Electrical and Computer Engineering Commons^™

Extending Geometric Acoustic Ray Tracing To Multi-Room Environments: A Case Study On Gunshot Sound Transmission Between Adjacent Rooms, Tyler Ton

Theses and Dissertations

Accurate localization of gunshots in multi-room building environments remains a challenging problem in acoustic forensics and public safety applications. Existing approaches model sound propagation within a single room, neglecting the transmission of acoustic energy through walls and other building materials. This thesis presents a study on modeling multi-room gunshot acoustic transmission, combining geometric ray tracing with structural acoustic transmission-loss modeling to generate impulse responses for two horizontally adjacent rooms separated by a shared wall, providing a foundation for future inter-room gunshot localization work. The proposed system uses GSound-SIR, a geometric acoustics engine, to simulate sound propagation in both of the …

Ai-Driven Biomarker Discovery & Progression Modeling For Precision Diagnosis Of Glaucoma, Cheng Huang

Computer Science and Engineering Theses and Dissertations

This dissertation presents a comprehensive study on the integration of artificial intelligence (AI) for glaucoma diagnosis and retinal image analysis. Leveraging multimodal imaging data including fundus photography, Optical Coherence Tomography Optical Coherence Tomography (OCT) and Optical Coherence Tomography Angiography (OCTA), the research develops a suite of deep learning frameworks designed to detect early glaucomatous changes with high precision, robustness, and interpretability. A series of novel architectures are introduced, spanning vessel segmentation networks, biomarker discovery pipelines, and multimodal fusion models, all designed to enhance diagnostic accuracy and generalizability across diverse populations. To facilitate reproducible and scalable ophthalmic AI research, this work …

The Sliding Aperture Transform: A Mathematical Method Applied To Radiation-Induced Dlts Capacitance Transients, Md Abu Bakkar Siddique

Graduate Masters Theses

This thesis presents the Sliding Aperture Transform (SLAPt), a novel mathematical technique for extracting exponential argument and pre-factor  from experimental data. The method transforms measured waveforms into an inverse-domain representation where exponential decay processes appear as distinct peaks, simplifying data analysis and reducing the effects of baseline offsets and noise. The technique is here applied to time dependent capacitance transients associated with irradiated and non-irradiated silicon pn junction diodes. The technique is further developed and applied to positive argument exponentials using an axillary function. This allows forward bias  current-voltage measurements, and forward pulse-bias current transient measurements to be SLAP analyzed, …

Evaluation Of General Voronoi Diagram Decomposition For Harmonic Fields In Navigation Of Dynamic Environments, Franco Abullarade

Master's Theses

Harmonic potential fields provide provably minimum-free navigation, but any change to the workspace geometry invalidates the field and forces a costly global recomputation, typically restricting them to static environments. This thesis extends the harmonic map framework of Vlantis et al., which maps the free workspace onto a unit disk and uses an atlas of per-region transformations, to dynamic indoor settings. First, we replace their manually annotated room partition with an automatic decomposition based on the Generalized Voronoi Diagram, allowing the atlas to be built from an arbitrary occupancy grid in an automated way. Second, we introduce a localized repair procedure …

Thermal Rating And Prediction Of Roadway-Embedded Power Electronics For Dynamic Wireless Power Transfer, Forrest D. Nichols

All Graduate Theses and Dissertations, Fall 2023 to Present

Electric vehicles can be charged while driving through wireless charging coils buried in the road surface. To avoid running expensive cables from roadside equipment to each charging pad, the electronics that control the power transfer can also be buried in the road. However, burying these circuit boards removes the ability to cool them with fans or flowing air, so the heat generated during operation must escape naturally into the surrounding road material. If the boards get too hot, components fail—a problem that has already been observed in prototype systems.

Predicting how hot each component on a circuit board will get …

Modeling Power Distribution Architectures And Maintaining Constant Power With Misalignment In Dynamic Wireless Charging Systems For Electric Vehicles, Mayank Chawla

All Graduate Theses and Dissertations, Fall 2023 to Present

With increasing demand for wireless power transfer systems from phone charging and medical devices, in-motion wireless charging of electric vehicles offers a unique advantage of charging the vehicle while in motion on an electrified roadway. Compared to the stationary or wired charging, electric vehicle users can significantly save time and cost with a reduction in the battery size. However, with large-scale infrastructure required for a wireless charging roadway and the driver’s ability to align with the electrified roadway, come significant challenges for the practical implementation of in-motion wireless charging systems.This dissertation aims to solve some of the problems associated with …

Modulating Linear Frequency Modulated Pulses To Send Communications Data In A Bistatic Sar Scenario, Jarren T. Worthen

All Graduate Theses and Dissertations, Fall 2023 to Present

Synthetic aperture radar (SAR) is the technology that enables the creation of images using radar waves, allowing images to be formed regardless of weather. In bistatic SAR a radar platform uses a radar pulse from a separate platform to form an image. It is important that these radar systems are able to communicate with each other. Rather than wasting energy and space flying with a separate communication system, the radar systems could use the already existing SAR system to send data between each other while still forming SAR images. The work of this thesis is to show how very simple …

Hardware-In-The-Loop Evaluation Of Sensor-Source Selection For Prosthetic Locomotion Intent Recognition, Victoria Asencio-Clemens

Master's Theses

Active lower-limb prostheses use intent-recognition systems to identify a user’s locomotion mode and select an appropriate control strategy, but sensor configurations that perform well offline may be unsuitable for resource-constrained embedded hardware. Existing sensor-selection methods generally prioritize classification accuracy without directly accounting for processing latency, memory usage, or other hardware-dependent requirements. To address this limitation, this thesis develops a hardware-in-the-loop source-selection framework for embedded classification of level walking, ramp ascent, ramp descent, stair ascent, and stair descent using multimodal biomechanical data from transtibial amputee participants. Subject-specific linear support vector machine classifiers were evaluated using trial-held-out validation, and candidate configurations from …

Machine Learning For Predictive Energy And Emissions Modeling Of Vehicles And Power Grids In The United States, S M Tanvir Faysal Alam Chowdhoury

Dissertations

The environmental benefits of electric vehicle (EV) adoption depend on more than replacing internal combustion engine vehicles with electric powertrains. EV adoption reshapes electricity demand, interacts with regional generation mixes, and influences travel behavior and congestion, creating a coupled transportation-energy system in which vehicle and power-plant emissions must be evaluated together. This dissertation develops machine-learning frameworks for predicting energy consumption and emissions from vehicles and power grids under rising EV adoption. The first component forecasts grid emissions from EV charging. Using simulation data from NREL's Cambium database, a Prophet-based time-series framework predicts carbon dioxide, nitrous oxide, and methane emission rates …

Development Of Dynamic Proof-Mass Configurations For Broadband Piezoelectric Energy Harvesting, Nico E. Galarza

Electrical and Computer Engineering ETDs

The purpose of this thesis is to investigate and develop dynamic proof-mass configurations for broadband piezoelectric energy harvesting. Conventional piezoelectric energy harvesters are typically limited by narrow operating bandwidths, restricting their performance under variable-frequency excitation. This research presents the design, fabrication, and experimental evaluation of multiple proof-mass concepts intended to increase the usable frequency range of cantilever-based piezoelectric energy harvesters. Several dynamic mass configurations were developed using additive manufacturing techniques and integrated with commercially available piezoelectric cantilevers. Experimental testing was conducted under controlled vibration conditions to characterize voltage response, resonant behavior, and bandwidth performance. The results demonstrate that dynamic proof-masses …

Synergizing Crowd Collaboration: Enhancing Crowdsourcing Matching Via Integration Of Matching Theory And Coalition Games, Rowan Aengus Kinney

Electrical and Computer Engineering ETDs

This paper tackles the challenges inherent in crowdsourcing dynamics by introducing the CROWDMATCH mechanism. Aimed at enabling crowdworkers to strategically select suitable crowdsourcers while contributing information to crowdsourcing tasks, CROWDMATCH considers incentives, information availability and cost, and the decisions of fellow crowdworkers to model the utility functions for both the crowdworkers and the crowdsourcers. Specifically, the paper presents an initial Approximate CROWDMATCH mechanism grounded in matching theory principles, eliminating externalities from crowdworkers’ decisions and enabling each entity to maximize its utility. Subsequently, the Accurate CROWDMATCH mechanism is introduced, being initiated by the outcome of the Approximate CROWDMATCH mechanism, and employing …

Developing A Dispersion Interferometer For Characterizing Power Flow Plasma Formation And Transport Studies, Nathan R. Hines

Electrical and Computer Engineering ETDs

Sandia's refurbished $Z$-pinch machine experiences persistent current loss in its post-hole convolute and inner magnetically insulated transmission line regions, widely attributed to low-density electrode plasmas whose formation and transport remain poorly constrained by existing diagnostics. This dissertation develops and validates a fiber-coupled, continuous-wave, second-harmonic orthogonally polarized dispersion interferometer for time-resolved measurements of electron areal density in millimeter-scale gaps. The diagnostic employs single-laser second-harmonic generation, non-steering differential phase control, and polarization-based phase retrieval to achieve sub-$10^{15}$~cm$^{-2}$ sensitivity, multi-hundred-megahertz bandwidth, and sub-$200$~$\mu$m effective cross-gap spatial resolution. Performance is benchmarked against a $94$~GHz interferometer on the UNM Helicon-Cathode plasma device and then fielded …

Enhanced Computational Modeling Of Photoionization And Streamer Formation, Anahita Alibalazadeh

Electrical and Computer Engineering ETDs

Photoionization is a key mechanism governing the formation and propagation of streamer discharges in air by generating electron-ion pairs ahead of the streamer front. Accurate and computationally efficient modeling of this non-local process is essential for reliable plasma simulations. However, the widely used Zheleznyak photoionization model relies on empirical assumptions and requires computationally expensive domain-wide integration.

This dissertation advances photoionization modeling in three ways. First, the classical integral model is enhanced by incorporating experimentally measured vacuum ultraviolet (VUV) emission spectra together with photoabsorption and photoionization cross-section data, enabling direct calculation of the photoionization source term as a function of pressure …

3d Electromagnetic Simulations Of A 1.6 Cell S-Band Photoinjector: Emittance Studies For Electron Microscopy, Trudy Bolin

Electrical and Computer Engineering ETDs

Modern beam-based materials research demands electron sources with increasingly precise time resolution, high brightness, and stability. For example, there are various instruments across the U.S. dedicated to ultrafast electron diffraction (UED), but fewer are dedicated to ultrafast electron microscopy (UEM), which demands beam stability. Modeling femtosecond electron bunches with ultra-low emittance < 50 nm-rad inside a 1.6-cell S-band (2856 MHz) rf photoinjector with full 3D electromagnetic simulations can require high-performance computing (HPC) environments due to the scale disparity between the macroscopic cavity geometry and the femtosecond-scale bunch kinematics. To enable optimization in a desktop computing environment, this work presents a streamlined 3D electromagnetic Particle-in-Cell (PIC) simulation framework optimized for 400-femtosecond bunch regimes. The covariance method was employed to study emittance properties for electron bunch counts ranging from thousands to millions and has successfully resolved highly transient, pure rf phase-space rotations, such as a localized energy-spread minimum occurring at the gun exit iris. To overcome the computational cost of these simulations, a machine-learning-based Bayesian optimization approach was deployed to construct multi-objective Pareto fronts from sparse datasets. Because the simulation software is scalable from desktop to HPC facilities, the framework is ready for experiments at the National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory (LBNL).

Real-Time Waveform Synthesis For Rfsoc-Based Quantum Control Systems, Tiamike I. Dudley

Electrical and Computer Engineering ETDs

RFSoCs are gaining adoption in many labs for quantum control systems thanks to their compactness and affordability. Making full use of the many components on an RFSoC evaluation board is a challenging engineering problem that must be solved to realize scalable control systems. In this dissertation, I evaluate the performance of various RFSoC components in the context of quantum information science. I present two custom FPGA engines that accelerate and parallelize arbitrary waveform generation. The first engine can be instantiated many times to power low-speed DACs for ion-shuttling trap electrodes. The second engine synthesizes CPMG-XY8n dynamical decoupling pulse sequences on …

Modeling For You: A Personalized Approach To Residential Energy Simulation And Distributional Reinforcement Learning, Nestor Gabriel Pereira

Electrical and Computer Engineering ETDs

The growing complexity and uncertainty of residential energy use, driven by electric

vehicles and renewable technologies, demand more intelligent and robust

management systems. Traditional methods often fail when faced with unpredictable

electricity prices and user behavior. This dissertation addresses this gap by presenting

a novel personalized framework combining detailed household energy modeling with

a risk-aware reinforcement learning agent for appliance scheduling.

The first contribution is a probabilistic, bottom-up simulation model that captures

the interdependent behaviors of occupants, appliances, and electric vehicles to

generate realistic, high-fidelity load profiles. The second contribution is a lightweight,

tabular Distributional Q-Learning (D-QL) algorithm that schedules …

Multi-Robot Cooperative System For Complex Aerospace Manipulation Tasks: Theory And Application, Longsen Gao

Electrical and Computer Engineering ETDs

Multi-robot systems can extend manipulation capabilities beyond the limits of a single robot, particularly for tasks involving large, flexible, delicate, or free-floating payloads. Reliable cooperative manipulation, however, remains difficult when payload dynamics, contact geometry, compliance properties, deformation-induced forces, and external disturbances are only partially known, and when safety constraints must be enforced during physical interaction. This dissertation develops a two-layer control framework for resilient multi-robot manipulation under uncertainty, with emphasis on space servicing, satellite stabilization, aerial transportation, and cooperative manipulation of free-floating structures.

Explainable Machine Learning For Biomedical Diagnostics: Optical Imaging And Eeg Signal Analysis, Fozia Rajbdad

LSU Doctoral Dissertations

The growing convenience of complex biomedical data begins new roads for better disease detection and functional identification via artificial intelligence (AI). Nevertheless, conventional analysis methods often rely on basic metrics that drop sensitive biotic differences, and various AI systems are difficult to infer, limiting their clinical reliability and practical use. There is a growing need for explainable, physiologically relevant computational models that can extract key biomarkers from diverse biomedical data sources. This dissertation addresses this problem by obtaining explainable machine learning and deep learning procedures for studying biomedical signals and optical imaging data.

This dissertation is divided into two parts; …

Assessing Computer Vision Based Conflict Detection In Uas Traffic Monitoring Under Secure Communication Constraints, Fadjimata Issoufou Anaroua

Doctoral Dissertations and Master's Theses

The rapid growth of Unmanned Aircraft Systems (UAS) and Advanced Air Mobility (AAM) is creating a new low-altitude airspace ecosystem where drones, air taxis, service suppliers, communication networks, sensors, and ground-based monitoring systems must work together safely. Within this ecosystem, UAS Traffic Management (UTM) is expected to provide a digital framework for coordinating operations beyond traditional air traffic control. However, reliable integration also requires resilient monitoring methods that can detect non-cooperative aircraft, protect communication links, and maintain timely situational awareness under real-world constraints.

This dissertation examines how computer vision can support cooperative monitoring systems such as Remote ID and ADS-B …

System Integration And Validation Of The Cal Poly Spacecraft Attitude Dynamics Simulator Mk. Iv, Bricen S. Rigby

Master's Theses

The Cal Poly Spacecraft Attitude Dynamics Simulator (SADS) is an ongoing project that seeks to enable the simulation and validation of sensors, actuators, and control logic related to spacecraft attitude control. The SADS platform rests atop a spher- ical air-bearing device which allows for nearly frictionless rotation in all three axes. The orientation of the platform is controlled by four reaction wheels arranged in a pyramidal configuration. Over the past few years, there have been significant updates to the reaction wheel subsystem, as well as requests for a more capable central com- puter. Therefore, a new system architecture for the …

Dc/Dc Converter For A Solar Module, Francine Therese A. Canal, Jesus Cruz, Juan Jose Gonzalez

Electrical Engineering

This project presents the design and implementation of a DC/DC power converter intended for photovoltaic (PV) modules with varying electrical output characteristics. Solar panels experience significant changes in output voltage and power due to variations in sunlight, temperature, and load conditions. To ensure reliable operation across a range of conditions, the proposed converter is capable of both step-up and step-down operation to accommodate solar modules with power ratings from 50 W to 450 W and open-circuit voltages between 10 V and 80 V. The system operates at load currents up to 10 A and provide a user-adjustable output voltage within …

Dc/Dc Converter For A Solar Module, Stella Uribe, Richie Zaragoza, Olivia Grace Tran, Phillip Tyler Rich

Electrical Engineering

This project focuses on the design and validation of a general-purpose DC/DC power converter intended for use with photovoltaic (PV) solar modules operating under variable environmental and loading conditions. Solar panels exhibit significant variation in output voltage, current, and available power due to changes in irradiance, temperature, and operating point, making direct connection to downstream loads impractical. The proposed system addresses this challenge by providing a single, user-adjustable regulated DC output capable of both stepping up and stepping down the solar module voltage. The converter is designed to interface with solar modules rated between 50 W and 400 W, with …

Stationary Bike Power/Efficiency Monitor, Paula J. Diaz, Pilar M. Cook, Danielle Rhind

Electrical Engineering

This project developed a real-time power and efficiency monitoring system for a SportsArt ECO-POWR stationary exercise bicycle. The goal was to measure rider mechanical power and electrical power delivered to the utility grid simultaneously, allowing the overall bike-to-grid efficiency to be calculated and displayed in real time. Rider power was measured using Garmin Rally ANT+ power pedals, while grid power was measured using a Yokogawa WT310E power analyzer. A Raspberry Pi 3 Model B+ synchronized both data sources, calculated efficiency, displayed live performance metrics through a graphical user interface, and logged measurement data to CSV files for later analysis. The …

Autonomous Terrain-Mapping Robot For Search And Rescue, Soumil Joshi, Seann Calub

Electrical Engineering

This report documents the design, modular testing, and challenges faced while developing an autonomous terrain-mapping robot intended to navigate to a destination waypoint and deliver a small payload for search-and-rescue applications. The system combines a LiDAR sensor, an IMU sensor, and a Raspberry Pi 3B as the onboard processor, and an ESP32 microcontroller interfacing with motor drivers over a four-wheel chassis. A companion mobile application was developed to enable remote control and monitoring of the robot over a WiFi hotspot connection. A lithium-ion battery pack supplies power to all onboard components, with power budgets verified against component datasheets. Testing progresses …

Veribrief: A Multi-Agent Retrieval-Augmented Generation System For Policy Decision Support, Imane Bahji

Electrical and Computer Engineering ETDs

VeriBrief is a multi-agent retrieval-augmented generation (RAG) system for evidence-grounded economic policy analysis. The system orchestrates a five-stage LangGraph pipeline, retrieval, research, analysis, synthesis, and critique, to produce cited, structured responses while detecting out-of-scope queries. An empirical evaluation on eight questions drawn from official U.S. macroeconomic releases compared VeriBrief against a single-pass RAG baseline. The multi-agent system achieved 100% refusal precision on unanswerable analytical queries versus 0% for the baseline. Unsupported claims fell substantially on answerable factual questions. A context-propagation defect discovered during evaluation was diagnosed and corrected. Limitations include failure of the evidence gate on policy-counterfactual queries and a …

Leader Election System For An Unmanned Ground Vehicle Swarm, Milan Chhetri, Brendan Beas, Paul Levin

Electrical Engineering

This senior project presents the design and implementation of a leader-election system for a leader-follower unmanned ground vehicle (UGV) swarm using embedded control and wireless communication. The objective of the project is to improve the robustness and mission longevity of a multi-agent robotic system by allowing the swarm to dynamically select the most suitable leader during operation. Each UGV is equipped with an ESP32 microcontroller, DWM1000 Ultra-Wideband (UWB) ranging modules, an MPU-6050 inertial measurement unit (IMU), motor drivers, and supporting power electronics to enable communication, sensing, and autonomous control. A battery monitoring subsystem was developed using the ESP32's built-in Analog-to-Digital …

Archimedean Spiral Antenna Array With Klopfenstein And Exponential Tapered Balun Feeds, Leo Joseph Alvelais Iv, Paul Obrecht, Naguib Abdulla, Preston Mavady, Collin Fan

Electrical Engineering

This project presents the design, fabrication, and experimental evaluation of a broadband 3x3 Archimedean spiral antenna array tile for 2.8-3.8 GHz. Each element combines a two-arm spiral on Rogers RO4350B, a printed 50 to 150 Ω tapered balun, and a conductive backplane. Klopfenstein and Exponential feed implementations were modeled in Ansys HFSS, generated and tuned with automated scripting, fabricated, and evaluated with calibrated network and anechoic-chamber measurements. The Klopfenstein-fed hardware met the -10 dB input-reflection criterion across the project band. The exponential array provided a broad matched response but reached approximately -8 dB near 2.95 GHz. Measured center-element patterns retained …

Vision-Based Autonomous Tracking Rover, Alejandro Ahumada, Erick Ayala, Jonathan Chavez

Electrical Engineering

AAC Vision designed and constructed a vision-based autonomous tracking rover capable of exploring an indoor environment, avoiding obstacles, generating a two-dimensional LiDAR map, detecting a standard orange basketball, and approaching the target without manual steering. The rover uses a Raspberry Pi 4, an Intel RealSense D435 RGB-D camera, an RPLIDAR C1, four JGB37-520 Hall-encoder motors, dual H-bridge motor drivers, a 12 V battery, and a custom aluminum chassis measuring approximately 8 in by 12 in and weighing 6.7 lb. The final mission emphasized reliable target discovery rather than travel between predetermined points. The software integrates Python, OpenCV, Ultralytics YOLO, RealSense …

The Neuropsychological Analysis Of The Effect Of Shame And Traumatic Memories In Paranoia: A Network Analysis, Anwesha Maitra

Clinical Psychology Dissertations

Paranoia is increasingly recognized as a multidimensional psychological phenomenon influenced by trauma-related distress, shame, maladaptive interpersonal experiences, and emotional functioning. Although these factors have been extensively associated with paranoia, their relationships with neurocognitive functioning, social cognition, and global functioning remain less well understood. The present study examined these relationships using traditional statistical analyses, network analysis, and machine-learning approaches in a non-clinical sample of 42 adults.

Participants completed self-report measures assessing trauma-related distress, childhood interpersonal experiences, shame, paranoia, depressive symptoms, fear of negative evaluation, self-esteem, and hostile attribution bias, in addition to a comprehensive neurocognitive battery, an emotion recognition task, and …

Improving Urban Search And Rescue Team Coordination Through Adaptive Context Awareness, Daniel Reyes Duran

Doctoral Dissertations and Master's Theses

Modern multi-agent Urban Search and Rescue (USAR) operations heavily rely on mobile geospatial Common Operating Pictures (COPs) to maintain team coordination and Situational Awareness (SA). However, the proliferation of high-frequency sensor telemetry at the tactical edge has introduced a data saturation paradox challenge: while information theoretically drives informed decision-making, unmanaged data surges induce increased operator cognitive overload and alert fatigue on mobile End-User Devices (EUDs), while downstream data-broadcasting models inherently strain edge processing and viewport environments.

To resolve these constraints, this dissertation presents a context-aware Value of Information (VoI) data-management framework integrated directly with a custom, event-driven Android Team Awareness …