Engineering Commons^™

Feed Network Design For Passive Beamforming In Hemispherical Phased Arrays, Daniel Flores

Theses and Dissertations

This thesis presents the design, fabrication, and evaluation of a four-element microstrip patch antenna array with a passive 1 to 4 corporate feed network operating at 5 GHz. A single inset-fed patch was developed on Rogers DiClad 880 to ensure accurate tuning and mechanical flexibility, achieving a measured resonance of 5.009 GHz with excellent return loss. The corporate feed network, synthesized using T-junction dividers and quarter-wave transformers, demonstrated strong impedance matching, balanced amplitude distribution, and broadside realized gain near 10 dBi when integrated with the array.

Beam steering was examined through simulation-based phase control, revealing effective scanning up to approximately …

Optimal & Robust Control Of A Bidirectional Dc-Dc Converter In Ev Systems, Yasser Ayeva

Electrical Engineering and Computer Science Faculty Publications and Presentations

This paper analyzes the performance of PI, LQR, and H∞ controllers for the regulation of a bidirectional buck boost converter in electric vehicle systems. To get the system state space equations, a continuous conduction average model is linearized. For analysis a PI controller will be used as baseline, the LQR controller will be used to improve transient response, and the H∞ controller will be used for the system robustness and disturbance rejection. The simulation results show that the advanced controllers surpass the PI controller in terms of overshoot, settling time, and voltage ripple, with the H∞ controller offering the best …

Reinforcement Learning Based Security Schemes For Distributed Ai Systems, Ashan Chamath Gunawardena

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Distributed machine learning (DML) is a component of modern intelligent systems, enabling collaborative training across devices such as mobile clients, vehicles, and edge networks. However, the decentralized nature of these systems introduces vulnerabilities, particularly data poisoning attacks that compromise model integrity and degrade performance. Traditional defenses, such as statistical filtering, robust aggregation, and privacy-preserving techniques, often struggle to adapt to overwhelming adversaries or operate under strict privacy and real-time constraints. This dissertation proposes the use of reinforcement learning (RL) and deep reinforcement learning (DRL) based misbehavior detection schemes that dynamically identify poisoning attempts in distributed AI systems, including federated learning, …

Rapid State-Of-Health Estimation Of Batteries Using Machine Learning With Limited Eearly-Discharge Voltage Data, Mohammad Bakhtiari

Durham School of Architectural Engineering and Construction: Dissertations, Theses, and Student Research

The utilization of lithium-ion batteries has been rapidly expanding across diverse sectors, including electric transportation, stationary energy storage systems, and the built environment. Ensuring a high level of reliability in these applications is essential, as the performance and safety of such systems depend strongly on the accurate assessment of the battery’s State of Health (SOH). Conventional SOH estimation techniques—often based on complex electrochemical models or extensive laboratory testing—tend to require a large number of measurements, advanced instrumentation, and high computational cost. These factors make them impractical for large-scale deployment or real-time monitoring. This study introduces a simplified machine-learning-based approach for …

Series Resonant Converters With Medium Voltage Sic Mosfets For Electric Aircraft Applications, Xinyuan Du

Graduate Theses and Dissertations

To develop high-performance high- power-density MV power converters, the emerging silicon carbide (SiC) devices are more attractive than their silicon (Si) counterparts, since the fast switch frequency brought by the SiC can effectively reduce the volume and weight of the filter components and thus increase the converter power density. From the converter topology perspective, with the MV dc distribution, the single stage isolated dc/dc converter are suitable for next-generation electric aircraft system due to soft switching and high power density. In this work, comprehensive static and dynamic characterizations were conducted for the latest 6.5 kV silicon carbide (SiC) MOSFETs from …

Design Of Phase Shifter And True Time Delay Gan Mmics For High-Temperature Ku-Band Applications, Michael Lee Thompson

Graduate Theses and Dissertations

This thesis presents the design, implementation, and high-temperature characterization of Gallium Nitride (GaN) monolithic microwave integrated circuits (MMICs) developed for beamforming and phased-array systems operating in the Ku-band (12-14 GHz). Two integrated circuits were designed: a 3-bit digital phase shifter and a 3-bit true time delay (TTD), both optimized for high linearity, low insertion loss, low phase error, and stable operation at elevated temperatures up to 300°C. Developing both a phase shifter and a TTD enabled a direct comparison of their beamforming performance and the evaluation of beam squint effects over frequency, a critical factor in wideband array design. The …

Flood-Level Estimation Using Aerial Imagery, Yisen Zhang

Electrical & Computer Engineering Projects for D. Eng. Degree

Reliable flood-level estimation using aerial UAV (Unmanned aerial vehicle) imagery is essential for effective post-disaster assessment and rapid emergency response. This study utilizes a UAV-based dataset, referred to as the UVA dataset, which integrates multiple public datasets and manually labeled UAV images, together with a multi-stage vehicle-centric framework for flood-depth estimation. The UVA dataset integrates images from multiple public sources, including Unmanned Drone Water Assessment (UDWA), Unmanned Aerial Vehicle Detection and Tracking (UAVDT), Car Parking Lot (CARPK), and additional UAV-view images collected from the internet, followed by manual annotation for water depth, viewing angle, and altitude labels. In the proposed …

Solar Powered Conservation: The Effects Of Solar Photovoltaic Facilities On Avian Community Composition, Michael Christopher Ferrara

Graduate Theses and Dissertations

The expansion of solar photovoltaic energy infrastructure is transforming landscapes worldwide. Increasingly, facilities are planted with native vegetation, yet how vegetation characteristics and landscape variables shape wildlife communities in solar facilities remains poorly understood. Because avian populations have been in decline and are sensitive to habitat changes, understanding how solar facilities influence avian communities is important. In Chapter 1, we used autonomous recording units, local vegetation measurements, and land use and land cover data to quantify how avian community occupancy is influenced by solar cover in solar facilities and comparable reference sites. We used a Bayesian multi-species occupancy model to …

A Study On Utilizing Coherently Coupled Orbital Angular Momentum Beams For Maritime Sensing And Communication, Evan Robertson

All Dissertations

A large portion of the world is covered in water which introduces a couple of key challenges in communication and sensing systems. The impact of particulates in the water will limit the ability to successfully transmit information through the water. The study of how the channel impacts specific frequencies and the ability to transmit more information at a single time can limit the impact of this environment in how it degrades an optical communication system. In sensing applications, it is important to detect information related to an object’s motion which will either be towards or away from a system, or …

Computational Methods For Complex Electromagnetic Geometries And Media, Edgar Bustamante

Open Access Theses & Dissertations

Additive manufacturing has enabled electromagnetic devices with increasingly complex geometries, but existing numerical tools remain limited in their ability to model and design such structures. This dissertation presents two major advancements that address these restrictions in the finite-difference frequency-domain method (FDFD) and the spatially-variant lattice algorithm (SVLA). These two numerical methods provide a foundation for future exploration in the simulation, optimization, and realization of next-generation electromagnetic devices. First, a general bianisotropic FDFD formulation based on the vector wave equation is presented that enables practical modeling of metamaterials using effective medium homogenized parameters rather than explicitly resolving subwavelength metamaterial features. The …

Further Insights Into The Network Link Outlier Factor's (Nlof) Light-Load Penalty, Sunday Oluwaleke Ogundele

Open Access Theses & Dissertations

This research investigates the performance of the Network Link Outlier Factor with Most Likely Links (NLOF:MLL), under varying network load conditions. Earlier studies reported that the NLOF:MLL algorithm experienced a noticeable drop in fault-localization accuracy when operating in lightly loaded networks. To further examine this limitation, 240 experiments were carried out to observe how the algorithm responds as overall network load increases. The evaluation focused on the classification performance metrics: precision, recall, and F1-score. The results show that NLOF:MLL’s effectiveness improves as network load increases but that the rate of improvement slows progressively, eventually stabilizing in a pattern consistent with …

Development And Optimization Of A Deep Level Transient Spectroscopy System, Samuel Ruiz

Open Access Theses & Dissertations

Deep-level transient spectroscopy (DLTS) remains one of the most widely used techniques for identifying electrically active defects that affect leakage current, carrier lifetime, and overall reliability in semiconductor devices. Legacy boxcar or capacitance meter implementations, however, often struggle with limited signal-to-noise ratio, labor-intensive data collection, and poor adaptability across diverse material systems. This thesis presents the design and optimization of a semi-automated, lock-in-amplifier-based DLTS platform. By pairing a Zurich HF2LI with PID-controlled cryogenic sweeps, precision signal generation, and MATLAB driven acquisition and processing scripts, the system will (i) enhance SNR through phase-sensitive detection, programmable low pass filtering, and parasitics calibration; …

Image And Signal Processing Methods For Clinical Decision Support: Reference-Based Lung Segmentation On Chest X-Rays And Ecg-Based Study Of Acute Hyperkalemia Using Machine Learning, Basavarajaiah Shanmukhayya Totada

Open Access Theses & Dissertations

ABSTRACT

Study-I: An Image Processing Pipeline for Reference Guided Lung Region Detection in Chest Radiographs with Shape Similarity Matching Accurate and reliable segmentation of the lung region in chest X-ray (CXR) images is essential for computer-aided diagnosis (CAD) systems, particularly in the early detection and monitoring of lung disorders. Traditional segmentation techniques often rely on manual annotations, limiting scalability and adaptability. The proposed reference-guided approach selects the most similar healthy CXRs dynamically, ensuring flexibility while benefiting from dataset-specific reference images. Building upon prior approaches that utilize shape similarity-based selection and SIFT-flow, this study introduces a fully automated segmentation pipeline that …

Application Of Natural Language Processing And Machine Learning For Analyzing Mining Accident Reports And Automating The Process Of Root Cause Analysis, Siddhartha Agarwal, Y. P. Chugh, Atul Singh, Vikram Sakinala, Ayan Mukherjee, Balbir Prasad, Cihan Dagli, Yuhao Zou

Engineering Management and Systems Engineering Faculty Research & Creative Works

Coal mining accidents are a major concern worldwide, necessitating effective safety measures and comprehensive analysis to prevent future accidents. Our proposed solution is the first attempt for Indian mines, inspired by the potential of Natural Language Processing (NLP) that can read and analyze vast repositories of accident records in seconds. In combination with machine learning (ML), NLP algorithms can extract unstructured text by eliminating manual data entry errors, reading poorly scanned reports, and understanding multiple versions of the event and cluster documents based on types that would otherwise take months to collate. In the case of accident records, it can …

Data Driven Design Of Ultra High Performance Concrete Prospects And Application, Bryan K. Aylas-Paredes, Taihao Han, Advaith Neithalath, Jie Huang, Ashutosh Goel, Aditya Kumar, Narayanan Neithalath

Electrical and Computer Engineering Faculty Research & Creative Works

Ultra-high-performance concrete (UHPC) is a specialized class of cementitious composites that is increasingly used in various applications, including bridge decks, connections between precast components, piers, columns, overlays, and the repair and strengthening of bridge elements. The mechanical and durability properties of UHPC are significantly influenced by factors such as low water-to-binder ratios, the inclusion of supplementary cementitious materials (SCMs), and fiber reinforcement. Machine learning (ML) has been employed to predict the performance of UHPC and optimize its mixture designs by using various raw materials. This study first provides a comprehensive review of ML applications in UHPC, focusing on predicting workability, …

Ai-Driven Electromagnetic Design And Performance Prediction Of Microstrip Antennas, Eduardo Javier Vazquez

Theses and Dissertations

This thesis investigates the application of Deep Learning to automate and accelerate microstrip antenna inverse design. The initial investigation was to predict microstrip antenna performance from its geometry parametric input, and found out that forward prediction with adopted geometric representation results in ill-posed scenario, high ambiguity and unstable mapping. The study later mostly focuses on the inverse prediction by machine learning from S11 parameter input to predict antenna patch geometry parameters instead.

A dataset of 5,000 ANSYS HFSS simulated antennas (later filtered to 4,136 valid samples) was generated using cubic spine -described geometry profiles. Multiple neural architectures were adopted for …

Volume Status Detection With Integral Pulse Frequency Modulation Model Of Peripheral Venous Pressure, Jeremiah Rhys Wimer

Graduate Theses and Dissertations

This thesis studies the effectiveness of utilizing a modified integral pulse frequency modulation (IPFM) algorithm to synthesize peripheral venous pressure (PVP) waveforms for the detection of several physiological conditions using logistic regression. PVP waveforms are collected from 18 human patients and 4 porcine subjects. Human data are used to train models for determining the hypovolemic status of the patient, while the porcine data are used to train models for determining level of anesthesia and detecting internal hemorrhaging. In the human dataset, the waveforms collected from the 18 patients are classified into two groups according to serum chloride levels: resuscitated (≥100 …

Extreme Bandgap Recessed-Gate Metal Oxide Semiconductor Heterostructure Field Effect Transistors With Drain Current 0.28 A Mm−1 And Threshold Voltage −1.5 V, Abdullah Al Mamun Mazumder, Abdullah Mamun, Kenneth Stephenson, Kamal Hussain, Tariq Jamil, Grigory Simin, Asif Khan

Faculty Publications

Herein, the first demonstration of hybrid high-k oxide (ZrO2-Al2O3) incorporation into extreme bandgap (EBG) Al_0.87Ga_0.13N/Al_0.64Ga_0.36N metal-oxide-semiconductor heterostructure field-effect transistors (MOSHFETs) is presented, with both planar and recessed-gate designs on the same AlN/sapphire template with a state-of-the-art low contact resistance of 1.4 Ω mm (contact resistivity, ρc ≈ 5.7 × 10−6 Ω cm2). The recessed-gate MOSHFETs achieve a threshold voltage shift of ΔVTH = 5.8 V, highlighting improved channel control. Static output measurements reveal a peak drain current (IDS) of 340 mA mm⁻¹ for the planar …

An Audio Data-Driven Roadway Digital Twin And Its Underlying Framework For A Digitized Transportation Construction Environment, Anisha Deria, Pedro J. Chacon Dominguez, Yong-Cheol Lee, Jin W. Choi

Michigan Tech Publications

The increasing need to build and maintain transportation systems has led project managers to manage multiple projects simultaneously. Roadway projects often entail several miles of job site, making it difficult to keep track of progress and maintenance activities. To improve the situation, this study proposes an audio data-driven roadway digital twin framework for real-time and remote monitoring of construction projects. The latent characteristics of a digital twin required for establishing a digitized work environment were investigated. As a primary method of seamlessly linking virtual and physical environments, audio data classified and analyzed by deep neural network (DNN) has been employed …

Complementary Color Laser Illumination For Perceptual Contrast Enhancement In Structurally Colored Samples, Tomoshree Dash

All Theses

Structural color, a phenomenon arising from nanoscale interaction between light and materials, has the potential to unveil biological, chemical, physical, and mechanical characteristics of the sample. It enables direct visualization of the sample by human users with high spatiotemporal resolution. However, its impact is often constrained by challenges in the perceptual differentiation of subtle color variations. This thesis introduces complementary color laser illumination (C²LI) as an imaging technique that enhances color perception of the Human Visual System (HVS) by accessing the psychophysical non-linearities in chromatic color perception. C²LI offers a platform optimized for the HVS by …

Editable 4d Gaussian Splatting: Scalable And Consistent Video Editing Via Uv-Texture Decomposition, Shuai Lyu

All Theses

Dynamic 3D videos are now widely used in VR, AR, and telepresence, where users often want to change the style or appearance of objects such as clothing over a whole sequence. However, editing such dynamic 3D content is still hard, because appearance, geometry, and motion are tightly coupled, so even a simple color change must stay consistent in all views and at all time steps. Existing editing methods based on 4D Gaussian Splatting often work in a frame-by-frame way, which is slow and makes it difficult to keep temporal and multi-view consistency.

This thesis proposes Editable-4DGS, a representation-centric framework that …

Isolated Dc-Dc Converter For An Ev Microgrid, Oscar Yu, William Leiker

Electrical Engineering

This product is a redesign of a DC-DC buck-boost converter which utilizes a new topology, the flyback converter, for use in an electric vehicle (EV) as a microgrid. The main driver behind the redesign is to provide electrical isolation between elements in the microgrid. The EV microgrid consists of the battery, motor, external DC and AC ports, and the power electronics (DC-DC converter and AC-DC inverter) which were designed and built in previous senior projects. Using EV’s as microgrids can help relieve stress from the main power grid caused by charging electric vehicles. Implementing EV’s as a microgrid enables the …

Data-Driven Evaluation Of Sustainable Waste-To-Energy Pathways For Intelligent Urban Systems, Izech Brian O. Edwin, King Harold A. Recto

Electronics, Computer, and Communications Engineering Faculty Publications

The handling of municipal solid waste (MSW) in swiftly urbanizing Philippine cities poses intricate energy and governance challenges. In Baguio City, reliance on landfills has reached critical levels due to diminishing capacity, rising transport costs, and opposition to trash transfers by nearby LGUs. Although shaped by unique topographical and governance constraints, Baguio’s situation reflects issues faced by other rapidly growing Philippine cities; therefore, analyzing it offers insights for national MSW decision-making. This study applies a triple bottom line (TBL) framework to assess three management scenarios: (1) Status Quo, where all MSW is landfilled with no energy recovery; (2) Landfill with …

Investigating The Efficiency Of Ingan P-N-P-N Homojunction Solar Cells, Moath Alhejji, Mohammad Alavijeh, Jacob Kupernik, Mirsaeid Sarollahi, Abbas Jammali, Seyed Taghavi, Reem Alhelais, Md Hel Uddin Maruf, Morgan Ware

Electrical Engineering and Computer Science Faculty Publications and Presentations

This research investigates the development of a novel p-n-p-n homostructure solar cell, through semiconductor simulations using the Nextnano software. InGaN was used as a model system in order to achieve a bandgap with optimized efficiency for a p-n homojunction solar cell. By increasing the uniform doping concentration from 1.5*10(16) cm(-3) to 1.5*10(17) cm(-3), the open circuit voltage (V-oc) increased while the short-circuit current density (J(sc)) decreased, as expected in simple p-n junctions. The p-n-p-n structure achieved a peak efficiency of 32.91% at a doping level of 6.5*10(16) cm(-3), a similar to 7% improvement over a conventional p-n junction's 25.31% efficiency …

Bridging Cybersecurity Practice And Law: A Hands-On, Scenario-Based Curriculum Using The Nice Framework To Foster Skill Development, Colman Mcguan, Aadithyan Vijaya Raghavan, Komala M. Mandapati, Chansu Yu, Brian Ray, Debbie Jackson, Sathish Kumar

Electrical and Computer Engineering Faculty Publications

In an increasingly interconnected world, cybersecurity professionals play a pivotal role in safeguarding organizations from cyber threats. To secure their cyberspace, organizations are forced to adopt a cybersecurity framework such as the NIST National Initiative for Cybersecurity Education Workforce Framework for Cybersecurity (NICE Framework). Although these frameworks are a good starting point for businesses and offer critical information to identify, prevent, and respond to cyber incidents, they can be difficult to navigate and implement, particularly for small-medium businesses (SMBs). To help overcome this issue, this paper identifies the most frequent attack vectors to SMBs (Objective 1) and proposes a practical …

End-To-End Direct Current For Standalone Power Network, Eyad Ahmad Aldarsi

All Dissertations

The primary issue that faces the humanity is climate change and because of that greenhouse gases (GHGs) emissions are rising. The consequences of this issue have emphasized the necessity for replacing the dominant method of electricity generation, which mostly utilizes fossil fuels, to be centered on access to all, green, low-cost, and renewable sources of energy. Currently, photovoltaics (PV) and wind turbines are the two technologies so far that can convert the source of renewable energy, which is produced by sun irradiance and wind respectively, into large-scale electric power that can be distributed into the electricity grid. The work in …

Robust Data-Driven Predictive Control Of Nonlinear Systems Under Modeling Uncertainty, Pegah Ghafghanbari

All Dissertations

Data-driven predictive control enables designing controllers directly from data, making it attractive for complex systems with hard-to-model dynamics. However, practical deployment is challenged by modeling inaccuracies and changing operating conditions. This dissertation develops predictive control frameworks that incorporate robustness and adaptability to address these issues in uncertain nonlinear systems.

The first part employs the Linear Parameter-Varying (LPV) framework, which represents nonlinear dynamics through simple linear form representation. To characterize the plant-model-mismatch often caused by limited data and numerical calculations, Bayesian Neural Networks (BNNs) are used, and their uncertainty estimates are integrated into two robust control approaches. The first is a …

Design And Testing Of A Gallium Nitride Power Amplifier For High-Temperature Radar Applications, Walker Landry Harbison

Graduate Theses and Dissertations

This thesis offers the design, fabrication, and evaluation of a gallium nitride (GaN) power amplifier integrated circuit (IC) intended for high-temperature radar applications. Radar systems are used in many different applications, such as defense, aerospace, and weather. For their function, these systems require high power, efficiency, and reliability under a wide range of operating conditions. Taking advantage of the material properties of GaN, including its high breakdown voltage, wide bandgap, and thermal conductivity bolstered by the use of silicon carbide in the substrate, this work focuses on examining amplifier performance in both ambient and elevated temperature conditions. The PA was …

Towards Trustworthy Federated Learning, Alina Basharat

Theses and Dissertations

Federated learning is a collaborative training model in which multiple clients optimize aglobal model by transmitting updates to a coordinating server while keeping raw data on-device, thereby reducing direct data exposure and enabling iterative global improvement. However, the iterative communication process is vulnerable to malicious attackers that either deliberately destroy the model or curious to infer raw data. Moreover, learning from multiple agents may result in unfair results. To enhance trustworthiness within this setting, we employ two-sided norm-based screening (TNBS) that removes both abnormally large and abnormally small updates, pair it with a q-fair objective to emphasize high-loss (disadvantaged) clients, …

Favorability Mapping For Hydrothermal Power Resource Assessments Of The Great Basin, Usa, Stanley P. Mordensky, Erick R. Burns, John Lipor, Jacob Deangelo

Electrical and Computer Engineering Faculty Publications and Presentations

Highlights

• • The new approach to predict hydrothermal resource favorability for the U.S. Great Basin is a synthesis of modern data-driven machine learning improvements from the last several years and predicts 85 % of power-producing systems with operating power plants in the most favorable 10 % of the total area with over half of the power-producing systems (10 of the 19 exposed power-producing systems and 5 of the 9 hidden power-producing systems) in the 99th percentile.
• • The new hydrothermal favorability map predicts both hidden and exposed power-producing hydrothermal systems equally well.
• • The new hydrothermal favorability map preferentially predicts …