Digital Commons Network^™

Effect Of Asynchronous Virtual Interviews On Ethnic Minority Matriculation Into A Doctor Of Physical Therapy Program, Conner Clark, Nanea Lagasca, Gladys Miller, Jasmine Puspos

UNLV Theses, Dissertations, Professional Papers, and Capstones

Purpose/Methods: This study examines the impact of the use of asynchronous virtual interviews (AVIs) in the admissions process of the Doctor of Physical Therapy (DPT) program at the University of Nevada, Las Vegas (UNLV). This research aims to examine racial and ethnic subgroup differences in AVI scores, evaluate the influence of AVIs on applicant scores in the admissions process, and assess the AVI inter-rater reliability among faculty evaluators using data from the 2019-2022 admissions cycles.

Results: Significant differences were found in AVI scores among racial and ethnic groups, with Black applicants scoring highest and Asian applicants scoring lowest. Additionally, inclusion …

Selectivity Studies Of Cbds Against Cb1 And Cb2 Using Docking Approach, Brandon Villanueva Sanchez, Andy Zhong

Theses/Capstones/Creative Projects

Cannabis sativa is an herbal plant that is used for recreational and medicinal purposes. The two main components, ∆9-Tetrahydrocannabinol (THC) and Cannabidiol (CBD), are responsible for the two different uses. Both compounds have been heavily researched, with their mechanisms of action, docking site, and binding affinity and efficacy identified. Researchers have synthesized various analogs by altering the carbon side chains of THC/CBD’s molecular structures. These synthetic analogs have been created to study the structure-function relationship of different molecules to the endocannabinoid system receptors, CB1 and CB2. Here, we conduct a docking study of various THC/CBD analogs to both receptors using …

Cybervictimization And Depression: A Cultural Standpoint, Paige Heagy

University Honors College

The author’s aim was to investigate the relationship between cybervictimization and depression, as well as using peer attachment and culture as moderators by giving questionnaires to 1347 participants (age range = 11-15 years) from India and the United States. Through four questionnaires, adolescents reported their levels of endorsement in either individualism or collectivism culture, levels of cybervictimization, levels of depression/depressive symptoms, and their levels of peer attachment. Adolescents reported that there is a significantly positive correlation between cybervictimization and depression. Differences were found according to culture and peer attachment, as well. Cybervictimization has begun to erupt worldwide as internet usage …

A Study Of Cybersecurity Landscape In The United States: Trend, Regional Variations, And Socioeconomic Factors, Trang Thi Thu Horn

All-Inclusive List of Electronic Theses and Dissertations

The Internet has become an essential part of our daily lives. Cyberspace has emerged significantly with an enormous number of users, creating a lucrative hunting field for cybercriminals. The exponential growth of internet users and online activities, along with the increased sophistication of cybercrimes, is raising significant global concerns for individuals, organizations, and governments. This research aims to explore the cybersecurity landscape in the United States, investigate regional variations, and the potential impact of the COVID-19 pandemic on the number of cybercrimes. The study utilizes a mixed research method approach, including historical analysis and a Delphi study. Historical analysis studied …

Learning Scene Semantics For 3d Scene Retrieval, Natalie Gleason

Honors Theses

This project presents a comprehensive exploration into semantics-driven 3D scene retrieval, aiming to bridge the gap between 2D sketches/images and 3D models. Through four distinct research objectives, this project endeavors to construct a foundational infrastructure, develop methodologies for quantifying semantic similarity, and advance a semantics-based retrieval framework for 2D scene sketch-based and image-based 3D scene retrieval. Leveraging WordNet as a foundational semantic ontology library, the research proposes the construction of an extensive hierarchical scene semantic tree, enriching 2D/3D scenes with encoded semantic information. The methodologies for semantic similarity computation utilize this semantic tree to bridge the semantic disparity between 2D …

Interpretation And Robustness Of Black-Box Ml Models For Secure Cyber Space, Qudrat E. Alahy Ratul

Boise State University Theses and Dissertations

The advent of sophisticated Machine Learning (ML) models has revolutionized the cybersecurity landscape, offering unprecedented capabilities to address complex challenges. Despite the ML model's capabilities, such models are still perceived as black boxes, the critical aspects of interpretability and robustness within these models often remain underexplored, rendering them susceptible to adversarial attacks and hindering their integration into sensitive applications. This dissertation focuses on interpretability and robustness of black-box ML models, aiming to fortify the cyberinfrastructure. Through a meticulous investigation of advanced techniques and methodologies, this work contributes towards elucidating and enhancing the interpretability and robustness of ML models in cybersecurity …

Care-Teach: Proposing An Open-Source Approach To Personalized Learning, Jaime Augusto Alvarez Perez

Theses and Dissertations

Care-Teach is an algorithmic educational model that provides teachers and educators with the tools to create interactive, text-based lessons that address a student’s need for continuity and reinforcement. Care-Teach is built around two core components: a Student Behavior Profile and the Skill Tree. These models work together to give each student a personalized learning experience that reinforces their pre-existing strengths and inclinations. The Student Behavior Profile model keeps track of a learner’s inclinations and mood, utilizing metrics such as average response time and accuracy to categorize opportunities for educator involvement. The Skill Tree is an organizational …

How Mathematics Instructors Foster The Development Of Black Students' Mathematics Identity In Undergraduate Active Learning Mathematics Courses, Ashly J. Olusanya

Theses and Dissertations

Black students must overcome unique challenges to succeed in mathematics. Educators are tasked with identifying equitable teaching practices to support these students. Active learning (AL) is a teaching pedagogy that engages students in rigorous mathematical activities and encourages student participation. This research study will explore the professors’ beliefs about how students learn mathematics and why they use active learning in their collegiate mathematics courses. The study explores the connections between these beliefs and their reported use of instructional practices. The study also identifies the instructors’ beliefs about developing students’ mathematics identities, particularly their Black …

The Perspectives Of Using Desmos For Students’ Conceptual Understanding And Procedural Fluency To Solve Linear Equations, Larmel Dimatulac Madrilejos

Theses and Dissertations

The study examines the perspectives of using the Desmos calculator of Algebra I students' conceptual understanding and procedural fluency to write, graph, and solve linear equations in Algebra I STAAR. While the students have continuously used technology for mathematics assessment, emergent bilingual students in South Texas still need help passing high-stakes testing. The framework of the study is grounded in the theory of mathematical education (knowledge of mathematics educators to teach), the theory of mathematical learning (understanding how students learn mathematics), and social constructivism. The study seeks ways to teach all students, mainly the minority, to learn …

Ethical Imperatives And Challenges: Review Of The Use Of Machine Learning For Predictive Analytics In Higher Education, Emily Barnes, James Hutson, Karriem Perry

Faculty Scholarship

The escalating integration of machine learning (ML) in higher education necessitates a critical examination of its ethical implications. This article conducts a comprehensive review of the application of ML for predictive analytics within higher education institutions (HEIs), emphasizing the technology's potential to enhance student outcomes and operational efficiency. The study identifies significant ethical concerns, such as data privacy, informed consent, transparency, and accountability, that arise from the use of ML. Through a detailed analysis of current practices, this review underscores the need for HEIs to develop robust ethical frameworks and technological infrastructures to navigate these challenges effectively. The findings reveal …

Multimodal Stylometry: A Novel Approach For Authorship Identification., Glory O. Adebayo

Electronic Theses and Dissertations

This dissertation introduces multimodal stylometry, a novel approach to authorship identification that integrates text and source code features for a comprehensive understanding of an author's unique style. Traditional stylometric methods have primarily focused on either text stylometry or source code stylometry, thereby neglecting the potential insights that multimodality may provide. This research aims to bridge this gap by proposing a framework that combines textual and source code data to enhance the accuracy and reliability of authorship identification. The study begins by reviewing existing literature on authorship identification and stylometry, highlighting the limitations of unimodal approaches. Leveraging recent advancements in multimodal …

Optimizing Adult Learner Success: Applying Random Forest Classifier In Higher Education Predictive Analytics, Emily Barnes, James Hutson, Karriem Perry

Faculty Scholarship

This study examines the application of the Random Forest Classifier (RF) model in predicting academic success among adult learners in higher education. It focuses on evaluating the model's effectiveness using key statistical measures like accuracy, precision, recall, and F1 score across a comprehensive dataset from 2013–14 to 2021–22, which includes variables such as age, ethnicity, gender, Pell Grant eligibility, and academic performance metrics. The research highlights the RF model's capability to handle large datasets with varying data types and demonstrates its superiority over traditional regression models in predictive accuracy. Through an iterative process, the study refines the RF model to …

Artificial Intelligence's Ability To Detect Online Predators, Olatilewa Osifeso

Electronic Theses, Projects, and Dissertations

Online child predators pose a danger to children who use the Internet. Children fall victim to online predators at an alarming rate, based on the data from the National Center of Missing and Exploited Children. When making online profiles and joining websites, you only need a name, an email and a password without identity verification. Studies have shown that online predators use a variety of methods and tools to manipulate and exploit children, such as blackmail, coercion, flattery, and deception. These issues have created an opportunity for skilled online predators to have fewer obstacles when it comes to contacting and …

Legislative Recommendations On Biometric Security And Privacy Jurisprudence, Joshua M. Morrow

All Student Scholarship

This project focuses on the prevalence of biometrics today, their various applications, and the biometric laws and legislations in place in the United States (U.S.) and Maine. Due to various threats and vulnerabilities imposing risk on collecting and using peoples’ biometric data, sufficient cyber protections related to citizens’ privacy rights, ethical control, and security of personally identifiable information (PII) must become necessary components of contemporary biometric laws and legislation. Without such explicit cyber protections, citizens participate in and comply with various technical domains and entities, such as private companies and governmental agencies, with minimal awareness or comprehension that their sensitive …

Developing Machine Learning Agency Among Youth: Characterizing Youth Critical Use, Examination, And Production Of Machine Learning Applications, Ibrahim Oluwajoba Adisa

All Dissertations

This study explores how middle school-aged youths at an afterschool center utilized, examined, and produced AI applications for social good with the support of adults and peers. The study employs a qualitative single case study design. It uses thematic analysis and quantitative ethnography methods to analyze data from multiple sources, including field notes, interviews, focus groups, story completions, video recordings, and artifacts. Findings indicated that engaging youths in critical exploration of AI tools enhanced their ability to design interest-based AI applications that provide solutions for healthcare problems, security, and accessibility. Moreover, the computational thinking practices that youth engaged in increased …

Exploring The Relationship Between Anxiety And Virtual Reality Sickness, David Wesley Woolverton

Graduate Theses and Dissertations (2019 - present)

As virtual reality (VR) becomes more commonly used in education, it is important to understand the technology’s weakness and mitigate any potential negative effects on student success. One adverse side-effect of VR use is simulation-induced motion sickness, known in the context of VR as VR sickness. Previous research by Howard and Van Zandt (2021) found that possessing a phobia had a significant positive correlation with VR sickness, but only if the phobia is triggered by the simulation, suggesting that symptoms are actually connected to the anxiety the phobia induces. This study explored the hypothesized correlation between anxiety and VR sickness, …

Resource Scarcity Caused By Environmental Changes: Driving Factor In Terrorism Attacks In Afghanistan, Pakistan, Syria, Amaris Bustamante

Open Access Theses & Dissertations

Climate change, resource scarcity, and terrorist attacks are ever-growing crises that disproportionately impact different states. They are crises that can impact the stability and resilience of humanity in the following decades if they are not addressed and mitigated. This study addresses the impact of resource scarcity caused by climate change that can then serve as a driving force in terrorist attacks in climate-sensitive and conflict-prone states. The objective of this mixed-methods study is to identify the correlation between climate changes that lead to resource scarcity such as rainfall and surface temperatures with terrorist attacks when taking into consideration other demographic, …

Identifying Temporomandibular Disorder Morphological Risk Factors Via Explainable Deep Learning And Multiscale Biomechanical Modeling, Shuchun Sun

All Dissertations

Clarifying multifactorial musculoskeletal disorder etiologies supports risk analysis and development of targeted prevention and treatment modalities. Deep learning enables comprehensive risk factor identification through systematic analysis of disease datasets but does not provide sufficient context for mechanistic understanding, limiting clinical applicability for etiological investigations. Conversely, multiscale biomechanical modeling can evaluate mechanistic etiology within the relevant biomechanical and physiological context. We propose a hybrid approach combining 3D explainable deep learning and multiscale biomechanical modeling; we applied this approach to investigate temporomandibular joint (TMJ) disorder etiology by systematically identifying risk factors and elucidating mechanistic relationships between risk factors and TMJ biomechanics and …

Design And Application Of Smart Systems To Address Analytical Problems, Lucas B. Ayres

All Dissertations

This dissertation is a multidisciplinary effort that integrates low-cost analytical instrumentation, redox chemistry, and artificial intelligence to overcome existing limitations in the fields of wearable sensing technology, Deep Eutectic Solvents (DES), and antioxidant chemistry. The overall goal behind each implemented strategy is to enhance the accuracy, efficiency, and accessibility of analytical processes and technologies. A general overview of the thesis, along with the research outcomes is included in Chapter One. The theoretical framework of this dissertation is presented in Chapter Two. Chapter Three describes the development of a wearable platform (sensor and instrumentation) to rapidly detect (~20 minutes) S. aureus …

Coarctation Duration And Severity Predict Risk Of Hypertension Precursors In A Preclinical Model And Hypertensive Status Among Patients, Arash Ghorbannia, Hilda Jurkiewicz, Lith Nasif, Abdillahi Ahmed, Jennifer Co-Vu, Mehdi Maadooliat, Ronald K. Woods, John F. Ladisa Jr.

Mathematical and Statistical Science Faculty Research and Publications

BACKGROUND:

Coarctation of the aorta (CoA) often leads to hypertension posttreatment. Evidence is lacking for the current >20 mm Hg peak-to-peak blood pressure (BP) gradient (BPGpp) guideline, which can cause aortic thickening, stiffening, and dysfunction. This study sought to find the BPGpp severity and duration that avoid persistent dysfunction in a preclinical model and test if predictors translate to hypertension status in patients with CoA.

METHODS:

Rabbits (n=75; 5–12/group) were exposed to mild, intermediate, or severe CoA (≤12, 13–19, ≥20 mm Hg BPGpp) for ≈1, 3, or 22 weeks using dissolvable and permanent sutures with thickening, stiffening, contraction, and endothelial …

Interpreting Shift Encoders As State Space Models For Stationary Time Series, Patrick Donkoh

Electronic Theses and Dissertations

Time series analysis is a statistical technique used to analyze sequential data points collected or recorded over time. While traditional models such as autoregressive models and moving average models have performed sufficiently for time series analysis, the advent of artificial neural networks has provided models that have suggested improved performance. In this research, we provide a custom neural network; a shift encoder that can capture the intricate temporal patterns of time series data. We then compare the sparse matrix of the shift encoder to the parameters of the autoregressive model and observe the similarities. We further explore how we can …

Vascular Brain Digital Twins For Medical Training And Education In Metaverse, Shamma Khaled Alghafri

Theses

This study addresses the need for innovative educational tools in the field of anatomy, specifically focusing on brain anatomy. The objective is to develop a virtual reality application and a 3D visualization that offer immersive and interactive learning experiences for students. The VR application, developed using Unity and designed for the Oculus Quest 2 headset, creates an immersive virtual laboratory environment. This environment includes interactive elements such as a table with buttons for displaying brain models and a whiteboard for user interaction. Users can manipulate and explore different brain structures, enhancing their understanding of complex anatomical features. Additionally, we integrated …

An Intelligent Academic Advising System For Course Recommendation Using Large Language Models, Malika Maya Iratni

Theses

Academic advising is an important resource for students, especially in higher education, in order to guide them to make the best possible decisions to improve their overall academic performance and overall academic journey. With the increasing number of students joining these institutions each year, traditional advising becomes a time-consuming and inefficient process that can leave students discouraged, and advisors overwhelmed. Therefore, there is a need to develop intelligent advising systems that make use of the recent advancements in technology, to support the advising process, and increase overall student satisfaction. In this work, an academic advising model that uses Recommender Systems …

Enabling Criticality-Aware Optimized Machine Perception At The Edge, Ila Nitin Gokarn

Dissertations and Theses Collection (Open Access)

Cyber-physical systems and applications have fundamentally changed people and processes in the way they interact with the physical world, ushering in the fourth industrial revolution. Supported by a variety of sensors, hardware platforms, artificial intelligence and machine learning models, and systems frameworks, CPS applications aim to automate and ease the burden of repetitive, laborious, or unsafe tasks borne by humans. Machine visual perception, encompassing tasks such as object detection, object tracking and activity analysis, is a key technical enabler of such CPS applications. Efficient execution of such machine vision perception tasks on resource-constrained edge devices, especially in terms of ensuring …

Identifying Disease-Related Gene-Environment Interactions Based On Method Of Moments, Linchuan Shen

UNLV Theses, Dissertations, Professional Papers, and Capstones

Human diseases are often caused by a complex interplay of multiple factors, including genetics and environmental factors. These factors can play critical roles in the development and progression of diseases. Although genome-wide association studies (GWAS) have successfully identified many genetic variants associated with human diseases, the estimated effects of these variants are small and can explain only a relatively small portion of the heritability of the underlying diseases.

Detecting gene-environment interactions (G × E) can shed light on the biological mechanisms of diseases. However, most existing methods that investigate G × E only look at how one environmental …

Online Learning For Acid-Fast Bacilli Detection In Histopathological Images, Shizhao Wang

UNLV Theses, Dissertations, Professional Papers, and Capstones

The acid-fast stain is frequently used for laboratory diagnosis of tuberculosis. It is a labor intensive task requiring thorough examination of extremely high-resolution images to pinpoint the presence of the mycobacteria. This paper presents a machine learning assisted slide image analysis tool with the aim of aiding histopathology professionals in the accurate diagnosis of tuberculosis in patients through the analysis of microscopic imagery. The proposed tool combines a digital whole slide image viewer with an online learning framework. We also conducted a survey of different state-of-the-art online learning methods, and found that MIR with pre-training has the best performance on …

Harnessing Social Media For Climate Action In Developing Countries: A Case Study Of Egypt, Nicolas Hamelin, Passant Halawa

Faculty Journal Articles

Like many developing nations, Egypt is facing a climate crisis due to its agricultural dependence and the Nile Delta’s vulnerability. Despite government plans for sustainable development, recent infrastructure projects have resulted in large-scale green space removal. Effective communication about environmental issues can spark pro-environmental behavior and citizen activism. This study explores social media’s potential to bridge this gap in Egypt. Utilizing Facebook AB testing with a limited budget, we reached a significant 2.3% of Egypt’s online population (nearly 2 million users). This study explored message framing, with findings showing that rational posts resonated best while fear appeals had minimal impact. …

Impact Of Pollution On Marginalized Communities: Case Study Of Omaha, Nebraska, Miqaela Davis

Department of Environmental Studies: Undergraduate Student Theses

Environmental justice has been a struggle within our country for years. The goal of Environmental justice is for the fair treatment and equal voice for every single individual regardless of race, income, gender, etc. There has been environmental injustice and racism in many cities, but this study focuses on Omaha, Nebraska. Key questions include: What are some specific pollutants that are prevalent in areas with differing racial majorities in Omaha? What are some of the health patterns in these areas and does it relate to environmental racism? How has Omaha reinforced environmental racism through city planning? Using the Climate and …

Educational Influences On Environmental Perception: A Semester Analysis Of The New Ecological Paradigm Scale In Undergraduates, Zoe Zingler

Department of Environmental Studies: Undergraduate Student Theses

This study evaluated the impact of a geography course, GEOG 181: Global Environmental Issues, at the University of Nebraska-Lincoln on students’ endorsement of the New Ecological Paradigm (NEP) using a pre-course and post-course NEP scale survey. Analyzing paired responses (n = 40) through t-tests and z-scores, only four of 15 statements had statistically significant shifts observed for the entire sample. However, a targeted analysis of students initially possessing lower endorsement of the NEP—early deniers—revealed significant paradigm shifts post-course. While women initially showed stronger NEP endorsement, men demonstrated notable changes following the course towards endorsement of the NEP. Academic majors, whether …

Understanding Stress And Coping Among Adults In The United States During The Covid-19 Pandemic, Jocy-Anna Chevalier

UNLV Theses, Dissertations, Professional Papers, and Capstones

Since the COVID-19 pandemic started, individuals in the United States (U.S.) and across the globe have experienced unprecedented levels of stress. The purpose of this study is to understand the stress experienced among adults in the U.S. and which coping processes affect their overall emotional well-being. Guided by Lazarus and Folkman’s (1987) Transactional Model of Stress and Coping (TMSC), this study conducted a secondary data analysis (n=404) of adults across the U.S who completed an online survey examining their experiences with stress and coping. A Pearson correlation was utilized to explore the relationship between stress and depressive symptoms. Paired samples …