Digital Commons Network^™

Phase Retrieval And Fidelity Preserving Quantum Channels, Kai Liu

Graduate Thesis and Dissertation post-2024

This thesis investigates the preservation of fundamental quantum properties under noisy quantum processes. Motivated by the challenges of maintaining coherence and information integrity in realistic quantum systems, we study three distinct structural properties: phase retrievability, orbit injectivity, and fidelity preservation. Each property reflects a unique facet of how quantum information can be robustly encoded, distinguished, or compared in the presence of environmental interactions.

In the first part of the thesis, we analyze phase retrievable quantum channels which allow recovery of a quantum state up to a global phase. We provide structural characterizations using the Kraus representation and the joint spectrum …

Analysis Of Numerical Methods For Spdes, And Applications Of Free Boundary Problems In Financial Mathematics, Corey A. Prachniak

Graduate Thesis and Dissertation post-2024

This dissertation studies the key properties of a fully discrete finite element method for a class of stochastic moving boundary problems. Then, free boundary problems and their applications in finance are explored.

The first part of this thesis studies the properties of a proposed fully discrete finite element method scheme with an interpolation operator for stochastic Cahn-Hilliard equations with functional-type noise. These solutions cannot be differentiated in time, so we provide Holder continuity results to aid in the scheme’s error analysis. We further derive the uniform boundedness of higher-order L²-norm moment for use in the analysis. Then nearly …

Youth Self-Injurious Thoughts And Behaviors: The Role Of Affect, Interpersonal Stress, And Parenting, Samantha J. Klaver

Graduate Thesis and Dissertation post-2024

Self-injurious thoughts and behaviors (SITBs) are associated with numerous adverse consequences, including an increased risk of suicide, for youth populations (Castellví et al., 2017; Kiekens et al., 2018). This study developed a more nuanced understanding of the factors associated with SITBs by examining proximal intrapersonal (i.e., daily youth negative affect) and interpersonal (i.e., daily youth interpersonal conflict) factors on youth SITBs utilizing experience sampling methods (ESMs). This study also examined how specific modifiable characteristics (i.e., parent-youth attachment and parental reflective functioning) may moderate these proximal associations. Results from a series of multilevel, mixed-effects negative binomial regression analyses conducted on a …

The Burden Of Blame: Self-Blame After Sexual Victimization And Its Relation To Identity, Cassandra Andrion

Graduate Thesis and Dissertation post-2024

Sexual victimization is a pervasive issue with profound psychological effects. One critical factor influencing post-assault outcomes is self-blame, which can manifest as behavioral (blaming one’s actions) or characterological (blaming one’s core self). Research has shown that self-blame is more strongly associated with sexual assault than with non-interpersonal traumatic events; however, comparisons between sexual assault and other interpersonal traumas remain underexplored. Furthermore, the relationship between specific types of self-blame and different trauma types has not been thoroughly examined. This distinction may be important, as each form of self-blame is linked to different psychological outcomes. Self-blame has been associated with several negative …

Breaking The Karen Curse: A Look At Anti-Mistreatment Signage's Impact On Customer Mistreatment Through Customer Empathy And Entitlement, Amanda Grinley

Graduate Thesis and Dissertation post-2024

This dissertation explores the phenomenon of customers mistreating service workers and examines how physical signage about customer behavior can influence the likelihood of such mistreatment occurring in a work environment. The impact of signage was studied broadly at an individual level in Study 1 by comparing the mistreatment service workers experience in workplaces with and without anti-mistreatment signage, and in more depth at an event level from the point of view of the customer in Study 2 using an experimental video vignette design. Results from the two studies indicate that anti-mistreatment signage can significantly reduce the likelihood of customer mistreatment …

The Role Individual Differences And Environmental Factors In Automated Driving Performance, John M. Duany

Graduate Thesis and Dissertation post-2024

A series of experiments were conducted to investigate the effects of ADHD diagnosis, inclement weather, non-driving-related tasks (NDRT), automation failures, and traffic density on driving performance and takeover performance. This study also examined the relationship between dispositional factors (i.e., trust in automation, cognitive failures, and self-efficacy) and dynamic factors (i.e., mental workload, situation awareness, and situational trust) in relation to automated driving performance. A total of 156 participants were recruited for this study, including drivers with and without attention-deficit hyperactivity disorder (ADHD). Each participant completed four experimental drives and two baseline drives. Mental workload, heart rate variability (HRV), situational trust, …

Examining Educational Inequalities And Driving Science’S Next Generation Forward: Geobus Program Theory Evaluation, Elise M. Lorenzo

Graduate Thesis and Dissertation post-2024

This study presents a theory-driven evaluation of GeoBus, a mobile science lab designed to deliver hands-on, “fun learning experiences” via a solar powered, technology-rich learning environment brought directly to K-12 students in Central Florida Title 1 schools. While STEM education is widely recognized as essential for promoting equity, many schools, particularly in under-resourced communities, continue to face barriers to accessing meaningful and inclusive science learning opportunities. GeoBus was created in response to this need, offering students an informal learning environment with exposure to geospatial technologies and interactive science content.

Drawing on mixed-methods data, including content from the GeoBus website and …

Hypertension, Diabetes, And Chronic Kidney Disease In Young Adults: Nhanes Data From 2013-2018, Ashly Rodriguez Reyes

Undergraduate Scholarship and Creative Works

Background. Several studies have reported the link between diabetes, cardiovascular disease, hypertension, and obesity as risk factors for the onset of chronic kidney disease (CKD), ultimately leading to renal replacement therapies such as dialysis and kidney transplantation. Although extensively researched in adults aged 55 years and older, CKD remains under-researched for young adults. Despite its emergence as a healthcare concern, limited data exists on risk factors impacting young adults without major comorbidities.

Objective. This research study aims to understand the potential risk factors unique to this population, seeking to guide prevention strategies and improve prognosis in already diagnosed individuals. Additionally, …

Multiclass Cyberbullying Detection Using Advanced Neural Network Architectures: A Comparative Study Amidst The Covid-19 Pandemic, Mahyar Alinejad

Data Science and Data Mining

Amidst the COVID-19 pandemic, the digital communication landscape has seen an unprecedented rise in cyberbullying incidents. Addressing this critical issue, our study develops and evaluates a novel multiclass cyberbullying detection framework employing several advanced neural network architectures—namely Neural Networks (NN), Convolutional Neural Networks (CNN), Long Short-Term Memory networks (LSTM), and Gated Recurrent Units (GRU). Utilizing a balanced dataset created through Dynamic Query Expansion, this research benchmarks the performance of these models in accurately classifying cyberbullying according to specific victim attributes such as age, ethnicity, gender, and religion. Our results demonstrate that LSTM and GRU models, in particular, exhibit superior performance …

Multiclass Cyberbullying Detection Using Advanced Neural Network Architectures: A Comparative Study Amidst The Covid-19 Pandemic, Mahyar Alinejad

Data Science and Data Mining

Amidst the COVID-19 pandemic, the digital communication landscape has seen an unprecedented rise in cyberbullying incidents. Addressing this critical issue, our study develops and evaluates a novel multiclass cyberbullying detection framework employing several advanced neural network architectures—namely Neural Networks (NN), Convolutional Neural Networks (CNN), Long Short-Term Memory networks (LSTM), and Gated Recurrent Units (GRU). Utilizing a balanced dataset created through Dynamic Query Expansion, this research benchmarks the performance of these models in accurately classifying cyberbullying according to specific victim attributes such as age, ethnicity, gender, and religion. Our results demonstrate that LSTM and GRU models, in particular, exhibit superior performance …

Elderly Woman With Bilateral Finger Pain, Eric Boccio, Claudia Risi

Florida Journal of Emergency Medicine (FJEM)

N/A

Paroxysmal, Severe, And Unilateral Facial Pain In Adult Male, Eric Boccio, Joshua Mcfarlane, Jeannine Bobadilla

Florida Journal of Emergency Medicine (FJEM)

No abstract provided.

Living In Fear: Be Empathetic (Life)-Tool Kit, Desiree A. Díaz, Heather Peralta, Samantha Stephenson, Danny Hernandez, Geraldine Luzincourt, Syretta Spears, Ann Marie Parker, Trysten Altamirano

Nursing Handouts, Tools, and Other Documents

Open source materials to immerse learners in rural and public health experiences are needed to ensure the new work force is equipped to care for a variety of people in differing circumstances. Public health remains a vital yet underemphasized component within healthcare education, specifically nursing education. This often limits opportunities for students to develop the skills necessary to become strong advocates for equity and systemic change. A

This project emerged from a commitment to provide experiential opportunities replicating the communities we serve. A Empathy Walk and LIFE Clinic (Díaz et al., 2025) was created as a strategy designed to engage …

Teachers' Feedback And Students' Emotional Wellbeing In Writing Courses, Amar Bahadur Sherma

Journal of English Learner Education

While feedback is a corrective business in every sphere of human life, most students do not have a positive perception of teachers’ feedback. Previous studies have emphasized the relationship between students’ writing achievements and the effectiveness of teachers’ feedback. However, no substantial research on how teachers’ feedback affects students’ emotional well-being has been undertaken. This article examines the relationship between students’ understanding of their teachers’ feedback on their writing assignments and emotional wellbeing. Data was collected from (N = 63) Nepali undergraduate students through Google Forms. The Forms consisted of structured and unstructured questions. According to the data, a mismatch …

Artificial Intelligence (Ai) Literacy: A Necessity In Modern Language Education, Samarnh Pang, Engheang Nol, Kimkong Heng

Journal of English Learner Education

This article aims to discuss the importance of artificial intelligence (AI) literacy in the context of an AI-driven world and argues that it is a necessity in modern language education. The article answers a few questions, focusing on why AI literacy matters for language students and educators, what AI competencies should be promoted, and how AI literacy can be effectively integrated into the curriculum and instruction. The article also brings to the fore key considerations for implementing AI literacy in language education. These considerations include providing support to students and teachers to navigate the complexity of AI use, offering AI …

Transforming K-12 Classrooms: Ten Essential Strategies For Cultural Responsiveness, Sandra Johnson, Stephanie Johnson, Regina Reber

Journal of English Learner Education

Across the United States, in K-12 classrooms, diverse student populations continue to increase, challenging educators to meet student cultural, linguistic, and academic needs. The study examined the best practices related to culturally responsive teaching (CRT) strategies to better meet all students' needs. A qualitative approach was used to collect data from licensed K-12 educators in New Mexico and Colorado. The findings revealed three essential themes: culturally responsive pedagogy, the positive impact of CRT, and the creation of physical spaces to support inclusivity. The findings revealed the significance of building strong relational capacity, encouraging collaboration, supporting multilingualism, and creating effective physical …

Why The “Whole Language Approach” To Reading Fails Ell Students & Instructional Strategies To Employ Instead, Caitlyn E. Petrus

Journal of English Learner Education

The research presented in this article demonstrates a qualitative view of the science of reading for phonemic awareness instruction, phonics instruction, vocabulary development, and reading comprehension strategies for English Language Learners (ELLs) in PK-12 schools. The research builds upon esteemed writers Dr. Sharon Vaughn and Dr. Sylvia Linan-Thompson’s work in their book Research-Based Methods of Reading Instruction for Learners, Grades K-4 and other reading experts such as Dr. Wiley Blevins and Dr. Lisa Moats to apply to the growing population for ELLs in PK-12 schools and how to shift from a “whole language classroom” to a classroom built on the …

Irish Environmental Humanities, Emily Reiff

James Joyce Literary Supplement

No abstract provided.

A Line Made By Farming, Seungho Lee

James Joyce Literary Supplement

No abstract provided.

Criticism By Other Means, Ericson Charlie

James Joyce Literary Supplement

No abstract provided.

Comparative Analysis Of Matrix Factorization And Neural Collaborative Filtering For Movie Recommendation Systems, Mahyar Alinejad

Data Science and Data Mining

This paper presents a comparative study of two recommendation system approaches for predicting movie ratings: Matrix Factorization with Stochastic Gradient Descent (SGD) optimization and Neural Collaborative Filtering (NCF) using Tensor Flow. The study aims to evaluate the effectiveness of these methods in recommending movies to users based on the MovieLens 100K dataset. The Matrix Factorization approach utilizes latent features to model user preferences and item characteristics, optimizing parameters through SGD. On the other hand, NCF integrates traditional collaborative filtering with neural networks to capture complex user-item interactions. Experimental results demonstrate the performance of both models in terms of Root Mean …

Detecting Physical Activity Using Wearable Sensor Data, Dipok Deb

Data Science and Data Mining

This study focuses on detecting physical activity using wearable sensor data, specifically distinguishing between walking and running. A dataset comprising accelerometer and gyroscope readings is used to train and evaluate various machine learning models, including logistic regression, random forest, k-nearest neighbors, naïve Bayes, and XGBoost. Extensive preprocessing, such as creating lag features and rolling statistics, is performed to enhance temporal data representation. The models are evaluated using metrics like accuracy, precision, recall, and F1 score. Incorporating lag and rolling features significantly improves model performance, with logistic regression achieving perfect scores across all metrics. These findings demonstrate the effectiveness of enhanced …

Public Health Simulation Infused Program (Pship) Toolkit, Desiree A. Díaz, Mindi Anderson, Francisco Guido-Sanz, Peggy Hill, Samantha Stephenson, Heather Peralta, Syretta Spears, Geraldine Luzincourt

Faculty Scholarship and Creative Works

Project Narrative

PURPOSE AND NEED

Purpose: Priorities set forth by the Health Resources & Services Administration (HRSA) are addressed in the proposed simulation program in an effort to meet curricular needs and foster care to the medically underserved in Florida, further exposing students to public healthcare needs. Interprofessional (nursing and social work) and intraprofessional (undergraduate nurse and Nurse Practitioner [NP]) instruction is essential in the simulation-based education (SBE) program, promoting important content on identifying risk factors and health assessment of the medically underserved community (MUC) (Education Priority 2, §831). Coordination of medical care is a vicarious learning opportunity for all …

Using Mini-Datasets To Build Quantitative Research Skills, Julio Montanez

Teaching Online Pedagogical Repository

This resource provides a gentle introduction to undergraduate students on the intricacies of creating quantitative datasets.

Performance Of Lasso And Ridge Regression For Variable Selection In Genome-Wide Association Studies Of Maize Flowering Time, Dipok Deb

Data Science and Data Mining

Genome-Wide Association Studies (GWAS) are instrumental in identifying genetic variants linked to complex traits, providing valuable insights into trait heritability and biological mechanisms. This study applies GWAS to investigate flowering time in maize, a critical adaptive trait, using a diverse dataset of 5,000 recombinant inbred lines across eight environments. Traditional GWAS methods often encounter challenges in high-dimensional datasets due to the presence of multiple small-effect genetic loci. To address this, we compared two penalized regression methods—LASSO and Ridge regression—to perform variable selection and regression analysis within a GWAS framework. LASSO effectively reduced the number of predictors by selecting the most …

Data Science Job Salary Prediction Using Linear Regression, Dipok Deb

Data Science and Data Mining

In the evolving landscape of data science, accurate salary prediction plays a crucial role in shaping career expectations, informing educational strategies, and guiding organizational hiring decisions. This study investigates the key factors influencing entry-level data science salaries in the United States by applying a multiple linear regression model to a recent dataset spanning from 2020 to 2024. Through data preprocessing, transformation, and diagnostic evaluation, we identify how job roles, experience levels, employment types, work arrangements, residency status, and company size impact compensation. Despite challenges such as outliers, heteroscedasticity, and non-normal residuals, model refinements like the Box-Cox transformation and variable selection …

Handwritten Digit Recognition Using Machine Learning, Dipok Deb

Data Science and Data Mining

Handwritten Digit Recognition (HDR) remains a fundamental benchmark in pattern recognition and machine learning due to its practical applications and inherent classification challenges posed by diverse handwriting styles. This study investigates and compares two classical statistical classifiers—Gaussian Naive Bayes (GNB) and Linear Discriminant Analysis (LDA)—to recognize the digits from the MNIST dataset. Both models assume underlying normality in feature distributions and offer computational efficiency, making them suitable for high-dimensional input such as image pixels. Using 60,000 training and 10,000 test samples, we evaluate model performance through accuracy, precision, recall, F1 score, and confusion matrices. The results reveal that while GNB …

Clustering Dataset Using K-Mean Clustering, Dipok Deb

Data Science and Data Mining

Clustering is a fundamental technique in unsupervised machine learning, widely applied in various domains such as pattern recognition, data segmentation, and anomaly detection. This study evaluates the performance of the K-Means clustering algorithm on multiple benchmark datasets, including low-dimensional, high-dimensional, and imbalanced datasets. The clustering results are assessed using four key evaluation metrics: Mean Squared Error (MSE), Adjusted Rand Index (ARI), Normalized Mutual Information (NMI), and Silhouette Score. Experimental results demonstrate that K-Means performs effectively on datasets with well-separated clusters, particularly in high-dimensional spaces, where it achieves near-perfect clustering accuracy. However, its performance deteriorates in datasets with overlapping clusters and …

Using Generative Ai To Enrich Instructional Videos With Embedded Quizzes, Efren De La Mora Velasco, Shaurya Agarwal

Teaching Online Pedagogical Repository

This entry describes a strategy to enhance student engagement in asynchronous online courses by embedding AI-generated quizzes into instructional videos. Using ChatGPT and video transcripts, the instructor created targeted multiple-choice questions that aligned with key video topics and improved interactivity. Results from the CGN5341 course showed increased video view duration, higher engagement, and positive student feedback on the usefulness of short, segmented videos with embedded quizzes.

Florida Fish And Wildlife Conservation Commission Comment Tool For Proposed Changes To Bear Hunting Regulations, Amy Donley, Jacquelyn Reiss, Alexandria Mcclarty, Elise Lorenzo

Institute for Social and Behavioral Science (ISBS)

No abstract provided.