Digital Commons Network^™

Impact Of Snow Accumulation On Structural Integrity: Present And Future Perspectives, Kenneth K. Pomeyie

All Graduate Theses and Dissertations, Fall 2023 to Present

In the United States, accommodating the weight of accumulated snow on buildings is a crucial consideration in building design. Engineers are tasked with determining the design snow load, which is defined as the weight of accumulated snow that a structure should withstand to limit the risk of building collapse to an acceptably low level. Typically, this process involves analyzing historical data of the annual maximum snow accumulations for each snow season. However, accurately assessing these design snow loads entails navigating through a series of statistical challenges. This dissertation, composed of three papers, is dedicated to addressing these statistical hurdles in …

Testing For Patterns Of Deformation From The Yellowstone Hotspot Along The Gallatin River, Sw Montana, Jack Willard

All Graduate Theses and Dissertations, Fall 2023 to Present

Yellowstone has fascinated humans for thousands of years. Geologists have addressed many of the region’s mysteries, including the underlying mantle hotspot, the chain of calderas tracking the motion of the North American Plate over this hotspot, and the risks posed by the super volcano. However, the way that the hotspot impacts regional tectonics and topography remains under-studied. Influential previous work recognized the Yellowstone Crescent of High Terrain (YCHT), an arc of high topography around the Yellowstone Plateau with limbs extending to the west and south into central Idaho and northern Utah. The YCHT is also hypothesized to be the pattern …

Script Fading And Training: Evaluating The Necessity Of Visual Cues To Teach Contextually Appropriate Play Commenting, Devanio J. Cousins

All Graduate Theses and Dissertations, Fall 2023 to Present

Autism Spectrum Disorder (ASD) is marked by many areas of need, including play and communication. These areas of concern can have a negative impact on a child's development. Applied behavior analysis, specifically script training and fading procedures, has shown promise in teaching communication during play to young autistic children. However, traditional script training and fading methods have some limitations, including the skills the children already possess to learn the scripts and the resources needed to teach the scripts. Recent studies have shown that script frames can be taught without using traditional training formats (i.e., text, auditory) but by using generic …

Course Of Disease Progression And Time To Death Among Different Dementia Types In A Population Based Study, Kaitlyn E. Kauzor

All Graduate Theses and Dissertations, Fall 2023 to Present

Alzheimer’s disease (AD) is the most common type of dementia, Other types of dementia include vascular (VaD) and mixed forms, like AD with VaD, other mixed forms of dementia or dementia of unknown etiology (DUE). Research has focused on factors that may increase risk of developing dementia, with less understood about disease course. Factors associated with risk for developing dementia onset include age, female sex, family history of dementia, genetics (e.g. having the ε4 allele of the Apolipoprotein E or APOE gene), and various health conditions. This project used previously collected data from the Cache County Study on Memory and …

The Effect Of Indaziflam On Seed Production In Perennial Cool-Season Grasses, Benson F. Israelsen

All Graduate Theses and Dissertations, Fall 2023 to Present

Annual invasive grass weeds are a major problem in grass seed production as they contaminate seed lots and decrease the quality. Few effective herbicides are available to control invasive grass weeds in seed production systems. Indaziflam is a pre-emergence herbicide capable of providing annual weed control for 3-5 years after application. Indaziflam is not labeled for use in seed production as little is known of the effect it will have. The purpose of this study was to measure total seed yield, seed germination, seed mass, and seedling vigor when applying 0, 40, 77, and 93 g ai ha^-1 of …

Data-Driven Techno-Economic Analysis, Optimization, And Uncertainty Quantification Of Integrated Energy Systems In Deregulated Electricity Markets, Jacob A. Bryan

All Graduate Theses and Dissertations, Fall 2023 to Present

Electricity is a ubiquitous energy source in daily life, powering everything from stovetops and cellphones to vehicles and industrial processes. While wind and solar power have become increasingly common sources of electricity, the majority of electricity is still produced by burning fossil fuels, releasing greenhouse gases and propelling climate change. Wind and solar power cannot economically replace these fossil fuel energy sources on their own because they do not produce consistent power; the wind must be blowing, and the sun must be shining for them to make electricity. Nuclear power is a reliable source of energy that does not generate …

Aggregate And Disaggregate Effects Of The Us-China Trade War On Us Agriculture, Aflatun Kaeser

All Graduate Theses and Dissertations, Fall 2023 to Present

In 2018 and 2019, the US-China trade war caused a significant shift in US agricultural trade dynamics. This thesis conducts an aggregate and disaggregate analysis of the impact, using event study analysis to reveal varying effects on US agricultural exports, with a substantial effect on Soybean and Dairy exports. The analysis also found that there are heterogeneous effects on other agricultural commodities such as fruits, wheat, and tree nuts. Using Bayesian Structural Time Series Modeling, the study finds a 29% decline in soybean exports during the trade war period. These findings underscore the importance of considering the heterogeneity in the …

Designing Technology-Enriched Learning Environments: The Effects Of An Agent-Based Computer Model On Biology Students' Understanding Of The Covid-19 Pandemic And The Nature Of Models In Science, April Sullivan

All Graduate Theses and Dissertations, Fall 2023 to Present

Science education researchers have called for increased attention to the science practice of modeling to engage students in authentic scientific inquiry. A major challenge to integrating the modeling practice into science instruction is that students tend to conceptualize models as static end-products of research rather than generative tools for theory-building. Engaging students in using computer models, specifically agent-based computer models (ABMs), to explain and predict scientific phenomena could improve students' understanding of models in science. In this design-based research project I investigate the effects of an ABM-supported learning environment on high-school biology students' understanding of the COVID-19 pandemic and the …

Assessing Canopy Features, Its Shading Factor, And Their Influence In The Estimation Of Evapotranspiration In Almond Orchards Using Uas Information And The Two-Source Energy Balance Model, Moises R. Duran-Gomez

All Graduate Theses and Dissertations, Fall 2023 to Present

This study explored how canopy biomass and shadows affect evapotranspiration (ET) estimates, a crucial factor for irrigation management in almond orchards in California’s Central Valley. Data from 24 drone flights over three almond plots in 2021 and 2022 were analyzed using the Two-Source Energy Balance (TSEB) model, combined with meteorological data from EC-towers. The study found that filtering out shadows improved ET estimation, particularly in young orchards, and identified the importance of using new Leaf Area Index (LAI) models for better accuracy. This research is part of the T-REX initiative, which integrates drone and ground-based data to enhance water use …

The Geoarchaeology Of An Early Agricultural Landscape On Clear Creek, Fremont Indian State Park, Utah, Michael D. Bianchini

All Graduate Theses and Dissertations, Fall 2023 to Present

Clear Creek is a major Fremont early agricultural landscape in central Utah. The Fremont culture occupied the northern Colorado Plateau and the eastern Great Basin for approximately 1,000 years between AD 300–1300. This study builds an alluvial chronology that details the local history of alluvial fan development and erosion and examines the geoarchaeological context at Five Finger Ridge, the major occupation site in the valley. Geochronologic dating of sediment deposits, analyses of sediment types, AMS radiocarbon dating, and optically stimulated luminescence dating (OSL) ages has helped identify geomorphic contexts of Fremont agriculture in Clear Creek Canyon. This study focuses on …

Molecular Pathways Of Odontogenic Keratocysts: A Systematic Review, Paolo Boffano, Francesca Neirotti, Matteo Brucoli, Muhammad Ruslin

Journal of Dentomaxillofacial Science

The odontogenic keratocyst (OKC) stands out as one of the most prevalent odontogenic tumors. Since its initial description, numerous studies have delved into various aspects of this lesion, aiming to unravel its distinctive biological behavior.

Recent investigations have specifically focused on the molecular aspects of OKC, shedding light on its biological characteristics. Substantial differences at the molecular level between OKC and other odontogenic cystic lesions indicate a distinct biological origin. Genetic and molecular research in the realm of odontogenic tumors, particularly OKC, has contributed significantly to the growing knowledge and understanding of their physiopathological pathways. The molecular findings may open …

Relationship Between Risk Factors Of Dysphagia, Occlusal Tooth Contact And Oral Health-Related Quality Of Life In The Elderly, Muslita Indrasari, Lindawati S. Kusdhany, Randi Dias

Journal of Dentomaxillofacial Science

Objective: Tooth loss and changes in the swallowing mechanism in the aging process can lead to dysphagia. Individuals who are at risk of experiencing dysphagia have an impact on the health and quality of life and contribute to the cost of health care. The aim of this study to analyze the relationship between risk factors of dysphagia, occlusal tooth contact and oral health-related quality of life (OHRQoL) and find out which factors contribute the most to OHRQoL among the elderly.

Material and Methods: This cross-sectional study using consecutive sampling method from 121 respondents aged 60 years and over. The General …

Constructing Qur’An Recitation Classification Using Alexnet Algorithm, Harits Ar Rosyid, Dzulkifli Abdullah, Mohammed S. Alqahtani

Knowledge Engineering and Data Science

The growing demands for accurate and efficient methods in the Qur'an recitation classification highlight the limitations of existing models, particularly in assisting the memorization process. This study aims to address these challenges by implementing the AlexNet Convolutional Neural Network architecture, widely recognized for its effectiveness in image classification, to classify the Qur'an recitations using the Mel Frequency Cepstral Coefficient (MFCC) as the feature extraction method. The research involves several stages, including data collection, preprocessing (audio segmentation by verse), data augmentation, feature extraction, and classification using the AlexNet architecture, followed by performance evaluation. Key results demonstrate that the combination of MFCC …

Gotcha ! This Model Uses My Code ! Evaluating Membership Leakage Risks In Code Models, Zhou Yang, Zhipeng Zhao, Chenyu Wang, Jieke Shi, Dongsum Kim, Donggyun Han, David Lo

Research Collection School Of Computing and Information Systems

Leveraging large-scale datasets from open-source projects and advances in large language models, recent progress has led to sophisticated code models for key software engineering tasks, such as program repair and code completion. These models are trained on data from various sources, including public open-source projects like GitHub and private, confidential code from companies, raising significant privacy concerns. This paper investigates a crucial but unexplored question: What is the risk of membership information leakage in code models? Membership leakage refers to the vulnerability where an attacker can infer whether a specific data point was part of the training dataset. We present …

Shield-U: Safeguarding Traffic Sign Recognition Against Perturbation Attacks, Shengmin Xu, Jianfei Sun, Hangcheng Cao, Yulan Gao, Ziyang He, Cong Wu

Research Collection School Of Computing and Information Systems

Traffic sign recognition systems are crucial for the navigation and situation awareness of autonomous vehicles. They leverage deep learning technologies to swiftly and accurately identify traffic signs, even in the most challenging traffic environments. However, security researchers have uncovered a critical vulnerability in these systems: learning-based TSRs are particularly susceptible to physical-world perturbation attacks. Through subtle modifications (i.e., attaching well-designed patches on traffic signs), attackers can deceive the recognition system into making erroneous judgments, which can further lead to serious traffic accidents. Although several defense mechanisms have been proposed to enhance the security of sign recognition systems, these solutions generally …

A Comprehensive Study On Static Application Security Testing (Sast) Tools For Android, Jingyun Zhu, Kaixuan Li, Sen Chen, Lingling Fan, Junjie Wang, Xiaofei Xie

Research Collection School Of Computing and Information Systems

To identify security vulnerabilities in Android applications, numerous static application security testing (SAST) tools have been proposed. However, it poses significant challenges to assess their overall performance on diverse vulnerability types. The task is non-trivial and poses considerable challenges. Firstly, the absence of a unified evaluation platform for defining and describing tools’ supported vulnerability types, coupled with the lack of normalization for the intricate and varied reports generated by different tools, significantly adds to the complexity. Secondly, there is a scarcity of adequate benchmarks, particularly those derived from real-world scenarios. To address these problems, we are the first to propose …

Lilac: Log Parsing Using Llms With Adaptive Parsing Cache, Zhihan Jiang, Jinyang Liu, Zhuangbin Chen, Yichen Li, Junjie Huang, Yintong Huo, Pinjia He, Jiazhen Gu, R. Michael Lyu

Research Collection School Of Computing and Information Systems

Log parsing transforms log messages into structured formats, serving as the prerequisite step for various log analysis tasks. Although a variety of log parsing approaches have been proposed, their performance on complicated log data remains compromised due to the use of human-crafted rules or learning-based models with limited training data. The recent emergence of powerful large language models (LLMs) demonstrates their vast pre-trained knowledge related to code and logging, making it promising to apply LLMs for log parsing. However, their lack of specialized log parsing capabilities currently hinders their parsing accuracy. Moreover, the inherent inconsistent answers, as well as the …

Automating Maritime Risk Data Collection And Identification Leveraging Large Language Models, Donghao Huang, Xiuju Fu, Xiaofeng Yin, Haibo Pen, Zhaoxia Wang

Research Collection School Of Computing and Information Systems

Maritime risk research is crucial yet challenging for improving safety, efficiency, and sustainability in maritime operations. This paper presents an innovative method for automating the collection and identification of risk data related to global maritime risks from news sources, addressing the limitations of traditional manual methods. To evaluate the proposed method, different learning-based models, including conventional machine learning approaches and advanced Large Language Models (LLMs) such as GPT-4 and LLaMA-3.1, are comprehensively studied for comparison. In addition, not only do we use popular evaluation metrics to assess the proposed method, but we also introduce a new evaluation metric, called the …

Custom Permission Misconfigurations In Android: A Large-Scale Security Analysis, Rui Li, Wenrui Diao, Debin Gao

Research Collection School Of Computing and Information Systems

Android’s popularity is due to its openness and vast app ecosystem. Global developers can use Android Studio and rich Android APIs to create their apps. Within this ecosystem, Android permissions play a crucial role in managing access to resources, with system permissions controlled by system apps and custom permissions declared by third-party apps. However, the security of custom permissions has not received enough attention from the mobile security community, resulting in a lack of thorough evaluation of security practices for app developers using custom permissions. This study systematically evaluated the misconfiguration of custom permissions by Android app developers. It is …

Chain Of Preference Optimization: Improving Chain-Of-Thought Reasoning In Llms, Xuan Zhang, Chao Du, Tianyu Pang, Qian Liu, Wei Gao, Min Lin

Research Collection School Of Computing and Information Systems

The recent development of chain-of-thought (CoT) decoding has enabled large language models (LLMs) to generate explicit logical reasoning paths for complex problem-solving. However, research indicates that these paths are not always deliberate and optimal. The tree-of-thought (ToT) method employs tree-searching to extensively explore the reasoning space and find better reasoning paths that CoT decoding might overlook. This deliberation, however, comes at the cost of significantly increased inference complexity. In this work, we demonstrate that fine-tuning LLMs leveraging the search tree constructed by ToT allows CoT to achieve similar or better performance, thereby avoiding the substantial inference burden. This is achieved …

User Acceptance Of Advice By Ai Agents: Expectation-System Fit Perspective, Jingyuan Cai, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

Algorithms have increasing influence on our daily decisions, especially when the recommendations are presented by human-like AI agents. This study applies the Theory of Effective Use to investigate how the fit between the user’s role expectation for an AI agent and the agent’s interaction style impacts AI advice adoption. We proposed a new concept termed Perceived Expectation-System Fit (PESF) and empirically examined its impact on user perceptions and advice acceptance. We found that low PESF reduces advice acceptance by diminishing cognitive and affective trust in the AI agent. Furthermore, increased algorithm transparency increases PESF's impact on decision-making. Our findings provide …

Impacts Of Stream Bed Adjustment On Local Bridge Morphology At Highway 281, Molly G. Likins

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

Nebraska sand-bed rivers have long been a part of sediment transport studies and have been used in the development of numerous well-known empirical bedload equations. Some of these studies have shown how adjustments in streambed elevation led to changes in local stream morphology. The sand-bed rivers of Nebraska are highly susceptible to such changes due to their wide, shallow cross-sections and erodibility. The objective of our study is to synthesize a hydrodynamic model with high-resolution field data and improved methods of representing sediment transport to better predict both short and long-term channel adjustments for an aggraded sand-bed river.

The field …

Using Symbolic Execution To Analyze The Hardware Tcp Protocol, Nianhang Hu

School of Computing: Dissertations, Theses, and Student Research

As the demand for high performance and flexible networking capabilities increases, the shift from software to hardware implementations of stateful networking functions (such as TCP) is becoming increasingly important. This transition not only enhances processing efficiency in modern networking environments where data transmission rates are rising, but it also reduces the inherent CPU overhead found in software implementations, allowing hardware devices to handle network traffic more efficiently. However, validating the correctness of these hardware designs poses significant challenges due to the complex timing requirements and the vast input space associated with packet-level properties.

The verification of packet-level properties requires coverage …

Leveraging Geo-Ai To Evaluate Conservation Land Conditions In Nebraska, Usa, Fnu Jahangeer

Community and Regional Planning Program: Theses

Wetlands are among the most vital natural resources, offering extensive ecosystem services that benefit human societies. However, human activities and disturbances have led to widespread wetland degradation and loss worldwide. Key factors contributing to this degradation include pollution, exploitation of biological resources, modifications to natural systems, and agricultural and aquacultural practices. This study examines wetland conservation efforts in Nebraska, focusing on three main areas: (1) AI-Driven Applications in Google Earth Engine for Surface Water Monitoring, Assessment, and Management; (2) Assessing Wetland Hydrological Performance under Three Conservation Programs in Nebraska through AI-Driven Google Earth Engine Analysis; and (3) Identifying Potential Wetland …

Echo And Drag As Resistance: Coloniality, Queerness, And Practices Of Reading Student Texts, Joshua Barsczewski, Florianne Jimenez

The Journal of the Assembly for Expanded Perspectives on Learning

In this article, a postcolonial theorist and a queer studies scholar reconsider the role of student resistance in Writing Studies’ social justice turn, arguing for a way of reading student texts that accounts for why students might choose to take up social justice or not in their own writing. Through examples from their ongoing research projects, the writers discuss how students’ resistance surfaced not as visible and explicit signs of a changed epistemological framework or political perspective, but as a series of normative rhetorical choices that made space for more transgressive or subversive possibilities.

Stealing Graceland And Evicting Aunt Mary Ann: Real Property, Erica L. Sullivan

Mercer Law Review

This Article surveys developments in Georgia real property law between June 1, 2023, and May 31, 2024. This Article reviews several cases decided during the Survey period and highlights real estate trends and news both in Georgia and nationally.

Local Government, Jacob Stalvey O'Neal, Russell A. Britt, Mathis L. Gales, Jennifer Dorminey Herzog, Nicholas A. Kinsley, M.Blake Walker

Mercer Law Review

As usual, the Survey saw multiple published cases involving the doctrine of sovereign immunity. Georgia courts clarified multiple sovereign immunity waivers, including waivers for injunctive and declaratory relief claims, waivers for nuisance claims, and waivers for claims involving negligent uses of government vehicles. This Article attempts to summarize the highlights and noteworthy cases.

Wills, Trusts, Guardianships, And Fiduciary Administration, Mary F. Radford

Mercer Law Review

This Article discusses significant cases decided by the Georgia appellate courts during the period of June 1, 2023, through May 31, 2024, and significant Georgia legislation enacted in that same period that relate to Georgia probate and trust law, guardianship, and estate planning. The cases discussed fall under three categories: wills and the administration of decedents’ estates (including cases relating to testamentary capacity, inheritance by children born out of wedlock, undue influence, and the disposition of a decedent’s remains); trusts and trustees (specifically a trustee’s entitlement to have attorney fees paid from the trust when defending against charges of maladministration …

Under Observation: Wilson V. Inthachak Shows That Georgia’S Emergency Care Statute Still Lacks A Uniform Interpretation, Thomas S. Kiser

Mercer Law Review

This year, pro- and anti-tort reform forces met on the battleground of O.C.G.A. § 51-1-29.5(c), a statute that gives doctors increased protection from malpractice claims when they provide “emergency medical care in a hospital emergency department . . . .” When healthcare providers or hospitals are sued for negligence under these circumstances, the plaintiff must have clear and convincing evidence that the provider was grossly negligent, a greater hurdle than an ordinary medical malpractice plaintiff would need to overcome. While the statute is crystal clear in its purpose, Georgia courts have not reached a consensus regarding its application. Wilson v. …

Two Bites, Different Apples: The Georgia Supreme Court Revolutionizes Forty-Year Precedent On First-Offender Appeals In Howard V. State, Joshua R. Wright

Mercer Law Review

Since 1968, Georgia’s First Offender Act has provided for an alternative sentencing procedure for criminal defendants who have not previously been convicted of a felony. The Act allows trial courts to place a defendant on probation or sentence them to a term of confinement before a conviction and without entering a judgment. The significance of this procedure is that, if a defendant successfully completes the terms of their first-offender status, they are exonerated and the prosecution’s case is discharged by law. The former defendant receives no criminal conviction and their civil rights and liberties are preserved.