudio y Satisfacción Académica (CEAYS). Porcentajes, rotación varimax, análisis multidimensional SSA. El rendimiento académico se relaciona con las actitudes hacia uno mismo y hacia el aprendizaje, así como con las conductas de uso de materiales y las de estudio. El autoconcepto y la autoestima académica general correlacionan con la frecuencia de las conductas de estudio y con el rendimiento académico. Las conductas concretas de estudio no se relacionan significativamente de manera directa con el rendimiento académico. De acuerdo con la teoría motivacional de Schwartz, se observa que el alumnado organiza sus valores en 10 tipos: Universalismo, Benevolencia, Conformidad, Seguridad, Poder, Logro, Hedonismo, Estimulación y Autodirección. Se observa que el estudio parece ser percibido por el alumnado de BUP como una actividad social normativamente impuesta. Tras la intervención educativa se observa una mejora moderada en el rendimiento académico y el efecto de la Autoconfrontación no depende del rendimiento académico previo, lo que significa que la intervención contribuye de igual forma a los diferentes colectivos estudiantiles. Considerando la eficacia de la intervención de la Autoconfrontación en relación a su coste y al esfuerzo invertido, esta intervención se revela como altamente eficaz para la mejora del rendimiento académico del alumnado.