Open Access. Powered by Scholars. Published by Universities.®

Digital Commons Network™

Open Access. Powered by Scholars. Published by Universities.®

Discipline
Institution
Keyword
Publication Year
Publication
Publication Type
File Type

Articles 127501 - 127530 of 1806383

Full-Text Articles in Entire DC Network

Learning Positive Deviance Techniques: How Non-Conformity To Vote-Buying Is Practiced And Its Outcomes, The Ugandan Context, Collins Kwarisima Jan 2025

Learning Positive Deviance Techniques: How Non-Conformity To Vote-Buying Is Practiced And Its Outcomes, The Ugandan Context, Collins Kwarisima

Electronic Theses and Dissertations

This research has investigated the use of positive deviance or exemplary behavior as an innovative approach to addressing political corruption, specifically the vote-buying practice in Uganda. To understand the techniques of positive deviance in vote-buying, this study was guided by the main research question: How is non-conformity to vote-buying practiced, and what are its outcomes? Individual and focus group interviews were utilized to collect qualitative data from 40 respondents (voters and political leaders) who deter the vote-buying practice in Rukungiri District, Western Uganda. With the help of community gatekeepers, the study followed the inclusion criteria to identify voters and political …

Go to article

Developing Proportional Hazards Mixture Cure Models And Predicting Risk For Persons With End-Stage Kidney Disease, Nathan Meyer Jan 2025

Developing Proportional Hazards Mixture Cure Models And Predicting Risk For Persons With End-Stage Kidney Disease, Nathan Meyer

Electronic Theses and Dissertations

Traditional survival analysis techniques assume that all individuals will eventually experience the event of interest. This is as opposed to allowing for a subset of cured individuals. Hence, we consider a mixture cure model that can allow a subset of people to be cured of the disease and will never experience the event of interest. This gives a more accurate interpretation of survivability by analyzing both the shortand long-term effects of a set of variables on the individuals’ survival probabilities. However, the cure status is considered an unknown variable. Thus, the expectationmaximization algorithm is required to estimate this latent variable …

Go to article

What Do We Get Out Of Our Entertainment? Empirically Determining The Differences Between Narrative Engagement And Flow Using Video Games, Lars Wagener Jan 2025

What Do We Get Out Of Our Entertainment? Empirically Determining The Differences Between Narrative Engagement And Flow Using Video Games, Lars Wagener

Electronic Theses and Dissertations

Immersion is an important aspect of entertainment media because it both drives the use of media and heightens one’s experience with that media (Nilsson et al., 2016). There are three core aspects of immersion. These aspects are (1) narrative engagement, (2) flow, and (3) enjoyment. This study set out to determine whether these aspects are statistically distinct from one another when observed in video games. The result indicated that these aspects were distinct from one another when examined through a structural equation model. This indicates that creating an overarching immersion variable that combines the different aspects of immersion may not …

Go to article

A Multifactorial Approach To Improve Piglet Health And Survival, Aryeri Stephanie Bardales Castellanos Jan 2025

A Multifactorial Approach To Improve Piglet Health And Survival, Aryeri Stephanie Bardales Castellanos

Electronic Theses and Dissertations

Pre-weaning mortality (PWM) remains a significant challenge in modern swine production systems, particularly in the context of hyper prolific sows. Although genetic selection has successfully increased litter sizes, these advancements have also intensified physiological stress on sows and increased the vulnerability of neonatal piglets. The majority of PWM occurs within the first 72 hours postpartum, with crushing by the sow as the leading cause of death. Additionally, iron deficiency anemia remains one of the most widespread nutritional disorders in piglets, further compromising survival, immune function, and growth. This thesis adopts a multifactorial approach to evaluate two management interventions aimed at …

Go to article

Impact Of Automated Controlled Tile Drainage On Field Discharge Water, Soil Moisture, And Crop Yield In Southeastern South Dakota, Joshua Becker Jan 2025

Impact Of Automated Controlled Tile Drainage On Field Discharge Water, Soil Moisture, And Crop Yield In Southeastern South Dakota, Joshua Becker

Electronic Theses and Dissertations

Automated controlled tile drainage is an innovative approach to water management, using dynamic weir settings programmed to drain water out of the tile system if it encroaches into the root zone at pre-programmed depths and duration. While past studies have indicated potential yield and water quality benefits of controlled drainage, there has been very little research into the performance of automated controlled drainage. In addition to overall performance, there is a gap in knowledge of management settings to optimize yield and water quality benefits. Two experiments, one plot-scale and one modeling, were conducted to assess the impact of automated controlled …

Go to article

Large Scale Crop Damage Mapping Using Optical And Sar Satellite Data Fusion And Deep Learning, Santosh Subedi Jan 2025

Large Scale Crop Damage Mapping Using Optical And Sar Satellite Data Fusion And Deep Learning, Santosh Subedi

Electronic Theses and Dissertations

No abstract provided.

Go to article

Exploring The Role Of Clinical And Social Factors In Predicting All-Cause Mortality In End-Stage Kidney Disease Patients: A Machine Learning Framework, Addy Smith Jan 2025

Exploring The Role Of Clinical And Social Factors In Predicting All-Cause Mortality In End-Stage Kidney Disease Patients: A Machine Learning Framework, Addy Smith

Electronic Theses and Dissertations

No abstract provided.

Go to article

Mechanisms Leading To Cell Survival Through Membrane Repair In Pyroptosis, Prafulla Shrestha Jan 2025

Mechanisms Leading To Cell Survival Through Membrane Repair In Pyroptosis, Prafulla Shrestha

Electronic Theses and Dissertations

No abstract provided.

Go to article

Balanced Benchmarking Of Zero-Shot And Rag Approaches For Biomedical Term Normalization, Thanh Son Do, Daniel B. Hier, Tayo Obafemi-Ajayi Jan 2025

Balanced Benchmarking Of Zero-Shot And Rag Approaches For Biomedical Term Normalization, Thanh Son Do, Daniel B. Hier, Tayo Obafemi-Ajayi

Electrical and Computer Engineering Faculty Research & Creative Works

Normalization of medical concepts to an ontology is a key aspect of the natural language processing of biomedical text. It enables the mapping of medical expressions to standardized ontology terms and their identifiers, thereby enhancing the interoperability and computability of medical concepts. Although large language models (LLMs) can identify and standardize medical terms, they may struggle to accurately map ontology terms to their corresponding ontology identifiers. These challenges arise from the stochastic nature of LLMs, their limited exposure to uncommon ontology identifiers during training, and their lack of an integrated lookup mechanism. We generated test sets of synthetic terms to …

Go to article

Enhanced Continual Reinforcement Learning-Based Output Feedback Control Of Heterogeneous Quadrotors Formation, Ehsan Soleimani, S. Jagannathan Jan 2025

Enhanced Continual Reinforcement Learning-Based Output Feedback Control Of Heterogeneous Quadrotors Formation, Ehsan Soleimani, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a unified framework for the safe and optimal control of heterogeneous quadrotor unmanned aerial vehicles (QUAVs) in formation, enabling multitask missions without requiring precise system dynamics. To address partial state observability, a multilayer neural network (MNN) observer is designed to estimate unmeasured states. Reinforcement learning (RL) is employed for optimal control utilizing an MNN ensuring adaptability. Barrier Lyapunov Functions (BLFs) are integrated into the RL framework to enforce safety by maintaining QUAVs within predefined constraints. An enhanced continual learning (ECL) method is proposed to improve the adaptability of MNNs. This method enables effective multitask learning while mitigating …

Go to article

Spatially Distributed Optical Fiber Sensing With Weak Fiber Bragg Grating Arrays Based On Microwave Photonics, Wassana Naku, Osamah Alsalman, Chen Zhu Jan 2025

Spatially Distributed Optical Fiber Sensing With Weak Fiber Bragg Grating Arrays Based On Microwave Photonics, Wassana Naku, Osamah Alsalman, Chen Zhu

Electrical and Computer Engineering Faculty Research & Creative Works

Fiber Bragg gratings (FBGs) have been one of the most widely used optical fiber sensors in both scientific and industrial applications due to their unique advantages of high sensitivity, ease of signal transduction, and capabilities for remote operation and multiplexing. However, the majority of sensing systems based on FBGs can only achieve quasi-distributed sensing along the fiber under test, leaving dark zones in between discrete FBG elements. In this work, we propose and demonstrate a microwave photonics enabled approach for the interrogation of cascaded FBGs to achieve spatially distributed sensing. The core of the system includes an incoherent optical frequency-domain …

Go to article

Benchmarking Deep Learning Architectures For Ecg-Based Multi-Label Heart Disease Prediction Using Mimic-Iv Database, Eyiara Oladipo, Sarwar Nazrul, Mohamed Nafea Jan 2025

Benchmarking Deep Learning Architectures For Ecg-Based Multi-Label Heart Disease Prediction Using Mimic-Iv Database, Eyiara Oladipo, Sarwar Nazrul, Mohamed Nafea

Electrical and Computer Engineering Faculty Research & Creative Works

Cardiovascular disease (CVD) is a leading cause of global mortality, accounting for an estimated 17.9 million deaths annually. CVD is broadly defined as a group of medical conditions influenced by modifiable or non-modifiable risk factors that affect the heart's ability to function properly. Machine learning (ML) has emerged as a powerful tool for analyzing complex medical data, aiding in early detection and accurate diagnosis of CVD and improving patient outcomes. Recent studies proposed various deep learning (DL) architectures for detecting CVD, yet there is a lack of robust benchmarks for comparing their performance on large-scale databases. In this work, we …

Go to article

Honey-Reram Enabled Sustainable Edge Ai System For Iot Applications, Jinhui Wang, Feng Zhao, Mohammad Rafeeq Khan, Md Mehedi Hasan Tanim, Zoe Templin, Harshvardhan Uppaluru Jan 2025

Honey-Reram Enabled Sustainable Edge Ai System For Iot Applications, Jinhui Wang, Feng Zhao, Mohammad Rafeeq Khan, Md Mehedi Hasan Tanim, Zoe Templin, Harshvardhan Uppaluru

Electrical and Computer Engineering Faculty Research & Creative Works

This paper is toward a promising solution to address the environmental sustainability challenge in computing by building brain-inspired and green non-Von Neumann systems with Resistive Random-Access Memory (ReRAM) made from natural organic materials, honey, for energy-efficient operation, renewable material resources, sustainable device manufacturing, and environmentally-friendly disposal. In this paper, honey-ReRAM and its arrays are firstly manufactured and tested. The resistance modulation mechanism of honey-ReRAM is analyzed and investigated. Then a Computing-in-Memory (CIM) architecture based on honey-ReRAM for edge AI and IoT applications is proposed and evaluated. The experimental results indicate that the proposed edge AI systems with the VGG8 and …

Go to article

Ethics Vs.. Regulation: Converging Frameworks For Trustworthy Human-Centered Ai In Biomedical Research, Tayo Obafemi-Ajayi, Tiffani J. Bright, Emily F. Wong, Donald Wunsch, Joan Peckham, Jason H. Moore Jan 2025

Ethics Vs.. Regulation: Converging Frameworks For Trustworthy Human-Centered Ai In Biomedical Research, Tayo Obafemi-Ajayi, Tiffani J. Bright, Emily F. Wong, Donald Wunsch, Joan Peckham, Jason H. Moore

Electrical and Computer Engineering Faculty Research & Creative Works

The accelerating impact of AI in biomedical research is driving significant advances in precision medicine. As these systems increasingly shape health outcomes, the imperative to develop trustworthy, reliable, and ethically grounded AI becomes more pressing, particularly in addressing concerns related to data integrity, patient safety, and equitable outcomes. While the potential of AI to transform biomedical research is clear, its responsible integration depends on more than technological capability. Ensuring that these systems are aligned with societal values requires a dual commitment: the operationalization of ethical principles throughout the AI life cycle and the establishment of robust regulatory mechanisms. Ethics provides …

Go to article

Case Report: Prominent Coronary Artery Flow In Fetuses With Congenital Heart Disease, Is It A Marker Of In Utero Distress?, Mohamed Aashiq Abdul Ghayum, Maria Kiaffas, Ashley Warta, Melanie Kathol, David Christopher Mundy, Kelsey Brattrud, Nitin Madan Jan 2025

Case Report: Prominent Coronary Artery Flow In Fetuses With Congenital Heart Disease, Is It A Marker Of In Utero Distress?, Mohamed Aashiq Abdul Ghayum, Maria Kiaffas, Ashley Warta, Melanie Kathol, David Christopher Mundy, Kelsey Brattrud, Nitin Madan

Manuscripts, Articles, Book Chapters and Other Papers

Prominent coronary artery (CA) flow observed on a fetal echocardiogram has been associated with fetal growth restriction and myocardial dysfunction. We present two cases with this finding, in the presence of congenital heart disease (CHD) and absence of growth restriction or myocardial dysfunction. Both the cases rapidly progressed to extremis, necessitating emergent delivery. Our cases highlight the importance of recognizing prominent CA flow in fetuses with CHD as a potential marker for in utero distress.

Go to article

Improved Optimal Tracking Of Uncertain Nonlinear Discrete-Time Systems Using Experience Replay, Maxwell Geiger, Sarangapani Jagannathan Jan 2025

Improved Optimal Tracking Of Uncertain Nonlinear Discrete-Time Systems Using Experience Replay, Maxwell Geiger, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper addresses the infinite horizon optimal tracking control problem for partially uncertain control-affine nonlinear discrete-time (DT) systems, where the control input dynamics are known. Multi-layer critic and actor neural networks (MNNs) are utilized for online estimation of the infinite horizon value function and optimal control input. The NN weights are tuned online using a direct temporal difference error (TDE)-driven learning approach, which modifies the singular values of the gradient with respect to the NN weights to accelerate their convergence. The critic NN uses a novel experience replay technique to improve sample efficiency without introducing biased TDEs and guarantee the …

Go to article

Multi-Model Safe Neuro-Optimal Output Tracking Control Of Autonomous Surface Vessels With Explainable Ai, Behzad Farzanegan, S. Jagannathan Jan 2025

Multi-Model Safe Neuro-Optimal Output Tracking Control Of Autonomous Surface Vessels With Explainable Ai, Behzad Farzanegan, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a safety-aware deep reinforcement learning (DRL)-based trajectory tracking control of autonomous surface vessels (ASVs). A multilayer neural network (MNN) observer estimates the ASV's state and uncertain dynamics. By utilizing the estimate state vector from the observer, a safety-aware DRL-based optimal policy is formulated using control barrier function (CBF) and Karush-Kuhn-Tucker (KKT) conditions. An actor-critic MNN with singular value decomposition (SVD)-based update mitigates vanishing gradients. To enhance adaptability, an online safe lifelong learning (SLL) scheme counters catastrophic forgetting across varying ASV dynamics. The Shapley Additive Explanations (SHAP) method identifies key features influencing the control policy. Simulations on an …

Go to article

Online Adaptive Optimal Tracking Control Of Uncertain Strict Feedback Discrete-Time Systems With Hardware Verification Using A Quadrotor Uav, Maxwell Geiger, S. Jagannathan Jan 2025

Online Adaptive Optimal Tracking Control Of Uncertain Strict Feedback Discrete-Time Systems With Hardware Verification Using A Quadrotor Uav, Maxwell Geiger, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This article considers the infinite time horizon optimal tracking control problem for discrete time (DT) partially uncertain strict feedback systems with application to quadrotor UAVs. First, the strict feedback DT system is transformed into an equivalent affine nonlinear DT system in terms of tracking error dynamics. The optimal tracking control problem is solved using an augmented system approach, where a horizon of future reference trajectory points are used in the augmented state, as compared to using a single point. The internal dynamics of the original nonlinear strict feedback system and the transformed affine system in terms of error dynamics are …

Go to article

Active Microwave-Thermographic Signal Reconstruction, Logan M. Wilcox, Emma T. Bohannon, Kristen M. Donnell Jan 2025

Active Microwave-Thermographic Signal Reconstruction, Logan M. Wilcox, Emma T. Bohannon, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Active microwave thermography (AMT) is a coupled electromagnetic (EM) and thermographic nondestructive testing and evaluation (NDT&E) technique. AMT utilizes a radiating EM source (e.g., an antenna) that induces dielectric/magnetic heating on a specimen under test (SUT) which is subsequently spatiotemporally imaged with an infrared (IR) camera. As all antennas have spatial variation in their radiated power density, a nonuniform thermal excitation results within (or on the surface of) the SUT. This nonuniform heating causes uncertainty in defect detection and has the potential to lead to false positives and/or negatives. To this end, thermographic signal reconstruction (TSR), a well-established thermographic signal …

Go to article

Aperture-Based Fss For Dielectric Thickness Sensing, Alexander Hook, Gage Donahue, Kristen M. Donnell Jan 2025

Aperture-Based Fss For Dielectric Thickness Sensing, Alexander Hook, Gage Donahue, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Frequency selective surfaces (FSSs) are planar arrays of patch- or aperture-based elements that have a particular transmissive or reflective response. As FSS performance is affected by changes in the local (to the FSS) environment, FSSs may be used to detect changes in strain, temperature, or nearby material (substructure) thickness, amongst other parameters. To this end, an aperture-based FSS can be considered as a sensor for substructure thickness monitoring for surface mounted sensing scenarios. An aperture-based design was selected due to its ability to operate in reflection mode (and hence a one-sided measurement) without the need for a conductive backplane. In …

Go to article

Dual Parameter Fss-Based Sensing For Structural Health Monitoring Applications, Swathi Muthyala Ramesh, Doyle T. Motes, Kristen M. Donnell Jan 2025

Dual Parameter Fss-Based Sensing For Structural Health Monitoring Applications, Swathi Muthyala Ramesh, Doyle T. Motes, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

frequency selective surfaces (FSSs) are periodic arrays of conductive elements or apertures that reflect and/or transmit incident electromagnetic energy. Their response depends on parameters, such as element shape, unit cell dimensions, dielectric properties, and the local environment, making them suitable for structural health monitoring (SHM) applications. This article presents a dual-parameter FSS-based sensor design capable of measuring small-scale uni-directional longitudinal strain (0%–0.5%) and temperature (23 ◦C–223 ◦C). The sensor integrates two-unit cells: 1) a patch-based cell on a thin substrate for strain sensing, offering enhanced strain transfer and superior sensitivity (~16–18 MHz/0.1%) and 2) a loop-based cell with a temperature-sensitive …

Go to article

Reinforcement Learning-Based Nonlinear Optimal Discrete-Time Control Of Power Systems, Vijay Kumar Singh, Behzad Farzanegan, S. Jagannathan Jan 2025

Reinforcement Learning-Based Nonlinear Optimal Discrete-Time Control Of Power Systems, Vijay Kumar Singh, Behzad Farzanegan, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a partially model-free adaptive optimal tracking control method for power systems, specifically targeting a synchronous generator connected through a reactive transmission line. By integrating the tracking error dynamics with reference trajectory dynamics, an augmented system is created. A discounted performance function is introduced to address the nonlinear tracking problem optimally. Unlike traditional methods that compute feedforward and feedback terms separately, the proposed approach calculates both simultaneously by minimizing the discounted performance function. The discrete-time tracking Bellman and Hamilton-Jacobi-Bellman (HJB) equations are derived, and a reinforcement learning (RL)-based technique is employed to solve the optimal policy online without …

Go to article

Active Microwave-Thermographic Signal Reconstruction With Adaptive Polynomial Regression, Logan M. Wilcox, Alexander Hook, Emma T. Bohannon, Kristen M. Donnell Jan 2025

Active Microwave-Thermographic Signal Reconstruction With Adaptive Polynomial Regression, Logan M. Wilcox, Alexander Hook, Emma T. Bohannon, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Active microwave thermography (AMT) is a coupled electromagnetic (EM) and thermographic nondestructive testing and evaluation (NDT&E) technique. AMT utilizes a radiating EM source (e.g., an antenna) that induces dielectric/magnetic heating on a specimen under test (SUT). The inspection surface of the SUT is imaged with an infrared (IR) camera over the inspection time. As the thermal excitation originates from a spatially varying radiated power density, a nonuniform thermal excitation results within (or on the surface of) the SUT that is directly related to this power density. This nonuniform heating causes uncertainty in defect detection and has the potential to lead …

Go to article

Enhancing Fiber Optic Interferometric Sensing With Microwave Photonics-Based Dispersion Fourier Transform And Integrated Magnitude–Phase Analysis, Chen Zhu, Ruimin Jie, Chenxi Huang, Jie Huang Jan 2025

Enhancing Fiber Optic Interferometric Sensing With Microwave Photonics-Based Dispersion Fourier Transform And Integrated Magnitude–Phase Analysis, Chen Zhu, Ruimin Jie, Chenxi Huang, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Fiber optic inline interferometers are widely used for high-precision sensing due to their sensitivity, compactness, and immunity to electromagnetic interference. Traditional optical spectral analysis methods suffer from limited dynamic range due to free spectral range (FSR) constraints, while microwave photonic filtering (MPF) techniques based on dispersion Fourier transform (DFT) provide an alternative by mapping optical signals into the radio frequency (RF) domain. However, conventional passband frequency tracking in MPF systems has limited sensitivity, and the recently demonstrated phase-based methods, though highly sensitive, are constrained by phase wrapping beyond 2π. In this work, we propose and experimentally demonstrate an integrated magnitude–phase …

Go to article

Phase-Variation Microwave Resonator For Highly Sensitive Dynamic Sensing, Chen Zhu, Rex E. Gerald, Jie Huang Jan 2025

Phase-Variation Microwave Resonator For Highly Sensitive Dynamic Sensing, Chen Zhu, Rex E. Gerald, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

High-precision dynamic sensing is critical in fields, such as industrial automation, structural health monitoring, and environmental sensing, where real-time responses to minuscule changes can prevent system failures or optimize performance. In this work, we introduce and demonstrate a phase-variation coaxial cable resonator (CCR) as a highly sensitive sensor for dynamic sensing applications. As a proof of concept, a prototype device based on a custom-designed CCR is thoroughly investigated for dynamic displacement measurements, as displacement is a fundamental quantity essential to numerous applications. The sensor consists of two components: a static CCR device and a movable conducting plate. As the conducting …

Go to article

Discrimination Of Temperature And Strain By Characterizing Two Femtosecond Laser-Written Coincident Sapphire Fiber Bragg Gratings For Harsh Environment Applications, Farhan Mumtaz, Bohong Zhang, Koustav Dey, Jeffrey D. Smith, Ronald J. O'Malley, Jie Huang Jan 2025

Discrimination Of Temperature And Strain By Characterizing Two Femtosecond Laser-Written Coincident Sapphire Fiber Bragg Gratings For Harsh Environment Applications, Farhan Mumtaz, Bohong Zhang, Koustav Dey, Jeffrey D. Smith, Ronald J. O'Malley, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

In this study, two co-incident sapphire fiber Bragg gratings (SFBGs) were successfully inscribed utilizing a femtosecond (fs) laser to achieve a high fringe contrast interferogram. These two SFBGs employ a unique configuration, one parallel to the center axis, called p-SFBG, and the other forming an angle from the center-axis, called a-SFBG, allowing for simultaneous strain and temperature measurements with low crosstalk. As a proof of concept, p-SFBG and a-SFBG using line-by-line method are characterized, which are shorter in length (i.e., 1.5 mm), producing reflectivity of ~3dB. This effort demonstrates the use of two coincident SFBGs forming an angle of 2.29° …

Go to article

Simultaneous Measurement Of Early-Stage Corrosion And Strain Levels In Steel Rebar Based On Graphene Oxide-Coated Ncf-Fbg Fiber Optic Sensor, Fujian Tang, Baihe Qu, Hong Nan Li, Jie Huang Jan 2025

Simultaneous Measurement Of Early-Stage Corrosion And Strain Levels In Steel Rebar Based On Graphene Oxide-Coated Ncf-Fbg Fiber Optic Sensor, Fujian Tang, Baihe Qu, Hong Nan Li, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Rebar corrosion significantly reduces the lifespan of reinforced concrete structures. The value of rebar strain, especially for some key structural components, indicates the safety margin of structures. In this study, a graphene oxide (GO) coated no-core fiber-fiber Bragg grating (NCF-FBG) fiber optic sensor is proposed for simultaneously measuring strain values and early-stage corrosion of steel rebar for the first time. The impact of GO coating thickness on the monitoring sensitivity is considered. A setup was manufactured to simultaneously perform tension, optical, and corrosion tests. The strain was applied up to 1200 μϵ. The rebar corrosion was assessed using electrochemical method …

Go to article

Safe Optimal Control Of Quadrotor Formations Using Multilayer Neural Networks And Continual Learning, Ehsan Soleimani, Irfan Ahmad Ganie, S. Jagannathan Jan 2025

Safe Optimal Control Of Quadrotor Formations Using Multilayer Neural Networks And Continual Learning, Ehsan Soleimani, Irfan Ahmad Ganie, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This article presents an integral reinforcement learning-based optimal formation tracking scheme for multiple quadrotors unmanned aerial vehicles (QUAVs) experiencing nonlinear coupled dynamics and subject to constraints. We use multilayer neural networks (MNN) within an actor-critic framework where the MNN weights are tuned using singular value decomposition (SVD) of the activation function gradient to approximate optimal control policy via backstepping. Additionally, barrier Lyapunov functions (BLF) are introduced to ensure set invariance, thereby maintaining the quadrotors within a defined safety space due to constraints. A novel weight update law for each layer is derived using the HJB approximation error and control input …

Go to article

An Extensive Analysis Of Match-Tracking Methods For Artmap, Niklas M. Melton, Leonardo Enzo Brito Da Silva, Donald C. Wunsch Jan 2025

An Extensive Analysis Of Match-Tracking Methods For Artmap, Niklas M. Melton, Leonardo Enzo Brito Da Silva, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This paper identifies and studies five match-tracking (MT) methods in the adaptive resonance theory (ART) literature and conducts a detailed comparative analysis of these in ARTMAP applications. We focus on model performance for each MT method with respect to time and space efficiency as well as classification accuracy. Experimental results indicate that one MT variant, used in ARTMAP applications for the first time in this work, provides significant improvements in computational efficiency: depending on the ARTMAP variant, it was able to achieve up to one order of magnitude reduction in both time and space requirements, albeit with a compromise in …

Go to article

Large-Range And High-Sensitivity Displacement Sensing Based On Extrinsic Fabry-Perot Interferometer Assisted Microwave Photonic Filter, Shiyu Li, Ruimin Jie, Osamah Alsalman, Jie Huang, Chen Zhu Jan 2025

Large-Range And High-Sensitivity Displacement Sensing Based On Extrinsic Fabry-Perot Interferometer Assisted Microwave Photonic Filter, Shiyu Li, Ruimin Jie, Osamah Alsalman, Jie Huang, Chen Zhu

Electrical and Computer Engineering Faculty Research & Creative Works

Displacement is a pivotal physical parameter, and advancements in displacement sensor technology have enabled the creation of a diverse array of physical and mechanical sensors through seamless integration with mechanical transducers. In this study, we introduce a displacement sensing technique leveraging an extrinsic Fabry-Perot interferometer (EFPI) assisted microwave photonic filter. By translating displacement-induced variations in the EFPI's optical reflection into peak frequency shifts within its frequency response, we achieve large-dynamic-range displacement measurements with outstanding signal quality and demodulation ease. Proof-of-concept demonstrations showcase a substantial 5 mm range with a remarkable sensitivity of 1.148 GHz/mm, achieved using a basic single-mode fiber-based …

Go to article

First Prev Next Last