Digital Commons Network^™

Quasipseudometric Value Functions With Dense Rewards, Khadichabonu Valieva

Honors Theses

Goal-conditioned reinforcement learning (GCRL) serves as an extension of reinforce- ment learning (RL) that focuses on goals that can be adjusted, making it useful for many applications, especially in complex robotics tasks. Recent research has established that the optimal value function of GCRL, denoted as Q∗(s, a, g), has a quasipseudometric structure. This finding has led to the development of targeted neural architectures that respect such a structure. However, prior analyses have predominantly focused on sparse reward settings, which are known to increase challenges related to sample complexity. In this work, I with the guidance of my advisor show that …

Public Building Accessibility: An Expanded Access Analysis Metric, Carolyn Wilkinson

Honors Theses

Quality accessibility features significantly impact the user experience in public service facilities; however, much of the research in this area tends to focus on code compliance, limiting the ability to analyze accessibility quality in depth. Additionally, studies often concentrate on common mobility challenges, leaving less focus on other disabilities, such as cognitive and visual impairments. As a public institution, the University of Southern Mississippi depends on students' abilities to access its services, directly linking the institution’s value to the quality of its accessibility. To address this, we developed a set of survey questions to evaluate the accessibility features of campus …

The Effect Of A Peptide Targeting Ligand On Transfection Efficiency Of Polymeric Nanoparticles To Dendritic Cells, Anthony Radka

Honors Theses

Autoimmune diseases affect approximately 5-8% of the global population, leading to chronic symptoms, long-term treatment, and reduced quality of life. Current therapies primarily rely on lifelong administration of immunosuppressants, which are associated with severe side effects and heightened susceptibility to infections. This has spurred interest in cellular therapies that manipulate dendritic cells (DCs) effectively and can selectively treat these diseases. This work aims to improve the efficacy of dendritic cell-based therapies using cationic polymers that can electrostatically complex with nucleic acids, forming nanoparticles referred to as polyplexes, that can deliver therapeutic nucleic acid cargo. These particles are a favorable alternative …

Mathematical Melodies: The Exploration Of Music Using Fourier Signal Analysis, Courtney Francois

Honors Theses

Upon initial inspection, mathematics and music appear to be distinct disciplines lacking any connections to one another. However, many complex intersections lie beneath the surface. This paper seeks to explore these connections through the analysis of the Fourier series and the Fourier transformation of musical sound signals. Orthogonal functions of various frequencies are used to approximate and recover sound signals. Following the examination of the basis of Fourier signal analysis, MATLAB is utilized to visualize the connectedness of mathematics and music through sound signals from varied musical instruments and by performing Fourier signal analysis to the sound signals. Then, the …

Privacy-Aware Ai-Based Agricultural Monitoring Using Internet Of Drones, Md Benozir Hossain

Honors Theses

Artificial Intelligence (AI) has become a vital tool for agricultural farming. AI-based image processing models utilizing different machine learning (ML) algorithms and deep learning (DL) offer advanced functionalities in disease detection, yield estimation, land use, etc. This thesis examines AI-driven techniques utilizing Convolutional Neural Networks (CNN) with the addition of Federated Learning (FL) to analyze satellite and drone images for agricultural insights, especially in detecting Cotton diseases. The AI models improve agricultural farming in many ways, such as using data to make critical decisions, reducing labor costs, pest infestations, etc. Moreover, these models allow farmers to minimize yield losses by …

Development And Characterization Of A Pro-Angiogenic Peptide Amphiphile For Deep Dermal Burn Healing Via Spray Delivery, Loria Dimartino

Honors Theses

Severe burns and other dermatological injuries are frequently accompanied by a range of comorbidities and aesthetic challenges that patients must contend with. The complexity of burn care is exacerbated by the lack of a standardized surgical protocol, as treatment strategies are tailored to individual patient factors, including overall health status, wound size and location, as well as the expertise and resources available to the surgical team. Most commonly, deep dermal burns are treated through grafting, which effectively covers the injury site, but requires the creation of a second wound on the body of approximately the same size. This produces a …

Tailoring The Morphology Of Block Copolymers Via Solvent-Vapor Annealing, Bayleigh Madelin Loving

Honors Theses

Triblock polystyrene-polyisobutylene-polystyrene (PS-PIB-PS) copolymers have widespread applications from thermoplastic elastomers to protective coatings for ballistic applications. The incompatibility between the soft PIB and hard PS phases leads to phase separation and subsequent formation of morphological domains like lamellae and cylinders. The structures are stabilized by physical crosslinks, which can greatly improve the toughness of the triblock systems by preventing chain pullout during tensile deformation. We tailored the morphologies (achieving different morphologies with the same block copolymer) by changing the annealing conditions of the block copolymers. Solvent vapor annealing was used to selectively activate the mobility of a particular block, causing …

Globally Adaptive Exponential Integrators For Stiff Systems Of Odes, Anzhelika Vasilyeva

Honors Theses

This thesis introduces a novel method for solving systems of Ordinary Differential Equations (ODEs) resulting from the spatial discretization of Partial Differential Equations (PDEs). The proposed approach builds upon an existing technique that employs Krylov projection, which requires evaluating a matrix function at each timestep. The innovation of the new method lies in its reuse strategy, which shifts the perspective from direct matrix function evaluation to polynomial interpolation. Numerical experiments conducted on constant and variable coefficient heat equations, with both smooth and discontinuous initial data, demonstrate the computational time advantage of the new approach. The results indicate that this method …

Letters From The Periphery: L.E. Faulkner’S Crusade Against Communism, Cameron Melendez

Honors Theses

This thesis explores L.E. Faulkner’s political activism. Faulkner, a railroad executive from Hattiesburg, Mississippi, launched a number of anti-communist crusades throughout the 1940s and 1950s. Utilizing his personal correspondence, political articles, and newspapers, this thesis argues that anti-communist networks were influential and powerful tools used by Faulkner and other local activists to shape the national discourse around anti-communism. Faulkner created an interconnected web of anti-communists that linked protestant fundamentalism, capitalist advocacy, racial politics, and Americanism. His 1943–1944 civic education campaigns with Rotary International and Kiwanis International and his 1954 opposition to the World Council of Churches serve as case studies …

Measuring Agricultural Adaptation Using Remote Sensing: A Study Of Pigeonpea In Malawi, Maria Gorret Nabuwembo

Graduate Theses and Dissertations

Drought, heatwaves, and flooding cause tremendous damage to agricultural production in Malawi, and the continuous production of maize has led to widespread soil degradation. Additionally, climate change is transforming the environment at a scale beyond historical records, posing significant challenges to social, political, and economic systems. To combat these issues, agricultural innovations have been implemented, such as the installation of irrigation systems and development of heat/drought resilient crop varieties. Pigeonpea is one of the prominent drought-tolerant and temperature resilient crops grown as a diversification strategy since it allows farmers to adapt to changes while maintaining subsistence needs. This research investigates …

From Seasonality To Causality: Understanding Urban Water Usage Using Statistical And Machine Learning Models, Kelsey Hawkins

Electrical Engineering and Computer Science (MS) Theses

This study examines the relationship between climate conditions and residential water usage, focusing on how seasonal and environmental changes influence water consumption. Utilizing data from over 100,000 households across three micro-climate zones for over a five-year period, we apply statistical analysis and machine learning techniques to assess the impact of temperature, precipitation, evapotranspiration, and location on water usage. By integrating climate and billing data, this research provides a data-driven approach on water usage behaviors in Irvine, CA, in collaboration with Irvine Ranch Water District (IRWD).

Our analysis utilizes time series modeling, including a Seasonal Autoregressive Integrated Moving Average (SARIMA) and …

Implementation Of Residual Tandem Neural Networks For Photonic Inverse Design, Ponthea A. Zahraii

Electrical Engineering and Computer Science (MS) Theses

Deep-learning approaches can greatly benefit the modeling and design of nanophotonic and optical structures. Traditional full-wave simulations are time and resource-intensive, which can act as a bottleneck in photonic design. On the other hand, deep-learning approaches for designing the response of nanophotonic geometries can be computationally inexpensive and produce accurate and efficient results. In this project, we specifically investigate the case of optical forces near meta-structures. We propose using an inverse design approach with residual blocks to account for the deep nature of this architecture and inherently address the non-uniqueness problem. A tandem approach, which consists of two interconnected models, …

Standardizing Wind Energy Project Bid Process, Phillip Ilarion Pletnikkoff

Student Projects for Graduate Degrees

The SWEPP initiative addressed critical inefficiencies in STG Inc.'s wind energy project bidding. Previously, fragmented practices led to unpredictable outcomes and ineffective knowledge utilization. The project developed two key deliverables through stakeholder analysis: a Comprehensive Bidding Guide and a Lessons-Learned Integration System. The Bidding Guide establishes standardized templates and processes while maintaining flexibility for customization. The Lessons Learned System captures and applies insights from past projects, transforming individual experience into organizational knowledge. Despite initial resistance from experienced professionals, an inclusive approach incorporating their expertise helped overcome implementation challenges—the modular design balanced standardization with flexibility to address diverse requirements. Early results …

Application Of Project Management To Develop A Multifunctional Wheelchair Mount In The Non-Profit Sector, Ruger Johnsen

Student Projects for Graduate Degrees

There are currently few commercially available multi-function accessory mounts for electric wheelchairs that are practical for high-level quadriplegics. Consequently, an individual user must design and create one for themselves, an undertaking that requires significant resources in the form of expertise, time, and money. Wes Price, a quadriplegic, has developed a concept mount for operating a hunting rifle. This project optimized the proof-of-concept by building a prototype and completing a design that can be offered to the public. The primary tasks and deliverables of this project include: 1) Research and develop improvements to the proof-of-concept and prototype 2) Fabricate prototypes 3) …

Survey On Application Of Large Language Models In Network Attack And Defense, Prisha Purohit

Honors Theses

The emergence of Large Language Models (LLMs) has significantly transformed the technological and cybersecurity landscape, introducing both unprecedented opportunities and formidable challenges. With the public release of ChatGPT in 2022, LLMs have gained global prominence, redefining natural language processing capabilities and enabling advancements across various fields. In cybersecurity, these models represent a dual-use technology: while they offer powerful tools for threat detection, automated analysis, and security training, they also pose risks when leveraged by malicious actors for phishing, social engineering, and the creation of evasive malware. This thesis presents a comprehensive literature review exploring the dual roles of LLMs in …

Bridging The Nature Gap: Understanding Barriers And Promoting Outdoor Engagement Among African Americans In Chattanooga, Kennie Almonor

Honors Theses

This paper outlines my process of writing a physical guidebook for outdoor engagement in Chattanooga. It explores the historical context of Black exclusion from outdoor spaces and examines the health disparities that disproportionately affect Black communities. The physical connection between outdoor activity and overall well-being will also be explained. Additionally, this paper details my methodology for conducting focus groups to better understand barriers to outdoor engagement and how participant insights could inform the guidebook’s development. This paper also outlines my research on best practices for structuring an effective guide, writing process, challenges faced, and considerations for extending this project in …

Synthesis Of Single Chain Polymer Nanoparticle Networks By Reinitiating Raft Polymerization, Dallas Donovan

Honors Theses

Hydrogel materials, which are polymer networks comprised mostly of water, hold significant promise for biomedical applications due to their compatibility with biological systems. Conventional hydrogel materials are often brittle and weak, but most applications in biomedical systems require materials to be strong and tough. The topology of a polymer network dictates its mechanical properties. An important strategy for designing tougher hydrogels is the release of stored length, such as from the unfolding of polyprotein cross-linkers. Inspired by the success of the strategy, we report progress towards a fully synthetic design using single chain nanoparticles (SCNPs) into a hydrogel. SCNPs, which …

Arthroscopy And The Future Of Surgery: Personal And Public Health Benefits, Preston T. Koski

Honors Thesis

Arthroscopy focuses on operating on the body using probes and working through keyhole incisions on the skin. This rapidly evolving field has seen many innovations in its technology, aided by advances in optical and surgical capabilities. Moreover, it presents many advantages over traditional surgery that directly impact the patient. Shorter recovery time and lessened scarring, reduced postoperative pain and opioid dependence, and less risk of infection are key benefits over open surgery. These benefits can also be applied to areas of public health. Minimizing the burden on hospital resources, reducing the environmental impact of surgery, and improving cost-effectiveness in healthcare …

Sonochemically Synthesized Zno Nanowires (Nws)-Based Sensor For Non-Invasive Glucose Detection In Sweat, G. M. Mehedi Hossain, Ahmed Hasnain Jalal, Hasina Huq, Nazmul Islam, Karen Lozano, Nezih Pala, Fahmida Alam

Electrical and Computer Engineering Faculty Publications

Glucose is a crucial metabolic marker, providing critical insights into energy regulation and insulin sensitivity, making its monitoring essential for managing diabetes and overall metabolic health. In this context, flexible biosensors have gained considerable attention for their potential to enable real-time and non-invasive glucose monitoring. One promising advancement in this domain is using Zinc-Oxide (ZnO) nanostructures through sonochemical synthesis. ZnO has a wide bandgap of ∼3.37 eV and a large binding energy of 60 meV. This research focuses on ZnO-Nanowires' growth for the first time on a flexible polymer substrate. The average length and diameter of the nanowires are 2.5µm …

Improving Research Software Engineering In Mathematics, Abram Miller

Honors Theses

Research Software Engineering is critical to modern mathematical research, enabling the creation, maintenance, and dissemination of computational tools that bridge theory and practice. However, the field faces systemic challenges, including insufficient funding, lack of institutional recognition, and gaps in training and infrastructure. This thesis investigates these challenges through two approaches: (1) a comparative survey study focused on mathematicians and (2) hands-on contributions to an open-source research software project.

The Improving Research Software Engineering in Mathematics survey, conducted from September 2024 to January 2025, adapts the survey framework developed by Carver et al. in A survey of the state of the …

Reconfigurable Python Autopilot Software For Rc Aircraft, Kate Doiron

Honors Theses

No abstract provided.

Contrastive Representation Learning For Highly Imbalanced Multivariate Time Series With Extreme Instance Strategy, Onur Vural

All Graduate Theses and Dissertations, Fall 2023 to Present

Time series data refers to a sequence of data points collected or recorded at regular time intervals. In many fields including space weather, healthcare, and finance, predicting events from such data is crucial because these predictions can help protect infrastructures, improve healthcare outcomes, and forecast financial trends. However, one challenge in working with time series data is the presence of rare events, which are often underrepresented in the data. This imbalance makes it difficult for traditional prediction methods to provide accurate results, as they tend to focus more on the more frequent events and overlook the rare ones. To tackle …

Investigating Stability Of Cone-Derived Hypersonic Waverider Vehicles Via Design Space Exploration, Adam S. Weaver

All Graduate Theses and Dissertations, Fall 2023 to Present

It may come as no surprise that man-made objects flying at 5, 10, or even 25 the speed of sound (termed hypersonic) are difficult to design, inefficient in flight, and expensive to deploy. Most hypersonic vehicles are effectuated in ballistics, which simplify aerodynamic considerations owing to their fixed trajectory. However, maneuverable hypersonic vehicles can revolutionize commercial flight, national defense, and space travel. One candidate for such missions are waverider vehicles. Waverider vehicles cruise on a cushion of air generated by its own shock wave, essentially enjoying extra lift without any extra drag penalties (which are usually inherent to extra …

“I Can Run At Night!”: Using Augmented Reality To Support Nighttime Guided Running For Low-Vision Runners, Yuki Abe, Keisuke Matsushima, Kotaro Hara, Daisuke Sakamoto, Tetsuo Ono

Research Collection School Of Computing and Information Systems

Dark environment challenges low-vision (LV) individuals to engage in running by following sighted guide—a Caller-style guided running—due to insufficient illumination, because it prevents them from using their residual vision to follow the guide and be aware about their environment. We design, develop, and evaluate RunSight, an augmented reality (AR)-based assistive tool to support LV individuals to run at night. RunSight combines see-through HMD and image processing to enhance one’s visual awareness of the surrounding environment (e.g., potential hazard) and visualize the guide’s position with AR-based visualization. To demonstrate RunSight’s efficacy, we conducted a user study with 8 LV runners. The …

Assessment Of Energy Efficiency Measures Recommended For Industrial Facilities: Environmental, Economic, And Life Cycle Perspectives, Dariush Jafari

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

This study assesses the economic, environmental, and life cycle impacts of more than 800 industrial Energy Efficiency Measures (EEMs) identified in manufacturing facilities across Nebraska. These EEMs are notable for their rapid implementation and minimal disruption to the facility’s building structure or core processes.

The research evaluates the financial viability of EEMs by analyzing utility savings, implementation costs, and payback periods. It also examines their cost-effectiveness in reducing greenhouse gas (GHG) emissions, including calculations of net cost and cost of mitigated CO₂-eq.

Key findings indicate that adding insulation to hot pipes and buildings, replacing personal fans with High-Volume, Low-Speed (HVLS) …

Optimization-Based Distributed Controller For Multi-Agents System In Microgrid Secondary Control, Fahad S. Alshammari, Ayman El-Refaie, Saleh Alyahya, Sheroz Khan

Electrical and Computer Engineering Faculty Research and Publications

Micro-grids function to connect to power system power produced by the renewable energy resources. In islanded micro-grids, grid-forming units collaborate to maintain the micro-grids voltage and frequency by utilizing droop control technique that includes primary, secondary and tertiary levels. Secondary control intervenes to improve power sharing and restore voltage and frequency to their nominal levels. However, the conventional droop control applied to a grid with mismatched line parameters experiences a trade-off between reactive power sharing and voltage regulations. This paper applies real-time trajectory tracking convex optimization to ensure by communicating power sharing between units in a consensus topology. The optimization …

Understanding The Breadth And Impact Of The Ias [President’S Message], Ayman El-Refaie

Electrical and Computer Engineering Faculty Research and Publications

No abstract provided.

Tennessee Magnet Schools: Examining The Relationship Between Magnet School Designation And Student Achievement In Secondary Public Schools, Alex Turner

Electronic Theses and Dissertations

The purpose of this quantitative study was to investigate the relationship between magnet school designation and student achievement in Tennessee secondary public schools. Three years (2021-2023) of student achievement data from the Tennessee Department of Education was used to analyze student performance in 24 magnet and 287 traditional non-magnet schools. Schools were included in the study if they operated continuously throughout the study period and were categorized as either a public magnet school or a traditional non-magnet school. Excluded from the study were virtual, charter, alternative schools, and early colleges.

Four research questions were crafted to guide this study. Student …

Mathematics Outcomes For Career And Technical Students Enrolled At A Community College In East Tennessee, Malissa Trent

Electronic Theses and Dissertations

The primary purpose of this study was to compare the success of college-ready and academically underprepared community college students in a college-level math course designed for career and technical programs. A non-experimental two-group comparative design with existing data examined differences in academic metrics based on participation in a corequisite learning support mathematics course. The study used a sample size of 1070 students from a community college in East Tennessee who were enrolled in a college-level Trigonometric Applications course between the fall of 2015 and the spring of 2024. Due to a lack of prior academic preparation, 500 of these students …

The Food Truck: A Multi-Product Newsvendor With Trans-Shipment Cost, Samuel Ajibola

Electronic Theses and Dissertations

The Newsvendor Problem is a key model in supply chain management that focuses on determining the optimal order quantity to minimize costs under uncertain demand. This thesis introduces the Food Truck Problem, an extension of the Newsvendor model that incorporates nonlinear transshipment costs for inventory transportation. In this context, a Food Truck must determine the optimal stock levels for multiple products while minimizing costs related to stock shortages, excess inventory, and transportation. Unlike traditional Newsvendor models, our approach explicitly considers a quadratic transshipment cost, which necessitates the use of Lagrangian duality and Karush-Kuhn-Tucker (KKT) conditions for analysis. Moreover, we apply …