Digital Commons Network^™

Seedlings Of Pacific Northwest Plants: A Photographic Guide, Gabriel E. Campbell-Martinez, Roxy Olsson

Rae Selling Berry Seed Bank and Plant Conservation Program

This document presents a visual, non-technical field guide of native and exotic/invasive seedlings that grow wild in the Pacific Northwest. It contains over 550 taxa representing a broad range of families and ecosystems, focusing on species that occur in Oregon and Washington. Species were selected to reflect ecological importance, frequency of occurrence, and relevance to land management, restoration, and conservation. It is intended for a broad audience, including restoration practitioners, land managers, botanists, ecologists, students, naturalists, and others interested in identifying plants at early life stages.

Comparative Analysis Of Machine Learning Models For Glioblastoma Survival., Muna Awel

All Graduate Theses, Dissertations, and Other Capstone Projects

Glioblastoma multiforme (GBM) remains one of the most lethal brain tumors, necessitating improved survival prediction models that integrate clinical and molecular data. This study develops a comprehensive machine learning pipeline leveraging TCGA-derived multi-omics datasets to predict binary survival outcomes. The framework integrates four classifiers Logistic Regression, Random Forest, XGBoost, and Support Vector Machine (SVM) and includes rigorous preprocessing with MCAR testing, KNN imputation, feature scaling, and hyperparameter optimization via GridSearchCV. SMOTE was applied to mitigate class imbalance and enhance model robustness for minority survival classes. Comparative performance analyses revealed Random Forest and XGBoost as top performers, achieving the highest recall …

Education Is Not A Commodity – It Is A Human Right, Barbara Stark

Denver Journal of International Law & Policy

America has embraced neoliberalism, and virtually everything that is tangible—and much that is not—has been commodified. Natural resources once thought of as ‘free,’ such as water, have been packaged and branded. ‘Value’ is routinely conflated with ‘cost.’ This article explains why education should not be regarded as a commodity, but as an internationally recognized human right. Like the right to free speech, it should be free and meaningful. It should be a national priority. The United States does not recognize education as a human right. If it did, public education in this country would probably be in better shape. Equally …

Completions 2024-25, Southwestern Oklahoma State University

IPEDS

Welcome to the IPEDS Completions survey component. The Completions component is one of several IPEDS components that is conducted during the Fall data collection period. It collects the number of degrees and certificates awarded by field of study, level of award, race/ethnicity, and gender. The reporting period for the Completions component is during the12-month time period beginning July 1 of the previous calendar year and ending June 30 of the current calendar year; therefore, for this year’s Completions component, the reporting period is between July 1, 2023 and June 30, 2024. The Completions component is also collecting the number of …

Fall Enrollment 2024-25, Southwestern Oklahoma State University

IPEDS

IPEDS Report created by the SWOSU Office of Institutional Research

Rotary Operations Management & Automation Platform (Romap): Modernizing Attendance Tracking And Data Submission For Rotary Clubs, Zaineel Mithani

2025 Fall Honors Capstones Projects - Archive

As Technical Lead of the Rotary Operations Management & Automation Platform (ROMAP), my Honors contribution focused on developing a Bluetooth Low Energy proximity-based attendance system enabling automatic, hands-free member check-ins. I researched and selected beacon hardware, designed RSSI-based distance calculation algorithms, and implemented platform-specific background processing for iOS and Android, achieving 97% detection accuracy. Beyond this Honors component, I architected the complete backend infrastructure including a Node.js API with 20+ endpoints, PostgreSQL database with Prisma ORM, and JWT authentication. I also developed a novel GPT-4 Vision automation system that intelligently populates web forms through computer vision, achieving 95% success rate …

Identifying The Constituents Of Pyrolysis Oil Using Supercritical Fluid Chromatography- Fraction Collection (Sfc-Fc) And Gas Chromatography- Mass Spectrometry/Vacuum Ultraviolet Spectroscopy (Gc-Ms/Vuv), Sadid Morshed

2025 Fall Honors Capstones Projects - Archive

Plastic waste continues to accumulate as production increases and disposal methods remain insufficient. Even with recycling programs in place, much of the discarded plastic still ends up in landfills or waterways, eventually breaking down into harmful microplastics. One promising solution is the conversion of plastic waste into pyrolysis oil, which can also serve as an alternative feedstock for chemicals. Pyrolysis oil is produced by heating plastics to approximately 800 °C in the absence of oxygen, resulting in a complex mixture of hydrocarbons that includes paraffins, isoparaffins, olefins, naphthenes, and aromatics. Analyzing the amount of oxygen, nitrogen, and sulfur in these …

How Self-Perceptions Relate To Recorded Proficiency: An Action Research Project Aimed At Implementing A Supplemental Reading Program For Balinese Students, Katherine L. Johnson

2025 Fall Honors Capstones Projects - Archive

English as a Foreign Language (EFL) education has had a complex history globally. This is especially true for Bali, Indonesia, where tourism is the main driver of the local economy. Learning English is highly valued, yet many students are left struggling to build the skills needed to rise above the local poverty line. In this action research study, the primary goal was to analyze students’ reading proficiencies to recommend the implementation of a reading program that could be appropriately tailored to individual students. This was done through administering a reading test, tracking both comprehension and reading speed, and a survey …

The Effect Of Zebra Mussels On Minnesota Fish Communities, Benjamin D. Strei

Journal of Earth and Life Science

Zebra mussels Dreissena polymorpha are an aquatic invasive species that has been spreading quickly throughout Minnesota water bodies since 1989. Zebra mussels are known to change certain morphological conditions in lakes such as turbidity, phytoplankton abundance, and aquatic invertebrate populations. However, studies showing impacts of the infestation of zebra mussels on the health of a fish community have been hard to prove due to a lack of repeated surveys and a suite of other confounding variables such as natural and seasonal variability, plant community, and lake morphometry. Therefore, the objective of this study is to determine whether zebra mussels have …

Hybrid Agentic System For Schema-Aware Nl2sql Generation, David Omondi Onyango

All Graduate Theses, Dissertations, and Other Capstone Projects

The natural language to SQL (NL2SQL) task enables non-expert users to interact with relational databases via natural language interfaces. However, NL2SQL frameworks often rely on Large Language Models (LLMs), raising concerns about computational overhead, data privacy, and deployment in resource-limited environments. To address these issues, we propose a hybrid schema-aware agentic system using Small Language Models (SLMs) as primary agents, with a selective LLM fallback mechanism. The LLM activates only when errors are detected in SLM-generated queries, reducing inference costs. Experiments on the BIRD benchmark dataset show our system achieves an execution accuracy of 53.91% and validation efficiency score of …

Advancing Particle Detection In High-Energy Physics Through Simulation And Experimentation, Ilker Parmaksiz

Physics Dissertations - Archive

Particle detectors are the cornerstone of experimental high energy physics. They enable physicists to study fundamental interactions and characterize subatomic particles. Recent advancements in detector technology have been propelled by the inventive integration of simulation, advanced materials, and improved electronic readouts. The primary motivation of this thesis is to advance the detector technologies to enhance sensitivity to neutrinoless double beta decay in high pressure xenon time projection chambers. Additionally, it includes work on other detector technologies, such as liquid argon time projection chambers, and documents my involvement in assembly, measurement, and simulation efforts.

Summary of the Chapters and Appendices Included …

Signal Analysis Of Calcium Dynamics In Pancreatic Cells, Abhidha Kunwar

2025 Fall Honors Capstones Projects - Archive

Calcium (Ca²⁺) signaling plays a critical role in insulin secretion from pancreatic βcells. Photo-biomodulation (PBM) of red or near-infrared wavelengths is applied to enhance cellular metabolism and Ca²⁺ activity in pancreatic cells. This study aims to rigorously analyze how PBM influences calcium dynamics in pancreatic cells by applying the Fast Fourier Transform (FFT), converting Ca²⁺ spiking patterns to the frequency domain to determine dominant oscillatory behaviors. Using a calcium-binding fluorophore, Ca²⁺ activity was acquired before and after PBM at 810 nm, processed with a machine learning algorithm, and further analyzed in MATLAB using FFT to assess changes in calcium signal …

Direct Partial Oxidation Of Methane To Methanol Using Dioxygen Over Superhydrophobic Modified Catalysts, Oluchukwu V. Igboenyesi

Chemistry & Biochemistry Dissertations - Archive

Various methods for enhancing catalysts activity and productivity in gas to liquid synthesis like Direct Methane to Methanol Conversion and Fischer Tropsch Synthesis have been studied over the years. Some of these methods include the use of promoters, bifunctional catalysts, introducing steam, optimizing reaction conditions and catalyst modification. The choice of catalysts and their modification plays a critical role in improving the overall productivity in gas to liquid synthesis.

This research explored the superhydrophobic modification of heterogenous catalysts used in Direct Methane to Methanol Conversion (DMTM) and Fischer Tropsch Synthesis (FTS). The catalysts were modified with Perfluoro alkyls (PFSMA). The …

Copper-Based Oxide Semiconductors: Transparent Conductors And Ternary Alloys, Abhishek Rawat

Chemistry & Biochemistry Dissertations - Archive

This dissertation explores the strategic design and development of copper-based metal oxide semiconductors for photoelectrochemical (PEC) and optoelectronic applications, with a focus on advancing materials for sustainable energy technologies. Through a comprehensive investigation into copper vanadates and copper oxides, the work aims to understand and enhance charge transport, light-harvesting capabilities, and electronic structure modulation. The research integrates fundamental materials chemistry with applied photoelectrochemical studies to uncover the role of copper's d-electrons in mid-gap state formation, multifunctionality through electronic structure tuning, and the development of low-temperature transparent conductive oxides.

In chapter 2, we have discussed the attributes of copper metavanadate (CuV …

The Impact Of Inter-Subunit Communication On F420h2:Nadp+ Oxidioreductase: A Kinetic Approach, Jamariya A. Howard

Chemistry & Biochemistry Dissertations - Archive

F₄₂₀H₂:NADP⁺ Oxidoreductase (Fno) catalyzes the reversible reduction of NADP⁺ to NADPH using reduced F₄₂₀ as the hydride donor. Both NADPH and the F₄₂₀ cofactor play significant roles in various metabolic pathways, including glycolysis and methanogenesis, particularly in methanogenic and sulfate-reducing archaea. These organisms play an essential role in global carbon cycling by converting carbon dioxide to methane through the methanogenic pathway, which is directly tied to energy production. This thesis investigates the hydride transfer mechanism of Fno from the extreme thermophile Archaeoglobus fulgidus, using fluorescence binding, steady-state and pre steady-state kinetics.

Chapter 1 outlines the structural and spectral characteristics …

Statistical Analysis Of Climate Trends And Variability In Tarrant County Using Annual, Decade, And Three-Decade Time Periods, Quinnton Debolt

Earth & Environmental Sciences Theses - Archive

This study is a statistical analysis of climate trends within the Dallas-Fort Worth metroplex according to several time-scale models to understand how the climate for the locality has changed and to provide a basis for projections of what future climate might look like. Trends in mean temperature and precipitation for North Central Texas generally correlate with corresponding global trends linked to natural variability and anthropogenic-induced climate change. Temperature rises in this region annually by 0.08°C and by 0.22°C for a three-decade average. Seasonal increases in three-decadal averages of temperature for North Central Texas relative to the average of the reference …

Spatiotemporal Analysis Of Extreme Precipitation Events In Texas, Anusha Kandi Ravi

Earth & Environmental Sciences Theses - Archive

Extreme precipitation events (EPEs) are among the most critical weather hazards in Texas, frequently leading to floods, infrastructure damage, and costly economic losses. Therefore, analyzing the spatiotemporal patterns of EPEs is vital, particularly for improving regional climate predictions and hazard preparedness. Although the propagation of EPEs has been previously investigated using complex network theory, the evolution of their climate network has not yet studied. For this purpose, we first collected precipitation data from the NOAA AORC dataset for the 1980-1989, 1990-1999, 2000-2009, 2010-2019, and 2020-2024 periods. The EPEs were identified based on the 95th percentile of wet-day precipitation (≥ 1 …

Advancing Machine Learning Approaches Through Robust Methodologies In Llm Code Generation, Adversarial Text Classification, And Unsupervised Learning, Anahita Samadi

Computer Science and Engineering Dissertations - Archive

This dissertation combines insights across text, code, and image modalities to advance the robustness, efficiency, and adaptability of machine learning models. Specifically, we address challenges like adversarial vulnerability in text, the impact of test strategies on code generation, and dimensionality in image representation in unsupervised learning domain. These efforts highlight pipelines for designing machine learning systems that are not only efficient, but also adaptable to complex environments. In addition, these efforts together help form the basis for a multimodal AI capable of thriving in medical applications that this dissertation prototypes for future efforts.

3d Perception, Mapping, And Navigation For Mobile Cobot, Tuan T. Dang

Computer Science and Engineering Dissertations - Archive

Service robots are migrating from tightly controlled factory lines into offices, hospitals, and homes, where they must perceive, remember, and act amid people, clutter, and perpetual change. Humans solve this daily by forming compact, task-relevant “cognitive maps”: we sample just enough sensory detail to guide the moment, stitch those snapshots into a sparse topological scaffold, and continuously refine it as we move. Guided by that insight, this dissertation proposes a biologically inspired mapping framework that turns partial RGB-D observations into a hybrid temporal-spatial memory—locally metric for centimeter-scale navigation yet globally topological for room-to-building navigation. The system first distills raw depth …

Environment And Intention Awareness For Navigation And Collaboration, Bhaskar Chandra Trivedi

Computer Science and Engineering Dissertations - Archive

Unmanned Aerial Systems (UAS) have become increasingly popular as versatile platforms for tasks such as surveillance, inspection, delivery, and maintenance. In many applications, UAS operate in environments frequented by people or containing sensitive infrastructure, which introduces physical risks in case of vehicle failure, as well as psychological and privacy concerns that may limit their acceptability. Ensuring safe and efficient operation thus requires that UAS consider these risks when planning navigation strategies. While prior information, such as city maps and building layouts, can partially inform risk assessment, such data is often incomplete, necessitating real-time augmentation of risk maps using sensor information. …

Scalable, Secure, And Adaptable Perception Systems Through Adversarial Analysis And Federated Fine-Tuning, Arkajyoti Mitra

Computer Science and Engineering Dissertations - Archive

Perception systems are fundamental to intelligent machines, enabling them to sense, understand, and interpret complex environments. However, as perception increasingly underpins critical applications such as autonomous vehicles, IoT healthcare devices, and smart trading platforms, challenges related to security, scalability, and environmental understanding have become more pressing. This work addresses three core research questions: (1) How can we identify, analyze, and mitigate adversarial vulnerabilities in perception systems to ensure reliable operation under adversarial conditions? (2.1) How can AVPS models be efficiently scaled and fine-tuned across decentralized and resource-constrained environments while preserving privacy and performance? (2.2) How can we scale generative models …

Reversal And Visualization Of Guitar Stomp Box Effects Using Digital Signal Processing Techniques, Zayaan Sharif Chowdhury

2025 Fall Honors Capstones Projects - Archive

This project presents an approach that develops a Digital Signal Processing (DSP) system that analyzes, and reverses audio effects produced by a custom-built multi-effect guitar stomp box. Using real-time input from the stomp box, the DSP system digitizes the audio signal through an analog-to-digital converter and processes it in Python using NumPy and SciPy libraries. It visualizes parameters such as frequency spectrum, modulation rate, depth, and total harmonic distortion (THD) to evaluate the quality of analog effects like tremolo, delay, vibrato, and reverb. Beyond visualization, the system explores reversing these effects through digital filtering and signal reconstruction, aiming to approximate …

Parsimony, Parallelism, And Presentation: The Impact Of Presentation On Evaluation, Peter Mclemore

Psychology Theses - Archive

In professional and academic settings, support for creative ideas often hinges on how effectively those ideas are communicated in writing. This study examined how two sentence-level rhetorical features—parsimony and parallelism—influence the evaluation, support, and recall of written proposals featuring creative restaurant concepts. Using a 2×2 within-subjects design, 211 undergraduates reviewed proposals manipulated to vary in parsimony (high vs. low) and parallelism (high vs. low). Participants rated each proposal on quality, originality, elegance, support, and completed a recall task. Contrary to expectations, proposals with low parsimony and low parallelism received the highest evaluations across all three creative indicators (i.e., quality, originality, …

Discrete Time Risk Processes With Stochastic Premiums And Dividends, Enoch J. Dangbe

Mathematics Dissertations - Archive

Risk processes typically emerge in insurance and finance and are concerned with stochastic representation of uncertainties of real-world events. Main objective amounts to quantifying the chances of both desirable and undesirable events and balancing their mutual impact for the purpose of developing models that in some sense optimize the outcome from the business perspective. Our research is concerned with studying the evolution of the surplus process in which time and assets are integer-valued. Initial capital, random premiums, random claims, dividend payments based on assets’ performance constitute the components of our model. Our findings established recursive formulas for the total expected …

Modified Core-Line Techniques For Vortex Identification Using Liutex, Bassam Albalawi

Mathematics Dissertations - Archive

Vortex dynamics govern critical processes in turbulent flows, yet conventional identification methods struggle to resolve individual structures' morphology and evolutionary pathways. Detecting and extracting vortex structures by objective algorithms may lead to a better understanding of turbulence regeneration dynamics through the automated and quantitative assessment of the structures. Although there are many vortex-identification criteria available, they pinpoint only the spatial regions belonging to vortices, with no information on the specific identity, topology, and shape of individual vortices. In this dissertation, we develop a new scheme based on Vortex axis tracking by iterative propagation (VATIP), called modified VATIP algorithm, for three-dimensional …

Examining Student Understanding Of Series Convergence Using Script Writing, Eduardo Torres Manzanarez

Mathematics Dissertations - Archive

This exploratory study investigates second-semester calculus students’ understanding of series convergence using both nonscripting and scripting-based tasks. Researchers recognize that students encounter difficulties with learning series, including series convergence, and that there is a need for more meaningful tasks that aid students’ learning of series. Script writing, used mainly with prospective mathematics teachers, can be used to explore mathematical understandings. Thus, this study examines how script writing, in the form of a scripting task, elicits students’ understanding of series convergence in contrast to nonscripting-based tasks to determine the potential of script writing in assessing this student understanding. We examine students’ …

Enhancing Inquiry-Based Science Instruction: The Role Of Professional Learning Communities And Instructional Coaching For Elementary Science Teachers, Marc T. Sager, Karen Pierce, Jessica Murillo

Publications

Inquiry-based science instruction fosters critical thinking, problem-solving, and scientific literacy by engaging students in exploration, questioning, and reflective learning. However, implementing inquiry-based practices presents significant challenges for elementary teachers, who often balance multiple subjects and may feel less confident facilitating open-ended investigations. This study examines how school-based coaching and professional learning communities (PLCs) support teachers in adopting inquiry-based science instruction. Grounded in distributed cognition theory of learning, this research draws on qualitative data from classroom observations and artifacts from coaching sessions and PLC meetings. Using a multiple case study design, this study identifies four case studies to illustrate varying levels …

The Genesis Of Constitutions: A Natural Language Processing Approach, Tejas Ramdas, Patrick Chung-Chia Huang, Nuno Garoupa, Martin T. Wells, Yun-Chien Chang, Tom Ginsburg

Public Law and Legal Theory Working Papers

The diffusion of constitutional ideas and models has been the subject of extensive scholarship. In this paper, we use natural language processing methods to examine the persistence of constitutional ideas and models, focusing on how 16 core and iconic constitutions influence 572 newer constitutions over a long period (1900–2020). Our findings indicate that “old” core constitutions (such as those of the U.S. of 1789, Spain of 1812, France of 1848, and to a lesser extent France of 1791) have maintained significant influence over those 121 years. Austria of 1920 and France of 1946 are the most influential among the 20th …

Resetting The Imposter Phenomenon Reality: A Mixed Methods Research Study Of An Immediate Cognitive Behavioral Intervention On Stem Practitioners, Peter D. Smith

Dissertations

Imposter Phenomenon (IP) remains an essential framework for understanding how professionals attribute success to chance or misconceptions rather than genuine abilities. IP is especially pertinent for individuals who feel like frauds when attaining higher positions, convinced the promotions resulted from luck rather than accomplishments and credibility. The misguided mindset cultivates feelings of inadequacy or deceit, even when accolades, experiences, and qualifications prove the contrary. The prevalence of IP is widespread, impacting numerous individuals who have faced or continue to endure episodes of varying intensity. The psychological state makes individuals vulnerable to feelings of inadequacy, leading to reduced productivity, increased procrastination, …

Explainable Diagnosis Prediction Through Neuro-Symbolic Integration, Qiuhao Lu, Rui Li, Elham Sagheb, Andrew Wen, Jinlian Wang, Liwei Wang, Jungwei W Fan, Hongfang Liu

Faculty, Staff and Student Publications

Diagnosis prediction is a critical task in healthcare, where timely and accurate identification of medical conditions can significantly impact patient outcomes. Traditional machine learning and deep learning models have achieved notable success in this domain but often lack interpretability which is a crucial requirement in clinical settings. In this study, we explore the use of neuro-symbolic methods, specifically Logical Neural Networks (LNNs), to develop explainable models for diagnosis prediction. Essentially, we design and implement LNN-based models that integrate domain-specific knowledge through logical rules with learnable weights and thresholds. Our models, particularly Mmulti-pathway and Mcomprehensive, demonstrate superior performance over traditional models …