High security level must be guaranteed in applications in order to mitigate risks during the deployment of information systems in open network environments. However, a significant number of legacy systems remain in use which poses security risks to the enterprise' assets due to the poor technologies used and lack of security concerns when they were in design. Software reengineering is a way out to improve their security levels in a systematic way. Model driven is an approach in which model as defined by its type directs the execution of the process. The aim of this research is to explore how model driven approach can facilitate the software reengineering driven by security demand. The research in this thesis involves the following three phases. Firstly, legacy system understanding is performed using reverse engineering techniques. Task of this phase is to reverse engineer legacy system into UML models, partition the legacy system into subsystems with the help of model slicing technique and detect existing security mechanisms to determine whether or not the provided security in the legacy system satisfies the user's security objectives. Secondly, security requirements are elicited using risk analysis method. It is the process of analysing key aspects of the legacy systems in terms of security. A new risk assessment method, taking consideration of asset, threat and vulnerability, is proposed and used to elicit the security requirements which will generate the detailed security requirements in the specific format to direct the subsequent security enhancement. Finally, security enhancement for the system is performed using the proposed ontology based security pattern approach. It is the stage that security patterns derived from security expertise and fulfilling the elicited security requirements are selected and integrated in the legacy system models with the help of the proposed security ontology. The proposed approach is evaluated by the selected case study. Based on the analysis, conclusions are drawn and future research is discussed at the end of this thesis. The results show this thesis contributes an effective, reusable and suitable evolution approach for software security.

Software products have been racing against aging problem for most of their lifecycles, and evolution is the most effective and efficient solution to this problem. Model-Driven Architecture (MDA) is a new technique for software product for evolving development and reengineering methods. The main steps for MDA are to establish models in different levels and phases, therefore to solve the challenges of requirement and technology change. However, there is only a standard established by Object Management Group (OMG) but without a formal method and approach. Presently, MDA is widely researched in both industrial and research areas, however, there is still without a smooth approach to realise it especially in electronic learning (e-learning) system due to the following reasons: (1) models’ transformations are hard to realise because of lack of tools, (2) most of existing mature research results are working for business and government services but not education area, and (3) most of existing model-driven researches are based on Model-Driven Development (MDD) but not MDA because of OMG standard’s preciseness. Hence, it is worth to investigate an MDA-based method and approach to improve the existing software development approach for e-learning system. Due to the features of MDA actuality, a MDA-based evolution method and approach is proposed in this thesis. The fundamental theories of this research are OMG’s MDA standard and education pedagogical knowledge. Unified Modelling Language (UML) and Unified Modelling Language Profile are hired to represent the information of software system from different aspects. This study can be divided into three main parts: MDA-based evolution method and approach research, Platform-Independent Model (PIM) to Platform-Specific Model (PSM) transformation development, and MDA-based electronic learning system evolution. Top-down approach is explored to develop models for e-learning system. A transformation approach is developed to generate Computation Independent Model (CIM), Platform-Independent Model (PIM), and Platform-Specific Model (PSM); while a set of transformation rules are defined following MDA standard to support PSM’ s generation. In addition, proposed method is applied in an e-learning system as a case study with the prototype rules support. In the end, conclusions are drawn based on analysis and further research directions are discussed as well. The kernel contributions are the proposed transformation rules and its application in electronic learning system.

Strategic alliances are a prevalent form of business organization. The critical characteristics of strategic alliances are detailed using Coase (1937) and the resulting definition tested through primary research and the alternative form, the infrastructure alliance posited. The thesis examines whether strategic alliances add value in the European banking sector through four types of analysis at two levels of engagement - a 23 historical review (at industry level); a review of over 400 papers in the academic literature; a questionnaire survey (at firm level) and in-depth interviews (at firm level). Bankers high pre-existing propensity to enter into strategic alliances is determined and three lifecycles, and the underpinning, conditions identified - Clubs and Consortium Banks, Bankassurance and the Virtual bank - the latter involving a fundamental change in Coase (1937) enabled by the underpinning technology. Bankers were found to be followers of potential business steams and the strategic alliance was one form of market entry. The questionnaire research, however, identified European bankers prefer to enter into alliances (as opposed to own branch or M&A) only in countries which had the appropriate supporting conditions such as definable, enforceable and terminable contracts, the provision of accounting information, stable governments and economic freedom. Direct discussions with senior bankers resulted in a number of valuable insights into the conceiving, forming, organizing evolving and dissolving of alliances. Further research into the infrastructure alliance, including 'oscillation' between infrastructure and strategic forms is proposed. The Co-Evolution Model of Strategic Alliances is proposed and taxonomy consisting of parallel co-evolution, convergent coevolution, divergent co-evolution and the subsidiary taxonomy of differential parallel coevolution, differential convergent co-evolution and differential divergent co-evolution detailed and further research suggested. Strategic alliances are found to add value in European banking but this value is contingent on the strength of the business stream, the global, national and industry conditions and the nature of managerial decisions and drive.

A Tomografia por Impedância Elétrica tem como objetivo estimar a distribuição de impedância elétrica dentro de uma região a partir de medidas de potencial elétrico coletadas apenas em seu contorno externo quando corrente elétrica é imposta neste mesmo contorno. Uma das aplicações para esta tecnologia é o monitoramento das condições pulmonares de pacientes em Unidades de Tratamento Intensivo. Dentre vários algoritmos, destacam-se os filtros de Kalman que abordam o problema de estimação sob o ponto de vista probabilístico, procurando encontrar a distribuição de probabilidade do estado condicionada à realização das medidas. Para que estes filtros possam ser utilizados, um modelo de evolução temporal do sistema sendo observado deve ser adotado. Esta tese propõe o uso de um modelo de evolução para a variação de volume de ar nos pulmões durante a respiração de um paciente sob ventilação artificial. Este modelo é utilizado no unscented Kalman filter, uma extensão não linear do filtro de Kalman. Tal modelo é ajustado em paralelo à estimação do estado, utilizando um esquema dual de estimação. Um algoritmo de segmentação de imagem é proposto para identificar as regiões pulmonares nas imagens estimadas e assim utilizar o modelo de evolução. Com o intuito de melhorar as estimativas, o método do erro de aproximação é utilizado no modelo de observação para mitigar os erros de modelagem e informação a priori é adicionada na solução do problema inverso mal-posto. O método é avaliado através de simulações numéricas e ensaio experimental coletado em um voluntário. Os resultados mostram que o método proposto melhora as estimativas feitas pelo filtro de Kalman, propiciando a visualização de imagens absolutas, dinâmicas e com bom nível de contraste entre os tecidos e órgãos internos. / Electrical impedance tomography estimates the electrical impedance distribution within a region given a set of electrical potential measurements acquired along its boundary at the same time that electrical currents are imposed on the same boundary. One of the applications of this technology is lung monitoring of patients in Intensive Care Units. One class of algorithms employed for the estimation are the Kalman filters which deal with the estimation problem in a probabilistic framework, looking for the probability density function of the state conditioned to the acquired measurements. In order to use such filters, an evolution models of the system must be employed. This thesis proposes an evolution model of the variation of air in the lungs of patients under artificial ventilation. This model is used on the Unscented Kalman Filter, a nonlinear extension of the Kalman filter. This model is adjusted in parallel to the state estimation, in a dual estimation scheme. An image segmentation algorithm is proposed for identifying the lungs in the images. In order to improve the estimate, the approximation error method is employed for mitigating the observation model errors and prior information is added for the solution of the ill-posed inverse problem. The method is evaluated with numerical simulations and with experimental data of a volunteer. The results show that the proposed method increases the quality of the estimates, allowing the visualization of absolute and dynamic images, with good level of contrast between the tissues and internal organs.

Made available in DSpace on 2010-04-20T20:51:06Z (GMT). No. of bitstreams: 3 154789.pdf.jpg: 18069 bytes, checksum: ff12d70b21d014f039393abb671f279c (MD5) 154789.pdf: 1049389 bytes, checksum: 0ff63917a934eb6da5ca371a9c03217c (MD5) 154789.pdf.txt: 321453 bytes, checksum: a86ebeb8c378360bbdfaebf51cba963d (MD5) Previous issue date: 2006-11-14T00:00:00Z / The main purpose of this research was to fully understand the agglomeration phenomenon, specifically at shoes clusters of Franca, which is an important shoes productor the country, responsible for approximately 10% of the Brazilian total shoes production. The concept of cluster, developed by Porter (1990) was used. A model was presented to explain the development of clusters, The presupposes of the model were observed in Franca´s cluster. A case study was elaborated from the interviews made at nine shoes company, suppliers and support organisms. With some exceptions, the pressuposts were observed in Franca´s shoes cluster. As a result, also, was made an evaluation of Franca based on Porter´s (1990) diamond model. All the factors from the diamond model were assessed. The sources used were primary and secundary. Finally, some actions are purposed and policies to increase the competitiveness of Franca. / O objetivo deste trabalho foi compreender o fenômeno da concentração geográfica de empresas, especificamente no cluster calçadista de Franca, importante pólo produtor calçadista no país, responsável por aproximadamente 10% do total da produção calçadista brasileira. Utiliza-se o conceito de cluster desenvolvido por Porter (1990). É apresentado um modelo com pressupostos que explicariam o surgimento e evolução dos clusters. Os pressupostos do modelo foram observados no cluster de Franca. O principal pressuposto do modelo é que uma inovação revolucionária no processo, combinada com condições locais específicas, pode originar um cluster. Foi elaborado um estudo de caso a partir das entrevistas feitas em nove empresas do setor calçadistas, empresas de setores fornecedores e setores de apoio. Com algumas exceções, os pressupostos foram observados na trajetória de evolução do cluster calçadista de Franca. No momento, o cluster está atravessando sua fase de maturidade, e devem ser feitas políticas e ações coordenadas para evitar o declínio ou pós-maturidade do cluster. Como resultado também, foi feita a avaliação do cluster de Franca segundo o modelo do diamante de Porter (1990) para caracterizar os principais pilares para a manutenção da vantagem competitiva do cluster. Foram analisadas as condições dos fatores, condições da demanda, setores correlatos e de apoio e a estratégia, estrutura e rivalidade das empresas. As fontes utilizadas foram primárias e secundárias. Finalmente, são propostas algumas ações e políticas no sentido de incrementar a competitividade do cluster calçadista de Franca.

A Tomografia por Impedância Elétrica tem como objetivo estimar a distribuição de impedância elétrica dentro de uma região a partir de medidas de potencial elétrico coletadas apenas em seu contorno externo quando corrente elétrica é imposta neste mesmo contorno. Uma das aplicações para esta tecnologia é o monitoramento das condições pulmonares de pacientes em Unidades de Tratamento Intensivo. Dentre vários algoritmos, destacam-se os filtros de Kalman que abordam o problema de estimação sob o ponto de vista probabilístico, procurando encontrar a distribuição de probabilidade do estado condicionada à realização das medidas. Para que estes filtros possam ser utilizados, um modelo de evolução temporal do sistema sendo observado deve ser adotado. Esta tese propõe o uso de um modelo de evolução para a variação de volume de ar nos pulmões durante a respiração de um paciente sob ventilação artificial. Este modelo é utilizado no unscented Kalman filter, uma extensão não linear do filtro de Kalman. Tal modelo é ajustado em paralelo à estimação do estado, utilizando um esquema dual de estimação. Um algoritmo de segmentação de imagem é proposto para identificar as regiões pulmonares nas imagens estimadas e assim utilizar o modelo de evolução. Com o intuito de melhorar as estimativas, o método do erro de aproximação é utilizado no modelo de observação para mitigar os erros de modelagem e informação a priori é adicionada na solução do problema inverso mal-posto. O método é avaliado através de simulações numéricas e ensaio experimental coletado em um voluntário. Os resultados mostram que o método proposto melhora as estimativas feitas pelo filtro de Kalman, propiciando a visualização de imagens absolutas, dinâmicas e com bom nível de contraste entre os tecidos e órgãos internos. / Electrical impedance tomography estimates the electrical impedance distribution within a region given a set of electrical potential measurements acquired along its boundary at the same time that electrical currents are imposed on the same boundary. One of the applications of this technology is lung monitoring of patients in Intensive Care Units. One class of algorithms employed for the estimation are the Kalman filters which deal with the estimation problem in a probabilistic framework, looking for the probability density function of the state conditioned to the acquired measurements. In order to use such filters, an evolution models of the system must be employed. This thesis proposes an evolution model of the variation of air in the lungs of patients under artificial ventilation. This model is used on the Unscented Kalman Filter, a nonlinear extension of the Kalman filter. This model is adjusted in parallel to the state estimation, in a dual estimation scheme. An image segmentation algorithm is proposed for identifying the lungs in the images. In order to improve the estimate, the approximation error method is employed for mitigating the observation model errors and prior information is added for the solution of the ill-posed inverse problem. The method is evaluated with numerical simulations and with experimental data of a volunteer. The results show that the proposed method increases the quality of the estimates, allowing the visualization of absolute and dynamic images, with good level of contrast between the tissues and internal organs.

Flooding is an important concern for the UK, as evidenced by the many extreme flooding events in the last decade. Improved flood risk intervention strategies are therefore highly desirable. The application of hydroinformatics tools, and optimisation algorithms in particular, which could provide guidance towards improved intervention strategies, is hindered by the necessity of performing flood modelling in the process of evaluating solutions. Flood modelling is a computationally demanding task; reducing its impact upon the optimisation process would therefore be a significant achievement and of considerable benefit to this research area. In this thesis sophisticated multi-objective optimisation algorithms have been utilised in combination with cutting-edge flood-risk assessment models to identify least-cost and most-benefit flood risk interventions that can be made on a drainage network. Software analysis and optimisation has improved the flood risk model performance. Additionally, artificial neural networks used as feature detectors have been employed as part of a novel development of an optimisation algorithm. This has alleviated the computational time-demands caused by using extremely complex models. The results from testing indicate that the developed algorithm with feature detectors outperforms (given limited computational resources available) a base multi-objective genetic algorithm. It does so in terms of both dominated hypervolume and a modified convergence metric, at each iteration. This indicates both that a shorter run of the algorithm produces a more optimal result than a similar length run of a chosen base algorithm, and also that a full run to complete convergence takes fewer iterations (and therefore less time) with the new algorithm.

My thesis is dealing with the Learnable Evolution Model (LEM), a new evolutionary method of optimization, which employs a classification algorithm. The optimization process is guided by a characteristics of differences between groups of high and low performance solutions in the population. In this thesis I introduce new variants of LEM using classification algorithm AdaBoost or SVM. The qualities of proposed LEM variants were validated in a series of experiments in static and dynamic enviroment. The results have shown that the metod has better results with smaller group sizes. When compared to the Estimation of Distribution Algorithm, the LEM variants achieve comparable or better values faster. However, the LEM variant which combined the AdaBoost approach with the SVM approach had the best overall performance.

Die Arbeit widmet sich der Entwicklung und numerischen Implementierung eines nichtlokalen kontinuumsmechanischen Schädigungsmodells zur Beschreibung des duktilen Versagens eines austenitischen TRIP-Stahlgusses. Dieser weist eine martensitische Phasenumwandlung während der Verformung auf. Das Umwandlungs- und Verfestigungsverhalten des Untersuchungswerkstoffs hängt stark von Temperatur und Spannungszustand ab. Deshalb wird ein vollständig thermomechanisch gekoppeltes Viskoplastizitätsmodell zugrunde gelegt, welches die temperaturabhängige Zug-Druck-Asymmetrie von Verfestigung und verformungsinduzierter Martensitentwicklung abbildet. Bei erhöhter Dehnrate können experimentell beobachtete Kreuzungseffekte der Fließkurven vorhergesagt werden. Die Schädigungsmodellierung baut auf dem viskoplastischen Grundmodell auf, wobei das netzunabhängige Verhalten durch eine Gradientenerweiterung im Rahmen der mikromorphen Theorie erreicht wird. Im Modell können verschiedene Ansätze für Schädigungsinitiierung und -entwicklung kombiniert werden. Die Einflüsse der Modellparameter auf die Ergebnisse von Risswachstumssimulationen werden für ausgewählte Modellvarianten untersucht und bewertet. Mithilfe erarbeiteter Kalibrierungsstrategien können die qualifizierten Varianten erfolgreich an experimentelle Ergebnisse von Kerbzugversuchen und bruchmechanischen Kompaktzugproben angepasst werden. / The present thesis comprises the development and numerical implementation of a non-local damage model in order to describe ductile failure of a cast austenitic TRIP-steel. The TRIP-steel shows a martensitic phase transformation during deformation. The transformation and strain hardening behavior is strongly dependent on temperature and stress state. For this reason, a fully thermomechanically coupled viscoplasticity model is proposed, which exhibits the temperature dependent tension-compression-asymmetry of strain hardening and deformation-induced martensite evolution. Experimentally observed crossing effects of the flow curves can be predicted at increased strain rates. The damage modeling is based on the viscoplastic basic model, whereby the mesh-independent behavior is achieved by a gradient extension within the framework of micromorphic theory. Different approaches for damage initiation and evolution can be combined within the model. The influences of the model parameters on results of crack growth simulations are investigated and evaluated for selected model variants. With the help of developed calibration strategies the qualified variants can be successfully adapted to experimental results of notched tensile tests and compact tension tests.

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