Joint modelling of longitudinal and survival data on breast cancer

Tese de Doutoramento em Ciências (Especialidade em Matemática)

Extreme value Birnbaum-Saunders regression models applied to environmental data

Extreme value models are widely used in different areas. The Birnbaum–Saunders distribution is receiving considerable attention due to its physical arguments and its good properties. We propose a methodology based on extreme value Birnbaum–Saunders regression models, which includes model formulation, estimation, inference and checking. We further conduct a simulation study for evaluating its performance. A statistical analysis with real-world extreme value environmental data using the methodology is provided as illustration.

Estimation of statistical cure from cancer using population-based data

Dissertação de mestrado em Estatística

Modelling tyre-road noise with data mining techniques

The research aimed to establish tyre-road noise models by using a Data Mining approach that allowed to build a predictive model and assess the importance of the tested input variables. The data modelling took into account three learning algorithms and three metrics to define the best predictive model. The variables tested included basic properties of pavement surfaces, macrotexture, megatexture, and uneven- ness and, for the first time, damping. Also, the importance of those variables was measured by using a sensitivity analysis procedure. Two types of models were set: one with basic variables and another with complex variables, such as megatexture and damping, all as a function of vehicles speed. More detailed models were additionally set by the speed level. As a result, several models with very good tyre-road noise predictive capacity were achieved. The most relevant variables were Speed, Temperature, Aggregate size, Mean Profile Depth, and Damping, which had the highest importance, even though influenced by speed. Megatexture and IRI had the lowest importance. The applicability of the models developed in this work is relevant for trucks tyre-noise prediction, represented by the AVON V4 test tyre, at the early stage of road pavements use. Therefore, the obtained models are highly useful for the design of pavements and for noise prediction by road authorities and contractors.

Estimativa dos parâmetros de compactação de solos usando técnicas de data mining

Dissertação de mestrado integrado em Engenharia Civil

Avaliação do desempenho de carteiras de fundos verdes em diferentes estados de mercado

Dissertação de mestrado em Finanças

High strain rate constitutive modeling forhistorical structures subjected to blast loading

Doctoral Thesis Civil Engineering

Removal of Erythrosine B dye from water effluents using crop waste pumpkin seed hulls as adsorbent

Erythrosine B is widely used for coloring in various applications, especially in the food industry, despite its already proved toxicity and carcinogenicity. The agrowaste pumpkin seed hulls were applied as potential adsorbent for the removal of Erythrosine from aqueous solutions. Adsorption mechanism and kinetics were analyzed for design purposes. The seed hulls were characterized by specific techniques before and after dye retention. It was found that the attachment of Erythrosine B molecules on adsorbent surface may be attributed to the interactions between carboxyl and/or carbonyl groups of both dye and agrowaste wall components. A univariate approach followed by a factorial design was applied to study and analyze the experimental results as well as to estimate the combined effects of the process factors on the removal efficiency and dye uptake. Adsorption mechanism may be predominantly due to intraparticle diffusion, dependent on pore size. The four equilibrium models applied fitted the data well; the maximum adsorption capacity for Erythrosine was 16.4 mg/g. The results showed that adsorbent is effective for Erythrosine B removal for a large concentration range in aqueous solutions (5400 mg/L) in batch systems.

Nanocomposites: the contribution of multiscale modelling to improve the dispersion levels

Tese de Doutoramento em Ciência e Engenharia de Polímeros e Compósitos

Modelos de regressão multinível no estudo do desempenho escolar

Dissertação de mestrado em Estatística

Nonparametric estimation of the survival function for ordered multivariate failure time data: a comparative study

In longitudinal studies of disease, patients may experience several events through a follow-up period. In these studies, the sequentially ordered events are often of interest and lead to problems that have received much attention recently. Issues of interest include the estimation of bivariate survival, marginal distributions and the conditional distribution of gap times. In this work we consider the estimation of the survival function conditional to a previous event. Different nonparametric approaches will be considered for estimating these quantities, all based on the Kaplan-Meier estimator of the survival function. We explore the finite sample behavior of the estimators through simulations. The different methods proposed in this article are applied to a data set from a German Breast Cancer Study. The methods are used to obtain predictors for the conditional survival probabilities as well as to study the influence of recurrence in overall survival.