Digital Commons Network^™

The Atmospheric Waves Experiment (Awe), L. Scherliess, M. J. Taylor, P.-Dominique Pautet, Y. Zhao, B. Lamborn, H. Latvakoski, G. Cantwell, P. Sevilla, E. Syrstad, J. Forbes, S. Eckermann, D. Fritts, D. Janches, H. Liu, J. Snively

Space Dynamics Laboratory Publications

Modern theory and modeling indicate that atmospheric gravity waves (AGWs) play an important role in vertical coupling of the atmosphere-ionosphere system. Although small-scale AGWs (horizontal wavelengths ~30–300 km) are thought to account for the dominant energy and momentum inputs at Ionosphere-Thermosphere-Mesosphere (ITM) altitudes, the sources, variability, and influences of small-scale AGWs are still major unknowns. NASA’s Atmospheric Waves Experiment (AWE) mission is a Heliophysics Small Explorers Mission of Opportunity designed to investigate how terrestrial weather affects space weather, via small-scale AGWs produced in Earth’s atmosphere. Installed on the International Space Station (ISS) in November 2023, AWE began its 2-year mission …

Clinic Vs. Daily Life Gait Characteristics In Patients With Spinocerebellar Ataxia, Vrutangkumar V. Shah, Daniel Muzyka, Adam Jagodinsky, Hannah Casey, James Mcnames, Mahmoud El-Gohary, Kristen Sowalsky, Delaram Safarpour, Patricia Carlson-Kuhta, Fay B. Horak, Christopher M. Gomez

Electrical and Computer Engineering Faculty Publications and Presentations

Background:

Recent findings suggest that a single gait assessment in a clinic may not reflect everyday mobility.ObjectiveWe compared gait measures that best differentiated individuals with spinocerebellar ataxia (SCA) from age-matched healthy controls (HC) during a supervised gait test in the clinic vs. a week of unsupervised gait during daily life.

Methods: Twenty-six individuals with SCA types 1, 2, 3, and 6, and 13 (HC) wore three Opal inertial sensors (on both feet and lower back) during a 2-minute walk in the clinic and for seven days in daily life. Seventeen gait measures were analyzed to investigate the group differences using …

Data Compression In Additive Manufacturing: Recent Progress And Opportunities, Dongmin Ethan Kang, Wenmeng Tian

Publications

A crucial aspect of quality control for Additive Manufacturing (AM) processes is the acquisition of diverse data from the entire lifecycle of the product. AM data has grown significantly in terms of diversity and volumes, resulting in diverse data formats of increasing volumes, including time series, images, and point clouds. Large quantities of these data are essential for effective in-situ process monitoring and ex-situ non-destructive evaluation. However, this will result in large manufacturing and inspection datasets that are difficult to manage for users, which will delay the broader adoption of AM for mission critical applications. This motivates the urgent need …

Distributed Coherent Beamforming At 60 Ghz Enabled By Optically-Established Coherence, Drake Silbernagel, Yu Rong, Isabella Lenz, Prithvi Hemanth, Carl Morgenstern, Owen Ma, Nolan Matthews, Nadar Zaki, Kyle W. Martin, John D. Elgin, Jacob Holtom, Daniel W. Bliss, Kimberly Frey

Space Dynamics Laboratory Publications

We implement and experimentally demonstrate a 60 GHz distributed system leveraging an optical time synchronization system that provides precise time and frequency alignment between independent elements of the distributed mesh. Utilizing such accurate coherence, we perform receive beamforming with interference rejection and transmit nulling. In these configurations, the system achieves a coherent gain over an incoherent network of N nodes, significantly improving the relevant signal power ratios. Our system demonstrates extended array phase coherence times, enabling advanced techniques. Results from over-the-air experiments demonstrate a 14.3 dB signal-to-interference-plus-noise improvement in interference-laden scenarios with a contributing 13.5 dB null towards interference in …

Optimizing Object Detection For Remote Monitoring With Owl Ducklink Radios, Colin Ren-Jin Babian

Electrical Engineering

This project develops an AI powered object detection system integrated with OWL DuckLink radios to enable real time remote monitoring. The system benchmarks multiple AI accelerators using a Raspberry Pi 5 to determine their efficiency in low power, long range communication environments. By evaluating the Raspberry Pi 5 CPU (7.62W, 14.5 camera FPS, 3.8 inference FPS), Raspberry Pi AI Camera with Sony IMX500 (6.45W, 30 camera FPS, 9.2 inference FPS), and Raspberry Pi AI Hat with Hailo-8L chipset (7.80W, 30 camera FPS, >30 inference FPS), this project identifies the most effective combination of hardware and software for edge AI applications. …

Restoration Of 6-Axis Industrial-Grade Robotic Arms, Bryce Andrew Paulson, Warren Douglas Howard

Electrical Engineering

The Staubli TX60 and TX60CR are industrial-grade, six-axis robotic arms originally designed to perform complex automation tasks in manufacturing environments. Following their retirement from active industrial use, both units were restored to full operational status. As part of this project, they were reprogrammed to execute a pick-and-place routine using kids shape-sorting toys that mirrors typical workflows found in factory settings. The six degrees of freedom afforded by each robot enable a wide range of motion, making them well-suited for tasks such as material handling, product sorting, and repetitive operations typically carried out by human workers. Each model is equipped with …

A Tailored Analog-To-Digital Converter Architecture For Optimal Performance In Troponin Cardiac Protein Detection, Karem Abdelgawad, Sameh O. Abdellatif

Electrical Engineering

In recent years, the detection of troponin cardiac proteins has emerged as a crucial component in the diagnosis and management of acute coronary syndromes. This paper presents a tailored analog-to digital converter(ADC) architecture specifically designed to enhance the performance of diagnostic systems for troponin detection. Utilizing a 180 nm CMOS process technology, the developed 8-bit Successive Approximation Register(SAR) ADC integrates key components, including a preamplifier, comparator, and a digital-to-analog converter(DAC), to optimize signal processing and ensure accurate data conversion from analog to digital formats. The ADC architecture is evaluated for its ability to achieve a substantial sampling rate of 10 …

Comparative Analysis Of Different Magnetic Anomaly Datasets Using Navigation Performance With Flight Test Data, Aaron P. Nielsen, Brandon M. Blakely, Patrick Duff

Faculty Publications

Magnetic Anomaly Navigation (MagNav) is a map-based method of navigation which relies on accurately obtaining the anomaly field to a high level of precision to achieve good navigation results. This requires utilizing high quality sensors, accurately modeling disturbance fields from the aircraft & other sources, and creating high-fidelity maps. Aeromagnetic survey data or marine track survey data must be processed into a product that can be used as a reference for a magnetic navigator and a variety of techniques can be utilized for this processing. The data collection for different survey types reflects choices typically made to study the underlying …

Waste By-Products In Asphalt Concrete Pavement Construction: A Review, Nuha S. Mashaan, Daniel O. Oguntayo, Chathurika Dassanayake

Research outputs 2022 to 2026

The use of mining by-products in bitumen and asphalt mixture modification has drawn a lot of interest lately since it can improve pavement performance while advancing the goals of the circular economy and environmental sustainability. Mining by-products such as steel slag, red mud, silica fume, and fly ash have demonstrated good results as sustainable materials for improving the chemical, mechanical, durability, and rheological properties of asphalt binders and mixtures while also reducing the environmental degradation brought about by the disposal of these by-products. This study reviews research efforts on mining by-products (specifically steel slag, silica fume, red mud, and fly …

Diffusion Mri Biomarkers For Predicting Treatment Outcomes In Infantile Epileptic Spasms Syndrome With Non-Lesional Mri, Daniel Ackom, Scott A. Beardsley, Jennifer Meylor, Kayleigh Butler, Ricardo Vega, Andrew J.D. Crow, Hema Patel, Brian D. Schmit, Pradeep Javarayee

Biomedical Engineering Faculty Research and Publications

Background

Infantile epileptic spasms syndrome (IESS) is a devastating developmental epileptic encephalopathy (DEE) and patients exhibit diffuse white matter alterations and structural remodeling. However, the correlation between these structural changes and brain network properties, or their effect on the efficacy of treatment outcomes in MRI non-lesional IESS patients is not clear.

Method

This retrospective study was conducted on IESS patients using fixel-based analysis (FBA) of diffusion MRI and graph theory analysis of structural connectivity, involving 26 non-lesional IESS patients aged 2 to 12 months and 120 age-matched controls. We further examined the differences between antiseizure medication (ASM) responders and non-responders …

Experimental Study Of Gas-Dynamic Heating In Hartmann-Sprenger Tubes For Rocket Engine Ignition, Jacob T. Huff

Master's Theses

Ignition systems for chemical rocket engines typically rely on hypergolic propellants or auxiliary electrical hardware to supply the energy required to initiate combustion. The resonance igniter is a simple and robust alternative to these conventional methods, capable of inducing autoignition of non-hypergolic propellants without an external ignition source. At the core of this concept is the Hartmann-Sprenger Tube (HST), a device in which a high-velocity jet of gas impinges on a resonance cavity. This interaction establishes self-sustaining gas oscillations within the cavity that heat the propellants to their autoignition temperature. To facilitate the development of a functional resonance igniter at …

Large Language Models For Construction Risk Classification: A Comparative Study, Abdolmajid Erfani, Hussein Khanjar

Michigan Tech Publications

Risk identification is a critical concern in the construction industry. In recent years, there has been a growing trend of applying artificial intelligence (AI) tools to detect risks from unstructured data sources such as news articles, social media, contracts, and financial reports. The rapid advancement of large language models (LLMs) in text analysis, summarization, and generation offers promising opportunities to improve construction risk identification. This study conducts a comprehensive benchmarking of natural language processing (NLP) and LLM techniques for automating the classification of risk items into a generic risk category. Twelve model configurations are evaluated, ranging from classical NLP pipelines …

Enhancing Network Security: Dynamical Intrusion Detection Systems Leveraging Zero Trust Architecture, Ekramul Haque

Tennessee State University Alumni Theses and Dissertations

This thesis discussed two original methodologies for proposing security frameworks incorporating machine learning (ML) and Zero Trust Architecture (ZTA) principles to manage advanced persistent threats faced by Unmanned Aerial Vehicles (UAVs) and Network intrusion detection systems (IDS). The first methodology examined the use of RF signals and deep learning to identify and classify UAVs. The RF signal characteristics used in the method for detecting UAVs improved the ability to determine RF drone protocols. Although the models led to promising findings, their lack of ability to generalize to new drone types identified the need to improve both the data set and …

Physics-Based Machine Learning Framework For Predicting Structure-Property Relationships In Ded-Fabricated Low-Alloy Steels †, Atiqur Rahman, Md Hazrat Ali, Asad Waqar Malik, Muhammad Arif Mahmood, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The Directed Energy Deposition (DED) process has demonstrated high efficiency in manufacturing steel parts with complex geometries and superior capabilities. Understanding the complex interplays of alloy compositions, cooling rates, grain sizes, thermal histories, and mechanical properties remains a significant challenge during DED processing. Interpretable and data-driven modeling has proven effective in tackling this challenge, as machine learning (ML) algorithms continue to advance in capturing complex property structural relationships. However, accurately predicting the prime mechanical properties, including ultimate tensile strength (UTS), yield strength (YS), and hardness value (HV), remains a challenging task due to the complex and non-linear relationships among process …

Case Article—Optimizing Transportation And Equity In A District Zoning Problem For Orville Public Schools, Kelly M. Sullivan, Ashlea Bennett Milburn

Industrial Engineering Faculty Publications and Presentations

“Optimizing transportation and equity in a district zoning problem for ORville public schools” is a case developed to expose students to an optimization decision problem with ethical considerations incorporated. Specifically, students are asked to solve a school district zoning problem in which all residential addresses in a school district must be assigned to middle schools having capacity limits on the numbers of students that they can accommodate.

Enhancing Non-Player Character Dialogue In Video Gages: An Evaluation Of Large Language Model-Generated Responses, Lam P. Quach

Master's Theses

As video games increasingly emphasize narrative depth and player immersion, the quality of Non-Player Character (NPC) dialogue has become crucial for creating engaging gaming experiences. This thesis investigates the potential of Large Language Models (LLMs) to generate high-quality NPC dialogue by comprehensively evaluating four state-of-the-art models: Gemma 3 27B, Mistral 7B, QWEN 2.5, and LLAMA 3.1. The study employs a mixed-methods approach, combining human evaluation (N=50 participants) with AI-based assessment across five key benchmarks: coherence, personality expression, engagement, style/tone appropriateness, and overall quality. Participants evaluated 32 dialogue samples (8 per model) generated for a fantasy game context featuring two distinct …

Single-Molecule Orientation And Localization Microscopy, Sophie Brasselet, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

Single-molecule localization microscopy (SMLM) offers enhanced spatial resolution in optical microscopy, providing detailed insights into the spatial organization of proteins in cells at the nanoscale. Over the past decade, SMLM has progressively incorporated the capability to retrieve the orientations of single molecules using their polarized dipolar emission pattern. Here we explore recent advancements in single-molecule orientation and localization microscopy (SMOLM), which yields super-resolved images of molecular three-dimensional (3D) orientations, wobble and 3D positions. This advancement opens possibilities to explore the nanoscale organization and conformation of biological molecules as well as to monitor and design local 3D optical fields in nanophotonics. …

Guiding State-Specific Studies On Highway Disasters: Examining Differences In Postdisaster Funding, Mariam Elazhary, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The highway sector is frequently and severely impacted by natural disasters. To mitigate these effects and reduce the need for large relief budgets or emergency funds, it is crucial to study the resilience of the transportation network. As such, defining resilience in absolute terms is not enough; instead, it is equally important to analyze specific case studies and build a lessons-learned rapport. This is critical because it helps identify unique vulnerabilities and strengths that might be overlooked in broader analyses. However, current research on highway resilience often lacks empirical evidence to support the selection of these unique and significant case …

Sparse-Data Orbit Estimation In Low Earth Orbit Using The Markov Chain Monte Carlo Ensemble Gaussian Mixture Filter, Nicholas J. Oden

Master's Theses

The number of space objects (SOs) in low Earth orbit (LEO) continues to increase rapidly, creating challenges for the current ground-based tracking network, which cannot accommodate the projected growth in SOs. Catalog maintenance relies on frequent observations for reliable reacquisition, with Two-Line Element (TLE) sets typically generated daily to mitigate rapid error growth from poor TLE accuracy. This constraint limits the ability to track more objects with existing infrastructure. This work evaluates the Markov Chain Monte Carlo Ensemble Gaussian Mixture Filter (MCMC EnGMF), a nonlinear, non-Gaussian filter well-suited for sparse tracking scenarios where higher post-update accuracy is needed to reduce …

Price Adjustment Clauses: Enhanced Price Volatility Forecasting For Construction Materials, Ahmed Shiha, Mariam Elazhary, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Price adjustment clauses (PACs) are used by state departments of transportation (DOTs) to share the risk of material price fluctuations. Existing models that depict the price fluctuations of materials forecast a mean within a horizon while relying on the assumption of a constant volatility throughout that horizon. However, none of them examine whether the prices of construction material exhibit similar volatility following a sudden price surge or a price drop. The prospect of PACs and their associated trigger values is hindered in the absence of empirical assessments of their capacity to capture the volatilities in material prices. This paper fills …

Mitigating Melanin-Induced Bias In Pulse Oximetry: Optical, Algorithmic, Engineering, Hardware And Modeling Tools, Mckenzie Bradley, Sydnee Barrett, Ty Mckelvey, Jeremiah Carpenter, Delphine Dean

Publications

Melanin, the primary determinant of skin pigmentation, absorbs light at wavelengths that can have significant impact on the accuracy of pulse oximetry and other optical biosensing methods. This narrative review examines key factors influencing melanin-dependent pulse oximetry inaccuracies, including optical interference in transmission and reflectance modes. These inaccuracies further highlight the need for use of standardized skin tone metrics in device testing and design such as the Monk Skin Tone scale and Individual Typology Angle for performance stratification. There are several approaches in development that hope to address the errors in pulse oximetry measurements on melanin-rich skin. These include algorithmic …

Performance Evaluation Of Kytc Bridge Deck Overlays Used For Maintenance Activities, Sudhir Palle, Christopher Goff

Kentucky Transportation Center Research Report

State departments of transportation use bridge deck overlay systems to prolong bridge deck service lives. Consisting of a thin layer of material applied to a concrete bridge deck surface, overlays form a protective barrier that improves ride quality, protects embedded reinforcement from harsh environmental conditions, enhances structure durability, and improves deck drainage. Over the past 20 years, the Kentucky Transportation Cabinet has made significant investments in overlays, rehabilitating nearly 5,000 bridge decks with them — roughly ¹/₃ of all bridges statewide. Given the significant investment in overlays, and the fact they degrade over time — eventually re-exposing bridge …

Electrical Characterization Of Germanium Tin Alloys And Devices For Space Reliability, Kevin K. Choe

Theses and Dissertations

GeSn (germanium tin) alloys are potentially well suited for near-mid infrared space optoelectronic applications. Alloys of GeSn have similar properties to group III-V and mercury-cadmium-telluride semiconductors and are compatible with cost-effective complementary metal oxide semiconductor (CMOS) manufacturing technology. Recent progress in non-equilibrium remote plasma-enhanced chemical vapor deposition (RPECVD) has enabled the crystalline growth of GeSn with Sn concentrations of up to 10% without Sn surface segregation. Several experimental studies in previous literature report CVD- or molecular beam epitaxy (MBE)-grown GeSn alloys achieving a direct bandgap with 6%-9% Sn content. This novel growth technique opens opportunities for a cost-effective, next-generation optical …

Validation And Proposed Expansion Of The Data-Driven D Region Model, Kevin M. Watson

Theses and Dissertations

Predicting ionosphere effects on radio wave propagation is critical for communications and over-the-horizon radar systems. The D region is challenging to model for several reasons, one of which is chemical complexity. Ion density changes during sunrise/sunset introduce substantial uncertainty in electron density profiles (EDPs). The Data Driven D Region (D3R) model solves electron densities through an ion chemistry model and assimilates relevant space weather inputs. This study evaluates D3R against the Faraday International Reference Ionosphere (FIRI) and measurements using Very Low Frequency (VLF) propagation paths. Space weather event impacts on D3R EDPs are evaluated during the disturbed period from 8-12 …

Tensile Creep Of A Hybrid Polymer-Matrix/Ceramic-Matrix Composite At Elevated Temperature, Waleed S. Alshehri

Theses and Dissertations

Advanced aerospace systems require structural materials that can perform reliably in high-temperature environments for long durations. The performance of standard polymer matrix composites (PMCs) in these conditions is often limited by their susceptibility to time-dependent deformation, such as creep. The objective of this research is to characterize the high-temperature creep behavior of a novel unitized material system comprising a polymer matrix composite (PMC) and a ceramic matrix composite (CMC) co-cured together. The PMC part consists of the polyimide matrix reinforced with laminated carbon fibers woven in an eight harness satin weave (8HSW). The CMC part consists of a zirconia-based ceramic …

Multi-Fidelity Machine Learning Modeling For Aerodynamic Response Prediction Of Aerospace Vehicles, Ethan S. Jackman

Theses and Dissertations

Hypersonic vehicle design requires understanding complex aerodynamic phenomena across the full flight regime. This study presents a novel MF surrogate modeling methodology that enables the prediction the full field response across a vehicle’s surface. A Space-Filling Curve (SFC) is used to convert unstructured data into 1D vectors. The a Convolutional Autoencoder is used with transfer learning to reduce the dimensionality of the data. An Emulator-Embedded Neural Network (E2NN) combines multi-fidelity data for fast, accurate predictions. A benchmark analytical example and hypersonic application are used to evaluate the methodology. Using various numbers of samples and sampling strategies it is found that …

Low-Cost Transfers For Cislunar Liaison Navigation, Ka'eo J. Swartzmiller

Theses and Dissertations

CubeSats have an inherent limitation on volume due to their small form factor. Naturally, this extends to the capacity of on-board ΔV, thus limiting the maneuverability of the satellites. This limited maneuverability makes it extremely important to be intentional when planning out mission trajectories. The cislunar region subjects these trajectories to the gravitational forces of both the Earth and the Moon, making it all the more necessary to deliberately plan out maneuvers. The Circular Restricted Three Body Problem (CR3BP) provides a simpler model for estimating the motion of spacecraft within the cislunar region, allowing for the gravitational forces to be …

Designing An Experiment To Create And Evaluate Behavioral Changes In Air Force Pilots' Fuel Efficiency, Jackson Macias

Theses and Dissertations

Fuel represents over 70% of the logistical resupply demand within the Department of Defense, with the United States Air Force accounting for most of that consumption. While prior fuel efficiency efforts have primarily focused on technical upgrades, this research explores how behavioral interventions can influence pilot decision-making and operational energy outcomes. Using the Theory of Planned Behavior (TPB) as a guiding framework, this study investigates the effects of targeted behavioral strategies on pilots’ attitudes, subjective norms, perceived behavioral control, intentions, and actual fuel-efficient behaviors. A quasi-experimental design was applied through a controlled pilot study using simulator flights. Six participants were …

Designing The Protocol For An Experimental Flight Simulation Study Encouraging Fuel Efficient Behavior, Thomas S. Reardon

Theses and Dissertations

This study designed and tested an experimental instrument to examine how pilots respond to fuel efficiency feedback in a flight simulator. A standardized flight plan, script, and hardware setup were created using X-Plane 12 software and physical flight simulator hardware. The chosen sortie guided participants from Monterey Regional Airport to Moffett Federal Airfield using instrument flight rules (IFR). The flight script provided step-by-step guidance to ensure consistent behavior across participants. The simulator was mapped to match real cockpit controls and allowed for precise data collection including flight time, altitude, heading, and fuel use. The goal was to support a larger …

Implementing Lean Principles To Enhance Warehouse Operations At King Abdulaziz Air Base(Kaab): A Case Study Of Royal Saudi Air Force (Rsaf), Saleh A. Alghamdi

Theses and Dissertations

The Royal Saudi Air Force (RSAF) relies on efficient logistics to sustain readiness. At King Abdulaziz Air Base, warehouse receiving inefficiencies caused delays and waste. This study used Lean principles and a six-month time–motion analysis, with Pareto and Fishbone tools, to identify 55% waste in dead pile and 75% in palletized shipments. Standard times of 5.98 and 6.55 minutes were set. Key recommendations include SOPs, cross-training, forklift certification, layout redesign, and RFID. Lean adoption could save 100+ labor hours and $4,000 annually, improving safety, accuracy, and mission readiness.