Physical Sciences and Mathematics Commons^™

Fpga-Augmented Secure Crash-Consistent Non-Volatile Memory, Yu Zou

Electronic Theses and Dissertations, 2020-2023

Emerging byte-addressable Non-Volatile Memory (NVM) technology, although promising superior memory density and ultra-low energy consumption, poses unique challenges to achieving persistent data privacy and computing security, both of which are critically important to the embedded and IoT applications. Specifically, to successfully restore NVMs to their working states after unexpected system crashes or power failure, maintaining and recovering all the necessary security-related metadata can severely increase memory traffic, degrade runtime performance, exacerbate write endurance problem, and demand costly hardware changes to off-the-shelf processors. In this thesis, we summarize and expand upon two of our innovative works, ARES and HERMES, to design …

Development And Surface Science Investigations Of Epitaxial Thin Films Suitable For Elucidating Mechanisms Of Water Formation And Migration On The Moon, Bijoya Dhar

Electronic Theses and Dissertations, 2020-2023

The growth and characterization of epitaxial thin films see ubiquitous use in both research and applications spanning a number of scientific and industrial fields with overlapping interests in materials science. The central theme of this work centers on leveraging the structural control afforded through the ultrahigh vacuum (UHV) approaches to thin-film epitaxy to derive atomically specific structure-chemistry relationships of key importance to various interface-mediated reactions. The first project was aimed at developing gold (Au) and ceria (CeO2) thin films using advanced surface-science techniques. In that project, a thoroughly wetted Au film on Ta metal substrate has been identified. This model …

Evaluating Augmented Reality Tools For Physics Education, Corey Pittman

Electronic Theses and Dissertations, 2020-2023

While we are in the midst of a renaissance of interest in augmented reality (AR), there remain a small number of application domains that have seen significant development. One domain that often benefits from additional visualization capabilities is education, specifically physics and other sciences. This paper summarizes interviews with secondary school educators about their experience with AR and their most desired features. Three prototypes were created which were used to collect usability information from students and educators about their preferences for AR applications in their physics courses. Additionally, we introduce the concept of Environmental Integration, a novel method of defining …

Modeling And Analysis Of Covid-19 And Dynamical Systems In Biology And Physics, Vladimir Grbic

Honors Undergraduate Theses

In this paper, we study various examples of dynamical systems found in nature and extract the necessary concepts to build upon. Then, we develop and propose a new deterministic model for COVID-19 propagation. Our model should serve two purposes. First, we will approximate the infected and deceased individuals after a given time during the pandemic. Then, using a linearized subsystem describing infectious compartments about the disease- free equilibrium (DFE), we will determine the basic reproductive number (R0) by the next-generation matrix method.

Family Communication: Examining The Differing Perceptions Of Parents And Teens Regarding Online Safety Communication, Tara Rutkowski

Honors Undergraduate Theses

The opportunity for online engagement increases possible exposure to potentially risky behaviors for teens, which may have significant negative consequences (Hair et al., 2009). Effective family communication about online safety can help reduce the risky adolescent behavior and limit the consequences after it occurs. This paper contributes a theory of communication factors that positively influence teen and parent perception of communication about online safety and provides design implications based on those findings. Previous work identified gaps in family communication, however, this study seeks to empirically identify factors that would close the communication gap from the perspective of both teens and …

Transforming Agriculture In The Pilbara: Interpretation Of Airborne Electromagnetic (Aem) Data, Aaron C. Davis, Mike Donn, John A. Simons, Christopher Schelfhout Dr, Olga Barron

Natural resources commissioned reports

This report focusses on hydrogeophysical and geological interpretation of the inversion results of an airborne electromagnetic (AEM) survey conducted north of Newman, Western Australia, in October and November 2019. The interpretation of the inversions is regional in scale, although we pay specific attention to interpretation of the near-surface transported cover sequences north and west of the Fortescue River. Specifically, we attempt to locate aquifers and near-surface geological structures that are likely to provide good quality groundwater for future extraction and storage. Analysis of the electrical conductivity structure of the ground also provides an estimate of the depth of the groundwater …

Photoluminescence Properties Of Polycyclic Aromatic Sulfur Heterocycles And Their Sorption And Desorption Onto Microplastics., Sadia Arif

Electronic Theses and Dissertations, 2020-2023

Polycyclic aromatic sulfur heterocycles (PASHs) are sulfur analogues of polycyclic aromatic hydrocarbons (PAHs) commonly found in environmental samples exposed to oil contamination. The determination of PASHs in complex samples is far more difficult than PAHs because of the sulfur atom in the heterocyclic ring, which increases the total number of possible isomeric compounds. Since their toxicological properties vary considerably from isomer to isomer, the unambiguous determination of specific isomers in environmental samples is crucial for ecotoxicological purposes and human safety. GC-MS has been the primary analytical technique for the determination of PASHs in environmental samples. Unfortunately, as the number of …

Contextual Understanding Of Sequential Data Across Multiple Modalities, Sangwoo Cho

Electronic Theses and Dissertations, 2020-2023

In recent years, progress in computing and networking has made it possible to collect large volumes of data for various different applications in data mining and data analytics using machine learning methods. Data may come from different sources and in different shapes and forms depending on their inherent nature and the acquisition process. In this dissertation, we focus specifically on sequential data, which have been exponentially growing in recent years on platforms such as YouTube, social media, news agency sites, and other platforms. An important characteristic of sequential data is the inherent causal structure with latent patterns that can be …

Plasmonic Properties Of Nanopatterned Graphene, Muhammad Waqas Shabbir

Electronic Theses and Dissertations, 2020-2023

Graphene is an atomically thin two-dimensional material with carbon atoms arranged in a honeycomb lattice. It has been successfully mechanically exfoliated from graphite and characterized in 2004 by Andre Geim and Konstantin Novoselov at the University of Manchester, UK. While suspended graphene holds the world record in mobility exceeding 100,000 cm2/Vs, which means that graphene could increase the operating frequency of electronic devices up to the THz regime. For example, imaging computer chips running at a few THz frequency, which would be about 1000 times faster than current chips. However, there are two main obstacles for using graphene in electronics …

2021 January - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Report

No abstract provided.

Review On Carbon Dioxide Utilization For Cycloaddition Of Epoxides By Ionic Liquid-Modified Hybrid Catalysts: Effect Of Influential Parameters And Mechanisms Insight, Jimmy Nelson Appaturi, Rajabathar. Jothi Ramalingam, Muthu Kumaran Gnanamani, Govindasami Periyasami, Prabhakarn Arunachalam, Rohana Adnan, Farook Adam, Mohammed D. Wasmiah, Hamad A. Al‐Lohedan

Center for Applied Energy Research Faculty and Staff Publications

The storage, utilization, and control of the greenhouse (CO₂) gas is a topic of interest for researchers in academia and society. The present review article is dedicating to cover the overall role of ionic liquid-modified hybrid materials in cycloaddition reactions. Special emphasis is on the synthesis of various cyclic carbonate using ionic liquid-based modified catalysts. Catalytic activity studies have discussed with respect to process conditions and their effects on conversion and product selectivity for the reaction of cycloaddition of CO₂ with styrene oxide. The reaction temperature and the partial pressure of CO₂ have found to play …

2020 - Tennessee Annual Climate Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Report

No abstract provided.

Compiled Dataset From The National Reservoir Research Program 1989 Dataset, Nicky M. Faucheux, Leandro E. Miranda

College of Forest Resources Publications and Scholarship

This dataset was compiled from the National Reservoir Research Program 1989 dataset. The NRRP dataset includes data from rotenone and creel studies at reservoirs throughout the continental US during the 1980s. We compiled the species level biomass data into total biomass for each of five trophic guilds (piscivores, detritivores, herbivores, invertivores, and planktivores). This compiled dataset was used to investigate the Cascading Reservoir Continuum Concept across 16 river basins in a study conducted by the 2020 Management of Impounded Rivers Class.

Forecasting The Prices Of Cryptocurrencies Using A Novel Parameter Optimization Of Varima Models, Alexander Barrett

Computational and Data Sciences (PhD) Dissertations

This work is a comparative study of different univariate and multivariate time series predictive models as applied to Bitcoin, other cryptocurrencies, and other related financial time series data. ARIMA models, long regarded as the gold standard of univariate financial time series prediction due to both its flexibility and simplicity, are used a baseline for prediction. Given the highly correlative nature amongst different cryptocurrencies, this work aims to show the benefit of forecasting with multivariate time series models—primarily focusing on a novel parameter optimization of VARIMA models outlined in this paper.

These models are trained on 3 years of historical data, …

Applications Of Machine Learning To Facilitate Software Engineering And Scientific Computing, Natalie Best

Computational and Data Sciences (PhD) Dissertations

The use of machine learning has risen in recent years, though many areas remain unexplored due to lack of data or lack of computational tools. This dissertation explores machine learning approaches in case studies involving image classification and natural language processing. In addition, a software library in the form of two-way bridge connecting deep learning models in Keras with ones available in the Fortran programming language is also presented.

In Chapter 2, we explore the applicability of transfer learning utilizing models pre-trained on non-software engineering data applied to the problem of classifying software unified modeling language diagrams where data is …

An Ecological Comparison Between Resource Subsidies: Pacific Lamprey (Entosphenus Tridentatus) And Pacific Salmon (Oncorhynchus Spp.), Jocelyn Wensloff

All Master's Theses

Historically, oligotrophic Pacific Northwest (PNW) streams received annual returns of spawning anadromous fish that provided resource subsidies in the form of marine-derived nutrients (MDN), thus driving stream food web productivity. To date, many studies in the PNW have focused on Pacific salmon (Oncorhynchus spp.) as a resource subsidy, overlooking other anadromous fish species such as Pacific lamprey (Entosphenus tridentatus). Both Pacific salmon and Pacific lamprey are culturally important to PNW tribes for ceremonial, medicinal, and subsistence purposes, and have been since time immemorial. Unfortunately, both salmon and lamprey populations are in decline. Historically, lamprey have been disregarded …

Fracking Florida, Emily Faulconer

Publications

• Traditional Hydraulic Fracturing
• Why Frack?
• Why it’s Controversial
• Acid Fracking
• What’s in the Wastewater?
• Ethylene Glycol
• 2-Butoxyethanol
• Benzene
• So Where Does the Wastewater Go?
• “Halliburton Loophole”
• Drilling in Florida
• Timeline of Events at Collier-Hogan Well
• Lease Termination & Permit Revocation
• Frack Fluid used at Collier-Hogan Well
• Groundwater Monitoring Wells
• FDEP Tested 142 Analytes
• House Bills 71 & 157: Fracturing Chemical Usage Disclosure Act
• Proposed Sabal Trail Pipeline
• Hands Across the Sand” Rally
• My $0.02

Unraveling A Trifecta Of Weak Non-Covalent Interactions: The Dissociation Energy Of The Anisole-Ammonia 1:1 Complex, John L. Loman, James T. Makuvaza, Damian L. Kokkin, Scott A. Reid

Chemistry Faculty Research and Publications

The anisole-ammonia 1:1 complex is a challenge for both experiment and theory. Early studies supported a non-planar structure, involving a trifecta of weak non-covalent interactions: N-H/O, N-H/π, and C-H/N. The calculated structure and binding energy of the complex proved remarkably sensitive to the level of theory employed. Here, we report the first experimental measurement of the ground state dissociation energy of the complex, and derive an excited (S₁) state dissociation energy that is in excellent agreement with the cutoff observed in the experimental excitation spectrum. Results are compared with previous predictions and new calculations based on benchmarked Density …

Fabrication Of Metal-Silicon Nanostructures By Reactive Laser Ablation In Liquid, Eric J. Broadhead

Theses and Dissertations

Metal-silicon nanostructures are a growing area of research due to their applications in multiple fields such as biosensing and catalysis. In addition, silicon can provide strong support effects to metal nanoparticles while being more cost effective than traditionally used supports, like titania. Traditional wet-chemical methods are capable of synthesizing metal-silicon nanostructures with a variety of composition and nanoparticle shapes, but they often require high temperatures, toxic solvents, strong reducing agents, or need capping agents added to stabilize the nanoparticles. Laser processing is an emerging technique capable of synthesizing metal-silicon composite surfaces that offers a faster, simpler, and greener synthesis route …

Continual Learning For Multi-Label Drifting Data Streams Using Homogeneous Ensemble Of Self-Adjusting Nearest Neighbors, Gavin Alberghini

Theses and Dissertations

Multi-label data streams are sequences of multi-label instances arriving over time to a multi-label classifier. The properties of the data stream may continuously change due to concept drift. Therefore, algorithms must adapt constantly to the new data distributions. In this paper we propose a novel ensemble method for multi-label drifting streams named Homogeneous Ensemble of Self-Adjusting Nearest Neighbors (HESAkNN). It leverages a self-adjusting kNN as a base classifier with the advantages of ensembles to adapt to concept drift in the multi-label environment. To promote diverse knowledge within the ensemble, each base classifier is given a unique subset of features and …

K-Nearest Neighbors Density-Based Clustering, Avory C. Bryant

Theses and Dissertations

Traditional density-based clustering approaches rely on a distance-based parameter to define data connectivity and density. However, an appropriate value of this parameter can be difficult to determine as it is highly dependent on the underlying distribution of the data. In particular, distribution parameters affect the scale of inter-group distances (e.g., variance); this dependence leads to a well-known inability to simultaneously detect clusters at varying levels of density. In this work, connectivity and density are defined according to the rank-order induced by the distance metric (i.e., invariant to the expected scale of the distances). Connectivity by k-nearest neighbors and density by …

Reliable And Interpretable Machine Learning For Modeling Physical And Cyber Systems, Daniel L. Marino Lizarazo

Theses and Dissertations

Over the past decade, Machine Learning (ML) research has predominantly focused on building extremely complex models in order to improve predictive performance. The idea was that performance can be improved by adding complexity to the models. This approach proved to be successful in creating models that can approximate highly complex relationships while taking advantage of large datasets. However, this approach led to extremely complex black-box models that lack reliability and are difficult to interpret. By lack of reliability, we specifically refer to the lack of consistent (unpredictable) behavior in situations outside the training data. Lack of interpretability refers to the …

Topics In Design And Analysis Of Experiments: Calibration, Sequential Experimentation, And Model Selection, Christine Miller

Theses and Dissertations

Experiments are widely used across multiple disciplines to uncover information about a system or processes. Experimental design is a statistical technique devoted to the methodology of selecting the appropriate samples to aid in the subsequent analysis. We research three open problems in experimental designs regarding calibration, sequential experimentation, and model selection. First, we focus on calibration; the impact of experimental design choice on the performance of statistical calibration is largely unknown. We investigate the performance of several experimental designs with regards to inverse prediction via a comprehensive simulation study. Specifically, we compare several design types including traditional response surface designs, …

Red Drum And Spotted Seatrout Live-Release Tournament Mortality And Dispersal, T. Reid Nelson, Crystal Hightower, Sean P. Powers

University Faculty and Staff Publications

Although catch-and-release fishing tournaments undoubtedly reduce mortality of target species, postrelease mortality and fish stockpiling at release sites remain common concerns related to these tournaments. The impacts of liverelease tournaments on freshwater species have been widely studied. However, research on estuarine sport fishes is lacking even though catch-and-release tournaments targeting these species are prevalent and popular recreational fisheries exist. Therefore, we estimated the post-weigh-in mortality and dispersal of Red Drum Sciaenops ocellatus and Spotted Seatrout Cynoscion nebulosus released from the 2016–2018 Alabama Deep Sea Fishing Rodeo live-weigh-in categories using acoustic telemetry. To concurrently estimate overall post-weigh-in mortality and dispersal, we …

Improving Space Efficiency Of Deep Neural Networks, Aliakbar Panahi

Theses and Dissertations

Language models employ a very large number of trainable parameters. Despite being highly overparameterized, these networks often achieve good out-of-sample test performance on the original task and easily fine-tune to related tasks. Recent observations involving, for example, intrinsic dimension of the objective landscape and the lottery ticket hypothesis, indicate that often training actively involves only a small fraction of the parameter space. Thus, a question remains how large a parameter space needs to be in the first place — the evidence from recent work on model compression, parameter sharing, factorized representations, and knowledge distillation increasingly shows that models can be …

Statistical Approaches For Estimation And Comparison Of Brain Functional Connectivity, Jifang Zhao

Theses and Dissertations

Drug addiction can lead to many health-related problems and social concerns. Functional connectivity obtained from functional magnetic resonance imaging (fMRI) data promotes a variety of fundamental understandings in such association. Due to its complex correlation structure and large dimensionality, the modeling and analysis of the functional connectivity from neuroimage are challenging. By proposing a spatio-temporal model for multi-subject neuroimage data, we incorporate voxel-level spatio-temporal dependencies of whole-brain measurements to improve the accuracy of statistical inference. To tackle large-scale spatio-temporal neuroimage data, we develop a computationally efficient algorithm to estimate the parameters. Our method is used to identify functional connectivity and …

The 3d Printing Of Dielectric Elastomer Films Assisted By Electrostatic Force, Yuhao Wang, Yanfen Zhou, Wenyue Li, Zhanxu Liu, Bangzi Zhou, Shipeng Wen, Liang Jiang, Shaojuan Che, Jianwei Ma, Tony Betts, Stephen Jerrams, Fenglei Zhou

Articles

ompared with traditional methods for preparing dielectric elastomer (DE) films, electrohydrodynamic (EHD) 3D printing displays many advantages, notably full automation, computer control and flexible design. It also confers high printing resolution, high preparation efficiency with minimal probability of nozzle clogging. In this article, EHD 3D printing was employed to fabricate silicone rubber (SR) based DE films. In order to increase their dielectric constant, high dielectric copper phthalocyanine (CuPc) particles were added into the SR ink. Optimal printing conditions were determined by analyzing the effects of printing voltage and ink properties on the formation of liquid cone and the printed line …

Radium Isotopes As Submarine Groundwater Discharge (Sgd) Tracers: Review And Recommendations, J. Garcia-Orellana, V. Rodellas, Joseph Tamborski, M. Diego-Feliu, P. Van Beek, Y. Weinstein, M. Charette, A. Alorda-Kleinglass, H.A. Michael, T. Stieglitz, J. Scholten

OES Faculty Publications

Submarine groundwater discharge (SGD) is now recognized as an important process of the hydrological cycle worldwide and plays a major role as a conveyor of dissolved compounds to the ocean. Naturally occurring radium isotopes (Ra-223, Ra-224, Ra-226 and Ra-228) are widely employed geochemical tracers in marine environments. Whilst Ra isotopes were initially predominantly applied to study open ocean processes and fluxes across the continental margins, their most common application in the marine environment has undoubtedly become the identification and quantification of SGD. This review focuses on the application of Ra isotopes as tracers of SGD and associated inputs of water …

A Mathematical Analysis Of The Wind Triangle Problem And An Inquiry Of True Airspeed Calculations In Supersonic Flight, Leonard T. Huang, Lisa I. Cummings

International Journal of Aviation, Aeronautics, and Aerospace

In the first half of this paper, we present a fresh perspective toward the Wind Triangle Problem in aerial navigation by deriving necessary and sufficient conditions, which we call "go/no-go conditions", for the existence/non-existence of a solution of the problem. Although our derivation is based on simple trigonometry and basic properties of quadratic functions, it is mathematically rigorous. We also offer examples to demonstrate how easy it is to check these conditions graphically. In the second half of this paper, we use function theory to re-examine another problem in aerial navigation, namely, that of computing true airspeed — even in …

Co2 Reduction Measures In The Aviation Industry: Current Measures And Outlook, Florian Mathys, P. Wild, J. Wang

International Journal of Aviation, Aeronautics, and Aerospace

This article gives a holistic overview of the current CO₂ reduction measures and analyses the effectiveness of measures that are feasible for implementation in the future. To achieve the objectives of the Paris Agreement, the aviation industry needs to implement reduction measures because of its forecasted growth and contribution to global warming. The focus is set on CO₂ reduction measures, categorized in technology, operations, infrastructure/air traffic management (ATM), and market-based measures. The most promising long-term technologies to reduce CO₂ emissions are hydrogen-powered aircrafts and sustainable aviation fuels (SAF). In terms of operations, CO₂ emissions can be …