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2. Turn-to-Turn Overvoltage Test Technology for Dry-Type Smoothing Reactor

Author

Liu, Qingsong, Huang, Jiajie, Liu, Chenlei, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Dong, Xuzhu, editor, Yang, Qingxin, editor, and Ma, Weiming, editor

Published
2023
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5. An Integrated Medical Recommendation Mechanism Combining Promote Product Singular Value Decomposition and Knowledge Graph

Author

Sun, Yibo, Liu, Chenlei, Tong, Xue, Hu, Bing, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Chen, Weitong, editor, Yao, Lina, editor, Cai, Taotao, editor, Pan, Shirui, editor, Shen, Tao, editor, and Li, Xue, editor

Published
2022
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6. A Collaborative Filtering Recommendation Method with Integrated User Profiles

Author

Liu, Chenlei, Yuan, Huanghui, Xu, Yuhua, Wang, Zixuan, Sun, Zhixin, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Chen, Weitong, editor, Yao, Lina, editor, Cai, Taotao, editor, Pan, Shirui, editor, Shen, Tao, editor, and Li, Xue, editor

Published
2022
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13. A Blockchain-Based Detection and Control System for Model-Generated False Information.

Author

Liu, Chenlei, Xu, Yuhua, Hu, Bing, and Sun, Zhixin

Subjects
DIGITAL technology, QUALITY of service, SOCIAL networks, INFORMATION resources management, ACCURACY of information
Abstract

In the digital age, spreading false information has a far-reaching impact on various areas, such as society, politics, and the economy. With the popularization of applications of text generation models, the cost of producing false information has significantly decreased, making it challenging for human beings to screen it. Therefore, research on detection screening and early warning control for model-generated false information becomes particularly important. In this paper, we propose a model-generated false information detection and control system based on blockchain. Firstly, we design a model-generated false information detection method combining model-generated text discrimination based on a self-attention network and text similarity detection based on a twin network. Secondly, we construct a blockchain-based model-generated false information control and traceability system. It utilizes the proposed detection algorithm to provide early warning and control of model-generated false information involving important and sensitive events before social network release. For information judged to be model-generated false, the stored data on the blockchain is utilized to track and trace the publisher. Ultimately, experimental tests prove that the proposed detection method improves the accuracy of false information detection. In addition, the operational efficiency of the prototype system can meet quality of service requirements. [ABSTRACT FROM AUTHOR]

Published
2024
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14. A Multi-Agent Reinforcement Learning-Based Task-Offloading Strategy in a Blockchain-Enabled Edge Computing Network.

Author

Liu, Chenlei and Sun, Zhixin

Subjects
*DEEP reinforcement learning, *REINFORCEMENT learning, *MACHINE learning, *MOBILE computing, *DATA privacy, *MOBILE learning
Abstract

In recent years, many mobile edge computing network solutions have enhanced data privacy and security and built a trusted network mechanism by introducing blockchain technology. However, this also complicates the task-offloading problem of blockchain-enabled mobile edge computing, and traditional evolutionary learning and single-agent reinforcement learning algorithms are difficult to solve effectively. In this paper, we propose a blockchain-enabled mobile edge computing task-offloading strategy based on multi-agent reinforcement learning. First, we innovatively propose a blockchain-enabled mobile edge computing task-offloading model by comprehensively considering optimization objectives such as task execution energy consumption, processing delay, user privacy metrics, and blockchain incentive rewards. Then, we propose a deep reinforcement learning algorithm based on multiple agents sharing a global memory pool using the actor–critic architecture, which enables each agent to acquire the experience of another agent during the training process to enhance the collaborative capability among agents and overall performance. In addition, we adopt attenuatable Gaussian noise into the action space selection process in the actor network to avoid falling into the local optimum. Finally, experiments show that this scheme's comprehensive cost calculation performance is enhanced by more than 10% compared with other multi-agent reinforcement learning algorithms. In addition, Gaussian random noise-based action space selection and a global memory pool improve the performance by 38.36% and 43.59%, respectively. [ABSTRACT FROM AUTHOR]

Published
2024
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24. An MD Simulation Study of Decomposition Characteristics of C5F10O/CO2 Gas Mixture Under the Presence of Thermal and Electric Field

Author

Tuo, Jinghui, Liu, Chenlei, Zhao, Tong, Sun, Ying, Wang, Xiaosong, and Wang, Xiaolong

Abstract

$\text{C}_{{5}}\text{F}_{{10}}\text{O}$ has outstanding insulation properties and low global warming potential (GWP), which could be potentially used as alternative gas for SF6 and has attracted much attention for researchers. However, there are few reports focusing on its decomposition characteristics under atrocious conditions which are closely related to its insulation performance, as well as its safety issue. In this article, CO2 is selected as the buffer gas. Based on ReaxFF, the decomposition path and reaction mechanism of $\text{C}_{{5}}\text{F}_{{10}}\text{O}$ /CO2 gas mixture were analyzed from the molecular level. The results show that under high temperature conditions $\text{C}_{{5}}\text{F}_{{10}}\text{O}$ cleavage produces CF3, F, $\text{C}_{{4}}\text{F}_{{7}}\text{O}$ , $\text{C}_{{3}}\text{F}_{{6}}$ , CF2, CO, CF4, and other by-products. The break and recombination of C–C single bond and C–F single bond are the main reasons for the formation of fluorocarbons in the products. The addition of the electric field makes the C–F single bond and the C=O double bond in $\text{C}_{{5}}\text{F}_{{10}}\text{O}$ become more active and reactive. The conclusion is complementary to the characteristics of environmental protection insulating gas $\text{C}_{{5}}\text{F}_{{10}}\text{O}$ in insulation and provides reference for related engineering applications.

Published
2023
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36. Influence of Capacitor Voltage Transformer's Transient Response on Commutation of HVDC Transmission System

Author

Zhao Dan-dan, Zhao Sanshan, Cao Yilie, Gu Danzhen, and Liu Chenlei

Subjects
Model predictive control, Computer science, Control theory, Capacitor voltage transformer, Inverter, Commutation, Transient response, Transient (oscillation), Fault (power engineering), Voltage
Abstract

The capacitor voltage transformer (CVT) has a transient response when a fault occurs on the inverter side of HVDC. The output voltage at the secondary side of CVT can not accurately reflect the change of the input voltage at the primary side in time, which will affect the commutation process of the DC system. This paper first establishes a simulation model in PSCAD/EMTDC with the actual parameters of the 220kV saturated CVT, and analyzes the effects of different factors on the transient process. The principle of commutation failure predictive control (CFPREV) is analyzed, and its input voltage has an impact on the commutation process of the DC system. Based on the simulation of East China Power Grid Ge Nan DC model, the AC voltage considering the CVT transient response is used as the input voltage for CFPREV, and the CFPREV link and commutation process are analyzed.

Published
2020

40. Earth surface potential induced by ground-return current of HVDC links — Part I: Measurement and estimation of the earth resistivity

Author

Pan Zhuohong, Lu Hailiang, Wei Li, Xishan Wen, and Liu Chenlei

Subjects
Engineering, Linear programming, business.industry, Estimation theory, 020209 energy, Numerical analysis, Computation, Direct current, 02 engineering and technology, Magnetotellurics, Electrical resistivity and conductivity, 0202 electrical engineering, electronic engineering, information engineering, Electronic engineering, business, Linear combination
Abstract

During the commissioning stage or pole outage of high-voltage direct current (HVDC) links, ground-return currents (GRCs) are injected into dc grounding electrodes. Therefore, earth surface potential (ESP) is induced by GRC. Moreover, nonuniform distribution of ESP in wide areas usually leads to half-cycle saturation of power transformers and interference of metallic underground infrastructures, especially pipelines and cables in long distance. As GRCs flow into the earth by dc grounding electrodes, ESP is determined by the resistivity of the earth. However, the heterogeneity of the earth brings difficulty in simulating ESP. In this paper, measurement and estimation of the earth resistivity is studied in detail. First, measurement technique for earth resistivity is introduced, including both the four-point method (FPM) and the magnetotelluric method (MT). A group of apparent resistivity can be obtained by changing the interval of FPM, which indicates the shallow earth resistivity. By using MT, another group of apparent resistivity representing the deep earth is scanned by tuning the receiving frequency. Second, both FPM and MT are proposed to measure the earth resistivity of wide areas. Measurement data of both methods are used as raw data for earth parameter estimation (EPE). EPE is an optimal problem of finding a good enough earth model to interpret the measured data. Third, this paper introduces an overall objective function (OOF) for EPE. The horizontal layered soil (HLS) is chosen as the ideal earth type. Then based on this assumption, HOF is set to a linear combination of the objective functions of FPM and MT. Finally, a hybrid optimization method named LevenbergMarquardt based artificial bee colony (LMABC) algorithm is presented to minimize OOF. Other optimization method such as genetic algorithm (GA), Levenberg-Marquardt (LM), and artificial bee colony (ABC) are also used to compare the performance of EPE. Results shown that LMABC is the most sophisticated method of EPE, which is capable of interpreting the measured data of FPM and MT precisely. This paper helps converting the field-test data into an HLS model, which enable the computation of ESP of wide areas. The numerical analysis of ESP and its applications will be introduced in the second part of this paper.

Published
2016

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