Digital Commons Network^™

Faculty Perceptions And Use Of Open Educational Resources In Postsecondary Stem Classrooms, Gabriel Posadas

Theses and Dissertations

This study examined how faculty in Science, Technology, Engineering, and Mathematics (STEM) or STEM-related fields perceive and utilize open educational resources (OER) in their classrooms and how faculty characteristics (e.g., age, teaching experience, OER experience) influence their adoption. A quantitative survey was administered to 48 STEM faculty across 8 colleges at a large, southeastern university. Findings revealed that faculty generally acknowledged OER’s benefits, particularly its cost-saving potential, and all faculty without prior OER experience and 86.5% of faculty with OER experience expressed neutral to positive perceptions regarding OER’s ability to reduce financial burdens. Faculty with OER experience also recognized its …

The Relationship Between Internal Coherence And Student Learning In High Achieving Middle Schools: A Mississippi Study, Christina Coleman Reynolds

Theses and Dissertations

In order to determine ways in which Mississippi is improving in education, a quantitative research study was designed and conducted to examine ten high achieving middle schools in the state. The 10 schools had to obtain an A ranking or B ranking for the 2021-2022 school year and/or 2022 – 2023 school year from the MDE. The purpose of the study was to determine if relationships existed between the student achievement scores (Reading Proficiency, Reading Growth, Math Proficiency, and Math Growth) assigned by the state to each school and levels of Internal Coherence of the administrators and staff employed in …

Raad-Llm: Adaptive Anomaly Detection Using Llms And Rag Integration, Alicia Russell-Gilbert

Theses and Dissertations

Anomaly detection in complex industrial environments poses unique challenges, particularly in contexts characterized by data sparsity and evolving operational conditions. Predictive maintenance (PdM) in such settings demands methodologies that are adaptive, transferable, and capable of integrating domain-specific knowledge. This work presents RAAD-LLM, a novel framework for adaptive anomaly detection, leveraging large language models (LLMs) integrated with Retrieval-Augmented Generation (RAG). This approach addresses the aforementioned PdM challenges. By effectively utilizing domain-specific knowledge, RAAD-LLM enhances the detection of anomalies in time-series data without requiring fine-tuning on specific datasets. The framework's adaptability mechanism enables it to adjust its understanding of normal operating conditions …

Integrating Case Studies With Meteorologists’ Insight: Assessing Meteorologists’ Perception And Utilization Of Composite Indices, Brianna Marie Salazar

Theses and Dissertations

Meteorologists from sectors, including broadcast, academia, and operations, use derived composite indices such as 0-1km and 0-3km energy helicity index (EHI), effective-layer supercell composite parameter (SCP), fixed-layer and effective layer significant tornado parameter (STP), in addition to other resources, when developing severe local storm forecasts. This study utilizes the Weather Research and Forecasting (WRF) model to create simulations of composite indices for two tornado-producing events: 31 March 2023 and 3 May 1999. With modifications to geographical location, these simulated scenarios are then utilized in the survey to gauge how meteorologists assess where tornado potential is highest. Additionally, a combination of …

Application Of Pu Learning In Detection Of Ddos Attacks, Gagana Sathya Narayana Prasad

Theses and Dissertations

The gcore radar 2024 says, the number of DDoS attacks has been increased by 46% in 12 months. Supervised and unsupervised techniques struggle detecting DDoS attacks due to the scarcity of labeled attack samples and an overwhelming presence of benign traffic. In contrast PU- Learning offers a promising solutions by dividing the data into positive and unlabeled data. This study explores the effectiveness of PU-learning in detecting DDoS attacks by comparing it with unsupervised methods. This method employs PU Bagging, Two Step method and auto-encoder based models to extract meaningful patters from network traffic data, utilizing CICDDoS2017 dataset for evaluation. …

Measuring What Matters: A Policy Analysis Of Statewide Accountability Systems Through The Lens Of College And Career Readiness, Steven Deandre Shadwick

Theses and Dissertations

A disconnect exists between statewide accountability systems and college and career readiness (CCR) outcomes measured by the ACT and SAT. The goal of a statewide accountability system is to enable, implement, and support success for all students in areas that demonstrate high academic achievement through federal- and state-mandated metrics. Under the Every Student Succeeds Act (2015), states have been granted flexibility in how to measure CCR via a number of School Quality and Student Success (SQSS) indicators. Through a quantitative correlational design, data were collected from 44 states with ACT and SAT participation rates ≥ 90%, ≤ 10% or closest …

Zeroizing Trust In A Naïve Federated Zero Trust Environment, Keith E. Strandell

Theses and Dissertations

The position of the United States on the global stage is predicated on information dominance and the ability to project power through cooperative engagements with mission partners in both wartime and peacetime. Recent cyber-attacks highlighted the need for a more robust cybersecurity posture. As the United States progresses toward the adoption of Zero Trust, it is incumbent on the Department of Defense to assess the impact to the ability to share data across strategic partnerships while securing the data of both the United States and its partners. This paper proposes research into ensuring an environment rooted in Zero Trust and …

Synthetic Data Augmentation For Retinoblastoma Using Diffusion, Andrew Thompson

Theses and Dissertations

Many AI models rely on large and high quality datasets for optimal training. In certain cases, data can be difficult or expensive to obtain, making training difficult. Rare medical conditions are one of these cases. Datasets for retinoblastoma are severely lacking in quantity. Diffusion has been used to create synthetic data in the industrial, medical, and financial domains. By applying the latest Diffusion methods to retinoblastoma, this work seeks to improve predictive model performance on identifying retinoblastoma.

The Role Of K-12 Educators In Shaping Stem Pathways: Examining Social Capital And Self-Efficacy In Stem Education, Holly Trisch

Theses and Dissertations

This dissertation examines the impact of K-12 educators on students’ pathways in STEM (Science, Technology, Engineering, and Mathematics) by focusing on two main factors: the social capital of K-12 and elementary school teachers and the self-efficacy of preservice teachers in STEM education instruction. The first study investigates the social capital of first year engineering students, emphasizing the relationships and resources they gained during their K-12 education that influenced their decision to major in engineering. A quantitative study using survey data collected from first-year undergraduate engineering students indicates that K-12 educators play a crucial role by providing mentorship and resources that …

Work-Life Balance And The Impact Of Covid-19 On Faculty At Historically Black Community Colleges (Hbccs), Taneshia Turner Winston

Theses and Dissertations

This research study was conducted to determine how the COVID-19 pandemic affected the work-life balance of faculty at HBCCs based on their race, gender, age, marital status, and tenure status. The study employed a quantitative research design utilizing Exploratory Factor Analysis (EFA) to conduct time-based activities separately and group perception-based response variables into meaningful categories to uncover patterns. To analyze the differences in race, gender, age, marital status, and tenure status, Regression and Chi-square test analyses were used to evaluate the collected data. Regression analysis explored relationships between time spent on activities and perceptions of stress, productivity, and satisfaction. Chi-square …

Evaluating Rainfall Sensitivity Over Land To Tropical Cyclone Parameters Using Idealized Wrf, Madison C. Yawn

Theses and Dissertations

Tropical cyclones (TCs) are extreme weather events impacting the United States nearly every year. These events often cause severe damage due to the associated responses they produce including storm surge and rainfall, and the accurate estimation of these TC hazards is necessary to support coastal engineering, risk assessment, and emergency management activities. Evaluating TC-driven hazards is often done in combination with numerical models to simulate how environmental interactions alter the physical processes and responses of these storms. The purpose of this study was to simulate synthetic TC events using the Advanced Weather Research and Forecasting (WRF) model to understand how …

Data In The Classroom: The Impact Of A Data-Centric, High School Program To Motivate Career Interest In Stem Fields, Tyler Stabiler

Theses and Dissertations

This dissertation proposes to analyze the importance of introducing data-centric STEM (Science, Technology, Engineering, and Mathematics) studies at the high school level. In today's digital age, the importance of studying data-centric STEM in high school cannot be overstated. This dissertation looks to discover educational capabilities of high school students in various grade levels by understanding their drive, desire, and ambitions in a different STEM course than what is currently offered at the high school. Finally, the study analyzes the students’ participation in lectures, laboratory environment, and model/simulations to identify the significance in high schools adding data-centric curriculums to their academic …

Efficient Eeg Epilepsy Classification And Feature Selections Based On Hellinger Distance, Muhammed Sadiq

Theses and Dissertations

Accurate and efficient detection of epileptic seizures from EEG signals remains a critical challenge due to high-dimensional data, class imbalance, and the limitations of standard classifiers. This thesis introduces two novel models to address these challenges. The first model presents a new classifier based on the Hellinger Distance, specifically designed to enhance discriminative capability and robustness against imbalanced datasets. By integrating the Hellinger Distance Classifier with Particle Swarm Optimization (PSO) for feature selection, this model significantly improves classification performance while reducing computational complexity. Experimental evaluations on the Bonn dataset demonstrate an accuracy of 96.25%, an F1-score of 97.74%, a recall …

Applications Of The Mathieu Groups And Information Theory In Dna Encoding Functions, Juan C. Nava Jr

Theses and Dissertations

A foundational idea in mathematics lies in breaking down existing components into their bare fundamentals. As evidenced by prime numbers and composites, we learn this idea at an early age. Categorizing these broken-down components into their simplest form allows mathematicians to construct proofs from emergent patterns. John Conway’s Atlas of Finite Groups in the 1990s was particularly concerned with the categorization of structures known as groups. There are certain axioms a group must adhere to, which amount to the retention of symmetry; ultimately a group helps us to better understand symmetric actions performed on a set with a binary operation. …

The Evolution And Impact Of Blog Analysis Tools: A Study Of Blogtracker's Comprehensive Approach To Digital Discourse Analysis, Oyindamola Koleoso

Theses and Dissertations

This study presents BlogTracker, a comprehensive web-based platform designed to address the growing complexities of analyzing the modern blogosphere. We detail BlogTracker's evolution from earlier blog analysis tools, highlighting its innovative integration of features including real-time data collection, advanced content analysis, sentiment analysis, influence tracking, and narrative analysis. At the core of our contribution is a robust content extraction system that achieves 91.33% accuracy across diverse blog formats, providing a reliable foundation for all analytical functions. This extraction system effectively distinguishes between primary content and peripheral elements, ensuring high-quality inputs for downstream analysis regardless of source blog structure. The platform's …

Modeling Cross-Platform Narrative Templates: A Temporal Knowledge Graph Approach, Ridwan Amure

Theses and Dissertations

Over the past decade, social media platforms have rapidly evolved in scale, functionality, and user engagement, encouraging individuals to maintain active presences across multiple networks. This complex, interconnected ecosystem has also enabled information actors to exploit cross-platform dynamics to amplify the reach of their content and strategically target diverse audiences. Recognizing the persistence and adaptability of such actors, this research emphasizes the need for robust models that can effectively capture and analyze cross-platform narrative diffusion. To this end, we propose a framework that utilizes temporal knowledge graphs to model the evolution and relationships among narratives across platforms. We extract temporal …

Decoding Symbolic Influence On Youtube Engagement, Emotion Resonance And Trust In Information Campaigns, Diwash Poudel

Theses and Dissertations

This study examined how symbolic images in YouTube videos influences viewers’ emotions, trust, and engagement with political content online. Approximately 2,000 videos were collected and analyzed, with a focus on both thumbnails and standout frames. The findings revealed that cultural symbols were particularly effective at capturing attention and evoking strong emotional reactions—especially anger and disgust. Notably, these same symbols also enhanced viewer trust, making audiences less susceptible to misinformation. Statistical tests confirmed that these effects were consistent and significant. To ensure the validity of these results, additional analyses were conducted to assess potential biases in YouTube’s recommendation algorithm, as well …

Method Development For The Analysis Of Drugs Of Abuse Using Solid Phase Extraction And High Pressure Liquid Chromatography, Sangeeta Kurre

Theses and Dissertations

The accurate detection and quantification of drugs of abuse and their metabolites for HPLC analysis is key in the medical, forensic, and environmental sectors. Additionally, the detection of compounds related to substance use disorders in clinical settings can play a crucial role in effective treatment decisions by healthcare practitioners. The ability to detect these compounds at trace levels in any given sample matrix is a known challenge. Coupling a reliable sample preparation method to HPLC analysis for matrix interference reduction and the preconcentration of species for enhanced detection limits may provide a preferred solution to the analysis of drugs of …

El Podcast Como Herramienta Pedagógica Entre Docentes Del Nivel Superior En Una Escuela Privada Del Este De Puerto Rico, Lorell Marie Varela Morales

Theses and Dissertations

El objeto del estudio se centró en comprender la disposición de los docentes de nivel

superior hacia el uso de podcasts como recurso pedagógico en una escuela del este de Puerto Rico. Este análisis abordó las percepciones, actitudes y factores que influyen en la

aceptación de esta innovadora herramienta educativa. Se identificaron los beneficios

percibidos de los podcasts como herramienta pedagógica, así como los desafíos y

preocupaciones asociados con su integración en el proceso de enseñanza-aprendizaje.

Los modelos teóricos que sustentan este estudio se basaron en la revisión de especialistas

en innovación y aceptación tecnológica por parte de los docentes …

Sustainable Process Valorization For Bioactives From Invasive Plants Environmental Burden And Their Efficacy As Antimicrobial Agents, Shamprasad Br

Theses and Dissertations

Agri-food industries produce large quantities of fruit waste which are usually discarded and one such major beverage juice waste is Citrus waste. Likewise, invasive plants like Prosopis juliflora, which is richly distributed across Tamil Nadu, are underutilized for secondary metabolites/bioactives isolation. Halophytes are another rich source of bioactives present around mangrove forests and distributed in the salt rich marshy land.

1. Separation of phenylpropanoids from the Citrus waste through solvent extraction and pH-assisted precipitation was developed. The PPCM precipitated (phenylpropanoids form Citrus medica) were analysed by HPTLC and were found to contain Rutin, Naringin, Quercetin-3-beta-glycoside, Chlorogenic acid, Ferulic acid and optimization …

Existence Of Traveling Waves In A Predator-Prey Invasion Model With Nonlocal Dispersal And Delayed Effects In Dispersal, Austin Simms

Theses and Dissertations

We investigate the existence and stability of traveling wave solutions in a predator--prey population model that incorporates both nonlocal dispersal and time-delayed interactions. The problem arises when species distributions and feeding or reproduction processes do not respond instantaneously, but rather exhibit lags in space and time. Our aim is to understand how these delays and nonlocal effects impact the wavefront speed and the eventual establishment of a predator population in previously prey-dominated regions. To accomplish this, we derive a PDE--integro--delay system from ecological considerations of prey self-regulation, predator ratio dependence, and jump-type dispersal kernels. We then employ a traveling wave …

A Preliminary Study Of Hilbert–Kunz Functions: Coefficient Behavior In A Normal Affine Semigroup Ring, Jesus A. Mendiola Herrera

Theses and Dissertations

In 1890, David Hilbert published a set of notes on what now constitutes one of the bases of Commutative Algebra; his work would eventually influence the efforts of mathematicians like Ernst Kunz. In 1969, Ernst Kunz introduced a particular mapping regarding modules of regular local rings. His goal was to characterize Noetherian local rings of prime characteristic by computing the length of the composition series under Frobenius power transformations. In this thesis, the focus will be on stating the initial steps on finding the coefficients of the Hilbert-Kunz function of the normal affine semigroup ring of the form R = …

Displaced Nostalgia, Nava Derakhshani

Theses and Dissertations

Exploring themes of identity, displacement, gender, and belonging, this paper examines the artist's work and her approach to her art. She covers the many influences that she has access to while unable to visit her ancestral homelands. Acknowledging the translation that comes from this removal, her art is in conversation with other diasporic, exiled, marginalised groups. She makes art with various materials such as clay, shadow, light, and paint, to work on the themes that she is pursuing.

Paintings And Paintings, Anna T. Gregor

Theses and Dissertations

This thesis argues for a renewed distinction between mere paintings and capital-P Paintings, contending that meaning arises through sustained, reciprocal engagement between viewer and artwork. Amid "postmodern" disorientation, it proposes a reorientation toward individual works as sites of immanent logic and shared perception, rather than relying on external narratives or historical clichés.

4 In 10 Tiktok Users Find Their ‘For You’ Page Extremely Or Very Interesting, Aashish Gadani

Theses and Dissertations

Using video supercuts, sculptural forms, and digital prints on textiles in my work, I explore how images/videos can be used to reflect on cultural and personal trends. In this paper, I discuss how the structure of software recommendation systems combines with ideas of the post-internet image and creates unintended cultural consequences.

Assessing The Effect Of Covid-19 On Air Quality For Five Texas Metro Areas Using Daily Air Quality Index Values, Rahul Sahajpal

Theses and Dissertations

Air pollution is one of the biggest health hazards known to humans. The quality of the air that we breath is mainly determined by the level of six major air pollutants, Carbon Monoxide (CO), Nitrogen dioxide (NO₂), Particulate Matter 10 (PM 10), Particulate Matter 2.5 (PM 2.5), Sulfur dioxide (SO₂) and Ozone (O₃). The main source of these air pollutants are fossil fuels (Oil, Coal and Natural gas). Their levels in the air are reported using an Air Quality Index (AQI). Higher AQI values indicate bad air quality and vice versa. In this study …

Dynamic Approaches To Missing Data In Healthcare: Evaluating Ensemble Models, Feature Selection, And Meta-Features, Dylan Dominguez Sulca

Theses and Dissertations

Missing data is pervasive in healthcare, where incomplete observations commonly arise from patient dropout, sensor failures, or privacy constraints. This research presents an investigation into handling such data, focusing on (1) Missingness-Aware Dynamic Ensemble Weighting (MDEW), (2) feature selection under varying missing rates, (3) autoencoder-based imputation (ODAE), and (4) a meta-feature analysis guiding pipeline selection. We evaluate our experiments on four diverse datasets, Cleveland Heart Disease, Diabetic Retinopathy, Breast Cancer Wisconsin, EEG Eye State. Our research shows that MDEW adaptively selects imputer classifier pipelines, outperforming single model and uniform averaging baselines at moderate to high missingness 10% to 50%. Filter …

Unpaired Virtual Histological Staining Of Tissue From Autofluorescence Using Regularized Cycle-Consistent Adversarial Networks, Zhesi Wen

Theses and Dissertations

We present a regularized CycleGAN with a Dense Residual U-Net to virtually stain autofluorescence images of tissue into H&E-like images. Our method outperforms standard architectures, reduces artifacts, and achieves superior FID scores, enabling efficient, label-free, and accurate digital pathology for unpaired datasets using multi-channel fluorescence inputs.

False Virtues And Fragile Honor: The Weight Of Reputation In Shakespeare’S Works, Amanda Sheps

Theses and Dissertations

"False Virtues and Fragile Honor: The Weight of Reputation in Shakespeare’s Works" analyzes the intersection between honor and social standing in William Shakespeare's Othello and Much Ado About Nothing, specifically in regards to the gender roles prevalent in the plays' societies. In both plays, women who are perceived as a threat to the prevailing norms of society are ostracized, ridiculed, and may even face violence at the hands of their male love interests. The innocence of Desdemona and Hero, however, calls into question the validity of this cruel treatment. These negative reactions reflect the pressure that men have to preserve …

Intuiting Interaction: Meta-Reasoning And Meta-Learning As Foundations For Intelligent User Interfaces, Jeffrey Hsu

Theses and Dissertations

This research presents MARCO—a cognitive framework for Intelligent User Interfaces that uses meta-reasoning for context-aware adaptation across diverse tasks. It integrates multiple reasoning modules coordinated by a Meta-Cognitive Unit that selects strategies based on evolving demands. Evaluations show MARCO outperforms baselines in reasoning accuracy and computational efficiency.