Engineering Commons^™

Lecun-Pso Hybrid Initialization Of Neural Network Using Asymmetric Gait Features For Classification Of Parkinson’S Disease, Michael Joseph Carter

Theses and Dissertations

Parkinson's disease (PD) is a complex condition with a wide range of clinical symptoms. It is a progressive neurological disorder that has afflicted an estimated 1 million people in the US and 10 million worldwide. The diagnosis of PD is typically based on the presence of clinical features, with no specific diagnostic test or biomarker. The methods of assessment for PD are also used, in whole or in part, for similar symptom diseases such as Multiple Sclerosis, Essential Tremors, Multiple System Atrophy, Supranuclear Palsy, Dementia with Lewy bodies and Huntington’s disease. Many of the current clinical tests have low sensitivity …

Novel Experimental Techniques For Pressure Transients, Luliang Zhang

Theses and Dissertations

This dissertation introduces novel experimental techniques for analyzing pressure transients, focusing on dynamic strain and pressure measurements to advance the understanding and application of Pulse Pressure Amplification in percussive devices. The research evaluates a high-speed linescan extensometer utilizing linescan Digital Image Correlation (DIC) on a Kolsky Bar to obtain strain data at high strain rates. This data is critical for accurate material characterization and simulations to model dynamic behavior. Additionally, a novel method for measuring dynamic pressure waves in pipe systems has been developed, enabling direct assessments of pressure amplification in devices such as tapered pipe systems. The findings contribute …

Leveraging Google Earth Engine For Computationally Efficient Pixel-Level Analysis And Vector Delineation From Satellite Data., Rishita Garg

Theses and Dissertations

Analyzing large-scale, high-resolution satellite imagery is a computationally intensive task requiring time and computing resources. This can be accelerated using cloud computing platforms such as Google Earth Engine (GEE) where computational and storage requirements can be scaled based on demand. However, cloud-based platforms for processing high-resolution imagery remain underutilized in environmental applications such as agriculture, and forest health. This thesis explored the application of GEE to two geospatial problems in agricultural conservation and disease mapping in forestry: 1) Extraction of agricultural field boundaries from Sentinel-2 satellite imagery, for use in conservation, precision agriculture, land management, and organization, etc., and 2) …

Study On Vehicle-Pedestrian Interaction Autonomy By Risk Potential Theory, Riku Kikuta

Theses and Dissertations

Vehicle–pedestrian interaction is a critical aspect of autonomous vehicle (AV) development, as socially acceptable AVs must account for pedestrian intention and behavior. Risk Potential (RP) theory provides a framework to build human-like AVs by modeling expert driver risk perception, but conventional RP models treat pedestrians as static obstacles and neglect their dynamics. This dissertation extends RP theory by incorporating pedestrian velocity and orientation into three new models: the RP velocity model, the RP related-velocity model, and the RP Pedestrian Potential Position (PPP) model. These models were implemented in the Navigating All Terrains Using Robotic Exploration (NATURE) autonomy stack and tested …

A Case Study On Redesigning Classroom Activities And Assessments For Generation Z Students, Sushma Shrinivasan

Theses and Dissertations

This dissertation investigates the dynamic interplay between pedagogical strategies, learner diversity, and emerging educational technologies through three interconnected studies. Study 1 compares Traditional instruction, Problem-Based Learning (PBL), and Simulation-Based Learning (SBL), revealing that while PBL and SBL enhance student performance—particularly PBL—their impact on perceived learning varies. Notably, SBL reduced perceived learning despite strong outcomes, underscoring the affective and metacognitive complexities of active learning. Study 2 examines the role of demographic factors such as gender, ethnicity, employment, and first-generation status, finding no significant main effects but identifying a key two-way and three-way interactions, suggesting that instructional effectiveness is influenced by the …

Integrated Experimental, Numerical, And Machine-Learning Framework For The Analysis Of Spray Dynamics In Diesel And Gasoline Direct-Injection (Gdi) Engines, Yassine El Marnissi

Theses and Dissertations

The regulation of diesel and gasoline direct injection (GDI) during cold starts has become subject to stricter numerical limits by both the Environmental Protection Agency (EPA) in the US and the European Commission (EC). For diesel engines, the EPA’s Clean Trucks Plan (Model Year 2027+) sets a certification NOₓ limit of 0.035 g/bhp-hr and an in-use fleet average limit of 0.050 g/bhp-hr, along with a PM limit of 0.005 g/bhp-hr, representing an 82.5% reduction in NOₓ compared to the former 0.2 g/bhp-hr standard. For gasoline engines, US standards regulate cold-start pollutants such as hydrocarbons (HC) ranging from 0.03 to 0.08 …

Power Resilience In Utah's Water Sector: A Survey Of Stakeholder Practices, Preferences And Potential, Tyler Christopher Peterson

Theses and Dissertations

Drinking water and wastewater services are vulnerable to disruptions because they rely heavily on the electric grid. As a result, power outages can lead to water outages, creating cascading failures that compromise sanitation, firefighting, healthcare, and daily routines. Although an important topic, there are little to no studies of water and wastewater power resilience at a geographic or state level. In this study we investigate the extent of existing backup power and renewable energy integration as well as the motivations and barriers around their power resilience. We collect our data through semi-structured interviews with staff at 19 urban and rural …

Climate-Driven Flood Risk Mapping And Adaptive Strategy Modelling For Coastal Tamil Nadu, Sakthi Kiran Dr Mr

Theses and Dissertations

Background: Tamil Nadu’s coastal corridor (Cuddalore–Sirkazhi; ~2,740 km²) experiences recurring floods driven by climate change, rapid urban expansion, and inadequate drainage across low-lying deltaic terrain. Existing flood assessments remain largely reactive and rely on static methods that fail to incorporate future climate projections, demographic growth, and evolving urban patterns.

Methods: This research develops a dynamic, climate-resilient flood risk framework integrating (i) long-term hydroclimatic trend analysis (1984–2023), (ii) satellite-based flood hazard mapping using multi-temporal Sentinel-1A and RISAT-1A SAR, (iii) CORDEX REMO2015 (RCP 4.5)–driven HEC-RAS 2D hydrodynamic modelling, (iv) machine-learning-based susceptibility modelling (RF, DT, SVM), and (v) scenario-based evaluation of structural mitigation …

Experimental And Theoretical Characterization Of Molten Salt Thermal Conductivity, Jacob C. Numbers

Theses and Dissertations

Molten salts form an ideal heat transfer fluid for advanced energy generation systems, including molten salt reactors (MSR). Accurate characterization of molten salt thermal conductivity is needed to confidently predict transient thermal behavior and optimize salt properties. Measurements are hindered by salts' challenging material properties, which---in the case of the needle probe device---induced unaccounted physical changes that limited its accuracy and repeatability. Sparse thermal conductivity data in general is exacerbated by a limited fundamental understanding of molecular energy transfer in liquids. This work extends the experimental capacity for compositional studies using the needle probe and proposes a theoretical model for …

Feed Network Design For Passive Beamforming In Hemispherical Phased Arrays, Daniel Flores

Theses and Dissertations

This thesis presents the design, fabrication, and evaluation of a four-element microstrip patch antenna array with a passive 1 to 4 corporate feed network operating at 5 GHz. A single inset-fed patch was developed on Rogers DiClad 880 to ensure accurate tuning and mechanical flexibility, achieving a measured resonance of 5.009 GHz with excellent return loss. The corporate feed network, synthesized using T-junction dividers and quarter-wave transformers, demonstrated strong impedance matching, balanced amplitude distribution, and broadside realized gain near 10 dBi when integrated with the array.

Beam steering was examined through simulation-based phase control, revealing effective scanning up to approximately …

Ai-Driven Electromagnetic Design And Performance Prediction Of Microstrip Antennas, Eduardo Javier Vazquez

Theses and Dissertations

This thesis investigates the application of Deep Learning to automate and accelerate microstrip antenna inverse design. The initial investigation was to predict microstrip antenna performance from its geometry parametric input, and found out that forward prediction with adopted geometric representation results in ill-posed scenario, high ambiguity and unstable mapping. The study later mostly focuses on the inverse prediction by machine learning from S11 parameter input to predict antenna patch geometry parameters instead.

A dataset of 5,000 ANSYS HFSS simulated antennas (later filtered to 4,136 valid samples) was generated using cubic spine -described geometry profiles. Multiple neural architectures were adopted for …

Boundary-Layer Mechanisms In Flow Over Triangular Porous-Textured Flat Plates: A Computational Fluid Dynamics Study, Luis Angel Alvarez

Theses and Dissertations

Growing demand for energy-efficient vehicles drives research into flow control strategies that mitigate aerodynamic drag. Active devices such as morphing flaps or plasma actuators offer real-time authority but require external power. Passive concepts, including riblets, tubercles, porous coatings, and miniature vortex generators, reshape the boundary layer without additional energy input. We propose an integrated passive solution called Triangular Porous Texturing (TPT). TPT combines the two mechanisms: a periodic array of triangular prisms that generate controlled streamwise vortices, and an embedded porous matrix that locally adjusts pressure gradients near the wall. Acting synergistically, these features attenuate near-wall turbulence, redistribute momentum, and …

Development And Testing Of A Prototype Erbium-Doped Lithium Tantalate Based Sensor For Infrastructure Crack Detection And Measurement, Alejandro Barrera

Theses and Dissertations

Ensuring the safety and longevity of infrastructure is crucial to safeguarding communities and preserving economic stability. In this study, the development of a novel sensor for detecting and characterizing cracks in infrastructure, particularly suited for deployment on Unmanned Aerial Vehicles (UAVs), is presented. The device utilizes a laser (operating at 980 nm) for excitation of erbium-doped lithium tantalate nanoparticles that emit 1550 nm wavelength, which stimulates a photodiode for data collection. The data was utilized to collect, process, and reconstruct topological information. The synthesized lithium tantalate nanoparticle samples vary in erbium doping percentages of 0.5%, 3%, and 10%. Experimental evaluation …

Feature Extraction From Railroad Bearing Onboard Vibration Sensors Using Machine Learning Models, Diego Cantu

Theses and Dissertations

The University Transportation Center for Railway Safety (UTCRS) has developed an algorithm capable of identifying defective railroad bearings, determining damaged component(s) within, and quantifying severity of the defects. The defect-detection algorithm requires the operating speed as an input, which is not readily available in field operation of onboard sensors. Therefore, onboard sensors deployed in rail revenue service must rely on Global Positioning Systems (GPS) to obtain speed, which can be power-intensive and susceptible to signal interference. This study covers the development of a vibration-based model that extracts operating speed from wireless sensor data to enable fully autonomous onboard diagnostics. Signal …

Towards Trustworthy Federated Learning, Alina Basharat

Theses and Dissertations

Federated learning is a collaborative training model in which multiple clients optimize aglobal model by transmitting updates to a coordinating server while keeping raw data on-device, thereby reducing direct data exposure and enabling iterative global improvement. However, the iterative communication process is vulnerable to malicious attackers that either deliberately destroy the model or curious to infer raw data. Moreover, learning from multiple agents may result in unfair results. To enhance trustworthiness within this setting, we employ two-sided norm-based screening (TNBS) that removes both abnormally large and abnormally small updates, pair it with a q-fair objective to emphasize high-loss (disadvantaged) clients, …

When Textures Trim Drag: Micro-Structures For Adaptive Drag Reduction And Flow Authority, Miguel Angel Olvera

Theses and Dissertations

Turbulent boundary layers are a major source of drag and performance loss. This thesis investigates Triangular Porous Texturing (TPT), apex-forward microstructures with optional bleed channels, as a passive concept for simultaneously reducing skin friction and strengthening boundary layer momentum near separation. Low-speed wind tunnel tests are conducted over tripped turbulent boundary layers on flat plates with three surfaces: a smooth baseline, a solid-crest TPT array isolating the knife-edge “slip-cut” effect, and a porous-bleed TPT array whose paired micro-channels vent a small fraction of the free stream. Time-resolved PIV provides wall-normal velocity fields; skin friction is inferred from near-wall shear, and …

Optimizing Pv Solar Array Design By Analysis Of The Industrial And Training Assessment Center (Itac) Database, Angel Samuel Fernandez

Theses and Dissertations

Since 2017, the Industrial Training and Assessment Center (ITAC) at UTRGV has included photovoltaic (PV) system evaluations in its industrial energy assessments. A review of these reports showed inconsistencies in PV system design, including variations in sizing methods, performance assumptions, and application of NEC requirements. To address these issues, this thesis develops a standardized and NEC-compliant methodology for designing PV systems, incorporating demand-based sizing, solar-geometry principles, and electrical calculations guided by NEC Articles 690 and 705.

This thesis focuses on demand-based PV system sizing and incorporates NEC-guided electrical design to ensure technical compliance and safety. System performance is evaluated using …

Performance Assessment Of Reconditioned Freight Rail Bearings Using Eddy Current Array For Enhanced Nondestructive Inspection, Eduardo Miranda

Theses and Dissertations

In North America, freight bearings removed from service must undergo a reconditioning process in accordance with Association of American Railroads recommended guidelines before reuse, with approximately 80% having been reconditioned at least once. This process includes bearing inspection, where repairable defects may be refurbished and returned to service with an extended performance range of 50,000 to 250,000 miles. Motivated by this extensive range in performance, researchers at the University Transportation Center for Railway Safety, in collaboration with MxV Rail, utilized a nondestructive evaluation method to enhance the reconditioning inspection process. An Eddy Current Array (ECA) was applied to bearing cup …

Examining The Relationship Between Title 14 Code Of Federal Regulations (Cfr) Part 147 Maintenance School Aviation Maintenance Technician (Amt) Instructor Experience And Instructor Pass Rates For Airmen Certification Standards (Acs) Element Subject Areas, Richard Lyman Johnson

Theses and Dissertations

This quantitative, correlational study examined the relationship between Aviation Maintenance Technician (AMT) instructor experience and student pass rates in 14 CFR Part 147 maintenance schools. Data were collected from February to August 2025 using purposive and snowball sampling, which yielded 67 complete responses. Instructor experience, measured in months of A&P-rated maintenance work prior to teaching, ranged from 1 to 684 months (M = 253.54, SD = 197.97). Student pass rates, defined as the proportion of students passing ACS element subject area courses, ranged from .52 to 1.00 (M = .95, SD = .07). Most instructors were male, White, over 50 …

Comparative Assessment Of Lower Limb Neuromusculoskeletal Activation And Joint Kinematics In Normal And Impaired Gait, Jack Ryan Schule

Theses and Dissertations

This thesis evaluates whether accessible and affordable technologies can provide clinically significant, quantifiable gait analysis comparable to traditional marker-based motion capture systems. Modern high-end systems offer excellent accuracy but remain financially and logistically inaccessible to many clinicians and researchers. To address this gap, a framework was developed using markerless pose estimation using the model, MediaPipe, inertial measurement units (IMUs) processed through an Extended Kalman Filter (EKF), and surface electromyography (sEMG) to measure joint kinematics and neuromuscular activity during gait. An experiment was performed where data was collected from participants with both normal gait and pathologies including: Osgood–Schlatter disease, Plica Band …

Effect Of Capillary And Viscous Forces On Carbon Dioxide Desorption In Porous Adsorbent Layers, Caroline Isabel Mcclung

Theses and Dissertations

Temperature swing adsorption-based (TSA) carbon dioxide (CO₂) separation processes, which involve an alternating flow of gases and liquids in adsorbent-coated microchannels, have been shown to yield superior and environmentally friendly performance than the existing processes. This technique begins by sending the impure gas mixture through hydrophobic silicalite adsorbent-coated microchannels, which results in the adsorption of CO₂. Subsequently, hot water heat transfer fluid (HTF) flows through the same channels, displaces the purified gas stream, heats the adsorbent, desorbs the CO₂, and removes that desorbed CO₂ from the channel. This stage is followed by cooling …

Qualitative Stereo Vision Using Distributed Extended Waltz Filtering, Ben Mathew

Theses and Dissertations

Stereo vision is a fundamental problem in computer vision, aimed at reconstructing three-dimensional scene structure from two or more two-dimensional images. Traditional stereo algorithms rely on quantitative disparity estimation, often constrained by calibration precision, lighting variations, and surface texture. In contrast, our proposed Qualitative Stereo Vision seeks to understand depth relationships and spatial configurations from multiple planar views through symbolic reasoning and constraint satisfaction, offering a more flexible and cognitively plausible approach to scene interpretation.

This dissertation presents a novel framework called Distributed Extended Waltz Filtering, designed to provide qualitative stereo vision, particularly in the presence of occlusions—a persistent challenge …

Modeling Xilinx 7-Series Fpgas Within The Verilog To Routing Project, Joshua Peter Fife

Theses and Dissertations

Verilog to Routing (VTR) is the most widely used open-source tool for experimenting with FPGA placement and routing algorithms, as well as assessing how architectural changes impact routability, timing, and power consumption.

Historically, VTR has been tailored specifically for Intel’s Altera-like FPGAs, lacking support for key features that would enable greater flexibility in describing other architectures. In this work, we introduce a fully functional 7-Series architecture capture from the Xilinx family, utilizing VTR’s scalable architecture description language. We detail the necessary upgrades to achieve this description, including the ability to describe L and T-shaped wires and target hard multipliers with …

Blockchain-Driven Pharma Supply Chains Towards Industry 6.0, Vijay Ramasamy R

Theses and Dissertations

The pharmaceutical supply chain is undergoing an unprecedented evolution in the wake of Industry 6.0, driven by the need for heightened transparency, security, and real-time intelligence. However, current systems suffer from legacy Enterprise Resource Planning (ERP) constraints, the risk of counterfeit products, temperature sensitivity, and scalability issues due to the surge in Internet of Things (IoT) data.

This research proposes a unified, blockchain-based framework that integrates legacy ERP systems, advanced AI driven forecasting, IoT-enabled traceability, and quantum-enhanced blockchain security to modernize pharmaceutical supply chains.

The study begins by addressing interoperability between ERP and blockchain using middleware and smart contracts, facilitating …

Manufacturing Of Origami-Inspired Mechanisms Via Sheet Lamination, Tyler R. Stevens

Theses and Dissertations

Origami-inspired mechanisms combine compact, lightweight, reconfig- urable devices, yet despite decades of growth in origami theory, industrial uptake remains limited. As a result, origami predominately appears as prototypes or in low-volume, bespoke applications. Manufacturing (which has received little development) remains the chief bottleneck: most origami fabrication routes are still under-explored, labor-intensive, and fundamentally unsuited to scale. This dissertation addresses that barrier by establishing a process-centric framework for origami manufacturing and demonstrates fabrication workflows capable of transitioning designs from prototypes to production. A survey of more than 180 publications on origami manufacturing approaches yields a manufacturing-oriented taxonomy that links each surrogate …

Electrode Engineering To Minimize Degradation In Lithium-Sulfur Batteries, Saheed Adewale Lateef

Theses and Dissertations

Lithium-Sulfur (Li-S) batteries have recently received significant attention as a potential candidate for next-generation energy storage technology. This is due to its high theoretical capacity (1675 mAh/g) which can provide theoretical energy density of 2500 Wh/kg as compared to 400 Wh/kg of the current Lithium-ion batteries. Moreover, the earth-abundant sulfur element as well as its environmental friendliness endows unique advantages on the cost and environmental impact. However, there are several roadblocks that need to be addressed for commercial adoption of Li-S batteries, such as: (i) poor conductivity of sulfur and its discharged product; (ii) solubility of lithium polysulfides and their …

Deep Learning-Based Change Detection In High-Resolution Remote Sensing Imagery, Hazem Badawy

Theses and Dissertations

Remote sensing has become a key tool for monitoring Earth’s surface over time, offering valuable insights into both natural and human-driven changes. Among its many applications, change detection focuses on analyzing multi-temporal imagery to reveal how specific areas evolve across different time periods. It plays a pivotal role in Earth observation applications, including urban development monitoring, environmental degradation assessment, and disaster response. However, existing approaches often struggle with limited contextual awareness, high sensitivity to noise, and imprecise localization of change boundaries, especially with high-resolution imagery. This thesis investigates the complex problem of change detection in remote sensing imagery by proposing …

Influence Of Channel Geometry And Inflow Hydrograph On Hydraulics And Air Volume Around Shafts Of A Stormwater Main, Lylie Vindie Wilkie

Theses and Dissertations

Stormwater management in urban areas is complex, in part because of difficulties related to modeling water flowing in closed conduits, as well as to controlling odor, noise, and pipe corrosion. This thesis summarizes the main findings of a study on how changes in inflow discharge and the geometry of a stormwater main may affect water flow, and how changes in water depth impact air volume and pressure around an air shaft. The study is conducted using CHAN, a one-dimensional model that simulates both flow hydraulics in mains and associated changes in air volume and pressure around air shafts. Main difference …

Ai-Driven Autonomous Manufacturing: A Novel Taxonomy, Vision-Guided Planning, And Diversity-Aware Active Learning Frameworks, Ibrahim Yousif

Theses and Dissertations

Manufacturers face two opposing challenges: the escalating demand for customized products and the pressure to reduce lead times. Current manufacturing equipment, although reliable, operates at the limits of its technology and lacks adaptability to dynamic environments. This trade-off has been described as the optimal degree of automation, a threshold beyond which further automation incurs more cost than benefit. Smart manufacturing has introduced adaptive, data-driven systems, but many deployments still lack the contextual adaptability and autonomous decision-making required to handle unplanned disruptions. This underscores the need for intelligent, autonomous systems capable of real-time adaptation without costly reconfiguration, minimizing human intervention during …

Towards Accurate First-Principles Modeling In Heterogenous Catalysis: Ethane Dehydrogenation And Hydrogenolysis Over Pt Catalysts, Mubarak Ayo Bello

Theses and Dissertations

First-principles modeling has become central to heterogeneous catalysis research, offering mechanistic insight and guiding catalyst design, yet conventional approaches often struggle to accurately describe complex catalytic systems due to methodological uncertainties, simplified assumptions, and the structural diversity of nanoparticle catalysts. This dissertation addresses these challenges using ethane dehydrogenation (EDH) and hydrogenolysis (EH) over platinum catalysts as model systems. The first study benchmarks density functional theory (DFT) functionals against the random phase approximation (RPA) for the EDH network on Pt(111), identifying cost-effective functionals and demonstrating the efficiency of BEEF-vdW ensembles for capturing functional uncertainty. The second study (addressed in prior work) …