Electrical and Computer Engineering Commons^™

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 …

Grid Forming Inverters For Microgrid Operation Enhancement, Jan Westman

All Dissertations

Modern electric power systems are confronted with several major challenges including the increasing frequency and severity of weather events, aging infrastructure, high material costs, cyber-attacks, and substantial delays in global supply chains. Microgrids provide a solution to these challenges by insulating customers from the power outages occurring in their local distribution system. A microgrid is a small independent power system with its own power generation and energy storage resources that can supply customers’ electricity needs. When an outage occurs, a circuit breaker will disconnect the microgrid from the distribution system. Successful operation of the microgrid requires one or more devices …

Networked Multi-Agent Deep Reinforcement Learning Framework For The Provision Of Ancillary Services In Hybrid Power Plants, Muhammad Ikram, Daryoush Habibi, Asma Aziz

Research outputs 2022 to 2026

Inverter-based resources (IBRs) are becoming more prominent due to the increasing penetration of renewable energy sources that reduce power system inertia, compromising power system stability and grid support services. At present, optimal coordination among generation technologies remains a significant challenge for frequency control services. This paper presents a novel networked multi-agent deep reinforcement learning (N—MADRL) scheme for optimal dispatch and frequency control services. First, we develop a model-free environment consisting of a photovoltaic (PV) plant, a wind plant (WP), and an energy storage system (ESS) plant. The proposed framework uses a combination of multi-agent actor-critic (MAAC) and soft actor-critic (SAC) …

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

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 …

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 …

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 …

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 …

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 …

Advanced Day-Ahead Scheduling Of Hvac Demand Response Control Using Novel Strategy Of Q-Learning, Model Predictive Control, And Input Convex Neural Networks, Rahman Heidarykiany, Cristinel Ababei

Electrical and Computer Engineering Faculty Research and Publications

In this paper, we present a Q-Learning optimization algorithm for smart home HVAC systems. The proposed algorithm combines new convex deep neural network models with model predictive control (MPC) techniques. More specifically, new input convex long short-term memory (ICLSTM) models are employed to predict dynamic states in an MPC optimal control technique integrated within a Q-Learning reinforcement learning (RL) algorithm to further improve the learned temporal behaviors of nonlinear HVAC systems. As a novel RL approach, the proposed algorithm generates day-ahead HVAC demand response (DR) signals in smart homes that optimally reduce and/or shift peak energy usage, reduce electricity costs, …

Optimization-Based Distributed Controller For Multi-Agents System In Microgrid Secondary Control, Fahad S. Alshammari, Ayman El-Refaie, Saleh Alyahya, Sheroz Khan

Electrical and Computer Engineering Faculty Research and Publications

Micro-grids function to connect to power system power produced by the renewable energy resources. In islanded micro-grids, grid-forming units collaborate to maintain the micro-grids voltage and frequency by utilizing droop control technique that includes primary, secondary and tertiary levels. Secondary control intervenes to improve power sharing and restore voltage and frequency to their nominal levels. However, the conventional droop control applied to a grid with mismatched line parameters experiences a trade-off between reactive power sharing and voltage regulations. This paper applies real-time trajectory tracking convex optimization to ensure by communicating power sharing between units in a consensus topology. The optimization …

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.

Development Of Si-Based Germanium-Tin Infrared Photodiode, Sylvester Amoah

Graduate Theses and Dissertations

Short-wave infrared (SWIR) and mid-wave infrared (MWIR) photodetectors have attracted increasing attention for the past few decades. SWIR and MWIR detectors are used for a wide range of applications in military and civilian defense, such as future automotive night vision, video surveillance security cameras, and integrated night vision in mobile/wearable electronics. The current market-dominating IR photodetector technology is mainly developed with the costly III-V or II-V material systems, such as InGaAs, InSb, and HgCdTe. While many efforts have been made towards the hybrid integration of III-Vs or II-VIs on a Si substrate, it is highly desirable to develop an alternative …

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 …

Scheduling Charging For Fleets Of Battery Electric Vehicles: Techniques For Modeling And Real-Time Operation, Justin J. Whitaker

All Graduate Theses and Dissertations, Fall 2023 to Present

While electric vehicles (EVs) are becoming increasingly popular and can provide cost, maintenance, and environmental benefits, they present unique challenges for regular operation, especially in fleets of vehicles. The limited range, long charging times, and high power requirements of EVs complicate the operations of fleets comprised of EVs. Additionally, the charging costs of EVs can be complex, depending on the time of charging, the energy charged, and the power level of the charging session. These complex charging costs can be significantly affected by the presence of uncontrolled loads. These challenges are further complicated by the inevitable variations in the real …

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, …

Blind Construction Of A Party Check Matrix For Arbitrary Linear Block Codes, Aaron J. Womack

All Graduate Theses and Dissertations, Fall 2023 to Present

Communication systems are systems in which a transmitter sends data across a channel to a receiver. In any modern communication system, Forward Error Correction (FEC) is used to detect and correct errors that occur during transmission. As communication systems have developed over the years, many FEC algorithms have been proposed. Each FEC algorithm has parameters that can be selected based on the needs of the communication system. Typically, the transmitter and receiver are both aware of the FEC parameters, but in some cases the receiver may not know how the transmitter encoded its message. In this case, the receiver must …

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 …

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 …

Development Of A Portable Electroencephalogram With Display, Seth D. Davis

Electronic Theses and Dissertations

In this experiment, the goal was to design, build, and test an Electroencephalogram (EEG) circuit that would then be paired with a touchscreen display as a portable unit for use in Schizophrenic research at East Tennessee State University at the Quillen College of Medicine. The requirements for this prototype denoted that the device had to be able to obtain a signal from two electrodes placed on the head of an individual with a third attached to the ankle as a ground, amplify and filter the signal, and display the results on a touchscreen display for recording and analyzing. The circuit …

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 …