58 resultados para Feature scale simulation
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Dissertação apresentada para obtenção do Grau de Doutor em Engenharia do Ambiente, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia
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Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão Industrial
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ABSTRACT - It is the purpose of the present thesis to emphasize, through a series of examples, the need and value of appropriate pre-analysis of the impact of health care regulation. Specifically, the thesis presents three papers on the theme of regulation in different aspects of health care provision and financing. The first two consist of economic analyses of the impact of health care regulation and the third comprises the creation of an instrument for supporting economic analysis of health care regulation, namely in the field of evaluation of health care programs. The first paper develops a model of health plan competition and pricing in order to understand the dynamics of health plan entry and exit in the presence of switching costs and alternative health premium payment systems. We build an explicit model of death spirals, in which profitmaximizing competing health plans find it optimal to adopt a pattern of increasing relative prices culminating in health plan exit. We find the steady-state numerical solution for the price sequence and the plan’s optimal length of life through simulation and do some comparative statics. This allows us to show that using risk adjusted premiums and imposing price floors are effective at reducing death spirals and switching costs, while having employees pay a fixed share of the premium enhances death spirals and increases switching costs. Price regulation of pharmaceuticals is one of the cost control measures adopted by the Portuguese government, as in many European countries. When such regulation decreases the products’ real price over time, it may create an incentive for product turnover. Using panel data for the period of 1997 through 2003 on drug packages sold in Portuguese pharmacies, the second paper addresses the question of whether price control policies create an incentive for product withdrawal. Our work builds the product survival literature by accounting for unobservable product characteristics and heterogeneity among consumers when constructing quality, price control and competition indexes. These indexes are then used as covariates in a Cox proportional hazard model. We find that, indeed, price control measures increase the probability of exit, and that such effect is not verified in OTC market where no such price regulation measures exist. We also find quality to have a significant positive impact on product survival. In the third paper, we develop a microsimulation discrete events model (MSDEM) for costeffectiveness analysis of Human Immunodeficiency Virus treatment, simulating individual paths from antiretroviral therapy (ART) initiation to death. Four driving forces determine the course of events: CD4+ cell count, viral load resistance and adherence. A novel feature of the model with respect to the previous MSDEMs is that distributions of time to event depend on individuals’ characteristics and past history. Time to event was modeled using parametric survival analysis. Events modeled include: viral suppression, regimen switch due virological failure, regimen switch due to other reasons, resistance development, hospitalization, AIDS events, and death. Disease progression is structured according to therapy lines and the model is parameterized with cohort Portuguese observational data. An application of the model is presented comparing the cost-effectiveness ART initiation with two nucleoside analogue reverse transcriptase inhibitors (NRTI) plus one non-nucleoside reverse transcriptase inhibitor(NNRTI) to two NRTI plus boosted protease inhibitor (PI/r) in HIV- 1 infected individuals. We find 2NRTI+NNRTI to be a dominant strategy. Results predicted by the model reproduce those of the data used for parameterization and are in line with those published in the literature.
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics
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Dissertação para obtenção do Grau de Mestre em Engenharia Informática
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Dissertação para obtenção do Grau de Doutor em Engenharia Química
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Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão Industrial
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Dissertação para obtenção do Grau de Mestre em Engenharia do ambiente, perfil de engenharia sanitária
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We contribute to the stated preference literature by addressing scale usage heterogeneity regarding how individuals answer attitudinal questions capturing lack of trust in institutions and fairness issues. Using a latent class model, we conduct a contingent valuation study to elicit the willingness-to-pay to preserve a recreational site. We find evidence that respondents within the same class, that is, with similar preferences and attitudes, interpret the Likert scale differently when answering the attitudinal questions. We identify different patterns of scale usage heterogeneity within and across classes and associate them with individual characteristics. Our approach contributes to better a understanding of individual behavior in the presence of protest attitudes.
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Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e de Computadores
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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics
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Dissertação para obtenção do Grau de Mestre em Engenharia do Ambiente, Perfil de Engenharia Sanitária
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Benefits of long-term monitoring have drawn considerable attention in healthcare. Since the acquired data provides an important source of information to clinicians and researchers, the choice for long-term monitoring studies has become frequent. However, long-term monitoring can result in massive datasets, which makes the analysis of the acquired biosignals a challenge. In this case, visualization, which is a key point in signal analysis, presents several limitations and the annotations handling in which some machine learning algorithms depend on, turn out to be a complex task. In order to overcome these problems a novel web-based application for biosignals visualization and annotation in a fast and user friendly way was developed. This was possible through the study and implementation of a visualization model. The main process of this model, the visualization process, comprised the constitution of the domain problem, the abstraction design, the development of a multilevel visualization and the study and choice of the visualization techniques that better communicate the information carried by the data. In a second process, the visual encoding variables were the study target. Finally, the improved interaction exploration techniques were implemented where the annotation handling stands out. Three case studies are presented and discussed and a usability study supports the reliability of the implemented work.
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This work is divided into two distinct parts. The first part consists of the study of the metal organic framework UiO-66Zr, where the aim was to determine the force field that best describes the adsorption equilibrium properties of two different gases, methane and carbon dioxide. The other part of the work focuses on the study of the single wall carbon nanotube topology for ethane adsorption; the aim was to simplify as much as possible the solid-fluid force field model to increase the computational efficiency of the Monte Carlo simulations. The choice of both adsorbents relies on their potential use in adsorption processes, such as the capture and storage of carbon dioxide, natural gas storage, separation of components of biogas, and olefin/paraffin separations. The adsorption studies on the two porous materials were performed by molecular simulation using the grand canonical Monte Carlo (μ,V,T) method, over the temperature range of 298-343 K and pressure range 0.06-70 bar. The calibration curves of pressure and density as a function of chemical potential and temperature for the three adsorbates under study, were obtained Monte Carlo simulation in the canonical ensemble (N,V,T); polynomial fit and interpolation of the obtained data allowed to determine the pressure and gas density at any chemical potential. The adsorption equilibria of methane and carbon dioxide in UiO-66Zr were simulated and compared with the experimental data obtained by Jasmina H. Cavka et al. The results show that the best force field for both gases is a chargeless united-atom force field based on the TraPPE model. Using this validated force field it was possible to estimate the isosteric heats of adsorption and the Henry constants. In the Grand-Canonical Monte Carlo simulations of carbon nanotubes, we conclude that the fastest type of run is obtained with a force field that approximates the nanotube as a smooth cylinder; this approximation gives execution times that are 1.6 times faster than the typical atomistic runs.