Electrical and Electronics Commons^™

Polysaber: A Custom Reactive Lightsaber Soundboard, Pedro B. Medeiros

Computer Engineering

The PolySaber project was developed as a custom reactive lightsaber control system built as a fully custom PCB design. The purpose of the project was to create a lower-cost and more customizable alternative to commercially available lightsaber soundboards while simultaneously providing hands-on experience in PCB design, embedded systems development, and hardware integration. Commercial lightsaber soundboards are expensive, proprietary, and difficult for hobbyists to customize. The PolySaber project addresses this by creating a modifiable hardware platform built around the ESP32 microcontroller. The system supports programmable firmware, RGB NeoPixel blade control, motion sensing, reactive swing and clash effects, onboard audio amplification, and …

Design And Characterization Of A Pulsed Electric Field Chamber For Microalgae Lysis, Connor Strutin

Electrical Engineering

Microalgae are a promising renewable source of biofuel due to their high lipid content and rapid growth rates; however, algae cells must be electroporated (lysed) to release these lipids. The system developed in this project applies short (40 μs–10 ms), high-intensity (up to 33 kV/cm) pulsed electric fields (PEF) across cell membranes to enable electroporation.

Our lab-scale PEF chamber generates uniform, high-intensity electric fields using parallel-plate electrodes with sub-millimeter spacing. The system is designed to efficiently lyse microalgae cells for lipid extraction and biofuel production.

Analysis And Design Of A 2-Bit Millimeter-Wave Reconfigurable Intelligent Surface And Investigation Of Fss-Assisted Angular Stability, Max Spalek

Master's Theses

Millimeter-Wave (mm-wave) technology utilizes high frequency spectrum and can deliver multi-gigabit speeds, ultra-low latency, and massive bandwidth capacity. However, this technology is rather new and many technical challenges remain. On the other hand, Reconfigurable Intelligent Surfaces (RIS) have emerged as promising structures for controllable electromagnetic wavefront manipulation in wireless communication systems. This thesis presents the design of a 2-bit RIS unit-cell element operating throughout the 30–34 GHz mm-wave band, where the structure was progressively refined from an initial resonating geometry toward a grounded reflective RIS configuration. The proposed structure utilizes PIN-diode switching states to produce four discrete reflected phase states …

Development Of A Multi-Mode Switching-Inverter Laboratory Module For An Introductory Power Electronics Course, Darcy Eliasi

Master's Theses

DC–AC converters, or inverters, are essential power‑electronic interfaces widely used in photovoltaic systems, microgrids, energy‑storage installations, and numerous other modern electrical applications. This thesis presents the design, construction, and testing of an improved laboratory module developed as a student learning tool for demonstrating four fundamental inverter switching techniques: simple square wave (SSWI), modified square wave (MSWI), bipolar PWM, and unipolar PWM. Building upon the previous module, the improved design centers on three key enhancements. These include the selection of a more suitable wave‑generation solution, a multiplexer‑based mode‑selection architecture that reduces user complexity and eliminates conflicting signal configurations, and the integration …

Autonomous Exploration Of An Environment With Static Obstacles Using A Ppo Agent, Brandon Knight

Theses

Research in autonomous exploration has created many effective algorithms that have been tested and proven to work in many different virtual and physical environments. Many optimizations have also been developed to reduce computational effort and increase exploration speed.

However, despite optimizations, these algorithms can still require considerable computational effort and time to explore even small environments. To obtain further improvements in computation and exploration speed, a reinforcement learning agent using actor-critic style proximal policy optimization (PPO) is trained to explore various environments efficiently, then compared to an algorithm using contemporary exploration methods.

Testing is performed in virtual environments with ideal …

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, …

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 …

Radio Frequency Resonate And Fire (Rf-Raf) Neurons Supporting Device Classification, David L. Weathers, Michael A. Temple, Brett J. Borghetti

Faculty Publications

Radio Frequency Fingerprinting (RFF) enables passive physical-layer device authentication by exploiting unintentional hardware variations in wireless transmitters. Neuromorphic implementations are attractive, given their potential for low-latency, energy-efficient inference capability under Size, Weight, and Power (SWaP) constraints at the edge. A new RFF capability is demonstrated here using recently introduced Radio Frequency Resonate-and-Fire (RF-RAF) neurons and eight WirelessHART devices. Performance is evaluated for RF-RAF-generated fingerprints against the established Gabor Transform (GTX) baseline using three classifier architectures: Random Forest (RndF), Convolutional Neural Network (CNN), and a Time-Incremented Spiking Neural Network (TI-SNN). The results show that RF-RAF fingerprints achieve an average classification accuracy …

Riki&Dolphin: Real Time Data Transmission From The Bottom Of A Cave To A Website, Luca Tringali, Giacomo Canciani Dr., Tecla Tripari, Alexander Debenjak, Caterina Bearzotti

International Journal of Speleology

Coming from over 10 years of experience in cave monitoring in northeast Italy, Gruppo Speleologico Talpe del Carso, has designed Riki and Dolphin: customizable, low cost, and easy to assemble tools for getting real time data transmission from the bottom of a cave, even underwater, to a webserver. Their use has been tested to monitor air temperature inside the Abisso Bonetti Cave (Classical Karst, Italy), proving for the first time that a cave in Gorizian Karst can systematically be colder than the outdoor temperature even in winter, recording an internal temperature even lower than 0°C. The Dolphin device can be …

Data-Driven Physical-Layer Optimization For Rf And Optical Communications: Transmitarray Metasurfaces, Contextual-Bandit Mud, And Coherent Optical Links, Chengtao M. Xu

Doctoral Dissertations and Master's Theses

This dissertation studies three physical-layer optimization problems that share a common difficulty: the forward model, whether an electromagnetic solver or a statistical channel model, is either too expensive to evaluate at design scale or too unstable to hold across a single processing block. The first two problems are treated in their own right, as problems in antenna design and in multi-user detection over time-variant channels; the third carries the methodology onto a coherent optical link, where size, weight, and power constraints make a small-satellite deployment the natural target.

The antenna work targets a tri-layer pixelated unit cell fabricated on Avient …

Woodward Cuk Converter, Aditi Venkatesh, Jennifer Pereira

Honors Capstones

The purpose of this senior design project is to design and build a Cuk converter, a type of buck–boost converter. The project involves developing an analytical model and validating it through hardware testing. Cuk converters are important because they are widely used in everyday electronics, particularly in renewable energy systems such as solar power, power supplies, and electric vehicles. Their ability to increase, decrease, and reverse the polarity of voltage makes them flexible. The continuous input and output currents result in low ripple, reducing component stress and improving efficiency. To achieve these goals, simulations will be conducted using LTspice to …

Small-Scale Analog Spiking Neural Network: Design And Simulation Of An Analog Deep Neural Network, Lucas Hogue

Electrical Engineering and Computer Science Undergraduate Honors Theses

A small-scale analog schematic of a spiking neural network (SNN) is designed and demonstrated through the analog design environment (ADE) within Cadence Virtuoso. An SNN is a type of neuromorphic system that utilizes components mimicking the function of the neurons and synapses found in biological neural networks. The SNN designed in this project is composed of four layers: one input layer, two hidden layers, and one output layer. The inclusion of more than one hidden layer classifies the network as “deep” and increases the network’s efficiency at handling data with increased complexity. The SNN categorizes inputs by producing a set …

Quantifying Spatiotemporal Ev In-Motion Load Dynamics For Flexible Distribution Grid Operations, Travis Newbolt

Open Access Theses & Dissertations

The emergence of novel in-motion Electric Vehicle (EV) charging through Dynamic Wireless Power Transfer (DWPT) technology is enabling the transformation of traditional roadway infrastructures into fully integrated Electrified Transportation Networks (ETNs) by the direct coupling of roadways with electric power grids. This paradigm has the potential to improve charging safety, extend driving ranges, reduce EV manufacturing costs through smaller battery sizes, and shift EV charging demand to periods when Distributed Energy Resources (DERs) are more readily available. In addition, the transition to ETNs can improve air quality and reduce noise pollution by displacing fossil fuel consumption from vehicles to centralized …

Transformer Vulnerability To Geomagnetically Induced Currents Using Layered Soil Conductivity Models, Junior A. Sterling

Masters Theses

Geomagnetically induced currents (GICs) pose a significant threat to modern power transformers connected to long high-voltage transmission systems, particularly in regions with low subsurface electrical conductivity. During geomagnetic disturbances (GMDs), time-varying magnetic fields induce surface electric fields that drive quasi-DC currents through grounded transformer neutrals. These currents can bias transformer cores, leading to saturation, waveform distortion, and potential system instability. Despite extensive research, the role of regional Earth conductivity in shaping electric fields and transformer response remains an area requiring deeper investigation.

This study analyzes how contrasting Earth conductivity profiles influence GIC magnitude and transformer saturation risk using two representative …

Central Pattern Generator Test Bench Report, Stephanie Wing-Yee Lee, Dustin Wong, Joseph Hernandez

Electrical Engineering

The project presents the design, fabrication, and implementation of a PCB test bench that interfaces with a custom VLSI chip designed to emulate the neural activity of a Central Pattern Generator (CPG). The test bench provides a precise and reliable platform for supporting signal operations and validating neuromorphic functionality. The design integrates both analog and digital circuitry to provide stable biasing, signal routing, and measurement access for chip characterization. The incorporation of op-amp buffers and adjustable potentiometers enables precise voltage tuning, resulting in controlled neuron-like behavior within the custom IC. The two-layer PCB supports modular interfacing with standard laboratory instruments …

Optimization-Based Power Management For Hybrid Towing Vessels: A Comparative Framework Toward Mission-Aware Control, Rachel K. Burchill

LSU New Orleans Theses and Dissertations

This thesis presents an optimization-based framework for power management in hybrid towing vessels operating under dynamic mission conditions. A physically consistent modeling approach is developed, incorporating battery state-of-charge dynamics (SOC), unified power flow, and operational constraints. The framework evaluates rule-based control using fixed heuristic thresholds, Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and multi-objective Non-Dominated Sorting Genetic Algorithm II (NSGA-II) under a representative harbor-assist mission profile. Results show that optimization-based methods significantly outperform rule-based control. PSO achieves the lowest fuel consumption and near-perfect tracking with minimal battery use, while GA provides balanced performance with moderate battery utilization. NSGA-II reveals a …

Enhancing Reliable Performance Of Microgrids With Autonomous Control Of Distributed Energy Resources, Sahand Liasi

All Dissertations

This dissertation presents a comprehensive investigation into enhancing the reliability, efficiency, and autonomous operation of modern power networks through advanced microgrid integration and control strategies. The research addresses critical challenges across three interconnected domains: microgrid control, thermodynamic modeling of heat recovery system (HRS), and optimal distribution network reliability.

In the realm of microgrid control, this work introduces novel methodologies for grid forming inverter-based resources (IBRs). A significant contribution is the development and validation of an "Auto Frequency Change" controller, which drastically reduces microgrid synchronization time with the main grid from several minutes to approximately four seconds, with theoretical potential for …

Conditioning Hierarchical Diffusion Transformers On Rf Circuit Parameters, Ethan Morton

McKelvey School of Engineering Graduate Student Theses & Dissertations

As modern ML techniques have become increasingly advanced, they have begun to be integrated into wireless RF systems for classification, identification, and spectrum management. Deep Neural Networks (DNNs) enable RF system operators and designers to design more flexible systems with greater robustness to errors and attacks. However, neural networks require significant amounts of properly annotated data to train. Current data labeling methods lack the ability to obtain reliable true labels for circuit properties such as carrier frequency offset (CFO), power amplifier (PA) non-linearity, and in-phase/quadrature (IQ) imbalance. This thesis investigates the efficacy of a novel architecture, RF-Diffusion, for generating high-quality …

Data-Driven Multimodal Mri Representation Learning For Subtype Discovery And Disease Progression Modeling In Parkinson’S Disease, Zihan Zhou

McKelvey School of Engineering Graduate Student Theses & Dissertations

Parkinson’s disease (PD) exhibits substantial clinical and neuroanatomical heterogeneity, limiting robust patient stratification and clinically meaningful progression modeling from MRI. We propose a unified multimodal 3D generative representation-learning framework that learns an interpretable latent space from co-registered baseline T1/T2 MRI with an edge-aware channel. Confound-corrected latent embeddings support unsupervised subtype discovery, while disease duration provides weak supervision to orient a continuous progression axis. On an independent external cohort (PPMI, N=171), the discovery-trained subtype structure shows significant partial replication (ARI=0.35; permutation test p=0.001) and enables longitudinal clinical stratification: mixed-effects modeling reveals subtype-dependent MDS-UPDRS III progression, with the strongest effect in subtype …

Laser-Induced Acoustic Signal Generation, Resonance Characterization, And Optical Sensing In Metallic Plates, Xinghang Zhao

All Theses

This thesis investigates laser-induced acoustic signal generation, resonance characterization, and optical sensing in metallic plates as a foundational study for damage-sensitive inspection. Rather than presenting a complete defect-detection system, the work focuses on how measurable acoustic responses can be generated, amplified, and interpreted in a controlled laboratory setting. Experiments showed that pulsed-laser excitation can produce strong and repeatable acoustic responses in metallic structures. Repetition-rate sweeping identified narrow resonant responses, including a cantilever resonance at 57.862 kHz and a maximum circular-disk response at an FFT frequency of 48.8 kHz with a laser repetition rate of about 49.1 kHz. High-Q resonances exceeding …