Digital Commons Network^™

Variable Selection In Mixture Cure Models Using Elastic Net Penalty: Application To Covid-19 Data, Aluwani Ramalata, Akim Adekpedjou, Maseka Lesaoana

Mathematics and Statistics Faculty Research & Creative Works

In survival analysis, it is often assumed that all individuals will eventually experience the event of interest if followed long enough. However, in many real-world scenarios, a subset of individuals remains event-free indefinitely. For instance, in clinical studies, some patients never relapse and are considered cured rather than censored. Traditional survival models are inadequate for capturing this heterogeneity. Mixture cure models address this limitation by distinguishing between cured and susceptible individuals while modeling the survival of the latter. A key challenge in mixture cure modeling is selecting relevant covariates, particularly when dealing with time-varying effects. This study develops a penalized …

Generative Artificial Intelligence Dependency: Scale Development, Validation, And Its Motivational, Behavioral, And Psychological Correlates, Adalia Yin Hui Goh

Dissertations and Theses Collection (Open Access)

The growing integration of generative artificial intelligence (AI) into everyday life has raised questions about its potential psychological and behavioral consequences. The present research develops and validates the Generative AI Dependency Scale, a multidimensional tool developed to assess individual differences in dependency on generative AI systems. Across six studies involving 1,223 participants from the United States and Singapore, the Generative AI Dependency Scale demonstrated strong psychometric properties, including a stable three-factor structure (cognitive preoccupation, negative consequences, withdrawal) and good test-retest reliability (ICC = .85). Confirmatory factor analysis supported a higher-order dependency construct, and scalar measurement invariance was established across sex …

The Impact Of Maternal Age On The Expression Of Transgenerational Plasticity In Daphnia Pulicaria, Calvin Nguyen

2025 Spring Honors Capstone Projects - Archive

Transgenerational plasticity refers to heritable, non-genetic changes in phenotype that persist across multiple generations and can enhance offspring survivability in variable environments. In Daphnia, increasing maternal age has been associated with maladaptive plasticity. To investigate this relationship, six clones were collected from two Wisconsin lakes and acclimated to laboratory conditions through a common garden rearing process. For each clone, ten replicates were generated and evenly divided between young (clutches 2–4) and old (clutches 5–8) maternal age groups. Offspring were exposed to three dietary treatments for three experimental generations: one fed only green algae, one fed only cyanobacteria (a nutritionally …

Cuegen: Customizing Sensor Captions For Neon Bending Tutorials, Gunnika Kapoor

2025 Spring Honors Capstone Projects - Archive

Methods of knowledge transfer that rely primarily on visual and/or auditory formats do not effectively convey context-specific or implicit skills, known as tacit skills. This limits knowledge transfer. In this work, the use of customizable pitch captions and spatial audio vibration captions is proposed to aid in conveying this tacit knowledge for neon glass bending video tutorials. Such a system is designed to provide users with greater control and support, which may maximize the information they obtain from, improve the autonomy they have with, and experience they have with a learning tool. As such, a system interface was developed that …

Controlling A Mobile Inverted Pendulum And Optimizing Leaning Angle To Apply Force Using Reinforcement Learning, Aryan Mediratta

2025 Spring Honors Capstone Projects - Archive

Reinforcement Learning is a Machine Learning paradigm that involves simulating learning through rewards and penalties in intelligent systems. This technique is often employed in robotics when traditional control methods are insufficient or when human intuition does not provide a good solution on how to control robot systems, This project involves training a Segway-style Mobile Inverted Pendulum (MIP) robot to balance and push a box forward. The BeagleBone Blue board is used that includes a built-in Inertial Measurement Unit (IMU) and encoder ports. These sensors enable the system to measure its current state. The goal is to find the optimal leaning …

Bismuth-207 For Purity Monitoring System For Lartpc: Dune And Proto-Dune, Rohit Raut

2025 Spring Honors Capstone Projects - Archive

The Deep Underground Neutrino Experiment (DUNE), the U.S. flagship neutrino experiment, relies on high purity liquid argon (LAr) for optimal detector performance. Ensuring and monitoring LAr purity is crucial, as electronegative impurities can degrade signal quality in detectors. As part of Proto-DUNE, a prototype detector at CERN for DUNE, this study explores the use of Bismuth-207 (Bi-207) as a novel tool for real-time LAr purity monitoring and calibration. Bi-207 emits monochromatic internal conversion electrons, allowing precise impurity assessment without interfering with standard detector operations. By simulating the behavior of radioactive Bi-207 and analyzing data from the Proto-DUNE Vertical Drift detector, …

Tutortech: A Web App For A Smarter And More Efficient Tutoring System, Smarika Pathak

2025 Spring Honors Capstone Projects - Archive

The Computer Science and Engineering (CSE) department faces challenges with managing its tutoring services, especially tracking attendance, booking sessions, and overall management of the tutoring system - all of which severely limits the ability for tutors to connect and engage with students. To help overcome these issues, TutorTech, a web-based application that provides improved management of the tutoring system and supports more engaging learning experiences between students and tutors was designed. Through this project, the aim was to optimize the TutorTech search capabilities - assisting students to find tutors based on skills, while also considering the effect of user interface …

Generating Motivational Messages For Behavior Change: Encouraging Users To Be More Physically Active, Hananeel Pankaj

2025 Spring Honors Capstone Projects - Archive

High levels of sedentary lifestyles can cause adverse effects in individuals’ health. This has prompted researchers to analyze ways to increase physical activity, including the use of Large Language Models (LLMs) to generate motivational messages. While research has found LLMs to be feasible for this task, the findings are limited in availability and scope given that the research focuses on a conversational, chatbot setting—which is not ideal in the real world. This research assesses OpenAI’s GPT-4o mini’s (one of several models powering ChatGPT) ability to tailor messages towards a user. This is done by passing user health data to the …

Navigation Of Unmanned Aerial Vehicle Using Computer Vision In Raytheon Drone Competition, Joseph R. Pavlik Iii

2025 Spring Honors Capstone Projects - Archive

A major problem with using GPS to navigate an unmanned aerial vehicle is that GPS signals do not accurately work while inside a building. This work presents the usage of the Simultaneous Localization and Mapping library, ORB-SLAM2, in C++ to solve this issue. By using the camera attached to the unmanned aerial vehicle, a map of the area covered by the drone will be created, and landmarks in area will be utilized to navigate throughout the interior of the building without the GPS. Based on previous studies, this navigation method should be viable. Preliminary tests show that this method will …

On The Challenges Posed By Non-Machian Solutions To Relationalism In General Relativity, Zachary Matthew Zito

Undergraduate Honors Capstone Projects

The relationship between Mach’s Principle and solutions to Einstein’s field equations is examined, with special attention to Friedmann-Lematre-Robertson-Walker (FLRW) cosmology. Mach’s Principle is outlined, and the extent to which general relativity fulfills Machs vision is assessed. It is argued that several important solutions to Einsteins equations, particularly the FLRW cosmological models, embody key Machian features. In order to elucidate the FLRW cosmological model, the associated energy-momentum tensor for a perfect fluid under the assumptions of large-scale homogeneity and isotropy is derived and used to obtain the Friedmann equations that govern cosmic expansion. It is shown that FLRW cosmology can be …

Diversity-Augmented Training For Generalizable Ai Agents, Wenjun Li

Dissertations and Theses Collection (Open Access)

Deep Reinforcement Learning (RL) has achieved remarkable success over the past decade, from superhuman performance in video games to real-world applications like robotics. However, RL models often lack generalization, making them unreliable when deployed in unfamiliar scenarios. For example, robots must adapt to varying terrains with different slopes and obstacles, yet standard RL training does not explicitly promote such adaptability. While various methods have been proposed to enhance RL robustness, achieving reliable generalization remains an open challenge.

This dissertation focuses on improving the generalization capability of agents in three major settings: infinite horizon RL agents, finite horizon RL agents, and …

Toward The Application Of Natural Language Processing In Electronic Health Record Analysis For Taxonomy Development, Latoya Mcdonald

All Dissertations

Electronic health records (EHRs) are pivotal resources for nurse practice because they increase the timeliness and reliability of patient information at the point of care and support access by multiple healthcare providers and the individual patients themselves. However, it is widely recognized that data extraction from EHRs is challenging due to the variability in the language used in clinical care notes and the lack of standardized terminology across healthcare systems. The broad objective of this dissertation is to develop taxonomy-based classification models for nursing care by applying feature engineering approaches to EHRs that include nursing care of ostomy patients following …

Earthscape Ai Dataset V1.1, Matthew Massey, Abdullah-Al-Zubaer Imran

Research Data--KGS

EarthScape v1.1 Dataset Download Links:

esv1p1_smokeset.zip (197 MB)

esv1p1_splits.zip (2.5 MB)

esv1p1_usa_ky_data.zip (1 MB)

esv1p1_usa_ky_hardin_howevalley.zip (26.3 GB)

esv1p1_usa_ky_hardin_sonora.zip (26.3 GB)

esv1p1_usa_ky_warren.zip (166 GB)

Surficial geologic mapping is essential for understanding Earth surface processes and supporting applications in engineering, hazard assessment, and resource management. However, traditional mapping approaches are labor-intensive, limiting spatial coverage and introducing subjectivity. To address these challenges, we introduce EarthScape, a multimodal, AI-ready geospatial dataset designed for surficial geologic mapping and Earth surface analysis. EarthScape integrates high-resolution aerial RGB and near-infrared (NIR) imagery, digital elevation models (DEM), multi-scale terrain features derived from DEMs, and hydrologic and infrastructure vector …

An Analysis Of Bias Towards Women In Large Language Models Using Likert Scale Evaluations, Sarah T. Fieck

Electrical Engineering and Computer Science (MS) Theses

Closed-source large language models (LLMs) developed by large technology companies continue to grow in popularity. However, ethical conversations surrounding the safety of model outputs have been a prominent topic of discussion. This project aims to assess three leading closed-source LLMs: OpenAI’s ChatGPT, Google’s Gemini, and Anthropic’s Claude, to analyze how their outputs perform when treated as a subject of several psychological evaluation scales measuring biased behaviors against women. The Ambivalent Sexism Index, Modern Sexism Scale, and Belief in Sexism Shift evaluations were used to get descriptions of how the LLMs respond to traditional and modern prompts involving sexism and gender …

Cultural Health Benefits And Challenges Of Food Preparation And Consumption: A Comparative Study Of The United States, Italy, And Norway, Natalie G. Link

Undergraduate Honors Thesis Collection

This study aims to investigate the cultural health benefits and challenges associated with food preparation and consumption in the United States, Italy, and Norway, with a particular focus on citizens in lower socioeconomic levels. By examining the dietary habits, social structures, and health outcomes in these three countries, this research aims to uncover broader insights into the health status and well-being of their respective populations. The study will employ secondary data analysis approach examining existing research on cultural practices and social support systems. The findings of this research will contribute to a deeper understanding of the complex interplay between food …

How Do Simulated Phishing Attacks Impact Cybersecurity Awareness And The Enhancement Of Security Protocols Among Faculty Members In A University Environment?, Navnoor Sandhu

University Honors Program Senior Projects

Phishing attacks are cyber threats where attackers deceive users into performing actions that compromise the user’s security and benefit the attacker. In 2024 alone, phishing attacks have resulted in estimated damages of around 800 million dollars [1]. In response, many institutions have implemented internal simulated phishing attacks to enhance their employees' cybersecurity awareness. This training exercise has been proven beneficial in improving cybersecurity awareness on an enterprise scale[4]. This study aims to evaluate the potential effectiveness of a simulated phishing attack within a university setting, which is a relatively unseen practice thus far. Universities, like other secure organizations, store sensitive …

Survey On Application Of Large Language Models In Network Attack And Defense, Prisha Purohit

Honors Theses

The emergence of Large Language Models (LLMs) has significantly transformed the technological and cybersecurity landscape, introducing both unprecedented opportunities and formidable challenges. With the public release of ChatGPT in 2022, LLMs have gained global prominence, redefining natural language processing capabilities and enabling advancements across various fields. In cybersecurity, these models represent a dual-use technology: while they offer powerful tools for threat detection, automated analysis, and security training, they also pose risks when leveraged by malicious actors for phishing, social engineering, and the creation of evasive malware. This thesis presents a comprehensive literature review exploring the dual roles of LLMs in …

Synthesis Of Single Chain Polymer Nanoparticle Networks By Reinitiating Raft Polymerization, Dallas Donovan

Honors Theses

Hydrogel materials, which are polymer networks comprised mostly of water, hold significant promise for biomedical applications due to their compatibility with biological systems. Conventional hydrogel materials are often brittle and weak, but most applications in biomedical systems require materials to be strong and tough. The topology of a polymer network dictates its mechanical properties. An important strategy for designing tougher hydrogels is the release of stored length, such as from the unfolding of polyprotein cross-linkers. Inspired by the success of the strategy, we report progress towards a fully synthetic design using single chain nanoparticles (SCNPs) into a hydrogel. SCNPs, which …

“I Can Run At Night!”: Using Augmented Reality To Support Nighttime Guided Running For Low-Vision Runners, Yuki Abe, Keisuke Matsushima, Kotaro Hara, Daisuke Sakamoto, Tetsuo Ono

Research Collection School Of Computing and Information Systems

Dark environment challenges low-vision (LV) individuals to engage in running by following sighted guide—a Caller-style guided running—due to insufficient illumination, because it prevents them from using their residual vision to follow the guide and be aware about their environment. We design, develop, and evaluate RunSight, an augmented reality (AR)-based assistive tool to support LV individuals to run at night. RunSight combines see-through HMD and image processing to enhance one’s visual awareness of the surrounding environment (e.g., potential hazard) and visualize the guide’s position with AR-based visualization. To demonstrate RunSight’s efficacy, we conducted a user study with 8 LV runners. The …

A Kinetic Analysis On Hydrolysis And Hydrothermal Conversion Of Cellulose To Dodecane, Joel Nyangoka Onyancha

Electronic Theses and Dissertations

Cellulose, the most abundant biomass on Earth, offers a promising pathway for alternative energy through conversion into alkane hydrocarbons. Traditional methods rely on high temperatures and high-pressure hydrogen, often derived from petroleum. In this study, we investigated the conversion of Microcrystalline Cellulose using hydrogen metal oxides (bronzes) under milder conditions. Following ASTM E3417-24 hydrolysis protocols, we employed hydrogen bronzes with toluene for product extraction. This approach enabled conversion at lower temperatures without pressurized hydrogen. Products were analyzed using Gas Chromatography Mass Spectrometer for identification and Gas Chromatography Flame Ionization Detector for quantification. Our findings revealed the formation of a possible …

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 …

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 …

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 …

Exploring Educational Affordances Of Interactive Murals, Alyshia Bustos

Computer Science ETDs

Interactive murals are a new technology that blend traditional mural painting and embedded electronics. My work contrasts traditional STEAM projects by introducing youth to programming, building electronics, and interaction design principles within the context of designing and constructing interactive murals. Accordingly my dissertation addresses the following: 1) How can we integrate traditional mural practices and ubiquitous computing in an interactive mural, 2) How do interactive murals support youth in learning how to program and build electronics, and 3) How can we design learning activities that support youth as interaction designers?

To address my research questions, I first conducted technical tests …

The 1991 California 'Miracle March': Precipitation Myth Or Miracle?, Cody D. Poulsen, Rachel E.S. Clemesha, Ian M. Howard, Alexander Gershunov, Michael D. Dettinger, Zhenhai Zhang, Rosa Luna-Nino, David W. Stahle, Ralph F. Martin

Geosciences Faculty Publications and Presentations

The term 'Miracle March' is colloquially used in California to describe an anomalously wet spring that alleviates drought conditions caused by a winter precipitation deficit. This study centers on the influential water year 1991, which is the standard reference point for this phenomenon. The spring precipitation impact on water year totals and the geographic extent of the spring precipitation anomaly during the 1991 'Miracle March' (MM91) is without equal in the observational record. This exceptional precipitation episode was initiated by a week-long sequence of extreme atmospheric rivers that started landfalling on February 27th. To this day, MM91 is routinely referenced …

Quantum Oscillation Studies Of The Nodal Line Semimetal Ni3in2s2-Xsex, M. M. Sharma, Santosh Karki Chhetri, Gokul Acharya, David Graf, Dinesh Upreti, Sagar Dahal, Md Rafique Un Nabi, Sumaya Rahman, Joshua Sakon, Hugh O.H. Churchhill, Jin Hu

Physics Faculty Publications and Presentations

Ternary shandite compounds with the general formula T3M2X2 (T = Ni, Co, Rh or Pd; M = Sn, In, or Pb; and X = S or Se) have emerged as a large pool of topological semimetals. This family of compounds hosts different topological phases for various combinations of T, M and X. This paper reports the observation of quantum oscillations under the high magnetic fields in Ni3In2S2-xSex single crystals. Angular dependence of oscillation frequency suggests an evolution of the Fermi surface from three-dimensional to two-dimensional on Se substitution for S in Ni3In2S2. The effective mass obtained for each composition by …

Resilience Webtool: Engaging Community Partners To Humanize Data For Use In Local Resilience Planning In Valley County, Idaho, Sabrina Akther

Boise State University Theses and Dissertations

Advancements in technology have made hazard data increasingly available. However, officials in rural communities with limited resources often face challenges in accessing, interpreting, and applying these data to assess vulnerabilities and plan future development. Furthermore, when hazard data is not paired with relevant population and infrastructure, data vulnerability assessments become increasingly difficult. To address this challenge, this project aims to co-create a web tool with decision makers in Valley County, Idaho following a user-centered design approach, consolidating hazards, social vulnerability, and infrastructure data to help local officials with risk management, decision-making, and resilience planning. The project started with listening sessions, …

Alphamissense Predictions And Clinvar Annotations: A Deep Learning Approach To Uveal Melanoma, David J. Taylor Gonzalez, Mak B. Djulbegovic, Meghan Sharma, Michael Antonietti, Colin K. Kim, Vladimir N. Uversky, Carol L. Karp, Carol L. Shields, Matthew W. Wilson

Wills Eye Hospital Papers

OBJECTIVE: Uveal melanoma (UM) poses significant diagnostic and prognostic challenges due to its variable genetic landscape. We explore the use of a novel deep learning tool to assess the functional impact of genetic mutations in UM.

DESIGN: A cross-sectional bioinformatics exploratory data analysis of genetic mutations from UM cases.

SUBJECTS: Genetic data from patients diagnosed with UM were analyzed, explicitly focusing on missense mutations sourced from the Catalogue of Somatic Mutations in Cancer (COSMIC) database.

METHODS: We identified missense mutations frequently observed in UM using the COSMIC database, assessed their potential pathogenicity using AlphaMissense, and visualized mutations using AlphaFold. Clinical …

Community Voices, Climate Action Choices: Working Towards A Resilient Monterey County, Lesley A. Solano Alonso

Capstone Projects and Master's Theses

Vulnerable communities in Monterey County face disproportionate environmental and health impacts due to climate change, yet many residents remain unaware of the tools and resources available to support local action. This capstone project was implemented in partnership with Ecology Action (EA) and the Resilient Central Coast (RCC) campaign to increase awareness and engagement with the RCC platform. Serving diverse communities across Monterey County, the project included bilingual outreach efforts, community tabling, educational presentations, and a climate action survey. Over 650 residents were engaged directly, resulting in 99 new household sign-ups on the RCC website, a major milestone for the agency. …

Phoneme Recognition For Pronunciation Improvement, Matthew Heywood

Theses/Capstones/Creative Projects

This project aims to improve English pronunciation by investigating speech errors and developing a tool to provide precise feedback. The study focuses on creating a new pronunciation tool that offers localized feedback, identifies specific errors, and suggests corrective measures. By addressing the shortcomings of current methods, this research seeks to enhance pronunciation refinement.

Utilizing cutting-edge technology, the tool leverages speech-to-phoneme AI models and modified lazy string matching algorithms to compare the user's spoken input with the intended pronunciation. This allows for a detailed analysis of discrepancies, providing users actionable insights into their phonetic errors. The speech-to-phoneme AI models mark a …