Physical Sciences and Mathematics Commons^™

Adaptive Multi-Label Classification On Drifting Data Streams, Martha Roseberry

Theses and Dissertations

Drifting data streams and multi-label data are both challenging problems. When multi-label data arrives as a stream, the challenges of both problems must be addressed along with additional challenges unique to the combined problem. Algorithms must be fast and flexible, able to match both the speed and evolving nature of the stream. We propose four methods for learning from multi-label drifting data streams. First, a multi-label k Nearest Neighbors with Self Adjusting Memory (ML-SAM-kNN) exploits short- and long-term memories to predict the current and evolving states of the data stream. Second, a punitive k nearest neighbors algorithm with a self-adjusting …

Graph Coloring Reconfiguration, Reem Mahmoud

Theses and Dissertations

Reconfiguration is the concept of moving between different solutions to a problem by transforming one solution into another using some prescribed transformation rule (move). Given two solutions s₁ and s₂ of a problem, reconfiguration asks whether there exists a sequence of moves which transforms s₁ into s₂. Reconfiguration is an area of research with many contributions towards various fields such as mathematics and computer science.
The k-coloring reconfiguration problem asks whether there exists a sequence of moves which transforms one k-coloring of a graph G into another. A move in this case is a type …

Using Superatomic Clusters And Charge Transfer Ligands To Control Electronic Characteristics Of Phosphorene Nanoribbons And Phosphorene Monolayer, Ryan Lambert

Theses and Dissertations

Phosphorene is a two-dimensional electron poor p-type semiconductor with high carrier mobility and great promise for applications in electronics and optoelectronics. As the main theme in this dissertation, the following work represents different investigations of various electronic properties associated with phosphorene. Most notable are the findings on charge transfer doping with metal-chalcogenide superatoms which displays novel control of the two most important properties of a semiconductor – the band gap energy and the nature of carriers. By tuning the width of the gap and p-/n-type character of conduction, we gain control over a material’s capacity to play a certain role …

Asymmetric Cuh-Catalyzed Reductive Coupling Of Allenamides With Carbonyl Electrophiles & Development Of Nanocatalysts For Heterogeneously Catalyzed Buchwald-Hartwig Amination, Raphael K. Klake

Theses and Dissertations

Many drugs and natural products contain multiple stereogenic carbons bearing heteroatoms throughout their carbon framework. Therefore, methods that can efficiently install multiple heteroatoms on a molecule are valuable. Reductive coupling reactions have been extensively studied, and the allylation of carbonyls via the reductive coupling approach has been a key method for generating chiral tertiary and secondary allylic alcohols. This work utilizes inexpensive Cu for the asymmetric reductive coupling of allenamides with carbonyls to simultaneously install two heteroatoms (oxygen and nitrogen) on the product. These molecules have a polarity profile that make them difficult to make using traditional methods. Herein, we …

Innovations In Drop Shape Analysis Using Deep Learning And Solving The Young-Laplace Equation For An Axisymmetric Pendant Drop, Andres P. Hyer

Theses and Dissertations

Axisymmetric Drop Shape Analysis (ADSA) is a technique commonly used to determine surface or interfacial tension. Applications of traditional ASDA methods to process analytical technologies are limited by computational speed and image quality. Here, we address these limitations using a novel machine learning approach to analysis. With a convolutional neural network (CNN), we were able to achieve an experimental fit precision of (+/-) 0.122 mN/m in predicting the surface tension of drop images at a rate of 1.5 ms^-1 versus 7.7 s^-1, which is more than 5,000 times faster than the traditional method. The results are validated on real images …

Mechanisms Of Emulsion Destabilization: An Investigation Of Surfactant, Stabilizer, And Detergent Based Formulations Using Diffusing Wave Spectroscopy, Jordan N. Nowaczyk

Theses and Dissertations

Conventional approaches for studying emulsions, such as microscopy and macroscopic phase tracking, present challenges when it comes to establishing detailed mechanistic descriptions of the impact of emulsifier and stabilizer additives. Additionally, while a combination of sizing methods and macroscopic phase tracking can provide insights into droplet size changes and concentration, the use of multiple measurements can be cumbersome and error-prone. It is the focus of this work, to present a new method for studying water in oil (W/O) emulsions that involves using diffusing wave spectroscopy (DWS) to examine the impact of three different surface stabilizing additives at varying concentrations. By …

Model-Based Imputation Of Below Detection Limit Missing Data And Group Selection In Bayesian Group Index Regression, Matthew Carli

Theses and Dissertations

Investigations into the association between chemical exposure and health outcomes are increasingly focused on the role of chemical mixtures, as opposed to individual chemicals. The analysis of chemical mixture data required the development of novel statistical methods, one of these being Bayesian group index regression. A statistical challenge common to all chemical mixture analyses is the ubiquitous presence of below detection limit (BDL) data. We propose an extension of Bayesian group index regression that treats both regression effects and missing BDL observations as parameters in a model estimated through a Markov Chain Monte Carlo algorithm that we refer to as …

Effects Of Slip On Highly Viscous Thin-Film Flows Inside Vertical Tubes (Constant Radius, Constricted And Flexible), Mark S. Schwitzerlett

Theses and Dissertations

Viscous liquid film flows in a tube arise in numerous industrial and biological applications, including the transport of mucus in human airways. Previous modeling studies have typically used no-slip boundary conditions, but in some applications the effects of slip at the boundary may not be negligible. We derive a long-wave model based on lubrication theory which allows for slippage along the boundary. Linear stability analysis verifies the impact of slip-length on the speed, growth rate, and wavelength of the most unstable mode. Nonlinear simulations demonstrate the impact of slip-length on plug formation and wave dynamics. These simulations are conducted for …

Face Anti-Spoofing And Deep Learning Based Unsupervised Image Recognition Systems, Enoch Solomon

Theses and Dissertations

One of the main problems of a supervised deep learning approach is that it requires large amounts of labeled training data, which are not always easily available. This PhD dissertation addresses the above-mentioned problem by using a novel unsupervised deep learning face verification system called UFace, that does not require labeled training data as it automatically, in an unsupervised way, generates training data from even a relatively small size of data. The method starts by selecting, in unsupervised way, k-most similar and k-most dissimilar images for a given face image. Moreover, this PhD dissertation proposes a new loss function to …

Material Extrusion-Based Additive Manufacturing: G-Code And Firmware Attacks And Defense Frameworks, Haris Rais

Theses and Dissertations

Additive Manufacturing (AM) refers to a group of manufacturing processes that create physical objects by sequentially depositing thin layers. AM enables highly customized production with minimal material wastage, rapid and inexpensive prototyping, and the production of complex assemblies as single parts in smaller production facilities. These features make AM an essential component of Industry 4.0 or Smart Manufacturing. It is now used to print functional components for aircraft, rocket engines, automobiles, medical implants, and more. However, the increased popularity of AM also raises concerns about cybersecurity. Researchers have demonstrated strength degradation attacks on printed objects by injecting cavities in the …

Variability In Causal Effects On A Binary Outcome And Noncompliance In A Multisite Randomized Trial, Xinxin Sun

Theses and Dissertations

Noncompliance to treatment assignment is widespread in randomized trials and presents challenges in causal inference. In the presence of noncompliance, the most commonly estimated effect of treatment assignment, also known as intent-to-treat (ITT) effect, is biased. Of interest in this setting is the complier average causal effect (CACE), the ITT effect among compliers. Further complication arises when the outcome variable is partially observed.

My research focuses on estimating the distribution of a site-specific CACE in a multisite randomized controlled trial (MRCT) by maximum likelihood (ML). Assuming compliance missing at random (MAR). We express the likelihood as an integral with respect …

I. Preparation Of Strategic Synthetic Building Blocks For World Health Organization Essential Medicines. Ii. Applying The Principles Of Process Intensification To The Synthesis Of Fluoroquinolone Antibiotics., Jeffrey M. Noble

Theses and Dissertations

The synthesis of active pharmaceutical ingredients is often a time-consuming and expensive process. Due to the nature of pharmaceutical manufacturing, these costs are carried forward to the final purchase price by the consumer. Although there are many factors which are involved in the final costing of a pharmaceutical, the cost associated with the synthesis is the primary one which can be managed by chemists and engineers.

This work discusses the synthetic routes of four active pharmaceutical ingredients as well as the synthetic techniques and equipment used with an emphasis on how the application of specific techniques can be applied to …

Selected Problems In Graph Coloring, Hudson Lafayette

Theses and Dissertations

The Borodin–Kostochka Conjecture states that for a graph G, if ∆(G) ≥ 9 and ω(G) ≤ ∆(G) − 1, then χ(G) ≤ ∆(G) − 1. We prove the Borodin–Kostochka Conjecture for (P5, gem)-free graphs, i.e., graphs with no induced P5 and no induced K1 ∨P4.

For a graph G and t, k ∈ Z+ at-tone k-coloring of G is a function f : V (G) → [k] such that |f(v) ∩f (w)| < d(v,w) for all distinct v, w ∈ V(G). The t-tone chromatic number of G, denoted τt(G), is the minimum k such that G is t-tone k-colorable. For small values of t, we prove sharp or nearly sharp upper bounds on the t-tone chromatic number of various classes of sparse graphs. In particular, we determine τ2(G) exactly when mad(G) < 12/5 and also determine τ2(G), up to a small additive constant, when G is outerplanar. Finally, we determine τt(Cn) exactly when t ∈ {3, 4, 5}.

Investigations In The Semi-Strong Product Of Graphs And Bootstrap Percolation, Kevin J. Mccall

Theses and Dissertations

The semi-strong product of graphs G and H is a way of forming a new graph from the graphs G and H. The vertex set of the semi-strong product is the Cartesian product of the vertex sets of G and H, V(G) x V(H). The edges of the semi-strong product are determined as follows: (g₁,h₁)(g₂,h₂) is an edge of the product whenever g₁g₂ is an edge of G and h₁h₂ is an edge of H or g₁ = g₂ and h₁h_{2 …}

Development Of Tangible Code Blocks For The Blind And Visually Impaired, Hyun Woo Kim

Theses and Dissertations

The fields of Science, Technology, Engineering, and Mathematics (STEM) have been growing at an accelerating rate in recent times. Knowing how to program has become one key skill for entering all of these STEM fields. However, many students find programming difficult. The block based programming language, Scratch, was specifically designed to lower hurdles to learning how to program for sighted students. Unfortunately, although very effective and widely used in K12 classrooms, Scratch, similar to other block based languages, is inaccessible to students who are blind and visually impaired (BVI). This thesis is part of a larger project to make the …

Minimal Sets, Union-Closed Families, And Frankl's Conjecture, Christopher S. Flippen

Theses and Dissertations

The most common statement of Frankl's conjecture is that for every finite family of sets closed under the union operation, there is some element which belongs to at least half of the sets in the family. Despite its apparent simplicity, Frankl's conjecture has remained open and highly researched since its first mention in 1979. In this paper, we begin by examining the history and previous attempts at solving the conjecture. Using these previous ideas, we introduce the concepts of minimal sets and minimally-generated families, some ideas related to viewing union-closed families as posets, and some constructions of families involving poset-defined …

Investigating The Dynamics And Fragmentation Of Nitroaromatic Radical Cations Through Femtosecond Time-Resolved Mass Spectrometry And Computational Chemistry, Hugo Andres Lopez Pena

Theses and Dissertations

Chemists have sought to control molecular dissociation with lasers for decades. Effective control of unimolecular dissociation was only achieved with the development of high-intensity ultrashort pulsed lasers and coherent control techniques that operate on timescales faster than vibrational energy redistribution. In view of this, our lab has specialized in the study of polyatomic radical cations using femtosecond time-resolved mass spectrometry (FTRMS). The interest in radical cations stems from the fact that they are highly reactive species that contribute to many physical, chemical, and biological processes. For instance, radical cations participate in shock initiation of detonated energetic materials used as explosives …

Enhancing Neuromorphic Computing With Advanced Spiking Neural Network Architectures, Paolo Gabriel Alejandro Cachi Delgado

Theses and Dissertations

This dissertation proposes ways to address current limitations of neuromorphic computing to create energy-efficient and adaptable systems for AI applications. It does so by designing novel spiking neural networks architectures that improve their performance. Specifically, the two proposed architectures address the issues of training complexity, hyperparameter selection, computational flexibility, and scarcity of neuromorphic training data. The first architecture uses auxiliary learning to improve training performance and data usage, while the second architecture leverages neuromodulation capability of spiking neurons to improve multitasking classification performance. The proposed architectures are tested on Intel's Loihi2 neuromorphic chip using several neuromorphic datasets, such as NMIST, …

Rainbow Turan Methods For Trees, Victoria Bednar

Theses and Dissertations

The rainbow Turan number, a natural extension of the well-studied traditional
Turan number, was introduced in 2007 by Keevash, Mubayi, Sudakov and Verstraete. The rainbow Tur ́an number of a graph F , ex*(n, F ), is the largest number of edges for an n vertex graph G that can be properly edge colored with no rainbow F subgraph. Chapter 1 of this dissertation gives relevant definitions and a brief history of extremal graph theory. Chapter 2 defines k-unique colorings and the related k-unique Turan number and provides preliminary results on this new variant. In Chapter 3, we explore the …

Multi-Modality Automatic Lung Tumor Segmentation Method Using Deep Learning And Radiomics, Siqiu Wang

Theses and Dissertations

Delineation of the tumor volume is the initial and fundamental step in the radiotherapy planning process. The current clinical practice of manual delineation is time-consuming and suffers from observer variability. This work seeks to develop an effective automatic framework to produce clinically usable lung tumor segmentations. First, to facilitate the development and validation of our methodology, an expansive database of planning CTs, diagnostic PETs, and manual tumor segmentations was curated, and an image registration and preprocessing pipeline was established. Then a deep learning neural network was constructed and optimized to utilize dual-modality PET and CT images for lung tumor segmentation. …

Learning Robot Motion From Creative Human Demonstration, Charles C. Dietzel

Theses and Dissertations

This thesis presents a learning from demonstration framework that enables a robot to learn and perform creative motions from human demonstrations in real-time. In order to satisfy all of the functional requirements for the framework, the developed technique is comprised of two modular components, which integrate together to provide the desired functionality. The first component, called Dancing from Demonstration (DfD), is a kinesthetic learning from demonstration technique. This technique is capable of playing back newly learned motions in real-time, as well as combining multiple learned motions together in a configurable way, either to reduce trajectory error or to generate entirely …

Incorporating Ontological Information In Biomedical Entity Linking Of Phrases In Clinical Text, Evan French

Theses and Dissertations

Biomedical Entity Linking (BEL) is the task of mapping spans of text within biomedical documents to normalized, unique identifiers within an ontology. Translational application of BEL on clinical notes has enormous potential for augmenting discretely captured data in electronic health records, but the existing paradigm for evaluating BEL systems developed in academia is not well aligned with real-world use cases. In this work, we demonstrate a proof of concept for incorporating ontological similarity into the training and evaluation of BEL systems to begin to rectify this misalignment. This thesis has two primary components: 1) a comprehensive literature review and 2) …

Biotic Characteristics Of Managed And Unmanaged Coastal Dunes In The Outer Banks, North Carolina, Andrew E. White

Theses and Dissertations

Under future climate change and sea level rise scenarios, Natural and Nature-Based Features (e.g., dunes) that protect coastal habitat and infrastructure will be exposed to increased wave energy and storm surge. Understanding how these forces will impact coastal dunes is necessary for their continued use as protective features. Coastal dunes develop through feedback between vegetation and sediment deposition, a process complicated by species-specific growth rates and responses to burial. Wave flume studies have tested the effects of dune vegetation on erosion and found multiple plant organs across several functional types to be important for resisting erosion. Although dune building and …

Estimating Weighted Panel Sizes For Primary Care Providers: An Assessment Of Clustering And Novel Methods Of Panel Size Estimation On Electronic Medical Records, Martin A. Lavallee

Theses and Dissertations

Primary Care is on the frontlines of healthcare, thus they see the most diverse set of patients. In order to achieve high functioning primary care, a practice must establish empanelment, the pairing of patients to providers. Enumeration of empanelment, or estimating panel sizes, helps ensure that the demands of the patients demand the supply of providers and optimize the balance of primary care resources to improve quality of care. Further we can adjust panel sizes by using patient-level data on healthcare utilization and complexity extracted from the electronic medial record to determine the amount of care or burden of work …

Direction Modulated Brachytherapy For The Treatment Of Cervical Cancer, Dylan Richeson

Theses and Dissertations

Purpose: To evaluate and compare the performance of 9 experimental DMBT tandem models of varying physical dimensions in relation to 24 previously planned HDR cervical cancer treatment plans from multiple institutions that used conventional tandem and rings or ovoid applicators.

Methods and Materials: The DMBT tandem is designed to be used concurrently with IGABT and is made from an MRI-compatible tungsten-alloy rod with 6 channels grooved out of its periphery. 9 experimental DMBT tandem prototypes were provided. Each of the models was of equal lengths but varied in thickness, channel diameter size, and circle channel diameter size. Replanning …

Progress Towards Next Generation Modulators Of Ctbp's Oncogenic Effects, Jacqueline L. West

Theses and Dissertations

Human C-terminal binding proteins (CtBP1 and CtBP2) are transcriptional coregulators of multiple genes in the human genome, including tumor suppressor genes (e.g., Bik, PTEN, BRCA1, and E-cadherin) as well as oncogenes (e.g. MDR1 and Tiam1). Both homologues of CtBP are overexpressed in many types of cancer, including breast cancer (92%), ovarian cancer (83%), colorectal cancer (64%), hepatocellular carcinoma (60%), gastric cancer, prostate cancer, and pancreatic adenocarcinoma. Further, expression levels of CtBP correlate with worse prognostic outcomes and more aggressive tumor features because it promotes proliferation, epithelial-mesenchymal transition, and cancer stem cell self-renewal activity.

Our laboratory has identified a lead inhibitor …

Molten Salt Technologies For Advanced Nuclear Fuel Cycles And Molten Salt Reactors, Dimitris Killinger

Theses and Dissertations

This dissertation provides five topics—an assessment of different monitoring and analytical techniques often cited in the literature for molten salt systems and designs for nuclear engineering applications. First, we explored commonly used materials for quasi-reference electrodes in molten chloride salts. Second, the limitations of the electrochemical analysis known as cyclic voltammetry due to the concentration of uranium(III) present were being investigated. Third, we provided an experimental assessment on the development of a spectroelectrochemical cell for interrogating various spectroelectrochemical techniques, namely chronoabsorptometry and chronofluorometry, and their limitations due to the presence of uranium(III) ions. Fourth, a study on the corrosion resistance …

Evaluating Long-Range Transportation Plans For Mainstreaming Of Climate Adaptation Among Virginia Mpos, Sebastian L. Shetty

Theses and Dissertations

Despite the strides made towards addressing climate change through greenhouse gas (GHG) emissions reduction strategies, it has become increasingly apparent that attempting to mitigate the crisis in such a manner alone is insufficient. This thesis joins a growing body of research on how our societies must adapt to a changing climate, contributing more evidence on common barriers to adaptation and how they might be overcome. Through an attempt to evaluate the progress made towards mainstreaming, or integrating, climate change concerns into five Virginia MPOs’ long-range transportation plans (LRTPs), this study provides support for prior hypotheses around the potential for MPOs …

Metal Nanoparticle Synthesis Via Laser-Induced Photochemical Reduction Of Metal Salts, Laysa M. Frias Batista

Theses and Dissertations

Significant attention has been focused on metal nanoparticles (MNPs) due to their unique optical, catalytic, and electronic properties. In the last two decades, laser synthesis techniques have emerged as versatile routes to MNPs that enable control over particle size, shape, and surface chemistry without the use of chemical reducing agents or surface-blocking capping ligands. A method gaining increasing attention is the direct laser-driven reduction of metal salts, called Laser Reduction in Liquid (LRL). LRL typically involves the use of intense laser pulses of picosecond or femtosecond duration to ionize and dissociate solvent molecules, generating plasmas with reactive chemical species such …

Mathematical Models Of Infection Prevention Programs In Hospital Settings, Kelly A. Reagan

Theses and Dissertations

Hospitals play a vital role in providing for the healthcare needs of a community. Patients can develop hospital-acquired infections (HAIs) during their hospitalization due to exposure to foreign bacteria, viruses, and fungi. Infection prevention programs target and reduce HAIs, but implementing the infection prevention programs often comes with a cost. The goal of my research is to use mathematical models to quantify the impact of infection prevention programs on cases of HAIs and total healthcare costs. First, I use a Markov chain model to quantify how one infection prevention program reduces general HAIs in the hospital. Then, I calculate the …