Digital Commons Network^™

Evaluation Of Solar Reflective Pigments For Use In Direct-To-Metal Coatings, William J. Diment

Master's Theses

Solar reflective coatings offer a promising strategy to mitigate the urban heat island effect by reducing absorption of near-infrared solar energy. This thesis project investigates the feasibility of incorporating near-infrared reflective pigments into waterborne direct-to-metal (DTM) latex coating systems while maintaining acceptable color comparison characteristics and coating performance. An all acrylic latex DTM formulation with titanium dioxide as the sole pigment was prepared and tinted with a variety of conventional and solar reflective commercial colorants across the yellow, red, blue, and green color ranges. Coatings were evaluated for solar reflectance, CIELAB color, gloss, contrast ratio, rheological behavior, accelerated ultraviolet weathering …

High-Resolution Queries, Low-Resolution Context: Scaling Vision Transformers With Asymmetric Spatial Reduction, James M. Dwyer

Master's Theses

Vision Transformers (ViTs) have demonstrated great performance on image classifica tion benchmarks, however, the quadratic complexity of the self-attention mechanism with respect to sequence length limits their scalability to higher resolution inputs. The attention score matrix grows as O(N2) in both compute and memory, where N is the number of patch tokens, making ViTs computationally expensive and memory intensive for applications that require real-time inference or operate under resource constraints.

This thesis investigates whether the key and value sequences of the self-attention mechanism can be compressed using the local spatial structure of the image — while keeping queries at full …

Scorespeak: An Agentic System For Natural Language Control Of Musical Scores, Nathan S. Lim

Master's Theses

With the recent popularization of large language models (LLMs), natural language has become one of the most accessible and powerful ways for people to interact with creative tools. Although they have become common in mainstream domains like image and audio editing, there is currently no robust AI-based system that can reliably turn free-form language into edits for symbolic musical scores. This gap represents a missed opportunity to improve human workflows for creating and editing sheet music, but it is also a fundamental limitation for other agentic music systems; without a robust mechanism for translating free-form language into structured scores, AI …

Social Media Is A Juggernaut: Lagged Correlation Analysis Using Ngram Data On “Internet” And “Social Media” With Amplification By The Advent Of The “Iphone”, William Zywiak, Gao Niu, Nicolas Petrell, Victoria Nichele, Kirsten Hokeness

Mathematics and Economics Faculty Journal Articles

The amount of new information transmitted per day can be overwhelming. The data available through Ngram Viewer allows statistical examination to determine the most salient topics, as well as lagged correlation and lagged variance to support possible causal connections between concepts. Using this database, we determined that COVID, crypto, microplastics, and especially social media are important topics of the last few years. We also present results that suggest the development of the internet and the iPhone fueled the prominence of social media, and the access of the iPhone also increased access to the internet.

Constructing Orthonormal Bases With The Residuals Of Successive Approximations, An Introduction To Multiresolution Analysis, Elijah J. Guptill

Master's Theses

Wavelets and wavelet analysis are used in the study of signal processing, quantum field theory, functional analysis, multifractal analysis, and various other areas of mathematics. Multiresolution analysis provides a framework for building a wavelet basis of $\mathcal{L}^{2}(\mathbb{R})$ from a scaling function $\phi$, whose dyadic dilations and translations, $\{2^{j /2}\phi(2^{j}x-k):j,k\in \mathbb{Z}\}$, approximate $\mathcal{L}^{2}(\mathbb{R})$. One of the key properties of  $\phi$ is that it must satisfy $\phi(x)=\sum_{k\in \mathbb{Z}}{p_{k}2^{j /2}\phi(2^{j}x-k)}$ with respect to the norm on $\mathcal{L}^{2}(\mathbb{R})$. This equation is called a two-scale difference equation. Such equations enforce a regularity on the ordinary generating function $2^{-1 /2}\sum_{k\in \mathbb{Z}}{p_{k}z^{k}}$, known as the quadrature condition. …

Improving The Reliability And Performance Of A Supersonic Indraft Tube Wind Tunnel, Christian J. Kaml

Master's Theses

Access to supersonic testing is increasing in demand, and wind tunnels remain one of the safest and most cost-effective methods for gathering high-speed flow data. Despite being more economical than alternative options, supersonic wind tunnel facilities often require substantial investment to construct, operate, and maintain.

The novel indraft tube tunnel architecture was conceived as a high-speed flow testbed that incorporates features of both Ludwieg tubes and indraft wind tunnels to maintain costs low enough to be accessible even to small universities. This design was first developed and tested in 2018 at California Polytechnic State University, featuring a cost per test …

An Evaluation Of Road Network Structure As A Predictor Of Traffic Volume, Colin M. Mcdonald

Master's Theses

This thesis evaluates the relationships between various graph theory metrics and taxi traffic volume for the cities of San Francisco, California and Porto, Portugal. We also evaluate a modified betweenness centrality metric which incorporates the count of distinct origin-destination pairs from the taxi data as the weight function. This thesis extends a paper by Pengyao Ye, Bo Wu, and Wenbo Fan by reducing circularity through a temporal train-test split and by comparing both line-graph and primal-graph formulations of betweenness centrality.

We found that past traffic volume is almost perfectly correlated with future traffic volume and that the modified betweenness centrality …

2026 Cyber-Resilient Health Care Workshop Report, Malcolm Schongalla, Sergey Bratus

Computer Science Technical Reports

The ISTS and the Dartmouth College Cybersecurity Cluster hosted the successful, inaugural Cyber-Resilient Health Care (CRHC) Workshop, March 5th & 6th, 2026. The event theme was "Innovation and Implementation," in response to the need to shift from reactive to proactive resiliency measures in the healthcare sector. Approximately 30 experts in clinical health care, cybersecurity, medical technology, policy, and innovation met to discuss solution-focused innovations addressing hard, cyber-related problems in health care. The agenda featured keynotes, an expert panel, innovation pitches, small group discussions, and a tabletop infrastructure disaster exercise. Participants gained insights into the obstacles and solutions involved in supporting …

(R2133) Analysis Of A Bulk Queue With Balking, Adaptive Overloading Service, Multiple Vacation, Inspection And Rework, S. Karpagam, R. Lokesh

Applications and Applied Mathematics: An International Journal (AAM)

We consider a queueing system that utilizes a single server to manage product flow through bulk and overload service modes, depending on queue length. Balking occurs when the queue length reaches ‘N’. After completion of service, products undergo quality inspection, with defective products sent for rework based on specific probabilities. If the product is non-defective, the server continues processing until the queue length exceeds a certain threshold; beyond this point, the server is either routed back to bulk service or directed to an overload service. Also, the server goes into a vacation mode when the queue size is below a …

Fairlinked: Data Fairification Tools For Materials Data Science, Van D. Tran, Brandon Lee, Ritika Lamba, Henry Dirks, Quynh D. Tran, Balashanmuga Priyan Rajamohan, Ozan Dernek, Laura S. Bruckman, Yinghui Wu, Erika I. Barcelos, Roger H. French

Student Scholarship

FAIRLinked is a software package created to support the FAIRification of materials science data, ensuring proper alignment with FAIR principles: Findable, Accessible, Interoperable, and Reusable. It is built to be compatible with MDS-Onto, an ontology designed to capture the semantics of various types of materials data, enabling integration and sharing across different research workflows. The package is subdivided into three subpackages: InterfaceMDS, RDFTableConversion, and QBWorkflow. The first subpackage, InterfaceMDS allows users to search for terms using either string search or various filters, explore different domains and subdomains, and add terms to MDS-Onto. RDFTableConversion is used for serialization and deserialization of …

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 …

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 …

Spatiotemporal Pah Patterns In Size-Fractionated Particles (Pm>10-Pm0.1) From Northern Thailand Biomass Burning Via Sentinel-2, Phakphum Paluang, Watinee Thavorntam, Sarawut Sangkham, Phuchiwan Suriyawong, Hisam Samae, Thaneeya Chetiyanukornkul, Masami Furuuchi, Worradorn Phairuang

Research outputs 2022 to 2026

Biomass burning, particularly from forest fires and crop residue burning during the dry season, is a major source of particulate pollution across many Asian countries. However, accurately identifying these emissions remains challenging due to uncertainties in burned area estimation and the limited availability of country-specific emission factors. This study quantified the spatiotemporal distribution of emissions from biomass burning using satellite imagery. Burned areas were classified using a random forest (RF) algorithm implemented on the Google Colaboratory (Colab) platform. The RF model showed strong performance, with a kappa coefficient of 0.85 and an average accuracy of 0.81. Emission estimates for the …

Western Kentucky University Stormwater Utility Survey 2026, Warren Campbell

SEAS Faculty Publications

In the U.S., more than 2200 stormwater utilities have been enacted. This year, we have expanded the survey to include stormwater utilities in other countries. Many of these stormwater assessments are called taxes, but if the assessment is recurring, is not an ad valorem tax, and is dedicated to stormwater purposes, we call it a stormwater utility. With the help of ChatGPT we have been able to identify 25 stormwater fees in Australia. We were also able to identify 3 in New Zealand, and some in Europe as well.

Shared Language For Responsible Ai Integration, Asa B. Stone, Mark C. Stone, Alisha Bevins, Jean Claude Niyomugabo, Irene Magara, Jacob Abaare, Derek M. Heeren, Mubarak Abu Zouriq

PRAIRIE: Pioneering Responsible AI for Research, Innovation, and Education

As AI rapidly reshapes how we work and learn, employers increasingly seek graduates who can think before they prompt, exercising judgment under pressure rather than merely producing output. Yet students are praised for AI use in one course and penalized for it in the next, and faculty are left to lead responsibly on shifting ground, with no shared language to guide them.

This paper introduces the PRAIRIE Framework for AI Integration, a shift from reactive gatekeeping toward proactive stewardship. It emerged from a qualitative sentiment analysis of three communities (students, faculty, and industry partners) whose concerns converged on one need: …

What Collaboration Means To Me: From Coordination To Collective Action: Cclp And Cyclops As Infrastructure For Collaborative Collection Stewardship, Boaz Nadav-Manes

Collaborative Librarianship

Academic libraries face growing pressure to manage complex collections under significant resource constraints. While consortial collaboration has long been recognized as a strategic response, existing models remain limited, often failing to influence the full collections lifecycle. This article examines how the Collaborative Collections Lifecycle Project (CCLP) and the Cyclops platform together offer a new model for moving beyond coordination toward genuine collective action in collection stewardship. CCLP provides a community-governed framework structuring collaboration from selection and acquisition through preservation and deaccessioning, while Cyclops complements it with an open, analytics-driven infrastructure that aggregates data across institutions, enabling cross-institutional analysis and translating …

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 …

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, …

Final Butte Priority Soils Operable Unit (Bpsou) Unreclaimed (Ur) Sites New And Mahoney (Ur-23) Construction Completion Report (Ccr), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Validation Of Electromagnetic Shower Development In A Reduced Alice Focal-E Detector Model Using Geant4, Isaac Lara Romo

Physics

This project focuses on the preliminary simulation of a reduced FoCal-E detector model for the ALICE experiment at CERN. Beamline tests were simulated using an electron gun at various incident energies, and the results were compared with those of the FoCal group. The longitudinal charge deposition per sensor layer was compared between the two setups to verify that the reduced model exhibited expected calorimeter behavior. Additionally, the transverse signal across the high-granularity sensor layers was examined to determine whether the reduced model reproduced the expected lateral development of electromagnetic showers. The results obtained from these measurements show that the reduced …

Hydpn: A Hybrid Deep Reinforcement Learning, Programming, And Neighborhood Operations Framework For Integrated Scheduling On Parallel Batch Processing Machines, Yuqi Wang, He Luo, Guoqiang Wang, Zhaoxia Wang

Research Collection School Of Computing and Information Systems

Batch processing machines (BPMs) are widely used in industries such as semiconductors, metal processing, and healthcare, where jobs are processed in batches. As production, inventory, and distribution become increasingly integrated to improve efficiency, research on their joint scheduling in parallel BPM environments remains scarce. This paper addresses the integrated scheduling problem in parallel BPMs, involving production, inventory, and distribution stages, with the objective of minimizing total costs. A unified cost-based model is first formulated, applicable to both in-facility and external distribution scenarios. A hybrid algorithm framework, HyDPN, combining deep reinforcement learning, dynamic programming, and neighborhood operations is proposed. Extensive experiments …

On-The-Fly Generation-Quality Enhancement Of Deep Code Models Via Model Collaboration, Weifeng Sun, Naiqi Huang, Meng Yan, Zhongxin Liu, Hongyan Li, Yan Lei, David Lo

Research Collection School Of Computing and Information Systems

The growing prominence of deep code models in automating software engineering tasks is undeniable. However, their deployment encounters significant challenges in on-the-fly performance enhancement, which refers to dynamically improving the performance of deep code models during real-time execution. Conventional techniques, such as retraining or fine-tuning, are effective in controlled pre-deployment scenarios but fall short when adapting to on-the-fly adjustments post-deployment. CodeDenoise, a notable on-the-fly performance enhancement technology, leverages uncertainty-based methods to identify misclassified inputs and applies an input modification strategy to rectify classification errors. While effective for classification tasks, this approach is inapplicable to generative tasks due to two key …

Interfold: Learning Interpretable Diffusion Manifolds Beyond Binary Samples, Alexander Vincent Lewi, Rainer Tan, Shengfeng He

Research Collection School Of Computing and Information Systems

We propose InterFold, a framework for learning and applying interpretable semantic manifolds in latent diffusion models, without requiring binary or paired supervision. Existing methods for semantic editing either rely on limited paired data or uncover only coarse, unsupervised directions that fail to capture user-specific, fine-grained attributes. InterFold addresses these limitations by learning a target attribute manifold in the H-space of diffusion models using only a set of positive, unlabeled examples. To edit a new image, InterFold projects its H-space representation toward this learned manifold through test-time optimization, enabling precise, identity-preserving modifications of complex, non-binary concepts. To make these edits effective …

Sok: Understanding Zkvm: From Research To Practice, Guomin Yang, Yunbo Yang, Yuejia Cheng, Haibo Tang, Bingsheng Zhang, Kui Ren

Research Collection School Of Computing and Information Systems

Zero-knowledge virtual machine (zkVM) is a powerful infrastructure for proving the correctness of a program execution with a succinct proof, attracting significant interest from researchers, developers, and users. It has been widely used in applications such as blockchain rollups, privacy-preserving machine learning, and off-chain computation. As the field grows, a wide range of zkVMs have been proposed. However, they adopt different choices in instruction formats, trace layouts, and proving backends, which results in a highly heterogeneous design landscape and makes it difficult to understand the relations among these systems.To bridge this gap, we provide a comprehensive study of zkVMs that …

Vehicle-Based Multi-Services For Future Smart Cities, Hao Sun, Jinhua Zhao, Hai Yang, Shenhao Wang, Hamsa Balakrishnan, Thomas W. Malone, Hai Wang

Research Collection School Of Computing and Information Systems

Vehicles are crucial for sustaining socioeconomic activity and improving quality of life in modern cities by offering diverse services. These include passenger mobility, goods delivery, information acquisition, and acting as mobile servers such as food trucks and mobile lockers. At the same time, they also contribute to traffic congestion and air pollution. This tension fosters the rise of urban resource-conserving and sustainable service solutions. In this article, we introduce the concept of “Vehicle-Based Multi-Services” (VeMuS), in which a single vehicle offers multiple services simultaneously. Drawing on practical use cases, we examine service classification and integration for vehicles and the potential …

Esg Reporting Lifecycle Management With Large Language Models And Ai Agents, Thong Hoang, Mykhailo Klymenko, Xiwei Xu, Shidong Pan, Yi Ding, Xushuo Tang, Zhengyi Yang, Jieke Shi, David Lo

Research Collection School Of Computing and Information Systems

Environmental, Social, and Governance (ESG) standards have been increasingly adopted by organizations to demonstrate accountability towards ethical, social, and sustainability goals. However, generating ESG reports that align with these standards remains challenging due to unstructured data formats, inconsistent terminology, and complex requirements. Existing ESG lifecycles provide guidance for structuring ESG reports but lack the automation, adaptability, and continuous feedback mechanisms needed to address these challenges. To bridge this gap, we introduce an agentic ESG lifecycle framework that systematically integrates the ESG stages of identification, measurement, reporting, engagement, and improvement. In this framework, multiple AI agents extract ESG information, verify ESG …

Inverse Modeling The Geo-Spread Of Covid-19 In Brazil, Cameron Keith Mills

ETDs from 2020-2029

In 2021 Fitzgibbon, Morgan, Webb, and Wu used a modified SEIR (susceptible, exposed, infected, and recovered) model to predict how COVID-19 spread through Brazil [12]. For their model, six constant coefficients were used that were fitted, referenced, or assumed. In this thesis, we geo-spatially modify their SEIR model and formulate an inverse problem to recover the now spatial coefficients of the model. We first show there exists a unique solution to the modified model. To solve the inverse problem, we modify an inverse method [17] that focused on minimizing convex functionals. These recovered spatial coefficients can be used with Matlab’s …

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, …

Investigation Of Warfarin–Human Serum Albumin Binding By Ultrafast Affinity Extraction Using Single- And Dual-Column Affinity Microcolumn Systems, Samiul Alim

Department of Chemistry: Dissertations, Theses, and Student Research

This dissertation examined the interaction of warfarin with human serum albumin (HSA) by using affinity chromatography, with particular emphasis on ultrafast affinity extraction (UAE) and affinity microcolumns. HSA affinity supports were prepared by immobilizing HSA onto diol-bonded silica via Schiff base chemistry and used to prepare affinity microcolumns for chromatographic studies under physiological-like conditions at pH 7.4 and 37.0 °C. UAE studies were performed to investigate the effects of residence time, flow rate, and column configuration on the measured apparent free fraction of warfarin and on the calculated apparent binding parameters. The results showed that the measured apparent free fraction …

Pso-Style Social Influence In An Ant Colony Algorithm For Continuous-Domain Optimization, Ashraf M. Abdelbar, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

ACOR is a well-established Ant Colony Optimization (ACO) algorithm for continuous-domain optimization. In this paper, we propose an extension (which we call ACOR∗) in which several fundamental modifications are made to ACOR's solution construction process, including the incorporation of a social influence mechanism borrowed from Particle Swarm Optimization (PSO). Our modifications to the ACOR algorithm are intended to promote search diversity and combat premature convergence. We experimentally evaluate our proposal in the context of training feedforward neural networks for classification using 65 widely used datasets from the University of California Irvine (UCI) repository, as well as the optimization of several …