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Articles 2941 - 2970 of 53198

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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 Jan 2025

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 …

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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 Jan 2025

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 …

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Microwave Photonic Fiber Ring Resonator For Optical Sensing Based On In-Ring And Out-Of-Ring Modulation, Shiyu Li, Chen Zhu Jan 2025

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 …

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Ibis Model Simulation Accuracy Improvement With Slew Rate Correction, Yifan Ding, Chulsoon Hwang Jan 2025

Ibis Model Simulation Accuracy Improvement With Slew Rate Correction, Yifan Ding, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

The accuracy of Power-Supply-Induced Jitter (PSIJ) simulation in Input/Output Buffer Information Specification (IBIS) models is critical for ensuring robust high-speed signal integrity analysis, but it lacks accuracy in predicting the PSIJ when the pre-driver exists in the model. Previous studies have proposed methods to improve IBIS PSIJ simulation accuracy with pre-driver effect included in the IBIS switching coefficients modification process. However, these methods fail to accurately model the output waveform slew rate change with varied power noise. In this work, an improved modification method was proposed to incorporate power-aware characteristics into the modified IBIS model, thereby improving the accuracy of …

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A High Step-Up Soft-Switched Converter Based On Coupled Inductor And Current-Fed Voltage Multiplier, Koosha Choobdari Omran, Reza Beiranvand, Pourya Shamsi Jan 2025

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 …

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Balanced Benchmarking Of Zero-Shot And Rag Approaches For Biomedical Term Normalization, Thanh Son Do, Daniel B. Hier, Tayo Obafemi-Ajayi Jan 2025

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 …

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Measurement- And Simulated Annealing (Sa) Optimization-Based Inductor Model Coupled To Chassis, Junyong Park, Reza Vahdani, Donghyun Kim Jan 2025

Measurement- And Simulated Annealing (Sa) Optimization-Based Inductor Model Coupled To Chassis, Junyong Park, Reza Vahdani, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

In automotive systems, a metal chassis protects the components against the external environment. However, the metal chassis is conductive, which results in unwanted conducted emission (CE) coupling to electric components. An inductor used for power factor correction (PFC) is one of the affected components. When the inductor is mated with the metal chassis, the impedance of the inductor changes. It is also hard to predict the CE coupling due to the structure-dependent characteristics. That is, the CE coupling is not negligible and hard to clarify. Therefore, this article proposes an efficient modeling method for the inductor which is mated with …

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Design And Optimization Of A Miniaturized Spiral Antenna For Ultra-Wideband Applications, Mckennan Starkey, Cody Goins, Victor Khilkevich, Daryl Beetner Jan 2025

Design And Optimization Of A Miniaturized Spiral Antenna For Ultra-Wideband Applications, Mckennan Starkey, Cody Goins, Victor Khilkevich, Daryl Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

Ultra-wideband communication in the frequency range from 3.1 to 10.6 GHz is popular for short range wireless networks. Designing a wideband antenna that covers the entire 7.5 GHz band is challenging, particularly if the antenna should be small, unobtrusive, and should effectively communicate with another antenna as their positions and orientations change. A miniaturized wideband circularly polarized Archimedean spiral antenna is developed in this study which is wideband and circularly polarized. Miniaturization and optimization techniques are introduced to enable an antenna size of $30 \text{mm} \times 30 \text{mm}$ and a thickness less than 0.5 mm.

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A Non-Destructive And Simple Setup Method For Dielectric Liquid Characterization In A Wide Frequency Range With Djordjevic-Sarkar Model, Reza Vahdani, Reza Asadi, Seyedmehdi Mousavi, Xiaoning Ye, Donghyun Kim Jan 2025

A Non-Destructive And Simple Setup Method For Dielectric Liquid Characterization In A Wide Frequency Range With Djordjevic-Sarkar Model, Reza Vahdani, Reza Asadi, Seyedmehdi Mousavi, Xiaoning Ye, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

This paper introduces a non-destructive and simple setup method for characterizing dielectric liquids over a broad frequency range (up to 30 GHz) using the Djordjevic-Sarkar model. By employing a differential microstrip line and comparing scattering parameters in air-filled and liquid-immersed scenarios, the proposed method achieves precise dielectric constant (DK) and dissipation factor (Df) extraction. 2 Liquid samples (PAO4 and DC-15) were tested using this method. Validation against the cavity resonance method demonstrates a strong agreement for the extracted DK values, with a relative error of less than 1.5 %, indicating high accuracy. However, the method is less sensitive to Df, …

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Method Of Termination With Absorbers For Far-End Crosstalk Measurements, Daniel L. Commerou, Reza Asadi, Sathvika Bandi, Seyed Mostafa Mousavi, Xiaoning Ye, Donghyun Kim Jan 2025

Method Of Termination With Absorbers For Far-End Crosstalk Measurements, Daniel L. Commerou, Reza Asadi, Sathvika Bandi, Seyed Mostafa Mousavi, Xiaoning Ye, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

The increasing demand for higher data rates in modern electronic systems has heightened the challenges of maintaining signal integrity, particularly in addressing farend crosstalk (FEXT). This paper presents a novel approach using absorber-based terminations to perform signal integrity measurements in high-speed PCB designs. The performance of magnetically and electrically loaded absorber materials is evaluated against traditional 50Ω terminations with performance parameters such as S-parameters, Time-Domain reflectometry (TDR), and induced far-end crosstalk voltage. Simulations and experimental measurements demonstrate that electrically loaded absorbers can achieve performance characteristics comparable to high-quality terminations, particularly for reflections and impedance matching. The results indicate that absorbers …

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Usb 3.0 Ibis-Ami Model Construction Using Measurement And Neural Network, Jiahuan Huang, Wenchang Huang, Muqi Ouyang, Hank Lin, Bin Chyi Tseng, Chulsoon Hwang Jan 2025

Usb 3.0 Ibis-Ami Model Construction Using Measurement And Neural Network, Jiahuan Huang, Wenchang Huang, Muqi Ouyang, Hank Lin, Bin Chyi Tseng, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

The input/ output modes are essential for high-speed signal integrity analysis and channel simulation. This work aims to develop a method for generating an IBIS-AMI model for USB 3.0 using measurement data. Instead of requiring a specially designed motherboard with test points for specific measurements, this method uses measurement data obtained from an assembled motherboard. The only available data for measurement in this case is the output voltage waveform from the USB 3.0 port on the motherboard. To address this, a novel approach is proposed to extract all the required parameters for the IBIS-AMI model from a single available measurement …

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Mitigating Optical Module Emi Using Common- And Differential-Mode Filters, Shivali Singh, Rakshith Kumar Gopalaiah, Di Li, Mokshit Tejasvi, Shipra Shipra, Victor Khilkevich Jan 2025

Mitigating Optical Module Emi Using Common- And Differential-Mode Filters, Shivali Singh, Rakshith Kumar Gopalaiah, Di Li, Mokshit Tejasvi, Shipra Shipra, Victor Khilkevich

Electrical and Computer Engineering Faculty Research & Creative Works

A strategy to mitigate electromagnetic interference in quad/octal small form-factor pluggable interfaces using a common-mode/differential-mode filter is presented in this research. Differential source imbalance produces significant common- and differential-mode noise in the differential pseudorandom binary sequence signal. EMI associated with this noise can be reduced by incorporating a band stop filter onto the differential line on a printed circuit board. Two kinds of filters were tested: common mode and common/differential mode. It was demonstrated that the application of a common-mode/differential-mode filter is more advantageous than a common-mode filter and allows to achieve the suppression of the total radiated power by …

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Radiated Susceptibility Testing Using Near-Field Scanning, Mckennan Starkey, Aaron Harmon, Cody Goins, Kristen Donnell, Victor Khilkevich, Daryl Beetner Jan 2025

Radiated Susceptibility Testing Using Near-Field Scanning, Mckennan Starkey, Aaron Harmon, Cody Goins, Kristen Donnell, Victor Khilkevich, Daryl Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

Determining locations and components in a system responsible for radiated coupling is challenging. Methods, such as near field injection susceptibility scanning or direct power injection, can only find locations and frequencies where a component is sensitive to the near field or to an injected signal but cannot deduce if the component is well coupled to the far-field. In this paper, a method to experimentally determine the levels of radiated coupling within a target system is proposed. A near-field differential loop probe is scanned over the target device while measuring the radiated energy in a stirred-mode tent. By sweeping the near …

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Graph-Based Reinforcement Learning Approach For Multi-Power-Domain Pcb Pdn Shape And Stackup Synthesis, Haran Manoharan, Hanfeng Wang, Jingnan Pan, Yuchu He, Jianmin Zhang, Xu Gao, Chulsoon Hwang Jan 2025

Graph-Based Reinforcement Learning Approach For Multi-Power-Domain Pcb Pdn Shape And Stackup Synthesis, Haran Manoharan, Hanfeng Wang, Jingnan Pan, Yuchu He, Jianmin Zhang, Xu Gao, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

Efficient power plane and stack up optimization is critical for Printed Circuit Board (PCB) Power Delivery Networks (PDNs), particularly in multi-power-domain designs with stringent DC Resistance (DCR) specifications. This work presents a novel reinforcement learning-based framework that assigns stack up layers for each power domain and iteratively refines power plane shapes to meet design constraints while ensuring non-overlapping layouts. The approach leverages Minimum Spanning Trees (MSTs) for initializing power plane shapes. It dynamically refines them using the A∗ (A-Star) algorithm with weighted pathfinding, ensuring optimal connectivity and compliance with DCR requirements. Tested extensively on multi-power-domain scenarios, the algorithm demonstrates robust …

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Optimized Modeling Of Pcb Vias With Nonfunctional Pads And High-Frequency Behavior Up To 150 Ghz, Mehdi Mousavi, Kevin Cai, Chaofeng Li, Sathvika Bandi, Manish Mathew, Mehdi Khaleghi, Shameem Ahmed, Donghyun Kim Jan 2025

Optimized Modeling Of Pcb Vias With Nonfunctional Pads And High-Frequency Behavior Up To 150 Ghz, Mehdi Mousavi, Kevin Cai, Chaofeng Li, Sathvika Bandi, Manish Mathew, Mehdi Khaleghi, Shameem Ahmed, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents an enhanced closed-form approach for modeling and optimizing high-frequency PCB vias, implemented in Python and validated against industry standard tools such as ADS and HFSS. The model incorporates resistance alongside inductance and capacitance to capture frequency-dependent losses and integrates non-functional pads (NFPs), demonstrating significant improvements in signal integrity by reducing reflections and enhancing return loss, particularly at 100 GHz. The methodology extends the frequency range of previous models from 100 GHz to 150 GHz, ensuring compatibility with next-generation standards like PCIe Gen 6. Validation results show insertion loss deviations under 3 dB and consistent return loss across …

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Ai-Driven Traffic Scene Understanding Using Static Lidar Sensors, Elham Binshaflout, Chaima Zaghouani, Charalampos Antoniadis, Hakim Ghazzai, Nawfal Guefrachi, Ahmad Alsharoa, Sameh Najeh, Gianluca Setti Jan 2025

Ai-Driven Traffic Scene Understanding Using Static Lidar Sensors, Elham Binshaflout, Chaima Zaghouani, Charalampos Antoniadis, Hakim Ghazzai, Nawfal Guefrachi, Ahmad Alsharoa, Sameh Najeh, Gianluca Setti

Electrical and Computer Engineering Faculty Research & Creative Works

Traffic congestion and road safety remain critical challenges in urban environments, driving the need for more effective traffic monitoring solutions. While recent advancements in computer vision have enhanced traffic perception, the dynamic viewpoint of autonomous vehicles is often insufficient for comprehensive traffic management. To address this gap, we propose an AI-driven framework for enhanced traffic scene understanding using static LiDAR sensors at road intersections. The system collects 3D point clouds from roadside static LiDAR sensors, providing a complete view of vehicles and pedestrians. We integrate state-of-the-art 3D object detection (i.e., PV-RCNN) and instance segmentation models (i.e., PointGroup3heads) to accurately identify …

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Obstacles And Mitigations For An Accurate Low Impedance, Low Frequency Measurement, Faye Squires, Yifan Ding, Matthew Doyle, Matteo Cocchini, Samuel Connor, Francesco De Paulis, Albert E. Ruehli, Chulsoon Hwang, Lijun Jiang Jan 2025

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 …

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Data Representation And Preprocessing Effects On S-Parameter Modeling Of High-Speed Channels Using Machine Learning, Hyunwook Park, Davit Kharshiladze, Yifan Ding, Ling Zhang, Natalia Bondarenko, Hanqin Ye, Kaushal Sanjay Mhalgi, Brice Achkir, Chulsoon Hwang Jan 2025

Data Representation And Preprocessing Effects On S-Parameter Modeling Of High-Speed Channels Using Machine Learning, Hyunwook Park, Davit Kharshiladze, Yifan Ding, Ling Zhang, Natalia Bondarenko, Hanqin Ye, Kaushal Sanjay Mhalgi, Brice Achkir, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, the effects of data representations and preprocessing on machine learning based S-parameter modeling of high-speed channels are investigated. Using a transformer network as a base model, two S-parameter representations in real/imaginary and magnitude/phase are compared and studied. Considering S-parameter data distributions, various preprocessing techniques including MinMax normalization, standardization, robust scaling, power transformation, and quantile transformation are compared and analyzed to improve accuracy. Moreover, the accuracy results are compared depending on the electrical length of target channels.

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Differential Via Modeling Using Multilayer Perceptron-Sequential (Mlp-Seq) Neural Network, Hyunwook Park, Shruti Sawant, Bandi Sathvika, Arun Chada, Soumya Singh, Seema Pk, Taein Shin, Haeseok Suh, Junyong Park, Bhyrav Mutnury, Donghyun Kim Jan 2025

Differential Via Modeling Using Multilayer Perceptron-Sequential (Mlp-Seq) Neural Network, Hyunwook Park, Shruti Sawant, Bandi Sathvika, Arun Chada, Soumya Singh, Seema Pk, Taein Shin, Haeseok Suh, Junyong Park, Bhyrav Mutnury, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, an encoder-decoder structured multi-layer perceptron-sequential (MLP-SEQ) networks are proposed to model high-speed differential vias for estimating differential insertion loss (IL) and return loss (RL). Sequential neural networks including recurrent neural network (RNN), long short-term memory (LSTM), and gated recurrent unit (GRU) are introduced as the decoder NN to treat frequency responses as sequences. The proposed models are validated by finite element method (FEM) simulation results. The accuracy and training times of MLP-RNN, MLP-LSTM, and MLP-GRU models are compared and analyzed. Based on the MLP-LSTM model, various design of experiments (DoEs) are conducted to enhance the reproducibility and …

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Coupling Path Analysis Of Data Center Ssd Storage Systems Based On Visualization Technique, Xiangrui Su, Haran Manoharan, Jihun Kim, Lalit Kumar, Heewon Kang, Chunghyun Ryu, Chulsoon Hwang Jan 2025

Coupling Path Analysis Of Data Center Ssd Storage Systems Based On Visualization Technique, Xiangrui Su, Haran Manoharan, Jihun Kim, Lalit Kumar, Heewon Kang, Chunghyun Ryu, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

Electrostatic discharge (ESD) is a major source of electromagnetic interference, capable of causing damage, malfunctions, or disruptions in electronic devices. As a result, ESD immunity testing is a critical component of electromagnetic compatibility (EMC) standards. In this study, the radiation emitted from the ESD gun body over 2 GHz is characterized and modeled using Huygens' principle. The equivalent field source was validated across three different environments, demonstrating accuracy with errors of less than 10 dB. A coupling path visualization technique was then employed to identify critical coupling paths, providing guidance for the strategic placement of absorbers. Simulation results showed that …

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Design Strategies For Skew Compensation In Highspeed Pcb Strip Line Interconnects, Sathvika Bandi, Reza Asadi, Zhekun Peng, Srinivas Venkataraman, Granthana Rangaswamy, Santosh Pappu, Xu Wang, Donghyun Kim Jan 2025

Design Strategies For Skew Compensation In Highspeed Pcb Strip Line Interconnects, Sathvika Bandi, Reza Asadi, Zhekun Peng, Srinivas Venkataraman, Granthana Rangaswamy, Santosh Pappu, Xu Wang, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a comprehensive analysis of the impact of intra-pair PN skew compensation in printed circuit board (PCB) strip line (SL) traces, for a high-speed 224 Gbps lane for the first time. The study investigates the effects of skew compensation placement both with and without via discontinuities. Detailed evaluations are performed in both time and frequency domains, examining critical parameters such as time-domain reflectometry (TDR), input impedance, return loss, insertion loss, and common-mode S -parameters. The findings reveal that, in a simple strip line trace without via discontinuities, the location of skew compensation has negligible influence on signal margins. …

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Enhanced Continual Reinforcement Learning-Based Output Feedback Control Of Heterogeneous Quadrotors Formation, Ehsan Soleimani, S. Jagannathan Jan 2025

Enhanced Continual Reinforcement Learning-Based Output Feedback Control Of Heterogeneous Quadrotors Formation, Ehsan Soleimani, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a unified framework for the safe and optimal control of heterogeneous quadrotor unmanned aerial vehicles (QUAVs) in formation, enabling multitask missions without requiring precise system dynamics. To address partial state observability, a multilayer neural network (MNN) observer is designed to estimate unmeasured states. Reinforcement learning (RL) is employed for optimal control utilizing an MNN ensuring adaptability. Barrier Lyapunov Functions (BLFs) are integrated into the RL framework to enforce safety by maintaining QUAVs within predefined constraints. An enhanced continual learning (ECL) method is proposed to improve the adaptability of MNNs. This method enables effective multitask learning while mitigating …

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Modeling Of Slot-Backed Microstrip Line For Emi Applications, Jongsuk Hyun, Wenchang Huang, Chulsoon Hwang Jan 2025

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 …

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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 Jan 2025

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 …

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Structural Analysis Of Multi-Domain Dynamic Systems Modeled Via Bond Graphs, Arnold A. Fernandes, Jonathan W. Kimball Jan 2025

Structural Analysis Of Multi-Domain Dynamic Systems Modeled Via Bond Graphs, Arnold A. Fernandes, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

Structural Observability (SO) and Structural Monitorability (SM) are structural properties utilized to determine the state and fault-free operation of components, respectively, in a bond graph (BG) model. BGs enable qualitative system analysis, evaluating whether existing sets of sensors and actuators ensure Structural Observability (SO) and Structural Controllability (SC) without knowledge of parametric values. Furthermore, the analysis determines whether there are sufficient sensors available to identify component faults accurately. This work provides a framework for automated sensor placement in a multi-domain physical system while analyzing the SO and SM properties. The MATLAB Structural Analysis Toolbox (MATSAT) conducts sensor placement in a …

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Benchmarking Deep Learning Architectures For Ecg-Based Multi-Label Heart Disease Prediction Using Mimic-Iv Database, Eyiara Oladipo, Sarwar Nazrul, Mohamed Nafea Jan 2025

Benchmarking Deep Learning Architectures For Ecg-Based Multi-Label Heart Disease Prediction Using Mimic-Iv Database, Eyiara Oladipo, Sarwar Nazrul, Mohamed Nafea

Electrical and Computer Engineering Faculty Research & Creative Works

Cardiovascular disease (CVD) is a leading cause of global mortality, accounting for an estimated 17.9 million deaths annually. CVD is broadly defined as a group of medical conditions influenced by modifiable or non-modifiable risk factors that affect the heart's ability to function properly. Machine learning (ML) has emerged as a powerful tool for analyzing complex medical data, aiding in early detection and accurate diagnosis of CVD and improving patient outcomes. Recent studies proposed various deep learning (DL) architectures for detecting CVD, yet there is a lack of robust benchmarks for comparing their performance on large-scale databases. In this work, we …

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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 Jan 2025

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 …

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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 Jan 2025

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 …

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Corona Discharge To Touchscreen Modeling Using Nonlinear Time-Dependent Corona Streamer Propagation Model In Spice, Zhekun Peng, Daniel Szanto, Jianchi Zhou, Darryl Kostka, David Pommerenke, Daryl G. Beetner Jan 2025

Corona Discharge To Touchscreen Modeling Using Nonlinear Time-Dependent Corona Streamer Propagation Model In Spice, Zhekun Peng, Daniel Szanto, Jianchi Zhou, Darryl Kostka, David Pommerenke, Daryl G. Beetner

Electrical and Computer Engineering Faculty Research & Creative Works

SPICE-based methods for predicting coupling from an ESD-induced corona streamer to printed-circuit board (PCB) structures beneath a touchscreen display are evaluated in this paper. Results demonstrate that the non-linear time-dependent propagation model can capture the coupling much better than other models and accurately predict the overall current waveform.

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An Entropy-Bounded, General, Model-Based Framework For Lossy Compression Of Sensor Data, Steven Thompson, Maciej Zawodniok Jan 2025

An Entropy-Bounded, General, Model-Based Framework For Lossy Compression Of Sensor Data, Steven Thompson, Maciej Zawodniok

Electrical and Computer Engineering Faculty Research & Creative Works

In many industries, digital twinning has become an indispensable element of advanced technologies. However, digital twins are heavily reliant on extensive Internet of Things (IoT) sensor measurement data to function effectively. Consequently, data mining has become a lucrative endeavor, akin to gold rushes in the XIX century. However, the substantial volume of collected data often stresses the storage capacities for smaller to medium-sized enterprises, necessitating efficient compression techniques. Error-bound lossy compression offers substantial data reduction advantages, but introduces distortion that, when uncontrolled, can adversely affect analysis. This paper proposes an information optimization scheme that employs information entropy as a comprehensive …

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