Digital Commons Network^™

Advanced Algorithms For Cancer Cell Detection And Tracking, Qibing Jiang

Graduate Thesis and Dissertation 2023-2024

Microscopy image processing is critical for precision oncology and immunotherapy, two approaches in cancer treatment often combined to enhance patient outcomes. Numerous scientists have studied the effects of drugs on the immune system and tumors. To quantify the impact of various drugs on different immune and cancer cell types, medical researchers conduct ex vivo assays. In these assays, patient-derived live cells are placed in an artificial microenvironment where drug responses are monitored over time. Brightfield microscopy captures one image every half hour of numerous patient-derived cells in an ex vivo reconstruction of the tumor microenvironment treated with 31 drugs for …

Connecting In Crisis: Exploring Online Informal Communications In Florida’S Unemployment Struggle, Anna V. Eskamani

Graduate Thesis and Dissertation 2023-2024

The COVID-19 pandemic led to widespread unemployment, significantly impacting Floridians who faced delays and systemic issues with the state's unemployment system. This study examines crisis communication within a Reddit community, focusing on how individuals used informal communications to navigate the unemployment benefits crisis. Guided by Rhetorical Arena Theory (RAT) and Uses and Gratification Theory (U&G), the research addresses: (1) How did individuals in the active audience discuss challenges faced when trying to access Florida’s unemployment system? (2) What lessons can be drawn from the analysis of informal communications on social media for improving crisis communication strategies during future crises? A …

Examining How Pejorative Stereotypes About Black Women Shape Their Experiences In Physics Ph.D. Programs, Camille A. Coffie

Graduate Thesis and Dissertation 2023-2024

This research study is part of a larger study that examines the experiences of Black women in physics graduate programs to identify priorities for departmental change initiatives to remove structures that keep out and/or push out Black women. This research also reinforces the ongoing necessity to raise awareness about the impact of stereotypes on how Black women are perceived and how stereotypes affect the matriculation of Black women in physics graduate programs. Black women represent the lowest percentage of students in physics graduate programs and often contend with stressors like microaggressions, bias, and stereotype threats that impede their success and …

Spectral Approaches For Characterizing Heterogeneity In Infectious Disease Models, Seoyun Choe

Graduate Thesis and Dissertation 2023-2024

Heterogeneity, influenced by diverse factors such as age, gender, immunity, behavior, and spatial distribution, plays a critical role in the dynamics of infectious disease transmission. Discrete mathematical structures, including matrices and graphs, can offer effective tools for modeling the interactions among these diverse factors, resulting heterogeneous epidemiological models. This dissertation explores analytical approaches, specifically utilizing eigenvalues and eigenvectors of discrete structures, to characterize heterogeneity within mathematical models of infectious diseases. Theoretical results, along with numerical simulations, enhance our understanding of heterogeneous epidemiological processes and their significant implications for disease control strategies.

In this dissertation, we introduce a unified approach to …

Globalizing Tele-Support Coaching: Exploring The Impact Of Online Adaptations Of Practice-Based Coaching For Special Education Teachers And Related Personnel, Danica Tania Moise

Graduate Thesis and Dissertation 2023-2024

The global prevalence of autism spectrum disorder (ASD) presents significant challenges, particularly in low- and middle-income countries (LMIC) where there is a lack of trained professionals, limited access to evidence-based practices, and insufficient government support. This dissertation explores the potential of technology-based interventions to bridge the knowledge gap and improve the quality of services for children with ASD in LMIC.

The first chapter provides an overview of the current landscape of educator preparatory programs and highlights the limitations of traditional clinical experiences in preparing special education teachers and related personnel. It introduces the Tele-Support Coaching Framework (TCF) as a promising …

Mesmerizing Moon Mysteries: Unraveling The Compositions Of Irregular Mare Patches (Imps) Using Remote Observations, Nicholas G. Piskurich

Graduate Thesis and Dissertation 2023-2024

Compositional characterization of lunar surface features informs our understanding of the Moon's thermal and magmatic evolution. We investigated the compositions of hypothesized volcanic features known as irregular mare patches (IMPs) and their surroundings to constrain formation mechanisms. We used six datasets to assess the composition of 12 IMPs: 1) Moon Mineralogy Mapper (M³) derived spectral parameters (e.g., band center positions, shapes), 2) Lunar Reconnaissance Orbiter (LRO) Diviner Radiometer Experiment (Diviner) measured Christiansen feature (CF) position, 3) SELENE (Kaguya) Multiband Imager (MI) FeO abundance, 4) Clementine 5-band (Ultraviolet/Visible)-derived FeO abundance, 5) LRO Wide Angle Camera (WAC) TiO₂ abundance, …

Optical Seed Development For Yb-Fiber Laser, James G. Brutus

Graduate Thesis and Dissertation 2023-2024

Master Oscillator Power Amplifiers (MOPA) are laser systems that utilize a seed and pump amplification system to boost the output power of high-quality lower power seeding signals. MOPAs can generate high gain while avoiding many of the nonlinearities that negatively affect resonance-based lasers that are known to feature higher internal intensities. Additionally, MOPAs provide an easy alternative to the construction of novel laser technologies for higher output power as they can be easily combined with existing laser sources to amplify their output power.

This thesis outlines the design of an ytterbium-doped fiber laser (YDFL), featuring a MOPA architecture. The YDFL …

The Case For Photothermal Spectroscopy In The Future Of Planetary Science Missions, Christopher T. Cox

Graduate Thesis and Dissertation 2023-2024

Optical PhotoThermal InfraRed (O-PTIR) is a relatively new spectroscopy method for studying materials. It produces transmission-like spectra using a remote reflectance technique that is rapid, requires little sample preparation, and is well-suited for the technique to be adapted for a space flight instrument. The method involves a tunable pulsed IR laser creating a photothermal effect on the surface of a material and measuring the distortion of a probing visible laser in the same region of the sample, which can be obtained at sub-micron spatial resolutions. A measurement campaign was performed utilizing Photothermal Spectroscopy Corporation's O-PTIR instrument, mIRage®. In this campaign, …

From Crisis To Classroom: Evaluating Academic Success In Vulnerable Populations During The Covid-19 Emergency Education Era, Jake Novak

Graduate Thesis and Dissertation 2023-2024

This study investigated school closures' impact on students from vulnerable populations in elementary classrooms. The research places an emphasis on the importance of an equitable and effective educational system in every community. It highlights the role of formal education in providing opportunities for social advancement and promoting the development of individuals and nations. The impact of the COVID-19 Emergency on access to quality education and the challenges and inequities faced by vulnerable populations are emphasized. This research also discusses the Sustainable Development Goals (SDGs) established by the United Nations in 2015 to ensure inclusive and equitable education for all children …

Impacts Of Professional Development On Elementary Mathematics Teachers' Implementation Of Cognitively Demanding Tasks, Maria Porras Monroy

Graduate Thesis and Dissertation 2023-2024

This study provided insight into the impact a professional development series on cognitively demanding tasks had on teachers’ identification and implementation of tasks, as well as, determined which aspects of the professional development were beneficial to participants’ understanding of cognitively demanding tasks. The professional development included five sessions and was centered on the Instructional Quality Assessment (IQA) Potential of the Task and Implementation of the Task Rubrics (Boston et al., 2019). As part of the study, participants submitted tasks and student artifacts pre and post professional development. The investigation included an analysis of tasks, student artifacts, and a thematic analysis …

A Multiscale Meshless Method For Simulating Cardiovascular Flows, Kyle Beggs

Graduate Thesis and Dissertation 2023-2024

The rapid increase in computational power over the last decade has unlocked the possibility of providing patient-specific healthcare via simulation and data assimilation. In the past 2 decades, computational approaches to simulating cardiovascular flows have advanced significantly due to intense research and adoption of methods in medical device companies. A significant source of friction in porting these tools to the hospital and getting in the hands of surgeons is due to the expertise required to handle the geometry pre-processing and meshing of models. Meshless meth- ods reduce the amount of corner cases which makes it easier to develop robust tools …

Visual Experience Enhancement In Augmented Reality Displays, Qian Yang

Graduate Thesis and Dissertation 2023-2024

In the dynamic arena of display technology, augmented reality (AR) displays represent a pivotal advancement, seamlessly bridging the digital and physical worlds. This dissertation delves into the realm of AR display technologies, spotlighting the challenges and limitations of current systems, including transparent and near-eye displays, and proposes innovative solutions to enhance user experience and display performance. With a focus on overcoming issues such as diffraction-induced image blur, the trade-off between resolution and field of view (FoV) in near-eye displays, and FoV constraints in waveguide-based displays, this research introduces new evaluation methods, optimization techniques, and system designs. First, the dissertation presents …

Opto-Electronic Oscillator Driven Electro-Optic Modulator Based Optical Frequency Comb, Lawrence Trask

Graduate Thesis and Dissertation 2023-2024

Optical frequency combs (OFC) are now a well-known tool for utilizing broad optical bandwidths with electronic resolution. Several applications including spectroscopy, metrology, ultra-wideband signal processing, and communications are being propelled forward by optical frequency combs. The advent of high repetition rate optical frequency combs for use in astrophotonics has elucidated the need for newer architectures. This dissertation discloses a self-oscillating, self-stabilizing, and self-referenced opto-electronic oscillator (OEO) driven electro-optic modulated (EOM) based optical frequency comb. We demonstrate a new path towards high repetition rate OFCs with two major developments. The use of a photonically filtered OEO simultaneously stabilizes the optical carrier …

Validating Machine And Human Decision-Making In Forensic Fire Debris Analysis, Frances A. Whitehead

Graduate Thesis and Dissertation 2023-2024

This work presents a background on the chemical complexity of fire debris analysis, including an ever-present matrix of pyrolysis products as the catalyst that led to the creation of the National Center for Forensic Science's Fire Debris Database. A selection of these 1,000+ casework-relevant ground truth samples was used to create two newly proposed analyst workflows to connect the current method of categorical reporting with evaluative reporting practices reflective of the strength of the evidence. Both workflows use linear sequential unmasking to help mitigate bias, a discrete scoring system for quantification of the analysis, and receiver operating characteristic (ROC) curves …

An Analysis Of Teacher Characteristics And Perceptions Of Grading Practices On Student Grade Outcomes, Michael B. Meechin

Graduate Thesis and Dissertation 2023-2024

The purpose of this study was to examine the relationship, if any, between teachers' grade distributions and other moderating factors (i.e., teacher perceptions of grading practices as indicated on the Teacher Perceptions of Grading Practices Survey (TPGPS), grade level taught, enrollment in teacher preparation program, and grading practice methodology). A Pearson correlation was used to research statistical significance in the relationship of a teacher’s perceptions of grading practices as measured by the TPGPS and their grade distribution (as measured by an average of scores, calculated on a 4.0 scale, in one course over one academic quarter). A one-way ANOVA was …

Dual Frequency Comb Mid-Ir – Thz Spectroscopy, Dmitrii Konnov

Graduate Thesis and Dissertation 2023-2024

The optical frequency comb is a coherent light source whose spectrum consists of hundreds of thousands perfectly equidistant narrow frequency components and precisely expressed in just two radio frequencies. Even though optical frequency combs were developed 25 years ago, that led to the Nobel Prize in Physics 2005, only recently there was a significant progress in generating broadband optical frequency combs in the mid-infrared. These achievements became possible due to the development of new types of robust fiber and solid-state lasers and the efficient downconverting of their frequencies through different techniques based on advanced nonlinear crystals. In this dissertation, I …

Understanding Health-Seeking Decision-Making Process And Behavior Among Haitian Immigrants: A Grounded Theory Approach, Shelleta Ladonice

Graduate Thesis and Dissertation 2023-2024

Black people in the U.S. die at younger ages, have significantly higher rates of death from treatable medical conditions, are more likely to have late-stage breast and colon cancer diagnoses and more likely to die from these cancers, and are at higher risk for chronic illnesses compared to other racial and ethnic groups. Accessing healthcare is crucial to health and well-being; however, U.S. immigrants' use of healthcare services is far less than native-born Americans. Haitian immigrants experience health disparities at the highest rate compared to other Black immigrants in the U.S. Given their unique history, culture, and immigration experience, it …

Human Visual Search Performance For Close Range Detection Of Static Targets From Moving Sensor Platforms, Jennifer Hewitt

Graduate Thesis and Dissertation 2023-2024

Search models based on human perception have been developed by military researchers over the past few decades and have both military and commercial applications for sensor design and implementation. These models are created primarily for static imagery, and accurately predict task performance for systems with stationary targets and stationary sensors, if the observer is given infinite time to make targeting decisions. To account for situations where decisions must be made on a shortened time scale, the time-limited search model was developed to describe how task performance evolves with time. Recent variations of this model have been made to account for …

Enhancing Scanning Tunneling Microscopy With Automation And Machine Learning, Darian Smalley

Graduate Thesis and Dissertation 2023-2024

The scanning tunneling microscope (STM) is one of the most advanced surface science tools capable of atomic resolution imaging and atomic manipulation. Unfortunately, STM has many time-consuming bottlenecks, like probe conditioning, tip instability, and noise artificing, which causes the technique to have low experimental throughput. This dissertation describes my efforts to address these challenges through automation and machine learning. It consists of two main sections each describing four projects for a total of eight studies.

The first section details two studies on nanoscale sample fabrication and two studies on STM tip preparation. The first two studies describe the fabrication of …

Towards Energy-Efficient In-Memory Computing Systems Using Electronic Design Automation, Muhammad Rashedul Haq Rashed

Graduate Thesis and Dissertation 2023-2024

The exponential growth in digital data has fueled the emergence of data-intensive applications like large language models, digital twins, and metaverse. These applications have unprecedented computing demands that exceed the capabilities of today's high-performance computing systems. To address this challenge, new computing paradigms are being explored. One promising solution is to perform processing in memory (PIM) using emerging hardware. However, PIM paradigms are still in their infancy. A major obstacle to the widespread adoption of PIM paradigms is the lack of advanced electronic design automation (EDA)-based designs to ensure the system is both robust and energy-efficient.

This dissertation presents electronic …

Exploring The Challenges Of First Grade Students' Non-Exit From Mathematics Intervention: A Comparative Analysis Of Mathematics Instruction And Best Practices During Intervention, Lori Hart

Graduate Thesis and Dissertation 2023-2024

This qualitative study aimed to examine the challenges surrounding the non-exit of first grade students from mathematics intervention programs, particularly focusing on Atlantic Elementary School within the Gulf County Public School District. Against the backdrop of declining mathematics proficiency, exacerbated by the COVID-19 pandemic, this study investigates the effectiveness of mathematics intervention and its alignment with best practices in mathematics instruction. While mathematics intervention aims to support students needing additional support with mathematical concepts, there exists a notable gap in understanding why many primary students do not transition successfully from mathematics intervention on grade level prior to advancing to the …

Lesson Study As A Catalyst For Including Concepts And Procedures In Planning And Implementing Fraction-Based Mathematics Lessons: An Elementary School Case Study, Nisha A. Phillip Malahoo

Graduate Thesis and Dissertation 2023-2024

This qualitative case study investigated how lesson study influenced teachers’ pedagogical strategies and content knowledge by leveraging the interplay between conceptual understanding and procedural fluency, with conceptual knowledge forming the foundation for procedural fluency in the planning and implementation of fraction-based mathematics tasks. The study aimed to address two research questions: (1) How does the engagement of teachers in the creation and analysis of fraction-based mathematics tasks in lesson study influence their instructional decision-making processes? and (2) How do teachers construct pedagogical strategies that integrate procedural and conceptual knowledge through lesson study? The sample size consisted of seven elementary school …

Advancing Policy Insights: Opinion Data Analysis And Discourse Structuring Using Llms, Aaditya Bhatia

Graduate Thesis and Dissertation 2023-2024

The growing volume of opinion data presents a significant challenge for policymakers striving to distill public sentiment into actionable decisions. This study aims to explore the capability of large language models (LLMs) to synthesize public opinion data into coherent policy recommendations. We specifically leverage Mistral 7B and Mixtral 8x7B models for text generation and have developed an architecture to process vast amounts of unstructured information, integrate diverse viewpoints, and extract actionable insights aligned with public opinion. Using a retrospective data analysis of the Polis platform debates published by the Computational Democracy Project, this study examines multiple datasets that span local …

Application Of Artificial Intelligence In The Study Of Saturated And Unsaturated Hydraulic Properties Of Compacted Soil Barriers In Landfills, Poyu Zhang

Graduate Thesis and Dissertation 2023-2024

Machine learning models (MLMs) were developed to predict the saturated hydraulic conductivity of compacted soil barriers and help to identify appropriate soils for the construction of landfill liners and covers. Three machine learning algorithms (random forest, gradient boosting decision tree, and neural network) were used to develop MLMs, and multiple linear regression was used to compare the precision of predictions with the MLMs. Results from this study showed that the random forest model provided the best prediction of the hydraulic conductivity of compacted soil barriers, with 100% of predicted hydraulic conductivity within 100-time differences to measured hydraulic conductivity and 93% …

Exploring How Administrative Factors Including Mentoring, Compensation, And Workload Impact The Retention Rates Of Novice Title I Teachers, Danielle Jones

Graduate Thesis and Dissertation post-2024

This study explores the administrative factors impacting the experiences and retention rate of Title I beginning-year teachers that have 1-3 years of experience. Considering Title I schools primarily serve students from marginalized backgrounds, understanding the role of administrative factors becomes crucial. These factors significantly influence both student outcomes and teacher effectiveness, emphasizing the need for further exploration. For this reason, this research seeks to identify and understand the impacts administrative structures have on the performance, satisfaction, and retention of new teachers in Title I schools. This quantitative study will examine the experiences and outcomes of new teachers in Title I …

Bootstrap Regression For Investigating Macroeconomics Factors Affecting Usa Home Prices, Benedict Kongyir, Emil Agbemade

Data Science and Data Mining

This study investigates the impact of macroeconomic indicators on US home prices, underscoring the importance of understanding these dynamics due to their signifcant socioeconomic consequences. Utilizing a dataset from Kaggle, originally collected by FRED, the research examines variables like the Consumer Price Index, Population, Unemployment, GDP, Stock Prices, Income, and Mortgage Rate to discern their efect on housing market fuctuations. The analysis identifes multicollinearity among predictors, necessitating a shift from traditional multiple linear regression to a more robust bootstrap regression method due to violations of parametric assumptions. Key fndings reveal that Real Disposable Income is a signifcant predictor of home …

Combating Cyberbullying On Social Media: A Machine Learning Approach With Text Analysis On Twitter, Amir Alipour Yengejeh

Data Science and Data Mining

The popularity of the electronic mobile devices along with social media as well as networking websites have been tremendously increased in the recent year. Most people around the world daily engage in the variety of cyberspace additives. Even though the users can take most advantages of these system such as exchange the idea and information, being sociable, and enjoyments, they might be faced with such adverse behaviors such as toxicity, bullying, extremism, and cruelty. The recent statistics reports that such mentioned behaviors has been noticeably grown on the cyberspace such that can threaten the individuals and even any community. Thus, …

Predicting Road Accident Injury Severity For Drivers In Automobile Crashes In United States Using Machine Learning Models And Ai, Emil Agbemade, Benedict Kongyir

Data Science and Data Mining

This study analyzes data from the National Highway Trafc Safety Administration’s 2021 Crash Report Sampling System to identify key factors contributing to the severity of injuries in car accidents. By utilizing various machine learning algorithms and cross-validation techniques, we assessed metrics such as accuracy, sensitivity, precision, specifcity, and the area under the curve (AUC) to evaluate the efectiveness of predictive models. All data preprocessing and model building was done using KNIME Analytical software [9]. Our fndings reveal signifcant correlations between certain variables such as airbag injection, weather conditions, intoxication, vehicle state, driver distractions, and injury severity. These insights underscore the …

Diagnostic In Neuroimaging: A Comparative Study Of Deep Learning And Traditional Approaches, Amina Issoufou Anaroua

Data Science and Data Mining

In the realm of medical diagnostics, precise classification of brain tumors is pivotal. This study conducts a comprehensive comparative analysis of a Convolutional Neural Network (CNN) against traditional machine learning models, Logistic Regression (LR) and Support Vector Machines (SVM) on a dataset of MRI scans for multi-class brain tumor classification. The CNN, tailored for image recognition, is evaluated alongside LR and SVM, which have established benchmarks in classification tasks. The investigation reveals that the traditional models hold their ground in terms of precision and interpretability, with the SVM, in particular, achieving remarkable accuracy. However, the CNN distinguishes itself by demonstrating …

The Impact Of Gun Violence: A Study On Mass Killings In The United States, Abigail Wright, Oma Persaud, Tindrew Chen

High Impact Practices Student Showcase Fall 2024

This study examines the impacts of gun violence in the United States from 2006 to October 2024, focusing on factors influencing the casualties in mass shooting incidents. Utilizing the predictors: number of offenders, region, location, incident type, and gun type we employed a Negative Binomial Regression Model due to its suitability for handling high variance and over-dispersion in the response variable. The dataset "Mass Killings in America" reports 1,018 casualties from over 100 incidents in the past four years alone. This research sheds light on correlations between the predictors and response, providing valuable insights to enhance community vigilance and prevention …