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Faculty Senate Minutes October 6, 2025
No full textCall to Order Approval of Minutes - September 8, 2025 University Business Faculty Senate Business Information EPC Report - September 4, 2025 Report EPC Annual Report Old Business New Business Adjourn - 4:30 p
Visible Image-Based Machine Learning for Identifying Abiotic Stress in Sugar Beet Crops
No full textPrevious researches have proved that the synchronized use of inexpensive RGB images, image processing, and machine learning (ML) can accurately identify crop stress. Four Machine Learning Image Modules (MLIMs) were developed to enable the rapid and cost-effective identification of sugar beet stresses caused by water and/or nitrogen deficiencies. RGB images representing stressed and non-stressed crops were used in the analysis. To improve robustness, data augmentation was applied, generating six variations on each image and expanding the dataset from 150 to 900 images for training and testing. Each MLIM was trained and tested using 54 combinations derived from nine canopy and RGB-based input features and six ML algorithms. The most accurate MLIM used RGB bands as inputs to a Multilayer Perceptron, achieving 96.67% accuracy for overall stress detection, and 95.93% and 94.44% for water and nitrogen stress identification, respectively. A Random Forest model, using only the green band, achieved 92.22% accuracy for stress detection while requiring only one-fourth the computation time. For specific stresses, a Random Forest (RF) model using a Scale-Invariant Feature Transform descriptor (SIFT) achieved 93.33% for water stress, while RF with RGB bands and canopy cover reached 85.56% for nitrogen stress. To address the trade-off between accuracy and computational cost, a bargaining theory-based framework was applied. This approach identified optimal MLIMs that balance performance and execution efficiency
Creating Sustainable School and Home Gardens: Water-Wise Gardening
No full textWater-wise gardening, also known as xeriscaping, involves using water efficiently and effectively to create a functional and aesthetically pleasing landscape for residential and commercial properties. This fact sheet defines water-wise gardening, its benefits, and provides ideas for planning and improving a landscape to conserve a precious resource: water
A First Look Into Parental Strategies, and Challenges Around Children’s Device Usage in Urban Nepal
No full textThere have been substantial changes in the landscape of technology use by children in Global South during COVID-19, when the shift to online learning platforms necessitated parents to avail personal devices (e.g., smartphones, computers) for their children to fulfill their educational needs. However, the use of devices by children are not limited to serving educational purpose only. Our study positions itself in a critical post-pandemic period in Nepal, characterized by the increase in device use by children, while a little study to date, investigated parental mediation in this developing country. To this end, we conducted semi-structured interviews with 20 parents, who reported having at least one child aged below 14. Our findings unveil the situated parental strategies and challenges in regulating children’s device usage in Nepal, more broadly, in Global South. Based on our findings, we provide recommendations on the design of inclusive parental control tools
Product Testing: Research Shows Benefits of Biostimulants May Vary by Variety
No full textThe use of plant biostimulants is showing some promise as a potential means of helping onion crops thrive despite certain environmental challenges, according to new research at Utah State University
Machine Learning Applications: Cell Tracking and Nonparametric Estimation of Non-Smooth Divergences
No full textThis thesis brings together two important research directions: how to compare different sets of data more accurately, and how to better understand how brain cancer cells move and change shape.
In the first part, we look at a problem in statistics: measuring how different two data sources are from each other. Traditional methods often make strong assumptions, which may not always hold in real situations. Our approach avoids those assumptions by using an ensemble method, a way of combining many weak estimators into one stronger result. This makes the method more flexible and reliable, especially when dealing with complex or unknown types of data.
The second part focuses on glioblastoma, a fast-growing and deadly brain tumor. We used computer-based tools to track cancer cells in microscope videos and studied how their shapes change over time. By applying advanced methods to analyze these shapes, we discovered patterns in how different cells behave. Some moved slowly and were more rounded, while others were faster and more stretched out. We also trained a machine learning model to predict how fast a cell moves just by looking at its shape, helping us link cell structure to movement.
Together, these studies improve our ability to analyze both complex data and cancer cell behavior. The results could lead to better tools for scientific discovery and may help future research in cancer treatment and diagnosis
Target Consumers for Bottled Tart Cherry Juice
No full textA study was conducted by Utah State University (USU) in the fall of 2024 to determine western U.S. consumer preferences and willingness to pay for regionally sourced processed food products. Researchers examined consumer preferences, purchasing habits, and pricing for three processed food products, one of which was bottled tart cherry juice (32-ounce bottle). This fact sheet describes the target market (consumer group) for bottled tart cherry juice. Target consumers were identified as those who consume tart cherry juice at least several times weekly
U.S. West Consumer Processed Food Preferences and Consumption Habits
No full textThis fact sheet provides an overview of study results, including respondent demographics, common lifestyle and food behaviors, product characteristics, labeling preferences, and processed food purchasing and consumption habits. Producers, food manufacturers, and processors can use the information included in this fact sheet to inform their decision-making related to product development, pricing, placement, and promotion. Additional fact sheets in this series examine consumer preferences and willingness to pay for specialty labeled foods, as well as the impact of providing labeling information. Three fact sheets discuss target markets or consumer groups for each of the processed products examined
Crime Statistics and Taxi Transportation in New York City: An Exploratory Data Analysis
No full textIn a heavily populated city as busy and vibrant as New York City, people are constantly on the move. Some of that movement might be connected to the occurrence of certain crimes. This study explores how movement, especially from yellow taxicabs, relates to crime occurrences within different parts of the city. By looking at the 2018 taxi trip and crime data, alongside population data from the 2020 U.S. Census, this project aims to explore how individuals travel within the city and whether there is any relationship with the types of crime that occur within those areas. Visual tools and maps were created using R, a free software for data analysis, which helps display these connections. The goal is to offer insights that could help support public safety and gain a general sense of movement within New York City
Team History: The Latter-day Saint Historical Enterprise, 1986-2025
No full textThe annual Leonard J. Arrington Mormon History Lecture, featuring distinguished historian Richard E. Turley Jr. will be held on September 18, 2025 at the Russell/Wanlass Performance Hall. His lecture, titled Team History: The Latter-day Saint Historical Enterprise, 1986–2025, will explore how collaboration transformed modern Latter-day Saint history research