Physical Sciences and Mathematics Commons^™

Improving Fairness On Semantic Segmentation Using Large Language Models, Samuel E. Burggraf

Electrical & Computer Engineering Projects for D. Eng. Degree

As machine learning systems are increasingly integrated into critical decision-making processes, ensuring fairness in their design and implementation has become a significant concern. While fairness research has primarily focused on specific protected attributes, less attention has been given to spatial fairness, which can affect individuals at specific locations. If fairness is not addressed, models may systematically underperform in certain regions or across populations which can lead to unequal access to accurate predictions and potentially biased decision-making. Fairness considerations should extend across all machine learning applications to align with the National Institute of Standards and Technology (NIST) guidelines of fair and …

Temperature-Induced Uncertainty In Fixed-Context Retrieval-Augmented Generation, Steven Zeng, Murat Kuzlu

Cybersecurity Undergraduate Research Showcase

This study examines how decoding temperature affects output uncertainty in a fixed-context retrieval-augmented generation (RAG) system. We define uncertainty as the semantic dispersion among repeated answers under the same fixed retrieved context, with greater dispersion interpreted as higher uncertainty. To isolate this answer-generation variability from retrieval drift, each question was paired with a fixed retrieved context, and repeated generations differed only in temperature. The experiment used nine questions drawn from a machine-learning textbook corpus, with three questions each at easy, moderate, and hard difficulty. Each question was evaluated at five temperatures (0.0, 0.25, 0.5, 0.75, and 1.0) over 30 iterations, …

Phishing Restraint: University Simulated Phishing Campaigns, Alexander M. Abou Khir

Cybersecurity Undergraduate Research Showcase

Universities face heightened vulnerability to phishing attacks due to their open information-sharing culture and diverse user populations. This study examines how phishing exploits human factors within campus environments and evaluates three major training strategies: embedded phishing, microlearning, and role-based instruction to understand their individual and combined effectiveness. I explored studies that implement these strategies in pairs and use the strategies alone, identified trends in susceptibility reduction, behavioral reinforcement, and contextual relevance. I suggest that, while each method independently improves user awareness, multiple approaches offer stronger, more adaptable protection by addressing both psychological triggers and role-specific risks. The paper contributes a …

Hijacking The Prompt: A Survey Of Prompt Injection Attacks, Detection, And Defense In Large Language Models, Edward J. Griggs

Cybersecurity Undergraduate Research Showcase

Prompt injection attacks, ranked the number-one vulnerability in AI systems by OWASP's 2025 Top 10 for Large Language Model Applications, remain largely unsolved, and this survey examines why. As large language models (LLMs) are deployed across enterprise workflows, agentic systems, and consumer tools, their fundamental inability to distinguish trusted instructions from untrusted user data has created a persistent and expanding attack surface. This paper presents a structured taxonomy of prompt injection attack vectors, including direct injection, indirect injection, multimodal attacks, tool and agent exploitation, hybrid chained techniques, and autonomous propagating threats. These vectors are mapped across five impact categories (data …

Limitations Of Signature-Based Network Intrusion Detection Under Modern Traffic Conditions, Henry Guidry

Cybersecurity Undergraduate Research Showcase

Network Intrusion Detection Systems are tools used to monitor network traffic and alert to suspicious or harmful activity before it can cause harm. Signature-based versions of these systems are a foundation for intrusion detection, operating by finding common patterns and forming malicious signatures. However, three developments in modern network environments have greatly impacted the significance of Network Intrusion Detection Systems. These three developments are the near-complete adoption of end-to-end encryption, the use of sophisticated packet fragmentation techniques, and the processing demands of high-throughput networks. Encryption makes deep packet inspection practically infeasible by transforming inspectable payloads into ciphertext, forcing NIDS to …

Artificial Intelligence Moderation In Online Gaming: A Cybersecurity Analysis Of Risks And Defenses, Labib Khan

Cybersecurity Undergraduate Research Showcase

This research paper will examine the role of artificial intelligence (AI) moderation systems in enhancing cybersecurity within online gaming environments. As multiplayer platforms increasingly rely on real-time text, voice communication, and user-generated content, developers have implemented AI-driven tools such as natural language processing (NLP), speech recognition, and behavioral analytics to detect harassment, toxic behavior, cheating coordination, and other malicious activity. These systems enable gaming companies to efficiently monitor large volumes of player interactions, improving response times and helping maintain safer and more controlled digital environments for users across global gaming communities of varying sizes and activity levels.

While these technologies …

Escaping Isolation: An Analysis Of Virtual Machine And Container Breakout Vulnerabilities, Felix Iov

Cybersecurity Undergraduate Research Showcase

Cloud computing providers rely on multi-tenant architectures to maximize resource efficiency. This infrastructure depends on virtualization, which provides isolation between clients. This comes primarily in the form of Virtual Machines (VMs) and Containers. However, “breakout attacks” or “escapes” are a critical threat where attackers bypass these isolation layers to gain unauthorized access to the host system and neighboring environments. This paper surveys virtualization escape threats and analyzes three case studies: a runc container escape (Leaky Vessels), a VMware ESXi VM escape (VSOCKPuppet), and an NVIDIA GPU container escape (NVIDIAScape). Each demonstrates different attack surfaces, including file descriptor misuse, kernel driver …

Bio-Cybersecurity: Securing The Healthcare Industry, Amanda D. Coleman

Cybersecurity Undergraduate Research Showcase

Bio-cybersecurity refers to the aspect of cybersecurity that applies to the biological sciences and the protection of digital biomedical information. Today’s healthcare industry has evolved with the enhancement of internet and biomedical technology. While hospitals and private medical providers remain compliant with the Health Information Portability and Accountability Act (HIPAA) through traditional means of securing documented patient information, the emergence of beneficial internet-based healthcare services like virtual appointments and digital patient records requires new policies and healthcare cybersecurity frameworks to protect sensitive information from unauthorized access. This paper examines the role of cybersecurity in healthcare, the vulnerabilities that exist and …

Ai's Double Edged Sword: Fighting Against Synthetic Csam, Shekhinah Adra Green

Cybersecurity Undergraduate Research Showcase

The rapid advancements in generative artificial intelligence has introduced new challenges in the production and distribution of synthetic child sexual abuse material (CSAM). AI has the capabilities of creating highly realistic imagery and videos, which  raises serious legal and ethical concerns, increasing the risk of harm, exploitation, and revictimization.

This paper discusses the legal improvements needed in order to lower the change of legal loopholes, how digital forensic analyst use advanced tools to identify and investigate synthetic material, and different methods to start the reduction of synthetic CSAM.

The Psychology Behind Ai-Generated Phishing And Social Engineering Attacks, A’Shya Reynolds

School of Cybersecurity Master's Level Projects and Papers

Cybercrime has evolved significantly with the integration of artificial intelligence (AI), transforming traditional phishing and social engineering attacks into highly sophisticated and personalized threats. While early phishing attempts relied on generic messaging and low success rates, modern AI-driven attacks leverage advanced data analytics, natural language processing, and behavioral prediction to manipulate victims more effectively.

This research examines how cybercriminals utilize AI to enhance psychological manipulation techniques in phishing and social engineering attacks, increasing victim susceptibility. Drawing from interdisciplinary literature in cybersecurity and psychology, this study explores key psychological mechanisms, including cognitive biases, emotional triggers, and decision-making processes that influence victim …

Enhancing Urban Garden Capacity By Linking Biodiversity And Ecosystem Function, Mary T. Nguyen, Carleen Rauh, Shelby Gresch, Charlotte Correiro, Heidi Elmendorf, Adriane Fugh-Berman, Gina Wimp, Alexandra L. Decandia

Virginia Journal of Science

Urban agriculture broadly describes food and plant cultivation in metropolitan areas. While biodiversity is thought to support ecosystem health and resilience, the relationship between above-ground and below-ground diversity has been understudied in urban green spaces. This study examines plant, animal, bacterial, and fungal diversity across three distinct urban habitats: a turf lawn, a forb garden, and a farming space. Using bacterial 16S rRNA and fungal ITS2 sequencing, soil nutrient analyses, and surveys of vegetation and wildlife, we connect diverse philosophies in urban agriculture to their role in advancing community diversity and ecosystem function. We found that different urban gardens support …

Optimization Of Niobium Film For Particle Accelerators And Quantum Applications, Bektur Abdisatarov

Electrical & Computer Engineering Theses & Dissertations

Niobium (Nb) films play a central role in superconducting technologies used in particle accelerators and superconducting quantum circuits. Optimizing the physical properties of Nb films is therefore critical for improving both radiofrequency (RF) performance in superconducting radiofrequency (SRF) cavities and coherence in superconducting qubits. This thesis investigates the relationship between Nb film microstructure, impurity content, and electromagnetic response across these two application domains.

For particle accelerator applications, we studied Nb films deposited using high-power impulse magnetron sputtering (HiPIMS) with DC bias onto a 1.3 GHz elliptical SRF cavity. Nb film cavities exhibit a pronounced medium-field Q-slope, limiting their achievable accelerating …

Radicals Transforming Organic Matter: Implications For Non-Pyrogenic Black Carbon And Nitrogen Formation, Molecular Dynamics In Tropical Soils, And Lignin Valorization, João Vitor Dos Santos

Chemistry & Biochemistry Theses & Dissertations

Radicals drive the transformation of organic matter in natural and engineered systems, altering its structure, reactivity, and stability. Condensed aromatic carbon (ConAC) and condensed aromatic nitrogen (ConAN) are among the most persistent forms of organic matter in soils and are traditionally interpreted as products of biomass burning. This dissertation challenges the long-standing assumption that these materials are exclusively pyrogenic, showing that iron-mediated radical chemistry can generate condensed aromatic structures under ambient conditions.

Chapters II and III show that Fenton-like radical oxidation of lignin-rich biomass produces condensed aromatic structures compositionally similar to pyrogenic black carbon and black nitrogen when assessed with …

Quantifying Nutrient Fluxes Across The Sediment-Water Interface In The Lafayette River Estuary, Adriana E. Amrhein

OES Theses and Dissertations

The Lafayette River, a shallow, eutrophic tributary of the Chesapeake Bay, experiences seasonal harmful algal blooms (HABs). While management efforts focus on reducing external nutrient inputs, internal loading from benthic sediments remains poorly constrained. This study quantifies spatial and seasonal variability in nutrient and radium isotope fluxes across the sediment–water interface at three sites where HABs are known to initiate and represent contrasting sediment textures and hydrodynamic conditions. Sediment cores and porewater samples were collected in summer 2023 and winter 2024 to measure grain size, porosity, dissolved nutrients (NH₄⁺, NOₓ⁻, PO₄³⁻), and radionuclide activities (²²⁴Ra and ²²⁸Th). Radium isotope disequilibrium …

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 …

Exclusive Neutral Pion Electroproduction Cross Section Measurements With A Neutral Particle Spectrometer, Mitchell R. Kerver

Physics Theses & Dissertations

Deep Virtual Compton Scattering (DVCS), the exclusive electron-proton scattering process ep →e′p′γ, provides access to generalized parton distributions (GPDs), which correlate informa tion about the longitudinal momentum and transverse spatial structure of quarks inside the nucleon. Experiment E12-13-010 in Hall C at Jefferson Lab was designed to take high-precision measure ments of the DVCS cross section over an extended kinematic range using the newly commis sioned Neutral Particle Spectrometer (NPS). The NPS features a high-resolution electromagnetic calorimeter and a streaming data acquisition system optimized for operation at high luminosities. This thesis presents the detector and analysis work carried out to …

A Study Of Short-Range Correlated Pair Formation Mechanisms, Noah S. Swan

Physics Theses & Dissertations

Short-Range Correlations (SRCs) refers to pairs of nucleons that are temporary high density fluctuations with high relative momenta and lower center-of-mass momenta com pared to the nuclear Fermi momentum (kF). SRCs account for 20–25% of the nucleons in medium to heavy nuclei, make up essentially all nucleons with momentum greater than kF, and contribute most of the kinetic energy carried by nucleons in nuclei.

The existing semi-inclusive and exclusive measurements only cover a handful of light nu clei or heavy elements. This does not allow for a systematic study of the dependence of SRC pairs on nuclear mass and proton-neutron …

Pushing High-Performance Private Inference Towards Resource-Constrained Edge Clients, Xiangrui Xu

Computer Science Theses & Dissertations

The widespread adoption of Machine Learning as a Service (MLaaS) has enabled resource constrained edge clients, such as mobile and IoT devices, to leverage powerful deep learning mod els hosted on the cloud. However, this paradigm introduces critical privacy challenges regarding the client’s sensitive input data and the server’s proprietary model parameters. While cryptographic techniques like Homomorphic Encryption (HE) and Multi-Party Computation (MPC) enable Private Inference (PI), existing frameworks impose prohibitive computational and communication overheads that render them impractical for edge deployment. This dissertation introduces three novel frameworks—SPOT, LUTless, and PrivShap—to systematically address the efficiency bottlenecks of PI in edge …

Observations Of An Oscillatory Mechanochemical Reaction Between Tetrathiafulvalene And Chloranilic Acid, Alastair Deans

Physics Theses & Dissertations

Mechanochemistry is the study of chemical reactions driven by the input of mechanical en ergy in addition to thermal activation. Mechanochemical reactions from powders are carried out by manual grinding or milling using various types of ball mills, or in twin extruders. While mechanochemistry has great potential affording economically and environmentally advantageous “green” synthetic methods, a drawback is that its chemical mechanisms are not well understood. One example of such a reaction currently under study involves tetrathiafulvalene, an organic elec tron donor with two polymorphs (orange and brown), and chloranilic acid, an electron acceptor. Previous results show that neat grinding …

Ultra-High Vacuum Outgassing Characterization Of Thermally Processed Low-Carbon Steel For Advanced Particle Accelerator And Gravitational Wave Detector Applications, Aiman H. Al-Allaq

Mechanical & Aerospace Engineering Theses & Dissertations

This dissertation investigated AISI 1020 low-carbon steel as an alternative vacuum chamber material to conventional stainless steel for ultra-high vacuum (UHV) and extreme-high vacuum (XHV) applications. After a 400 °C/48 h bake, AISI 1020 tube chambers achieved a hydrogen outgassing rate of 2.4 × 10⁻¹⁶ Torr·L·s⁻¹·cm⁻², approximately 2,300 times lower than the prebaked 316L stainless-steel comparator, among the lowest hydrogen outgassing rates ever reported for an uncoated metallic vacuum chamber. Bare and magnetite-coated AISI 1020 chambers were then compared using throughput and rate-of-rise methods. The magnetite coating yielded 5× lower water outgassing at room temperature, but this advantage disappeared after …

Downstream Effects Of Post Aerobic Digestion And Divalent Cation Treatment: Dewaterability, Phosphorus Mitigation, And Process Odors, Maya Marisol Quijano Garcia

Civil & Environmental Engineering Theses & Dissertations

This study evaluated post-aerobic digestion (PAD) with aeration, mixing, and divalent cation addition to improve phosphorus capture, dewaterability, and odor control in thermal hydrolysis process (THP)–treated anaerobic digestate at the Hampton Roads Sanitation District’s Atlantic Treatment Plant. A three-day PAD process was operated under constant air flow (5 LPM) and dissolved oxygen (DO)-setpoint (0.2 mg/L) aeration conditions with Ca(OH)₂ or Mg(OH)₂ dosing. Aeration and mixing alone increased polymer demand by 14–46 % relative to untreated influent, indicating enhanced extracellular polymeric substance release. Chemical conditioning partially mitigated this increase but did not restore polymer demand to baseline levels. Dewatered cake total …

Dissecting The Etiology Of Alcohol Use Disorder By An Integrative Heritable Component Approach, Ivy Garrenton

Computer Science Theses & Dissertations

Alcohol Use Disorder (AUD) is a pervasive condition characterized by complex interplay among genetic, phenotypic, and environmental factors. Although previous studies have identi fied genetic loci associated with alcohol consumption, these efforts have not captured the genetic heterogeneity and gene-environment interactions underlying AUD pathogenesis. To address this critical gap, we developed a novel statistical methodology that integrates phenotypic, genotypic, and environmental data through an environmentally modified Genetic Relationship Matrix (GRM) to derive AUD-related traits with enhanced heritability.

This approach demonstrated superior performance in both simulated and real-world datasets. Traits derived using the environmentally modified GRM exhibited significantly higher estimated heritability …

Learning Techniques In Prediction Of Functional Epigenomic Events, Mohammad Shiri

Computer Science Theses & Dissertations

Accurately predicting functional epigenomic events from DNA sequences is critical to understanding gene regulation and the functional impact of non-coding variants. Despite considerable progress, critical challenges hamper the effectiveness and efficiency of existing deep learning approaches. These challenges include negative transfer in multi-task learning (MTL), suboptimal network architectures, and pervasive label noise, particularly the positive-unlabeled problem arising from data sparsity in single-cell assays. This dissertation presents a cohesive framework of novel learning techniques to effectively address these challenges. First, a highly scalable task grouping framework is presented to mitigate negative transfer in deep MTL. This method clusters tasks based on …

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 …

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 …

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.