Electrical and Computer Engineering Commons^™

Pressure Switch Tester, Michael Starasinich, Andrew Dobson, Jordan Huschen, Mitchell Smith, Melvin Brown Iii

Honors Capstones

Abstract—- The Pressure Switch Test Stand is a comprehensive and automated testing solution designed to streamline the actuation and validation of simultaneously. At the core of the system is a PLC-controlled architecture that enables precise control and simulation of pressure conditions, replicating real-world scenarios to ensure accurate and reliable switch performance.

This test stand integrates robust mechanical fixtures, a reliable pneumatic control system, custom-designed electrical circuits, and a modular software interface, working in unison to deliver consistent and high-fidelity testing outcomes. Each pressure switch undergoes a sequence of pressure ramps and holds, with the system continuously monitoring switch states, activation …

Development Of A Cost-Effective Daq For Measuring Brake Performance In Race Cars, Adrin Alias

2025 Spring Honors Capstone Projects - Archive

This project explores the feasibility of creating a cost-effective data acquisition (DAQ) system for high-speed, real-time brake performance testing of Formula SAE racecars. The research addresses the limitations of the current MoTeC DAQ system currently employed by the team, which is costly and time-consuming to set up for on-car testing. The team will use a brake dynamometer for steady-state comparisons of different brake pad compounds (senior design project), but evaluating real-world performance requires on-car testing. By systematically comparing various hardware platforms, sensors, communication protocols, and storage solutions, this project aims to balance cost-efficiency with reliability and performance. The research evaluates …

Automation Programming For Uhv-Cvd Growth Of Group Iv Materials, William Hay

Electrical Engineering and Computer Science Undergraduate Honors Theses

The automation programming of a UHV-CVD reactor for group IV materials was performed. The reactor was programmed to perform all the necessary functions for a Germanium (Ge) growth with little response from the user. The overall goal was to fix an Argon purge program to clean out the process chamber of gases and create an Excel output program to ease any work on the user. There were also general fixes and address name changes that occurred throughout the program. Then, a one step and two step growth of a Ge material was formed in a UHV-CVD reaction for analysis. Germanium …

Defect Characterization Of Sic Schottky Barrier Diode Using Deep Level Transient Spectroscopy, Zachary I. Mccoy

Electrical Engineering and Computer Science Undergraduate Honors Theses

The aim of this project is to use deep level transient spectroscopy (DLTS) to energetically evaluate defects by using the carrier concentration dependence on temperature and where these carriers may experience deviation from standard predictions. These defects become apparent through multiple C-V measurements that are swept through a temperature range. By analyzing trends with respect to temperature, the defects can be energetically “located,” and thus identified. This identification can help streamline semiconductor material manufacturing/growth because DLTS identifies potential defect causes by providing data to characterize semiconductor mid-band defects. DLTS can assess nearly all parameters associated with traps/defects including density, thermal …

An Approach Of Implementing Mtncl And Mtd3l Asynchronous Logic Paradigms On Fpgas, Kile T. Harvey

Electrical Engineering and Computer Science Undergraduate Honors Theses

This thesis describes the creation of component libraries for the implementation of Multi-Threshold NULL Convention Logic (MTNCL) and Multi-Threshold Dual-spacer Dual-rail Delay-insensitive Logic (MTD³L) on AMD 7 Series, AMD UltraScale, and AMD UltraScale+ FPGAs. The utilization of these libraries is identical to those used in the creation of MTNCL and MTD³L application-specific integrated circuits (ASICs), leading to intuitive use for designers familiar with the logic paradigms. Single-stage and pipelined designs were created using both libraries, which were then tested and verified to be logically equivalent to their ASIC counterparts. Future work will include creating and testing …

Design, Simulation, And Testing Of Planar Transformer For Smart Green Power Node (Sgpn) Isolation Using Ansys, Brooke Scott

Electrical Engineering and Computer Science Undergraduate Honors Theses

The goal of this project was to design and simulate a small, high-frequency, planar, ferrite-core transformer which can be used in a variety of applications, the most relevant of which is photovoltaic (PV) converter systems, which often require bulky transformers to function properly. The current research involved several processes: (1) Understanding and designing a tutorial for the use of Ansys software to aid in the efficient development and modeling of transformers, (2) designing and simulating a planar transformer in Ansys to be used in a solar converter, specifically the Smart Green Power Node (SGPN), and (3) testing the planar transformer …

Investigation And Characterization Of Silicon Carbide Power Mosfets, Vincent Hassman

Electrical Engineering and Computer Science Undergraduate Honors Theses

As engineers constantly seek to make solar power systems smaller, cheaper, and more efficient, technological enhancements in the electronics that run them are required. One of the most fundamental electronic components of any solar system is the inverter, which takes DC current from the solar cell and turns it into AC current that is supported by the grid. This is done with metal oxide semiconductor field effect transistors (MOSFETs). Through more advanced MOSFET technology, inverters can switch at a higher frequency, increasing efficiency and reducing size and cost.

MOSFET performance can be enhanced by swapping the traditional silicon substrate with …

Emerging Applications On Reconfigurable Computing Platforms, Zhenyu Xu

All Dissertations

Security and high-performance computing have become two of the most critical demands in modern technology. The increasing complexity of digital systems, the need for real-time processing, and the emergence of sophisticated cyber threats require computing solutions that balance computational power with adaptability and security. Reconfigurable computing platforms, particularly Field-Programmable Gate Arrays (FPGAs), offer a promising solution to these challenges by combining flexibility with hardware acceleration. Many new applications have emerged with the developing of reconfigurable platforms.

FPGAs can be utilized in two primary directions: as control and high-precision measurement units for security-sensitive applications, and as accelerators capable of outperforming GPUs …

A Study Of The Impact Of Balancing, Geometric Transformation, Generative Networks, And Roi Techniques In Eye Diseases Classification, Sghaira Hareb Alnuaimi

Theses

Automatic detection of ocular diseases helps medical professionals efficiently identify eye disorders, reduce diagnostic errors, and accelerate diagnoses to prevent blindness. Deep learning has been successfully utilized in various fields, including medical image classification. However, in spite of these advancements, challenges remain in ocular disease classification.

The objective of this work is to address these challenges using data processing, data augmentation in combination with Region of Interest (ROI) techniques. Medical datasets often suffer from scarcity, imbalance, and low-quality images, leading to inaccurate classification. To mitigate these issues, we utilize the ODIR dataset, which contains 7,000 labelled training images for both …

Design Of A Novel Low-Cost Hybrid V-Shape Spoke-Type Ferrite Ipm-Synrm For Ev Traction Using Fem Software, Kenghao Cai

Master's Theses

This paper presents a hybrid V-shape spoke type ferrite Interior Permanent Magnet Synchronous Reluctance Machine (PMA-SynRM) for electric vehicle traction application. Ferrite or ceramic IPM-SynRMs compared to Neodymium (NdFeB) based IPM-SynRMs typically have lower torque, power density, and efficiency overall. Motivated by rising costs and international policies making it increasingly more challenging to obtain rare-earth metals, alternatives should be explored. With the help of finite element method (FEM) software, Ansys Maxwell, this study probes into a novel three-phase ferrite-only hybrid Spoke-type V-shaped IPM-SynRM using Tesla Model 3's neodymium powered V-shape interior permanent magnet machine as a benchmark. The proposed motor …

A Heuristic Approach To Portrait Segmentation And Its Application To Synthetic Bokeh Generation, Charles J. Snead

Master's Theses

Segmentation of portrait images is an important technique used to separate the foreground and background of an image. This separation of layers is useful for selectively applying post-processing techniques to enhance the quality of the image, such as blurring the background. Automatic portrait segmentation is a complex process that can be completed with a high degree of accuracy using deep learning with neural networks, but training and inference are often very computationally expensive. This thesis aims to take a heuristic approach to portrait segmentation by combining classical image processing and computer vision techniques into a solution that can be run …

Optimizing And Training An Svm-Based Breast Cancer Tumor Classifier, Kevin Lopatka

Master's Theses

With advancements in technology, turning to machine learning has become a popular choice for aiding clinicians in the diagnoses of breast cancer malignancies. While the neural networking approach has been vetted thoroughly, this work aims to take advantage of traditional machine learning techniques; mainly support vector machine learning and the optimizing of feature extraction. The discrete-wavelet transform is used in the feature extraction stage of machine learning. Previous works that use this feature extraction technique are analyzed and expanded upon by utilizing a variety of different wavelets as well as other color-spaces with the goal of achieving higher result metrics …

Enhanced Post-Capture Automatic White Balance For Srgb Images, Eric Huang

Master's Theses

Automatic white balancing (AWB) aims to correct color casts caused by varying illumination conditions, typically assuming access to RAW sensor data. However, many real-world applications involve only sRGB images that have already been processed by in-camera pipelines. In these cases, traditional AWB algorithms often underperform due to the nonlinear transformations done by these pipelines.

This thesis builds upon a data-driven color correction framework introduced by Afifi et al. that relies on RGB-UV histograms and learned color transforms. A revised automatic white balancing (AWB) framework that improves both color accuracy and runtime efficiency is proposed. A fallback routine is implemented to …

Modeling And Analysis Of A Hybrid Ac/Dc Green Seaport Power System With Photovoltaic Generation And Battery Energy Storage Systems, Corey Zaas

Master's Theses

This thesis investigates the modeling, simulation, and analysis of a Green Seaport power system integrating photovoltaic (PV) generation, battery energy storage systems (BESS), and coordinated protection within a hybrid AC/DC framework. The work improves a previously established model, enhancing it with detailed protection studies and simultaneous AC/DC power flow analysis using EasyPower software. The system was evaluated under a wide range of operating conditions, including varying solar irradiance, battery charge and discharge states, and both full and zero load conditions. Key performance indicators included voltage regulation, power factor behavior, equipment loading, protection device coordination, and total system power losses. Simulation …

Modality Distillation Using A Sam-Guided Multimodal Teacher For Unimodal Wildfire Segmentation And Temperature Prediction, Michael N. Marinaccio

All Theses

Wildfires are one of the world’s most devastating natural disasters that affect the environment, communities, and more critically, humans that live in and around those communities. Due to the threat of large-scale destruction in landscapes and human inhabited areas, it has become increasingly more important to develop wildfire detection, management, and suppression strategies to mitigate and prevent these negative outcomes. Wildfire research encompasses many different areas. Most notably, the development of communication, navigation, remote sensing, and monitoring systems. In wildfire monitoring, limitations discovered in-ground and satellite observation have shifted the focus toward Unmanned Aerial Vehicle (UAV) based wildfire research, which …

On The Optimal Design Of Coreless Afpm Machines With Halbach Array Rotors For Electric Aircraft Propulsion, Matin Vatani, John F. Eastham, Xiaoze Pei, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

This paper provides a comprehensive analysis of the winding factor and winding harmonic distribution in coreless stator axial flux permanent magnet (AFPM) machines. The topology of this type of machine and its similarities to conventional cored AFPM machines are discussed. Popular pole/coil number combinations in coreless stator AFPM machines are identified and analyzed in detail. It is demonstrated that the winding factor in these machines varies with radius and can be expressed as the product of the conductor distribution factor, pitch factor, and coil group factor. The formulas for each factor are derived and presented in multiple forms based on …

Hybrid Fea And Meta-Modeling For De Optimization Of A Highly Saturated Spoke Ipm, Oluwaseun A. Badewa, Marcelo Silva, Rosemary E. Alden, Pedram Asef, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

This paper introduces a novel approach for high performance electric motor design that combines machine learning (ML)-based meta-modeling with a differential evolution (DE) optimization algorithm. The method leverages finite element analysis (FEA) results to train the ML meta-model, enabling efficient design optimization for high-power density cored machines, such as spoke interior permanent magnet motors (IPM), which exhibit complex nonlinearities and saturation effects. This hybrid ML-DE framework seeks to provide an alternative for physics-based electric motor design and optimization, offering significant reductions in computational effort while maintaining accuracy. The meta-model’s accuracy in capturing the nonlinear relationships between design parameters, core losses, …

Optimal Design Of Coreless Axial Flux Pm Machines Using A Hybrid Machine Learning And Differential Evolution Method, Matin Vatani, David R. Stewart, Pedram Asef, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

Coreless stator axial flux permanent magnet (AFPM) machines require computationally intensive three dimensional finite element analysis (FEA) for accurate performance evaluation, making optimization time-consuming and impractical for large-scale design studies. This paper presents a hybrid optimization approach that integrates differential evolution (DE) with artificial neural networks (ANNs) to accelerate the optimization of coreless AFPM machines. In this method, DE driven FEA simulations generate a dataset used to train an ANN surrogate model, significantly reducing reliance on direct FEA computations. The effectiveness of this approach is demonstrated through a multi-objective DE optimization, where the ANN’s predictions are validated against FEA results. …

Winding Factors And Harmonics Of Coreless Axial Flux Pm Machines, Matin Vatani, John F. Eastham, Xiaoze Pei, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

This paper provides a comprehensive analysis of the winding factor and winding harmonic distribution in coreless stator axial flux permanent magnet (AFPM) machines. The topology of this type of machine and its similarities to conventional cored AFPM machines are discussed. Popular pole/coil number combinations in coreless stator AFPM machines are identified and analyzed in detail. It is demonstrated that the winding factor in these machines varies with radius and can be expressed as the product of the conductor distribution factor, pitch factor, and coil group factor. The formulas for each factor are derived and presented in multiple forms based on …

Analog Low Dropout Regulator Design Within A 12nm Finfet Node, Harshdeep Singh

Graduate Theses and Dissertations

Modern ICs require the use of multiple voltage regulators to regulate power, this creates the need for analog low dropout regulator (LDO) designs in more advanced nodes such as for the 12nm FinFET process. Analog design is particularly challenging in FinFET processes due to a variety of factors, such as quantized parameters, large parasitic values and length of diffusion effects. An analog LDO was chosen for its improved power supply rejection ratio (PSRR) over digital and hybrid approach which is a key metric for voltage sensitive applications. The LDO was designed through an iterative approach to address the difficulty of …

Intelligent Crowdsourcing Based On Online Social Networks, Adedamola Adesokan

Electrical and Computer Engineering ETDs

The prevalence of Online Social Networks has completely changed how individuals communicate and cooperate. This dissertation explores the integration of intelligent crowdsourcing mechanisms into OSNs, focusing on game theory, reinforcement learn- ing, and social network dynamics to enhance the allocation of tasks, participation by users, and distribution of rewards. It proposes several models that utilize trust- based models, hedonic coalition games, and influencer dynamics for optimization of crowdsourcing. The major challenges to be addressed include task selection, reward distribution, and incentivizing participation, taking into consideration aspects re- lated to social influence, trust, and user engagement. The models so proposed have …

Robust Distributed Learning Against Both Distributional Shifts And Byzantine Attacks, Guanqiang Zhou, Ping Xu, Yue Wang, Zhi Tian

Electrical and Computer Engineering Faculty Publications

In distributed learning systems, robustness threat may arise from two major sources. On the one hand, due to distributional shifts between training data and test data, the trained model could exhibit poor out-of-sample performance. On the other hand, a portion of working nodes might be subject to Byzantine attacks, which could invalidate the learning result. In this article, we propose a new research direction that jointly considers distributional shifts and Byzantine attacks. We illuminate the major challenges in addressing these two issues simultaneously. Accordingly, we design a new algorithm that equips distributed learning with both distributional robustness and Byzantine robustness. …

Implementation Of Residual Tandem Neural Networks For Photonic Inverse Design, Ponthea A. Zahraii

Electrical Engineering and Computer Science (MS) Theses

Deep-learning approaches can greatly benefit the modeling and design of nanophotonic and optical structures. Traditional full-wave simulations are time and resource-intensive, which can act as a bottleneck in photonic design. On the other hand, deep-learning approaches for designing the response of nanophotonic geometries can be computationally inexpensive and produce accurate and efficient results. In this project, we specifically investigate the case of optical forces near meta-structures. We propose using an inverse design approach with residual blocks to account for the deep nature of this architecture and inherently address the non-uniqueness problem. A tandem approach, which consists of two interconnected models, …

Sonochemically Synthesized Zno Nanowires (Nws)-Based Sensor For Non-Invasive Glucose Detection In Sweat, G. M. Mehedi Hossain, Ahmed Hasnain Jalal, Hasina Huq, Nazmul Islam, Karen Lozano, Nezih Pala, Fahmida Alam

Electrical and Computer Engineering Faculty Publications

Glucose is a crucial metabolic marker, providing critical insights into energy regulation and insulin sensitivity, making its monitoring essential for managing diabetes and overall metabolic health. In this context, flexible biosensors have gained considerable attention for their potential to enable real-time and non-invasive glucose monitoring. One promising advancement in this domain is using Zinc-Oxide (ZnO) nanostructures through sonochemical synthesis. ZnO has a wide bandgap of ∼3.37 eV and a large binding energy of 60 meV. This research focuses on ZnO-Nanowires' growth for the first time on a flexible polymer substrate. The average length and diameter of the nanowires are 2.5µm …

Towards Mitigation Of The Light Network Load Performance Penalty Of The Network Link Outlier Factor (Nlof), Jaime Merin Guzman

Open Access Theses & Dissertations

Detecting and localizing faults in communication networks is critical to maintaining reliable and efficient network operations. The Network Link Outlier Factor with Most Likely Link (NLOF: MLL) algorithm has demonstrated its potential to automate this task but suffers from significant performance degradation under low network load conditions, where limited network flow data reduces its ability to localize faults. This thesis proposes and evaluates the performance of a synthetic traffic generation algorithm to be used with NLOF:MLL. This algorithm strategically injects synthetic flows that supplement the insufficient real network flows, thereby improving NLOF:MLL's performance under low-load conditions. Specifically, we select network …

Construction And Characterization Of An Rf Anechoic Range, Logan Gentry

Electrical Engineering and Computer Science Undergraduate Honors Theses

Anechoic RF ranges are electromagnetically quiet spaces intended to provide conditions suitable for testing and classifying electronic equipment. Typically, ranges are constructed indoors, which presents a number of design challenges related to room geometry, cost, and material selection. This report describes the creation of an indoor anechoic range intended for characterization of antennas. Furthermore, the range is characterized for performance across a wide range of discrete frequencies in the UHF band according to CISPR standards, resulting in the determination of a lower frequency limit at which the room performance begins to degrade. The characterization of this range agrees with far-field …

Hybrid Dc-Dc Converters For Soft Charging Capacitive Actuators: Modeling, Analysis And Design, Bahlakoana Mabetha

Dartmouth College Ph.D Dissertations

Recent trends in haptics, microrobotics and ultrasound technology have shown an increasing use of piezoelectric and other electrostatic actuators. These actuators are suited for miniaturized applications due to their high power density and favorable scalability at a small size. Their electrical impedance at lower frequency (their typical operating range) is capacitive, therefore, they can be modeled as capacitive loads.

The driving circuits for capacitive actuators need to deliver and recover (bidirectional) dominantly reactive power, unlike typical power electronics converters for resistive loads which deliver (unidirectional) real power to the load. Therefore, the circuits, operation, and optimization required to drive these …

Design Considerations Of A Gpu, Nicholas M. Devilliers

Electrical Engineering and Computer Science Undergraduate Honors Theses

With the current era of AI technology, the era of single instruction multiple data has become an increasingly viable solution to accelerate training. The problem is that while software to use GPUs and other hardware accelerators, designing GPUs and ASIC devices has become increasingly more expensive and there aren’t great examples of generic GPUs that anyone can use and modify. In this thesis, there are four design considerations that will be discussed and how they affect the result of a generic GPU. The four considerations that were talked about in the thesis are, word width, arithmetic type, number of stages, …

C-Band Air To Ground Communication System For Uav, Mubark Alghamdi

Theses and Dissertations

C band spectrum 5030-5091 MHz is allocated for command-and-control communication services with unmanned aircraft systems. This document evaluates the possibility of using 3GPP 5G standards for provisioning of such services. Channelization of the spectrum and major system parameters are proposed. The performance of the proposed system in channel fading environment is evaluated using MATLAB based simulations. The evaluations examine SINR, and average throughput of the proposed system at different altitudes of the unmanned aircraft system. MATLAB simulations are used to evaluate system performance in free-space environments. Signal-to-Interference-plus-Noise Ratio (SINR) and Reference Signal Received Power (RSRP) are predicted at different UAS …

Characterizing Human Mobility Patterns In Saudi Arabia Using Cellular Data, Meshal Alnefaie

Theses and Dissertations

The study analyzes human mobility in Saudi Arabia. Using crowd-source data, Riyadh mobility is analyzed to find trends and highlight mobility patterns of individuals in Riyadh. Then, the mobility of Riyadh is compared with that of Jeddah and Dammam in a similar data collection and analysis. Four mobility metrics are utilized: Number of Visited Locations (NLOC), Number of Unique Locations (NULOC), Radius of Gyration (RGYR), and Distance Traveled (DTRV). The results show interesting outcomes about individuals in the three cities. Although these cities are far from each other, they observe the same mobility patterns. These findings have the potential to …