Physical Sciences and Mathematics Commons^™

Optimizing Group Utility In Itinerary Planning: A Strategic And Crowd-Aware Approach, Junhua Liu, Aldy Gunawan, Kristin L. Wood, Kwan Hui Lim

Research Collection School Of Computing and Information Systems

Itinerary recommendation is a complex sequence prediction problem with numerous practical applications. The task becomes significantly more challenging when optimizing multiple factors simultaneously, such as user queuing times, crowd levels, attraction popularity, walking durations, and operating hours. These factors, combined with the dynamic and unpredictable nature of visitor flow, introduce substantial complexities, particularly when accounting for collective user behavior. Existing solutions often adopt a single-user perspective, overlooking critical challenges arising from natural crowd dynamics. For example, the Selfish Routing problem illustrates how individual decision-making can lead to suboptimal outcomes for the group as a whole. To address these challenges, we …

Revised Draft Final Butte Treatment Lagoons (Btl) Groundwater Treatment System Routine Operations, Maintenance, And Monitoring (Om&M) Plan, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Oyster Shell Recycling Efforts In Horry County, Corabella Dieguez

Goal 14: Life Below Water

No abstract provided.

Reducing Single-Use Plastic In Georgetown County, Alex Gaspar

Goal 12: Responsible Consumption and Production

No abstract provided.

Sccosmix: A Mixed-Effects Framework For Differential Coexpression And Transcriptional Interactions Modeling In Single-Cell Rna-Seq, Anderson Bussing, Giampiero Marra, Daping Fan, Russell Shinohara, Danni Tu, Yen-Yi Ho

Faculty Publications

Advancements in single-cell RNA-sequencing (scRNA-seq) technologies generate a wealth of gene expression data that provide exciting opportunities for studying gene-gene interactions systematically at individual cell resolution. Genetic interactions within a cell are tightly regulated and often highly dynamic in response to internal cellular signals and external stimuli. Evidence of these dynamic interactions can often be observed in scRNA-seq data by examining conditional co-expression changes. Existing approaches for studying these dynamic interaction changes in scRNA-seq data do not address the multi-subject hierarchical design commonly considered in single-cell experiments. In this paper, we propose a Mixed-effects framework for differential Coexpression and transcriptional …

Geochemical And Stratigraphic Characterization Of The Morrison Formation And Cedar Mountain Formation Contact In The Island Park Quadrangle, Uintah County, Utah, Emily Mcdermott

All Graduate Theses and Dissertations, Fall 2023 to Present

The Upper Jurassic Morrison Formation and Lower Cretaceous Cedar Mountain Formation are among the richest sources of dinosaur fossils. Despite a 24-million-year gap in time (the Jurassic–Cretaceous unconformity), these formations are difficult to distinguish due to their similar rock types and colors. In Utah's Island Park quadrangle (IPQ), these formations are not separated on existing geological maps. This study focuses on identifying and understanding the formational boundary between them using field observations, stable isotope analysis, clay mineralogy, and chemical techniques such as X-ray diffraction (XRD) and X-ray fluorescence (XRF).

Unlike other areas where a conglomerate layer marks the boundary, the …

Evaluating The Effects Of 3d User Interactions And Virtual Displays On Human Cognition And Perception For Immersive Analytics, Dongyun Han

All Graduate Theses and Dissertations, Fall 2023 to Present

This research investigates how virtual reality (VR) can be utilized effectively for users to explore data. Traditional data analysis typically takes place on flat, two-dimensional computer screens. In contrast, immersive technologies like VR offer a three-dimensional environment where users can engage with data more naturally and intuitively. Such immersive experiences have the potential to improve comprehension, memory, and insight during data analysis tasks. Despite this potential, several challenges remain in making immersive analytics practical and effective. Key questions include which types of 3D interaction techniques are most helpful and how accurately people perceive visual information in immersive environments. To address …

Empirical Evaluation Of Bayes Error Rate Bounds In Binary Classification, Riley May

All Graduate Theses and Dissertations, Fall 2023 to Present

Classification tasks are fundamental in statistical machine learning. In classification tasks, a general goal is to build or select a model that can correctly classify data with as few errors as possible. However, for a particular dataset, the minimal number of errors achievable is seldom zero since overlap in the data makes errors unavoidable. As a result, it is often difficult for machine learning practitioners and data scientists to know whether classification errors can be reduced through further refinement. A potential solution to this lies in the Bayes error rate (BER). The BER is the lowest error rate achievable for …

Evaluating Uplift At The Leading Edge Of The Yellowstone Hotspot - A Study Of The Shoshone River Drainage, Emma Tombaugh

All Graduate Theses and Dissertations, Fall 2023 to Present

The stationary mantle plume (or hotspot) underlying the Yellowstone region has caused parts of the surrounding landscape to rise as the continental plate migrates over it. However, scientists do not fully agree on the spatial pattern of this uplift and few measurements of the landscape have been made to provide estimates of uplift rates. To better understand uplift patterns and rates, this study examines the Shoshone River, which flows across the predicted zone of highest uplift at the northeastern, leading edge of the hotspot. Digital-terrain analysis is used to measure channel steepness and field and imagery approaches are used to …

Aquatic Habitat Representation For Robust Water Resources Management And Fish Conservation Decision-Making, Gregory C. Goodrum

All Graduate Theses and Dissertations, Fall 2023 to Present

We rely on rivers to provide water supply, flood control, and hydroelectricity for people and to sustain aquatic ecosystems. The development of dams and reservoirs to provide water for people did not consider environmental impacts to rivers, leading to widespread decline of freshwater species and habitat. Improving environmental outcomes of water management is needed to protect and restore aquatic ecosystems. However, rivers are complex and variable, making them difficult to represent as objectives for water management. This dissertation explores approaches to improve aquatic habitat representation and environmental objectives for water resources management and river conservation and restoration.

Chapter 2 uses …

Using Geomorphic Change And Sediment Modeling To Calculate Debris Flow Volumes From The 2020 El Dorado Wildfire In The Southern San Bernardino Mountains, California, Sevag Injean

Electronic Theses, Projects, and Dissertations

Four years after the occurrence of the 2020 El Dorado Fire, Yucaipa Ridge and the surrounding communities of Oak Glen and Forest Falls still experience the devastation caused by debris flows. Wildfires can instigate a series of events leading to hydrophobic soils, loss of vegetation, and increased sediment availability which amplify post-fire debris flow risks. This study tested the hypothesis that post-wildfire geomorphic changes can be accurately quantified and predicted using high-resolution LiDAR-derived digital elevation models. To investigate this hypothesis, multi-temporal LiDAR datasets were analyzed to quantify geomorphic changes, including erosion and deposition, within two severely burned basins in the …

Predicting Music Origin With Deep Learning, Fruzsina Ladanyi

Electronic Theses, Projects, and Dissertations

This project explores the usage of a late fusion deep learning architecture to predict the geographic origin of music. Mel-Frequency Cepstral Coefficients (MFCCs) and the language of the music sample are used as features. MFCCs were extracted from audio files to capture sound features. The language was identified using OpenAI’s Whisper model to provide additional context. A late fusion neural network architecture combining Long Short-Term Memory (LSTM) layers for sequential MFCC input and dense layers for non-sequential language features were employed to support both classification and regression tasks. The classification model achieved an accuracy of 33.03% across 56 countries or …

Fact-Checker: A Web Application For Leveraging Large Language Models For Fact-Checking Youtube Videos, Andrew R. Craig

Electronic Theses, Projects, and Dissertations

Fact-Checker is a web application that allows users to fact-check YouTube videos. It feeds YouTube’s closed captioning transcript to a large language model (LLM) to extract claims. It then uses multiple LLMs, such as Gemini, Llama, and Claude, to verify these claims. The modular design makes it easy to change to a different LLM or model if needed. The application is built using Python for access to Application Programming Interfaces (APIs) and Streamlit as the front-end framework. The utilization of Docker and Dockerfiles enables easy distribution and deployment. It enables the application to be deployed on almost any hardware platform …

A Focus On Student Education: Determining Student Attitudes Towards Transparent Autograding And Developing Artificially Intelligent Tools To Help Students Succeed, Andra Rice

All Graduate Theses and Dissertations, Fall 2023 to Present

This thesis is composed of two parts both relating to helping students succeed. First, the focus is on determining how we can help students feel more comfortable using an AI tool that can provide them immediate feedback. Second, machine learning algorithms are explored in relation to tracking student tasks to encourage healthy study habits.

The development of effective autograders is key for scaling assessment and feedback. While AI based autograding systems for open-ended response questions have been found to be beneficial for providing immediate feedback, autograders are not always liked, understood, or trusted by students. Our research tested the effect …

Impacts Of 4r Nitrogen Management And Water Optimization On Soil Health, Kamaldeep Kamaldeep

All Graduate Theses and Dissertations, Fall 2023 to Present

Farmers in Utah and Idaho are facing growing challenges due to high fertilizer costs, limited irrigation water, and pressure to improve long-term soil health. To better understand current practices and grower attitudes, a survey was conducted in 2020 targeting 5,000 producers of small grains, corn, and potatoes. Although the response rate was low, 146 growers representing over 25,000 hectares of cropland participated. Survey results showed that most growers are open to improving nitrogen and irrigation practices and care about their soil health, even if not all are fully using 4R or precision agriculture methods.

This thesis includes two field studies …

Setting Salinity Water-Quality Standards Protective Of Aquatic Life: Insights From Analyses Of The Effects Of Salinity On Stream Insects, Katlyn M. Gardner

All Graduate Theses and Dissertations, Fall 2023 to Present

Freshwater ecosystems are becoming saltier due to human activities like agriculture, urbanization, and resource extraction. This change in salinity is important because we know very little of how stream salinity affects aquatic insects at natural concentrations, much less at elevated concentrations. Increases in salinity may harm aquatic macroinvertebrates, which play important roles in stream food webs and are widely used as indicators of ecosystem health. Understanding how salinity affects aquatic insect growth, survival, and distribution is critical for developing effective criteria protective of aquatic life, but existing methods often rely on field surveys where multiple environmental factors covary, making it …

Out Of Core And Adaptive Image Blending Approach For Large Scale Image Mosaics, Marcus Quincy

All Graduate Theses and Dissertations, Fall 2023 to Present

When creating large stitched images, like those used in maps made from aerial photos, it’s important to make sure the seams between individual pictures aren’t visible. This process, known as color blending, helps smooth out differences in lighting or weather across the images. But blending very large images, such as those made from many high-resolution aerial photos, can require huge amounts of memory, making it hard to do on a typical computer.

In this work, we developed a method that breaks the problem into smaller pieces, so only a small part of the image needs to be worked on at …

Understanding Hydroclimate In The Contiguous United States: Roles Of Temperature Vs Precipitation And Subtropical Pacific Warming, Grace Esenam Affram

All Graduate Theses and Dissertations, Fall 2023 to Present

This study investigates the physical drivers and mechanisms of hydroclimate variability across the Contiguous United States (U.S.), using a combination of observable data, reanalysis data, land modeling, and coupled climate model experiments. One of the major findings is that the historic 2021 drought event across the Western U.S. was primarily driven by a severe lack of precipitation rather than increased temperatures. The study further finds that anthropogenic forcing has substantially increased the risk of this extreme drought by approximately 26 times relative to a world without the influence.

Additionally, the study reveals that the Pacific Meridional Mode (PMM) characterized by …

Twisted Equivariant Matrix Factorizations, Jan-Luca Spellmann

All Graduate Theses and Dissertations, Fall 2023 to Present

We introduce and study categories of twisted equivariant matrix factorizations MF^α_G(R, w), which are categories of matrix factorizations of a potential w over the local ring R = C[x₁, . . . , x_n] together with an action by a finite group G that is twisted via a 2-cocycle α. These categories provide rich examples of Z/2Z-differentially graded categories in the context of non-commutative geometry and come up naturally in the study of boundary conditions of 3d Rozansky–Witten theories. We prove that under certain assumptions on (R, w …

A Value Sensitive Design Approach To Reimagining Parental Control Apps, Prakriti Dumaru

All Graduate Theses and Dissertations, Fall 2023 to Present

Parental control apps are often used by families to regulate children's device usage and keep them safe online. However, existing tools focus on monitoring and restricting children, which can lead to tension and mistrust within families. This research takes a new approach by exploring how parental control apps can be redesigned to support positive family values, like encouraging open communication between parents and children and helping children self-regulate their behaviors. Through four in-depth studies, this dissertation looks at how these values play out in different real-life situations. It includes families with children on the autism spectrum, divorced households where parents …

Explainable Machine Learning Surrogate Modeling For Exit Gradient Prediction In Hydraulic Structures Using Numerical Simulations, Prayas Rath, Jianting Zhu, Kevin M. Befus

Geosciences Faculty Publications and Presentations

Accurate prediction of exit gradients is essential for designing impounding hydraulic structures, such as dams and levees, to mitigate seepage-induced piping failures. Conventional analytical methods often neglect boundary effects and anisotropy, limiting their applicability in complex geological settings. This study develops an XGBoost-based machine learning surrogate model trained and tested on 8,000 MODFLOW numerical simulations to predict exit gradients under varying hydraulic and geological conditions. The data set covers numerous parameters, including anisotropy, head differences, structure width, cut-off wall depth, aquifer thickness, and uninterrupted riverbed length. The coefficient of determination for test data is 0.88, demonstrating reliable exit gradient prediction …

Automated Chick Sexing Using Computer Vision, Marta Veganzones Rodriguez

Graduate Theses and Dissertations

This thesis presents two complementary approaches to chick sexing, a critical task in poultry production that demands accurate and early gender identification. By investigating both facial and vent-based modalities, we present two complementary methods that aim to improve the efficiency, scalability, and ethical standards of gender classification in day-old chicks through the use of computer vision and deep learning. The first approach draws inspiration from human facial gender recognition to introduce facial chick sexing, a minimally invasive technique that eliminates the need for expert knowledge. This system encompasses a complete pipeline that includes image acquisition, facial detection and alignment, keypoint …

Certified Computation Of Julia Sets Via Numerical Methods, Hannah Kaufman

All Theses

The chaotic and fractal nature of Julia sets makes them difficult to graph. This research aims to provide graphical approximations of Julia sets with known and guaranteed levels of accuracy. We implement three methods to approximate Julia sets with c values chosen from the main cardioid of the Mandelbrot set. Each method utilizes different properties of these Julia sets. The exclusion method makes use of the fact that a Julia set of this type is topologically a circle. Attracting and repelling fixed points are used to find a region on the interior of the Julia set and a region on …

Mixture Effects On Metal Accumulation In The Asian Clam, Corbicula Fluminea, Mark A. Huff

Electronic Theses and Dissertations

Field collected Corbicula fluminea were exposed to trace level copper, lead, and zinc with the aim of examining the preferential accumulation between the soft tissue and shell. Metal levels were based on those in a permitted industrial effluent. At 1X effluent and 2X effluent exposure levels, copper was found to preferentially accumulate in the clam soft tissue, lead was found to preferentially accumulate in the clam shell, and zinc was found to excrete back into the diluent after preferentially accumulating in the clam soft tissue. When exposed as a mixture at 1X effluent levels, copper and lead were found to …

Machine Learning Based Medical Ultrasound Image Classification And Grad-Cam Interpretation, Victoria C. Hemphill

All Theses

This work takes a step in creating a diagnostic tool for the classification decision process of Achilles tendinopathy using ultrasound images. An attention-based multiple instance learning model is developed to classify the images. Typically, doctors capture multiple ultrasound images of the Achilles tendon during a study to determine a complete diagnosis. Multiple instance models adopt this behavior by providing a single label for a set of instances (images). The images are grouped into ”bags” at the study level and passed into the model. The MIL model then uses its attention property to assign an importance score to each image to …

Small Stream Restoration In The Piedmont Of South Carolina: Comparison Of Evaluation Tools And Water Quality’S Effects On Salamanders, Camryn Lachica

All Theses

For many years, the United States Army Corps of Engineers (USACE) used the Guidelines for Preparing a Compensatory Mitigation Plan worksheets to guide pre-restoration evaluation and determine post-restoration mitigation credits in South Carolina. Recently, the USACE in South Carolina transitioned to the Stream Quantification Tool (SQT), which provides a more comprehensive assessment framework. Our first objective was to compare these assessment methodologies across different landscape types to determine what the SQT adds to mitigation calculations that were not considered in prior worksheets. We evaluated 16 streams in the Piedmont of South Carolina, with four replicates each of forested, suburban, urban, …

On The Garoufalidis-Kashaev State-Integral Invariant, Amelia Palmer Dusenbury

Boise State University Theses and Dissertations

This thesis explores a construction of the family of topological invariants for certain oriented 3-manifolds based on the state-integral approach developed by Andersen, Garoufalidis, and Kashaev in the Archimedean setting. Starting from an ideal triangulation of a 3-manifold equipped with angle data, variables are assigned to the faces and tetrahedra, taking values in a so-called 'Gaussian group'. The invariant is defined by integrating a distribution defined from the combinatorics of the triangulation and a special function over a product of the Gaussian group. The special function is a quantum dilogarithm, whose valuable feature, the pentagon relation, ensures the resulting integral …

Final Quarterly Operations And Maintenance Report Butte Treatment Lagoon System – Third Quarter 2022, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Revised Draft Final Quarterly Operations And Maintenance Report Butte Treatment Lagoon System – Second Quarter 2024, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Estimation Methods For Bayesian Exponential Random Graph Models Under The Horseshoe Prior., Pamela Linares

Electronic Theses and Dissertations

Networks are powerful tools for modeling the complexity of social interactions, biological systems, and information spread. A leading statistical frameworks for analyzing network data are Exponential Random Graph Models (ERGMs), which provide a principled approach to capturing structural dependencies. However, ERGMs remain challenging to estimate, especially in sparse or high-dimensional settings where models suffer from degeneracy and unstable parameter inference. This paper proposes a penalized Bayesian approach to ERGMs that utilizes the horseshoe prior, a sparsity-inducing global-local shrinkage prior. This prior offers robust regularization while preserving important signals, improving estimation by shrinking irrelevant parameters and reducing the impact of extreme …