Unsupervised edge map scoring: a statistical complexity approach

We propose a new Statistical Complexity Measure (SCM) to qualify edge maps without Ground Truth (GT) knowledge. The measure is the product of two indices, an \emph{Equilibrium} index $\mathcal{E}$ obtained by projecting the edge map into a family of edge patterns, and an \emph{Entropy} index $\mathcal{H}$, defined as a function of the Kolmogorov Smirnov (KS) statistic. This new measure can be used for performance characterization which includes: (i)~the specific evaluation of an algorithm (intra-technique process) in order to identify its best parameters, and (ii)~the comparison of different algorithms (inter-technique process) in order to classify them according to their quality. Results made over images of the South Florida and Berkeley databases show that our approach significantly improves over Pratt's Figure of Merit (PFoM) which is the objective reference-based edge map evaluation standard, as it takes into account more features in its evaluation

Accuracy of MAP segmentation with hidden Potts and Markov mesh prior models via Path Constrained Viterbi Training, Iterated Conditional Modes and Graph Cut based algorithms

In this paper, we study statistical classification accuracy of two different Markov field environments for pixelwise image segmentation, considering the labels of the image as hidden states and solving the estimation of such labels as a solution of the MAP equation. The emission distribution is assumed the same in all models, and the difference lays in the Markovian prior hypothesis made over the labeling random field. The a priori labeling knowledge will be modeled with a) a second order anisotropic Markov Mesh and b) a classical isotropic Potts model. Under such models, we will consider three different segmentation procedures, 2D Path Constrained Viterbi training for the Hidden Markov Mesh, a Graph Cut based segmentation for the first order isotropic Potts model, and ICM (Iterated Conditional Modes) for the second order isotropic Potts model. We provide a unified view of all three methods, and investigate goodness of fit for classification, studying the influence of parameter estimation, computational gain, and extent of automation in the statistical measures Overall Accuracy, Relative Improvement and Kappa coefficient, allowing robust and accurate statistical analysis on synthetic and real-life experimental data coming from the field of Dental Diagnostic Radiography. All algorithms, using the learned parameters, generate good segmentations with little interaction when the images have a clear multimodal histogram. Suboptimal learning proves to be frail in the case of non-distinctive modes, which limits the complexity of usable models, and hence the achievable error rate as well. All Matlab code written is provided in a toolbox available for download from our website, following the Reproducible Research Paradigm

Nominal Debt as a Burden on Monetary Policy

We characterize the optimal sequential choice of monetary policy in economies with either nominal or indexed debt. In a model where nominal debt is the only source of time inconsistency, the Markov-perfect equilibrium policy implies the progressive depletion of the outstanding stock of debt, until the time inconsistency disappears. There is a resulting welfare loss if debt is nominal rather than indexed. We also analyze the case where monetary policy is time inconsistent even when debt is indexed. In this case, with nominal debt, the sequential optimal policy converges to a time-consistent steady state with positive -- or negative -- debt, depending on the value of the intertemporal elasticity of substitution. Welfare can be higher if debt is nominal rather than indexed and the level of debt is not too high.nominal debt; indexed debt; optimal monetary policy; time consistency; Markov-perfect equilibrium

Updated facts on the U.S. distributions of earnings, income, and wealth

Wealth ; Income distribution

Physical activity, approach-avoidance temperament and depressive symptoms

The goal was to assess the connections between vigorous physical activity (VPA), approach-avoidance temperament and depressive symptoms. Two studies were conducted. Study 1, correlational, to assess the mediating role of both dimensions of temperament, approach-avoidance contrast, between physical activity and depressive symptoms. Participants, 335 college students, completed the International Physical Activity Questionnaire, the Depressive Symptoms Scale (DSS) and the Approach-Avoidance Temperament Questionnaire (Ap-AvTQ). Results showed that approach-avoidance contrast could be considered a potential mediator between VPA and depressive symptoms. The global model was significant, F(2, 351)=3.22, p<.001, R2=14.91%, R2 adjusted=14.42%, and the bootstrapped upper and lower limits did not contain zero with the lower limit at -.05 and the upper at -14, suggesting a connection between VPA and depressive symptoms mediated by the approach-avoidance contrast temperament. Study 2, longitudinal, to test if a physical activity program could produce changes in approach-avoidance contrast temperament, manipulating the depressive symptoms. A VPA program was conducted with 149 college students. Participants completed the DSS and the Ap-AvTQ. The true intraindividual change modeling technique, a more direct approach to modeling interindividual differences in intraindividual change without using a control group, showed that participants’ depressive symptoms were predicted through the mediation of the approach-avoidance contrast temperament (γ=-.36, p<.001). VPA was positively linked to the approach-avoidance contrast temperament that was negatively connected to depressive symptoms, and negatively linked to the approach-avoidance contrast temperament that was positively connected to depressive symptoms. It seems possible to influence depressive symptoms through approach-avoidance contrast temperament using VPA

Dual‐Inverter Circuit Topologies for Supplying Open‐Ended Loads

Power electronic converters are nowadays the most suitable solution to provide a variable voltage/current in industry. The most commonly used power converter is the three-phase two-level voltage source inverter which transforms a direct-current input voltage into alternating-current output voltage with adjustable magnitude and frequency. Power inverters are used to supply three-phase loads which are typically connected in wye or delta configurations. However, in previous years, a type of connection consisting on leaving both terminal ends of the load opened has been studied as an alternative to standard wye or delta connection. To supply loads with this type of connection, two power inverters (one at each terminal end of the load) are required in a circuit topology called dual-inverter. In this chapter, a general study of the dual-inverter topology is presented. The advantages and issues of such converter are studied and different modulation strategies are shown and discussed. Moreover, multilevel dual-inverter converters are presented as an extension to the basic two-level idea. For evaluation purposes, simulations results are presented

A new approach to image segmentation with two-dimensional hidden Markov models

Image segmentation is one of the fundamental problems in computer vision. In this work, we present a new segmentation algorithm that is based on the theory of twodimensional hidden Markov models (2D-HMM). Unlike most 2DHMM approaches we do not apply the Viterbi Algorithm, instead we present a computationally efficient algorithm that propagates the state probabilities through the image. This approach can easily be extended to higher dimensions. We compare the proposed method with a 2D-HMM standard algorithm and Iterated Conditional Modes using real world images like a radiography or a satellite image as well as synthetic images. The experimental results show that our approach is highly capable of condensing image segments. This gives our algorithm a significant advantage over the standard algorithm when dealing with noisy images with few classes.Fil: Baumgartner, Josef. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina.Fil: Flesia, Ana Georgina. Universidad Tecnológica Nacional; Argentina.Fil: Flesia, Ana Georgina. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina.Fil: Flesia, Ana Georgina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Gimenez, Javier. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina.Fil: Pucheta, Julián. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina.Sistemas de Automatización y Contro

Energy reserves mobilization: Strategies of three decapod species

In food deprivation assays, several different responses have been observed in crustaceans. However, studying energy reserves utilization among more than one species during the same starvation period has not yet been performed, particularly to discern whether the responses are due to intrinsic and/or environmental factors. We hypothesize that decapod species with similar feeding habits have the same strategies in the use of energetic reserves during starvation, even though they inhabit different environments. The aim of this study was to compare the energy reserves mobilization of three decapods species (Cherax quadricarinatus, Palaemon argentinus and Munida gregaria) with similar feeding habits, exposed to similar food deprivation conditions. The crayfish, shrimp and squat-lobster were experimentally kept at continuous feeding or continuous starvation throughout 15 days. Every 3rd day, the midgut gland index (MGI), and the glycogen, lipid and protein contents were measured in the midgut gland (MG) and pleon muscle. Palaemon argentinus mobilized more reserves during starvation, followed by C. quadricarinatus, and the last M. gregaria. The starved shrimps presented low MGI, whereas MG showed a reduction in glycogen (from day 6 to 15), lipid (from day 3 to 15), and protein levels (at day 9 and 15) while in their muscle, lipid reserves decreased at days 3 and 6. In C. quadricarinatus, the most affected parameters in the MG were MGI, glycogen (from day 6 to 15), and lipids (at day 12 and 15). In the MG of M. gregaria only the glycogen was reduced during fasting from 3 to 15 days. Even though the three studied species have similar feeding habitats, we found that their energetic profile utilization is different and it could be explained by the habitat, life span, temperature, organ/tissue, and metabolism of the species. Our results may be useful to understand the several different responses of crustaceans during starvation.Fil: Sacristán, Hernán Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas; ArgentinaFil: Rodriguez, Yamila Eliana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencia Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; ArgentinaFil: Pereira, Nair de Los Angeles. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencia Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; ArgentinaFil: Lopez, Laura Susana. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Biodiversidad y Biología Experimental y Aplicada. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Biodiversidad y Biología Experimental y Aplicada; ArgentinaFil: Lovrich, Gustavo Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas; ArgentinaFil: Fernandez Gimenez, Analia Veronica. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencia Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; Argentin

Estimación de parámetros de modelos a priori para segmentación contextual de imágenes

Tesis (Doctor en Matemática)--Universidad Nacional de Córdoba, Facultad de Matemática, Astronomía y Física, 2014.En esta tesis se trabaja en el problema de la estimación del parámetro de una familia exponencial de distribuciones de Gibbs, y su relación con el proceso de segmentación contextual de imágenes vía el algoritmo Iterated Conditional Modes (ICM), trabajando bajo el supuesto que el mapa de clases de la imagen sigue un modelo de Potts isotrópico, y que cada clase emite datos radiométricos Gaussianos multivariados. En una primera etapa se estudió la consistencia asintótica del estimador de Pseudo-Máxima Verosimilitud (PMV), logrando una prueba más general para la clase de estimadores de PMV correspondiente a densidades de Gibbs con especificaciones no invariantes por traslaciones, que cumplen propiedades específicas detalladas en la tesis. En una segunda etapa, dentro del mencionado contexto de segmentación, se define un nuevo estimador del parámetro de suavidad del modelo de Potts isotrópico, en el que no solo se tiene en cuenta la información del mapa de clases, sino también la verosimilitud de la información radiométrica proveniente de la imagen original. Este nuevo estimador es el estimador de PMV correspondiente al modelo no invariante a posteriori del mapa de clases, y su consistencia se probó bajo determinadas condiciones sobre el modelo de emisión. En una tercera etapa, se estudió mediante simulación el desempeño del estimador a muestra finita y bajo condiciones de contaminación usuales en la práctica.In this thesis we study the problem of parameter estimation of an exponential family of Gibbs distribu-tions, and its relation to the process of image contextual segmentation via Iterated Conditional Modes (ICM),under the assumption that the image map class is an isotropic Potts model realization, and each class issues multivariate Gaussian radiometric data.In a first step, the asymptotic consistency of the estimator of Pseudo-Maximum Likelihood (PML) was studied, obtaining a more general outcome for the class of PML estimators corresponding to Gibbs densities with non-invariant specifications, under specific assumptions detailed in the thesis.In a second step, within the aforementioned context of segmentation, a new smoothness parameter estimator of the isotropic Potts model was defined. This estimator not only takes into account class map information, but also the radiometric observation likelihood. This new estimator is the PML estimator for the non-invariant posterior model of class map, and its consistency is proved under certain conditions on the emission model.In a third step, the finite sample performance of our estimator was studied by simulation, and its sensibility assessed under usual conditions seen on the practice.Fil: Gimenez Romero, Javier Alejandro. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física; Argentina