Engineering Commons^™

Applications And Comparisons Of Machine Learning Methods In Ultra-Fast Laser Control, Aasma Aslam

Electrical and Computer Engineering ETDs

This dissertation demonstrates the applications and comparative analyses of machine learning methods in ultrafast laser control. By learning the relationship between the system’s input parameters and output pulse characteristics, the performance of a laser can be significantly improved. In this work, the results are presented in two stages by utilizing data from the femtosecond laser system. The first stage concerns two neural networks, named NN1 (fitrnet) and NN2 (feedforwardnet). The second stage, which extended with five different models, namely the linear regression (fitlm), the support vector machine (SVM), the Gaussian process regression (GPR), the boosted tree (fitrensemble), and LASSO (fitrlinear), …

Cortical Bone Density And Thickness Assessment Of Intraradicular Sites In Adolescent Patients Using Cbct Imaging, Sara Endo

UNLV Theses, Dissertations, Professional Papers, and Capstones

Background: The indications for the use of cone beam computed tomography (CBCT) in orthodontics has grown since it was first introduced and dentists are discovering new ways that 3D images enhance diagnosis and treatment planning. Evaluating bone quality and quantity can be measured as bone density and thickness in CBCT imaging and is helpful for temporary anchorage device (TAD) placement in orthodontic treatment. TADs rely on primary stability and are commonly used in orthodontic treatment to increase anchorage and expand the limit that nonsurgical orthodontics can provide.

Objectives: This study aims to assess the bone thickness and density at different …

Machine Learning Assisted Development Of Al0.2cufemnni High Entropy Alloy Through Selective Laser Melting, Hareharen K Mr

Theses and Dissertations

High Entropy Alloys (HEAs) are an emerging class of advanced materials that have gained significant attention due to their exceptional mechanical strength, thermal stability, and structural performance. Unlike conventional alloys based on a single principal element, HEAs are composed of multiple elements in a near-equiatomic ratio. Despite these advantages, designing HEAs with tailored properties is difficult because of the enormous number of possible combinations and the limitations of traditional trial-and-error methods. To overcome these challenges, this study presents a machine learning (ML) based approach to accelerate the design and development of an HEA.

In this work, a newly designed composition, …

Design And Uncertainty Methodology In High Efficiency Filtration Media Testing, Jeremy Andrei Adriano

Theses and Dissertations

Electrospun nanofiber media are being developed as potential alternatives to conventional HEPA filtration materials due to their small fiber diameters and tunable microstructures. To support future testing of these materials, the Small-Scale Test Stand (SSTS) at the Institute for Clean Energy Technology (ICET) requires modifications to ensure accurate and repeatable aerosol filtration measurements. Electrospun filters introduce challenges including fragile media structures and uncertain filtration efficiencies that may allow particle penetration to downstream instrumentation. This work evaluates adaptations to the SSTS design to support testing of electrospun filtration media. In addition, an uncertainty framework for aerosol measurements obtained using a Scanning …

The Effects Of Experiential Learning On Engineering Self-Efficacy: A Study Of The Impact Of Inperson And Virtual Internships, Co-Ops, And Research Experiences, Sunny Bharat Patel

Theses and Dissertations

This dissertation examined the relationship between participation in Engineering Learning Experiences (ELEs) and engineering self-efficacy, with particular attention to differences among ELE types (internships, cooperative education, and undergraduate research) and delivery modalities (in-person versus hybrid/virtual). Grounded in social cognitive theory, this study sought to better understand how work-related experiential formats influence students’ confidence in their ability to succeed in engineering tasks and professional contexts. As engineering programs and industry increasingly adopt flexible and technology-mediated environments, examining how these experiences shape beliefs about engineering capability is both timely and necessary. Using a mixed-methods approach, quantitative analyses compared self-efficacy outcomes across students …

Experimental Investigation Of The Effectiveness Of Various Stitching Methods On Arresting Mode-Ii Interlaminar Damage Propagation In Geometrically-Scaled Stitched Resin-Infused Composites, Allison Jean White

Theses and Dissertations

This thesis presents an experimental and analytical investigation of mode-II interlaminar fracture in geometrically-scaled quasi-isotropic resin-infused composites, with emphasis on through-thickness stitching as reinforcement. A global-local framework integrating load-displacement response, size effect fracture energy analysis, and digital image correlation-based separation measurements enabled direct comparison between unstitched and stitched configurations. Unstitched laminates exhibited pseudo-ductile behavior but significant post-peak load drops (16.7–26.8%) and a small fracture process zone (FPZ) of 0.73 mm, limiting stable crack growth. Stitching preserved pre-peak stiffness while reducing post-peak load drops by 43–95%, increasing effective fracture energy by 39.7% (to 2.413 N/mm), and expanding the FPZ to 2.85 …

Development Of Carbon-Fiber-Reinforced Composite Rotor Sleeves For High-Speed, Multi-Layer Ferrite-Based Interior Permanent-Magnet Motors, Andrew Walters

Theses and Dissertations

This research investigated whether a non-wound carbon fiber reinforced composite (CFRC) sleeve could serve as an effective retention mechanism for a high-speed, multi-layer ferrite-based interior permanent magnet motor. Material characterization testing was conducted on IM7/CYCOM-5320 and IM7/8552, with IM7/8552 selected due to its superior commercial availability. Experimentally obtained properties for both materials fell within acceptable tolerances of published values. Sleeves were manufactured to rotor design specifications (50-mm width, 1.2-mm thickness, 88.6-mm diameter) and tested per ASTM D2290 Procedure A to determine apparent hoop-failure stress. These experimental results validated a finite element model of the D2290 test, confirming realistic strain patterns …

Feasibility-Aware Deep Reinforcement Learning For Sustainable Timber Procurement Under Hurricane Demand Uncertainty, Jarod Wright

Theses and Dissertations

The timber supply chain connects landowners and mills to provide wood products but faces challenges from stochastic demand, seasonal variations, and disruptions such as hurricanes. Fur- thermore, sustainability concerns like transportation emissions create trade-offs in procurement. This study proposes a feasibility-aware Deep Reinforcement Learning framework for sustainable timber procurement and inventory control under joint demand–hurricane uncertainty. We develop a stochastic mathematical model capturing mill-landowner interactions, seasonal demand, hurricane- driven pricing, and carbon emissions. The problem is formulated as a constrained Markov decision process and solved using Proximal Policy Optimization with a feasibility-enforcing layer. A Mississippi-based case study with 2,100 landowners …

Improving And Supporting Flight Instructor’S Decisions For First Solo, Isabella Piasecki

Theses and Dissertations

Flight instructors have the burden of determining when a student is ready for their first solo flight, and many have expressed uncertainty over their own decision-making skills during this phase of a student’s training. Prior studies have examined flight instructors’ pre-solo decisions in other countries, but no such study has been conducted with American flight instructors. For this study, current flight instructors with multiple prior endorsements for a student pilot’s first solo were interviewed to identify the more abstract concepts they use to guide their decision. Qualitative themes were identified from their experiences. Using this information, a checklist was developed …

A Cradle To Grave Life Cycle Assessment Of Captured Landfill Methane Abatement Strategies, Joshua Caleb Richard

Theses and Dissertations

Landfill methane mitigation strategies are commonly evaluated using percentage-based leakage assumptions and linear scaling models. These approaches may misrepresent system performance at varying throughput levels and real-world operating scenarios. This thesis develops a system-level life cycle assessment framework that incorporates both fixed infrastructure losses and employs sensitivity analysis to more accurately characterize emissions from landfill gas management pathways. Three scenarios are evaluated: methane capture and flare, methane capture and combustion for electricity generation, and methane upgrading with pipeline injection as renewable natural gas. Results demonstrate that emissions models over- dependance on static factors may inadvertently lead to under-reporting and provide …

Machine Learning-Based Decision Support Models With Applications In Postsecondary Education, Marco Paolo Anglesio

Theses and Dissertations

This dissertation investigates the deployment of machine learning methodologies in an industrial engineering framework for the development of advanced decision support systems in the context of enrollment management. Drawing on techniques from educational data mining, the research addresses three key phases in the lifecycle of traditional and non-traditional students. First, it analyzes student retention using predictive classification models designed to identify individuals at elevated risk of attrition. Second, it employs temporal convolutional networks for time series forecasting, estimating aggregate enrollment levels over highly variable, finite planning horizons on the basis of partially observed data and using an asymmetric loss function. …

Developing And Evaluating U.S. Army Bridging For Ship Simulation, Jacob C. Hodges

Theses and Dissertations

This research investigates the intricacies of ship simulation and developmental processes for integrating wet gap crossing capabilities into a simulated environment. The US Army Mark III Bridge Erection Boat (BEB) and Improved Ribbon Bridge (IRB) were modeled in commercial off the shelf (COTS) and Government Co-Owned (GCO) navigation software suites to determine their performance capabilities and limitations. Each model was constructed using naval architecture concepts to accurately capture their hydrostatic and hydrodynamic effects before being validated against available performance data and expert elicitation from expert US Army watercraft operators. Models were configured and tested in simulated river flows with current …

Harmonic Response Analysis Of Asymmetric Double-Wishbone Suspension Systems For Amphibious Vehicle Stability, Harper K. Mccraw

Theses and Dissertations

Amphibious vehicles in the surf zone face severe hydrodynamic forcing, yet their internal suspension dynamics remain under-characterized. This research quantifies the non-linear dynamic response of an asymmetric double-wishbone suspension under regular wave impact. Using a physical model in a wave flume and a Qualisys motion-capture system, global rigid-body roll angles were processed through a decoupled kinematic numerical framework to isolate time-domain strut displacements. To evaluate stability, the data was transformed into the frequency domain to calculate Total Harmonic Distortion (THD). Results indicate that all test configurations exhibited significant non-linearity, primarily driven by mechanical clipping as struts reached their physical travel …

Exploring Ai-Driven Scaffolding For Critical Questioning In Argument Evaluation, Ebenezer A. Belete

UNLV Theses, Dissertations, Professional Papers, and Capstones

The fast-paced changes caused by generative AI (GenAI) innovations call for exploring the potential benefits of GenAI in empowering 21st-century pedagogical strategies. Previous studies in the field of argumentation have shown how students can benefit from using critical questions. However, scaffolding argument evaluation through custom GenAI using critical questions has not been systematically investigated. This study involved two components: (1) designing and determining the usability of a GPT-powered conversational assistant (CQMAA Conversational Assistant) and (2) testing its impact on participants' efficacy for argument evaluation and their acceptance of GenAI as a learning tool through a pretest–posttest experiment. A convergent mixed-methods …

A Near Linear-Phase Analog Frequency Sampling Filter Design Framework Using A Second-Order Trust-Region Optimization Technique, Edreese Basharyar

UNLV Theses, Dissertations, Professional Papers, and Capstones

Analog frequency sampling filters (FSFs) provide an efficient means of realizing finite impulse response (FIR)-like behavior in continuous-time systems, but their practical implementation is constrained by the requirement for perfect pole-zero cancellation along the imaginary axis. Because exact cancellation is physically unattainable due to component variations, ideal linear-phase Type 1 analog FSFs exhibit uncancelled poles that result in system instability. To address this limitation, this thesis introduces a near-linear-phase design framework for Type 1 analog FSFs that achieves both stability and design flexibility through the inclusion of a damping constant, ρ, which shifts the poles into the left half of …

Criticality Safety Evaluation To Address Potential Over Conservative Restrictions In 49 Cfr Fissile Materials – Exceptions, Avian Blumhorst

UNLV Theses, Dissertations, Professional Papers, and Capstones

The U. S. Department of Transportation’s (DOT) 49 CFR 173.453 Fissile Exceptions provide a regulatory classification that helps eliminate burdensome regulatory requirements. The current fissile exceptions are based on past technical basis reviews. These reviews may be overly conservative, and the final ruling potentially applied significant administrative over-conservatism. This thesis reviewed and presents several recommendations to the fissile exception criteria, as well as 49 CFR 173.453 section’s additions.

Using Monte Carlo N-Particle (MCNP) code version 6.3.0, several infinite sea mixtures and array systems were modeled for fissile isotopes 233U and 235U. The research demonstrated that for fissile exception (a) there …

An Optimization Method For Near-Linear Phase Analog Frequency Sampling Filter Design, Leonardo Ledesma

UNLV Theses, Dissertations, Professional Papers, and Capstones

Analog frequency sampling filters (FSFs) realize a desired frequency response by interpolating a frequency response through a set of harmonically related frequency samples from the filter’s frequency response and are magnitude and phase coefficients used in the filters transfer function. FSFs can be designed to have exact linear phase which makes the FSF attractive for many applications. A FSF’s system transfer function (STF) shows that the filter can be implemented by a series connection of a comb filter and a parallel array of resonators. However, the FSF requires that the zeros created by the comb filter cancel the imaginary axis …

Visual Interpretability Of Multimodal Tissue Perfusion Classification Using Grad-Cam And Saliency Maps, Metehan Zorluoglu

UNLV Theses, Dissertations, Professional Papers, and Capstones

Accurate identification of the tissue perfusion phase from hand images can aid doctors in decision-making with non-invasive techniques. The present study proposes a multimodal deep learning model for classifying the tissue perfusion phase using infrared, thermal, and visible spectrum images of the human hand. The proposed model consists of various preprocessing techniques such as manipulation, homography alignments, and masking. The significant contribution of this thesis is the interpretability analysis of deep learning models, achieved through the analysis of saliency maps and the Gradient-weighted Class Activation Mapping (Grad-CAM) methods. The purpose of this method is to find out how the convolutional …

Model Based Control And Hil Verification Of An Integrated Battery Management System, Catalin Sabou

UNLV Theses, Dissertations, Professional Papers, and Capstones

The rapid advancement of electric vehicle technologies necessitates highly reliable Battery Management Systems (BMS); however, validating embedded supervisory logic presents a notable challenge. While physical pack testing is accurate, it is costly and hazardous for early stage software evaluation. This thesis presents the design, implementation, and rigorous validation of an integrated BMS developed for the Battery Workforce Challenge, bridging the gap between model based design and safe hardware execution. The core of this work is a model based supervisory controller, developed in MATLAB/Simulink and executed on an STM32G4 embedded target. To facilitate embedded validation while preserving a representative battery environment, …

Performance Analysis Of Video Coding For Machines With Vision Transformers, Vaishnavi Dhulipudi

Electronic Theses and Dissertations

This thesis investigates the performance of Video Coding for Machines (VCM) with Vision Transformer based object detection models. While existing VCM studies and tool designs have largely been developed under CNN-based assumptions, recent advances in computer vision have shown the growing importance of transformer based models. Motivated by this shift, this work studies whether VCM compressed data remains suitable for Vision Transformer based inference in addition to conventional CNN-based task networks.

To address this problem, three representative transformer based object detection models were selected: DETR, SWIN, and YOLOS. These models were chosen to represent different architectural styles, namely a CNN …

A Study & Comparison Of Lift Boosters For An Unmanned Aerial Vehicle, Trevor Sean Dady

Theses and Dissertations

Unmanned aerial vehicles are becoming increasingly prevalent in modern society for tasks, such as package delivery, defense, and cinematography. Due to this surge in applications, many researchers have begun to search for improvements to unmanned aerial vehicles for their lift and thrust properties. Potential solutions to magnify an unmanned aerial vehicle’s thrust capability are the implementation of Coanda surfaces, nozzles, or bowl-shaped structures on each propeller. Coanda surfaces provide additional lift force by creating a vacuum in response to the adhesion of fluid to the smooth surface. Nozzles can constrict the flow of air, while also increasing its velocity. The …

The Use Of Tactile Stimulations To Mitigate Somatic Anxiety Responses: A Pilot Study, Abigail C. Robbins

Masters Theses

Anxiety is the body’s response to detected danger or stress. Physiological responses include shallow breathing, increased heart rate, sweating, shaking, and muscle tension. Roughly 33.7% of the population experiences anxiety, with approximately 40 million adults in the United States being affected by the disorder. Anxiety can create severe personal, social, and economic burdens. Traditional treatments of anxiety disorders such as medication and psychotherapy can be effective, but present multiple barriers such as cost, accessibility, and side effects. As a result, there is a growing industry for non-invasive, low-cost solutions that can help individuals regulate their physiological anxiety responses and reduce …

Experimental Measurements Of The Forces Acting On A Submerged Beam Using High-Speed Videography, Madelyn Burrell

Masters Theses

The interaction of structures and fluids is highly relevant in many fields but difficult to accurately and reliably characterize. This study demonstrates a novel method of simplifying such problems by analyzing the structural deformations directly, without needing to explicitly solve for the fluid aspect. Six cantilever beams of varying properties were submerged in still water and released from an initial deflection at the free end: the cases consisted of three beam shapes (one of uniform width, one with a narrower free end, and one with a wider free end), with an end mass attached or detached. High-speed videography was utilized …

Fault Location In Dc Microgrids Using Traveling Waves, Sajay Krishnan Paruthiyil

Electrical and Computer Engineering ETDs

In DC power systems, rapid fault location is crucial for maintaining reliable operation, particularly with the prevalence of DC-DC converters. This study investigates fault location techniques in DC systems utilizing Traveling Waves (TWs). Following data normalization, multi-resolution analysis employs discrete wavelet transform to capture high-frequency patterns of TW's wavelet coefficients. Parseval's theorem is utilized to quantify the energy of these coefficients. First, a curve-fitting technique is employed to estimate fault locations in DC microgrids. Then, two transfer learning approaches are proposed: first approach integrates Parseval energy curves into a Gaussian process estimator, while second employs feedforward neural network for fault …

Comprehensive Analysis Of Spray Development And Low Temperature Combustion Characteristics In A Cvcc With Nvh Of Renewable Aerospace Fuels: Hefa & Ft Synthetic Kerosene (S8) Compared To Jet-A & Ulsd, Coleman Norton

Honors College Theses

A comprehensive analysis was conducted to research the viability of Hydroprocessed Esters and Fatty Acids (HEFA) and S8 Synthetic Kerosene fuels as a drop-in replacement for conventional petroleum-based fuels, Jet-A and ULSD (Ultra Low Sulfur Diesel). Global transportation remains heavily dependent on liquid fossil fuels, while renewable aerospace fuels offer a promising pathway to reducing life cycle greenhouse gas emissions and pollution. However, the combustion performance and long-term feasibility of these fuels remain insufficiently characterized. This study performed a thorough assessment of each fuel's thermophysical and combustion properties. Thermophysical characterization encompassed viscosity, freezing point, energy density, spray atomization, and volatility. …

Investigating Creative Possibility Using Automated Composition, Kian Drees

Undergraduate Honors Theses

As a constructive method, Johann Joseph Fux’s theory of counterpoint defines a space of musical possibility for contrapuntal composition. I developed a computational method for generating melodies to systematically investigate selected properties of this space. My program recursively generates a tree of all possible cantus firmus melodies of a specified length or all possible first species counterpoints on a given cantus firmus, starting with an empty root node and adding child nodes representing possible musical notes at each step until the specified length is reached. I then investigated several properties of the generated melodies, such as the approximate relationship between …

Active Brazing Of Single Crystal Al2o3 To Kovar Alloy With Agcuzr Filler Metal, Anthony M. Mcmaster

Mechanical Engineering ETDs

Brazing provides high strength and hermetic joining between metal, ceramic, and composite materials. Origins of the brazing process trace back to 3000BC, yet the technique continues to maintain relevance and demand across aerospace, medical, electronic, optical, and mechanical engineering. Here, single crystal Al2O3 (sapphire) was joined to Kovar in a single step via an AgCuZr active braze filler metal. The microstructure of the completed joint was investigating using microscopy and spectroscopy techniques. A unique braze chamber, paired with an optically clear top substrate (sapphire), allowed further investigation into the dynamics of the active braze process via in situ video monitoring. …

Improving Human Visual Search: Enhancing Lung Cancer Nodule Detection In Medical Images, Christopher Khajira

Masters Theses

Human visual search involves the identification of relevant signals within information-rich environments, which is a fundamental problem in visual perception. While detection accuracy and response time are commonly used to evaluate performance in visual search, these measures do not reveal the underlying cognitive and computational structure that produces observable behavior. A key challenge lies in distinguishing between competing processing architectures, particularly in complex visual domains where different models can produce similar behavioral outcomes. This study addresses this challenge by developing a computational experimental framework for analyzing visual search behavior using System Factorial Technology (SFT). The experimental framework integrates naturalistic medical …

Simulated Intelligence, Surveillance, And Play, Atienah Cape

Theses - ALL

This MFA thesis explores modern panopticism and the feeling of being watched by creating and installing Four Real Friends, an interactive robotic artwork inspired by the 1998 Furby. The project looks at how surveillance technologies are not just outside forces, but part of daily life, often feeling familiar, playful, and even social. The installation uses hardware design, custom circuits, computer vision, and real-time data display to collect and process how visitors interact in the gallery. Its nostalgic and friendly look encourages people to take part, while still showing how data is collected and displayed as it happens. This makes surveillance …

Scalable Advanced Control Of Building Hvac Systems Using Physics-Informed Machine Learning, Xuezheng Wang

Dissertations - ALL

Buildings account for approximately 40% of total energy consumption in the United States, with HVAC systems representing the single largest energy end-use. Advanced control strategies such as model predictive control (MPC), reinforcement learning (RL), and differentiable predictive control (DPC) have demonstrated significant energy savings in individual studies, yet their widespread adoption remains limited by the lack of scalable, control-oriented dynamic models, the absence of consensus on control strategy selection, and the gap between single-zone research and multi-zone real-building deployment. This dissertation addresses these barriers through an integrated research program spanning physics-informed machine learning (PIML) model development, advanced control evaluation, and …