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Identifying Early Warning Signs Of Construction Labor Shortages, Ahmed Shiha, Islam H. El-Adaway
Identifying Early Warning Signs Of Construction Labor Shortages, Ahmed Shiha, Islam H. El-Adaway
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Construction labor shortages constrain project-level objectives and national development plans. The goal of this study is to utilize the lagged effects of macroeconomic conditions as early warning signs of construction labor shortages. To this end, the authors adopted a methodology, encompassing (1) retrieval of publicly available data and preprocessing of construction labor shortage as the target variable and macroeconomic measures as the explanatory variables, (2) identification of short-term associations between shortages and economic cycles using the Granger causality test, (3) examination of long-term relationships between labor shortages and economic conditions using the Johansen cointegration test, and (4) estimation of the …
Forecasting State-Level Construction Labor Earnings For Enhanced Project Cost Control: An Econometric And Deep-Learning Analysis Of The Leading Economic Indicators, Ahmed Shiha, Islam H. El-Adaway
Forecasting State-Level Construction Labor Earnings For Enhanced Project Cost Control: An Econometric And Deep-Learning Analysis Of The Leading Economic Indicators, Ahmed Shiha, Islam H. El-Adaway
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
As a major input to several work packages, the labor element constitutes a critical component for successful performance of construction projects. Localized labor shortages, fundamental changes in prevailing wage laws, and historical shifts in the unionization rates of construction workers impair the adequate estimation of construction labor costs in diverse labor market dynamics. Meanwhile, existing studies have utilized national-level indicators to study the trends of construction labor costs, but the relationship between the multifaceted local economic factors and state-level construction labor costs remains understudied. This paper fills such a knowledge gap. A three-stage methodology is adopted: (1) data collection of …
Aqueous Carbonation Of Steel Slags: A Comparative Study On Mechanisms, Nannan Zhang, Gao Deng, Wenyu Liao, Hongyan Ma, Chuanlin Hu
Aqueous Carbonation Of Steel Slags: A Comparative Study On Mechanisms, Nannan Zhang, Gao Deng, Wenyu Liao, Hongyan Ma, Chuanlin Hu
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
This study investigated the aqueous carbonation mechanisms of three typical steel slags: ladle metallurgy furnace (LMF) slag containing high Al content, electric arc furnace (EAF) slag featuring high Si content and relatively low Al content, and ladle-arc fusion (LAF) slag with medium-Al content. It was found that the carbonation kinetics of the three slags were similar and followed the surface coverage model within the first 6 h of carbonation. Initially, the carbonation process was primarily governed by the reaction product precipitation. After 3 h of carbonation, the process was dominated by mineral dissolution, controlled by the uncovered reactive sites. The …
Material Suppliers’ Perspective On Collaboration In Industrial Construction Projects, Seogjae Choi, William J. O'Brien
Material Suppliers’ Perspective On Collaboration In Industrial Construction Projects, Seogjae Choi, William J. O'Brien
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Material suppliers' involvement in construction project planning has been recommended as an effective measure to improve project performance by using their expertise. However, the recommendation is not universal, and some researchers disputed the value of early involvement of suppliers depending on material type. Moreover, prior studies considered main contractors' and owners' perspectives mostly in examining how to increase the involvement of suppliers. To add material suppliers' perspective, this study conducted interviews with experienced professionals from 16 material suppliers including standardized, make-to-order, and custom products. The results are specified by separating the type of materials and sub-phases of planning. The results …
Polarimetry Based Radar Estimation Of Extreme Rainfall: Case Studies, Bong Chul Seo, Witold F. Krajewski, James A. Smith
Polarimetry Based Radar Estimation Of Extreme Rainfall: Case Studies, Bong Chul Seo, Witold F. Krajewski, James A. Smith
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
The study evaluated radar-derived polarimetric rainfall estimates for extreme rain events that occurred in the Kansas City Metropolitan area in the United States. To derive quantitative precipitation estimates (QPE), we implemented two polarimetric algorithms based on specific attenuation (A) and specific differential phase (KDP), along with the reflectivity (Z) based one using data from two radars in the study area. The analysis to assess radar-rainfall estimates (R) utilizes ground observations from a dense network of about 170 rain gauges. Based on our analysis results, the two polarimetric estimates from R(A) and R(KDP) outperform the conventional estimation R(Z). R(A) appeared to …
Every Publication Needs An Author Verified Tl;Dr Statement, Sarah Oerther, Daniel B. Oerther
Every Publication Needs An Author Verified Tl;Dr Statement, Sarah Oerther, Daniel B. Oerther
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
No abstract provided.
Cognitive Fatigue Detection Using Photoplethysmography (Ppg) And Reaction Time Data, Anhar Sami Mohammed, Prajoy Podder, Maciej Jan Zawodniok, Cihan Dagli
Cognitive Fatigue Detection Using Photoplethysmography (Ppg) And Reaction Time Data, Anhar Sami Mohammed, Prajoy Podder, Maciej Jan Zawodniok, Cihan Dagli
Electrical and Computer Engineering Faculty Research & Creative Works
This paper presents a framework for real-time cognitive fatigue detection among shift workers using an integrated approach that combines photoplethysmography (PPG) data and reaction time analysis with advanced deep learning models, including Long Short-Term Memory (LSTM) networks and Feedforward Neural Networks (FNNs). The system leverages heart rate variability (HRV) and reaction time data to identify fatigue indicators. The results demonstrate significant performance, with the first FNN model achieving a test accuracy of 98.94% and a loss of 0.2928, while the second FNN model achieved the same accuracy with a slightly higher loss of 0.3089. The LSTM model, designed for sequential …
High-Frequency Accurate Dual-Side Equivalent Circuit Model For Transformers, Reza Vahdani, Junyong Park, Manish Kizhakkeveettil Mathew, Zhekun Peng, Chiuk Song, Hyucksu Kweon, Jiang Lijun, Donghyun Kim
High-Frequency Accurate Dual-Side Equivalent Circuit Model For Transformers, Reza Vahdani, Junyong Park, Manish Kizhakkeveettil Mathew, Zhekun Peng, Chiuk Song, Hyucksu Kweon, Jiang Lijun, Donghyun Kim
Electrical and Computer Engineering Faculty Research & Creative Works
This study delves into the modeling of a transformer in the frequency range of 100 KHz to 30 MHZ. The coupling coefficient was considered as a function of leakage and self-inductance and incorporated in the optimization process of transformer modeling in the proposed method. The equivalent circuit focused on the critical aspects of leakage inductance, parasitic capacitance, and winding effects. At first, the winding effect of an air-core inductor over wide frequency range with both single-layer and double-layer windings was shown. Then an equivalent circuit was proposed to model a transformer over this frequency range. The comparison between the measured …
Design And Numerical Investigation Of Surface Plasmon Resonance–Based Refractive Index Sensor, Inamullah Sario, Ghulam Abbas Lashari, Abdul Aziz Memon, Farhan Mumtaz
Design And Numerical Investigation Of Surface Plasmon Resonance–Based Refractive Index Sensor, Inamullah Sario, Ghulam Abbas Lashari, Abdul Aziz Memon, Farhan Mumtaz
Electrical and Computer Engineering Faculty Research & Creative Works
A photonic crystal fiber–surface plasmon resonance (PCF-SPR)-based refractive index (RI) sensor with a novel design is presented in this paper. This sensor detects the anomalies in the sample analyte by detecting the change in its RI. Silver (Ag) is used as a plasmonic material with a unique terracotta structure to sense the RI variations in the surrounding medium, also called an analyte or sample. A thin layer of titanium dioxide (TiO2) measuring 10 nm is applied on top of the plasmonic material to prevent the oxidation of silver. The designed sensor detected a good range of analyte RI from 1.31 …
Annotated 3d Point Cloud Dataset For Traffic Management In Simulated Urban Intersections, Elham Binshaflout, Chaima Zaghouani, Nawfal Guefrachi, Charalampos Antoniadis, Hakim Ghazzai, Ahmad Alsharoa, Gianluca Setti
Annotated 3d Point Cloud Dataset For Traffic Management In Simulated Urban Intersections, Elham Binshaflout, Chaima Zaghouani, Nawfal Guefrachi, Charalampos Antoniadis, Hakim Ghazzai, Ahmad Alsharoa, Gianluca Setti
Electrical and Computer Engineering Faculty Research & Creative Works
Ensuring accurate traffic perception and road safety in complex urban environments remains a significant challenge. Advanced traffic monitoring increasingly relies on deep learning, which requires large data volumes. However, existing datasets are often limited to CCTV video footage or focus on dynamic scenarios captured by sensors mounted on ego vehicles. This narrow perspective reduces the effectiveness of comprehensive traffic monitoring, particularly for LiDAR sensors, which typically capture only the vehicle's viewpoint and miss critical areas such as intersections and pedestrian crossings. To address these limitations, we propose a holistic strategy for rapid data collection in urban settings using simulated 3D …
Distributed Sapphire Fiber Bragg Grating-Based Thermal Profiling Of Submerged Entry Nozzles, Farhan Mumtaz, Hanok W. Tekle, Bohong Zhang, Xiaodong Li, Sunday Abraham, Bryant Mathis, Jeffrey D. Smith, Ronald J. O'Malley, Jie Huang
Distributed Sapphire Fiber Bragg Grating-Based Thermal Profiling Of Submerged Entry Nozzles, Farhan Mumtaz, Hanok W. Tekle, Bohong Zhang, Xiaodong Li, Sunday Abraham, Bryant Mathis, Jeffrey D. Smith, Ronald J. O'Malley, Jie Huang
Electrical and Computer Engineering Faculty Research & Creative Works
This article focuses on the application of sapphire fiber Bragg gratings (FBGs) for instrumentation in submerged entry nozzles (SENs) within the steelmaking industry. The SEN is pivotal for transferring molten steel from a tundish to a mold, while preventing the infiltration of oxygen and nitrogen from the surrounding environment. Maintaining optimal flow conditions in the mold is crucial for ensuring casting process stability and maintaining high-quality steel. Sapphire FBG sensors have been instrumented in SENs to enable distributed thermal mapping for monitoring the health of the SEN. The optical sensor comprises three cascaded sapphire FBGs inscribed using femtosecond (FS) laser …
Nonlinear Control Of Buck-Type Converters For Micro-Wind Generators, Noah Wilding, Shuzan Kumar Sarkar, Shruti Pandey, Michael L. Mcintyre
Nonlinear Control Of Buck-Type Converters For Micro-Wind Generators, Noah Wilding, Shuzan Kumar Sarkar, Shruti Pandey, Michael L. Mcintyre
Electrical and Computer Engineering Faculty Research & Creative Works
Small-scale wind turbines offer a promising solution for distributed renewable energy generation. However, this approach often leads to wasted energy when battery capacity is reached, as excess energy is typically dissipated into resistors. The reliance on batteries further increases the cost and complexity of such systems. This paper presents a nonlinear control algorithm for regulating buck-type converters, providing a more efficient energy management solution. By employing a grid-connected inverter, excess energy is utilized rather than dissipated, potentially eliminating the need for batteries and reducing micro-wind turbine installation costs. The proposed control strategy manages the DC-link voltage for the inverter by …
Ibis Model Simulation Accuracy Improvement With Slew Rate Correction, Yifan Ding, Chulsoon Hwang
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 …
A High Step-Up Soft-Switched Converter Based On Coupled Inductor And Current-Fed Voltage Multiplier, Koosha Choobdari Omran, Reza Beiranvand, Pourya Shamsi
A High Step-Up Soft-Switched Converter Based On Coupled Inductor And Current-Fed Voltage Multiplier, Koosha Choobdari Omran, Reza Beiranvand, Pourya Shamsi
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, a novel non-isolated DC-DC converter that combines coupled inductor (CI) and voltage multiplier (VM) techniques is proposed. The leakage energy of the CI is effectively recycled, and soft-switching conditions are achieved for all switches and diodes. Resonance between the leakage inductor of the CI and VM capacitors provides soft-switching conditions, without requiring a separate resonant tank. The use of VM stages not only lowers the voltage stress on semiconductor components but also allows for the use of low-voltage-rated devices, leading to reduced conduction losses, lower cost, and improved efficiency. High voltage gain can be achieved by appropriately …
Balanced Benchmarking Of Zero-Shot And Rag Approaches For Biomedical Term Normalization, Thanh Son Do, Daniel B. Hier, Tayo Obafemi-Ajayi
Balanced Benchmarking Of Zero-Shot And Rag Approaches For Biomedical Term Normalization, Thanh Son Do, Daniel B. Hier, Tayo Obafemi-Ajayi
Electrical and Computer Engineering Faculty Research & Creative Works
Normalization of medical concepts to an ontology is a key aspect of the natural language processing of biomedical text. It enables the mapping of medical expressions to standardized ontology terms and their identifiers, thereby enhancing the interoperability and computability of medical concepts. Although large language models (LLMs) can identify and standardize medical terms, they may struggle to accurately map ontology terms to their corresponding ontology identifiers. These challenges arise from the stochastic nature of LLMs, their limited exposure to uncommon ontology identifiers during training, and their lack of an integrated lookup mechanism. We generated test sets of synthetic terms to …
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
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, …
Method Of Termination With Absorbers For Far-End Crosstalk Measurements, Daniel L. Commerou, Reza Asadi, Sathvika Bandi, Seyed Mostafa Mousavi, Xiaoning Ye, Donghyun Kim
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 …
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
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 …
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
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 …
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
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 …
Obstacles And Mitigations For An Accurate Low Impedance, Low Frequency Measurement, Faye Squires, Yifan Ding, Matthew Doyle, Matteo Cocchini, Samuel Connor, Francesco De Paulis, Albert E. Ruehli, Chulsoon Hwang, Lijun Jiang
Obstacles And Mitigations For An Accurate Low Impedance, Low Frequency Measurement, Faye Squires, Yifan Ding, Matthew Doyle, Matteo Cocchini, Samuel Connor, Francesco De Paulis, Albert E. Ruehli, Chulsoon Hwang, Lijun Jiang
Electrical and Computer Engineering Faculty Research & Creative Works
The two-port shunt configuration is often heralded as the gold standard for low-impedance measurements. However, this measurement method is not without its own issues. The shunt configuration inherently creates a ground loop between the measurement device's reference plane and the reference of the device under test (DUT). Additionally, probes often must be oriented in such a way that allows inductive coupling to occur. This work uses microprobes to measure the shunt impedance of a non-ideal short to explore the limitations of this measurement method in terms of both frequency and impedance. It highlights the importance of ground loop isolation and …
Multi-Objective Inverse Optimization Of High-Speed Interconnects Using Cascaded Deep Neural Network, Yicheng Zhang, Ling Zhang, Hyunwook Park, Bo Pu, Xiao Ding Cai, Chulsoon Hwang, Bidyut Sen, Jun Fan, Er Ping Li, James L. Drewniak
Multi-Objective Inverse Optimization Of High-Speed Interconnects Using Cascaded Deep Neural Network, Yicheng Zhang, Ling Zhang, Hyunwook Park, Bo Pu, Xiao Ding Cai, Chulsoon Hwang, Bidyut Sen, Jun Fan, Er Ping Li, James L. Drewniak
Electrical and Computer Engineering Faculty Research & Creative Works
This paper proposes a novel multi-objective inverse optimization method for high-speed interconnects based on a cascaded deep neural network (DNN) structure, which can efficiently optimize characteristic impedance, insertion loss, and far-end crosstalk (FEXT) simultaneously. Parameter optimization for high-speed interconnects is essential to the signal integrity and electrical performance of complex designs such as multilayer printed circuit boards (PCBs) and chiplets. Conventional optimization approaches often rely on numerous optimization iterations, which is highly time-consuming, especially in high dimensional parameter spaces. This paper proposes a novel DNN based method by cascading an inverse-prediction network and a forward-prediction network to achieve multi-objective optimization …
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
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.
Enhanced Continual Reinforcement Learning-Based Output Feedback Control Of Heterogeneous Quadrotors Formation, Ehsan Soleimani, S. Jagannathan
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 …
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
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. …
Modeling Of Slot-Backed Microstrip Line For Emi Applications, Jongsuk Hyun, Wenchang Huang, Chulsoon Hwang
Modeling Of Slot-Backed Microstrip Line For Emi Applications, Jongsuk Hyun, Wenchang Huang, Chulsoon Hwang
Electrical and Computer Engineering Faculty Research & Creative Works
Radiated emissions from the noise-generating components in modern electronic devices are a significant concern for both electromagnetic interference and RF interference. Shielding cans are commonly used to suppress emissions from noise sources, but accurate shielding effectiveness evaluation requires a clean, well-defined radiation source that can reliably mimic real emissions for repeatable measurements. Slot-backed microstrip antennas provide a practical alternative to loop antennas, offering zero height, low parasitic radiation, and seamless printed circuit board integration. This article proposes an analytical model for estimating the magnetic dipole moment of slot-backed microstrip structures. The model captures both the discontinuity effects and radiated characteristics …
Characterization And Full-Wave Modeling Of Corona Discharge Induced Coupling To Touchscreen Displays, Zhekun Peng, Shubhankar Marathe, Javad Meiguni, Ali Foudazi, Jianchi Zhou, Li Shen, Viswa Pilla, Cheung Wei Lam, Donghyun Kim, David Pommerenke, Daryl G. Beetner
Characterization And Full-Wave Modeling Of Corona Discharge Induced Coupling To Touchscreen Displays, Zhekun Peng, Shubhankar Marathe, Javad Meiguni, Ali Foudazi, Jianchi Zhou, Li Shen, Viswa Pilla, Cheung Wei Lam, Donghyun Kim, David Pommerenke, Daryl G. Beetner
Electrical and Computer Engineering Faculty Research & Creative Works
An electrostatic discharge (ESD) to the glass of a touchscreen display can damage capacitive touch sensor circuitry and traces. The ESD creates a sparkless corona discharge on the glass surface, which couples to sense patches on the other side of the glass. Currents induced on sense traces during the corona discharge are measured in an evaluation setup, which resembles the touchscreen design. Waveforms for current induced at different distances from the discharge position are recorded and compared. The induced currents are analyzed by their peak value and the total charge or energy delivered to the sense trace for different discharge …
Topology And Parameter Joint Identification In Imbalanced Low-Voltage Distribution Networks Based On Load Characteristic Propagation, Yanan Zhang, Gan Zhou, Huan Mao, Wei Gu, Yanjun Feng, Rui Bo
Topology And Parameter Joint Identification In Imbalanced Low-Voltage Distribution Networks Based On Load Characteristic Propagation, Yanan Zhang, Gan Zhou, Huan Mao, Wei Gu, Yanjun Feng, Rui Bo
Electrical and Computer Engineering Faculty Research & Creative Works
Low-voltage distribution networks often suffer from incomplete or outdated network records, making it challenging to obtain the topology and line parameters under actual operating conditions. To address this issue, a joint identification method is proposed based on the propagation of load transient characteristics. First, the principle of load characteristic propagation is elaborated, and the concept of coupling impedance is introduced. Second, a set of linear regression equations is established based on the changes in current and voltage of the terminal measurements before and after load switching, and then these equations are solved using the least squares method to form the …
Structural Analysis Of Multi-Domain Dynamic Systems Modeled Via Bond Graphs, Arnold A. Fernandes, Jonathan W. Kimball
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 …
Centralized And Federated Heart Disease Classification Using Uci Dataset: A Benchmark With Interpretability Analysis, Mario Padilla Rodriguez, Eyiara Oladipo, Mohamed Nafea
Centralized And Federated Heart Disease Classification Using Uci Dataset: A Benchmark With Interpretability Analysis, Mario Padilla Rodriguez, Eyiara Oladipo, Mohamed Nafea
Electrical and Computer Engineering Faculty Research & Creative Works
Cardiovascular disease (CVD) is a leading cause of global mortality, highlighting the need for accurate diagnostic methods. This study benchmarks centralized and federated learning (FL) algorithms for heart disease binary classification using the UCI dataset, which includes 920 patient records from four hospitals in the USA, Hungary, and Switzerland. Our benchmark is supported by Shapley-value as well as Local Interpretable Model-agnostic Explanations (LIME) interpretability analyses to quantify feature importance for classification. In the centralized setup, various classification algorithms are trained on pooled data, with the Naive Bayes classifier achieving the highest test accuracy of 81.1%. Further, FL algorithms with four …