Coronary heart disease rates show substantial geographic variation in England, which could be due to environmental variables (e.g. climate, air quality) or behavioural risk factors for coronary heart disease within populations. Previous work investigating this geographic variation has either used ecological analysis (i.e. areas as units of observation) or individual-level analysis. Ecological studies have been unable to account adequately for differences in behavioural risk factors within populations; individual-level studies have been under-powered at the area-level to include all potentially explanatory environmental variables. This thesis reports on ecological multi-level and spatial error regression analyses of coronary heart disease mortality and hospitalisation rates for all wards in England using environmental variables and synthetic estimates of the prevalence of behavioural risk factors as explanatory variables. Existing sets of synthetic estimates were subjected to studies of their validity. Validated synthetic estimates of the prevalence of smoking, low fruit and vegetable consumption, raised blood pressure, obesity and raised cholesterol were combined into a single index of unhealthy lifestyle to take account of collinearity between them. Final models successfully explained around 80% of large scale geographic variation (i.e. variation between wards in different areas of the country) in mortality rates for coronary heart disease and 60% in hospitalisation rates, and around 20% of the small scale geographic variation (i.e. variation between wards in close proximity) in mortality rates, and 30% in hospitalisation rates. The climate explained around 15% of large scale geographic variation in coronary heart disease rates after adjustment for the index of unhealthy lifestyle and socioeconomic deprivation. Urbanicity and air pollution explained a small amount of small scale geographic variation in coronary heart disease rates. The majority of explained geographic variation was due to the index of unhealthy lifestyle and deprivation. The results of this thesis confirm and extend findings from the British Regional Heart Study, report on the validity of synthetic estimates currently used to guide healthcare resource allocation, and introduce an index of unhealthy lifestyle that could be used in future ecological studies of chronic disease.

Interpolation error estimates in terms of geometric quality measures are established for harmonic coordinates on polytopes in two and three dimensions. First we derive interpolation error estimates over convex polygons that depend on the geometric quality of the triangles in the constrained Delaunay triangulation of the polygon. This characterization is sharp in the sense that families of polygons with poor quality triangles in their constrained Delaunay triangulations are shown to produce large error when interpolating a basic quadratic function. Non-convex polygons exhibit a similar limitation: large constrained Delaunay triangles caused by vertices approaching a non-adjacent edge also lead to large interpolation error. While this relationship is generalized to convex polyhedra in three dimensions, the possibility of sliver tetrahedra in the constrained Delaunay triangulation prevent the analogous estimate from sharply reflecting the actual interpolation error. Non-convex polyhedra are shown to be fundamentally different through an example of a family of polyhedra containing vertices which are arbitrarily close to non-adjacent faces yet the interpolation error remains bounded.

The purpose of this study is to determine whether oil and gas producing companies smooth their ending reserve quantities. Smoothing is defined as a reduction in variance in the trend of ending reserve quantities over time compared to the trend of ending reserve quantities less the hypothesized smoothing variable over time. This study focuses on two variables that are most susceptible to manipulation—revisions of previous estimates and additions. This study also examines whether revisions are positively or negatively biased and the variability of the revisions. The sample consists of 70 companies chosen from oil & Gas Reserve Disclosures: 1980-1984 Survey of 400 Public Companies by Arthur Andersen and Company. For each company, ending reserve quantities for the years 1978-1984 were regressed over time, and the standard deviation of the estimate (SDE) was calculated. Then the ending reserve quantities less the hypothesized smoothing variable were regressed over time, and the SDE was calculated. A linear model and a semi-logarithmic model were used. A smoothing ratio (SR) was determined by dividing the SDE of reserves less the hypothesized smoothing variable by the SDE of ending reserve quantities. An SR greater than one indicates smoothing, and an SR less than one indicates that smoothing did not occur. The mean percentage revision and a t-test were used to test for positive or negative bias in the revisions. The mean absolute percentage revision was used to assess the relative variability of revisions. The number of companies classified as smoothers of oil reserves was statistically significant for the semi-logarithmic model but not for the linear model. Under both models the number of companies classified as smoothers of gas reserves was statistically significant. Few companies had mean percentage revisions that were significantly different from zero. The majority of companies had mean absolute revisions of under ten percent.

The purpose of this study was to explore the subject of timescale estimating for rule-based systems. A model for estimating the timescale necessary to build rule-based systems was built and then tested in a controlled environment.

The problem of this study was to investigate the strategies used by high school students of limited estimation ability for the estimation of the answers to computational problems. The Assessing Computational Estimation Test was administered to 460 students, and 40 of them were selected for interviews. Each student interviewed was asked to estimate the answers to fourteen computation and application problems.

This thesis concentrates on stochastic programming problems based on empirical and theoretical distributions and their relationship. Firstly, it focuses on the case where the empirical distribution is an independent random sample. The basic properties are shown followed by the convergence between the problem based on the empirical distribution and the same problem applied to the theoretical distribution. The thesis continues with an overview of some types of dependence - m-dependence, mixing, and also more general weak dependence. For sequences with some of these types of dependence, properties are shown to be similar to those holding for independent sequences. In the last section, the theory is demonstrated using numerical examples, and dependent and independent sequences, including sequences with different types of dependence, are compared.

The demographic development of the population in the city of Litoměřice in the years 1700-1799 Abstract The aim of Thesis is capturing the development of natural change in city of Litomerice and its suburbs in the 18th century and characterizing the basic demographic indicators. Absolute number of marriages, births and deaths was found by using Name excerpts from parish registers. Based on the aggregate method, the data was classified according to the needs analysis for individual years or decades. The development of natural change of Litoměřice was compared with the results of local probes in southern Bohemia, on the estate Stahlavy, in Usti nad Labem and in the cities of Frydek and Mistek. Comparator sites were chosen to represent different areas as well as geographically close or distant cities. Results of comparation confirmed the different demographic developments in urban and rural areas and showed the influence of geographical distance of each city. Keywords: development of natural change, 18th century, Litoměřice, the population estimates

Approved for public release; distribution is unlimited / The defense response to a Chemical and Biological attack would be importantly based on predicting the dispersion of a toxic cloud. Considering that an Unmanned Air Vehicle would provide the capability for embedding and positioning inertial and air data sensors geographically as required, real-time wind estimation can be performed for every actual position of the flying device in order to predict the plume moving direction. The efforts in this thesis concentrate on the demonstration and validation of procedures for obtaining Wind Estimation close to real-time and its instantaneous display. The presented work is based on a particular UAV platform available at the NPS Aeronautical Department and it aims to establish a general methodology, which may be used on other flying devices with similar available sensors. An accurate estimation of real wind for a particular combat scenario will enable operational units to have a near real-time decision aid. This final result could be integrated into a Command and Control net, to assist in a focused way the response to a Chemical and Biological attack and to map the source or the region to be affected. / Lieutenant Commander, Chilean Navy

La thèse porte sur l’analyse d’erreur a posteriori pour la résolution numérique de l’équation linéaire des ondes , discrétisée en temps par le schéma de Newmark et en espace par la méthode des éléments finis. Nous adoptons un choix particulier de paramètres pour le schéma de Newmark, notamment β = 1/4, γ = 1/2, qui assure que la méthode est conservative en énergie et d’ordre deux en temps. L’estimation d’erreur a posteriori, d’un ordre optimal en temps et en espace, est élaborée à partir de la discrétisation complète. L’erreur est mesurée dans une norme qui découle naturellement de la physique: H1 en espace et Linf en temps. Nous proposons d’abord un estimateur dit «à 3 points» qui fait intervenir la solution discrète en 3 points successifs du temps à chaque pas de temps. Cet estimateur fait appel à une approximation du Laplacien de la solution discrète qui doit être calculée à chaque pas de temps, en résolvant un problème auxiliaire d'éléments finis. Nous proposons ensuite un estimateur d’erreur alternatif qui permet d’éviter ces calculs supplémentaires: l’estimateur dit «à 5 points» puisqu’il met en jeu le schéma des différences finies d’ordre 4, qui fait intervenir la solution discrète en 5 points successifs du temps à chaque pas de temps. Nous démontrons que nos estimateurs en temps sont d’ordre optimal pour des solutions suffisamment lisses, sur des maillages quasi-uniformes en espace et uniformes en temps, en supposant que les conditions initiales soient discrétisées à l’aide de la projection elliptique. La trouvaille la plus intéressante de cette analyse est le rôle capitale de cette discrétisation : des discrétisations standards pour les conditions initiales, telles que l’interpolation nodale, peuvent être néfastes pour les estimateurs d’erreur en détruisant leur ordre de convergence, bien qu’elles fournissent des solutions numériques tout à fait acceptables. Des expériences numériques prouvent que nos estimateurs d’erreur sont d’ordre optimal en temps comme en espace, même dans les situations non couvertes par la théorie. En outre, notre analyse a posteriori s’étend au schéma de Newmark d’ordre deux plus général (γ = 1/2). Nous présentons des comparaisons numériques entre notre estimateur à 3 points généralisé et l’estimateur sur des grilles décalées, proposé par Georgoulis et al. Finalement, nous implémentons un algorithme adaptatif en temps et en espace basé sur notre estimateur d’erreur a posteriori à 3 points. Nous concluons par des expériences numériques qui montrent l’efficacité de l’algorithme adaptatif et révèlent l’importance de l’interpolation appropriée de la solution numérique d’un maillage à un autre, surtout vis à vis de l’optimalité de l’estimation d’erreur en temps. / This thesis focuses on the a posteriori error analysis for the linear second-order wave equation discretized by the second order Newmark scheme in time and the finite element method in space. We adopt the particular choice for the parameters in the Newmark scheme, namely β = 1/4, γ = 1/2, since it provides a conservative method with respect to the energy norm. We derive a posteriori error estimates of optimal order in time and space for the fully discrete wave equation. The error is measured in a physically natural norm: H1 in space, Linf in time. Numerical experiments demonstrate that our error estimators are of optimal order in space and time. The resulting estimator in time is referred to as the 3-point estimator since it contains the discrete solution at 3 points in time. The 3-point time error estimator contains the Laplacian of the discrete solution which should be computed via auxiliary finite element problems at each time step. We propose an alternative time error estimator that avoids these additional computations. The resulting estimator is referred to as the 5-point estimator since it contains the fourth order finite differences in time and thus involves the discrete solution at 5 points in time at each time step. We prove that our time estimators are of optimal order at least on sufficiently smooth solutions, quasi-uniform meshes in space and uniform meshes in time. The most interesting finding of this analysis is the crucial importance of the way in which the initial conditions are discretized: a straightforward discretization, such as the nodal interpolation, may ruin the error estimators while providing quite acceptable numerical solution. We also extend the a posteriori error analysis to the general second order Newmark scheme (γ = 1/2) and present numerical comparasion between the general 3-point time error estimator and the staggered grid error estimator proposed by Georgoulis et al. In addition, using obtained a posteriori error bounds, we implement an efficient adaptive algorithm in space and time. We conclude with numerical experiments that show that the manner of interpolation of the numerical solution from one mesh to another plays an important role for optimal behavior of the time error estimator and thus of the whole adaptive algorithm.

Thesis advisor: Henry I. Braun / City Connects is a school-based model that identifies the strengths and needs of every student and links each child to a tailored set of intervention, prevention, and enrichment services in the school or community. The purpose of this study was to conduct a comprehensive evaluation of the City Connects treatment effects on academic performance (both MCAS scores and grade point average (GPA) grades) in middle school using student longitudinal records. Parallel analyses were conducted: one evaluated the City Connects elementary intervention (serving kindergarten to fifth grades) and the other one evaluated the City Connects middle school intervention (serving sixth to eighth grades). A series of two-level hierarchical linear models with middle school achievement scores adjusted and/or propensity score weights applied were used to answer the research questions of interest. In addition, to make a causal inference, a sensitivity analysis was conducted to examine whether or not the estimated treatment effects resulted from the first two analyses were robust to the presence of unobserved selection bias. The results showed that students who were exposed to the City Connects elementary intervention significantly outperformed their counterparts, who graduated from the comparison elementary schools, on academic achievement in all middle school grades. However, in the case of the City Connects intervention schools that served middle school grades, since all students only received a maximum of one year of City Connects middle school intervention, it was still too soon to expect any significant changes. Moreover, the estimated treatment effects of the City Connects elementary intervention were only mildly sensitive to the presence of some forms of hidden bias, which made the causal inference of City Connects on middle school academic achievement quite plausible. / Thesis (PhD) — Boston College, 2015. / Submitted to: Boston College. Lynch School of Education. / Discipline: Educational Research, Measurement and Evaluation.