In this thesis we deal with statistical inference related to extreme value phenomena. Specifically, if X is a random vector with values in d-dimensional space, our goal is to estimate moments of ψ(X) for a suitably chosen function ψ when the magnitude of X is big. We employ the powerful tool of regular variation for random variables, random vectors and time series to formally define the limiting quantities of interests and construct the estimators. We focus on three statistical estimation problems: (i) multivariate tail estimation for regularly varying random vectors, (ii) extremogram estimation for regularly varying time series, (iii) estimation of the expected shortfall given an extreme component under a conditional extreme value model. We establish asymptotic normality of estimators for each of the estimation problems. The theoretical findings are supported by simulation studies and the estimation procedures are applied to some financial data.

Introduction. This present thesis focuses on occupational adaptation in the empirical context of vulnerable populations relative to ageing (Study II, III), disability (Study I, II) and poverty (Study IV) and in a theoretical context (V). Aim. The overall aim was to explore and describe occupational adaptation in diverse contexts with a focus on persons in vulnerable life situations. Methods. The thesis was conducted with a mixed design embracing quantitative and qualitative methods and a literature review. The data collection methods comprised questionnaires (Study I, II, III), individual interviews (Study II, IV), group interviews (Study III) and data base searches (Study V). Altogether 115 persons participated in the studies and 50 articles were included in the literature review. Qualitative content analysis was used to analyse the interviews (Study I, II, III, IV) and the literature review (Study V). Parametric and non-parametric statistics were applied when analysing the quantitative data (Study II, III). Results: Women in St Petersburg, Russia, who have had a minor stroke reported more dependence in everyday occupations than the stroke symptoms indicated and they overemphasized their disability and dysfunction. When the environmental press did not meet their competence, it caused negative adaptive behaviour (Study I). In home rehabilitation for older persons with disabilities, interventions based on the occupational adaptation model was compared with interventions based on well-tried professional experience. The results indicated that the use of the occupational adaptation model increased experienced health and the participants acquired adaptive strategies to manage every day occupations. (Study II). An occupation based health-promoting programme for older community dwelling persons was compared with a control group. The intervention group showed statistically significant improvement in general health variables as vitality and mental health, but there were no statistically significant differences between the groups. A qualitative evaluation, in the intervention group, showed that participation in meaningful, challenging occupations in different environments stimulated the occupational adaptation process (Study III). Occupational adaptation among vulnerable EU citizens begging in Sweden was explored by interviews. The results showed that the participants experienced several occupational challenges when begging abroad. The results show a variety of adaptive responses, but whether they are experienced as positive or negative is a matter of perspective and can only be determined by the participants themselves (Study IV). Finally, the results from a literature review (Study V) showed that research on occupational adaptation was mainly based on Schkade and Schultz’s and Kielhofner’s theoretical approaches. Occupational adaptation was also used without further explanation or theoretical argument (Study V). Conclusion: The surrounding context was shown to play an important role for the participants’ occupational adaptation. There were no general occupational challenges or adaptive responses to the various vulnerable life situations, but some common features in the participant groups’ adaptive responses were found. For example, if the environment put too great demand on the person and social support was lacking, there was a risk of negative adaptation. Moreover, persons with low functional capacity were vulnerable to environmental demands and dependent on a supportive environment for their adaptive response. However, persons living in supportive environments developed adaptive responses by themselves. Further, personal factors needed to be strengthened to meet the demands of the environment. Upholding occupational roles was a driving force in finding ways to adapt and perform occupations. Considering the theoretical context, the occupational adaptation theoretical approaches need to be further developed in relation to negative adaptation and to support use within community-based and health-promotive areas.

This thesis compares different theoretical principles concerning the relationship between minimum wages and unemployment. In the empirical part examines the impact of minimum wages on unemployment in the Czech Republic for the period 1994 - 2012. The results of the econometric analysis indicate that the minimum wage significantly affects unemployment. I conclude that a 1% increase in the real minimum wage compared to the previous year will result in approximately a 0.17% increase in the unemployment rate for workers with at most primary education compared to the previous year and approximately 0.07% increase in the unemployment rate of men compared to previous year. Based on the extension of the basic models is rejected that the minimum wage statistically negatively influenced overall unemployment, unemployment of women and unemployment of workers under 25 years.

Enantioselective reactions are one of the ways to produce pure chiral compounds. Understanding the basis of this selectivity makes it possible to guide enzyme design towards more efficient catalysts. One approach to study enzymes involved in chiral chemistry is through the use of computational models that are able to simulate the chemical reaction taking place. The potato epoxide hydrolase is one enzyme that is known to be both highly enantioselective, while still being robust upon mutation of residues to change substrate scope. The enzyme was used to investigate the epoxide hydrolysis mechanism for a number of different substrates, using the EVB approach to the reaction both in solution and in several enzyme variants. In addition to this, work has been performed on new ways of performing simulations of divalent transition metals, as well as development of new simulation software.

The basis of this research project stems from reflections upon the process of composition for electroacoustic audio-visual music. These are fixed media works in which sound and image materials are accessed, generated, explored and configured in creation of a musically informed audio-visual expression. Within the process of composition, the composer must decide how to effectively draw relationships between these time based media and their various abstract and mimetic materials. This process usually has no codified laws or structures and results in relationships that are singular to the individual artworks. The composer uses their own experience and intuition in assessing how best to associate sounds and images and they will use their own interpretation of the materials to evaluate the how successful they are in realising their intentions. But what is there to say that the interpretation made by the composer bares any resemblance to interpretations made by audiences? The current research sought to assess any trends or commonalities in how people interpret such works. Utilising a combination of empirical research, composition and scholarly study, the project investigated various theoretical approaches to interpretation and the occurrence of correlation between compositional intention and audience interpretation. Models from different theoretical disciplines were combined in order to build up a picture of the processes involved in making interpretations, and to aid in the rationalisation of empirical data. The application of three methodological approaches allowed for the topic to be considered from a diversity of perspectives, and for triangulation to take place in confirmation of the research outcomes. The way in which individuals build up interpretations from non-codified abstract and mimetic materials also provided a suitable case study for the critique and assessment of various theoretical approaches to interpretation. The project challenges structuralist approaches to interpretation, drawing together theoretical materials and empirical research findings in support of a post-structrualist model of interpretation that demonstrates the absolutely vital role played by context - the framing of the artwork in the consciousness of the individual audience member.

In a typical modern gas turbine engine, the nozzle guide vanes (NGVs) endure the highest operating temperatures. There exists a great drive in the turbine industry to increase the turbine inlet temperatures leading to higher thermal efficiency. This has led to a drive to increase turbine vane- and blade-cooling. Numerical modelling has to a large degree replaced empirical codes and models as the main research tool regarding simulation of blade-cooling. Outdated empirical solvers have made way for commercial CFD solvers such as FLUENT, a Reynolds-averaged Navier-Stokes (RANS) solver. One such empirical solver, TACT1, has until recently still proved to yield acceptable results. A comparative study has been done using the T56 NGV blade to establish the differences, advantages and disadvantages of these 2 codes. The engine and subsequent NGV blade were analysed using NREC, STAN5, LOSS3D and TACT1. RANS simulations were found to be computationally expensive. TACT1 yielded acceptable results compared with computational cost. For modern-day designers, RANS would be the preferred tool. / Dissertation (MEng)--University of Pretoria, 2009. / Mechanical and Aeronautical Engineering / unrestricted

A crescente adoção do paradigma experimental na pesquisa em Engenharia de Software visa a obtenção de evidências experimentais sobre as tecnologias propostas para garantir sua correta avaliação e para a construção de um corpo de conhecimento sólido da disciplina. Uma das abordagens de pesquisa experimental é a revisão sistemática, um método rigoroso, planejado e auditável para a realização da coleta e análise crítica de dados experimentais disponíveis sobre um determinado tema de pesquisa. Apesar de produzir resultados confiáveis, a condução de uma revisão sistemática pode ser trabalhosa e muitas vezes demorada, principalmente quando existe um grande volume de estudos a serem considerados, selecionados e avaliados. Uma solução encontrada na literatura é a utilização de ferramentas de Mineração Visual de Textos (VTM) como a Projection Explorer (PEx) para apoiar a fase de seleção e análise de estudos primários no processo de revisão sistemática. Neste trabalho foi realizada uma reengenharia de software na ferramenta PEx com dois objetivos principais: apoiar, utilizando VTM, a fase de seleção e análise de estudos primários no processo de revisão sistemática e implementar novos requisitos não-funcionais relativos à melhoria da manutenibilidade e escalabilidade da ferramenta. Como resultado foi construída uma plataforma modular para a instanciação de ferramentas de visualização e, a partir da mesma, uma ferramenta de revisão sistemática apoiada por VTM. Os resultados de um estudo de caso executado com a ferramenta mostraram que a abordagem de aplicação de técnicas VTM usada nesse contexto é viável e promissora, melhorando tanto a performance quanto a efetividade da seleção / The increasing adoption of the experimental paradigm in Software Engineering research aims at obtaining experimental evidence of the proposed technologies to ensure their proper evaluation and to build a solid body of knowledge for the discipline. One approach of experimental research is the systematic review, a rigorous, auditable and planned method to carry out the collection and analysis of experimental data available on a particular research topic. Despite producing reliable results, conducting a systematic review can be a cumbersome and often lengthy process, especially when a large volume of studies is to be considered, selected and evaluated. One solution found in the literature is the use of Visual Text Mining (VTM) tools such as the Projection Explorer (PEx) to support the selection and analysis of primary studies in the systematic review process. In this work a software re-engineering was performed on PEx with two main goals: to support, using VTM, the stage of selection and analysis of primary studies in the systematic review process and to implement new non-functional requirements related to improving the maintainability and scalability of the tool. The results were the building of a modular platform for instantiating visualization tools and, from it, the instantiation of a systematic review tool supported by VTM. The results of a case study carried out with the tool showed that the VTM approach used in this context is feasible and promising, improving both performance and the effectiveness of selection

O escopo desta dissertação é o desenvolvimento de uma metodologia para a detecção e diagnóstico de falhas em processos industriais baseado em modelos empíricos no subespaço das variáveis do processo com expansão não linear das bases. A detecção e o diagnóstico de falhas são fundamentais para aumentar a segurança, confiabilidade e lucratividade de processos industriais. Métodos qualitativos, quantitativos e baseados em dados históricos do processo têm sido estudados amplamente. Para demonstrar as vantagens da metodologia proposta, ela será comparada com duas metodologias consideradas padrão, uma baseada em Análise de Componentes Principais (PCA) e a outra baseada em Mínimos Quadrados Parciais (PLS). Dois estudos de casos são empregados nessa comparação. O primeiro consiste em um tanque de aquecimento com mistura e o segundo contempla o estudo de caso do processo da Tennessee Eastman. As vantagens da metodologia proposta consistem na redução da dimensionalidade dos dados a serem usados para um diagnóstico adequado, além de detectar efetivamente a anormalidade e identificar as variáveis mais relacionadas à falha, permitindo um melhor diagnóstico. Além disso, devido à expansão das bases dos modelos é possível trabalhar efetivamente com sistemas não lineares, através de funções polinomiais e exponenciais dentro do modelo. Adicionalmente o trabalho contém uma metodologia de validação dos resultados da metodologia proposta, que consiste na eliminação das variáveis do melhor modelo obtido pelos Modelos Empíricos, através do método Backward Elimination. A metodologia proposta forneceu bons resultados na área do diagnóstico de falhas: conseguiu-se uma grande diminuição da dimensionalidade nos sistemas estudados em até 93,55%, bem como uma correta detecção de anormalidades e permitiu a determinação das variáveis mais relacionadas às anormalidades do processo. As comparações feitas com as metodologias padrões permitiram demonstrar que a metodologia proposta tem resultados superiores, pois consegue detectar as anormalidades em um espaço dimensional reduzido, detectando comportamentos não lineares e diminuindo incertezas. / Fault detection and diagnosis are critical to increasing the safety, reliability, and profitability of industrial processes. Qualitative and quantitative methods and process historical data have been extensively studied. This article proposes a methodology for fault detection and diagnosis, based on historical data of processes and the creation of empirical models with the expansion of nonlinear bases (polynomial and exponential bases) and regularization techniques. To demonstrate the advantages of the proposed approach, it is compared with two standard methodologies: Principal Components Analysis (PCA) and the Partial Least Squares (PLS), performed in two case studies: a mixed heating tank and the Tennessee Eastman Process. The advantages of the proposed methodology are the reduction of the dimensionality of the data used, in addition to the effective detection of abnormalities, identifying the variables most related to the fault. Furthermore, the work contains a methodology to validate the diagnosis results consisting of variable elimination from the best empirical models with the Backward Elimination algorithm. The proposed methodology achieved a promising performance, since it can decrease the dimensionality of the studied systems up to 93.55%, reducing uncertainties, and capturing nonlinear behaviors.

The objective of this research is to show the utility of roles and personality characteristics to the evaluation and formation of software development teams. The goals of this research include demonstrating empirically that Belbin's team roles can be used to form and evaluate software teams, providing a partial validation of the analyses by using the Belbin roles to analyze teams from the software industry, and comparing the personality data collected for this research to data from two previous studies and to the general population. In the highly competitive software industry, improving the software development process can be critical to a company's success. More specifically, improving a team's productivity can save employers significant time and money. This investigation addresses the productivity of software development teams in a series of studies. First, controlled studies empirically show that Belbin's roles can be used in team formation to improve team performance. Second, additional studies, both qualitative and quantitative, demonstrate that Belbin's roles can be used as criteria in team evaluation and formation. Finally, teams from the software development industry are evaluated, providing a partial validation of the usefulness of Belbin's roles to software teams. The cumulative effect of the results of the studies in this investigation demonstrate that Belbin's roles can be used effectively in team formation and evaluation. Specifically, Belbin's roles for leadership and innovation are shown in empirical studies to be important in the formation of software teams, and all of the Belbin roles are used in the evaluation of teams in academia as well as in industry. The results of this investigation should be used in team formation and evaluation, in an academic setting as well as in the software development industry. For team evaluation, deficiencies uncovered in the Belbin roles should be remedied, and positive aspects should be encouraged. In team formation, teams should contain the complement of Belbin roles and should specifically contain the leadership and innovation roles focused on as part of this investigation. It is clear from this investigation that Belbin's roles can be used effectively to improve software development teams. / Ph. D.

L’estimation structurelle des modèles de demande sur des marchés de produits différenciés joue un rôle important en économie. Elle permet de mieux comprendre les choix des consommateurs et, entre autres, de mesurer les effets d’une fusion d’entreprise, de l’introduction d’un nouveau produit sur le marché ou d’une nouvelle régulation. L’approche traditionnelle consiste à spécifier un modèle d’utilité, typiquement un modèle d’utilité aléatoire additif, à en calculer ses demandes et à inverser ces dernières pour obtenir des équations de demande inverse qui serviront de base pour l’estimation. Toutefois, en général, ces demandes inverses n’ont pas de forme analytique. L'estimation exige donc une inversion numérique et l’emploi de procédures d’estimation non-linéaire, qui peuvent être difficiles à mettre en oeuvre et chronophages.Cette thèse adopte une approche différente, en développant de nouveaux modèles de demande inverse qui sont cohérents avec un modèle d’utilité de consommateurs hétérogènes. Cette approche permet de capter de façon plus flexible les substitutions entre les produits, grâce à de simples régressions linéaires basées sur des données incluant les parts de marché, les prix et les caractéristiques des produits. Le premier chapitre de cette thèse développe le modèle inverse product differentiation logit (IPDL), qui généralise les modèles logit emboîtés, permettant ainsi de capter de façon flexible les substitutions entre les produits, y compris de la complémentarité. Il montre que le modèle IPDL appartient à une classe de modèles de demande inverse, nommée generalized inverse logit (GIL), laquelle inclut une grande majorité de modèles d’utilité aléatoire additifs qui ont été utilisés à des fins d'estimation de la demande. Le second chapitre développe le modèle flexible inverse logit (FIL), un modèle GIL qui utilise une structure de nids flexible avec un nid pour chaque pair de produits. Il montre que le modèle FIL, projeté dans l’espace des caractéristiques des produits, permet d’obtenir des élasticités-prix qui dépendent directement des caractéristiques des produits et, en utilisant des simulations de Monte-Carlo, qu’il est capable de reproduire celles du "flexible" modèle logit à coefficients aléatoires. Le troisième chapitre étudie la micro-fondation du modèle GIL. Il montre que les restrictions que le modèle GIL impose sur la fonction de demande inverse sont des conditions nécessaires et suffisantes de cohérence avec un modèle de consommateurs hétérogènes maximisant leur fonction d’utilité, connu sous le nom de perturbed utility model (PUM). Il montre également que tout modèle GIL génère une fonction de demande qui satisfait une légère variante des conditions de Daly-Zachary, laquelle permet de combiner substituabilité et complémentarité en demande. / Estimation of structural demand models in differentiated product markets plays an important role in economics. It allows to better understand consumers’ choices and, amongst other, to assess the effects of mergers, new products, and changes in regulation. The standard approach consists in specifying a utility model, typically an additive random utility model, computing its demands, and inverting them to obtain inverse demand equations, which will serve as a basis for estimation. However, since these inverse demands have generally no closed form, estimation requires numerical inversion and non-linear optimization, which can be painful and time-consuming. This dissertation adopts a different approach, developing novel inverse demand models, which are consistent with a utility model of heterogeneous consumers. This approach allows to accommodate rich substitution patterns thanks to simple linear regressions with data on market shares, prices and product characteristics. The first chapter of this dissertation develops the inverse product differentiation logit (IPDL) model, which generalizes the nested logit models to allow for richer substitution patterns, including complementarity. It also shows that the IPDL model belongs to the class of generalized inverse logit (GIL) models, which includes a vast majority of additive random utility models that have been used for demand estimation purposes. The second chapter develops the flexible inverse logit (FIL) model, a GIL model that uses a flexible nesting structure with a nest for each pair of products. It shows that the FIL model, projected into product characteristics space, makes the price elasticities depending on product characteristics directly and, using Monte Carlo simulations, that it is able to mimic those from the "flexible" random coefficient logit model. The third chapter studies the micro-foundation of the GIL model. It shows that the restrictions that the GIL model imposes on the inverse demand function are necessary and sufficient for consistency with a model of heterogeneous and utility-maximizing consumers, called perturbed utility model. It also shows that any GIL model yields a demand function that satisfies a slight variant of the Daly-Zachary conditions, which allows to combine substitutability and complementarity in demand.