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Progress in Applied Electrical Engineering (PAEE)

作者： Mariusz Pelc Dariusz Mikołajewski Tuukka Ruotsalo Luis A. Leiva Adam Sudoł Edward Jacek Gorzelańczyk Adam Łysiak Aleksandra Kawala-Sterniuk Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland Institute of Computer Science Kazimierz Wielki University Bydgoszcz Poland University of Helsinki Finland University of Copenhagen Denmark Department of Computer Science University of Luxembourg Luxembourg Luxembourg Faculty of Natural and Technical Sciences University of Opole Opole Poland Institute of Philosophy Kazimierz Wielki University Bydgoszcz Poland

This paper presents a preliminary study on the use of machine learning-based methods to select the appropriate parameters of cascade filters in the analysis of brain signals recorded using functional infrared spectroscopy (fNIRS), which shows the level of oxygenation in the brain and, unlike EEG signals (showing electrical brain activity), are less prone to potential interference, disturbances or artifacts occurrence.

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EEG-GNet: GCN-Based EEG Signal Fatigue Detection Network for Edge Devices

EEG-GNet: GCN-Based EEG Signal Fatigue Detection Network for...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Fuquan Zhang Yu Wu Xinxin Xu Chuansheng Wang Minjia Ma Antoni Grau Jiayan Huang School of Computer and Big Data Minjiang University Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China College of New Engineering Industry Putian University Putian China Department of Automatic Control Polytechnic University of Catalonia Barcelona Spain School of Robotics Xi’an Jiaotong-Liverpool University Suzhou China College of New Engineering Industry Putian University Fujian Ruituo Information Technology Limited Company Putian China

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

Fatigue driving is a common potential traffic safety hazard. To detect and analysis the driver Fatigue degree in real-time, more attention have been increasing paid to application research of EEG fatigue detection device. However, existing methods suffer from complex model structure or large-scale model parameters. In the other words, they requires high computational consumption and large memory footprint, which creates a contradiction between model and portable EEG machine with limited hardware resources. In this work, we take both time and frequency domains of EEG signal into account and design an lightweight and efficient driver fatigue detection network based on GCN (EEG-GNet), which is available edge-end device application. Experiments on 4th Raspberry Pi on a public baseline dataset show that our EEG-GNet outperforms the state-of-the-art methods and takes good tradeoff between detection accuracy and resource consumption. Our EEG-GNet provides a new potential opportunity for future applications in practical portable/wearable (P/W) devices.

关键词： Accuracy Computational modeling Image edge detection Frequency-domain analysis Fatigue Brain modeling Feature extraction Electroencephalography Real-time systems Time-domain analysis

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Distributed Finite Time k-means Clustering with Quantized Communucation and Transmission Stopping

arXiv

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arXiv 2022年

作者： Rikos, Apostolos I. Oliva, Gabriele Hadjicostis, Christoforos N. Johansson, Karl H. The Division of Decision and Control Systems KTH Royal Institute of Technology StockholmSE-100 44 Sweden The Unit of Automatic Control Department of Engineering Università Campus Bio-Medico di Roma via Álvaro del Portillo 21 Rome00128 Italy The Department of Electrical and Computer Engineering University of Cyprus Nicosia1678 Cyprus

In this paper, we present a distributed algorithm which implements the k-means algorithm in a distributed fashion for multi-agent systems with directed communication links. The goal of k-means is to partition the network’s agents in mutually exclusive sets (groups) such that agents in the same set have (and possibly share) similar information and are able to calculate a representative value for their group. During the operation of our distributed algorithm, each node (i) transmits quantized values in an event-driven fashion, and (ii) exhibits distributed stopping capabilities. Transmitting quantized values leads to more efficient usage of the available bandwidth and reduces the communication bottleneck. Also, in order to preserve available resources, nodes are able to distributively determine whether they can terminate the operation of the proposed algorithm. We characterize the properties of the proposed distributed algorithm and show that its execution (on any static and strongly connected digraph) will partition all agents to mutually exclusive clusters in finite time. We conclude with examples that illustrate the operation, performance, and potential advantages of the proposed algorithm. © 2022, CC BY.

关键词： K-means clustering

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Performance guarantees of forward and reverse greedy algorithms for minimizing nonsupermodular nonsubmodular functions on a matroid

arXiv

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arXiv 2021年

作者： Karaca, Orcun Tihanyi, Daniel Kamgarpour, Maryam Automatic Control Laboratory D-ITET ETH Zürich Switzerland Electrical and Computer Engineering Department University of British Columbia Vancouver Canada

This letter studies the problem of minimizing increasing set functions, or equivalently, maximizing decreasing set functions, over the base of a matroid. This setting has received great interest, since it generalizes several applied problems including actuator and sensor placement problems in control theory, multi-robot task allocation problems, video summarization, and many others. We study two greedy heuristics, namely, the forward and the reverse greedy algorithms. We provide two novel performance guarantees for the approximate solutions obtained by these heuristics depending on both the submodularity ratio and the curvature. Copyright © 2021, The Authors. All rights reserved.

关键词： Combinatorial optimization

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Improving routing efficiency in vehicular AD Hoc Networks

Improving routing efficiency in vehicular AD Hoc Networks

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International Conference on control, Decision and Information Technologies (CoDIT)

作者： W. Akermi N. Alyaoui A. B. Guiloufi K. Chabbir N. Nasri Automatic Industrial Systems Department Applied Science and Technology Gafsa University Gafsa Tunisia Laboratory of Modeling Analysis and Control of Systems (MACS) National Engineering School of Gabes (ENIG) Gabes University Gabes Tunisia Computer Science and Telecommunications Department Higher Institute of Applied Science and Technology Gafsa University Gafsa Tunisia Preparatory Institute for Engineering Studies of Gabes Laboratory of Modeling Analysis and Control of Systems (MACS) National Engineering School of Gabes (ENIG) Gabes University Gabes Tunisia Computer Science Department-Gafsa Gafsa University Gafsa Tunisia Laboratory of Smart Systems for Engineering and E-Health Based on Technologies of Image and Telecommunications (SETIT) Sfax University Sfax Tunisia

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

Vehicular networks, also known as Vehicular Ad Hoc Networks (VANETs), have become a crucial technology for vehicle communication, providing wireless connectivity among vehicles and between vehicles and infrastructure. However, the dynamic and complex nature of these networks presents unique challenges in routing and resource management. In this study, we explore the use of artificial intelligence (AI) to improve the performance of vehicular networks, focusing on two widely used routing protocols: Optimized Link State Routing (OLSR) and Destination-Sequenced Distance Vector (DSDV).We aim to evaluate the performance of these traditional routing protocols within the context of vehicular networks by integrating machine learning techniques such as neural network regression (MLRegression). Our goal is to understand how the integration of artificial intelligence can enhance the prediction and optimization of vehicular network performance. Using MLRegression, we aim to develop accurate prediction models for performance metrics such as latency, throughput, packet delivery rate, and more, based on network parameters and environmental conditions. This comparative evaluation, which involves incorporating an AI-based approach, will allow us to better understand the strengths and weaknesses of each protocol and provide recommendations for improving vehicular networks.

关键词： Measurement Wireless communication Adaptation models Adaptive systems Vehicular ad hoc networks Routing Throughput Routing protocols Vectors Vehicle dynamics

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Monitoring of Energy Processes in the Electrohydraulic Complex with a Variable-Frequency Electric Drive in Unsteady Operation Modes

Monitoring of Energy Processes in the Electrohydraulic Compl...

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International Conference on Modern Electrical and Energy Systems (MEES)

作者： Mohamed Zaidan Qawaqzeh Viktoriya Kovalchuk Tetyana Korenkova Oleksandr Serdiuk Oleksandr Bilyk Department of Electrical and Electronics Engineering Al-Balqa’ Applied University Al-Salt Jordan Department of Systems of Automatic Control and Electric Drive Kremenchuk Mykhailo Ostrohradskyi National University Kremenchuk Ukraine Department Of Computer Engineering and Electronics Kremenchuk Mykhailo Ostrohradskyi National University Kremenchuk Ukraine

ISBN: (纸本)9798350346848

An energy model of an electrohydraulic complex has been developed. It allows analyzing the energy processes in the power channel in dynamic modes during the development of cavitation and turbulent oscillations in the pipeline network. It has been shown that the nature of energy processes in the considered cases is periodic constant power fluctuations in the analyzed time interval. The variable component in technological and energy signals of the electrohydraulic complex has been assessed. Their frequency analysis has been performed. The coefficient of power controllability of the electrohydraulic complex and its critical values, whereat the development of emergency modes is possible, have been determined.

关键词： Time-frequency analysis Pipelines Process control controllability Hydrodynamics Harmonic analysis Mathematical models

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Artificial Intelligence Based Segmentation for Skin-Layer Visualization from Optical Coherence Tomography Images

Artificial Intelligence Based Segmentation for Skin-Layer Vi...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Gilang Titah Ramadhan Yori Pusparani Ardha Ardea Prisilla Wei-Cheng Shen Hsu-Tang Cheng Ben-Yi Liau Yih-Kuen Jan Wen-Thong Chang Chih-Yang Lin Chi-Wen Lung Department of Computer Science and Information Engineering Asia University Taichung Taiwan Department of Visual Communication Design Budi Luhur University Jakarta Indonesia Department of Digital Media Design Asia University Taichung Taiwan Department of Fashion Design LaSalle College Jakarta Jakarta Indonesia Department of Creative Product Design Asia University Taichung Taiwan Division of Plastic Surgery Asia University Hospital Taichung Taiwan Department of Automatic Control Engineering Feng Chia University Taichung Taiwan Department of Kinesiology and Community Health University of Illinois Urbana USA Department of Mechanical Engineering National Central University Taoyuan Taiwan

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

Changes in epidermal thickness are linked to various skin diseases, such as diabetic foot. Optical Coherence Tomography (OCT), a noninvasive imaging technology, enables detailed visualization of skin layers. This study employed a deep learning approach using the U-Net architecture to analyze OCT images, specifically focusing on the stratum corneum (SC) and epidermis (ED) layers. Utilizing a dataset of 10,000 images, the U-Net model achieved 92 % accuracy in predicting SC and 95% accuracy for ED. These results highlight the potential of this method for accurate 3D visualization of SC and ED layers, paving the way for precise assessment of skin layer thickness and its changes in medical applications.

关键词： Deep learning Visualization Solid modeling Image segmentation Accuracy Three-dimensional displays Optical coherence tomography Medical services Predictive models Epidermis

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Continual Learning for Robust Gate Detection under Dynamic Lighting in Autonomous Drone Racing

Continual Learning for Robust Gate Detection under Dynamic L...

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International Joint Conference on Neural Networks (IJCNN)

作者： Zhongzheng Qiao Xuan Huy Pham Savitha Ramasamy Xudong Jiang Erdal Kayacan Andriy Sarabakha ERI@N Interdisciplinary Graduate Programme Nanyang Technological University Singapore Department of Electrical and Computer Engineering Aarhus University Aarhus Denmark Institute of Infocomm Research (I2R) Agency for Science Technology and Research (A*STAR) Singapore School of Electrical and Electronic Engineering Nanyang Technological University Singapore Automatic Control Group (RAT) Paderborn University Paderborn Germany

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

In autonomous and mobile robotics, a principal challenge is resilient real-time environmental perception, particularly in situations characterized by unknown and dynamic elements, as exemplified in the context of autonomous drone racing. This study introduces a perception technique for detecting drone racing gates under illumination variations, which is common during high-speed drone flights. The proposed technique relies upon a lightweight neural network backbone augmented with capabilities for continual learning. The envisaged approach amalgamates predictions of the gates' positional coordinates, distance, and orientation, encapsulating them into a cohesive pose tuple. A comprehensive number of tests serve to underscore the efficacy of this approach in confronting diverse and challenging scenarios, specifically those involving variable lighting conditions. The proposed methodology exhibits notable robustness in the face of illumination variations, thereby substantiating its effectiveness.

关键词： Continuing education Robot kinematics Neural networks Lighting Logic gates Robustness Real-time systems

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Numerical approach to design of low frequency magnetic field irradiation system for lab on chip experiments

Numerical approach to design of low frequency magnetic field...

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ELEKTRO

作者： Roman Radil Marek Bajtoš Lucia Č arnecká Klaudia Hargaš ová Patrik Kamencay Department of Electromagnetic and Biomedical Engineering University of Zilina Zilina Slovakia Department of Systems Biology and Engineering Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland Dept. of Electromagnetic and Biomedical Engineering Organization University of Zilina Zilina Slovakia

ISBN: (数字)9781665467261

ISBN: (纸本)9781665467278

The article is focused on design of specific electromagnetic coil system using numerical modelling and simulation methods. The proposed solution would be capable of delivering magnetic field of desired strength/ flux density and homogeneity within the specific area to affect the cultivation process of single cells in lab on chip experiments.

关键词： Radiation effects Numerical models Magnetic fields Electromagnetics

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Development of the System of Initial Excitation of the Autonomous Induction Generator 2nd

Development of the System of Initial Excitation of the Auton...

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2nd Electric Power and Renewable Energy Conference, EPREC 2021

作者： Chenchevoi, Volodymyr Kuznetsov, Valeriy Zachepa, Iurii Chornyi, Oleksii Chencheva, Olga Kuznetsov, Vitaliy Yatsiuk, Rostyslav Luhova, Olha Department of Systems of Automatic Control and Electric Drive Kremenchuk Mykhailo Ostrohradskyi National University Kremenchuk Kremenchuk Ukraine Electric Power Department Railway Research Institute Chlopickiego str. 50 Warsaw Poland Manufacturing Engineering Department Kremenchuk Mykhailo Ostrohradskyi National University Kremenchuk Kremenchuk Ukraine Department of the Electrical Engineering and Electromechanic National Metallurgical Academy of Ukraine Gagarina ave. 4 Dnipro Ukraine Department of Automation and Computer-Integrated Technologies Kremenchuk Mykhailo Ostrohradskyi National University Kremenchuk Kremenchuk Ukraine Department of Electric Machines and Devices Kremenchuk Mykhailo Ostrohradskyi National University Kremenchuk Kremenchuk Ukraine

ISBN: (纸本)9789811692383

The article defines the conditions of self-excitation of an inductive generator with capacitor excitation as part of an autonomous power source. Recommendations for the design of an autonomous power source based on an asynchronous machine in terms of the implementation of self-excitation conditions and optimal operating modes are formulated. A simulation model of an autonomous inductive generator and a solar battery for the analysis of transient, static and dynamic modes of operation has been developed. The conducted theoretical studies of capacitive self-excitation of inductive machines have created a good basis for solving problems related to the practical use of autonomous sources based on an inductive generator. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Asynchronous generators

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