Physical Sciences and Mathematics Commons^™

On Bed Posture Recognition Using Deep Learning With Pressure Sensors, Farheen Akhter Ms

Electronic Theses, Projects, and Dissertations

In healthcare applications such as disease prevention, sleep quality evaluation, and patient monitoring, bed posture recognition is essential. Using pressure sensor arrays placed on top of or embedded in mattresses, this study investigates the application of deep learning models for non-invasive posture classification. Although they have been widely employed, traditional machine learning approaches like support vector machines (SVM) and k-nearest neighbors (KNN) sometimes struggle with feature extraction and real-time performance necessitating considerable processing resources. I implemented a model using conventional approaches to get over these restrictions, then fine-tuned it using the following deep learning architectures for bed posture recognition: ResNet-50, …

Ml Playground: Data Modification/Preprocessing And Model Simulation Tool, Marco D. Cerrato

Electronic Theses, Projects, and Dissertations

There is a heavy reliance on programming when it comes to learning machine learning (ML). This often creates barriers for students and newcomers unfamiliar with coding. While the lessons you learn in the classroom provide essential foundational understanding, some technical or practical aspects of ML—such as data preprocessing, feature engineering, and model tuning—are best learned through hands-on interaction. ML Playground was developed to act as a proof-of-concept application to address this gap by offering a browser-based, graphical user interface that lets users engage with core ML workflows without writing code. Designed with educational accessibility in mind, the application allows users …

Supporting Novice Programmers With Scaffolded And Open-Ended Generative Ai Interfaces: Insights From A Design-Based Research Study, Justin Olmanson, Azadeh Hassani, Gretchen K. Larsen

Department of Teaching, Learning, and Teacher Education: Faculty Publications

In this study, we explore student experiences in coding and learning programming with scaffolded and unscaffolded generative AI interfaces. Specifically, we supported higher education students in using ChatGPT, an open ended interface for interacting with generative AI; and Giuseppe, a specialized interface with an OpenAI backend service that offers personalized supports specifically for helping students overcome early-stage challenges in learning to code, and working on education technology prototyping projects. This study contributes to the field by offering design insights for scaffolding initial learning interactions between generative AI interfaces and novice programmers. Our findings suggest that those new to coding welcome …

Reuben Hersh's What Is Mathematics, Really? (Book Review), Calvin Jongsma

Faculty Work Comprehensive List

Reuben Hersh’s 1997 book What is Mathematics, Really? popularized a trend in the philosophy of mathematics that was gaining some traction at the time it was written. This essay examines Hersh’s work within the broader historical context of 19th- and 20th-century developments in mathematics and philosophy of mathematics. It also focuses on Hersh’s antagonism toward the influence of religion on (philosophy of) mathematics, concluding by briefly considering two positions taken by Christian mathematicians associated with ACMS in defense of such a connection.

Setting Up Students For Success: Analysis Of Effectiveness For Mathematics Placement, Jeff Carvell, Jason N.E. Ho, Dave Klanderman, Sarah Klanderman

Faculty Work Comprehensive List

How do we effectively and equitably place students into math classes in a way that provides them the best chance of success? As many higher education institutions veer away from placement based on standardized testing, many departments are seeking placement alternatives that will properly support students. Additionally, math placement determines not only a student’s mathematics courses but also influences their progress in related fields, including physics, chemistry, engineering, and more. This paper will describe three different existing placement systems at each of our liberal arts institutions as well as the affordances and constraints of each approach. Further, we analyze data …

Revolutionizing Higher Ed: Ai’S Impact On Faculty And Pedagogy, George Antoniou, David G. Wolf, Ellen Ramsey, Matteo Peroni, Saidi Porta, Philip L. Fazio, Kristen Migliano

Faculty and Staff Publications & Presentations

No abstract provided.

A Mineralogical And Geochemical Investigation Of The Influence Of Tectonic Setting On Accessory Mineral Assemblages In Serpentinites Along The Western North American Margins, Bryan H.T. Seymour

Electronic Theses, Projects, and Dissertations

Serpentinites are metamorphic rocks typically produced by hydrating mantle peridotites to form assemblages containing one or more serpentine minerals. They occur in various tectonic and geologic settings, such as submarine hydrothermal systems, ophiolite sequences, and the forearc mantle. Serpentinites are associated with highly reduced conditions, as indicated by low oxygen fugacity (ƒO₂) values. Previous investigations suggest that oxygen fugacity varies with tectonic setting due to differences in environmental conditions. To test this hypothesis, we analyzed serpentinites from a wide variety of tectonic settings in western North America: The New Idria forearc diapir (CA), Canyon Mountain Island arc complex (OR), Josephine …

Post-Fire Debris Flow Initiation Potential Based On Forensic Analysis Of Debris Flow Occurrence From The 2020 El Dorado Wildfire On Yucaipa Ridge, San Bernardino County California, Seth Clemen D. Saludez

Electronic Theses, Projects, and Dissertations

This study focuses on the potential debris flow initiation and effect in areas affected by the El Dorado Fire in the Southern San Bernardino Mountains. It uses novel technology combining drone-based photography and LiDAR imaging to create surface models of areas where potential debris flows could initiate, flow, and be deposited. The scans were repeated as geomorphic change occurred through the wet season to document spatial and volumetric changes resulted from the flows. These measurements were combined with traditional fire assessment and observational methods to characterize pertinent conditions.

As we investigated potential debris flow risk in this study area, we …

Investigating The Privacy-Utility Trade-O↵ In Synthetic Data Generation Using Correlated Attribute Mode, Kofi Sarfo

Electronic Theses and Dissertations

This thesis explores the privacy-utility trade-off in synthetic data generation using the Correlated Attribute Mode of DataSynthesizer, which employs Bayesian networks to model attribute dependencies. It focuses on integrating differential privacy mechanisms, particularly the Laplace mechanism, to inject controlled noise into synthetic data and enhance privacy protection. As organizations face challenges balancing data-driven decision-making with privacy regulations such as the General Data Protection Regulation and the California Consumer Privacy Act, synthetic data offers a solution by creating artificial datasets that preserve statistical properties while balancing data privacy and utility. This research investigates how different differential privacy parameters epsilon affect data …

The Role Of Ai In Enhancing Teamwork, Resilience And Decision-Making: Review Of Recent Developments, Satyadhar Joshi

Harrisburg University Other Works

This paper explores the transformative impact of artificial intelligence (AI) on organizational teamwork, decision-making, and resilience. This paper furthur reviews recent literature on the integration of Artificial Intelligence (AI) in various organizational functions, focusing on its impact on innovation management, leadership paradigms, and organizational resilience. We provide groundwork required to enhance frameworks that can integrate cognitive scaffolding with antifragile team dynamics, employing behavioral economics and neurocognitive principles. We introduce methodologies for enhancing team resilience through adaptive AI systems, cross-training interventions, and pre-mortem simulation techniques. The framework addresses key challenges in confirmation bias mitigation, cultural dimension alignment, and vigilance decrement prevention. …

Exploring The Robustness Of The Effect Of Evo On Intention Valuation Through Replication: Supplemental Material, Yesugen Baatartogtokh, Kaitlyn Cook, Alicia M. Grubb

Computer Science: Faculty Publications

Supplemental material for the paper: "Exploring the Robustness of the Effect of EVO on Intention Valuation through Replication"

Antiproliferative Effects Of Salvia On Breast Cancers., Allison C. Portaro

College of Arts & Sciences Senior Theses

Breast cancer is the most common cancer diagnosed in female adults, with 2.3 million new cases worldwide in 2020. Plants have been used in traditional medicine and are a potential source of pharmaceuticals. One example is the large Lamiaceae (mint) family. The Salvia genus, commonly known as the sages, is the largest genus in Lamiaceae with almost 900 known species. Salvia lyrata (lyre-leaved sage) has a history of Native American medicinal use to treat cancers and other ailments resulting in this plant being referred to as ‘cancer weed.’ Extracts were produced from the leaves of S. lyrata, S. lyrata …

How Graphene’S Berry Dipole Is Determined By Its Atomic Registry With A Substrate, Hannah K. Isbell

Physics Undergraduate Honors Theses

Since graphene’s discovery in 2004, it has been established as one of the most important materials in recent condensed matter history. Understanding its properties and potential uses has been the subject of intense scientific research around the world. Graphene’s unique physical properties allow it to serve a wide variety of purposes, from its everyday role in the formation of graphite in pencils to its more cutting-edge scientific functions in electronics and energy storage. Gaining a better understanding of graphene’s rich quantum landscape through geometric and topological phenomena, like Berry curvature and Berry dipole, could have significant implications for both theoretical …

Enhancing The University Of Arkansas' Operations Through Data Science, Aura L. Pinto-Avelar

Data Science Undergraduate Honors Theses

As universities navigate financial constraints and resource allocation challenges, data driven financial analysis has become increasingly important. Universities employ various methods to assess financial efficiency, predict future expenditures, and optimize student credit hour distribution. However, the approaches to financial analysis vary widely, with some institutions leveraging advanced predictive modeling and business intelligence tools, while others rely on traditional budgeting techniques and manual forecasting.

This thesis examines how the University of Arkansas' (“Uark”) financial analysis methods compare to those of other institutions and alternative data-driven approaches. Using four years of financial and student credit hour data, this study evaluates cost trends …

Lucky Charms: Leveraging Consumer Data Analysis For Strategic Decision-Making At General Mills, Katherine Page Thomas

Data Science Undergraduate Honors Theses

This undergraduate thesis examines the application of data analytics in sales strategy and consumer insights from the perspective of a summer internship at General Mills. It gives an overview of the company’s background, industry position, and intern’s role within the sales organization. It outlines the personal learning objectives established before the internship and how they evolved through practical experience.

A central focus of the summer internship was the analysis of consumer demographics within the cereal category to enhance sales performance and optimize retail execution. Using the Data Science Analytics Process as a framework, this thesis details the problem statements, methodologies, …

Optimizing Fire Station Placement In Sugar Land, Tx: A Socioeconomic Risk-Based Approach, Alicia Gallemore

Data Science Undergraduate Honors Theses

Fire station placement has a critical role in emergency response efficiency and community safety. Traditional optimization models focus on mainly the minimization of response times and the maximization of coverage. However, this approach may overlook potential socioeconomic disparities that can influence emergency demand. This study seeks to expand upon the existing project of zoning a fire station in Sugar Land, TX, by integrating spatial road network analysis and publicly available census data—including population density, median household income, and age-based vulnerability—into a Maximal Coverage Location Problem (MCLP) framework. Using a road network-based travel time with realistic constraints, the goal is to …

Attribute Based Assortment Using Machine-Learning, Hector Negron

Data Science Undergraduate Honors Theses

Retail success is influenced by a store's demographic and environmental context, both of which impact item-level sales performance. This study applies machine learning techniques to optimize item allocation based on club attributes at Sam’s Club locations. By analyzing store- specific factors such as proximity to universities, income levels, and regional preferences, the research identifies patterns that contribute to product demand. The results offer insights into how clubs can enhance inventory decisions, improving sales outcomes while reducing inefficiencies. This study reinforces the value of data-driven retail strategies and presents a practical framework for implementing predictive models in a real-world business context.

Shortage To Surge - Studying The Post-Covid-19 Guitar Retail Market, Jed H. Kim

Data Science Undergraduate Honors Theses

The COVID-19 pandemic was one of the most catalyzing events of the 21st century, leading to supply chain disruptions, lifestyle changes, and a massive shift towards digital technologies. During the COVID-19 lockdown, many people had more free time, and over 16 million individuals learned to play guitar in the first 2 years of the pandemic. According to a study by Fender, 62% of these new guitar learners cited the pandemic as their primary reason for learning the instrument. However, pandemic policies and supply chain disruptions meant that many guitar retailers were unable to satisfy demand, and backorders accumulated. After the …

Computer Vision In Soccer: Yolov11 Analytics Engine For Quantifying Game Strategy, Connor S. Maurer

Data Science Undergraduate Honors Theses

Single-shot object detection capabilities significantly reduce computational overhead for real-time computer vision in sports analytics at 60 FPS. YOLO11’s lightweight CNN gives promising accuracy while meeting the low-latency demand of dynamic soccer matches. As data-driven approaches take over the sport of soccer, efficient player tracking systems become critical for informing coach’s strategies. I prototype the ETL (Extract, Transform, Load) process of data collected from a single- shot detection program and evaluate its viability for estimating player fatigue. YOLO11 detects players, the ball, and other characteristics, with the output transformed by homography to estimate the positions in the real world. These …

Mitigating Nitrogen Losses: The Role Of Enhanced Efficiency Fertilizers In Sustainable Corn Production, Dipesh Giri

Department of Agronomy and Horticulture: Dissertations, Theses, and Student Research

Nitrogen (N) is essential for crop production, but its inefficient use often leads to environmental losses through nitrate leaching, ammonia volatilization, and nitrous oxide (N₂O) emissions. Enhanced efficiency fertilizers (EEFs), such as nitrification inhibitors (NIs) and urease inhibitors (UIs), have been developed to minimize these losses and improve nitrogen use efficiency (NUE). This research combined a multi-year field experiment and a controlled laboratory study to evaluate how dual-inhibitor fertilizers compare to conventional urea and single-inhibitor formulations in Nebraska cropping systems. The main objective was to understand how nitrogen inhibitors influence N availability, crop performance, and nitrogen losses across different environmental …

Extending Cover Crop Growing Window To Improve The Health Of Environmentally Sensitive Soils, Noshin Ara Tunazzina

Department of Agronomy and Horticulture: Dissertations, Theses, and Student Research

Sloping and sandy soils are highly susceptible to degradation. The health of these soils could be improved with cover crops (CCs). However, CC effectiveness in improving soil health mainly depends on CC biomass production, which is often low in temperate regions. The question is: how can we increase CC biomass production? Lengthening the CC growing window can be a potential strategy. This study assessed how 1) interseeded and terminated early (2-3 weeks before crop planting) CC, 2) interseeded and terminated late (at crop planting) CC, 3) drilled (after harvest) and terminated early CC, 4) drilled and terminated late CC, and …

Nutmeg: Separating Signal From Noise In Annotator Disagreement, Jonathan W. Ivey, Susan Gauch, David Jurgens

Data Science Undergraduate Honors Theses

NLP (natural language processing) models often rely on human-labeled data for training and evaluation. Many approaches crowdsource this data from a large number of annotators with varying skills, backgrounds, and motivations, resulting in conflicting annotations. These conflicts have traditionally been resolved by aggregation methods that assume disagreements are errors. Recent work has argued that for many tasks annotators may have genuine disagreements and that variation should be treated as signal rather than noise. However, limited work has combined the two frameworks to separate signal from noise in human-labeled data. In this work, we introduce NUTMEG, a new Bayesian model that …

1785 Parisian Salon Project: New Methods And Practical Innovations In Digital Heritage Reconstruction, James Hutson, Charles O'Brien, Wesley Wolfe, Kayla Kraff, Trent Olsen

Faculty Scholarship

The 1785 Salon Unreal Engine Reconstruction Project represents a significant advance in digital heritage and immersive art historical research by combining generative AI-based asset creation, modular user experience (UX) design, and historically informed workflows. During the Spring 2025 phase, the project achieved major milestones, including the successful development of a replicable pipeline for transforming 2D reference images into period-accurate 3D sculpture models using generative AI and digital sculpting tools. Simultaneously, a robust and adaptable Inspection System was engineered within Unreal Engine, offering granular interaction controls, bilingual (English/French) content integration, dynamic metadata display, and enhanced accessibility. These innovations collectively enabled historically …

Application Of Regression Techniques On Designed Economic Data, Naomi O. Edegbe

All Theses

Evaluating stock market data and public companies' performance is an overwhelming task for day traders and brokers in the United States and internationally. As a financial metric of a company's overall valuation, earnings per share is a commonly researched measure of a company's profitability. We investigate relationships between earnings per share, multiple financial measures reported from company income statements, and classifiers such as market capitalization and sector. Multiple linear regression models are developed and assessed for this data. Results conclude that there is a significant difference between sectors and earnings per share recorded for a given company. Individual stock analysis …

Modeling Dna Repair In Escherichia Coli Using A Boolean And Stochastic Framework, Gabrianne Ivey

All Theses

DNA can be damaged through both internal and external sources. Therefore, cells have created methods to repair DNA damage. In Escherichia coli, the system responsible for DNA repair is termed the SOS response. This system consists of more than 50 genes and contains three main repair pathways: nucleotide excision repair, translesion synthesis, and homologous recombination. The response is initiated when DNA lesions result in the accumulation of single-stranded DNA (ssDNA). The protein RecA is activated by binding to ssDNA and is then denoted RecA*. RecA* assists in the auto-cleavage of LexA which is the primary repressor protein involved in …

Evaluating Climate Benefits In The Conservation Reserve Program: Methane Emissions And Carbon Storage In Restored Wetlands, Annika Kuleba

All Theses

As climate change progresses, Nature-based Climate Solutions (NbCS) have emerged as a key strategy for mitigation. Historically, wetlands were drained to increase arable land area, resulting in habitat degradation and soil erosion. To address these issues, the United States Department of Agriculture (USDA) incentivizes wetland restoration under the Conservation Reserve Program (CRP), in which landowners retire agricultural land to reestablish native habitat. Although wetlands can act as carbon sinks, they are also sources of methane, a more potent greenhouse gas (GHG). Therefore, the effectiveness of wetlands as a NbCS remains under debate due to assumed high methane emissions. Wetland functions …

Impacts Of Cognitive Workload On Veteran Driver Reaction Time: Predictive Modeling Using Bayesian And Machine Learning Methods, Kenneth Ofosu-Kwabe

All Theses

In high-demand environments, the ability to manage cognitive workload can mean the difference between optimal or safe performance and critical failure or accidents. Veterans face an elevated risk of fatal motor vehicle accidents due to post-deployment stress, combat-related injuries, and challenges readjusting to civilian driving. This study explores how cognitive workload affects reaction time performance using a driving simulator by collecting and analyzing subjective workload ratings (using the NASA-TLX survey), physiological signals from eye-tracking and performance data from a sample of 28 Veterans.

We examined how task difficulty, cognitive indicators and personal attributes influence reaction times across an interactive driving …

Evaluation Of High Temperature Borehole Heat Exchangers For Thermal Energy Storage, Robert J. Mcdaniel

All Theses

The development of renewable power sources like solar panels and wind turbines is crucial to lowering greenhouse gas emissions and slowing the increase in global temperature. These sources are limited by the intermittency of power output depending on factors such as weather or time of day. Storing energy during periods of peak productivity improves the efficiency of renewable sources and makes them more competitive with fossil fuels. The excess energy can be stored underground as heat. At high enough temperatures (>150ºC) and discharge rates (>70 kW) the stored energy can be converted back into electricity. This turns the …

The Effect Corrugated Fiberboard Has On The Environment In Terms Of Compostability, Plant Growth, And Per-And-Poly-Fluoroalkyl Substance Contamination, Meredith Clem

All Theses

The “Lasagna Method” is a popular and sustainably perceived technique that many gardeners use as a free and convenient method to dispose of cardboard (corrugated fiberboard) packaging while also improving their gardens. Many claim that this creates benefits for your garden, but many others have proposed their concerns, including the safety of the practice. This research analyzes the compostability of cardboard, the effect it has on plant growth and development of lettuce, and its contamination of a prominent chemical that has known negative effects on human health. The results of these studies showed that cardboard, as it is currently produced …

Evaluating The Role Of Electrostatic Forces In The Adsorption Of Perfluoroalkyl Substances To Granular Activated Carbon, Thomas A. Mccall

All Theses

In response to new drinking water regulations announced by the EPA in 2024, many municipalities will need to monitor concentrations and implement new treatments to address PFAS, a class of anthropogenic organic contaminants. A leading technology for this application is GAC adsorption due to its familiarity and availability. The adsorption of four PFAS species (PFBA, PFBS, PFOA and PFOS) to Calgon Filtrasorb400 (F400) was evaluated for a range of pH and ionic strength conditions to investigate the role of electrostatic interactions in adsorption capacity. These PFAS are all strong acids, so pH was used as a control for GAC surface …