Physical Sciences and Mathematics Commons^™

Diffractive Liquid Crystal Optical Elements For Near-Eye Displays, Jianghao Xiong

Electronic Theses and Dissertations, 2020-2023

Liquid crystal planar optics (LCPO) with versatile functionalities is emerging as a promising candidate for overcoming various challenges in near-eye displays, like augmented reality (AR) and virtual reality (VR), while maintaining a small form factor. This type of novel optical element exhibits unique properties, such as high efficiency, large angular/spectral bandwidths, polarization selectivity, and dynamic modulation. The basic molecular configuration of these novel reflective LCPO is analyzed, based on the simulation of molecular dynamics. In contrast to previously assumed planar-twist structure, our analysis predicts a slanted helix structure, which agrees with the measured results. The optical simulation model is established …

Polymer Derived Ceramic For Lithium-Ion Storage, And Electrospun Polyelectrolyte Fiber For Heavy Metal Ions Removal, Zeyang Zhang

Electronic Theses and Dissertations, 2020-2023

This dissertation includes two major projects. The first project investigated the great potential of polymer-derived ceramics (PDCs) as lithium-ion battery anode materials with good cycling stability and large capacity. SiCNO ceramic nanoparticles were produced by pyrolysis of polysilazane nanoparticles synthesized via an oil-in-oil emulsion crosslinking. The SiCNO nanoparticles had an average particle size of around 9 nm and contained graphitic carbon, Si3N4, and SiO2 domains. The electrochemical behavior of SiCNO nanoparticles anode was investigated to evaluate the Li-ion storage performance and understand its mechanism of Li-ion storage. The lithiation of SiCNO was observed at ~0.385 V versus Li/Li+. The anode …

Function Approximation Guarantees For A Shallow Neural Network Trained By Gradient Flow, Russell Gentile

Electronic Theses and Dissertations, 2020-2023

This work features an original result linking approximation and optimization theory for deep learning. Several examples from recent literature show that, given the same number of learnable parameters, deep neural networks can approximate richer classes of functions, with better accuracy than classical methods. The bulk of approximation theory results though, are only concerned with the infimum error for all possible parameterizations of a given network size. Their proofs often rely on hand-crafted networks, where the weights and biases are carefully selected. Optimization theory indicates that such models would be difficult or impossible to realize with standard gradient-based training methods. The …

First And Third Order Susceptibility Of Organic Molecules, Hao-Jung Chang

Electronic Theses and Dissertations, 2020-2023

Illuminating a material with intense laser excitation may change its properties and result in nonlinear absorption (NLA) and nonlinear refraction (NLR). In this dissertation we study the nonlinear absorption of organic compounds, the effect of extremely nondegenerate NLR in semiconductors, and the linear refractive index of organic solvents. In liquids, the refractive index has been studied for decades and different kinds of refractometers have been proposed. However, most of the reported values are in the visible region and only for commonly used solvents. We proposed a new interferometer-based refractometer that allows us to measure the refractive index from the visible …

An Analysis Of Associations Between Polarimetric Supercell Signatures, Erik Green

Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research

Supercell thunderstorms produce unique polarimetric radar signatures that are not often observed in unorganized deep convection. Repetitive signatures include deep and persistent differential reflectivity (Z_DR) columns and the Z_DR arc signature, which are both indicative of thermodynamic and microphysical processes intrinsic to supercells. Prior investigations of supercell polarimetric signatures, both those observed by operational and research radars, and those simulated numerically, reveal positive correlations between the Z_DR column depth and cross-sectional area and quantitative characteristics of the radar reflectivity field. This study expands upon prior work by incorporating a dataset of discrete, right moving supercells …

2022 January - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Report

No abstract provided.

2021 - Tennessee Annual Climate Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Report

No abstract provided.

Investigaion Of The Gamma Hurdle Model For A Single Population Mean, Alissa Jacobs

Electronic Theses and Dissertations

A common issue in some statistical inference problems is dealing with a high frequency of zeroes in a sample of data. For many distributions such as the gamma, optimal inference procedures do not allow for zeroes to be present. In practice, however, it is natural to observe real data sets where nonnegative distributions would make sense to model but naturally zeroes will occur. One example of this is in the analysis of cost in insurance claim studies. One common approach to deal with the presence of zeroes is using a hurdle model. Most literary work on hurdle models will focus …

A Contentious Crop: Exploring The Regulatory Debate Of Solar Power Production Facilities In Kittitas County, Washington, Daphne Condon

All Master's Theses

Between 2010 and 2018, Kittitas County, Washington faced an influx of Solar Power Production Facility (SPPF) proposals that challenged its traditional rural land management governance. Despite state support of decarbonized energy, variegated interpretations of project permitting procedures induced heated contentions amongst stakeholders. To explore this, this research constructs a multijurisdictional legal framework for SPPF advancement. It uses these laws to divulge the permitting processes of three case study projects founded in Kittitas County’s renewable energy history: The Wild Horse Wind Facility, the Iron Horse Solar Project, and the Columbia Solar Projects. Through a mixed methodology of project archival analysis and …

Determining The Effects Of Chemical Exposure On Hepatocyte Mitochondrial Networks And Cell Viability, Bethany Eaton

All Master's Theses

Mitochondria are cellular organelles that are becoming more recently studied. One of their main functions is the production of energy through cellular respiration, which is crucial to cell life. However, they are also associated with numerous disease states. It is hypothesized that reactive oxygen species (ROS), largely produced in mitochondria, induce oxidative stress and affect mitochondrial morphology along with cell viability. This study compares chemical exposure of menadione, an ROS producer, and phthalates (plasticizers) on two mouse hepatocyte cell lines to determine the effects they have on mitochondrial morphology and cell viability. Three experiments were performed to analyze the effects …

Detecting Impacts Of Historic And Undocumented Landslide Tsunamis At High Latitude Sites Using Ndvi, Trent Adams

All Master's Theses

In the last century most of the largest landslide tsunamis on record have occurred in remote regions of the world, which has led to a limited understanding of their impacts on landscapes. The goal of this work is to present a methodology to identify impacts of landslide tsunamis with a technique that does not require field work in extremely remote locations. Although landslide tsunamis have occurred that were not directly witnessed by anyone, evidence of landslide tsunamis can still be observed via satellite. Using multispectral satellite images, we calculated normalized difference vegetation index (NDVI) to identify tsunami-impacted sites, estimate tsunami …

Molecular Dynamics On Quantum Annealers, Igor Gaidai, Dmitri Babikov, Alexander Teplukhin, Brian K. Kendrick, Susan M. Mniszewski, Yu Zhang, Sergei Tretiak, Pavel A. Dub

Chemistry Faculty Research and Publications

In this work we demonstrate a practical prospect of using quantum annealers for simulation of molecular dynamics. A methodology developed for this goal, dubbed Quantum Differential Equations (QDE), is applied to propagate classical trajectories for the vibration of the hydrogen molecule in several regimes: nearly harmonic, highly anharmonic, and dissociative motion. The results obtained using the D-Wave 2000Q quantum annealer are all consistent and quickly converge to the analytical reference solution. Several alternative strategies for such calculations are explored and it was found that the most accurate results and the best efficiency are obtained by combining the quantum annealer with …

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 …

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. …

Universal Design In Bci: Deep Learning Approaches For Adaptive Speech Brain-Computer Interfaces, Srdjan Lesaja

Theses and Dissertations

In the last two decades, there have been many breakthrough advancements in non-invasive and invasive brain-computer interface (BCI) systems. However, the majority of BCI model designs still follow a paradigm whereby neural signals are preprocessed and task-related features extracted using static, and generally customized, data-independent designs. Such BCI designs commonly optimize narrow task performance over generalizability, adaptability, and robustness, which is not well suited to meeting individual user needs. If one day BCIs are to be capable of decoding our higher-order cognitive commands and conceptual maps, their designs will need to be adaptive architectures that will evolve and grow in …

Computational Analysis Of Drug Targets And Prediction Of Protein-Compound Interactions, Sina Ghadermarzi

Theses and Dissertations

Computational prediction of compound-protein interactions generated a substantial amount of interest in the recent years owing to the importance of the knowledge of these interaction for drug discovery and drug repurposing efforts. Research suggests that the currently known drug targets constitute only a fraction of a complete set of drug targets, limiting our ability to identify suitable targets to develop new drugs or to repurpose current drugs for new diseases. These efforts are further thwarted by our limited knowledge of protein-drug (and more generally protein-compound) interactions, where only a subset of drug targets is typically known for the currently used …

Algorithm Vs. Algorithm, Cary Coglianese, Alicia Lai

All Faculty Scholarship

Critics raise alarm bells about governmental use of digital algorithms, charging that they are too complex, inscrutable, and prone to bias. A realistic assessment of digital algorithms, though, must acknowledge that government is already driven by algorithms of arguably greater complexity and potential for abuse: the algorithms implicit in human decision-making. The human brain operates algorithmically through complex neural networks. And when humans make collective decisions, they operate via algorithms too—those reflected in legislative, judicial, and administrative processes. Yet these human algorithms undeniably fail and are far from transparent. On an individual level, human decision-making suffers from memory limitations, fatigue, …

Antitrust By Algorithm, Cary Coglianese, Alicia Lai

All Faculty Scholarship

Technological innovation is changing private markets around the world. New advances in digital technology have created new opportunities for subtle and evasive forms of anticompetitive behavior by private firms. But some of these same technological advances could also help antitrust regulators improve their performance in detecting and responding to unlawful private conduct. We foresee that the growing digital complexity of the marketplace will necessitate that antitrust authorities increasingly rely on machine-learning algorithms to oversee market behavior. In making this transition, authorities will need to meet several key institutional challenges—building organizational capacity, avoiding legal pitfalls, and establishing public trust—to ensure successful …

From Negative To Positive Algorithm Rights, Cary Coglianese, Kat Hefter

All Faculty Scholarship

Artificial intelligence, or “AI,” is raising alarm bells. Advocates and scholars propose policies to constrain or even prohibit certain AI uses by governmental entities. These efforts to establish a negative right to be free from AI stem from an understandable motivation to protect the public from arbitrary, biased, or unjust applications of algorithms. This movement to enshrine protective rights follows a familiar pattern of suspicion that has accompanied the introduction of other technologies into governmental processes. Sometimes this initial suspicion of a new technology later transforms into widespread acceptance and even a demand for its use. In this paper, we …

Mapping The Dna Damaging Effects Of Polypyridyl Copper Complexes With Dna Electrochemical Biosensors, Anna Banasiak, Nicolò Zuin Fantoni, Andrew Kellett, John Colleran

Articles

Several classes of copper complexes are known to induce oxidative DNA damage that mediates cell death. These compounds are potentially useful anticancer agents and detailed investigation can reveal the mode of DNA interaction, binding strength, and type of oxidative lesion formed. We recently reported the development of a DNA electrochemical biosensor employed to quantify the DNA cleavage activity of the well-studied [Cu(phen)₂]²⁺ chemical nuclease. However, to validate the broader compatibility of this sensor for use with more diverse—and biologically compatible—copper complexes, and to probe its use from a drug discovery perspective, analysis involving new compound libraries is …

Maintenance Optimization In A Digital Twin For Industry 4.0, Abhijit Gosavi, Vy Khoi Le

Engineering Management and Systems Engineering Faculty Research & Creative Works

The advent of Internet of Things and artificial intelligence in the era of Industry 4.0 has transformed decision-making within production systems. In particular, many decisions that previously required significant human activity are now made automatically with minimal human intervention via so-called digital twins (DTs). In the context of maintenance and reliability modeling, this naturally calls for new paradigms that can be seamlessly integrated within DTs for decision-making. The input data for time to failure needed in reliability computations are directly collected from the work center in a digital setting and often do not satisfy a known distribution. A neural network …

Robophobia, Andrew Keane Woods

University of Colorado Law Review

Robots-machines, algorithms, artificial intelligence-play an increasingly important role in society, often supplementing or even replacing human judgment. Scholars have rightly become concerned with the fairness, accuracy, and humanity of these systems. Indeed, anxiety about machine bias is at a fever pitch. While these concerns are important, they nearly all run in one direction: we worry about robot bias against humans; we rarely worry about human bias against robots.

This is a mistake. Not because robots deserve, in some deontological sense, to be treated fairly-although that may be true-but because our bias against nonhuman deciders is bad for us. For example, …

Stroke Clustering And Fitting In Vector Art, Khandokar Shakib

Senior Independent Study Theses

Vectorization of art involves turning free-hand drawings into vector graphics that can be further scaled and manipulated. In this paper, we explore the concept of vectorization of line drawings and study multiple approaches that attempt to achieve this in the most accurate way possible. We utilize a software called StrokeStrip to discuss the different mathematics behind the parameterization and fitting involved in the drawings.

Estimating Transport Of Diesel Particulate Emissions In The Portland Metro Using Lagrangian-Based Dispersion Modeling, Andrew Mckinley Rogers

Environmental Science and Management Professional Master's Project Reports

Air pollution from diesel combustion is a well-known and serious problem which adversely impacts human and environmental health throughout the world. One of the primary pollutants of concern from diesel combustion are the solid particles formed as a byproduct of the incomplete combustion of the diesel, also known as diesel particulate matter. As a result of the ubiquitous use of diesel-fired engines in urban environments, understanding the transport of diesel particulate matter from the exhaust is paramount in assessing human exposure to this toxic pollutant. Air dispersion modeling is one method to study how diesel particulate matter is transported and …

Carli Creek Regional Water Quality Project: Assessing Water Quality Improvement At An Urban Stormwater Constructed Wetland, Christopher L. Desiderati

Environmental Science and Management Professional Master's Project Reports

Stormwater management is an ongoing challenge in the United States and the world at-large. As state and municipal agencies grapple with conflicting interests like encouraging land development, complying with permits to control stormwater discharges, “urban stream syndrome” effects, and charges to steward natural resources for the long-term, some agencies may turn to constructed wetlands (CWs) as aesthetically pleasing and functional natural analogs for attenuating pollution delivered by stormwater runoff to rivers and streams. Constructed wetlands retain pollutants via common physical, physicochemical, and biological principles such as settling, adsorption, or plant and algae uptake. The efficacy of constructed wetlands for pollutant …

Cycle Decomposition For Integral Current Homology, Kristin Julia Duling

Graduate Theses, Dissertations, and Problem Reports

A standard graph theoretical result states that every element of the cycle space of a graph has a cycle decomposition. Georgakopoulos expands this result to a primitive decomposition and minimal representation of each element in a modified 1-dimensional singular homology. We modify the m-dimensional integral current homology in order to ensure a primitive decomposition for each element.

Counting The Moduli Space Of Pentagons On Finite Projective Planes, Maxwell Hosler

Senior Independent Study Theses

Finite projective planes are finite incidence structures which generalize the concept of the real projective plane. In this paper, we consider structures of points embedded in these planes. In particular, we investigate pentagons in general position, meaning no three vertices are colinear. We are interested in properties of these pentagons that are preserved by collineation of the plane, and so can be conceived as properties of the equivalence class of polygons up to collineation as a whole. Amongst these are the symmetries of a pentagon and the periodicity of the pentagon under the pentagram map, and a generalization of …

Wildfire Simulation Using Agent Based Modeling: Expanding Controlled Burn Season, Morgan C. Kromer

Senior Independent Study Theses

The United States is home to many different and unique forests. Prior to the 21st century, the United States Forests Service assumed that the best way to protect these forests was to put all efforts to keeping them alive. An enemy to these efforts were wildfires, thus the US adopted a complete fire suppression approach. At the turn of the century, the US realized that wildfires are a necessary part of a forest ecosystem, as they help return nutrients to the soil and reduce ground fuels. However, after suppressing all fires for over 100 years, the forests evolved into a …

The Infinity Conundrum: Understanding Topics In Set Theory And The Continuum Hypothesis, Sabrina Grace Helck

Senior Independent Study Theses

This project is concerned with articulating the necessary background in order to understand the famous result of the undecidability of the continuum hypothesis. The first chapter of this independent study discusses the foundations of set theory, stating fundamental definitions and theorems that will be used throughout the remainder of the project. The second chapter focuses on ordinal and cardinal numbers which will directly relate to the final chapter. First, there is a clear explanation of the notion of order and what it means for a set to be well-ordered. Then ordinal numbers are defined and some properties are listed and …

On Implementing And Testing The Rsa Algorithm, Kien Trung Le

Senior Independent Study Theses

In this work, we give a comprehensive introduction to the RSA cryptosystem, implement it in Java, and compare it empirically to three other RSA implementations. We start by giving an overview of the field of cryptography, from its primitives to the composite constructs used in the field. Then, the paper presents a basic version of the RSA algorithm. With this information in mind, we discuss several problems with this basic conception of RSA, including its speed and some potential attacks that have been attempted. Then, we discuss possible improvements that can make RSA runs faster and more secure. On the …