Digital Commons Network^™

The Tones And Frequencies Of A Glockenspiel, Edward Czudak

Theses, Dissertations and Culminating Projects

In this thesis, I will analyze the tones and frequencies of a glockenspiel based on the results of Warburton’s 1954 article, “The Vibration Of Rectangular Plates,” [12]. I will be measuring and modeling the frequencies of a glockenspiel and connect them with the analytical and expected numerical solutions. The solutions will be based on the plate equation along with the boundary conditions of a rectangle free on all edges. I will look at the high modes of vibration for the bars and their corresponding overtones in the acoustic spectrum.

Inertial Dynamics Of Non-Spherical Particles In Fluid Flows, Takashi Yashiro

Theses, Dissertations and Culminating Projects

We investigate the dynamics of small inertial spherical and non-spherical particles in fluid flows. We consider the Maxey-Riley-Gatignol (MRG) equation, which models well the motion of spherical inertial particles in low Reynolds number flows. To study how shape affects the dynamics, we implement a corrective factor on the Stokes drag term in the MRG equation. This corrective factor, or shape factor, is based on the geometric properties of the particles. The Basset-Boussinesq history term in the MRG equation is often neglected to simplify analytical and computational studies involving the equation. We include this history term and implement a multi-step integration …

Urban Heat Mitigation In Newark, New Jersey Using Remote Sensing And Spatial Analysis, Ama Akowa Rhule

Theses, Dissertations and Culminating Projects

This study examines urban heat patterns in Newark, New Jersey, using remote sensing and spatial analytics to support targeted mitigation strategies. Land Surface Temperature (LST) was derived from a Landsat 8 Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) scene acquired on July 28, 2025, representing a summer snapshot of surface thermal conditions. While urban heat island effects are typically considered long-term climatic phenomena, this study uses a single-date observation to capture spatial variability in temperature across the city. Land cover variables, including tree canopy and impervious surface fractions, were obtained from the National Land Cover Database (NLCD), and demographic variables, including …

Friend Or Foe? The Benefits And Risks Of Llms In Cybersecurity, Niklas P. Dobler

Honors Theses

The rapid growth of Large Language Models (LLMs) and their continuous increase in capabilities have affected many professions and people. Due to advancements in areas such as coding and data analysis, they are now also being utilized in Cybersecurity. Recent research has examined their use in many different areas such vulnerability detection in code and analyzing network traffic. With this rapid growth, most organizations around the world are eager to advance faster than their competition, with limited considerations for the potential harm and risks these tools could bring. Some research has been conducted on malicious uses, but as the benefits …

Implementation Of A Droplet Interface Lipid Bilayer System For Electrical Characterization, Olivia J. Ziemer

Honors Theses

Lipid bilayers are the fundamental structural framework of cell membranes, providing cells with both protection from the environment and interaction with the surrounding environment. Experimental investigation of lipid bilayers and embedded protein channels often involves the formation of an artificial membrane within an electrical circuit. The focus of this project is to implement and verify the functionality of a lipid bilayer characterization technique known as the droplet interface bilayer (DIB), with emphasis on cost-effective system design. To achieve this, the amplifier and software from the ELEMENTS black lipid membrane (BLM) kit were repurposed to reduce the cost of implementing a …

Search For Slow-Moving Magnetic Monopoles With An Improved High-Energy Event Removal Algorithm, Reeshi N. Gihosal

Honors Theses

Fermilab’s NOvA (NuMI Off-axis 𝑣𝑒 Appearance) experiment focuses on understanding the behavior of neutrinos and how they affect the cosmos. A sub-focus of the NOvA experiment is the search for magnetic monopoles. These elusive particles have not yet been observed in nature, leaving their behavior to be mysterious. The Far Detector, located in Ash River, MN, is integral in the search for these particles. This project is on simulated magnetic monopoles with speeds thousandths the speed of light, with focus on the role of slicing algorithms in event reconstruction using the NOvA experiment’s reconstruction algorithm. Using sample data, analysis occurred …

Energetic Eutectics: An Experimental And Computational Investigation On Explosive Deep Eutectic Solvents, Connor J. Parker

All Theses

This study reports on the incorporation an extreme gradient boosting (XGBoost) machine learning strategy tailored to identifying potential high-energy, insensitive explosive deep eutectic solvents. 1,1-diamino-2,2-dinitroethylene (FOX-7) was investigated as the explosive of interest in our eutectic modeling. The resulting predictions highlighted a wide range of binary compositions demonstrating significant depression from the FOX-7 melting temperature with >70% probabilities of formation. Subsequent computational investigation into select mixtures provided underlying stabilization energies and optimized mixture geometries, which were then assessed experimentally with near simulant compounds oxalyldihydrazide and 1-methyl-3- nitroguanidine replacing FOX-7.

Experimental results with these chosen simulants did not demonstrate classical eutectic …

Func: Reducing The Impact Of Android Framework Evolution On Malware Detection, Hailong Yu, Tiantian Wang, Lwin Khin Shar, Hanmeng Li, David Lo

Research Collection School Of Computing and Information Systems

Android malware detection approaches commonly use APIs and permissions as features for classifying malware. However, since the release of the first Android operating system in 2008, the Android framework has undergone numerous version updates. The evolution of the Android framework over time has led to changes in APIs and permissions, including deprecations and replacements. These changes can result in inaccurate characterization of Android malware, thereby affecting performance of malware detectors. There is a lack of methods to mitigate the impact of Android framework evolution on malware detection. To fill this gap, we conduct a systematic study of the impact of …

Beyond The Interface: Human Perceptions Of Generative-Ai Chatbots As Conversational Partners, Browning W.E. Blair

All Theses

Generative AI (gen-AI) chatbots are becoming embedded in everyday communicative life, yet it remains unclear whether users perceive these systems as socially reciprocative conversational partners. Therefore, this study examines how young adults understand and interact with gen-AI chatbots, focusing on perceptions of conversational partnership, anthropomorphism, politeness, discomfort, and technical understanding. Guided by the CASA framework, Media Equation Theory, and the uncanny valley hypothesis, this study employed four semi-structured, online focus groups with 15 undergraduate students and recent college graduates in the United States. Findings indicate that participants did not broadly perceive gen-AI chatbots as conversational partners in the interpersonal sense. …

Design And Verification Of The Multi-Slit Solar Explorer Camera Field Programmable Gate Arrays, Jordan M. Johnson

All Graduate Reports and Creative Projects, Fall 2023 to Present

The Multi-Slit Solar Explorer, or MUSE, is a NASA mission that will take images of the Sun to study solar flares and the solar corona. The mission will provide insight into the mechanisms behind space weather. The mission consists of two cameras: the Spectrograph (SG), and the Context Imager (CI). The Utah State University Space Dynamics Laboratory is providing both cameras for the mission.

This report describes a part of the design and verification process for a central component on these cameras known as the Field Programmable Gate Arrays (FPGAs). These FPGAs are programmed to acquire, handle, and send images …

Autonomous Deficiency Detection And Vision-Language Summarization For Underground Infrastructure On Embedded Edge Systems, Johny Lopez

LSU New Orleans Theses and Dissertations

Aging underground infrastructure poses significant risks to public health and environmental safety, yet structural condition assessment remains bottlenecked by labor-intensive manual CCTV inspections. This thesis proposes a comprehensive algorithmic framework enabling fully autonomous, real-time deficiency detection, geometric assessment, and natural language reporting on resource- constrained edge computing platforms. Three core components address this challenge. First, RAPID-SCAN, a novel semantic segmentation architecture utilizing a Dynamic Feature Pyramid Network and Channel-Spatial Attention, achieves real-time, pixel-precise defect localization with dramatically reduced parameters. Second, an Edge-Optimized Vision-Language Model pipeline employing LoRA and 4-bit QLoRA quantization compresses Phi-3.5 for local deployment, en- abling autonomous technical …

Privacy Protection In Machine Learning: Methods For Structured And Unstructured Data, Karuna Bhaila

Graduate Theses and Dissertations

As machine learning models become increasingly integrated into data-driven decision-making, the protection of sensitive information throughout the model lifecycle is a paramount concern. As these models process and memorize sensitive, proprietary, or personal data, they risk leaking information through their outputs or internal states, especially in domains such as healthcare and finance. The protection of data in machine learning has thus been a crucial field of study. Within this paradigm, researchers have studied theoretical and application-oriented mechanisms for realizing privacy protections for various data formats. Nonetheless, privacy in machine learning still has many open problems, especially with the emergence of …

Efficient Deep Neural Networks For Autonomous Perception, Reeshad Khan

Graduate Theses and Dissertations

Autonomous perception systems must operate reliably under uncertainty arising from noisy observations, incomplete supervision, and hardware constraints. This dissertation investigates the design of efficient deep neural networks for autonomous perception through a unified perspective that treats uncertainty, efficiency, and sensing as interconnected challenges. The first contribution develops adaptive extensions of unbiased risk estimators, including eSURE and ePURE, enabling unsupervised training of deep neural networks for magnetic resonance image denoising under Gaussian and Poisson noise. However, these methods rely on known noise assumptions, which motivates the second contribution: a unified diffusion and Bayesian risk framework that estimates and adapts to unknown …

Sedimentary Provenance Of The Pliocene – Pleistocene Giant Foresets Formation, Offshore Taranaki Basin, Aotearoa New Zealand, Anurag Kulkarrni

Graduate Theses and Dissertations

Sediment input and dispersal in the Taranaki Basin, offshore New Zealand’s North Island, was influenced by a complex interplay of ocean currents and sea level fluctuations over the late Neogene. This period of time was recorded in the Pliocene-Pleistocene Giant Foresets Formation (GFF) that represents a rapid progradation of the western continental shelf into the basin. High sedimentation rates during this time were likely a major contributing factor to the emplacement of multiple, large-scale (up to ~3,500 km3) mass-transport deposits (MTD) that were caused by shelf and slope collapse within the GFF of similar scale to that of the well-studied …

Developmental Mathematics As A Potential Barrier To Degree Completion In Community Colleges, Cynthia Bernice Fletcher

Graduate Theses and Dissertations

Developmental mathematics is often seen as a barrier to student progression in community colleges, especially for students pursuing Associate of Science degrees requiring math coursework. This quantitative, ex post facto, non-experimental study examined how developmental mathematics factors predicted Associate of Science degree completion at a two-year community college in the West South-Central United States. Specifically, it assessed how academic performance in developmental mathematics, placement method, math pathway, and number of developmental math courses related to Associate of Science degree completion, as well as differences across student subgroups. Archival institutional data were used for first-time-in-college students across four cohorts: 2018, 2019, …

Genre Prediction Using Rnns And Llm-Enhanced Video Game Review Data, Gabriel Young

Graduate Theses and Dissertations

LLMs (Large Language Models) are powerful tools for engaging with textual data, carrying many advantages over classical NLP (Natural Language Processing) and ML (Machine Learning) approaches. However, a classical ML model can still be faster, more efficient to run, and accessible than an LLM. We seek to gain the benefits of LLM text comprehension and preserve them in a classical ML model, a hybrid approach. The LLM operates on text to surface relevant information and associations in our problem space, then the ML model trains on the LLM output. The model may learn from the LLM and provide a more …

From Phenology To Yield Zones: Functional Clustering Of Satellite Time Series For Crop Growth Monitoring, Ikram Morso

Graduate Theses and Dissertations

Remote sensing and land surface phenology provide a strong basis for characterizing crop development, but their usefulness for within-field yield-zone delineation depends on whether crop development is analyzed as a phenological trajectory and whether the resulting zones are evaluated with spatially defensible statistics. These questions are especially relevant in soybean production because soybean is one of the most important row crops in the United States and the country’s dominant oilseed crop. This relevance is strong in Arkansas, where soybean is a major component of agricultural production. In soybean production, within-field yield variability reflects the combined influence of soil properties, stand …

Structural Relaxation In Glass-Forming Liquids At Extreme Pressure: Photon-Correlation Spectroscopy And Constrained Thermodynamic Surface Modeling, Kevin Wayne Lyon

Graduate Theses and Dissertations

Structural relaxation in glass-forming liquids is strongly dependent on both temperature and pressure, yet direct measurement of structural α-relaxation under multi-gigapascal compression has remained experimentally challenging. This work extends depolarized photon correlation spectroscopy (DPCS) to pressures approaching 5 GPa in a diamond anvil cell, representing the highest-pressure implementation of this technique and enabling direct measurement of the structural α-relaxation in a pure liquid at extreme compression. This capability provides access to dynamical regimes previously unexplored by photon correlation spectroscopy and establishes a platform for probing glassy dynamics at high pressure. To describe these measurements, a constrained relaxation-time surface framework is …

From Data Digitization To Personalized Care: Deep Learning And Decision Analytics In Healthcare Systems, Ahla Ko

Graduate Theses and Dissertations

This dissertation traces a progression from foundational data infrastructure to individualized clinical decision-making, developing and evaluating three computational frameworks that advance healthcare efficiency and personalization through deep learning and decision analytics. The first study presents an end-to-end pipeline for automated recognition of handwritten medical forms, addressing persistent challenges in health data digitization. Integrating a YOLO-based field detection model, a Convolutional Recurrent Neural Network (CRNN) for text transcription, and a confidence-based human-in-the-loop quality assurance framework, the system achieved 99.75\% Exact Match Accuracy and a 0.13\% Character Error Rate on medical forms collected from a tuberculosis research project in Moldova. A GPU-accelerated …

Solid Embedded Telemetry, Pranav Balasubramanian Natarajan

Graduate Theses and Dissertations

This thesis explores the integration of the Solid decentralized data framework within embedded and legacy energy control systems to enable secure, access-controlled, and interoperable data exchange. Two implementations were developed to evaluate Solid’s practical applicability: an ESP32 client implementing Solid-OIDC authentication and telemetry publication to a Solid Pod, and a Modbus-to-Solid bridge translating Modbus RTU communications into RDF-based data for bidirectional control. Experimental evaluation highlighted the effects of task scheduling and blocking operations on the ESP32, and polling-based communication latency within the Modbus bridge. These findings reveal the architectural and computational trade-offs involved in extending Solid to constrained or protocol-bound …

A Spatial Analysis Of Socioeconomic Characteristics And Community Vulnerability To Natural Hazards In Arkansas, Emma Steuber, Brad Peter

Geosciences Undergraduate Honors Theses

Natural hazards have become more frequent in recent years, and because of their destructive impacts, it is crucial to locate regions that are most affected historically by hazardous events and identify what socioeconomic characteristics co-occur spatially. While many studies have analyzed this relationship at national and state scales, few have focused specifically on Arkansas, and even fewer have incorporated multiple socioeconomic characteristics. Comparing the spatial distribution of community characteristics in Arkansas with zones of common natural hazards is essential for identifying who is most at risk. This study utilizes Geographic Information Science (GISci) to examine and map the spatial relationship …

Atmospheric Remote Sensing Using X-Band Radar In The Marine Atmospheric Surface Layer, Daniel P. Greenway

Electronic Theses and Dissertations

Atmospheric remote sensors have always offered promising technological advancements for measuring atmospheric properties over large spatial areas at high spatiotemporal resolution – a feat not currently possible with present atmospheric measurement technologies. However, remote sensors do not measure these atmospheric properties directly; they rely on robust calibrations or conversions, complex mathematical inversion methods, and/or machine learning to retrieve these properties. These inverse methods rely on the selection of an objective function, a machine learning technique, and an accurate parameterization for atmospheric property estimation. By leveraging inverse methods to improve the characterization of properties measured by remote sensors, this work enables …

Numerical And Harmonic Analysis Of Simplex Number Parity, Hunter Dm Hannula

All NMU Master's Theses

The primary object of this thesis is the study of periodicity in the parity of simplex numbers by number-theoretic and harmonic methods. The regular d-simplex numbers are introduced geometrically, arithmetically, and combinatorially. We demonstrate that all sequences indexing even d-simplex numbers are defined by finitely many congruences in a single modulus, and are thus quasiperiodic. We therefore show that these "even index-sequences" are  particular elements in an affine space of functions, providing a natural decomposition result. We then introduce the discrete Fourier transform to construct the periodic parts of each index sequence, enabling the development of explicit forms for the …

2026 Workshop On Bridging The Gaps: Tackling Microplastics And Nanoplastics Challenges In Coastal Ecosystems, Shenghua Wu, Kaushik Venkiteshwaran, Melike Dizbay-Onat, Alexandra Stenson, Jinhui Wang, Tina Miller-Way, Ebenezer Nyadjro, Bhuvnesh Bharti, John Weinstein, Yi Bao, Shihui Shen, Valerie Longa, Shenghua Zha, John Cleary, Marty Lind

Workshops

This report presents the findings from the 2026 Workshop on Tackling Microplastics and Nanoplastics (MNPs) in Coastal Ecosystems, which took place in Mobile, Alabama. More than 140 experts from universities, government, industry, and community organizations gathered to address the increasing issue of MNPs in coastal regions.

Uncertainty In Neural Networks: An Interval Approach, Yahriel Isaac Guel

Open Access Theses & Dissertations

Neural networks produce predictions but not reliable measures of how much to trust them. A clinician handed an output such as "97% chance malignant" has no way to tell whether that 97% reflects the model's actual reliability on inputs like this one, or whether the same number would have appeared on an image the model has no business classifying. The standard approaches to uncertainty quantification - Bayesian neural networks, deep ensembles, and Monte Carlo dropout - are useful. However, sometimes the uncertainty we need to handle only comes as lower and upper bounds. This raises a natural question: what if …

Active And Passive Seismic Studies Across Glacial And Geothermal Environments, Lucia Fernanda Gonzalez

Open Access Theses & Dissertations

The collection of passive and active-source seismic data remains central to the detailed investigation and understanding of complex Earth processes across diverse and often inaccessible environments. Of equal importance is the selection of methodologies that must be tailored to the geological setting and dataset resolution to accurately depict the subsurface. In this dissertation, we apply a range of classic and/or "newly" developed algorithms, unique to each chapter, on seismic datasets from distinct glaciological and geothermal settings to evaluate their performance and enhance subsurface interpretation. In Chapter 1, we analyze active-source seismic data from Lemon Creek Glacier in Juneau, Alaska, using …

Robust Logistic Regression With Elastic Net For Contaminated High-Dimensional Data, Chitra Bahadur Karki

Open Access Theses & Dissertations

High-dimensional logistic regression is particularly vulnerable to outliers, which can distort estimation, weaken variable selection, and harm prediction accuracy. This dissertation introduces RobENetLog, a robust elastic net logistic regression method that jointly selects informative variables and reliable observations by extending ideas from least trimmed squares regression to the classification setting. The proposed approach combines adaptive outlier detection with trimmed penalized estimation so that it can address contamination in both predictors and responses across a wide range of dimensional settings. Simulation studies show that RobENetLog consistently improves predictive performance and robustness in the presence of outliers, while remaining competitive with standard …

Mississippi Early Childhood Math Resource Guide: Supporting Mathematical Development From Birth Through Age Eight, Melissa Luckett, Systems Change Lab, Mississippi State University, Social Science Research Center, Mississippi State University

Books

The Mississippi Early Childhood Math Resource Guide is a comprehensive, research-informed digital publication designed to support the development of foundational mathematical skills in children from birth through age eight. Developed by the Systems Change Lab at Mississippi State University's Social Science Research Center, the guide translates evidence-based early mathematics concepts into practical, accessible strategies for educators, families, and caregivers. 

Organized by developmental stages, the guide integrates learning domains, age-appropriate math skills, and everyday instructional practices to promote the use of "math talk" and embedded learning opportunities across settings. It incorporates activities, instructional strategies, and resources aligned to support both formal …

Improving Online Political Discussion With Automated Bot Intervention, Bethanie E. Hackett

Departmental Honors & Graduate Capstone Projects

The quality of political discussions occurring on online platforms or social media sites has been deemed quite poor. To address this issue, I investigated whether a Large Language Model (LLM) can be used to promote civil and productive political discussions by identifying and responding to unproductive dialogue. I fine-tuned an existing LLM to detect elements of problematic dialogue, namely misinformation, misrepresentation of sources, logical fallacies, bias, and toxic language, and then respond in a corrective yet non-confrontational manner. The resulting model is referred to as FroBot and was evaluated through an experiment in which a human participant was placed in …

Using Ai For Data Loss Prevention, Camden A. Wright

Theses/Capstones/Creative Projects

Data Loss Prevention (DLP) systems play a critical role in protecting modern systems that handle sensitive information from both accidental and malicious exposure. Traditional DLP approaches often rely on static rules and methods that can struggle to adapt to complex and evolving data patterns. This paper presents a hybrid DPL system that integrates machine learning-based message classification, rule based policy enforcement, and context-aware access control to improve both detection accuracy and decision reliability. In addition, the system introduces a second stage access control model that evaluates user context, including role of clearance level and job title to determine whether access …