Digital Commons Network^™

Robust Graph Learning On The Web: Challenges, Methods, And Applications, Ao Xiang, Yang Liu, Guansong Pang, Yuanhao Ding, Hezhe Qiao, Dawei Cheng, Qing He

Research Collection School Of Computing and Information Systems

Graph learning is transforming web intelligence, powering applications from recommender systems to anomaly detection. However, most existing approaches implicitly assume ideal conditions where training and testing data are accurate, complete, and free from manipulation. In reality, web environments rarely exhibit such stability. Dynamic user behavior, incomplete or outdated content, adversarial interference, and sudden distribution shifts can all erode the reliability of even state-of-the-art models, leading to biased or unsafe outcomes. This tutorial provides a comprehensive survey of emerging strategies for robust graph learning on the web. We first present a structured taxonomy of the principal robustness threats specific to web …

Zero-Shot Transfer Of Foundation Time-Series Forecasters To Datacenter Operational Telemetry: Mapping A Domain Nobody Gets To Study, David Pace Jr

LSU New Orleans Theses and Dissertations

This thesis asks how best to forecast real datacenter operational telemetry. Can pretrained foundation time-series forecasters do it zero-shot, or do trained classical baselines perform best? On a single-site benchmark of eight audited targets and four horizons (32 slices), the zero-shot foundation forecasters Moirai, Chronos, and TimesFM win 26 of 32 slices against multivariate classical baselines. However, the foundation wrappers operate per-channel on the target history, while classical baselines consume the full feature tensor. When the same classical models are retrained univariate, the foundation lead persists (27 of 32 slices) and a 3-seed rerun of a classical challenger reproduces it; …

Environmental And Socioeconomic Effects Of Roundtable On Sustainable Palm Oil Certification: A Systematic Review And Meta-Analysis, Kibrom T. Sibhatu, Matin Qaim

All Peer-Reviewed Publications

Palm oil is the most widely produced and consumed vegetable oil worldwide, but its production is associated with deforestation and other environmental and social problems. Roundtable on Sustainable Palm Oil (RSPO) is the only internationally-recognized voluntary certification standard aimed at mitigating such problems. Many studies examine RSPO’s effects on particular outcomes in specific contexts, but a consolidated global assessment is lacking. Here, we systematically review the literature and identify 53 original studies covering RSPO effects in various countries of Asia, Africa, and Latin America. Where data availability permits, we also conduct meta-analysis. Results reveal that RSPO can lead to environmental …

Litigating The Youth Mental Health Crisis: Mechanisms To Regulate Addictive Social Media Design, Talia Elliott

Washington and Lee Law Review

While social media offers real benefits to users, such as providing access to information and facilitating the free exchange of ideas, excessive social media use is associated with increases in anxiety, depression, and other serious mental-health harms. Social media platforms are designed to maximize profit by capturing user attention, resulting in interfaces that are dangerously addictive and prone to exposing users to harmful content. Currently, social media users alone bear the burden of navigating the dangers of social media. This is untenable. Young users, whose less developed brains leave them more vulnerable to addictive design features, find self-regulation especially challenging. …

Experimental-Motion-Driven Cfd Investigation Of Slosh Dynamics In Propellant Tanks Of Spacecraft And Launch Vehicles, Priyanshu Savaliya

Doctoral Dissertations and Master's Theses

Liquid sloshing in partially filled propellant tanks can generate transient forces and moments that affect spacecraft and launch vehicle stability, guidance, and control. This research develops a one-way experimental-to-Computational Fluid Dynamics (CFD) integration framework to investigate free-surface slosh behavior under realistic excitation conditions.

The overarching goal of this thesis is to develop and evaluate a one-way experimental-motion-driven computational framework for predicting liquid slosh response in a partially filled cylindrical tank. Rather than relying on idealized sinusoidal inputs, this work uses experimentally measured actuator-feedback motion as the prescribed excitation for high-fidelity CFD. The central objective is to establish the experimental and …

A Machine-Learning-Based Systematic Framework For Modeling Compression And Recompression Indices For Florida Soils, Michael Morales

Doctoral Dissertations and Master's Theses

This thesis develops a machine-learning framework for estimating the compression index and the recompression index of Florida soils from routinely measured index properties, and reports two studies that build it. Consolidation settlement design requires both indices, and both are obtained from the incremental-loading oedometer test, which occupies a specimen for one to two weeks; the index tests that accompany it are complete within hours. Empirical correlations have filled that interval since the 1950s, but their coefficients are calibrated on specific soil populations and transfer poorly between regions. The first study analyzes 376 consolidation tests compiled for the Florida Department of …

Enhancing Virtual Reality Cockpit Procedure Training With Haptic Feedback, Christian K. Jaedicke

Doctoral Dissertations and Master's Theses

Pilot training is time-consuming and costly, and not all phases require full-flight simulators or actual aircraft. Virtual reality (VR) offers a potential means to reduce cost and duration while supporting practical cockpit procedure training. While prior research in the VR domain suggests that providing haptic feedback can support training of muscular control and increase perceived immersion, it remains unclear whether haptic feedback improves spatial cognition in an unfamiliar VR environment. This study examined whether haptic feedback and cockpit complexity affected response time and position error under limited-visibility, time-constrained conditions in a VR cockpit environment (i.e., a quasi-blindfold cockpit check).

Grounded …

Evaluating The Safety Efficiency Of U.S. Air Traffic Control Tower Operations Using Data Envelopment Analysis, Kenneth James Gilbert Ii

Doctoral Dissertations and Master's Theses

Air traffic control (ATC) tower safety efficiency remains inadequately measured despite critical workforce challenges, including staffing shortages, training pipeline constraints, and geographic retention difficulties. This mixed-methods study developed and validated a comprehensive framework for measuring tower safety efficiency by integrating subject-matter expert insights with multi-model data envelopment analysis (DEA) across 66 Federal Aviation Administration (FAA) tower facilities from 2016 to 2024. Six focus group interviews with experienced professionals (100% with > 20 years of experience), averaging 96.4 minutes, identified critical efficiency factors through systematic coding, achieving substantial inter-rater reliability (Cohen's kappa 𝜅 = .68). Qualitative findings showed that staffing shortages don't …

Online Ppo-Based Multi-Hop Task Offloading Strategy For Vehicular Edge Computing, Wenzhu Zhang, Yuewei Bian, Fuli Xiong, Siqi Cai

Journal of System Simulation

Abstract: To address the problems of frequent communication link interruptions caused by dynamic network topologies and the sharp increase in computational complexity triggered by high-dimensional decision spaces in the vehicular edge computing (VEC) environment, a multi-hop task offloading strategy for VEC based on an online PPO algorithm was proposed. A multi-hop task offloading optimization model simultaneously considering link effective time, transmission rate, and computing resource constraints was constructed; a multi-hop A* path search algorithm integrating link stability and end-to-end delay was designed; an online offloading decision framework based on PPO was proposed, which transformed the 0-1 mixed integer nonlinear programming …

Research On Temporal Action Localization Methods For Cross-Modal Understanding, Jinwei Li, Xiaoyang Liu, Rusheng Ju

Journal of System Simulation

Abstract: To address the problems of insufficient localization accuracy and high model complexity in the temporal action localization (TAL) task for video-text cross-modal understanding, an anchor-free action transformer (AFAT) model was proposed. Based on the anchor-free framework, the local self-attention mechanism of Transformer was introduced to enhance the global modeling capability of temporal features. A multi-scale feature pyramid structure was combined to strengthen the representation of actions with different durations, and a lightweight predictor was adopted to reduce computational redundancy. Experimental results show that the average precision of this model on the THUMOS14 dataset is significantly improved compared with the …

Comparative Analysis Of Task Scheduling In Multi-Tier Fog-Cloud Computing: From Classical Approaches To Greedy Multi-Objective Optimization, Zafril Rizal M. Azmi, Najmul Haque, Saydul Akbar Murad

Faculty Publications

Fog computing extends cloud services to the network edge, enabling low-latency processing for time-sensitive applications. However, scheduling complexity significantly increases due to heterogeneous resources, dynamic workloads, and strict Quality-of-Service (QoS) constraints. Although numerous scheduling techniques have been proposed, existing studies often assess only a narrow subset of algorithms or rely on offline metaheuristics unsuitable for real-time environments. This paper presents a comprehensive comparative evaluation of twelve scheduling algorithms, including five classical, one heuristic, and six metaheuristic-inspired approaches, within a realistic 20-node multi-tier fog-cloud topology. Across 1,365 experiments spanning seven utilization levels, we analyze each algorithm’s deadline adherence, load distribution, and …

Medical Monitoring Working Group Meeting Minutes, Mike Mcanulty, Eric Hassler

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Influence Of Stormwater Flooding Events On The Mobile County School District Student Population, Kadence Kali Johnston

Honors Theses

Mobile County, Alabama, receives among the highest annual rainfall totals in the United States resulting in frequent stormwater flooding that intersects with existing socioeconomic vulnerabilities. Within the Mobile County Public School System (MCPSS), 77% of students are economically disadvantaged and over 10% experience homelessness, creating heightened risk for educational disruption during flood events. This study investigates how stormwater flooding influences school attendance, closures, and academic performance across MCPSS, providing insight into how climate-driven hazards exacerbate educational inequities. The research integrates flood frequency, school performance metrics, and GIS flood-zone mapping and teacher perceptions to understand how flooding affects student learning opportunities. …

What We Know About Accounting Ratios: Methodological Considerations, Wojciech Kuryłek, Oskar Kowalewski

Studia i Materiały Wydział Zarządzania Uniwersytet Warszawski

Purpose: This paper provides a comprehensive literature review of the methodological aspects of financial ratio analysis, consolidating dispersed knowledge on the computation, statistical properties, and appropriate usage of accounting ratios.

Design/Methodology/Approach: The study adopts a narrative literature review methodology, systematically surveying published research on financial ratio distributions, normality testing, data transformations, outlier handling, the proportionality assumption, dimensionality reduction techniques, compositional data analysis, and recommended ratio sets for corporate financial research.

Findings: Financial ratios predominantly deviate from normal distributions, exhibiting skewness, excess kurtosis, and sensitivity to outliers. Transformation techniques such as logarithmic, square root, and Box‑Cox methods yield mixed results in …

Studia I Materiały 1/2026 (44)

Studia i Materiały Wydział Zarządzania Uniwersytet Warszawski

Entire Volume Studia i Materiały 1/2026 (44)

Mengukur Capaian Dan Identifikasi Konvergensi Pembangunan Infrastruktur Antarprovinsi Di Indonesia, Ressa Isnaini Arumnisaa', Aisyah Fitri Yuniasih

Jurnal Ekonomi dan Pembangunan Indonesia

Indonesia’s economic challenges are characterized by stagnant economic growth and regional development disparities. This study analyzes the achievement and convergence of infrastructure development across provinces in Indonesia during 2011–2021 through the construction of an Infrastructure Development Index (IPI). The study employs panel data from 33 provinces, using factor analysis to construct the IPI and the First Difference Generalized Method of Moments (FD-GMM) to examine convergence and its determinants. The results show that many provinces still have IDI scores below the national average. Furthermore, the FD-GMM model shows that σ-convergence and β-convergence occur in Indonesia. In addition, GRDP per capita, inflation, …

Food Insecurity, Economic Shocks, Poverty, And Inequality In Nigeria, Ibrahim Tijjani Salihu, Jahen F. Rezki

Jurnal Ekonomi dan Pembangunan Indonesia

Drawing on the 2018/2019 Nigeria General Household Survey — a nationally representative sample of 5,000 households across six geopolitical zones obtained using multi-stage stratified sampling — this study applied linear probability and probit models to examine poverty’s socioeconomic drivers. Findings show food insecurity and economic shocks worsen poverty, while remittances, credit access, employment, safety nets, and education help reduce it. Using poverty indices and the Gini coefficient, the analysis found rural households face greater poverty incidence, depth, and severity than urban households, despite urban areas showing marginally higher income inequality. Inequality among lower-income households, however, was nearly identical across both …

How Important Is Clean Energy To Utahns?, Elizabeth Brunner, Stacia Ryder

Utah People and Environment Poll (UPEP)

Utah's energy mix has changed significantly over the past several decades as it has moved to cleaner forms of generation. For example, according to the Energy Information Administration, in 2024, coal fueled about 45% of Utah's total electricity net generation, down from 75% in 2015. As can be seen in the chart below, the state anticipates demand growth, with further reductions in coal alongside a significant increase in solar, storage, and natural gas by 2032. Though not represented in these charts, plans for nuclear power generation have been proposed in Brigham City as well as outside of Green River. Utah …

How Can Implementing A Consistent Social And Emotional Learning Curriculum In An Elementary School Setting Promote Academic Success And Help The Overall Well-Being Of Our Teachers And Students?, Joseph Rydel

School of Education and Leadership Student Capstone Projects

Elementary schools are seeing an increase in students' social, emotional, and behavioral needs, making it more difficult for teachers to meet the needs of their students. While research shows that Social and Emotional Learning (SEL) can improve behavior, academic performance, and overall well-being, many schools still do not have a consistent curriculum to teach these skills. The purpose of this capstone project was to explore how implementing a consistent SEL curriculum in an elementary school setting can improve academic success while supporting the overall well-being of both students and teachers.

To answer this question, I created a project that reviewed …

Fostering The Success Of Indigenous Students: How Educators Can Address Systemic Barriers In Schools, Samantha Hamlin

School of Education and Leadership Student Capstone Projects

This qualitative study sought to gain information into the connection that Indigenous students have with education and the ways that educators can work to make education more accessible. The study gave background knowledge as to the history of Indigenous people and the greater implications of colonization. It explores ways that educators could incorporate Indigenous knowledge into curriculum to uplift and engage Indigenous students. The accompanying project is a compilation of ideas for lesson plans across subject areas that teach through an Indigenous lens, rather than a white centered one. In the conclusion, implications and limitations of the study are discussed …

Advanced Mathematics In The Elementary School: Supporting Teachers And Students Through A Resource Compilation, Abigail Friedel

School of Education and Leadership Student Capstone Projects

Addressing the needs of every student within an elementary mathematics classroom is a difficult and time-consuming task that educators are charged with. The range of abilities in a general education classroom can span multiple grade levels, especially in upper elementary. Teachers are often encouraged to focus on students that are below grade level, which can lead to higher ability students being bored and disengaged when they are in the classroom (Livers et al., 2018). To address this issue, this capstone project seeks to answer the question of how can elementary classroom teachers best support their advanced learners in math after …

Decolonizing Minnesota Mathematics: Incorporating Indigeneity Into Middle School Mathematics, Tia Ahmed

School of Education and Leadership Student Capstone Projects

The invisibility of Native Americans in mainstream mathematics education has contributed to the academic underachievement and cultural disconnect experienced by Native American youth. Grounded in the frameworks of Tribal Critical Race Theory (TribalCrit), culturally relevant teaching, and ethnomathematics, this project investigates: How can the historical and current cultural contexts, mathematical understandings, perspectives, and issues relating to Dakota, Anishinaabe, and Urban Indigenous communities be incorporated into Minnesota middle school math curriculum in a way that fosters strong math identities among Native American students and supports the needs of Minnesota’s American Indian tribes and communities? Along with research on the intersectionality of …

Enhancing Second Language Acquisition Through Hands-On Learning In French Immersion Schools, Vanessa Hendrikson

School of Education and Leadership Student Capstone Projects

Learning a second language at school is a valuable experience. However, the journey toward fluency can sometimes be long and challenging for both students and educators. This capstone explores how hands-on learning activities can support second language learning by providing students with meaningful and engaging experiences. It is guided by the research question: How can hands-on learning activities support second language acquisition among students in French immersion schools? Grounded in research on second language acquisition and experiential learning, the project examines how games, manipulatives, and other hands-on activities can help students build their language skills while providing opportunities for authentic …

Establishing Ferromagnetism In Van Der Waals Antiferromagnets Mps3, Dinesh Upreti

Graduate Theses and Dissertations

Recent discoveries of magnetism in low dimensions not only have gained fundamental scientific interest but also holds significant potential in numerous technological applications, such as spintronics. This has led to a wide range of efforts in the synthesis of new layered materials or tuning their existing magnetic properties, which has been instrumental in understanding the novel physical concept and development of new technological frontiers. Transition metal thiophosphate, MPS3, is a class of layered antiferromagnet family. The rich magnetic/crystal structure with delicate choice of transition metal (M) together with intriguing optical, electronic, and ferroelectric properties have placed them as a model …

The Gravity Of The Ukraine War: Measuring Conflict Impacts On European Grain Trade, Stefan Bonchis

Graduate Theses and Dissertations

This thesis investigates the heterogeneous structural disruptions caused by the war in Ukraine on the European Union’s agricultural trade architecture, focusing on three critical commodities: wheat, maize, and sunflower seeds. Employing a structural gravity model framework across all 27 EU Member States, the study evaluates two conflict episodes, the 2014 Crimea annexation and the 2022 full-scale invasion, to identify the net beneficiaries and heavily impacted nations within the EU agricultural trade network. The empirical strategy utilizes a dual-test design to capture the full scope of the disruption. Test A (Ukraine towards the EU trade) reveals a distinct geographic logic in …

Enhancing Deep Learning Image Reconstruction In Breast Ct With Task-Driven Training And Physics-Informed Models, Megan Ariel Murphy

Dissertations (1934 -)

Dedicated breast X-ray computed tomography (breast CT) is a developing imaging modality that has potential as an alternative to mammography. Unlike traditional mammography, breast CT offers high-resolution, fully 3D anatomical detail, which aids in the detection of microcalfications and subtle lesions that are potential indicators of cancer. To be effective for screening, breast CT must limit radiation exposure by reducing CT view angles. However, traditional image reconstruction methods yield noisy, artifacted images in this sparse-view CT setting. This dissertation develops image restoration and reconstruction methods that address these limitations by integrating physics-informed iterative methods with machine learning tools, and a …

Gold & Blue, Summer 2026, St. Mary's University - San Antonio, Texas

Gold & Blue

This is the Summer 2026 edition of Gold & Blue, which is St. Mary’s University's official alumni magazine.

It's All In The (Exponential) Family: An Equivalence Between Maximum Likelihood Estimation And Control Variates For Sketching Algorithms, Keegan Kang, Kerong Wang, Ding Zhang, Rameshwar Pratap, Bhisham Dev Verma, Benedict Wong

Faculty Conference Papers and Presentations

Maximum likelihood estimators (MLE) and control variate estimators (CVE) have been used in conjunction with known information across sketching algorithms and applications in machine learning. We prove that under certain conditions in an exponential family, an optimal CVE will achieve the same asymptotic variance as the MLE, giving a fixed point algorithm for the MLE. Experiments show the fixed point algorithm is faster and numerically stable compared to other root finding algorithms for the MLE for the bivariate Normal distribution, and we expect this to hold across distributions satisfying these conditions. We show how this algorithm leads to reproducibility for …

Managing Risks Under Nuclear Power Plant Projects: A Latent Similarity-Guided Contract Customization, Mariam Elazhary, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Global energy is transforming, with nuclear power emerging as a pivotal player in achieving sustainable and low-carbon energy goals. The nature of nuclear technology introduces unique challenges, such as stringent safety and environmental requirements. Existing studies focus on general risk identification, such as supply chain delays, cost overruns, and public perception issues. However, these studies fail to address integrating these risks into tailored contractual provisions, which are critical for navigating the unique challenges of nuclear projects. The goal of this paper is to examine how standard construction contracts can be tailored to better accommodate the risks inherent in nuclear power …

Digital Twin-Assisted Optimization Of 6g Wireless Networks: Ensuring Deterministic Communication, Yingpu Nian, Bo Yi, Xingwei Wang, Sajal K. Das

Computer Science Faculty Research & Creative Works

With the rapid advancement of 6G technology and the increasing use of smart devices, Deterministic 6G Wireless Networks (D6WN) have emerged to meet the growing network transmission demands. In particular, applications such as autonomous vehicles, remote surgery, and industrial automation require extremely low transmission latency to function effectively, highlighting the critical need for D6WN in supporting these time-sensitive use cases. Yet, the conventional TCP/IP framework lacks effective unified traffic and congestion control scheduling, aggravating latency and uncertainty, posing a challenge to ensuring reliable real-time critical applications. To address the challenges of deterministic transmission in D6WN, this paper integrates Digital Twin …