Electrical and Computer Engineering Commons^™

An Experimental Investigation Of Signal Processing Techniques For Vibration-Based Structural Health Monitoring In Residential Buildings Subjected To Base Excitation, Fedaa Ali

Electrical Engineering Theses

Coastal regions, particularly in the southeastern United States, are consistently confronted with the ongoing threat of hurricane-induced damage to their buildings. Consequently, there is a pressing need to concentrate efforts on the evaluation and prediction of structural integrity and reliability in such environments. This is paramount for minimizing losses and enhancing public safety in the face of these challenging climatic conditions. Current structural health monitoring systems are typically customized for specific buildings, rendering them excessively expensive and impractical for residential structures. This research presents a comprehensive study of signal processing techniques and damage detection for an economical yet efficient structural …

Etherealbreathing: A Holographic Biofeedback Game To Support Relaxation In Autistic Children, Arturo Morales Téllez, Isabel López Hurtado, Franceli L. Cibrian, Monica Tentori

Engineering Faculty Articles and Research

Biofeedback training for box breathing is becoming increasingly accessible due to advancements in consumer-grade breathing sensors. However, there is limited research on their design and applications for specialized populations. This study evaluates a novel biofeedback holographic game, EtherealBreathing, designed to support autistic children. In EtherealBreathing, children practice box breathing to collect virtual elements to maintain the Earth's balance, using a wearable sensor to measure chest expansion for breath detection. A deployment study with 20 autistic children revealed that EtherealBreathing effectively promotes box breathing, leading to better health-related outcomes, such as lowering participants’ heart and respiratory rates than traditional practices. Biofeedback …

Identifying Subject Bias In Wifi-Based Human Activity Recognition Evaluation Methods, Amany Elkelany, Robert J. Ross, Susan Mckeever

Conference papers

WiFi-based Human Activity Recognition (HAR) has emerged as a promising approach for monitoring and analysing human activities in a non-intrusive manner, leveraging WiFi signals for activity classification. Despite advancements, existing WiFi-based HAR research lacks consideration of subject (human) bias. This results in learning models performing well on individuals used in the training samples but failing to generalise to new/unseen subjects, in contrast to known good practices in machine learning. In this paper, we address this oversight directly by systematically examining the evaluation methodology for the WiFi-based HAR context. Specifically, we investigate the impact of Leave-One-Subject-Out Cross-Validation (LOSOCV) in a hybrid …

Towards Rare Event And Anomaly Prediction In Manufacturing: Bridging Methodological Gaps In Industrial Applications, Chathurangi Shyalika, Renjith Prasad, Ruwan Wickramarachchi, Amit Sheth

Publications

Rare event prediction is critical in industrial applications, including real-world Industry 4.0 applications. These events, defined by their low occurrence frequency, are often difficult to predict due to the skewed data distribution, which complicates modeling and evaluation. In our research, we provide a comprehensive review of current approaches to rare event prediction across four key dimensions: rare event data, data processing techniques, algorithmic approaches, and evaluation methodologies [1]. By analyzing diverse datasets with multiple modalities, including numerical, image, text, and audio, we categorize the primary challenges and present the gaps in current research. Specifically, we present three novel research contributions …

Reevaluating The Opportunity For Wind Energy In Kentucky: Advancing Technology, Changing Economics, And Generation Complementarity, Lawrence E. Holloway, Aron Patrick, Dan M. Ionel

Electrical and Computer Engineering Faculty Publications

Recent developments in wind turbine technology, new wind resource data, and new federal tax credits for renewable energy are increasing the suitability of wind electricity generation in Kentucky. In 2022, Kentucky had 68% of its electricity from coal and in 2023 was one of eight U.S. states with no utility-scale wind generation. In the past, the state has been viewed as being generally unsuitable for wind power generation. While wind is not the most economic resource in Kentucky, all states bordering the Commonwealth have wind power. Wind power generation in Kentucky appears increasingly likely in the coming decades to play …

Interdigitated Gear-Shaped Screen-Printed Electrode Using G-Pani Ink For Sensitive Electrochemical Detection Of Dopamine, Pritu P. Sarkar, Ridma Tabassum, Ahmed Hasnain Jalal, Ali Ashraf, Nazmul Islam

Electrical and Computer Engineering Faculty Publications

In this research, a novel interdigitated gear-shaped, graphene-based electrochemical biosensor was developed for the detection of dopamine (DA). The sensor’s innovative design improves the active surface area by 94.52% and 57% compared to commercially available Metrohm DropSens 110 screen-printed sensors and printed circular sensors, respectively. The screen-printed electrode was fabricated using laser processing and modified with graphene polyaniline conductive ink (G-PANI) to enhance its electrochemical properties. Fourier Transform Infrared (FTIR) Spectroscopy and X-ray diffraction (XRD) were employed to characterize the physiochemical properties of the sensor. Dopamine, a neurotransmitter crucial for several body functions, was detected within a linear range of …

Dynamic Resource Allocation For Beyond 5g Networks Through Uav-Assisted Communication, Iman Adel Sami

Thesis/ Dissertation Defenses

In response to the surging demand for cellular services, driven partly by the post-COVID-19 era, network operators are grappling with the challenge of enhancing network capacity and throughput. Fifth-generation mobile technology and beyond (6G) with techniques like network slicing are emerging as promising solutions for faster data speeds and improved network performance across various devices. In network slicing, distributing radio resources between different virtual operators (slices) is often performed in a static manner. Therefore, due to the dynamic user demand, the users of one virtual operator could suffer from a lack of resources, whereas another virtual operator with overlapping cells …

Deciphering Mechanochemical Influences Of Emergent Actomyosin Crosstalk Using Qcm‑D, Emily M. Kerivan, Victoria N. Amari, William B. Weeks, Leigh H. Hardin, Lyle Tobin, Omayma Y. Al Azzam, Dana N. Reinemann

Faculty and Student Publications

Purpose: Cytoskeletal protein ensembles exhibit emergent mechanics where behavior in teams is not necessarily the sum of the components’ single molecule properties. In addition, filaments may act as force sensors that distribute feedback and influence motor protein behavior. To understand the design principles of such emergent mechanics, we developed an approach utilizing QCM-D to measure how actomyosin bundles respond mechanically to environmental variables that alter constituent myosin II motor behavior.

Methods: QCM-D is used for the first time to probe alterations in actin-myosin bundle viscoelasticity due to changes in skeletal myosin II concentration and motor nucleotide state. Actomyosin bundles were …

Applying Positive Unlabeled Learning Techniques And Using The Kullback-Leibler Divergence To Improve Geothermal Surveying Assessments, Martín Thomas Rodriguez

Dissertations and Theses

As we face the current climate crisis, the discovery of geothermal energy resources has the potential to greatly reduce our dependence on fossil fuels worldwide. However, the development of any new energy infrastructure is expensive and depends on the willingness of energy agencies and developers to make initial investments based on calculated risk measures. One such measure, called geothermal favorability, is the likelihood that a site has conditions favorable for geothermal systems containing recoverable energy potential. Its prediction from existing geophysical datasets proves to be a nontrivial task. The prediction of geothermal favorability can be framed as a binary classification …

Propagation Modeling Of Terahertz Reflections And Reflector Design For Mimo Channel, Thanh Ngoc Dan Le

Dissertations and Theses

Wireless communication has transformed connectivity, enabling seamless access across devices without physical constraints. Terahertz (THz) frequencies, ranging from 100 GHz to 10 THz, promise high-bandwidth channels crucial for applications like IoT and virtual reality. However, deploying THz communication faces challenges due to significant propagation limitations such as high attenuation and environmental absorption. The motivation behind this research is to develop a comprehensive understanding of THz propagation dynamics and utilize reflective surfaces to create multipath environments for an improvement in the capacity performance of MIMO channels.

This research investigates the potential of Multi-Input Multi-Output (MIMO) channels at THz frequencies to overcome …

Medium-Entropy Engineering Of Magnetism In Layered Antiferromagnet CuXNi2(1-X)CrXP2S6, Dinesh Upreti, Rabindra Basnet, M. M. Sharma, Santosh Karki Chhetri, Gokul Acharya, Md Rafique Un Nabi, Joshua Sakon, Mourad Benamara, Mansour Mortazavi, Jin Hu

Physics Faculty Publications and Presentations

Antiferromagnetic van der Waals-type M₂P₂X₆ compounds provide a versatile material platform for studying 2D magnetism and relevant phenomena. Establishing ferromagnetism in 2D materials is technologically valuable. Though magnetism is generally tunable via a chemical way, it is challenging to induce ferromagnetism with isovalent chalcogen and bimetallic substitutions in M₂P₂X₆. Here, we report co-substitution of Cu¹⁺ and Cr³⁺ for Ni²⁺ in Ni₂P₂S₆, creating Cu_xNi_2(1-x)Cr_xP₂S₆ medium-entropy alloys spanning a full substitution range ( …

Microwave Flow Cytometer For Single Cell Detection, Differentiation, And Drug Effect Study, Neelima Dahal

All Dissertations

New methods to rapidly detect and identify pathogens in patients’ blood are needed for timely disease treatment. In this work, a tunable microwave interferometer was used to measure single Candida cells of C. albicans, C. tropicalis, C. parapsilosis, and C. krusei at multiple frequencies between 0.265 GHz and 7.76 GHz. A Quadratic Discriminate Analysis was used to classify Candida species with an accuracy of 0.875. Likewise, a microwave device was used to measure single Escherichia coli cells of B and K-12 strains at multiple frequencies between 500 MHz and 8 GHz. A LightGBM model was developed to …

A Fiber Optics Based Surface Enhanced Raman Spectroscopy Sensor For Chemical And Biological Sensing, Jiayu Liu, Bohong Zhang, Amjed Abdullah, Sura A. Muhsin, Jie Huang, Mahmoud Almasri

Electrical and Computer Engineering Faculty Research & Creative Works

This paper investigates an innovative surface-enhanced Raman scattering (SERS) sensor developed on a side-polished multimode optical fiber core. The optical fiber was integrated into specifically designed 3-dimensional printed mold, where manual polishing of the fiber took place. Microsphere Photolithography (MPL) techniques was employed to pattern periodic nanoantenna arrays on the polished surface, incorporating multiple disk diameters at a fixed periodicity. Subsequent gold deposition/lift-off were carried out to transfer the pattern from the photoresist to the fiber core, resulting in highly periodic hexagonal closed pack (HCP) arrays of nano disks. These arrays can significantly enhance the SERS signal intensity compared to …

Exploring Smart Thermostat, Don P. Dang

2024 Fall Honors Capstone Projects - Archive

This study examines the security, privacy, and compatibility challenges associated with smart thermostats in smart home systems. Smart thermostats, as part of the growing Internet of Things (IoT) ecosystem, face vulnerabilities such as unauthorized access, data breaches, and inconsistent security protocols. Using a mixed-methods approach, this research evaluates encryption techniques, communication protocols (Zigbee, Z-Wave, Wi Fi), and user behaviors that impact system security and efficiency. Key findings indicate that 35% of users are concerned about hacking risks, while 25% express data privacy concerns. Many users lack awareness of security measures, such as firmware updates and password management, which increases vulnerabilities. …

Learning To Represent Temporal Dynamics And Generative Factors For Intelligent Visual Navigation, Sahand Khoshdel

All Theses

Visual navigation systems are crucial in various applications, including autonomous driving, unmanned aerial systems (UAS), and industrial automation. For these systems to operate efficiently in dynamic environments, they must not only interpret complex surroundings but also anticipate changes over time. Temporal prediction—forecasting environmental changes like moving obstacles or shifting lighting conditions—enables navigation systems to act proactively, enhancing both safety and performance. This dissertation investigates representation learning methods both as a backbone feature extractor for RL agents as well as a proxy for systems oriented for Explainable AI (XAI). Two main projects are presented as case studies to achieve the aforementioned …

Leveraging P4 Programmable-Hardware Switches For In-Network Pmu Packet Recovery, Evan Michael Bonar

Electrical Engineering and Computer Science Undergraduate Honors Theses

Phasor Measurement Unit (PMU) systems are essential for real-time power grid monitor- ing but often face data loss due to network delays, equipment malfunctions, or transmis- sion errors. Traditional centralized recovery solutions introduce significant latency and scalability challenges. This thesis presents a P4-based in-network recovery mechanism that embeds detection and recovery directly into the data plane of P4-enabled programmable switches, significantly reducing recovery time and infrastructure complexity. Using the Aurora 610 switch, the system detects missing packets via sequence number analysis and recovers magnitudes with an efficient register-based algorithm.

Evaluation demonstrates high accuracy and low latency, achieving a mean absolute …

Enhancing Webtas: From An Atam Simulator To A Developmental Environment, Elizabeth G. Schmidt

Electrical Engineering and Computer Science Undergraduate Honors Theses

As interest in a niche research area, like the abstract Tile Assembly Model (aTAM), grows it is crucial to ensure that simulation tools are accessible and user-friendly for a broad audience. Existing resources can pose challenges for less experienced users, highlighting the need for enhancements that improve usability and functionality. To address these issues, key upgrades to the current online simulation platform, WebTAS, were implemented, including breakpoint functionality and nondeterminism checks, alongside features such as XML file integration, image capturing, and simulation view resets. These enhancements collectively elevate the platform from a basic learning tool to a comprehensive environment for …

Artificial Intelligence Computational Techniques Of Flywheel Energy Storage Systems Integrated With Green Energy: A Comprehensive Review, Abdelmonem Draz, Hossam Ashraf, Peter Makeen

Electrical Engineering

In recent years, the operation of the electric power grid has become more efficient and resilient due to the integration of renewable energy sources (RESs). Solar and wind energy are being incorporated aggressively into the main grid, while other RESs like biomass and geothermal energy are also on the rise. However, the intermittent nature of these RESs necessitates the use of energy storage devices (ESDs) as a backup for electricity generation such as batteries, supercapacitors, and flywheel energy storage systems (FESS). This paper provides a thorough review of the standardization, market applications, and grid integration of FESS. It examines the …

A Secure Cross-Domain Authentication Scheme Based On Threshold Signature For Mec, Lei Chen, Chong Guo, Bei Gong, Muhammad Waqas, Lihua Deng, Haowen Qin

Research outputs 2022 to 2026

The widespread adoption of fifth-generation mobile networks has spurred the rapid advancement of mobile edge computing (MEC). By decentralizing computing and storage resources to the network edge, MEC significantly enhances real-time data access services and enables efficient processing of large-scale dynamic data on resource-limited devices. However, MEC faces considerable security challenges, particularly in cross-domain service environments, where every device poses a potential security threat. To address this issue, this paper proposes a secure cross-domain authentication scheme based on a threshold signature tailored to MEC’s multi-subdomain nature. The proposed scheme employs a (t,n) threshold mechanism to bolster system resilience and security, …

Clusteredlog: Optimizing Log Structures For Efficient Data Recovery And Integrity Management In Database Systems, Mariha Siddika Ahmad, Brajendra Panda

Electrical Engineering and Computer Science Faculty Publications and Presentations

In modern database systems, efficient log management is crucial for ensuring data integrity and facilitating swift recovery from potential data corruption or system failures. Traditional log structures, which store operations sequentially as they occur, often lead to significant delays in accessing and recovering specific data objects due to their scattered nature across the log. ClusteredLog addresses the limitations of traditional logging methods by implementing a novel logical organization of log entries. Instead of simply storing operations sequentially, it groups related operations for each data item into clusters. As a result, ClusteredLog enables faster identification and recovery of damaged data items …

Perceptual Hash Based Content Matching, Nicholas Daniel Chenevey

Master's Theses

The proliferation of video content and AI generated imagery has introduced a number of new challenges in content identification and verification. The ability to trace content back to its source has become a critical problem as video content increases both naturally and synthetically through AI generation. This thesis provides the design, analysis, and experimental verification for a perceptual hash based framework aimed at addressing these challenges. Perceptual hashing is a method for encoding the visual content of images into compact and easily comparable binary strings. This process is used as the foundation for content matching in videos and source verification …

Photophoretic Optical Particle Trapping Improvements Using Beam Reflection, Ian A. Garcia, Xiaomin Jin Phd., Kun Hua Phd.

Master's Theses

Current research has shown that photophoretic optical trapping (POT) is a promising method for creating true three-dimensional holograms. A landmark study by Smalley et. al. at BYU was able to generate a full hologram within a 2 cm edge cube with remarkable success. However, a key drawback to this method is its poor ability to hold trapped particles within the focal point of the laser for an extended period of time. An investigation from our group presented at SPIE Photonics West 2023 sought to improve these results by varying the focal length of the trapping and the wavelength of the …

Security Of Mobile Radiological Sources: Overview Of Industry Applied Technologies, Ann M. Archer, Ashleigh Wickham

International Journal of Nuclear Security

Small radiological sources used in industrial settings recurrently require transit between job sites. Securing these sources, while stationary, can be addressed with standard security approaches and equipment. Transport of these sources increases the risk and complexity of managing and maintaining control of these sources. Implementing methodologies to securely monitor and locate sources improves response and resolution of anomalous events during transit. The Mobile Source Transit Security (MSTS) system was developed to improve security and provide situational awareness of these mobile sources throughout their job cycle. The MSTS development effort focused on creating a set of systems that could be successfully …

Ellipticity-Controlled Exceptional Points From Nanoscale Metasurfaces, Benjamin Goldberg

McKelvey School of Engineering Graduate Student Theses & Dissertations

Precise control over light polarization is critical for advancing technologies in telecommunica- tions, quantum computing, and image sensing. However, existing methods for manipulating polarization around exceptional points in non-Hermitian systems, have exclusively focused on circular polarization and work with reflected light. To address this limitation, we de- velop a novel metasurface platform with high-Q resonators that enables tunable control of polarization exceptional points across arbitrary ellipticity for transmitted light. Our design uses orthogonally polarized guided mode resonators in a two-layer silicon metasurface, where careful tuning of the dipolar guided mode resonances (DGMRs) and layer spacing allows us to control the …

Ohmic Contacts For Fabrication Of Sic Cmos Devices, Anthony Di Mauro

Graduate Theses and Dissertations

Today’s world of electronics is dominated by semiconductor devices which utilize silicon as their substrate material. Though, silicon is not ideal for semiconductor devices in high-voltage or high-temperature applications. Additionally, the efficiency of silicon devices becomes drastically reduced in nonideal operating conditions. Therefore, finding alternatives to silicon?based devices has been a topic for decades now. A few great candidates to replace silicon devices for said applications include Silicon Carbide (SiC), Gallium Nitride (GaN), and Aluminum Arsenide (AlAs). SiC has grown its reputation as the best candidate, when compared to other potential alternatives, due to its wide bandgap, high operating frequency, …

Gate Driver Design In High-Temperature Cmos Process For Heterogeneous Integration Inside Sic Power Module, Khandoker Asif Faruque

Graduate Theses and Dissertations

The shift toward electrification in transportation, including electric and hybrid vehicles, presents challenges for power electronic converters. Silicon Carbide (SiC) power devices are promising due to their high efficiency, temperature tolerance, and reduced losses compared to traditional silicon devices. However, their use is hindered by issues such as parasitic capacitances and gate inductances, which can lead to voltage spikes and stress on the device gate oxide, hence impacting converter reliability. Increasing gate resistance can help manage these issues, but it reduces switching speed and increases losses. Snubber circuits can mitigate switching stress but add extra components, reducing efficiency. Active gate …

A Cmos Ldo Voltage Regulator For Low Power Applications, Nicolaus Vail

Graduate Theses and Dissertations

This thesis presents the design, simulation, layout, and testing of a low dropout linear voltage regulator (LDO) in a 180 nm CMOS process. The LDO is intended for use in low-power, battery-operated applications, and it has an adjustable output for a variety of different implementations. It can supply up to 100 mA of current, which is enough to power many small electronic circuits. It has a dropout voltage of 150 mV, and it consumes less than 200 μA of current during operation, which is on par with many commercial regulators. The line regulation is also comparable to commercially available LDOs, …

Reinforcement Learning-Based Optimal Control Of Uncertain Nonlinear Systems, Miguel Garcia, Wenjie Dong

Electrical and Computer Engineering Faculty Publications

This paper considers the optimal control of a second-order nonlinear system with unknown dynamics. A new reinforcement learning based approach is proposed with the aid of direct adaptive control. By the new approach actor-critic reinforcement learning algorithms are proposed with three neural network approximation. Simulation results are presented to show the effectiveness of the proposed algorithms.

Surgical Suturing Skill Assessment Using Estimated Hand Roll Angle From A Deep-Learning Computer Vision Algorithm, Jianxin Gao, Amir Mehdi Shayan, Simar P. Singh, Joe Bible, Ravikiran Singapogu, Richard E. Groff

Publications

This paper proposes a deep-learning computer vision algorithm to estimate hand roll angles for metric-based assessment of surgical suturing skills. The number of rolls metric, previously calculated directly from IMU data, counts the number of hand roll reversals during a single suture. To calculate this metric using computer vision, we apply a deep-learning algorithm that can reliably estimate hand roll angles after training on suturing videos collected on the SutureCoach simulator. Results show that the estimation accuracy of the deep-learning algorithm is robust to different video backgrounds. The number of rolls metrics were used to analyze suturing performance in the …

Myofibroblast Targeted Liposomes For The Treatment Of Skin Fibrosis, Elfa Beaven

Open Access Theses & Dissertations

Continuous overactivation of myofibroblasts leads to excessive deposition of profibrotic proteins, which in turn causes tissue stiffness and, ultimately, organ failure. One of those proteins, Cadherin-11 (CDH11), is reported to be overexpressed in the tissue of fibrotic skin, specifically on myofibroblasts. Similarly, chronic inflammation drives fibrosis progression in autoimmune-related illnesses like systemic sclerosis (SSc). Therefore, it is hypothesized that CDH11 could be a target for cell-specific delivery of antifibrotic therapies to fibrotic skin tissue. Here, a CDH11 peptide conjugated liposome loaded with Tofacitinib, a JAK inhibitor, was developed to understand the potential of targeted therapies to treat skin fibrosis. The …