Engineering Commons^™

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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. …

Spectrum Optimization For Advanced Air Mobility Communications Using Deep Reinforcement Learning., Rafael D. Apaza

Electronic Theses and Dissertations

As aviation operations expand and new participants enter the National Airspace System (NAS), the demand for aeronautical communications will experience a significant rise. This surge is propelled by increased air travel and the emergence of Urban Air Mobility (UAM) operations, a subset of Advanced Air Mobility (AAM). UAM aims to facilitate intra-city transportation of people and cargo utilizing remotely piloted aircraft capable of electric vertical takeoff and landing operations. The growing dependence on efficient wireless communication systems underscores the critical importance of intelligent spectrum allocation and effective airspace management to ensure safe, seamless, and technologically advanced air operations. However, the …

Development Of A Square Wave Voltage Field-Oriented Controller For A Linear Vapor Compressor., Thomas Everson

Electronic Theses and Dissertations

In this thesis, a novel control strategy for an inverter-driven linear compressor system is proposed in which the overall electrical losses of a coupled inverter-linear motor system are reduced through the use of a modified square wave inverter modulation scheme to minimize inverter switching losses at the expense of a modest increase in conduction losses. The controller is based on a single-phase field-oriented control strategy, and to achieve the FOC control objectives, the fundamental and dc components of the applied square wave voltage are matched to the corresponding values requested by the current controller. To validate the efficiency improvements offered …

Co-Emulation Of Robotics And Software-Defined Radio Based 5g Wireless Communications., Bhaskara Venkata Raju Garuda

Electronic Theses and Dissertations

The convergence of robotics and 5G wireless communication technologies has opened new avenues for real-time, dynamic robotic applications. This dissertation introduces a novel framework that integrates the Robot Operating System (ROS), Software-Defined Radios (SDRs), and 5G wireless networks to achieve seamless coemulation of robotic systems. The research emphasizes the unique features of 5G, such as ultra-low latency and high throughput, which enable critical applications like remote surgery, industrial automation, and autonomous vehicles. The methodology combines ROS for robotic control, SDRs for programmable communication channels, and 5G testbeds for high-speed, reliable data transmission. The experimental evaluation focuses on both position-based and …

Open-Source Cubesat Flight Board, Braydon M. Burkhardt

Electrical Engineering

The Helmsman Flight Board is an open-source main flight computer and electrical power system for educational and entry-level CubeSats. The board incorporates commercial off-the-shelf (COTS) components in conjunction with simplified monitoring and management circuitry, supporting easy adoption, modifiability, and affordability while crucially enabling the emerging aerospace industry’s rapid ‘design-build-test’ methodology in student satellite teams. Its design includes essential CubeSat subsystems such as battery management, command and data handling, attitude determination, on-board processing, and is built to support real-time embedded operating systems. Key features include an Arm Cortex-M7 based STM32, radiation-resistant memory for OS storage, bulk Flash memory, real-time clock, two …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

Developing A Bioengineered Nanoparticle For Improving Oral Absorption Of Iron Supplements., Mila Biswas

Open Access Theses & Dissertations

Iron deficiency (ID) and iron deficiency anemia (IDA) are widespread nutritional issues, affecting millions globally. Conventional iron supplements often suffer from low absorption rates and gastrointestinal side effects. We investigated β-glucan derivatives as potential carriers to enhance iron absorption and mitigate these drawbacks. This study explored a novel β-glucan-based carrier system loaded with ferrous sulfate heptahydrate. In-vitro studies demonstrated sustained iron stability for over six hours in simulated gastric fluids due to the carrier's affinity for stomach mucin. Particle size analysis and scanning electron microscopy (SEM) images confirmed this specific binding. Additionally, drug release studies revealed a pH-dependent release profile, …

Chipless 3d Microfluidic Rf Sensing, Sheikh Dobir Hossain

Open Access Theses & Dissertations

Effective management of the cold chain is essential to uphold the quality and safety of products vulnerability to physical factors like temperature, humidity, pressure, etc., including perishable foods, pharmaceuticals, and vaccines. Chipless Radio Frequency Identification (RFID) sensors have become increasingly favored as a viable technology for tracking, inventory, and sensing industries due to their wireless and non-line of sight (NLOS) situations, straightforward fabrication, cost efficiency, and adaptability to challenging environmental conditions. However, there is still a need for advancements in RFID sensors to make them promise for cold chain applications. Integration of flexibility and non-volatile memory into the existing RFID …

Low-Cost Vehicle Controller Testing System, Kevin R. Jung

Electrical Engineering

This project aims to create a system to facilitate easier evaluation of PCBs designed for low-voltage vehicle applications with an emphasis on accessibility for student teams in collegiate design series' such as Formula SAE. Student teams or smaller vehicle electronics manufacturers often need to verify designs and validate functionality during both development and manufacturing. An inexpensive, small, and portable, yet capable, system for taking measurements and simulating inputs would allow designers to put their boards into vehicle-representative conditions and environments without needing to connect to actual vehicle hardware. Additionally, while systems exist off-the-shelf that could fulfill the requirements needed by …

Debtor Eligibility Prediction Using Deep Learning With Chatbot-Based Testing, Reski Noviania, Enny Itje Sela, Luther Alexander Latumakulita, Steven R. Sentinuwo

Knowledge Engineering and Data Science

Predicting debtor eligibility is essential for effective risk management and minimizing lousy credit risks. However, financial institutions face challenges such as imbalanced data, inefficient feature selection, and limited user accessibility. This study combines Recursive Feature Elimination (RFE) and Deep Learning (DL) to improve prediction accuracy. It integrates a chatbot interface for user-friendly testing. RFE effectively identifies critical features, while the DL model achieves a validation accuracy of 97.62%, surpassing previous studies with less comprehensive methodologies. The chatbot's novel design not only ensures accessibility but also enhances user engagement through flexible input options, such as approximate values, enabling non experts to …

Optimal Strategy For Handling Unbalanced Medical Datasets: Performance Evaluation Of K-Nn Algorithm Using Sampling Techniques, Yulita Salim, Aulia Putri Utami, Abdul Rachman Manga, Huzain Azis, Fadhila Tangguh Admojo

Knowledge Engineering and Data Science

This study addresses the critical role of medical image classification in enhancing healthcare effectiveness and tackling the challenges of imbalanced medical datasets. It focuses on optimizing classification performance by integrating Canny edge detection for segmentation and Hu-moment feature extraction and applying oversampling and undersampling techniques. Five diverse medical datasets were utilized, covering Alzheimer’s and Parkinson’s diseases, COVID-19, brain tumours, and lung cancer. The K-Nearest Neighbors (K-NN) algorithm was implemented to enhance classification accuracy, aiming to develop a more robust framework for medical image analysis. The evaluation, conducted using cross-validation, demonstrated notable improvements in key metrics. Specifically, oversampling significantly enhanced lung …

A Hierarchical Density-Based Spatial Clustering Of Applications With Noise (Hdbscan) Approach For Identifying Potential Villages In Buleleng Regency, Dina Nur Amalina, Achmad Fauzan

Knowledge Engineering and Data Science

Buleleng Regency, located in Bali Province, possesses diverse village potential, including agricultural production and tourist attractions. However, this potential has not been fully optimized. Therefore, it is important to enhance village potential by clustering villages based on their specific characteristics to identify and prioritize those requiring special attention. This approach aims to promote equitable village development and reduce poverty levels. This study clusters villages in Buleleng Regency based on their potential using the Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) method. The data utilized in this study comprises village potential data obtained from the Buleleng Regency Statistics Office …