Digital Commons Network^™

Utilizing Brain Computer Interfaces That Interact With A Virtual Keyboard, Skye Lilienthal

Honors Theses

A brain-computer interface (BCI) can allow someone to utilize electrical signals in their brain to complete tasks using a computer. BCIs can help people take advantage of technology to type without the need for a traditional keyboard setup. This paper used the OpenBCI Mark IV to test the effectiveness of non-invasive BCIs with dry electrodes within the OpenViBE P300 Speller. This paper shows how to use the P300 speller through a setup pipeline. Results indicate that electrode placement affects P300 accuracy and that areas related to visual processing improve accuracy, suggesting that P300 signals can be detected within OpenBCI Mark …

Structure-Property Relationships In Epoxy/Amine-Derived Polyester Thermosets, Jeffrey Aguinaga

Dissertations

This dissertation relates to ester-containing aromatic epoxy monomers and thermosets formed via reaction of those monomers with either ester-containing or non-ester-containing amine comonomers.  Due to the wide array of potential reactants (many bioderivable) to form ester-containing epoxy monomers that are closely related in structure, fundamental study of structure-property relationships was highly practical for this platform of materials.

Though properties of aromatic epoxy thermosets of relatively high-crosslink density and network strand rigidity vary widely with chemical composition and architecture, relatively low fracture toughness and impact resistance due to lack of ductility are typical. Integration of ester functionality and aliphatic spacers/connectors for …

Exploring The Effects Of Polymer-Graphene Interactions On Bulk Composite Properties Using Finite Element Analysis, Bryant Grove

Dissertations

As a filler in high performance materials, graphene significantly enhances the mechanical properties of polymer composites. Experimental characterization of graphene composite enhancements is limited by labor-intensive processes in both synthesizing composites for different purposes and in characterizing the interactions between graphene and polymer composites that lead to these enhancements. Computational approaches such as finite element analysis (FEA) are suitable alternatives that go beyond experimental analysis. This dissertation demonstrates the utility of FEA in analyzing polymer graphene composites with an emphasis on modeling the interaction between graphene fillers and the matrix within the interphase formed between them. The accessible design framework …

Sustainability Savvy: The Role Of Competence And Efficacy In Promoting Pro-Environmental Behavior, Lorenna Graham

Environmental Studies Honors Projects

Combatting environmental issues requires both large-scale and individual change. While many understand that personal pro-environmental behavior (PEB) is necessary, individuals do not always engage in this behavior (Hines, 1986, Goh, 2022). Thus, there is a need to investigate psychological factors which encourage PEB. Prior research suggests competence and outcome efficacy as likely PEB predictors (Bentler, 2023, Lavergne & Pelletier, 2015, Priolo, 2016), while cognitive dissonance has been shown to both encourage and discourage PEB (Bouwman, 2022, Dickerson, 1992, Ehrich & Irwin, 2005). Study 1 investigates the relationship between cognitive dissonance and PEB with competence and outcome efficacy as potential moderators. …

Sustainability Concepts In "Lab" Projects For Calculus I, Ii, And Iii (Poster), Joshua Holden

Faculty Publications - Mathematics

No abstract provided.

The Impact Of Community On Professional Identity In Computer Science Education, Ian A. Kollipara

School of Computing: Dissertations, Theses, and Student Research

This thesis explores the application of Communities of Practice (CoPs) in Computer Science Education. The work consists of two qualitative studies examining related but distinct populations: (1) K–12 CS teachers and (2) undergraduate CS students. The first study presents a retrospective analysis of conneCTION, an online CoP for K–12 CS educators, identifying strengths, weaknesses, and design considerations that inform future platform development. The second study investigates how participation in a CoP can mitigate negative and exclusionary stereotypes in CS. This study was conducted in an under-explored context: a small, private, religious, Midwestern university, and examines an existing community, the Programming …

Advancement In Electrochemical Generation-Collection: Snapshot Redox Cycling Voltammetry For Rapid Analysis At Chip-Based, Individually Addressable Microband Electrode Arrays, Blake Aleck Sterling

Graduate Theses and Dissertations

Snapshot redox cycling voltammetry (Snapshot RCV) is introduced as a rapid electrochemical technique that reconstructs the current-potential profile of a redox active species using a microband electrode array. By simultaneously biasing individual generator electrodes alternating in the array to different voltages across the analyte’s potential range while individually holding collector electrodes at a reversing potential, “spatial” voltammetry is achieved in as little as 1 s with the temporal speed of chronoamperometry, rapidly capturing the steady-state redox cycling (RC) profiles. During RC (a mode of generation-collection), the analyte is oxidized (or reduced) at generator electrodes and converted back at neighboring collector …

Explainability In Deep Learning For Density Regression, Dalton James Oxford

Graduate Theses and Dissertations

Classical statistical methods focus on explainability and inferential power. Machine learning and deep learning can handle non-linear, high-dimensional data better than traditional methods. In modeling, a clear understanding and interpretation are essential to decision-making. Recent work in quantile regression and extreme modeling has begun to use deep learning due to its performance on high-dimensional, non-linear data. Semi-Parametric Quantile Regression (SPQR) is a nonparametric spline-based approach to quantile regression that estimates the conditional PDF and CDF of the response. Semi-Parametric Quantile Regression for Extremes (SPQRx) is a recent extension of SPQR that provides two features: out-of-sample estimation and accurate extreme-tailed estimation. …

Strain Engineering Of Excitonic And Vibrational Properties In Two-Dimensional Transition Metal Dichalcogenides, Sneha Minesh Patel

Graduate Theses and Dissertations

Mechanical strain represents a robust and non-invasive method for tuning the electronic and vibrational properties of two-dimensional transition-metal dichalcogenides (TMDs). This work examines homogeneous biaxial strain as a symmetry-preserving control parameter that governs excitonic and interlayer dynamics in atomically thin TMDs. In monolayer MoSe2, biaxial tensile strain is intrinsically generated during high-temperature physical vapor deposition due to thermal expansion mismatch with amorphous substrates. Optical spectroscopy demonstrates substantial and tunable excitonic energy shifts exceeding 100 meV per percent strain. Polarization-resolved second harmonic generation confirms the retention of lattice symmetry under biaxial deformation. The investigation is further extended to bilayer MoS2, where …

Model Stormwater Standards 2026, Unh Stormwater Center

UNH Stormwater Center

The purpose of post-construction stormwater management standards is to provide reasonable guidance for the regulation of stormwater runoff to protect local natural resources from degradation and prevent adverse impacts to adjacent and downstream land, property, facilities, and infrastructure. These standards regulate discharges from stormwater and runoff from land development projects and other construction activities to control and minimize increases in stormwater runoff rates and volumes, soil erosion, stream channel erosion, and nonpoint source pollution associated with stormwater runoff.

Comparative Development Of Mof‑Based And Mof‑Free Agnp Functionalized Zno Nanorod–Cotton Fabric Composites For Photocatalytic Applications, Md Al Mamun

Master's Theses

Photocatalysis offers a cost‑effective and environmentally friendly strategy for degrading organic pollutants and addressing energy and environmental challenges. This study initially explored MOF‑based cotton‑fabric‑supported ZnO nanorod composites but found that the MOF component primarily acted as an adsorbent rather than an effective photocatalyst. Consequently, MOF‑free composites were developed by directly growing ZnO nanorods on cotton fabric and functionalizing them with silver nanoparticles. Photocatalytic testing revealed that AgNP‑modified ZnO nanorods, particularly at 10 mM AgNP, exhibited superior dye degradation efficiency, thereby demonstrating a scalable and effective photocatalytic platform.

Synthesis Of Novel 1,2,3-Triarylnaphthalenes Via Intermolecular Dehydro-Diels-Alder Reaction, Ethan C. Dailey

Honors Theses

The photo-dehydro-Diels–Alder (PDDA) reaction is a useful method for the construction of substituted naphthalene derivatives from acyclic precursors. While intramolecular variants of this transformation are well established, intermolecular PDDA reactions remain rare due to challenges associated with controlling reactivity under photochemical conditions. Previous studies suggest that electron-withdrawing substituents can promote intermolecular cycloaddition by increasing alkyne polarization and stabilizing reactive intermediates. In this work, the effect of enhanced electron-withdrawing character on intermolecular PDDA reactivity was investigated through the incorporation of a 2,3,5,6-tetrafluoropyridinyl substituent. Corresponding alkyne substrates were synthesized and subjected to photochemical conditions, resulting in the formation of 1,2,3-triarylnaphthalene products. The …

Calibrating Human Trust In The Age Of Generative Ai: An Examination Of Ethical And Social Challenges, Abigail M. Mondido

Honors Theses

Generative AI (GenAI), a set of AI technologies with the ability to generate original, human-like outputs, is beginning to transform the way that information is distributed, composed, published, obtained, analyzed, and consumed. GenAI has seen massive adoption by internet users, businesses, and organizations in recent years despite the persistence of major ethical concerns and social implications. In particular, existing research has identified multiple critical trust-related issues associated with AI in general, including widespread mistrust and distrust, overreliance on AI, and a lack of trustworthiness of AI. There remains a need for a broader understanding of these issues as they relate …

Evaluating The Effects Of Urbanization On Meiofauna Biodiversity In Chattanooga’S Lentic Ecosystems Through Gis Applications, Keyle M. Bryant

Honors Theses

Urbanization is a leading driver of biodiversity loss in freshwater ecosystems, yet its effects on meiofauna—microscopic invertebrates that serve as key bioindicators of ecosystem health—remain poorly understood in lentic environments. This study evaluated the effects of urbanization on meiofaunal biodiversity in ten lentic waterbodies across Hamilton County, Chattanooga, Tennessee, by integrating environmental DNA (eDNA) metabarcoding, in-situ abiotic measurements, and Geographic Information Systems (GIS)-based land use analysis. Water samples were collected between January and April 2023 and processed using 18S rRNA amplicon sequencing to assess biodiversity as richness (amplicon sequence variants or ASVs, phylogenetic diversity or PD, and community composition). Land …

An Exploration Of The Autorotating Pendulum Model, Vlad Nita

Theses, Dissertations and Culminating Projects

Autorotation is the spontaneous rotation of an object, usually caused by an external fluid flow. The study of autorotation has many physical applications, such as in the design of wind/water turbines. In this thesis, we explore a nonlinear pendulum ordinary differential equation (ODE) which is used to model rotating plates in a fluid and has the capacity to reveal autorotation. In the context of an ODE, autorotation emerges as a bifurcation past oscillations, when the initial velocity of the system crosses a particular threshold. In his classic study from 1983, Lugt [14] utilizes this equation to capture experimental autorotation. Copeland’s …

Conceptualizing A Responsive Design Pedagogy To Support Teachers' Responsiveness To Students' Mathematical Ideas Through Making, Denish Ogweno Akuom

Theses, Dissertations and Culminating Projects

This study develops Responsive Design Pedagogy (RDP), a conceptual and analytic model of teacher responsiveness in design-based environments, to account for how responsiveness emerges through interactions among students, tools, and tasks. Although responsiveness has been widely studied in mathematics education, limited attention has been given to responsiveness within mathematical design activity and to how teachers attend to the multiple modes through which students express their mathematical ideas. Addressing these gaps, this qualitative study examined one teacher’s enactment of responsiveness in a Learning-by-Design classroom where students designed and used 3D-printed mathematical tools. Data sources included classroom video, student design artifacts, teacher …

Data Driven Monitoring And Control Of Laser Powder Bed Fusion Process, Jose De Jesus Galarza

Theses and Dissertations

The Laser Powder Bed Fusion Process (LPBF) has been one of the main processes of additive manufacturing, enabling the manufacturing of complex geometries, customization, and lightweight parts. Modern LPBF processes have integrated monitoring systems that capture the light emissions per layer for quality assurance. However, standard defect detection algorithms have not yet achieved the high precision required due to the inherently variable nature of the signal, insufficient data for model training, and the confounding effects of the print.

The processes still have some challenges, such as characterizing the roughness from the build parameters alone, improving the pore detection using the …

I Am Still Learning, Too!: Pre-Service Teachers' Experiences Of Mathematics Anxiety In An Inquiry-Based Mathematics Education Course At Utrgv, Jeremiah James Adriano Dela Rosa

Theses and Dissertations

Mathematics anxiety is a prevalent issue in mathematics education that negatively impacts students’ learning, performance, and engagement in mathematics. Prior research suggests that mathematics anxiety is often shaped by students’ experiences and emotional responses within the classroom environment.

The purpose of this study is to explore how Pre-Service Teachers experience mathematics anxiety in an Inquiry-Based Mathematics Education (IBME) classroom. This study employed a qualitative research design supported by descriptive survey data collected through the Abbreviated Mathematics Anxiety Scale (AMAS), selected components of the Fennema-Sherman Mathematics Anxiety Scale (FSMAS), and semi-structured interviews. The survey instruments were used to provide descriptive background …

Do I Have To Know Someone? The Impact Of Factors Beyond The Playing Field That Affect Mlb Hall Of Fame Voting., Jackson Wollscheid

Economics Undergraduate Honors Theses

With the creation of WAR (Wins above Replacement), it has created an index to measure the player’s value using a variety of statistics relevant to that player’s position. The higher a player’s career WAR then the greater the impact that player had on the game during his career. However, players are not simply inducted into the Hall of Fame on this measure of value but on voting from members of the BBWAA (Baseball Writers’ Association of America). This research investigates external factors outside of standard playing statistics’ influence on Hall of Fame voting, including team affiliation, career length, and other …

F.L.A.I.R. -- A Flow-Level Autoencoder For Intrusion Recognition, Joseph P. Dumond

Electrical Engineering and Computer Science Undergraduate Honors Theses

Industrial Internet of Things (IIoT) networks underpin critical infrastructure worldwide, yet securing them remains an open challenge. Traditional intrusion detection systems require labeled attack data for training, a resource that is rarely available in real industrial deployments. They also fail against novel threats, a model trained on known attacks has no basis for detecting anything outside its training set. This thesis presents a Flow-Level Autoencoder for Intrusion Recognition, or FLAIR, a fully unsupervised deep learning system for network intrusion detection in IIoT environments. FLAIR is built on a Gated Recurrent Unit (GRU) autoencoder trained exclusively on normal network traffic. Rather …

From Mobilenet To Repvit: A Survey Of Edge-Optimized Computer Vision Architectures, Eli A. Bosch

Electrical Engineering and Computer Science Undergraduate Honors Theses

Edge-optimized computer vision is a constantly evolving field where the definition of efficiency has changed repeatedly. This thesis presents a literature survey of four recent Convolutional Neural Network (CNN) families, all analyzed through a consistent framework of accuracy, parameter count, and Multiply-Accumulate Operations (MACs), alongside a survey of five CNN and Vision Transformer (ViT) hybrid models to examine the direction of the field. It was found that accuracy follows a logarithmic curve with respect to parameter count, exhibiting diminishing returns as models scale. This suggests that architectural design contributes more to performance gains than parameter count alone. Theoretical efficiency metrics …

A Case Study On Using Large Language Models To Drive Convergence-Oriented Literature Discovery In Critical Infrastructure Security, Caden J. Williamson

Electrical Engineering and Computer Science Undergraduate Honors Theses

In the world of cybersecurity, the rapid development of artificial intelligence proposes a constant challenge for researchers to defend critical infrastructure. Attacks on critical infrastructure can be catastrophic, and emerging strategies of cyber-adversaries that implement leading AI models can expose vulnerabilities in critical infrastructure much faster than previous tools. To defend against this emerging threat, the Cybersecurity Research Working Group at the University of Arkansas is aiming to develop a cross-domain and cross-discipline center of excellence. To support this effort, the group is writing a literature review on the topics of AI and critical systems security. Literature review is an …

A Study Of Visualized Diagnostics In Early Stage Digital Twin Implementation Of An Industrial Control System, Michael R. Kinzel

All-Inclusive List of Electronic Theses and Dissertations

Industrial Control Systems (ICS) are used for process control in almost all industries. An ICS combines Operational Technologies (OT) with Information Technologies (IT) to allow human supervision of a process through surveillance of process variables and manipulation of controlling elements such as valves to maintain stable process conditions. ICSs have been in-service for several decades and may remain operational past their technological service life. Organizational personnel interact with the ICS through visual displays that both indicate the process variables and also the controlling elements. The Human Machine Interface (HMI) allows visibility of the process and the ability to manipulate controlling …

Prism: Priming Relationships In Syntax And Mathematics, Michelle J. Zhu

Honors Scholar Theses

The implementation of sheltered education programs has become increasingly prevalent in schools as new research in second language acquisition emerges. Yet despite this growing attention to ESL instructional practice, far less is known about the cognitive processes that underlie how bilingual students engage with academic content. This study investigates cross-domain structural priming between mathematical and linguistic processing in monolingual and bilingual individuals, focusing on how bilingual experience influences syntactic attachment preferences. Prior research suggests that mathematical and linguistic structures share underlying cognitive representations, and that exposure to structures in one domain can influence processing in another. Additionally, bilingualism has been …

You Can’T Spell Audit Without Ai: The Current Uses Of Artificial Intelligence In Audit, Jena Perkins

Senior Honors Theses

The accounting profession continuously adapts to the innovations provided by the broader context in which it exists. Artificial intelligence (AI) is a forerunner among tools used to enhance and optimize auditing services within the accounting profession. The realm of AI offers advancements to procedures used within an audit to detect misstatements. Based on the proprietary platforms developed by Big 4 accounting firms, AI is a key component in maintaining an advanced approach towards auditing.

Deep Learning For Predicting Impact Energy And Compression After Impact Strength Of Composite Materials Using C-Scan Images, K. T. Tan, Jason P. Mack, Faizan Mirza, Zhong-Hui Duan

University Research

Traditional assessment of post-impact performance in carbon fiber reinforced polymer (CFRP) composites often relies on simplified scalar metrics that fail to capture the complex spatial interactions driving failure. This study addresses this limitation by developing an automated, end-to-end deep learning framework that shifts from manual feature extraction to the direct interpretation of raw damage morphology from ultrasonic C-scans. Using a ResNet18-based convolutional neural network (CNN) trained on 1,428 augmented images, the model achieved coefficients of determination (R2) of 0.7948 ± 0.0847 for compression after impact (CAI) strength and 0.9436 ± 0.0098 for impact energy. Beyond prediction, this dual-purpose methodology serves …

An Analysis Of The Rapid Intensification Of Hurricane Milton, Ayden Rodriguez, Mark Sinclair

Publications

Hurricane Milton (October 2024) provides a compelling case study of a multiscale pathway to rapid intensification (RI), highlighting the alignment of synoptic preconditioning, favorable environmental conditions, and rapid inner-core structural evolution. The storm originated from the interaction of multiple tropical waves embedded within a low-level trough associated with the Central American Gyre, which enhanced low-level vorticity and moisture convergence prior to development. Upon entering the Gulf of Mexico, Milton encountered an environment characterized by anomalously warm sea surface temperatures, high ocean heat content, and weak vertical wind shear, enabling steady intensification and the onset of explosive RI that exceeded conventional …

Course Insight Portfolio: Math 1020 Business Calculus I, Ibrahim Khalilullah, M.G.M. Al Faruque, Jessica Ratovondranto, Leslie Spahr

Publications

This portfolio presents an overview of the student educational context, key course concepts, and some approaches to clarify student misconceptions associated with MATH 1020 (Business Calculus I). The portfolio includes a concept map illustrating the major topics of the course and an overview of common student misconceptions, and lesson plans designed to address those misconceptions through research informed instructional practices.

The concept map highlights the interconnected nature of topics such as functions, limits, continuity, differentiability, derivatives, optimization, graph interpretation, and applications of calculus. Particular attention is given to areas where students commonly experience difficulty, including distinguishing domain, codomain, and range; …

Public Health Responsible Ai Capability (Ph-Raic) Framework: A Conceptual Model For Integrating Ai Into Public Health Agencies, Arnob Zahid, Ravishankar Sharma, Rezwan Ahmed

All Works

Background: Artificial intelligence (AI) is transitioning from experimental pilots to core public health functions such as disease surveillance, resource planning, and analysis of social and structural determinants of health. Yet, health data collection and stewardship remain fragmented across the globe; some jurisdictions still rely on paper-based systems, while others operate noninteroperable digital systems that can exacerbate inequities. Treating health data as a global good therefore requires governance that enables innovation while protecting rights, safety, and trust. This study aims to develop a conceptual meso-level capability framework that translates responsible AI principles into organizational practices for public health agencies. Methods: We …

Population Structure And Connectivity Of Atlantic Nurse Sharks (Ginglymostoma Cirratum) In The Bahamas And Outlying Areas, Baylie A. Fadool

School of Natural Resources: Dissertations, Theses, and Student Research

Understanding animal ecosystem dynamics and behavior at the individual and population levels is essential for identifying life-history patterns and important areas for management and conservation. Marine fish species often face minimal geographic barriers to movement, but environmental (temperature, salinity, current) or intrinsic barriers (philopatry, site fidelity) can dictate gene flow. Atlantic nurse sharks (Ginglymostoma cirratum) are an International Union for Conservation of Nature (IUCN) listed ‘vulnerable’ species and present a unique opportunity to investigate patterns of population structure and connectivity in large-bodied sharks. They are benthic and display reproductive philopatry, with recent work suggesting they have the capacity …