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IEEE International Symposium on Electromagnetic Compatibility (EMC)

作者： Dr. Victor Khilkevich Scott Hinaga Dept. of Electrical and Computer Engineering – Electromagnetic Compatibility Laboratory Missouri University of Science and Technology Rolla MO USA Cisco Systems Inc San Jose CA USA

ISBN: (数字)9798350360394

ISBN: (纸本)9798350360400

Printed circuit board dielectric substrates are composite materials produced by embedding fiber glass fabrics into epoxy resin. Because of this the medium in the PCB transmission lines is inhomogeneous which often leads to degradation of the signal integrity performance of the lines, particularly due to the differential skew. The detrimental effect of the fiber weave can be modeled relatively accurately using full-wave analysis, but at a high computational cost. Alternative modelling techniques are less demanding, but often lack accuracy. This article investigates a possibility of using the 2D cross-sectional analysis for the fiber weave effect modeling, which considerably decreases the computational cost of modeling while retaining the accuracy inherent to the field solvers.

关键词： Geometry Analytical models Accuracy Computational modeling Printed circuits Glass Nonhomogeneous media Fabrics Computational efficiency Signal integrity

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Co-Design of Network Topology and Qubit Allocation for Distributed Quantum Computing

Co-Design of Network Topology and Qubit Allocation for Distr...

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Quantum Communications, Networking, and Computing (QCNC), International Conference on

作者： Jiyao Liu Lei Fan Yuanxiong Guo Zhu Han Yu Wang Department of Computer and Information Sciences Temple University Philadelphia USA Dept. of Engineering Technology University of Houston Houston USA Dept. of Electrical and Computer Engineering University of Houston Houston USA Department of Information Systems and Cyber Security University of Texas at San Antonio San Antonio USA

ISBN: (数字)9798331531591

ISBN: (纸本)9798331531607

Distributed Quantum Computing (DQC) enables the execution of quantum circuits across multiple interconnected quantum processing units (QPUs), but requiring efficient qubit allocation and network topology design to optimize computational performance. Proper qubit allocation minimizes entanglement costs across QPUs, balances computational workload, and ensures efficient execution of quantum computing tasks. Meanwhile, network topology plays a crucial role in reducing entanglement routing complexity and communication overhead for remote quantum gate operations. In this paper, we propose a joint optimization framework for network topology design and qubit allocation in DQC to minimize the communication overhead. We formulate the problem as a tractable integer nonlinear programming model that explicitly incorporates entanglement routing, thereby ensuring a more tractable optimization process. To further improve computational efficiency, we present a partially linearized version of the problem, making it solvable using any classical optimization solver. Extensive simulations on both random and real-world quantum circuits validate the effectiveness of our proposed approach, demonstrating its capability to handle complex quantum circuits while reducing communication costs in DQC.

关键词： Costs Network topology Computational modeling Qubit Topology Computational efficiency Resource management Quantum circuit Integrated circuit modeling Optimization

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Tightly Integrated Motion Classification and State Estimation in Foot-Mounted Navigation systems

Tightly Integrated Motion Classification and State Estimatio...

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International Conference on Indoor Positioning and Indoor Navigation (IPIN)

作者： Isaac Skog Gustaf Hendeby Manon Kok Dept. of Electrical Engineering Uppsala University Uppsala Sweden Dept. of Electrical Engineering Linköping University Linköping Sweden Delft Center for Systems and Control Delft University of Technology Delft The Netherlands

A framework for tightly integrated motion mode classification and state estimation in motion-constrained inertial navigation systems is presented. The framework uses a jump Markov model to describe the navigation system’s motion mode and navigation state dynamics with a single model. A bank of Kalman filters is then used for joint inference of the navigation state and the motion mode. A method for learning unknown parameters in the jump Markov model, such as the motion mode transition probabilities, is also presented. The application of the proposed framework is illustrated via two examples. The first example is a foot-mounted navigation system that adapts its behavior to different gait speeds. The second example is a foot-mounted navigation system that detects when the user walks on flat ground and locks the vertical position estimate accordingly. Both examples show that the proposed framework provides significantly better position accuracy than a standard zero-velocity aided inertial navigation system. More importantly, the examples show that the proposed framework provides a theoretically well-grounded approach for developing new motion-constrained inertial navigation systems that can learn different motion patterns.

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Tightly Integrated Motion Classification and State Estimation in Foot-Mounted Navigation systems

arXiv

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arXiv 2023年

作者： Skog, Isaac Hendeby, Gustaf Kok, Manon Dept. of Electrical Engineering Uppsala University Uppsala Sweden Dept. of Electrical Engineering Linköping University Linköping Sweden Delft Center for Systems and Control Delft University of Technology Delft Netherlands

关键词： Inertial navigation systems

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Normal Vector Direction-based 3D LiDAR Point Cloud Planar Surface Removal for Object Cluster Minimization in Human Activity Monitoring System

Normal Vector Direction-based 3D LiDAR Point Cloud Planar Su...

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IEEE Instrumentation and Measurement technology Conference

作者： Nova Eka Budiyanta Eko Mulyanto Yuniarno Tsuyoshi Usagawa Mauridhi Hery Purnomo Dept. of Electrical Engineering Faculty of Intelligent Electrical and Informatics Technology (F-Electics) Institut Teknologi Sepuluh Nopember Surabaya Indonesia Dept. of Electrical Engineering Dept. of Computer Engineering Faculty of Intelligent Electrical and Informatics Technology (F-Electics) Institut Teknologi Sepuluh Nopember Surabaya Indonesia Department of Computer Science and Electrical Engineering Graduate School of Science and Technology Kumamoto University Kumamoto Japan Dept. of Electrical Engineering Dept. of Computer Engineering Faculty of Intelligent Electrical and Informatics Technology (F-Electics) Institut Teknologi Sepuluh Nopember University Center of Excellence on Artificial Intelligence for Healthcare and Society (UCE AIHeS) Surabaya Indonesia

The use of 3-Dimensional Light Detection and Ranging (3D LiDAR) point cloud as the alternative data to reduce privacy exposure in monitoring systems has been carried out in several studies. Unfortunately, various challenges in using point clouds intersect with the amount of data and computational costs. Several studies attempted to optimize the point cloud processing approach by segmenting the ground plane to get the object clusters separated. However, many unnecessary points can still burden the computation process. Since the ground plane mainly represents the horizontal planar plane on the x, y axis, this study tried to reduce the points on the vertical planar plane on the x, z and y, z axes with the x, y horizontal planar plane as well based on the surface normal vector direction of each point. The proposed approach has successfully reduced the raw point cloud by 79.29% removing the point cloud that indicates the planar surface of the three axes while maintaining the essential object of the monitoring system on the KITTI raw dataset. Therefore, the object cluster can be minimized, supporting the computational costs for further research in human activity monitoring systems.

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Improving Obstacle Avoidance Strategies in Autonomous Navigation of a Sailboat

Improving Obstacle Avoidance Strategies in Autonomous Naviga...

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On-Line Conference (ONCON), Industrial Electronics Society Annual

作者： Pedro Paiva Luís Gomes Dep. Electrical and Computer Engineering NOVA School of Science and Technology — FCT-NOVA NOVA University Lisbon Caparica Portugal School of Science and Technology Center of Technology and Systems (UNINOVA-CTS) and Associated Lab of Intelligent Systems (LASI) NOVA University Lisbon Caparica Portugal

This work explores the different mechanisms involved in creating a behavioural system for route planning and collision avoidance, taking into account the constraints imposed by the navigational characteristics of the sailboat. The implementation of these mechanisms is accompanied by an introduction to fundamental concepts, including Artificial Potential Fields, Histograms of Vector Fields, Navigation in the No-Go Zone, Differentiation of the Nature of Obstacles resulting in Different Operations, and the Constitution of Different Areas of Actuation. Finally, multiple simulations are conducted in a virtual environment to verify the resilience of the proposed navigation strategy.

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Calorie Burn Estimator on Stationary Bike using Human Body Pose Detector

Calorie Burn Estimator on Stationary Bike using Human Body P...

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International Seminar on Intelligent technology and Its Applications (ISITIA)

作者： Iwap Saputra Batan Eko Mulyanto Yuniarno Mauridhi Hery Purnomo Ahmad Ramadhani Dept. of Electrical Engineering Faculty of Intelligent Electrical and Informatics Technology (F-Electics) Institut Teknologi Sepuluh Nopember Surabaya Indonesia Dept. of Electrical Engineering Dept. of Computer Engineering Faculty of Intelligent Electrical and Informatics Technology (F-Electics) Institut Teknologi Sepuluh Nopember Surabaya Indonesia Dept. of Electrical Engineering Dept. of Computer Engineering Faculty of Intelligent Electrical and Informatics Technology (F-Electics) Institut Teknologi Sepuluh Nopember University Center of Excellence on Artificial Intelligence for Healthcare and Society (UCE AIHeS) Surabaya Indonesia

During the pandemic, we must maintain our body’s immunity at best. Outdoor activities have been closed; therefore, there are limitations to activities that can be done. A solution to staying healthy during the pandemic is indoor exercise. One type of indoor exercise is regularly riding stationary bikes. We maintain the body’s fitness and burn calories by riding stationary bikes. However, some stationary bikes could not show accurate calories burned; they calculated it only based on speed, resistance, and duration, so people with different weights seem to burn the same amount of calories. Therefore, this paper proposed an additional parameter essential in calorie burning: body weight. We used the human body pose estimator to detect the activity of riding the stationary bike and calculated it by adding the person’s weight. The result shows a difference between the estimated calorie burned and the data directly from the stationary bike. The difference is between 0.0225 to 2.8775. The heavier the person, the more differences in the calories burned. The proposed method helped prove that a person’s weight affects the calories burned while doing an activity, especially riding a stationary bike.

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electrical Tree Propagation in Epoxy Resin under Superimposed Sinusoidal and Repetitive Pulse Waveforms for Converter-fed Motor Insulation

Electrical Tree Propagation in Epoxy Resin under Superimpose...

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electrical Insulation Conference and electrical Manufacturing & Coil Winding Conference

作者： Takahiro Umemoto Masahiro Sato Ayato Yoshida Kunihiko Hidaka Yuta Yamanaka Takuro Yamada Tetsushi Okamoto Akiko Kumada Dept. of Electrical Engineering and Information Systems The University of Tokyo Tokyo Japan Dept. of Electrical and Electronic Engineering Tokyo Denki University Tokyo Japan Advanced Technology R&D Center Mitsubishi Electric Corporation Amagasaki Japan Rotating Machinery Systems Division Toshiba Mitsubishi-Electric Industrial Systems Corporation Nagasaki Japan

ISBN: (数字)9798350360431

ISBN: (纸本)9798350360448

The ground-wall insulation (epoxy/mica insulation) of form-wound converter-fed rotating machines is subjected to pulse width modulation (PWM) waveforms during operation. In this study, the behavior of electrical trees in epoxy resin, a major cause of the insulation degradation, is experimentally investigated under simulated operating waveforms, i.e. superimposed sinusoidal and repetitive pulse waveforms. Tree length, propagation speed, and morphology are evaluated through microscope observations. The results show that the tree propagation speed becomes significantly faster with an increase in pulse voltage ratio, compared to the case of the AC waveform alone. Considering the observation of the tree morphology, it is inferred that the tree channel density under the superimposed waveforms becomes sparser than that under the sinusoidal alone, resulting in the electric field enhancement at the tip of the tree channels and the faster propagation.

关键词： Degradation Insulation Rotating machines Microscopy Morphology Epoxy resins Voltage

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Enhanced Driver Stress Prediction from Multiple Biosignals via CNN Encoder-Decoder Model

Enhanced Driver Stress Prediction from Multiple Biosignals v...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Vishal Singh Roha Maggie Ezzat Gaber Gendy Kaveti Pavan Thomas M. Deserno Nagarajan Ganapathy Mehmet R. Yuce Dept. of Electrical & Computer Systems Monash University Melbourne Australia Dept. of Biomedical Engineering Indian Institute of Technology Hyderabad Hyderabad India PLRI Lab for Medical Informatics Technical University of Braunschweig Brunswick Germany

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

In this work, we present PhysioFuseNet, a novel framework designed to enhance driver stress state classification. PhysioFuseNet integrates a CNN-based encoder-decoder model with multimodal biosignal fusion. Using a driving simulator, different multimodal signals were acquired, namely electrocardiography, electrodermal activity, photoplethysmography, and respiration rate from (N = 25) healthy subjects. The experiment is of 35 minutes duration and contains different stress states (baseline (5 minutes), while normal, cognitive, and emotional sessions for 10 minutes). Multimodal features are extracted and employed in an encoder-decoder network. Extracted encoder features are combined through intermediate fusion and fed to support vector machine (SVM) and random forest (RF) classifiers. Experimental results demonstrate the efficacy of our approach, outperforming previous methods by achieving accuracies of 0.95 and 0.94 for SVM and RF, respectively. Notably, the framework excels in classifying emotional and cognitive stress states. In summary, the proposed framework could be useful in stress assessment in real-time and clinical conditions.

关键词： Support vector machines Radio frequency Biological system modeling Anxiety disorders Predictive models Electrocardiography Feature extraction Photoplethysmography Real-time systems engineering in medicine and biology

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Dynamic Adaptation Gain Design and Tuning for Threat Discrimination

Dynamic Adaptation Gain Design and Tuning for Threat Discrim...

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IEEE Conference on Decision and Control

作者： Kangkang Zhang Kaiwen Chen Marios M. Polycarpou Thomas Parisini Dept. of Electrical and Electronic Engineering Imperial College London London U.K. Dept. of Electrical and Computer Engineering KIOS Research and Innovation Center of Excellence University of Cyprus Nicosia Cyprus Department of Electronic Systems Aalborg University Denmark Department of Engineering and Architecture University of Trieste Italy

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

Considering potential threats to cyber-physical systems such as component faults and stealthy cyber-attacks, an adaptive observer-based threat discrimination method is proposed for identifying the occurring threat type. Typically, stealthy attacks have only weak effects easily obscured by disturbances on the system outputs. To solve this problem, a parameter adaptation algorithm based on a newly designed dynamic adaptive gain generator is proposed, aiming at improving the sensitivity of the adaptive threat discrimination scheme to potential threats. Only the strictly positive real condition of the proposed gain generator sufficiently ensures the stability of the adaptive observer error system. A moment-matching method is then developed to determine the proper parameters of the gain generator, allowing for the improvement of the sensitivity of the threat discriminators. A numerical example to demonstrate the effectiveness of the proposed methodology is presented.

关键词： Fault diagnosis Sensitivity Adaptive systems Heuristic algorithms Observers Cyber-physical systems Generators Cyberattack Tuning Numerical stability

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