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Full-Text Articles in Physical Sciences and Mathematics

Minimal Separating Sets In Surfaces, Christopher Nelson Aagaard Sep 2024

Minimal Separating Sets In Surfaces, Christopher Nelson Aagaard

Dissertations and Theses

Given a connected topolgical space X, we say that L ⊆ X is a minimal separating set if removing L from X gives a disconnected surface, butremoving any proper subset of L leaves the surface connected. We classify which embeddings of topological graphs are minimal separating in an orientable surface X with genus g, and construct a computer program to compute the number of such embeddings, and the number of topological graphs which admit such an embedding for g ≤ 5.


Yang-Baxter Equations, David Lovitz Jun 2024

Yang-Baxter Equations, David Lovitz

Dissertations and Theses

Multiple equations in math, physics, quantum information, and elsewhere are referred to as "the" Yang-Baxter equation, in spite of being a broad family of equations. Most of the equations are nonlinear matrix equations, where the unknown variable is a matrix. This is the case for the so called braided, algebraic, and generalized forms of "the" equation, which are the primary focus of this dissertation. Finding solutions to the various forms of these equations has been the subject of much research. The equations in all their forms are largely considered intractable in high dimensions, and only in dimension 2 have the …


Some Hypergeometric Identities And Related Leonard Pairs, Taiyo Summers Terada May 2024

Some Hypergeometric Identities And Related Leonard Pairs, Taiyo Summers Terada

Dissertations and Theses

The notion of a Leonard pair was introduced by Terwilliger in 2001 to simplify Leonard's theorem, which classifies the orthogonal polynomials in the terminating branch of the Askey-Wilson scheme. In the same year, Kresch and Tamvakis made a conjecture about a certain 4F3 hypergeometric series while studying the arithmetic analogues of the standard conjectures for the Grassmanian G(2,n). The 4F3 series appearing in their conjecture is closely related to a family of orthogonal polynomials in the Askey-Wilson scheme. Consequently, the theory of Leonard pairs provides a useful framework for understanding their conjecture.

In …


Computational Tools For Exploring Eigenvector Localization, Robyn Ashley Markee Reid May 2024

Computational Tools For Exploring Eigenvector Localization, Robyn Ashley Markee Reid

Dissertations and Theses

We develop computational tools for exploring eigenvector localization for a class of selfadjoint, elliptic eigenvalue problems regardless of the cause for localization. The user inputs a desired region R (not necessarily connected), a tolerance for the amount localization in R, and the desired energy range [a,b]. The tool outputs eigenvectors concentrated within the tolerance inside R and within [a, b]. We develop ample theory that justifies our algorithm, which involves a complex, compact perturbation of the operator L, Ls = L+isχR, for some (small) s > 0. Our central idea can be summarized as follows: if (λ,ψ) is an eigenpair of …


H1-Conforming Finite Elements On Nonstandard Meshes, Samuel Edward Reynolds May 2024

H1-Conforming Finite Elements On Nonstandard Meshes, Samuel Edward Reynolds

Dissertations and Theses

We present a finite element method for linear elliptic partial differential equations on bounded planar domains that are meshed with cells that are permitted to be curvilinear and multiply connected. We employ Poisson spaces, as used in virtual element methods, consisting of globally continuous functions that locally satisfy a Poisson problem with polynomial data. This dissertation presents four peer-reviewed articles concerning both the theory and computation of using such spaces in the context of finite elements. In the first paper, we propose a Dirichlet-to-Neumann map for harmonic functions by way of computing the trace of a harmonic conjugate by numerically …


Doubly Almost Bipartite Leonard Pairs, Shuichi Masuda Apr 2024

Doubly Almost Bipartite Leonard Pairs, Shuichi Masuda

Dissertations and Theses

In Linear algebra, the concept of Leonard pair (LP) was motivated by the theory of Q-polynomial distance-regular graphs. In this dissertation, we will first give a brief introduction to LPs and to two closely-related classes of objects: (i) bipartite Leonard pairs (BLPs) and (ii) almost bipartite Leonard pairs (ABLPs). Taking these as departure points, we will introduce a new class of object - doubly almost bipartite Leonard pairs (DABLPs). The primary aim of our work is to fully classify (up to isomorphism) this new family. In addition, since there is known to be a natural correspondence between Leonard pairs …


Understanding Waveguides In Resonance, Pieter Johannes Daniel Vandenberge Mar 2024

Understanding Waveguides In Resonance, Pieter Johannes Daniel Vandenberge

Dissertations and Theses

Several important classes of modern optical waveguides, including anti-resonant reflecting and photonic bandgap fibers, make use of geometries that guide energy in low refractive index material, a property that makes them of significant interest in numerous applications, notably including high-power delivery and guidance. These waveguides frequently exhibit resonance phenomena, in which their ability to propagate an input signal is sharply curtailed at particular operating frequencies. In this work we detail new advances in understanding these resonance effects and their implications for numerical modeling of these structures.

Part 1 focuses on the fields of slab waveguides, relatively simple structures for which …


Forest Generating Functions Of Directed Graphs, Ewan Joaquin Kummel Nov 2023

Forest Generating Functions Of Directed Graphs, Ewan Joaquin Kummel

Dissertations and Theses

A spanning forest polynomial is a multivariate generating function whose variables are indexed over both the vertex and edge sets of a given directed graph. In this thesis, we establish a general framework to study spanning forest polynomials, associating them with a generalized Laplacian matrix and studying its properties. We introduce a novel proof of the famous matrix-tree theorem and show how this extends to a parametric generalization of the all-minors matrix-forest theorem. As an application, we derive explicit formulas for the recently introduced class of directed threshold graphs.

We prove that multivariate forest polynomials are, in general, irreducible and …


Secondary Features Of Importance For A Url Ranking, Atajan Abdyyev Aug 2023

Secondary Features Of Importance For A Url Ranking, Atajan Abdyyev

Dissertations and Theses

This paper investigates the impact of secondary ranking factors on webpage relevance and rankings in the context of Search Engine Optimization (SEO), focusing on the jewelry domain within the United States e-commerce market. By generating a keyword list related to jewelry and retrieving top URLs from Google's search results, the study employs machine learning models including XGBoost, CatBoost, and Linear Regression to identify key features influencing webpage relevance and rankings.The findings highlight specific optimal ranges for features like Outlinks, Unique Inlinks, Flesch Reading Ease Score, and others, indicating their significant impact on better rankings. Notably, Random Forest model performed best …


Survival Times And Investment Analysis With Dynamic Learning, Zhenzhen Li Jun 2023

Survival Times And Investment Analysis With Dynamic Learning, Zhenzhen Li

Dissertations and Theses

The central statistical problem of survival analysis is to determine and characterize the conditional distribution of a survival time given a history of some observed health markers.

This dissertation contributes to the modeling of such conditional distributions in a setup where the health markers evolve randomly over time in a manner that can be represented by an Ito stochastic process, that is, a stochastic process that can be written as a sum of a time integral of some stochastic process and an Ito integral of some stochastic process, with both integrands subject to certain restrictions.

The random survival time is …


Mathematical Analysis Of Convolutional Neural Networks, Daniel Mccarter Jan 2023

Mathematical Analysis Of Convolutional Neural Networks, Daniel Mccarter

Dissertations and Theses

In this thesis, the main topic is convolution as a mathematical operation and Convolutional Neural Networks (CNN’s). While convolution is classically defined as a function, it can also be defined as an operator from Lp(R) to itself for 1 ≤ p ≤ 2 where Tw(f ) = f ∗ w given some w ∈ L1(R). CNN’s use convolution in its convolutional layers. Defining a neural network to be the composition of layer maps, we find that the neural network is, by necessity, Lipschitz. While CNN’s can be very powerful for image classification, slight changes to an image can completely fool …


Explorations Of A Topology Constructed On The Maximal Ideals Of A Boolean Algebra, Abbigal Moos Jan 2023

Explorations Of A Topology Constructed On The Maximal Ideals Of A Boolean Algebra, Abbigal Moos

Dissertations and Theses

The primary purpose of this thesis is to construct a topology on the collection of maximal ideals of a distributive and complemented lattice using the hull-kernel methodology. Through the construction of this topological space, we discovered that the space is compact, zero-dimensional, and Hausdorff. Next, we looked at the properties of some lattices, namely the power set of a finite set ordered by inclusion and the set of all positives divisors for some arbitrary integer ordered by divisibility. Whenever these lattices were both distributive and complemented, we constructed a topology on the collection of maximal ideals of the lattices using …


Decorrelated Deep Neural Networks: Learning Bias Invariant & Scanner Independent Features, And Causal Relationships Using A Novel Deep Learning Methods Based On Distance Correlation, Pranita Patil Aug 2022

Decorrelated Deep Neural Networks: Learning Bias Invariant & Scanner Independent Features, And Causal Relationships Using A Novel Deep Learning Methods Based On Distance Correlation, Pranita Patil

Dissertations and Theses

Advancements in deep learning or deep neural networks have made it possible to reach expert-level performance in a variety of applications, even in challenging situations. However, a central challenge in all deep learning, as well as machine learning applications, is dealing with its dependency on the quality of data which can be significantly impacted by biases, confounders, and irrelevant variations in data which leads to spurious relationships and erroneous decisions. The main purpose of this dissertation is to build a robust deep learning model which considers and mitigates these biases. Another challenge with the deep learning model is learning associations …


Equidistant Sets In Spaces Of Bounded Curvature, Logan Scott Fox May 2022

Equidistant Sets In Spaces Of Bounded Curvature, Logan Scott Fox

Dissertations and Theses

Given a metric space (X,d), and two nonempty subsets A,BX, we study the properties of the set of points of equal distance to A and B, which we call the equidistant set E(A,B). In general, the structure of the equidistant set is quite unpredictable, so we look for conditions on the ambient space, as well as the given subsets, which lead to some regularity of the properties of the equidistant set. At a minimum, we will always require that X is path connected (so that E( …


Linear Nearest Neighbor Flocks With All Distinct Agents, Robert G. Lyons Feb 2022

Linear Nearest Neighbor Flocks With All Distinct Agents, Robert G. Lyons

Dissertations and Theses

This dissertation analyzes the global dynamics of 1-dimensional agent arrays with nearest neighbor linear couplings. The equations of motion are second order linear ODE's with constant coefficients. The novel part of this research is that the couplings are different for each agent. We allow the forces to depend on the relative position and relative velocity (damping terms) of the agents, and the coupling magnitudes differ for each agent. Further, we do not assume that the forces are "Newtonian'" (i.e., the force due to A on B equals minus the force of B on A) as this assumption does not apply …


An Analysis Of Capillary Flow In Finite Length Interior Corners, Samuel Shaw Mohler Jul 2021

An Analysis Of Capillary Flow In Finite Length Interior Corners, Samuel Shaw Mohler

Dissertations and Theses

We analyze the mathematical robustness of slow massively parallel interior corner flows in low gravity environments. An interior corner provides a preferential orientation in low gravity environments. This is a luxury usually only found on earth. It also provides a passive pumping mechanism due to geometry of a conduit. The driving force for this flow is a pressure difference due to local surface curvature gradients. An alternative reasoning is that due to the geometrical constraints the interior corner surface energy is unbounded below. This results in the liquid wicking into corners indefinitely. Interior corner flow's main quantity of interest is …


Numerical Techniques And Simulations For Studying Various High Power Optical Fiber Amplifiers, Particularly For Ytterbium (Yb+3), And Thulium (Tm+3) Doped Fibers, Tathagata Goswami Jun 2021

Numerical Techniques And Simulations For Studying Various High Power Optical Fiber Amplifiers, Particularly For Ytterbium (Yb+3), And Thulium (Tm+3) Doped Fibers, Tathagata Goswami

Dissertations and Theses

In this dissertation we present a simplified scalar numerical model, derived from Maxwell's field equations, for the fiber laser amplifier simulations. Maxwell's equations are reduced using a technique called Coupled Mode Theory (CMT).

The reduced model is made more efficient through a new scale model, referred to as an equivalent short fiber, which captures some of the essential characteristics of a longer fiber. The equivalent short fiber can be viewed as a fiber made using artificial (nonphysical) material properties that in some sense compensates for its reduced length. The computations can be accelerated by a factor approximately equal to the …


A Posteriori Error Estimates For Maxwell's Equations Using Auxiliary Subspace Techniques, Ahmed El Sakori Nov 2020

A Posteriori Error Estimates For Maxwell's Equations Using Auxiliary Subspace Techniques, Ahmed El Sakori

Dissertations and Theses

The aim of our work is to construct provably efficient and reliable error estimates of discretization error for Nédélec (edge) element discretizations of Maxwell's equations on tetrahedral meshes. Our general approach for estimating the discretization error is to compute an approximate error function by solving an associated problem in an auxiliary space that is chosen so that:

-Efficiency and reliability results for the computed error estimates can be established under reasonable and verifiable assumptions.

-The linear system used to compute the approximate error function has condition number bounded independently of the discretization parameter.

In many applications, it is some functional …


Guided Reinvention As A Context For Investigating Students' Thinking About Mathematical Language And For Supporting Students In Gaining Fluency, Kristen Vroom Jul 2020

Guided Reinvention As A Context For Investigating Students' Thinking About Mathematical Language And For Supporting Students In Gaining Fluency, Kristen Vroom

Dissertations and Theses

Fluency with mathematical language is important for students' engagement in many disciplinary practices such as defining, conjecturing, and proving; yet, there is growing evidence that mathematical language is challenging for undergraduate students. This dissertation study draws on two design experiments with pairs of students who were supported to encode their mathematical meanings with more formal language. I aimed to investigate the teaching and learning of mathematical language, and particularly the language in statements with multiple quantifiers, by engaging students in this type of activity. In the first paper, I investigated the complex ways in which the students in my study …


Convex And Nonconvex Optimization Techniques For Multifacility Location And Clustering, Tuyen Dang Thanh Tran Jun 2020

Convex And Nonconvex Optimization Techniques For Multifacility Location And Clustering, Tuyen Dang Thanh Tran

Dissertations and Theses

This thesis contains contributions in two main areas: calculus rules for generalized differentiation and optimization methods for solving nonsmooth nonconvex problems with applications to multifacility location and clustering. A variational geometric approach is used for developing calculus rules for subgradients and Fenchel conjugates of convex functions that are not necessarily differentiable in locally convex topological and Banach spaces. These calculus rules are useful for further applications to nonsmooth optimization from both theoretical and numerical aspects. Next, we consider optimization methods for solving nonsmooth optimization problems in which the objective functions are not necessarily convex. We particularly focus on the class …


Leveraging Model Flexibility And Deep Structure: Non-Parametric And Deep Models For Computer Vision Processes With Applications To Deep Model Compression, Anthony D. Rhodes May 2020

Leveraging Model Flexibility And Deep Structure: Non-Parametric And Deep Models For Computer Vision Processes With Applications To Deep Model Compression, Anthony D. Rhodes

Dissertations and Theses

My dissertation presents several new algorithms incorporating non-parametric and deep learning approaches for computer vision and related tasks, including object localization, object tracking and model compression. With respect to object localization, I introduce a method to perform active localization by modeling spatial and other relationships between objects in a coherent "visual situation" using a set of probability distributions. I further refine this approach with the Multipole Density Estimation with Importance Clustering (MIC-Situate) algorithm. Next, I formulate active, "situation" object search as a Bayesian optimization problem using Gaussian Processes. Using my Gaussian Process Context Situation Learning (GP-CL) algorithm, I demonstrate improved …


Tropical Cyclone Hazards In Relation To Propagation Speed, Jiehao Huang Jan 2020

Tropical Cyclone Hazards In Relation To Propagation Speed, Jiehao Huang

Dissertations and Theses

As the population and infrastructure along the US East Coast increase, it becomes increasingly important to study the characteristics of tropical cyclones that can impact the coast. A recent study shows that the propagation speed of tropical cyclones has slowed over the past 60 years, which can lead to greater accumulation of precipitation and greater storm surge impacts. The study presented herein is meant to examine and analyze the relationships that exist between the propagation speed of tropical cyclones, their surface wind strength, displacement angles, and cyclone averaged winds. This analysis is focused on tropical cyclones spanning from 1950-2015 in …


Predicting Absenteeism Of Female Students In Alabama, Funmilola Okelana Aug 2019

Predicting Absenteeism Of Female Students In Alabama, Funmilola Okelana

Dissertations and Theses

Abstract

Students are chronically absent when they miss at least 15 days of the school year. Past researchers have identified income and environment as factors that affect school absenteeism. Alabama is a poor state with a high crime rate. The hypothesis for this research is that the absenteeism of female students in Alabama is high. Do we reject or fail to reject this hypothesis. If we fail to reject this hypothesis, then what other factors can affect absenteeism in schools? How can we best predict the absenteeism of female students in Alabama? What is the effect of bad data on …


Necessary Conditions For Stability Of Vehicle Formations, Pablo Enrique Baldivieso Blanco May 2019

Necessary Conditions For Stability Of Vehicle Formations, Pablo Enrique Baldivieso Blanco

Dissertations and Theses

Necessary conditions for stability of coupled autonomous vehicles in R are established in this thesis. The focus is on linear arrays with decentralized vehicles, where each vehicle interacts with only a few of its neighbors. Decentralized means that there is no central authority governing the motion. Instead, each vehicle registers only velocity and position relative to itself and bases its acceleration only on those data. Explicit expressions are obtained for necessary conditions for asymptotic stability in the cases that a system consists of a periodic arrangement of two or three different types of vehicles, i.e. configurations as follows: ...2-1-2-1 or …


A New Finite Difference Time Domain Method To Solve Maxwell's Equations, Timothy P. Meagher May 2018

A New Finite Difference Time Domain Method To Solve Maxwell's Equations, Timothy P. Meagher

Dissertations and Theses

We have constructed a new finite-difference time-domain (FDTD) method in this project. Our new algorithm focuses on the most important and more challenging transverse electric (TE) case. In this case, the electric field is discontinuous across the interface between different dielectric media. We use an electric permittivity that stays as a constant in each medium, and magnetic permittivity that is constant in the whole domain. To handle the interface between different media, we introduce new effective permittivities that incorporates electromagnetic fields boundary conditions. That is, across the interface between two different media, the tangential component, Er(x,y), …


Presidential Job Approval Rating Analysis Through Social Media, Subramanian Venkataraman, Subramanian Venkataraman Oct 2017

Presidential Job Approval Rating Analysis Through Social Media, Subramanian Venkataraman, Subramanian Venkataraman

Dissertations and Theses

The aim of this study is to identify patterns in President Trump’s approval in the

Twitter universe through Social Media and Sentiment Analysis, and compare

against scientific polling to get meaningful insights on the limitations of Social

Media Analytics. For the purposes for this exercise, results from scientific polling

will be considered the true measure of approval, and will be used as control. In

order to perform sentiment analysis, we have used supervisory learning using

Naive Bayes Classifier algorithm which produced 0.862667 accuracy levels.


Generalized Differential Calculus And Applications To Optimization, R. Blake Rector Jun 2017

Generalized Differential Calculus And Applications To Optimization, R. Blake Rector

Dissertations and Theses

This thesis contains contributions in three areas: the theory of generalized calculus, numerical algorithms for operations research, and applications of optimization to problems in modern electric power systems. A geometric approach is used to advance the theory and tools used for studying generalized notions of derivatives for nonsmooth functions. These advances specifically pertain to methods for calculating subdifferentials and to expanding our understanding of a certain notion of derivative of set-valued maps, called the coderivative, in infinite dimensions. A strong understanding of the subdifferential is essential for numerical optimization algorithms, which are developed and applied to nonsmooth problems in operations …


Computational Algorithms For Improved Representation Of The Model Error Covariance In Weak-Constraint 4d-Var, Jeremy A. Shaw Mar 2017

Computational Algorithms For Improved Representation Of The Model Error Covariance In Weak-Constraint 4d-Var, Jeremy A. Shaw

Dissertations and Theses

Four-dimensional variational data assimilation (4D-Var) provides an estimate to the state of a dynamical system through the minimization of a cost functional that measures the distance to a prior state (background) estimate and observations over a time window. The analysis fit to each information input component is determined by the specification of the error covariance matrices in the data assimilation system (DAS). Weak-constraint 4D-Var (w4D-Var) provides a theoretical framework to account for modeling errors in the analysis scheme. In addition to the specification of the background error covariance matrix, the w4D-Var formulation requires information on the model error statistics and …


Orthomorphisms Of Boolean Groups, Nichole Louise Schimanski Aug 2016

Orthomorphisms Of Boolean Groups, Nichole Louise Schimanski

Dissertations and Theses

An orthomorphism, π, of a group, (G, +), is a permutation of G with the property that the map x → -x + π(x) is also a permutation. In this paper, we consider orthomorphisms of the additive group of binary n-tuples, Zn2. We use known orthomorphism preserving functions to prove a uniformity in the cycle types of orthomorphisms that extend certain partial orthomorphisms, and prove that extensions of particular sizes of partial orthomorphisms exist. Further, in studying the action of conjugating orthomorphisms by automorphisms, we find several symmetries within the orbits and stabilizers of this action, and …


Tree Graphs And Orthogonal Spanning Tree Decompositions, James Raymond Mahoney May 2016

Tree Graphs And Orthogonal Spanning Tree Decompositions, James Raymond Mahoney

Dissertations and Theses

Given a graph G, we construct T(G), called the tree graph of G. The vertices of T(G) are the spanning trees of G, with edges between vertices when their respective spanning trees differ only by a single edge. In this paper we detail many new results concerning tree graphs, involving topics such as clique decomposition, planarity, and automorphism groups. We also investigate and present a number of new results on orthogonal tree decompositions of complete graphs.