Electrical and Computer Engineering Commons^™

Distributed Energy Trading Models Utilizing Reinforcement Learning And Game-Theoretic Based Approaches In Smart Grids, Nicholas Kemp

Electrical and Computer Engineering ETDs

Community-driven energy initiatives have become crucial for effective energy management, particularly in trading and management. The rise of Distributed Energy Resources in smart grids demands a redesign of traditional Demand Response Management (DRM) models to account for prosumers' dynamic behavior in energy markets. Decentralization, including peer-to-peer (P2P) energy trading, is vital for resilience and sustainability. This thesis introduces two coalitional DRM models: one based on hedonic community formation games, and the other combining matching theory with coalition games. These models empower prosumers to autonomously select energy trading communities using partially available data. To optimize energy consumption, two additional models are …

Embedding Direction Of Arrival And Antenna Beamforming Algorithms On Automated Software Defined Radio Platforms, Adrian J. Lewis

Electrical and Computer Engineering ETDs

Antenna arrays are an essential technology in the modern era in both communications and radar applications. The algorithms used for antenna arrays are beginning to be embedded in smart device applications to enable greater communication abilities. This thesis explores the idea of embedding direction of arrival and beamforming algorithms using a software defined radio platform. Specifically, the Multiple Signal Classification (MuSiC) algorithm and Minimum Variance Distortionless Response (MVDR) algorithm are combined. The combination of similar algorithms has the potential to be used in many internet of things applications to enable more dynamic communication ability.

Adaptive Screen Capture Video Analysis, Ugesh Egala

Electrical and Computer Engineering ETDs

This thesis presents a system for analyzing student activities during class sessions to gain insights into the learning process. A dataset consisting of 14 screen recordings, with 2 videos labeled across two stages, was used for training, validation, and testing. The methodology employs adaptive sampling, initially at 10 frames per minute to identify active regions, followed by detailed analysis at 1 frame per second using OCR to detect typing activities through character changes. The results demonstrate over a 50% reduction in computational load while maintaining high accuracy in detecting student engagement. A total of 26 hours of screen capture videos …

On The Surface Topography Of Local Overheating And Plasma Formation Due To Initial Condition Perturbations Sourcing The Electrothermal Instability On High-Current-Density Conductors, Maren Whiting Hatch

Electrical and Computer Engineering ETDs

The electrothermal instability (ETI) is a Joule heating-driven instability that instigates runaway heating on conductors driven to high current density, altering the 3D evolution of the expansion and phase state. Most metals include complex distributions of imperfections (voids, resistive inclusions) which seed ETI. To simplify comparison with modeling and theory, experiments examined growth of ETI from various alloys of stainless steel as well as relatively void/inclusion free, 99.999% pure, diamond-turned, 1 mm-diameter aluminum rods. Aluminum surfaces included a variety of deliberately machined and well-characterized perturbations, including 10-micron-scale quasi-hemispherical voids, or “engineered” defects (ED), and sinusoidal patterns of varying wavelength and …

Pulsed Secondary Electron Yield Measurements Of Metallic And Dielectric Materials Of Interest For High Power Vacuum Electron Devices, Bilal Ahmed Malik

Electrical and Computer Engineering ETDs

Secondary electron emission (SEE) from conductors is thought to play an important role in the initiation of Multipactor breakdown in vacuum electron devices. The SEE of dielectric materials plays a crucial role in numerous scientific and technological applications, including particle accelerators, spacecraft charging, and plasma diagnostics. Additionally, the SEE of an insulator may depend on its electrical stress history. In both cases, SEE strongly depends on any conditioning of the material surface. We present measurements on both conducting and insulating materials of interest in these applications. Measurements are being made in an existing test stand, recently modified to enable measurements …

Deep Learning For Multiple Unmanned Aerial Vehicle Coordination In Air Corridors, Liangkun Yu

Electrical and Computer Engineering ETDs

In the future, city skies will be filled with Unmanned Aerial Vehicles (UAVs) for rapid urban transport, including parcel deliveries and air taxis. NASA's Urban Air Mobility (UAM) envisions UAVs navigating air corridors. These virtual pathways ensure safety and compliance with regulations. However, current research on UAM practical applications is limited. This dissertation focuses on designing air corridors, developing UAV control systems, and ensuring the robustness of control algorithms against disturbances in real-world environments.

Our design features an air corridor system with horizontal lanes and on-off ramps, conceptualized as cylindrical spaces and tori, respectively. To enable each UAV to locally …

Advancing Influence In Social Networks Based On Game Theory, Adedamola Adesokan

Electrical and Computer Engineering ETDs

Online Social Networks (OSNs) have become part of our everyday life, as a means of interacting with people, sharing content, attending events, etc. Influencers are professional OSN users, who have a large loyal audience and use the OSNs to market various goods or services based on brand partnerships. In this thesis, we introduce a novel mechanism to enable OSN users to become influencers by strategically deciding their activity within the OSN. Initially, the concepts of social coordinates and social communities are proposed. Then, a non-cooperative game is introduced to enable the users to make optimal decisions regarding their activity in …

Deep Learning Framework For Graph-Based Molecular Drug Discovery, Daniel Manu

Electrical and Computer Engineering ETDs

This dissertation proposes the GraphGANFed framework, which combines Graph Convolutional Networks (GCN), Generative Adversarial Networks (GAN), and Federated Learning (FL) to generate novel molecules while preserving data privacy. FL allows learning from distributed clients without sharing local datasets, GCN extracts molecular structural properties, and GAN generates new molecules retaining the learned properties. Extensive simulations on three benchmark datasets show GraphGANFed's effectiveness, producing molecules with high novelty (≈ 100) and diversity (> 0.9). Results indicate a trade-off among evaluation metrics, and the right dropout ratio avoids mode collapse. Additionally, Conditional GraphGANFed (cGraphGANFed) incorporates a critic network from Reinforcement Learning (RL) to …

Engineering Composite Gridlines For Improved Solar Module Reliability, Andre Chavez

Electrical and Computer Engineering ETDs

Renewable energy sources, such as solar power, are rapidly expanding worldwide to meet increased energy demands. However, these sources are exposed to challenging environmental stressors, such as extreme wind, heavy snow loads, and hailstorms that can cause irreversible damage to the crystalline semiconductor solar cells. Today, single crystalline silicon solar cells dominate the market, and our work is focused on improving their reliability against environmental stressors. One of the main degradation mechanisms caused by environmental stressors is cell cracks. These microcracks can go virtually undetected and lead to reduced power output from solar modules over time. To solve this engineering …

Securing The Skies: Safety-Constrained Decentralized Multi-Uav Coordination With Deep Reinforcement Learning, Jean-Elie Pierre

Electrical and Computer Engineering ETDs

In the dynamic landscape of autonomous aerial systems, the integration of uncrewed aerial vehicles (UAVs) has sparked a paradigm shift, offering unprecedented opportunities and challenges in collaborative decision-making and navigation. This thesis explores the application of multi-agent reinforcement learning (MARL) for the planning and coordination of UAVs in complex environments.

The first part of this thesis provides an introduction to single-agent reinforcement learning and MARL. We provide examples of the use of MARL for countering uncrewed aerial systems (C-UAS). We formulate the Counter-UAS problem as a multiagent partially observable Markov decision process (MAPOMDP), and we propose Multi-AGent partial observable deep …

Plasma Diagnostics For Anode Cathode Plasmas And High Energy Density Physics On A Linear Transformer Driver, Robert Beattie-Rossberg

Electrical and Computer Engineering ETDs

A twelve-brick air insulated linear transformer driver (LTD) was characterized by charging to voltages ranging from 30 to 70 kV and delivering energy to two separate resistive loads. Various plasma diagnostics were built and fielded with an emphasis on the design, implementation and analysis of a Mach Zehnder interferometer, a moiré deflectometer and a spectroscopy system providing information on the temporal evolution of plasma electron density and atomic composition. Rogowski coils, XRD radiation detectors, framing camera images and time integrated DSLR images are used to further understand load conditions where current data, x ray radiation data, velocity data and instability …

W/V-Band Propagation Modeling, Nolan Rebernick

Electrical and Computer Engineering ETDs

Enhancing the accuracy of atmospheric loss modeling holds the potential to significantly refine estimations of received power, thereby enhancing the overall quality of satellite communication links. This study aims to pioneer and validate an innovative modeling framework to reliably predict atmospheric attenuation along satellite-to-ground propagation paths, particularly focusing on portions of the W-band (81-86 GHz) and V-band (71-76 GHz). By leveraging meteorological data, this approach will encompass various weather scenarios, including clear skies, cloud cover, and diverse forms of precipitation. Utilizing the generated time domain data, the research aims to construct complementary cumulative distribution functions, enabling the analysis of satellite …

Ml/Ai Enabled Intelligent Next Generation Autonomous Network System: Performance Enhancement And Management, Harsh Kumar

Electrical and Computer Engineering ETDs

The smart next generation autonomous system for network performance enhancement and management, specifically suitable for networks like 5G, B5G, 6G, and SDN, is presented in this PhD dissertation powered by ML/AI. The dissertation has been divided into six critical parts. First, it focuses on QoS monitoring and provisioning using intelligent QoS agent design in 6G network. Second, it elaborates on LSTM and SP-LSTM comparative analysis towards network traffic prediction in 6G networks. Third, digging into 6G frontier navigation using SE-DO for intelligent Agent Optimization. Fourth, the dissertation delves into role delegation function as a service to improve reliability and latency …

A Framework For Managing System Resources And Pricing In Multi-Provider Edge Computing Environments, Matthew Paul Salcido

Electrical and Computer Engineering ETDs

Multi-provider multi-user multi-access edge computing provides a recent market driven networking paradigm facilitating the user data offloading process. In this thesis, we introduce the AGORA framework, which employs a sophisticated multi-leader multi-follower Stackelberg game that jointly optimizes the data offloading, computing resource allocation, and computing resource pricing, all facilitated through a non-cooperative game-theoretic approach. In order to support the aforementioned modeling and approach, a novel utility function that quantifies the users satisfaction, factoring in the computing service cost, and an innovative profit function for the MEC providers is introduced, emphasizing the market penetration and the computing service provision costs. Numerical …

A Symbiotic Content Caching Approach In Next-Generation Information-Centric Networks Based On Game Theory, Aisha B Rahman

Electrical and Computer Engineering ETDs

The continuous growth of mobile data traffic with strict time requirements calls for the development of sustainable edge content caching solutions. This becomes more prominent in the setting of Information-Centric Networking (ICN) architectures, where different ICNs are leasing caching slices to the available content providers (CPs), who in turn offer their services to the users. In this thesis, we introduce a novel symbiotic content caching framework that provides the necessary economic benefits to the ICNs and the CPs to mutualistically collaborate among each other. The corresponding mutualistic interactions among the ICNs and CPs are studied under the prism of two …

A Bio-Inspired Alternative Positioning, Navigation, And Timing Approach Based On A Potential Game-Theoretic Model, Md Sadman Siraj

Electrical and Computer Engineering ETDs

This thesis addresses the challenge of designing of alternative Positioning, Navigation, and Timing (PNT) solutions. Inspired by the evolution of biological ecosystems, we introduce a novel symbiotic PNT solution, based on the principles of Game Theory and the exploitation of Reconfigurable Intelligent Surfaces (RISs). A set of actors, consisting of anchor nodes and RISs with known coordinates, collaborator nodes having a rough estimate of their positions, and targets of unknown positions, are cooperating to accurately determine the targets’ positioning and timing. The key objective is to minimize the estimation error of each target and collaborator node, as well as of …

Location Aware Task Offloading Framework For Edge Computing Empowered By Reconfigurable Intelligent Surfaces, Md Sahabul Hossain

Electrical and Computer Engineering ETDs

In this thesis, an energy efficient task offloading mechanism in a multi-access edge computing (MEC) environment is introduced, based on the principles of Contract Theory. The technology of Reconfigurable Intelligent Surfaces (RIS) is adopted and serves as the enabler for the energy efficient task offloading, from the perspective of location-awareness and improved communication environment. Initially a novel positioning, navigation, and timing solution is designed, based on the RIS technology and an artificial intelligent method that selects a set of RISs to perform the multilateration technique and determine the Internet of Things (IoT) nodes’ positions in an efficient and accurate manner …

Ai Assisted Workflows For Computational Electromagnetics And Antenna Design, Oameed Noakoasteen

Electrical and Computer Engineering ETDs

These days large volumes of data can be recorded and manipulated with relative ease. If valuable information can be extracted from them, these vast amounts of data can be a rich resource not just for the digital economy but also for scientific discovery and development of technology. When it comes to deriving valuable information from data, Machine Learning (ML) emerges as the key solution. To unlock the potential benefits of ML to science and technology, extensive research is needed to explore what algorithms are suitable and how they can be applied.

To shine light on various ways that ML can …

A Moving Target Architecture As A Side-Channel Countermeasure, Rachel M. Cazzola

Electrical and Computer Engineering ETDs

We investigate a novel side-channel attack countermeasure called Side-channel Power analysis Resistance for Encryption Algorithms using Dynamic partial reconfiguration (SPREAD). The countermeasure leverages a strategy that is best characterized as a moving target architecture. Modern field-programmable gate array (FPGA) architectures provide support for dynamic partial reconfiguration (DPR), a feature that allows real-time reconfiguration of portions of the programmable logic (PL) while the FPGA continues to carry out computing tasks. Using the Advanced Encryption Standard (AES), the proposed moving target architecture leverages DPR to change the implementation characteristics of the substitution boxes (SBOX) in real time. We present experimental hardware results …

Study Of Si-Gan Photoconductive Switches Operating Modes Using Near-Ir Radiation, Nicolas Eduardo Gonzalez Padilla

Electrical and Computer Engineering ETDs

One of the most promising solid-state devices for fast switching and radio frequency generation applications is the photoconductive switch (PCSS). These devices have been thoroughly explored since the late 1980s and exhibit remarkable switching properties in gallium arsenide (GaAs). With recent advances in wide bandgap (WBG) semiconductor manufacturing processes, there has been an increasing interest in using WBG semiconductors to implement PCSS. WBG semiconductors could exhibit the same switching characteristics as GaAs while overcoming their poor power management and short lifetime under pulsed power conditions, making PCSS a reliable option in high-power applications. Gallium Nitride (GaN) has emerged as one …

Design, Optimization, And Hardware Deployment Of A Deep Learning Model For Gps Spoofing Detection Using Gnss Satellite Receiver Protocol Data, Clarizza Morales Chacon

Electrical and Computer Engineering ETDs

The contemporary GPS infrastructure plays a vital role in advancing Position, Navigation, and Timing (PNT) applications across various sectors, including transportation, commerce, finance, and aviation. To provide a robust and authenticated infrastructure for users, it is important to develop a methodology for verifying the authenticity of satellite navigation signals, especially in civilian applications using the C/A code. This thesis explores Machine Learning (ML) techniques, focusing on the analysis of Global Navigation Satellite System (GNSS) protocol messages like UBX and NMEA to detect anomalies in receiver and satellite behavior, indicative of potential spoofing. The research demonstrates the deployment of Machine Learning …

Optimal Management Of Renewable Energy Resources To Increase Resilience Of Power Systems, Tohid Khalili

Electrical and Computer Engineering ETDs

The main goal of this dissertation is to improve the resilience of power systems using different techniques and optimization approaches regarding new technologies. Thus, several test cases with various objective functions are proposed. Voltage regulation and demand response programs are used to investigate and improve the system's financial and reliability status. In addition, COVID-19’s effect with the high presence of renewable energy resources is examined from financial, risk, and reliability points of view. Finally, a new model for the wildfire risk is proposed in a large distribution system to increase the reliability of the system with the usage of reclosers …

Characterization Analysis And Design Of Mid-Wave Infrared Iii- V-Based Type-Ii Superlattice Nbn Photodetectors For Space Applications, Alexander Timothy Newell

Electrical and Computer Engineering ETDs

The performance of the mid-wave infrared InGaAs/InAsSb nBn photodetector is investigated and its viability for space applications is assessed. Three structures are grown with unique absorber layer doping profiles via molecular beam epitaxy. Material and device characterizations are performed and analyzed to determine the effects of doping on fundamental material parameters and detector performance. Noise-equivalent irradiance is calculated to be a factor of 4x that of an ideal detector exhibiting Rule 07 dark current and 100% quantum efficiency, demonstrating high sensitivity. The structures are then irradiated with 63 MeV protons to evaluate the extent of performance degradation over the course …

Dynamic Spectrum Management In 3d Networks Inspired By Biological Systems, Jordan Anthony Patrizi

Electrical and Computer Engineering ETDs

In this thesis, the challenge of dynamic spectrum management is treated following an economic-based perspective. In particular, a novel bioinspired spectrum allocation from the Network Service Providers (NSPs) to the users is introduced, exploiting the theory of symbiosis under the free competition. The overall objective is to determine the NSPs optimal bandwidth prices to maximize their profit, while satisfying the users bandwidth needs. The aforementioned spectrum management framework is analyzed while exploiting a novel 3D network architecture consisting of High Altitude Platforms (HAPs), Unmanned Aerial Vehicles (UAVs), and ground gNBs NSPs, each one of them presenting different operational characteristics and …

Enabling Intelligent Network Management Through Multi-Agent Systems: An Implementation Of Autonomous Network System, Petro Mushidi Tshakwanda

Electrical and Computer Engineering ETDs

This Ph.D. dissertation presents a pioneering Multi-Agent System (MAS) approach for intelligent network management, particularly suited for next-generation networks like 5G and 6G. The thesis is segmented into four critical parts. Firstly, it contrasts the benefits of agent-based design over traditional micro-service architectures. Secondly, it elaborates on the implementation of network service agents in Python Agent Development Environment (PADE), employing machine learning and deep learning algorithms for performance evaluation. Thirdly, a new scalable approach, Scalable and Efficient DevOps (SE-DO), is introduced to optimize agent performance in resource-constrained settings. Fourthly, the dissertation delves into Quality of Service (QoS) and Radio Resource …

Electromagnetic Simulations Of The Lansce Chopper Structure, Yusuf Sahin

Electrical and Computer Engineering ETDs

Particle accelerators are important for basic research as well as in applications such as ion implantation and cancer therapy. One important accelerator is the Los Alamos Neutron Science Center (LANSCE) located at Los Alamos National Laboratory (LANL) that primarily produces neutrons for research. The beam chopper simulation described here is a study to provide better modeling of this subsystem of LANSCE. A chopper is a device in which particles are intermittently sliced and directed to a target and/or experiment. The simulations in this thesis are used to analyze the correct operating parameters of the chopper. A good chopper model can …

Speaker Diarization Of Noisy Classrooms From A Single Microphone Based On An Array Of Virtual Microphones And Machine Learning, Richard Briggs

Electrical and Computer Engineering ETDs

Speaker diarization from a single microphone is extremely challenging in noisy classroom environments. A new method based on simulating a microphone array has shown promising results, while requiring very little training. It used a minimum distance classifier to identify the speaker among a list of possible speakers. This thesis investigates machine learning methods for determining the speaker. The AOLME dataset that was used contains 758 samples totaling 894.4 seconds. Each is taken from a noisy classroom environment, focusing on five speakers - any one of whom could be active in a given sample - lasting an average of 1.2 seconds. …

Wirelessly Powering A Sea Of Sensors For Perimeter Security Applications, Ian River Chavez

Electrical and Computer Engineering ETDs

his thesis presents an innovative application of Inductive Power Transfer (IPT) technology for perimeter security systems. The approach leverages the physical properties of IPT to detect intrusions by monitoring voltage changes in wirelessly powered sensor nodes, which can double as components of an intrusion detection system. Disturbances in node orientation, indicative of potential intrusions, alter the sensor node’s resonant frequency and create measurable voltage shifts. This study explores the concept in-depth, from the analysis of resonant inductive coupling in various resonant inductive modes, to the design of transmit loops, sensor nodes, and the techniques required to ensure optimum power transfer. …

Noise-Resilient And Adaptive Distributed Control Techniques For Microgrids, Seyed Iman Habibi

Electrical and Computer Engineering ETDs

This dissertation focuses on addressing the critical tasks of secondary control in microgrids, particularly in the islanding operating mode. The presence of noise in sensors and communication links necessitates the design of a noise-resilient secondary control approach. In response, this dissertation introduces the Nonlinear Generalized Minimum Variance (NGMV) control approach into the islanded AC and DC microgrid's secondary control system. The effectiveness of the proposed approach is demonstrated through MATLAB simulations. Additionally, the dissertation presents an adaptive, model-free, and data-driven control approach for secondary voltage control in AC microgrids, addressing uncertainties. By employing Unfalsified Adaptive Control (UAC), the approach selects …

Comparison Of Random Coupling Model To Stochastic Dyadic Green’S Function When Coupling To A Distributed Port, Evelyn Anne Dohme

Electrical and Computer Engineering ETDs

The Random Coupling Model (RCM) provides statistical representation of coupling between ports in a highly overmoded resonant cavity based on knowledge of radiation impedances of system ports and cavity properties. A recent variant of RCM, the Stochastic Dyadic Green’s Functions (S-DGF), provides the statistical distribution of fields in the cavity. By using Source Reconstruction Methods (SRM) to approximate equivalent surface currents, I hypothesized that the S-DGF can calculate the fields at their location, enabling a statistical estimate of the coupled power. Using nearfield radiation from simple patch antenna simulations and the SRM to estimate the equivalent fields and account for …