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Ncf Sensor Coated With Cofe1.96la0.04o4/Lafeo3 Heterostructures For Room-Temperature Detection Of Liquefied Petroleum Gas Concentration, Ziqiang Liu, Fujian Tang, Yufang He, Jie Huang
Ncf Sensor Coated With Cofe1.96la0.04o4/Lafeo3 Heterostructures For Room-Temperature Detection Of Liquefied Petroleum Gas Concentration, Ziqiang Liu, Fujian Tang, Yufang He, Jie Huang
Electrical and Computer Engineering Faculty Research & Creative Works
Liquefied petroleum gas (LPG) is a highly flammable fuel widely used for cooking, heating and transportation, making real-time leak detection essential for preventing fire, explosion, and suffocation hazards. In this study, a room-temperature no-core fiber (NCF) sensor coated with CoFe1.96La0.04O4/LaFeO3 heterostructures was developed for LPG detection. The heterostructures were characterized using XRD, Raman spectroscopy, SEM, TEM, XPS, PL spectroscopy, and UV–vis spectroscopy. Experimental results showed that La incorporation and heterostructure formation refined the particles size, improved surface accessibility, and modulated the electronic structure and band gap, thereby enhancing LPG adsorption, carrier redistribution, and …
Ph-Compensated Hydrogen Peroxide Quantification Using A Dual-Modal Fiber-Optic Probe, Homayoon Soleimani Dinani, Bohong Zhang, Maryam Karimi, Rex E. Gerald, Shelley D. Minteer, Jie Huang
Ph-Compensated Hydrogen Peroxide Quantification Using A Dual-Modal Fiber-Optic Probe, Homayoon Soleimani Dinani, Bohong Zhang, Maryam Karimi, Rex E. Gerald, Shelley D. Minteer, Jie Huang
Electrical and Computer Engineering Faculty Research & Creative Works
We report a dual-modal fiber-optic probe that integrates electrochemical quantification of hydrogen peroxide (H₂O₂) with co-localized fluorescent pH sensing for pH-indexed interpretation of the H₂O₂ response. H₂O₂ is a reactive oxygen species involved in oxidative stress, inflammation, and cellular signaling, and local pH modulates both its production and electrochemical response. Many electrochemical H₂O₂ sensors exhibit pH-dependent sensitivity, creating ambiguity unless pH is measured and used for compensation, which is difficult in small, heterogeneous, or rapidly changing microenvironments. A three-electrode configuration—working (WE), counter (CE), and Ag/AgCl pseudo-reference (pRE) electrodes—is fabricated directly on the cylindrical surface of a 710-µm-diameter optical fiber using …
Thermo-Mechanical Behaviour Of Metal-Coated Optical Fibers For Distributed High-Temperature Sensing: From Laboratory Characterization To Industrial Case Validation, Koustav Dey, Rony Kumer Saha, Bohong Zhang, Laura Bartlett, Jeffrey D. Smith, Ronald J. O'Malley, Jie Huang
Thermo-Mechanical Behaviour Of Metal-Coated Optical Fibers For Distributed High-Temperature Sensing: From Laboratory Characterization To Industrial Case Validation, Koustav Dey, Rony Kumer Saha, Bohong Zhang, Laura Bartlett, Jeffrey D. Smith, Ronald J. O'Malley, Jie Huang
Electrical and Computer Engineering Faculty Research & Creative Works
Reliable distributed temperature sensing in high-temperature environments remains a significant challenge due to the thermal and mechanical limitations of conventional optical fibers. In particular, polymer-coated fibers degrade above ∼300 °C due to coating failure, mechanical fragility and hydrogen ingress. Metal-coated optical fibers offer a robust alternative for harsh environments such as Electric Arc Furnaces (EAFs), aerospace engines, nuclear systems, and oil and gas wells, owing to their superior mechanical strength and hermetic sealing. In this work, a first comprehensive experimental investigation of the thermo-mechanical behavior of metal-coated optical fibers for distributed high temperature sensing is presented over a wide temperature …
Graphene Oxide–Driven In Situ Bismuth Reduction Enables Highly Efficient Electroreduction Of Co2 To Formic Acid, Hao Feng, Bohong Zhang, Jie Huang, Xinhua Liang
Graphene Oxide–Driven In Situ Bismuth Reduction Enables Highly Efficient Electroreduction Of Co2 To Formic Acid, Hao Feng, Bohong Zhang, Jie Huang, Xinhua Liang
Electrical and Computer Engineering Faculty Research & Creative Works
To enable large scale efficient electrochemical CO2 reduction reaction (CO2RR) to formic acid (HCOOH), it is important to develop catalysts that can be operated in a wide potential window with good stability. Herein, we successfully synthesized Bi2O3 catalyst supported on graphene oxide (GO) and graphene (G) and found that Bi2O3/GO catalyst had a better overall performance than Bi2O3/G. The Bi2O3/GO catalyst demonstrated an outstanding CO2RR performance with a greater than 90% faradaic efficiency (FE) across a wide applied potential window …
Linear Relationships Of Gibbs Free Energy For Rare Earth Element Oxide, Hydroxide, Chloride, Fluoride, Carbonate, Ferrite, And Zirconate Minerals And Crystalline Solids, Ruiguang Pan, Alexander P. Gysi, Artaches A. Migdisov, Nicole C. Hurtig, Chen Zhu
Linear Relationships Of Gibbs Free Energy For Rare Earth Element Oxide, Hydroxide, Chloride, Fluoride, Carbonate, Ferrite, And Zirconate Minerals And Crystalline Solids, Ruiguang Pan, Alexander P. Gysi, Artaches A. Migdisov, Nicole C. Hurtig, Chen Zhu
Electrical and Computer Engineering Faculty Research & Creative Works
Rare Earth Elements (REE) are classified as critical minerals and materials essential for the transition from fossil fuels to renewable and clean energy. Accurate thermodynamic properties of REE minerals and other crystalline solids are crucial for geochemical modeling of REE speciation, solubility, and transport in ore deposits and for extraction, chemical processing, and recycling. However, the standard Gibbs free energy of formation (∆Gof,REEX) for these solids vary by 10s kJ mol−1 across different sources from literature. We applied the Sverjensky linear free energy relationship (LFER) to evaluate internal consistency for isostructural REE solid groups and predicted ∆Gof values for solid …
Mxene-Based Optical Fiber Sensors For Chemical And Biosensing: Review And Perspectives, Chen Zhu, Huaijun Guan, Chenxi Huang, Rex E. Gerald, Jie Huang
Mxene-Based Optical Fiber Sensors For Chemical And Biosensing: Review And Perspectives, Chen Zhu, Huaijun Guan, Chenxi Huang, Rex E. Gerald, Jie Huang
Electrical and Computer Engineering Faculty Research & Creative Works
No abstract provided.
Multi-Parametric Nonlinear Programming For Lossy Lmp Sensitivity Analysis Using Outer Progressive Cuts, Yuhan Huang, Tao Ding, Chenggang Mu, Rui Bo, Pengwei Du
Multi-Parametric Nonlinear Programming For Lossy Lmp Sensitivity Analysis Using Outer Progressive Cuts, Yuhan Huang, Tao Ding, Chenggang Mu, Rui Bo, Pengwei Du
Electrical and Computer Engineering Faculty Research & Creative Works
Accurate sensitivity analysis of locational marginal price (LMP) is crucial for risk hedging and market management. This paper proposes multiparametric nonlinear programming for sensitivity analysis of LMP with nonlinear network loss, also known as lossy LMP. Global analytical solutions for lossy LMP and the corresponding critical regions are derived. An outer progressive cut algorithm is developed to constrain the network loss error within a specific range for the whole parametric domain. Case studies show the improved accuracy over methods with lossless or fixed loss factors, and a two-order-of-magnitude online speedup over Monte Carlo methods while maintaining lower total computational time.
Distinct Regulatory Dna Methylation Signatures Across Multiple Sclerosis, Neuromyelitis Optica, And Neurological Post-Acute Sequelae Of Covid-19, Syed Ilyas Munzir, Daniel B. Hier, Michael D. Carrithers
Distinct Regulatory Dna Methylation Signatures Across Multiple Sclerosis, Neuromyelitis Optica, And Neurological Post-Acute Sequelae Of Covid-19, Syed Ilyas Munzir, Daniel B. Hier, Michael D. Carrithers
Electrical and Computer Engineering Faculty Research & Creative Works
Background/Objectives: Our prior epigenome-wide association study (EWAS) on multiple sclerosis (MS) identified myeloid-associated methylation signatures and an association with enhancer regions. Here we compared differential DNA methylation across three central nervous system inflammatory disorders: MS, neuromyelitis optica (NMO), and neurologic post-acute sequelae of COVID-19 (neuro-PASC). Methods: Whole-blood DNA was profiled on Infinium MethylationEPIC arrays. Analyses included EWAS at the CpG level, differentially methylation region (DMR) analysis, and gene regulatory-element enrichment using Locus Overlap Analysis (LOLA). Limma linear models were adjusted for race, EPIC array version, age, sex, disease-modifying treatment class, and blood cell composition. Results: All three diseases were associated …
Converting Co2 Into Carbon Nanotubes Via Sequential Co2 Methanation And Methane Pyrolysis, Kaiying Wang, Hao Feng, Ahmad Helaley, Xiaoqing He, Bohong Zhang, Jie Huang, Xinhua Liang
Converting Co2 Into Carbon Nanotubes Via Sequential Co2 Methanation And Methane Pyrolysis, Kaiying Wang, Hao Feng, Ahmad Helaley, Xiaoqing He, Bohong Zhang, Jie Huang, Xinhua Liang
Electrical and Computer Engineering Faculty Research & Creative Works
This study presents a sequential thermochemical catalytic process for converting CO2 into carbon nanotubes (CNTs), achieving nearly 99% overall CO2 conversion and solid carbon yields of up to 49% in a single pass. The overall transformation is divided into two thermodynamically favorable steps: (1) low-temperature CO2 methanation to CH4 over a sol-gel-prepared Ni87Ce6.5Zr6.5-SG catalyst, which achieved >95% CO2 conversion at 250 °C in a single pass, and (2) subsequent methane pyrolysis to CNTs and H2 over a Ni@Al2O3-IE core-shell catalyst, which showed improved stability and carbon …
An Instance Segmentation Based Global Mppt Method For Pv Systems Under Partial Shading Condition, Ehab Ur Rahman, Yousef Mahmoud, Rui Bo
An Instance Segmentation Based Global Mppt Method For Pv Systems Under Partial Shading Condition, Ehab Ur Rahman, Yousef Mahmoud, Rui Bo
Electrical and Computer Engineering Faculty Research & Creative Works
Partial shading in photovoltaic (PV) systems creates multiple Local Maximum Power Points (LMPPs) on the power-voltage (P-V) curve, causing conventional Maximum Power Point Tracking (MPPT) algorithms to converge prematurely to suboptimal operating points and resulting in significant energy losses. This work proposes a novel vision-based framework that integrates computer vision with Global Maximum Power Point Tracking (GMPPT) to maximize energy harvesting in partially shaded PV systems. The proposed method captures real-time imagery of PV panels to identify cell-level shading patterns, which are subsequently mapped to module electrical characteristics to enable direct analytical estimation of the GMPP voltage. An instance segmentation …
Enhanced Uav Surveillance With Rf-Based Drone Identification Using Transfer Learning, Prajoy Podder, Maciej Jan Zawodniok, Sanjay Madria
Enhanced Uav Surveillance With Rf-Based Drone Identification Using Transfer Learning, Prajoy Podder, Maciej Jan Zawodniok, Sanjay Madria
Electrical and Computer Engineering Faculty Research & Creative Works
With the development of technology and the decrease in costs, drones are now becoming easily accessible to the public. As the accessibility of this technology continues to grow, the concerns of security and surveillance increase, and to ensure a sense of security, the need to have reliable drone detection and identification systems is more urgent than ever. Besides, many civilian applications have been found for drones, which play a huge role in modern security and warfare. Unauthorized drones can be very dangerous regarding security issues, as they can be used for spying, smuggling, or even attacks against critical infrastructure. We …
Pso-Style Social Influence In An Ant Colony Algorithm For Continuous-Domain Optimization, Ashraf M. Abdelbar, Donald C. Wunsch
Pso-Style Social Influence In An Ant Colony Algorithm For Continuous-Domain Optimization, Ashraf M. Abdelbar, Donald C. Wunsch
Electrical and Computer Engineering Faculty Research & Creative Works
ACOR is a well-established Ant Colony Optimization (ACO) algorithm for continuous-domain optimization. In this paper, we propose an extension (which we call ACOR∗) in which several fundamental modifications are made to ACOR's solution construction process, including the incorporation of a social influence mechanism borrowed from Particle Swarm Optimization (PSO). Our modifications to the ACOR algorithm are intended to promote search diversity and combat premature convergence. We experimentally evaluate our proposal in the context of training feedforward neural networks for classification using 65 widely used datasets from the University of California Irvine (UCI) repository, as well as the optimization of several …
Multiplexed Fabry-Pérot High-Temperature Sensing Based On Dispersive Microwave-Photonic Frequency-Time Domain Analysis, Ruimin Jie, Chen Zhu, Bohong Zhang, Koustav Dey, Jie Huang
Multiplexed Fabry-Pérot High-Temperature Sensing Based On Dispersive Microwave-Photonic Frequency-Time Domain Analysis, Ruimin Jie, Chen Zhu, Bohong Zhang, Koustav Dey, Jie Huang
Electrical and Computer Engineering Faculty Research & Creative Works
We propose and experimentally demonstrate a multiplexed high-temperature Fabry-Pérot (FP) fiber sensing system interrogated by dispersive microwave-photonic frequency-time domain analysis (DM-FTDA). In the proposed architecture, incoherent broadband probing light is modulated by radio-frequency (RF) signals and then reflected by a parallel network of hollow-core photonic crystal fiber FP (HCPCF-FP) sensors. A chirped fiber Bragg grating provides strong dispersion to map the composite FP spectral response into a well-defined microwave transfer function. Unlike conventional optical Fourier-domain multiplexing that requires deliberate cavity-length allocation, the proposed approach achieves multiplexing via delay-dominated discrimination. Distinct delay fibers are assigned to each sensor branch, and an …
Advances In The Design Of Bio-Organic Resistive Switching Memory, Muhammad Awais, Yi Sheng Wong, Feng Zhao, Kuan Yew Cheong
Advances In The Design Of Bio-Organic Resistive Switching Memory, Muhammad Awais, Yi Sheng Wong, Feng Zhao, Kuan Yew Cheong
Electrical and Computer Engineering Faculty Research & Creative Works
Bio-organic materials have garnered significant attention as sustainable candidates for non-volatile resistive switching memory (RSM) because of their specialized chemical, structural, and environmental advantages. This review presents a design-centered perspective on bio-organic RSM by outlining the key device components required for effective device engineering, including electrode materials, memristive thin films, intermediate layers, substrates, and electrical measurement strategies. Each component is discussed in detail with respect to the material properties and operational parameters that influence overall device performance, such as functional groups, interfacial interactions, and processing conditions. The review further analyses the critical roles of electrode pairing, interfacial chemistry, additive incorporation, …
Rioi: A Microwave-Photonic Rf-Interferometric Interrogation Technique For Enhanced Fiber Optic Sensing, Chen Zhu, Ruimin Jie, Chenxi Huang, Jie Huang
Rioi: A Microwave-Photonic Rf-Interferometric Interrogation Technique For Enhanced Fiber Optic Sensing, Chen Zhu, Ruimin Jie, Chenxi Huang, Jie Huang
Electrical and Computer Engineering Faculty Research & Creative Works
Fiber optic interferometric (FOI) sensors are widely recognized for their high sensitivity, design flexibility, and multiplexing capabilities, making them ideal for applications ranging from structural health monitoring to biomedical diagnostics. However, conventional optical-domain interrogation techniques are often limited by the performance constraints of spectrometers. In this work, we present a radiofrequency (RF)-interferometric optical interrogation (RIOI) method for FOI sensors. This approach leverages microwave photonic (MWP) processing to encode the optical interference phase into an RF signal, which is then combined with a reference RF signal to produce a microwave-domain interferogram. By tracking spectral shifts in the RF domain, RIOI achieves …
Corrigendum To “Advanced Techniques In Quartz Wafer Precision Processing: Stealth Dicing Based On Filament-Induced Laser Machining” [Opt. Laser Technol. 171 (2024) 110474] (Optics And Laser Technology (2024) 171, (S0030399223013671), (10.1016/J.Optlastec.2023.110474)), Yun Wang, Yutang Dai, Farhan Mumtaz, Kaiyan Luo
Corrigendum To “Advanced Techniques In Quartz Wafer Precision Processing: Stealth Dicing Based On Filament-Induced Laser Machining” [Opt. Laser Technol. 171 (2024) 110474] (Optics And Laser Technology (2024) 171, (S0030399223013671), (10.1016/J.Optlastec.2023.110474)), Yun Wang, Yutang Dai, Farhan Mumtaz, Kaiyan Luo
Electrical and Computer Engineering Faculty Research & Creative Works
The authors regret, that the affiliation for author Yun Wang was incomplete. To accurately reflect both the author's academic affiliation and the research platform where the work was conducted. The correct affiliation for Yun Wang is updated as above. The authors would like to apologize for any inconvenience caused.
Applying Two-Stage Risk-Based Market Structures For Energy Hub-Based Plug-In Electric Vehicles Using Information Decision Gap Theory And A Hybrid Recurrent Convolutional Network, A. Heidari, R. C. Bansal, R. Bo
Applying Two-Stage Risk-Based Market Structures For Energy Hub-Based Plug-In Electric Vehicles Using Information Decision Gap Theory And A Hybrid Recurrent Convolutional Network, A. Heidari, R. C. Bansal, R. Bo
Electrical and Computer Engineering Faculty Research & Creative Works
This paper investigates the optimal operation of an energy hub engaged in both day-ahead and real-time trading. A two-stage optimization framework Information Gap Decision Theory (IGDT) for day-ahead bidding and stochastic programming with Monte Carlo scenarios for real-time recourse is applied. Risk-neutral, risk-averse, and risk-taking strategies are considered to capture different risk preferences. The hub integrates combined heat and power, renewable energy, plug-in electric vehicles, and vehicle-to-grid and grid-to-vehicle technologies. Price and load forecasts are generated using a hybrid recurrent convolutional network (HRCN). Results highlight the trade-off between risk management and economic performance: costs are 16.5 % higher in the …
Microwave Dielectric Properties Of Geopolymer Precursor Powders, Linh T. Duong, Abu Naser Rashid Reza, Kristen M. Donnell, Christopher R. Shearer
Microwave Dielectric Properties Of Geopolymer Precursor Powders, Linh T. Duong, Abu Naser Rashid Reza, Kristen M. Donnell, Christopher R. Shearer
Electrical and Computer Engineering Faculty Research & Creative Works
Geopolymers are sustainable structural materials with properties similar to ordinary Portland cement concrete. To better understand the fundamental reaction mechanisms of geopolymers, a microwave materials characterization approach is used. In this research work, the dielectric properties (permittivity and loss factor) of common precursor powders used to make geopolymers (GPPs)—fly ash, lime, metakaolin, silica fume, slag, and zeolite—are measured over the S- and X-band frequency ranges (i.e., 2.0–4.0 GHz and 8.2–12.4 GHz, respectively). The physical characteristics, elemental composition, mineralogical properties, and phase characterization of the GPPs are then correlated to dielectric properties. Permittivity of GPP, classified as pozzolanic or latent hydraulic, …
Machine Learning In Peak Demand Forecasting: Foundations, Trends, And Insights, Shuang Dai, Fanlin Meng, Hongsheng Dai, Qian Wang, Xizhong Chen, Wenlei Bai, Peizhi Shi, Richard Allmendinger, Yuchen Zhang, Jian Liu
Machine Learning In Peak Demand Forecasting: Foundations, Trends, And Insights, Shuang Dai, Fanlin Meng, Hongsheng Dai, Qian Wang, Xizhong Chen, Wenlei Bai, Peizhi Shi, Richard Allmendinger, Yuchen Zhang, Jian Liu
Electrical and Computer Engineering Faculty Research & Creative Works
Peak demand forecasting involves predicting the maximum electricity demand within a specific period, which plays a key role in maintaining the efficiency and stability of power systems. The rapid evolution of power systems, driven by advanced metering infrastructure, local energy applications such as electric vehicles, and the increasing adoption of intermittent renewable energy, has introduced greater randomness and reduced predictability in peak demand. Given the pressing need to address more diverse implementation requirements across different contexts, accurate and reliable peak demand forecasting has become increasingly important. To the best of our knowledge, this study is the first to provide a …
Robust And High-Efficiency Demodulation Of Ultra-Weak Fbg Arrays In Ofdr-Based Distributed Sensing, Zhaopeng Zhang, Yuxuan Cao, Xu Liu, Dingcheng Wang, Bo Liu, Chen Zhu
Robust And High-Efficiency Demodulation Of Ultra-Weak Fbg Arrays In Ofdr-Based Distributed Sensing, Zhaopeng Zhang, Yuxuan Cao, Xu Liu, Dingcheng Wang, Bo Liu, Chen Zhu
Electrical and Computer Engineering Faculty Research & Creative Works
A robust and high-efficiency demodulation scheme for optical frequency domain reflectometry (OFDR) based ultra-weak fiber Bragg grating (UWFBG) array detection system, originating from the Buneman frequency estimation (BFE) algorithm, is proposed and experimentally demonstrated. Due to the current limitations and imperfections of FBG inscription technology, the quasi-continuous inscription approach, along with its less-than-ideal outcomes, gives rise to problems of grating spectrum splitting and spectral distortion during the grating demodulation process. This renders the traditional approach of directly applying the BFE algorithm for grating demodulation ineffective, despite its significant enhancement of demodulation efficiency. To address this issue, we propose utilizing the …
Sapphire Optical Fiber Bragg Grating Sensors Based On Dispersive Microwave-Photonic Frequency-Time Domain Analysis, Ruimin Jie, Chen Zhu, Farhan Mumtaz, Koustav Dey, Bohong Zhang, Jie Huang
Sapphire Optical Fiber Bragg Grating Sensors Based On Dispersive Microwave-Photonic Frequency-Time Domain Analysis, Ruimin Jie, Chen Zhu, Farhan Mumtaz, Koustav Dey, Bohong Zhang, Jie Huang
Electrical and Computer Engineering Faculty Research & Creative Works
Sapphire fiber Bragg gratings (SFBGs) have attracted growing interest for high temperature sensing in harsh environments, yet their interrogation typically relies on optical spectrum measurements, demanding a high-resolution optical spectrum analyzer (OSA) that is bulky, expensive, and constrained in acquisition speed. Moreover, the inherently multimode nature of sapphire fiber further complicates spectrum-based demodulation, thereby limiting the achievable sensing resolution. In this paper, we propose and experimentally demonstrate a microwave-photonic interrogation approach for SFBG sensors. Instead of measuring the optical reflection spectrum, the complex frequency response in the microwave domain of an SFBG is acquired using a vector network analyzer (VNA) …
Multi-Period Coordinated Planning Of Xfcs In Coupled Tn-Pdn Networks: Integrating Demand Charge Reduction And Pre-Existing Infrastructure, Waqas Ur Rehman, Siyuan Wang, Liheng Lv, Jonathan W. Kimball, Rui Bo
Multi-Period Coordinated Planning Of Xfcs In Coupled Tn-Pdn Networks: Integrating Demand Charge Reduction And Pre-Existing Infrastructure, Waqas Ur Rehman, Siyuan Wang, Liheng Lv, Jonathan W. Kimball, Rui Bo
Electrical and Computer Engineering Faculty Research & Creative Works
The widespread adoption of electric vehicles (EVs) and transportation electrification is encumbered by two chief barriers: i) the limited driving range of EVs in the market today and ii) inadequate charging infrastructure support. This paper aims to address the latter bottleneck and proposes a strategic multi-period coordinated planning model to optimally site and size battery energy storage system (BESS) assisted extreme fast charging stations in a highway transportation network and solar systems in a power distribution network. The proposed approach accounts for pre-existing charging stations, the increasing EV penetration levels, decreasing technology costs, and technological advancements in the future and …
Enhancing Measurement Accuracy: The Impact Of Missing Data On Parameter Estimation In Mass-Spring-Damper Systems, Michkath Omanda Bouraima, Steven Thompson, Maciej J. Zawodniok
Enhancing Measurement Accuracy: The Impact Of Missing Data On Parameter Estimation In Mass-Spring-Damper Systems, Michkath Omanda Bouraima, Steven Thompson, Maciej J. Zawodniok
Electrical and Computer Engineering Faculty Research & Creative Works
In sensor-driven dynamic systems, missing data can severely degrade parameter estimation accuracy. This article investigates the impact of missing data on phase estimation in a mass-spring-damper system using an information-theoretic framework based on the Cramér-Rao Lower Bound (CRLB). Closed-form CRLB expressions are derived for four scenarios: complete data, missing completely at random (MCAR) deletion, MCAR-based imputation, and missing at random (MAR) missingness via a selection-weighted formulation. These bounds are used as theoretical benchmarks to evaluate classical imputation methods (last observation carried forward (LOCF), linear interpolation) and advanced approaches (Kalman filtering, Rauch-Tung-Striebel (RTS) smoothing, Bayesian inference, and transformer-based imputation) through Monte …
Temperature Compensation In Loop And Patch Fss Strain Sensors: Analysis And Experimental Validation, Swathi Muthyala Ramesh, Kristen M. Donnell
Temperature Compensation In Loop And Patch Fss Strain Sensors: Analysis And Experimental Validation, Swathi Muthyala Ramesh, Kristen M. Donnell
Electrical and Computer Engineering Faculty Research & Creative Works
Frequency selective surfaces (FSSs) are arrays of conductive elements or apertures that exhibit frequency-dependent reflection and transmission properties. Their electromagnetic response is influenced by geometry and environmental conditions, making them attractive for wireless strain-sensing applications. However, temperature variations can produce frequency shifts similar to those caused by strain, reducing measurement accuracy. This work investigates the effects of intrinsic temperature compensation on two common FSS unit cell geometries—loop and patch—through comprehensive simulation analysis. The results show that loop-based cells offer superior thermal stability, while patch-based cells provide greater strain sensitivity, illustrating the trade-off between thermal robustness and mechanical responsiveness. A patch-type …
Mitigating Hysteresis In Metal-Coated Fibers Via Optimized Thermal Treatment For Advanced Distributed High-Temperature Sensing Applications, Koustav Dey, Rony Kumer Saha, Bohong Zhang, S. Narasimman, Farhan Mumtaz, Jeffrey D. Smith, Rex E. Gerald, Ronald J. O'Malley, Jie Huang
Mitigating Hysteresis In Metal-Coated Fibers Via Optimized Thermal Treatment For Advanced Distributed High-Temperature Sensing Applications, Koustav Dey, Rony Kumer Saha, Bohong Zhang, S. Narasimman, Farhan Mumtaz, Jeffrey D. Smith, Rex E. Gerald, Ronald J. O'Malley, Jie Huang
Electrical and Computer Engineering Faculty Research & Creative Works
Metal-coated optical fibers are widely employed in sensing applications owing to their superior mechanical strength and corrosion resistance. However, their calibration at elevated temperatures is hindered by hysteresis, manifested as discrepancies between heating and cooling cycles, primarily caused by residual strain from mismatched thermal expansion coefficients (TECs) between the metal coating and silica cladding. This research introduces an optimal heat treatment procedure aimed at minimizing the impact of the mismatch in TECs between the cladding and the coating materials that causes the residual strain in gold (Au) and copper (Cu) coated fibers for achieving reliable distributed high temperature sensing up …
Large Language Models For Neurology: A Mini Review, Donald C. Wunsch, Daniel B. Hier
Large Language Models For Neurology: A Mini Review, Donald C. Wunsch, Daniel B. Hier
Electrical and Computer Engineering Faculty Research & Creative Works
Large language models have the potential to transform neurology by augmenting diagnostic reasoning, streamlining documentation, and improving workflow efficiency. This Mini Review surveys emerging applications of large language models in Alzheimer's disease, Parkinson's disease, multiple sclerosis, and epilepsy, with emphasis on ambient documentation, multimodal data integration, and clinical decision support. Key barriers to adoption include bias, privacy, reliability, and regulatory alignment. Looking ahead, neurology-focused language models may develop greater fluency in biomedical ontologies and FHIR standards, improving data interoperability and supporting more seamless collaboration between clinicians and AI systems. Two future developments have the potential to be particularly impactful: (1) …
Evaluation Of Multiple Generative Large Language Models On Neurology Board-Style Questions, Mohammad Almomani, Vijaya Valaparla, James Weatherhead, Xiang Fang, Alok Dabi, Chih Ying Li, Peter Mccaffrey, Dan Hier, Jorge Mario Rodríguez-Fernández
Evaluation Of Multiple Generative Large Language Models On Neurology Board-Style Questions, Mohammad Almomani, Vijaya Valaparla, James Weatherhead, Xiang Fang, Alok Dabi, Chih Ying Li, Peter Mccaffrey, Dan Hier, Jorge Mario Rodríguez-Fernández
Electrical and Computer Engineering Faculty Research & Creative Works
Objective: To compare the performance of eight large language models (LLMs) with neurology residents on board-style multiple-choice questions across seven subspecialties and two cognitive levels. Methods: In a cross-sectional benchmarking study, we evaluated Bard, Claude, Gemini v1, Gemini 2.5, ChatGPT-3.5, ChatGPT-4, ChatGPT-4o, and ChatGPT-5 using 107 text-only items spanning movement disorders, vascular neurology, neuroanatomy, neuroimmunology, epilepsy, neuromuscular disease, and neuro-infectious disease. Items were labeled as lower- or higher-order per Bloom's taxonomy by two neurologists. Models answered each item in a fresh session and reported confidence and Bloom classification. Residents completed the same set under exam-like conditions. Outcomes included overall and …
Safety Aware Continual Reinforcement Learning-Based Output Tracking Control Of Nonlinear Continuous-Time Systems, Irfan Ganie, Sarangapani Jagannathan
Safety Aware Continual Reinforcement Learning-Based Output Tracking Control Of Nonlinear Continuous-Time Systems, Irfan Ganie, Sarangapani Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
An output feedback (OF)-based control scheme utilizing both a scalable multilayer neural network (MNN) observer and actor–critic MNN via integral reinforcement learning (IRL)/adaptive dynamics programming (ADP) approach for a class of nonlinear systems with output constraints is introduced. The proposed observer, critic, and actor MNN weight updates are derived using a singular value decomposition (SVD) of MNN activation function gradient along with output error, Bellman and control input errors, respectively. Next, the approach incorporates continual learning (CL), utilizing a penalty function in the weight update laws for both actor–critic MNNs to consolidate knowledge from previous tasks and enhance learning in …
Multi-Parameter Optimization And Adaptive Temperature Compensation For Fbg Strain Sensors In Wide-Temperature-Range Aerospace Applications, Ruling Zhou, Jiacheng Yu, Yutang Dai, Jianguan Tang, Minghong Yang, Farhan Mumtaz
Multi-Parameter Optimization And Adaptive Temperature Compensation For Fbg Strain Sensors In Wide-Temperature-Range Aerospace Applications, Ruling Zhou, Jiacheng Yu, Yutang Dai, Jianguan Tang, Minghong Yang, Farhan Mumtaz
Electrical and Computer Engineering Faculty Research & Creative Works
Accurate strain measurement in cryogenic fuel pipelines is crucial for ensuring the structural integrity and reliability of rocket engine systems operating under extreme thermal conditions. Fiber Bragg grating (FBG) sensors show significant potential for such applications; however, their inherent temperature-strain cross-sensitivity limits performance over wide temperature ranges. This research presents an enhanced compensation strategy combining multi-parameter optimization with temperature-zone-specific adaptation to improve the accuracy and stability of FBG-based strain sensing in harsh aerospace environments. Four special steel substrate materials including S03, S06, S07, and 1Cr18Ni9Ti, were evaluated using strain transfer theory and thermo-mechanical coupling simulations. Genetic algorithms optimized key design …
Safe Optimal Control Framework For Cooperative Manipulation Of Objects In Human–Robot Teams, Irfan Ganie, Sarangapani Jagannathan
Safe Optimal Control Framework For Cooperative Manipulation Of Objects In Human–Robot Teams, Irfan Ganie, Sarangapani Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
This article introduces a distributed deep neural network (NN)-based adaptive control framework for cooperative object manipulation in human–robot teams with unknown agent dynamics by using three distinct multilayer NN observers (MNNOs). The first observer, termed the reference point estimator, enables each robotic agent to estimate the object's reference center using consensus-based learning, even without direct access to global reference trajectories. The second observer, referred to as the human force-to-trajectory estimator, uses human-applied forces to infer the intended position, velocity, and acceleration of the object, enabling real-time estimation of human intent. Together, these two observers allow distributed estimation of human-intended motion. …