Avec l’avènement de la prochaine génération de télescope de plus de 30m de diamètre, il devient primordial de réduire le coût des observations et d’améliorer leur rendement scientifique. De plus il est essentiel de construire ces instruments sur des sites disposant d’une qualité optique maximale. J’ai donc essayé, au cours de ma thèse, de développer un outil fiable, facile d’utilisation et économique permettant de satisfaire ces exigences. J’ai donc utilisé le modèle de prévision météorologique Weather Research and Forecasting et le modèle de calcul de la turbulence optique Trinquet-Vernin pour prédire, plusieurs heures à l’avance, les conditions optiques du ciel tout au long de la nuit. Cette information permettrait d’améliorer la gestion du programme d’observation, appelée "flexible scheduling", et ainsi de réduire les pertes dues à la variation des conditions atmosphériques. Les résultats obtenus et les améliorations apportées au modèle WRF-TV lui permettent de présenter un bon accord entre les mesures et les prévisions ce qui est prometteur pour une utilisation réelle. Au delà de cette gestion, nous avons voulu créer un moyen d’améliorer la recherche et le test de sites astronomiquement intéressants. Nous avons donc définit un paramètre de qualité qui prend en compte les conditions météorologiques et optiques. Ce paramètre a été testé au-dessus de l’île de La Palma aux Canaries et a montré que l’Observatorio del Roque de los Muchachos est situé au meilleur emplacement de l’île. Enfin nous avons créé une routine d’automatisation du modèle WRF-TV afin d’avoir un outil opérationnel fonctionnant de manière autonome. / With the next generation of extremely large telescope having mirror with a diameter larger than 30m, it becomes essential to reduce the cost of observations and to improve their scientific efficiency. Moreover it is fundamental to build these huge infrastructures in location having the best possible optical quality. The purpose of my thesis is to bring a solution easier and more economical than before. I used the Weather Research and Forecasting (WRF) model and the Trinquet-Vernin parametrization, which computes the values of the optical turbulence, to forecast a couple of hours in advance the evolution of the sky optical quality along the coming night. This information would improve the management of observation program, called "flexible scheduling", and thereby reduce losses due to the atmospheric variations. Our results and improvements allow the model us WRF-TV to have a good agreement between previsions and in-situ measurements in different sites, which is promising for a real use in an observatory. Beyond the flexible scheduling, we wanted to create a tool to improve the search for new sites or site testing for already existing sites. Therefore we defined a quality parameter which takes into account meteorological conditions (wind, humidity, precipitable water vapor) and optical conditions (seeing, coherence time, isoplanatic angle). This parameter has been tested above La Palma in Canary island showing that the Observatorio del Roque de los Muchachos is located close to the best possible location of the island. Finally we created an automated program to use WRF-TV model in order to have an operational tool working routinely.

Researchers perform multivariate techniques MANOVA, discriminant analysis and factor analysis. The most common applications in social science are to identify and test the effects from the analysis. The use of this multivariate technique is uncommon in investigating the effects of power usage and Province in South Africa on the amounts of the five power modes. This dissertation discusses this issue, the methodology and practical problems of the three multivariate techniques. The author examines the applications of each technique in social public research and comparisons are made between the three multivariate techniques. This dissertation concludes with a discussion of both the concepts of the present multivariate techniques and the results found on the use of the three multivariate techniques in the energy household consumption. The author recommends focusing on the hypotheses of the study or typical questions surrounding of each technique to guide the researcher in choosing the appropriate analysis in the social research, as each technique has some strengths and limitations. / Statistics / M. Sc. (Statistics)

Tato práce zkoumá existující možnosti a metody detekce korelovaných mutací v proteinech. Práce začíná teoretickým úvodem do zkoumané problematiky. Využití informací o korelovaných mutacích je především při predikci terciální struktury proteinu či hledání oblastí s významnou funkcí. Dále následuje přehled v současnosti používaných metod detekce a jejich výhody a nevýhody. V této práci jsou zkoumány zejména metody založené na statistice (například Pearsonově korelačním koeficientu nebo Pearsonově chi^2 testu), informační teorii (Mutual information - MI) a pravděpodobnosti (ELSC nebo Spidermonkey). Dále jsou popsány nejdůležitější nástroje s informací o tom, které metody používají a jakým způsobem. Také je diskutována možnost návrhu optimálního algoritmu. Jako optimální z hlediska úspěšnosti detekce je doporučeno využít více zmíněných metod. Také je doporučeno při detekci využít fyzikálně-chemických vlastností aminokyselin. V praktické části byla vyvinuta metoda využívající fyzikálně-chemických vlastností aminokyselin a fylogenetických stromů. Výsledky detekce byly porovnány s nástroji CAPS, CRASP a CMAT.

The introduction to operational nuclear reactors focusing on light-water pressurized reactor VVER 1000 is in the beginning of this Master´s thesis. This thesis covers basic technology of VVER 1000 reactor with focus on reactor core and nuclear fuel TVSA-T. A significant part of the thesis deal with basic concepts of nuclear safety and its methods. The main goal is to create a model of VVER 1000 reactor, which can be used in nuclear burn-up calculations using KENO code. Therefore a part of this thesis deals with explanation of statistical Monte Carlo method and the KENO code.

Indiana University-Purdue University Indianapolis (IUPUI) / Robustness and generalizability of supervised learning algorithms depend on the quality of the labeled data set in representing the real-life problem. In many real-world domains, however, we may not have full knowledge of the underlying data-generating mechanism, which may even have an evolving nature introducing new classes continually. This constitutes a partially-observed setting, where it would be impractical to obtain a labeled data set exhaustively defined by a fixed set of classes. Traditional supervised learning algorithms, assuming an exhaustive training library, would misclassify a future sample of an unobserved class with probability one, leading to an ill-defined classification problem. Our goal is to address situations where such assumption is violated by a non-exhaustive training library, which is a very realistic yet an overlooked issue in supervised learning. In this dissertation we pursue a new direction for supervised learning by defining self-adjusting models to relax the fixed model assumption imposed on classes and their distributions. We let the model adapt itself to the prospective data by dynamically adding new classes/components as data demand, which in turn gradually make the model more representative of the entire population. In this framework, we first employ suitably chosen nonparametric priors to model class distributions for observed as well as unobserved classes and then, utilize new inference methods to classify samples from observed classes and discover/model novel classes for those from unobserved classes. This thesis presents the initiating steps of an ongoing effort to address one of the most overlooked bottlenecks in supervised learning and indicates the potential for taking new perspectives in some of the most heavily studied areas of machine learning: novelty detection, online class discovery and semi-supervised learning.

Indiana University-Purdue University Indianapolis (IUPUI) / Safety researchers have devoted extensive attention to safety performance behaviors. However, current safety performance models have yet to differentiate between safety citizenship behaviors directed towards the organization and those directed towards individuals. This might be a potential oversight, considering that citizenship behaviors targeted at different beneficiaries might be associated with different antecedents. As such, the purpose of the present study was to develop and validate a new safety performance scale. Items from existing measures formed the item pool and those tapping into the proposed dimensions were selected. Next, items were pilot tested using an online panel of 333 employees from various safety-related industries. A 4-factor structure emerged after exploratory factor analysis and the scale was further refined using reliability analysis and item response theory analysis. Finally, confirmatory factor analysis was conducted to replicate the factor structure using data from 137 employees. Theoretically related variables were correlated with the safety performance dimensions to establish the nomological network. Results supported the 4-factor structure of the new safety performance scale and construct validation hypotheses were largely supported. Implications, study limitations, and directions for future research are discussed.

Indiana University-Purdue University Indianapolis (IUPUI) / This thesis is aimed at creating a pipeline for analyzing DNA methylation epigenetics data and creating a data model structured well enough to store the analysis results of the pipeline. In addition to storing the results, the model is also designed to hold information which will help researchers to decipher a meaningful epigenetics sense from the results made available. Current major epigenetics resources such as PubMeth, MethyCancer, MethDB and NCBI’s Epigenomics database fail to provide holistic view of epigenetics. They provide datasets produced from different analysis techniques which raises an important issue of data integration. The resources also fail to include numerous factors defining the epigenetic nature of a gene. Some of the resources are also struggling to keep the data stored in their databases up-to-date. This has diminished their validity and coverage of epigenetics data. In this thesis we have tackled a major branch of epigenetics: DNA methylation. As a case study to prove the effectiveness of our pipeline, we have used stage-wise DNA methylation and expression raw data for Lung adenocarcinoma (LUAD) from TCGA data repository. The pipeline helped us to identify progressive methylation patterns across different stages of LUAD. It also identified some key targets which have a potential for being a drug target. Along with the results from methylation data analysis pipeline we combined data from various online data reserves such as KEGG database, GO database, UCSC database and BioGRID database which helped us to overcome the shortcomings of existing data collections and present a resource as complete solution for studying DNA methylation epigenetics data.

Indiana University-Purdue University Indianapolis (IUPUI) / Population estimations for the year 2000 indicate an increase in poor and minorities in the United States (Loden & Rosener, 1991). In view of this growth trend, Berger (1989) suggests a need for social workers with sensitivity to such populations. The presence of minority perspectives provides a valuable contribution to service delivery (Mullen et al., 1993). Efforts to enhance student persistence in graduate schools of social work will contribute to the pool of social workers available in the next century. The purpose of this study is to determine the factors that contribute to African American student persistence in graduate schools of social work. This study applies aspects of Astin's, Tinto's and Green's theories of persistence. Astin's theory of involvement (1975) considers student investment of time in educational pursuits. Tinto's (1975) theory of departure includes background, social and academic aspects in persistence decisions. Green's (1997) theory focuses on the ability of the student to cope with racial issues (racial resilience) and the racial climate of the school (racial responsiveness). One hundred and thirty-five students from two predominantly white and two historically black universities participated in surveys administered to determine the effect of involvement, background, academic, social, resilience factors, and college type upon student persistence outcomes. Interviews held with administrative personnel at each institution provided contextual data. Correlations were used to examine the relationships among all of the variables in the study. T-Tests were conducted to compare outcomes due to university type. Multiple regressions were used to explore the relationships between significant independent variables and persistence. The findings of this study indicate that persistence outcomes of African American graduate social work students are influenced by: (a) academic performance, faculty-student relationships, (c) health, (d) the ability to deal with stress, and (e) ethnic pride (impressions of ethnic group). These findings suggest that social work programs that incorporate aggressive grade monitoring practices, provide diverse opportunities for student-faculty interaction, offer opportunities for health care, stress alternatives, and a culturally relevant curriculum, may positively influence African American student persistence.

Indiana University-Purdue University Indianapolis (IUPUI) / Background: Online courses in healthcare programs like Dietetics have increased in availability and popularity. Objective: The purpose of this study was to investigate the connections between online learning environments and Myers-Briggs Type Indicator (MBTI) dimensions among Nutrition Professionals. This research will add to the knowledge base of educators responsible for the design and development of online nutrition courses and will enhance Nutrition Professionals’ academic and professional outcomes. Design: Semi-experimental study design. Subjects/Setting: Thirty-one Nutrition Professionals with mean age of 29 years old. All elements of the study were done online. Statistical Analysis: MBTI dimension summaries were done for descriptive statistics. Fisher’s Exact Test was used to compare frequency of MBTI dimensions in the learning modules (LM) and to analyze learning modality preference based on MBTI dimensions. Two-Sample T-Tests compared test scores for LM groups and test scores for extraverts and introverts. Paired T-Test assessed improvement in test scores related to LM preference. Chi-Square Test compared preferences for the second learning module for both LM groups. Results: The majority of participants’ MBTIs were ESFJ at 35% or ISFJ at 19%. There were more extraverts (71%) compared to introverts (29%). Both LM groups had similar MBTI dimensions. Extraverts and introverts had similar improvements in scores and LM preferences. LM groups performed similarly and in general participants preferred the second learning module they were assigned. Preference for the second LM could be because participants enjoyed the first LM and wanted to learn more information. Both LM groups significantly improved their scores (P=<.0001) in their first and second learning modules regardless of learning module design. Participants were highly motivated to learn as evidenced by their enrollment in this study and completion of 10 hours of learning modules. Motivation to learn may have been the strongest reason performance significantly improved. Conclusion: LM groups significantly improved their LM scores and learned similar amounts. MBTI dimensions extravert and introvert and preferred learning modality had limited impact on performance for this sample of Nutrition Professionals. These results indicate that motivation may be the key to increasing performance in online nutrition courses.

Multiple-outcome longitudinal data are abundant in clinical investigations. For example, infections with different pathogenic organisms are often tested concurrently, and assessments are usually taken repeatedly over time. It is therefore natural to consider a multivariate modeling approach to accommodate the underlying interrelationship among the multiple longitudinally measured outcomes. This dissertation proposes a multivariate semiparametric modeling framework for such data. Relevant estimation and inference procedures as well as model selection tools are discussed within this modeling framework. The first part of this research focuses on the analytical issues concerning binary data. The second part extends the binary model to a more general situation for data from the exponential family of distributions. The proposed model accounts for the correlations across the outcomes as well as the temporal dependency among the repeated measures of each outcome within an individual. An important feature of the proposed model is the addition of a bivariate smooth function for the depiction of concurrent nonlinear and possibly interacting influences of two independent variables on each outcome. For model implementation, a general approach for parameter estimation is developed by using the maximum penalized likelihood method. For statistical inference, a likelihood-based resampling procedure is proposed to compare the bivariate nonlinear effect surfaces across the outcomes. The final part of the dissertation presents a variable selection tool to facilitate model development in practical data analysis. Using the adaptive least absolute shrinkage and selection operator (LASSO) penalty, the variable selection tool simultaneously identifies important fixed effects and random effects, determines the correlation structure of the outcomes, and selects the interaction effects in the bivariate smooth functions. Model selection and estimation are performed through a two-stage procedure based on an expectation-maximization (EM) algorithm. Simulation studies are conducted to evaluate the performance of the proposed methods. The utility of the methods is demonstrated through several clinical applications.