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Articles 901 - 930 of 17246
Full-Text Articles in Entire DC Network
A High Step-Up Soft-Switched Converter Based On Coupled Inductor And Current-Fed Voltage Multiplier, Koosha Choobdari Omran, Reza Beiranvand, Pourya Shamsi
A High Step-Up Soft-Switched Converter Based On Coupled Inductor And Current-Fed Voltage Multiplier, Koosha Choobdari Omran, Reza Beiranvand, Pourya Shamsi
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, a novel non-isolated DC-DC converter that combines coupled inductor (CI) and voltage multiplier (VM) techniques is proposed. The leakage energy of the CI is effectively recycled, and soft-switching conditions are achieved for all switches and diodes. Resonance between the leakage inductor of the CI and VM capacitors provides soft-switching conditions, without requiring a separate resonant tank. The use of VM stages not only lowers the voltage stress on semiconductor components but also allows for the use of low-voltage-rated devices, leading to reduced conduction losses, lower cost, and improved efficiency. High voltage gain can be achieved by appropriately …
Balanced Benchmarking Of Zero-Shot And Rag Approaches For Biomedical Term Normalization, Thanh Son Do, Daniel B. Hier, Tayo Obafemi-Ajayi
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 …
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 …
Modeling Of Slot-Backed Microstrip Line For Emi Applications, Jongsuk Hyun, Wenchang Huang, Chulsoon Hwang
Modeling Of Slot-Backed Microstrip Line For Emi Applications, Jongsuk Hyun, Wenchang Huang, Chulsoon Hwang
Electrical and Computer Engineering Faculty Research & Creative Works
Radiated emissions from the noise-generating components in modern electronic devices are a significant concern for both electromagnetic interference and RF interference. Shielding cans are commonly used to suppress emissions from noise sources, but accurate shielding effectiveness evaluation requires a clean, well-defined radiation source that can reliably mimic real emissions for repeatable measurements. Slot-backed microstrip antennas provide a practical alternative to loop antennas, offering zero height, low parasitic radiation, and seamless printed circuit board integration. This article proposes an analytical model for estimating the magnetic dipole moment of slot-backed microstrip structures. The model captures both the discontinuity effects and radiated characteristics …
Spatially Distributed Optical Fiber Sensing With Weak Fiber Bragg Grating Arrays Based On Microwave Photonics, Wassana Naku, Osamah Alsalman, Chen Zhu
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 …
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 …
Topology And Parameter Joint Identification In Imbalanced Low-Voltage Distribution Networks Based On Load Characteristic Propagation, Yanan Zhang, Gan Zhou, Huan Mao, Wei Gu, Yanjun Feng, Rui Bo
Topology And Parameter Joint Identification In Imbalanced Low-Voltage Distribution Networks Based On Load Characteristic Propagation, Yanan Zhang, Gan Zhou, Huan Mao, Wei Gu, Yanjun Feng, Rui Bo
Electrical and Computer Engineering Faculty Research & Creative Works
Low-voltage distribution networks often suffer from incomplete or outdated network records, making it challenging to obtain the topology and line parameters under actual operating conditions. To address this issue, a joint identification method is proposed based on the propagation of load transient characteristics. First, the principle of load characteristic propagation is elaborated, and the concept of coupling impedance is introduced. Second, a set of linear regression equations is established based on the changes in current and voltage of the terminal measurements before and after load switching, and then these equations are solved using the least squares method to form the …
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 …
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 …
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
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 …
In-Situ Thermographic Monitoring And Numerical Simulations Of Laser-Foil-Printing Additive Manufacturing, Tunay Turk, Tao Liu, Chia Hung Hung, Richard Billo, Jonghyun Park, Ming C. Leu
In-Situ Thermographic Monitoring And Numerical Simulations Of Laser-Foil-Printing Additive Manufacturing, Tunay Turk, Tao Liu, Chia Hung Hung, Richard Billo, Jonghyun Park, Ming C. Leu
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Laser-foil-printing (LFP) is an additive manufacturing (AM) technique offering advantages over traditional powder-based methods. A deeper understanding of the melt pool dynamics is crucial for optimizing process parameters and achieving high-quality builds. This paper presents a combined approach utilizing numerical simulations and in-situ thermographic monitoring to investigate the relationship between scanning strategies, melt pool dimensions, and cooling rate in LFP. The numerical simulations are employed to predict melt pool behavior using a time-dependent thermal finite element analysis (FEA). Results demonstrate that the simulations accurately predict melt pool dimensions, showing strong agreement with experimental data. Simultaneously, real-time melt pool dynamics were …
Implementation Of Miniature Tensile Specimens In Mechanical Properties Assessment Of Directed Energy Deposited Ti-6al-4v: As-Built And Heat Treated, Saeid Alipour, Sung Heng Wu, Frank Liou, Arezoo Emdadi
Implementation Of Miniature Tensile Specimens In Mechanical Properties Assessment Of Directed Energy Deposited Ti-6al-4v: As-Built And Heat Treated, Saeid Alipour, Sung Heng Wu, Frank Liou, Arezoo Emdadi
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Within the last two decades, additive manufacturing (AM), a. k.a. 3D printing, has provided promising solutions for producing near-net-shape components with intricate geometries. From the material perspective, titanium alloys, one of humankind's most essential structural materials, are being considered the first candidate for AMed parts due to their unique characteristics in strength-weight-corrosion combinations. However, measuring the mechanical properties of designed geometry remains a challenge due to the ineffectiveness of conventional standard tensile specimens in assessing the site-specific and intricate geometries. In AM, the current approach often consists of evaluating standard-sized samples with the assumption that components with complex geometries possess …
A Ground Thermal Vacuum Facility For Simulating Cryogenic Space Environment Conditions, Emmanuel Kofi Asuako Wie-Addo, Lucas Scott, Daoru Han
A Ground Thermal Vacuum Facility For Simulating Cryogenic Space Environment Conditions, Emmanuel Kofi Asuako Wie-Addo, Lucas Scott, Daoru Han
Mechanical and Aerospace Engineering Faculty Research & Creative Works
This work presents the ongoing progress of a vacuum facility upgrade at the Gas and Plasma Dynamics Laboratory (GPDL) at Missouri University of Science and Technology. A movable shroud has been fabricated and installed to enable the simulation of extreme cold conditions. The cooling rate of the shroud, a dummy test article, and a platform, using liquid nitrogen as the thermal fluid, is analyzed and reported under varying vacuum conditions for cryogenic runs. Preliminary testing revealed substantial thermal exchange between the shroud and the chamber walls, underscoring the necessity for implementing effective thermal isolation measures to mitigate heat transfer.
Multifidelity Dust Erosion Analysis Of Mars Entry Vehicles, Adam Boland, Dominic Zanti, Serhat Hosder, Andrew Hinkle
Multifidelity Dust Erosion Analysis Of Mars Entry Vehicles, Adam Boland, Dominic Zanti, Serhat Hosder, Andrew Hinkle
Mechanical and Aerospace Engineering Faculty Research & Creative Works
The objective of this paper is to present a multifidelity approach for estimating recession rate and kinetic energy impact rate on the surface of planetary entry vehicles operating in dusty atmospheric environments at hypersonic speeds. The multifidelity model used a co-Kriging approach that combined a low-fidelity correlation with a correction factor from high-fidelity CFD solutions. The developed multifidelity model enables efficient and accurate exploration of a design space to determine at what conditions encountering dust is most dangerous to TPS survivability. Two sample problems are used to demonstrate the effectiveness of the approach: the Mars 2020 lander and a HIAD-type …
Improving Neural Network Efficiency With Multi-Fidelity And Dimensionality Reduction Techniques, Vignesh Sella, Thomas O'Leary-Roseberry, Xiaosong Du, Mengwu Guo, Joaquim R.R.A. Martins, Omar Ghattas, Karen Willcox, Anirban Chaudhuri
Improving Neural Network Efficiency With Multi-Fidelity And Dimensionality Reduction Techniques, Vignesh Sella, Thomas O'Leary-Roseberry, Xiaosong Du, Mengwu Guo, Joaquim R.R.A. Martins, Omar Ghattas, Karen Willcox, Anirban Chaudhuri
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Design problems in aerospace engineering often require numerous evaluations of expensive to-evaluate high-fidelity models, resulting in prohibitive computational costs. One way to address the computational cost is through building surrogates, such as deep neural networks (DNNs). However, DNNs may only be an effective surrogate when sufficient evaluations of the high-fidelity model are required such that the up-front training cost is amortized, or in situations that require real-time responses (such as interactive visualizations). Typically, the data requirements for adequately accurate training of DNNs are often impractical for engineering applications. To alleviate this issue, the proposed work utilizes output dimensionality reduction along …
Tensile Behavior Of Directed Energy Deposited Bi-Metallic Ti-Ni-Based Alloy At Interfacial Area, Yitao Chen, Cesar Ortiz Rios, Frank Liou
Tensile Behavior Of Directed Energy Deposited Bi-Metallic Ti-Ni-Based Alloy At Interfacial Area, Yitao Chen, Cesar Ortiz Rios, Frank Liou
Mechanical and Aerospace Engineering Faculty Research & Creative Works
A Ti-Ni-based bi-metallic shape memory alloy was fabricated using directed energy deposition, and the tensile testing behavior at two sections after post-heat treatments were focused. The Ti-rich Ti-Ni-Cu ternary shape memory alloy was first fabricated on a TiNi shape memory alloy with near-equiatomic composition to achieve multi-functional shape memory behaviors using powder-based additive manufacturing. The bi-metallic part then underwent 400°C and 600°C heat treatment at the interfacial area, and the interfacial area was subject to tensile loading and unloading. The digital image correlation technique was applied to extract the tensile stress–strain behavior and map out the local strain evolution of …
Characterizing Intralaminar Distal Crack And Delamination In Multidirectional Laminates Under Low Velocity Impact: Modeling Approach With Ultrasound Testing Validation, Niildiip Chandraa, Rachel Van Lear, Arief Yudhanto, Yuqing Zhao, David A. Jack, Douglas E. Smith
Characterizing Intralaminar Distal Crack And Delamination In Multidirectional Laminates Under Low Velocity Impact: Modeling Approach With Ultrasound Testing Validation, Niildiip Chandraa, Rachel Van Lear, Arief Yudhanto, Yuqing Zhao, David A. Jack, Douglas E. Smith
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Multidirectional laminated composites are essential for load-bearing structures, especially under frequent impact loading. While existing modeling techniques simulate various impact damage modes, our understanding of the underlying mechanisms, specifically the initiation and progression of intralaminar distal cracks and interlaminar delamination, needs improvement. Validating these mechanisms is crucial for enhancing modeling accuracy and expediting the design process. In this work, we propose a three-dimensional finite element modeling (3D FEM) approach aimed at elucidating the impact damage mechanisms in multidirectional carbon fiber reinforced polymer (CFRP). Our model incorporates cohesive zone models (CZM) to simulate the behavior of intralaminar cracks at distal points …
Sift Feature-Based Relative Altitude Estimation Enhanced With Siamese Network, Shirin Nasr-Esfahani, S. Jagannathan
Sift Feature-Based Relative Altitude Estimation Enhanced With Siamese Network, Shirin Nasr-Esfahani, S. Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
In GPS-denied environments or when GPS signals are unreliable or unavailable, alternative methods of accurate localization with coordinate generation become critical. To address localization, the scale-invariant feature transform (SIFT) algorithm, along with its numerous adaptations, is extensively utilized in computer vision and remote sensing for matching image features to identify objects and perform localization. This article presents a novel approach for estimating the relative altitude of unmanned aerial vehicles (UAVs) using SIFT features' scale (size), omitting the need for additional data like camera intrinsic parameters, as well as extensive image datasets are also required for training. Furthermore, the approach enhances …
Microwave Photonics-Assisted Interrogation Of Fiber-Optic Interferometric Sensors With Joint Frequency-Time Domain Analysis, Ruimin Jie, Jie Huang, Chen Zhu
Microwave Photonics-Assisted Interrogation Of Fiber-Optic Interferometric Sensors With Joint Frequency-Time Domain Analysis, Ruimin Jie, Jie Huang, Chen Zhu
Electrical and Computer Engineering Faculty Research & Creative Works
Fiber-optic interferometers are widely used in localized sensing applications due to their compact size, high sensitivity, and immunity to electromagnetic interference. In this paper, we propose and experimentally demonstrate a novel interrogation scheme for fiber-optic interferometric sensors, utilizing microwave photonics (MWP) and joint frequency-time domain analysis. As a proof of concept, a miniature fiber in-line Fabry-Perot interferometer (FPI) is integrated with a microwave photonic single-passband filter, enhanced by a dispersion compensation module to improve sensing performance. By applying an inverse Fourier transform to the system's complex frequency response, the time-domain representation of the signal is obtained, translating spectral shifts of …
Enhanced Multidimensional Harmonic Retrieval In Mimo Wireless Channel Sounding, Yanming Zhang, Wenchao Xu, A. Long Jin, Tianquan Tang, Min Li, Peifeng Ma, Lijun Jiang, Steven Gao
Enhanced Multidimensional Harmonic Retrieval In Mimo Wireless Channel Sounding, Yanming Zhang, Wenchao Xu, A. Long Jin, Tianquan Tang, Min Li, Peifeng Ma, Lijun Jiang, Steven Gao
Electrical and Computer Engineering Faculty Research & Creative Works
This paper introduces a recursive parallel dynamic mode decomposition (RPDMD) scheme tailored for multidimensional harmonic retrieval (MHR), specifically applied to MIMO wireless channel sounding. The RPDMD algorithm is devised to address the complexities inherent in multidimensional scenarios, leveraging the dynamic mode decomposition (DMD) framework within a recursive parallel structure. Initially, the observed tensorial multidimensional harmonic data is transformed into a two-dimensional matrix format along the r-th dimension. Subsequently, DMD dissects this matrix data into eigenvalues and their associated modes. The real and imaginary components of the DMD eigenvalues yield damping factors and frequencies in the r-th dimension, respectively. Furthermore, recursive …
Miniaturized Wearable Biosensors For Continuous Health Monitoring Fabricated Using The Femtosecond Laser-Induced Graphene Surface And Encapsulated Traces And Electrodes, Homayoon Soleimani Dinani, Tatianna Reinbolt, Bohong Zhang, Ganggang Zhao, Rex E. Gerald, Zheng Yan, Jie Huang
Miniaturized Wearable Biosensors For Continuous Health Monitoring Fabricated Using The Femtosecond Laser-Induced Graphene Surface And Encapsulated Traces And Electrodes, Homayoon Soleimani Dinani, Tatianna Reinbolt, Bohong Zhang, Ganggang Zhao, Rex E. Gerald, Zheng Yan, Jie Huang
Electrical and Computer Engineering Faculty Research & Creative Works
Wearable sensors are increasingly being used as biosensors for health monitoring. Current wearable devices are large, heavy, invasive, skin irritants, or not continuous. Miniaturization was chosen to address these issues, using a femtosecond laser-conversion technique to fabricate miniaturized laser-induced graphene (LIG) sensor arrays on and encapsulated within a polyimide substrate. The femtosecond laser-converted conductive traces can have a size of 20 to 2 μm compared to the traditionally larger CO2 laser dimensions of around 300 to 100 μm. This marks a 93-98% decrease in trace size when using a femtosecond laser. This miniaturization allows for the ability to process temperature, …
A Low-Frequency-Stable Higher-Order Isogeometric Discretization Of The Augmented Electric Field Integral Equation, Maximilian Nolte, Riccardo Torchio, Sebastian Schöps, Jürgen Dölz, Felix Wolf, Albert E. Ruehli
A Low-Frequency-Stable Higher-Order Isogeometric Discretization Of The Augmented Electric Field Integral Equation, Maximilian Nolte, Riccardo Torchio, Sebastian Schöps, Jürgen Dölz, Felix Wolf, Albert E. Ruehli
Electrical and Computer Engineering Faculty Research & Creative Works
This contribution investigates the connection between Iso geometric analysis (IGA) and integral equation (IE) methods for full-wave electromagnetic problems up to the low-frequency limit. The proposed spline-based IE method allows for an exact representation of the model geometry described in terms of nonuniform rational B-splines (NURBS) without meshing. This is particularly useful when high accuracy is required or when meshing is cumbersome, for instance, during the optimization of electric components. The augmented electric field IE (EFIE) is adopted, and the deflation method is applied, so the low-frequency breakdown is avoided. The extension to higher-order basis functions is analyzed and the …
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
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 …
Component Level Em Emission Assessment And Management For Rf Desensitization, Xiangrui Su, Wenchang Huang, Junghee Cho, Joonki Paek, Chulsoon Hwang
Component Level Em Emission Assessment And Management For Rf Desensitization, Xiangrui Su, Wenchang Huang, Junghee Cho, Joonki Paek, Chulsoon Hwang
Electrical and Computer Engineering Faculty Research & Creative Works
Radio frequency (RF) desensitization is a common issue caused by high-speed components in modern electronic devices. Consequently, numerous studies have focused on characterizing and quantifying electromagnetic (EM) emission sources by using near field scanning to detect EM noise sources. However, before near field scanning, no predetermined threshold is available to quickly assess whether an EM noise source will pose RF desensitization risks in the receiving antenna. This article presents a method to optimize near field scanning settings through EM emission management analysis. Drawing on experience from numerous EM emission studies, we introduce an EM emission management procedure for two common …
Explainable And Safety Aware Deep Reinforcement Learning-Based Control Of Nonlinear Discrete-Time Systems Using Neural Network Gradient Decomposition, Behzad Farzanegan, S. Jagannathan
Explainable And Safety Aware Deep Reinforcement Learning-Based Control Of Nonlinear Discrete-Time Systems Using Neural Network Gradient Decomposition, Behzad Farzanegan, S. Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
This paper presents an explainable deep-reinforcement learning (DRL)-based safety-aware optimal adaptive tracking (SOAT) scheme for a class of nonlinear discrete-time (DT) affine systems subject to state inequality constraints. The DRL-based SOAT utilizes a multilayer neural network (MNN)-based actor-critic to estimate the cost function and optimal policy while the MNN update laws are tuned both using the singular value decomposition (SVD) of activation function gradient in order to mitigate the vanishing gradient issue and safety-aware Bellman error at each layer. An approximate safety-aware optimal policy is developed using Karush–Kuhn–Tucker (KKT) conditions by incorporating the higher-order control barrier function (HOCBF) into the …
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
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 …
Microwave Photonic Fiber Ring Resonator For Optical Sensing Based On In-Ring And Out-Of-Ring Modulation, Shiyu Li, Chen Zhu
Microwave Photonic Fiber Ring Resonator For Optical Sensing Based On In-Ring And Out-Of-Ring Modulation, Shiyu Li, Chen Zhu
Electrical and Computer Engineering Faculty Research & Creative Works
Intensity-modulated optical fiber sensors (IM-OFSs) have garnered significant research interest due to their advantageous characteristics, including simplified fabrication procedures, cost-efficient systems, and straightforward signal demodulation, leading to their widespread application across diverse fields. Nevertheless, the multiplexing technique for IM-OFSs remains underexplored, primarily because isolating the contributions of individual sensors within the system using traditional power measurements poses a significant challenge. In this study, we introduce and experimentally validate a novel approach leveraging a simple microwave-photonic fiber ring resonator (MWP-FRR). This approach enables the concurrent interrogation of two IM-OFSs based on an in-and-out-of-ring-modulation (IORM) strategy. The transmission losses of both IM-OFSs …
Advancing Temperature Monitoring Of The Bottom Anode In A Direct Current Electric Arc Furnace Operations With Distributed Optical Fiber Sensors., Ogbole Collins Inalegwu, Rony Kumer Saha, Yeshwanth Reddy Mekala, Farhan Mumtaz, Nicholas Dionise, Zane Voss, Jeffrey D. Smith, Ronald J. O'Malley, Rex E. Gerald, Jie Huang
Advancing Temperature Monitoring Of The Bottom Anode In A Direct Current Electric Arc Furnace Operations With Distributed Optical Fiber Sensors., Ogbole Collins Inalegwu, Rony Kumer Saha, Yeshwanth Reddy Mekala, Farhan Mumtaz, Nicholas Dionise, Zane Voss, Jeffrey D. Smith, Ronald J. O'Malley, Rex E. Gerald, Jie Huang
Electrical and Computer Engineering Faculty Research & Creative Works
The bottom anode in the Direct Current Electric Arc Furnace (DC EAF) is critical for completing the electrical circuit necessary for sustaining the arc within the furnace. For pin-type bottom anodes, monitoring of the temperature of select pins instrumented with thermocouples is performed to track bottom wear in the EAF and inform the operator when the furnace should be removed from service. This work presents the results from a plant trial using distributed temperature monitoring of bottom anode pins in a 165-ton DC EAF over a two-month service period utilizing two optical fiber sensing techniques: fiber Bragg grating (FBG) and …
Training Neural Networks With A Self-Adaptive Ant Colony Algorithm, Ashraf M. Abdelbar, Donald C. Wunsch
Training Neural Networks With A Self-Adaptive Ant Colony Algorithm, Ashraf M. Abdelbar, Donald C. Wunsch
Electrical and Computer Engineering Faculty Research & Creative Works
ACOR is a well-established ant colony optimization algorithm that has been applied to neural network training. We present an approach for the dynamic adaptation of the ACOR algorithm's search intensification/diversification parameter q, based on using several pre-specified parameter configurations, which we call personalities. Before an ant begins to generate a candidate solution, it stochastically adopts a personality based on the relative past success of the different personalities. The success of a personality is measured, in turn, by the relative quality of previous solutions generated by ants adopting that personality. The premise of our approach is that some personalities will be …
Annotated 3d Point Cloud Dataset For Traffic Management In Simulated Urban Intersections, Elham Binshaflout, Chaima Zaghouani, Nawfal Guefrachi, Charalampos Antoniadis, Hakim Ghazzai, Ahmad Alsharoa, Gianluca Setti
Annotated 3d Point Cloud Dataset For Traffic Management In Simulated Urban Intersections, Elham Binshaflout, Chaima Zaghouani, Nawfal Guefrachi, Charalampos Antoniadis, Hakim Ghazzai, Ahmad Alsharoa, Gianluca Setti
Electrical and Computer Engineering Faculty Research & Creative Works
Ensuring accurate traffic perception and road safety in complex urban environments remains a significant challenge. Advanced traffic monitoring increasingly relies on deep learning, which requires large data volumes. However, existing datasets are often limited to CCTV video footage or focus on dynamic scenarios captured by sensors mounted on ego vehicles. This narrow perspective reduces the effectiveness of comprehensive traffic monitoring, particularly for LiDAR sensors, which typically capture only the vehicle's viewpoint and miss critical areas such as intersections and pedestrian crossings. To address these limitations, we propose a holistic strategy for rapid data collection in urban settings using simulated 3D …