Physical Sciences and Mathematics Commons^™

Using Remote Sensing Technology To Develop A Framework For Improving Hydrologic Models, Marissa Cook

Theses, Dissertations and Capstones

With increased storm intensity due to climate change and urbanization, flash flooding has become an increasingly significant issue globally and regionally. Although the factors influencing urban flash flooding are well-known, there is a growing need for technology to accurately and remotely predict the chance of a flash flood occurring from any given rain event to give people time to prepare. This study aims to use multispectral satellite imagery to provide a framework for improving near real-time flood predictions in an urban area of a high gradient, fourth order stream impacted by flooding. Specifically, we utilize satellite imagery to create the …

A Variance Decomposition Approach To Inconclusives In Forensic Black Box Studies, Amanda Luby, Joseph B. Kadane

Mathematics and Statistics Faculty Work

In the USA, ‘black box’ studies are increasingly being used to estimate the error rate of forensic disciplines. A sample of forensic examiner participants is asked to evaluate a set of items whose source is known to the researchers but not to the participants. Participants are asked to make a source determination (typically an identification, exclusion, or some kind of inconclusive). We study inconclusives in two black box studies, one on fingerprints and one on bullets. Rather than treating all inconclusive responses as functionally correct (as is the practice in reported error rates in the two studies we address), irrelevant …

Paleo-Environmental Change In Deer Lagoon, Whidbey Island Interpreted From Diatoms And Lithology, Lourdes Garcia

All Master's Theses

Puget Sound is a densely populated, tectonically active area that can be affected by earthquakes from local crustal faults and the Cascadia subduction zone capable of producing abrupt coseismic subsidence. Tidal wetlands are particularly sensitive to abrupt changes because they are depositional environments that reside at sea-level and their lithology and ecological communities are strongly controlled by elevation within the tidal frame. As a result, coseismic subsidence can disrupt established environmental gradients and leave distinguishable signatures preserved within the stratigraphy, like tidal mud directly over peat deposits. These preserved records provide an opportunity to reconstruct past earthquakes and associated relative …

The Geomorphology And Hydrogeology Of Pre-Restoration West Fork Teanaway River, Wa, Usa, Shana M. Egan

All Master's Theses

The West Fork Teanaway (WFT) River in Kittitas County, WA is an entrenched bedrock river channel with disturbed floodplain geomorphology and degraded riparian ecology. Two stream restoration approaches, “stage 0” valley bottom reset and engineered logjam installation, will be installed at the WFT in summer 2026 by collaborators at the Washington State Department of Fish and Wildlife and Mid-Columbia Fisheries Enhancement Group. The objective of this study was to constrain the pre-restoration geomorphic and hydrologic conditions of the WFT. The WFT has an unconsolidated floodplain aquifer of predominantly coarse-grained fluvial deposits. Monitoring of groundwater and surface water levels began in …

Understanding The Cost Of Catastrophe: Wildfire Suppression Costs Drivers By Fire Size Class, Stephanie Overla

All Master's Theses

While most wildfires burn less than 100 acres, the western United States experiences much larger fires annually, placing increasing pressure on suppression resources. Changes in weather patterns, fuel composition, and the spatial complexity of human development have rapidly altered historic fire regimes, increasing both the frequency of large wildfires and the challenges of managing them. This study compares two wildfire classes—Fires of Unusual Size (FOUS, >90,000 acres with at least one rapid growth event), and Large Fires (LF, 25,000–90,000 acres), —to identify differences in how size- and growth-based fire classes influence wildfire suppression costs. Suppression cost data for 60 …

Pre-Eruptive Timescales Via Olivine Diffusion Chronometry For Lava And Tephra Of The Schreibers Meadow Cinder Cone Eruption, Mount Baker (Kulshan), Wa, Sabrina Ansari

All Master's Theses

Mount Baker is a very-high threat Cascade volcano and is located near densely populated areas in northern Washington, putting many at risk if an eruption were to occur. Schreibers Meadow cinder cone is located on the southern flank of Mount Baker and produced the Sulphur Creek (SC) tephra and lava 9.8 ka. Previous work on the SC eruption used petrology and geochemistry to reconstruct the pre-eruptive magmatic architecture beneath Mount Baker Volcanic Field, including olivine-hosted melt inclusions to determine crystallization pressures, as well as plagioclase- and clinopyroxene-derived diffusion timescales to determine magma storage timescales of several months and recharge-to-eruption timescales …

Floodnet Methodology For Determining Flood Sensor Locations, Polly Pierone, Véronëque Ignace, Hannah Eisler Burnett, Hayley Elszasz, Brett F. Branco, Andrea Silverman

The Science and Resilience Institute at Jamaica Bay, SRIJB

FloodNet NYC is a collaboration between the City University of New York (CUNY), New York University (NYU) and NYC government agencies. In 2022, the NYC Department of Environmental Protection (NYC DEP) funded FloodNet NYC to install up to 500 flood sensors across New York City (NYC) by the end of June 2027. To meet this goal, FloodNet developed and continued to refine a flood sensor placement methodology to ensure the usefulness of sensor data for flood response, preparedness, mitigation, and overall resilience. Members of the FloodNet team from both technical and community-facing aspects of the project worked together to develop …

Tracking Co2 Illinois Ccs Monitoring Wells, University Of North Dakota. Energy And Environmental Research Center

EERC Brochures and Fact Sheets

Fact sheet about the Illinois carbon capture and storage (CCS) project. Includes information on the project's CO₂ monitoring system.

Future Mining: Learning For Safety And Security, Md Sazedur Rahman, Mizanur Rahman Jewel, Sanjay Madria

Computer Science Faculty Research & Creative Works

Mining industry is rapidly transforming into an AI-driven cyber-physical ecosystem where safety and operational reliability depend on robust perception, resilient communication, trustworthy distributed intelligence and continuous monitoring of miners and equipment. Real-world mining environments impose severe constraints like poor illumination, dust, occlusion, GPS-denied conditions, irregular underground topologies, and intermittent connectivity. These factors degrade perception quality, disrupt situational awareness, impair trajectory prediction and weaken the reliability of distributed learning systems. Emerging cyber-physical threats, including backdoor triggers, sensor spoofing, label-flip attacks and poisoned model updates, further jeopardize operational safety, particularly as mines increasingly adopt autonomous vehicles, humanoid assistance, and federated learning for …

Dynamic Hub-Aware Knowledge Distillation For Efficient Traffic Flow Forecasting, Xiangjie Kong, Can Shu, Wenchao Weng, Zhenzhen Zhao, Guojiang Shen, Lei Wang, Sajal K. Das

Computer Science Faculty Research & Creative Works

Real-time traffic forecasting acts as a critical enabling service for IoT-driven Intelligent Transportation Systems (ITS). While existing Spatiotemporal Graph Neural Networks (STGNNs) achieve superior forecasting accuracy, their intensive computational complexity and high latency create a deployment bottleneck for resource-constrained IoT edge devices. To address this resource-accuracy mismatch, we propose a novel framework termed Dynamic Hub-Aware Knowledge Distillation (DHKD). Unlike traditional uniform distillation paradigms, DHKD introduces a topology-aware strategy to transfer knowledge from a complex teacher to a lightweight Spatiotemporal Multi-Layer Perceptron (STMLP) student model. Specifically, we design a dynamic hub-aware gating (DHAG) mechanism that adaptively identifies time-varying pivotal sensing nodes …

Digital Twin Freshness Maximization In Edge Computing, Jing Li, Jianping Wang, Weifa Liang, Quan Chen, Sajal K. Das, Xiaohua Jia

Computer Science Faculty Research & Creative Works

Mobile Edge Computing (MEC) shifts powerful computing resource provisioning from remote powerful data centers to the edge of core networks. Meanwhile, Digital Twin (DT) has surfaced as a promising technology to provide comprehensive and dynamic descriptions of physical objects in cyberspace with bidirectional and real-time interactions. Moreover, Internet of Things (IoT) devices have contributed abundant, heterogeneous and continuous data from interconnected devices to the explosion of DTs. With technologies evolution, there is an increasing necessity to address the freshness of both DT states and DT data, through timely synchronizations between DTs and their objects in a highly dynamic IoT environment. …

Feddot: Defending Federated Learning Against Overwhelming Targeted Attacks, Priyesh Ranjan, Ashish Gupta, Federico Coro, Sajal K. Das

Computer Science Faculty Research & Creative Works

Federated Learning (FL), which facilitates collaborative model training and protects users' privacy, has drawn great interest from the research community. With FL, participants train their models on local data and submit the corresponding updates for aggregation to a server. While concealing the identities of the participants, FL may attract adversaries in order to hamper the underlying model. In this paper, we propose an FL framework, FedDOT, to defend against adversaries performing targeted attacks. FedDOT incorporates two powerful defense algorithms, Maximum Spanning Tree based attacker detection (MSTAD) and Densest graph-based attacker detection (Density-AD), which leverage correlation between weight updates and graph …

Utility-Preserving Federated Graph Learning With Dual-Perspective Fairness, Renqiang Luo, Huafei Huang, Shuo Yu, Fengqi Yu, Feng Xia, Sajal K. Das, Chengqi Zhang

Computer Science Faculty Research & Creative Works

Fairness-aware federated graph neural networks (FedGNNs) necessitate consideration of both the server and the clients. However, fairness-aware methods struggle to enhance dual-perspective (i.e., server and clients) fairness without sacrificing utility due to the distributed learning framework. As a consequence, the utility sacrifices of fairness-aware graph learning methods are even exacerbated in federated frameworks. In this work we propose F3GL, a dual-perspective fairness federated graph learning method that enhances both global (for the server) and local fairness (for clients) while preserving utility. Through theoretical analysis, we delineate the similarity between original sensitive features and those after convolution under different spectra. Our …

Escher: Efficient And Scalable Hypergraph Evolution Representation With Application To Triad Counting, S. M. Shovan, Arindam Khanda, Sanjukta Bhowmick, Sajal K. Das

Computer Science Faculty Research & Creative Works

Higher-order interactions beyond pairwise relationships in large complex networks are often modeled as hypergraphs. Analyzing hypergraph properties such as triad counts is essential, as hypergraphs can reveal intricate group interaction patterns that conventional graphs fail to capture. In realworld scenarios, these networks are often large and dynamic, introducing significant computational challenges. Due to the absence of specialized software packages and data structures, the analysis of large dynamic hypergraphs remains largely unexplored. Motivated by this gap, we propose ESCHER, a GPU-centric parallel data structure for Efficient and Scalable Hypergraph Evolution Representation, designed to manage largescale hypergraph dynamics efficiently. We also design …

Beyond Full Fine-Tuning: The New Playbook For Adapting Deep Neural Networks, Cristian S. Mcgee

Honors Undergraduate Theses

Fine-tuning is the process of teaching and specializing a pre-trained neural network on a downstream task. Fine-tuning is a rapidly growing topic in artificial intelligence domains; however, many fine-tuning endeavors are highly specialized without a coherent framework connecting them. This work presents a unified perspective on fine-tuning methods and performance metrics. Our perspective organizes the methods in terms of how they are applied to fine-tuning. This framework showcases methods that (i) update effective subspaces of the pre-trained model, (ii) change the adaptation optimization procedure, and (iii) alter the representations of the embedded input. Additionally, we present unconventional metrics such as …

Deep Learning Approaches For Voltammetric Analysis Of Coffee, Ryan Koes

Honors Theses

This thesis investigates deep learning approaches for voltammetric analysis of brewed coffee using a low-cost electrochemical system and screen-printed electrodes (SPEs). Traditional analytical methods, such as high-performance liquid chromatography (HPLC) and gas chromatography-mass spectrometry (GC-MS), provide precise quantification of key compounds but require expensive instrumentation and specialized expertise, limiting accessibility. While SPEs offer a more accessible alternative, they yielded poor results with traditional processing; however, when combined with a neural network, the system proved more effective. In experiments with 132 coffee samples, mean errors for caffeine, CGA, and TDS predictions were 52.98 ppm, 70.48 ppm, and 0.08%, respectively. These findings …

Sedimentology, Paleontology, And Depositional Environments Of The Upper Devonian Lock Haven Formation In West Burlington Quarry, North-Central Pa, Michael Harman

Honors Theses

The Upper Devonian Lock Haven Formation in north-central Pennsylvania preserves evidence of significant climactic and evolutionary transitions, including the fin-to-limb transition and initial arborescence. The formation contains abundant sedimentary features, palynomorphs, trace fossils, and fish body fossils, making it crucial for reconstructing these paleoenvironments. However, integrated studies on the Lock Haven Formation are rare. This study characterizes the depositional environments, ichnology, paleontology, and age of the Lock Haven Formation. A recent exposure at the Insinger-Ward West Burlington Quarry reveals three middle to early late Famennian lithofacies associations (FAs). FA1 consists of red sandstone, shale, and mudstone containing rhizoliths (deeply penetrating …

Utilizing Computer Modeling To Optimize Electric Fields Within Xenon Time Projection Chambers, Miles Meloni

Honors Theses

XENONnT is a physics experiment designed with the goal of detecting dark matter particles. The detector is a time projection chamber; a series of charged electrodes creates an electric field, surrounding a central body filled with liquid and gaseous xenon. Photomultiplier tubes (PMTs), positioned on either end of the chamber, serve to detect light signals. We seek to minimize the root mean square of the electric field norms experienced by the PMTs. This quantity corresponds to the variance in the electric field observed by the PMTs. Establishing a consistent electric field is important to maintaining these sensitive components. The electric …

Inequality In The Urban Forest: Modeling Tree Canopy Dynamics Through Demographics And Restoration Strategies, Eve Johansson

Honors Theses

Urban tree canopies play an important role in environmental quality, public health, and neighborhood livability, yet their distribution is highly uneven and often reflects historical patterns of inequality. In Brooklyn, long-term processes such as redlining, uneven development, and demographic change have contributed to persistent disparities in access to green space.

This thesis examines how urban tree canopy evolves across space and time in Brooklyn and how different restoration strategies affect long-run outcomes. The analysis uses demographic and canopy data from 1990-2020, considering race, income, employment, and educational attainment. Among these, education is the most consistent predictor of canopy coverage, with …

A Web-Based Wizard-Of-Oz Platform For Collaborative And Reproducible Human-Robot Interaction Research, Sean O'Connor

Honors Theses

The Wizard-of-Oz (WoZ) technique is widely used in Human-Robot Interaction (HRI) research, but two persistent problems limit its effectiveness: existing tools impose technical barriers that exclude non-engineering domain experts (the Accessibility Problem), and the fragmented landscape of robot-specific implementations makes interaction scripts difficult to port across platforms (the Reproducibility Problem- concerning execution consistency and portability, not third-party replication). Through a literature review, I identified three design principles to address both: a hierarchical specification model, an event-driven execution model, and a plugin architecture that decouples experiment logic from robot-specific implementations. I realized these principles in HRIStudio, an open-source, web-based platform providing …

Barriers To Immunity: Understanding Covid-19 Vaccine Uptake In Africa, Emilia Blechschmidt

Honors Theses

This thesis examines the factors influencing COVID-19 vaccine uptake across African countries, with a focus on structural, informational, and behavioral barriers to immunization. Drawing on cross-country data, the study analyzes how access to transportation, reliable information, and healthcare resources shape vaccination rates, alongside the effect of demographics and institutional factors in shaping individual perceptions of risk and vaccine safety.

The findings emphasize that the broader strength and preparedness of national health systems strongly influence vaccine uptake. Countries that demonstrated higher coverage of routine childhood immunizations, such as polio and hepatitis B, also tended to perform better in COVID-19 uptake efficiency …

Group-Based Integer Factorization: Theory And Performance, Phuong Cao

Honors Theses

Integer factorization, the problem of finding a nontrivial factor of a composite integer N=pq for large primes p,q, particularly at the size of RSA moduli, is a notoriously difficult challenge that takes classical methods such as Trial Division and Fermat’s Algorithm trillions of years to solve. This thesis studies four probabilistic algorithms that exploit algebraic group structures to achieve significantly better, subexponential efficiency for certain classes of N: Pollard’s p-1, Williams’ p+1, Lenstra’s Elliptic Curve Method, and Pell’s Conic Method. In each case, the algorithm operates on a group over ℤ/Nℤ that decomposes, via the Chinese Remainder Theorem, into corresponding …

Paleoflood Chronology For The West Branch Of The Susquehanna River Using Abandoned Chute Channel Sediments, Pennsylvania, Usa, Juliette A. Vanluven

Honors Theses

Anthropogenic climate change is altering the hydrologic cycle, increasing flood frequency and severity, with associated increased risks in population exposure. This is associated with increasing risks to the population of the Susquehanna River Valley, which supports over 600,000 people today. However, our understanding of the frequencies of large floods is limited by relatively short instrumental records. By studying sediments from an abandoned chute channel in the Robert Allen Natural Area near Williamsport, PA, we can extend the existing flood records using paleoflood slackwater sediments along the West Branch of the Susquehanna River.  Sylvan Dell is an abandoned chute channel that …

Sedimentological Characterization Of Main And Chute Channel Scroll Bars Along The Kantishna River, Alaska, Cooper Sentz

Honors Theses

Scroll bars, arcuate sediment ridges found along the inner banks of river bends, are common floodplain features in meandering river systems that form during lateral channel migration. Two hypothesized formation mechanisms described in prior studies are the aggradation of suspended load onto abandoned inner bank levee (IBL) deposits during overbank flow and the migration of transverse bar packages from the channel bed up onto the point bar during flooding events. To study the sedimentology and geometry of these features, we conduct remote sensing and field analysis on a 60 km portion of the Kantishna River, AK: a highly sinuous, pro-glacial …

Anuran Occupancy Of Created Wetlands Within Reforested Legacy Surface Mines In Kentucky And West Virginia, Jillian C. Newman, Steve Price, Jacquelyn C. Guzy, Joshua Castle, John J. Cox, Jeffery L. Larkin, Christopher D. Barton

Forestry and Natural Resources Faculty Publications

Restoration of habitat is an important component of wildlife management. Surface coal mining has altered forest cover in the Central Appalachians, and most reclamation activities on previously mined lands result in non-native grasslands or shrub lands. The Forestry Reclamation Approach (FRA), which emphasizes non-native vegetation removal, soil decompaction, planting of native trees and shrubs, and, in some cases, wetland creation represents an alternative to grassland-based reclamation that may promote forest-associated wildlife on legacy surface mines. We used automated recording units to evaluate the response of anurans to created wetlands and the FRA in Kentucky and West Virginia, USA. We used …

Law Librarianship And Legal Information Science In The Age Of Genai, Paul D. Callister

Faculty Works

This article examines the relationship between law librarianship and legal information science in the age of generative AI (GenAI), arguing that closer integration between the two is essential to navigating a rapidly evolving legal information landscape. It contends that law librarianship—long grounded in stable classification systems and cognitive authority—must adopt the analytical methods of legal information science to remain effective in the digital era. Together, these fields can reinforce the rule of law by improving the organization, retrieval, and stability of legal information. The article identifies emerging subfields of legal information science that support this integration and develops several concepts …

Deep Crustal Boundaries As Fluid Conduits: A Geochemical Investigation Of Mvt Mineralization In Kentucky And Beyond, Dairian Boddy M. Boddy

Theses and Dissertations--Earth and Environmental Sciences

Critical minerals are vital to the United States economy and national security, yet their supply chains are at risk. Common minerals in Mississippi Valley-type (MVT) deposits, such as sphalerite, galena, fluorite, and barite, host critical metals such as barium, gallium, germanium, and zinc, which are essential for energy technologies. An investigation of three MVT mineral districts in Kentucky elucidated previously unrecognized systematics, genetic relationships, and sources of ore components using stable and radiogenic isotope geochemistry, particularly from galena, sphalerite, barite, and gangue minerals (e.g., carbonates). The localization and dominant type of mineralization in each district are potentially influenced by deep …

Using Grounded Iceberg Wake Patterns To Interpret Catastrophic Flood Events In Southcentral Alaska, Jana K. Macinnis

All Master's Theses

Catastrophic flood events such as landslide tsunamis and jökulhlaups in glaciated areas can transport and strand icebergs, which obstruct the flow of floodwaters and leave a unique and recognizable grounded iceberg wake pattern in the sediment surface. Grounded iceberg wake patterns (GIWs) were identified at the two study areas in Southcentral Alaska; the outwash plain of a 1967 landslide tsunami at the Grewingk Glacier and proglacial lake, and the Matanuska River valley which experienced an unrecorded jökulhlaup in recent geological times. From these sites, 110 GIWs were identified through visual interpretation of lidar imagery and characterized by measuring their geometry, …

A Nonstandard Exploration Of Approximate Identity And Unitization, Tong (Nicole) Wu

HMC Senior Theses

The goal of this senior thesis is to explore general nonstandard analysis and some possible applications to 𝐶^*-algebras in functional analysis. More specifically, we shall define an approximate identity of a 𝐶^*-algebra using nonstandard analysis and study nonstandard hulls of internal 𝐶^*-algebra in the context of different unitizations. We shall also prove a few results for ideals in 𝐶^*-algebra using nonstandard definitions of approximate identities. We shall also briefly discuss the history and developments of nonstandard analysis.

Supporting K-5 Computer Science Integration Through High-Quality Teacher Professional Development, Shanan Chappell Moots, Joanna K. Garner, Joseph A. Brobst, Melani Loney, Lisa Steffian, Jennifer Maeng

Center for Educational Partnerships Publications

Workforce development and education leaders have increasingly emphasized the need for high-quality computer science (CS) instruction for K-12 students. Though states have created and mandated the implementation of CS curriculum standards, few in-service teachers have been provided sufficient opportunities to develop CS pedagogical content knowledge and self-efficacy. This study evaluated the effect of a CS integration professional development (PD) program on K-5 teachers' perceptions of their capacity to teach CS and their implementation of CS-integrated lessons using a randomized controlled trial design. Treatment included an intensive online summer institute with school year follow-up. Results indicate statistically significant effects of the …