Physical Sciences and Mathematics Commons^™

Divergence-Free Tensor Densities In Two Dimensions, Tyler Hansen

All Graduate Theses and Dissertations, Fall 2023 to Present

In physics, a common method for exploring the way a physical system changes over time is to look at the system’s energy. Roughly speaking, the energy in these systems are either motion-based (kinetic energy, a bullet in flight) or position-based (potential energy, a rock sitting at the top of a hill). The difference between the system’s total kinetic and potential energies is quantified by an expression called the Lagrangian. Using a special procedure, this Lagrangian is massaged to produce a group of equations called the Euler-Lagrange equations; if the initial configuration of the system is provided, the solution to these …

Generative Ai In Education From The Perspective Of Students, Educators, And Administrators, Aashish Ghimire

All Graduate Theses and Dissertations, Fall 2023 to Present

This research explores how advanced artificial intelligence (AI), like the technology that powers tools such as ChatGPT, is changing the way we teach and learn in schools and universities. Imagine AI helping to summarize thick legal documents into something you can read over a coffee break or helping students learn how to code by offering personalized guidance. We looked into how teachers feel about using these AI tools in their classrooms, what kind of rules schools have about them, and how they can make learning programming easier for students. We found that most teachers are excited about the possibilities but …

Spatial Ecology Of Mule Deer Migrations From Grand Teton National Park And The Teton Range, Justin K. Schwabedissen

All Graduate Theses and Dissertations, Fall 2023 to Present

The Greater Yellowstone Ecosystem hosts several of the longest, fully intact ungulate migrations remaining in the continental United States. However, expanding development and an increasing human footprint continue to truncate migratory routes. While the endpoints are often a seasonal range on protected lands, these migration corridors frequently cross other jurisdictional boundaries, including large tracts of private or multiple-use lands, with varying levels of protection. Thus, it is critical resource managers understand the dynamics of migratory movements to define population-level corridors and prioritize appropriate conservation strategies. Mule deer in Wyoming have been documented traveling long distances between summer and winter ranges; …

A Review Of Student Attitudes Towards Keystroke Logging And Plagiarism Detection In Introductory Computer Science Courses, Caleb Syndergaard

All Graduate Theses and Dissertations, Fall 2023 to Present

The following paper addresses student attitudes towards keystroke logging and plagiarism prevention measures. Specifically, the paper concerns itself with changes made to the “ShowYourWork” plugin, which was implemented to log the keystrokes of students in Utah State University’s introductory Computer Science course, CS1400. Recent work performed by the Edwards Lab provided insights into students’ feelings towards keystroke logging as a measure of deterring plagiarism. As a result of that research, we have concluded that measures need to be taken to enable students to have more control over their data and assist students to feel more comfortable with keystroke logging. This …

Analysis And Numerical Simulation Of Tumor Growth Models, Daniel Acosta Soba

Masters Theses and Doctoral Dissertations

In this dissertation we focus on the numerical analysis of tumor growth models. Due to the difficulty of developing physically meaningful approximations of such models, we divide the main problem into more simple pieces of work that are addressed in the different chapters. First, in Chapter 2 we present a new upwind discontinuous Galerkin (DG) scheme for the convective Cahn–Hilliard model with degenerate mobility which preserves the pointwise bounds and prevents non-physical spurious oscillations. These ideas are based on a well-suited piecewise constant approximation of convection equations. The proposed numerical scheme is contrasted with other approaches in several numerical experiments. …

Comprehensive Question And Answer Generation With Llama 2, Matous Hybl

MS in Computer Science Theses

Since the introduction of transformers, large language models have proven capable in many natural language processing fields. However, existing systems still face challenges in generating high-quality extractive questions. Base models and public chatbots fall short if the question source or quantity are critical. Our contribution is a question and answer generator for generating comprehensive, extractive questions and answers. This approach includes fine-tuning a LLaMA 2 base model for answer extraction (AE) and question generation (QG). We evaluate the resulting system using common automated metrics and a manual evaluation. We find that our system is comparable to the latest research and …

Feed More, Waste Less, Kaitlyn Dietz

Honors Projects

With college prices and the cost of food increasing, so has the rate of food insecurity among college students. Food insecurity is defined as the lack of availability or access to food to meet someone’s basic and necessary needs. Food insecurity is associated with lower grades, depression, higher perceived stress, and lower graduation rates. Campuses across the country are responding to the problem in a variety of ways, including distribution of food directly to students through food pantries. Meal plans are expensive in the addition to college tuition and housing. The lowest cost for a meal plan at Bowling Green …

Luminescence And Structural Properties Of Silicon-Germanium Quantum Structures Fabricated By Ion Implantation, Matheus Coelho Adam

Electronic Thesis and Dissertation Repository

The advancement of semiconductor materials has played a crucial role in driving positive technological breakthroughs that impact humanity in numerous ways. The presence of defects significantly alters the physical properties of semiconductors, making their analysis essential in the fabrication of semiconductor devices. I presented a new method to quantify surface and near-surface defects in single crystal semiconductors. Epitaxially-grown silicon was measured by low energy electron diffraction (LEED) to obtain the surface Debye temperature (θ_D). The results showed the surface θ_D of bulk Si (001), 1.0 μm, and 0.6 μm Si on sapphire of 333 K, 299 K, …

Post-Modeling Adjustments And Delivered Dose Verification Of The 6fff Beam Model Commissioned For The Monaco Treatment Planning System, Grant C. Debevec

LSU Master's Theses

External beam radiation therapy has been shown to be an effective treatment method for tumors and abnormalities of the spine and vertebral region. Treating the spine using a stereotactic body radiation therapy (SBRT) technique can reduce toxicity to the spinal cord. The 6 MV flattening filter free (6FFF) beam model is currently used to plan and calculate dose for SBRT treatment plans, and the treatment plans are delivered using a linear accelerator (LINAC).

The commissioned beam model represents an invariant component of a LINAC. For volumetric modulated arc therapy (VMAT) treatment plans, the multileaf collimator (MLC) positions are changing throughout …

All-Optical Probes Of Particle-Like Charge Migration Dynamics, Kyle A. Hamer

LSU Doctoral Dissertations

Particle-like charge migration (CM) is the coherent, back-and-forth motion of a positively-charged electron hole along the backbone of a molecule following a sudden ionization. CM in small molecules generally occurs on an Angstrom (10^-10 m) spatial scale and an attosecond (10^-18 s) timescale. I use time-dependent density-functional theory (TDDFT) to simulate CM modes in organic molecules, and to explore all-optical probes of this attosecond electron dynamics using high-harmonic spectroscopy (HHS). By leveraging my results from previous studies of two-center interferences in carbon dichalcogens, in which I separated the harmonic signal into contributions from individual Kohn-Sham orbitals, I first …

Exploration Of Characteristic Curve In Fox Float 3 Shock Dampers To Expedite Shock Damp Tuning., Joshua R. Moore

Honors College Theses

The shock absorber is an integral part of a vehicle suspension system and has a strong influence on its performance, especially in the case of motorsports. It is important to study the force versus velocity relationship, commonly known as the characteristic curve of the shock absorber both during compression and rebound. Vendor-supplied characteristics often reflect the behavior of the shock absorber in a particular setting. However, during the installation, the settings inside the shock absorber are adjusted to increase the human comfort level and performance of the vehicle. This may change the characteristic curve of the shock. The available data …

Navigating Murky Waters: State-Level Strategies For Wetland Preservation And Tile Drainage Regulation After Sackett V. Epa, Caleb M. Swanson

Honors Thesis

Wetlands are some of the world’s most valuable ecosystems, serving as provisioners of species habitat, carbon sequestration, flood mitigation, water quality purification, and other ecosystem services. Human development has resulted in substantial wetland loss the world over. In the 1970s, the United States Congress passed the Clean Water Act, giving the EPA broad authority over wetland protection. However, in the summer of 2023, the United States Supreme Court decided Sackett v. EPA, limiting the EPA’s jurisdiction over wetlands to those indistinguishably connected to generally recognized “Waters of the United States” and removing federal protection for millions of acres of wetlands, …

Applying Mathematical Modeling To The Study Of Family Systems, Dahlia Maxwell

Theses and Dissertations

Mathematical modeling provides a powerful framework for insight into current scientific theories as well as hypothesis generation for further research. Despite its undeniable potential to enrich scientific advancement, the application of mathematical modeling remains conspicuously scarce in the field of family science. The complexity inherent in family dynamics, coupled with the intricate interplay of emotions in the individual, underscores the necessity of a robust analytical approach. Addressing this critical gap in the literature, this thesis introduces a sophisticated mathematical model of family dynamics integrating essential elements from family systems theory, emotion dynamics, and appraisal theory. The model is implemented as …

Advancing Single-Cell Proteomics Through Innovations In Liquid Chromatography And Mass Spectrometry, Kei Grant Isaac Webber

Theses and Dissertations

Traditional proteomics studies can measure many protein biomarkers simultaneously from a single patient-derived sample, promising the possibility of syndromic diagnoses of multiple diseases sharing common symptoms. However, precious cellular-level information is lost in conventional bulk-scale studies that measure tissues comprising many types of cells. As single cells are the building blocks of organisms and are easier to biopsy than traditional bulk samples, performing proteomics on a single-cell level would benefit clinicians and patients. Single-cell proteomics, combined with mass spectrometry imaging, can be used to analyze cells in their microenvironment, preserving spatial information. We have previously used laser-capture microdissection to isolate …

Applications Of Survival Estimation Under Stochastic Order To Cancer: The Three Sample Problem, Sage Vantine

Honors Program Theses and Research Projects

Stochastic ordering of probability distributions holds various practical applications. However, in real-world scenarios, the empirical survival functions extracted from actual data often fail to meet the requirements of stochastic ordering. Consequently, we must devise methods to estimate these distribution curves in order to satisfy the constraint. In practical applications, such as the investigation of the time of death or the progression of diseases like cancer, we frequently observe that patients with one condition are expected to exhibit a higher likelihood of survival at all time points compared to those with a different condition. Nevertheless, when we attempt to fit a …

Robot Proficiency Self-Assessment Using Assumption-Alignment Tracking, Xuan Cao

Theses and Dissertations

A robot is proficient if its performance for its task(s) satisfies a specific standard. While the design of autonomous robots often emphasizes such proficiency, another important attribute of autonomous robot systems is their ability to evaluate their own proficiency. A robot should be able to conduct proficiency self-assessment (PSA), i.e. assess how well it can perform a task before, during, and after it has attempted the task. We propose the assumption-alignment tracking (AAT) method, which provides time-indexed assessments of the veracity of robot generators' assumptions, for designing autonomous robots that can effectively evaluate their own performance. AAT can be considered …

Modeling And Numerical Analysis Of The Cholesteric Landau-De Gennes Model, Andrew L. Hicks

LSU Doctoral Dissertations

This thesis gives an analysis of modeling and numerical issues in the Landau-de Gennes (LdG) model of nematic liquid crystals (LCs) with cholesteric effects. We derive various time-step restrictions for a (weighted) $L^2$ gradient flow scheme to be energy decreasing. Furthermore, we prove a mesh size restriction, for finite element discretizations, that is critical to avoid spurious numerical artifacts in discrete minimizers that is not well-known in the LC literature, particularly when simulating cholesteric LCs that exhibit ``twist''. Furthermore, we perform a computational exploration of the model and present several numerical simulations in 3-D, on both slab geometries and spherical …

Interactive Effects Of Co2, Temperature, And Nitrate Limitation On The Growth And Physiology Of Marine Cyanobacterium Synechococcus Sp. Ccmp 1334, Alyssa K. Sharbaugh

LSU Master's Theses

The marine cyanobacterium Synechococcus sp. CCMP 1334 was grown in a continuous culture system on a 12:12 h light:dark cycle at all combinations of low and high pCO2 (400 and 1000 ppmv, respectively), nitrate availability (nitrate-limited and nutrient-replete conditions), and temperatures of 21°C, 24°C, 28°C, 32°C, and 35°C. The maximum median nutrient-replete growth rate was ~1.15 d−1 at 32 –35°C. Median growth rates at 1000 ppmv pCO2 were higher than those at 400 ppmv at all temperatures, but most of the differences were statistically insignificant. Carbon:nitrogen ratios were independent of pCO2 at a fixed relative growth rate but decreased with …

Use Of Unoccupied Aerial Vehicle (Drones) Based Remote Sensing To Model Platform Topography And Identify Human-Made Earthen Barriers In Salt Marshes, Joshua J. Ward

Masters Theses

Elevation is a foundational driver of salt marsh morphology. Elevation governs inundation and hydrological patterns, vegetation distribution, and soil health. Anthropogenic impacts at grand scales (e.g., rising sea levels) and local scales (e.g., infrastructure) have altered the elevation of the salt marsh surface, changing the topography and morphology of these ecosystems. This study establishes and assesses means to document and analyze these impacts using Unoccupied Aerial Vehicle (UAV) based remote sensing to model platform topography. This thesis’s first and primary study presents and compares methods of producing high-resolution digital terrain models (DTMs) with UAV-based Digital Aerial Photogrammetry (DAP) and Light …

Extracting Dnn Architectures Via Runtime Profiling On Mobile Gpus, Dong Hyub Kim

Masters Theses

Due to significant investment, research, and development efforts over the past decade, deep neural networks (DNNs) have achieved notable advancements in classification and regression domains. As a result, DNNs are considered valuable intellectual property for artificial intelligence providers. Prior work has demonstrated highly effective model extraction attacks which steal a DNN, dismantling the provider’s business model and paving the way for unethical or malicious activities, such as misuse of personal data, safety risks in critical systems, or spreading misinformation. This thesis explores the feasibility of model extraction attacks on mobile devices using aggregated runtime profiles as a side-channel to leak …

An Analysis And Ontology Of Teaching Methods In Cybersecurity Education, Sarah Buckley

LSU Master's Theses

The growing cybersecurity workforce gap underscores the urgent need to address deficiencies in cybersecurity education: the current education system is not producing competent cybersecurity professionals, and current efforts are not informing the non-technical general public of basic cybersecurity practices. We argue that this gap is compounded by a fundamental disconnect between cybersecurity education literature and established education theory. Our research addresses this issue by examining the alignment of cybersecurity education literature concerning educational methods and tools with education literature.

In our research, we endeavor to bridge this gap by critically analyzing the alignment of cybersecurity education literature with education theory. …

Sensor Analytics For Subsea Pipeline And Cable Inspection: A Review, Connor R. Vincent

LSU Master's Theses

Submarine pipelines and cables are vital for transmitting physical and digital resources across bodies of water, necessitating regular inspection to assess maintenance needs. The safety of subsea pipelines and cables is paramount for sustaining industries such as telecommunications, power transmission, water supply, waste management, and oil and gas. Incidents like those involving the Nord Stream subsea pipeline and the SEA-ME-WE 4 subsea communications cable exemplify the severe economic and environmental consequences of damage to these critical infrastructures. Existing inspection methods often fail to meet accuracy requirements, emphasizing the need for advancements in inspection technologies. This comprehensive survey covers the sensors …

Investigation Of Gas Dynamics In Water And Oil-Based Muds Using Das, Dts, And Dss Measurements, Temitayo S. Adeyemi

LSU Master's Theses

Reliable prediction of gas migration velocity, void fraction, and length of gas-affected region in water and oil-based muds is essential for effective planning, control, and optimization of drilling operations. However, there is a gap in our understanding of gas behavior and dynamics in water and oil-based muds. This is a consequence of the use of experimental systems that are not representative of field-scale conditions. This study seeks to bridge the gap via the well-scale deployment of distributed fiber-optic sensors for real-time monitoring of gas behavior and dynamics in water and oil-based mud. The aforementioned parameters were estimated in real-time using …

Multi-Scale Simulations Of Dynamic Protein Structures And Interactions, Yumeng Zhang

Doctoral Dissertations

Intrinsically disordered proteins (IDPs) are functional proteins that lack stable tertiary structures in the unbound state. They frequently remain dynamic even within specific complexes and assemblies. IDPs are major components of cellular regulatory networks and have been associated with cancers, diabetes, neurodegenerative diseases, and other human diseases. Computer simulations are essential for deriving a molecular description of the disordered protein ensembles and dynamic interactions for mechanistic understanding of IDPs in biology, diseases, and therapeutics. However, accurate simulation of the heterogeneous ensembles and dynamic interactions of IDPs is extremely challenging because of both the prohibitive computational cost and demanding force field …

An Efficient Privacy-Preserving Framework For Video Analytics, Tian Zhou

Doctoral Dissertations

With the proliferation of video content from surveillance cameras, social media, and live streaming services, the need for efficient video analytics has grown immensely. In recent years, machine learning based computer vision algorithms have shown great success in various video analytic tasks. Specifically, neural network models have dominated in visual tasks such as image and video classification, object recognition, object detection, and object tracking. However, compared with classic computer vision algorithms, machine learning based methods are usually much more compute-intensive. Powerful servers are required by many state-of-the-art machine learning models. With the development of cloud computing infrastructures, people are able …

Automated Identification And Mapping Of Interesting Mineral Spectra In Crism Images, Arun M. Saranathan

Doctoral Dissertations

The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) has proven to be an invaluable tool for the mineralogical analysis of the Martian surface. It has been crucial in identifying and mapping the spatial extents of various minerals. Primarily, the identification and mapping of these mineral spectral-shapes have been performed manually. Given the size of the CRISM image dataset, manual analysis of the full dataset would be arduous/infeasible. This dissertation attempts to address this issue by describing an (machine learning based) automated processing pipeline for CRISM data that can be used to identify and map the unique mineral signatures present in …

Data To Science With Ai And Human-In-The-Loop, Gustavo Perez Sarabia

Doctoral Dissertations

AI has the potential to accelerate scientific discovery by enabling scientists to analyze vast datasets more efficiently than traditional methods. For example, this thesis considers the detection of star clusters in high-resolution images of galaxies taken from space telescopes, as well as studying bird migration from RADAR images. In these applications, the goal is to make measurements to answer scientific questions, such as how the star formation rate is affected by mass, or how the phenology of bird migration is influenced by climate change. However, current computer vision systems are far from perfect for conducting these measurements directly. They may …

Policy Gradient Methods: Analysis, Misconceptions, And Improvements, Christopher P. Nota

Doctoral Dissertations

Policy gradient methods are a class of reinforcement learning algorithms that optimize a parametric policy by maximizing an objective function that directly measures the performance of the policy. Despite being used in many high-profile applications of reinforcement learning, the conventional use of policy gradient methods in practice deviates from existing theory. This thesis presents a comprehensive mathematical analysis of policy gradient methods, uncovering misconceptions and suggesting novel solutions to improve their performance. We first demonstrate that the update rule used by most policy gradient methods does not correspond to the gradient of any objective function due to the way the …

Multi-Slam Systems For Fault-Tolerant Simultaneous Localization And Mapping, Samer Nashed

Doctoral Dissertations

Mobile robots need accurate, high fidelity models of their operating environments in order to complete their tasks safely and efficiently. Generating these models is most often done via Simultaneous Localization and Mapping (SLAM), a paradigm where the robot alternatively estimates the most up-to-date model of the environment and its position relative to this model as it acquires new information from its sensors over time. Because robots operate in many different environments with different compute, memory, sensing, and form constraints, the nature and quality of information available to individual instances of different SLAM systems varies substantially. `One-size-fits-all' solutions are thus exceedingly …

Quantum Chaos, Integrability, And Hydrodynamics In Nonequilibrium Quantum Matter, Javier Lopez Piqueres

Doctoral Dissertations

It is well-known that the Hilbert space of a quantum many-body system grows exponentially with the number of particles in the system. Drive the system out of equilibrium so that the degrees of freedom are now dynamic and the result is an extremely complicated problem. With that comes a vast landscape of new physics, which we are just recently starting to explore. In this proposal, we study the dynam- ics of two paradigmatic classes of quantum many-body systems: quantum chaotic and integrable systems. We leverage certain tools commonly employed in equilibrium many-body physics, as well as others tailored to the …