Transportation accidents and the resulting fires are an important field of study. At the University of Waterloo Live Fire Research Facility (UWLFRF), an experiment was conducted in partnership with Sandia National Laboratories in Albuquerque, New Mexico. This experiment was designed to simulate an aircraft accident where fuel is spilled on the runway and is subsequently ignited. A crosswind pushes the 2.0 m diameter pool fire towards the aircraft fuselage and the conditions around the fire are monitored. Literature on the subject is examined first, examining the relationship between the fire, the crosswind, and the 2.7 m diameter blocking object (aircraft fuselage). A full wind characterization is then presented of the UWLFRF both with and without the blocking object in place, using five distinct wind speeds ranging from 3 m/s to 13.5 m/s. Turbulence intensity measurements are made on the centerline of the facility when possible. Details about the two sets of live fire tests are presented, a control experiment without the blocking object in place and then fire tests with the blocking object in place. Additionally, the control experiment has two different setups, one involving a floor surround in order to diminish the effect of the forward facing step on the front of the fuel pan. The fuel regression rate, the wind speed, the ambient conditions and the heat flux near the fuel pan are monitored during each live fire test. The fuel regression rate, defined as the rate at which the height of the liquid fuel level decreases as the fire burns, is then analyzed versus all other monitored variables. During no blocking object tests, trends of increasing wind speed and increasing heat flux on some gauges and decreasing flux on others was observed with increasing fuel regression rate when the floor surround was in place. During no blocking object tests without the floor surround and tests with the blocking object in place, no strong trends were observed when comparing the monitored variables. The ambient conditions were not observed to have an effect on any test. The average fuel regression for tests without the blocking object in place is 4.0 mm/min without the floor surround, and 4.4 mm/min with it in place. With the blocking object in place the average fuel regression rate was measured to be 4.8 mm/min using load cells and 4.1 mm/min using the sight glass.

The case-control studies are primary tools for the study of risk factors (exposures) related to the disease interested. The case-control studies using longitudinal data are cost and time efficient when the disease is rare and assessing the exposure level of risk factors is difficult. Instead of GEE method, the method of using a prospective logistic model for analyzing case-control longitudinal data was proposed and the semiparametric inference procedure was explored by Park and Kim (2004). In this thesis, we apply an empirical likelihood ratio method to derive limiting distribution of the empirical likelihood ratio and find one likelihood-ratio based confidence region for the unknown regression parameters. Our approach does not require estimating the covariance matrices of the parameters. Moreover, the proposed confidence region is adapted to the data set and not necessarily symmetric. Thus, it reflects the nature of the underlying data and hence gives a more representative way to make inferences about the parameter of interest. We compare empirical likelihood method with normal approximation based method, simulation results show that the proposed empirical likelihood ratio method performs well in terms of coverage probability.

Application Engineering is a field where software organizations develop software products from a predefined Software Product Line. The time and cost allotted to come up with a new product variant is limited. Lack of systematic support in testing leads to redundancy. Redundancy in this context can be found in test-cases that do not contribute towards fault-detection and testing leads to an increased testing effort. This thesis work proposes a framework to reduce the testing effort, aimed at avoiding testing redundancy. Feature Model diagrams have been constructed from the assumed specification requirements. These Feature Model diagrams have been used to derive test models such as Object Model diagram and State Chart diagram. Unit testing and System testing have been performed on test models to obtain test cases that have been stored in the repository. Regression testing has been applied to these test cases to classify them into Reusable, Re-testable and Obsolete.

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Background: MY7 clinical trial compared dexamethasone plus melphalan (MD) vs. prednisone plus melphalan (MP) in multiple myeloma treatment and found no statistically significant difference in overall survival (OS) between the two groups. But, patients reacted to treatment differently. We aimed to identify patients who might have benefited from dexamethasone, and characterize them by their baseline demographic and clinical factors. Methods: First, the prognostic model for OS was developed on the MP arm. The estimated coefficients and baseline hazard were applied to the MD arm to derive martingale residuals (MR). Classification and regression tree analysis was done to identify independent predictive factors for OS and MR was used as response variable. All covariates in categorical shape were used as independent variables to develop the predictive model in MD arm. MP arm was divided accordingly. Subgroups with negative mean MR (survived > expected) were candidates for positive responders while those with positive mean MR (survived < expected) were candidates of negative responders. Mean MR in each subgroup and p values from comparison of OS (log rank test stratified by subgroups) were used to combine the appropriate subgroups as the positive responders or negative responders. Results: A total of 97 patients (42%) in MD arm were identified as positive responders and their OS (median of 44.5 months) was significantly longer than that (median of 33 months) in the corresponding subgroups in MP arm (HR = 0.56, 95% CI 0.4-0.8; p = 0.0014). All positive responders had three common baseline characteristics: aged ≤75 years, calcium concentration ≤2.6 mmol/L and Durie-Salmon stages 2 or 3. Among patients with ECOG performance status<2 those with either HGB≥100 mg/dl or HGB<100 mg/dl and WBC≥4,000 and <4 lytic bone lesions were categorized as positive responders. Also, among the patients with ECOG performance status≥2, males with >3 lytic bone lesions were positive responders. Negative responders (HR = 1.56, 95% confidence interval 1.1 – 2.2; p = 0.006) included patients aged >75 or aged ≤75 with calcium concentration >2.6 mmol/L or aged ≤75 with calcium concentration ≤2.6 mmol/L but had Durie-Salmon stage 1. Conclusions: Evaluation of the hypotheses validity warrants further studies. / Thesis (Master, Community Health & Epidemiology) -- Queen's University, 2008-07-21 13:46:53.748

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Syfte Studien ämnar ge investerare en bättre förståelse för i vilken utsträckning olika variabler påverkar storleken på svenska aktiefonders förvaltningsavgift, samt vilka tre faktorer som tillsammans har störst påverkan på förvaltningsavgiftens storlek.   Metodval De test som utförts är korrelationsanalys samt multipel regressionsanalys. Dessa ger tillsammans svar på styrkan och riktningen i sambandet mellan de undersökta variablerna och en fonds förvaltningsavgift.   Resultat Resultatet visar att de tre faktorer som tillsammans förklarar störst del av variationerna i förvaltningsavgifter är huruvida en fond är en indexfond eller aktivt förvaltad, förvaltarens erfarenhet samt den riskjusterade avkastningen (Sharpekvot) på fem års sikt. Den sistnämnda visar upp ett negativt samband med förvaltningsavgiften, vilket stämmer överens med tidigare forskning på ämnet.   Slutsats Studiens slutsats blir att en stor del av förvaltningsavgifterna går att undvika genom att investerare minskar sin okunskap och passivitet. De sparare som av passivitet behåller sina dåligt presterande fonder kommer över tid att få höjda förvaltningsavgifter, vilket ytterligare bör vara ett incitament till att byta fond.

In this paper we consider optimum design of experiments for correlated observations. We approximate the error component of the process by an eigenvector expansion of the corresponding covariance function. Furthermore we study the limit behavior of an additional white noise as a regularization tool. The approach is illustrated by some typical examples. (authors' abstract) / Series: Research Report Series / Department of Statistics and Mathematics