Engineering Commons^™

Lidar Scene Reconstruction Using Imagery And Frame Overlap From A Texel Camera, Blake Chamberlain

All Graduate Theses and Dissertations, Fall 2023 to Present

A small unmanned aerial vehicle (sUAV) can be used to reconstruct a large area of terrain by capturing 3D scans, consisting of LiDAR point clouds and an overlaid image, and combining the scans together. Forming a complete 3D scene using texel image data (fused LiDAR and digital image scans) from an entire flight can be computationally prohibitive on low-cost hardware, so combining registering scans is done using a streaming method which processes the scans in consecutive chunks. Depending on the flight pattern, matching points in the scene may be visible from scans which were not captured around the same time, …

Conversion Of Thermal Energy Stored In Conductive Concrete To Electricity With Thermoelectric Generators, Moustafa M. Al Adawi

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

This paper presents a proof-of-concept experimental study on the use of conductive concrete as thermal energy storage and its conversion into electricity. The conductive concrete is heated to 100°C by supplying electricity, and the stored thermal energy is converted back into electricity using thermoelectric generators (TEGs). Measurement results demonstrate that the conductive concrete effectively stores thermal energy up to 100°C, and this energy can be successfully converted into electricity. The findings highlight the potential of conductive concrete as a reliable medium for thermal energy storage.

Advisor: Lim Nguyen

Deep Learning In Lung Cancer Pre- And Post-Radiation Therapy: Diagnosis Of Malignancy And Radiation-Induced Lung Injury From 3d X-Ray Ct., Benjamin Peter Veasey

Electronic Theses and Dissertations

Lung cancer remains the leading cause of cancer-related mortality worldwide, with early detection and accurate diagnosis being critical for improving patient outcomes. Additionally, the progression of Radiation-Induced Lung Injury (RILI) following Stereotactic Body Radiation Therapy (SBRT) for lung cancer presents a significant diagnostic challenge. This dissertation addresses these challenges by developing deep learning-based diagnostic tools for both pre-treatment lung nodule malignancy classification and post-treatment RILI identification using 3D X-ray CT imaging. The research is divided into two primary objectives. First, for lung nodule malignancy classification, we developed a biopsy-confirmed dataset, called NLSTx, to train and evaluate deep learning models while …

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 …

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 …

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, …

Finding Groundwater With Electricity: Research And Testing Of An Electro-Resistive Ground-Surveying Device For Use In Well-Drilling Applications, Samuel L. Heath

Senior Honors Theses

A custom-built electro-resistive water detection device is tested under various conditions to evaluate its overall performance and sensitivity to changing variables. The tests, designed to assess accuracy and precision, revealed that the prototype exhibits high reliability (~ 99%) for both Schlumberger and Wenner arrays across different electrode spacings and soil conditions. Moreover, the measured resistivity values from the soil tests aligned with established literature ranges for each soil type. The device also showed the ability to consistently detect changes in soil water content by producing measurable variations in resistivity. At a total cost of $181, this prototype can serve as …

Predictive Modeling Of Electro-Optic Modulators Under Electromagnetic Interference, Hasan Ahmed

Optical Science and Engineering ETDs

In this age of electronic warfare, directed energy research is of utmost importance to ensure national security, robust military defense systems and gain a competitive edge in research worldwide. This thesis explores the intentional directed energy impacts on electro-optic devices by developing analytical predictive models through experimental data validation. An electro-optic modulator known as Mach-Zehnder modulator (MZM) is used to understand the implications of intentional EMI. A low frequency RF signal is injected in the MZM to create an EMI environment. The MZM behavior changes due to EMI during a pseudo-random bit sequence signal modulation were studied through analyzing receiver …

Physics Embedded Neural Network: A Novel Data-Free Numerical Method For Solving Computational Physics Problems, Pawan Gaire

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

A novel approach for solving partial differential equations (PDEs) using neural networks for scientific computing is introduced. The proposed approach, referred to as physics-embedded neural network (PENN), features a unique architecture that incorporates the PDE and boundary conditions information directly within the final fully-connected layer of the feed-forward neural network (NN). The key aspect of PENN is the parallel numerical embedding of a differential equation associated with physical problems within the activation function of the network’s final layer. This integration leads to a new class of computational solvers competitive with classical methods like the Finite Element Method (FEM) and capable …

Modeling Degradation In Li-Ion Batteries: Analyzing Single-Cell Degradation And Applying It To Customized Pack-Level, Mohannad Y. Alkhalil

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

The rapid expansion of lithium-ion (Li-ion) battery applications in areas such as electric vehicles (EVs), renewable energy storage, and portable electronics has drawn attention to the need for improving their performance, safety, and longevity. As Li-ion batteries become essential across technologies, understanding degradation mechanisms is critical for optimizing design and ensuring reliable operation. This work provides a detailed overview of modeling degradation in Li-ion batteries, focusing on single-cell behavior and its implications for pack-level performance.

The PyBaMM (Python Battery Mathematical Modeling) package, an open-source battery simulation tool written in Python, is used for single-cell simulations. Liionpack, another Python-based library, is …

Generative Ai For 3d Printed Antenna Design, Jennifer Ann Chavez

Open Access Theses & Dissertations

This research explores the integration of generative artificial intelligence (AI) with a physics-informed particle swarm optimizer (PSO) to develop 3D printable microstrip patch antennas. A neural network was trained on a dataset of microstrip patch antenna geometries and their corresponding performance metrics: return loss and gain. The PSO used a fitness function prioritizing low return loss in potential antennas, eventually yielding novel antenna geometries with parasitic components. 3D printing constraints were also hard coded into the framework, thus preventing any geometries being generated that cannot be fabricated. When simulated using Ansys HFSS, the AI generated microstrip patch antennas exceeded the …

Inference Per Joule: A Performance Metric For Artificial Intelligence In Space Applications, Eduardo Macias Zugasti

Open Access Theses & Dissertations

The use of artificial intelligence (AI) has grown exponentially in recent years. This growth is driven in part by the significant advancements in computing capabilities, which have also increased exponentially. Computers have not only become more powerful but also smaller in size, thanks to the evolution of transistor technology. These developments have enabled AI to become a widely accessible tool, even in recreational activities such as image creation and entertainment videos.

More recently, the use of AI has extended to space applications, where it can enhance and optimize various tasks. However, space conditions pose significant challenges for conventional computers due …

Fibrin-Polycaprolactone Scaffolds For The Differentiation Of Human Neural Progenitor Cells Into Dopaminergic Neurons, Salma Paulina Ramirez

Open Access Theses & Dissertations

This project aimed to develop a tissue-on-a-chip platform for studying Parkinson's Disease (PD) using dopaminergic (DA) neurons. PD is a neurodegenerative disorder characterized by progressive loss of DA neurons, leading to involuntary movements and other symptoms. Early diagnosis and deeper understanding of PD pathogenesis are crucial for improving disease management and patient outcomes. To model PD in vitro, this research utilized human-induced pluripotent stem cell (hiPSC)-derived neural progenitor cells (NPCs) cultured on electrospun (ES) polycaprolactone (PCL) scaffolds. Given PCL's hydrophobicity, ECM-based biomaterial coatings, including Cell Basement Membrane (CBM) proteins, Matrigel, and Fibrin, were explored to enhance NPC adhesion, differentiation, and …

Picosecond Laser Ranging At 1.5 Μm Using Dispersive Interferometry, Behzad Boroomandisorkhabi, Xiangrui Su, Mina Esmaeelpour

Electrical and Computer Engineering Faculty Research & Creative Works

Precise displacement measurement is essential for engineering, industrial, and scientific purposes. Ultrafast laser techniques are preferred for real-time applications due to their single-shot measurement capability and high resolution. To create a high-performance and cost-effective system with less complexity, capable of achieving real-time measurement with high micrometer spatial resolution, we have used a picosecond pulsed laser at the telecommunication wavelength of 1.5 μm in combination with dispersive interferometry. The instantaneous frequency measurement took place using the time-stretch technique incorporating dispersion compensating fiber induced chirp. Results using a 7-picosecond laser at 1.5 μm with a 10 MHz repetition rate are presented. Frequency …

Lightlink: Visible Light Communication For Batteryless Devices With Variable Computational Load, Charles Phillips

All Theses

Visible Light Communication (VLC) devices have been experimentally proven to work as a suitable communication medium for batteryless devices. However, the effects of practical load have yet to be fully explored. To that end, we have developed LightLink, a new MAC and PHY layer protocol for VLC within batteryless devices, and have studied various ways that computational load can affect transmission accuracy in realistic scenarios. Our key findings point us towards an adaptive VLC reception system based on inferred environmental variables.

Blockchain-Integrated Version Control For Secure And Transparent Software Supply Chains, Iwinosa W. Aideyan

All Theses

The software supply chain encompasses all stages of software development and delivery from initial coding and version control to integration and deployment. As development environments become increasingly distributed and reliant on external dependencies, ensuring the integrity, auditability, and consistency of code changes has become a pressing challenge. Traditional version control systems like Git, while effective for collaboration and tracking revisions, do not inherently provide tamper-evident commit histories. Features such as history rewriting (e.g., git rebase, git push --force) can be exploited to manipulate commit logs without detection, posing risks in security-sensitive domains. This thesis proposes a blockchain-integrated version control framework …

Fairness And Robustness In Decentralized Federated Learning, Kaichuang Zhang

Theses and Dissertations

Federated Learning (FL) has emerged as a privacy-preserving paradigm that allows multiple clients to collaboratively train a machine learning model without sharing raw data. However, traditional FL relies on a central server for model aggregation, which introduces a single point of failure and makes the system vulnerable to server-side attacks or breakdowns. To address these limitations, Decentralized Federated Learning (DFL) has been proposed, eliminating the need for a central server and enhancing system resilience. Despite these advantages, DFL faces critical challenges related to fairness and robustness, especially under non-i.i.d. data distributions and adversarial conditions. In this thesis, we propose a …

Spin Coater Design With Pid Algorithm Using Polynomial Regression Approach And Bias Tuning For Tio2 Deposition Process, Geo Surya Andika, Nofrijon Sofyan, Donanta Dhaneswara, Akhmad Herman Yuwono

Journal of Materials Exploration and Findings

The thin-film deposition technique using spin coating offers a cost-effective alternative to Chemical Vapor Deposition (CVD) and Physical Vapor Deposition (PVD). The spin-coating process requires precise control of the motor drive system to ensure that the rotational speed, measured in rotations per minute (RPM), aligns with the set point and remains stable. This study presents the design and development of a spin coater prototype to achieve uniform thin-film deposition. The control method employed utilizes a Proportional-Integral-Derivative (PID) algorithm, incorporating a polynomial approach with bias tuning. The PID control was chosen to achieve stable operation in a non-linear system. The performance …

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 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 …

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 …

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 …

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 …

Understanding The Breadth And Impact Of The Ias [President’S Message], Ayman El-Refaie

Electrical and Computer Engineering Faculty Research and Publications

No abstract provided.

Adaptive Delay Compensation Frameworks For Distributed Real-Time Co-Simulation In Power Systems, Elutunji Buraimoh

All Dissertations

This dissertation presents a model-free, adaptive delay prediction and compensation framework for geographically distributed real-time power system co-simulation environments. Communication delays—both constant and real-time-varying—significantly degrade the accuracy, fidelity, and stability of co-simulated systems, particularly in dynamic and transient analyses of partitioned power systems. To address this, a predictor-based framework is developed that compensates for delays without requiring system models, computationally intensive signal transformations, or manual intervention.

The proposed solution leverages a Damping Impedance Method as the interface algorithm, combined with a sliding-mode control-inspired predictor system. Both single-parameter and multi-parameter predictor configurations are implemented, with the multi-parameter design providing an additional …

Toward The Application Of Natural Language Processing In Electronic Health Record Analysis For Taxonomy Development, Latoya Mcdonald

All Dissertations

Electronic health records (EHRs) are pivotal resources for nurse practice because they increase the timeliness and reliability of patient information at the point of care and support access by multiple healthcare providers and the individual patients themselves. However, it is widely recognized that data extraction from EHRs is challenging due to the variability in the language used in clinical care notes and the lack of standardized terminology across healthcare systems. The broad objective of this dissertation is to develop taxonomy-based classification models for nursing care by applying feature engineering approaches to EHRs that include nursing care of ostomy patients following …

Enhancing Photovoltaic Inverter Reliability Through Advanced Hardware Protection And Simulation Techniques, Buck Brown

All Dissertations

Power electronics converter reliability is an issue in today’s grid, and it is an issue that will only become more prevalent as the nation and world move toward greater renewable energy penetration. While a significant amount of research has been conducted pertaining to power electronics converter reliability, (1) there lacks a universal way to protect the most critical component in a power electronics converter—the power device—from the two most common failure modes—short- and open-circuit faults; and (2) there does not exist a tool that considers both the component- and system-levels of a photovoltaic (PV) inverter for the purposes of lifetime …

Adversarial Voltage Transients In Multi-Tenant Fpga Environments, Andrew J. Gerber

All Graduate Theses and Dissertations, Fall 2023 to Present

A Field Programmable Gate Array (FPGA) is a special type of computer chip that can be reconfigured to implement a nearly unlimited number of functions. Recent trends have led some companies to offer cloud-based FPGA solutions. Researchers are exploring how to properly secure multi-tenant environments where the designs from two or more customers are placed on the same FPGA with logical and spatial isolation, though multi-tenancy is not yet commercially available in cloud FPGAs. The digital circuits within an FPGA require a clock to synchronize timing within the design. The maximum speed that this clock can run at is determined …

Empowering Optimal Operations With Renewable Energy Solutions For Grid Connected Merredin Wa Mining Sector, Md Ohirul Qays, Ravi Kumar, Minhaz Ahmed, Stefan Lachowicz, Uzma Amin

Research outputs 2022 to 2026

Mining sectors require a continuous and reliable power supply; however, reliance on traditional grid utilities results in high costs and disruptions and increases extreme carbon emission. The Merredin WA sector seeks to resolve critical energy challenges affecting mining operations in Western Australia. Thus, this research proposes an optimal solar PV system with battery storage and backup generation for the mining sector to ensure a stable and cost-effective power supply that reduces harmful environmental effect. A hybrid data-driven long short-term memory (LSTM)-classical optimization framework is designed here, thereby optimizing PV-battery storage operational cost savings and energy usage. The optimization results indicate …