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Obstacles And Mitigations For An Accurate Low Impedance, Low Frequency Measurement, Faye Squires, Yifan Ding, Matthew Doyle, Matteo Cocchini, Samuel Connor, Francesco De Paulis, Albert E. Ruehli, Chulsoon Hwang, Lijun Jiang
Obstacles And Mitigations For An Accurate Low Impedance, Low Frequency Measurement, Faye Squires, Yifan Ding, Matthew Doyle, Matteo Cocchini, Samuel Connor, Francesco De Paulis, Albert E. Ruehli, Chulsoon Hwang, Lijun Jiang
Electrical and Computer Engineering Faculty Research & Creative Works
The two-port shunt configuration is often heralded as the gold standard for low-impedance measurements. However, this measurement method is not without its own issues. The shunt configuration inherently creates a ground loop between the measurement device's reference plane and the reference of the device under test (DUT). Additionally, probes often must be oriented in such a way that allows inductive coupling to occur. This work uses microprobes to measure the shunt impedance of a non-ideal short to explore the limitations of this measurement method in terms of both frequency and impedance. It highlights the importance of ground loop isolation and …
Efficient Decoupling Capacitor Impact Calculation, Faye Squires, Yifan Ding, Matthew Doyle, Matteo Cocchini, Samuel Connor, Francesco De Paulis, Albert E. Ruehli, Chulsoon Hwang, Lijun Jiang
Efficient Decoupling Capacitor Impact Calculation, Faye Squires, Yifan Ding, Matthew Doyle, Matteo Cocchini, Samuel Connor, Francesco De Paulis, Albert E. Ruehli, Chulsoon Hwang, Lijun Jiang
Electrical and Computer Engineering Faculty Research & Creative Works
Methods of optimizing decoupling capacitor placement on power distribution networks (PDNs) are often limited due to the computational complexity required to calculate the impact of connecting loads to an impedance matrix with hundreds of rows and columns. This work proposes that by removing all but one member of the impedance matrix before calculating, checking the impact of adding capacitors to the matrix can be done efficiently, and optimization methods can be viable even when requiring millions of impedance calculations.
Characterization And Full-Wave Modeling Of Corona Discharge Induced Coupling To Touchscreen Displays, Zhekun Peng, Shubhankar Marathe, Javad Meiguni, Ali Foudazi, Jianchi Zhou, Li Shen, Viswa Pilla, Cheung Wei Lam, Donghyun Kim, David Pommerenke, Daryl G. Beetner
Characterization And Full-Wave Modeling Of Corona Discharge Induced Coupling To Touchscreen Displays, Zhekun Peng, Shubhankar Marathe, Javad Meiguni, Ali Foudazi, Jianchi Zhou, Li Shen, Viswa Pilla, Cheung Wei Lam, Donghyun Kim, David Pommerenke, Daryl G. Beetner
Electrical and Computer Engineering Faculty Research & Creative Works
An electrostatic discharge (ESD) to the glass of a touchscreen display can damage capacitive touch sensor circuitry and traces. The ESD creates a sparkless corona discharge on the glass surface, which couples to sense patches on the other side of the glass. Currents induced on sense traces during the corona discharge are measured in an evaluation setup, which resembles the touchscreen design. Waveforms for current induced at different distances from the discharge position are recorded and compared. The induced currents are analyzed by their peak value and the total charge or energy delivered to the sense trace for different discharge …
Centralized And Federated Heart Disease Classification Using Uci Dataset: A Benchmark With Interpretability Analysis, Mario Padilla Rodriguez, Eyiara Oladipo, Mohamed Nafea
Centralized And Federated Heart Disease Classification Using Uci Dataset: A Benchmark With Interpretability Analysis, Mario Padilla Rodriguez, Eyiara Oladipo, Mohamed Nafea
Electrical and Computer Engineering Faculty Research & Creative Works
Cardiovascular disease (CVD) is a leading cause of global mortality, highlighting the need for accurate diagnostic methods. This study benchmarks centralized and federated learning (FL) algorithms for heart disease binary classification using the UCI dataset, which includes 920 patient records from four hospitals in the USA, Hungary, and Switzerland. Our benchmark is supported by Shapley-value as well as Local Interpretable Model-agnostic Explanations (LIME) interpretability analyses to quantify feature importance for classification. In the centralized setup, various classification algorithms are trained on pooled data, with the Naive Bayes classifier achieving the highest test accuracy of 81.1%. Further, FL algorithms with four …
Benchmarking Deep Learning Architectures For Ecg-Based Multi-Label Heart Disease Prediction Using Mimic-Iv Database, Eyiara Oladipo, Sarwar Nazrul, Mohamed Nafea
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 …
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
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 …
Reference Dependence In Queue Design And Pricing Strategies, Jian Liu, Yongpin Zhou, Jian Chen, Peng Li
Reference Dependence In Queue Design And Pricing Strategies, Jian Liu, Yongpin Zhou, Jian Chen, Peng Li
Electrical and Computer Engineering Faculty Research & Creative Works
This research investigates the effect of reference dependence on waiting times in service systems which formerly used a first-in-first-out (FIFO) service but have introduced a priority line with a fee. Our model combines reference-dependent gain-loss utility with standard customer utility, and we posit that customers are pleased with shorter-than-expected waiting times, whereas longer-than-expected times lead to dissatisfaction and an increased likelihood of balking. The study explores two scenarios: a captive customer system (CCS) and a noncaptive customer system (NCCS), with a focus on optimal pricing and segmentation strategies for revenue and social welfare maximization. The results reveal that, in a …
Impact Of Electrical Testing Strategies On The Performance Metrics Of Bio-Organic-Based Resistive Switching Memory, Muhammad Awais, Hao Zhe Leong, Nadras Othman, Mohamad Danial Shafiq, Feng Zhao, Kuan Yew Cheong
Impact Of Electrical Testing Strategies On The Performance Metrics Of Bio-Organic-Based Resistive Switching Memory, Muhammad Awais, Hao Zhe Leong, Nadras Othman, Mohamad Danial Shafiq, Feng Zhao, Kuan Yew Cheong
Electrical and Computer Engineering Faculty Research & Creative Works
Resistive Random-Access Memory (ReRAM) is considered as one of the most promising non-volatile memory technologies because of its high scalability, fast switching speed, and low power consumption. While many review papers are focused on investigating material types, material properties, device fabrication methods, and device structures, the influence of electrical testing strategies on ReRAM performance has yet been reviewed, particularly for bio-organic-based ReRAM. This review compiled, analyzed, and discussed how compliance current, voltage sweep rate, voltage sweep range, and voltage sweeping direction affect the ON/OFF ratio, read memory window, and both SET and RESET voltages of ReRAM.
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
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 …
Effects Of Silver Nanoparticles In Pectin Polysaccharide Thin Film On Resistive Switching Characteristics, Jia Zheng Yeoh, Muhammad Awais, Feng Zhao, Kuan Yew Cheong
Effects Of Silver Nanoparticles In Pectin Polysaccharide Thin Film On Resistive Switching Characteristics, Jia Zheng Yeoh, Muhammad Awais, Feng Zhao, Kuan Yew Cheong
Electrical and Computer Engineering Faculty Research & Creative Works
This study investigates the resistive switching characteristics of Ag nanoparticle (AgNP)-incorporated pectin (pectin-AgNP) as a memristive thin film, with varying concentrations of AgNP (0.0 wt.%, 0.5 wt.%, and 1.0 wt.%) and pectin (5.0 mg/L, 5.5 mg/L, 6.0 mg/L, 6.5 mg/L, and 7.0 mg/L), sandwiched between Au and indium tin oxide (ITO) electrodes on glass substrate. The structural, chemical, and electrical properties of these pectin-AgNP thin films were evaluated. With AgNP concentration of 0.5 wt.% in a pectin concentration of 5.5 mg/mL, the Fourier transform infrared (FTIR) spectra indicated the highest presence of C–O bonds. This suggests the incorporation of AgNP …
A Deep Autoencoder For Electric Double Layer Capacitance Prediction In Electrochemical Sensors, Mason Mcgarrity, Feng Zhao
A Deep Autoencoder For Electric Double Layer Capacitance Prediction In Electrochemical Sensors, Mason Mcgarrity, Feng Zhao
Electrical and Computer Engineering Faculty Research & Creative Works
This study explores the application of a deep autoencoder neural network to accurately predict the electric double layer capacitance from real-world parameters in binary, asymmetric electrolytes under low concentration conditions. By utilizing a modest simulation-based dataset of just 250 samples, the deep autoencoder neural network model developed in this study effectively predicted the capacitance by learning the critical features and relationships of the electric double layer model and encoding this learned representation into a low-dimensional latent space. From the latent variables, the decoder block of the neural network learned to effectively recreate the high-dimensional input. To enhance the model's robustness, …
A Review On Photoacoustic Spectroscopy Techniques For Gas Sensing, Dakshith Ruvin Wijesinghe, Md Abu Zobair, Mina Esmaeelpour
A Review On Photoacoustic Spectroscopy Techniques For Gas Sensing, Dakshith Ruvin Wijesinghe, Md Abu Zobair, Mina Esmaeelpour
Electrical and Computer Engineering Faculty Research & Creative Works
The rapid growth of industry and the global drive for modernization have led to an increase in gas emissions, which present significant environmental and health risks. As a result, there is a growing need for precise and sensitive gas-monitoring technologies. This review delves into the progress made regarding photoacoustic gas sensors, with a specific focus on the vital components of acoustic cells and acoustic detectors. This review highlights photoacoustic spectroscopy (PAS) as an optical detection technique, lauding its high sensitivity, selectivity, and capability to detect a wide range of gaseous species. The principles of photoacoustic gas sensors are outlined, emphasizing …
256-Level Honey Memristor-Based In-Memory Neuromorphic System, Harshvardhan Uppaluru, Zoe Templin, Mohammed Rafeeq Khan, Md Omar Faruque, Feng Zhao, Jinhui Wang
256-Level Honey Memristor-Based In-Memory Neuromorphic System, Harshvardhan Uppaluru, Zoe Templin, Mohammed Rafeeq Khan, Md Omar Faruque, Feng Zhao, Jinhui Wang
Electrical and Computer Engineering Faculty Research & Creative Works
Promising synaptic behavior has been exhibited by memristors based on natural organic materials. Such memristor-based neuromorphic systems offer notable benefits, including environmental sustainability, low production and disposal costs, non-volatile storage capability, and bio/Complementary Metal-Oxide-Semiconductor (CMOS) compatibility. Here, a 256-level honey memristor-based neuromorphic system is experimentally evaluated for image recognition. In detail, first, 256-level honey memristors are manufactured and tested based on in-house technology; next, the non-linear characteristics and inherent variation of honey memristor devices, which lead to imprecise weight updates and limit the inference accuracy, are investigated. Experimental results indicate that the inference accuracy of the 256-level honey memristor-based neuromorphic …
Predicting Iot Distributed Ledger Fraud Transactions With A Lightweight Gan Network, Charles Rawlins, Jagannathan Sarangapani
Predicting Iot Distributed Ledger Fraud Transactions With A Lightweight Gan Network, Charles Rawlins, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
Decision-making and consensus in traditional blockchain protocols is formulated as a repeated Bernoulli trial that solves a computationally intense lottery puzzle, called Proof-of-Work (PoW) in Bitcoin. This approach has shown robustness through practice but does not scale with increasing network size and generation of new transactions. Resource constrained Internet of Things (IoT) networks are incompatible with full computation of schemes like Bitcoin's PoW. Our effort proposes a first step towards an alternative consensus using machine learning-based decision-making with prediction of fraud transactions to alleviate need for intense computation. To improve base approval probabilities for fraud detection in an ideal security …
Optical Frequency Domain Reflectometry-Based High-Performance Distributed Sensing Empowered By A Data And Physics-Driven Neural Network, Zhaopeng Zhang, Wei Peng, Osamah Alsalman, Lingmei Ma, Jie Huang, Chen Zhu
Optical Frequency Domain Reflectometry-Based High-Performance Distributed Sensing Empowered By A Data And Physics-Driven Neural Network, Zhaopeng Zhang, Wei Peng, Osamah Alsalman, Lingmei Ma, Jie Huang, Chen Zhu
Electrical and Computer Engineering Faculty Research & Creative Works
Optical frequency domain reflectometry (OFDR) based distributed strain sensors are the preferred choice for achieving accurate strain measurements over extensive sensing ranges while maintaining exceptional spatial resolution. However, the simultaneous realization of high spatial resolution, high strain resolution, large strain range, and an extended sensing range presents an exceedingly challenging endeavor. In this study, we introduce and experimentally demonstrate a data and physics-driven neural network-empowered OFDR system designed to attain high-performance distributed sensing. In our experiments, we successfully maintained an impressive sensing resolution of sub-microstrain (0.91 µε) alongside a sharp spatial resolution of sub-millimeter (0.857 mm) across a 140-m sensing …
Prescribed-Time Nash Equilibrium Seeking For Pursuit-Evasion Game, Lei Xue, Jianfeng Ye, Yongbao Wu, Jian Liu, D. C. Wunsch
Prescribed-Time Nash Equilibrium Seeking For Pursuit-Evasion Game, Lei Xue, Jianfeng Ye, Yongbao Wu, Jian Liu, D. C. Wunsch
Electrical and Computer Engineering Faculty Research & Creative Works
Dear Editor, this letter is concerned with prescribed-time Nash equilibrium (PTNE) seeking problem in a pursuit-evasion game (PEG) involving agents with second-order dynamics. In order to achieve the prior given and user-defined convergence time for the PEG, a PTNE seeking algorithm has been developed to facilitate collaboration among multiple pursuers for capturing the evader without the need for any global information. Then, it is theoretically proved that the prescribed-time convergence of the designed algorithm for achieving Nash equilibrium of PEG. Eventually, the effectiveness of the PTNE method was validated by numerical simulation results.
A Reputation System For Provably-Robust Decision Making In Iot Blockchain Networks, Charles C. Rawlins, Sarangapani Jagannathan, Venkata Sriram Siddhardh Nadendla
A Reputation System For Provably-Robust Decision Making In Iot Blockchain Networks, Charles C. Rawlins, Sarangapani Jagannathan, Venkata Sriram Siddhardh Nadendla
Electrical and Computer Engineering Faculty Research & Creative Works
Blockchain systems have been successful in discerning truthful information from interagent interaction amidst possible attackers or conflicts, which is crucial for the completion of nontrivial tasks in distributed networking. However, the state-of-the-art blockchain protocols are limited to resource-rich applications where reliably connected nodes within the network are equipped with significant computing power to run lottery-based proof-of-work (pow) consensus. The purpose of this work is to address these challenges for implementation in a severely resource-constrained distributed network with internet of things (iot) devices. The contribution of this work is a novel lightweight alternative, called weight-based reputation (wbr) scheme, to classify new …
Microwave Holography For Emi Source Imaging, Xin Yan, Jiangshuai Li, Wei Zhang, Kaustav Ghosh, Philippe Sochoux, Daryl G. Beetner, Victor Khilkevich
Microwave Holography For Emi Source Imaging, Xin Yan, Jiangshuai Li, Wei Zhang, Kaustav Ghosh, Philippe Sochoux, Daryl G. Beetner, Victor Khilkevich
Electrical and Computer Engineering Faculty Research & Creative Works
Emission Source Microscopy Technique Can Be Utilized to Localize the Radiation Sources in Complex and Electrically Large Electronic Systems. in the Two-Dimensional Emission Source Microscopy Algorithm, Both Magnitude and Phase of the Field Need to Be Measured, and a Vector Network Analyzer or an Oscilloscope Has to Be Used as a Receiver, Resulting in Reduced Signal-To-Noise Ratio and Longer Measurement Time Compared to a Spectrum Analyzer (SA). in This Article, a Phase less Electromagnetic Interference Source Imaging Method is Proposed based on Microwave Holography. the Field Produced by the Device under Test is Not Measured Directly, Instead, the Interference Pattern …
On The Use Of Machine Learning And Data-Transformation Methods To Predict Hydration Kinetics And Strength Of Alkali-Activated Mine Tailings-Based Binders, Sahil Surehali, Taihao Han, Jie Huang, Aditya Kumar, Narayanan Neithalath
On The Use Of Machine Learning And Data-Transformation Methods To Predict Hydration Kinetics And Strength Of Alkali-Activated Mine Tailings-Based Binders, Sahil Surehali, Taihao Han, Jie Huang, Aditya Kumar, Narayanan Neithalath
Electrical and Computer Engineering Faculty Research & Creative Works
The escalating production of mine tailings (MT), a byproduct of the mining industry, constitutes significant environmental and health hazards, thereby requiring a cost-effective and sustainable solution for its disposal or reuse. This study proposes the use of MT as the primary ingredient (≥70%mass) in binders for construction applications, thereby ensuring their efficient upcycling as well as drastic reduction of environmental impacts associated with the use of ordinary Portland cement (OPC). The early-age hydration kinetics and compressive strength of MT-based binders are evaluated with an emphasis on elucidating the influence of alkali activation parameters and the amount of slag or cement …
Miniature Optical Fiber Fabry-Perot Interferometer Based On A Single-Crystal Metal-Organic Framework For The Detection And Quantification Of Benzene And Ethanol At Low Concentrations In Nitrogen Gas, Farhan Mumtaz, Bohong Zhang, Narasimman Subramaniyam, Mohammad Roman, Peter Holtmann, Abhishek Prakash Hungund, Ryan O'Malley, Thomas M. Spudich, Michael Davis, Rex E. Gerald, Jie Huang
Miniature Optical Fiber Fabry-Perot Interferometer Based On A Single-Crystal Metal-Organic Framework For The Detection And Quantification Of Benzene And Ethanol At Low Concentrations In Nitrogen Gas, Farhan Mumtaz, Bohong Zhang, Narasimman Subramaniyam, Mohammad Roman, Peter Holtmann, Abhishek Prakash Hungund, Ryan O'Malley, Thomas M. Spudich, Michael Davis, Rex E. Gerald, Jie Huang
Electrical and Computer Engineering Faculty Research & Creative Works
This study reports for the first time, to the best of our knowledge, a real-time detection of ultralow-concentration chemical gases using fiber-optic technology, combining a miniaturized Fabry-Perot interferometer (FPI) with metal-organic frameworks (MOFs). The sensor consists of a short and thick-walled silica capillary segment spliced to a lead-in single-mode fiber (SMF), housing a tiny single crystal of HKUST-1 MOF, imparting chemo selectivity features. Ethanol and benzene gases were tested, resulting in a shift in the FPI interference signal. The sensor demonstrated high sensitivity, detecting ethanol gas concentrations (EGCs) with a sensitivity of 0.428 nm/ppm between 24.9 and 40.11 ppm and …
An Impedance-Source-Based Soft-Switched High Step-Up Dc-Dc Converter With An Active Clamp, Saeed Habibi, Ramin Rahimi, Mehdi Ferdowsi, Pourya Shamsi
An Impedance-Source-Based Soft-Switched High Step-Up Dc-Dc Converter With An Active Clamp, Saeed Habibi, Ramin Rahimi, Mehdi Ferdowsi, Pourya Shamsi
Electrical and Computer Engineering Faculty Research & Creative Works
This article proposes a high step-up dc-dc converter based on a trans-inverse impedance-source structure, in which the voltage gain of the converter is increased by using a lower number of turns ratio of the coupled inductors (CI) windings. The proposed converter achieves a very high voltage gain and a very low voltage stress on the switches. An active clamp is incorporated into the topology of the proposed converter, helping to absorb the energy of the leakage inductances of the CI, and to recycle that energy to the output of the converter to further increase the voltage gain. Furthermore, the active …
Multilayered Energy Management Framework For Extreme Fast Charging Stations Considering Demand Charges, Battery Degradation, And Forecast Uncertainties, Waqas Ur Rehman, Jonathan W. Kimball, Rui Bo
Multilayered Energy Management Framework For Extreme Fast Charging Stations Considering Demand Charges, Battery Degradation, And Forecast Uncertainties, Waqas Ur Rehman, Jonathan W. Kimball, Rui Bo
Electrical and Computer Engineering Faculty Research & Creative Works
To achieve a cost-effective and expeditious charging experience for extreme fast charging station (XFCS) owners and electric vehicle (EV) users, the optimal operation of XFCS is crucial. It is, however, challenging to simultaneously manage the profit from energy arbitrage, the cost of demand charges, and the degradation of a battery energy storage system (BESS) under uncertainties. This article, therefore, proposes a multilayered Mult timescale energy flow management framework for an XFCS by considering long- and short-term forecast uncertainties, monthly demand charges reduction, and BESS life degradation. in the proposed approach, an upper scheduling layer (USL) ensures the overall operation economy …
Advances In Growth, Doping, And Devices And Applications Of Zinc Oxide, Vishal Saravade, Zhe Chuan Feng, Manika Tun Nafisa, Chuanle Zhou, Na Lu, Benjamin Klein, Ian T. Ferguson
Advances In Growth, Doping, And Devices And Applications Of Zinc Oxide, Vishal Saravade, Zhe Chuan Feng, Manika Tun Nafisa, Chuanle Zhou, Na Lu, Benjamin Klein, Ian T. Ferguson
Electrical and Computer Engineering Faculty Research & Creative Works
Zinc oxide is a breakthrough multifunctional material of emerging interest applicable in the areas of electronics, computing, energy harvesting, sensing, optoelectronics, and biomedicine. Zno has a direct and wide bandgap and high exciton binding energy. It is nontoxic, earth-abundant, and biocompatible. However, the growth and characterization of high-quality zno has been a challenge and bottleneck in its development. Efforts have been made to synthesize device-quality zinc oxide and unleash its potential for multiple advanced applications. Zno could be grown as thin films, nanostructures, or bulk, and its properties could be optimized by tuning the growth techniques, conditions, and doping. Zinc …
Continual Online Learning-Based Optimal Tracking Control Of Nonlinear Strict-Feedback Systems: Application To Unmanned Aerial Vehicles, Irfan Ganie, Sarangapani Jagannathan
Continual Online Learning-Based Optimal Tracking Control Of Nonlinear Strict-Feedback Systems: Application To Unmanned Aerial Vehicles, Irfan Ganie, Sarangapani Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
A novel optimal trajectory tracking scheme is introduced for nonlinear continuous-time systems in strict feedback form with uncertain dynamics by using neural networks (NNs). The method employs an actor-critic-based NN back-stepping technique for minimizing a discounted value function along with an identifier to approximate unknown system dynamics that are expressed in augmented form. Novel online weight update laws for the actor and critic NNs are derived by using both the NN identifier and Hamilton-Jacobi-Bellman residual error. A new continual lifelong learning technique utilizing the Fisher Information Matrix via Hamilton-Jacobi-Bellman residual error is introduced to obtain the significance of weights in …
Toward Smart And Sustainable Cement Manufacturing Process: Analysis And Optimization Of Cement Clinker Quality Using Thermodynamic And Data-Informed Approaches, Jardel P. Gonçalves, Taihao Han, Gaurav Sant, Narayanan Neithalath, Jie Huang, Aditya Kumar
Toward Smart And Sustainable Cement Manufacturing Process: Analysis And Optimization Of Cement Clinker Quality Using Thermodynamic And Data-Informed Approaches, Jardel P. Gonçalves, Taihao Han, Gaurav Sant, Narayanan Neithalath, Jie Huang, Aditya Kumar
Electrical and Computer Engineering Faculty Research & Creative Works
Cement manufacturing is widely recognized for its harmful impacts on the natural environment. In recent years, efforts have been made to improve the sustainability of cement manufacturing through the use of renewable energy, the capture of CO2 emissions, and partial replacement of cement with supplementary cementitious materials. To further enhance sustainability, optimizing the cement manufacturing process is essential. This can be achieved through the prediction and optimization of clinker phases in relation to chemical compositions of raw materials and manufacturing conditions. Cement clinkers are produced by heating raw materials in kilns, where both raw material compositions and processing conditions …
Dynamic Model Of Ac-Ac Dual Active Bridge Converter Using The Extended Generalized Average Modeling Framework, Kartikeya Jayadurga Prasad Veeramraju, Jonathan W. Kimball
Dynamic Model Of Ac-Ac Dual Active Bridge Converter Using The Extended Generalized Average Modeling Framework, Kartikeya Jayadurga Prasad Veeramraju, Jonathan W. Kimball
Electrical and Computer Engineering Faculty Research & Creative Works
The ac-ac dual active bridge (DAB) converter is an advanced bidirectional two-port grid interface converter that facilitates active and reactive power flow control between two grids without a dc-link capacitor. This article presents a novel modeling approach for the ac-ac DAB converter using the extended generalized average modeling (EGAM) technique. Unlike the conventional generalized average modeling (GAM) framework, the ac-ac DAB converter's dynamic state variables, including the leakage inductor current and ac grid side LC filters, exhibit grid and switching frequency components, making the standard GAM framework unsuitable for dynamic modeling involving two distinct excitation frequencies. Furthermore, the 2-D GAM …
Understanding Roles And Evaluating Reactivity Of Fly Ashes In Calcium Aluminate Binders, Sai Akshay Ponduru, Taihao Han, Jie Huang, Narayanan Neithalath, Gaurav Sant, Aditya Kumar
Understanding Roles And Evaluating Reactivity Of Fly Ashes In Calcium Aluminate Binders, Sai Akshay Ponduru, Taihao Han, Jie Huang, Narayanan Neithalath, Gaurav Sant, Aditya Kumar
Electrical and Computer Engineering Faculty Research & Creative Works
Calcium aluminate cement (CAC) is an alternative to Portland cement, valued for its superior early strength and thermal resistance. Partially replacing CAC with Fly ash (FA) can reduce carbon footprint and production costs of CAC, producing sustainable cementitious binders. This research investigates on various properties (i.e., hydration kinetics; phase assemblage evolution; compressive strength) of [CAC + FA] binders. Using 13 distinct FAs, up to 50% of CAC was substituted. The study measures hydration kinetics, compressive strength, and employs the number of constraints to estimate FA reactivity. Advanced quantitative analysis draws links between hydration kinetics and compressive strength and elucidate the …
Miniaturized Fluorescence Ph Sensor With Assembly Free Ball Lens On A Tapered Multimode Optical Fiber, Bohong Zhang, Farhan Mumtaz, Muhammad Roman, Dinesh Reddy Alla, Rex E. Gerald, Jie Huang
Miniaturized Fluorescence Ph Sensor With Assembly Free Ball Lens On A Tapered Multimode Optical Fiber, Bohong Zhang, Farhan Mumtaz, Muhammad Roman, Dinesh Reddy Alla, Rex E. Gerald, Jie Huang
Electrical and Computer Engineering Faculty Research & Creative Works
In biochemistry, the absence of a compact, assembly-free pH sensor with high sensitivity and signal-to-noise ratio has been a persistent hurdle in achieving accurate pH measurements in real time, particularly in complex liquid environments. This manuscript introduces what we believe to be a novel solution in the form of a miniaturized pH sensor utilizing an assembly-free ball lens on a tapered multimode optical fiber (TMMF), offering the potential to revolutionize pH sensing in biochemical applications. A multimode optical fiber (MMF) was subjected to tapering processes, leading to the creation of an ultra-thin needle-like structure with a cross-sectional diameter of about …
Unsupervised Blstm-Based Electricity Theft Detection With Training Data Contaminated, Qiushi Liang, Shengjie Zhao, Jiangfan Zhang, Hao Deng
Unsupervised Blstm-Based Electricity Theft Detection With Training Data Contaminated, Qiushi Liang, Shengjie Zhao, Jiangfan Zhang, Hao Deng
Electrical and Computer Engineering Faculty Research & Creative Works
Electricity theft can cause economic damage and even increase the risk of outage. Recently, many methods have implemented electricity theft detection on smart meter data. However, how to conduct detection on the dataset without any label still remains challenging. In this article, we propose a novel unsupervised two-stage approach under the assumption that the training set is contaminated by attacks. Specifically, the method consists of two stages: (1) a Gaussian mixture model is employed to cluster consumption patterns with respect to different habits of electricity usage, and with the goal of improving the accuracy of the model in the posterior …
Design Of Experiment Analysis On Multiple Pim Sources In An Rf Antenna System, Shengxuan Xia, Yuchu He, Haicheng Zhou, Hanfeng Wang, Chulsoon Hwang
Design Of Experiment Analysis On Multiple Pim Sources In An Rf Antenna System, Shengxuan Xia, Yuchu He, Haicheng Zhou, Hanfeng Wang, Chulsoon Hwang
Electrical and Computer Engineering Faculty Research & Creative Works
Passive intermodulation (PIM) has been identified as one of the common root causes for receiving sensitivity degradation (desense) on radiofrequency (RF) antennas working in frequency-division duplex mode. The component-level PIM characterization and simulation have been well-established over the years. However, the study has been using an ideal 50 Ω transmission line system while antenna modules are more complicated than a simple transmission line structure. Moreover, the metallic contacts can exist in multiple locations with different connection topologies in real applications. This paper provides a method to simulate the PIM performance caused by the metallic contacts in a practical environment. In …