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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 …
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
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 …
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
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 …
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. …
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 …
Modeling Of Slot-Backed Microstrip Line For Emi Applications, Jongsuk Hyun, Wenchang Huang, Chulsoon Hwang
Modeling Of Slot-Backed Microstrip Line For Emi Applications, Jongsuk Hyun, Wenchang Huang, Chulsoon Hwang
Electrical and Computer Engineering Faculty Research & Creative Works
Radiated emissions from the noise-generating components in modern electronic devices are a significant concern for both electromagnetic interference and RF interference. Shielding cans are commonly used to suppress emissions from noise sources, but accurate shielding effectiveness evaluation requires a clean, well-defined radiation source that can reliably mimic real emissions for repeatable measurements. Slot-backed microstrip antennas provide a practical alternative to loop antennas, offering zero height, low parasitic radiation, and seamless printed circuit board integration. This article proposes an analytical model for estimating the magnetic dipole moment of slot-backed microstrip structures. The model captures both the discontinuity effects and radiated characteristics …
Spatially Distributed Optical Fiber Sensing With Weak Fiber Bragg Grating Arrays Based On Microwave Photonics, Wassana Naku, Osamah Alsalman, Chen Zhu
Spatially Distributed Optical Fiber Sensing With Weak Fiber Bragg Grating Arrays Based On Microwave Photonics, Wassana Naku, Osamah Alsalman, Chen Zhu
Electrical and Computer Engineering Faculty Research & Creative Works
Fiber Bragg gratings (FBGs) have been one of the most widely used optical fiber sensors in both scientific and industrial applications due to their unique advantages of high sensitivity, ease of signal transduction, and capabilities for remote operation and multiplexing. However, the majority of sensing systems based on FBGs can only achieve quasi-distributed sensing along the fiber under test, leaving dark zones in between discrete FBG elements. In this work, we propose and demonstrate a microwave photonics enabled approach for the interrogation of cascaded FBGs to achieve spatially distributed sensing. The core of the system includes an incoherent optical frequency-domain …
Characterization And Full-Wave Modeling Of Corona Discharge Induced Coupling To Touchscreen Displays, Zhekun Peng, Shubhankar Marathe, Javad Meiguni, Ali Foudazi, Jianchi Zhou, Li Shen, Viswa Pilla, Cheung Wei Lam, Donghyun Kim, David Pommerenke, Daryl G. Beetner
Characterization And Full-Wave Modeling Of Corona Discharge Induced Coupling To Touchscreen Displays, Zhekun Peng, Shubhankar Marathe, Javad Meiguni, Ali Foudazi, Jianchi Zhou, Li Shen, Viswa Pilla, Cheung Wei Lam, Donghyun Kim, David Pommerenke, Daryl G. Beetner
Electrical and Computer Engineering Faculty Research & Creative Works
An electrostatic discharge (ESD) to the glass of a touchscreen display can damage capacitive touch sensor circuitry and traces. The ESD creates a sparkless corona discharge on the glass surface, which couples to sense patches on the other side of the glass. Currents induced on sense traces during the corona discharge are measured in an evaluation setup, which resembles the touchscreen design. Waveforms for current induced at different distances from the discharge position are recorded and compared. The induced currents are analyzed by their peak value and the total charge or energy delivered to the sense trace for different discharge …
Topology And Parameter Joint Identification In Imbalanced Low-Voltage Distribution Networks Based On Load Characteristic Propagation, Yanan Zhang, Gan Zhou, Huan Mao, Wei Gu, Yanjun Feng, Rui Bo
Topology And Parameter Joint Identification In Imbalanced Low-Voltage Distribution Networks Based On Load Characteristic Propagation, Yanan Zhang, Gan Zhou, Huan Mao, Wei Gu, Yanjun Feng, Rui Bo
Electrical and Computer Engineering Faculty Research & Creative Works
Low-voltage distribution networks often suffer from incomplete or outdated network records, making it challenging to obtain the topology and line parameters under actual operating conditions. To address this issue, a joint identification method is proposed based on the propagation of load transient characteristics. First, the principle of load characteristic propagation is elaborated, and the concept of coupling impedance is introduced. Second, a set of linear regression equations is established based on the changes in current and voltage of the terminal measurements before and after load switching, and then these equations are solved using the least squares method to form the …
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 …
Benchmarking Deep Learning Architectures For Ecg-Based Multi-Label Heart Disease Prediction Using Mimic-Iv Database, Eyiara Oladipo, Sarwar Nazrul, Mohamed Nafea
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 …
Honey-Reram Enabled Sustainable Edge Ai System For Iot Applications, Jinhui Wang, Feng Zhao, Mohammad Rafeeq Khan, Md Mehedi Hasan Tanim, Zoe Templin, Harshvardhan Uppaluru
Honey-Reram Enabled Sustainable Edge Ai System For Iot Applications, Jinhui Wang, Feng Zhao, Mohammad Rafeeq Khan, Md Mehedi Hasan Tanim, Zoe Templin, Harshvardhan Uppaluru
Electrical and Computer Engineering Faculty Research & Creative Works
This paper is toward a promising solution to address the environmental sustainability challenge in computing by building brain-inspired and green non-Von Neumann systems with Resistive Random-Access Memory (ReRAM) made from natural organic materials, honey, for energy-efficient operation, renewable material resources, sustainable device manufacturing, and environmentally-friendly disposal. In this paper, honey-ReRAM and its arrays are firstly manufactured and tested. The resistance modulation mechanism of honey-ReRAM is analyzed and investigated. Then a Computing-in-Memory (CIM) architecture based on honey-ReRAM for edge AI and IoT applications is proposed and evaluated. The experimental results indicate that the proposed edge AI systems with the VGG8 and …
Ethics Vs.. Regulation: Converging Frameworks For Trustworthy Human-Centered Ai In Biomedical Research, Tayo Obafemi-Ajayi, Tiffani J. Bright, Emily F. Wong, Donald Wunsch, Joan Peckham, Jason H. Moore
Ethics Vs.. Regulation: Converging Frameworks For Trustworthy Human-Centered Ai In Biomedical Research, Tayo Obafemi-Ajayi, Tiffani J. Bright, Emily F. Wong, Donald Wunsch, Joan Peckham, Jason H. Moore
Electrical and Computer Engineering Faculty Research & Creative Works
The accelerating impact of AI in biomedical research is driving significant advances in precision medicine. As these systems increasingly shape health outcomes, the imperative to develop trustworthy, reliable, and ethically grounded AI becomes more pressing, particularly in addressing concerns related to data integrity, patient safety, and equitable outcomes. While the potential of AI to transform biomedical research is clear, its responsible integration depends on more than technological capability. Ensuring that these systems are aligned with societal values requires a dual commitment: the operationalization of ethical principles throughout the AI life cycle and the establishment of robust regulatory mechanisms. Ethics provides …
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
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.
An Extensive Analysis Of Match-Tracking Methods For Artmap, Niklas M. Melton, Leonardo Enzo Brito Da Silva, Donald C. Wunsch
An Extensive Analysis Of Match-Tracking Methods For Artmap, Niklas M. Melton, Leonardo Enzo Brito Da Silva, Donald C. Wunsch
Electrical and Computer Engineering Faculty Research & Creative Works
This paper identifies and studies five match-tracking (MT) methods in the adaptive resonance theory (ART) literature and conducts a detailed comparative analysis of these in ARTMAP applications. We focus on model performance for each MT method with respect to time and space efficiency as well as classification accuracy. Experimental results indicate that one MT variant, used in ARTMAP applications for the first time in this work, provides significant improvements in computational efficiency: depending on the ARTMAP variant, it was able to achieve up to one order of magnitude reduction in both time and space requirements, albeit with a compromise in …
Active And Reactive Power Flow Control Of The Dual Active Bridge Converter, Lauryn Morris, Thomas W. Francois, Jonathan Saelens, Oroghene Oboreh-Snapps, Arnold Fernandes, Praneeth Uddarraju, Sophia A. Strathman, Jonathan W. Kimball
Active And Reactive Power Flow Control Of The Dual Active Bridge Converter, Lauryn Morris, Thomas W. Francois, Jonathan Saelens, Oroghene Oboreh-Snapps, Arnold Fernandes, Praneeth Uddarraju, Sophia A. Strathman, Jonathan W. Kimball
Electrical and Computer Engineering Faculty Research & Creative Works
The Dual Active Bridge (DAB) is a reliable and efficient converter capable of providing bi-directional power transfer and galvanic isolation. An ac-ac DAB can control both active and reactive power flow. The present work introduces a combined feedback/feed-forward current control system, utilizing the calculated and measured converter currents translated into the dq reference frame, to control the output power. The system was simulated in PLECS to demonstrate the control algorithm's ability to track the dq currents and provide the necessary output power.
Large-Range And High-Sensitivity Displacement Sensing Based On Extrinsic Fabry-Perot Interferometer Assisted Microwave Photonic Filter, Shiyu Li, Ruimin Jie, Osamah Alsalman, Jie Huang, Chen Zhu
Large-Range And High-Sensitivity Displacement Sensing Based On Extrinsic Fabry-Perot Interferometer Assisted Microwave Photonic Filter, Shiyu Li, Ruimin Jie, Osamah Alsalman, Jie Huang, Chen Zhu
Electrical and Computer Engineering Faculty Research & Creative Works
Displacement is a pivotal physical parameter, and advancements in displacement sensor technology have enabled the creation of a diverse array of physical and mechanical sensors through seamless integration with mechanical transducers. In this study, we introduce a displacement sensing technique leveraging an extrinsic Fabry-Perot interferometer (EFPI) assisted microwave photonic filter. By translating displacement-induced variations in the EFPI's optical reflection into peak frequency shifts within its frequency response, we achieve large-dynamic-range displacement measurements with outstanding signal quality and demodulation ease. Proof-of-concept demonstrations showcase a substantial 5 mm range with a remarkable sensitivity of 1.148 GHz/mm, achieved using a basic single-mode fiber-based …
A Data-Driven Adaptive Control Approach For Enhancing The Dynamic Response Ff Vsgs In Varying Grid Conditions, Shah Fahad, Buxin She, Junjie Yin, Fangxing Li, Hantao Cui, Rui Bo
A Data-Driven Adaptive Control Approach For Enhancing The Dynamic Response Ff Vsgs In Varying Grid Conditions, Shah Fahad, Buxin She, Junjie Yin, Fangxing Li, Hantao Cui, Rui Bo
Electrical and Computer Engineering Faculty Research & Creative Works
Conventionally, a virtual synchronous generator (VSG) is designed for islanded mode (IM) operation to meet specific operational requirements such as the rate of change of frequency (RoCoF). However, the operation of VSG designed for IM may not meet the operational and control criteria in grid connected mode (GCM) when the grid conditions vary. In addition, conventional VSG control technology does not consider the influence of the presynchronization scheme when connected to a weak grid, which degrades the RoCoF in IM. To overcome the aforementioned challenges, the proposed study presents a twin-delayed deep deterministic policy gradient (TD3) algorithm to improve the …
Microwave Photonic Fiber Ring Resonator For Optical Sensing Based On In-Ring And Out-Of-Ring Modulation, Shiyu Li, Chen Zhu
Microwave Photonic Fiber Ring Resonator For Optical Sensing Based On In-Ring And Out-Of-Ring Modulation, Shiyu Li, Chen Zhu
Electrical and Computer Engineering Faculty Research & Creative Works
Intensity-modulated optical fiber sensors (IM-OFSs) have garnered significant research interest due to their advantageous characteristics, including simplified fabrication procedures, cost-efficient systems, and straightforward signal demodulation, leading to their widespread application across diverse fields. Nevertheless, the multiplexing technique for IM-OFSs remains underexplored, primarily because isolating the contributions of individual sensors within the system using traditional power measurements poses a significant challenge. In this study, we introduce and experimentally validate a novel approach leveraging a simple microwave-photonic fiber ring resonator (MWP-FRR). This approach enables the concurrent interrogation of two IM-OFSs based on an in-and-out-of-ring-modulation (IORM) strategy. The transmission losses of both IM-OFSs …
Print Quality Assessment Of Additively Manufactured Resonant Structures, Logan M. Wilcox, Alexander Hook, Emma T. Bohannon, Cody Morrow, Doyle T. Motes, Kristen M. Donnell
Print Quality Assessment Of Additively Manufactured Resonant Structures, Logan M. Wilcox, Alexander Hook, Emma T. Bohannon, Cody Morrow, Doyle T. Motes, Kristen M. Donnell
Electrical and Computer Engineering Faculty Research & Creative Works
Due to the increased popularity of additive manufacturing (AM) and availability of electrically conductive filaments, the potential for using AM to fabricate high frequency resonant structures has been realized. As these structures require specific operating conditions to provide the desired resonant response (such as substrate/superstrate material, operating frequency, polarization, etc.), print quality validation through an assessment of the resonant response can be difficult to accomplish. To this end, active microwave thermography (AMT) is proposed as an alternative technique to assess and validate an AM resonant structure. Two AM resonant structures were manufactured using fused deposition modeling (FDM) and the resonant …
Advancing Temperature Monitoring Of The Bottom Anode In A Direct Current Electric Arc Furnace Operations With Distributed Optical Fiber Sensors., Ogbole Collins Inalegwu, Rony Kumer Saha, Yeshwanth Reddy Mekala, Farhan Mumtaz, Nicholas Dionise, Zane Voss, Jeffrey D. Smith, Ronald J. O'Malley, Rex E. Gerald, Jie Huang
Advancing Temperature Monitoring Of The Bottom Anode In A Direct Current Electric Arc Furnace Operations With Distributed Optical Fiber Sensors., Ogbole Collins Inalegwu, Rony Kumer Saha, Yeshwanth Reddy Mekala, Farhan Mumtaz, Nicholas Dionise, Zane Voss, Jeffrey D. Smith, Ronald J. O'Malley, Rex E. Gerald, Jie Huang
Electrical and Computer Engineering Faculty Research & Creative Works
The bottom anode in the Direct Current Electric Arc Furnace (DC EAF) is critical for completing the electrical circuit necessary for sustaining the arc within the furnace. For pin-type bottom anodes, monitoring of the temperature of select pins instrumented with thermocouples is performed to track bottom wear in the EAF and inform the operator when the furnace should be removed from service. This work presents the results from a plant trial using distributed temperature monitoring of bottom anode pins in a 165-ton DC EAF over a two-month service period utilizing two optical fiber sensing techniques: fiber Bragg grating (FBG) and …
Training Neural Networks With A Self-Adaptive Ant Colony Algorithm, Ashraf M. Abdelbar, Donald C. Wunsch
Training Neural Networks With A Self-Adaptive Ant Colony Algorithm, Ashraf M. Abdelbar, Donald C. Wunsch
Electrical and Computer Engineering Faculty Research & Creative Works
ACOR is a well-established ant colony optimization algorithm that has been applied to neural network training. We present an approach for the dynamic adaptation of the ACOR algorithm's search intensification/diversification parameter q, based on using several pre-specified parameter configurations, which we call personalities. Before an ant begins to generate a candidate solution, it stochastically adopts a personality based on the relative past success of the different personalities. The success of a personality is measured, in turn, by the relative quality of previous solutions generated by ants adopting that personality. The premise of our approach is that some personalities will be …
Annotated 3d Point Cloud Dataset For Traffic Management In Simulated Urban Intersections, Elham Binshaflout, Chaima Zaghouani, Nawfal Guefrachi, Charalampos Antoniadis, Hakim Ghazzai, Ahmad Alsharoa, Gianluca Setti
Annotated 3d Point Cloud Dataset For Traffic Management In Simulated Urban Intersections, Elham Binshaflout, Chaima Zaghouani, Nawfal Guefrachi, Charalampos Antoniadis, Hakim Ghazzai, Ahmad Alsharoa, Gianluca Setti
Electrical and Computer Engineering Faculty Research & Creative Works
Ensuring accurate traffic perception and road safety in complex urban environments remains a significant challenge. Advanced traffic monitoring increasingly relies on deep learning, which requires large data volumes. However, existing datasets are often limited to CCTV video footage or focus on dynamic scenarios captured by sensors mounted on ego vehicles. This narrow perspective reduces the effectiveness of comprehensive traffic monitoring, particularly for LiDAR sensors, which typically capture only the vehicle's viewpoint and miss critical areas such as intersections and pedestrian crossings. To address these limitations, we propose a holistic strategy for rapid data collection in urban settings using simulated 3D …
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 …
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 …
Mapping Biomedical Ontology Terms To Ids: Effect Of Domain Prevalence On Prediction Accuracy, Thanh Son Do, Daniel B. Hier, Tayo Obafemi-Ajayi
Mapping Biomedical Ontology Terms To Ids: Effect Of Domain Prevalence On Prediction Accuracy, Thanh Son Do, Daniel B. Hier, Tayo Obafemi-Ajayi
Electrical and Computer Engineering Faculty Research & Creative Works
This study evaluates the ability of large language models (LLMs) to map biomedical ontology terms to their corresponding ontology IDs across the Human Phenotype Ontology (HPO), Gene Ontology (GO), and UniProtKB terminologies. Using counts of ontology IDs in the PubMed Central (PMC) dataset as a surrogate for their prevalence in the biomedical literature, we examined the relationship between ontology ID prevalence and mapping accuracy. Results indicate that ontology ID prevalence strongly predicts accurate mapping of HPO terms to HPO IDs, GO terms to GO IDs, and protein names to UniProtKB accession numbers. Higher prevalence of ontology IDs in the biomedical …
An Extendable Soft-Switched Step-Up Interleaved Converter Integrated With Voltage Multiplier Cells, Amir Hasan Babanezhad, Koosha Choobdari Omran, Reza Beiranvand, Pourya Shamsi
An Extendable Soft-Switched Step-Up Interleaved Converter Integrated With Voltage Multiplier Cells, Amir Hasan Babanezhad, Koosha Choobdari Omran, Reza Beiranvand, Pourya Shamsi
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, a multiphase high step-up interleaved converter is introduced, which ensures low-input current ripple, low-component currents, and voltage stresses. The proposed circuit guarantees ZVS operation for power switches and ZCS operation for power diodes, which significantly reduce converter switching losses and EMI emission and improve its efficiency. Therefore, its passive components volume can be reduced by using high switching frequencies. In addition, the interleaved technique reduces input current ripple and input filter volume and provides high-power density. High-voltage gain and low-voltage stresses on the components are also achieved due to the integration of the converter structure with the …
Online Learning-Driven Human Intent Estimation And Control For Human-Robot Interaction, Irfan Ganie, S. Jagannathan
Online Learning-Driven Human Intent Estimation And Control For Human-Robot Interaction, Irfan Ganie, S. Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
This paper presents a novel Stackelberg-game theoretic multilayer-online learning framework for cooperative control of nonlinear Physical Human-Robot Interaction (pHRI), where the human is modeled as the leader guiding a robot follower. This hierarchical interaction is captured as a dynamic Stackelberg game, with the human's intention estimated in real-time through online multilayer neural networks (MNNs). We introduce SVD-based weight update laws for actor-critic MNNs, which approximate value functions and control inputs for both human and robot, eliminating the need for predefined basis functions. In this framework, the human objective is first inferred and used to guide the robot actions by shaping …
An Entropy-Bounded, General, Model-Based Framework For Lossy Compression Of Sensor Data, Steven Thompson, Maciej Zawodniok
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 …