A competition-based deformable template for junction extraction

Comunicación presentada en el VIII Simposium Nacional de Reconocimiento de Formas y Análisis de Imágenes, Bilbao, mayo 1999.

Deformable templates for tracking and analysis of intravascular ultrasound sequences

Deformable Template models are first applied to track the inner wall of coronary arteries in intravascular ultrasound sequences, mainly in the assistance to angioplasty surgery. A circular template is used for initializing an elliptical deformable model to track wall deformation when inflating a balloon placed at the tip of the catheter. We define a new energy function for driving the behavior of the template and we test its robustness both in real and synthetic images. Finally we introduce a framework for learning and recognizing spatio-temporal geometric constraints based on Principal Component Analysis (eigenconstraints).

Bayesian models for finding and grouping junctions

In this paper, we propose two Bayesian methods for detecting and grouping junctions. Our junction detection method evolves from the Kona approach, and it is based on a competitive greedy procedure inspired in the region competition method. Then, junction grouping is accomplished by finding connecting paths between pairs of junctions. Path searching is performed by applying a Bayesian A* algorithm that has been recently proposed. Both methods are efficient and robust, and they are tested with synthetic and real images.

An inverse method to obtain porosity, fibre diameter and density of fibrous sound absorbing materials

Characterization of sound absorbing materials is essential to predict its acoustic behaviour. The most commonly used models to do so consider the flow resistivity, porosity, and average fibre diameter as parameters to determine the acoustic impedance and sound absorbing coefficient. Besides direct experimental techniques, numerical approaches appear to be an alternative to estimate the material’s parameters. In this work an inverse numerical method to obtain some parameters of a fibrous material is presented. Using measurements of the normal incidence sound absorption coefficient and then using the model proposed by Voronina, subsequent application of basic minimization techniques allows one to obtain the porosity, average fibre diameter and density of a sound absorbing material. The numerical results agree fairly well with the experimental data.

An alternative disjunctive optimization model for heat integration with variable temperatures

This paper presents an alternative model to deal with the problem of optimal energy consumption minimization of non-isothermal systems with variable inlet and outlet temperatures. The model is based on an implicit temperature ordering and the “transshipment model” proposed by Papoulias and Grossmann (1983). It is supplemented with a set of logical relationships related to the relative position of the inlet temperatures of process streams and the dynamic temperature intervals. In the extreme situation of fixed inlet and outlet temperatures, the model reduces to the “transshipment model”. Several examples with fixed and variable temperatures are presented to illustrate the model's performance.

Rigorous Design of Complex Distillation Columns Using Process Simulators and the Particle Swarm Optimization Algorithm

We present a derivative-free optimization algorithm coupled with a chemical process simulator for the optimal design of individual and complex distillation processes using a rigorous tray-by-tray model. The proposed approach serves as an alternative tool to the various models based on nonlinear programming (NLP) or mixed-integer nonlinear programming (MINLP) . This is accomplished by combining the advantages of using a commercial process simulator (Aspen Hysys), including especially suited numerical methods developed for the convergence of distillation columns, with the benefits of the particle swarm optimization (PSO) metaheuristic algorithm, which does not require gradient information and has the ability to escape from local optima. Our method inherits the superstructure developed in Yeomans, H.; Grossmann, I. E.Optimal design of complex distillation columns using rigorous tray-by-tray disjunctive programming models. Ind. Eng. Chem. Res.2000, 39 (11), 4326–4335, in which the nonexisting trays are considered as simple bypasses of liquid and vapor flows. The implemented tool provides the optimal configuration of distillation column systems, which includes continuous and discrete variables, through the minimization of the total annual cost (TAC). The robustness and flexibility of the method is proven through the successful design and synthesis of three distillation systems of increasing complexity.

Constraint qualifications in linear vector semi-infinite optimization

Linear vector semi-infinite optimization deals with the simultaneous minimization of finitely many linear scalar functions subject to infinitely many linear constraints. This paper provides characterizations of the weakly efficient, efficient, properly efficient and strongly efficient points in terms of cones involving the data and Karush–Kuhn–Tucker conditions. The latter characterizations rely on different local and global constraint qualifications. The global constraint qualifications are illustrated on a collection of selected applications.

Robust Solutions of MultiObjective Linear Semi-Infinite Programs under Constraint Data Uncertainty

The multiobjective optimization model studied in this paper deals with simultaneous minimization of finitely many linear functions subject to an arbitrary number of uncertain linear constraints. We first provide a radius of robust feasibility guaranteeing the feasibility of the robust counterpart under affine data parametrization. We then establish dual characterizations of robust solutions of our model that are immunized against data uncertainty by way of characterizing corresponding solutions of robust counterpart of the model. Consequently, we present robust duality theorems relating the value of the robust model with the corresponding value of its dual problem.

Isobutane Alkylation Process Synthesis by means of Hybrid Simulation-Multiobjective Optimization

Multiobjective Generalized Disjunctive Programming (MO-GDP) optimization has been used for the synthesis of an important industrial process, isobutane alkylation. The two objective functions to be simultaneously optimized are the environmental impact, determined by means of LCA (Life Cycle Assessment), and the economic potential of the process. The main reason for including the minimization of the environmental impact in the optimization process is the widespread environmental concern by the general public. For the resolution of the problem we employed a hybrid simulation- optimization methodology, i.e., the superstructure of the process was developed directly in a chemical process simulator connected to a state of the art optimizer. The model was formulated as a GDP and solved using a logic algorithm that avoids the reformulation as MINLP -Mixed Integer Non Linear Programming-. Our research gave us Pareto curves compounded by three different configurations where the LCA has been assessed by two different parameters: global warming potential and ecoindicator-99.

Retrofit of heat exchanger networks with pressure recovery of process streams at sub-ambient conditions

This paper presents a new mathematical programming model for the retrofit of heat exchanger networks (HENs), wherein the pressure recovery of process streams is conducted to enhance heat integration. Particularly applied to cryogenic processes, HENs retrofit with combined heat and work integration is mainly aimed at reducing the use of expensive cold services. The proposed multi-stage superstructure allows the increment of the existing heat transfer area, as well as the use of new equipment for both heat exchange and pressure manipulation. The pressure recovery of streams is carried out simultaneously with the HEN design, such that the process conditions (streams pressure and temperature) are variables of optimization. The mathematical model is formulated using generalized disjunctive programming (GDP) and is optimized via mixed-integer nonlinear programming (MINLP), through the minimization of the retrofit total annualized cost, considering the turbine and compressor coupling with a helper motor. Three case studies are performed to assess the accuracy of the developed approach, including a real industrial example related to liquefied natural gas (LNG) production. The results show that the pressure recovery of streams is efficient for energy savings and, consequently, for decreasing the HEN retrofit total cost especially in sub-ambient processes.

Constraint qualifications in convex vector semi-infinite optimization

Convex vector (or multi-objective) semi-infinite optimization deals with the simultaneous minimization of finitely many convex scalar functions subject to infinitely many convex constraints. This paper provides characterizations of the weakly efficient, efficient and properly efficient points in terms of cones involving the data and Karush–Kuhn–Tucker conditions. The latter characterizations rely on different local and global constraint qualifications. The results in this paper generalize those obtained by the same authors on linear vector semi-infinite optimization problems.

Spectrally tunable light source based on light-emitting diodes for custom lighting solutions

This study describes a novel spectral LED-based tunable light source used for customized lighting solutions, especially for the reconstruction of CIE (Commission Internationale de l’Éclairage) standard illuminants. The light source comprises 31 spectral bands ranging from 400 to 700 nm, an integrating cube and a control board with a 16-bit resolution. A minimization algorithm to calculate the weighting values for each channel was applied to reproduce illuminants with precision. The differences in spectral fitting and colorimetric parameters showed that the reconstructed spectra were comparable to the standard, especially for the D65, D50, A and E illuminants. Accurate results were also obtained for illuminants with narrow peaks such as fluorescents (F2 and F11) and a high-pressure sodium lamp (HP1). In conclusion, the developed spectral LED-based light source and the minimization algorithm are able to reproduce any CIE standard illuminants with a high spectral and colorimetric accuracy able to advance available custom lighting systems useful in the industry and other fields such as museum lighting.

Essays on the Effects of Corporate Taxation

Cette thèse est une collection de trois articles en macroéconomie et finances publiques. Elle développe des modèles d'Equilibre Général Dynamique et Stochastique pour analyser les implications macroéconomiques des politiques d'imposition des entreprises en présence de marchés financiers imparfaits. Le premier chapitre analyse les mécanismes de transmission à l'économie, des effets d'un ré-échelonnement de l'impôt sur le profit des entreprises. Dans une économie constituée d'un gouvernement, d'une firme représentative et d'un ménage représentatif, j'élabore un théorème de l'équivalence ricardienne avec l'impôt sur le profit des entreprises. Plus particulièrement, j'établis que si les marchés financiers sont parfaits, un ré-échelonnement de l'impôt sur le profit des entreprises qui ne change pas la valeur présente de l'impôt total auquel l'entreprise est assujettie sur toute sa durée de vie n'a aucun effet réel sur l'économie si l'état utilise un impôt forfaitaire. Ensuite, en présence de marchés financiers imparfaits, je montre qu'une une baisse temporaire de l'impôt forfaitaire sur le profit des entreprises stimule l'investissement parce qu'il réduit temporairement le coût marginal de l'investissement. Enfin, mes résultats indiquent que si l'impôt est proportionnel au profit des entreprises, l'anticipation de taxes élevées dans le futur réduit le rendement espéré de l'investissement et atténue la stimulation de l'investissement engendrée par la réduction d'impôt. Le deuxième chapitre est écrit en collaboration avec Rui Castro. Dans cet article, nous avons quantifié les effets sur les décisions individuelles d'investis-sement et de production des entreprises ainsi que sur les agrégats macroéconomiques, d'une baisse temporaire de l'impôt sur le profit des entreprises en présence de marchés financiers imparfaits. Dans un modèle où les entreprises sont sujettes à des chocs de productivité idiosyncratiques, nous avons d'abord établi que le rationnement de crédit affecte plus les petites (jeunes) entreprises que les grandes entreprises. Pour des entreprises de même taille, les entreprises les plus productives sont celles qui souffrent le plus du manque de liquidité résultant des imperfections du marché financier. Ensuite, nous montré que pour une baisse de 1 dollar du revenu de l'impôt, l'investissement et la production augmentent respectivement de 26 et 3,5 centimes. L'effet cumulatif indique une augmentation de l'investissement et de la production agrégés respectivement de 4,6 et 7,2 centimes. Au niveau individuel, nos résultats indiquent que la politique stimule l'investissement des petites entreprises, initialement en manque de liquidité, alors qu'elle réduit l'investissement des grandes entreprises, initialement non contraintes. Le troisième chapitre est consacré à l'analyse des effets de la réforme de l'imposition des revenus d'entreprise proposée par le Trésor américain en 1992. La proposition de réforme recommande l'élimination des impôts sur les dividendes et les gains en capital et l'imposition d'une seule taxe sur le revenu des entreprises. Pour ce faire, j'ai eu recours à un modèle dynamique stochastique d'équilibre général avec marchés financiers imparfaits dans lequel les entreprises sont sujettes à des chocs idiosyncratiques de productivité. Les résultats indiquent que l'abolition des impôts sur les dividendes et les gains en capital réduisent les distorsions dans les choix d'investissement des entreprises, stimule l'investissement et entraîne une meilleure allocation du capital. Mais pour être financièrement soutenable, la réforme nécessite un relèvement du taux de l'impôt sur le profit des entreprises de 34\% à 42\%. Cette hausse du taux d'imposition décourage l'accumulation du capital. En somme, la réforme engendre une baisse de l'accumulation du capital et de la production respectivement de 8\% et 1\%. Néanmoins, elle améliore l'allocation du capital de 20\%, engendrant des gains de productivité de 1.41\% et une modeste augmentation du bien être des consommateurs.

Determinants of Financial Capital Use: Review of theories and implications for rural businesses. Factor Markets Working Paper No. 19, February 2012

This paper presents a review of financial economics literature and offers a comprehensive discussion and systematisation of determinants of financial capital use. In congruence with modern financial literature, it is acknowledged here that real and financial capital decisions are interdependent. While the fundamental role of the (unconstrained) demand for real capital in the demand for finance is acknowledged, the deliverable focuses on three complementary categories of the determinants of financial capital use: i) capital market imperfections; ii) factors mitigating these imperfections or their impacts; and iii) firm- and sector-related factors, which alter the severity of financial constraints and their effects. To address the question of the optimal choice of financial instruments, theories of firm capital structure are reviewed. The deliverable concludes with theory-derived implications for agricultural and non-agricultural rural business’ finance.

Comportamentos seguros: análise numa empresa do sector da indústria automóvel

Dissertação apresentada para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Segurança e Higiene no Trabalho