Digital Commons Network^™

Influencing Factors Of Angle-Of-Arrival Estimator Based On Deep Learning, Guohao Pang

Dissertations and Theses

Deep learning (DL)-based angle-of-arrival (AoA) estimation offers significant advantages over traditional signal processing methods, especially in complex and high-noise environments. However, situational complexity and differences in hardware can significantly impact the estimator's performance. It is therefore of interest to investigate the relationship between the performance of deep learning models and the variation of physical parameters such as the number of signal sources, the number of receiving antennas, and the signal-to-noise ratio (SNR). In this study, we investigate the impact of these variations on deep learning-based AoA estimation by systematically analyzing how the variations in the characteristics of the received signal …

Optimization Of Renewable Energy Systems: Comparative Analysis Of Advanced Algorithms And Photovoltaic-Electrolyzer Performance For Cost Reduction And Efficiency Enhancement, Mohamed-Amine Babay, Mustapha Adar, Ahmed Chebak, Mustapha Mabroukia

Journal of Electrochemistry

The increasing demand for cost-effective and efficient renewable energy solutions presents significant optimization challenges in hybrid energy systems. This paper addresses these challenges by conducting a comparative analysis of three advanced optimization algorithms—Lévy Flight Optimization (LFO), Archimedean Optimization (AO), and Quantum Gorilla Optimization (QGO)—to minimize the Total Net Present Cost (TNPC) and Levelized Cost of Energy (LCOE) in hybrid renewable energy systems. The study integrates critical cost parameters such as Capital Expenditure (CAPEX), Operational Expenditure (OPEX), replacement costs, and salvage values into an advanced optimization framework. Three system configurations are evaluated: Wind Turbines and Fuel Cells (WT/FC), Photovoltaic Systems and …

Design And Optimization Of Low-Loss, High-Gain Metamaterial-Based Log-Periodic Dipole Array Antenna For Full Ka-Band Coverage, Mohamed El Moniar, Ahmed Abd El Hady, Yasser Ismail, Nihal Areed

Turkish Journal of Electrical Engineering and Computer Sciences

This work describes a microstrip log-periodic dipole array (MLPDA) antenna that uses metamaterials and operates across the whole Ka-band. The suggested MLPDA antenna layout provides a wide bandwidth with fewer dipole elements than traditional MLPDA antennas while maintaining the same resonance frequencies. To reduce size while covering a wide operational spectrum, the antenna design includes bending dipoles as radiating elements, as well as an incomplete ground plane. Furthermore, the proposed MLPDA antenna’s energy loss has been reduced while boosting its signal strength (gain) by inserting a metamaterial-based structure in front of it at a certain distance and on the same …

Experimentally Driven Numerical Model Of Carbon/Polyaniline-Based Glucose Monitoring Sensors: An Evaluation Using A New Figure Of Merit, Kyrillos Selim, Ziad Khalifa, Amira Ali, Sameh O. Abdellatif

Electrical Engineering

This study presents an experimentally driven numerical model for evaluating carbon/polyaniline (PANI)-based glucose monitoring sensors (GMSs), focusing on innovative configurations using graphene-PANI and carbon nanotube (CNT)-PANI composites. We performed a thorough analysis of the morphological, electrophysical, and electrical properties of these materials, ultimately leading to the extraction of key electrical parameters for integration into a finite element model (FEM). This model simulates the entire sensor, enabling the estimation of critical performance metrics such as sensitivity, limit of detection (LOD), linearity, and power consumption. Our findings demonstrate that the CNT-PANI configuration significantly outperforms the laser-induced graphene (LIG)-PANI electrode, achieving a figure …

Detecting And Analyzing Frequency Events In Power Systems Using Tunable Parameters-Based Algorithms: Development, Optimization, And Analysis, Hussain A. Alghamdi

Dissertations and Theses

This dissertation addresses the challenge of detecting frequency events in diverse power systems by enhancing existing frequency event detection methods through detection process modifications and developing unique tunable parameters. Since system characteristics differ across regions, frequency event detection algorithms must be customized by domain experts for each balancing area using tunable parameters. By optimizing these parameters for specific power system, the algorithms can accurately detect frequency events and can also be used for further analysis to determine trends in frequency events over time, ensuring system stability.

This dissertation focuses on the enhancement and optimization of frequency event detection algorithms. These …

Design Of A Subthreshold Cmos Inverter-Based Amplifier For Low-Noise And Low-Power Applications, Landon Alexander Schmucker

Electrical and Computer Engineering ETDs

Amplification is a fundamental function in most analog circuits. There is a fast-growing demand for low-power, low-noise, and high-gain amplifiers. Modern semiconductor processes are increasingly optimized for digital applications, which has introduced new challenges in analog design. To address these challenges, analog designers have investigated replacing conventional analog circuits with digital implementations. One promising application is the typical CMOS inverter as an amplifier.

This research presents a CMOS inverter-based amplifier with feedback designed to achieve low power consumption, low input noise, and high gain. Unlike typical CMOS inverter-based amplifiers, this topology has two distinctive features: (1) it uses a MOSFET …

Aerial Robotic Studies Of Volcanic Co2 Emissions, John Ericksen

Computer Science ETDs

Volcanic systems are inherently complex, involving dynamic interactions among magma flow, gas emissions, and atmospheric dispersion. This dissertation focuses on developing and analyzing autonomous UAS algorithms for efficiently surveying volcanic CO2 plumes, introducing several novel methods: the LoCUS algorithm, a swarm coordination and self-healing algorithm that supports gradient-based plume tracking, a transect-based technique that employs a 2D Gaussian fit to calculate CO2 plume flux, and the Sketch algorithm for rapid plume boundary tracing. By treating multiple UAS as a single scientific instrument, these methods leverage swarm algorithms to use in-situ data in ways impossible with individual drones. Validated through simulations …

Improved Electric Load Modeling Of Residential Air Conditioning, Julius Johnson

UNLV Theses, Dissertations, Professional Papers, and Capstones

The recent increase in energy production from renewable resource introduces a new challenge in managing and maintaining balance between electricity supply and demand, due to uncertainty and variability of wind speed and solar irradiance. To address this growing problem, demand-side management, such as Demand Response (DR) programs, is employed to adjust power consumption. Residential air conditioners (ACs) are the most suitable candidates for DR, due to their intensive power consumption and inherent thermal inertia that allows flexibility in their operations (by adjusting their set-point temperatures) without sacrificing customer comfort. Most prior research on AC load models assumes that such a …

Explorations Of Amplified Feedback In Quantum Circuits, Maxwell B. Weiner

Dartmouth College Master’s Theses

The Josephson Traveling Wave Parametric Amplifier (TWPA) has emerged as a key technology for high-fidelity qubit readout in superconducting quantum computing. By leveraging the nonlinear inductance of an array of Josephson Junctions, the TWPA enables broadband, near-quantum-limited amplification with minimal added noise, significantly improving the signal-to-noise ratio in qubit measurements. Unlike traditional resonant parametric amplifiers, which suffer from bandwidth constraints, the traveling wave design of the TWPA allows for wideband operation, making it particularly suited for multiplexed readout of both simple qubits and large-scale quantum processors.

In this thesis, we explore how the TWPA can be integrated into a feedback …

Automated Solar Panel For Lmu Campus, Michael Hennessy, Jack Michaelis, Jack Leon, Nick Aiello, Mustafa Mozael

Honors Thesis

This Final Design Review outlines the design and implementation of an automated sun-tracking solar panel system for Loyola Marymount University's campus. The project aims to improve the efficiency of existing static solar panels by designing a new system of sun-tracking panels at a low cost and high power efficiency. The report covers the project's background, including LMU's current solar energy infrastructure and sustainability goals. It analyzes the advantages of automated solar panels over static ones, presenting comparative studies that demonstrate significant increases in energy capture. The report details the calculations for solar angle tracking, along with the mechanics and electronics …

Real-World Implementation Of A Noninvasive, Ai-Augmented, Anemia-Screening Smartphone App And Personalization For Hemoglobin Level Self-Monitoring, Robert G. Mannino, Julie Sullivan, Jennifer K. Frediani, Paul George, Jeremy Whitson, James Tumlin, L. Andrew Lyon, Erika A. Tyburski, Wilbur A. Lam

Engineering Faculty Articles and Research

Anemia, characterized by low blood hemoglobin (Hgb) levels, afflicts >2 billion individuals worldwide. Here, we report real-world data generated by a smartphone app that noninvasively screens for anemia using only “fingernail selfies.” App data for anemia screening were obtained from >1.4 million uses across the United States enabling geographic mapping of Hgb levels. Of those, 9,061 users also self-reported complete blood count Hgb levels for comparison, resulting in accuracy and performance that match gold standard laboratory testing and a sensitivity and specificity of 89% and 93%, respectively, when using an anemia cutoff of 12.5 g/dL. Geotagged data enabled construction of …

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

Thesis/ Dissertation Defenses

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 …

Designing An Economically Viable Off-Grid Photovoltaic System Considering The Battery Discharge Rate, Ahmed S. Abdelrazek, Eslam Mohamed Ahmed, Mahmoud Elsisi, Mokhtar Said

Mansoura Engineering Journal

The primary significance of harnessing power from clean and renewable sources lies in the fact that numerous rural areas are far from the utility system. Among the renewable energy technologies catering to power needs in residential areas is the solar photovoltaic (PV) system. Despite the potential of PV technology and the abundant sun radiation exposure in Hurghada, Egypt, there is a lack of empirical studies evaluating the feasibility of off-grid power production using this system. A notable aspect of this study is the consideration of the discharge rate of the battery for sizing the off-grid system, involving the distribution of …

Functional Devices Based On Freestanding 2d Materials, Shijue Xu

McKelvey School of Engineering Graduate Student Theses & Dissertations

Two-dimensional (2D) materials have attracted extensive attention in the field of nanoelectronics due to their atomic-scale thickness, high surface-to-volume ratio, tunable electronic properties, and compatibility with low-temperature processing. These characteristics make them highly suitable for the construction of emerging device architectures, particularly in both ionic and electronic devices.

In this work, we investigate the application of 2D materials in two distinct classes of devices: ionically-driven memristors and electronically-dominated metal–semiconductor contacts. For the memristor study, we fabricate heterostructure-based resistive switching devices using h-BN and WSe₂ as active layers. These 2D material-based memristors exhibit stable power consumption loops and high linearity …

Development Of Interactive Games On An Affordable Braille Display, Daniel Tsivkovski, Dylan Ravel, Maryam Etezad

Student Scholar Symposium Abstracts and Posters

Developing an affordable and STEM learning-focused Braille display addresses a significant disparity in the market for Braille displays, where most fail to provide a cost-effective, accessible, and education-oriented solution. This research aims to bridge this gap through innovative hardware and software development, offering a comprehensive learning experience to elementary school children (K-6) who are blind/visually impaired. The hardware features a piezo-electric tactile display that displays up to six Braille characters at once or a shape in an 8x8 pin array configuration. The educational software includes a user-friendly website packed with engaging STEM activities specifically designed for blind/visually impaired children. The …

Praxly: An Online Ide For The Praxis Cs Test Pseudocode, Benjamin Saupp

James Madison Undergraduate Research Journal (JMURJ)

No abstract provided.

Characterization Of A Magnetically Contained Hot Filament Plasma Source With A Wide-Sweeping Langmuir Probe, Jonas Rowan

Doctoral Dissertations and Master's Theses

Ionospheric plasma research in the Space and Atmospheric Instrumentation Laboratory’s Space Plasma Chamber has been hindered by the lack of a suitable plasma diagnostic instrument and understanding of its hot-filament plasma source. This thesis describes efforts made to remedy both problems. A wide-range Sweeping Langmuir Probe was developed with a ±35 V sweeping range to fully analyze ion and electron saturation regions in the entire IV curve. A method was derived to estimate the chamber source’s filament temperatures. The new Langmuir probe was integrated into a refurbished automated system designed in Python to measure plasma parameters for various chamber conditions, …

A Wireless Flex Sensors Based Man-Machine Interface, Maram F. Badkook, Razan A. Alshehri, Saeed Qaiser

Effat Undergraduate Research Journal

Abstract. The recent technological advancements are focusing on developing the smart systems to facilitate the subscribers and to improve their lifestyle. The machine learning algorithms and artificial intelligence are becoming the elementary tools, which are used in the establishment of modern smart systems across the globe. In this study, a flex sensors-based Man to Machine Interface (MMI) is proposed. It is beneficial for a category of people with reduced mobility or special needs like deaf, dumb, parallelized, etc. The system prototype is realized by using an array of flex sensors and a front-end processor, wirelessly connected to the central processing …

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 …

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 …

Validating An Electronics Cooler Experiment And Optimizing Its Performance Using Ansys Icepak, Daniel V. Curl

Mechanical Engineering Undergraduate Honors Theses

Researchers at the University of Arkansas' Mechanical and Electrical Engineering Research Departments have designed and built a cold plate and substrate design for a 10 kV SiC MOSFET power module. Many variables define the design of the cold plate and substrate system and have quantifiable effects on the device’s performance. These variables include but are not limited to geometry and material selection of the fins and substrate. Manufacturing many test designs, running experiments, and comparing their performance is a time-consuming and expensive design optimization method that may be effective for some low-cost applications. Still, simulation is often a more cost-effective …

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 …

Multimodal Emotion Recognition For Human-Robot Interaction Across Neuro-Diverse Populations., Ruchik Mishra

Electronic Theses and Dissertations

This dissertation explores the integration of multimodal data streams and artificial intelligence pipelines to understand human affect in neurotypical and children with Autism Spectrum Disorder (ASD). This dissertation captures human affect in the context of human-robot interaction. For this, multiple studies have been presented with both children with ASD and neurotypical adults. This dissertation makes four contributions: 1) The first study introduces autonomy during perspective-taking teaching sessions by making verbal content generation through large language models (LLMs). This system is the first of its kind for teaching perspective-taking in a semi-autonomous manner under the supervision of domain experts. Furthermore, this …

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 …

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 …

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 …

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 …

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 …

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 …