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A Bayesian k-vector estimation method for electromagnetic waves in magnetized cold plasma

URSI Radio science Bulletin 2023年第378期2021卷 77-82页

作者： Yuji Tanaka Mamoru Ota Shoya Matsuda Yoshiya Kasahara Division of Electrical Engineering Graduate School of Engineering Kyoto University Kyotodaigaku-Katsura Nishikyo-ku Kyoto Kyoto Japan Department of Electrical and Control Systems Engineering National Institute of Technology Toyama College 13 Hongo-machi Toyama Toyama Japan Division of Electrical Engineering and Computer Science Graduate School of Natural Science and Technology Kanazawa University Kakuma Kanazawa Ishikawa Japan

Using the plasma wave characteristics and remote sensing technology, the k-vector direction of plasma waves can provide important information for understanding the global features of space plasma. In this study, we proposed a Bayesian k-vector estimation method in magnetized cold plasma based on the wave distribution function method. The proposed method can be applied to various types of sensors with easy visualization and calculation of the estimation accuracy. We verified the effectiveness of the proposed method through simulations.

关键词： Estimation Plasmas Electromagnetics Mathematical models Magnetic sensors Bayes methods Plasma waves

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Self-powered highly stretchable ferroelectret nanogenerator towards intelligent sports

Nano Trends

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Nano Trends 2024年 8卷

作者： Wang, Yiqin Cai, Xianfa Guo, Yufeng Chen, Zhi Cao, Yunqi Du, Wangdi Xia, Tian Sepulveda, Nelson Li, Wei College of Integrated Circuit Science and Engineering Nanjing University of Posts and Telecommunications Jiangsu Nanjing 210023 China College of Control Science and Engineering Zhejiang University Zhejiang Hangzhou 310027 China College of Engineering and Mathematical Sciences University of Vermont Burlington 05405 VT United States Department of Electrical and Computer Engineering Michigan State University East Lansing 48824 MI United States

Ferroelectret nanogenerators (FENGs), recognized for their porous structures that facilitate charge retention, thereby creating giant electric dipoles and exhibiting remarkable piezoelectric properties, are utilized in the development of various flexible transducers. However, despite their flexibility, most developed ferroelectret nanogenerators lack adequate stretchability and satisfactory transverse piezoelectric properties, significantly inhibiting their widespread deployment in wearable or skin-mounted electronics. Here, we introduce a highly stretchable ferroelectret nanogenerator (HS-FENG) built from laser-induced graphene (LIG), Ecoflex and anhydrous ethanol, demonstrating exceptional flexibility and stretchability, along with longitudinal and transverse piezoelectric effects. The stretchability of HS-FENG can reach a record of 468 %, while the quasi-static piezoelectric coefficients d₃₃ and d₃₁ are approximately 120 pC/N and 70 pC/N, respectively. To our knowledge, this is the first demonstration of the developed FENG with remarkably high stretchability. Furthermore, leveraging the performance of the created HS-FENG, we construct a skin-mounted intelligent kinesiology tape capable of effectively monitoring motion signals from human muscles and joints, thereby offering a deeper understanding of movement for users across different levels of physical activity, from professional athletes to individuals undergoing rehabilitation. The development of intelligent kinesiology tape exemplifies the potential of HS-FENG technology in enhancing professional athletic training and personalized healthcare. It contributes to the advancement of inconspicuous skin-mounted biomechanical feedback systems and human-machine interfaces, marking progress in the field. © 2024 The Authors

关键词： Ferroelectret Flexible Nanogenerator Sports training Stretchable Transverse piezoelectricity

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Continuous-Time LiDAR-Inertial-Vehicle Odometry Method with Lateral Acceleration Constraint

Continuous-Time LiDAR-Inertial-Vehicle Odometry Method with ...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Bin He Weichen Dai Zeyu Wan Hong Zhang Yu Zhang State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China School of Computer Science Hangzhou Dianzi University Hangzhou China Key Laboratory of Collaborative sensing and autonomous unmanned systems of Zhejiang Province Hangzhou China

In this paper, we propose a continuous-time-based LiDAR-inertial-vehicle odometry method, which can tightly fuse the data from Light Detection And Ranging (LiDAR), inertial measurement units (IMU), and vehicle measurements. The lateral acceleration constraint is further added to trajectory estimation to make the estimated trajectory follow the motion characteristics of vehicles. In addition, since vehicle model parameters vary with different motion conditions and tyre pressure, we estimate vehicle correction factors that rectify changes in vehicle model parameters online, and also analyze the observability of these vehicle correction factors. In experiments, the proposed method is evaluated and compared with state-of-the-art methods in the public dataset. The experimental results show that the proposed method achieves more accurate results in all sequences since we add additional sensor measurements and utilize the characteristic of vehicle motion to restrict the trajectory estimation. The ablation study also proved the effectiveness of continuous-time representation, online correction factor estimation, and incorporation of lateral acceleration constraint.

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An Assessment of Multilevel Converters Submodules EMI Emissions Considering Three Configurations Including Parasitic Parameters

An Assessment of Multilevel Converters Submodules EMI Emissi...

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IEEE International Symposium on Electromagnetic Compatibility - EMC Europe

作者： Amr Madi Waseem Elsayed Ahmed Hebala Michal Przybylski Piotr Lezynski Robert Smolenski Institute of Automatic Control Electronics and Electrical Engineering Doctoral School of Exact and Technical Sciences University of Zielona Gora Zielona Gora Poland Electrical Engineering Mathematics & Computer Science (EEMCS) University of Twente Enschede Netherlands Electrical and Control Engineering College of Engineering Arab Academy for Science Technology and Maritime Transport Alexandria Egypt Institute of Automatic Control Electronics and Electrical Engineering University of Zielona Gora Zielona Gora Poland

With the expanding use of modular multilevel converters in power installations it became more important to lower the total conducted emissions. One of the most important key factors in controlling electromagnetic interference emissions is the type of submodules used and the utilized switches. This paper compares three well-known submodules which are half bridge, full bridge and double-clamped half bridge effect on the electromagnetic interference emissions. For making the model more accurate the parasitic components were included in all the circuits Additionally, the same configurations are carried out and compared under two switches which are insulated gate bipolar transistors and metal oxide semiconductor field effect transistors operating at two different switching frequencies. The results were obtained by a simulation in a Matlab/Simulink environment.

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A Property Preservation Method for Intelligent Manufacturing System Reconfiguration

A Property Preservation Method for Intelligent Manufacturing...

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Frontiers Technology of Information and computer (ICFTIC), IEEE International Conference on

作者： Min Wang Shanchen Pang College of control science and engineering China university of petroleum (east China) Qingdao China College of Computer Science and Technology China university of petroleum (east China) Qingdao China

Intelligent manufacturing systems (IMS) can realize the rapid production of small batches and multiple varieties according to the individual needs of users. However, the realization of fast and on-demand flexible reconfigurability is a key problem in IMS. The reason is that it is difficult to ensure that the IMS can realize the requirements reliably, safely and effectively. This paper models the IMS based on rewritable Petri nets, which establishes the resource modules and scheduling structures model of the system. Furthermore, we construct the rewritable rule library to preserve the property before and after the system reconfiguration.

关键词： Job shop scheduling Computational modeling Petri nets Production Libraries Manufacturing Reliability

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Sentiment Classification of Chinese Railway Review Text Based on Multi-Feature Fusion Gated Recurrent Unit

Sentiment Classification of Chinese Railway Review Text Base...

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2021 International Conference on Information science, Parallel and Distributed Systems, ISPDS 2021

作者： Su, Chenglang Jiang, Lekang Pi, Shaorui Shenzhen University College of Mechatronics and Control Engineering Shenzhen China University of Nottingham Department of Computer Science Nottingham United Kingdom University of Liverpool Department of Electrical Engineering and Electronics Liverpool United Kingdom

ISBN: (纸本)9781665417389

Posting comments through online platforms has become the main channel for many users to express their opinions. Many Chinese private companies have rectified their marketing strategies by collecting online user comments and using them as a reference. However, since many Chinese state-owned enterprises are within the system, they can only rectify and reform according to the plan provided by the government but with little effect. China's railway system is faced with such problems. Traditional sentiment classification methods may encounter some problems when processing short texts. Our research provides a Gated Recurrent Unit (GRU) sentiment classification method based on multi-feature fusion and sentiment classification of user reviews about China's railway system. And through classification, we get 1244 comments with negative emotions and 919 non-emotional comments © 2021 IEEE.

关键词： Railroads

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Exploring Gender Differences in EEG-Based Emotion Recognition with Haptic Vibration

Exploring Gender Differences in EEG-Based Emotion Recognitio...

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IEEE International Conference on Development and Learning, ICDL

作者： Xin Wang Baoguo Xu Jiajin Wang Wenbin Zhang Aiguo Song The State Key Laboratory of Digital Medical Engineering Jiangsu Key Laboratory of Remote Measurement and Control School of Instrument Science and Engineering Southeast University Nanjing China College of Computer and Information Hohai University Nanjing China

The study of gender differences in emotions has attracted interest in psychology and neuroscience for decades. However, gender differences in the emotions evoked by haptic stimuli still need to be investigated further. In this paper, we applied visual-auditory-haptic fusion stimuli to evoke four target emotions (joy, sadness, fear, and neutral), and the electroen-cephalogram (EEG) signals were recorded synchronously. The differential entropy (DE) feature was extracted, and the support vector machine (SVM) was employed for emotion classification. Experimental results indicated that females generally behaved with lower brain activation changes than males in most frequency bands and brain regions. Meanwhile, haptic stimuli improved emotion classification accuracy, especially for females. In addition, females showed greater individual differences than males, and haptic stimuli reduced the differences in the same gender, particularly in males. This research promises to facilitate the application of emotion recognition in haptic interactions.

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Text Generation of Speech Imagery Based on an Enhanced CTA-BiLSTM Model Utilizing EEG Signals

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IEEE Transactions on Consumer Electronics 2025年

作者： Pan, Hongguang Chu, Xin Miao, Rui Wang, Mei Wang, Yiran Li, Zhuoyi College of Electrical and Control Engineering Xi’an University of Science and Technology Xi’an710054 China Xi’an Key Laboratory of Electrical Equipment Condition Monitoring and Power Supply Security Xi’an710054 China LTD Company of Shenzhen HQVT Technology Co Shenzhen518100 China College of Computer Science and Technology Xi’an University of Science and Technology Xi’an710054 China Northwestern Polytechnic University School of Automation Xi’an710072 China

Recent studies have demonstrated the potential application of speech imagery neural signals in brain–computer interface (BCI) technology. Text generation based on speech imagery offers a natural communication method for individuals with speech disabilities. However, the limitations in imagined content and the immaturity of text generation technology currently constitute an obstacle to its applications. Therefore, this study proposes an enhanced CTA-BiLSTM model for efficient text generation utilizing speech imagery electroencephalography (EEG) signals, significantly enhancing the accuracy and fluency of text generation. Firstly, distinct from the prevailing imagination of characters and words, this study has assembled a sentence-level EEG dataset from ten subjects to facilitate communication. Subsequently, addressing the temporal dynamics characteristics and sequence dependencies of sentence signals, we employ dynamic time warping (DTW) and hidden Markov models (HMM) for accurate temporal alignment and signal annotation to generate fine-grained sentence labels. Finally, the proposed CTA-BiLSTM model leverages channel-time attention mechanism to dynamically adjust weights across channels and time, emphasizing critical features. Concurrently, the bidirectional long short-term memory (BiLSTM) network captures and utilizes long-term dependencies in the EEG signals, thereby enhancing the accuracy of the model in decoding complex temporal patterns. The experimental results demonstrate that the average sentence decoding accuracy can reach 67.50% on the self-built dataset, realizing a better evaluation accuracy and validating its potential for application. © 1975-2011 IEEE.

关键词： Hidden Markov models

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Lightweight Trust Model with Machine Learning scheme for secure privacy in VANET 18

Lightweight Trust Model with Machine Learning scheme for sec...

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18th International Learning and Technology Conference, L and T 2021

作者： Junejo, Muhammad Haleem Ab Rahman, Ab Al-Hadi Shaikh, Riaz Ahmed Yusof, Kamaludin Mohamad Kumar, Dileep Memon, Imran Faculty of Electrical Engineering Universiti Teknologi Malaysia Johor Skudai81310 Malaysia Department of Computer Science Faculty of Computing and Information Technology King Abdulaziz University Jeddah Saudi Arabia State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China Department of Computer Science Bahria University Karachi campus sindh Pakistan

A vehicular ad hoc network (VANETs) is transforming public transport into a safer wireless network, increasing its safety and efficiency. The VANET consists of several nodes which include RSU (Roadside Units), vehicles, traffic signals, and other wireless communication devices that are communicating sensitive information in a network. Nevertheless, security threats are increasing day by day because of dependency on network infrastructure, dynamic nature, and control technologies used in VANET. The security threats could be addressed widely by using machine learning and artificial intelligence on the road transport nodes. In this paper, a comparison of trust and cryptography was presented based on applications and security requirements of VANET. © 2021 The Authors. Published by Elsevier B.V.

关键词： Machine learning

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Flexible control of the Interline DC Power Flow controller Using Virtual Capacitor in VSC-HVDC Grids

Flexible Control of the Interline DC Power Flow Controller U...

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Power Electronic and Drive Systems and Technologies Conference (PEDSTC)

作者： Mirhamed Pourmirasghariyan Mirsajed Pourmirasghariyan Seyed Saeid Heidari Yazdi Seyyed Yousef Mousazadeh Mousavi Kumars Rouzbehi G. B. Gharehpetian Departement of Electrical and Computer Engineering Amirkabir University of Technology Tehran Iran School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Department of Electrical & Computer Engineering School of Engineering and Digital Science Nazarbayev University Nur-Sultan Kazakhstan Faculty of Engineering and Technology University of Mazandaran Sari Iran Department of Systems and Automatic Control Engineering University of Seville Seville Spain

The performance of Interline DC Power Flow controllers (IDC-PFCs) in Voltage Source Converters (VSC)-based High Voltage Direct Current (HVDC) grids, can be affected due to different issues. The current limitation of HVDC lines, the voltage limitation of HVDC buses, and DC voltage of the IDC-PFC intermediary capacitor prevent effective and efficient operation of IDC-PFCs. In this paper, it is shown that this issue can be overcome by using a virtual capacitor in parallel with the IDC-PFC intermediary capacitor. Also, an energy control-based scheme is proposed for the operation of IDC-PFCs in VSC-HVDC grid. The benefits of using the virtual capacitor are: widening the operational area of the IDC-PFCs for the determined duty cycle and injecting more voltage in series to the interconnected HVDC line to control the related HVDC line current. The proposed solution is successfully evaluated on a CIGRE three-terminal VSC-HVDC grid which is modeled by linearized space-state equations.

关键词： Fluctuations HVDC transmission Capacitors High-voltage techniques Boosting Mathematical models Power conversion

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