Digital Commons Network^™

Parent Perspectives On Primary And Secondary Online Learning, Barbara Tanner Sandberg

Theses and Dissertations

Given the growth of K-12 online learning and the expanded responsibilities parents often assume in this learning context, the purpose of this dissertation is to understand parents' perspectives on K-12 online learning. The first article reviews and synthesizes literature documenting parents' perspectives on how instructional modality affects parental support. Instructional modality affects parental support roles, parental perception of online school support, parents' lives outside the online course, and students' online learning support needs. Hence, parents expect modality decisions to account for modality affordances, student engagement, and personal circumstances. The second article examines parent perspectives on the decision to leave a …

Panda-Plus-Bench: A Clinical Benchmark For Evaluating The Robustness Of Ai Foundation Models In Prostate Cancer Diagnosis, Joshua L. Ebbert, Dennis Della Corte

Faculty Publications

Artificial intelligence foundation models are increasingly deployed for prostate cancer Gleason grading, where GP3/GP4 distinction directly impacts treatment decisions (active surveillance vs. intervention). However, these models may achieve high validation accuracy by learning specimen-specific artifacts rather than generalizable biological features, limiting real-world clinical utility. We introduce PANDA-PLUS-Bench, a curated benchmark dataset derived from expertly annotated prostate biopsies designed specifically to quantify this failure mode. The benchmark comprises nine carefully selected whole slide images from nine unique patients containing diverse Gleason patterns, with non-overlapping tissue patches extracted at both 512 × 512 and 224 × 224-pixel resolutions across eight augmentation conditions. …

An Informationally Novel Sense Of Triviality For Harman’S Clutter Principle, Joseph D. Rasmussen

Undergraduate Honors Theses

Gilbert Harman (1986) argues that we ought not believe some logical consequences of our beliefs. To do this, he uses the Clutter Principle—that we should not clutter our minds with trivialities—and claims that some logical consequences are in some sense trivial. I show that interpreting Harman’s argument using an interest-driven sense of triviality (e.g. what Friedman calls junk) conflicts with a plausible epistemic norm. In light of this, epistemologists have turned the Clutter Principle into a norm on inquiry. This, however, loses the strength of the Clutter Principle in Harman’s argument. In this paper, I provide an alternate sense of …

Rethinking Functional Groupings In Basketball Wings Through Ecological Trait Frameworks, Dhruv Mehrotra

Theses and Dissertations

This paper starts with a review about Plant Functional Types and then goes deeper into the conceptual foundations of Plant Functional Types (PFT's) with detailed discussion of global trait spectra such as the leaf economics spectrum and the fast-slow continuum. Using concepts like response and effect traits, the review then talks about how a trait based ecological framework can provide a more robust guideline to classify plants. The review then talks about how players in basketball have been classified in the past along with some of the newer typologies. The review starts to draw some parallels between the ecological framework …

The Reliability Of Yolo Object Detection On The Amd Versal In A Proton Radiation Environment, Jacob D. Brown

Theses and Dissertations

Object detection is an important operation for satellites to be able to perform, and in outer-space missions it is crucial that machine learning models perform inference on satellite images accurately and reliably. Where size, weight, power, and other constraints exist, meeting this goal for accurate and reliable object detection is challenging. Additionally, soft errors caused by radiation further disrupt and degrade the operation of object detection in satellites. This thesis studies the performance of a deep learning model on an embedded device, the AMD Versal, in the presence of soft errors. The well-known and high-performing YOLO convolutional neural network was …

The Lawyer Is In!: Copyright Litigation Over Time, Ellen Amatangelo, Marissa Bischoff, Morgan Capitan, Jack Newman

Faculty Publications

This presentation is an overview of copyright litigation that has affected libraries. The session provides a hands-on look at specific cases and how they have affected and changed library work over time. A lawyer from the BYU Copyright Office provides commentary on each case and librarians discuss the impact of these cases on library policy. This helps to alleviate librarians' fear of copyright and legislation and provides guiding principles for the future.

This session was hosted by the Copyright Education Roundtable and presented at the Utah Library Association 2026 Annual Conference.

Real-Time Instruction Internalization For Large Language Models, Brenden Smith

Theses and Dissertations

For the end user, Large Language Models (LLMs) are programs that process natural language inputs into natural language outputs. In popular usage, this tends to take the form of conversation: a user asks a question, provides information, or gives instructions, and the LLM (hopefully) replies in a manner we would expect of an informed and compliant person. While convenient and intuitive for users, this natural conversational format encourages the misconception that LLMs are learning from conversations, when they do not. This work presents the benefits and practicality of a language model paradigm that meets this user expectation -- that is, …

Beyond Pedagogical Inertia: Understanding And Overcoming The Barriers To Effective Faculty Work In Higher Education, Yoshihiko Ariizumi

Learning, Teaching, & Researching Optimization

Academic faculty are among the most educated professionals in the world. Yet a striking body of empirical research demonstrates that they face profound, systematic barriers to performing their own work effectively—barriers that are cognitive, institutional, cultural, and structural in origin. This paper extends the analysis of “pedagogical inertia” beyond the classroom to the full scope of faculty professional life: research, writing, service, advising, and self-directed learning. Drawing on evidence from organizational psychology, cognitive neuroscience, higher education research, and behavioral science, we identify six classes of barriers that consistently impede effective faculty work, and we analyze—with reference to documented successful cases—the …

Neuroscience-Based Intellectual Productivity: A Ten-Principle Methodology For Knowledge Workers, Yoshihiko Ariizumi

Learning, Teaching, & Researching Optimization

This paper presents a comprehensive, neuroscience-grounded methodology for enhancing intellectual productivity among knowledge workers—particularly academic faculty and researchers operating under conditions of chronic cognitive overload. Drawing on ten foundational principles derived from contemporary cognitive neuroscience, we argue that substantial gains in research output, creative ideation, and knowledge integration are achievable not by working harder, but by working in deliberate alignment with the brain’s native computational architecture.

The ten principles address: strategic activation of the Default Mode Network (DMN) for incubation and creative insight; prefrontal cortex (PFC) energy management through temporal task separation; externalization of cognitive load via AI-assisted working memory …

Working Smarter, Not Harder: A Practical Guide To Intellectual Productivity, Yoshihiko Ariizumi

Learning, Teaching, & Researching Optimization

This guide offers general suggestions drawn from recent research. Every person thinks, works, and recharges differently. Please treat what follows not as a checklist to follow slavishly, but as a menu of ideas — pick what resonates, adapt freely, and discard whatever does not fit your life.

Engagement Modeling And Inference For Risk-Aware Path Planning Under Adversarial Uncertainty, Grant Stagg

Theses and Dissertations

This dissertation develops methods for planning safe and efficient trajectories for autonomous vehicles operating in environments containing adversarial and environmental threats with uncertain parameters. The central objective is to quantify and control the risk of adverse events--such as interception or detection--when threat characteristics are imperfectly known. To address this challenge, probabilistic weapon engagement zone (PEZ) models are introduced to estimate the likelihood of violating adversarial engagement constraints under uncertainty in pursuer state and capabilities. Multiple computational strategies are developed for PEZ evaluation, including first-order sensitivity-based approximations, Monte Carlo estimation, and neural-network surrogate models. These approaches enable rapid engagement-probability assessment and …

Analysis Of Approximations In Flash Thermal Diffusivity Measurements Using High‑Fidelity Simulations, Tage T. Burnett, Jakob G. Bates, Matthew R. Jones, Christopher R. Dillon, John Tencer

Faculty Publications

Thermal diffusivity is an important material property for understanding and characterizing transient behavior in many heat transfer applications. This study investigates the accuracy and approximations of inverse mathematical models for measuring thermal diffusivity of materials via the widely used Flash Method. High-fidelity simulations of the Flash Method in copper, silicon carbide, silicon, and glass were performed as numerical experiments and included physics such as in-depth absorption, radial conduction, and surface convection. Data from those numerical experiments were used to estimate material thermal diffusivity using seven traditional and new inverse models. Parker’s original model had relative errors 𝜖< 5% when the approximations it makes were enforced in numerical experiments. Newer models performed well even when experimental restrictions were relaxed. Models that include radial heat conduction were capable of accurately measuring thermal diffusivity (𝜖< 1%) when a Gaussian energy source was used. Models with radial conduction and in-depth material absorption of the laser source could calculate thermal diffusivity for semi-transparent materials such as silicon (𝜖< 1%) and even transparent materials like glass (𝜖< 10%). Convective losses from the material’s front surface had a negligible impact on measurements except for very low thermal diffusivity materials. Using temperatures from many locations of the test material’s surface increased resilience to noise, reducing the distribution of thermal diffusivity measurements by more than an order of magnitude. The models developed in this study could enable a more relaxed Flash Method experimental setup that maintains thermal diffusivity accuracy and extend the utility of the Flash Method to semitransparent materials.

Full Issue

The Bridge

No abstract provided.

What Makes Leaders In Human Services Effective? A Pilot Study Linking Systems Thinking, Perspective-Taking, And Leadership Success, Ryan Witterschein

Journal of Nonprofit Innovation

Leadership effectiveness is a persistent challenge in human services nonprofits, where organizations serving individuals with disabilities and complex needs have grown dramatically but lack validated tools for assessing the cognitive competencies that distinguish effective leaders. This quantitative pilot study introduces the ABA Leadership Assessment Tool version 2.0 (ABLA 2.0), a 48-item instrument integrating transformational and transactional leadership frameworks with three constructs from Relational Frame Theory—perspective-taking, temporal reasoning, and systems thinking. Eight Board Certified Behavior Analysts in organizational leadership roles completed the assessment, yielding 100% completion and strong preliminary reliability across all subscales (α = .71–.94). Leaders who demonstrated stronger cognitive …

A Comparative Study Of Tin Electrorefining In Molten Licl–Kcl–Cacl₂: Experimental Two-Electrode Current Control And Theoretical Three-Electrode Potential Control, Bryant Johnson, George Ankrah, Ander Fuller, Devin Rappleye

Reviews, Analyses, and Instructional Studies in Electrochemistry (RAISE)

Molten salt electrorefining is a mature technology for metal recovery, yet conventional current‑controlled, two‑electrode operation provides limited electrochemical selectivity and restricted insight into electrode‑specific behavior. In this work, a simplified model is developed to compare current‑controlled two‑electrode electrorefining data with a potential‑controlled three‑electrode electrorefining simulation using tin in molten LiCl–KCl–CaCl₂ as a surrogate for plutonium processing. The model examines anodic and cathodic limitations under fixed‑potential operation and evaluates implications for selectivity, efficiency, and runtime relative to experimentally demonstrated two‑electrode performance. Results indicate that independent potential control enables operation closer to thermodynamic selectivity limits, with the potential to suppress impurity oxidation …

The Low-Temperature Heat Capacity And Thermodynamic Functions Of Mg3n2, Ca3n2, And Sr3n2, Natalie Parkinson

Undergraduate Honors Theses

Alkaline earth nitrides are highly hygroscopic materials used in metal refinement and various synthetic processes. In this work, the low-temperature heat capacities of Mg₃N₂, Ca₃N₂, and Sr₃N₂ were measured for the first time. The Ca₃N₂ sample contained impurities, necessitating corrections to the heat capacity data. The absolute entropies of Mg₃N₂, Ca₃N₂, and Sr₃N₂ at 298.15 K were determined to be 75.1, 114.9, and 188.5 J∙K⁻¹∙mol⁻¹, respectively. Gibbs energies of formation were …

Mcgehee Blow Up And Collision Manifold Of Planar (2+2)-Body Problem, Nathaniel Scott Sill

Theses and Dissertations

This thesis analyzes the dynamics of the Planar (2+2)-Body Problem which consists of two asteroids moving under the gravitational force of each other and of two larger primaries. We use the McGehee blow up technique to remove the singularities in the dynamics associated with a triple collision with one of the primaries by introducing a new set of variables. Additional variables are introduced to reduce the dimension of the problem. We then derive the dynamics for these new variables. We then use the energy relation that comes from the original Hamiltonian to describe the collision manifold which is pasted in …

Differentiable Objectives For 3d Scene Relighting Via Gradient Descent On Olat Basis Coefficients, Anson Savage

Theses and Dissertations

Designing effective lighting is an iterative and often time-consuming process. This work contributes to automatic lighting design research by presenting a render-engine agnostic optimization routine: gradient descent on RGB multipliers of one-light-at-a-time (OLAT) basis images. We compare several objective functions to accomplish lighting tasks and show that our method is capable of quickly and effectively exploring different lighting styles using either text prompts or reference images. We also present several datasets specific to lighting tasks and show that fine-tuning on these datasets can improve performance.

Maximizing Uinta Basin Oil Well Yield Through Geochemical Fingerprinting Of Produced Water, Troy W. Day

Theses and Dissertations

The Uinta Basin is an unconventional oil play that has, since 2017, annually increased hydrocarbon extraction through modern drilling and fracing techniques with increased frac loading. The primary production target is the Uteland Butte Member of the Green River Formation, which consists of interbedded limestones, dolostones, and thick, organic-rich mudstones. Along with increased hydrocarbon production, volumes of produced water from the Uteland Butte Member have also risen. Water is co-produced with hydrocarbons and is an undesirable byproduct of hydrocarbon extraction. Large frac operations now consistently have highly variable percentages of recovered water volume relative to oil. This increase in water …

Robust And Interpretable Cross-Domain Arabic Readability Prediction Using Hybrid Modeling: Evidence On The Limitations Of Transformer-Based Classifiers, Sarah Alzu'bi

Theses and Dissertations

Automatic readability assessment aims to predict how difficult a text is for readers to understand. The concept of readability has been widely studied across languages due to its significant impact on reading comprehension, leading to the development of various methods and approaches. In this study, I addressed two key challenges in readability assessment. First, I examine the performance of statistical classifiers and transformer-based models, including CAMeLBERT(Inoue et al, 2021.) with a focus on their ability to generalize under domain, genre, and stylistic shifts. Second, I investigate the interpretability of transformer performance in readability task, which are often criticized for their …

Probing The Disequilibrium Chemistry Of Two Late T-Dwarfs Using Planetary Intensity Code For Atmospheric Scattering, Crystal-Lynn Jacqueline Bartier

Theses and Dissertations

We have performed a detailed analysis of the atmospheric properties of two late-T type brown dwarfs, 2MASSI J0415195-093506 and 2MASS J05591914-140448. For each brown dwarfs, we combined the spectra of each brown dwarf from the ground at 1-2.5 µm, AKARI at 2.5-5 µm, and from the Spitzer Space Telescope at 5-15 µm. For this project, we are particularly interested in probing the extent of vertical mixing. For this analysis, we used the Planetary Intensity Code for Atmospheric Scattering (PICASO), which is a code that creates a radiative transfer model for a given set of atmospheric parameters. With PICASO we find …

The Relational Good Life: Entrepreneurship Education And Grounded Sumak Kawsay In Otavalo, Ecuador, Vanessa I. Lozano Hardman

Theses and Dissertations

Indigenous Kichwa communities in Ecuador’s Otavalo region have long participated in local and transnational markets, historically as mindalaes, specialized traders of the northern Andes. Yet in recent years, international development-oriented NGOs have framed entrepreneurship education as newly necessary for economic development. These approaches emphasize individualized narratives of vision, self-reliance, and growth, often characterizing Indigenous peoples as lacking entrepreneurial skills or the appropriate mindset. Drawing on ethnographic research with youth, mothers, and teachers at Saminay–El Legado, an agro- technical, intercultural bilingual secondary school (UECIB) in the parish of San José de Quichinche, this article examines how entrepreneurship education intersects with grounded …

Lists Of Selected Full-Text Databases By Subscription In East Asian Studies, Anlin Yang, Michiko Ito, Ellie Kim, Jian P. Lee

Journal of East Asian Libraries

No abstract provided.

The Taichung Polyglot, Mårten S. Saarela

Journal of East Asian Libraries

No abstract provided.

A Masked-Perturbation Model For Destabilization Security Games In Feedback Systems, Gabriel Michael Perry

Theses and Dissertations

In this thesis, we present a mathematical formulation for increasing cyberphysical system security. This model allows a system administrator to use assumptions about exposed signals to derive defense strategies meant to mitigate the system's vulnerability to feedback perturbation attacks. We begin with a survey of game theory with the goal of building the concepts of resource and security games. We then introduce our model, which is a security game; targets in this game are exposed signals in the model map of the system, and resources are perturbed or introduced dynamical relationships between these signals. This formulation, called the masked-perturbation model, …

Theoretical Expressivity Of Self-Attention As A Model Of Binary Sequence-To-Sequence Functions And Other Explorations, Dustin Angerhofer

Theses and Dissertations

The self-attention mechanism lies at the heart of modern sequential modeling with deep neural networks, especially in the context of Large Language Models (LLMs). The basic role of self-attention is to capture pairwise interactions between tokens in a sequence. This allows token embeddings to be endowed with context-dependent information before further processing. Despite its widespread use, our theoretical understanding of self-attention is still nascent. In this work, we examine self-attention as a model of binary sequence-to-sequence (seq2seq) functions, which is the simplest non-trivial case to analyze. We find, using VC dimension and the Sauer-Shelah lemma, that in the limit of …

The Lookahead Transformer, Justin P. Olcott

Theses and Dissertations

Large Language Models (LLMs) are transformer models that generate text autoregressively in two stages: prefill and decode. The prefill stage processes all input tokens in parallel and caches them into the KV cache. The decode stage uses the KV cache, processes a single token at a time, and is generally memory-bandwidth constrained. Each decode step generates a token probability distribution, samples from it, appends the token to the cache, and repeats. This left-to-right, one-at-a-time generation paradigm has proven effective for language modeling in many domains; however, it also has limitations such as token permanence, constant compute per token generation, constant …

Detection Of The Presence And Growth Of E. Coli Bacteria In A Droplet-Based Microfluidic System Using Laser Induced Fluorescence, Oshira Peiris

Theses and Dissertations

Antimicrobial resistance is a biomedical event, wherein an infectious microbe becomes non-responsive to the dosage of a particular antibiotic due to previous overuse or overexposure. Currently, agar plate disc diffusion is used as the gold standard for detecting antimicrobial resistance. The possibility of miniaturizing and speeding up detection techniques for antimicrobial resistance is investigated in this thesis. Microfabrication techniques were used in developing two droplet microfluidic systems interfaced with laser induced fluorescence detection. Microfluidic devices were manufactured with different droplet generating geometries using poly-dimethyl siloxane, soft lithography and hydrophobic surface treatment. The microfluidic devices were tested for droplet quality using …

Model Unification: A Systematic Approach For The Cluster Expansion, Kolten Barfuss

Theses and Dissertations

A systematic approach for model unification of cluster expansion models is developed and demonstrated. The method builds on previous work with the Manifold Boundary Approximation Method (MBAM) to identify supremal models. The work is motivated by the exercise of unifying cluster expansion models – characterized by Π matrices – for two binary alloys that share one atomic species to form a model for the ternary alloy. The result is the Supremal Π Algorithm, a systematic unification algorithm that relies on an MBAM-informed understanding of models and on the singular value decomposition. The algorithm yields ΠΛ, a Π matrix for the …

Some Closure On The Relation Between Cfg And Peg, Nathan J. Bulloch

Theses and Dissertations

We work toward a practical, unified language formalism for structurally recursive languages by expressing the mathematical theories underlying context-free grammars with lookahead (CFGLA) in the Rocq theorem prover and leveraging CFGLA semantics to analyze interactions between between recursion and negative lookahead. We give examples of grammars with left-recursive negation cycles for the parsing expression grammar (PEG) variant due to Medeiros et al. and for the translation from PEG to CFGLA due to Miyazaki and Minamide. To study the interaction between left recursion and negative lookahead in a PEG context, we introduce FPEG, a left-recursive extension of PEG with Fitting semantics.