Digital Commons Network^™

Investigation Of Arm Stiffness Modulation During Overground Physical Human-Human Interaction, Henry Tien

Masters Theses

The vision of advancing robots capable of direct physical engagement with humans begins with an understanding of how humans interact with each other. Even rudimentary interactive tasks, such as shaking hands, provides tremendous challenges for modern robotics and current research into the biomechanics of such interactions is limited. Thus, further analysis of physical Human-Human Interaction (pHHI) will bolster efforts to enhance collaborative robot capabilities. To this end, a custom Force Perturbation Handle (FPH) was developed, including the requisite mechanical, electrical, and software systems, to investigate the unique role of arm stiffness modulation in haptic communication between humans. The novel device …

Isolation And Characterization Of A Halophilic, Extremely Acidophilic, Iron-Oxidizing Bacterium, Connor Crites

Masters Theses

This thesis describes the isolation and characterization of a halophilic iron- oxidizing bacterium from sediments obtained from Lake Magic; an extremely acidic, saline lake located in Western Australia. The purpose for the isolation of novel, halotolerant/halophilic iron-oxidizing bacteria is to aid in metal-mining bioleaching operations. Currently used iron- and sulfur-oxidizing bacteria are extremely sensitive to chloride, which restricts their use in these industries.

A singular bacterial morphology was isolated from Lake Magic sediments that was roundly-rod shaped, 1-2 um in length, and stained Gram-negative. This organism was able to grow in a modified medium (DSM14174) using ferrous sulfate as an …

System Design For Highly Accurate And Efficient Target Detection In Triaxial Testing, Qingqing Fu

Masters Theses

Accurate and automated recognition of coded targets is crucial for high-precision photogrammetry-based measurements in triaxial testing. Traditional recognition methods, including those based on deep learning and table decoding, often struggle with issues such as perspective distortion, rotation, and variable lighting, leading to unreliable results. While deep learning approaches offer some improvements, they remain computationally intensive and sensitive to environmental factors.

This thesis introduces an innovative system that replaces deep learning algorithms with a blob analysis-based method for efficient and robust recognition of coded targets. The system also employs newly designed solid points of varying sizes and patterns, eliminating the need …

Development Of A Method To Measure Blast Overpressure Exposure Using Orthogonal Sensor Orientations, Nicholas Kuehl

Masters Theses

Measuring and recording blast exposure to military personnel from shoulder-fired weaponry or improvised explosive devices to correlate health outcomes like mild traumatic brain injury has been a goal for many years. As such, many wearable sensors have been developed and tested for accuracy and reliability. Despite this, knowing the sensor orientation in relation to the blast source is important to fully correlate the actual personnel exposure to clinical outcomes. This research investigates whether pressures recorded at three independent orientations in the x, y and z planes can be combined to a representative pressure that is independent of orientation. Important metrics …

Power Flow Control Of The Triple Active Bridge Converter, Lauryn Reece Morris

Masters Theses

With the rise of renewable energies, electric vehicles, and microgrids, the development of power electronic topologies that can seamlessly integrate these systems into the grid is crucial. The triple active bridge is an extension of the dual active bridge topology and is capable of energy storage or renewable energy integration into a power electronic converter and thus the power grid. Consisting of three H-Bridge converters, the triple active bridge topology is an expanding area of research to meet these growing demands. With the addition of the third bridge, the system has additional nonlinear characteristics which introduce complexity in solving for …

Ground Testing Of Cryogenic Environments In Vacuum Conditions, Lucas A. Scott

Masters Theses

The environment in the vacuum of space is unforgiving and ever-changing. Not only facing the lack of a protective atmosphere, but powerful radiation and extreme temperature ranges as well. Equipment destined for space must be hardened to withstand them. Just launching satellites that are theoretically able to survive these conditions is unfeasibly costly in the event of failure. Because of this, spacecraft must be tested in a simulated environment that can match the harsh climate in space. Therefore, it is the goal of the Gas and Plasma Dynamics Lab's (GPDL) to test and prove specific methods of recreating these conditions. …

Critical Behavior Ofthedilutedquasi-Onedimensionalquantum Ising Model, Logan Bradley Sowadski

Masters Theses

We explore the phase transition in the diluted quasi-one-dimensional quantum Ising model. We begin by giving an introduction to the Ising model followed by derivations of the properties and observables. A brief overview of Monte-Carlo simulations is also given focusing on two algorithms that make simulations for physically realizable systems possible, the Metropolis and Wolff algorithms. We finally discuss the concept of random disorder in the system and the effects this can have on the bulk of the system.

These concepts are then directly applied to a quasi-one-dimensional Ising model. Motivated by recent experiments on the spin-chain material cobalt niobate, …

Constraint Programming For Optimized Degree Paths, Mitchell Lee Skaggs

Masters Theses

This work presents a degree planning tool developed as part of the Pervasive Cyberinfrastructure for Personalized eLearning and Instructional Support (PERCEPOLIS) project which generates complete, valid, and personalized degree paths at any point from admission to graduation. This eliminates tedious calculation and double-checking, allowing advisors to focus on a student’s long-term plans and students to proactively explore potential degree paths. The original research contribution of this work is the use of a unified model for academic requirements to automatically translate complex, real-world curricula into a constraint programming model that can be quickly optimized based on personalized student criteria.

Automatically translating …

Overpressure Waveform Comparison Of High Explosive, Methane, And Coal Dust Explosions, Frank James Schott

Masters Theses

Methane and coal dust explosions remain a leading cause of catastrophic mining accidents, making it critical to understand their overpressure characteristics for better hazard modeling, mitigation, and regulation. Although high explosives (HE), flammable gases, and dusts have been studied separately, direct waveform comparisons in identical environments are rare. This study addresses that gap by comparing overpressure waveforms from HE, methane-air mixtures, and coal dust explosions to assess differences in peak pressure, impulse, rise time, and phase duration. Twenty-seven tests were conducted using standardized instrumentation and sensor arrays. Results showed that HE generated the highest peak pressures with short positive phases …

Auto-Tuning And Applications Of Transient Voltage Suppressor Models In Full-Wave Simulations, Daniel Peter Szanto

Masters Theses

System efficient electrostatic design (SEED) combines full-wave geometry information with SPICE models of non-linear protection devices, typically transient voltage suppression (TVS) diodes, to allow optimization and validation of electrostatic design (ESD) protection early in the design process. TVS models have previously been developed which may be used in SPICE simulation tools like Keysight ADS, but these models could not be used directly in full-wave simulation tools like CST Studio. A process was developed for converting existing ADS models of TVS devices to a form that can be used within a CST full wave/SPICE hybrid simulation. Three TVS models were converted …

Frequency-Tracker And Power Supply For Piezoelectric Lunar Dust Removal Actuator, Praneeth Uddarraju

Masters Theses

"This work presents a reconfigurable phase-locked loop (PLL)-based control system for the resonant excitation of piezoelectric actuators aimed at automated removal of particulate contaminants from photovoltaic (PV) surfaces—particularly in extraterrestrial environments such as the lunar surface. Regolith or lunar dust buildup on solar panels is a serious hazard to the effectiveness of energy harvesting on extended missions. By using high-frequency structural excitation and inertial forces the suggested system removes surface impurities. Tunable Sallen-Key low-pass filters for reliable feedback conditioning are used in conjunction with a digitally implemented PLL on an FPGA (XLR8 platform) to precisely lock the drive frequency to …

An Experimental Study Into The Methods Of Water Coupling And Their Impact On Kinetic Energy And Blast Over Pressure Through The Use Of A Ballistic Pendulum, Jeremiah Alan Cohn

Masters Theses

Water coupled charges utilize the material properties of water to alter their behavior for reductions in overpressure and increases in kinetic energy. Although water coupling has been studied directly, combined usage of the two primary methods of water coupling, tamping and pushing, hinders further research. This study addresses the gap in literature by comparing ballistic pendulum and blast data for charges with water tamping and pushing to determine differences in kinetic energy, peak overpressure, impulse, noise and duration of fireball. The results showed that water tamping provided a 69.1% increase in kinetic energy, an 18.6% reduction in incident overpressure, a …

Selective Surface Activation And Flotation Of Pyrite For The Recovery Of Tellurium From Sulfide Tailings, Mulenga Mutema Chibesa

Masters Theses

Copper sulfide tailings from past and present mining operations are important secondary sources of critical elements such as tellurium (Te), a key component in cadmium–telluride photovoltaic solar cells. Characterization of tailing streams from copper porphyry (CP) ore flotation revealed that Te-bearing minerals are predominantly hosted in pyrite, which is usually depressed and discarded. Enhancing pyrite recovery is therefore a critical first step toward concentrating Te minerals for downstream extraction. However, pyrite flotation is often hindered by hydrophilic surface complexes formed during prior processing. This research investigated selective flotation of Te-bearing pyrite from CP tailings using micro flotation and bench-scale flotation, …

Aerodynamic Design Workflow Optimization For Fsae: Advanced Cfd And Hpc Automation, Kyle Maynor

Masters Theses

This research identifies and resolves inefficiencies in the Computational Fluid Dynamics (CFD) workflow of the Missouri S&T Racing Formula SAE Team’s aerodynamic development. Key bottlenecks were found in simulation runtime, laborious simulation preparation, an overly manual simulation submission process, and unchecked mesh quality. A fully reimagined workflow was implemented with simulation parameters to adjust vehicle attitudes. From this, an automated design sweep could be executed to generate aero maps of the developing vehicle using the Design Manager Project. A Python-based submission app handles the terminal interfacing and macro editing that significantly slowed the job submission process before. Using a university …

Evaluating Tropospheric Delay Modeling For Enhanced Geospatial Accuracy, Adeyinka Olaoluwa Olaseinde

Masters Theses

Interferometric Synthetic Aperture Radar (InSAR) is a vital technique for monitoring ground surface deformation across large spatial scales. However, variability in atmospheric water vapor, pressure, and temperature introduces tropospheric delays that can significantly affect measurement accuracy. These delays are often corrected using outputs from numerical weather prediction (NWP) models. RAiDER, an open-source Python package, facilitates this by estimating tropospheric delays using models such as the High-Resolution Rapid Refresh (HRRR). Previous studies have shown that weather model–based corrections can substantially reduce atmospheric noise in InSAR data but also highlight persistent residual errors, especially at spatial scales smaller than the model grid …

Design Of A Spacecraft Power System Experiment, Jay Bakulkumar Kamdar

Masters Theses

This research delves into the design, implementation, and analysis of a controlled experimental framework for photovoltaic cell characterization and its application in spacecraft power systems. Such a system was simulated and validated by benchmarking characteristics of a photovoltaic module and implementing them in a system design simulation yielding performance data for comparative analysis. A hardware setup was developed to perform IV characterization tests under steady state thermal conditions. Experiments conducted across various thermal regulation profiles helped quantify the effects of temperature on the photovoltaic performance parameters. Active cooling reduced the steady state cell temperature by 17.9% and improved the cell …

Overall Tropospheric Noise Over The St. Louis Using Isce And Fringe Processing, Maryann Lee

Masters Theses

Interferometric Synthetic Aperture Radar (InSAR) is a satellite-based technique that is used to measure various aspects such as ground deformation, earthquakes, volcanic activity, and motions of glaciers. Although the technique has proved very useful, measurements errors such as ionospheric and tropospheric noise, and deformation often cause problems with making precise measurements. InSAR is a tool used in geodesy that is used to measure the change of surface deformation over time through a series of repeated SAR acquisitions. These errors in the acquisitions occur from factors of signal decorrelation, atmospheric delays, and phase unwrapping errors that affect the accuracy and precision …

Enabling Drone-Integrated Active Microwave Thermography Via A Slot Antenna Design, Alec P. Fitzmaurice

Masters Theses

Civil infrastructure inspection quality and inspector safety may be enhanced from the advancement in the capabilities of nondestructive testing and evaluation of remote or otherwise hard-to-reach areas such as nuclear power plants, wind turbines, bridges, or other civil infrastructure using drone-based Active Microwave Thermography (AMT). AMT is a nondestructive testing technique that utilizes high frequency energy (often radiated from an antenna) to induce heating in a specimen. Following this thermal excitation, an infrared camera is used to measure the resulting surface thermal profile. From this, defect indications may be detected. To enable drone-based deployment of AMT, where the antenna size …

Performance Of Standard Medical Mllms On Ecg Image Data, Prisha Anil

Masters Theses

This work presents a structured benchmarking study of multimodal large language models (MLLMs) applied to electrocardiogram (ECG) interpretation tasks. We evaluate three representative architectures: MedGemma, HuatuoGPT-Vision, and LLaVA-Med, across progressive experimental stages involving text-only structured prompt normalization, text–image fusion with ECG plots, and full multimodal fusion incorporating time-series signals. A standardized five-section cardiology prompt was designed to enforce consistent output structure and SCP-code alignment, enabling reproducible metric computation across models. Quantitative evaluation using BERTScore, token-level F1, and diagnostic accuracy demonstrates that HuatuoGPT-Vision achieves the highest semantic and diagnostic alignment, while MedGemma exhibits superior formatting stability and reproducibility. In contrast, LLaVA-Med …

Multimodal Spatio-Temporal Pest Prediction In Precision Agriculture, V N S Kameswari Sri Sindhu Manchikanti

Masters Theses

Accurate and timely prediction of pest outbreaks is a cornerstone of Agriculture 5.0, which emphasizes intelligent, data-driven, and sustainable decision-making in crop production. This research presents a multimodal deep learning framework that integrates heterogeneous data sources, including weather parameters, satellite-derived vegetation indices, and static and dynamic soil attributes, to forecast pest population dynamics under varying management and ecological conditions. The proposed framework employs modality-specific deep encoders to capture distinct temporal and spatial representations from each data stream and merges them through a late-fusion architecture that learns cross-modal dependencies critical to pest emergence. The design further incorporates treatment-aware and multiclass extensions, …

Application Of Artificial Intelligence Techniques To Improve Leadership Decision Making With Uncertainty, Michael David Parrish

Doctoral Dissertations

"Every good leader is a good manager, but not every good manager is a good leader. The difference between the leader and the manager is critical decision-making. Today’s decision-making environment is characterized as Volatile, Uncertain, Complex, and Ambiguous (VUCA). With the exponential increase in the technical capabilities of systems, the human has become the weakest link in the use of such systems. To remain relevant, good leaders must continuously adapt to new advances in technology and processes.

The research contributions of this work provide several unique and novel solutions for leaders to utilize artificial intelligence tools to improve and optimize …

Process-Structure-Property Relationships In Laser Powder Bed Fusion Produced 17-4 Ph Steel, Ben Brown

Doctoral Dissertations

Laser powder bed fusion (LPBF) is a metal additive manufacturing method that produces non-traditional microstructures as a result of the rapid solidification and thermal cycling inherent to the process. When using LPBF-produced material in application, these unique microstructures challenge the applicability of well-developed mechanical property databases achieved by conventional heat treatments. For wider adoption of this technology, a more holistic understanding is necessary on how process attributes develop material structure, which dictate mechanical properties. This dissertation explores the process structure-property relationships in LPBF 17-4 PH steel through systematic evaluation of atmospheric processing and heat treatment effects on microstructure and mechanical …

Generalizations Of Finiteness Conditions And Extension Monads In Algebras With Infinitely Many Or Infinitary Operations, Danielle Christienne Bowerman

Doctoral Dissertations

In this work, we extend the results of finiteness conditions and extension monads found in Insall from finitely many finitary operations to infinitely many finitary operations, as well as touching on infinitary operations. We also examine varieties of algebras, including the notion of strong varieties introduced in Insall, and common constructions of extension monads in varieties of algebras. We see that for finite collections of algebras of the same signature, the extension monad operation on a variety of algebras commutes with the direct product operation, and all retractions from an enlargement or extension monad are trivial. We also see that …

Phase-Field Modeling Of Rapid Solidification Processes, Nima Najafizadeh

Doctoral Dissertations

"Many advanced manufacturing processes such as additive manufacturing utilize rapid solidification of alloys, as it enables the formation of exotic non-equilibrium microstructure and thus improved properties. However, the interrelationship between the processing parameters and the resulting microstructure in rapid solidification is yet to be fully understood. We aim to investigate the microstructure evolutions during the rapid solidifications using phase-field modeling. The phase-field method assumes a diffuse interface, which avoids tracking the moving interface and hence enables efficient numerical simulations for complex microstructure evolution. A phase-field model with coupled solute-thermal diffusion and solute trapping effect is developed to investigate the rapid …

Lifelong Machine Learning With Adaptive Resonance Theory, Sasha Petrenko

Doctoral Dissertations

"This publication option dissertation is composed of three papers concerning the study of the problem lifelong machine learning with Adaptive Resonance Theory (ART) algorithms. Lifelong learning (L2) is a challenging machine learning paradigm that both encompasses and formalizes the fields of continual learning and incremental learning. The field is concerned with the mitigation of the phenomenon of catastrophic forgetting whereby learning agents that are faced with incrementally novel information deleteriously overwrite previous knowledge if that learning process is not regularized to counteract this consequence. ART algorithms solve this stability-plasticity dilemma by optimally assigning learning to categories or instantiating new knowledge …

Exploring The Feasibility Of Innovative Integration Of Phase Change Materials For Thermo-Adaptive Asphalt Pavements, Farshad Saberi Kerahroudi

Doctoral Dissertations

"Current research examined the feasibility and efficiency of employing phase change materials (PCMs) in asphalt pavement materials to result in thermo-adaptive asphalt pavement. The PCM was introduced to the asphalt materials in three different scales, including asphalt binder, asphalt mastic, and asphalt mixture. After investigating asphalt at different scales, mix blending method was found as the easiest method without any complexity to mix asphalt binder with PCM. The testing results could reveal an improvement in the high temperature performance of asphalt binder without sacrificing the low temperature performance with the presence of PCM and Gilsonite. Also, introducing PCM to asphalt …

Systematic Esd Analysis And Modeling For Electronic Device, Zhekun Peng

Doctoral Dissertations

Systematic ESD analysis provides good pre-compliance to ESD robustness evaluation on the electronic device from device level to component/system level to on-chip level. The whole process involves corona discharge on display, system level ESD analysis on PCB for race condition and transient response and 3D IC package impact to on-die ESD.

ESD to the display cover glass can damage touchscreen traces by sparkless corona discharges on the glass surface. A non-linear time dependent transmission-line model is proposed to model corona streamer propagation in terms of the coupling current and propagation speed. Results are highly promising to model the corona discharge …

Epitaxial Growth Of Metal-Organic Framwork Thin Films By Electro-Conversion And Electrodeposition, Xiaoting Zhang

Doctoral Dissertations

Electrochemical epitaxy is a facile and inexpensive soft-solution process to fabricate highly ordered thin films. This research focuses on the epitaxial growth of metal-organic framework (MOF) thin films by electrochemical methods which include electro-conversion and electrodeposition.

First, an electrochemical conversion pathway was invented to achieve epitaxial MOF thin films. Epitaxial single-domain Cu-BTC(111) thin films were manufactured by electrochemical oxidation of Cu₂O(111) films electrodeposited on single-crystal Au(111). The single-crystal-like Cu-BTC(111) thin films with out-of-plane and in-plane order provide well-aligned 3.5 Å triangular windows along the [111] direction. Cu-BTC(111) foils were fabricated from the Cu-BTC/Cu₂O system by electrochemical …

Message From Workshop Chairs, Sushil K. Prasad, Srishti Srivastava, Satish Puri, David Bunde, Shubbhi Taneja, Buddhi Ashan Mallika Kankanamalage

Computer Science Faculty Research & Creative Works

No abstract provided.

Alertble: Alert Workzone Hazards Using Hybrid Filtering And Machine-Learning-Enabled Ble, Samuel Akinyede, Sejun Song

Computer Science Faculty Research & Creative Works

Collision hazard detection in industrial work zones faces challenges from signal instability, mobility-induced fluctuations, and nonline-of-sight (NLOS) conditions. While Bluetooth low energy (BLE) offers cost-effective proximity sensing, its received signal strength indicator (RSSI) variability - fluctuating by ±10 dBm even at fixed distances - limits reliability in safety-critical applications. This article presents AlertBLE, a hybrid BLE-based hazard detection system that combines extended Kalman filter (EKF) and adaptive moving average (AMA) algorithms to achieve up to 94% RSSI variance reduction in static NLOS conditions. The system introduces speed-aware safety thresholds based on reaction time and braking distance models, dynamically expanding hazard …