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Full-Text Articles in Entire DC Network
Perspectives Of Trauma Among Licensed Trauma Therapists: A Concept Mapping Study, Sean W. Bullock
Perspectives Of Trauma Among Licensed Trauma Therapists: A Concept Mapping Study, Sean W. Bullock
Master's Theses
To address gaps between research and psychotherapeutic intervention for trauma and trauma-related issues, the current study elicited and analyzed the perspectives of licensed trauma therapists via a concept mapping process. A literature review was conducted to explore the history and limitations of trauma’s current medical use as outlined by Criterion A of posttraumatic stress disorder in the DSM-5-TR. To answer the research question regarding how practitioners understand trauma, the researcher recruited licensed trauma therapists (n = 17) to participate in concept mapping. Participants generated 126 unique statements, which they then sorted based on similarity and rated individually on importance. Hierarchical …
Enso-Induced Oceanographic Anomalies And Their Potential Impacts On Coral Species In The Phoenix Islands Protected Area, Jason T. Gonsalves
Enso-Induced Oceanographic Anomalies And Their Potential Impacts On Coral Species In The Phoenix Islands Protected Area, Jason T. Gonsalves
Master's Theses
The 2015/16 El Niño event is one of the strongest El Niño Southern Oscillation (ENSO) events on record. Coral reefs in the Phoenix Islands Protected Area (PIPA) were exposed to the effects of the 2015/16 El Niño event and experienced moderate to severe coral bleaching and mortality. This study examines the variability in three key oceanographic variables before, during, and after the 2015/16 El Niño event within PIPA: sea surface temperature (SST), sea surface salinity (SSS), and estimated chlorophyll-a (chl-a) as a proxy for regional productivity. I used remote sensing data for SST, SSS, and estimated chl-a coupled with in-situ …
Powers' Conjecture On The Third Largest Eigenvalue Of A Graph, Kevin Schmidt
Powers' Conjecture On The Third Largest Eigenvalue Of A Graph, Kevin Schmidt
Master's Theses
In 1989, David Powers conjectured that for any connected graph G on n vertices, the k-th largest eigenvalue of the adjacency matrix satisfies λk(G) ≤ ⌊n/k⌋ for every 1 ≤ k ≤ n/2. The conjecture has since been resolved case by case, in the sharper form λk(G) ≤ n/k − 1: the case k = 1 is classical, k = 2 was settled independently by Hong and by Powers in 1988, and k ≥ 4 was shown to fail by Nikiforov and Linz. This thesis surveys the resolution of the remaining case, k = 3, achieved in March 2026 by …
Fear, Threat, And Google Searches: Examining Ideological Shifts Using Big Data, Erin M. Cerasaro
Fear, Threat, And Google Searches: Examining Ideological Shifts Using Big Data, Erin M. Cerasaro
Master's Theses
In their review of research on factors that affect political conservatism, Jost et al. brought together research from several theoretical viewpoints. This produced a model of psychological needs and motives in individuals which react with stimuli that make them feel fearful and threatened (F/T), increasing adherence to conservative ideology. While some research supports these claims, evidence shows that in some contexts these variables increase ideological polarization overall, but may also have a greater impact on conservative attitudes specifically. Researchers have had difficulty in investigating these relationships in naturalistic settings due to an inability to manipulate events that precipitate this ideological …
Knowledge-Enhanced Feature Store For Operational Ml And Llm Workflows, Saurabh Suman
Knowledge-Enhanced Feature Store For Operational Ml And Llm Workflows, Saurabh Suman
Master's Theses
Modern machine learning (ML) organizations rely on feature stores to manage training and production data, yet as catalogs grow to thousands of features, semantic management becomes the bottleneck: discovery, governance, and metric selection remain largely manual. This thesis proposes and evaluates a knowledge-enhanced feature store that augments a dual-plane store with a hybrid knowledge layer—relational provenance, a lineage graph, semantic vector retrieval, and an online cache—and an LLM-driven multi-agent layer for profiling, matching, grounded metric recommendation, and pipeline generation. A working prototype was evaluated across three task families—semantic profiling, feature-matching retrieval, and discovery—using classification, ranking, and operational metrics computed by …
Differential Effects Of Generative Artificial Intelligence On Formative And Summative Assessment Performance: A Quasi-Experimental Longitudinal Study, Md Istiak Morsalin
Differential Effects Of Generative Artificial Intelligence On Formative And Summative Assessment Performance: A Quasi-Experimental Longitudinal Study, Md Istiak Morsalin
Master's Theses
Generative artificial intelligence has unsettled a core assumption of course assessment: that scores on unsupervised work reflect what students can do unassisted. This study tests whether the widespread availability of ChatGPT altered student performance differently on formative versus summative assessments in Business Analytics and Foundations, a required undergraduate quantitative-methods course taught by one instructor across nine cohorts. In a quasi-experimental longitudinal design, the Fall~2022 cohort ($n = 90$), the last to finish before ChatGPT's public release, serves as a control against eight post-ChatGPT cohorts spanning Spring~2023 through Summer~2025 ($N = 646$). Outcomes were drawn from McGraw-Hill Connect records using matched …
Evaluation Of General Voronoi Diagram Decomposition For Harmonic Fields In Navigation Of Dynamic Environments, Franco Abullarade
Evaluation Of General Voronoi Diagram Decomposition For Harmonic Fields In Navigation Of Dynamic Environments, Franco Abullarade
Master's Theses
Harmonic potential fields provide provably minimum-free navigation, but any change to the workspace geometry invalidates the field and forces a costly global recomputation, typically restricting them to static environments. This thesis extends the harmonic map framework of Vlantis et al., which maps the free workspace onto a unit disk and uses an atlas of per-region transformations, to dynamic indoor settings. First, we replace their manually annotated room partition with an automatic decomposition based on the Generalized Voronoi Diagram, allowing the atlas to be built from an arbitrary occupancy grid in an automated way. Second, we introduce a localized repair procedure …
Determining The Role Of Maumee River Sediments In Microbial Nitrogen Transformations And Net Fluxes, Ashlyn Stanalonis
Determining The Role Of Maumee River Sediments In Microbial Nitrogen Transformations And Net Fluxes, Ashlyn Stanalonis
Master's Theses
The Maumee River watershed is the largest of any river feeding into the Laurentian Great Lakes and is primarily comprised of agricultural land uses. Most cultivated crops require fertilizer applications to sustain growth and productivity. Fertilizer runoff is a major source of nutrient loading to the river, and total nitrogen (N) and phosphorus (P) inputs contribute to eutrophication and cyanobacterial blooms in the western basin of Lake Erie. This study aimed to characterize Maumee River sediments as net N sinks or sources to the western basin and evaluate N removal efficiency (a valuable ecosystem service) to determine if river sediments …
Id-More Vision: Real-Data Machine-Learning Assessment For A Digital-Twin-Inspired, Xr-Ready Rehabilitation Prototype, Rickey L. Clark
Id-More Vision: Real-Data Machine-Learning Assessment For A Digital-Twin-Inspired, Xr-Ready Rehabilitation Prototype, Rickey L. Clark
Master's Theses
Rehabilitation assessment often relies on periodic observation, while many XR prototypes show scripted rather than recorded-motion evidence. iD-MORE Vision is an offline pipeline trained on KIMORE and IRDS and linked through JSON packets to a two-mode Unity desktop prototype. Both datasets include controls and rehabilitation participants with neurologic, musculoskeletal, or mobility impairments. This improves relevance but does not clinically validate the system.
Under fixed subject-wise splits, the primary five-seed Random Forest predicted KIMORE clinician scores with MAE 6.087 ± 0.044 cTS and R² 0.568 ± 0.006; the subject-level R² interval crossed zero. The primary IRDS five-run CUDA GRU averaged 0.877 …
Comparing Online Versus In-Person Administration Of Cognitive Tasks And Evaluating Their Predictive Utility Of Inattention Symptoms And Related Behaviors, Cameron Pothoven
Comparing Online Versus In-Person Administration Of Cognitive Tasks And Evaluating Their Predictive Utility Of Inattention Symptoms And Related Behaviors, Cameron Pothoven
Master's Theses
Attention-Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder associated with less developed working memory (WM) processes, theorized to be a core contributing factor in the development of ADHD and a predictor of ADHD symptom severity (Alderson et al., 2013; Rapport et al., 2008). Objective measures inclusive of working memory tasks, when used in conjunction with self-report measures, have been previously shown to increase the accuracy of diagnosing ADHD (Marshal et al., 2021. However, given that WM is typically assessed by a trained clinician, it is unclear how accurate and comparable online administration of adapted WM tasks are to their in-person counterparts. …
A Comparison Of Survival, Growth, And Stress Resilience In Three Different Lineages Of The Pacific Oyster (Crassostrea Gigas) Farmed On The California Central Coast, Victoria F. Hanshaw
A Comparison Of Survival, Growth, And Stress Resilience In Three Different Lineages Of The Pacific Oyster (Crassostrea Gigas) Farmed On The California Central Coast, Victoria F. Hanshaw
Master's Theses
Aquaculture of Pacific oysters on the US West Coast is routinely impacted by seasonal unexplained mortality events. To better understand these large-scale mortality events in oyster aquaculture, shellfish growers and scientists in California have partnered together to conduct comparative, multi-estuary farm trials of discrete Pacific oyster (Crassostrea gigas) lineages. In this thesis we investigate how the more recently imported Midori lineage performs compared to the historically used Miyagi lineage, as well as a Hybrid (Midori x Miyagi) lineage. As part of a 7-month long field study from April-November of 2024 in Morro Bay and Tomales Bay, California, we evaluated …
Electromagnetic Enhancement Of A Potassium-Seeded Rotating Detonation Engine, Anthony Joseph Presto Jr.
Electromagnetic Enhancement Of A Potassium-Seeded Rotating Detonation Engine, Anthony Joseph Presto Jr.
Master's Theses
Rotating detonation engines offer a route to pressure-gain combustion by sustaining one or more detonation waves in an annular chamber supplied by continuous propellant injection. This thesis evaluates whether potassium seeding can make the high-temperature product flow of a hydrogen–air rotating detonation engine conductive enough to serve as the working fluid for magnetohydrodynamic acceleration. To the author’s best knowledge, the complete configuration modeled here has not been reported previously in open literature. This configuration consists of a hydrogen–air RDE with KOH-based potassium seeding, local conductivity estimates, and imposed Lorentz-force acceleration. The thesis therefore develops an initial computational model for this …
Sentinel: Evaluating Occlusion-Centered Next-Best-View Selection Using Rgb-Derived Pseudo-Geometry, Paul Nassar
Sentinel: Evaluating Occlusion-Centered Next-Best-View Selection Using Rgb-Derived Pseudo-Geometry, Paul Nassar
Master's Theses
Three-dimensional cameras provide direct geometric measurements, but their cost, weight, power requirements, and calibration constraints can limit their use in various lightweight or large-scale sensing systems. A potential alternative is to use conventional two-dimensional RGB cameras together with geometric reconstruction models that infer a partial three-dimensional representation from images. This thesis evaluates that possibility for next-best-view (NBV) selection through Sentinel, an occlusion-centered system for static, object-centric scenes with known camera poses and intrinsics. Sentinel converts source RGB observations into pseudo-geometry using monocular depth or point-map predictions, combines those predictions with camera-ray evidence, identifies occluded unknown regions, and selects a candidate …
Predicting Student Belonging In Computing Education: A Multimodal Machine Learning Approach Using Eeg And Survey Data, Hannah Moshtaghi
Predicting Student Belonging In Computing Education: A Multimodal Machine Learning Approach Using Eeg And Survey Data, Hannah Moshtaghi
Master's Theses
Measuring students’ sense of belonging, characterized by feelings of acceptance, inclusion, and encouragement from teachers, remains a significant challenge in computing education. Prior research has associated this multidimensional construct with positive academic outcomes and has identified instructors’ growth- and fixed-mindset messaging as a potential influence. However, belonging is a complex and deeply personal experience that is difficult to capture through direct observation alone. Current measurement methods rely on self-report surveys, which may not capture every aspect of an experience that can also involve emotional and cognitive responses.
This thesis investigates whether combining EEG data recorded during a belonging questionnaire with …
A Maintainable Extensible And Performant Compiler Toolchain For The Trustguard Architecture, Ethan N. Emery
A Maintainable Extensible And Performant Compiler Toolchain For The Trustguard Architecture, Ethan N. Emery
Master's Theses
TrustGuard is a hardware architecture implementing a CAVO (Containment Architecture with Verified Output) model, which provides security guarantees by bootstrapping trust of a system to a hardware component known as the Sentry. Rather than verifying an entire system, TrustGuard re-executes trusted computation on the Sentry and validates the host system's execution before allowing values to pass to the outside world, thereby containing the effects of erroneous computation. Implementing this architecture in practice without hardware modifications to a host CPU requires a compiler toolchain capable of automatically generating instrumented binaries for both the untrusted host and the trusted Sentry from C …
Synthesis And Characterization Of Carbon Quantum Dots And Gold Nanoparticles For Norovirus Biosensing Applications In Water Systems, Breanne Evans
Synthesis And Characterization Of Carbon Quantum Dots And Gold Nanoparticles For Norovirus Biosensing Applications In Water Systems, Breanne Evans
Master's Theses
Rapid, reliable detection of viral pathogens remains a significant challenge across water-treatment and environmental monitoring systems, including drinking-water, wastewater, water reuse, and environmental surveillance applications. Waterborne viral contamination can pose substantial public-health risks, making early detection essential for protecting water quality and responding quickly to treatment failures or contamination events. Direct potable reuse (DPR) is one particularly demanding example because it requires continuous verification of treatment performance and the broader need for rapid virus monitoring extends across many water-treatment and environmental surveillance applications. Norovirus is a priority target because of its widespread occurrence in wastewater, environmental persistence, and exceptionally low …
Enabling Multi-Task Neural Network Inference On Heterogeneous Edge Devices, Redwanul Islam Arif
Enabling Multi-Task Neural Network Inference On Heterogeneous Edge Devices, Redwanul Islam Arif
Master's Theses
Deep neural networks are increasingly required to run on the devices that generate the data. If such a device must perform more than one task, the standard practice is deploying one model per task, which makes memory grow linearly with task count, which is unacceptable when the entire budget is kilobytes. This thesis asks one question in three settings: how much capability can a network acquire without incurring deployment cost?
The first study takes an ImageNet-pretrained ResNet-18, sweeps the branch point across every residual stage and the classification-head depth across one, ten, and twenty layers, and deploys the resulting multi-head …
Spatial And Hydrologic Effects Of Climate Change And Urbanization On Freshwater Fish Communities In North Georgia Watersheds, Mayuko Mizutani
Spatial And Hydrologic Effects Of Climate Change And Urbanization On Freshwater Fish Communities In North Georgia Watersheds, Mayuko Mizutani
Master's Theses
Urbanization and climate change are altering streamflow and land cover across the southeastern United States, threatening freshwater biodiversity in rivers already burdened by impoundments and habitat loss. I investigated how changes in streamflow and land cover might affect fish community biodiversity in the Etowah River watershed of North Georgia. By combining a dataset of fish collections from 1999 through 2019 with contemporaneous land use and daily streamflow, I was able to model fish community responses to urbanization and climate-driven hydrologic changes and then forecast fish community structure under multiple CMIP6 global climate models and greenhouse gas emissions scenarios (SSP2-4.5 and …
Federated Learning For Early Medical Diagnosis: Enhanced Diabetic Retinopathy Detection In Smart Healthcare, Mohammad Nasajpour Esfahani
Federated Learning For Early Medical Diagnosis: Enhanced Diabetic Retinopathy Detection In Smart Healthcare, Mohammad Nasajpour Esfahani
Master's Theses
This thesis investigates the role of federated learning as a privacy-preserving solution for modern healthcare challenges. In traditional machine learning, sensitive medical data must be centralized for model training, raising concerns about privacy, security, and regulatory compliance. Federated learning offers an alternative by allowing hospitals, clinics, and personal health devices to collaboratively train shared models without exchanging raw patient data. The study first explores how federated learning is being used across various healthcare domains, including cancer detection, medical imaging, and disease prediction— highlighting its potential to support secure collaboration across institutions. It addresses key benefits such as data privacy, scalability, …
Examining Transcultural Approaches In Art Education: Transversality, Identity Formation, And Intercultural Understanding, Alexandra Grace Parsons
Examining Transcultural Approaches In Art Education: Transversality, Identity Formation, And Intercultural Understanding, Alexandra Grace Parsons
Master's Theses
Art education is often treated as marginal within formal schooling, valued as enrichment rather than recognized as a vital contributor to students' intellectual, cultural, and emotional development. Funding and policy decisions made by state and local bodies produce significant regional disparities in access to art education across the United States. This thesis examines how transcultural approaches to art education can respond to increasingly diverse, post-migrant school communities. Using a comparative qualitative case study design, the study analyzes program structures, partnership models, and pedagogical practices at Birmingham Arts School in the United Kingdom alongside schools within Fulton County and Atlanta Public …
Timelines Over Tokens: Summarization, Prompting, And Explainable Fine-Tuning For User-Level Suicide Risk Detection, Aditya Tekale
Timelines Over Tokens: Summarization, Prompting, And Explainable Fine-Tuning For User-Level Suicide Risk Detection, Aditya Tekale
Master's Theses
This research presents a two-stage pipeline for user-level suicide risk detection from Reddit: first, inference-only prompting with summarization; second, fine-tuned encoder classification with explainability and expert validation. The data are user-level: each of the 500 C-SSRS Reddit items is one user’s chronologically concatenated posts and comments (a user timeline), annotated by psychiatrists. Stage one: six prompting strategies zero-shot, few-shot, chain-of-thought, tree-of-thought, least-to-most, and self-consistency are evaluated across six LLMs on multi-class and binary formulations; simple zero-shot achieves the highest balanced accuracy (0.53 multi-class). Error analysis shows longer inputs associate with misclassification (p = 0.002); domain-specific summarization (timelines >2,000 tokens) reduces …
Investigating Learning In Immersive Virtual Reality, Andrew Negrette
Investigating Learning In Immersive Virtual Reality, Andrew Negrette
Master's Theses
Students often struggle with learning challenging subjects throughout their education. This also tends to lead to lower enjoyment and science self-efficacy for learning. Some subjects may be better represented in 3-dimensional spaces utilizing immersive virtual reality (IVR). Recently, IVR headsets have become more accessible and affordable and therefore are in wider use. The purpose of this study was to investigate whether differences in science selfefficacy, enjoyment, presence and knowledge retention exist between IVR and controls on an ocean acidification lesson. I predicted that participants taking the lesson in IVR would score higher compared to a laptop on all measures, due …
Spatial Heterogeneity And Temporal Trends Of California Extreme Heat Using High-Resolution Earth System Model Simulations, Eleni Konstantelos
Spatial Heterogeneity And Temporal Trends Of California Extreme Heat Using High-Resolution Earth System Model Simulations, Eleni Konstantelos
Master's Theses
Extreme heat threatens California’s diverse landscapes and populations through intensifying and geographically shifting patterns. This study examined the temporal trend and spatial heterogeneities of California’s extreme heat for 1994–2015. The analysis was based on the fully coupled Energy Exascale Earth System Model version 2 (E3SMv2), specifically its 25-km regionally refined configuration. While the Desert/Inland region exhibited the highest number of days ≥ 35 °C and the highest heatwave severity, Central Valley showed the fastest increase in the number of days ≥ 35 °C and heatwave events, as well as the fastest increases of days exceeding various heat index thresholds over …
Match Made In Ml: Developing Compatibility Relationships In Evidential Reasoning Approaches With Machine Learning, Ella Jolie Thomas
Match Made In Ml: Developing Compatibility Relationships In Evidential Reasoning Approaches With Machine Learning, Ella Jolie Thomas
Master's Theses
The presented expectation maximization informed evidential reasoning model extends the ability of the evidential reasoning calculus to support decision making by integrating an adaptive model learning capability. Compatibility relationships in Evidential Reasoning models are traditionally built by human domain experts. This process is labor-intensive, especially for large and complex models. Additionally, when new data becomes available, compatibility relationships must be reconstructed. Using machine learning and the expectation maximization algorithm, it is demonstrated that compatibility relationships can be constructed that learn relationships between domain knowledge that is used to make decisions. Using drug development as a domain of application, a traditional …
Superresolution Spectroscopy Of Atomically Thin Semiconductors And Moiré Heterostructures, Chien-Chu (Charity) Wei
Superresolution Spectroscopy Of Atomically Thin Semiconductors And Moiré Heterostructures, Chien-Chu (Charity) Wei
Master's Theses
Atomically thin semiconductors and moir’e heterostructures provide an important platform for studying quantum phenomena shaped by reduced dimensionality, interlayer coupling, strain, and local structure. In MoS2, the transition from bulk to monolayer form changes the material from an indirect to a direct band gap, while stacked and strain-engineered systems can produce spatially varying moir’e potentials on nanometer length scales. Because these effects are highly localized, conventional far-field optical spectroscopy is often limited in its ability to resolve them directly. This thesis explores superresolution vibrational spectroscopy as a route toward probing local behavior in atomically thin semiconductors and moir’e heterostructures. Far-field …
The Zeal Instruction Set Architecture, Joseph A. Gerani
The Zeal Instruction Set Architecture, Joseph A. Gerani
Master's Theses
The Instruction Set Architecture of a CPU (Central Processing Unit) determines what type of instructions the CPU is able to understand, how those instructions are encoded, and what it should output upon receiving those instructions as input. There are currently three popular ISAs meant for the consumer market: x86, RISC-V, and ARM, as well as a fourth that mostly now exists in the server market by the name of Power. One of the most important parts of an ISA is for engineers to be able to understand it and make use of it. If an ISA is too complicated, nobody …
Impacts Of Physical Extremes On The Reproductive Output And Dispersal Of Stephanocystis Osmundacea, Jessica J. Franks
Impacts Of Physical Extremes On The Reproductive Output And Dispersal Of Stephanocystis Osmundacea, Jessica J. Franks
Master's Theses
Population replenishment is vital for species survival and depends on reproductive output and recruitment success. Many marine organisms rely on both short- and long-distance dispersal to sustain and expand their populations. Marine dispersal involves microscopic or planktonic stages that are influenced by currents, physical processes, and biological traits such as planktonic duration and sinking behavior. Depth and light gradients affect primary producer growth, impacting reproduction, especially in morphologically plastic seaweeds. This study examined how depth-related factors influence reproductive morphology, reproductive output, and dispersal of the subtidal brown seaweed Stephanocystis osmundacea in central California. Using field, lab, and computational methods, depth-driven …
Error-Tolerant Metric Dimension, Leander Ten Hoff
Error-Tolerant Metric Dimension, Leander Ten Hoff
Master's Theses
Metric dimension is a graph parameter that measures the smallest distance-based unique coordinate system on a graph. Fault-tolerant metric dimension is a variant that requires redundancy. Inspired by this idea, we propose and investigate a new variant we call error-tolerant metric dimension. We first prove some fundamental results to gain familiarity with this more complex variant. Then, we use these tools to study relative behaviors of error-tolerant metric dimension. We prove explicit computations for simple graph families, including bipartite complete graphs and paths. Finally, we extend extremal results from previous papers on metric dimension, including a full correction of an …
The Characterization Of Bridging Waters And Ions In Protein-Rna Complexes, Leslie Duong
The Characterization Of Bridging Waters And Ions In Protein-Rna Complexes, Leslie Duong
Master's Theses
Here we explore the role of bridging waters and ions in protein-RNA complexes. From an initial set of 33 high-resolution X-ray crystal structures, 17 were identified such that protein-RNA complex and component protein and RNA chains were found within 1 pH unit as indicated by crystallization conditions and their diffraction temperatures meeting one of two ranges: above or below freezing. To define an even more realistic set, 12 unbound-unbound and unbound-pseudo-unbound complexes from the 17-set were studied, showing the large fraction of complexes indicating more protein and RNA water hydrogen bonding in their actual interfacial regions as opposed to those …
The Relationship Between Foliations Of The Plane, Kaplan Diagrams, And Non-Hausdorff 1-Manifolds, Monique Justine Howe
The Relationship Between Foliations Of The Plane, Kaplan Diagrams, And Non-Hausdorff 1-Manifolds, Monique Justine Howe
Master's Theses
In this paper we seek to explain the relationship between foliations of the plane, Kaplan diagrams, and simply connected non-Hausdorff 1-manifolds with countable basis that are orientable with an ordering on branch points. We will walk the reader through the definitions of all of these objects, and provide examples with a focus on the motivating example of the Reeb foliation. This paper will describe and define the known bijection from the set of foliations of the plane, F, to the set of Kaplan diagrams, K, its inverse, and the one-to-one map from F to the set of simply connected non-Hausdorff …