Digital Commons Network^™

Architecture As A Camera: Utilizing Photographic Principles To Tell Stories Through Design, Ryan Gabriel Scherf

Architecture Theses

This thesis examines the relationship between memory, photography, and architecture as a framework for spatial design, framing memory as a fragmented phenomenon contingent upon light and time. Drawing on the theoretical work of Goffi, Barthes, and Bordeleau, it positions architecture as a temporal montage in which meaning emerges through layered absences, material “puncta,” and the interpretive gaps between fragments. Situated at the Botallack Mines in England, the project explores the intersection of photographic logic and industrial ruin by treating the site’s extractive history as a series of active fragments. Through compressed volumes and curated views, it translates photographic principles into …

Birds, Bees, + Butterflies: Restoring Suburban Wildlife Homes And Habitats In Bismarck, Nd, Elena Joubert

Landscape Architecture Theses

For centuries humanity has been expanding its borders, stretching in and across a wide range of ecosystems, optimizing the land for human use and habitation. Animal-aided design is a possible solution to the loss of habitats; a new methodology of designing green spaces for the use of specific native species. Green spaces are vital to the mental and physical well-being of people, and the presence of native species such as songbirds or butterflies can further increase those benefits. Only 4.2% of North Dakota is developed land, referring to urban and industrial usage, but within these spaces are opportunities to conserve …

Re:Place: Leveraging Cultural Memory To Transform Communities Through Adaptive Reuse, Olivia Leingang

Architecture Theses

This thesis investigates how adaptive reuse can leverage cultural memory to transform declining small-town economies, specifically addressing the socio-economic erosion in Mandan, North Dakota. By reimagining the 1958 Mandan High School as the "Mandan Marketplace," the research proposes a 165,000-square-foot multi-use commercial hub designed to reverse regional retail leakage and density imbalances. The project utilizes a research-driven Design Framework and Strategic Building Program to integrate 23 new amenities, including a food hall, business incubator, and wellness center, into the local fabric. Through a methodology of six adaptive reuse types, the design preserves the building’s role as a "custodian of memory" …

Byproducts In Bakken: Integrating Agricultural Waste Into Architecture As A Path To Sustainable Design In Western North Dakota, Noah Boen

Architecture Theses

Sustainable design can be seen as threatening in regions where local industries are expected to decline if introduced. This thesis explores how this can be solved in western North Dakota where fracking is a large part of the economy. North Dakota leads the nation in wheat production, and recent advancements have allowed for the waste product from harvest to be utilized in architectural applications. By introducing this as a feasible means for sustainable design in the region, through the typology of a visitor center in the North Unit of Theodore Roosevelt National Park, the local population can become better educated …

Neurointerventional Advances In 2025, Amol Mehta, Sunil A Sheth, Ashutosh P Jadhav

Faculty, Staff and Student Publications

No abstract provided.

Computational Modeling Meets 3d Bioprinting: Emerging Synergies In Cardiovascular Disease Modeling, Tanmay Mukherjee, Mehdi Salar Amoli, Sarah Rezapourdamanab, Lama Rita El Shammas, Martin L Tomov, Emilio A Mendiola, Vahid Serpooshan, Reza Avazmohammadi

Faculty, Staff and Student Publications

Cardiovascular diseases (CVDs) remain the leading cause of death worldwide, underscoring the need for improved strategies in diagnosis, treatment, and disease modeling. Traditional in vitro models often fall short in replicating human CV physiology, prompting efforts to advance cardiac tissue engineering and computational modeling. Among these, three-dimensional (3D) bioprinting has emerged as a transformative tool, enabling the creation of biomimetic CV constructs that more faithfully replicate native tissue structure and function. However, challenges persist in achieving appropriate mechanical properties and long-term performance of engineered CV constructs. Computational modeling offers powerful solutions to assist with these challenges, providing predictive insights into …

Flicking Fibres: Microfibres Act As Sensory Disruptors In A Marine Crustacean, Ari Drummond, Alexander D.M. Wilson, Lucy M. Turner, Mark Briffa

School of Biological and Marine Sciences

Anthropogenic inputs to the environment—including microplastics and microfibres—are global stressors known to impair multiple facets of organismal biology. However, the effects of these pollutants on sensory structures remain critically understudied. Sensory systems mediate organism-environment interactions, and pollution-derived impairment at these interfaces may cascade through bioprocessing, from information acquisition to behaviour and ultimately fitness. Microfibres, in particular, pose an additional threat, potentially physically obstructing sensory organs and chemically interfering with sensory processes. Using an invertebrate model of sensory biology, Pagurus bernhardus, we tested whether dryer lint—a complex, heterogeneous mix of treated microplastic and cellulose fibres, and other anthropogenic contaminants—acts as a …

Evaluating The Rural/Urban Divide In Conservation: Methods Of Improvement In Conservation Programming Across Kentucky, Lauren Tackett

Honors College Theses

Kentucky’s lands and waterways have always defined the state. Our unique karst landscape, combined with the Appalachian Mountains and Ohio River, help characterize the state and its identity. However, across Kentucky conservation efforts within recent years have been under attack. Through legislation changes and policy challenges, various bills have sought to repeal Kentucky’s conservation efforts regarding water, soil, and land use. Furthermore, there has been a rise in environmental disasters within the state that cause long term issues for both rural and urban communities to contend with. The responsibility of land stewardship falls on a variety of entities but weighs …

Erratum For "Soil Freezing Characteristic Surface For Partially Frozen Soils", Antai Dong, Xiong Zhang, Ming Xiao

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The following corrections should be made to "Soil Freezing Characteristic Surface for Partially Frozen Soils" by Antai Dong, Xiong Zhang, and Ming Xiao, https://doi.org/10.1061/JGGEFK.GTENG -13924: In the third sentence of the Abstract, the value for suction when completely dried is incorrect. It should be 106 kPa. The label at the end of the suction axes in Figs. 1(a) and 2 is similarly inaccurate. Corrected versions of Figs. 1 and 2 are provided herein. To preserve the published version of record, these details have been corrected only in this erratum. (Figure Presented)

Thermo-Hydro-Chemical Coupled Numerical Modeling Of Hydrogen-Thermal Co-Development In Hydraulically Fractured Peridotite, Jiacheng Dai, Zhonglin Ma, Yunzhi Yue, Yujie Yuan, Shouceng Tian

Research outputs 2022 to 2026

Hydrogen generation through serpentinization reactions in peridotite formations under high temperature conditions represents a promising avenue for subsurface hydrogen production. However, the thermal energy in the formation environment have not been sufficiently considered. To integrate hydrogen production with thermal energy development, this study develops a thermo-hydro-chemical coupled numerical model, which is used to investigate hydrogen-thermal co-development in hydraulically fractured peridotite. Given that the hydrogen-thermal co-development process involves fluid flow, heat transfer and serpentinization reactions, the governing equations are formulated based on Darcy flow and energy conservation equations, with serpentinization kinetics incorporated through the reactive source terms. To evaluate hydrogen production …

Understanding Customer Engagement Behavior In Virtual Try-On Services: Evidence From Indonesia, Nyoman Sri Subawa, Ni Putu Chantika Aprilia Nariswari, Made Maenita Dewi, Anak Agung Gede Wiranata, Caren Angellina Mimaki, Made Srinitha Millinia Utami

Research outputs 2022 to 2026

The adoption of immersive technologies, such as Virtual Try-On (VTO), has transformed how consumers evaluate products, interact digitally, and engage with brands. This study investigates the effects of experiential value, flow, perceived enjoyment, customer trust, and customer satisfaction on customer engagement behavior, within the Stimulus–Organism–Response (S–O–R) framework. Experiential value serves as the stimulus, flow and psychological states as the organism, and engagement as the response. Data were collected from 320 Indonesian e-commerce using a purposive sampling technique, targeting respondents with prior experience using Virtual Try-On (VTO) features through an online questionnaire distributed via Google Forms, and were subsequently analyzed using …

2026 May, Morehead State University. Office Of Communications & Marketing.

Morehead State Press Release Archive, 1961 to the Present

Press releases for May of 2026.

Predicting Flight Fares With Machine Learning: Enhancing Aviation Industry Pricing Forecasting, Reem Almulla

Theses

This research investigates the increasing challenge of accurate flight fare prediction for travel agencies that are functioning and working in the post-pandemic aviation market. As the prices fluctuate while demand is unstable and competition pressure increases, therefore it influences decision-making and profitability. In most cases, traditional ticket pricing methods often can be ineffective when capturing complex and non-linear relationships within factors that influence the ticket fare dynamics. As a result, highlighting the urge of more adaptive pricing and data-driven predictive machine learning models. In response to this challenge, the research examines the effectiveness of machine learning techniques for enhancing flight …

Genui: Customizing And Improving User Interfaces In Real-Time With Generative Ai, Ursula Parker

Theses

MOTIVATION: Users must conform to the interfaces they are given, which are designed for a generalized user base rather than individual workflows or preferences. Existing UI customizations are often limited to fixed options predetermined by developers, restricting meaningful user control. Advances in generative AI introduce the possibility of modifying the underlying code of a production system that defines interfaces, enabling more flexible and targeted adaptations. However, the feasibility, scalability, and usability of such user-driven customization remain open questions. GOAL: The goal of this work is to help people customize their user interfaces, by investigating how they can linguistically specify the …

Existing Buildings Against Climate Zone Shifts: Analysis Of The Resilience Of Existing Buildings In Changing Climate Zones, Adriana Rodriguez

Theses

This thesis investigates how climate zone shifts affect the hygrothermal performance and durability of existing building wall assemblies designed under previous International Energy Conservation Code (IECC) requirements. As global climate change continues to alter temperature, humidity, and extreme weather patterns, building codes and climate classifications are increasingly challenged to keep pace with current and future environmental conditions. The research focuses on whether 2×6 wood-framed wall assemblies designed under the 2018 IECC remain resilient under updated climate zone classifications and future climate scenarios. A comparative analysis of four U.S. counties—Davidson (TN), Garfield (OK), Allegany (MD), and Marion (IN)—was conducted based on …

Dark Current And Persistence In Hgcdte-On-Si Infrared Detectors, Lazar Buntic

Theses

This thesis investigates the performance of Raytheon’s mercury-cadmium-telluride-on-silicon (MCT-on-Si) infrared detector arrays, with particular emphasis on the impact of the heteroepitaxial silicon growth process on dark current and persistence characteristics. Infrared detectors have been the cornerstone of astronomical discovery for the past four decades and remain essential for current and future flagship observatories, including the James Webb Space Telescope and the Nancy Grace Roman Space Telescope. Traditionally, the highest-performance HgCdTe (MCT) arrays are grown on lattice-matched cadmium-zinc-telluride (CZT) substrates, which are costly and limited in size. To enable low-cost, large-format arrays, Raytheon developed a process for growth of MCT on …

The Quality Assurance Machine – A Software Quality Assurance Architecture For Ml-Enabled Systems, Shane E. Downing

All-Inclusive List of Electronic Theses and Dissertations

This dissertation evaluates whether a reusable assurance architecture, the Quality Assurance Machine (QAM), can provide effective product and process quality assurance for ML-enabled software platforms. The QAM is a system-level SQA architecture that turns plans and policies into versioned configurations, executes them in controlled environments, and produces preserved run evidence that supports traceability, auditability, and controlled change. The study follows Design Science Research and evaluates the instantiated artifact using eight assurance requirements (AR1–AR8) synthesized from standards-based guidance, including IEEE 730 and ISO/IEC/IEEE 15026. A four-year longitudinal evaluation combines two methods. First, operational evidence from routine regression and release-validation runs, defect …

Antidistillation Sampling For Classification Models, Khawaja Abaid Ullah

Theses

Knowledge distillation enables adversaries to replicate the functionality of proprietary machine learning models by querying their APIs and training surrogate student models on the returned soft-label distributions. Antidistillation Sampling (ADS), recently proposed for large language models, perturbs the output distribution of a teacher model at inference time to degrade the quality of the resulting distilled model while preserving utility for legitimate users. We adapt ADS to the supervised classification setting and identify a structural obstacle to its direct transfer: the high-confidence, near-one-hot output distributions characteristic of well-trained classifiers leave insufficient probability mass on non-target classes for the additive penalty to …

Biohybrid Robotic Jellyfish For Swimming-Enhanced Vertical Ocean Profiling, Kelsi M. Rutledge, Sean Colin, John H. Costello, Noa Yoder, Simon R. Anuszczyk, Kelly R. Sutherland, Brad L. Gemmell, John O. Dabiri

Arts & Sciences Faculty Publications

Ocean monitoring is essential for understanding climate change and marine ecosystem dynamics, yet achieving comprehensive global coverage remains a challenge in oceanography. Current technologies face limitations in cost, power, hardware, and depth capacity that restrict widespread monitoring capabilities. Here we show that biohybrid robotic jellyfish (Aurelia aurita) can serve as autonomous vertical ocean profilers by integrating microcontrollers with positively buoyant sensor payloads, achieving controlled vertical-profiling capabilities. Laboratory experiments demonstrated repeatable up–down trajectories, quantified force balance limits, and identified predictable, size-dependent descent swimming speeds. Field deployments in Massachusetts coastal waters and the open ocean off the Florida Keys demonstrated field operation …

Enhancing Traffic Safety Through Ai-Driven, Privacy-Preserving, And Secure Impaired Driving Detection Systems, Razan Alsulieman

Dissertations

Drunk driving remains a major threat to road safety worldwide, contributing significantly to traffic injuries and fatalities each year. Traditional detection approaches are largely reactive and vehicle-centric, relying on in-vehicle sensors, breathalyzers, or post-incident enforcement. These methods often depend on driver cooperation, intrusive hardware installations, or limited monitoring environments, restricting their scalability and effectiveness in large transportation systems. At the same time, modern cities increasingly deploy roadside cameras, surveillance networks, and drone- based monitoring systems, creating new opportunities for proactive intoxication detection at the infrastructure level. However, leveraging such external monitoring introduces challenges related to secure data collection, reliable AI-based …

Place, Democracy, Law, And The Necessity Of Local News, Erin C. Carroll

Georgetown Law Faculty Publications and Other Works

In 2025, the painter Amy Sherald pulled her show American Sublime from the Smithsonian after the museum considered removing a painting of a transgender Statue of Liberty to avoid angering President Trump. The Baltimore Museum of Art stepped in, and it was important that it did. American Sublime needs to be seen in person. It comprises dozens of portraits of Black Americans—a farmer, a bicyclist, a balloon-holder, a child on a playground slide. The portraits are dignified, beautiful, warm, and alluring. They are, in a word, human.

In the gallery, the paintings were hung low on the walls to increase …

Mechanisms Of Synergy Between Nanosecond Pulsed Electric Field (Nspef) And Cold Atmospheric Pressure Plasma Discharge (Cap) In Pancreatic Cancer: The Role Of Ros-Mediated Oxidative Stress And Apoptosis, Zobia Minhas

Biomedical Sciences Theses & Dissertations

Pancreatic ductal adenocarcinoma is a highly lethal malignancy characterized by poor prognosis and resistance to conventional therapies. Novel treatment strategies are needed to overcome this resistance. Non-thermal physical modalities, including nanosecond pulsed electric field (nsPEF) and cold atmospheric pressure plasma discharge (CAP), have emerged as potential anticancer approaches; however, the mechanisms underlying their combined effects remain unclear.

This study evaluated whether nsPEF enhances CAP-induced cytotoxicity and investigated the associated molecular mechanisms using the murine Pan02 pancreatic cancer cell line. Cell viability was assessed by WST-1 metabolic activity assays and electric cell–substrate impedance sensing (ECIS). Intracellular reactive oxygen species (ROS) were …

Llms-Based Text-To-Sql For Geospatial Information Retrieval, Temitayo Olamilekan Ogunsusi

All Theses

Text-to-SQL aims to translate natural language questions into SQL queries that can be executed on databases, enabling non-expert users to retrieve information without learning formal query languages. Early Text-to-SQL systems relied on rule-based methods and semantic parsers, while recent advances in deep learning have achieved strong performance by jointly encoding user questions and database schemas. However, these approaches typically require large, annotated datasets and specific model architectures. With the emergence of large language models (LLMs), such as GPT-4, Llama, and Gemma, Text-to-SQL systems can leverage powerful natural language understanding capabilities to generate SQL queries using zero-shot or few-shot prompting. Despite …

Multi-Task Growing Interpretable Neural Network For Multi-Target Symbolic Regression, Hussein Rajabu

All Theses

Over the past decade, deep learning has achieved remarkable success across domains such as computer vision and natural language processing. Despite their strong predictive capabilities, these models often function as black boxes, limiting transparency and making them difficult to trust in high-stakes applications such as healthcare and business decision-making. While explainable artificial intelligence (XAI) methods improve interpretability, most approaches remain post-hoc, focusing on statistical associations rather than uncovering the underlying functional mechanisms governing predictions.

Symbolic regression (SR) has emerged as a promising direction within XAI by directly discovering explicit mathematical expressions that describe relationships between inputs and outputs. Unlike traditional …

The Political Transformation Of Corporate America, 2001–2022, Reilly S. Steel

Faculty Scholarship

This article reconciles conflicting views about the political landscape of corporate America with new data on the revealed political preferences of 97,469 corporate directors and executives at 9,005 different U.S. companies. Driven largely by turnover, I find that average observed ideology for directors and executives has shifted meaningfully to the left over time, changing from modestly conservative in 2001 to roughly centrist by 2022. This finding supports a middle-ground position between conventional wisdom casting “big business” as a conservative stronghold and revisionist views holding the opposite. Counterfactual simulations and a difference-in-differences design suggest multifaceted reasons for these changes, and hand-collected …

Enameling Coating Of Pipes: Thermal Proprieties And Corrosion Tests, Signo Reis, Genda Chen, Mike Koenigstein, Liang Fan

Materials Science and Engineering Faculty Research & Creative Works

Enamel coating on pipelines can be done in several ways such as the wet process, plasma spray, and electrostatic process. Wet process requires little capital expenses and provides an acceptable finish for industrial applications particularly when the part to be coated is small. Electrostatic process of enamel powder is most promising to coating large pipelines in field conditions. The enamel coating applied by the electrostatic process is very consistent and smooth since each particle is glass only. However, the powder is very fragile until fired and the charge retention is lowered in high humidity conditions. Coupons cut from a full-size …

Effect Of Environmental Conditions On Fracture Of Composite Materials And Thin Films, Victor Birman

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Environmental conditions, i.e., temperature and moisture, affect mechanical properties of materials, including composites. In this paper, we concentrate on one of the aspects of the effect of environment on fracture in a composite lamina. The paper demonstrates an analytical approach to account for the effect of the changes in environment on the strain energy release rate of composite materials and thin films. These analytically determined strain energy release rates should be compared to fracture toughness to predict the susceptibility of the material to fracture. Numerical examples are presented for several polymeric and metal matrix composites using available experimental data for …

Validity Of The Schrage Equation In Prediction Of Evaporation Rate Of Liquid N-Dodecane In High-Pressure Nitrogen Gas: A Molecular Dynamics Study, Wazih Tausif, Jordan Hartfield, Md Amin Haque, Zhi Liang

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Evaporation of liquid fuel in a high-pressure air is a process that critically influences fuel–air mixing in advanced propulsion systems. In this work, we use molecular dynamics (MD) simulations to study the validity and accuracy of the Schrage equation in quantifying the evaporation and condensation rates of n-dodecane (a diesel surrogate) in air (approximated as N2 gas) with gas pressure varying from 0 atm to above the critical pressure of n-dodecane. The MD simulation results show that the evaporation coefficient (αe) is higher than the condensation coefficient (αc) at the evaporating n-dodecane surface and is lower than αc at the …

A Federated Learning Framework For Data-Sovereign Predictive Maintenance In Distributed Smart Manufacturing, Md Sazol Ahmmed, Sriram Praneeth Isanaka, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Featured Application: The proposed federated learning framework can be applied in distributed smart manufacturing environments where multiple factories or production facilities collaboratively develop predictive maintenance models without sharing sensitive operational data. This approach is particularly useful for industrial networks involving geographically distributed plants, contract manufacturing partners, and multi-site production systems where data sovereignty and avoidance of raw data sharing are critical. Predictive maintenance enables early detection of machine failures and reduces unexpected production downtime. However, conventional approaches typically rely on centralized data collection and model training which introduce challenges related to data sovereignty, communication overhead and data ownership. To address …

Measurements And Scaling Of Ion Propulsion Impulse During Driven Magnetic Reconnection, Fatima Ebrahimi, Nicholas A. O'Gorman, Kush Maheshwari, Jongsoo Yoo, Alexandre Sainterme, Hantao Ji

Faculty Publications

Impulse scaling during magnetic reconnection, the magnetic energy conversion to kinetic energy, via direct Mach probe measurements in Magnetic Reconnection Experiment is examined. Ion exhaust velocity and impulse scalings with reconnecting magnetic field during the push phase of driven reconnection are presented. The outflows and impulse measurements are compared with global MHD simulations. Both measurements and simulations reveal a favorable scaling, greater than linear, of impulse with reconnecting field. These scaling results establish that magnetic reconnection could be utilized for plasma propulsion.