Digital Commons Network^™

Relationships Between Benthic Macroinvertebrate Communities And Environmental Conditions In Headwater Tributaries Of The Pend Oreille Lake Watershed, Idaho, Devlin Mee

EWU Masters Thesis Collection

Benthic macroinvertebrates are widely used indicators of stream condition, and their communities respond to thermal and land-use conditions in headwater streams. This study characterized macroinvertebrate biomass, community composition, and diversity across forested headwater tributaries of the Pend Oreille lake watershed in northern Idaho, and examined their relationships with summer temperature, land development, and road proximity. Samples from thirteen streams collected in 2024 were identified to genus, measured, and converted to estimated biomass using published length–mass regressions; ten streams had recovered temperature loggers. Because environmental variables were characterized once per stream, all analyses were conducted at the stream level.

Estimated total …

Microgravity-Induced Alterations In Left Atrial Hemodynamics And Thrombogenic Risk: Insights From Healthy And Atrial Fibrillation Models, Grace M. Hoeppner

Dissertations, Master's Theses and Master's Reports

Background: Microgravity exposure alters cardiovascular loading, yet its impact on left atrial flow dynamics and thrombotic risk remains poorly understood. This study investigates how spaceflight-relevant microgravity-induced changes in cardiac outflow affect left atrial hemodynamics in healthy individuals and patients with atrial fibrillation.

Methods: Patient-specific left atrial models were generated for three healthy individuals and three AF patients. Computational fluid dynamics (CFD) simulations were performed using each patient’s baseline mitral outflow waveform and two modified waveforms representing short- and long-duration post-flight cardiac loading changes derived from echocardiographic observations. Hemodynamic metrics included left atrial velocity, time averaged wall shear stress, oscillatory shear …

Geospatial Analysis Of Sinkhole Density And Characteristics In West Virginia, Marissa Shannon Loftus

Graduate Theses, Dissertations, and Problem Reports (ETD)

Creation of a sinkhole map of West Virginia provides useful data to help identify areas susceptible to sinkhole related hazards, as well as allowing for detailed analysis of factors controlling karst development. Newly available, statewide LiDAR-derived digital elevation data have made mapping sinkholes over larger spatial extents feasible. For this study, sinkholes were mapped for all areas of West Virginia that are underlain by carbonate rocks; then the distribution and characteristics were evaluated overall and in four focus areas (Berkeley and Jefferson counties, Pendleton County, Greenbrier County, and Monroe County). These areas correspond to broader physiographic regions, with Berkeley, Jefferson, …

Comparison Of Push-Pull Air Curtain To Overhead Downdraft Systems On Aerosol Containment And Distribution In Controlled Environments, Manal Mutairi

Graduate Theses, Dissertations, and Problem Reports (ETD)

Abstract

Comparison of Push-Pull Air Curtain to Overhead Downdraft Systems on Aerosol Containment and Distribution in Controlled Environments.

This dissertation looks at the ongoing issue of tiny airborne particles created during medical and dental procedures and evaluates ways to reduce the risk of exposure for healthcare workers and patients to these particles. The first study focuses on the size, how long particles stay in the air, and how far they travel from common medical procedures that create aerosols, showing that tiny particles (less than 5 µm) can stay in the air long enough to escape basic droplet controls. As a …

Timing, Spectral, And Single-Pulse Properties Of Radio Pulsars, Evan Francis Lewis

Graduate Theses, Dissertations, and Problem Reports (ETD)

Radio pulsars are highly magnetized, rapidly rotating neutron stars which emit beams of radio waves from their magnetic poles. Their incredible rotational stability allows for their use in a variety of high-energy astrophysical studies, though the details of their internal structure and emission mechanisms are still unknown. We use observations of a cross-section of the pulsar population in order to investigate the nature of their evolution, their emission properties, and their environments.

First we derive timing solutions for three pulsars discovered through their sporadic single pulses. It was possible to obtain timing solutions through a set of single-pulse times of …

Preliminary Analysis Of Soil Volatile Organic Compounds As Soil Health Indicators, Thorne Taul

Graduate Theses, Dissertations, and Problem Reports (ETD)

Over the past decade, soil health (SH) has gained popularity due to the novelty of sustainable soil use related to human wellbeing. Soil health describes the overall quality of soil and its capacity to function over time. As interest in SH grows, researchers continue to explore new soil health indicators that can improve knowledge on how soil health is assessed and managed. Some indicators directly reflect soil health status, and some indirectly relate to processes and functions occurring within the soil. Volatile organic compounds (VOCs) are naturally occurring compounds that play a role in multiple soil processes. They are associated …

The Deposition, Prevalence, And Persistence Of Gunshot Residue In Standard And Less Lethal Ammunition, Liliana Claire Barbosa

Graduate Theses, Dissertations, and Problem Reports (ETD)

During the discharge of a firearm, gunshot residue (GSR) is released and settles into nearby surfaces, leaving traces that can provide valuable information for forensic investigations. This study aims to improve understanding of the deposition, prevalence, and persistence of standard and less-lethal ammunition through an analytical framework that examines collection and analysis protocols, revealing connections among multiple traces for effective use in investigations and courtroom proceedings.

Research into the chemical residues of less lethal ammunition (LLA) is a critical frontier in shooting investigations. While standard leaded ammunition has over a century of established literature, the chemical fingerprints of LLA residues …

Sedimentological And Geochemical Investigation Of The Origin Of Upper Pennsylvanian Black Shales, East-Central Appalachian Basin, Tyler Hickey

Graduate Theses, Dissertations, and Problem Reports (ETD)

In the east-central Allegheny foreland basin, laminated black shales overlying Upper Pennsylvanian Glenshaw Fm. coal seams record paleoenvironmental conditions associated with the termination of peat swamp deposition before, during, and after the Carboniferous Coal Forest Collapse (CCFC), a major paleobotanical evolutionary event during the Late Paleozoic Ice Age (LPIA) that contributed to extinction of lepidodendrons near the Desmoinesian-Missourian boundary (~306 Ma). Previous investigations of the CCFC commonly implicate an episode of aridification during intensification of LPIA glaciation that stressed the lepidodendrons beyond their ecological tipping point; however, the cause of this aridification is unclear. An investigation of Glenshaw Fm. black …

Deposition And Diagenesis Of Permo-Triassic Gypsum From Wyoming And Texas: Saline Lake And Groundwater Systems Of Equatorial Pangea, Maya Yamei Bradford

Graduate Theses, Dissertations, and Problem Reports (ETD)

Knowledge of gypsum textures and the processes that yield them is important for interpreting the history of environments, climates, and life on Earth. This is because gypsum textures are products of specific environmental, microbiological, and diagenetic processes, and because gypsum is relatively common in the Earth’s sedimentary record. Despite this significance, gypsum is relatively understudied. The fundamental goal of this dissertation is to advance our understanding of gypsum textures by presenting detailed, petrography-based investigations of Permo-Triassic gypsum from the continental interior of Pangea.

Gypsum is typical in the Permo-Triassic sedimentary record of tropical Pangea, where it is associated with red …

High-Resolution Laser Diagnostics For Ion Measurements In Magnetized Plasmas, Katey Stevenson

Graduate Theses, Dissertations, and Problem Reports (ETD)

In this work, we investigate ion heating in two plasma systems (helicon plasmas and flux rope plasmas) using the PHAse Space MApping (PHASMA) experiment. Our studies rely on high-resolution laser diagnostics, specifically laser-induced fluorescence (LIF), to measure ion velocity distribution functions (IVDFs). The temperature and bulk flow of each species are inferred from their respective VDFs. This dissertation is organized into three main parts: the study of ion heating in helicon plasmas, pulsed LIF modeling and diagnostic development, and the study of ion heating in flux rope plasmas. Helicon plasma sources efficiently generate high-density plasmas and are widely used to …

Studies On The Depth Formula And On Reducing Dimensions, Brian Mccourt Laverty

Graduate Theses, Dissertations, and Problem Reports (ETD)

This dissertation presents the author’s recent research, conducted under the supervision of Professor Olgur Celikbas, and based on two articles—one published and one in progress. These works develop two closely related research directions in commutative algebra. Together, they contribute to the subject by addressing aspects of existing conjectures, establishing new results, and introducing methods for studying homological invariants.

The first research direction concerns the depth formula, namely the equality \[ \depth_R(M)+\depth_R(N)=\depth(R)+\depth_R(M\otimes_RN) \] where $M$ and $N$ are finitely generated $R$-modules. A classical result of Auslander \cite{Aus} shows that the depth formula holds provided that either $M$ or $N$ has finite …

A Digital Calibration Source For 21 Cm Cosmology Telescopes, Kalyani Balkrishna Bhopi

Graduate Theses, Dissertations, and Problem Reports (ETD)

Precise calibration of radio telescope beams and gains is a central requirement for 21 cm intensity mapping experiments, which aim to measure large scale cosmological structure through the redshifted emission line of neutral hydrogen. Bright astrophysical foregrounds dominate the sky at these frequencies, and separating them from the cosmological signal demands precise control over instrumental systematics, particularly the telescope beam and its frequency-dependent response. Existing aerial calibration sources are incoherent broadband emitters, detectable only as total power. They provide no direct phase information and suffer from poor sensitivity in low signal-to-noise regimes.

We present the Precision Emitter for 21cm Array …

A New Parsimony-Based Method For Reconstructing Sequences Of Developmental Events And Estimating Rates Of Intraspecific Variation, With Applications To Trilobites, Alexander Benjamin Bradley

Graduate Theses, Dissertations, and Problem Reports (ETD)

Ontogenetic Sequence Analysis (OSA) is a method for reconstructing multiple sequences of abrupt phenotypic transformations (developmental events) for sampled populations of any kind of organism. It makes use of cladistic parsimony software to produce a network, or graph, whose vertices represent unique phenotypes at different stages of maturity (“semaphoronts”) and whose edges describe the developmental events occurring between semaphoronts. It is a powerful tool for constraining the range of developmental variation possible for a given species and generating sample statistics capable of identifying both the most common and the outlier ontogenetic sequences. However, OSA has seen little use since its …

Development Of Novel Methods For Investigative Leads In Firearm And Explosive Related Incidents, Addio Joseph Fiordigigli Jr.

Graduate Theses, Dissertations, and Problem Reports (ETD)

Criminal outbreaks and gun violence persist as a multifaceted global crisis, marked by escalating rates of homicide, suicide, and terrorism that destabilize communities and strain public resources. The proliferation of illicit firearms and homemade explosive devices, along with the complexity of modern criminal networks, necessitates innovative scientific tools to strengthen preventive intelligence operations and ensure that the legal process is grounded in physical evidence. More efficient detection of traces left behind at a crime scene can help prevent further harm or injury from follow-up attacks. This study aims to develop and evaluate new triage methods for characterizing gunshot residues (GSR) …

I Think, Therefore I Can: Self-Efficacy, Self-Regulation, And Sense Of Belonging In Introductory Physics, Danielle Christine Maldonado

Graduate Theses, Dissertations, and Problem Reports (ETD)

Cognitive and affective beliefs in physics classrooms are important indicators of student success beyond traditional measurements of academic performance. This body of work explores major beliefs and processes, including self-efficacy, self-regulation, and sense of belonging, as they relate to academic achievement among introductory undergraduate physics students. First, this dissertation explores the development of physics self-efficacy and physics sense of belonging, two highly correlated variables. This work identifies unique sources of physics self-efficacy and sense of belonging development from current and prior academic experiences, personality factors, and demographic variables. Then, relationships between early- semester self-efficacy and sense of belonging, mid-semester …

Optimization Of The Cmc Algorithm, Christopher Joseph Moner

Graduate Theses, Dissertations, and Problem Reports (ETD)

Cartridge cases recovered from discharged firearms contain tool marks produced by the internal mechanisms of said firearm. Firearm and tool mark examiners com pare these marks to determine whether two cartridge cases originated from the same firearm. Traditional comparison methods have been criticized for their subjective nature and reliance on examiner interpretation rather than objective decision thresholds. The Congruent Matching Cells (CMC) algorithm was developed as a quantitative, objective method for tool mark comparison. CMC is a surface topography correlation algorithm that partitions a tool mark into small regions, or cells, and evaluates their similarity using the areal cross-correlation function …

New Fossil Mygalomorph Spiders (?Idiopidae, Pycnothelidae) From The Lower Cretaceous Crato Formation Of Brazil, Elis Maria Gomes Santana

Graduate Theses, Dissertations, and Problem Reports (ETD)

The infraorder Mygalomorphae represents one of the earliest-diverging lineages of spiders, but its fossil record remains sparse relative to the modern diversity of the group. This is a reflection of both ecological and preservational biases, such as the predominantly fossorial habits of many mygalomorphs and the strong bias of the spider fossil record toward amber deposits. Compression fossils from rock deposits are therefore especially important for documenting the evolutionary history of the group. Here, two new mygalomorph fossils from the Lower Cretaceous Crato Formation, Araripe Basin (Brazil) are described. The first specimen is tentatively referred to ?Idiopidae based on male …

Factors Influencing Eastern Wild Turkey (Meleagris Gallopavo Silvestris) Productivity And Nesting Chronology In West Virginia, Kirstin Palumbo

Graduate Theses, Dissertations, and Problem Reports (ETD)

Identifying drivers of variation in the timing of breeding behaviors, such as courtship activities and nesting chronology, is important for the effective management of avian species. Likewise, productivity is an important component of game bird population dynamics and can be broken up into multiple components such as the probability of nesting, clutch size, and nest success. One species that experiences a relatively long reproductive season is the Eastern wild turkey (Meleagris gallopavo silvestris). Contemporary research in the southeastern United States has raised concerns regarding declines in both wild turkey populations and overall productivity. West Virginia, however, is unique …

Multi-Timescale Monitoring And Modeling For Resilient Smart Grids: Pmu Anomaly Detection And Battery Digital Twins, Muhammad Imran Hossain

Graduate Theses, Dissertations, and Problem Reports (ETD)

Modern power systems face failures at very different timescales. Cyber-physical disturbances may emerge within seconds, while battery degradation develops over hundreds of operating cycles. Both monitoring problems share the same underlying difficulty: power systems produce measurement data in abundance, but reliably labeled examples of abnormal or degraded operation are scarce. Rare grid events are difficult to label, and battery degradation data are heterogeneous across cells, cycling protocols, and chemistries. This thesis addresses these challenges through two complementary domain-informed learning frameworks that constrain representation learning using information specific to each physical problem.

First, at the system level, T-BiGAN, a Transformer-augmented bidirectional …

Comparing Unet And Hrnet For Geomorphic Feature Extraction From Digital Terrain Model-Derived Land Surface Parameters, Behnam Solouki

Graduate Theses, Dissertations, and Problem Reports (ETD)

Automated extraction of geomorphic features from high spatial resolution terrain data is important for environmental monitoring, geohazard assessment, and landscape change analysis. This study compares two convolutional neural network architectures, UNet and High-Resolution Network (HRNet), for semantic segmentation of mine benches and sinkholes from lidar-derived digital terrain models and land surface parameters. Mine benches represent anthropogenic, elongated, stepped landforms associated with historic surface mining, whereas sinkholes are natural, compact depressions common in karst terrain. Three terrain-derived input layers were used: square-root-transformed slope, broad-scale topographic position index, and fine-scale annulus topographic position index. Models were trained using five training sample sizes, …

Multimodal Representation Learning For Face Understanding: From Caption Supervision To Foundation Model Adaptation, Md Mahedi Hasan

Graduate Theses, Dissertations, and Problem Reports (ETD)

The rapid advancement of intelligent surveillance systems and the increasing demand for reliable biometric identification in border security, public safety, and digital forensics require robust face understanding under unconstrained conditions, including low resolution, pose variation, and occlusion. While Vision Transformer (ViT)-based foundation models have greatly improved visual representation learning, their patch-based tokenization and lack of spatial inductive bias limit their ability to capture fine-grained details in low-resolution inputs. This dissertation investigates multimodal representation learning for face understanding through natural language supervision, large-scale face-caption pre-training, and parameter-efficient foundation model adaptation. It hypothesizes that textual supervision provides complementary semantic cues that improve …

Dielectrophoretic Biomarkers For Cancer Detection And Cell Analysis: Integrating Microfluidics And Ai, Raphael Olumide Oladokun

Graduate Theses, Dissertations, and Problem Reports (ETD)

Pancreatic ductal adenocarcinoma (PDAC) carries a five-year survival rate of 13%, driven largely by late-stage diagnosis and the absence of sensitive noninvasive screening tools. Current diagnostic methods lack the sensitivity to detect disease-associated systemic changes at early and precancerous stages, representing a critical clinical gap. This dissertation addresses the central hypothesis that PDAC and its pathological subtypes induce measurable, disease-associated electrophysiological changes in circulating PBMCs that can serve as correlative liquid-biopsy biomarkers. To test this hypothesis, this work asks: can dielectrophoresis (DEP), impedance and zeta potential analysis with AI-assisted classification distinguish benign pancreatic conditions (non-malignant control), precancerous lesions (primarily IPMNs), …

Energy Partition And Heating Mechanisms In Asymmetric Antiparallel Magnetic Reconnection, Aleksandra Abova-Volkova

Graduate Theses, Dissertations, and Problem Reports (ETD)

Magnetic reconnection is a fundamental plasma physics process whereby a change in magnetic field connectivity drives the conversion of magnetic energy into energy of the surrounding plasma, often explosively. One of the many settings where it occurs is at the dayside magnetopause of Earth and other planets, where the magnetic field, number density, and/or temperature in the plasmas on the two sides upstream of the reconnection site are asymmetric. How the incoming magnetic energy gets partitioned into outgoing energies during asymmetric reconnection remains an outstanding question; of special interest is the fraction that gets converted into internal energy of ions …

Generating Synthetic Ct From Mri Data, Foysal Ahmed

Theses and Dissertations

Magnetic resonance imaging (MRI) provides excellent soft tissue contrast without ionizing radiation, making it a strong alternative to computed tomography (CT) in medical imaging workflows. However, CT remains essential for applications requiring electron density information, such as radiation therapy treatment planning. This study investigated the feasibility of generating synthetic CT (sCT) images from MRI using a deep learning-based U-Net architecture. A two-dimensional U-Net was trained on paired MRI-CT data from the SynthRAD 2025 dataset, consisting of 120 T1-weighted (T1W) and 60 T2-weighted (T2W) axial cases, including deformed CT (dCT) aligned to MRI. Model testing used an independent dataset of 30 …

Markov Chain Wave Generative Adversarial Network For Bee Bioacoustic Signal Synthesis, Kumudu Samarappuli, Iman Ardekani, Mahsa Mohaghegh, Abdolhossein Sarrafzadeh

Electrical & Computer Engineering Faculty Publications

This paper presents a framework for synthesizing bee bioacoustic signals associated with hive events. While existing approaches like WaveGAN have shown promise in audio generation, they often fail to preserve the subtle temporal and spectral features of bioacoustic signals critical for event-specific classification. The proposed method, MCWaveGAN, extends WaveGAN with a Markov Chain refinement stage, producing synthetic signals that more closely match the distribution of real bioacoustic data. Experimental results show that this method captures signal characteristics more effectively than WaveGAN alone. Furthermore, when integrated into a classifier, synthesized signals improved hive status prediction accuracy. These results highlight the potential …

Comparative Assessment Of Energy And Emission Costs For Geothermal Heat Pumps And Fossil-Fuel Heating Systems Across U.S. Climatic Zones, Md Shahin Alam, Shima Afshar, Seyed Ali Arefifar, Mohammad Haq

Electrical & Computer Engineering Faculty Publications

In response to growing concerns over global warming and energy sustainability, transitioning from fossil-fuel-based heating systems to renewable alternatives is essential. This study evaluates the economic and environmental performance of geothermal heat pumps for building heating and compares it with conventional coal-fired boilers, natural-gas boilers, and diesel furnaces. Using the heating degree-day (HDD) method, heating energy demand was analyzed for four U.S. cities—Anchorage (AK), San Francisco (CA), Salt Lake City (UT), and Las Vegas (NV)—representing diverse climatic zones. The analysis integrates thermodynamic and economic parameters, including the coefficient of performance (COP = 2–5) and annual fuel-utilization efficiency (AFUE = 80–97%), …

Digital Twin Technologies For Battery Systems: Advancements, Applications, And Future Directions, Seyed Saeed Madani, Yasmin Shabeer, Michael Fowler, Satyam Panchal, Carlos Ziebert, Hicham Chaoui, François Allard

Electrical & Computer Engineering Faculty Publications

The relationships among deep learning, edge computing, artificial intelligence (AI), and the most recent advancements in digital twin (DT) technology for battery energy storage systems are discussed in this paper. The study highlights the need for improved cloud-edge coordination, AI model development, and stronger cybersecurity features by demonstrating real-world applications of digital twin technology in electric vehicles (EVs), aircraft, and grid storage. It also described DT-based structures for fault detection, real-time monitoring, and optimization through standardization and battery management system (BMS) fusion. Because DT-based solutions for distributed energy resources (DERs) offer improved energy management systems, various studies have been conducted …

Interpretable Battery Soh Prediction: A Comparative Interpretability Framework For Multi-Architecture Ml Models, Shafiyee Islam, Gon Namkoong

Electrical & Computer Engineering Faculty Publications

This work introduces a unified interpretability-efficiency framework for lithium-ion battery state of health (SOH) prediction using hybrid deep learning architectures. We comparatively analyze four hybrid models: CNN LSTM MultiHead, CNN Feature Extractor LSTM, DNN LSTM, and DNN BiLSTM to disentangle how network topology, feature composition, and computational design influence both predictive fidelity and physical interpretability. By integrating Monte Carlo Shapley (MC Shapley), background occlusion SHAP (BoSHAP), and ablation analysis, we quantify the contribution and robustness of five electrochemical feature groups: time, capacity, voltage, dQ/dV and peaks of dQ/dV from NASA battery dataset. The results reveal a consistent dominance of differential …

An Explainable Cs-Mitigation Triangular (Ecsmt) Framework To Secure Graph Neural Networks, Sabah Ettahri, Sergio Pallas Enguita, Chung-Hao Chen, Wen-Chao Yang

Electrical & Computer Engineering Faculty Publications

This research addresses cyber risk by defending against backdoor attacks on Graph Neural Networks (GNNs). We propose the Explainable Complex System-Mitigation Triangular (ECSMT) Framework, which integrates Robust Training, Graph Regularization, and Data Sanitization into a lightweight, hardware-efficient defense layer. To evaluate structural generalizability, we conducted empirical evaluations across three distinct benchmark domains (AIDS, MUTAG, and PROTEINS) using a Graph Isomorphism Network (GIN) backbone. Under a baseline 5% backdoor subgraph trigger injection ratio, ECSMT achieves excellent utility retention, securing a Clean Accuracy (CA) of 97.33% (±0.62%) while reducing the Attack Success Rate (ASR) from 97.00% down to 69.45% on the primary …

Generalized Inverter Fault Detection Using Normalized Current Features And A Lightweight Bilstm Network, Mohammad Zamani Khaneghah, Mohamad Alzayed, Hicham Chaoui

Electrical & Computer Engineering Faculty Publications

Fault detection and diagnosis of three-phase inverter-fed motor drives is essential for ensuring system reliability, safety, and continuous operation in applications such as electric vehicles and industrial automation. This paper proposes a data-driven fault detection framework based on normalized current features and a lightweight bidirectional long short-term memory (BiLSTM) network which can be generalized to different motor power rating in the same controller system. A compact set of six time-domain features, consisting of the mean and root-mean-square (RMS) values of the phase currents, is extracted and normalized with respect to the average RMS value. This normalization effectively removes dependency on …