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Proof-Of-Concept For Converging Beam Small Animal Irradiator, Benjamin Insley 2024 The Texas Medical Center Library

Proof-Of-Concept For Converging Beam Small Animal Irradiator, Benjamin Insley

Dissertations & Theses (Open Access)

The Monte Carlo particle simulator TOPAS, the multiphysics solver COMSOL., and

several analytical radiation transport methods were employed to perform an in-depth proof-ofconcept

for a high dose rate, high precision converging beam small animal irradiation platform.

In the first aim of this work, a novel carbon nanotube-based compact X-ray tube optimized for

high output and high directionality was designed and characterized. In the second aim, an

optimization algorithm was developed to customize a collimator geometry for this unique Xray

source to simultaneously maximize the irradiator’s intensity and precision. Then, a full

converging beam irradiator apparatus was fit with a multitude …


Generative Ai In Education From The Perspective Of Students, Educators, And Administrators, Aashish Ghimire 2024 Utah State University

Generative Ai In Education From The Perspective Of Students, Educators, And Administrators, Aashish Ghimire

All Graduate Theses and Dissertations, Fall 2023 to Present

This research explores how advanced artificial intelligence (AI), like the technology that powers tools such as ChatGPT, is changing the way we teach and learn in schools and universities. Imagine AI helping to summarize thick legal documents into something you can read over a coffee break or helping students learn how to code by offering personalized guidance. We looked into how teachers feel about using these AI tools in their classrooms, what kind of rules schools have about them, and how they can make learning programming easier for students. We found that most teachers are excited about the possibilities but …


Divergence-Free Tensor Densities In Two Dimensions, Tyler Hansen 2024 Utah State University

Divergence-Free Tensor Densities In Two Dimensions, Tyler Hansen

All Graduate Theses and Dissertations, Fall 2023 to Present

In physics, a common method for exploring the way a physical system changes over time is to look at the system’s energy. Roughly speaking, the energy in these systems are either motion-based (kinetic energy, a bullet in flight) or position-based (potential energy, a rock sitting at the top of a hill). The difference between the system’s total kinetic and potential energies is quantified by an expression called the Lagrangian. Using a special procedure, this Lagrangian is massaged to produce a group of equations called the Euler-Lagrange equations; if the initial configuration of the system is provided, the solution to these …


Life On The Edge: The Cambrian Marine Realm And Oxygenation, Sara Pruss, Benjamin C. Gill 2024 Smith College

Life On The Edge: The Cambrian Marine Realm And Oxygenation, Sara Pruss, Benjamin C. Gill

Geosciences: Faculty Publications

The beginning of the Phanerozoic saw two biological events that set the stage for all life that was to come: (a) the Cambrian Explosion (the appearance of most marine invertebrate phyla) and (b) the Great Ordovician Biodiversification Event (GOBE), the subsequent substantial accumulation of marine biodiversity. Here, we examine the current state of understanding of marine environments and ecosystems from the late Ediacaran through the Early Ordovician, which spans this biologically important interval. Through a compilation and review of the existing geochemical, mineralogical, sedimentological, and fossil records, we argue that this interval was one of sustained low and variable marine …


Multi-Script Handwriting Identification By Fragmenting Strokes, Joshua Jude Thomas 2024 University of South Alabama

Multi-Script Handwriting Identification By Fragmenting Strokes, Joshua Jude Thomas

<strong> Theses and Dissertations </strong>

This study tests the effectiveness of Multi-Script Handwriting Identification after simplifying character strokes, by segmenting them into sub-parts. Character simplification is performed through splitting the character by branching-points and end-points, a process called stroke fragmentation in this study. The resulting sub-parts of the character are called stroke fragments and are evaluated individually to identify the writer. This process shares similarities with the concept of stroke decomposition in Optical Character Recognition which attempts to recognize characters through the writing strokes that make them up. The main idea of this study is that the characters of different writing‑scripts (English, Chinese, etc.) may …


A Review Of Student Attitudes Towards Keystroke Logging And Plagiarism Detection In Introductory Computer Science Courses, Caleb Syndergaard 2024 Utah State University

A Review Of Student Attitudes Towards Keystroke Logging And Plagiarism Detection In Introductory Computer Science Courses, Caleb Syndergaard

All Graduate Theses and Dissertations, Fall 2023 to Present

The following paper addresses student attitudes towards keystroke logging and plagiarism prevention measures. Specifically, the paper concerns itself with changes made to the “ShowYourWork” plugin, which was implemented to log the keystrokes of students in Utah State University’s introductory Computer Science course, CS1400. Recent work performed by the Edwards Lab provided insights into students’ feelings towards keystroke logging as a measure of deterring plagiarism. As a result of that research, we have concluded that measures need to be taken to enable students to have more control over their data and assist students to feel more comfortable with keystroke logging. This …


Learning Adversarial Semantic Embeddings For Zero-Shot Recognition In Open Worlds, Tianqi LI, Guansong PANG, Xiao BAI, Jin ZHENG, Lei ZHOU, Xin NING 2024 Singapore Management University

Learning Adversarial Semantic Embeddings For Zero-Shot Recognition In Open Worlds, Tianqi Li, Guansong Pang, Xiao Bai, Jin Zheng, Lei Zhou, Xin Ning

Research Collection School Of Computing and Information Systems

Zero-Shot Learning (ZSL) focuses on classifying samples of unseen classes with only their side semantic information presented during training. It cannot handle real-life, open-world scenarios where there are test samples of unknown classes for which neither samples (e.g., images) nor their side semantic information is known during training. Open-Set Recognition (OSR) is dedicated to addressing the unknown class issue, but existing OSR methods are not designed to model the semantic information of the unseen classes. To tackle this combined ZSL and OSR problem, we consider the case of “Zero-Shot Open-Set Recognition” (ZS-OSR), where a model is trained under the ZSL …


Diffusion-Based Negative Sampling On Graphs For Link Prediction, Yuan FANG, Yuan FANG 2024 Singapore Management University

Diffusion-Based Negative Sampling On Graphs For Link Prediction, Yuan Fang, Yuan Fang

Research Collection School Of Computing and Information Systems

Link prediction is a fundamental task for graph analysis with important applications on the Web, such as social network analysis and recommendation systems, etc. Modern graph link prediction methods often employ a contrastive approach to learn robust node representations, where negative sampling is pivotal. Typical negative sampling methods aim to retrieve hard examples based on either predefined heuristics or automatic adversarial approaches, which might be inflexible or difficult to control. Furthermore, in the context of link prediction, most previous methods sample negative nodes from existing substructures of the graph, missing out on potentially more optimal samples in the latent space. …


On The Feasibility Of Simple Transformer For Dynamic Graph Modeling, Yuxia WU, Yuan FANG, Lizi LIAO 2024 Singapore Management University

On The Feasibility Of Simple Transformer For Dynamic Graph Modeling, Yuxia Wu, Yuan Fang, Lizi Liao

Research Collection School Of Computing and Information Systems

Dynamic graph modeling is crucial for understanding complex structures in web graphs, spanning applications in social networks, recommender systems, and more. Most existing methods primarily emphasize structural dependencies and their temporal changes. However, these approaches often overlook detailed temporal aspects or struggle with long-term dependencies. Furthermore, many solutions overly complicate the process by emphasizing intricate module designs to capture dynamic evolutions. In this work, we harness the strength of the Transformer’s self-attention mechanism, known for adeptly handling long-range dependencies in sequence modeling. Our approach offers a simple Transformer model, called SimpleDyG, tailored for dynamic graph modeling without complex modifications. We …


Multigprompt For Multi-Task Pre-Training And Prompting On Graphs, Xingtong YU, Chang ZHOU, Yuan FANG, Xinming ZHAN 2024 Singapore Management University

Multigprompt For Multi-Task Pre-Training And Prompting On Graphs, Xingtong Yu, Chang Zhou, Yuan Fang, Xinming Zhan

Research Collection School Of Computing and Information Systems

Graph Neural Networks (GNNs) have emerged as a mainstream technique for graph representation learning. However, their efficacy within an end-to-end supervised framework is significantly tied to the availability of task-specific labels. To mitigate labeling costs and enhance robustness in few-shot settings, pre-training on self-supervised tasks has emerged as a promising method, while prompting has been proposed to further narrow the objective gap between pretext and downstream tasks. Although there has been some initial exploration of prompt-based learning on graphs, they primarily leverage a single pretext task, resulting in a limited subset of general knowledge that could be learned from the …


An Evaluation Of Heart Rate Monitoring With In-Ear Microphones Under Motion, Kayla-Jade BUTKOW, Ting DANG, Andrea FERLINI, Dong MA, Yang LIU, Cecilia MASCOLO 2024 Singapore Management University

An Evaluation Of Heart Rate Monitoring With In-Ear Microphones Under Motion, Kayla-Jade Butkow, Ting Dang, Andrea Ferlini, Dong Ma, Yang Liu, Cecilia Mascolo

Research Collection School Of Computing and Information Systems

With the soaring adoption of in-ear wearables, the research community has started investigating suitable in-ear heart rate detection systems. Heart rate is a key physiological marker of cardiovascular health and physical fitness. Continuous and reliable heart rate monitoring with wearable devices has therefore gained increasing attention in recent years. Existing heart rate detection systems in wearables mainly rely on photoplethysmography (PPG) sensors, however, these are notorious for poor performance in the presence of human motion. In this work, leveraging the occlusion effect that enhances low-frequency bone-conducted sounds in the ear canal, we investigate for the first time in-ear audio-based motion-resilient …


Spatial Ecology Of Mule Deer Migrations From Grand Teton National Park And The Teton Range, Justin K. Schwabedissen 2024 Utah State University

Spatial Ecology Of Mule Deer Migrations From Grand Teton National Park And The Teton Range, Justin K. Schwabedissen

All Graduate Theses and Dissertations, Fall 2023 to Present

The Greater Yellowstone Ecosystem hosts several of the longest, fully intact ungulate migrations remaining in the continental United States. However, expanding development and an increasing human footprint continue to truncate migratory routes. While the endpoints are often a seasonal range on protected lands, these migration corridors frequently cross other jurisdictional boundaries, including large tracts of private or multiple-use lands, with varying levels of protection. Thus, it is critical resource managers understand the dynamics of migratory movements to define population-level corridors and prioritize appropriate conservation strategies. Mule deer in Wyoming have been documented traveling long distances between summer and winter ranges; …


Analysis And Numerical Simulation Of Tumor Growth Models, Daniel Acosta Soba 2024 University of Tennessee at Chattanooga

Analysis And Numerical Simulation Of Tumor Growth Models, Daniel Acosta Soba

Masters Theses and Doctoral Dissertations

In this dissertation we focus on the numerical analysis of tumor growth models. Due to the difficulty of developing physically meaningful approximations of such models, we divide the main problem into more simple pieces of work that are addressed in the different chapters. First, in Chapter 2 we present a new upwind discontinuous Galerkin (DG) scheme for the convective Cahn–Hilliard model with degenerate mobility which preserves the pointwise bounds and prevents non-physical spurious oscillations. These ideas are based on a well-suited piecewise constant approximation of convection equations. The proposed numerical scheme is contrasted with other approaches in several numerical experiments. …


Development Of An Enhanced Sampling Workflow To Accelerate Molecular Docking With Sparse Biophysical Information, Zachary Stichter 2024 Western Kentucky University

Development Of An Enhanced Sampling Workflow To Accelerate Molecular Docking With Sparse Biophysical Information, Zachary Stichter

Masters Theses & Specialist Projects

Rapid docking of flexible biological macromolecules remains a significant open challenge in protein structure determination. While rigid docking is relatively simple with toolkits such as TagDock, a key obstacle to rapid flexible docking is the complexity and roughness of the free energy surface associated with protein conformational motion (often termed the many-minima problem), meaning conventional molecular dynamics methods do not effectively sample protein conformations near the interaction complex in accessible timescales. Methods such as metadynamics and replica exchange molecular dynamics exist to ameliorate this obstacle, yet these methods use nonphysical biases or random swaps to enhance sampling. In contrast, high …


Atmospheric Deposition Trends Are Primarily Decreasing In Arkansas And Tennessee, Anna McCarty 2024 University of Arkansas, Fayetteville

Atmospheric Deposition Trends Are Primarily Decreasing In Arkansas And Tennessee, Anna Mccarty

Crop, Soil and Environmental Sciences Undergraduate Honors Theses

Atmospheric deposition has likely changed with the influence of increasing global temperatures and subsequent changes in precipitation across the United States and globally. The objective of this project was to analyze atmospheric deposition across northern Arkansas and Tennessee. The three specific objectives were to: i) evaluate trends in atmospheric deposition of various element/compounds, ii) assess the relationship between atmospheric deposition and rainfall, and iii) evaluate if rainfall-adjusted atmospheric deposition is changing over time. Six sites were analyzed from 1980 to 2022, including AR16, AR27, TN00, TN04, TN11, and TN14, which span over northern Arkansas and across Tennessee. The Mann-Kendall Test …


Predictability Of The Overland Reintensification Of North Atlantic Tropical Cyclone Erin (2007), Ariel Tickner-Ernst 2024 University of Wisconsin-Milwaukee

Predictability Of The Overland Reintensification Of North Atlantic Tropical Cyclone Erin (2007), Ariel Tickner-Ernst

Theses and Dissertations

Tropical cyclones (TC) typically decrease in intensity upon interacting with land because of increased surface roughness and decreased surface evaporation. However, several studies have documented cases in which TCs maintain their intensity or even intensify over land within non- or weakly baroclinic environments. Yet, our understanding of the precise physical processes that support maintenance or intensification over land in non- or weakly baroclinic environments remains limited, and the predictive skill for these outcomes has yet to be quantified.

We begin this process by quantifying the predictive skill and forecast uncertainty of the overland intensification of North Atlantic Tropical Storm Erin …


Supporting Text And Data Analysis Across Campus From The Academic Library, Amy Kirchhoff, Hejin Shin PhD 2024 Ithaka

Supporting Text And Data Analysis Across Campus From The Academic Library, Amy Kirchhoff, Hejin Shin Phd

Digital Initiatives Symposium

The ability to comprehend and communicate with text-based data is essential to future success in academics and employment, as evidenced in a recent survey from Bloomberg Research Services which shows that nearly 97% of survey respondents now use data analytics in their companies and 58% consider data and text mining a business analytics tool (https://www.sas.com/content/dam/SAS/bp_de/doc/studie/ba-st-the-current-state-of-business-analytics-2317022.pdf). This has fueled a substantial growth in text analysis research (involving the use of technology to analyze un- and semi-structured text data for valuable insights, trends, and patterns) across disciplines and a corresponding demand on academic libraries to support text analysis pedagogy and text analysis …


Gpr-103 Personalized Pedagogy Through A Llm-Based Recommender System, Mourya Teja Kunuku, Bharath Y Yadla 2024 Kennesaw State University

Gpr-103 Personalized Pedagogy Through A Llm-Based Recommender System, Mourya Teja Kunuku, Bharath Y Yadla

C-Day Computing Showcase

The educational domain is undergoing transformation due to the incorporation of Artificial Intelligence (AI), Large Language Models (LLMs), and generative AI technologies, raising the need for educators to integrate cutting-edge technological advancements and methodologies into their teaching approaches. Pedagogical Design Patterns (PDPs) have become prominent for their role in sharing effective educational practices and narrowing the divide between academic research and actual teaching methods. Despite their potential, the lack of widely accessible resources and the scattered nature of publishing outlets pose significant barriers to the broad application of PDPS. To address this issue, we propose the application of large language …


Gc-104 Edai – Ai Enabled Teaching Robot For Informal Learning, Jennifer Bower, Shane Williams, Justice Fuller 2024 Kennesaw State University

Gc-104 Edai – Ai Enabled Teaching Robot For Informal Learning, Jennifer Bower, Shane Williams, Justice Fuller

C-Day Computing Showcase

We began our project by researching various popular, open-source AI tools that are available today. After we chose to focus on ChatGPT as our AI tool, we decided on cybersecurity as our subject matter. Next, we researched traditional cybersecurity training methods used by companies to train their employees on cybersecurity issues. Our project focused on determining whether or not open-source AI tools such as ChatGPT could replace traditional cybersecurity training tools and methods for companies.


Gc-67 Automatic Daily Financing Headlines Collection, Storage, Analysis And Presentation, Sahithi Atimamula, Jasminn O Evans, Julian Reyes, Victoria Castro, Krista G Settle 2024 Kennesaw State University

Gc-67 Automatic Daily Financing Headlines Collection, Storage, Analysis And Presentation, Sahithi Atimamula, Jasminn O Evans, Julian Reyes, Victoria Castro, Krista G Settle

C-Day Computing Showcase

The "Automatic Daily Financing Headlines Collection, Storage, Analysis, and Presentation" project aims to streamline the process of gathering financial headlines from financial news sources, storing them systematically, performing analysis, and presenting the insights in a user-friendly format. This automation project is designed to provide timely and relevant financial information to users interested in staying informed about market trends, economic news, and financial events. By automating the entire workflow, users can stay informed, make data-driven decisions, and navigate the dynamic landscape of financial news with ease. The project embodies the fusion of automation, data analytics, and user-centric design to create a …


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