Cette thèse s’inscrit dans le cadre de l’amélioration des prévisions aérothermiques qui suscite l’intérêt croissant des industriels aéronautiques. Elle consiste à évaluer l’apport des méthodes URANS avancées de type SAS dans la prévision des flux de chaleur turbulents et pariétaux pour des écoulements turbulents chauffés. Elle vise aussi à situer ces approches par rapports aux modèles URANS classiques de type DRSM et hybrides RANS/LES comme la ZDES. Une extension de l’approche SAS à un modèle DRSM a d’abord été proposé afin d’obtenir une meilleure restitution des tensions de Reynolds résolues et modélisées. Ce modale SAS-DRSM a été implanté dans le code elsA de l’ONERA. Nous avons ensuite évalué les approches SAS disponibles avec ce code sur la prévention d’écoulements aérothermiques rencontrés sur avion dans un compartiment de moteur. Ces études ont montré que les approches SAS améliorent la représentation des écoulements par rapport aux modèles URANS classiques. Elles aboutissent à des écoulements fortement tridimensionnels avec de nombreuses structures turbulentes. Ces structures induisent un mélange turbulent accru et donc une meilleure prévision du flux de chaleur pariétal. De plus, nos travaux ont situé les approches de type SAS comme des méthodes plus précises que les méthodes URANS classiques sans augmentation importante du coût de calcul. Les modèles SAS ne résolvent pas les plus petites structures caractéristiques du mouvement turbulent par rapport à la ZDES qui montre des prévisions supérieures. Le modèle SAS-RDSM offre néanmoins la meilleur alternative de type SAS. Enfin, l’étude du flux de chaleur turbulent semble retrouver le fait que l’hypothèse classique de nombre de Prandtl turbulent constat n’est pas valable dans toutes les zones de l’écoulement. / The improvement of aerothermal predictions is a major concern for aeronautic manufacturers. In line with this issue, SAS approaches are assessed on the prediction of wall and turbulent heat fluxes for heated-turbulent flows. This study also aims at evaluating these advanced URANS methods in regard to DRSM models and hybrid RANS/LES approaches as ZDES. Firstly, we proposed to combine the SAS approach and a DRSM model in order to better reproduce both resolved and modelled Reynolds stresses. This new model, called SAS-DRSM, was implemented in ONERA Navier-Strokes code elsA. Unsteady simulations of two heated turbulent flows encountered in an aircraft engine compartment were then performed to evaluate all the SAS models available in the code. These numerical studies demonstrated that SAS approaches improve prediction of the flows compared to classical URANS models. They lead to full 3D flows with many turbulent structures. These structures favour turbulent mixing and thus induce a better prediction of the wall heat fluxes. Moreover, the numerical simulations showed that SAS methods are more accurate than classical URANS models without increasing significantly calculation costs. SAS approaches are not able to resolve the smallest turbulent structures in relation to ZDES which provides better predictions. Finally, the investigation of the turbulent heat flux suggested that the constant turbulent Prendtl number assumption, that is characteristic of classical URANS models, may not be valid in some regions of the flow.

Experimentos cujas variaveis respostas s~ ao proporcoes ou contagens, sao muito comuns nas diversas areas do conhecimento, principalmente na area agricola. Na analise desses experimentos, utiliza-se a teoria de modelos lineares generalizados, bastante difundida (McCullagh & Nelder, 1989; Demetrio, 2001), em que as respostas sao independentes. Caso a variancia estimada seja maior do que a esperada, estima-se o parametro de dispersao, incluindo-o no processo de estimaçao dos parametros. Quando a variavel resposta e observada ao longo do tempo, pode haver uma correlacao entre as observacoes e isso tem que ser levado em consideracao na estimacao dos parametros. Uma forma de se trabalhar essa correlacao e aplicando a metodologia de equacoes de estimacao generalizada (EEG), discutida por Liang & Zeger (1986), embora, neste caso, o interesse esteja nas estimativas dos efeitos fixos e a inclusao da matriz de correlacao de trabalho sirva para se obter um melhor ajuste. Uma outra alternativa e a inclusao, no preditor linear, de um efeito latente para captar variabilidades nao consideradas no modelo e que podem in uenciar nos resultados. No presente trabalho, usa-se uma forma combinada de efeito aleatorio e parametro de dispersao, incluidos conjuntamente na estimacao dos parametros. Essa metodologia e aplicada a um conjunto de dados obtidos de um experimento com camu-camu, com objetivo de se avaliarem quais os melhores metodos de enxertia e tipos de porta-enxertos que podem ser utilizados, atraves da proporcao de pegamentos da muda. Varios modelos sao ajustados, desde o modelo em parcelas subdivididas (supondo independencia), ate o modelo em que se considera o parametro de dispersao e efeito aleatorio conjuntamente. Ha evidencias de que o modelo em que se inclui o efeito aleatorio e o parametro de dispersao, conjuntamente, resultam em melhores estimativas dos parametros. Outro conjunto de dados longitudinais, com milho transgenico MON810, em que a variavel resposta e o numero de lagartas (Spodoptera frugiperda), e utilizado. Neste caso, devido ao excesso de respostas zero, emprega-se o modelo de regressao Poisson in acionado de zeros (ZIP), alem do modelo Poisson padrao, em que as observacoes sao consideradas independentes, e do modelo Poisson in acionado de zeros com efeito aleatorio. Os resultados mostram que o efeito aleatorio incluido no preditor foi nao significativo e, assim, o modelo adotado e o modelo de regressao Poisson in acionado de zeros. Os resultados foram obtidos usando-se os procedimentos NLMIXED, GENMOD e GPLOT do SAS - Statistical Analysis System, versao 8.2. / Experiments which response variables are proportions or counts are very common in several research areas, specially in the area of agriculture. The theory of generalized linear models, well difused (McCullagh & Nelder, 1989; Demetrio, 2001), is used for analyzing these experiments where the responses are independent. If the estimated variance is greater than the expected variance, the dispersion parameter is estimated including it on the parameter estimation process. When the response variable is observed over time a correlation among observations might occur and it should be taken into account in the parameter estimation. A way of dealing with this correlation is applying the methodology of generalized estimating equations (GEEs) discussed by Liang & Zeger (1986) although, in this case, the interest is on the estimates of the xed efect being the inclusion of a working correlation matrix useful to obtain more accurate estimates. Another alternative is the inclusion of a latent efect in the linear predictor to explain variabilities not considered in the model that might in uence the results. In this work the random efect and the dispersion parameter are combined and included together in the parameter estimation. Such methodology is applied to a data set obtained from an experiment realized with camu-camu to evaluate, through proportion of grafting well successful of seedling, which kind of grafting and understock are suitable to be used. Several models are fitted, since the split plot model (with independence assumption) up to the model where the dispersion parameter and the random efect are considered together. There is evidence that the model including the random efect and the dispersion parameter together, produce better estimates of the parameters. Another longitudinal data set used here comes from an experiment realized with the MON810 transgenic corn where the response variable is the number of caterpillars (Spodoptera frugiperda). In this case, due to the excessive number of zeros obtained, the zero in ated Poisson regression model (ZIP) is used in addition to the standard Poisson model, where observations are considered independent, and the zero in ated Poisson regression model with random efect. The results show that the random efect included in the linear predictor was not significant and, therefore, the adopted model is the zero in ated Poisson regression model. The results were obtained using the procedures NLMIXED, GENMOD and GPLOT available on SAS - Statistical Analysis System, version 8.2.

This thesis is focused on SAS Enterprise Intelligence Platform product and it's capabilities to integrate within a Business Intelligence solution. The aim of the thesis is to describe integration technolgies that the platform features, as well as to determine their application field and compare them, eventually add usage examples. The first part of the thesis explains the general concept and architecture of Business Intelligence, afterwards the reader gets familiar with the SAS Enterprise Intelligence Platform, it's stucture and components and it's Business Intelligence market position. The second part of the thesis contains description (how they work and what they are good for) of the integration technologies available in SAS Enterprise Intelligence Platform. Those technologies are mostly implementations of the most common industry standards (database APIs, COM/DCOM, CORBA, web services). The study also includes description of these standards supported by SAS. The thesis features also comparisions of the integration technologies, namely comparison of database API implementations and comparision of Integrated Object Model API with SAS BI Web Services.

This master's degree thesis focuses on predictive analytics. This type of analysis uses historical data and predictive models to predict future phenomenon. The main goal of this thesis is to describe predictive analytics and its process from theoretical as well as practical point of view. Secondary goal is to implement project of predictive analytics in an important insurance company operating in the Czech market and to improve the current state of detection of fraudulent insurance claims. Thesis is divided into theoretical and practical part. The process of predictive analytics and selected types of predictive models are described in the theoretical part of the thesis. Practical part describes the implementation of predictive analytics in a company. First described are techniques of data organization used in datamart development. Predictive models are then implemented based on the data from the prepared datamart. Thesis includes examples and problems with their solutions. The main contribution of this thesis is the detailed description of the project implementation. The field of the predictive analytics is better understandable thanks to the level of detail. Another contribution of successfully implemented predictive analytics is the improvement of the detection of fraudulent insurance claims.

The master' s thesis deals with cluster data analysis. There are explained basic concepts and methods from this domain. Result of the thesis is Cluster analysis tool, in which are implemented methods K-Medoids and DBSCAN. Adjusted results on real data are compared with programs Rapid Miner and SAS Enterprise Miner.

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A customers propensity to buy a certain product is a widely researched field and is applied in multiple industries. In this thesis it is showed that using binary classification on data from Scandinavian Airlines can predict their customers propensity to book a flight within the next coming seven days. A comparison between logistic regression and support vector machine is presented and logistic regression with reduced number of variables is chosen as the final model, due to it’s simplicity and accuracy. The explanatory variables contains exclusively booking history, whilst customer demographics and search history is showed to be insignificant. / En kunds benägenhet att göra ett visst köp är ett allmänt undersökt område som applicerats i flera olika branscher. I den här studien visas det att statistiska binära klassificeringsmodeller kan användas för att prediktera Scandinavian Airlines kunders benägenhet att köpa en resa de kommande sju dagarna. En jämförelse är presenterad mellan logistisk regression och stödvektormaskin och logistisk regression med reducerat antal parametrar väljs som den slutgiltiga modellen tack vare sin enkelhet och träffsäkerhet. De förklarande variablerna är uteslutande bokningshistorik medan kundens demografi och sökdata visas vara insignifikant.

本研究旨在探討影響台灣地區的會計師事務所決定專業服務費用之各項因素，採用實 證方法（郵寄問卷）搜集開業於台灣地區（含台北市及高雄市）的執業會計師的意見 。本研究之目的有三：（一）瞭解影響會計師決定專業服務費用之因素。（二）會計 師事務所之特性與決定專業人員計費標準之關係。（三）協助會計師事務所研擬較合 理/的收費水準。 本研究之立論基於二組假設：（一）影響公費的因素（二）事務所的特質。前者含十 七個變數。一、時間二、專業技能及知識。三、成本。四、服務價值。五、法律責任 。六、過去收費標準。七、爭取業務之考慮。八、客戶的營業規模及狀況。九、事務 所聲譽。十、客戶的財務狀況及支付能力。十一、客戶的支付意願。十二、固定收費 標準。十三、通貨膨脹。十四、公會的收費標準。十五、競爭事務所的收費標準。十 六、國外會計師事務所之收費標準。十七、同行的收費標準。後者有十一個變數：一 、地理位置。二、組織結構。三、辦公室數目。四、人口。五、未執業會計師人數。 六、合夥人數。七、來自上市公司之公費收入。八、主要收入項目。九、專業服務收 入金額。十、計費標準。十一、國外會計師之合作關係。 本研究利用ＳＡＳ統計軟體，對回收之問卷作分析。分析結果顯示第一組之假設變數 中，「爭取業務之考慮」、「客戶財務狀況及支付能力」、「客戶支付意願」、「通 貨膨脹」、「競爭事務所的收費標準」、「國外會計師事務所之收費標準」大多數之 會計師事務所均不同意其為決定專業服務費用之因素。第二組變數中，」所在地區」 及「主要收入項目」經卡方檢定，顯示與專業人員計費標準之決定並無顯著之關係。