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Radio Frequency Resonate And Fire (Rf-Raf) Neurons Supporting Device Classification, David L. Weathers, Michael A. Temple, Brett J. Borghetti May 2026

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 …


Spad Camera Image Analysis, Pratheen Reddy Pininti May 2026

Spad Camera Image Analysis, Pratheen Reddy Pininti

Electronic Theses and Dissertations 2020 - Present

I present a thorough noise characterization of the Canon MS-500, a Single-Photon Avalanche Diode (SPAD) camera system, tested under both lit and dark conditions. The camera outputs 10-bit digital number (DN) values produced by an internal processing pipeline whose design is not publicly documented. All analyses in this thesis therefore describe the camera’s DN output — the signal that any downstream detection, tracking, or classification system will actually receive — rather than the photon-counting statistics of the underlying SPAD array. All computations were performed on the native 10-bit data. Where a measured quantity has a known photon-counting analog, the relationship …


Testing And Qualification Of Low-Voltage Power Supplies For The Atlas Tile Hadronic Calorimeter Phase-Ii Upgrade, Justice A. Jones May 2026

Testing And Qualification Of Low-Voltage Power Supplies For The Atlas Tile Hadronic Calorimeter Phase-Ii Upgrade, Justice A. Jones

2026 Spring Honors Capstones Projects

The High Luminosity upgrade of the Large Hadron Collider (HL-LHC) places increased thermal and operational demands on detector electronics, requiring highly reliable power systems. The ATLAS Tile Hadronic Calorimeter (TileCal) uses low-voltage power supply (LVPS) bricks to power front-end electronics, but these units operate in inaccessible regions, making failures difficult to repair. Therefore, rigorous qualification procedures are essential. This work focuses on improving LVPS reliability through a structured burn-in process. Each unit undergoes pre-burn-in electrical verification using a Single Test Stand (STS), followed by sustained operation under load and elevated temperature, and post-burn-in requalification. Standard cooling conditions limit temperatures to …


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 May 2026

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 …


Largest 2-Regular Subgraphs In Complete S-Partite Graphs, Yiyang Jiang May 2026

Largest 2-Regular Subgraphs In Complete S-Partite Graphs, Yiyang Jiang

McKelvey School of Engineering Graduate Student Theses & Dissertations

In this thesis, we focus on the class of complete $S$-partite graphs, for $S$ an undirected graph possibly with self-loops, and address the problem of finding largest $2$-regular subgraphs of these graphs, which can be formulated as an integer linear program. Roughly speaking, a complete $S$-partite graph is obtained by replacing every single node of $S$ with a number of nodes, preserving the edge/non-edge relations of $S$. Our motivation in studying largest $2$-regular subgraphs is rooted in the structural systems theory, particularly in the problem of finding largest subnetworks that can sustain controllability or asymptotic stability of the corresponding subsystems. …


Rgfc: Registry Grounded Function Calling With Stage-Decomposed Evaluation, Ritvik Garimella, Vedant Khandelwal, Anvi Kohli, Amit Sheth May 2026

Rgfc: Registry Grounded Function Calling With Stage-Decomposed Evaluation, Ritvik Garimella, Vedant Khandelwal, Anvi Kohli, Amit Sheth

Publications

Tool-calling evaluations often report whether the final call matches a reference answer, but this single outcome merges different failures: choosing a function outside the available registry, violating the selected schema, or filling arguments with values not supported by the user request. These failures matter more when models must choose from larger tool registries. We introduce RFCD, a registry-scaled function-calling benchmark built from BFCL, Glaive Function Calling v2, and Tool-Call-Data, with standardized JSON-schema registries ranging from 5 to 3,000 functions. We also introduce TAAG, a deterministic stage-decomposed evaluator for registry conformance, structural completeness, and argument grounding. Across six locally served sub-4B …


Leveraging Information Theory And Ecological Network Analysis To Monitor Communication Networks In A Student Aerospace Team, Christine Sessions May 2026

Leveraging Information Theory And Ecological Network Analysis To Monitor Communication Networks In A Student Aerospace Team, Christine Sessions

Doctoral Dissertations and Master's Theses

Effective communication is a critical component of successful collaboration in group projects and team settings. However, systematically tracking and analyzing team communications can be challenging, especially in complex, multi-member teams such as those found in the aerospace industry. This paper explores an information-theoretic approach that leverages encoding techniques and graph theory to analyze communication networks within a university’s multi-year, student-led cubesat design project (Project COMET). By utilizing Shannon Entropy as a measure of information flow, encoding communication patterns, and analyzing Ecological Network Analysis parameters, this research aims to understand how an Embry-Riddle Aeronautical University student project team evolves over the …


Data-Driven Physical-Layer Optimization For Rf And Optical Communications: Transmitarray Metasurfaces, Contextual-Bandit Mud, And Coherent Optical Links, Chengtao M. Xu May 2026

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 May 2026

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 …


Development Of Hybrid Self-Cleaning Coating Using Lanthanide-Based Light Spectral Response Material To Enhance Photovoltaic (Pv) Panel Efficiency In Operational Environment, Khishn Kumar Kandiah May 2026

Development Of Hybrid Self-Cleaning Coating Using Lanthanide-Based Light Spectral Response Material To Enhance Photovoltaic (Pv) Panel Efficiency In Operational Environment, Khishn Kumar Kandiah

Student Works (2020-2029)

The efficiency of photovoltaic (PV) panels is crucial, as solar energy has become an alternative energy source that meets today’s global energy demands. Hence, dust accumulation and spectral mismatch have major effects on the efficiency of PV panels, around 20 %, but in extreme situations, this can reach up to 64 %. Therefore, initiatives are underway to address these issues, including PV cooling systems, conventional cleaning methods, and various coatings to enhance efficiency. In this work, a novel coating is fabricated with high transparency, excellent self-cleaning properties, and good spectral-modifying properties. Two types of powder composites are employed in this …


Designing Enhanced Nonlinearity In Plasmonic Devices With Epsilon-Near-Zero Films, Kevin Tran Le May 2026

Designing Enhanced Nonlinearity In Plasmonic Devices With Epsilon-Near-Zero Films, Kevin Tran Le

Electrical Engineering and Computer Science (MS) Theses

The growing demand for energy-efficient optical information processing motivates compact nonlinear photonic devices that can operate at low power. Silicon photonics is a mature platform for linear optical functions, but nonlinear operation remains challenging because of its weak Kerr response, two-photon absorption at telecommunication wavelengths, and limited compatibility with deeply subwavelength plasmonic confinement. This thesis computationally investigates epsilon-near-zero thin films integrated into plasmonic waveguide architectures as a route toward stronger light–matter interaction in compact nonlinear devices.

Two waveguide geometries are examined: a hybrid metal-insulator-metal plasmonic slab waveguide incorporating an ultrathin indium tin oxide epsilon-near-zero layer (5–50 nm), and a dielectric-loaded …


Reconfigurable Antennas Using Varactors On A Planar Parasitic Layer And Pin Diodes On A Dome Parasitic Layer, Andrew J. Hendricks May 2026

Reconfigurable Antennas Using Varactors On A Planar Parasitic Layer And Pin Diodes On A Dome Parasitic Layer, Andrew J. Hendricks

All Graduate Theses and Dissertations, Fall 2023 to Present

This research explores two types of reconfigurable, steerable antennas. These antennas change their beam direction based on electric input signals. The antennas have a layer that overlays the main antenna circuit board. The layer has small copper rectangles (pixels) that may be connected using either varactor diodes (which behave as voltage-controlled capacitors) or PIN diodes (electronic switches). The first antenna can steer in the xz-plane in any direction within about 23° from boresight (straight up from the antenna) and in the yz-plane to about 29° from boresight. The antenna uses varactor diodes on a planar layer. The second …


Design And Verification Of The Multi-Slit Solar Explorer Camera Field Programmable Gate Arrays, Jordan M. Johnson May 2026

Design And Verification Of The Multi-Slit Solar Explorer Camera Field Programmable Gate Arrays, Jordan M. Johnson

All Graduate Reports and Creative Projects, Fall 2023 to Present

The Multi-Slit Solar Explorer, or MUSE, is a NASA mission that will take images of the Sun to study solar flares and the solar corona. The mission will provide insight into the mechanisms behind space weather. The mission consists of two cameras: the Spectrograph (SG), and the Context Imager (CI). The Utah State University Space Dynamics Laboratory is providing both cameras for the mission.

This report describes a part of the design and verification process for a central component on these cameras known as the Field Programmable Gate Arrays (FPGAs). These FPGAs are programmed to acquire, handle, and send images …


Design Of A Low-Power Magneto-Inductive Magnetometer, Rowan Antonuccio May 2026

Design Of A Low-Power Magneto-Inductive Magnetometer, Rowan Antonuccio

All Graduate Theses and Dissertations, Fall 2023 to Present

Measuring magnetic fields in space helps scientists understand phenomena that can affect satellite communications and navigation systems on Earth. This research develops a new low-power magnetic field sensor for spacecraft that improves upon existing designs by moving the sensitive parts away from electrical interference and using energy-efficient digital electronics for precise measurements. The sensor’s power-efficient design is particularly important for small satellites, where power is limited and must be carefully managed. It will fly on future NASA missions to study disturbances in Earth’s upper atmosphere that can disrupt radio signals and GPS. This work contributes to our ability to better …


Small-Scale Analog Spiking Neural Network: Design And Simulation Of An Analog Deep Neural Network, Lucas Hogue May 2026

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 …


​Autonomous Agentic Orchestration For Physics-Aware Scientific Discovery: An Integrative Multimodal Framework For 2d Material Characterization​, Sankalp Pandey May 2026

​Autonomous Agentic Orchestration For Physics-Aware Scientific Discovery: An Integrative Multimodal Framework For 2d Material Characterization​, Sankalp Pandey

Electrical Engineering and Computer Science Undergraduate Honors Theses

The advancement of next-generation semiconductor and quantum technologies relies on the scalability of the fabrication of two-dimensional (2D) van der Waals heterostructures. However, this process is severely bottlenecked by characterization workflows. Optical microscopy provides high-throughput imaging of 2D material flakes, but lacks the explicit physical priors required for the discernment of sub-nanometer thickness variations, such as distinguishing monolayers from bilayers. The use of computer vision models to automate the localization and characterization process of the flakes was proposed. As a part of this effort, we develop QuantumFlake, an open-source framework to streamline the integration and deployment of computer vision models …


Domain-Specific Design On Fpga And Npu For Scientific Computing And On-Device Llm Inference, Miaoxiang Yu May 2026

Domain-Specific Design On Fpga And Npu For Scientific Computing And On-Device Llm Inference, Miaoxiang Yu

All Dissertations

High-performance computing (HPC) is changing rapidly as scientific simulations and large language model (LLM) workloads push the need for higher performance under tight power and memory constraints. Conventional platforms such as CPUs and GPUs accelerate computation through instruction-driven parallelism, relying on multithreading, SIMD, and SIMT execution, but increasingly encounter scalability limits imposed by the power and memory walls. In contrast, Field-Programmable Gate Arrays (FPGAs) and Neural Processing Units (NPUs) offer a high-efficiency alternative through dataflow-oriented architectures that exploit deep pipelining and customized memory hierarchies to reduce data movement. However, the performance potential of these spatial accelerators remains largely unrealized when …


Quantifying Spatiotemporal Ev In-Motion Load Dynamics For Flexible Distribution Grid Operations, Travis Newbolt May 2026

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 May 2026

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 …


Utility-Scale Battery Energy Storage Systems - Field Pilot Unit Experience, Analysis, And Review Of Technological Advancements, Kwabena A. Kyeremeh, Shaun E. Lavin, Grant M. Fischer, Dan M. Ionel, Aron Patrick May 2026

Utility-Scale Battery Energy Storage Systems - Field Pilot Unit Experience, Analysis, And Review Of Technological Advancements, Kwabena A. Kyeremeh, Shaun E. Lavin, Grant M. Fischer, Dan M. Ionel, Aron Patrick

Electrical and Computer Engineering Graduate Research

Utility-scale Battery Energy Storage Systems (BESS) are becoming increasingly important in modern power systems, providing services ranging from backup support to load balancing and peak shaving. The long-term operational performance and reliability of these systems with expanding deployment remain insufficiently documented. This paper provides an operational assessment of a 1MW/2MWh utility-scale BESS alongside a systematic review of technology developments across major subsystems. Operational metrics including round-trip efficiency (RTE), outage characteristics, and degradation patterns are examined to identify performance trends and the underlying causes of outages. In addition, testing and operational principles aligned with utility practice and standards are presented to …


An Energy- And Area- Efficient Two-Stage Latch Comparator Using Common-Mode Reset, Larry Yu May 2026

An Energy- And Area- Efficient Two-Stage Latch Comparator Using Common-Mode Reset, Larry Yu

Electrical Engineering Theses and Dissertations

This thesis presents an energy-and-area-efficient two-stage comparator implemented in TSMC 65 nm CMOS that incorporates a Floating Inverter Amplifier (FIA) followed by a latch using a common-mode reset scheme. The FIA improves input sensitivity and reduces kickback noise by isolating the input nodes from large latch voltage swings. The proposed latch resets its output nodes to a common-mode voltage rather than one of its supply rails, thereby reducing switching energy during the reset phase. The comparator can resolve differential input voltages as small as 2 mV with a clock period of 500 ps, achieving 74.33 μV input-referred noise while consuming …


A Full System Co-Simulation Platform For Evaluating Edge Machine Learning Inference Using Compute-In-Memory, Belsen Lee May 2026

A Full System Co-Simulation Platform For Evaluating Edge Machine Learning Inference Using Compute-In-Memory, Belsen Lee

Electrical Engineering and Computer Science (MS) Theses

We present a full-system co-simulation platform for evaluating embedded machine learning (ML) inference using compute-in-memory (CIM). CIM architectures aim to reduce data movement overhead by performing matrix operations in memory, but end-to-end benefits depend on system-level integration costs that are difficult to assess with isolated hardware models alone. To address this gap, we develop an integrated RISC-V QEMU-SystemC co-simulation environment that allows standard embedded Linux to interact with a transaction-level CIM accelerator model via memory-mapped I/O, direct memory access (DMA), and interrupts. To evaluate performance, we benchmark an MNIST image inference workload and a synthetic fully connected neural network, comparing …


A Low Power Fpga Compute Array For Machine Learning And Artificial Intelligence Applications, Todd Wilson May 2026

A Low Power Fpga Compute Array For Machine Learning And Artificial Intelligence Applications, Todd Wilson

All Graduate Theses and Dissertations, Fall 2023 to Present

Modern small satellites often lack the ability to analyze their data in real time, relying instead on downlinking raw measurements to Earth before any scientific interpretation can occur. This delay restricts missions that require rapid awareness of environmental or space-weather events. This thesis presents the Low-power Array for Cubesat Edge Computing Architecture, Algorithms, and Applications (LACE-C3A), a hardware platform designed to enable in-orbit data processing within the power and volume limits of CubeSat-class spacecraft. 

LACE-C3A uses a modular cluster of flash-based FPGAs, which offer low power consumption, radiation resilience, and in-flight reconfigurability. The system consists of a Controller board responsible …


Measurements And Scaling Of Ion Propulsion Impulse During Driven Magnetic Reconnection, Fatima Ebrahimi, Nicholas A. O'Gorman, Kush Maheshwari, Jongsoo Yoo, Alexandre Sainterme, Hantao Ji May 2026

Measurements And Scaling Of Ion Propulsion Impulse During Driven Magnetic Reconnection, Fatima Ebrahimi, Nicholas A. O'Gorman, Kush Maheshwari, Jongsoo Yoo, Alexandre Sainterme, Hantao Ji

Faculty Publications

Impulse scaling during magnetic reconnection, the magnetic energy conversion to kinetic energy, via direct Mach probe measurements in Magnetic Reconnection Experiment is examined. Ion exhaust velocity and impulse scalings with reconnecting magnetic field during the push phase of driven reconnection are presented. The outflows and impulse measurements are compared with global MHD simulations. Both measurements and simulations reveal a favorable scaling, greater than linear, of impulse with reconnecting field. These scaling results establish that magnetic reconnection could be utilized for plasma propulsion.


Power System Small-Signal Stability Migration And Metric Trends In A Test System With Increasing Ibr Penetration, Brandon Marshall May 2026

Power System Small-Signal Stability Migration And Metric Trends In A Test System With Increasing Ibr Penetration, Brandon Marshall

LSU New Orleans Theses and Dissertations

With the increasing demand of cleaner energy, inverter-based resources (IBRs) provide a greener alternative to traditional generation methods. IBRs fundamentally work different from traditional generators, though, and power system stability will change as IBRs are integrated into the system. The limitations of IBRs include providing less reactive power support to the system and lacking a spinning rotor for inertia to dampen disturbances. This study examines how small-signal stability is impacted when increasing IBR penetration on a test system. Stability impacts are realized by the migration of eigenvalues and relationships between power system metrics and small-signal stability metrics.


Central Pattern Generator Test Bench Report, Stephanie Wing-Yee Lee, Dustin Wong, Joseph Hernandez May 2026

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 …


Uav-Based Sensor Integration For In-Situ Lake Water Quality Monitoring, Alec R. Campbell May 2026

Uav-Based Sensor Integration For In-Situ Lake Water Quality Monitoring, Alec R. Campbell

Biological and Agricultural Engineering Undergraduate Honors Theses

Surface water monitoring is often constrained by limited spatial and temporal coverage due to the labor-intensive nature of traditional sampling methods, particularly in environments that are difficult to access or pose safety risks. Unmanned aerial vehicles (UAVs) offer a promising solution by enabling more frequent, spatially distributed, and cost-effective data collection. This study presented the design, development, and field evaluation of a UAV-based system for real-time, in-situ water quality monitoring. The system integrated multiple sensors, including oxidation-reduction potential (ORP), RGB spectrometry, pH, electrical conductivity (EC), dissolved oxygen (DO), and a multispectral spectrometer within a UAV platform.

Field testing was conducted …


Experimental Data-Driven System Identification Of Scale-Model Airboat Dynamics For Control And Autonomy Applications, Miguel A. Trejos May 2026

Experimental Data-Driven System Identification Of Scale-Model Airboat Dynamics For Control And Autonomy Applications, Miguel A. Trejos

LSU New Orleans Theses and Dissertations

To achieve autonomous control of a surface watercraft requires an accurate model describing the dynamics of the system. To this end, the modeling of dynamics of an airboat with a combustion engine-based propulsion system is investigated. Specifically, a black-box data-based approach using neural networks. To facilitate this, a custom data collection system was developed to record linear and rotational motion during field tests. Due to the airboats unique ability to traverse different terrains, not just water, the modeling of dynamics on different terrains was investigated.


Optimization-Based Power Management For Hybrid Towing Vessels: A Comparative Framework Toward Mission-Aware Control, Rachel K. Burchill May 2026

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 …


Hardware Integration Of Preamble Based 802.11a Wi-Fi Frame Location For Usrp Radios, Nicholas P. Margavio May 2026

Hardware Integration Of Preamble Based 802.11a Wi-Fi Frame Location For Usrp Radios, Nicholas P. Margavio

Honors Theses

Internet of Things (IoT) refers to a network of devices that can exchange information over the internet, and its deployments are projected to reach 30.9 billion by 2025, with most lacking encryption. One solution for these unencrypted devices is to use Specific Emitter Identification (SEI). SEI exploits distinct, native, and unintentional features of a radio’s signal to identify it and enhance wireless network security uniquely. For example, IEEE 802.11a Wireless-Fidelity (Wi-Fi) radio waveforms have a fixed structure that occupies the first 16 microseconds, from which SEI features can be extracted and used to identify the originating radio. By removing the …