Digital Commons Network^™

Global Spectral Clustering Of Temporally Stable Pixels For Epics Identification, Validation, And Hyperspectral Assignment For Satellite Calibration, Juliana Maria Fajardo Rueda

Electronic Theses and Dissertations

No abstract provided.

Refinement Of Trend-To-Trend Cross Calibration Total Uncertainties Utilizing Extended Pseudo Invariant Calibration Sites (Epics) Global Temporally Stable Target, Minura Samaranayake

Electronic Theses and Dissertations

Cross-calibration is an essential technique for calibrating Earth Observation satellite sensors, which involves taking nearly simultaneous images of a ground target to compare uncalibrated sensor to a well-calibrated reference sensor. This study introduces the hyperspectral Trend-to-Trend (T2T) cross-calibration technique utilizing EPICS Cluster 13 Global Temporally Stable (Cluster 13-GTS) as the calibration target, offering better temporal stability than previous targets used in T2T cross-calibration by an absolute difference of 0.4%, between coefficients of variation across all bands excluding CA band. A multispectral sensor-specific normalized hyperspectral profile was developed using the EO-1 Hyperion hyperspectral profile over Cluster 13-GTS to improve Spectral Band …

Design Of An Active-Control Pressure Regulator For A Rocket, Seth Arkwright

Williams Honors College, Honors Research Projects

An electronically actuated pressure-regulation valve and controller are necessary for maintaining pressure levels in a pressure-fed liquid-fueled rocket engine. Mechanical regulators are too heavy and have unacceptably high-pressure variation throughout the operation of a dynamic system like a rocket. Developing an electronic pressure regulator using a PID controller is a method by which a reliable, accurate, and lightweight flow regulator can be built for use on a rocket vehicle. This work will outline the development of flow simulations, PID controller, physical valve hardware, and initial testing.

Zips Racing Electric - Vehicle Control Unit, Ryan Stoller, Brian Glen, John Wozencraft, Tetra Engdahl

Williams Honors College, Honors Research Projects

Zips Racing Electric is a design team at the university that builds and races electric cars. The racing team wants to design a four-wheel drive system to increase performance, but the current computer on the vehicle cannot control the more complex power train. The goal of the project will be to build a hardware device that can read sensor inputs and control the torque output to each motor individually. The control device being designed will need to interface with the existing systems on the car and control regenerative breaking, torque vectoring, and other auxilliary systems on the car.

Voice Operated Automatic Chessboard, Logan Pursley, Rafael Soler, Jason Roser, Tyler Hoxworth

Williams Honors College, Honors Research Projects

Chess is a board game played at a variety of skill levels worldwide. Over 1000 years, chess has always required players to move the pieces manually. Unfortunately, anyone who lacks dexterity in their hands or arms cannot manually move the chess pieces on their own. Consequently, a chess board that can be played without hands or arms must be created to accommodate a broader audience. This is the motivation behind the Automatic Chessboard. This design will allow a player to engage in a dynamic and physical game of chess using only their voice. A 3-axis control system will allow for …

Automatic Cat Caretaker, Connor Mcclenathan, Ryan Anderson, Andrew Tate

Williams Honors College, Honors Research Projects

This project will involve developing and constructing a self-cleaning litter box with feeding and watering functions attached. The machine will have a user interface for setting both the feeding and watering times, as well as how much to fill the food and water bowls at the same time. The project will involve the use of motors for the cleaning, feeding, and watering functions, sensors to detect when to perform those functions, and a microcontroller to process all the data and to tell the motors when to perform their respective functions. This project's goal is to make the task of caring …

Cochlear Electrode Insertion Training Model, Sarah Powell, Kaelyn E. Kraley, Nathan J. Smith

Williams Honors College, Honors Research Projects

Cochlear implant surgery is a delicate procedure performed by Otolaryngologists (ENTs) to implant an electronic device into the inner ear to provide a sense of sound for people who are profoundly deaf or hard of hearing. The current practices of training involve cadavers and 3D-printed models. Cadavers are commonly used but are expensive, single-use, and do not provide visual and haptic feedback, which are essential for medical students. 3D printed models are less commonly used and are hard to fabricate and not as realistic. If medical students are not properly trained for this delicate procedure, then risks are significantly increased …

Autonomous Landscape Exploration Rover Using Imaging Surface Navigation (Alexis), Noah Jones, Dominic Salupo

Williams Honors College, Honors Research Projects

The objective is to develop a small-form-factor rover prototype that can be used to prove out a novel traversal method for use on extraterrestrial surfaces. The novel traversal method being proposed is LIDAR/CV-enhanced navigation, provided by a detachable flight vehicle that can communicate with the rover. On planets with thin atmospheres, cold gas thrusters or similar may be needed, but for the scope of this project more traditional flight/propulsion methods will be used.

All-In-One Security System, Nathaniel Rohr, Elizabeth M. Daniels, Kyle H. Sturgin, Jonathan R. Carozza

Williams Honors College, Honors Research Projects

The proposed All-in-One Security system is a security system capable of automatically or manually arming and disarming the building it is installed in. When armed, the system rolls down the window shades and locks the front door. When disarmed, the system unlocks the front door and rolls up the window shades. The system will have a keypad by the front door for arming and disarming the system. Additionally, there will be a smartphone app that can arm and disarm the system via bluetooth.

Vector Estimation For Continuous Tracking Of Observed Radio Signals (V.E.C.T.O.R.) Lunar Navigation System, Dimitry Melnikov, Evan Bartel, Andrew Burrier, Goran Gjorgievski

Williams Honors College, Honors Research Projects

NASA's Artemis program requires precise navigation capabilities to establish the first sustained presence on the lunar surface. However, as launches bring necessary orbital infrastructure, the Artemis program will face a critical period during which reliable lunar navigation is not possible. To address this challenge, the V.E.C.T.O.R. system tracks assets, such as rovers and astronauts, as User Terminals relative to a pre-existing cell tower, or Base Station. To do so, the system leverages existing Base Station hardware to calculate the location of User Terminals in conjunction with existing communications infrastructure.

Non-Line-Of-Sight Classification In Urban Areas Based On Machine Learning Algorithms, Mohamed Ali Ezzelarab, Mohamed Abdelazim Mohamed, Eman Abdelhalim, Ashraf Abosekeen

Mansoura Engineering Journal

Non-Line-Of-Sight (NLOS) and multipath errors are significant causes of poor accuracy in Global Navigation Satellite Systems (GNSS). These errors occur when satellite signals are diffracted or reflected by obstacles instead of traveling directly along the Line-Of-Sight (LOS), particularly in urban environments. Such diffracted or reflected signals can reach GNSS receivers, skewing pseudorange measurements and posing challenges to accurate GNSS positioning. This study introduces an innovative approach using supervised Machine Learning (ML) models to detect and mitigate NLOS error. To develop and validate these models, GNSS data collected during the smartLoc project from Frankfurt and Berlin in Germany were leveraged, representing …

Enhancing Channel Data Savings And Information Transfer Efficiency In Ultrasound Imaging, Sai Konda, Hicham Chaoui

Electrical & Computer Engineering Faculty Publications

Ultrasound is a popular imaging technique mainly due to its non-invasive nature. And so, it is being used in a variety of applications. Due to plane wave imaging technique in ultrasound, frame rate of ultrasound imaging has the potential for being very high. Due to which, many channel data frames are being generated within a few seconds. As a result, tasks such as storing data frames and transferring them from front end ultrasonic system to processing computers are presenting significant challenges. Our current research work minimized these issues. We proposed and implemented: (a) Data encoding technique - We combined every …

Computational Assessment Of Vitrimers Self-Healing For Renewable Energy And Aerospace Structures, Walaaeldin Mohamed Ahmed Derbala

Browse all Theses and Dissertations

Self-healing polymers, particularly vitrimers, are emerging as promising candidates in the development of advanced materials for renewable energy and aerospace structures. These materials exhibit dynamic covalent bond exchange mechanisms that enable reprocess ability, damage repair, and extended operational lifetime under harsh conditions. This study presents a density functional theory (DFT)-based computational investigation of the mechanistic pathways and energetics of bond exchange reactions in model vitrimer systems. We explore transition states, energy barriers, and thermodynamic features corresponding to associative and dissociative self-healing reactions in vitrimers. The study focuses on Diaminodiphenyl disulfide (AFD), a bifunctional molecule composed of two para-substituted aminophenyl rings …

Hydrogen Storage Density And Adsorption Energy Barriers On Li-Decorated Bc3 Nanosheet, Sri Venkat Pavan Upasi

Browse all Theses and Dissertations

Hydrogen is considered an emerging carrier of clean energy with renewable capabilities. Widespread hydrogen energy utilization necessitates efficient storage strategies. Functionalized nanomaterials, such as Li-decorated BC3 nanosheets, are among the primary candidate materials for hydrogen storage. This research investigates the feasibility of hydrogen storage by estimating energy barriers and their dependence on storage density on Li-decorated BC3 nanosheet. Density functional theory (DFT) simulations provide estimates of adsorption energies and saddle points for hydrogen storage and compare corresponding reaction rates. The results are expected to help us understand the advantages and possible shortcomings of hydrogen storage on such nanomaterials.

Mobile Weather Satellite Receiver, Luke Datsko, Sam Watts, Jason Do, Adam Bechtler

Williams Honors College, Honors Research Projects

The "Mobile Weather Satellite Receiver" project aims to create a portable, user-friendly device that receives and displays weather information from geostationary satellites, addressing the limitations of traditional weather sources like the Internet and weather radio, particularly in remote areas. This device will collect and demodulate satellite data, including imagery and Emergency Managers Weather Information Network (EMWIN) forecasts, to provide users with detailed local forecasts and real-time alerts.

Designed with a user-centric approach, the system includes a satellite dish, Software Defined Radio (SDR), a Raspberry Pi, and a custom software interface for ease of use. Its portability and ability to function …

A Novel Real-Time Threshold Algorithm For Closed-Loop Epilepsy Detection And Stimulation System, Liang Hung Wang, Zhen Nan Zhang, Chao Xin Xie, Hao Jiang, Tao Yang, Qi Peng Ran, Ming Hui Fan, I. Chun Kuo, Zne Jung Lee, Jian Bo Chen, Tsung Yi Chen, Shih Lun Chen, Patricia Angela R. Abu

Department of Information Systems & Computer Science Faculty Publications

Epilepsy, as a common brain disease, causes great pain and stress to patients around the world. At present, the main treatment methods are drug, surgical, and electrical stimulation therapies. Electrical stimulation has recently emerged as an alternative treatment for reducing symptomatic seizures. This study proposes a novel closed-loop epilepsy detection system and stimulation control chip. A time-domain detection algorithm based on amplitude, slope, line length, and signal energy characteristics is introduced. A new threshold calculation method is proposed; that is, the threshold is updated by means of the mean and standard deviation of four consecutive eigenvalues through parameter combination. Once …

Quantized Average Agreement Algorithms With Error Correction For Digraphs, Shuaib A. Mughal

Honors Undergraduate Theses

Multi-agent systems have become more and more prevalent as technology increasingly gets integrated into our daily lives. Some of these technological systems are large in size; for example, the smart grid where multiple devices are used to monitor and control different aspects of the energy grid. Another example is a team of autonomous systems deployed for a specific task. When these systems are spatially distributed, an important component of distributed algorithms is the ability for the agents to reach consensus on the global state of the system. Reaching agreement enables the spatially distributed agent make decisions or determine the next …

Behavior Analysis Of Simple And Complex Workloads, Davi D. Dantas

Honors Undergraduate Theses

Complex tasks have evolved rapidly in recent times due to tremendous advancements in computational power and data availability. With the ever-increasing presence of complex applications, this paper attempts to distinguish between complex and simple applications. This paper explored side-channel analysis as a method to differentiate complex workloads from simple workloads by monitoring system-level metrics such as power consumption, cache behavior, and memory accesses. By leveraging side-channel effects such as power analysis and memory access, this study seeks to establish unique hardware signatures for complex workloads. Using tools such as Intel Pin, the data will be collected from complex and simple …

Review: Dielectric Barrier Discharge Plasma Actuators For In-Flight Applications, Sabeel Saleem Mohammed

Anthós

Dielectric barrier discharge (DBD) is a phenomenon observed when high voltage is passed through a dielectric barrier at high frequencies. Current DBD plasma actuators (PAs) excel at laminar fluid boundary layer control but suffer from limited momentum flux and fluid mechanic inefficiencies. In this article, Mohammed analyzes previous discourse on DBD PAs and offers directions for future research and potential DBD PA applications. Previous work on DBD PAs documented thrust generation at high voltages and frequencies, thrust in varying fluid compositions, and vortex generation. However, certain arrangements hinder flow magnitudes, limiting the use of multiple DBD PAs in close proximity. …

Measurement Of Moisture Levels In Oils And Lubricants Using A Novel Moisture Sensor, Aaron Swartz

Theses and Dissertations--Electrical and Computer Engineering

It is very challenging to measure moisture levels in oils. There is not a good method to measure it. Using the novel moisture sensor, we tried various methods to measure the moisture levels in oils. The initial trials are to immerse the sensor chip into the oils to see any sensor reading changes with the change of moisture levels in oils. It was observed that the sensor reading was unstable. The idea for immersion of the sensor chip into the oils failed. The last idea is to heat the oil to let all moisture evaporate fully. Before heating, the dew …

Computing With Photonic Phase Change Memory, David B. Pippen

Theses and Dissertations--Electrical and Computer Engineering

A recent breakthrough in silicon photonics includes the discovery and use of phase changing materials (PCMs). These materials can be programmed to store nonvolatile values, and when a stored value in a PCM cell is read, it changes the amplitude of the read signal, imprinting the value held into the PCM cell on the amplitude of the read signal. This thesis proposes a new approach to using PCM cells not only for photonic memory but also as a substrate to perform multiplications in the photonic domain. The proposed multiplier uses PCM cells to encode amplitude-analog weight values and differing lengths …

Scalable Hypergraph Structure Learning With Diverse Smoothness Priors, Benjamin T. Brown

Theses and Dissertations--Electrical and Computer Engineering

In graph signal processing, learning weighted connections between nodes from signals is a fundamental task when the underlying relationships are unknown. With the extension of graphs to hypergraphs, where edges can connect more than two nodes, graph learning methods have similarly been generalized to hypergraphs. However, the absence of a unified framework for calculating total variation has led to divergent definitions of smoothness and, consequently, differing approaches to hyperedge recovery. This challenge is confronted in this work through generalization of several previously proposed hypergraph total variations, allowing ease of substitution into a vector-based optimization. To this end, a novel hypergraph …

Electromagnetic Integral Equation Methods For High-Order Field Predictions, Jordon N. Blackburn

Theses and Dissertations--Electrical and Computer Engineering

Methods like the Method of Moments (MoM) or the locally-corrected Nyström (LCN) method are employed to discretize and solve electromagnetic integral equations. This process results in large, dense systems of linear equations that must be solved. In many cases, the elements of the system matrix can be computed analytically or approximated with high-order numerical methods. In this thesis, various approaches are presented to improve the accuracy and efficiency of integral equation solutions.

The second chapter derives a modified form of the low-rank matrix approximation algorithm known as the adaptive cross approximation (ACA). The original ACA has been observed to lose …

Multi-Objective Design Optimization Of Power Converters For Electric Aircraft Propulsion, Ben Luckett

Theses and Dissertations--Electrical and Computer Engineering

As global focus shifts to the electrification of the aviation sector, the need for high efficiency, lightweight, and reliable electric aircraft propulsion power converter systems has become apparent. These goals can be somewhat conflicting with each other, and a single multi-domain-optimized solution is not guaranteed. The search for a design which presents satisfactory merits becomes a drudge through various trade-off studies which can expend vast quantities of manpower and time. As a remedy to this, design automation allows the process to be computer-assisted. This dissertation presents the core fundamentals for a general multi-objective design optimization framework intended for the design …

Enhance The Design Of Low-Cost Fast Charging Battery Systems For Electric Mobility Systems, Omar Matar, Abdalrahman S. Alneklawy, Yara M. El-Hawary, Ahmed M. Elbeshbeshy, Ali Shoman, Ahmed R. Alagmy, Ahmed Mashaly, Arwa G. Saheen, Sahar S. Kaddah, Basem M. Badr

Mansoura Engineering Journal

The need of electric mobility (E-Mobility) systems increases daily, where the E-Mobility systems contribute in decreasing gas emissions from transportation Electric motorcycles (E-Motorcycles) are one of the E-Mobility systems, which reduce the problems resulting from traditional fossil fuel exhausts. This paper discusses the design and development of low-cost battery systems for E-Motorcycles, where a fast charging system is simulated, analyzed, and deployed to charge a battery package that outputs 72V & 8A at rated performance. Research and analysis of different power converter topologies are performed with respect the cost and system performance. A battery tester circuit is designed and built …

Advancing Electrical Stimulation: Full-Head Mri Segmentation For Abnormal Brain Anatomy With Tdcs, Andrew Birnbaum

Dissertations and Theses

Evaluating the effectiveness of transcranial direct current stimulation (tDCS) is essential for guiding its integration into therapeutic and performance-enhancement applications. In our laboratory, we investigate the efficacy of tDCS across multiple experimental models, including both animal and human studies. I have contributed significantly to the execution and analysis of these experiments, which include studies in rats and healthy human participants aimed at evaluating whether electrical stimulation of the motor cortex can enhance motor learning. These studies assess improvements in fine motor performance resulting from tDCS. In stroke patients, I contribute to our investigation of tDCS as a rehabilitative intervention, particularly …

From Tpu To Qpu: Bridging Fidelity Gaps Across Next-Generation Computing Systems, Mohammad Walid M. Charrwi

Dissertations and Theses

Modern computing systems continue to advance rapidly, enabling unprecedented computational capabilities across diverse domains. Among these powerful architectures are AI accelerators such as Tensor Processing Units (TPUs) and quantum computing systems utilizing Quantum Processing Units (QPUs) stand out as trans-formative technologies. Despite their potential, these systems share significant challenges related to hardware infidelity, manifested as error-induced degradation in computational accuracy and reliability. This thesis explicitly addresses cost-effective methods to screen-out defective AI accelerators across next-generation computing architectures and boost quantum circuit output fidelity through hierarchical circuit optimization using advanced machine learning methodologies.

This thesis first proposes a cost-effective testing methodology …

Metasurfaces And Their Applications In Photonic Devices, Shuwei Guo

Dissertations and Theses

Metasurfaces are flat artificial optical elements composed of dielectric and/or metallic nanostructures. They can manipulate light in unprecedented ways by altering amplitude, phase, and polarization at subwavelength scales. The ability of these two-dimensional elements to perform multiple optical functions within compact optical systems—while offering high functionality, small form factors, and easy integration into optoelectronic devices—has sparked significant interest across various fields and industries. These applications span imaging, sensing, nonlinear and quantum optics, optical computing, automotive technology, augmented and virtual reality, and more.

In this dissertation, we explore and design new multifunctional metasurfaces with a focus on manipulating spectral responses. First, …

Design, Fabrication, & Laboratory Testing Of A Strain Gage Instrumentation System For Marine Applications, Salem C. Homrighausen

UNF Graduate Theses and Dissertations

A strain gage-based instrumentation system was designed and fabricated to measure the moment present at the base of a mock, diesel-engine snorkel for a submerged vehicle designed to operate in the surf zone. Afterwards, a lab experiment was designed and executed to determine the accuracy of the instrument and a 2-dimensional, matrix-vector equation was formulated to relate pairs of voltages, Vx and Vy, to moments, Mx and My for the experiment. Three versions of this model were built. The first model was created using traditional statics equations governing strain, stress, moment, force. The second and third models were built directly …

Solar Energy Prediction Using Advanced Hybrid Machine Learning Models, Jelawi A. Alqhtani

UNF Graduate Theses and Dissertations

Accurate short-term forecasting of solar power generation is critical for the reliable and cost-effective operation of renewable-based microgrids, where sudden weather-induced variability can compromise grid stability, battery scheduling, and energy trading decisions. Traditional physical and statistical models struggle to capture the complex non-linear relationships and localized weather effects, while individual deep learning architectures often exhibit systematic biases such as chronic under-prediction of peak generation. This thesis proposes a novel Cross-Feedback Ensemble framework that combines the complementary strengths of Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and one-dimensional Convolutional Neural Network (1D-CNN) models through an iterative cross-feedback mechanism and a …