Digital Commons Network^™

Deep Multimodal Sensor Fusion For Autonomous Driving: A Real-World Deployment On Little Blue, Raphael T. Pamie-George

Electrical & Computer Engineering Theses & Dissertations

Accurate perception and control systems are essential for autonomous vehicles to safely interpret and navigate complex environments. Individual sensing modalities such as cameras, LiDAR, and inertial measurement units (IMUs) provide valuable environmental and vehicle state information; however, each sensor exhibits inherent limitations when used independently. Camera performance can degrade under varying lighting conditions, LiDAR measurements may be sparse or affected by environmental noise, and IMU measurements are susceptible to drift over time. Little Blue, a research autonomous vehicle platform from ODU (Old Dominion University), previously relied primarily on camera-based data for neural network training, limiting the system’s ability to exploit …

Exploring The Determinants Of User Discontinuance In Ai-Driven Usage-Based Insurance, Wenzhuo Li

Theses and Dissertations in Business Administration

While interest in algorithmic decision-making continues to grow, limited research has examined the post-adoption phase. This study examines how users evaluate their post-adoption experiences with algorithmic decision-making in the context of usage-based insurance (UBI), focusing on how expectation disconfirmation shapes satisfaction and the intention to discontinue use. It explores two key questions: What factors influence users’ discontinuance intention toward AI-based UBI systems? And how do specific algorithmic characteristics alter how users form these post-adoption evaluations? To investigate these questions, this study develops a comprehensive theoretical model that integrates the Expectation Confirmation Model and Reactance Theory, incorporating additional factors such as …

Individual Differences In Generative Ai Effectiveness: An Empirical Puzzle For Hrd Research, Nolan C. Lovett

Educational Leadership & Workforce Development Faculty Publications

Professionals with similar backgrounds, given identical generative AI tools, achieve sharply different outcomes. This perspectives piece examines what explains that variance, reviewing evidence on cognitive capacity, domain expertise, metacognition, epistemic calibration, personality, and culture, and argues that existing user typologies describe these differences without predicting their consequences. It then extends the puzzle in a direction the static account misses: the same individual differences that shape AI effectiveness are themselves reshaped by sustained AI use, as cognitive offloading, deskilling, and upskilling inhibition operate differently across the expertise distribution. Recent evidence, including deskilling among experienced clinicians and suppressed learning among students using …

The Tragedy Of The Cognitive Commons: How Ai Could Disrupt The Regeneration Of Professional Expertise, Nolan C. Lovett

Educational Leadership & Workforce Development Faculty Publications

Artificial intelligence is reshaping cognitive work, but Human Resource Development scholarship has treated this transformation as an organizational training challenge, leaving the collective regeneration of professional expertise unexamined. This conceptual paper introduces the Cognitive Commons framework, integrating commons theory, HRD scholarship, and distributed cognition to explain how rational AI adoption decisions can deplete the shared expertise pool professions require for renewal. The framework distinguishes Internalized Mastery (deep domain knowledge from sustained practice) from Distributed Mastery (orchestrating human-AI systems), and develops the Validation Tether: effective AI oversight depends on the expertise AI adoption may undermine. Early labor market and clinical evidence …

Building Adaptive Leaders: Examining The Relationship Between Undergraduate Co-Curricular Leadership Roles, Change Readiness, And Leadership Self-Efficacy, Reneldo N. Randall

Educational Leadership & Workforce Development Theses & Dissertations

The contemporary workforce is characterized by ongoing organizational change, requiring individuals to demonstrate adaptability and the capacity to lead within evolving conditions. Institutions of higher education increasingly emphasize leadership development as a mechanism for preparing students for these demands; however, limited empirical research has examined how participation in formal co-curricular undergraduate leadership roles relates to students’ readiness to engage with organizational change. This study addresses the gap by examining the relationship between leadership self-efficacy and resistance to change among undergraduate student leaders.

Guided by the Leadership Identity Development (LID) model, this quantitative study employed a non-experimental, correlational design. Data were …

Career Pathways Program Annual Report For Ay 2025/26, Wie Yusuf

Career Pathways

Career Pathways launched in August 2017 as the university-wide initiative to provide career and professional development to graduate students. It encompasses both the Preparing Future Faculty (PFF) and the Preparing Future Professionals (PFP) Certificates. The Preparing Future Faculty Certificate was established in 2007, while the Preparing Future Professionals Certificate was launched in 2017, concurrently with the introduction of Career Pathways. The Career Pathways program prepares graduate students for a successful transition into thriving careers. With the PFP Certificate, the emphasis has been on addressing the existing gap in career and professional development for master’s and doctoral students with career plans …

Check Before You Trust: Teaching K–12 Students To Evaluate Digital Information, Elexia Hertel

Resources for Educators

[First paragraph]

Students in K–12 schools encounter digital information every day, but they are not always prepared to decide whether that information is credible, useful, biased, incomplete, or misleading. This chapter is written specifically for K–12 school library and classroom instruction, not for academic library users or college-level research instruction. Its primary audience is upper elementary, middle school, and early high school learners who are beginning to conduct research, cite sources, compare online information, and participate in digital life.

Advancing Imbalanced Classification Through Representation Learning, Morteza Mohammady Gharasuie

Computer Science Theses & Dissertations

Real-world datasets frequently exhibit severe class imbalance, where certain categories are significantly underrepresented relative to others, leading standard empirical risk minimization to bias learning toward majority classes and degrade performance on minority categories. This dissertation addresses imbalanced classification across both structured tabular data and long-tailed visual recognition by developing methods that improve representation learning and decision reliability under skewed distributions. For tabular data, it introduces Conditional Probability Representation (CPR), a target-based encoding framework that embeds feature–label relationships directly into the representation space, enhanced by a progressive feature upgrading mechanism for semi-supervised settings and a class-frequency–aware extension that improves robustness to …

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 …

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 …

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 …

Landscaping Of Mcp: An Overview Of Mcp Mitigations And Tools, Arden Michel

Cybersecurity Undergraduate Research Showcase

The Model Context Protocol (MCP) has quickly become the standard for enabling agentic AI systems to interact with external tools, data sources, and services. Since its debut in 2024, MCP has been adopted by companies such as Google, Apple, Meta, and IBM. While this integration greatly improves the capabilities of large language models (LLMs), it also creates a new attack surface that the security community is only beginning to understand systematically.

A key architectural challenge is MCP's fundamental reliance on implicit trust: servers often run locally with high privileges, tool descriptions are accepted without question, and external servers are presumed …

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 …

Security Risks Of Ai-Generated Code In Software Development, Maame Agyekum

Cybersecurity Undergraduate Research Showcase

Artificial Intelligence(AI) has recently forced change globally, public Institutions and as well as national security. Advancement in machine learning, mixed datasets have enabled significantly powerful systems while being capable of operating at a large scale. As innovation and technological advancement increases at rapid pace, issues like a regulation gap where scientific development far exceeds the government’s ability to regulate and establish an effective oversight. As a result, Artificial Intelligence has been controlled by private companies, leading to an industry where speed and profit often outweigh safety and ethical responsibility.

Program: Virginia Academy Of Science 104th Annual Meeting, 2026, Virginia Academy Of Science

Virginia Journal of Science

Full program of the 104th Annual Meeting of the Virginia Academy of Science. Held at  Christopher Newport University, Newport News, Virginia on May 28, 2026.

Proceedings Of The 104th Annual Virginia Academy Of Science Meeting, 2026, Virginia Academy Of Science

Virginia Journal of Science

Proceedings (abstracts) of the 104th Annual Meeting of the Virginia Academy of Science, May 28, 2026, at Christopher Newport University, in Newport News, Virginia.

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 …

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 …

Development Of A Benchmark Building Condition Index Utilizing Discrete Facility Subsets For Use In Risk Prioritization Analysis, Christopher A. May

Engineering Management & Systems Engineering Theses & Dissertations

Within the healthcare facilities management arena, key performance-based condition indices such as a calculated Building Condition Index (BCI) are currently utilized as a governing indicator of facility health and performance. However, BCI alone does not adequately support enterprise-level risk prioritization and fails to provide a validated facility-to-facility risk prioritization model. Assets within the same enterprise receiving similar sustainment funding experience different rates of degradation depending on asset type and construction age thus impairing the BCI rating scale. Statistical analysis of facility metrics indicates a strong correlation between facility degradation drivers and prediction of a subset-based benchmark BCI. The research validates …

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 …

Effects Of Cross-Language Instructional Design On Foreign Language Learners' Cognitive Load: Approaching The Redundancy Principle Of Multimedia Learning, Leonor Mendiola Adams

STEMPS Theses & Dissertations

Because conceptualizations of cognitive resources play a critical role in determining the effectiveness of instructional design (Greeno, 2011; Greeno et al., 1996; Mayer, 2011, 2019), this study explores the effects of cross-language instructional design on learners’ perceived intrinsic, extraneous, and germane cognitive load content corresponding to content complexity, instructional presentation demands, and depth of understanding and schema construction, respectively.

Grounded in the redundancy principle of the Cognitive Theory of Multimedia Learning, this research further investigates whether the principle operates differently when learners’ native language is strategically incorporated into foreign language learning contexts. According to the cognitive theory of multimedia learning, …

Education And Training In Water Operator Certification And Its Role In Water Utility System Performance, Heath A. Edelman

Educational Leadership & Workforce Development Theses & Dissertations

Access to safe and reliable drinking water is a foundational component of public health and environmental protection. The United States drinking water sector is highly regulated and increasingly challenged by workforce shortages, aging infrastructure, and variability in operator training requirements across states. Despite the federal mandate for operator certification under the Safe Drinking Water Act Amendments of 1996, empirical evidence on the effectiveness of certification policies in improving regulatory compliance outcomes remains limited.

This study examined the relationship between operator certification policies and drinking water compliance outcomes under the Safe Drinking Water Act, with particular attention to differences across violation …

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. …

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 …

Exploring System Wide Trust And Dependency Behavior Within An Aviation Environment, Austin Jackson

Psychology Theses & Dissertations

The present study examined the theory of system-wide trust within the context of a multi-tasking aviation environment. Previous research suggested that unreliable automation can negatively affect a human operator’s trust in reliable automation within the same system (Rice & Geels-Blair, 2010). However, previous studies have not looked at how trust develops in the context of a multi-tasking environment, nor how different types of errors may affect trust in and the use behavior of automation. The current study employed a 2 x 2 mixed design with drone reliability (60% reliable vs 90% reliable) and error bias (false alarm vs. miss errors) …