Digital Commons Network^™

Experimental Analysis Of Satellite Operator Training Using Game-Based Virtual Reality Simulation, Lana Laskey

Doctoral Dissertations and Master's Theses

Satellite data plays a vital role in modern global infrastructure by enabling communications, navigation, and weather forecasting. As demand for satellite technology grows, so does the need for highly trained satellite ground operators. Traditional training regimens for satellite operators employ simulation using two-dimensional computer console displays paired with the varied ability of trainees to generate abstract mental imagery of the scenario. However, this development of mental imagery imposes a considerable learning curve and cognitive workload on the trainee, which may negatively impact the user experience and knowledge gained during the training scenario.

This experimental study investigated the effects of game-based …

Effect Of Vehicular Electrification On Transportation Emissions In Florida, Shreya Sapkota Dhakal

Doctoral Dissertations and Master's Theses

Vehicular emissions from fuel-based passenger cars emit an array of gases and particles that are detrimental for human health and the environment. In that regard, electric vehicles (EVs) present a viable, sustainable solution. This study investigated the impact of electrification of passenger cars on air quality in Florida, in five major urban counties namely Miami-Dade, Duval, Hillsborough, Orange, and Leon. Between 2018 and 2022, these counties experienced a significant increase of 219.50 ± 52.32% in EV adoption, coupled with a 11.55 ± 6.13% decrease in fuel-based vehicle usage. Herein, we characterize five pollutants primarily generated from fuel-based passenger vehicles- carbon …

Graduate School Blog - July 2025 Volume 1, Cynthia Haynes

UofM Grad School Blog

The July 2025 UofM Graduate School Blog – Volume 1 continues the Cost of Graduate School Guide with a deep dive into hidden and variable expenses such as residency-based tuition differences, program-specific fees, and differential tuition. The blog provides practical tips for prospective students on how to ask the right financial questions when comparing programs. It also features a student spotlight on Billy Brooks, a dual MHA/MBA candidate motivated to transform healthcare access and equity. Upcoming events include a Virtual Fall 2025 Open House with Financial Aid and USBS, a Dissertation Writers Retreat, and both in-person and virtual Graduate Student …

Biocomputing Approach To Modeling And Modulating Calcium Signaling, Sehee Sun

School of Computing: Dissertations, Theses, and Student Research

Biocomputing is an emerging field that seeks to perform computational tasks using biological substrates and processes. Unlike conventional computing systems based on silicon hardware, biocomputing leverages the parallelism, energy efficiency, and complex dynamics of living systems. Among various cellular mechanisms, calcium (Ca2+) signaling stands out as a central regulator of diverse biological functions, offering a promising basis for programmable logic and control in living cells.

This thesis introduces a novel framework for modeling and modulating Ca2+ dynamics using biologically inspired Boolean logic circuits. Specifically, we propose the Ca2+ Boolean Logic (CaBL) model, in which Ca2+ fluxes and interactions are abstracted …

Artificial Intelligence Introduction Section, Seth Newell, Sally Brown

Artificial Intelligence Exhibit

The introduction gives an overview of the exhibition, along with an explanation of AI literacy, AI vs. Google, and a basic AI timeline.

Artificial Intelligence In Education, Sally Brown, Jill Woods, Mohamed Hefeida, Jennifer Sano-Franchini, Megan Vendemia, Erin Brock Carlson, Megan Leight, Gangqing Hu, Nicole Fuller

Artificial Intelligence Exhibit

This section explores the intersection of AI and education, including an overview of WVU's AI statement and submissions from WVU faculty, classes, students, and staff on AI related projects.

Advancing Circular Bioeconomy Through A Systems-Level Assessment Of Food Waste And Industrial Sludge Codigestion, Md Nizam Uddin, Cassidy Hartog, Emma Murray, Jacob Loveless, Luke Roberson, Asli Aslan, Francisco Cubas, Stetson Rowles

Civil Engineering & Construction: Faculty Publications

Disposal of food waste (FW) in landfills remains an unsustainable practice for organic waste management. Simultaneously, pulp and paper mills produce significant amounts of recalcitrant organic waste that is difficult to decompose due to its high lignocellulosic content. In this study, we developed an innovative approach to improve the digestion of pulp and paper mill sludge (PPMS) by amending FW to produce a low chemical oxygen demand (COD) sludge while recovering methane in the process. This codigestion process was evaluated through lab-scale biogas production experiments coupled with a comprehensive economic and environmental sustainability assessment. Biomethane production results revealed that the …

Teaching Learning Newsletter Vol 5 Issue 1, Sastra Deemed To Be University

TLC Newsletter

No abstract provided.

Elucidating The Impact Of Common Stormwater Pollutants On Antibiotic Resistance: The Role Of Heavy Metals, Nutrients, And Salts, Kassidy N. O'Malley, Patrick J. Mcnamara, Walter M. Mcdonald

Civil and Environmental Engineering Faculty Research and Publications

Antibiotic resistance poses a significant global health threat, and the urban water cycle presents an opportunity to augment or limit the spread of antibiotic resistance. In particular, stormwater runoff has recently been revealed as a key conduit for antibiotic-resistant bacteria (ARB). The specific role of stormwater pollutants, however, on antibiotic resistance has not been isolated. Understanding the impact of specific pollutants common to stormwater could help optimize design and operation of stormwater systems for management of antibiotic resistance. The objective of this research was to establish the potential contributions of common stormwater pollutants to antibiotic resistance proliferation. Lab-scale stormwater microcosms …

Jme4110: Hydro-Excavator Robot, Diane L. Evans, Nathan Fenton, Grant Cole, Nicholas Sipe

Washington University / UMSL Mechanical Engineering Design Project JME 4110

In an environmental situation wherein, diesel has leaked into soil surrounding high voltage lines in an underground confined space where workers cannot access physically and for safety reasons. To alleviate the situation, the project goal is to create a remotely controlled robot, with umbilical attachments. Due to the nature of the environment containing sensitive and electrically charged equipment, mechanical means of removing the soil are not feasible. For this reason, the robot is to remove contaminated soil by using a powerful water sprayer and vacuum combination. Other options for features of this robot are that it uses tracks for movement, …

Jme 4110: Design And Evaluation Of A Remote-Operated Tool For High-Ceiling Light Bulb Maintenance, Faiq Kureshi, Austin Carr, Phuc Truong, Klevis Malaj

Washington University / UMSL Mechanical Engineering Design Project JME 4110

Changing light bulbs in high ceilings is a common but hazardous task. Existing tools are awkward, unstable, and often lead to dropped bulbs, damaged fixtures, or the need for ladders, increasing both risk and effort. There is a clear need for a safe, accurate, and efficient solution that allows bulb replacement from the ground without compromising speed or precision

Characterization Of Lactobacilli-Containing Catheter Segments Developed By Using Selective Laser Sintered Mold., Caden Maners

Master of Engineering Theses

Catheter-associated urinary tract infections (CAUTIs) are a major healthcare burden with current prevention strategies offering limited success. This study presents a novel, self-coating biomaterial approach using a silicone-based bioink embedded with thermally sensitive probiotic strains (L. crispatus, L. rhamnosus, and L. reuteri). Catheter segments were fabricated via bio-injection molding using 3D-printed CAD molds. These Lactobacilli, selected for their probiotic and antimicrobial potential, serve as a non- antibiotic strategy to reduce infection risk. These segments were evaluated for mechanical strength (Shore A hardness), thermal stability (TGA/DSC), porosity and bacterial presence (SEM), biofilm formation (crystal-violet assay), as well as mass retention in …

Optimization Of Thermoelectric Energy Harvester To Power Wireless Onboard Bearing Health Sensors During Rail Service, Danna Cecilia Capitanachi Avila

Theses and Dissertations

This work presents the optimization of a thermoelectric energy harvester designed to supply power to a wireless onboard bearing health monitoring device for critical freight rail components. The study demonstrates an enhancement in the circuitry through the integration of an energy management subsystem (E-Peas AEM20940), which features a boost converter with lower self-start voltage. The harvesting system was tested on dynamic bearing test rigs to closely replicate field service conditions. Test plans were conducted using common freight speeds and loads to simulate a representative urban route. The thermoelectric energy harvester was able to operate at temperature differentials as low as …

Federated Learning Using Fully Homomorphic Encryption, Sk Golam Kuddus

Master’s Dissertations

Traditional machine learning approaches require centralizing data for training, which raises significant privacy concerns when dealing with sensitive information. Federated learning (FL) addresses this by keeping data local and enabling multiple users to collaboratively train a shared machine learning model. In spite of this, FL remains vulnerable to inference attacks, as sensitive information can still be extracted from the model’s learned parameters. While traditional privacy-enhancing techniques such as di!erential privacy introduce noise to model updates to obscure individual data points, they often present a fundamental trade-o! between privacy and utility. Furthermore, these approaches still carry risks of data leakage if …

Integrating Ensemble Hydrologic Forecasts With Policy Optimization Models For Forecast-Informed Reservoir Operations (Firo), Alessandra Estefania Perez Salas

Theses and Dissertations

Effective reservoir management in hydrologically variable regions such as California’s Central Valley faces increasing pressure to balance flood control, water supply reliability, hydropower generation, and ecosystem health. Traditional rule-based operations, while operationally simple, often lack the adaptability required to respond to real-time hydrologic conditions and forecast uncertainty. This study presents an integration of a policy tree optimization model with ensemble streamflow forecasts to enhance Forecast-Informed Reservoir Operations (FIRO) at Folsom Reservoir. Building on historical data for inflow, storage, and release, an interpretable, threshold-based decision framework was developed and coupled with 14-day ensemble inflow forecasts from the California-Nevada River Forecast Center’s …

Towards Efficient Privacy-Preserving Deep Learning: He-Friendly Structures, Flexible Pruning, He-Efficient Architectures, And Secure Transformer Token Drop, Yifei Cai

Electrical & Computer Engineering Theses & Dissertations

Deep learning (DL) has become a powerful tool for solving complex problems, but developing DL models typically requires vast datasets, high computational resources, and expert knowledge—barriers that limit accessibility. Machine Learning as a Service (MLaaS) addresses this challenge by allowing resource-rich providers to deliver pre-trained DL models as services. However, privacy concerns arise: clients hesitate to share sensitive data, while providers protect their proprietary models. To address this, privacy-preserving MLaaS integrates cryptographic techniques into DL computations, as seen in frameworks like Cryptonets, SecureML, GAZELLE, CrypTFlow2, Cheetah, and BOLT. Among them, Homomorphic Encryption (HE) enables computation on encrypted data but remains …

A Wearable-Based Approach To Spinal Posture Tracking And Assessment, Sydney Marie Sherman, Noah Jeffery

Biomedical Engineering: Graduate Reports and Projects

This paper describes the design, manufacturing, and testing of a novel spinal posture tracking wearable device with embedded sensors. Currently on the market, most of the spinal posture tracking devices only focus on one segment of the spine and therefore do not track the entirety of human posture. The objective for this project was to create a wearable device in the form of a “smart shirt” that offers insights into posture trends throughout the day by tracking the entire spine. To begin the project, multiple designs were developed for the sensor array and wearable materials. These concepts were compared against …

Seconds From Impact: Anticipatory Vehicular Crash Prediction Using Video Vision Transormers, Ryan P. Geisen

Master's Theses

Vehicular collisions represent a significant public health concern, necessitating re search into advanced emergency notification systems. While deep learning has shown promise in accident detection, a research gap persists in applying state-of-the-art transformer architectures to the task of anticipatory, real-time crash prediction from video. This thesis addresses this gap by developing and evaluating a Video Vision Transformer (ViViT) for the binary classification of imminent vehicular collisions. Utilizing a curated dataset of 1,493 unique collision sequences, this study systemati cally investigates the impact of temporal context by comparing the ViViT against a single-frame Vision Transformer (ViT) baseline and conducting comprehensive exper …

Hardware Accelerated Simulation Of Buck Converters Using Physics-Informed Neural Networks, James Clayton Crews

Theses and Dissertations

Physics-informed neural networks (PINNs) are an emerging machine learning method for learning the behavior of physical systems described by governing differential equations. Dc-dc power-electronic converters are used in a variety of industry applications such as motor drives or power supplies where real-time simulation is critical for control and safety. This thesis investigates physics-informed machine learning as an approach to develop a real-time digital twin for dc-dc power converters. Traditional numerical integration methods are used to approximate discretized behavior, and the results are compared with a trained PINN model. Modern ML frameworks (such as PyTorch and TensorFlow/Keras) are used to quickly …

Saw Biosensor For The Detection Of Cyanobacteria And Cyanotoxin, Tally Bovender

Theses and Dissertations

The growing prevalence of cyanobacterial blooms and associated cyanotoxins, such as microcystin-LR (MC-LR), presents a significant threat to water quality and public health. Conventional detection methods, including ELISA and PCR, are often time-consuming, expensive, and require trained personnel, limiting their application in field settings. Hence, a miniaturized, quick testing sensor is proposed to circumvent the current sensing challenges for real time, in-situ diagnostics of MC-LR. The proposed high-frequency ultrasonic sensor employs surface acoustic waves (SAW). The sensor was designed using a multi-physics simulation tool to understand wave propagation in the piezoelectric substrate (lithium tantalate) and optimize the design of the …

Design Of Supercritical Reactors To Understand Supercritical Water Oxidation Process And Hydrothermal Flames, Victor Dubceac

Theses and Dissertations

Supercritical water oxidation (SCWO) has been a topic of immense interest as an effective technique/tool for hazardous aqueous waste disposal. SCWO can be achieved by introducing an oxidizer (e.g., H2O2), or a hydrothermal flame as an internal source of both heat and oxidizer species in an aqueous environment at conditions above the critical point of water (P > 218 atm and T > 647 K). SCWO poses important environmental advantages for the treatment of harmful organic materials contained in waste streams. An SCWO reactor has the potential to be compact in design and therefore can be an ideal alternative to existing technology …

Embeddable Multi-Material Wireless Micro-Sensors Utilizing Additive Manufacturing And Enhanced Microstructure, Nicholas Reed

Doctoral Dissertations and Master's Theses

The development of embeddable, multi-material wireless microsensors offers transformative potential for structural health monitoring (SHM) in aerospace applications. This work integrates additive manufacturing (AM) techniques with advanced microstructural design to produce flexible, high-resolution sensors that can be directly embedded into polymer substrates. By utilizing the vat photopolymerization process, customized embedded sensors are seamlessly integrated into polymer AM structures. These sensors are then continuously refined, targeting increases in performance, both internal and external. Microstructural enhancements are explored to modify the rheological properties of the fabricated embedded sensing channels and enhance the adhesive bonding between the embedded sensor and the AM structure. …

A Discrete-Time Adaptive Sliding Mode Controller For A Multicopter With A Suspended Payload, John Helzer

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

This thesis presents a Discrete-time Adaptive Sliding Mode Controller (DASMC) for control of a multicopter with a suspended payload. DASMC is designed to stabilize the multicopter at a desired position while minimizing the load oscillations induced by a significant hanging payload. The proposed DASMC minimizes the need for system-specific parameters like tunable gains and improves robustness to both external disturbances and model uncertainties compared with existing controllers. The controller is designed for direct digital implementation on a variety of multicopter platforms with considerations like discrete-time design, adaptive gain shrinking, and saturation handling. When deployed on a real multicopter in an …

Reduced Order Model-Based Framework For Microsecond Model Updating Of Two-Dimensional Structural Systems Using The Local Eigenvalue Modification Procedure, Emmanuel Abiodun Ogunniyi

Theses and Dissertations

Real-time model updating is crucial for active structures and electronic assemblies subjected to high-rate dynamic events. High-rate dynamic events refer to events that occur at high speeds and with rapid changes in the forces and energy involved. These events can include explosions, impacts, and crashes. These systems are characterized by a high dynamic response with a high rate (< 100 ms), high amplitude (> 100 gn), highly nonlinear, meaning that the response is not proportional to the applied force, and involve complex interactions between multiple objects or materials. A system exposed to high-rate dynamic environments is frequently prone to rapid plastic deformation, involving violent and …

Characterizing The Relationships Between Cranial Geometry, Brain Morphometry, And Brain Mechanical Properties Using Mr Imaging And Elastography, Jessica Restivo

Theses and Dissertations

Traumatic brain injury (TBI) is a global health concern, with over 69 million cases annually. TBI risk depends on subject-specific neuroanatomical variation, yet research often only considers generic finite element (FE) models, based on the geometry and material composition of a 50th percentile male head. Although highly accurate, subject-specific models require expensive magnetic resonance (MR) imaging, elastography, and time-consuming computational resources. There is a need to create subject-specific TBI models that account for subject-specific variations, without neuroimaging. This study aims to create mathematical models to predict brain morphometry (dimensions, volume) [Objective 1] and mechanical properties (shear stiffness, damping ratio, octahedral …

Elevating Next Generation Wireless Devices Towards Contactless Sensing For Healthcare Applications, Aakriti Adhikari

Theses and Dissertations

There is an increasing interest in technologies that can understand and perceive at-home human activities to provide personalized healthcare monitoring, aimed at early detection of disease markers and assisting physicians in making clinical decisions. Existing approaches, such as wearables, require users to wear sensors that can be cumbersome and cause discomfort. Vision based solutions, such as optical cameras, IRs, LiDARs, etc., can be used to design contactless at-home monitoring systems. However, these systems are limited by poor lighting and occlusion, and they are privacy-invasive. Fortunately, high-frequency millimeter-wave wireless devices provide an effective alternative to the existing systems to enable fine-grained …

A Recycling Route For E-Waste And Aluminium Scrap To Produce A2xxx And A3xx Al Alloys, Iman El-Mahallawi, Shaza Raji, Mayar M. Ali, Mai Mahmoud, Sara Atef, Mahmoud Tash, Serag Salem, Tarek Elmeligy

Mechanical Engineering

Electronic waste (e-waste) generation is significantly escalating, while traditional recycling methods, failing to meet sustainability criteria, are still used. The implementation of sustainability requirements calling for recycling will not be achieved unless intensive research is conducted for mitigating and tolerating the presence of accumulating tramp elements in the recycled alloys and even revising the existing standard specifications. This study explores an innovative approach to recycling electronic waste (e-waste) by integrating it with aluminum scrap through conventional melting techniques to produce high-performance industrial alloys aiming to develop novel aluminum alloys with enhanced properties suitable for various industrial applications. The experimental process …

Impactor Displacement As A Predictor Of Thoraco-Abdominal Organ Injury: Comparison Of Isolated Organ To Whole Body Tests., Jack Seifert, Jared Michael Koser, Alok Shah, Lance Frazer, Frank A. Pintar, Narayan Yoganandan, Dan Nicolella, Brian D. Stemper

Biomedical Engineering Faculty Research and Publications

Purpose

Body armor is used to protect the wearer from penetrating injuries. However, when the armor defeats the projectile, it deforms at high rates into the wearer, referred to as back face deformation (BFD). This deformation can cause a variety of superficial and internal injuries and consequently should be considered when designing body armor. However, current design standards do not adequately consider the effects of BFD, and new data are necessary to inform future design thresholds for BFD. The objective of this study was to develop blunt impact injury risk curves for in vitro thoraco-abdominal organs and determine their applicability …

Advances In Noninvasive Imaging For Detecting Radiation-Induced Lung Injury (Rili), Austen Nissen, Said H. Audi, Anne V. Clough, Brian Fish, Amit Joshi, Meetha Medhora, Jason Walter Sidabras, Heather A. Himburg

Biomedical Engineering Faculty Research and Publications

Purpose: Dr. Richard Hill performed pioneering work in the field of radiation-induced normal tissue injury to the lung including noninvasive imaging studies aimed at identifying imaging biomarkers of radiation-induced lung injury (RILI). RILI is a life-threatening toxicity of radiation exposure relevant to both cancer patients undergoing thoracic radiation therapy (RT) and victims of accidental radiation exposure. The ability to detect RILI noninvasively has the potential to guide treatment planning for RT and, in the case of victims of acute radiation exposures, inform the decision to start mitigative therapies. As part of this special issue of IJRB honoring Dr. Hill’s many …

Designing A Portable And Accessible Diffuse Reflectance Spectroscopy System For Real-Time Detection Of Cervical Intraepithelial Neoplasia, Allison Scarbrough, Diana Moses, Tongtong Lu, Bing Yu

Biomedical Engineering Faculty Research and Publications

Significance: Over 80% of cervical cancer cases occur in lower-to-middle income countries (LMIC’s). This is partly because current screening techniques lack affordability, accessibility, and/or reliability for use in LMIC’s.

Aim: To develop an optical technique for cervical cancer screening that is affordable, accessible, and reliable for use in LMIC’s.

Approach: We developed a portable diffuse reflectance spectroscopy (DRS) system, which costs < $2500 USD to manufacture, and employs a Raspberry Pi to extract the absorption (μ_a) and reduced scattering (μ'_s) coefficients of biological tissue. The system was subject to travel and intentional rough handling. It was further used to capture 320 DRS spectra taken from 64 tissue-mimicking phantoms. Two …