Digital Commons Network^™

Behavioral, System, And Informational Cyberattacks: A Human-In-The-Loop Driving Simulator Experiment, Samuel Petkac

Psychology Theses & Dissertations

Advanced technologies such as sensors and AI/ML algorithms have enabled increasing levels of automated driving system that detects, responds, and even predicts changes in a driving environment supported by wireless connectivity to nearby vehicles and infrastructure. Such connected and automated vehicles (CAVs) can be particularly vulnerable to cyberattacks targeting not only infotainment systems but also firmware and other applications, critically compromising driver safety. As we anticipate a “mixed” traffic where vehicles with various levels of automated technologies share the road for the foreseeable future, it is urgent to systematically examine types of possible cyberattacks and control human behaviors in such …

Learning In Motion: How Small Groups Can Promote Self-Regulated Learning In Physical Therapy Students, Sara Mclaren

STEMPS Theses & Dissertations

Self-regulated learning (SRL) is a critical skill for success in rigorous graduate health professions programs, where students must independently manage complex academic demands. Despite its importance, limited research has examined SRL processes among Doctor of Physical Therapy (DPT) students in the didactic phase of training. Guided by Zimmerman’s cyclical model of self-regulated learning, this study examined SRL behaviors among second-year DPT students and explored how small group learning contexts may influence engagement in SRL processes and academic performance.

This mixed-methods study included 39 DPT students enrolled in a physical therapy program at a public university in the southeastern United States. …

Personality Predictors Of Cybersecurity Vulnerability: Insights From Self-Reports And Stimulated Threat Scenarios, Saroja Roy Grandhi

Psychology Theses & Dissertations

In this cyber dependent and enabled era, understanding the role of human factors in digital security is essential. This study investigates the relationship between Big-Five personality traits and cybersecurity behaviors by examining both self-reported and stimulated behaviors in security threat scenarios. Participants completed validated questionnaires to report their personality traits, cybersecurity practices and engage in task-based stimulations to capture behaviors such as phishing detection, password creation, and response to security alerts. The study tested whether higher conscientiousness, openness, and agreeableness would be associated with stronger cybersecurity practices and smaller discrepancies between self-reported and observed behaviors. And, whether greater extraversion and …

A Theoretical Framework For Recursion In Complex System Governance, Gilbert Goddin

Engineering Management & Systems Engineering Theses & Dissertations

The purpose of this research was to construct an original theoretical framework for understanding recursion in Complex System Governance (CSG), grounded in the propositions and axioms of systems theory and management cybernetics. This framework addresses a research gap for cybernetic recursion relating to the governance of complex systems. Leveraging the CSG framework (Keating & Katina, 2019; Keating, 2022), holonic principles (Koestler, 1970; Mella, 2009), management cybernetics (Beer, 1979; Beer, 1984; Beer, 1995), and metacybernetics (Yolles, 2021; Yolles & Fink, 2015c; Yolles & Frieden, 2021), recursion is theorized as a governable capability, whereby metasystemic governance anticipates emerging complexity and purposefully regulates …

Biocrude From Organic Waste And Its Conversion To Hard Carbon: Experimental And Modeling Study, Isamu Umeda

Civil & Environmental Engineering Theses & Dissertations

This study establishes a technical and theoretical foundation for the efficient conversion of organic waste into biocrude and high-value carbon materials, aiming to facilitate the industrialization of hydrothermal and solvothermal liquefaction. The dissertation research is structured as follows:

Chapter 2 developed a novel chemical kinetic model for the HTL of corn stover based on elemental balances (C, H, N, and O). By incorporating temperature, residence time, solid loading as an independent variable, the model successfully predicted product yields and properties, revealing that there was non-pseudo-first-order reaction pathways in the conversion of water soluble organics in aqueous phase (AP) to hydrochar. …

Norfolk Flooding And Its Effect On Nutrient And Enterococcus Levels, Malachi R. Stephens

Knowledge and Creativity Expo

Tidal flooding is common in the City of Norfolk, VA due to high rates of sea rise in the region, as well as the region’s subsidence. This has led to increases in flooding at high tide, especially during the spring tide portion of the tidal cycle.  At high tide water from the Elizabeth and Lafayette Rivers can flood the landscape directly or can rise out of storm drains. This floodwater often stays on land for long periods of time and can deliver contaminants back into the rivers. To determine the amounts of nutrients and Enterococcus, a fecal indicator, delivered to …

Pong Revised: Network-Based Competitions Through Secure Socket Services, Noah T. Jennings, Destiny D. Hale, Jared D. Williams, Michael J. Lively-Scholz

Knowledge and Creativity Expo

We aim to provide a safe, thrilling, locally hosted, and educational multiplayer experience that can be quickly replicated in modern Capture The Flag (CTF) events.

Remediation Of Ammonium Perrhenate Via Tris(2,2’-Bipyridine)Ruthenium(Ii) Chloride, Kaylin L. Thomas, Sandra A. Abdellah, Alvin A. Holder

Knowledge and Creativity Expo

Pertechnetate (TcO₄⁻) is a persistent radioactive byproduct resulting from the decay of uranium-235 or plutonium-239 in the nuclear fuel cycle. Its high environmental mobility, long half-life, and significant beta radiation make TcO₄⁻ a critical contaminant. Structurally tetrahedral and water-soluble, TcO₄⁻ behaves similarly to the sulfate anion, facilitating its rapid introduction into ecosystems.

It bioaccumulates in lower-level organisms, propagating radioactive and toxic effects through food chains. In mammals, technetium-99 accumulates in the thyroid and may also impact fetal development. Its small charge, chemical stability, and solubility present significant challenges for effective remediation.

Current remediation methods often suffer from poor selectivity, dependence …

Reconstructing 5000 Years Of Hurricane Activity In Holyrood Pond Using Sediment Core Analysis, Jamie Mclaulin, Arielle Nogueira, Elizabeth Wallace

Knowledge and Creativity Expo

Hurricanes are hazardous and costly events that annually negatively impact people that live in coastal areas in North America.  The current observational record of hurricanes is short (1970- present) and does not offer insight into the effects of climate change on hurricane frequency.  One method of improving and extending our observational record of hurricanes is to reconstruct paleohurricanes using sediment cores.  These cores record hurricane activity in the form of coarse-grained overwash layers that are deposited when hurricanes move sand from beaches into backbarrier ponds.  In this project, we analyzed sediment cores from Atlantic Canada to locate coarse-grained storm layers …

Exploring Geometry Teaching And Learning Through Self-Study, Linnea Kallebo Ms., Ayse Ozturk

Knowledge and Creativity Expo

Self-study is a powerful tool for improving teacher effectiveness, particularly in mathematics instruction where misconceptions can significantly impact student learning. This self-study examines my evolving understanding of geometry concepts and common student misconceptions encountered during a teaching geometry course. Through reflection, peer discussion, and analysis of misconceptions, this study reveals how examining both my own learning and students’ thinking can inform self-adjustment of teaching strategies. Findings highlight the importance of building new geometry concepts on mastered ideas and pairing self-study with evaluation of student responses to improve instructional decision-making.

Self-Study In Learning And Teaching The Pythagorean Theorem, Julia Podolskiy, Ayse Ozturk

Knowledge and Creativity Expo

Old Dominion University undergrad student Julia Podolskiy performed self-study research on learning and teaching the Pythagorean Theorem. The poster provides purpose, methods, results, and future directions on how Julia Podolskiy's knowledge on the Pythagorean Theorem has improved over the course of a semester and how she plans to implement the theorem to her teaching.

Methane Consumption Rates By Coastal Virginia Beach Microbes, James R. Bailey Ii

Knowledge and Creativity Expo

This study measures whether microbial communities in the shallow coastal waters of Virginia Beach are capable of consuming methane in the water column. Using methane enrichment incubations and gas chromatography, we found no measurable methane oxidation of our samples over multi-day periods. These results suggest that these coastal waters may act as net sources of atmospheric methane.

Is The Chesapeake Bay Browning?, Samantha Williamson, Jessie Turner

Knowledge and Creativity Expo

Brownification is when water bodies turn brown over time. It occurs due to high amounts of color-dissolved organic matter (CDOM). CDOM is organic material, such as decaying leaves and organisms, that leaches into the water column like tea. It absorbs ultraviolet and blue light more than red light, causing the water to appear brown. After comparing surveys from 1987 and 2018, scientists discovered the Adirondack lakes underwent brownification as they recovered from acid rain. However, while increased CDOM can signify an ecosystem’s recovery, it can also hinder seagrass growth. Although scientists have studied this phenomenon in lakes, estuaries have not …

Living Shorelines As A Solution To Saltwater Marsh Erosion, Elizjah Eddy, Richard Hale

Knowledge and Creativity Expo

In recent years, saltwater marshes fringing the Lafayette River, a tributary of the Elizabeth River, have experienced degradation in response to increased inundation and ocean energy . These marshes provide critical ecological and economic benefits to the City of Norfolk, and prioritizing their long term health and sustainability is an important challenge. An emerging restoration tactic involves enhancing marsh elevation through the application of dredge material that would otherwise require disposal offshore (known as thin-layer placement or TLP). An important first step in TLP projects is characterizing the textural and geochemical properties of the existing marsh sediment. The goal of …

How Much Does Shape Matter: Investigating The Impact Of Marine Particle Morphological Features On In-Situ Settling Velocities Using Pca And Various Ml Models, Huanqing Huang, Alexander B. Bochdansky

Knowledge and Creativity Expo

Particle settling velocity serves as an essential component in ocean biological pump, as it determines particle retention time in the water column. Stokes’ law has been widely used to predict particle settling velocities by particle size and excess density in aquatic environments. However, an increasing number of studies suggest that Stokes’ law fits poorly in the size-velocity relationship of observations on small oceanic particles. Here, we present a series of novel approaches to investigate the relative contribution of settling velocities by the particle shape and optical densities using machine learning (ML) models and principal component analysis (PCA), based on 3906 …

Human Subject Studies For The Alignment Of Llm-As-A-Judge Evaluation Metric For Science News, Gabriel Vega Osborne

Knowledge and Creativity Expo

Science news has become an important vehicle to disseminate scientific breakthroughs, discoveries, and technological innovations. With the advancement of large language models and related AI models, it is possible to automatically generate science news from scientific papers, extending the reader population from domain scientists to a broader scope. However, how to evaluate the quality of the generated news warrants research. Traditional token based metrics have been shown to fail to evaluate the semantics and nuances of science news. Inspired by the fact that a major goal of science news is to educate readers with new knowledge, we thus propose knowledge …

Ran Walker, Randolph Walker Jr, Ran Walker

Virginia Poets Database: A Literary and Educational Resource

No abstract provided.

Critical Design And The Robotic Imaginary: Design Criticism And Critical Robots, Jörgen Behrendtz

The Journal of Sociotechnical Critique

This paper brings critical design and design criticism to critical robot studies. Critical design can be described as an umbrella term for approaches making use of speculative designs to highlight and challenge narrow assumptions, preconceptions or even taken-for-granted truths about the role products play (in a wide sense) in everyday life. Design criticism refers to a reasoned procedure that investigates emancipatory and/or limiting potentials of designs, theorizes the roles of affordances, materials and embodied perception as epistemological resources in media interaction, and clarifies connections between specific design choices and their associated experiential qualities, seductive powers, ideological underpinnings, material operations, and …

Threads Of Empathy: An Integrative Model Of Empathy In The Schools, Arthur J. Clark, Tara M. Simpson

Journal of Human Services Scholarship and Interprofessional Collaboration

Empathy has a distinctive and evolving history in education for cultivating human relationships and engendering mutual understanding. Within a school setting, empathic engagement is essential for the social and emotional development of children and adolescents. From an educational perspective, literature from multiple disciplines and specialties illustrate innovative practices to harness empathy in the classroom and beyond. The representative initiatives hold promise for developing an integrative model of empathy within a school or a school district through a program involving interprofessional collaboration.

A. Vs. I In Ai: Is There A Threshold To "Engineered" Intelligence?, Joshit Mohanty

Engineering Management & Systems Engineering Faculty Publications

Despite artificial intelligence reshaping the world, its development generates uncertainties regarding future capabilities. AI simultaneously exists as an artifact of engineering design and as autonomous intelligence, creating an observer-participant feedback loop. This paper proposes that embodied AI faces a bandwidth-limited intelligence threshold T_h that it arises from B = min(C_sens,C_Act). However, Shannon capacity measures bits while intelligence operates on concepts, necessitating a dual-channel model separating physical bandwidth B_io from representational capacity B_rep. Intelligence emerges as multi-dimensional rather than scalar, with components exhibiting different bandwidth dependencies. Surpassing T_h requires either new sensing methods expanding B, enhanced representational frameworks, or reconceptualization within …

Aura: An Ai-Powered Multimodal Prototype For Adaptive Apraxia Of Speech Therapy And Communication Support, Omotayo Omoyemi, Rachel K. Johnson

Speech-Language Pathology Faculty Publications

Apraxia of Speech (AOS) is a motor speech disorder that significantly limits communication and requires intensive, long-term therapy. Access to consistent treatment is often constrained by shortages of speech-language pathologists, high costs, and limited opportunities for continuous monitoring outside clinical settings. Recent advances in Artificial Intelligence (AI) provide new opportunities to support scalable and personalized speech therapy.

This paper presents AURA (Adaptive Understanding and Relearning Assistant for Apraxia), a multimodal AI framework designed to support speech therapy, progress monitoring, and communication for individuals with AOS. The system integrates speech analysis, machine learning–based error detection, reinforcement learning for adaptive therapy, and …

Part Ii: Industrial Information Integration Review 2020-2025, Jinzhi Li

Information Technology & Decision Sciences Faculty Publications

Industrial Information Integration Engineering (IIIE) has become increasingly essential for improving operational efficiency and harmonizing heterogeneous industrial systems through advanced digital integration approaches. Fueled by rapid advancements in Industry 4.0 technologies—including digital twins, artificial intelligence, immersive interfaces, and IoT infrastructures—IIIE is substantially transforming traditional enterprise architecture and integration frameworks. This systematic review synthesizes recent developments and emerging trends, with particular attention to the accelerating adoption of digital twins and the deepening convergence between operational technologies (OT) and information technologies (IT) across multiple sectors. While notable progress has been made, significant challenges persist, especially in developing resilient integration architectures and fully …

Ocular Surface Disease Following Lasik And Cataract Surgery: A Review Of Their Interrelated Complications, Matthew D. Spangler, Nila Kirupaharan, John D. Sheppard

Department of Ophthalmology Faculty Publications

Background: Ocular surface disease is a multifactorial condition that is very commonly caused by dry eye disease (DED). Ophthalmic procedures intended to improve visual outcomes, laser-assisted in situ keratomileusis (LASIK) and cataract surgery, can paradoxically cause or exacerbate underlying ocular surface disease. This results in worsening vision and quality of life.

Areas covered: This review examines the pathophysiological mechanisms contributing to ocular surface disease development following LASIK and cataract surgery. Both procedures are associated with the transection of corneal nerves, leading to decreased tear production, surface instability, altered neurotrophin production, and impairment of the blink reflex. Furthermore, these incisional procedures …

Identifying Relevant Covariates In Rna-Seq Analysis By Pseudo-Variable Augmentation, Yet Nguyen, Dan Nettleton

Mathematics & Statistics Faculty Publications

RNA-sequencing (RNA-seq) technology allows for the identification of differentially expressed genes, which are genes whose mean transcript abundance levels vary across conditions. In practice, RNA-seq datasets often include covariates that are of primary interest in addition to a set of covariates that are subject to selection. Some of these covariates may be relevant to gene expression levels, while others may be irrelevant. Ignoring relevant covariates or attempting to adjust for the effect of irrelevant covariates can compromise the identification of differentially expressed genes. To address this issue, we propose a variable selection method that uses pseudo-variables to control the expected …

Utilizing Machine Learning Techniques For Computer-Aided Covid-19 Screening Based On Clinical Data, Honglun Xu, Andrews T. Anum, Michael Pokojovy, Sreenath Chalil Madathil, Yuxin Wen, Md Fashiar Rahman, Tzu-Liang (Bill) Tseng, Scott Moen, Eric Walser

Mathematics & Statistics Faculty Publications

The COVID-19 pandemic has highlighted the importance of rapid clinical decision-making to facilitate the efficient usage of healthcare resources. Over the past decade, machine learning (ML) has caused a tectonic shift in healthcare, empowering data-driven prediction and decision-making. Recent research demonstrates how ML was used to respond to the COVID-19 pandemic. This paper puts forth new computer-aided COVID-19 disease screening techniques using six classes of ML algorithms (including penalized logistic regression, random forest, artificial neural networks, and support vector machines) and evaluates their performance when applied to a real-world clinical dataset containing patients’ demographic information and vital indices (such as …

Changepoint Analyses Confirms Global Tropical Cyclone Frequency Decline, Michael Wehner, Thomas Fisher, Norou Diawara, Robert Lund

Mathematics & Statistics Faculty Publications

Changes in tropical cyclone frequencies as the climate warms is a topic of significant current debate [1, 2]. There is no accepted theory of how tropical cyclogenesis might respond to a warmer ocean-atmosphere system as multiple controlling factors exist [3–7]. Anthropogenic warming of surface ocean temperatures due to increased greenhouse gas concentrations [8] increases the potential for tropical cyclogenesis [9–11]; however, realized cyclogenesis also requires an initial local disturbance [12–16] to develop. Most multi-decadal tropical cyclone permitting climate models (i.e. resolutions of 15-50km) exhibit frequency decreases in warmer climates, despite the increase in tropical cyclogenesis potential [17–25]. In this paper, …

A Composite Narxnn Approach To Photovoltaic Power Forecasting With Integrated Weather Inputs And Uncertainty Quantification, Denisse Urenda Castañeda, Sharmin Abdullah, Jackson Morgan, Honglun Xu, Michael Pokojovy, Tzu-Liang Tseng

Mathematics & Statistics Faculty Publications

Solar photovoltaics (PV) are a major source of sustainable energy. Yet, their power output is highly sensitive to environmental variability, particularly solar irradiance, cloud cover, wind, and temperature. Accurate forecasting of PV power is essential for efficient grid integration and energy planning, especially in applications requiring reliable longer-term forecasting rather than one-step-ahead predictions. This study presents a PV power forecasting approach using Nonlinear Autoregressive models with Exogenous Inputs (NARX), integrating large-scale numerical weather historical data as exogenous variables. Although NARX models effectively capture temporal dependencies, they can become overly dependent on historical power values, reducing responsiveness to real-time weather changes. …

Ai-Assisted Surface-Enhanced Raman Spectroscopy For Cardiovascular Diagnostics: From Plasmonic Materials To Clinical Translation, Anju Joshi, Gymama Slaughter

Center for Bioelectronics Publications

Raman spectroscopy (SERS) has emerged as a powerful analytical technique, offering molecular fingerprint specificity and ultrasensitive detection of cardiac biomarkers. Recent advances in plasmonic nanostructures, surface functionalization strategies, and flexible sensing platforms have significantly improved the analytical performance of SERS-based biosensors. In parallel, the integration of artificial intelligence (AI) and machine learning has enabled robust interpretation of complex spectral datasets, facilitating automated biomarker classification and improved diagnostic accuracy in heterogeneous biological environments. Despite these advances, the field remains fragmented, with limited integration between nanomaterial design, biomarker selection, and data-driven analysis, and persistent challenges related to reproducibility, standardization, and clinical validation. …

Eigenvalue Bound Preservation: Numerical Experiments On The 2d Q-Tensor Flow, Marcel C. Deguzman

Knowledge and Creativity Expo

We study the evolution of nematic liquid crystals in two dimensions using the Q-tensor model, a continuum framework that describes the orientational order of rod-like molecules via symmetric, traceless matrices. Focusing on the Landau-de Gennes energy and its associated gradient flow, we consider a reduced two-dimensional formulation in which the Q-tensor is fully described by two scalar functions. This reduction simplifies the system to a nonlinear, coupled PDE for the scalars, while preserving essential physical features. A key question is whether the eigenvalues of the Q-tensor remain within the physically admissible range under this flow. Building on a theoretical result …

A Macrocognitive Design Taxonomy For Simulation-Based Training Systems: Bridging Cognitive Theory And Human-Computer Interaction, Jessica M. Johnson

Virginia Digital Maritime Center (VDMC) Faculty Publications

Simulation-based training systems are increasingly deployed to prepare learners for complex, safety-critical, and dynamic work environments. While advances in computing have enabled immersive and data-rich simulations, many systems remain optimized for procedural accuracy and surface-level task performance rather than the macrocognitive processes that underpin adaptive expertise. Macrocognition encompasses higher-order cognitive processes that are essential for performance transfer beyond controlled training conditions. When these processes are insufficiently supported, training systems risk fostering brittle strategies and negative training effects. This paper introduces a macrocognitive design taxonomy for simulation-based training systems derived from a large-scale meta-analysis examining the transfer of macrocognitive skills from …