Digital Commons Network^™

Increasing Breastfeeding Rates: The Role Of Targeted Maternal Education, Saige O. Adams

Undergraduate Theses and Capstone Projects

About 83.2% of infants receive breast milk when first born, and then at three months, this number drops to 69.2%, again at six months, it drops to 55.8% (CDC, 2024). It is also noted that Central Virginia lags behind this national average. Based on this data, it has been discovered that some families do not breastfeed for as long as they intended to because of some unforeseen challenges or struggles that they were not aware of, like discomfort, time management, and stress. There are some mothers who end up in early cessation of breastfeeding because they were not properly equipped …

Catholicism, Islam, And Intersectional Feminism In Ireland And Morocco: A Fatima Mernissi And Sinead O’Connor Study, Tralee Pomerleau

All Theses And Dissertations

This research contends that the interpretation of the relationship between feminism and religion is rooted in the Western feminist framework, making it seem like they cannot work together. This framework does not look at feminism through an intersectional lens, which it needs to, so women can use their life experiences, culture, and religion to fight for equal rights for women from all over the world. Looking at feminism through an intersectional lens proves that there is a way to keep religion and faith while fighting for women’s equality in every aspect of life.

This paper outlines the broad relationship between …

Navigating End-Of-Life Decisions: Cultural Considerations For Latine Patients, Michelle Carbajal Hernandez

Honors Capstones

Healthcare professionals face many challenges when communicating terminal illness prognoses for individuals. This responsibility to address a terminal prognosis is further complicated when communicating with Latine patients who may face multiple barriers within the healthcare system and whose cultural preferences influence end-of-life care planning (Carrion, 2010). For example, Latines are less likely to enroll in end-of-life (EOL) care services (e.g., hospice) (Barragan-Carrillo et al., 2022). As well as engage in end-of-life care planning than White Non-Latines (Shen et al., 2016). To understand this hesitancy towards EOL care options, this literature review aims to explore how terminally ill Latine and …

Human Osteosarcoma Cell Line That Overexpresses Cd4/Ccr5 Or Cd4/Cxcr4 To Study Hiv-Host Interactions, Harry Baffour Awuah

Biotechnology Theses

Human immunodeficiency virus type 1 (HIV-1) entry into host cells occurs through interactions between the viral surface envelope glycoprotein (Env) and the host receptor CD4, and co-receptors CCR5 or CXCR4. However, understanding these interactions in membrane contexts remains limited due to low receptor and coreceptor densities in commonly used cell models. To address this, we developed cellular systems with elevated CD4 expression and either CCR5 or CXCR4. Human osteosarcoma cells (HOS), which lack endogenous surface expression of HIV receptor (CD4) and co-receptors (CCR5 or CXCR4), were engineered via lentiviral transduction to overexpress CD4 and either CCR5 or CXCR4. Cells were …

An Artist’S Playground: Building Bridges Between Children’S Education And Their Knowledge Of Art Through Multi-Modal Learning, Alice J. Cauchi

Theses

Not all museums welcome children as part of their main audience with open arms. Research suggests that experiencing museums as a child supports classroom learning and development, but only when the museums engage young children properly. This paper explores how incorporating multi-modal interactives into art museums can effectively engage children, ages 4 to 8, and build a foundation that supports lifelong learning. Drawing on ideas from early-childhood education, museum visitor-engagement studies, and interactivity sciences, this project results in a framework that guides art museums on how they can overlap play, interactives, and content to incorporate this age group effectively to …

Towards Reliable And Trustworthy Deep Learning Through Explainability And Interpretability, Dipkamal Bhusal

Theses

Deep neural networks achieve state-of-the-art performance across many domains, yet their deployment in high-stakes settings is constrained by two challenges: opaque decision-making and vulnerability to adversarial manipulation. This thesis investigates explainability and interpretability as principled mechanisms for improving the reliability and trustworthiness of deep learning models. First, we develop new post-hoc explanation methods that improve feature attribution and concept-based explanations. These methods provide faithful decision cues by modeling meaningful feature interactions and extracting faithful coherent concepts, enabling more reliable understanding of why a model predicts a given label. Second, we show that explanation quality is not solely a property of …

A Comparative Study Of Inference-Time Scaling Strategies For Large Language Models, Oluwamayowa Owolabi

Theses

Large language models (LLMs) have demonstrated strong performance on a range of reasoning tasks, however, their reliability often depends not only on model size or training data, but also on inference-time strategies. However, existing inference-time methods are typically evaluated in isolation and under differing experimental assumptions, making it difficult to draw systematic conclusions about their relative effectiveness. This thesis proposes a controlled empirical study of inference-time scaling strategies for large language models under fixed inference-time compute budgets. The findings reveal that no single strategy dominates uniformly. PRM guided selection with the IBM Granite verifier achieves the highest absolute accuracy across …

Hardware Integrity Checking On An Fpga Through Power Side-Channel Analysis, Ethan Vuong

Theses

FPGAs have seen extensive usage in applications such as cloud-computing, hardware acceleration, mobile devices, and military alike. While the reconfigurability of these devices allow them to be as adaptable as they are fast, it raises concerns of adversaries modifying not mere software, but hardware itself. Moreover, designers face an IP trust issue where they cannot be sure that a third-party IP was not modified in transaction, programming, or even post-programming. Cloud computing centers are hesitant to rent fabric on multi-tenant FPGAs due to the plethora of vulnerabilities and uncertainties that come with allowing users to reconfigure hardware. This thesis aims …

Software Vulnerability Recidivism In Open-Source Projects, Brandon Keller

Theses

Software vulnerabilities present a major threat to businesses and individuals alike and it is therefore critical that a culture exists among software engineers to encourage the discovery and patching of security flaws. Vulnerability counts are a common way of evaluating a project’s security. However, this metric can run counter to building a developer culture of fault recognition if more vulnerabilities is always seen as a bad thing. While these counts can present a rough idea of a project’s history with security, they provide no insight into how the development team improves and learns as a result of a vulnerability. A …

Leveraging Volatile Ecram Dynamics For Short-Term Plasticity In Neuromorphic Circuits, Sean Borkholder

Theses

Short Term Plasticity (STP) is fundamental for information processing and computational efficiency within biological neural systems. STP has previously been implemented at the circuit level using complex designs with high power and area overheads, resulting in designs that are not scalable in neuromorphic systems. Electrochemical random-access memory (ECRAM) devices naturally exhibit STP behavior through volatile ion dynamics, creating transient conductance modulation.  In previous ECRAM implementations, this behavior was seen as an undesirable artifact of device programming when implemented as a Compute in Memory (CIM) device; however, this thesis proposes leveraging the volatile  behavior to instead act as a computational resource. …

Under The Surface: A Scalable Experiential Framework For Accessible Design Archives, Lo Fasano

Theses

Preserving design history is usually done by hiding it away. While institutions like the Vignelli Center for Design Studies house over 750,000 artifacts, the vast majority remain in restricted storage, with minimal space dedicated to displaying process materials alongside canonical final works. Digital archives document portions of these collections, but typically present them as static image galleries, leaving the evolutionary logic of a design, and the human labor behind it, invisible to the public. Under the Surface is a scalable, interactive framework designed to bridge archival preservation and public discovery. By transforming preserved artifacts into real-time digital experiences, the project …

Efficiency Evaluation Of Water Pumping Stations Using Data Envelopment Analysis (Dea), Rowdha Abdullah Alblooshi

Theses

Water pumping stations are a critical component of water transmission systems, ensuring reliable delivery of potable water while maintaining operational requirements and international standards. With the increasing focus on sustainability and energy optimization, improving the efficiency of pumping stations has become a key priority. However, there is a lack of structured benchmarking approaches to evaluate the relative performance of pumping stations across multiple operational factors. This study addresses this gap by applying a Data Envelopment Analysis (DEA) framework to evaluate the efficiency of water pumping stations. A multi-model approach is adopted, including the CCR and BCC models, along with the …

Imaging Performance Analysis Of Euv Mask Stacks For Sub-24 Nm Features At High And Hyper Numerical Aperture, Abdusame Omran N. Berish

Theses

As extreme ultraviolet (EUV) lithography advances toward high numerical apertures (NAs) of 0.55 and 0.75, mask-3D effects degrade image fidelity, limiting resolution and the process window. This work investigates the performance of alternative EUV absorber materials for sub-12 nm half-pitch patterning under high-NA and hyper-NA conditions. The lithographic simulations were conducted using the PROLITH Maxwell rigorous model under dipole illumination optimized for sub-24 nm resolution dense line/space features. The EUV mask stacks were derived from five fabricated and tested absorbers: TaBN, Ru/Ta, Pt2W, Ni/CrN, and TaSi2.  The absorber thickness was recalibrated to an optimal value, ensuring a maximum normalized image …

Adapting Specpt For Hst Grism Spectroscopy Via Transfer Learning, Clive Kalathoor Binu

Theses

This thesis demonstrates the successful application of transfer learning to bridge ground-based and space-based spectroscopic analysis through adapting SpecPT (Spectroscopy Pre-trained Transformer) for Hubble Space Telescope WFC3 grism data for redshift prediction. Originally trained on high-resolution DESI spectra, SpecPT initially failed when applied directly to low-resolution, noisy HST WFC3 grism observations (Normalized Median Absolute Deviation (NMAD) = 0.2095, catastrophic outlier fraction ($\eta$) = 47.97\%). Through transfer learning on 8,530 high-quality 3D-HST spectra with emission-line SNR > 2.5 and z < 1.7, the model achieved substantial improvement (NMAD = 0.0724, $\eta$ = 26.69\%), representing a 65\% reduction in typical redshift error and 46\% decrease in catastrophic failures. The research addresses two primary objectives: establishing transfer learning effectiveness for cross-domain spectroscopic analysis and investigating whether supplementing grism spectra with broadband photometric data enhances performance. Counterintuitively, integrating comprehensive multi-wavelength photometric data from CANDELS significantly degraded performance (NMAD = 0.1641, $\eta$ = 36.51\%), challenging conventional astronomical assumptions about multi-modal data fusion and revealing critical failure modes in astronomical machine learning. This work establishes a unified framework for automated analysis of both ground-based and space-based spectroscopic surveys, with important implications for JWST, Euclid, and the Nancy Grace Roman Space Telescope. The demonstrated capability to adapt models across instrumental domains provides a scalable approach for processing large data volumes from next-generation missions, validating foundational model approaches that can be developed once and efficiently adapted across diverse observational contexts.

Sampling And Counting Graph Structures With Triangle Motifs, Sherry Robinson

Theses

Understanding the structure of real-world networks often relies on identifying significant (i.e., occurring significantly more frequently than random) subgraph patterns, or motifs, such as triangles. To assess their significance, null models generate random samples from a constrained distribution of graphs, preserving selected properties while randomizing others. These models may either generate random graphs or sample structures from a fixed input graph. This thesis focuses on the latter, specifically the problem of sampling and counting graph structures that incorporate triangle motifs. While efficient algorithms exist for sampling classical structures such as matchings, extending these methods to higher-order motifs remains an important …

Predicting Teacher Burnout Across Cultures: A Machine Learning Approach Using Talis 2018 Data, Fatma Fraishan Abdulla Hassan Alkhzaimi

Theses

Teacher burnout is a persistent global challenge with significant consequences for educator wellbeing, instructional quality, and school climate. Despite extensive research, most studies rely on small local samples, predefined burnout scales, and limited analytical techniques, leaving gaps in understanding the latent structure of burnout and the factors that predict it across diverse educational systems. This study addresses these gaps by applying a hybrid machine learning framework to the OECD TALIS 2018 teacher dataset (N = 38,081) to discover latent burnout profiles and build predictive models capable of identifying teachers at risk. Unsupervised k-means clustering was used to uncover naturally occurring …

Full-Field Experimental Analysis Of 3d Printed Open-Hole Plates Reinforced With Isotropic And Concentric Carbon Fibers, Mozah Alyammahi

Theses

Additive Manufacturing technology (AM) has become an attractive process for innovative products in recent decades. The applications of AM materials widen to include composite materials. The fabrication of composite materials via AM makes the process more cost-effective than traditional fabrication methods. Nowadays, there are 3D printers that can produce composite materials with different strategies which results in different mechanical properties. This study examines the impact of carbon fiber reinforcement, both isotropic and concentric, on 3D printed open-hole plates utilizing full-field experimental analysis.  Problem Statement  The research on investigating different fiber reinforcement is increasing rapidly. However, most of the studies are …

Beyond Anomaly Detection: Classifying Attacker Automation Level From Ssh Honeypot Behavioral Signatures, Ashley Alt

Theses

The proliferation of AI-assisted offensive tools has introduced a new category of cyber attacker that combines the speed of automation with the adaptive reasoning previously associated only with skilled human operators. Despite the richness of behavioral data captured by SSH honeypots, existing analyses treat interaction logs primarily as evidence of malicious activity rather than as a dataset capable of distinguishing between attacker types. This thesis investigates whether human-driven, traditionally automated, and AI-assisted attackers produce distinguishable behavioral signatures within SSH honeypot interactions, and whether machine learning techniques can reliably classify attacker behavior from session-level features. A controlled experimental architecture was developed …

Predicting Property Sale Prices In Dubai Using Machine Learning Regression Models, Mohammad Buabdulla

Theses

It has been observed that the fastness of digital real estate’s application has resulted in availability of large-scale property data which forms an opportunity to more precise and open property valuation practices. A lot of conventional real estate appraisal methodologies with much emphasis on manual evaluation and historical comparative value find it difficult to respond to the market dynamics or the dynamics that exist within the market at an alarming rate. This research will help mitigate these shortcomings by generating and testing machine learning regression models to determine the price of residential property at sale in Dubai by using real-life …

Nlp Crowdsourcing For Predominantly Oral Languages: The Case Of Bambara, Allahsera Auguste Tapo

Theses

Predominantly oral languages (POLs) face a significant "digital divide," as they are often excluded from the benefits of modern natural language processing (NLP) technologies, due to a lack of extensive, readily available machine learning (ML) datasets. We investigate methods to overcome this data scarcity for Bambara, a Manding language, spoken primarily in Mali, with a rich oral tradition but limited digital presence.     The research leverages crowdsourcing and community engagement to build high-quality ML ready dataset resources. Key contributions include methods for automatic speech recognition (ASR) and machine translation (MT) dataset collection and curation and for educational resource creation.      Our findings …

Predicting Luxury Car Sales Using Machine Learning: A Comparative Study Of Linear Regression, K-Nearest Neighbors, And Support Vector Machines, Khalifa Jamal Mohammad Saleh Alblooshi

Theses

This paper explores the use of machine learning to predict the sales of luxury cars in the globe, and BMW as a case study of its sales data in the global market between the period 2010 and 2024. The study focuses on three regression algorithms, which include the Linear Regression, K-Nearest Neighbours (KNN) and Support Vector Machines (SVM) and sees their predictive accuracy, generalisation performance and business applicability. In Python with the help of the Google Colab, an end-to-end analytical pipeline was developed entailing data preprocessing, outlier management, feature engineering, and time-sensitive traintest division. RMSE, MAE, MAPE, and R2 were …

Alternative Color Mode Design: Supporting Mobile App Creators With Evidence-Based Guidelines, Sarah Andrew

Theses

Alternative color modes, such as light, dark, dim, and high contrast modes, in mobile apps can improve accessibility for people with vision impairments and usability for people without vision impairments across situational contexts. However, current mobile apps exhibit inconsistent color implementations for UI elements (e.g., background, text, buttons, images, and non-selectable icons), leaving users with limited accessible options. My dissertation addresses a central question in human-computer interaction and accessibility: How can mobile app designers be supported to implement alternative color modes that meet the accessibility and usability needs of people with and without vision impairments? Through an eight-study mixed-methods investigation, …

Toward A Unified Framework For Open World Visual Learning, Yuansheng Zhu

Theses

Artificial intelligence systems have achieved remarkable performance across a wide range of visual tasks. However, most existing models operate under the unrealistic closed-world assumption, where training and test data are drawn from the same distribution. In real-world applications such as anomaly detection, autonomous driving, and medical diagnosis, learning systems frequently encounter novel or out-of-distribution scenarios. These settings require models that can recognize unknown inputs, adapt to new information over time, and maintain reliable performance under evolving conditions. This dissertation studies the problem of Open World Visual Learning, a paradigm that enables visual learning systems to operate robustly in dynamic and …

Ready-To-Teach Reads: Standards-Aligned Novel Studies For Seventh Grade Using Contemporary Middle Grade Fiction, Elizabeth Duvall

Senior Theses

This project aims to provide middle school English teachers with an easy way to update their curriculum to be culturally relevant using ready-to-teach unit plans based on diverse novels. Since research shows students benefit from reading texts from diverse cultures, each novel features minority voices. Both units include lesson plans for each day, and resources like slideshows, worksheets, and discussion questions. They were created using the South Carolina College and Career Ready Standards for English Language Arts. While these units are tailored to South Carolina teachers, they can be used by any educator whose standards align with the units’ learning …

Designing Surface-Induced Entatic States In Copper Complexes For Tunable Reactivity, Rachel Kiser

Senior Theses

Copper catalysts play an important role in electrocatalytic oxidation reactions due to their redox flexibility and relative abundance compared to noble metal catalysts. In biological systems, copper metalloenzymes often achieve enhanced reactivity through an entatic state. Entasis is described as an active site or metal center being constrained to a geometric and electronic state, minimizing primary sphere reorganization energy and achieving higher rates of electron transfer.  This study investigates whether entasis can be achieved in synthetic molecular catalysts by immobilizing Cu(I) complexes onto metal oxide surfaces. Two Cu(I) complexes bearing carboxylate-functionalized ligands were examined both in homogeneous solution and when …

Searching For Temporal Variations In The Fine-Structure Constant Using Espresso Spectrograph Data, David Hoffman Iv

Senior Theses

The fine-structure constant α is a dimensionless constant, defined as e²/(4πε₀ℏc) ≈ 1/137. On the order of human timescales, its value is very much unchanging, however, in recent years there has been extensive debate over whether or not the value of α has remained constant over cosmological timescales. With the natural corollary to a changing α being that either one or multiple of its constituent physical constants have also changed in value, observing a variation in the fine-structure constant would have vast ramifications for our understanding of the nature of the early universe and how it has evolved. While past …

Pastoral Listening Skills Training In The Black Baptist Church: Equipping Clergy To Better Support Congregants, Regina Pair Allen

Doctor of Ministry Projects and Theses

This study engages a historical survey of qualitative studies of perspectives of Black pastors regarding pastoral care, examining various avenues for training in pastoral listening and the role of ministers as theological clinicians in supporting church ministries and community needs. The findings highlight the ongoing need for professional development among pastors as primary educators and theological clinicians. The study underscores the importance of equipping Black Baptist pastors to address the clinical pastoral needs of African American congregants. The significance to this field of study is providing Black Baptist clergy with practical skills and tools, grounded in theological principles, to better …

Occupational Therapy’S Role In Supporting Caregivers Of Children And Adolescents With Type 1 Diabetes, Ania G. Millan

Student Capstone Papers

Caregivers of children and adolescents with Type 1 Diabetes (T1D) often experience increased stress, occupational imbalance, and challenges related to maintaining their own health and wellness while managing their child’s complex daily care needs. Despite the significant impact caregiving responsibilities may have on daily routines, self-care, and overall quality of life, occupational therapy’s (OT) role in supporting caregivers within endocrinology settings remains underrecognized. The purpose of this capstone project was to explore caregivers’ perceptions of their health and wellness and examine the differences and similarities between caregivers’ and occupational therapy practitioners’ (OTPs) perspectives regarding OT’s role in supporting caregivers of …

Kawasaki Strategic Analysis, Felicity Thompson

Honors Theses

Kawasaki Heavy Industries is a global manufacturing and engineering company that operates across  multiple industrial sectors, including aerospace, energy systems, railways, robotics, marine  engineering, and powersports. Kawasaki is structured around engineering capabilities and  large-scale industrial production, allowing it to develop innovative technologies and integrated  systems used in domestic and international markets. In FY2025, Kawasaki generated over 2,340  billion yen in annual revenue, showing its scale as a diversified industrial conglomerate. 

Kawasaki Heavy Industries operates in multiple business units that focus on different industries,  but are connected through shared engineering knowledge, research and development, and production  systems. This structure allows Kawasaki …

Differential Effects Of Veratridine And 5-Fluorouracil On Ubxn2a-Targeted Mortalin And Rictor Proteins In Patient-Derived Colorectal Cancer Cells, Kate S. Schraufnagel

Honors Thesis

Colorectal cancer (CRC) is a leading cause of cancer-related mortality, particularly in patients with metastatic CRC and/or those who have developed resistance to conventional chemotherapy. There has been a significant rise in early-onset CRC (EOCRC) incidences in patients under age 50. Due to lack of screening, these patients are commonly diagnosed in the later stages where there is a lack of effective therapies. This highlights the need for targeted therapies that address the molecular drivers of tumor progression and treatment resistance. UBXN2A is a tumor suppressor protein that regulates key oncogenic pathways in CRC, including Mortalin-2 (mot-2)-mediated p53 suppression and …