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2023 International Electrical engineering Congress, iEECON 2023

作者： Channgamthiang, Surasak Nusukhon, Pheeraphat Chansri, Pakpoom King Mongkut's University of Technology Thonburi Dept. Electrical Technology Education Bangkok Thailand King Mongkut's University of Technology Thonburi Dept. Control System and Instrumentation Engineering Bangkok Thailand

ISBN: (纸本)9798350332360

Factory waste includes the incomplete combustion of industrial fuels that causes carbon to precipitate in vents. These carbons might be put to good use. Therefore, the impact of using waste carbon in factories to produce electricity is investigated in this study by evaluating electrical characteristics: the type of electrode material's suitability, the size of the electrode's carbon contact surface area, and the distance between the electrodes. According to the findings, the maximum open circuit voltage (Voc) was 1.09 V for copper (+) and zinc (-) electrode materials, 1.11 V for the electrode's carbon contact surface area, and 1.29 V for the electrodes' spacing. The maximum of Voc was 1.11 V, maximum on-load voltage and current were 0.64V, 124.65 mA for optimum electrode carbon contact surface size 40 cm2. Optimum electrode distance at 2 cm that maximum open circuit voltage (Voc) was 1.29 V. The maximum load voltage and current were 0.77V, 128.32mA. Factory waste carbon can be useful in some applications for producing electricity from waste carbon and assisting in the reduction of factory waste. © 2023 IEEE.

关键词： Carbon

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Performance Evaluation of the Continuos Wavelt Transformation Data in Motor Fault Diagnosis through XAI Algorithm

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Transactions of the Korean Institute of Electrical Engineers 2022年第1期71卷 225-232页

作者： Han, Ji-Hoon Park, Sang-Uk Hong, Sun-Ki Dept. of Information Control Engineering Hoseo University Korea Republic of Dept. of System and Control Engineering Hoseo University Korea Republic of

The data mainly used for motor fault diagnosis is FFT. However, preprocessing such as continuous discrete wavelet transform is used. When using deep learning algorithms, the performance of the data is evaluated by the model output. However, in order to improve the learning possibilities and preprocessing performance of data, performance evaluation from a model perspective is required. For this purpose, data performance evaluation using the LRP algorithm, one of the XAI techniques, is studied. Initial fault state diagnosis using current data, which is difficult to solve with FFT data, is performed with STFT and CWT data, and performance is evaluated through LRP. Experimental Results STFT and CWT are preprocessing techniques that enable the use of current signals for early fault diagnosis. Among the two preprocessing methods, the use of CWT is more preferable because the flexibility of the preprocessing is increased. © 2022 Korean Institute of Electrical Engineers. All rights reserved.

关键词： Failure analysis

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Online PD Measurement by Detecting the Pulsed Compensating Current in High Voltage Equipment 8

Online PD Measurement by Detecting the Pulsed Compensating C...

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8th International Conference on engineering, Applied Sciences, and Technology, ICEAST 2022

作者： Srinangyam, Chissanupong Pannil, Pittaya Nimsanong, Phethai Chuayin, Chaitawat Thungsook, Kittisak Pattanadech, Norasage School of Engineering King Mongkut's Institute of Technology Ladkrabang Electrical Engineering Dept. Bangkok Thailand School of Engineering King Mongkut's Institute of Technology Ladkrabang Instrumentation and Control Engineering Dept. Bangkok Thailand Power System Operation and Control Section 2 Power System Control Dept. Metropolitan Electricity Authority Bangkok Thailand School of Engineering Rajamangala University of Technology Rattanakosin Electrical Engineering Dept. Bangkok Thailand

ISBN: (数字)9781665459198

ISBN: (纸本)9781665459198

This paper discusses the pulsed compensating current caused by partial discharge (PD) phenomena that flows inside the electrical equipment installed in the power system. Such electrical equipment like to be the capacitive coupler in the partial discharge test circuit. In order to study the pulsed compensating current of the PD measurement, artificial PD source such as corona, surface, and internal was used in this experiment. The electrical equipment like surge arrester combined with HFCT sensor utilized to detect the PD pulse current. Furthermore, this proposed technique has been applied for online PD measurement in substations. It was found that the surge arrester could compensate for the pulse current arising from the PD source. This study will be helpful information for online PD measurement. © 2022 IEEE.

关键词： Partial discharges

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Investigating the Impact of Data Preprocessing on Brain Tumor Detection using Neural Network Algorithms 5

Investigating the Impact of Data Preprocessing on Brain Tumo...

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5th IEEE International Conference on Communications, information, Electronic and Energy systems, CIEES 2024

作者： Bekturova, Adeliya Bissembayev, Alibek Suliyev, Rassim Iliev, Teodor Kang, Jeong Won Mukasheva, Assel Kazakh-British Technical University School of Information Technology and Engineering Almaty Kazakhstan Narxoz University School of Digital Technologies Almaty Kazakhstan University of Ruse Dept. of Telecommunications Ruse Bulgaria Korea National University of Transportation Dept. of Transportation System Engineering Uiwang-Si Korea Republic of

ISBN: (纸本)9798350352863

The present article analyses how data augmentation affects the performance of several deep learning models, including CNN, ResNet, and VGG19. By comparing performance indicators across different augmentation scenarios, this article assesses the effectiveness of augmentation strategies for each model. The results show that data augmentation greatly increased performance for the CNN model enhancing parameters like accuracy, precision etc. At the same time data augmentation had no influence on the ResNet model's finel results although it showed a positive increasing in the process. Experiments also reveal very minor gains for the VGG19 model. These findings underscore the need of adapting augmentation strategies to each model's unique traits. Future research should concentrate on optimizing and investigating innovative data augmentation techniques to improve model performance and generalization. © 2024 IEEE.

关键词： Adversarial machine learning

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Relation of Determinant Factors and Their Effect on Improving the Online Learning : A systematic literature review 5

Relation of Determinant Factors and Their Effect on Improvin...

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5th International Conference on Advancement in Data Science, E-Learning and information systems, ICADEIS 2023

作者： Widiartha, Ida Bagus Ketut Hwang, Junseok Nugraha, Ryan Adhitya University of Mataram Dept. of Informatics Engineering Mataram Indonesia Seoul National University Technology Management Economic Policy Program Seoul Korea Republic of Telkom University Dept. of Information System Bandung Indonesia

ISBN: (纸本)9798350303414

This study introduces the Harmony Model, which examines factors influencing the success of online learning and the workload of lecturers. Drawing upon the Theory of Action Reason, it explores the impact of student satisfaction and lecturers' willingness to prepare course materials. The model emphasizes the challenge faced by lecturers in creating high-quality content and highlights the importance of balancing supporting factors and alleviating the associated burden. Strategies to enhance online learning effectiveness should address both lecturers' motivation and student satisfaction. Identifying determinant factors and analyzing their impact on material development can increase lecturers' willingness to provide appropriate course materials. Knowledge extraction processes and satisfaction-related factors play crucial roles. This study offers insights to enhance the online learning experience, optimize learning outcomes, and improve overall effectiveness. © 2023 IEEE.

关键词： Curricula

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Study on Deep Reinforcement Learning for Mobile Robots Flocking control in Certainty Situations 19

Study on Deep Reinforcement Learning for Mobile Robots Flock...

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19th International Conference on Electrical engineering/Electronics, Computer, Telecommunications and information Technology, ECTI-CON 2022

作者： Kheawkhem, Pontakorn Khuankrue, Issarapong King Mongkut's University of Technology Thonburi Dept. of Control System and Instrumentation Engineering Bangkok Thailand

ISBN: (纸本)9781665485845

Mobile robots are the widely used machines that will be a part of life. It can easily be scaled to meet the requirements of human uses and can move to different target areas freely. However, mobile robots have a problem with mobility, which needs to respond to human activities and obstacles. Reinforcement learning (RT) is a part of machine learning, which enables the machine to learn by themselves. It can develop in a real-world environment without machine teaching or patterns. This paper proposed the study on the flocking control simulation, which avoids the obstacles. Mobile robots in simulation presented by using Multi-Agent Deep Deterministic Policy Gradient (MAD-DPG). The proposed algorithm, the deep reinforcement learning algorithm, is the main navigation of robots, which find the target, maintain distance between robots, and avoid collision with obstacles by learning features and characteristics with certainty environment, obstacle, robots, and target. On the simulation, the authors operate all of the positions in the environment, and robots speed in the environment as the state. © 2022 IEEE.

关键词： Reinforcement learning

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Securing Mobile Robotic Networks Against Replacement Attack

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IEEE Transactions on Automatic control 2025年

作者： Li, Yushan He, Jianping Chen, Cailian Guan, Xinping Cai, Lin Shanghai Jiao Tong University Dept. of Automation China Ministry of Education of China The Key Laboratory of System Control and Information Processing China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China University of Victoria Dept. of Electrical and Computer Engineering BC Canada

The security of mobile robotic networks (MRNs) has been an active research topic in recent years. This paper aims to secure the ubiquitous formation control of MRNs against the replacement attack, where an external robot can replace a formation robot by compromising the communication and physically interfering with the victim simultaneously. To counter this advanced attack, the novel idea of this work is to leverage the physical proximity of the formation shape and the interaction topology among robots for defense design. First, from the physical proximity perspective, we propose the convex neighbor polygon (CNP) to capture the geometric characteristic of the formation robots, and design a CNP-based security mechanism for the robots during the replacement attack. Then, from the interaction perspective, we introduce the indirect controllability to characterize the possibility that the attacker leverages the interaction between robots to deactivate the CNP mechanism, and establish the conditions regarding the topology structure and the attack input to counter the replacement. Finally, based on the obtained conditions, we demonstrate how to design the initiatory topology among the formation robots to enhance the defense performance. Comparative simulations verify the effectiveness of the proposed method. © 1963-2012 IEEE.

关键词： Topology

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Transformer-based Human Activity Recognition Using Wearable Sensors for Health Monitoring

Transformer-based Human Activity Recognition Using Wearable ...

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International Conference on Biomedical engineering and Applications (ICBEA)

作者： Pengyu Guo Masaya Nakayama Dept. Electronic Engineering and Information System The University of Tokyo Tokyo Japan Dept. Information Technology Center The University of Tokyo Tokyo Japan

ISBN: (数字)9798331535711

ISBN: (纸本)9798331535728

In modern society, the prevalence of sedentary lifestyles, driven by office work and the widespread use of technology such as smartphones, televisions, and computers, has led to insufficient physical activity and associated health issues like obesity. According to the World Health Organization (WHO), 31% of adults and 80% of adolescents fail to meet the recommended levels of physical activity. Many individuals also lack awareness of their daily exercise *** address this problem, we propose a transformer-based model that leverages wearable sensor data to monitor and classify whole-body movements, helping users determine whether they are physically inactive. The model was evaluated on four benchmark datasets: MobiAct, UniMiB SHAR, USC-HAD, and UCI HAR, achieving F1 Scores of 92.01%, 93.40%, 89.00%, and 87.89%, respectively, outperforming baseline models. These results demonstrate the model’s effectiveness in promoting physical activity awareness and addressing sedentary behaviors.

关键词： Accuracy TV Power demand Biological system modeling Benchmark testing Transformers Human activity recognition Wearable sensors Monitoring Smart phones

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Self-superviesed sleep staging model based on contrast learing 3

Self-superviesed sleep staging model based on contrast leari...

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3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing, AIAHPC 2023

作者： Ding, Huilong Zhang, Dong Qi, Kaiyuan Wu, Dong School of Electrical and Information Engineering Zhengzhou University Zhengzhou China System Software R&D Dept. Inspur Electronic Information Industry Co. Ltd. Jinan China

ISBN: (数字)9781510666580

ISBN: (纸本)9781510666573

In the method of sleep staging task, the artificial sleep staging process is complicated, while the traditional machine learning only realizes feature classification and relies on manual feature extraction. This paper presents a deep learning method which can automatically extract and classify EEG features. At the same time, in view of the slow improvement of staging accuracy and high model complexity of existing studies, and the high cost of data due to the dependence on annotated data sets, this paper constructs the end-to-end self-supervised sleep staging model for these problems and continuously improves it. An automatic sleep staging model based on Inception structure and BILSTM was proposed. The convolutional neural network of Inception structure extracts the corresponding features from different time scales, combines the application of attention mechanism and residual structure to carry out the EEG signal characterization learning, and uses BILSTM to carry out the sequence information feature learning. Finally, a self-supervised learning method based on comparison is used to learn the potential feature representation of EEG data from a large number of unlabeled data. In the experiment, the sleep-EDF dataset was used, and the results showed that self-supervision improved the overall classification accuracy of the model. Meanwhile, the classification results of various categories were equalized, and the overall performance of the Sleep staging model was improved. © 2023 SPIE.

关键词： Deep learning

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Switched-Capacitor Low-Pass Filter with Pole Frequency Tuning at Constant Frequency of Switching 16

Switched-Capacitor Low-Pass Filter with Pole Frequency Tunin...

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16th IEEE International Scientific and Technical Conference Actual Problems of Electronic Instrument engineering, APEIE 2023

作者： Denisenko, Darya Y. Titov, Alexey E. Alferova, Irina A. Kuznetsov, Dmitry V. Dept. of Scientific Research Don State Technical University Dept. of Automatic Control Systems Southern Federal University Rostov-on-Don Russia Dept. of Automatic Control Systems Southern Federal University Rostov-on-Don Russia Dept. of Scientific Research Dept. of Cyber Security of Information Systems Don State Technical University Rostov-on-Don Russia Dept. of Information Systems and Radio Engineering Don State Technical University Rostov-on-Don Russia

ISBN: (纸本)9798350330885

The circuitry of a switched-capacitor low-pass filter (SCF) is considered, in which it is possible to tune the pole frequency without changing the capacitances of the switched capacitors, for example, by selecting them of the same kind. To study the suggested SCF circuit, the analysis in the time domain was used, and the obtained characteristics of the SCF were further compared with the characteristics of a generalized second-order analog filter. It is shown that the parameters implemented by the suggested filter depend not only on the capacitance values of the switched capacitors, but also on the ratio of the resistances of two additional resistors. Moreover, the SCF pole frequency is determined by the switching frequency of the keys, the ratios of the capacitances of the switched capacitors, as well as the ratio of the resistances of additional resistors. Due to the goal-oriented selection of the resistances of these resistors, it is possible to lower the SCF pole frequency at constant and identical values of the capacitances of the switched capacitors. © 2023 IEEE.

关键词： Resistors

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