p. 1 - 154 / Submitted by Santiago Fabio (fabio.ssantiago@hotmail.com) on 2013-01-23T19:59:53Z No. of bitstreams: 1 333333.pdf: 616172 bytes, checksum: 1a19e0044e54f07cf7ed70740b658bd2 (MD5) / Made available in DSpace on 2013-01-23T19:59:53Z (GMT). No. of bitstreams: 1 333333.pdf: 616172 bytes, checksum: 1a19e0044e54f07cf7ed70740b658bd2 (MD5) Previous issue date: 2008 / As exigências do mercado por serviço e produtividade têm elevado o nível de complexidade operacional, estimulando a adoção de abordagens sofisticadas de gerenciamento logístico no âmbito das empresas. A logística, nesse contexto, surge como fonte de diferencial competitivo e fator determinante para o sucesso das organizações. O objetivo deste trabalho é verificar como as empresas de fertilizantes localizadas no Pólo de Aratu organizam e estruturam seus processos logísticos. Para tanto, foi selecionada uma amostra de três empresas sediadas na região, utilizando-se como base para coleta de dados o modelo Leading Edge Logistic, desenvolvido por Bowersox (1992). De acordo com esse modelo, o nível de desenvolvimento da estrutura logística de uma empresa pode ser analisado a partir de três dimensões básicas: formalização da organização logística, monitoramento de desempenho e o nível de adoção de tecnologia de informação. Desempenhos excelentes nessas três dimensões tendem a tornar a empresa mais flexível e eficiente. Constatou-se que as empresas de fertilizantes participantes deste estudo possuem uma estrutura logística formalizada. Além disso, apresentam sistematização dos indicadores de desempenho de forma abrangente e detalhada. Notou-se a necessidade de um melhor desenvolvimento de tecnologia da informação, principalmente na interação com parceiros externos, como, por exemplo, os fornecedores. Os resultados obtidos apontam que as empresas participantes da pesquisa possuem um longo caminho a trilhar em termos de desenvolvimento logístico. A dimensão tecnologia de informação ainda carece de melhor atenção. Os indicadores de desempenho logístico podem ser mais bem adequados às necessidades dos profissionais de logística. A expectativa é que o trabalho tenha contribuído para um maior conhecimento quanto à estruturação logística das empresas de fertilizantes localizadas no Pólo de Aratu, bem como para reflexão e debates à cerca do próprio segmento de fertilizantes. / Salvador

Genome-wide association studies have been used extensively to study hundreds of phenotypes and have determined thousands of associated SNPs whose underlying biology and causation is as yet largely unknown. Many previous studies attempted to clarify the causal biology by investigating overlaps of trait-associated variants with functional annotations, but lacked statistical rigor and examined incomplete subsets of available functional annotations. Additionally, it has been difficult to disentangle the relative contributions of different annotations that may show strong correlations with one another. In this thesis, we address these shortcomings and strengthen and extend the obtained results. Two methods, permutations and logistic regression, are applied in statistically rigorous analyses of genomic annotations and their observed enrichment or depletion of trait-associated SNPs. The genomic annotations range from genic regions and regulatory features to measures of conservation and aspects of chromatin structure. Logistic regressions in a number of trait-specific subsets identify genomic annotations influencing SNPs associated with both normal variation (e.g., eye or hair colour) and diseases, suggesting some generalities in the biological underpinnings of phenotypes. SNPs associated with phenotypes of the immune system are investigated and the results highlight the distinct aetiology for this subset. Despite the heterogeneity of the studied cancers, SNPs associated to different cancers are particularly enriched for conserved regions, unlike all other trait-subsets. Nonetheless, chromatin states are, perhaps surprisingly, among the most influential genomic annotations in all trait-subsets. Evolutionary conserved regions are rarely within the top genomic annotations despite their widespread use in prioritisation methods for follow-up studies. We identify a common set of enriched or depleted genomic annotations that significantly influence all traits, but also highlight trait-­‐specific differences. These annotations may be used for the computational prioritisation of variants implicated in phenotypes of interest. The approaches developed for this thesis are further applied to studies of a specific human complex trait (height) and gene expression in atherosclerosis.

This work investigates the factors that contribute to financial crises. We first study the Dow Jones index performance by grouping the daily adjusted closing value into a two-month window and finding several critical quantiles in each window. Then, we identify severe downturn in these quantiles and find that the 5th quantile is the best to identify financial crises. We then matched these quantiles with historical financial crises and gave a basic explanation about them. Next, we introduced all exogenous factors that could be related to the crises. Then, we applied a rapid Bayesian variable selection technique - Stochastic Search Variable Selection (SSVS) using a Bayesian logistic regression model. Finally, we analyzed the result of SSVS, leading to the conclusion that that the dummy variable we created for disastrous hurricane, crude oil price and gold price (GOLD) should be included in the model. / text

No description available.

Master of Science / Department of Computing and Information Sciences / William H. Hsu / Logistic regression is a model for function estimation that measures the relationship between independent variables and a categorical dependent variable, and by approximating a conditional probabilistic density function using a logistic function, also known as a sigmoidal function. Multinomial logistic regression is used to predict categorical variables where there can be more than two categories or classes. The most common type of algorithm for optimizing the cost function for this model is gradient descent. In this project, I implemented logistic regression using conjugate gradient descent (CGD). I used the 20 Newsgroups data set collected by Ken Lang. I compared the results with those for existing implementations of gradient descent. The conjugate gradient optimization methodology outperforms existing implementations.

Master of Science / Department of Statistics / Gary Gadbury / This report illustrates how to use two statistic methods to investigate the performance of a new technique to detect breast cancer and lung cancer at early stages. The two methods include logistic regression and classification and regression tree (CART). It is found that the technique is effective in detecting breast cancer and lung cancer, with both sensitivity and specificity close to 0.9. But the ability of this technique to predict the actual stages of cancer is low. The age variable improves the ability of logistic regression in predicting the existence of breast cancer for the samples used in this report. But since the sample sizes are small, it is impossible to conclude that including the age variable helps the prediction of breast cancer. Including the age variable does not improve the ability to predict the existence of lung cancer. If the age variable is excluded, CART and logistic regression give a very close result.

Com o advento da Internet, novas tecnologias de Geoprocessamento têm sido criadas para tratar, trocar, disponibilizar e acessar informações e dados espaciais como as Infraestruturas de Dados Espaciais, os Geobrowsers e os Serviços de Informações Geográficas. O número de aplicações que lida com atributos espaciais não somente cresceu como também se diversificou, no entanto problemas de interoperabilidade semântica ainda limitam a evolução nessa área. Ontologias formalizam o conhecimento necessário para organizar e permitir o uso de dados de diferentes fontes, pois são modelos de referência robustos devido à sua expressividade e capacidade de serem compartilhados pela internet. Nesta tese, ontologias foram desenvolvidas para aumentar a interoperabilidade semântica em sistemas de apoio à logística humanitária que utilizam serviços de informações geográficas. A aplicação de logística humanitária estudada foi a operação de bancos de alimentos. O conhecimento relativo aos processos logísticos, problemas logísticos de bancos de alimentos e serviços de informações geográficas úteis para os métodos de solução desses problemas foram formalizados em uma rede de ontologias. O número de serviços de informações geográficas disponíveis ainda é pequeno, mas a composição de serviços de informações geográficas em cadeias, formando novos serviços, abre uma perspectiva para que operações espaciais, não fiquem mais restritas às soluções proprietárias e possam ser melhor exploradas. As ontologias propostas neste trabalho podem ser usadas como base para o desenvolvimento de sistemas em que serviços de informações geográficas podem ser acoplados, na medida em que forem sendo disponibilizados. / With the advent of Internet, new technologies from GIS field have been created to access and exchange spatial data and information, such as Spatial Data Infrastructures, Geobrowsers and Geographic Information Services. The number of applications dealing with spatial attributes is growing and is also diversifying. However semantic interoperability problems still limit progress in this area. Ontologies formalize the knowledge necessary to organize and allow the use of data from different sources due to its expressiveness and ability to be shared over the Internet. In this thesis, ontologies have been developed to increase the semantic interoperability of humanitarian logistics support systems that use geographic information services. The application of humanitarian logistics operation studied was the food banks operation. The knowledge on logistics processes, logistics problems of food banks and geographic information services useful for the methods for solving these problems have been formalized into a network of ontologies. The number of geographical information services available is still small, but the composition of geographic information services in chains, creating new services, opens a perspective for new methods of spatial operations, which are not limited to proprietary solutions form GIS softwares available in the market. The ontologies proposed in this thesis can be used as a basis for developing systems in which geographic information services can be coupled, as it becomes available.

Bone cement surgery is a new technique widely used in medical field nowadays. In this thesis I analyze 48 bone cement types using their content of 20 elements. My goal is to ?find a method to classify new found bone cement sample into these 48 categories. Here I will use multinomial logistic regression method to see whether it works or not. Due to the lack of observations, I generate enough data by adding white noise in proper scales to the original data again and again, and then I get a data set of over 100 times as many points as the original one. Then I use purposeful variable selection method to pick the covariates I need, rather than stepwise selection. There are 15 covariates left after the selection, and then I use my new data set to fit such a multinomial logistic regression model. The model doesn't perform that good in goodness of ?fit test, but the result is still acceptable, and the diagnostic statistics also indicate a good performance. Combined with clinical experience and prior conditions, this model is helpful in this classification case.

"We analyze data (length, weight and location) from a study done by the Army Corps of Engineers along the Tennessee River basin in the summer of 1980. The purpose is to predict the probability that a hypothetical channel catfish at a location studied is toxic and contains 5 ppm or more DDT in its filet. We incorporate spatial information and treate it separetely from other covariates. Ultimately, we want to predict the probability that a catfish from the unobserved location is toxic. In a preliminary analysis, we examine the data for observed locations using frequentist logistic regression, Bayesian logistic regression, and Bayesian logistic regression with random effects. Later we develop a parsimonious extension of Bayesian logistic regression and the corresponding Gibbs sampler for that model to increase computational feasibility and reduce model parameters. Furthermore, we develop a Bayesian model to impute data for locations where catfish were not observed. A comparison is made between results obtained fitting the model to only observed data and data with missing values imputed. Lastly, a complete model is presented which imputes data for missing locations and calculates the probability that a catfish from the unobserved location is toxic at once. We conclude that length and weight of the fish have negligible effect on toxicity. Toxicity of these catfish are mostly explained by location and spatial effects. In particular, the probability that a catfish is toxic decreases as one moves further downstream from the source of pollution."

We consider the problem of maximum likelihood estimation of logistic sinusoidal regression models and develop some asymptotic theory including the consistency and joint rates of convergence for the maximum likelihood estimators. The key techniques build upon a synthesis of the results of Walker and Song and Li for the widely studied sinusoidal regression model and on making a connection to a result of Radchenko. Monte Carlo simulations are also presented to demonstrate the finite-sample performance of the estimators