Digital Commons Network^™

Quantifying The Performance Of The Sparta Toolkit For Use In Planetary Regolith Characterization Missions, Abigail S. Glover

Honors Undergraduate Theses

This research investigates the use of the Soil Properties Assessment, Resistance, and Thermal Analysis (SPARTA) Cone Penetration Tester (CPT) to quantify bulk density in lunar regolith simulant LHS-1E. Twenty-five penetration tests were conducted across five density profiles to derive slope parameters (G), which represent the rate of increase in resistance with depth. Results showed a consistent, nonlinear relationship between G and bulk density, validating the use of G slope as a diagnostic parameter and supporting the primary hypothesis that SPARTA CPT measurements vary meaningfully with density. Compared to prior work by Lucas et al. (2024), G values from SPARTA were …

Generation Z’S Perception Of Skin Cancer And How It Relates To Climate Change, Piercen Bogolea

Honors Undergraduate Theses

Skin cancer is the most common cancer worldwide, and climate change has been identified as a significant contributor. Preventative action early on can help reduce occurrence, but it is unknown if Generation Z is aware of this and is taking the necessary action now to protect themselves. This research aims to gauge the perception of Generation Z on the severity of skin cancer, the relationship between climate change and skin cancer, and the prevalence of preventative measures being taken. A survey was distributed to students aged 18 to 27 enrolled at the University of Central Florida through mixed sampling. The …

Entangled Photoelectron Attosecond Spectroscopy, Jonathan Sar-Shalom

Honors Undergraduate Theses

In this thesis we propose an interferometric scheme to retrieve the dynamics of an electron wave packet emitted from two distinct residual photo-ion channels in the ionization of an atom by an ultra-short UV pulse. EPAS (Entangled-Photoelectron Attosecond Spectroscopy) works by having a non-overlapping UV and few-cycle IR pulse, where the IR is tuned near the transition frequency between two electronic bound states of the photo-ion. Using a time-dependent simulation based on a two-channel atomic model, supported by a perturbative approach, we were able to compute the resulting interference in the angular distribution of the photoelectron and retrieve the energy-dependent …

Pathways To Nursing And Midwifery Education In Tanzania With Reflection To The Global Perspectives: A Narrative Review, Tumbwene Mwansisya, Mary Lyimo, Eunice Pallangyo

School of Nursing & Midwifery, East Africa

Background/Objectives:

This review aimed to explore the pathways of nursing and midwifery education in Tanzania and compare them with global perspectives. The goal was to identify similarities, differences, and areas for potential improvement to align with international standards.

Methods:

A narrative literature review was carried out through databases with published studies in nursing and gray literature. The database search included Medline, PubMed, Google Scholar, EBSCO, PsycINFO, clinical nursing, and gray literature from January 2014 up to December 2024. The search process was carried out by the authors with the following key words: admission, pathway to nursing profession, delivery mode, …

Supporting Human-Ai Interaction From User Expectations To Mental Models, Harishankar Vasudevanallur Subramanian

Doctoral Dissertations

Explainable AI (XAI) aims to unravel the "black box" nature of AI systems and provide insights into the inner workings that lead to a prediction. However, the best XAI communication varies depending on the individual, task, and broader context. It is challenging to anticipate the best XAI for a particular use case. One strategy is for users to build an appropriate mental model of AI with both prediction and system level XAI. To date, little research has focused on quantitatively measuring users interacting with system-level XAI. This dissertation has three primary contributions. The first contribution is a scoping review paper …

It’S Time To Stop Calling People "Stakeholders", Bethann Garramon Merkle, Evelyn Valdez-Ward, Priya Shukla, Skylar R. Bayer

Human–Wildlife Interactions

Although the term “stakeholder” has been widely used in science communication, recent expansion in the discourse around the negative connotations of the term necessitate that scientists and practitioners cease using the term. We discuss why this shift is necessary, how it affects our own praxis, and suggest resources for working through more respectful and just language. Looking to the science communication literature can help recalibrate terminology in positive ways.

Multi-Source Remote Sensing–Based Soil Moisture Prediction Using Machine Learning, Niraj Neupane

Electronic Theses and Dissertations

Soil moisture (SM) plays a central role in climatic and environmental processes, influencing shear strength of soil, agricultural productivity, land–atmosphere interactions, and hydrologic functioning. However, accurately estimating SM across diverse climatic regions remains challenging due to spatial heterogeneity, limited in situ measurements, and inconsistencies in sensor resolution. Machine learning (ML) and remote sensing offer promising avenues for improving SM prediction, yet many existing approaches struggle with generalization across climatic gradients and often fail to capture temporal variability. This study integrates multi-source satellite and climate datasets, including SMAP L4_SM, MODIS land surface temperature, Daymet meteorological variables, and in situ observations from …

Quantitative Assessment And Validation Of Thermal Profiles In The Protodune-Ii Horizontal Drift Detector Using Computational Fluid Dynamics, Hunter Wallster

Electronic Theses and Dissertations

The Deep Underground Neutrino Experiment (DUNE) aims to advance understanding of neutrino properties using large liquid Argon time projection chambers (LArTPCs). The ProtoDUNE-II Horizontal Drift (HD) detector, constructed at CERN in Switzerland, serves as 1:20 scale prototype to validate design and operational parameters for DUNE’s Far Detectors. Accurate prediction of cryostat thermal behavior is critical to predicting liquid Argon purity distributions and detector performance, motivating the development of a validated computational fluid dynamics (CFD) model. This research extends previous work at South Dakota State University by constructing a higher-fidelity CFD simulation of ProtoDUNE-II HD using Siemens Simcenter StarCCM+® 19.04.007. Geometry …

Quantifying Avian And Vegetation Communities On Agricultural Conservation Easement Wetlands In Eastern South Dakota, Katherine Millman

Electronic Theses and Dissertations

The Prairie Pothole Region of eastern South Dakota contains numerous small depressional wetlands, colloquially known as potholes, that provide important ecosystem services, including water storage, water quality improvement, and wildlife habitat. The Agricultural Conservation Easement Program (ACEP) was established by the U.S. Department of Agriculture to protect and restore wetlands and grasslands on private land through easements such as Wetland Reserve Easements. Although ACEP requires management practices intended to maintain or improve habitat quality, few studies have evaluated their effectiveness at supporting wildlife communities and vegetation integrity. To address this gap, we evaluated wetlands at 30 ACEP sites and 20 …

Enhancing Alfalfa Persistence In Rangelands: Evaluating Morphological Traits Of Medicago Sativa Subsp. Falcata Germplasm, Abdulallah Mohammed Alomair

Electronic Theses and Dissertations

Rangelands cover nearly half of the Earth’s surface, representing about 54% (79 million km2), and occur in different types and climates worldwide. Alfalfa (Medicago sativa L.) is a major component in rangelands and covers about (320 thousand km2), representing about 0.4% of total global rangeland area. As a critical perennial legume crop, alfalfa can improve soil health by fixing approximately 336 kg/ha/year of nitrogen and sequestering up to 614 kg/ha/year of carbon, while enhancing livestock production due to its high content level of vitamins, magnesium, minerals, fiber, and protein. However, environmental stresses such as drought, freezing, and grazing limit alfalfa …

Pave Outer Space And Put Up A Parking Lot: Lagrange Points Should Be The Common Heritage Of Mankind, David A. Koplow

Georgetown Law Faculty Publications and Other Works

Outer space offers a vast array of opportunities, with different locations or regions available for exploitation by diverse users for a growing variety of satellite functions. But not all sectors of space are equally valuable for all applications, and the most desirable venues can become crowded, affording a premium for those who gain access first and impeding the development of a fair and efficient all-inclusive international legal regime.

This article focuses on Lagrange points, a finite series of special locations in space where the gravitational forces from a pair of large celestial bodies interact in unusual ways. These points afford …

Development Of Bio-Based Coating Materials For Environmentally Friendly Controlled-Release Nitrogen Fertilizer Applications, Anne Carolyne Mendonca Cidreira

Electronic Theses and Dissertations

No abstract provided.

Discovery Of Photosynthetic Oxic N2-Fixation In Cyanobacteria Using Wet Lab And Machine Learning Approaches, James A. Young Iii

Electronic Theses and Dissertations

No abstract provided.

Computation-Efficient Deep Learning Models For Computer Vision And Multimodal Vision-Language Tasks Via Network Pruning, Abir Mohammad Hadi

Electronic Theses and Dissertations

With the rapid evolution of deep neural networks over the past decade, the demand for efficient, generalizable, and task-adaptable models, especially in computer vision, has increased significantly. To address the computational and deployment challenges posed by overparameterized models, the research community has extensively explored model compression techniques such as pruning, quantization, and distillation. These approaches aim to enhance model efficiency without compromising performance, particularly when adapting to domain-specific tasks under limited resources. This dissertation investigates several underexplored yet critical aspects of task-aware deep learning model compression, spanning both convolutional and vision-language architectures. In the early part of this work, we …

In The Footsteps Of Moose: Using Non-Invasive Techniques To Identify Cause-Specific Calf Mortalities And Evaluate Moose (Alces Alces) Movements Pertaining To Mineral Lick Locations On Ancestral Lands Of The Grand Portage Ojibwe, Anna B. Weesies

Electronic Theses and Dissertations

Following a sharp moose (Alces alces; mooz, Anishinaabemowin, Ojibwe language) population decline in northeastern Minnesota during the early 2000s, the Grand Portage Band of Lake Superior Chippewa initiated a long-term moose collaring effort to assess survival and mortality causes. Moose are a culturally important species to the Band, with annual subsistence hunts held on the Reservation and adjacent 1854 Ceded Territory. Continued research guides culturally appropriate management decisions aimed at bolstering calf and adult survival, helping to preserve this moose in Minnesota today and for subsequent generations. Chapter 1 identifies cause-specific calf mortality rates in this multi-predator system using minimally …

Characterizing A Free-Roaming Cat Population To Predict Predation Of Threatened Species In An Island Ecosystem, Sarah Gheida

Electronic Theses and Dissertations

No abstract provided.

Slum Area Detection In Dhaka City, Bangladesh, Using Satellite Remote Sensing And Deep Learning, Soubhoon Sadeq Shinjini

Electronic Theses and Dissertations

Dhaka City, a rapidly growing megacity and high-density developing area in Bangladesh, faces numerous urbanization challenges. Among these, informal settlements or slum areas pose serious concerns for authorities and policymakers striving to improve living conditions for slum dwellers. Dhaka City’s slums are characterized by high-density, one- or two-story structures made of low-cost materials, often located adjacent to natural water bodies and lacking basic public infrastructure (Ahmed 2014; Iqbal 2014; Jahan 2012). The need for accurate and up-to-date data on these settlements is crucial for researchers and policymakers, particularly for implementing slum upgradation and resettlement programs. However, traditional field surveys for …

An Integrated Wetland Condition Index And Environmental Metric Framework For The Prairie Pothole Region, Mercedes L. Batalla

Electronic Theses and Dissertations

The USDA-NRCS Agricultural Conservation Easement Program (ACEP) assists landowners with protecting, restoring, and enhancing wetlands. Evaluating wetland conservation efforts is crucial for informing future management decisions. However, assessment frameworks vary across regions and among stakeholders. The Prairie Pothole Region is an ecologically unique landscape characterized by its abundance of wetlands that provide important ecosystem services. To evaluate wetlands enrolled in ACEP, I sampled forty-five semi-permanent wetlands in the Prairie Pothole Region from July – August 2023 and 2024. I selected and sampled twenty-six wetlands enrolled in ACEP. Nineteen additional wetlands not enrolled in ACEP were also sampled; these included nine …

Simulating Positive Ion Distribution In The Protodune Single Phase Detector, Vishnu Pfeiffer

Electronic Theses and Dissertations

This work covers the validation and implementation of a model to solve for argon ion (Ar+) distribution in the ProtoDUNE-SP liquid argon time projection chamber (LArTPC). ProtoDUNE-SP undergoes a constant flux of cosmic ray muons due to surface operation. The performance of the ProtoDUNE-SP provided valuable insights into single-phase technology, membrane cryostat technology, and calibration of cryogenic instrumentation. Still, challenges in achieving precise measurements persist due to the space charge effect—the distortion of the electric field within the detector due to the accumulation of positive argon ions generated from constant cosmic muon flux. The overarching goal of this thesis is …

Developing Proportional Hazards Mixture Cure Models And Predicting Risk For Persons With End-Stage Kidney Disease, Nathan Meyer

Electronic Theses and Dissertations

Traditional survival analysis techniques assume that all individuals will eventually experience the event of interest. This is as opposed to allowing for a subset of cured individuals. Hence, we consider a mixture cure model that can allow a subset of people to be cured of the disease and will never experience the event of interest. This gives a more accurate interpretation of survivability by analyzing both the shortand long-term effects of a set of variables on the individuals’ survival probabilities. However, the cure status is considered an unknown variable. Thus, the expectationmaximization algorithm is required to estimate this latent variable …

Exploring The Role Of Clinical And Social Factors In Predicting All-Cause Mortality In End-Stage Kidney Disease Patients: A Machine Learning Framework, Addy Smith

Electronic Theses and Dissertations

No abstract provided.

Molecular Dynamics Simulations Of Key Parameters On Thermal Properties Of Carbon Nanotube Modified Epoxy Composites, Lida Najmi

Electronic Theses and Dissertations

The application of carbon nanotube (CNT)-reinforced epoxy matrix composites (CRECs) has attracted extensive attention in various industrial sectors due to the significant improvement of material properties imparted by CNTs. The thermal behavior of these nanocomposites is governed by complex heat transfer mechanisms operating at different scales, resulting in a complex relationship between the effective thermal response and the microstructural characteristics of the composite. In this study, molecular dynamics (MD) simulations were used to investigate the thermal conductivity of CRECs, focusing on the effects of key parameters such as the length and volume fraction of CNTs, the degree of cross-linking within …

Improved Optimal Tracking Of Uncertain Nonlinear Discrete-Time Systems Using Experience Replay, Maxwell Geiger, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper addresses the infinite horizon optimal tracking control problem for partially uncertain control-affine nonlinear discrete-time (DT) systems, where the control input dynamics are known. Multi-layer critic and actor neural networks (MNNs) are utilized for online estimation of the infinite horizon value function and optimal control input. The NN weights are tuned online using a direct temporal difference error (TDE)-driven learning approach, which modifies the singular values of the gradient with respect to the NN weights to accelerate their convergence. The critic NN uses a novel experience replay technique to improve sample efficiency without introducing biased TDEs and guarantee the …

Anti-Jamming Attack Mixed Strategy For Formation Tracking Control Via Game-Theoretical Reinforcement Learning, Lei Xue, Bei Ma, Yongbao Wu, Jian Liu, Chaoxu Mu, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

Communication plays a role in multi-UAV to perform formation tracking missions. In complex environments, UAV communication is often subject to jamming attacks, affecting the formation process. Therefore, studying the formation tracking control problem in jamming attacks is of great significance. Typically, the actions of the UAV consist of two fundamental modules: mobility strategy and communication strategy. In this paper, we design an anti-jamming attack mixed strategy for formation tracking control of the multi-UAV system. In practical scenarios, multi-UAV systems not only require the accomplishment of formation maneuvers but also necessitate effective mitigation of jamming attacks caused by other UAVs. Therefore, …

Multi-Dimensional Iot-Based Energy Management Approach For Smart Homes: A Unified Model For Comfort And Energy Efficiency, Muhammad Ans, Teodoro Montanaro, Ilaria Sergi, Ahmad Alsharoa, Miriam Pezzuto, Luigi Patrono

Electrical and Computer Engineering Faculty Research & Creative Works

As smart home technologies evolve, achieving energy-efficient indoor climate management while maintaining comfort and air quality is a growing priority. This paper introduces a novel optimization framework for smart buildings that minimizes energy costs and dynamically manages indoor environmental conditions, specifically temperature, CO₂ concentration, and illuminance. Unlike conventional systems, our model incorporates dynamic constraints that respond to day-night comfort requirements and leverage real-time variations in electricity prices and environmental conditions. By optimally controlling the power levels of air conditioning, air purification, and lighting systems, the framework ensures indoor comfort while significantly reducing operational costs.A nonlinear optimization approach with dynamic …

Aperiodically Intermittent Dynamic Event-Triggered Control For Predefined-Time Synchronization Of Stochastic Complex Networks, Lei Xue, Haoyu Zhou, Yongbao Wu, Jian Liu, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, the problem of practical predefined-time synchronization in mean square (PTSMS) of stochastic complex networks (SCNs) is investigated through dynamic event-triggered control (E-TC). Different from the existing literature, this paper considers the dynamic E-TC in an a periodically intermittent control framework and employs the average control rate, which makes it easier to satisfy the conditions of the theorem. In comparison to existing finite-time and fixed-time synchronization, by introducing the time-varying function, it can be guaranteed that all states of SCNs achieve the practical PTSMS within a preset time without calculating the convergence time. Combined with stochastic analysis theory, …

Safe Optimal Control Of Quadrotor Formations Using Multilayer Neural Networks And Continual Learning, Ehsan Soleimani, Irfan Ahmad Ganie, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This article presents an integral reinforcement learning-based optimal formation tracking scheme for multiple quadrotors unmanned aerial vehicles (QUAVs) experiencing nonlinear coupled dynamics and subject to constraints. We use multilayer neural networks (MNN) within an actor-critic framework where the MNN weights are tuned using singular value decomposition (SVD) of the activation function gradient to approximate optimal control policy via backstepping. Additionally, barrier Lyapunov functions (BLF) are introduced to ensure set invariance, thereby maintaining the quadrotors within a defined safety space due to constraints. A novel weight update law for each layer is derived using the HJB approximation error and control input …

Prescribed-Time Nash Equilibrium Seeking For Pursuit-Evasion Game Under Intermittent Control With Undirected/Directed Graph, Lei Xue, Jianfeng Ye, Yongbao Wu, Jian Liu, D. C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This paper studies the prescribed-time Nash equilibrium (PTNE) seeking problem of the pursuit-evasion game (PEG) with second-order dynamics under the intermittent control (IC) strategy. To achieve Nash equilibrium (NE) in a user-defined prescribed-time, a time-varying high-gain function is incorporated into the design. The core challenge lies in applying IC to NE seeking, which complicates the convergence analysis and control design. To address this sticking point, we construct an auxiliary function and propose a Lyapunov function considering second-order dynamics to solve the PTNE seeking problem of PEG. Building upon the results for undirected graphs, we further extend our findings to directed …

Fast-Sparse-Spanner: A Practical Algorithm For Constructing Low-Stretch Sparse Geometric Graphs, Fnu Shariful

UNF Graduate Theses and Dissertations

When constructing geometric graphs (vertices are points and edges are line segments connecting point pairs) on pointsets, stretch-factor (worst-case detour between any point pair) is often considered a quality metric. A low stretch-factor (a quantity that is usually > 1) guarantees short paths between all vertex pairs. A geometric graph having a stretch-factor of t is known as a t-spanner. Creating low stretch-factor geometric graphs for large pointsets with a low number of edges is an open problem in computational geometry.

In this work, we have designed and engineered a new simple and practical (fast and memory-efficient) algorithm named Fast-Sparse-Spanner algorithm …

Analysis Of Port Traffic Growth For Optimization Of Traffic Flow: A Microscopic Traffic Simulation Study Of Jaxport's Blount Island Marine Terminal, Amy A. Aida

UNF Graduate Theses and Dissertations

To accommodate increasing cargo volumes and remain competitive, ports worldwide are facing growing pressure to expand and modernize their facilities. However, these expansions can place additional strain on land transportation networks, leading to congestion, delays and operational inefficiencies. This study used VISSIM, a microscopic traffic simulation tool, to model and analyze the complex traffic dynamics at the Blount Island Marine Terminal in Jacksonville, Florida, which is currently undergoing expansion.

To account for future traffic conditions, time series analysis was employed to project growth in traffic demand, taking into consideration anticipated expansions in tenant yard facilities, as well as increases in …