Digital Commons Network^™

Alarm Fatigue Among Georgia Southern University Nursing Students: Examining Clinical Effects And Preventive Interventions, Madison T. Mills

Honors College Theses

Alarm fatigue, a response to constant exposure to clinical devices’ alarms that can lead to a decrease in responsiveness and safety in healthcare settings. Although it’s well researched in practicing nurses, yet there isn’t much known if alarm fatigue can start in nursing school and how it affects nursing students when in clinical settings. This study examines the importance and effects of alarm fatigue among Georgia Southern University nursing students and the faculty/staff through a mixed-methods survey. Prior research suggests that alarm fatigue can be developed through clinical exposure. Educational and technological interventions, such as alarm-management training and improved monitoring …

Investigating Patient Reported Outcomes (Pros) Of Long Covid, Luke A. Sims

Summer Research Program Abstracts

No abstract provided.

Interpreting The Trispectrum As The Cross-Spectrum Of The Wigner-Ville Distribution, Aviva Abosch

All Publications

The fourth-order time-invariant spectrum, or trispectrum, has a simple derivation as the cross-spectrum among frequency bands in the Wigner-Ville distribution (WVD). Viewed this way, the trispectrum gains intuitive meaning as a measure of the linear dependence of power across frequencies, which yields some insight into its structure and interpretation. We highlight, in particular, a two-dimensional subdomain as useful for identifying modulated oscillations when the modulating envelope is non-negative or lowpass. Spectral characteristics of the carrier and modulating signals are revealed along separate axes of a two-dimensional representation of this domain. The application of this framework, combined with a previously described …

Efficacy And Engagement In Digital Acceptance And Commitment Therapy: A Meta-Analysis And Investigation Of Mechanisms, Korena S. Klimczak

All Graduate Theses and Dissertations, Fall 2023 to Present

Digital mental health interventions offer a more accessible, affordable, and flexible option for mental health support. These apps and websites draw from the same therapeutic models as face-to-face therapy, but are available on demand at a fraction of the cost. In exchange, digital formats give up the personal relationship, accountability, and scheduled structure that keep people connected to treatment. This places a greater burden on users to stay involved on their own, and as a result, engagement is widely believed to be the main bottleneck limiting the impact of digital mental health care.

This dissertation examined engagement in digital programs …

International Aid And Post-Conflict Recovery In The Western Balkans, R. Mary Wall

All Graduate Theses and Dissertations, Fall 2023 to Present

After violent conflicts end, communities often receive international support to help rebuild their governments and economies. This study asks whether aid targeted toward physical reconstruction and institutional reform produces measurable outcomes in those areas. 

Examining five Western Balkans countries between 2000 and 2021, the study finds that infrastructure aid is associated with improved access to clean water and reductions in displaced populations, while aid directed toward strengthening government institutions shows no measurable association with improvements in government effectiveness within the same period. These findings suggest that in the years immediately following conflict, physical reconstruction produces more observable improvements than institutional …

Nature-Based Therapy In The Uae: Leveraging Ecosystems To Alleviate Depression And Anxiety, Aya Abdul Karim Al-Taani, Mahmoud Mohammad Al-Gharaibeh, Ahmed A. Al-Taani

All Works

This review synthesizes current evidence on the relationship between natural ecosystems and mental health outcomes with a particular focus on arid and rapidly urbanizing contexts such as the United Arab Emirates (UAE). It introduces the Multi-Ecosystem Therapeutic Framework for Arid Urban Environments, which moves beyond generalized "nature exposure" models by systematically linking distinct environmental systems to mental health outcomes through identifiable psychological, physiological and social mechanisms. The framework is structured around three interconnected components: ecosystem types (urban green spaces, desert landscapes, mountain environments and blue spaces), mediating mechanisms (including psychological restoration, stress reduction, physical activity and social interaction) and mental …

Hed-Id: A Federated Expert System For Interpretable And Resource-Adaptive Intrusion Detection On Edge Devices, Kushboo Nasir, Sahar K. Badri, Asad Khattak, Daniyal M. Alghazzawi, Mohammed Yahya Alghamdi, Mona Alkhozae, Abeer Almakky, Rania M. Alhazmi, Muhammad Zubair Asghar

All Works

The proliferation of edge computing in industrial and IoT networks necessitates expert systems that support accurate, interpretable, and resource-efficient intrusion detection under strict privacy and computational constraints. This paper presents HED-ID, a fully integrated federated expert system designed for real-time, edge-oriented anomaly detection. The system combines: (i) a stacked bidirectional GRU (BiGRU) architecture with hybrid temporal–spatial attention for sequential and feature-level anomaly modeling, (ii) a resource-adaptive Grey Wolf Optimizer (A-GWO) that modulates exploration–exploitation behavior based on real-time CPU utilization and Bayesian epistemic uncertainty, with formal convergence proof under bounded resource shifts (Appendix A), (iii) federated SHAP, which aggregates local explanations …

Fine-Tuning Large Language Models For Binary And Multiclass Target-Specific Hate Speech Detection, Sanaa Kaddoura, Sumaia Al-Kohlani

All Works

Social media platforms are widely used by individuals from diverse demographic backgrounds to share their opinions and daily experiences. The anonymity provided by these platforms has increased the prevalence of hate speech, causing significant psychological harm to targeted groups. Existing hate speech detection approaches predominantly rely on binary classification, which fails to capture the lexical and contextual diversity of hate categories, leading to the misclassification of hate against minority groups. This study addresses this limitation by evaluating the effectiveness of five large language models (LLMs) for target-specific multiclass hate speech detection across six classes. The evaluation uses a dataset of …

Tennessee General Education Preschool Teachers’ Perceptions Of Their Preparedness To Teach Young Children With Disabilities, Misty M. Moody

Electronic Theses and Dissertations

Under the Individuals with Disabilities Education Act (IDEA), local education agencies (LEAs) must educate young children with disabilities in the least restrictive environment (LRE) while ensuring opportunities to learn alongside their non-disabled peers. As inclusive opportunities for preschool-aged children with disabilities continue to expand, general education preschool teachers play an important role in providing instruction that meets the diverse needs of all children. However, limited research has examined general education preschool teachers’ perceptions of their preparedness to teach young children with disabilities, particularly in Tennessee.

This qualitative study explored Tennessee general education preschool teachers’ perceptions of their preparedness to teach …

Adaptive Active Snore Noise Control Using Microphone And Loudspeaker Arrays, Nathan Walker

All Graduate Theses and Dissertations, Fall 2023 to Present

Snoring can wreck a good night’s sleep, not just for the snorer but for their partner, and over time it can strain relationships. Common fixes like CPAP machines, nasal strips, and earplugs either have to be worn or don’t do much against the deep, low-pitched rumble that makes snoring so hard to ignore.

This research explores a different approach, a device that doesn’t need to be worn at all. It uses a small set of microphones to listen to the snoring and a set of speakers to play back carefully timed anti-snore noise, which is sound designed to cancel out …

Scalable Quality Assessment Of Ground Motion Records Via Interpretable Deep Learning Architectures, Ali Montazeri Namin

All Graduate Theses and Dissertations, Fall 2023 to Present

Earthquake engineers rely on accurate recordings of ground shaking to design safe and resilient buildings. However, sorting through thousands of these recordings to find the reliable ones and throwing out those ruined by sensor errors or background noise is traditionally done by hand. Because modern seismic networks collect massive amounts of earthquake data every day, this manual checking process is much too slow. To fix this, researchers are turning to artificial intelligence to automatically check the quality of these recordings.

While artificial intelligence offers a fast solution, there are limitations. These computer models can become massive and expensive to run, …

Cascaded Pid Control Of A Passive Bio-Inspired Rotating Empennage Aircraft, Zachary T. Jenkins

All Graduate Theses and Dissertations, Fall 2023 to Present

This thesis presents an autopilot for a Bio-Inspired Rotating Empennage (BIRE) aircraft. Most airplanes control yaw using a vertical stabilizer and a moving rudder, a design that has stayed essentially unchanged for nearly a century but adds weight, drag, and surface area to the aircraft. The BIRE removes the vertical tail entirely and instead allows the horizontal tail to rotate about the body x-axis of the airplane; tilting the horizontal tail produces a yaw force, doing the job of a rudder. This thesis first develops a controller for the BIRE where the empennage angle is commanded directly, then extends …

Physics-Data-Hybrid Modeling And Control For Vtol Aircraft, Samantha Dawn Burton

All Graduate Theses and Dissertations, Fall 2023 to Present

Vertical takeoff and landing (VTOL) aircraft are hybrid aircraft having both a helicopter flight mode and a fixed-wing plane flight mode. The objective of this dissertation is to examine and evaluate a new approach, physics-data-hybrid (PDH), for VTOL aircraft modeling and control. The PDH approach combines traditional, physics-based methods (Newtonian mechanics) with data driven methods (a machine learning technique called a Koopman operator model) to create an efficient and accurate modeling and control framework—mitigating the disadvantages of the purely physics-based and purely data-driven methods. The PDH approach is used to model scenarios when the VTOL aircraft transitions between helicopter mode …

Enhancing Agricultural Sustainability Under Climate Change: A Multi-Scale Framework Integrating Climate Extremes, Resource Efficiency, And Data-Driven Modeling, Shahryar Fazli

Computational and Data Sciences (PhD) Dissertations

Agricultural systems are increasingly challenged by climate variability, where shifting temperature regimes, hydrological variability, and the rising frequency of compound and cascading extremes threaten global food security and resource sustainability. Addressing these challenges requires integrated frameworks that bridge biophysical monitoring, predictive modeling, and adaptive decision-making. This dissertation develops a data-driven, multi-scale framework to quantify and enhance agricultural resilience by integrating remote sensing, climate analytics, and machine learning across the United States, with a focus on California and the Western U.S.

First, hyperspectral and thermal remote sensing data from EMIT and OpenET are integrated to characterize crop nitrogen–water interactions and assess …

Beyond Symptoms: Examining Perinatal Mental Health Care Among Black, Indigenous And People Of Color With Polyendocrine Metabolic Ovarian Syndrome, Vinaya Thomas

Electronic Theses and Dissertations

Perinatal mood and anxiety disorders (PMADs) are as a public health concern in the United States. Individuals from minoritized racial/ethnic groups face a significantly elevated risk of maternal morbidity, mortality, mental health disorders, and associated adverse outcomes. Emerging studies also reveal a higher likelihood of experiencing perinatal mental health concerns in individuals with polycystic ovarian syndrome (PCOS), currently known as polyendocrine metabolic ovarian syndrome (PMOS). People who identify as Black, Indigenous, or a person of color (BIPOC) face unique healthcare challenges given the added structural and social burdens. This online survey study aimed to 1) understand the relationship between PMOS …

Kinesiology Department Chairs’ Perceptions Of Their Training And Preparation, Kason O’Neil

Electronic Theses and Dissertations

Department chairs are responsible for leading academic departments in higher education.  These individuals regularly make important decisions regarding such things as managing faculty and academic programming, overseeing budgets, and supporting student needs. Despite these responsibilities, many people become department chairs without receiving formal leadership training. This study explored how kinesiology department chairs across the United States viewed their preparation for the role and the importance of leadership training. A total of 111 department chairs completed an online survey about their background, previous training, and the importance of training for different administrative responsibilities. The results showed that most chairs had little …

Analysis Of U.S. Army Body Composition Policies: Implementation Effectiveness And Recommendations For Policy Enhancement At Brooke Army Medical Center, Michael L. Rizzo

Doctor of Nursing Practice (DNP) Manuscripts

US Army body composition policies (AR 600-9 and recent directives) are essential for military readiness, injury prevention, and force health protection, yet implementation gaps persist, particularly with the 2026 Department of Defense (DoD)-mandated waist-to-height ratio (WHtR < 0.55) transition. This DNP project evaluated policy implementation effectiveness at Brooke Army Medical Center using the W.K. Kellogg Foundation Logic Model and CFIR 2.0 framework. Analysis of 2022–2025 de-identified administrative data and 16 stakeholder questionnaires identified ≥10 implementation gaps, including low awareness of new standards and workload impacts. The project developed 8 evidence-based recommendations and an implementation roadmap to improve compliance, optimize resources, reduce administrative burden, and strengthen military readiness.

Revisiting Ulam Stability For Boundary Value Problems, Martin Bohner, Snezhana Hristova, Agnieszka B. Malinowska, Ewa Girejko

Mathematics and Statistics Faculty Research & Creative Works

The main goal of this paper is to apply Ulam stability theory to boundary value problems for dynamic equations, while addressing several common misconceptions found in the existing literature. We identify the key issues that arise when applying Ulam stability to such problems and propose three distinct approaches to overcome them. To enhance clarity and accessibility, we begin with nonlinear ordinary differential equations and subsequently extend the analysis to nonlinear dynamic equations on time scales. Since a time scale is defined as any nonempty closed subset of the real numbers, our results are applicable to dynamic equations on continuous, discrete, …

Wildfire And Fuel Treatments In Utah: A Practical Guide And Outcomes From An Oak-Maple Ecosystem, Annie E. Prescott

All Graduate Theses and Dissertations, Fall 2023 to Present

Wildfire is a natural part of Utah’s landscapes, but as wildfires become more extreme and communities continue to expand into wildland areas, it is increasingly important to understand how wildfires behave and how their negative effects can be mitigated. One way to reduce wildfire risks and protect life, property, and ecosystem services is through fuel treatments — actions that reduce the amount and arrangement of flammable vegetation through mechanical removal, wildland fire, or other methods.

Information on wildfire behavior and fuel treatments is abundant but often scattered, ecosystem-specific and difficult to access. In addition, most research in the Western U.S. …

Toward Optimizing Fruit Production In Utah Soils: Apple Salt Tolerance Screening And Tart Cherry Fertility Management, Kaitlin Dabbs

All Graduate Theses and Dissertations, Fall 2023 to Present

Fruit production in Utah can be challenging due to local climate and soil conditions. Tart cherries and apples are major fruit crops in Utah, and improvements to these cropping systems would be beneficial for farmers and local consumers. Two experiments were conducted to evaluate desired improvements for these crops. The first study looked for salt tolerance in ten new apple rootstocks. Salty soils can be found throughout the state limiting the land suitable for apple production. When grown in salty soils apple trees often have reduced growth and production potential. A specialized drip irrigation system was constructed in a greenhouse …

The Willing And The Compelled: How Power And Place Shape Human-Bison Coexistence In Poland And The United States, Patrick Orville Kelly

All Graduate Theses and Dissertations, Fall 2023 to Present

Wildlife recovery programs depend not just on animals, but on how people feel about living with them. The degree to which people accept the disruptions wildlife brings to their lives, known as social tolerance, can determine whether a recovery program succeeds or fails, yet it remains understudied and underapplied in management plans. This dissertation studies how people in Poland and the western United States feel about living with the two living species of bison, the largest land animals in Europe and North America. In Poland, we surveyed 242 residents living at different distances from European bison habitat. Surprisingly, the most …

The Effects Of Eps Level And Presentation Format Of Analysts’ Forecast Deviation On Non-Professional Investors’ Investment Judgments, Clarence Goh, Prasart Jongjaroenkamol, Poh-Sun Seow

Research Collection School Of Accountancy

We experimentally investigate how the presentation format of the extent to which a firm's earnings per share (EPS) diverges from analysts' EPS forecasts (i.e. deviation information) and a firm's EPS level affect the investment judgments of non-professional investors (referred to hereafter as “investors”). Our results suggest that investors' investment judgments are more positive when firms with low (high) EPS levels disclose deviation information in percentage (absolute) terms. Furthermore, when the percentage of forecast deviation is held constant, investment judgments are more positive when EPS levels are high versus low if the deviation information is expressed in absolute terms. By contrast, …

A Projector-Rank Partition Theorem For Exact Degrees Of Freedom In Experimental Design, K. G. Nagananda

Mathematics and Statistics Faculty Publications and Presentations

In many experimental designs—split-plots, blocked or nested layouts, fractional factorials, and studies with missing or unequal replication—standard ANOVA procedures no longer tell us exactly how many independent pieces of information each effect truly contributes. We provide a general degrees of freedom (df) partition theorem that resolves this ambiguity. For N observations, we show that the total information in the data (i.e., N −1 df) can be split exactly across experimental effects and randomization strata by projecting the data onto each stratum and counting the df each effect contributes there. This yields integer df—not approximations—for any mix of fixed and random …

Soil-Science Expertise In An Ai-Exposed World: Competencies, Curricula, And Careers For Soil Security, Gian Franco Capra, Thiago Assis Rodrigues Nogueira, Arun Dilipkumar Jani

Biology, Agriculture and Chemistry Faculty Publications and Presentations

Generative artificial intelligence (AI) is reshaping the world of knowledge-based work, with highly qualified professions appearing more exposed to substitution than routine manual ones. Soil science occupies a hybrid position, being a field that requires extensive knowledge and at the same time a strong dependency on field and laboratory activities, time-consuming and intrinsically “embodied.” This review examines what AI entails for soil science, asking which competencies are more or less exposed, how curricula should respond, and what actions institutions should undertake in the current AI-dominant academic environment. The analysis rests on two axes, namely the AI exposure of a task …

Evaluating The Impact Of Research Equipment Availability On Scientific Rigor, Reproducibility, And Innovation Across Stem Disciplines, Lyndi G. Hraban

Honors Program: Senior Projects (Public)

Research infrastructure plays a central role in shaping the quality and innovative capacity of scientific research. This study evaluates how the availability of research equipment influences scientific rigor, reproducibility, and innovation across STEM disciplines. Drawing on literature from science-to-science research, policy studies, and discipline-specific analyses, this project synthesizes existing scholarship to explore the relationship between access to infrastructure and key research outcomes. Findings across the literature indicate that access to advanced and well-maintained equipment can strengthen scientific rigor by enabling more precise measurements, improved experimental control, and the implementation of standardized research protocols. Shared and centralized facilities are also associated …

In Adults Older Than 18 Years With Obesity Living In Massachusetts, Can Engaging In A Weight Loss Program Help Them Lose Weight After Insurance Stops Covering Their Weight Loss Medications?, Angel Nagawa

Capstones

Executive summary

The Problem

Obesity rates continue to rise sharply across the United States. Weight loss medications have high compliance but face major insurance restrictions. Strict clinical criteria leave many patients without accessible treatment options.

The Proposed Solution

Launch structured, lifestyle-focused clinical weight loss programs. Provide an effective, accessible alternative to restricted pharmaceutical therapies.

Supporting Evidence

Evaluated data from three distinct randomized controlled trials. Findings confirm successful long-term weight management for program participants. Results prove effective control over serious obesity-related comorbidities.

Policy recommendation

Implement structured lifestyle programs as a primary, frontline intervention modality. Improve broad-scale patient health outcomes across clinical …

Methods For Tagging Whale Sharks: Insights Into Performance And Best Practices With A Focus On Clamp Attachments, Freya C. Womersley, Sofia Green, Alberto Garcia-Baciero, Ronan Conlon, Amy L. Jeffries, Matt J. Waller, Sara S. Ratão, Nuno Queiroz, Pedro Afonso, Gonzalo Araujo, Adam Barnett, Christine Barry, Michael L. Berumen, Farukhkha Bloch, Ginevra Boldrocchi, Camrin D. Braun, Ryan Caillouet, Constance Chapman, Jesse E.M. Cochran

Faculty Publications

Background: Biologging and telemetry have transformed our understanding of marine megafauna movement ecology. Yet, methodological constraints continue to limit data quality and deployment duration. Devices recording whale shark (Rhincodon typus) behaviours and movements have been used for decades, but they remain challenging to deploy and vary in success. Recently, spring-loaded clamp-based systems have emerged as one of the most widely used approaches to attach electronic tags to the fins of this globally endangered species. Currently, however, no consensus guidelines exist as to how to optimise this approach, potentially leading to continued underperforming deployments limiting analysis potential. Here, we synthesise experiences …

A Global High-Resolution Comprehensive Heat Indices Dataset From 1950 To 2024, Abdul Malik, Sateesh Masabathini, Mohsin Ahmed Shaikh, Qinqin Kong, Muhammad Usman, Dasari Hari Prasad, Ibrahim Hoteit

All Works

Heatwaves are becoming more intense and frequent as global temperatures rise, affecting vulnerable populations, particularly in low-income communities. Addressing the impacts of heatwaves requires high-resolution data to assess their influence on labour productivity, public health, and climate risk. We introduce the Comprehensive Heat Indices (CHI) dataset, a high-resolution (0.1° × 0.1°) hourly dataset from 1950 to 2024, derived from the ERA5 and ERA5-Land reanalyses. The CHI dataset encompasses thirteen heat stress indices, including wet-bulb temperature, universal thermal climate index, mean radiant temperature, wind chill, and lethal heat stress index (Ls). Thresholds for Ls are empirically linked to mortality, enabling the …

Quantifying Customer Sentiment For Automobile Brand Perception Analysis Using Machine Learning On Twitter, Sujith Samuel Mathew, Kadhim Hayawi, Neethu Venugopal, May El Barachi

All Works

Social networking sites provide a platform for individuals to express their opinions publicly. Brand managers actively use these platforms to gain insights into brand perceptions, as users often share their views on products and services. In this study, we use sentiment analysis to assess customer sentiment towards five leading automobile brands, analyzing text content shared on Twitter(or X). The research models the ’Brand Polarity Score’, which indicates whether customers perceive the brand positively or negatively. This score is further weighted based on the tweet’s influence, characterized by the engagement metrics of the tweet and the author’s follower count. We also …

Dblp: Noise Bridge Consistency Distillation For Efficient And Reliable Adversarial Purification, Chihan Huang, Belal Alsinglawi, Islam Al-Qudah

All Works

Recent advances in deep neural networks (DNNs) have led to remarkable success across a wide range of tasks. However, their susceptibility to adversarial perturbations remains a critical vulnerability. Existing diffusion-based adversarial purification methods often require intensive iterative denoising, severely limiting their practical deployment. In this paper, we propose Diffusion Bridge Distillation for Purification (DBLP), a novel and efficient diffusion-based framework for adversarial purification. Central to our approach is a new objective, noise bridge distillation, which constructs a principled alignment between the adversarial noise distribution and the clean data distribution within a latent consistency model (LCM). To further enhance semantic fidelity, …