Physical Sciences and Mathematics Commons^™

Augmenting Deep Learning For Efficient Nextg Wireless Communication And Sensing Systems, Hem Kanta Regmi

Theses and Dissertations

Wireless networks have become an integral aspect of our daily lives. Over the years, earlier generations of wireless networks have enabled some innovative applications, such as wireless gaming, fast internet browsing, and home automation, which were previously unattainable. However, to support emerging technologies like autonomous driving, virtual reality, telemedicine, and intelligent manufacturing, which require high data throughput and low latency, there is a need for advanced wireless networks. Legacy networks like WiFi/LTE, which operate below 6 GHz, have limited bandwidth and are insufficient to fulfill the high data throughput demands of several applications. Millimeter-wave (mmWave) networks, operating between 30 GHz …

Building Trustable Methods For Group Recommendations: Advancing Fairness And Robustness Across Domains, Siva Likitha Valluru

Theses and Dissertations

On the internet, where the number of available choices for information is exponentially growing, there is a need to prioritize and deliver relevant results to users efficiently, on demand. Recommendation systems (RSs) address that need by searching through and filtering large amounts of dynamically generated information and providing users with recommendations tailored to them. These systems have primarily focused on (1) single-user models, where recommendations are tailored towards a specific individual, or (2) single-item models, where items are recommended based on a broader appeal to users and similarities in item metadata, in the past. In many real-world scenarios, however, recommendation …

Towards Connecting Requirements With Developer Artifacts In A Local Context: Supplemental Material, Sonora Halili, Karenna Kung, Paola Spoletini, Alicia M. Grubb

Computer Science: Faculty Publications

Supplemental material for the paper: "Towards Connecting Requirements with Developer Artifacts in a Local Context"

A Study Of Conceptual Primitive Elimination: Embedding Ingest Into Ptrans, Jamie C. Macbeth, Alexis Kilayko

Computer Science: Faculty Publications

In cognitive systems and cognitive linguistics, primitive decomposition systems attempt to explain cognitive phenomena by breaking things down into conceptual building blocks and provide rich and flexible representations for systems. A prime example is the Schank–Minsky Conceptual Dependency Trans-frames system, which maintains a commitment to keeping the number of primitives small and allowing them to be combined in complex ways in representing meaning, knowledge, and dynamic episodic memory. Motivated by the desire to keep the set of primitives small, this paper describes an effort to eliminate the Conceptual Dependency INGEST primitive and reconstitute its uses through combinations of the CD …

Neural Network-Based Low-Level 3d Point Cloud Processing, Pingping Cai

Theses and Dissertations

3D computer vision is a promising research field with the potential to revolutionize future lifestyles. Among various 3D representation formats, point clouds stand out for their efficiency in depicting 3D objects using a set of coordinates, enabling advancements in fields such as autonomous driving, virtual reality, and robotics. Due to the limitations of sensor fields of view and scanning trajectories, the collected point clouds are usually sparse, noisy, and incomplete, impeding the performance of many downstream applications. Thus, the tasks of low-level point cloud processing are proposed to refine and generate dense, clean, and complete point clouds. To accomplish these …

Toward A Global Roadmap: An Analysis Of National Strategies Toward Digital Education Improvements Across Southeast Asia And Southern Africa, Z Alexandra Anderson

Computer Science Undergraduate Theses

The rapid global expansion of digital technologies has created significant opportunities to transform education systems, foster innovation, and reduce inequalities. However, access to and benefits from these technologies remain unevenly distributed, shaped by differences in infrastructure, human capital, governance structures, and economic development. This thesis investigates how systemic approaches to digital education in Cambodia, Thailand, Myanmar, South Africa, Botswana, and Zimbabwe can inform a more inclusive and adaptive global roadmap for digital transformation in education.

Adopting a mixed-methods design, this study combines a comparative quantitative analysis of the CISCO Digital Readiness Index (DRI) with a qualitative content analysis of national …

Causal Models For Realistic Cognitive Reinforcement, Vivek Dhingra, Brandon Bazile, Andrew Forney

Computer Science Undergraduate Theses

Modeling complex hierarchical decision systems can be used for predicting the effects of policy changes before their enactment, such as understanding how new laws might influence students within an educational system. However, understanding the effects of policies on individuals versus populations requires a structured assertion of the system’s causal dynamics. As such, we propose a novel reinforcement learning framework that integrates causal modeling to optimize decision-making in multi-agent environments, like schools. The causal model captures relationships between these levels, providing agents with a structured understanding of how their actions propagate through the system. Compared to traditional reinforcement learning methods, our …

Extending Feature-Based Detection For Artificial Intelligence, Kayla Ahrndt

SPARK Symposium Presentations

AI text generation is rapidly developing, and, as a result, it is becoming increasingly difficult to differentiate it from human written text. Our base study by Leon Fröhling et al. proposed a feature-based detection model trained on GPT2, GPT3, and Grover data, as well as human-generated text. Our work extends their research by training a modified model with four neural networks on word embeddings, select features from the original study, as well as updated data (GPT3, GPT4, and Grover).

How The Biotic And Abiotic Factors In The Belle Forest Cave And Arboretum Soil Dictates Tree Species Prevalence, Amya A. Bingham

SPARK Symposium Presentations

A plethora of factors in the soil impact a plant’s health, including the presence of different biotic and abiotic factors. These include things like temperature, elevation, pH, microbial respiration and the presence of water, clay, loam, silt, sand, nitrogen, potassium, and phosphorus. Different soils will have varying amounts of these, which may dictate what is able to grow in them, and therefore also the surrounding area. This research project explores how the aforementioned biotic and abiotic factors affect the soil at the Belle Forest Cave and Arboretum. Three samples will be taken from four spots along a transect at this …

"Data Science For Digital Privacy: A Practical Guide For Non-Technical Audiences", Kayla Ahrndt

SPARK Symposium Presentations

As companies increasingly rely on consumer data for personalization and profit, the need for stronger user protections, security measures, and transparency in data practices grows. Legal frameworks must be continuously re-evaluated and updated to ensure accountability, while individuals must be equipped with the knowledge to make informed decisions about their digital presence. However, personal data privacy education remains widely inaccessible due to the technical language and the effort required to navigate complex policies. This project, presented in both zine and blog formats, addresses this gap by providing clear, actionable, and accessible recommendations for data privacy and personal cybersecurity. As an …

Investigating Mercury Contamination In Urban Fish: Atomic Absorption Spectroscopy And Histological Analysis For Environmental And Human Health, Indy L. Cockrill, Ross Andrew

SPARK Symposium Presentations

Mercury contamination in aquatic ecosystems is a pressing environmental and public health concern, particularly in urban areas where industrial runoff and wastewater contribute to heavy metal accumulation. This study investigates mercury presence in fish from Richland Creek in Nashville, TN, by analyzing histological changes in liver and muscle tissues. Mercury bioaccumulates in aquatic food chains, potentially leading to physiological damage in fish and posing health risks to humans who consume contaminated seafood. While prior research has established mercury’s toxic effects, there is a need for localized studies assessing its presence in urban waterways. The hope is to find histological abnormalities …

Moviequeue: Leveraging Graph Databases To Build Recommender Systems, Ryan C. Juricic

SPARK Symposium Presentations

In the era of abundant streaming content, viewers often face choice overload and inefficient recommendation systems limited to isolated platforms. MovieQueue is a graph-based, cross-platform movie recommender system built on a Neo4j knowledge graph and integrated with an interactive Streamlit application. Leveraging both user-specific ratings and extensive movie metadata — including genres, cast, crew, runtime, release year, and audience engagement — the system provides tailored recommendations grounded in content similarity and social context. Users receive recommendations not only based on genre overlap but also through shared actors, directors, and composers with previously highly-rated films, alongside filters for explicit genre selection. …

Patterns Within The Collatz Conjecture, Kiel Harrison

SACAD: Scholarly Activities

The Collatz Conjecture, also known as 3n+1, one of the most famous unsolved problems in mathematics, has been forever out of reach of being truly solved. However, through the application of traces, there is now a new pathway forward to working out a potential solution. This study shows how this pathway was found, and what steps need to be taken to follow it.

Draft Final 2024 Bpsou Subdrain Data Summary Report (Dsr), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Microbial Distortion? Impacts Of Delayed Preservation On Microbiome Diversity And Composition In A Marine Invertebrate, Brenna Hutchings, Susanna López-Legentil, Lauren Stefaniak, Marie Nydam, Patrick M. Erwin

Marine Science

Field collections of marine invertebrates are often accompanied by delays in preservation, which may impact microbiome composition. Here, we tested the effects of delayed preservation and relaxation methods on microbiome diversity and composition in the colonial ascidian Trididemnum solidum using 16S rRNA amplicon sequencing. Replicate samples collected from Belizean reefs were either (1) immediately preserved in ethanol (“control”), (2) held in ambient seawater for 3 h before preservation (“SW”), or (3) held in ambient seawater with menthol (a common pre-preservation relaxation technique for ascidian identification) for 3 h before preservation (“SW + M”). All T. solidum microbiomes were different from …

Estimating Climate Risk In Financial Markets, Olanrewaju Oluwadamilare Olaniyan

Masters Theses

The growing impact of climate change on financial markets necessitates a rigorous approach to climate risk assessment. This thesis examines methods for quantifying climate-related financial risks, with a focus on distinguishing climate risk from broader market movements (represented by S&P 500). Using a factor model, we isolate climate risk factors to better understand sector-specific volatility. The insurance sector is used as a proxy for climate risk exposure, given its sensitivity to climate-related losses and regulatory changes. We apply Extreme Value Theory (EVT); the Block Maxima Method and the Peaks Over Threshold Method, to identify excess risk patterns in financial portfolios. …

A Study Of Preconditions And Postconditions As Design Constraints For Llm Code Generation, Luke Newcomb

Doctoral Dissertations and Master's Theses

Large Language Models (LLMs) have significantly advanced automated code generation, but current methods predominantly rely on natural language descriptions. This approach encounters challenges when handling complex, class-level software generation tasks due to inherent ambiguity and under-specification. Few studies have investigated how more formal software engineering constraints, such as explicit preconditions and postconditions, influence class-level generation tasks. This work addresses this gap through a structured evaluation of six state-of-the-art LLMs generating software implementations from systematically designed class-level specifications. Results demonstrate that incorporating explicit design constraints significantly boosts initial generation accuracy (measured via the pass@k metric), particularly in Python but also in …

Discovery And Synthesis Of Novel, Porous Organic Cages Via Dynamic Imine Chemistry In Continuous Flow, Anzhi (Andy) Chen , '25

Senior Theses, Projects, and Awards

In recent years, Porous Organic Cages (POCs) have gained widespread research interest owing to the well-defined porosity and solution dispersity, which have given rise to various applications, such as molecular encapsulation and catalysis. A common synthetic strategy for POCs, Dynamic Covalent Chemistry (DCvC) exploits the reversibility of certain covalent reactions and allows for facile discovery and synthesis of well-defined macromolecules through error-correction mechanisms. Thermodynamic effects of DCvC systems have been widely studied via structure-focused strategies along with empirical methods. More recently, researchers have begun to incorporate kinetic factors in DCvC systems to discover and synthesise new macromolecular structures. However, thermodynamic …

From Image Enhancement To Model Protection Integrating Generative Ai And Secure Learning In Computer Vision, Mohammad Shahab Uddin

Electrical & Computer Engineering Theses & Dissertations

This dissertation aims to address critical challenges in the field of computer vision and machine learning, focusing on three key areas: image translation, denoising, and model security. The research encompasses novel methodologies and models that significantly advance existing techniques. This dissertation will not only provide valuable contributions to the academic community but also hold significant potential for practical applications in domains ranging from surveillance to autonomous systems.

Consequently, this dissertation proposes three goals. First, we present new approaches for converting optical videos to infrared videos using deep learning. To apply powerful deep learning based algorithms for object detection and classification …

Enhancing Iot Security Using Lightweight Machine Learning Algorithms: A Comprehensive Approach Using Ensemble Learning, Feature Selection, And Federated Transfer Learning, Khawlah Harahsheh

Electrical & Computer Engineering Theses & Dissertations

The rapid expansion of the Internet of Things (IoT) has introduced significant security vulnerabilities due to the resource-constrained nature of IoT devices and their exposure to cyber threats. Traditional security solutions are often infeasible due to the high computational and storage demands they impose. This dissertation presents a lightweight, AI-driven security framework that enhances IoT network resilience by integrating feature selection, ensemble learning, and federated transfer learning while maintaining data privacy and minimizing computational overhead.

The proposed framework consists of three primary components: Feature Selection for Intrusion Detection, which optimizes performance by reducing redundant data and improving detection accuracy with …

The Impact Of Drought And Socio-Economic Factors On Attitudes Toward Immigrants In South Africa, Pamela Antwi-Nimarko

Graduate Program in International Studies Theses & Dissertations

Estimates of the global migrant population have steadily increased, with current data from the International Organization for Migration (IOM) reporting approximately 281 million migrants worldwide. Alongside this growth, anti-immigrant sentiments have risen in many host countries. This study seeks to contribute to the research on attitudes toward immigrants by exploring climate-related factors, particularly drought, as a key influence.

Leveraging a unique dataset combining the World Values Survey (WVS) and Afrobarometer, the study examines how drought, along with individual and contextual factors, affects attitudes toward immigrants. This dataset allows for an in-depth analysis of the direct impact of drought on public …

Nanosecond Pulsed Electric Field And Plasma Jets For Cancer Therapy, Edwin Ayobami Oshin

Biomedical Engineering Theses & Dissertations

Nanosecond pulsed electric field (nsPEF) employs nanosecond-duration, high voltage pulses to induce oxidative stress, leading to temporary or permanent damage to cells or tissue (also known as reversible and irreversible electroporation), and has been considered a promising approach for cancer therapy. In parallel to this, nanosecond pulsed atmospheric pressure plasma jets (ns-APPJs) have also shown to be effective in inactivating cancer cells or increasing sensitivity of cells to electric fields. ns-APPJs are known to generate reactive chemical agents, including reactive oxygen and nitrogen species (RONS) which induces oxidative stress resulting in cell proliferation, apoptosis, and necrosis. In this dissertation, a …

Integrating Computational Thinking Into K–12 Classroom Instruction, Jorge Valenzuela

STEMPS Theses & Dissertations

In 2016, legislation mandated the integration of computer science (CS) and computational thinking (CT) skills across K–12 instruction in the Commonwealth of Virginia. CT integration is also a focus in many schools throughout the United States. Educators must understand CT/CS core concepts and practices, looking for practical ways to integrate CT across the K–12 curricula. To address this, the current study was conducted. The study compares the effects of the Jigsaw technique and teacher-directed instruction on the participants by surveying their self-efficacy for integrating CT in their teaching. This study uses a pre- and post-test design, and data collection took …

Mechanochemical Reaction Kinetics—A Theoretical Modeling And Experimental Study, Maria Dolores Masso Ramirez

Mechanical & Aerospace Engineering Theses & Dissertations

Mechanochemical reactions represent a class of chemical processes triggered by mechanical energy, widely recognized for their efficiency, solvent-free nature, and environmental benefits. They are increasingly applied in synthetic chemistry, a branch of science focused on creating new chemical compounds through controlled laboratory reactions. However, the mechanisms underlying mechanical activation remain poorly understood, primarily due to the difficulty in quantifying energy transfer during milling, where solid reactants are ground together using a ball mill. This thesis aims to bridge the gap in understanding the relationship between mechanical parameters and reaction kinetics by developing and validating a theoretical framework based on dimensional …

Stability Analysis In The Twist-Bend Nematic Liquid Crystal Model, Zhenqiang Li

Mathematics & Statistics Theses & Dissertations

The recently discovered twist-bend nematic liquid crystal (LC) phase is characterized by a nanoscale helical modulation of the nematic director n, forming a conical helix along the z-axis at an oblique angle θ. While many models assume a constant cone angle and equal elastic constants K11 = K22 = K33, this dissertation removes both assumptions by considering a fully anisotropic elastic energy with K11 ≠ K22 ≠ K33, and allowing θ to vary spatially. We analyze the stability of this system under frustrated and free boundary conditions using variational methods. …

Low Dissolved Oxygen Operation Enhances Biological Phosphorus Removal In Wastewater Treatment, Haley Morgan

Civil & Environmental Engineering Theses & Dissertations

Biological phosphorus (bio-P) removal occurs when bacteria are exposed to anaerobic/aerobic conditions that stimulate polyphosphate-accumulating organisms (PAOs) to uptake phosphorus. In most treatment plants, dissolved oxygen (DO) concentrations in the aeration tanks are commonly at or above 2.0 mg O₂/L, which is often referred to as the most optimal aeration condition for bio-P. If bio-P can happen efficiently at lower DO (< 0.3 mg O₂/L), then the energy demand of aeration can be decreased appreciably. This research was conducted in a biological nutrient removal (BNR) pilot plant to assess the performance of bio-P at progressively lower DO operation. This …

A Data-Driven Recommendation System For Selecting The Appropriate Mode Of Learning And Instructional Tools Based On Course Characteristics, Ayisha Manzoor

Theses

The rapid transformation of educational delivery methods during the COVID-19 pandemic required institutions to transition between online, hybrid, and offline learning approaches, creating both challenges and opportunities for educators and students. While online and hybrid learning modes ensured continuity, their effectiveness across different course types remained uncertain. This thesis addresses this gap by developing a datadriven recommendation framework that predicts Course Learning Outcome (CLO) achievement scores using regression, and recommends the most appropriate learning mode (online, hybrid, or offline) along with instructional tools based on course characteristics. This study analyzed 100 undergraduate and postgraduate courses from the College of Information …

Assessing Readiness For Transformation From Rulebased To Ai-Based Chatbot In Uae Healthcare: A Case Study Of A Rehabilitation Hospital In Abu Dhabi, Mubarak Alketbi

Theses

This study investigates the readiness for transforming rule-based chatbots to AI-based chatbots in UAE healthcare, examining a rehabilitation hospital in Abu Dhabi through quantitative research involving healthcare professionals (N=96) and technical analysis. Findings revealed positive perceptions of the current system alongside enhancement opportunities through AI capabilities, with perceived usefulness strongly correlating with behavioural intention, high service quality ratings for empathy and responsiveness, midcareer professionals demonstrating the highest AI acceptance levels, and system integration identified as the highest priority implementation area.

The research contributes to healthcare technology transformation knowledge in the UAE by providing a structured implementation framework addressing technical requirements, …

Evaluating Open-Source Machine Learning Ransomware Detection Techniques, Sydney Steckart

Master's Theses (2009 -)

Ransomware remains one of the most disruptive and damaging form of cyber threat affecting both larger and smaller organizations. It is becoming increasingly more important to find tools to mitigate this threat, and one route that is much more prevalent is using machine learning techniques for detection. This work explores open-source work geared towards ransomware detection with the aid of artificial intelligence as a means to provide a cost-effective alternative for organizations that may not have the funding to purchase the commercial solutions. Many tools and malware repositories were investigated, and one was further analyzed with a dataset specifically catered …

Evaluating The Effectiveness Of Llm-Generated Phishing Campaigns, Nathan Sniegowski

Master's Theses (2009 -)

This paper investigates the effectiveness and security implications of Large Language Models (LLMs) in phishing campaigns. Existing research has explored using LLMs and AI for enterprise security tools and automating phishing email processes. However, few studies evaluated the effectiveness of fine-tuned LLMs in generating phishing email content and measuring real-world user interaction. This research used LLMs to produce the body content of phishing emails with phishing links manually inserted post-generation. The researcher performed three core experiments: (1) evaluating the success rate of jailbreaking three commercial LLMs to generate phishing content, (2) analyzing ChatGPT-4o mini’s phishing emails based on institution-specific context …