Physical Sciences and Mathematics Commons^™

Principal Component Analysis-Based Anatomical Motion Models For Use In Adaptive Radiation Therapy Of Head And Neck Cancer Patients, Mikhail Aleksandrovich Chetvertkov

Wayne State University Dissertations

Purpose: To develop standard and regularized principal component analysis (PCA) models of anatomical changes from daily cone beam CTs (CBCTs) of head and neck (H&N) patients, assess their potential use in adaptive radiation therapy (ART), and to extract quantitative information for treatment response assessment.

Methods: Planning CT (pCT) images of H&N patients were artificially deformed to create “digital phantom” images, which modeled systematic anatomical changes during Radiation Therapy (RT). Artificial deformations closely mirrored patients’ actual deformations, and were interpolated to generate 35 synthetic CBCTs, representing evolving anatomy over 35 fractions. Deformation vector fields (DVFs) were acquired between pCT and synthetic …

Nonlinear Stochastic Systems And Controls: Lotka-Volterra Type Models, Permanence And Extinction, Optimal Harvesting Strategies, And Numerical Methods For Systems Under Partial Observations, Ky Quan Tran

Wayne State University Dissertations

This dissertation focuses on a class of stochastic models formulated using stochastic differential equations with regime switching represented by a continuous-time Markov chain, which also known as hybrid switching diffusion processes. Our motivations for studying such processes in this dissertation stem from emerging and existing applications in biological systems, ecosystems, financial engineering, modeling, analysis, and control and optimization of stochastic systems under the influence of random environments, with complete observations or partial observations.

The first part is concerned with Lotka-Volterra models with white noise and regime switching represented by a continuous-time Markov chain. Different from the existing literature, the Markov …

Cohomology Operations On Random Spaces, Matthew John Zabka

Wayne State University Dissertations

Topology has recently received more attention from statisticians as some its tools have been applied to understanding the shape of data. In particular, a data set can generate a topological space, and this space’s topological structure can give us insight into some properties of the data. This framework has made it necessary to study random spaces generated by data. For example, without an understanding of the probabilistic properties of random spaces, one cannot conclude with any degree of confidence what the tools of topology tell us about a data set. While some results are known about the cohomological structure of …

Variational Analysis And Stability In Optimization, M. Ebrahim Sarabi

Wayne State University Dissertations

The dissertation is devoted to the study of the so-called full Lipschitzian stability of local solutions to finite-dimensional parameterized problems of constrained optimization, which has been well recognized as a very important property from both viewpoints of optimization theory and its applications. Employing second-order subdifferentials of variational analysis, we obtain necessary and sufficient conditions for fully stable local minimizers in general classes of constrained optimization problems including problems of composite optimization as well as problems of nonlinear programming with twice continuously differentiable data. Based on our recent explicit calculations of the second-order subdifferential for convex piecewise linear functions, we establish …

A Topological Study Of Stochastic Dynamics On Cw Complexes, Michael Joseph Catanzaro

Wayne State University Dissertations

In this dissertation, we consider stochastic motion of subcomplexes of a CW complex, and explore the implications on the underlying space. The random process on the complex is motivated from Ito diffusions on smooth manifolds and Langevin processes in physics. We associate a Kolmogorov equation to this process, whose solutions can be interpretted in terms of generalizations of electrical, as well as stochastic, current to higher dimensions. These currents also serve a key function in relating the random process to the topology of the complex. We show the average current generated by such a process can be written in a …

Optimal Control Of A Perturbed Sweeping Process With Applications To The Crowd Motion Model, Tan Hoang Cao

Wayne State University Dissertations

The dissertation is devoted to the study and applications of a new class of optimal control problems governed by a perturbed sweeping process of the hysteresis type with control functions acting in both play-and-stop operator and additive perturbations. Such control problems can be reduced to optimization of discontinuous and unbounded dif- ferential inclusions with pointwise state constraints, which are immensely challenging in control theory and prevent employing conventional variation techniques to derive neces- sary optimality conditions. We develop the method of discrete approximations married with appropriate generalized differential tools of modern variational analysis to overcome principal difficulties in passing to …

Ergodicity Of Stochastic Switching Diffusions And Stochastic Delay Systems, Hongwei Mei

Wayne State University Dissertations

This dissertation contains two main parts. The first part focuses on numerical algorithms for approximating the ergodic means of suitable functions of solutions to stochastic differential equations with Markov regime switching. Our main effort is devoted to obtaining the convergence and rates of convergence of the approximation algorithms. The study is carried out by obtaining laws of large numbers and laws of iterated logarithms for numerical approximation to long-run averages of suitable functions of solutions to switching diffusions.

The second part is devoted to stochastic functional differential equations (SFDEs) with infinite delay. This part consists of two main themes. First, …

Some New Combinatorial Formulas For Cluster Monomials Of Type A Quivers, Ba Nguyen

Wayne State University Dissertations

Lots of research focuses on the combinatorics behind various bases of cluster

algebras. This thesis studies the natural basis of a type A cluster algebra, which consists of all cluster monomials. We introduce a new kind of combinatorial formulas for the cluster monomials in terms of globally compatible collections and broken lines. We give bijective proofs of these formulas by comparing with the well-known combinatorial models of the T-paths and of the perfect matchings in a snake diagram.

Multilinear And Multiparameter Pseudo-Differential Operators And Trudinger-Moser Inequalities, Lu Zhang

Wayne State University Dissertations

Pseudo-differential operators play important roles in harmonic analysis, several complex variables, partial differential equations and other branches of modern mathematics. We studied some types of multilinear and multiparameter Pseudo-differential operators. They include a class of trilinear Pseudo-differential operators, where the symbols are in the forms of products of Hormander symbols defined on lower dimensions, and we established the Holder type Lp estimate for these operators. They derive from the trilinear Coifman-Meyer type operators with flag singularities. And we also studied a class of bilinear bi-parameter Pseudo-differential operators, where the symbols are taken from the general Hormander class, and we studied …