Digital Commons Network^™

A2s Uplink Latency Minimization For Wildfire Monitoring Systems Using Mbse And Stochastic Modeling, Luis Giovanni Wang

Master's Theses

Wildfire response depends on how quickly a detection reaches the people who act on it, and the slowest remaining step is often the link that carries an alert from a remote sensing platform to a satellite. This thesis models the latency of that link, the Air-to-Space uplink, for a wildfire-monitoring UAV that carries a Starlink terminal and sends an ALERT packet to a serving Low Earth Orbit satellite. The uplink is difficult to predict because both the UAV and the satellite move, and because the wildfire environment degrades the channel at the moment the data matters most.

The thesis uses …

Multimodal Machine Learning For Soil Burn Severity Mapping Across California Wildfires, Sanjana Checker

Master's Theses

Accurate mapping of soil burn severity (SBS) is critical for post-fire watershed management, erosion risk assessment, and ecological recovery planning, yet traditional field-based approaches remain costly, time-intensive, and spatially limited. This thesis presents a machine learning pipeline for wall-to-wall SBS classification across California wildfires using multi-sensor satellite imagery, terrain derivatives, and bioclimatic covariates. Field-collected SBS observations (n = 2,180) from 52 wildfires occur- ring between 2013 and 2025, sourced from the U.S. Forest Service and CAL FIRE, were used to train and evaluate multiple classification architectures within a Google Earth Engine and Google Cloud-based prediction framework. After upsampling the unburned …

Draft Final 2023 Unreclaimed Sites Sampling: Ur-31 Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Reduced Product Type Monoid-Module Extensions, Darryl Jent

Dissertations

In 1955, I. M. James introduced the James Construction, a free topological monoid that models the loops on the suspension of a given space. In 1969, S. Y. Husseini generalized this idea to RPT monoids: topological monoids with a free-like monoid structure that can be used to model a broader class of loop spaces. In order to prove that these topological monoids are models of loop spaces, both I. M. James and S. Y. Husseini constructed contractible spaces on which these topological monoids act. We define a topological module as a space equipped with an action by a topological monoid. …

Deployment-Aware Deep Learning For Computer Vision: Efficient Architectures From 3d Segmentation To Mixed Reality, Bahar Uddin Mahmud

Dissertations

Deep learning has become the dominant approach for solving vision-centric problems; however, its successful deployment in real-world applications remains limited by high computational cost, data dependency, and insufficient integration with practical and human-centered environments. While state-of-the art deep learning models often achieve impressive performance in controlled settings, they frequently fail to generalize or operate efficiently under deployment constraints such as limited resources, complex data modalities, and real-time interaction requirements. These limitations motivate the need for a deployment-oriented deep learning framework that balances accuracy, efficiency, and practical usability.

This dissertation investigates the design and deployment of efficient deep learning architectures for …

From Total Domination To Graph Coloring, Sawyer Isaac Osborn

Dissertations

A question involving a chess piece called a prince on the 8×8 chessboard leads to a concept in graph theory involving total domination. We say a vertex u in a graph G totally dominates a vertex v if u is adjacent to v. A subset S of the vertex set of a graph G is a total dominating set for G if every vertex in G is totally dominated by at least one vertex of S. If S is a total dominating set of G, then σ_S(v) denotes the number of …

Ai, Medicine, And Social Determinants Of Health Data, Ryan Doyloo, Nicholson Price

Articles

This article examines how medical AI systems are incorporating SDoH data and the governance challenges that follow. The authors show that while SDoH integration can enhance clinical workflows and predictive accuracy — potentially improving outcomes for underserved populations — it also introduces acute risks of proxy discrimination, where facially neutral variables replicate protected characteristics. Surveying U.S., EU, and international frameworks, the authors argue that existing regimes lack clear ex ante guidance to distinguish beneficial from harmful uses of SDoH data. In response, they advance post-market monitoring as a pragmatic and scalable pathway: generating real-world, SDoH-stratified evidence that can support enforcement, …

From 5g To 6g: A Survey On Security, Privacy, And Standardization Pathways, Mengmeng Yang, Youyang Qu, Thilina Ranbaduge, Chandra Thapa, Nazatul Haque Sultan, Ming Ding, Hajime Suzuki, Wei Ni, Sharif Abuadbba, David Smith, Paul Tyler, Josef Pieprzyk, Thierry Rakotoarivelo, Xinlong Guan, Sirine Mrabet

Research outputs 2022 to 2026

The vision for 6G aims to enhance network capabilities, supporting an intelligent digital ecosystem where artificial intelligence (AI) is a key. However, the expansion of 6G raises critical security and privacy concerns due to the increased integration of IoT devices, edge computing, and AI. This survey provides a comprehensive overview of 6G protocols with a focus on security and privacy, identifying risks that have not been experienced in preceding 5G systems, and presenting mitigation strategies. While many vulnerabilities from earlier generations persist, the introduction of AI/ML introduces novel risks like model inversion and malicious manipulation of AI. Vulnerabilities in emerging …

Geometric Characterization Of Ideals In Bipolar Semigroups, Kittipong Laipaporn, Rasimate Maungchang, David M. Cook, Prathomjit Khachorncharoenkul

Research outputs 2022 to 2026

This paper develops a geometric framework for analyzing the ideal structure of the bipolar semigroup ��={(−��,��)∣��,��∈ℝ+0} under coordinate-wise addition. Subsets of B are interpreted as planar regions, allowing ideals to be described in terms of boundary behavior. In particular, we prove that the complement of a simply connected region is an ideal of the commutative additive semigroup (��,+) if and only if its boundary contains no strictly decreasing segment. This provides a direct and visually verifiable criterion for ideality, linking algebraic structure to geometric shape. Each ideal can be written as a union of translates of the form ��+��, with …

Rvit-Fusionnet: A Local Cross-Attention Feature Fusion-Based Hybrid Framework For Brain Tumor Classification, Naima Islam, Sajeeb Kumar Ray, Md Anwar Hossain, Syed Mohammed Shamsul Islam

Research outputs 2022 to 2026

Accurate brain tumor classification via MRI is essential for diagnosis and treatment. This study introduces RViT-FusionNet, a hybrid deep learning model that integrates convolutional and transformer architectures for enhanced tumor detection. The model utilizes ResNet-50 to capture textural details and a Vision Transformer for extracting global context. A Local Cross-Attention (LCA) module is proposed to align and merge these features, allowing the network to model local structures and long-range dependencies concurrently. To enhance generalization across varied imaging conditions and tumor types, a domain discriminator is included to discern spatial and domain-specific patterns, fostering the learning of domain-invariant representations. The approach …

Spatiotemporal Dynamics Of Riparian Land-Cover Change And Impervious-Cover Expansion In A Rapidly Urbanising Himalayan Capital City, Karma Jamtsho, Tashi Dorji, David Blake, Mark A. Lund, Eddie Van Etten

Research outputs 2022 to 2026

Urbanisation and impervious-cover expansion are reshaping riparian landscapes, particularly in mountain cities where steep terrain concentrates development along valley floors. This study examined spatiotemporal land-cover change within the regulated riparian corridors of Thimphu City, Bhutan, over a 25-year period from 1997 to 2022 using Landsat imagery, Random Forest classification and Google Earth Engine. Results show substantial transformation of riparian land cover, with impervious cover increasing from 26.14% to 32.63%, equivalent to an overall increase of 24.83%, while agriculture/barren/low-vegetation declined from 30.59% to 26.01%, equivalent to an overall decrease of 14.98%. A modest increase in detectable vegetation cover was also observed, …

Thermal Transformation Of Organic Matter And Impacts On Water Quality In Fire-Affected Jarrah Forest, Kuenzang Tshering, David Blake, Andrea Bravo Escobar, Konrad Miotlinski, Andrew Bath, Mary C. Boyce, Pauline Grierson, Pierre Horwitz

Research outputs 2022 to 2026

Fire in forested catchments significantly alters organic matter fluxes by generating dissolved organic matter (DOM) different from that generated under non-fire conditions. Elucidating the composition of DOM is key to understanding its persistence in the post-fire environment. This laboratory study aimed to establish a relationship between DOM quantity and quality with aspects of fire regime. Soil and litter samples were collected from areas with different burn histories (described as Time Since Last Fire – TSLF). Each sample was subjected to burn temperature treatments simulating different burn severity regimes in a muffle furnace (at 250°C – low severity, 350°C – moderate …

Navigating Oer Support Without Drowning In Ai, Lydia Burrage-Goodwin, Christine Moynihan

Joseph P. Healey Library Publications

This was a presentation at the June 2026 Boston Library Consortium at Connecticut College.

UMB Healey Librarians Lydia Burrage-Goodwin and Christine Moynihan talk about what experiences they have had with faculty using OER and AI, which led them to develop ethics guidelines to support librarians who work with faculty authors. Attendees learned about creating AI use statements for OERs, using AI transparency logos, and applying open licenses to fully AI generated content as well as OER adaptations.

Modeling Generative Ai Adoption In Higher Education: An Integrated Tam–Tpb–Sdt Framework With Sem Validation, Dina Tbaishat, Omar Alfandi, Faten Hamad, Syed Muhammad Salman Bukhari, Suha Al Muhaissen

All Works

This study investigates the determinants of university students' adoption of generative artificial intelligence (GAI) tools in higher education. Integrating the Technology Acceptance Model (TAM), the Theory of Planned Behavior (TPB), and Self-Determination Theory (SDT), it develops and tests a complete model that captures cognitive, social, and motivational influences on adoption. A cross-sectional survey was conducted among 517 undergraduate and postgraduate students at Jordanian universities. The data were analyzed using structural equation modeling (SEM) with a two-step approach: confirmatory factor analysis (CFA) to validate the measurement model, followed by SEM to test the hypothesized structural relationships. Reliability, validity, measurement invariance across …

A Proactive Food Demand Forecasting-Inventory Management Approach Under Weather Disruptions, Asmaa Seyam, Sujith Samuel Mathew, May El Barachi, Jun Shen

All Works

Effective demand forecasting has become crucial to strengthening system resilience, reducing food waste, and achieving sustainability in food systems. Despite recent advances in leveraging machine learning for food demand forecasting, most existing models remain static and assume stable demand patterns, posing a challenge for adapting to demand changes during disruption events. This paper develops a proactive approach that leverages demand forecasting outputs and weather disruption flags to guide inventory replenishment, ensuring adaptability to varying demand conditions across three weather disruption events while reducing waste. This paper first uses a stacking model to predict next-day demand for a food retailer, leveraging …

From Ethical Principles To Executable Governance: A Policy-As-Code Framework For Trustworthy Ai In Higher Education, Edmund Evangelista, Syed M. Salman Bukhari

All Works

Artificial intelligence holds great potential to transform higher education, but a persistent gap remains between ethical aspirations and their practical, auditable enforcement. This study addresses that gap by developing and validating an end-to-end executable governance framework grounded in a policy-as-code (PaC) paradigm. Using student dropout prediction as a high-stakes example, the framework operationalizes governance through an automated gatekeeper, a multi-strategy fairness mitigation toolbox, and a tamper-evident audit chain for full reproducibility. The governance compliance was tested across sixteen fixed model configurations evaluated under five policy tiers (strict, medium, lenient, and two deployment-realistic variants). None were approved, as fairness violations, dominated …

The Association Between Ethical Ai Use And Well-Being Among Young Adults In The Uae: A Structural Equation Modeling Approach, Areej Elsayary, Zeina Hojeij, Lames Abdul Hadi

All Works

This study examines the association between ethical AI use and young people’s emotional, social, and psychological well-being in the United Arab Emirates (UAE), where the number of hours spent on GenAI serves as a moderator. Framed within the Theory of Planned Behavior and aligned with the Sustainable Development Goals (SDGs), particularly SDG 3 (Good Health and Well-being) and SDG 13 (Climate Action), this research examines how responsible digital engagement is associated with both individual mental health and broader digital sustainability. A Structural Equation Modeling approach assessed how ethical AI behaviors are associated with well-being. A total of 204 participants, predominantly …

How To Save The Take-Home Essay With Oral Assessments, Matthew Hammerton, Jacqueline Ho

Research Collection School of Social Sciences

In a commentary, the authors opined that pairing take-home essays with oral assessments is a more effective response to AI than policing its use. Students who cannot adequately explain their work can be marked down, reducing incentives to rely on AI. They noted that oral exams help preserve key elements of university education – intellectual effort, ownership, and human relationships – while allowing take-home essays to remain relevant in an AI-driven landscape that demands greater emphasis on understanding, responsibility, and dialogue.

Investigating An Energy-Preserving Spectral Finite Difference Numerical Method For A Wave Equation On The Metric Graph, Tue Minh Tran

University Honors Theses

To investigate the accuracy and long-term energy conservation of a spectral finite difference numerical method for a wave equation on metric graphs. In conservative systems, numerical methods should preserve total energy. However, explicit finite difference methods require impractically small space steps and exhibit energy drift at end points. To address these limitations, a spectral finite difference method is implemented using a Fourier transformation. This semi-spectral method improves stability at endpoints while maintaining second-order accuracy, achieving an overall error of O(∆t²). We implement the semi-spectral method on the IEEE14 metric graph and provide visuals showing the initial condition …

Modeling Turbulent Accretion Flows Around Black Holes: Azimuthal Flux Derivative Density Curves In 3d Mhd Simulations, Sasmitha Purushothaman, Matthew D. Duez, Pavan Chawhan

University Honors Theses

When modeling two-dimensional axisymmetric accretion disks around Kerr black holes, setting the azimuthal terms of the MHD equations to zero causes the loss of turbulence and dynamo effects. In this paper, we use three-dimensional models to identify the turbulence that arises from azimuthal flux derivatives (AFDs) and create probability density functions to characterize them. We establish a pipeline for calculating the AFDs, creating a distribution, and normalizing it. Then, we plot the dependence of the conditional probability of the AFDs on density, magnetic field strength, and velocity for the continuity and magnetic induction equations. Future research can take this information …

Comparing The Sensitivity And Degree Of Boolean Functions Via The Hypercube, Anne-Caroline Rupp

University Honors Theses

This thesis studies three complexity measures of total Boolean functions f:{0,1}ⁿ → {0,1}: maximum sensitivity s(f), polynomial degree deg(f), and spectral sensitivity λ(f), where λ(f) is defined as the spectral norm of the adjacency matrix of the sensitivity graph. Building on the results of Aaronson et al., we examine the inequality chain √s(f) ≤ λ(f) ≤ deg(f) and investigate whether all three quantities can be simultaneously equal.

The first part of the thesis reverse engineers the equality cases of the two known inequalities to isolate necessary extremal conditions on both the Fourier structure of f and the local geometry …

Applications Of Prior And Novel Computational Tools In Mental Health Treatment, And Their Potential To Uncover The Explanatory Gap, Ambika Vyas

University Honors Theses

The explanatory gap is a widely discussed concept in scientific and philosophical literature. In neuroscience, the solution to the explanatory gap is highly sought out, but the general consensus is that it is unsolvable. Numerous articles discuss the explanatory gap alongside computational tools and how these tools could aid neuroscientists in uncovering the mental health explanatory gap. However, significant developments in machine learning have been made since 2020, coinciding with the rise in Large Language Models (LLMs). This thesis is a literature review on computational methods, tools, and devices developed and utilized by researchers to improve how mental health disorders …

Developing A High-Resolution Off-Axis Common-Mode Digital Holographic Microscope, Lucy Cook

University Honors Theses

Off-axis digital holographic microscopy (DHM) is a powerful tool for 3D, non-invasive live-cell tracking without moving parts. However, traditional setups face an inherent dilemma: split-path interferometers offer high spatial resolution but poor temporal stability, while more stable common-mode configurations are historically limited to lower numerical aperture (NA) regimes. This thesis bridges that gap by scaling a common-mode DHM architecture into a high-resolution benchtop instrument featuring NA = 0.65 objectives, paired with a high-power 520 nm laser source to combat transmission losses and sustain imaging frame rates across an expanded optical footprint. We map the multi-variable design space required to satisfy …

Conello Vendor Marketplace Capstone: A Review On The Capstone Process And Computer Science Degree, Levi Hauck

University Honors Theses

This Capstone Review Thesis discusses the current structure of the Computer Science Degree path and Computer Science Capstone at PSU. This thesis reviews the Conello Vendor Marketplace Capstone, a project designed to help address the issue of teambuilding in the workplace. It points out ways in which teamwork and organization is an underdeveloped skill in Computer Science. During the Capstone project, the project management method of Agile development was recommended and used. However, it became clear that the team, leader included, had a gap in knowledge and skills to be successful, as well as a lack of experience in team …

Not Everyone Gets A Tree: Housing Values, Street Trees, And Equity In Portland, Matthew Moller

University Honors Theses

Street trees are positively associated with Portland home sale prices, but exposure and capitalization are uneven by race/ethnic neighborhood context. Urban trees are ecological assets, but their economic and equity implications remain uneven. This thesis examines street-tree exposure and 2023 residential sale prices in Portland, Oregon (n = 6,414) using a mixed-methodology hedonic design. Ordinary least squares models measure inventoried street-tree counts within 20m, 50m, and 100m buffers together with structural controls and census-block racial and ethnic context. Trees are positively and significantly associated with logged prices at all radii, with scale-sensitive magnitudes and modestly better fit as wider buffers. …

Shallow-Marine Crinoid Genera May Have Been More Resilient Across Permian Extinction Events In Terms Of Richness Than Deep-Marine Crinoid Genera, Amelia C. Kolstad

University Honors Theses

Throughout the Phanerozoic, one of the most successful phyla of marine invertebrates has been Echinodermata. Echinodermata was particularly successful throughout the Paleozoic, with class Crinoidea making up a majority of occurrences. The proportion of echinoderm occurrences that are crinoids declined massively at the end of the Permian and continued to decrease into modern day, never fully recovering. One of the factors thought to have been so important for crinoid success in the Paleozoic and their decreasing success throughout geologic time has been their propensity for success in shallow-marine environments, though crinoids also exist within deep-marine environments. This study seeks to …

Optimizing Fpga And Wafer Test Coverage With Spatial Sampling And Machine Learning: Analysis Of Local Spatial Consistency, Weiquan Wang, K. M.Shahriar Alam Adib, Foisal Ahmed, Riaz Ul Haque Mian

Research outputs 2022 to 2026

Wafer and FPGA testing remains costly in semiconductor manufacturing. This paper studies random sampling, stratified sampling, and k-means sampling under a partial-measurement setting with Gaussian Process Regression (GPR), and introduces Short Distance Elimination (SDE), a spatial screening rule that spreads selected training points over the layout. Combining value-based sampling with SDE yields two hybrid methods: S-SDE, which applies SDE within stratified subsets, and K-SDE, which applies SDE within k-means clusters. A calibration-based protocol fixes the value-group labels and SDE thresholds before target-file prediction. The SDE thresholds are selected from (Formula presented.) configurations in (Formula presented.), excluding (Formula presented.), using local …

Municipality Of Bayamón V. Exxon Mobil Corp. (2025): Bringing Racketeering Charges For Climate Justice, Ilinca C. Johnson

Pace Environmental Law Review

Environmental justice communities should have their climate change damages heard in the courtroom. One means to increase environmental justice claims is through claims under the federal Racketeer Influence and Corrupt Organizations (RICO) Act. Using Municipality of Bayamón v. Exxon Mobil Corp. (2025) as a model, this Article suggests a novel RICO case strategy to pursue climate damages for marginalized communities. Fundamentally, environmental justice RICO claims involve careful case design based on the climate-related damages a marginalized community has faced because of the long-term deception by fossil fuel actors upon those communities. Pursuing such claims forwards the intersectional issues faced by …

Assessing The Effectiveness Of Tilt-Informed Assessments In Calculus I, Samuel Horelick

Inquiry: The Journal of the Virginia Community Colleges

Transparent Design in Learning and Teaching (TILT) is widely promoted as an evidence-based framework intended to clarify expectations, promote equity, and improve student learning. While prior research reports positive outcomes across many disciplines, less is known about how transparency functions in quantitative, problem-solving courses such as calculus, where students often value efficiency and autonomy. This study examines the effects of a TILT-informed assignment redesign in two sections of Calculus I at a Virginia Community College System institution. One section completed a traditional assignment, while the other completed an equivalent task redesigned to make the purpose, task, and evaluation criteria explicit. …

Intervention Levers For Stunting Reduction In Indonesia: Evidence From The 2023 Indonesian Health Survey Data, Iwan Ariawan, Hafizah Jusril, Zahra Izza Afifa, Azka Fitri, Elmarizha Sekar Utami, Mikail Hasan, Dwi Puspasari

Kesmas

Stunting remains the largest public health challenge among macro-nutrition problems in Indonesia, affecting almost a quarter of children under five in 2023. The prevalence is considered high according to the World Health Organization standard. This study analyzed 15 aggregated provincial variables from the 2023 Indonesian Health Survey using Structural Equation Modeling (SEM), focusing on determinants of stunting among children under two to identify primary intervention levers. Findings indicated that intervention urgency should focus on the first 1,000 days, particularly the steep increase in stunting prevalence observed in the 12–24-month age range. While the highest prevalence is in Eastern provinces (e.g., …