Electrical and Electronics Commons^™

A Multiscale Ai Framework For Forest And Agriculture Health Monitoring: Drone-Based Object Recognition And Segmentation For Automated Ecological Assessment, Sruthi Keerthi Valicharla

Graduate Theses, Dissertations, and Problem Reports (ETD)

Forest and agricultural ecosystems are increasingly at risk due to invasive species, pests, and diseases, necessitating scalable, automated, and intelligent monitoring solutions. Traditional field based forest and agriculture health assessments are limited by cost, time, and spatial coverage. This dissertation presents a multiscale deep learning framework that automates forest and agriculture health monitoring using drone imagery and computer vision techniques. The system operates across three spatial levels: forest level, tree level, and leaf level, combining object detection, segmentation, and classification models to support large scale ecological assessment.

At the forest level, high-altitude drone imagery is processed using object detection and …

An Investigation Into Energy Consumption And V2g Potential Of An Electric School Bus Fleet, Rupesh Dahal

Graduate Theses, Dissertations, and Problem Reports (ETD)

The transition towards sustainable public transportation demands detailed evaluation of alternative fuel technologies. This thesis presents a comprehensive energy assessment and comparative analysis of diesel and electric school buses (ESBs) operating within the Monongalia County school district, its Vehicle-to-Grid (V2G) potential, and efficiency analysis of charging system. Utilizing real-world operational data collected from buses running identical routes, the study quantifies and compares their mileage specific energy consumption. The analysis reveals an average fuel economy of approximately 6.17 miles per gallon (MPG) for the conventional diesel school bus, contrasted with an average energy consumption rate of 0.46 miles per kilowatt-hour (miles/kWh) …

Dc To Dc Buck Converter, Matthew Bildstein

Williams Honors College, Honors Research Projects

This research project focuses on the design, implementation, and optimization of a high-efficiency DC-to-DC buck converter that steps down 12V to 5V for applications such as USB-powered devices, embedded systems, and automotive electronics. Building on my Associate’s degree project, where a 555 timer-based was replace with a LM2576 switching regulator IC.

The research involves circuit simulation in Multisim, PCB layout optimization in Ultiboard, and prototype testing to assess voltage stability, efficiency, and thermal performance. The project will incorporate best practices in power electronics design, including proper grounding techniques and thermal management strategies.

Expected outcomes …

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 …

Mxenes In Biosensing: Enhancing Sensitivity And Flexibility - A Review Of Properties, Applications, And Future Directions, Ali Mohammad Amani, Lobat Tayebi, Ehsan Vafa, Alireza Jahanbin, Milad Abbasi, Ahmed Vaez, Hesam Kamyab, Lalitha Gnanasekaran, Shreeshivadasan Chelliapan

Electrical & Computer Engineering Faculty Publications

MXenes are a novel type of nanostructured material that has received a lot of attention for their potential applications in bioanalysis owing to their unique features. These materials, made from transition metal nitrides, carbides, or carbonitrides, have a number of advantages, including high hydrophilicity, a large surface area, strong metallic conductivity, superior ion transport capabilities, biocompatibility, and low diffusion barriers. Their surfaces are easily manipulated, making them more adaptable for a variety of applications, including biosensing. The outstanding properties of MXenes have attracted researchers of different fields, including renewable energy, fuel cells, supercapacitors, electronics, and catalysis. In the context of …

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 …

Surface Morphology And Moisture Adsorption/Desorption Characteristics Of Hybrid-Dielectric Moisture Sensors, Ronak Ali

Theses and Dissertations--Electrical and Computer Engineering

Relative humidity sensors are used for high-humidity measurement. Moisture sensors, or dew point sensors are used for low-humidity measurement (< 1 ppm_v). The dissertation contains two parts of studies. In the first part, the effect of surface morphology on the response speed of moisture sensors is studied. Moisture sensors using α-Al₂O₃ films as porous dielectric materials deposited by anodic spark deposition are studied. In this part of the study, a variety of small pores have been studied to investigate the response speed of moisture sensors. Three different surface morphologies have been studied using scanning electron microscopy. One …

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 …

Lifecycle Carbon Footprint And Sustainability Evaluation Of Dram-Based Processing In Memory Computing Architectures, Samrat Pravin Patel

Theses and Dissertations--Electrical and Computer Engineering

The use of computing technologies has significantly enhanced several aspects of our day-to-day lives. But it has still revealed significant environmental concerns, primarily related to greenhouse gas emissions and energy consumption. Initially, the primary environmental problems associated with computing were energy consumption during device operation. However, with the rapid advancement of technology and increasing computational demands, attention has shifted towards the embodied carbon footprint. This term refers to the total greenhouse gas emissions throughout a product’s lifecycle from the extraction of raw materials to end-of-life processing. It has become increasingly significant in the context of manufacturing integrated circuits (ICs), such …

Implementation Of Quantized Artificial Neural Networks With Spintronic Stochastic Computing, Saadi Sabyasachi Mr.

Theses and Dissertations

Artificial intelligence or machine learning is going through a rapid expansion. It also incurs significant costs for power and device footprints. Various approaches are being explored to design energy and hardware efficient machine learning models. Stochastic computing has been proposed for efficient machine learning implementation. It requires a source of random number generation which poses some practical challenges. So spintronic solutions such as magnetic tunnel junction has been used for random number generation. Again, spintronic random number generation to implement high precision circuit is prone to device-to-device variations. Hence we designed quantized artificial neural network with spintronic stochastic computing which …

Differential Equations' Coverage In Circuits And Heat Transfer Courses In An Engineering Technology Curricula, Otilia Popescu, Orlando Ayala

Engineering Technology Faculty Publications

Differential equations are at the core of any undergraduate engineering as well as of science programs. While a course in differential equations is required by any engineering degree, it is not a requirement for engineering technology programs, which usually require mathematics up to calculus I. This paper discusses the undergraduate engineering technology curricula, focusing on how differential equations are taught to engineering technology students and how they are covered in the programs. In particular, the paper will discuss the treatment of differential equations in electrical circuits and heat transfer courses.

Sensitivity Analysis Of The 197 Mhz Prototype Crab Cavity For Eic, Subashini De Silva, Jean R. Delayen, B. Xiao, E. Drachuk, I. H. Senevirathne, A. Castilla, N. Huque, Z. Li

Physics Faculty Publications

The Electron-Ion Collider at BNL requires several crabbing systems that will be operating at 197 MHz and 394 MHz to compensate for the loss of luminosity due to the large crossing angle of the colliding beams. Two 197 MHz crab cavity cryomodules containing two cavities each will be installed in the Hadron Storage Ring (HSR) at the IP6 interaction region. Due to its large size compared to previously developed crabbing cavities, the 197 MHz crabbing cavity system was identified as one of the critical rf systems in the EIC. Therefore, a cavity has been designed including the ancillaries, and is …

Simulated Efficiency Of A Modified Bmw I3 Traction Motor Operating As An Isolated Dc-Dc Converter, Shayne Taylor

Graduate Research Theses & Dissertations

Battery electric vehicles are currently fighting to have any advantage over internal combustion engine powered vehicles to reduce global transportation greenhouse gas emissions. Electric motors are typically deemed as the largest source of loss in many vehicles but have recently become more efficient on average than the AC-DC converter used to charge the vehicle. This paper investigates the potential for a dual three phase electric traction motor based on a BMW i3 electric vehicle traction motor to take the place of an isolated DC-DC converter, an important part of the AC-DC converter. This electric machine in simulations produced a similar …

3d Printing Metal Horn Antennas Using Periodic And Aperiodic Perforated Designs For Directed Energy Applications, Alexis Valencia

Open Access Theses & Dissertations

In the past decade, Additive Manufacturing (AM) has proven to be groundbreaking yet reliable technology. Not only has it revolutionized the way we approach problems in research, design, and production but it has enabled burgeoning discoveries and methods due to the technologyâ??s efficiency, speed, and low manufacturing cost. One area that benefits greatly from this includes radio frequency (RF) devices like horn antennas. At the moment, most horn antennas produced by conventional manufacturing are expensive, heavy, and limited in customization, yet they are necessary for various systems like satellite communication, radar, radio astronomy, and more. 3D printing technology would alleviate …

Fabrication Of Thylakoid Membrane-Based Photo-Bioelectrochemical Bioanode For Self-Powered Light-Driven Electronics, Amit Sarode, Gymama Slaughter

Center for Bioelectronics Publications

The transition toward sustainable and decentralized energy solutions necessitates the development of innovative bioelectronic systems capable of harvesting and converting renewable energy. Here, we present a novel photo-bioelectrochemical fuel cell architecture based on a biohybrid anode integrating laser-induced graphene (LIG), poly(3,4-ethylenedioxythiophene) (PEDOT), and isolated thylakoid membranes. LIG provided a porous, conductive scaffold, while PEDOT enhanced electrode compatibility, electrical conductivity, and operational stability. Compared to MXene-based systems that involve complex, multi-step synthesis, PEDOT offers a cost-effective and scalable alternative for bioelectrode fabrication. Thylakoid membranes were immobilized onto the PEDOT-modified LIG surface to enable light-driven electron generation. Electrochemical characterization revealed enhanced redox …

Antennas For Emerging Satellite Services, Jakub Przepiorowski

Doctoral

The NewSpace era has revolutionized access to space, driving advancements in satellite communication (SATCOM) systems and creating demand for low-cost, compact, and high-performance user terminals. This thesis addresses these needs by developing innovative antenna solutions tailored for user terminals designed for emerging satellite constellations and satellite Internet-of-Things (S-IoT) applications.

Neural Network-Based Image Compression, Atefeh Khoshkhahtinat

Graduate Theses, Dissertations, and Problem Reports (ETD)

The rapid advancement of information technology and the exponential growth of digital communication have significantly increased the demand for efficient data compression techniques that reduce storage requirements, minimize bandwidth consumption, and accelerate data transmission—without substantially compromising data quality. This dissertation addresses these challenges by investigating and developing advanced learned image compression (LIC) methods, with a particular focus on lossy compression for both natural images and scientific imagery obtained from NASA’s Solar Dynamics Observatory (SDO) mission. Traditional image compression standards—such as JPEG, JPEG2000, BPG, and HEVC—rely on manually engineered transforms and heuristic rules, which often lack the adaptability required to accommodate …

Development Of 2d Microfluidics Surface With Low-Frequency Electric Fields For Cell Separation Applications, Madushan Wickramasinghe, Dharmakeerthi Nawarathna

Electrical & Computer Engineering Faculty Publications

Cell separation techniques are widely used in many biomedical and clinical applications for the development of screening, diagnosis and therapeutic tests. Current 3D microfluidics-based cell separation methods have limited applications in part due to low throughput and technical complexity. To address these critical needs, we have developed a 2D microfluidics surface which is the miniaturized version of a 3D microfluids cell separation device. Using low-frequency electric fields (1–10 Vpp and 1 kHz–20 MHz), we have first studied dielectrophoresis, AC electro-osmosis and capillary flow within a sessile drop, and finally utilized the results to develop the 2D cell separation surface. Our …

A Novel Intelligent Thermal Feedback Framework For Electric Motor Protection In Embedded Robotic Systems, Mohamed Shili, Salah Hammedi, Hicham Chaoui, Khaled Nouri

Electrical & Computer Engineering Faculty Publications

As robotic systems advance in autonomy and sophistication while being used in uncertain environments, the challenge of building reliable and robust electric motors that are embedded into robotic systems has never been a more important engineering problem. Thermal distress caused by extended operation or excessive loading can negatively affect a motor’s performance and efficiency and lead to catastrophic hardware failure. This paper proposes a novel intelligent control framework that includes real-time thermal feedback for hybrid electric motors that are embedded into robotic systems. The framework relies on adaptive control techniques and lightweight machine learning techniques to estimate internal motor temperatures …

Flux-Weakening Control Methods For Permanent Magnet Synchronous Machines In Electric Vehicles At High Speed, Samer Alwaqfi, Mohamad Alzayed, Hicham Chaoui

Electrical & Computer Engineering Faculty Publications

Permanent magnet synchronous motors (PMSMs) are widely favored by manufacturers for use in electric vehicles (EVs) because of their many benefits, which include high power density at high speeds, ruggedness, potential for high efficiency, and reduced control complexity. However, since the Back Electromotive Force (EMF) increases proportionally with the motor’s rotational speed, it must be carefully controlled at high speeds. Flux-weakening (FW) control is required to avoid excessive electromagnetic flux beyond the power source and inverter’s voltage restrictions. This paper aims to compare various FW control strategies and analyze their effectiveness in maximizing the speed of PMSMs in EV applications …

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 …

Batteryless Nfc-Enabled Wireless Sensor Node: Design, Optimization, And Implementation, Rishin Patra

Dissertations, Master's Theses and Master's Reports

This thesis presents the design, construction, and testing of a batteryless Near-field communication (NFC) powered wireless sensor node intended for maintenance free, short range Internet of Things (IoT) applications. The work focuses on harvesting energy from a 13.56 MHz NFC field to power a very low-power sensing platform capa- ble of measuring temperature, pressure, and humidity without the use of batteries or wired power. The motivation behind this approach is the growing need for reliable, sustainable, and low-maintenance sensing systems that can operate in environments where battery replacement is impractical, undesirable, or environmentally costly. The prototype is built around a …

Design Of Fast Start-Up High-Q Oscillator For Wireless Sensor Nodes Transceiver Frequency Reference, Abdolraouf Rahmani

Student Works (2020-2029)

With the prevalence of wireless sensor networks and the Internet of Things (IoT), optimizing power in battery-powered wireless nodes is crucial due to the inconvenience and cost of replacing batteries in remote areas. Synchronized power modulation between "Sleep" and "Active" states, known as burst mode activation, allows nodes to conserve power. However, frequent transitions between these states consume significant energy, highlighting the need to reduce the start-up time of the slowest component, the high-Q crystal oscillator. Additionally, to ensure improved synchronization within the network and a cost-effective IoT device manufacturing, the device should be produced with low start-up time variations …

Bright And Dark Pulsed Fiber Lasers Based On Multimode Interference, Yu Chen

Student Works (2020-2029)

Pulsed lasers, particularly ultrashort pulsed lasers, find widespread application across various fields including telecommunications, bio-imaging, spectroscopy, atmospheric measurements, surgery, and material processing. This study focuses on harnessing the potential of the single mode-multimode-single mode (SMS) structure as a robust avenue for developing simple, compact, and cost-effective bright and dark pulsed erbium-doped fiber lasers (EDFLs). The SMS configuration serves as an ingenious artificial saturable absorber (SA), facilitating the generation of ultrashort pulsed lasers through the Kerr Effect with nonlinear multimode interference. By precisely fusion-splicing single mode fibers to both ends of a designated length of multimode fiber, the SMS architecture is …