The primary aim of this thesis is the elucidation of covariate effects on the dependence structure of random variables in bivariate or multivariate models. We develop a unified approach via a conditional copula model in which the copula is parametric and its parameter varies as the covariate. We propose a nonparametric procedure based on local likelihood to estimate the functional relationship between the copula parameter and the covariate, derive the asymptotic properties of the proposed estimator and outline the construction of pointwise confidence intervals. We also contribute a novel conditional copula selection method based on cross-validated prediction errors and a generalized likelihood ratio-type test to determine if the copula parameter varies significantly. We derive the asymptotic null distribution of the formal test. Using subsets of the Matched Multiple Birth and Framingham Heart Study datasets, we demonstrate the performance of these procedures via analyses of gestational age-specific twin birth weights and the impact of change in body mass index on the dependence between two consequent pulse pressures taken from the same subject.

In this thesis, a leading-order QCD analysis of structure functions in neutrinonucleon interactions is performed. From the CCFR nucleon structure function data, the QCD parameter Lambda has been extracted. This measurement also corresponds to a measurement of the strong coupling constant. Two fits to the data have been performed, the nonsinglet-only fit and the singlet-nonsinglet combined fit. The result for Lambda was found to be 289 +62 &iexcl / 59 &sect / 76 MeV, where the errors are statistical and systematical, respectively. This result is compared to the world-wide measurements of this quantity. In order to verify the agreement, also the logarithmic slopes of the QCD model and the structure function data are calculated and compared.

One of heavy oils upgrading processes is hydroconversion. As it is a complex process involving many chemical reactions, the mathematical model of hydroconversion process often has more kinetic parameters than can be estimated from the data. In this thesis, a model for hydroconversion processing of vacuum residue is proposed. It is proved that the model is structurally identifiable, but shown that it is inestimable and good parameter estimates may be impossible to obtain even if the model fit is good. As a proof to the model inestimability, it is shown that literature data can be fitted using a subset of only three (of seven) parameters. To improve parameter estimability, a method is proposed for designing additional experiments. The method is based on designing experiments that provide data that is complementary (in an appropriate sense) to existing data. The approach is illustrated using the hydroconversion model. For the hydroconversion model, using two additional experiments provides a good balance between parameter estimation and experimental effort. / Process Control

Graduation date: 1988

Stereopsis is the process of inferring the distance to objects from two or more images. It has applications in areas such as: novel-view rendering, motion capture, autonomous navigation, and topographical mapping from remote sensing data. Although it sounds simple, in light of the effortlessness with which we are able to perform the task with our own eyes, a number of factors that make it quite challenging become apparent once one begins delving into computational methods of solving it. For example, occlusions that block part of the scene from being seen in one of the images, and changes in the appearance of objects between the two images due to: sensor noise, view dependent effects, and/or differences in the lighting/camera conditions between the two images. Global stereopsis algorithms aim to solve this problem by making assumptions about the smoothness of the depth of surfaces in the scene, and formulating stereopsis as an optimization problem. As part of their formulation, these algorithms include a function that measures the similarity between pixels in different images to detect possible correspondences. Which of these match cost functions work better, when, and why is not well understood. Furthermore, in areas of computer vision such as segmentation, face detection, edge detection, texture analysis and classification, and optical flow, it is not uncommon to use colour spaces other than the well known RGB space to improve the accuracy of algorithms. However, the use of colour spaces other than RGB is quite rare in stereopsis research. In this dissertation we present results from two, first of their kind, large scale studies on global stereopsis algorithms. In the first we compare the relative performance of a structured set of match cost cost functions in five different global stereopsis frameworks in such a way that we are able to infer some general rules to guide the choice of which match cost functions to use in these algorithms. In the second we investigate how much accuracy can be gained by simply changing the colour representation used in the input to global stereopsis algorithms.

Atrial fibrillation (AF) is a complex, multifaceted arrhythmia. Pathogenesis of AF is associated with multiple aetiologies and the mechanisms by which it is sustained and perpetuated are similarly diverse. In particular, regional heterogeneity in the electrophysiological properties of normal and pathological tissue plays a critical role in the occurrence of AF. Understanding AF in the context of electrophysiological heterogeneity requires cell-specific ionic models of electrical activity which can then be incorporated into models on larger temporal and spatial scales. Biophysically-based models have typically dominated the study of cellular excitability providing detailed and precise descriptions in the form of complex mathematical formulations. However, such models have limited applicability in multidimensional simulations as the computational expense is too prohibitive. Simplified mathematical models of cardiac cell electrical activity are an alternative approach to these traditional biophysically-detailed models. Utilizing this approach enables the embodiment of cellular excitation characteristics at minimal computational cost such that simulations of arrhythmogensis in atrial tissue are conceivable. In this thesis, a simplified, generic mathematical model is proposed that characterizes and reproduces the action potential waveforms of individual cardiac myocytes. It incorporates three time-dependent ionic currents and an additional time-independent leakage current. The formulation of the three time-dependent ionic currents is based on 4-state Markov schemes with state transition rates expressed as nonlinear sigmoidal functions of the membrane potential. Parameters of the generic model were optimized to fit the action potential waveforms of the Beeler-Reuter model, and, experimental recordings from atrial and sinoatrial cells of rabbits. A nonlinear least-squares optimization routine was employed for the parameter fits. The model was successfully fitted to the Beeler-Reuter waveform (RMS error: 1.4999 mV) and action potentials recorded from atrial tissue (RMS error: 1.3398 mV) and cells of the peripheral (RMS error: 2.4821 mV) and central (RMS error: 2.3126 mV) sinoatrial node. Thus, the model presented here is a mathematical framework by which a wide variety of cell-specific AP morphologies can be reproduced. Such a model offers the potential for insights into possible mechanisms that contribute to heterogeneity and/or arrhythmia.

Thesis (Ph. D.)--Rutgers University, 2007. / "Graduate Program in Industrial and Systems Engineering." Includes bibliographical references (p. 181-186).

Thesis (Ph.D.)--Tufts University, 2003. / Adviser: Masoud Sanayei. Submitted to the Dept. of Civil Engineering. Includes bibliographical references. Access restricted to members of the Tufts University community. Also available via the World Wide Web;

Lic.-avh. Uppsala : Univ., 2004.

Thesis (M.App.Sc.) - Carleton University, 2005. / Includes bibliographical references (p. 161-165). Also available in electronic format on the Internet.