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Articles 30871 - 30900 of 196361

Full-Text Articles in Engineering

Improved System For Measuring Contact Induced Harmonics, Rui Mi, Leonhard Petzel, Sam Bai, Seyedmostafa Mousavi, Lijuan Qu, Yiqiang Zhang, David Pommerenke Jan 2023

Improved System For Measuring Contact Induced Harmonics, Rui Mi, Leonhard Petzel, Sam Bai, Seyedmostafa Mousavi, Lijuan Qu, Yiqiang Zhang, David Pommerenke

Electrical and Computer Engineering Faculty Research & Creative Works

Portable wireless devices cannot avoid electrical contact due to assembly and maintenance requirements. In this paper, an improved test system is proposed for systematic investigation of harmonic distortion induced by metal-to-metal contacts. The system supports harmonic distortion measurements, DC resistance measurements, fine control of contact force or contraction and automatic re-mating for statistical purposes. In this regard, forward and reflected harmonic signals are measured and ultrasonic vibration is applied to cure contacts. A novel sample holder structure is designed and fabricated as a test vehicle for the measurements.

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A Combined Model For Transient And Self-Heating Of Snapback Type Esd Protection Devices, Xin Yan, Seyed Mostafa Mousavi, Li Shen, Yang Xu, Wei Zhang, Sergej Bub, Steffen Holland, David Pommerenke, Daryl G. Beetner Jan 2023

A Combined Model For Transient And Self-Heating Of Snapback Type Esd Protection Devices, Xin Yan, Seyed Mostafa Mousavi, Li Shen, Yang Xu, Wei Zhang, Sergej Bub, Steffen Holland, David Pommerenke, Daryl G. Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

A simplified physics-based model for predicting the transient response and self-heating behavior of silicon-controlled rectifier (SCR) snapback-type transient voltage suppressors (TVS) is presented. Comparisons of the predicted quasi-static behavior and transient waveforms with measurements suggest that the proposed model accurately captures the most important characteristics of the device. Its simplified nature means it can be easily tuned using only data obtained from package-level measurements.

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Simulating Multi-Tapered Coaxial Baluns With An Isogeometric Surface Integral Equation Method, Maximilian Nolte, Riccardo Torchio, Sebastian Schops, Albert E. Ruehli Jan 2023

Simulating Multi-Tapered Coaxial Baluns With An Isogeometric Surface Integral Equation Method, Maximilian Nolte, Riccardo Torchio, Sebastian Schops, Albert E. Ruehli

Electrical and Computer Engineering Faculty Research & Creative Works

In this contribution we present the numerical analysis of multi-tapered coaxial baluns simulated with an Iso geometric surface integral equation method and demonstrate thereby an application of the work, which completes the studies on electrostatics conducted in [6] with the full-wave case.

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Deep-Learning-Based Accurate Beamforming Prediction Using Lidar-Assisted Network, Omar Rinchi, Ahmad Alsharoa, Ibrahem Shatnawi Jan 2023

Deep-Learning-Based Accurate Beamforming Prediction Using Lidar-Assisted Network, Omar Rinchi, Ahmad Alsharoa, Ibrahem Shatnawi

Electrical and Computer Engineering Faculty Research & Creative Works

Beamforming optimization can enhance the next-generation wireless networks. However, finding the optimal beamforming in real-time is hard due to the need for large beam training overhead. The problem can be more challenging in dynamic environments with small coherence channel time. In this paper, we propose an accurate beam prediction solution using light detection and ranging (LiDAR)-assisted radio frequency (RF) system. More specifically, we propose a deep-learning model based on long-sort term memory (LSTM) to predict future beam indices from a set of pre-defined beam steering codebook. In addition to solving the beamforming overhead problem, the proposed deep learning approach is …

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Accelerated Statistical Eye Diagram Estimation Method For Efficient Signal Integrity Analysis, Junyong Park, Youngwoo Kim, Donghyun Kim Jan 2023

Accelerated Statistical Eye Diagram Estimation Method For Efficient Signal Integrity Analysis, Junyong Park, Youngwoo Kim, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

This article proposes an accelerated statistical eye diagram estimation method for efficient signal integrity (SI) analysis. An eye diagram is a critical metric in the SI analysis, however obtaining an eye diagram is time-consuming in simulation. The required time might be a few weeks depending on the complexity. Because the eye diagram is obtained by superposition of the received waveforms. Statistical eye diagram estimation methods were proposed to make the eye diagram acquisition efficient, however, it still has a limited improvement due to a large number of convolution operations. To address this limitation, the proposed method includes two approaches: (i) …

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Towards Robust Consensus For Intelligent Decision-Making In Iot Blockchain Networks, Charles Rawlins, S. (Sarangapani) Jagannathan Jan 2023

Towards Robust Consensus For Intelligent Decision-Making In Iot Blockchain Networks, Charles Rawlins, S. (Sarangapani) Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

Distributed consensus is the core aspect of blockchain protocol security design. Recent protocols like IOTA have improved concurrency and scalability over Proof-of-work (PoW) with Bitcoin but have core design decisions that are inefficient for limited devices and do not take advantage of previous network experience to reduce calculations. This work proposes the first blockchain consensus protocol based on active machine-learning decisions, called Proof-of-history (PoH). PoH is setup as a distributed reinforcement-learning task for monitoring classification and training of blockchain transactions with an inner deep classifier. Early theoretical analysis and simulations show that PoH is robust to uncoordinated byzantine attacks through …

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Multiple Uav-Lidar Placement Optimization Under Road Priority And Resolution Requirements, Zachary Osterwisch, Omar Rinchi, Ahmad Alsharoa, Hakim Ghazzai, Yehia Massoud Jan 2023

Multiple Uav-Lidar Placement Optimization Under Road Priority And Resolution Requirements, Zachary Osterwisch, Omar Rinchi, Ahmad Alsharoa, Hakim Ghazzai, Yehia Massoud

Electrical and Computer Engineering Faculty Research & Creative Works

An unmanned aerial vehicle (UAV) integrated with the remote sensing technology of light detection and ranging (LiDAR) can provide accurate and real-time road traffic information. In this paper, we propose to equip UAVs with LiDAR sensors for Intelligent Transportation Systems (ITS) applications. The goal is to find the optimal 3D placement of multiple UAV-LiDAR (ULiDs) for a given road segmentation. We formulate an optimization problem to find the optimal placement such that the road coverage efficiency is maximized. The optimization problem is constrained by notable ULiD specifications such as field-of-view (FoV), point-cloud density, geographic information system (GIS) location, and road …

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Implementing The Fast Full-Wave Electromagnetic Forward Solver Using The Deep Convolutional Encoder-Decoder Architecture, He Ming Yao, Lijun Jiang, Michael Ng Jan 2023

Implementing The Fast Full-Wave Electromagnetic Forward Solver Using The Deep Convolutional Encoder-Decoder Architecture, He Ming Yao, Lijun Jiang, Michael Ng

Electrical and Computer Engineering Faculty Research & Creative Works

In this communication, a novel deep learning (DL)-based solver is proposed for the electromagnetic forward (EMF) process. It is based on the complex-valued deep convolutional neural networks (DConvNets) comprising an encoder network and a corresponding decoder network with pixel-wise regression layer. The encoder network takes the incident EM wave and the contrast (permittivity) distribution of the object as the input. It channels the processed data into the corresponding decoder network to predict the total EM field due to the scatter of the input incident EM wave. The training of the proposed DConvNets is done using the simple synthetic dataset. Due …

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Usdot Tier-1 University Transportation Center For Advancing Cybersecurity Research And Education, Yunpeng Jack Zhang, Kailai Wang, Lingguang Song, Amaury Lendasse, Houbing Herbert Song, Zhu Han, Rakesh Verma, Arlei Silva, Carlos Rubio-Medrano, Zhixia Richard Li, Guohui Zhang Jan 2023

Usdot Tier-1 University Transportation Center For Advancing Cybersecurity Research And Education, Yunpeng Jack Zhang, Kailai Wang, Lingguang Song, Amaury Lendasse, Houbing Herbert Song, Zhu Han, Rakesh Verma, Arlei Silva, Carlos Rubio-Medrano, Zhixia Richard Li, Guohui Zhang

Engineering Management and Systems Engineering Faculty Research & Creative Works

The Transportation Cybersecurity Center for Advanced Research and Education (Cyber-Care) is a Us Department of Transportation (Usdot) Tier-1 University Transportation Center (Utc) Funded in 2023. Cyber-Care Primarily Focuses on the Usdot Statutory Research Priority Area of 'reducing Transportation Cybersecurity Risks.' Cyber-Care Aims to Establish a Fundamental Knowledge Basis and Explore Advanced Theory to Mitigate the Impacts of Large-Scale Cyberattacks on Transportation Infrastructure and Connected and Automated Vehicle (Cav) Systems. the Research Projects at Cyber-Care Will Develop Conceptual Frameworks, Construct Comprehensive Datasets, Explore Novel Analytical Approaches, Support the Implementation of Public Policies and Infrastructure Investments, and Build a High-Quality Industry Workforce …

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A Computational Mapping Of Online News Deserts On African News Websites, Dani Madrid-Morales, Joan Ramon Rodríguez‐Amat, Peggy Lindner Jan 2023

A Computational Mapping Of Online News Deserts On African News Websites, Dani Madrid-Morales, Joan Ramon Rodríguez‐Amat, Peggy Lindner

Engineering Management and Systems Engineering Faculty Research & Creative Works

To date, the study of news deserts, geographic spaces lacking local news and information, has largely focused on countries in the Global North, particularly the United States, and has predominantly been interested in the causes and consequences of the disappearance of local media outlets (e.g., newspapers and TV stations) to the social fabric of a community. In this article, we extend the concept of "news deserts" by drawing on literature on the geography of news in Africa, where information voids have long been documented but have not been studied within the conceptual framework of news deserts. Using computational tools, we …

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Show-Me Resilience: Assessing And Reconciling Rural Leaders’ Perceptions Of Climate Resilience In Missouri, Zachary J. Miller, Caleb O'Brien, Casey I. Canfield, Lauren Sullivan Jan 2023

Show-Me Resilience: Assessing And Reconciling Rural Leaders’ Perceptions Of Climate Resilience In Missouri, Zachary J. Miller, Caleb O'Brien, Casey I. Canfield, Lauren Sullivan

Engineering Management and Systems Engineering Faculty Research & Creative Works

Rural areas of the United States play a vital role in coping with, adapting to and mitigating climate change, yet they often lag urban areas in climate planning and action. Rural leaders—e.g., policymakers, state/federal agency professionals, non-profit organization leadership, and scholars – are pivotal for driving the programs and policies that support resilient practices, but our understanding of their perspectives on climate resilience writ large is limited. We conducted semi-structured interviews with 23 rural leaders in Missouri to elucidate their conceptualizations of climate resilience and identify catalysts and constraints for climate adaptation planning and action across rural landscapes. We investigated …

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Deep Reinforcement Learning For Approximate Policy Iteration: Convergence Analysis And A Post-Earthquake Disaster Response Case Study, Abhijit Gosavi, L. (Lesley) H. Sneed, L. A. Spearing Jan 2023

Deep Reinforcement Learning For Approximate Policy Iteration: Convergence Analysis And A Post-Earthquake Disaster Response Case Study, Abhijit Gosavi, L. (Lesley) H. Sneed, L. A. Spearing

Engineering Management and Systems Engineering Faculty Research & Creative Works

Approximate Policy Iteration (API) is a Class of Reinforcement Learning (RL) Algorithms that Seek to Solve the Long-Run Discounted Reward Markov Decision Process (MDP), Via the Policy Iteration Paradigm, Without Learning the Transition Model in the Underlying Bellman Equation. Unfortunately, These Algorithms Suffer from a Defect Known as Chattering in Which the Solution (Policy) Delivered in Each Iteration of the Algorithm Oscillates between Improved and Worsened Policies, Leading to Sub-Optimal Behavior. Two Causes for This that Have Been Traced to the Crucial Policy Improvement Step Are: (I) the Inaccuracies in the Policy Improvement Function and (Ii) the Exploration/exploitation Tradeoff Integral …

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Modeling Of A Microstrip Line Referenced To A Meshed Return Plane, Zeyi Sun, Jian Liu, Xiaoyan Xiong, Yuan Liu, Victor Khilkevich, Donghyun Kim, Daryl G. Beetner Jan 2023

Modeling Of A Microstrip Line Referenced To A Meshed Return Plane, Zeyi Sun, Jian Liu, Xiaoyan Xiong, Yuan Liu, Victor Khilkevich, Donghyun Kim, Daryl G. Beetner

Engineering Management and Systems Engineering Faculty Research & Creative Works

Transmission Lines Referenced to Meshed Return Planes Are Widely Used Because of the Physical Flexibility Imparted by the Meshed Plane. Poor Accounting for the Meshed Ground, However, Can Lead to Severe Signal Integrity and Radio Frequency Interference Issues. Full-Wave Simulation Can Characterize the Electrical Performance at an Early Design Stage, But It is Both Time and Computational Resource Consuming. to Make the Simulation More Efficient, a Method is Proposed in This Study to Model Transmission Lines with a Meshed Reference Ground using 2D Analysis. the 2D Analysis is Performed at Several Locations Along the Length of the Trace above the …

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A Resilience-Oriented Multi-Stage Adaptive Distribution System Planning Considering Multiple Extreme Weather Events, Siyuan Wang, Rui Bo Jan 2023

A Resilience-Oriented Multi-Stage Adaptive Distribution System Planning Considering Multiple Extreme Weather Events, Siyuan Wang, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

Climate Change May Increase the Risk of an Area Being Hit by Multiple Extreme Weather Events, Which Brings Significant Challenges for Distribution System Planners in an Increasing Renewable Penetration Era. There is an Urgent Need for Planning Approaches to Be More Flexible and Allow for Adaptive Adjustments in the Future to Hedge Against High Uncertainties in Extreme Weather Event Scenarios. in This Work, We Propose a Resilience-Oriented Distribution System Planning Approach that Considers Multiple Extreme Weather Events. a Multi-Stage Hybrid-Stochastic-And-Robust Formulation is Developed to Model Decisions Not Only for Initial Investments, But Also for Adaptive Investments and Emergent Operations in …

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Detection Of Surface Cracks In Metals Using Microwave And Millimeter-Wave Nondestructive Testing Techniques-A Review, Mohamed A. Abou-Khousa, Mohammed Saif Ur Rahman, Kristen M. Donnell, Mohammad Tayeb Al (Tayeb) (Al) Qaseer Jan 2023

Detection Of Surface Cracks In Metals Using Microwave And Millimeter-Wave Nondestructive Testing Techniques-A Review, Mohamed A. Abou-Khousa, Mohammed Saif Ur Rahman, Kristen M. Donnell, Mohammad Tayeb Al (Tayeb) (Al) Qaseer

Electrical and Computer Engineering Faculty Research & Creative Works

Integrity Assessment of Metallic Structures Requires Inspection Tools Capable of Detecting and Evaluating Cracks Reliably. to This End, Many Microwave and Millimeter-Wave Nondestructive Testing and Evaluation (NDT&E) Methods Have Been Developed and Applied Successfully in the Past. Detection of Fatigue Cracks with Widths Less Than 5 Μ M using Noncontact Microwave-Based Inspection Methods Was Demonstrated in the 1970s. Since their Introduction, These Methods Have Evolved Considerably Toward Enhancing the Detection Sensitivity and Resolution. Undertaking Key Application Challenges Has Attracted Considerable Attention in the Past Three Decades and Led to the Development of the Near-Field Techniques for Crack Detection. to Address …

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Averaged Behavior Model Of Current-Mode Buck Converters For Transient Power Noise Analysis, Anfeng Huang, Jingdong Sun, Hongseok Kim, Zhenxue Xu, Shuai Jin, Songping Wu, Zhiping Yang, Kelvin Qiu, Jun Fan, Chulsoon Hwang Jan 2023

Averaged Behavior Model Of Current-Mode Buck Converters For Transient Power Noise Analysis, Anfeng Huang, Jingdong Sun, Hongseok Kim, Zhenxue Xu, Shuai Jin, Songping Wu, Zhiping Yang, Kelvin Qiu, Jun Fan, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

Accurate Evaluation and Simulation of Power Noise is Critical in the Development of Modern Electronic Devices. However, the Widely Used Target Impedance Fails to Predict the Low-Frequency Noise Generated in a Device Due to the Existence of the Dc–dc Converter, Whose Output Impedance Can Change under Different Loading Conditions. a Physical Circuit Model is Then Desired to Replicate the Behavior of a Voltage Regulator Module, and the Average Technique is an Efficient Method to Estimate the Noise of a Pulse Width-Modulated (PWM) Converter. with the Emergence of Converters with Adaptive On-Time (AOT) Controllers, More Complex Averaging Methods Are Required, But …

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Embeddable Soil Moisture Content Sensor Based On Open–End Microwave Coaxial Cable Resonator, Jing Guo, Yan Tang, Yongji Wu, Chen Zhu, Jie Huang Jan 2023

Embeddable Soil Moisture Content Sensor Based On Open–End Microwave Coaxial Cable Resonator, Jing Guo, Yan Tang, Yongji Wu, Chen Zhu, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

In This Paper, We Propose and Demonstrate a Novel Corrosion-Resistant, Embeddable Open-End Coaxial Cable Soil Moisture Sensor. This Microwave Resonator is Constructed using Two Reflectors Along the Coaxial Line. the First Reflector is a Metal Post at the Signal Input End, Short-Circuiting the Inner Conductor to the Outer Conductor. the Second Reflector Comprises a Welded Metal Plate Parallel to the Open-End of the Coaxial Line, Maintaining a Fixed Gap. a Moisture-Sensitive Polyvinyl Alcohol (PVA) Film is Inserted into This Gap. the Resonance Frequency of the Open-End Coaxial Cable Resonator is Highly Dependent on the Fringe Capacitance, Which Varies with Soil …

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Electromagnetic Transmit Array With Optical Control For Beamforming, Wei Zhang, Javad Meiguni, Yin Sun, Muqi Ouyang, Xin Yan, Xu Wang, Reza Yazdani, Daryl G. Beetner, Donghyun Kim, David Pommerenke Jan 2023

Electromagnetic Transmit Array With Optical Control For Beamforming, Wei Zhang, Javad Meiguni, Yin Sun, Muqi Ouyang, Xin Yan, Xu Wang, Reza Yazdani, Daryl G. Beetner, Donghyun Kim, David Pommerenke

Electrical and Computer Engineering Faculty Research & Creative Works

This Proof-Of-Concept Paper Demonstrates the Feasibility of using a Slide Projector to Steer the Beam of a Transmit Array by Adding Solar Cells and Varactor Diodes to Each Unit Cell. by Irradiating Each Solar Cell with the Light of Different Intensities from a Slide Projector, the Measured Phase of the Wave Transmitted by the 4x4 Transmit Array Shifts within 92° at 4.26 GHz, While the Variation in Magnitude is Measured within 4 DB. Different Light Configurations Are Identified Via a Searching Algorithm to Achieve Peak/null Beamforming in a Particular Direction. the Beam of the Prototypical 4x4 Transmit Array Can Be …

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An Extended Generalized Average Modeling Framework For Power Converters, Kartikeya Jayadurga Prasad Veeramraju, Jacob A. Mueller, Jonathan W. Kimball Jan 2023

An Extended Generalized Average Modeling Framework For Power Converters, Kartikeya Jayadurga Prasad Veeramraju, Jacob A. Mueller, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

The Generalized Averaged Modeling (GAM) technique is traditionally employed to capture the dynamic performance of power electronic converters. This paper proposes an improved version of it, named the Extended-GAM (EGAM) technique, which supports the multiplication of two Double Fourier Series (DFS) signals in the time domain. Multiplication of DFS signals in the time domain translates to the 2D-convolution of coefficients of the DFS terms of their equivalent Discrete Fourier Image (DFI) representations. Thus, the proposed EGAM technique, capable of capturing many harmonics present in the output of a power converter, effectively captures the dynamic behavior of power converters excited by …

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A Methodology For Predicting Improved Dipole Source Configurations From Near-Field Scan Data, Hossein Rezaei, Xin Yan, David J. Pommerenke, Daryl G. Beetner Jan 2023

A Methodology For Predicting Improved Dipole Source Configurations From Near-Field Scan Data, Hossein Rezaei, Xin Yan, David J. Pommerenke, Daryl G. Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

Equivalent sources found from near-electric and magnetic field scans are often used to predict and solve interference problems. While there are many ways to represent the source, the user lacks the ability to determine which of the many possible source configurations is more likely to represent the "true" source, and thus accurately represent field data outside the measurement area and in the presence of typical measurement errors. A methodology is proposed for estimating which of many possible dipole source representations of near-field scan data are likely to give better estimates of fields outside the measurement scan plane when utilizing imperfect …

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Multi-Layered Energy Management Framework For Extreme Fast Charging Stations Considering Demand Charges, Battery Degradation, And Forecast Uncertainties, Waqas Ur Rehman, Jonathan W. Kimball, Rui Bo Jan 2023

Multi-Layered 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 paper, therefore, proposes a multi-layered multi-time scale 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 …

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Particulate Matter Detection In Mines Using 3d Light Detection And Ranging Technology, Zachary Osterwisch, Alexander Mauntel, Nathanael Nisbett, Dibbya Barua, Ahmad Alsharoa Jan 2023

Particulate Matter Detection In Mines Using 3d Light Detection And Ranging Technology, Zachary Osterwisch, Alexander Mauntel, Nathanael Nisbett, Dibbya Barua, Ahmad Alsharoa

Electrical and Computer Engineering Faculty Research & Creative Works

This paper proposes a novel portable prototype and self-contained Air Quality (AQ) monitoring device that utilizes Light Detection and Ranging (LiDAR) technology to take its measurements. The novel device aims to improve mining safety by collecting and analyzing the AQ inside mines and displaying the real-time conditions to personnel. The intent is to create a 3D map of the environment and display potentially hazardous Atmospheric Particulate Matter (APM). To achieve this goal, we prototype a portable, compact, and easy-to-operate system that utilizes LiDAR to detect APM. Then, we propose how the collected data can be used to calculate real-time AQ …

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Solving Electromagnetic Inverse Scattering Problems In Inhomogeneous Media By Deep Convolutional Encoder-Decoder Structure, Huan Huan Zhang, He Ming Yao, Lijun Jiang, Michael Ng Jan 2023

Solving Electromagnetic Inverse Scattering Problems In Inhomogeneous Media By Deep Convolutional Encoder-Decoder Structure, Huan Huan Zhang, He Ming Yao, Lijun Jiang, Michael Ng

Electrical and Computer Engineering Faculty Research & Creative Works

This communication proposes a novel deep learning (DL) approach to solve electromagnetic inverse scattering (EMIS) problems in inhomogeneous media. The conventional approaches for solving inhomogeneous EMIS problems generally have to consider inhomogeneous Green’s functions or conduct approximation operations to media, which inevitably introduces various challenges, including complex mathematical derivation, high computation cost, unavoidable nonlinearity, and even strong ill-posedness. To avoid these challenges, we propose a DL approach based on the complex-valued deep convolutional neural networks (DConvNets), which comprise the deep convolutional encoder–decoder (DCED) structure. Its training data are collected based on the simple synthetic dataset. While the scattered fields received …

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Nanosecond Peak Detect And Hold Circuit With Adjustable Dynamic Range, Gabriel Fellner, Lucas Speckbacher, Seyed Mostafa Mousavi, David Johannes Pommerenke, Satyajeet Shinde, Michael Hillstrom, Ram Chundru, Cheung Wei Lam Jan 2023

Nanosecond Peak Detect And Hold Circuit With Adjustable Dynamic Range, Gabriel Fellner, Lucas Speckbacher, Seyed Mostafa Mousavi, David Johannes Pommerenke, Satyajeet Shinde, Michael Hillstrom, Ram Chundru, Cheung Wei Lam

Electrical and Computer Engineering Faculty Research & Creative Works

This article presents a novel peak detect and hold (PDH) circuit for the measurement of the peak voltage of electromagnetic-field probes. These probes are used to capture the fields generated by electrostatic discharge (ESD) events in nongrounded portable devices. Therefore, a circuit combining small size, low power consumption, and nanosecond operation is needed. A topology using a discrete bipolar transistor structure with operational transconductance amplifier (OTA) and common-base storage capacitor charge control optimally meets the requirements. The circuit performance is demonstrated for different bias point settings. The error between the captured value and the actual pulse peak value is shown …

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Observer-Based Model Predictive Control With Continuous Control Set For Single-Phase Rectifiers, Milad Dehghanzadeh, Rui Bo, Kamal Al-Haddad Jan 2023

Observer-Based Model Predictive Control With Continuous Control Set For Single-Phase Rectifiers, Milad Dehghanzadeh, Rui Bo, Kamal Al-Haddad

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a model predictive controller (MPC) is designed for a single-phase rectifier. The proposed MPC works with a continuous control set (CCS) that addresses variable switching issues in finite control set (FCS) MPCs. The observe-ability of the rectifier enables the design of a full-state observer to measure only output voltage in which the AC current of the rectifier is estimated. Both the proposed controller and observer are assessed with simulation studies and the results show the acceptable performance of the observer and CCS-MPC as well as good disturbance rejection in load and network parameter variations.

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Managing Reserve Deliverability Risk Of Integrated Electricity-Heat Systems In Day-Ahead Market: A Distributionally Robust Joint Chance Constrained Approach, Yang Chen, Jianxue Wang, Siyuan Wang, Rui Bo, Chenjia Gu, Qingtao Li Jan 2023

Managing Reserve Deliverability Risk Of Integrated Electricity-Heat Systems In Day-Ahead Market: A Distributionally Robust Joint Chance Constrained Approach, Yang Chen, Jianxue Wang, Siyuan Wang, Rui Bo, Chenjia Gu, Qingtao Li

Electrical and Computer Engineering Faculty Research & Creative Works

The integrated electricity and heat system (IEHS) is an emerging demand-side flexible resource for power systems. IEHS operators participating in electricity markets considering their capabilities in reserve provision will face the reserve deliverability risk due to the energy-limited storage nature of heat systems. To address this challenge and increase profitability, a distributionally robust joint chance-constrained mechanism with enhanced quantifications is adopted for the heating system and reserve deployment uncertainties. Detailed pipeline storage representation for thermal networks and integrated demand response are incorporated into this strategic participation model. A two-stage distributionally robust joint chance constrained program is then incorporated to effectively …

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Improved Quantification Of Defect Cross-Section For Active Microwave Thermography, Logan M. Wilcox, Kristen M. Donnell Jan 2023

Improved Quantification Of Defect Cross-Section For Active Microwave Thermography, Logan M. Wilcox, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Active microwave thermography (AMT) is an integrated nondestructive testing and evaluation (NDT&E) technique that features a microwave-based excitation and subsequent thermographic inspection via an infrared camera. AMT has been successfully employed in several industries including aerospace and civil for NDT&E inspections. Since the excitation is microwave-based, an antenna is used to irradiate the sample under test and hence the heating pattern will vary spatially (following the antenna pattern). This nonuniform thermal excitation may limit the ability of AMT to quantify defect cross-sections. Therefore, this work seeks to expand the capabilities of AMT by incorporating a post-processing technique to improve defect …

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Distributed Detection Over Blockchain-Aided Internet Of Things In The Presence Of Attacks, Yiming Jiang, Jiangfan Zhang Jan 2023

Distributed Detection Over Blockchain-Aided Internet Of Things In The Presence Of Attacks, Yiming Jiang, Jiangfan Zhang

Electrical and Computer Engineering Faculty Research & Creative Works

Distributed detection over a blockchain-aided Internet of Things (BIoT) network in the presence of attacks is considered, where the integrated blockchain is employed to secure data exchanges over the BIoT as well as data storage at the agents of the BIoT. We consider a general adversary model where attackers jointly exploit the vulnerability of IoT devices and that of the blockchain employed in the BIoT. The optimal attacking strategy which minimizes the Kullback-Leibler divergence is pursued. It can be shown that this optimization problem is nonconvex, and hence it is generally intractable to find the globally optimal solution to such …

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Transformer Leakage Inductance Design Methodology, Angshuman Sharma, Jonathan W. Kimball Jan 2023

Transformer Leakage Inductance Design Methodology, Angshuman Sharma, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

The leakage inductance exhibited by a transformer depends on its winding geometry, which generally involves the selection of several key design parameters in addition to the winding structure and the interleaving configuration. With few resources explaining the effects of these design choices on the observed leakage inductance, numerous trial-and-error iterations become necessary to realize the desired leakage inductance. This paper explores more than a hundred winding geometries feasible in a 2- winding transformer comprising the same magnetic core, number of turns, and wire gauge, and finds the leakage inductance for each unique design using 2-D finite element method (FEM) simulations …

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Modeling And Mitigation Of Radio Frequency Interference For Wireless Devices, Chulsoon Hwang, Jun Fan Jan 2023

Modeling And Mitigation Of Radio Frequency Interference For Wireless Devices, Chulsoon Hwang, Jun Fan

Electrical and Computer Engineering Faculty Research & Creative Works

This article reviews the electromagnetic framework used to model radio frequency interference (RFI) and the resulting development of mitigation methods. With the rise of IoT devices, wireless devices in which RF antennas are integrated with high-performance digital systems in small form factors suffer from electromagnetic interference, known as RF interference or RF desensitization. The simple yet rigorous framework can be used for a systematic RFI-aware design, saving time and effort for trial-and-error troubleshooting.

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