For nearly a quarter-century, from 1940 through 1963, Vancouver’s Theatre Under the Stars (TUTS) mounted annual summer seasons of musical theatre in Malkin Bowl, a converted bandshell in Stanley Park. By the early 1950s, TUTS, now a fully-professional company, had become an enormous popular and financial success, attracting crowds of up to 25,000 per week. For various reasons, the company closed down in 1963, yet so ingrained in Vancouver's cultural fabric had TUTS become, that in 1980 an amateur organization re-appropriated the name for its own summer musical productions in Malkin Bowl. Despite its acknowledged importance in Canadian theatre history, very little research has been devoted to this remarkable company. The purpose of this study, therefore, is to document the early history of TUTS, in particular the years 1940 through 1949 when TUTS was directly funded by the Vancouver Board of Parks and Recreation and dominated by the colourful, if somewhat erratic, personality of its general manager, Gordon Hilker. Material for the thesis was obtained primarily through sources located at the City of Vancouver Archives, supplemented by newspaper clippings and by personal interviews. Archival matter included programs, handbills, photographs, and Park Board records, especially minute books and correspondence files. This study will examine the circumstances leading to the creation and subsequent development of TUTS as a civic enterprise. Although the work is designed to be comprehensive, certain topics receive special attention: the nature of the programming; the evolution and training of Canadian talent; the development of a professional company; political factionalism in the elected Park Board; and the relationship between Hilker and the Park Board which varied from mutual admiration to mutual loathing. Particularly analyzed are the pivotal events of 1949 that resulted in a complete change of ownership and management.

Receiver operating characteristic (ROC) curves have been widely used in evaluation of the goodness of the diagnostic method in many study fields, such as disease diagnosis in medicine. The area under the ROC curve (AUC) naturally became one of the most used variables in gauging the goodness of the diagnosis (Mossman, Somoza 1991). Since medical diagnosis often is not dichotomous, the ROC curve and AUC need to be generalized to a multi-dimensional case. The generalization of AUC to multi-class case has been studied by many researchers in the past decade. Most recently, Nakas & Yiannoutsos (2004) considered the ordered d classes ROC analysis by only considering the sensitivities of each class. Hence, their dimension is only d. Cha (2005) considered more types of mis-classification in the ordered multiple-class case, but reduced the dimension of Ferri, at.el. from d(d-1) to 2(d-1). In this dissertation we are trying to adjust and calculate the VUS for an ordered multipleclass with Cha’s 2(d-1)-dimension method. Our methodology of finding the VUS is introduced. We present the method of adjusting and calculating VUS and their statistical inferences for the 2(d-1)-dimension. Some simulation results are included and a real example will be presented. Intellectual outcomes in pediatric brain-tumor patients were investigated in a prospective longitudinal study. The Standard-Binet Intelligence Scale-Fourth Edition (SB-IV) Standard Age Score (SAS) and Composite intelligence quotient (IQ) score are examined as cognitive outcomes in pediatric brain-tumor patients. Treatment factors, patient factors and time since diagnosis are taken into account as the risk factors. Hierarchical linear/quadratic models and Gompertz based hierarchical nonlinear growth models were applied to build linear and nonlinear longitudinal curves. We use PRESS and Volume Under the Surface (VUS) as the criterions to compare these two methods. Some model interpretations are presented in this dissertation.

The receiver operating characteristic (ROC) curves is a popular tool for evaluating continuous diagnostic tests. The traditional definition of ROC curves incorporates implicitly the idea of "hard" thresholding, which also results in the empirical curves being step functions. The first topic is to introduce a novel definition of soft ROC curves, which incorporates the idea of "soft" thresholding. The softness of a soft ROC curve is controlled by a regularization parameter that can be selected suitably by a cross-validation procedure. A byproduct of the soft ROC curves is that the corresponding empirical curves are smooth. The second topic is on combination of several diagnostic tests to achieve better diagnostic accuracy. We consider the optimal linear combination that maximizes the area under the receiver operating characteristic curve (AUC); the estimates of the combination's coefficients can be obtained via a non-parametric procedure. However, for estimating the AUC associated with the estimated coefficients, the apparent estimation by re-substitution is too optimistic. To adjust for the upward bias, several methods are proposed. Among them the cross-validation approach is especially advocated, and an approximated cross-validation is developed to reduce the computational cost. Furthermore, these proposed methods can be applied for variable selection to select important diagnostic tests. However, the above best-subset variable selection method is not practical when the number of diagnostic tests is large. The third topic is to further develop a LASSO-type procedure for variable selection. To solve the non-convex maximization problem in the proposed procedure, an efficient algorithm is developed based on soft ROC curves, difference convex programming, and coordinate descent algorithm.

Fourier Transform Infrared (FTIR) microscopy is a sensitive method for detecting difference in the morphology of biological cells. In this study FTIR spectra were obtained for uninfected cells, and cells infected with two different viruses. The spectra obtained are difficult to discriminate visually. Here we apply advanced statistical methods to the analysis of the spectra, to test if such spectra are useful for diagnosing viral infections in cells. Logistic Regression (LR) and Partial Least Squares Regression (PLSR) were used to build models which allow us to diagnose if spectral differences are related to infection state of the cells. A three-fold, balanced cross-validation method was applied to estimate the shrinkages of the area under the receiving operator characteristic curve (AUC), and specificities at sensitivities of 95%, 90% and 80%. AUC, sensitivity and specificity were used to gauge the goodness of the discrimination methods. Our statistical results shows that the spectra associated with different cellular states are very effectively discriminated. We also find that the overall performance of PLSR is better than that of LR, especially for new data validation. Our analysis supports the idea that FTIR microscopy is a useful tool for detection of viral infections in biological cells.

Fourier transform infrared (FTIR) spectroscopy, one method of electromagnetic radiation for detecting specific cellular molecular structure, can be used to discriminate different types of cells. The objective is to find the minimum time (choice among 2 hour, 4 hour and 6 hour) to record FTIR readings such that different viruses can be discriminated. A new method is adopted for the datasets. Briefly, inner differences are created as the control group, and Wilcoxon Signed Rank Test is used as the first selecting variable procedure in order to prepare the next stage of discrimination. In the second stage we propose either partial least squares (PLS) method or simply taking significant differences as the discriminator. Finally, k-fold cross-validation method is used to estimate the shrinkages of the goodness measures, such as sensitivity, specificity and area under the ROC curve (AUC). There is no doubt in our mind 6 hour is enough for discriminating mock from Hsv1, and Coxsackie viruses. Adeno virus is an exception.

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Decision-theoretic systems, such as Markov Decision Processes (MDPs), are used for sequential decision-making under uncertainty. MDPs provide a generic framework that can be applied in various domains to compute optimal policies. This thesis presents techniques that offer explanations of optimal policies for MDPs and then refine decision theoretic models (Bayesian networks and MDPs) based on feedback from experts. Explaining policies for sequential decision-making problems is difficult due to the presence of stochastic effects, multiple possibly competing objectives and long-range effects of actions. However, explanations are needed to assist experts in validating that the policy is correct and to help users in developing trust in the choices recommended by the policy. A set of domain-independent templates to justify a policy recommendation is presented along with a process to identify the minimum possible number of templates that need to be populated to completely justify the policy. The rejection of an explanation by a domain expert indicates a deficiency in the model which led to the generation of the rejected policy. Techniques to refine the model parameters such that the optimal policy calculated using the refined parameters would conform with the expert feedback are presented in this thesis. The expert feedback is translated into constraints on the model parameters that are used during refinement. These constraints are non-convex for both Bayesian networks and MDPs. For Bayesian networks, the refinement approach is based on Gibbs sampling and stochastic hill climbing, and it learns a model that obeys expert constraints. For MDPs, the parameter space is partitioned such that alternating linear optimization can be applied to learn model parameters that lead to a policy in accordance with expert feedback. In practice, the state space of MDPs can often be very large, which can be an issue for real-world problems. Factored MDPs are often used to deal with this issue. In Factored MDPs, state variables represent the state space and dynamic Bayesian networks model the transition functions. This helps to avoid the exponential growth in the state space associated with large and complex problems. The approaches for explanation and refinement presented in this thesis are also extended for the factored case to demonstrate their use in real-world applications. The domains of course advising to undergraduate students, assisted hand-washing for people with dementia and diagnostics for manufacturing are used to present empirical evaluations.

Baigiamojo magistro darbo tema – „Perdirbimo muitinės procedūrų taikymo įtakos prekių eksportui ir importui analizė ir perspektyvos”. Tokia tema aktuali tarptautinės prekybos kontekste, kadangi minėtų procedūrų vykdymas leidžia ūkio subjektams naudotis pigesnėmis žaliavomis arba pigesne darbo jėga bei teikia kai kurių kitų privalumų ir tokiu būdu padidinamas prekių konkurencingumas pasaulinėje rinkoje. Perdirbimo procedūrų taikymas teigiamai įtakoja bendras valstybės eksporto apimtis, gerina darbo rinkos padėtį ir prisideda prie tarptautinės prekybos liberalizavimo. Darbe siekiama išanalizuoti perdirbimo muitinės procedūrų teisinį reglamentavimą (pradedant tarptautinėmis konvencijomis ir baigiant Lietuvos Respublikos teisės aktais) ir įvertinti kokią realią įtaką šių procedūrų vykdymas turi šalies eksporto ir importo apimtims. Dar vienas iš darbo tikslų – įvertinti perdirbimo muitinės procedūrų teisinio reglamentavimo pokyčius ir ateities vystymosi prognozes. Darbas pagrįstas mokslinės literatūros, susijusios su tarptautine prekyba ir muitinės procedūromis, analize, taip pat Kioto (tarptautinės muitinės procedūrų supaprastinimo ir suderinimo) konvencijos, ES muitų teisės aktų bei kai Lietuvos Respublikos muitų teisės aktų vertinimu. Praktinis perdirbimo muitinės procedūrų įtakos eksportui ir importui įvertinimas atliktas remiantis Lietuvos Respublikos Muitinės informacinių sistemų centro ir Statistikos departamento pateiktais statistiniais duomenimis. Perdirbimo muitinės... [toliau žr. visą tekstą] / The topic of the thesis is "Analysis and perspectives of the influence of implementation of processing under customs procedures for the export and import of goods". This topic is relevant in the context of international trade since the implementation of the aforementioned procedures allows for the economic agents to use cheaper materials or cheaper labor force as well as provides some other advantages and thus increases the competitiveness of goods in the global market. The application of processing procedures positively affects the total country’s export volume, improves the situation in labor market and contributes towards the liberalization of the international trade. The thesis aims to analyze the legal framework of processing under customs procedures (from international conventions to legal acts of the Republic of Lithuania) and evaluate real impact of these procedures on the country’s export and import volumes. Another objective of the work is to assess the changes of legal framework of processing under customs procedures and future development forecasts. The work is based on the analysis of the scientific literature, which is related to international trade and customs procedures as well as evaluation of Kyoto (simplification and coordination of international customs procedures) convention, customs law of the EU as well as some customs laws of the Republic of Lithuania. Practical evaluation of the influence of processing under customs procedures to the export and... [to full text]

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Steered Response Power based algorithms are widely used for finding sound source location using microphone array systems. SRCP-PHAT is one such algorithm that has a robust performance under noisy and reverberant conditions. The algorithm creates a likelihood function over the field of view. This thesis employs image processing methods on SRCP-PHAT images, to exploit the difference in power levels and pixel patterns to discriminate between sound source and background pixels. Hough Transform based ellipse detection is used to identify the sound source locations by finding the centers of elliptical edge pixel regions typical of source patterns. Monte Carlo simulations of an eight microphone perimeter array with single and multiple sound sources are used to simulate the test environment and area under receiver operating characteristic (ROCA) curve is used to analyze the algorithm performance. Performance was compared to a simpler algorithm involving Canny edge detection and image averaging and an algorithms based simply on the magnitude of local maxima in the SRCP image. Analysis shows that Canny edge detection based method performed better in the presence of coherent noise sources.