Electrical and Computer Engineering Commons^™

Multi-Objective Optimization Strategy For Component Sizing In Solar-Hydrogen Microgrids Using An Advanced Hybrid Genetic Algorithm, Dylan Jones

UNF Graduate Theses and Dissertations

This thesis presents the development of a genetic algorithm (GA) optimization framework for the design and component sizing of hybrid solar-hydrogen microgrids. The framework addresses a critical gap in research and existing commercial tools by unifying performance maximization and cost minimization objectives across both grid-tied and islanded configurations. Integrating solar photovoltaics, electrolyzers, hydrogen storage, fuel cells, and batteries, the GA employs adaptive weighting and dynamic boundary constraints to balance technical feasibility with economic efficiency. To ensure real-world viability, the algorithm relies on a novel Daylight Sun Factor (DSF) for localized solar assessment and was rigorously validated against multi-year, high-fidelity irradiance …

Experimental Validation Of Optical Wireless Communication And Power Transfer For Uav Applications, Fnu Dhruv

UNF Graduate Theses and Dissertations

Unmanned Aerial Vehicles (UAVs) have revolutionized emergency response, disaster assessment, and search-and-rescue operations. However, their operational efficacy is fundamentally constrained by limited battery endurance and the susceptibility of traditional radio-frequency communication to disruption in adverse weather. To address these limitations, this thesis proposes and experimentally validates a novel architecture integrating Free-Space Optical (FSO) communication with Simultaneous Lightweight Information and Power Transfer (SLIPT). This system utilizes a split-beam configuration to concurrently enable high-bandwidth data transmission and optical energy harvesting to replenish the UAV's battery pack. The research was conducted in three progressive phases. Initially, system feasibility was established through rigorous optical …

Design, Fabrication Modeling, And Optical Metrology Of Mwir Silicon Metalenses, Weiyu Chen

Graduate Studies Theses and Dissertations 2026

Mid-wave infrared (MWIR) optical systems require compact, broadband, manufacturable components whose performance can be predicted and measured reliably. Silicon metalenses are attractive because silicon combines high refractive index, MWIR transparency, and semiconductor-compatible fabrication. This dissertation develops a scale-bridging design–fabrication-modeling–metrology framework for MWIR silicon metalenses.

A shared full-aperture framework connects meta-atom libraries, physical layout generation, angular-spectrum propagation, point-spread-function calculation, and focal-plane energy metrics. Building on this foundation, the Dispersive Sweatt Model (DSM) incorporates meta-atom dispersion into conventional ray-tracing software, enabling broadband co-optimization of metasurfaces and refractive elements. A process-aware design framework then incorporates scanning electron microscopy (SEM)-measured height–radius relationships produced by …

Securing The Energy Transition: Cyber-Physical Security And Resilience In Next-Generation Power Systems, Airin Rahman

Graduate Studies Theses and Dissertations 2026

Modern power systems are rapidly evolving into renewable-dominated and digitally interconnected cyber-physical infrastructures due to the increasing deployment of distributed energy resources (DERs), inverter-based technologies, and advanced control platforms. Maintaining reliability under high renewable penetration requires flexible resources capable of shifting energy across extended time horizons. Long-duration energy storage (LDES), particularly hydrogen-based energy systems, has therefore emerged as an important enabler of renewable integration, grid flexibility, and resilience. However, the growing dependence on communication, sensing, and distributed control also expands the cyber-physical attack surface of modern power systems, creating security and resilience challenges that conventional operational paradigms were not designed …

Communication-Aware Energy Optimization For Electric Vehicles With Adaptive Cruise Control, Shahriar Shahram

Graduate Studies Theses and Dissertations 2026

This dissertation develops information-driven methods to reduce traction energy in battery electric vehicles during adaptive and cooperative cruise control. Physics-grounded energetics are embedded in a predictive controller that accounts for intermittent V2V preview, sensing noise, packet loss, and powertrain limits. To ensure deployability, the nonconvex traction–power map is replaced by locally convex surrogates so each step solves a small, strictly convex QP in real time (average ≈ 70 ms/step on a desktop CPU: 8 cores/16 threads, 4.2–5.0 GHz), leaving margin at typical sampling rates (Ts =0.05–0.10 s; N=15–25).

Across standardized drive cycles from NREL DriveCAT—including FTP–75 (light duty), NREL Class …

Bond Graph And Extended Generalized Average Method With Applications In Cyber-Physical Systems And Power Electronics, Arnold Anthony Fernandes

Doctoral Dissertations

"This research examines two applications of control theory. The first application considers the bond graph (BG) modeling technique, which is used to develop the MATLAB structural analysis toolbox (MATSAT), an open-source toolbox for sensor placement and qualitative system analysis that considers the observability and fault-detection capabilities of multi-domain cyberphysical systems. The toolbox provides information on redundant sensors, guiding the system designer in cost and security trade-offs. The toolbox uses traditional BG causality assignment procedures. Additionally, MATSAT provides optimal causality assignment methods that perform significantly better at assigning causality to BGs with increased junctions, sources, and simple meshes, without encountering causality …

Lidar-Based Point-Cloud Human Modeling: Pose Estimation, Body-Parts Segmentation, 6g Localization, And Applications, Omar Rinchi

Doctoral Dissertations

"The human body represents a rich source of physiological and behavioral information, where precise analysis of anatomy, body parts, 3D pose, and motion enables cross-disciplinary precision applications. This dissertation formulates this challenge as a human modeling problem, where proposed algorithms convert the human body into a three-dimensional digital twin capturing anatomical structure and pose. These representations are further analyzed using additional algorithms to enable precision applications. To realize this vision, LiDAR sensing is adopted due to its privacy-preserving nature, robustness to lighting conditions, color-blind sensing characteristics, and decreasing cost.

Human modeling using LiDAR is challenging due to sparse, irregular, and …

Deep Learning And Computer Vision-Based Modeling For A Real-Time Traffic Congestion Monitoring Framework, Neil Dustin Benedict A. Agner, Angelo B. Dela Cruz, Aster Benedict A. Mangabat, Raphael B. Alampay, Patricia Angela R. Abu

Ateneo Laboratory for Intelligent Visual Environments

As intelligent traffic systems evolve to manage complex urban mobility, conventional congestion estimation techniques, such as the time-windowed Volume-to-Capacity (V/C) ratio, fail to capture capture the real-time traffic situation. Because these methods rely on vehicles crossing a specific point, they often fail to register stopped cars, creating a ‘zero flow’ paradox where complete gridlock is incorrectly categorized as an empty, free-flowing road. To address these limitations, this study proposes an end-to-end computer vision framework utilizing the Real-Time DEtection TRansformer (RT-DETR) model to quantify vehicle volume and immediately classify a roadway’s Level of Service (LOS) through spatial density. In processing video …

Artificial Sense-Making Dataset, Jason A. Bengtson, John Sandstrom, Nathan Camp

NMSU Library: Datasets

No abstract provided.

Improving Efficiency In Noma Schemes Having Inter-User Interference Using Mechanism Design, Zory Marantz

Publications and Research

Modern wireless systems utilize non-orthogonal multiple access to increase their rate capacities; however, the efficiency of the individual utility defined in bits per Joule has yet to be considered. Multiple variations of non-orthogonal multiple access have the interference of the signal-to-interference-plus-noise ratio as a function of the received power from multiple other users due to code implementations that are non-orthogonal or non-ideal cancellation in successive-interference-cancellation methods. Game theoretic concepts are used to improve user bits-per-Joule performance. Previous solutions increment transmit power and are not based on closed form systematic methods. The mechanism design presented here led to a non-cooperative Nash …

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 …

Sapphire Optical Fiber Bragg Grating Sensors Based On Dispersive Microwave-Photonic Frequency-Time Domain Analysis, Ruimin Jie, Chen Zhu, Farhan Mumtaz, Koustav Dey, Bohong Zhang, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Sapphire fiber Bragg gratings (SFBGs) have attracted growing interest for high temperature sensing in harsh environments, yet their interrogation typically relies on optical spectrum measurements, demanding a high-resolution optical spectrum analyzer (OSA) that is bulky, expensive, and constrained in acquisition speed. Moreover, the inherently multimode nature of sapphire fiber further complicates spectrum-based demodulation, thereby limiting the achievable sensing resolution. In this paper, we propose and experimentally demonstrate a microwave-photonic interrogation approach for SFBG sensors. Instead of measuring the optical reflection spectrum, the complex frequency response in the microwave domain of an SFBG is acquired using a vector network analyzer (VNA) …

Lidar-Based Framework For Detecting Suspicious Human Activities, Ahd Aljumah, Charalampos Antoniadis, Hakim Ghazzai, Nawfal Guefrachi, Ahmad Alsharoa, Gianluca Setti

Electrical and Computer Engineering Faculty Research & Creative Works

This study explores the development of Human Activity Recognition (HAR) systems capable of identifying suspicious activities to enhance security in public spaces. We propose an innovative solution that integrates LiDAR sensors with deep learning technologies. Our method employs advanced models operating on LiDAR point cloud, PV-RCNN for human detection, and LidarGait++ for classifying activities into categories such as standing or walking (non-suspicious) and sneaking or fighting (suspicious). Due to the scarcity of suitable real-world datasets for training such systems, we utilize a 3D simulation tool, Blender, to create realistic environments and generate labeled point cloud data. This synthetic dataset allows …

Deep Learning Approach For Microwave Imaging Based On Deep Convolutional Asymmetric Encoder-Decoder Structure And Physics-Induced Loss, He Ming Yao, Shiji Song, Michael Kwok Po Ng, Lijun Jiang

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, we introduce an innovative deep learning (DL) methodology designed for real-time quantitative microwave imaging (MWI). Our approach is centered around the utilization of a deep convolutional asymmetric encoder-decoder structure (DCAEDS), which requires only a single-frequency far-field measurement of the electromagnetic (EM) scattered field as input and subsequently predicts the contrasts (permittivities) of the target materials. During the offline training process, we incorporate an EM forward solver specifically crafted to compute the EM scattered field generated by the predicted target contrasts (permittivities) produced by the DCAEDS. The DCAEDS is seamlessly integrated with this EM forward solver to optimize …

Generative Ai And Llm Applications In Renewable Energy And Smart Grids: A Systematic Review For The Sustainable Energy Transition, Umit Cali, Ugur Halden, Merlinda Andoni, Ferhat Ozgur Catak, Si Chen, Benoit Couraud, Emre Kantar, Samuel Knapper, Ibrahim Kucukdemiral, Huseyin Kusetogullari, Murat Kuzlu, Yashar Mousavi, Sonam Norbu, Taha Selim Ustun, David Flynn

Engineering Technology Faculty Publications

The global energy transition toward decarbonization and digitalization requires advanced methods to manage decentralized, data-intensive cyber-physical energy systems. This systematic review analyzes 106 research studies on Generative Artificial Intelligence (GenAI) and Large Language Models (LLMs) in renewable energy and smart grids, organized into seven application clusters covering forecasting, system design, operation, reliability, data and cybersecurity, and energy markets. The review situates these applications within a Cyber-Physical-Social Systems (CPSS) framework. Results show that GANs dominate current applications (47.2%), followed by LLMs (10.4%) and VAEs (9.4%), with growing adoption of diffusion and score-based models (7.5% each). Selected studies report improved probabilistic forecasting …

Analytical And Semi-Analytical Modeling Of Solar Cells Using The Lambert W Function: A Comprehensive Review Of Equivalent Circuits, Adel El-Shahat, Martin Ćalasan, Snežana Vujoševic, Shady H. E. Abdel Aleem

Engineering Technology Faculty Publications

The modeling of photovoltaic (PV) cells through equivalent circuits forms a central element in the analysis, simulation, and optimization of solar energy systems. Traditional approaches often depend on iterative numerical methods to solve the implicit current–voltage (I–V) equations. In contrast, the Lambert W function has emerged as an effective mathematical tool that enables closed-form or semi-analytical expressions for a wide range of PV models. This paper presents a Lambert W-centered review of analytical and semi-analytical formulations for PV equivalent-circuit models, covering classical single-diode and multi-diode structures and modern variants incorporating additional elements, voltage-dependent parameters, and topology rearrangements. The models are …

Μmodules: A Low-Cost, Eurorack-Compatible Modular Audio Synthesis System, Nolan K. Juneau

Honors Theses and Capstones

The modular audio synthesizer is one of the fastest-growing industries in contemporary music technology. Unlike a traditional audio synthesizer, a modular synthesizer allows for the user to directly control the signal path and effects of the synthesized sound, allowing for a workflow that is completely customizable to an individual musician and their creative vision. However, the modules and cases currently in production for the common “Eurorack” design standard can be prohibitively expensive to new users, often costing thousands of dollars for even a small system. The µModules project aims to eliminate this financial barrier to modular synthesis by using inexpensive …

Adaptive Boundary-Aware Fact-Checker Placement For Misinformation Suppression In Social Networks, Mostafa Taghizade Firouzjaee, Ghazal Naderi, Ross Gore, Neda Moghim

School of Cybersecurity Faculty Publications

The spread of fake news on online social networks is driven by imitation-based user behavior and network topology, often leading to persistent misinformation clusters and echo chambers. In this study, we develop a spatial evolutionary game-theoretic framework in which agents update their latent opinions through payoff-biased imitation, while external fact-checkers act as non-imitative intervention nodes. Building on this formulation, we propose an adaptive, boundary-aware intervention mechanism that dynamically regulates both the density and spatial allocation of fact-checkers according to real-time system conditions. Competing information clusters are identified through local neighborhood composition, enabling boundary nodes, i.e., interfaces between fake-news and non-fake-news …

The Effects Of Physical Boundaries On The Complexity Of Resonance Processes In Finite-Size Dielectric Metasurfaces, Varsha Vijay Kumar

Dissertations, Master's Theses and Master's Reports

This work investigates dramatic effects produced by the presence of physical boundaries of finite-size metasurfaces, composed of identical cylindrical dielectric resonators without broken symmetry, on the complexity of their responses, observed at normal plane wave incidence, when constituent particles can support only dipolar Mie resonances. Owing to their periodicity, metasurfaces are conventionally analysed using their unit cells with periodic boundary conditions, so that their “finiteness” remains largely under-studied, even though all practical systems are finite.  We demonstrate the opportunities to excite in these finite structures extra high-quality resonance modes, quite distinct from the resonant modes in infinite structures and explain …

Multi-Level Energy Optimization For Connected And Automated Vehicles: From Cooperative Multi-Vehicle Control To Individual Powertrain Management, Pruthwiraj Santhosh

Dissertations, Master's Theses and Master's Reports

The transportation sector currently accounts for nearly 30% of global energy consumption, necessitating urgent advancements in vehicle efficiency to meet Net Zero targets. Leveraging connectivity and automation, this dissertation proposes and validates methodologies to reduce the energy consumption of light-duty vehicles at both fleet and individual levels.

First, a validation framework is developed to bridge the “simulation-to-real world” gap in Cooperative Automated Vehicle (CAV) research. Moving beyond virtual simulations, the study establishes a methodology for physically validating centralized control architectures via a custom Cellular V2X network. By synchronizing vehicle-powertrain models with physical test vehicles, the framework successfully orchestrates complex arterial …

Experimental Rate Feedback Control Of A Model-Scale Hourglass-Shaped Heaving Point Absorber, James R. Halverson

Dissertations, Master's Theses and Master's Reports

Buoy geometry greatly affects a point absorber wave energy converter's dynamic response to waves. Finding the optimal buoy shape and control method remains an open research area focused on maximizing the conversion of wave kinetic energy into electricity. This work presents an experimental comparison of closed-loop energy extraction between a cylindrical and a truncated cone buoy, both with the same submerged volume, across various wave frequencies and amplitudes. To ensure a fair comparison, the optimal rate feedback gain is calculated for each buoy at each wave condition. Multiple metrics, including power output, capture width, and actuator force, are used to …

Experimental Characterization Of Photonic Crystal Based Invisibility Cloak Under Tm-Polarized Microwaves, Muhammad Danyal

Dissertations, Master's Theses and Master's Reports

Electromagnetic invisibility cloaks guide waves around an object so that the transmitted wavefront remains undisturbed. Most experimental microwave cloaking studies have focused on transverse electric (TE) polarization due to established measurement techniques. In this thesis, the experimental realization and characterization of a dielectric photonic crystal cloak operating under transverse magnetic (TM) polarization are presented. A measurement system operating in the X-band was developed to map the electric field distribution of the transmitted waves. Cloaking performance was first evaluated qualitatively by comparing numerical and experimental field distributions, where restoration of a flat wavefront indicated effective cloaking. Quantitative evaluation was performed by …

Antenna-Based Sensors For Dielectric Characterization Of Materials, Hilary Scott Nkimbeng Cho

Dissertations, Master's Theses and Master's Reports

This research introduces antenna-based sensors for dielectric characterization aimed at overcoming the limitations of conventional microwave sensors. Although traditional microwave sensors are widely used for their noncontact operation, high sensitivity, and ability to penetrate various materials, they often face challenges such as large size and high-power consumption. To address these issues, antenna-based sensors are explored for their compactness, ease of fabrication, and flexible design adaptability across diverse sensing applications. An in-depth analysis of multiple antenna sensor configurations is conducted, followed by the design and development of high-performance sensing structures. A saw-tooth slot antenna sensor is developed for highly sensitive liquid …

High-Performance Circuit Manufacturing And Testing Exercises, Benjamin S. Keppers

Dissertations, Master's Theses and Master's Reports

An advanced demonstrator Printed Circuit Board (PCB) has been designed and implemented providing a framework for advancing students’ knowledge in hands-on PCB design and manufacturing process through industry recognized test coupons, stack ups, and transmission lines. Students are guided through several key aspects of design and simulation relating to manufacturing and qualifications. Manufacturing allows students to refine process development and analyze performance data with respect to qualification tests specified by Global Electronics Association standards. Results are then used to build a stackup model, and complete a design activity for calculating expected test results for a series of controlled impedance electrical …

Angular And Geometric Dependence Of Single-Event Effects In Gallium Nitride Hemts, Patrick Maloney

Graduate Studies Theses and Dissertations 2026

Gallium nitride (GaN) high electron mobility transistors (HEMTs) have become popular in commercial and space applications due to their desirable material properties compared to silicon. However, their susceptibility to radiation-induced single-event effects (SEE) remains a critical reliability concern. This work investigates on permanent SEE in GaN-based power devices, including single-event leakage current (SELC) and single-event burnout (SEB). The dependence of SEE susceptibility on electric field, ion angle of incidence, current rating, and metallization layers is investigated and conclusions are presented. Heavy-ion irradiation experiments demonstrate that the worst-case condition occurs at near-normal incidence (0°–15°), where charge deposition most effectively overlaps high-field …

Design And Characterization Of A Jet Nozzle Using Particle Image Velocimetry, Valerie K. Rodriguez

Graduate Studies Theses and Dissertations 2026

This paper presents the design and experimental characterization of the jet exit velocity from a supersonic nozzle injecting into a low-pressure vacuum chamber using Particle Image Velocimetry (PIV). The PIV method is employed to overcome limitations encountered in prior experiments characterizing a jet-in-crossflow, such as qualitative shock visualization and insufficient data on jet exit properties. The previous set of experiments used Classical Schlieren to visualize the flow as well as emission measurement with IR detectors. For the fuel injection cases, particular emphasis is placed on preventing condensation within the injection line and at the nozzle exit due to under expanded …

Adaptability And Applications Of Advanced Laser Absorption Diagnostics In High-Pressure Shock Tube Environments, Lucas R. Pitts

Graduate Studies Theses and Dissertations 2026

Theoretical application and physical implementation of various laser absorption spectroscopy (LAS) diagnostics are examined within a high-pressure shock tube facility. Research focuses on the rationale behind the specific optical alignment layouts used across three distinct experimental campaigns, detailing the methodology required to maintain signal integrity in varied reacting flow environments. The first research campaign addresses the pyrolysis of hydroxyl terminated polybutadiene (HTPB) solid propellant binders for solid fuel ramjet (SFRJ) applications by measuring the species time histories of alkenes and aromatics. Alignment configurations prioritized beam stability and signal strength for the decoupling of overlapping absorption features to ensure measurements accurately …

Neural Network Transceiver For Ltv Mimo Channels, Iresha Amarasekara

Electronic Theses & Dissertations (2024 - present)

Eigenfunctions are commonly employed to characterize kernels in various data-driven analyses. In machine learning, eigenfunction decomposition typically relies on Mercer's theorem, which assumes kernel symmetry. However, this condition is often unmet in communication systems, where channel kernels are asymmetric due to differences in downlink and uplink propagation environments. The High-Order Generalized Mercer's Theorem (HOGMT) provides a systematic approach for decomposing multidimensional asymmetric kernels into eigenfunctions. To address the complexity of eigen-decomposition, this work introduces a baseline neural network (NN) framework HNET. The HNET framework is further enhanced by incorporating the augmented Lagrangian method (ALM) to explicitly enforce orthogonality constraints. This …

Analysis Of Battery Degradation Effects On Optimized Torque Splitting In Dual-Motor Electric Vehicles, Homer E. Butcher

Graduate Theses, Dissertations, and Problem Reports (ETD)

Battery electric vehicle performance depends on both powertrain efficiency and battery-health. In dual-motor all-wheel-drive battery electric vehicles, driver-requested torque can be distributed between front and rear electric drive units, creating an opportunity to reduce electrical energy demand through torque allocation. However, lithium-ion battery aging changes the electrical behavior of the energy storage system through capacity fade and internal resistance growth. Capacity fade reduces the usable energy and vehicle range, while resistance growth increases voltage drop, current-related losses, and battery electrical loading. This thesis evaluates how these degradation effects influence the energy consumption, simulated range, and battery electrical behavior of optimized …

Fairness Without Demographic Attributes In Medical Vision–Language Models, Ahsan Habib Akash

Graduate Theses, Dissertations, and Problem Reports (ETD)

Vision–language models (VLMs) and the embedding models that underlie them have become the default representation layer for multimodal artificial intelligence. Trained by contrastive alignment over enormous, loosely curated image–text corpora, they inherit the demographic skew of that data, and they encode it in the geometry of the shared embedding space itself. The consequence is a model that performs unevenly across demographic groups even when no protected attribute is ever supplied as an input. In consumer applications this is an equity problem; in medicine it is a safety problem, because an embedding that is systematically less discriminative for one subpopulation translates …