Digital Commons Network^™

Mass Layoffs And Its Potential Security Risk, Riley M. Mcdonough

Cybersecurity Undergraduate Research Showcase

This research paper aims to understand the threats posed to the United States' protection of national security regarding the use of OSINT. This paper identifies the risks associated with displaying personal information, such as security clearances. Understanding the Potential national security risks that mass layoffs by Doge may cause. Examine how foreign actors exploit this information and how layoffs impact their efforts to recruit potential spies.

Detecting Generative-Ai-Enabled Polymorphic Malware: A Semantic-Behavior Approach, Allyson M. Morris

Cybersecurity Undergraduate Research Showcase

AI drastically reduces the effort required to produce malware that mutates both its code and behavior, thereby creating polymorphic and nondeterministic variants in which traditional signatures and many heuristic defenses fail. In this paper, I survey recent developments in AI-assisted malware generation, explain why conventional defenses are insufficient, and propose a layered detection architecture emphasizing semantic behavior, streaming anomaly detection, and defensive generative augmentation. I also outline why this approach generalizes to previously unseen AI-mutated samples, provide an evaluation plan with meaningful metrics, and describe a feasible MVP roadmap for practical deployment. Recent disclosures and threat intelligence further highlight the …

A Comprehensive Evaluation Of Next-Generation Firewall Effectiveness Against Encrypted And Evasive Threats In Enterprise Networks, John Costanzo, Favour Anene

Cybersecurity Undergraduate Research Showcase

Encrypted traffic is becoming a pillar of security and privacy in enterprise networks. According to Google Transparency Report, over 95 percent of internet traffic is encrypted with the use of Hypertext Transfer Protocol secure (HTTPS), Transport Layer Security (TLS) 1.3 and Quick UDP Internet Connections (QUIC). Although encryption safeguards confidentiality and integrity, it has also introduced new blind spots to the conventional security solutions. Encrypted channels are used to hide command-and-control (C2) traffic, issue malware and extract sensitive data without their notice.

To make the issue even harder, the opponents have sophisticated avoidance methods including traffic fragmentation, tunneling, and polymorphic …

Attributes Of Artificial Wetlands Colonized By Ambystoma Maculatum On A Virginia Surface Mine, Hunter Hill, Garrett Stiltner, Walter H. Smith

Virginia Journal of Science

Landscapes impacted by surface mineral extraction present a range of artificial wetland habitats potentially useable by pool-breeding amphibians, although little information exists in the literature detailing which attributes influence breeding site selection by wetland amphibian specialists in post-mined landscapes. We compared attributes of artificial wetlands consistently used and unused as oviposition sites by Spotted Salamanders (Ambystoma maculatum) over a six-year period on a 120-ha former surface mine in Wise County, Virginia, USA. Salamanders non-randomly selected wetlands as oviposition sites, with one-third of available wetlands within the study area showing evidence of ovipositioning. Wetlands used as breeding sites were …

Dissociation Of Subjective And Objective Measures Of Trust In Vehicle Automation: A Driving Simulator Study, Samuel Petkac, Tetsuya Sato, Kun Xie, Yusuke Yamani

Psychology Faculty Publications

Trust is a crucial factor that influences human-automation interaction in surface transportation. Previous research indicates that participants tend to display higher levels of subjective trust toward lower-level automated systems compared to high-level automated systems. However, administering subjective trust measures via questionnaires can interfere with primary task performance, limiting researchers' ability to measure trust continuously in a real-world manner. In the current driving simulator study, 25 drivers using an advanced driving system (ADS) were randomly assigned to either an active (L2) or passive (L3) automated driving condition. Participants experienced eight near-miss driving scenarios with or without obstructions in a distributed driving …

Novel Percutaneous Repair Of Femoral Pseudoaneurysms Using Perclose Proglide™: A Case Series, Ryan Mancoll, Emily Burnett, Nicholas Bandy, Benjamin Samberg, Thomas Cook, Jacob Hoffman, Christopher Murter, Matthew Rossi, David Dexter, Hosam El Sayed, Animesh Rathore Md

Cardiovascular Research Symposium

BACKGROUND - This case series details the novel use of the Perclose ProGlide closure device to successfully repair three separate cases of iatrogenic femoral pseudoaneurysms (PSAs) without attempting other modalities first. Conventional treatment methods of ultrasound-guided compression, duplex-directed thrombin injection (DDTI), or open surgical repair were contraindicated in these patients due to unique anatomy or advanced comorbidities.

METHODS – Details were gathered via a retrospective chart review.

RESULTS - In the first case, a 73-year-old female had an access site PSA off the superficial femoral artery (SFA) with concomitant arteriovenous fistula (AVF) and advanced cardiac disease. The ProGlide device was …

Sociohydrodynamics: Data-Driven Modeling Of Social Behavior, Daniel S. Seara, Jonathan Colen, Michel Fruchart, Yael Avni, David G. Martin, Vincenzo Vitelli

Data Science Faculty Publications

Living systems display complex behaviors driven by physical forces as well as decision-making. Hydrodynamic theories hold promise for simplified universal descriptions of socially generated collective behaviors. However, the construction of such theories is often divorced from the data they should describe. Here, we develop and apply a data-driven pipeline that links micromotives to macrobehavior by augmenting hydrodynamics with individual preferences that guide motion. We illustrate this pipeline on a case study of residential dynamics in the United States, for which census and sociological data are available. Guided by Census data, sociological surveys, and neural network analysis, we systematically assess standard …

Expectations In Instructional Design: A Comparison Of Hampton Roads Industry Requirements And Old Dominion University’S Curriculum, Haley Aguilar

STEMPS Master's Level Projects and Papers

This master’s thesis aims to analyze the alignment between Old Dominion University’s Instructional Design and Technology program curriculum and employer expectations for instructional designers in the Hampton Roads region. The study examined job listings from 50 positions and curriculum content from 22 courses across six skill categories: technical skills, design and development competencies, communication and facilitation skills, analysis and assessment skills, project management capabilities, and specialized skills. The findings contribute to understanding the challenges of preparing instructional design graduates for workforce entry.

Intersecting Realities And Evolving Landscapes: Mapping Generative Ai Within The Framework Of Digital Rhetoric, Joshua Troy Nieubuurt

English Theses & Dissertations

The increased usage of [Generative] AI technologies (GenAI) in the 21st century has called into the question the rhetorical agency of these digital things. [Gen]AI has historically been framed within a Heideggerian “readiness-to-hand” dynamic in which it has been unilaterally conceived as a tool to be used by humans. This dissertation proposes that the GenAI assemblage is capable of being a co-actor in rhetorical spaces. To provide evidence for this stance This dissertation utilizes Actor Network Theory to map the actants within a GenAI assemblage. In doing so it allows for an understanding of the stakeholders (both human and non-human) …

Enhancing The Design Of Strained Superlattice Gallium Arsenide Based Photocathodes With Distributed Bragg Reflector, Adam D. A. Masters

Electrical & Computer Engineering Theses & Dissertations

Particle accelerators play a crucial role in our understanding of matter and the universe and have numerous practical applications in various fields. These devices enable scientists to examine the smallest components of matter, study the forces that govern their interactions, and probe conditions from the early universe. Moreover, accelerators are valuable in medicine, industry, and research, enhancing imaging methods, cancer therapies, and manufacturing techniques. As the experiments conducted at these facilities evolve and require higher precision, improved particle sources must continue to advance to keep up with their requirements. To do that, we enhanced the design of spin polarized electron …

An Optimized Generalized Multi-Color Point Implicit Solver For Intel Gpus Using Intel Oneapis Esimd, Joseph Wassell

Computer Science Theses & Dissertations

The growing popularity of Computational Fluid Dynamics (CFD) simulations among engineers necessitates the use of GPU acceleration for increased efficiency. NASA FUN3D offers GPU accelerated CFD simulations using unstructured grids across the speed regime from incompressible to hypersonic flows involving reentry. This work focuses on the generalized multi-color point implicit solver used in FUN3D, accounting for roughly half of the run time. Specifically, this work focuses on developing three optimized multi-color linear-solver kernels for the Intel Data Center Max 1550 GPU that is available on the Argonne Leadership Computing Facility’s (ALCF) exascale machine, Aurora. These optimized kernels work for a …

Enhancing Data Usability For People With Visual Impairments, Yash Prakash

Computer Science Theses & Dissertations

Human-Data Interaction (HDI) focuses on how individuals engage with, analyze, and extract insights from data. For blind and visually impaired (BVI) users, interacting with data, whether searching for relevant information from structured data (e.g., web data items) or interpreting visualizations to draw insights (e.g., data charts), presents significant challenges. These challenges arise from the complexity and sheer volume of data which cannot be effectively handled by assistive technologies like screen readers and screen magnifiers. Despite its importance, data usability, the ease, efficiency, and satisfaction with which BVI individuals can interact with the data, has received less attention compared to data …

A Methodology For Model-Based Certification, Jay Albert Silverman

Engineering Management & Systems Engineering Theses & Dissertations

A need for a single source of knowledge for design decisions has led to the development of a new field of systems engineering, model-based systems engineering (MBSE) (Delligati, 2014). System certification is defined as affirming that regulatory requirements for a system have been met (Goodwin & Juzaitis, 2006). System certification is a specific application of system validation. System verification can be defined as ensuring that the system of interest (SOI), as designed, is in accordance with the design inputs/requirements. System validation can be defined as ensuring that the SOI, as designed, meets the defined system needs (Wolfgand, Katz, & Wheatcraft, …

Input Structure Based Optimization For Privacy Preserving Ai Systems, Feng Yizhou

Electrical & Computer Engineering Theses & Dissertations

As Artificial Intelligence (AI) systems become increasingly integrated into critical domains, ensuring privacy-preserving model design and system deployment has become a pressing priority. Safeguarding both sensitive user data and proprietary model parameters is critical throughout the AI model and system, from data acquisition and pre-processing to model inference and deployment. However, existing privacy-preserving frameworks face several limitations, including fragmented data ownership, incomplete protection across system stages, substantial computational overhead, and poor scalability to modern architectures such as large language models. This dissertation explores a unifying optimization strategy centered on input structure design to address these challenges. The core idea is …

Human Activity Recognition And Identification Driven Automated Deep Learning For Time-Series Classification, Justin Alan Gamble

Engineering Management & Systems Engineering Theses & Dissertations

The growing emphasis on Digital Engineering (DE) within the U.S. Department of Defense (DoD) demands advanced methods for leveraging vast time-series data generated by sensor-rich environments. Deep learning models offer promising solutions for complex timeseries classification tasks, however their design and optimization remain highly resource intensive, requiring specialized expertise. This dissertation addresses this challenge by developing and evaluating an Automated Machine Learning (AutoML) framework specifically tailored for the time-series classification task of Human Activity Recognition and Identification (HARI).

A systematic investigation was conducted using the Design Science Research Methodology (DSRM) comparing traditional search strategies of grid search and random search …

Unfolding Particle Detector Effects And Solving Qcd Inverse Problem With Generative Ai, Tareq Saeed Alghamdi

Computer Science Theses & Dissertations

Advancements in artificial intelligence (AI) have revolutionized high-energy physics by enabling generative models to address key detector-related Challenges. This work explores the generative model to mitigate smearing, acceptance, and inefficiency in particle detectors, enhancing experimental precision.

We present a generative model-based framework to model and correct detector distortions. Using the Jefferson Lab CLAS g11 experiment as a case study, our approach successfully unfolds detector effects in multi-particle final states while preserving multidimensional correlations despite complex reaction mechanisms. A key focus is addressing the acceptance problem—accurately modeling detector acceptance without computationally expensive simulations. By training generative model-based framework on simulated detector …

Effect Of Moderate Decrease In Contractility On Epithelial Cell-Cell Contacts Under External Stretch, Saika Sharmin

Mechanical & Aerospace Engineering Theses & Dissertations

Epithelial tissues are characterized by extensive cell–cell contacts and often subject to stretch during normal function. Cell-cell contact adhesion strength maintains mechanical continuity from cell to cell. Mechanical forces exerted by cells via actomyosin contractility are known to strengthen cell-cell adhesions to a certain extent. While it is known that a large decrease in contractility causes cell-cell contact rupture due to weakened adhesions, it is unclear how a moderate reduction in contractility affects cell-cell junction stability. Here, we studied how a moderate inhibition of non-muscle myosin II (NMII) affects the integrity of epithelial cell-cell contacts, especially when subject to the …

Systems Statistical Engineering – Hierarchical Fuzzy Constraint Propagation, Hengameh Fakhravar

Engineering Management & Systems Engineering Theses & Dissertations

Driven by the growing need in the 21st century for integrating rigorous statistical analysis into engineering research, there is a movement to develop an integrated statistical engineering science within statistics and quality communities (Hoerl & Snee, 2010; Anderson-Cook et al., 2012). Systems Statistical Engineering research seeks to integrate the Causal Bayesian hierarchical modeling (Pearl, 2009) and cybernetic control theory within Beer’s Viable System Model (1972, 1979, 1985) and the Complex Systems Governance framework (Keating, 2014; Keating & Katina, 2015, 2016) to produce multivariate systemic models for robust dynamic systems mission performance. Cotter & Quigley (2018) set forth the Bayesian systemic …

Examining The Impact Of A Utility Value Intervention On Self-Regulated Learning Engagement, Wanda D. Brooks

STEMPS Theses & Dissertations

The purpose of this study was to examine the impact of inserting a motivation intervention into a self-regulated learning training in an introductory biology course to increase academic performance and persistence to degree completion in science. The study was an experimental design with pre- and post-tests, with treatment and comparison groups. The training was in the form of three self-regulated learning cycles presented to students on a Blackboard Organization site where students were asked to record self-regulated learning activities in a journal during training. The primary aim of the intervention was to increase engagement in the self-regulated learning training by …

Valorizing Cement Kiln Dust And Glass Powder: A Binder Study On Sustainable Partial Cement Replacement, Sai Kiran Simhadri

Civil & Environmental Engineering Theses & Dissertations

The production of cement ranks as a major source of global CO₂ emissions because of the high energy requirements needed to create clinker. The construction industry is actively seeking ways to reduce its carbon footprint. Utilizing industrial waste materials to partially replace cement can lower emissions. This research evaluates a ternary binder system which uses Cement Kiln Dust (CKD) and Glass Powder (GP) to replace a portion of Type IL (Portland Limestone) cement. The mixes were made with a fixed water-to-binder ratio of 0.44 and contained 15% GP by mass while the CKD content ranged from 0% to 10%. The …

Effects Of Sediment Composition On Spartina Alterniflora And Juncus Roemerianus Productivity In Coastal Virginia: A Thin-Layer Sediment Placement Experiment, Caitlin Hemphill

Biological Sciences Theses & Dissertations

Climate change poses a major threat to the health of estuaries and their coastal wetland systems. The Chesapeake Bay’s coastal salt marshes are at high risk of inundation due to sea-level rise and land subsidence. Restoration techniques for maintaining coastal marsh resistance to sea-level rise are being developed and refined, with thin layer placement (TLP) emerging as a feasible solution in many areas of the United States. Despite TLPs use across the country, additional research is needed on species-specific responses, sediment types, and geographically focused studies in the lower Chesapeake Bay. My research addresses these gaps by combining both greenhouse …

A Strict Physicality-Preserving Scheme For A 2d Q-Tensor Flow With A Singular Potential, Md Mashud Parvez

Mathematics & Statistics Theses & Dissertations

Nematic liquid crystals are a state of matter that exhibit properties between those of conventional liquids and solid crystals. Their unique ability to align molecules in specific directions makes them essential in various applications, including display technologies and advanced materials. To model their complex behavior, mathematical frameworks such as the Q-tensor model are used to describe the orientation and degree of molecular order. In this work, we introduce a numerical scheme for a two-dimensional (2D) dynamic Q-tensor model, which is formulated as an L²-gradient flow driven by the liquid crystal free energy and incorporates a singular potential to …

Inter-Cellular Forces Modulate Cell-Ecm Traction Forces, Zaria Booth

Mechanical & Aerospace Engineering Theses & Dissertations

Epithelial cells are among the most abundant cell types in the human body, making up sheets of epithelial tissues that cover the linings of organs and body cavities. Cellular adhesion and force transmission across epithelial tissues are crucial in maintaining tissue integrity and ensuring proper tissue regeneration. Defects in cellular force transmission have been found in various diseases, including cancer. Force transmission at cell-cell and cell-ECM junctions drive cell survival and development. It has been previously shown that changes in cell-ECM traction directly modulates forces at cell-cell contacts. In this study, we aim to determine the effects of perturbations in …

Analysis On Plasma Propulsion Thruster Material Reconfiguration For Thrust Stabilization, Chinedumu Chidiebere Okafo

Mechanical & Aerospace Engineering Theses & Dissertations

Rocket propulsion has been a primary focus for scientific and technical advancement supporting space exploration. For long-duration, low-thrust space missions, propulsion systems designed with plasma energy as the primary source for generating thrust are of high interest. Plasma energy, like electric propulsion, involves the excited state of ionized atoms, where the ionized particles are separated and then act as a propellant to push a spacecraft in the intended direction for flight. Although more energy efficient compared to traditional rocket systems, plasma propulsion has the deficiency of consistent erosion of the metallic containment substrate, as plasma is being generated and released …

Enhancing Non-Visual Interaction With Online User-Generated Content, Mohan Krishna Sunkara

Computer Science Theses & Dissertations

The Web has become the dominant medium for our everyday activities, including communication, business, e-commerce, news, and entertainment. Consequently, the online world is experiencing an explosion of User-Generated Content (UGC), particularly on social media platforms and online review systems. To facilitate convenient interaction with UGC, web platforms have adopted various presentation strategies that enable users to efficiently browse and contribute to the UGC. However, these user interfaces are primarily designed for sighted individuals, so they do little to assist blind users who rely predominantly on audio-based screen reader assistive technology. The extant efforts to improve web interaction for blind users …

Analysis Of Multi Grade Deep Learning, Ronglong Fang

Mathematics & Statistics Theses & Dissertations

Multi-Grade Deep Learning (MGDL) is a training framework that incrementally builds deep neural networks. It does this by dividing the training process into multiple “grades,” where each grade sequentially trains a shallow neural network to learn the residue from the previous one, using the outputs of prior grades as input. This approach progresses from shallow to deep architectures. This dissertation offers a comprehensive theoretical and numerical analysis of the MGDL methodology.

We first demonstrate that MGDL can effectively learn target functions within the sum-composition learning format. In this context, MGDL approximates high-frequency components by composing multiple low-frequency functions. This unique …

Complex System Governance And Cyber Operations, Willie Gernard Mccallister

Engineering Management & Systems Engineering Theses & Dissertations

This dissertation examines the potential integration of Complex System Governance (CSG) within cybersecurity, emphasizing the development of a reference model for Cybersecurity Infrastructures. Traditional strategies for securing digital environments have struggled to address the intricate and dynamic layers inherent in modern cybersecurity systems. The purpose of this research is to explore the applicability of CSG as a framework to assess cybersecurity infrastructure using a case study research design. The research addresses two key questions: (1) How can the CSG reference model be adapted to explore cybersecurity infrastructure? (2) What results from CSG based exploration of cybersecurity infrastructure through a case …

Toward More Challenge-Engaging Stem Students: A Narrative Inquiry Into Student Persistence In The Face Of Failure, Stephanie R. Fahey

Educational Leadership & Workforce Development Theses & Dissertations

Science, Technology, Engineering, and Mathematics (STEM) postsecondary graduates greatly contribute to advances in technology and research, and STEM fields promise graduates careers with positive long-term outcomes. Many postsecondary students initially choose STEM majors; however, less than half of those students graduate with a STEM degree. High STEM attrition is a problem that continues to vex educators and researchers. One attributable factor to high STEM attrition is students adversely reacting to initial academic failure in challenging STEM educational contexts. However, there are a lack of studies that investigate the individual experiences of students who persist despite academic failure to better understand …

Computational Modeling For Automatic Superconducting Cavity Fault Prediction And Classification Using Time Series Signals, Md Monibor Rahman

Electrical & Computer Engineering Theses & Dissertations

Processing multivariate time series signals collected from sensor networks is challenging because of complex temporal dependencies and non-stationarity. With the advent of artificial intelligence (AI) like machine learning and deep learning, it has become possible to process sensor-driven time series data more effectively than traditional statistical methods.

This dissertation aims to develop machine learning and deep learning models to address machine fault diagnosis using multivariate time series signals collected from the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. The first goal of the proposed work is to develop deep learning–based classification models and an unsupervised fault clustering approach …

Two Analytic Issues Arising From Models In Probability And Materials Science, Giang Vu Thanh Nguyen

Mathematics & Statistics Theses & Dissertations

This dissertation explores two distinct topics centered on mathematical models in probability theory and materials science. The first part investigates a series of functions derived from an adaptive algorithm designed to address the score-based secretary problem, a classic challenge in probability theory. This problem involves making immediate decisions to select the best candidate from a sequence of interviews. The algorithm aims to maximize the probability of selecting the optimal candidate based on observed scores. We prove two fundamental analytic properties of this sequence of functions as a theoretic support of the algorithm: first, the functions in the sequence each possess …