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Articles 421 - 450 of 3518
Full-Text Articles in Engineering
Analysis On The Effect Of Averaging Duration On Radio Frequency Dosimetry In Residential Environments, Reza Asadi, Hadi Aliakbarian, Amir Sahraei, Reza Yazdani, Donghyun Kim
Analysis On The Effect Of Averaging Duration On Radio Frequency Dosimetry In Residential Environments, Reza Asadi, Hadi Aliakbarian, Amir Sahraei, Reza Yazdani, Donghyun Kim
Electrical and Computer Engineering Faculty Research & Creative Works
The Potential Hazards of Electromagnetic Waves Have Raised Concerns in Related Authorities to Propose Standards and Limit Lines on the Electromagnetic Field Levels. Most of the Radio Frequency (RF) Dosimetry Measurement Procedures Referred to in Safety Compliance Standards, suggest 6-Minute Averaging, in Addition to Spatial Averaging, Which Can Be Time-Consuming for Primary Measurements. Measurement Analysis in Residential Environment in This Paper Demonstrates that Lowering the Time Interval of Measurements to About 30 Seconds, Which Suggests the Possibility of Reducing the Measurement Time with Minimal Reduction to Measurement Accuracy. for All Measurement Results Shown in This Paper, having a 30-Second Averaging …
Roughness Losses Computation Through The Partial Elements Equivalent Circuit Method, Fabrizio Loreto, Daniele Romano, Giulio Antonini, Albert E. Ruehli, Mauro Lai
Roughness Losses Computation Through The Partial Elements Equivalent Circuit Method, Fabrizio Loreto, Daniele Romano, Giulio Antonini, Albert E. Ruehli, Mauro Lai
Electrical and Computer Engineering Faculty Research & Creative Works
Conductor Loss Caused by Conductor Surface Roughness is a Critical Aspect in the Design of High-Speed Electronic Systems Since It Significantly Affects their Performances. Well-Established Roughness Models Have Been Proposed over the Years but They Have Been Applied Only to the Transmission Line Models of Interconnects. Typically, the Roughness Models Are Used to Modify the Per-Unit-Length Impedance of the Transmission Line Which is Extracted by 2D Model Methods. The Aim of This Work is to overcome This Limitation Thus Making It Possible to Model Roughness Conductors in the Framework of 3D Full-Wave Methods. More Precisely, it is Presented How to …
Near Field Scanning-Based Emi Radiation Root Cause Analysis In An Ssd, Xiangrui Su, Wenchang Huang, Junghee Cho, Joonki Paek, Chulsoon Hwang
Near Field Scanning-Based Emi Radiation Root Cause Analysis In An Ssd, Xiangrui Su, Wenchang Huang, Junghee Cho, Joonki Paek, Chulsoon Hwang
Electrical and Computer Engineering Faculty Research & Creative Works
In Modern Portable Electronic Devices, Solid-State Drives (SSDs) Are Commonly Used and Have Been Identified as One of the Dominant Electromagnetic Interference (EMI) Noise Sources that Can Cause RF Desensitization Issues. in This Paper, the EM Emission Source from an SSD Module is Identified and Analyzed using Near Field Scanning and Dipole Moment Source Reconstruction. the Identified Noise Current Path Including the Power Management Integrated Circuit and the Decoupling Capacitor is Validated with the Assistance of Full-Wave Simulation. the Measured Noise Voltage is Used as an Excitation in the Simulation and the Simulated Near Fields Showed a Good Correlation with …
A Real-Time Microwave Camera Prototype With Zero-Bias Diode Detectors For Emi Source Imaging, Xin Yan, Liang Liu, Victor Khilkevich
A Real-Time Microwave Camera Prototype With Zero-Bias Diode Detectors For Emi Source Imaging, Xin Yan, Liang Liu, Victor Khilkevich
Electrical and Computer Engineering Faculty Research & Creative Works
Emission Source Microscopy (ESM) Could Be Utilized to Localize the Electromagnetic Interference (EMI) Sources that Contribute to the Far-Field Radiation. in Those Cases, the Electrical Field over a Two-Dimensional Plane is Collected by Mechanical Scanning, Resulting in a Long Measurement Time and the Presence of Mechanical Errors. in This Work, a Microwave Camera based on a Two-Dimensional Array of Elliptical Slot Antennas and Diode Detectors is Presented. Multiplexers Are Utilized to Access the Output of Each Detector and the Scanning of the Whole Array Could Be Done Multiple Times Per Second.
Lifelong Learning Control Of Nonlinear Systems With Constraints Using Multilayer Neural Networks With Application To Mobile Robot Tracking, Irfan Ganie, S. (Sarangapani) Jagannathan
Lifelong Learning Control Of Nonlinear Systems With Constraints Using Multilayer Neural Networks With Application To Mobile Robot Tracking, Irfan Ganie, S. (Sarangapani) Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
This Paper Presents a Novel Lifelong Multilayer Neural Network (MNN) Tracking Approach for an Uncertain Nonlinear Continuous-Time Strict Feedback System that is Subject to Time-Varying State Constraints. the Proposed Method Uses a Time-Varying Barrier Function to Accommodate the Constraints Leading to the Development of an Efficient Control Scheme. the Unknown Dynamics Are Approximated using a MNN, with Weights Tuned using a Singular Value Decomposition (SVD)-Based Technique. an Online Lifelong Learning (LL) based Elastic Weight Consolidation (EWC) Scheme is Also Incorporated to Alleviate the Issue of Catastrophic Forgetting. the Stability of the overall Closed-Loop System is Analyzed using Lyapunov Analysis. the …
Decomposition Measurement For Antenna Gain And Radio Sensitivity Of Wireless Receiving System, Chaoqiang Zang, Lidong Chi, Fuhai Li, James L. Drewniak, Gang Feng, Yihong Qi
Decomposition Measurement For Antenna Gain And Radio Sensitivity Of Wireless Receiving System, Chaoqiang Zang, Lidong Chi, Fuhai Li, James L. Drewniak, Gang Feng, Yihong Qi
Electrical and Computer Engineering Faculty Research & Creative Works
A General Procedure for Decomposition Measurements for Receiver Antenna Gain and Radio Sensitivity based on Received Signal Strength Indicator (RSSI) Reporting is Proposed in This Paper. This Procedure Standardizes the Measurement Steps for Eliminating Nonlinear Error in RSSI Reporting. after Path Loss Calibration and RSSI Uncertainty Calibration, the Real Performance of the Antenna and the Radio Working in the Actual Environment of Wireless Receiving System Can Be Measured. the Antenna Gain is Obtained from the Difference between RSSI Reporting and Transmit Power, and the Radio Sensitivity is Obtained from the Transmit Power. This Method Helps to Improve the Development Efficiency …
Oxidation Layer Formation On Aluminum Substrates With Surface Defects Using Molecular Dynamics Simulation, Emmanuel Olugbade, Hiep Pham, Yuchu He, Haicheng Zhou, Chulsoon Hwang, Jonghyun Park
Oxidation Layer Formation On Aluminum Substrates With Surface Defects Using Molecular Dynamics Simulation, Emmanuel Olugbade, Hiep Pham, Yuchu He, Haicheng Zhou, Chulsoon Hwang, Jonghyun Park
Electrical and Computer Engineering Faculty Research & Creative Works
Aluminum Oxide Layer Affects the Integrity of Electrical Contact and Can Contribute Adversely to Passive Intermodulation (PIM) Behavior in Radio Frequency (RF) Devices, necessitating a Need for Understanding its Formation Mechanism and Realistic Estimation of its Thickness. using ReaxFF Molecular Dynamics Simulation Technique, This Study Investigated the Impact of Surface Defects on Aluminum Oxide Layer Formation. Results Reveal that Crystallographic Orientation Did Not Affect the Kinetics of Oxidation Process of Aluminum. However, the Reaction Kinetics Increased Significantly with Surface Inhomogeneities Such as Cracks, Scratches, and Grain Boundaries. a Non-Uniform Oxide Layer with Thickness Variation in the Range of 72-77% Was …
Augmented Genetic Algorithm V2 With Reinforcement Learning For Pdn Decap Optimization, Haran Manoharan, Jack Juang, Hanfeng Wang, Jingnan Pan, Kelvin Qiu, Xu Gao, Chulsoon Hwang
Augmented Genetic Algorithm V2 With Reinforcement Learning For Pdn Decap Optimization, Haran Manoharan, Jack Juang, Hanfeng Wang, Jingnan Pan, Kelvin Qiu, Xu Gao, Chulsoon Hwang
Electrical and Computer Engineering Faculty Research & Creative Works
Genetic Algorithms (GAs) Use Many Hyperparameters, and Tuning These Parameters Can Determine the Optimization Performance. a GA with an Augmented Initial Population Was Proposed for Decap Optimization but It Had Convergence Issues by Getting Stuck in the Local Minimum. This Work Uses a Reinforcement Learning (RL) Approach to Adaptively Tune the Hyperparameters of GA during its Operation. with This Approach, the Agent Tries to Change the Parameters So that the GA Does Not Get Stuck in the Local Minimum. the Proposed Method Combining the RL Agent and Augmented GA Showed Better Performance in Terms of Solution Quality and Time Cost. …
Intelligent Control Schemes For Maximum Power Extraction From Photovoltaic Arrays Under Faults, Azhar Ul-Haq, Shah Fahad, Saba Gul, Rui Bo
Intelligent Control Schemes For Maximum Power Extraction From Photovoltaic Arrays Under Faults, Azhar Ul-Haq, Shah Fahad, Saba Gul, Rui Bo
Electrical and Computer Engineering Faculty Research & Creative Works
Investigation of power output from PV arrays under different fault conditions is an essential task to enhance performance of a photovoltaic system under all operating conditions. Significant reduction in power output can occur during various PV faults such as module disconnection, bypass diode failure, bridge fault, and short circuit fault under non-uniform shading conditions. These PV faults may cause several peaks in the characteristics curve of PV arrays, which can lead to failure of the MPPT control strategy. In fact, impact of a fault can differ depending on the type of PV array, and it can make the control of …
Predicting Compressive Strength And Hydration Products Of Calcium Aluminate Cement Using Data-Driven Approach, Sai Akshay Ponduru, Taihao Han, Jie Huang, Aditya Kumar
Predicting Compressive Strength And Hydration Products Of Calcium Aluminate Cement Using Data-Driven Approach, Sai Akshay Ponduru, Taihao Han, Jie Huang, Aditya Kumar
Electrical and Computer Engineering Faculty Research & Creative Works
Calcium aluminate cement (CAC) has been explored as a sustainable alternative to Portland cement, the most widely used type of cement. However, the hydration reaction and mechanical properties of CAC can be influenced by various factors such as water content, Li2CO3 content, and age. Due to the complex interactions between the precursors in CAC, traditional analytical models have struggled to predict CAC binders' compressive strength and porosity accurately. To overcome this limitation, this study utilizes machine learning (ML) to predict the properties of CAC. The study begins by using thermodynamic simulations to determine the phase assemblages of …
Cooperative Deep $Q$ -Learning Framework For Environments Providing Image Feedback, Krishnan Raghavan, Vignesh Narayanan, Sarangapani Jagannathan
Cooperative Deep $Q$ -Learning Framework For Environments Providing Image Feedback, Krishnan Raghavan, Vignesh Narayanan, Sarangapani Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
In This Article, We Address Two Key Challenges in Deep Reinforcement Learning (DRL) Setting, Sample Inefficiency and Slow Learning, with a Dual-Neural Network (NN)-Driven Learning Approach. in the Proposed Approach, We Use Two Deep NNs with Independent Initialization to Robustly Approximate the Action-Value Function in the Presence of Image Inputs. in Particular, We Develop a Temporal Difference (TD) Error-Driven Learning (EDL) Approach, Where We Introduce a Set of Linear Transformations of the TD Error to Directly Update the Parameters of Each Layer in the Deep NN. We Demonstrate Theoretically that the Cost Minimized by the EDL Regime is an Approximation …
Decentralized And Coordinated V-F Control For Islanded Microgrids Considering Der Inadequacy And Demand Control, Buxin She, Fangxing Li, Hantao Cui, Jinning Wang, Liang Min, Oroghene Oboreh-Snapps, Rui Bo
Decentralized And Coordinated V-F Control For Islanded Microgrids Considering Der Inadequacy And Demand Control, Buxin She, Fangxing Li, Hantao Cui, Jinning Wang, Liang Min, Oroghene Oboreh-Snapps, Rui Bo
Electrical and Computer Engineering Faculty Research & Creative Works
This Paper Proposes a Decentralized and Coordinated Voltage and Frequency (V-F) Control Framework for Islanded Microgrids, with Full Consideration of the Limited Capacity of Distributed Energy Resources (DERs) and V-F Dependent Load. First, the Concept of DER Inadequacy is Illustrated with the Challenges It Poses. Then, a Decentralized and Coordinated Control Framework is Proposed to Regulate the Output of Inverter-Based Generations and Reallocate Limited DER Capacity for V-F Control. the Control Framework is Composed of a Power Regulator and a V-F Regulator, Which Generates the Supplementary Signals for the Primary Controller. the Power Regulator Regulates the Output of Grid-Forming Inverters …
System Level Pdn Impedance Optimization Utilizing The Zeros Of The Decoupling Capacitors, Yifan Ding, Shuang Liang, Francesco De Paulis, Matteo Cocchini, Samuel Connor, Matthew Doyle, Albert E. Ruehli, Chulsoon Hwang, James L. Drewniak
System Level Pdn Impedance Optimization Utilizing The Zeros Of The Decoupling Capacitors, Yifan Ding, Shuang Liang, Francesco De Paulis, Matteo Cocchini, Samuel Connor, Matthew Doyle, Albert E. Ruehli, Chulsoon Hwang, James L. Drewniak
Electrical and Computer Engineering Faculty Research & Creative Works
System-Level Power Distribution Network (PDN) Impedance Optimization Utilizing the Zeros of the Decoupling Capacitors (Decaps) is Discussed in This Paper. an Example of a Practical PDN Application is Proposed to Validate the Poles and Zeros Algorithm (P&Z) Presented. the System-Level PDN is with the Printed Circuit Board (PCB), Package (PKG), and Chip, as Well as the Low-Frequency Decaps on the PCB and the On-PKG Decoupling Capacitors. the PDN Optimization Results Are Compared with Those from the Genetic Algorithm (GA) to Show the Reasonableness and Validity of the P&Z Algorithm.
Design And Construction Of An Arbitrary Pulse Compressive Amplifier, Cody Goins, Aaron Harmon, Victor Khilkevich, Daryl G. Beetner
Design And Construction Of An Arbitrary Pulse Compressive Amplifier, Cody Goins, Aaron Harmon, Victor Khilkevich, Daryl G. Beetner
Electrical and Computer Engineering Faculty Research & Creative Works
Compressive Pulse Amplifiers Are a Class of Amplifiers that Convert Long Low Amplitude Signals into Very Broadband Pulses of High Amplitude, Yielding a Very High Instantaneous Peak Power Output Pulse. However, in the Realm of Electronic Immunity and Susceptibility Testing, Very Broadband Short Pulses Are Not Always Desired. This Work Presents a Design for a Compressive Amplifier that is Aimed at Creating Arbitrary Pulsed Signals of Varying Bandwidths. Limitations of the Achievable Gain and Methods Used Are Discussed.
Predicting Dissolution Kinetics Of Tricalcium Silicate Using Deep Learning And Analytical Models, Taihao Han, Sai Akshay Ponduru, Arianit Reka, Jie Huang, Gaurav Sant, Aditya Kumar
Predicting Dissolution Kinetics Of Tricalcium Silicate Using Deep Learning And Analytical Models, Taihao Han, Sai Akshay Ponduru, Arianit Reka, Jie Huang, Gaurav Sant, Aditya Kumar
Electrical and Computer Engineering Faculty Research & Creative Works
The dissolution kinetics of Portland cement is a critical factor in controlling the hydration reaction and improving the performance of concrete. Tricalcium silicate (C3S), the primary phase in Portland cement, is known to have complex dissolution mechanisms that involve multiple reactions and changes to particle surfaces. As a result, current analytical models are unable to accurately predict the dissolution kinetics of C3S in various solvents when it is undersaturated with respect to the solvent. This paper employs the deep forest (DF) model to predict the dissolution rate of C3S in the undersaturated solvent. The …
A Data-Driven Approach To Multiresolution Analysis Of Near-Field Scanning, Yanming Zhang, Lijun Jiang
A Data-Driven Approach To Multiresolution Analysis Of Near-Field Scanning, Yanming Zhang, Lijun Jiang
Electrical and Computer Engineering Faculty Research & Creative Works
Near-field scanning has been widely adopted as a valuable tool in diagnosing electromagnetic compatibility (EMC) and electromagnetic interference (EMI) problems. This paper proposes a multiresolution dynamic mode decomposition (MRDMD)-based method for analyzing time-varying near-field radiation. MRDMD executes the traditional DMD method recursively and hierarchically. The distribution of DMD eigenvalues determines the slow and fast modes in a level's decomposition, in which the slow modes are reserved, and the fast modes are utilized to generate the input data for the next level. Finally, the multiresolution time-frequency representation of the near-field radiation field is obtained. And the spatial distributions corresponding to each …
Interval Analysis Method For The Uncertainty And Sensitivity Characterization In Transmission Line Systems, Ping Yuan, Lijun Jiang
Interval Analysis Method For The Uncertainty And Sensitivity Characterization In Transmission Line Systems, Ping Yuan, Lijun Jiang
Electrical and Computer Engineering Faculty Research & Creative Works
Uncertainty in electronic fabrication process could cause serious yield issues and stability concerns. Hence, identifying the resultant range caused by the uncertainty in the system is a critical topic in modern EDA design process. Monte Carlo method is considered as a golden standard but with many drawbacks. In the paper, we propose to use the interval analysis (IA) to analyze the signal integrity and power integrity problems in transmission line (TL) systems. Using the interval representing the uncertainty range of parameters in the system, the uncertainty range of the system can be derived by the derived analytical expression. It is …
Decoupling Optimization For Complex Pdn Structures Using Deep Reinforcement Learning, Ling Zhang, Li Jiang, Jack Juang, Zhiping Yang, Er Ping Li, Chulsoon Hwang
Decoupling Optimization For Complex Pdn Structures Using Deep Reinforcement Learning, Ling Zhang, Li Jiang, Jack Juang, Zhiping Yang, Er Ping Li, Chulsoon Hwang
Electrical and Computer Engineering Faculty Research & Creative Works
This Article Presents a New Optimization Method for Complex Power Distribution Networks (PDNs) with Irregular Shapes and Multilayer Structures using Deep Reinforcement Learning (DRL), Which Has Not Been Considered Before. a Fast Boundary Integration Method is Applied to Compute the Impedance Matrix of a PDN Structure. Subsequently, a New DRL Algorithm based on Proximal Policy Optimization (PPO) is Proposed to Optimize the Decoupling Capacitor (Decap) Placement by Minimizing the Number of Decaps While Satisfying the Desired Target Impedance. in the Proposed Approach, the PDN Structure Information is Encoded into Matrices and Serves as the Input of the DRL Algorithm, Which …
A Throughput Fast Measurement Method For Two-Antenna Equipped Wireless Mimo Terminals, Penghui Shen, Quan Yu, Daryl G. Beetner, Yihong Qi
A Throughput Fast Measurement Method For Two-Antenna Equipped Wireless Mimo Terminals, Penghui Shen, Quan Yu, Daryl G. Beetner, Yihong Qi
Electrical and Computer Engineering Faculty Research & Creative Works
According to the Third Generation Partnership Project Specification, a Period of 8-12.8 H is Required to Evaluate the Multiple-Input-Multiple-Output (MIMO) Performance of a Wireless Terminal for a Single Frequency Point and Channel Model Combination. the Following Article Proposes a Semi-Simulation, Semi-Measurement-Based MIMO throughput Modeling Scheme Which Can Reduce the 8-12.8-H Measurement Time to 40-60 Min, Corresponding to More Than a Ten Times Improvement of the Test Efficiency, Without Loss of the Test Accuracy.
Skin Lesion Segmentation In Dermoscopic Images With Noisy Data, Norsang Lama, Jason Hagerty, Anand Nambisan, Ronald Joe Stanley, William Van Stoecker
Skin Lesion Segmentation In Dermoscopic Images With Noisy Data, Norsang Lama, Jason Hagerty, Anand Nambisan, Ronald Joe Stanley, William Van Stoecker
Electrical and Computer Engineering Faculty Research & Creative Works
We Propose a Deep Learning Approach to Segment the Skin Lesion in Dermoscopic Images. the Proposed Network Architecture Uses a Pretrained Efficient Net Model in the Encoder and Squeeze-And-Excitation Residual Structures in the Decoder. We Applied This Approach on the Publicly Available International Skin Imaging Collaboration (ISIC) 2017 Challenge Skin Lesion Segmentation Dataset. This Benchmark Dataset Has Been Widely Used in Previous Studies. We Observed Many Inaccurate or Noisy Ground Truth Labels. to Reduce Noisy Data, We Manually Sorted All Ground Truth Labels into Three Categories — Good, Mildly Noisy, and Noisy Labels. Furthermore, We Investigated the Effect of Such …
Methodology For Analyzing Coupling Mechanisms In Rfi Problems Based On Peec, Xu Wang, Anfeng Huang, Wei Zhang, Reza Yazdani, Donghyun Kim, Takashi Enomoto, Taketoshi Sekine, Kenji Araki, Jun Fan, Chulsoon Hwang
Methodology For Analyzing Coupling Mechanisms In Rfi Problems Based On Peec, Xu Wang, Anfeng Huang, Wei Zhang, Reza Yazdani, Donghyun Kim, Takashi Enomoto, Taketoshi Sekine, Kenji Araki, Jun Fan, Chulsoon Hwang
Electrical and Computer Engineering Faculty Research & Creative Works
In This Article, a Method for Analyzing Coupling Mechanisms in Radio Frequency Interference (RFI) Problems is Proposed. the Partial Element Equivalent Circuit (PEEC) Method is First Used to Derive the Retarded Inductances and Capacitances between Different Mesh Cells. with the Introduction of a Novel Partitioning Algorithm, the Capacitive Coupling and Inductive Coupling between Arbitrary Layout Parts Can Be Quantified based on the Magnitude of the Displacement Current and Induced Voltage Drop. the Accuracy of the PEEC Models is Validated by Comparison with Different Commercial Tools. the Proposed Coupling Mechanism Analysis Flow Provides a Useful Prelayout Tool for RFI Risk Analysis.
Natural Organic Fructose-Based Nonvolatile Resistive Switching Memory For Environmental Sustainability In Computing, Yuan Xing, Feng Zhao
Natural Organic Fructose-Based Nonvolatile Resistive Switching Memory For Environmental Sustainability In Computing, Yuan Xing, Feng Zhao
Electrical and Computer Engineering Faculty Research & Creative Works
The fast growth and wide applications of Internet of Things (IoT) require enormous amounts of energy consumption and hardware devices for computation, which present significant challenges of energy efficiency and environmental sustainability. Von Neumann computing architecture is reaching its bottleneck and limited by low energy efficiency. Fabrication of conventional semiconductor devices results in depletion of nonrenewable resources, while the disposal of these devices causes electronic waste with serious ecological, health, and economic issues. One potential solution to address these challenges simultaneously is by brain-like neuromorphic computing with essential hardware components made from natural organic materials for energy efficient operation, sustainable …
A Machine Learning Approach To Support Neuromorphic Device Design And Microfabrication, Abdi Yamil Vicenciodelmoral, Md Mehedi Hasan Tanim, Feng Zhao, Xinghui Zhao
A Machine Learning Approach To Support Neuromorphic Device Design And Microfabrication, Abdi Yamil Vicenciodelmoral, Md Mehedi Hasan Tanim, Feng Zhao, Xinghui Zhao
Electrical and Computer Engineering Faculty Research & Creative Works
Neuromorphic chips provide a potential solution for sustainable computing, as they attempt to mimic the neuronal architectures in human brain and show great potentials in reducing energy consumption in the order of magnitude and also improve the computational performance. However, the fabrication process for neuromorphic chips is costly and currently based on trial-and-error, which adds complexity to the design process. In this paper, we address these challenges by designing and developing machine learning guided microfabrication process for Resistive Random Access Memory (RRAM), which is a key device in neuromorphic chips. Specifically, our research makes the following contributions: 1) we successfully …
An Extendable High Step-Up Dc-Dc Converter For Renewable Energy Applications, Saeed Habibi, Ramin Rahimi, Mehdi Ferdowsi, Pourya Shamsi
An Extendable High Step-Up Dc-Dc Converter For Renewable Energy Applications, Saeed Habibi, Ramin Rahimi, Mehdi Ferdowsi, Pourya Shamsi
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, a high step-up DC-DC converter based on a switched-inductor-capacitor-diode (SLCD) cell is proposed. the proposed converter provides a high voltage gain, low voltage stress on the power switches and diodes, and a low input current ripple. Moreover, the proposed converter is extendable, meaning that the voltage gain could be further increased by using a higher number of proposed cells in the topology. the steady-state analysis and comparison of the proposed converter to the other existing converters are presented. a 200 W, 40 V to 380 V experimental setup is developed to verify the steady-state analysis of the …
Study Of Carbon Nanotube Embedded Honey As A Resistive Switching Material, Md Mehedi Hasan Tanim, Brandon Sueoka, Zhigang Xiao, Kuan Yew Cheong, Feng Zhao
Study Of Carbon Nanotube Embedded Honey As A Resistive Switching Material, Md Mehedi Hasan Tanim, Brandon Sueoka, Zhigang Xiao, Kuan Yew Cheong, Feng Zhao
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, natural organic honey embedded with carbon nanotubes (CNTs) was studied as a resistive switching material for biodegradable nonvolatile memory in emerging neuromorphic systems. CNTs were dispersed in a honey-water solution with the concentration of 0.2 wt.% CNT and 30 wt.% honey. The final honey-CNT-water mixture was spin-coated and dried into a thin film sandwiched in between Cu bottom electrode and Al top electrode to form a honey-CNT based resistive switching memory (RSM). Surface morphology, electrical characteristics and current conduction mechanism were investigated. The results show that although CNTs formed agglomerations in the dried honey-CNT film, both switching …
Improvement For Mimo Systems By Increasing Antenna Isolation And Shaping Radiation Pattern Using Hybrid Network, Min Li, Yujie Zhang, Fan Jiang, Di Wu, Kwan Lawrence Yeung, Lijun Jiang, Ross Murch
Improvement For Mimo Systems By Increasing Antenna Isolation And Shaping Radiation Pattern Using Hybrid Network, Min Li, Yujie Zhang, Fan Jiang, Di Wu, Kwan Lawrence Yeung, Lijun Jiang, Ross Murch
Electrical and Computer Engineering Faculty Research & Creative Works
In this article, a novel method is proposed to design a hybrid network (HN) to increase isolation and shape radiation patterns for multiple-input multiple-output (MIMO) antenna systems. The HN is a combination of a decoupling feeding network and a defected ground network, which are populated by several surface-mounted reactive components whose reactances are determined by the N-ary optimization algorithm. Two decoupling examples are presented to validate the design methodology and elaborate on the design procedure. Measurement results show that the HN helps to realize impedance matching with reflection coefficients below -10 dB, isolation improvement from -5.4/-8.9 dB to below -20 …
Resistive Switching Characteristics Of Fullerene (C60) In Polymannose Thin Film, Kuan Yew Cheong, Ilias Ait Tayeb, Feng Zhao
Resistive Switching Characteristics Of Fullerene (C60) In Polymannose Thin Film, Kuan Yew Cheong, Ilias Ait Tayeb, Feng Zhao
Electrical and Computer Engineering Faculty Research & Creative Works
The effects of C60 incorporated in polymannose-based resistive switching memory have been systematically investigated for the first time in bioorganic-based resistive switching memory. C60 with different concentrations (0–7 wt.%) is dispersed in polymannose precursor, drop-casted on ITO/PET substrate, and dried to form a thin film. Electrochemically inert Au–Pd is used as top electrode. The devices with embedded C60 show better endurance and stability. Read memory window decreases and ON/OFF ratio increases as the concentration of C60 increases. Stable retention time up to 10 years is achieved for all of the devices except the one with 7 wt.% C60. Based on …
A Novel Microgrid Fault Detection And Classification Method Using Maximal Overlap Discrete Wavelet Packet Transform And An Augmented Lagrangian Particle Swarm Optimization-Support Vector Machine, Masoud Ahmadipour, Muhammad Murtadha Othman, Rui Bo, Zainal Salam, Hussein Mohammed Ridha, Kamrul Hasan
A Novel Microgrid Fault Detection And Classification Method Using Maximal Overlap Discrete Wavelet Packet Transform And An Augmented Lagrangian Particle Swarm Optimization-Support Vector Machine, Masoud Ahmadipour, Muhammad Murtadha Othman, Rui Bo, Zainal Salam, Hussein Mohammed Ridha, Kamrul Hasan
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, an intelligent method for fault detection and classification for a microgrid (MG) was proposed. The idea was based on the combination of three computational tools: signal processing using the maximal overlap discrete wavelet packet transform (MODWPT), parameter optimization by the augmented Lagrangian particle swarm optimization (ALPSO), and machine learning using the support vector machine (SVM). The MODWPT was applied to preprocess half cycle of the post-fault current samples measured at both ends of feeders. The wavelet coefficients derived from the MODWPT were statistically evaluated using the mean, standard deviation, energy, skewness, kurtosis, logarithmic energy entropy, max, min, …
Connecting Phenotype To Genotype: Phewas-Inspired Analysis Of Autism Spectrum Disorder, John Matta, Daniel Dobrino, Dacosta Yeboah, Swade Howard, Yasser El-Manzalawy, Tayo Obafemi-Ajayi
Connecting Phenotype To Genotype: Phewas-Inspired Analysis Of Autism Spectrum Disorder, John Matta, Daniel Dobrino, Dacosta Yeboah, Swade Howard, Yasser El-Manzalawy, Tayo Obafemi-Ajayi
Electrical and Computer Engineering Faculty Research & Creative Works
Autism Spectrum Disorder (ASD) is extremely heterogeneous clinically and genetically. There is a pressing need for a better understanding of the heterogeneity of ASD based on scientifically rigorous approaches centered on systematic evaluation of the clinical and research utility of both phenotype and genotype markers. This paper presents a holistic PheWAS-inspired method to identify meaningful associations between ASD phenotypes and genotypes. We generate two types of phenotype-phenotype (p-p) graphs: a direct graph that utilizes only phenotype data, and an indirect graph that incorporates genotype as well as phenotype data. We introduce a novel methodology for fusing the direct and indirect …
High-Sensitivity Optical Fiber Sensing Based On A Computational And Distributed Vernier Effect, Chen Zhu, Jie Huang
High-Sensitivity Optical Fiber Sensing Based On A Computational And Distributed Vernier Effect, Chen Zhu, Jie Huang
Electrical and Computer Engineering Faculty Research & Creative Works
This article reports a novel concept of computational microwave photonics and distributed Vernier effect for sensitivity enhancement in a distributed optical fiber sensor based on an optical carrier microwave interferometry (OCMI) system. The sensor system includes a Fabry-Perot interferometer (FPI) array formed by cascaded fiber in-line reflectors. Using OCMI interrogation, information on each of the interferometers (i.e., sensing interferometers) can be obtained, from which an array of reference interferometers can be constructed accordingly. By superimposing the interferograms of each sensing interferometer and its corresponding reference interferometer, distributed Vernier effect can be generated, so that the measurement sensitivity of each of …