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A BERT-Based Named Entity Recognition Method of Warm Disease in Traditional Chinese Medicine 18

A BERT-Based Named Entity Recognition Method of Warm Disease...

引用

18th ieee conference on Industrial Electronics and applications, ICIEA 2023

作者： Song, Zijun Xu, Wen Liu, Zhitao Chen, Liang Su, Hongye Polytechnic Institute Zhejiang University Hangzhou China Binzhou Medical University Yantai China Institute of Cyber-Systems and Control Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou China

ISBN: (纸本)9798350312201

Traditional Chinese medicine (TCM) documents have been handed down through the ages, containing rich theoretical knowledge and clinical experience. These unstructured data are the foundation for building the digital knowledge system of TCM. However, written in ancient Chinese, the TCM books have complex grammatical rules and terms which are different from modern medicine, inducing difficulty in entity annotation and recognition. In order to solve the problem of lacking labeled data, we construct a dataset with Wenbing Tiaobian, a classic work of TCM on the warm disease, identify six entities and annotate the book with the BIOES method. The BERT-BILSTM-CRF model is used to conduct experiments on the dataset with an F1 value of 91.4%. The results verify the effectiveness of the model in NER tasks and advance the construction of knowledge graphs in TCM. © 2023 ieee.

关键词： Deep learning

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An SGX and Blockchain-Based System for Federated Learning in Classifying COVID-19 Images 21

An SGX and Blockchain-Based System for Federated Learning in...

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21st ieee International Symposium on Parallel and Distributed Processing with applications, 13th ieee International conference on Big Data and Cloud Computing, 16th ieee International conference on Social Computing and Networking and 13th International conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Qin, Sihang Gu, Xianjun Jun, Xing Li, Haitao Huang, Mengqi Dai, Weiqi Huazhong University of Science and Technology Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Wuhan430074 China State Grid Wuhan Power Supply Company China

ISBN: (纸本)9798350329223

Federated learning, an emerging distributed learning framework, has gained prominence recently. However, two challenges arise when applying federated learning to medical data. The first challenge stems from the inability of model-generating nodes to ensure computational fairness. The second challenge involves the potential leakage of private information through gradient differences. This paper introduces a federated learning system that leverages Software Guard Extensions (SGX) and blockchain technology to enhance the fairness and security of federated learning for analyzing chest imaging data. The modeling of imaging factors for chest radiography data can effectively regulate the data quality of semi-trusted nodes. A blockchain smart contract is employed for data quality-aware proof, and the quality-aware block undergoes a two-stage rewriting process across distinct nodes. A notary membership model achieves notarized cluster consensus for imaging informatics data. The multi-channel layer model quantifies the distribution of computational workload across participating nodes within the medical consortium. Upon successful verification of the enclave command in the aggregation cycle, traceable and packaged signatures are generated to support computational fairness. To ensure robust information security, SGX remote authentication is used between downstream and upstream nodes. The federated learning system, built upon SGX and blockchain, has been implemented using the Fabric federated chain platform. The ResNet model underwent training through cross-sectional federated learning to effectively classify novel coronavirus lung medical image data. Following this, multiple experimental control and security analyses were conducted, revealing that the time loss incurred due to crossing channels is approximately 21.31%, while the time overhead of SGX remains within 5.2%, as allowed by the number of nodes. © 2023 ieee.

关键词： Blockchain

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Thickness Measurement of Brake Pads Based on Keypoint and Object Detection

Thickness Measurement of Brake Pads Based on Keypoint and Ob...

引用

2023 ieee International conference on Unmanned Systems, ICUS 2023

作者： Chang, Yujia Li, Ran Ma, Dengxin Ma, Xiangyu Song, Dalei School of Automation and Electrical Engineering Shenyang Ligong University Shenyang China EAVision Co . Limited Smart Business Division Suzhou China School of Information Science and Engineering Shenyang Ligong University Shenyang China School of Information Science and Enginnering Shenyang University of Technology Shenyang China

ISBN: (纸本)9798350316308

The wear condition of the brake pad, as one of the core components of high-speed trains, needs to be detected and identified based on its thickness. However, existing measurement methods primarily rely on direct detection of the edges of brake pads, which is sensitive to lighting and contrast conditions. As a result, the accuracy of the algorithm for applications is limited. In this paper, we propose a brake pad thickness measurement method based on keypoint and object detection. We apply YOLOV5 for brake pad localization and adopt the HRNet network for keypoint detection in order to calculate thickness. The positions of keypoints are adjusted based on detected edge features. Precise distance is achieved by utilizing depth infor-mation and world coordinates of keypoints to obtain the actual thickness of the brake pad. Experimental results demonstrate that compared with the original method, our proposed algorithm achieves an average error rate of 0.53mm, which is accurate enough for real-world applications using our self-made dataset in realistic environments. © 2023 ieee.

关键词： Thickness measurement

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Switched Capacitor-Boost PFC Converter Fed Sensorless BLDC Motor Drive For Air Conditioner 3

Switched Capacitor-Boost PFC Converter Fed Sensorless BLDC M...

引用

3rd ieee International conference on Smart Technologies for Power, Energy and control, STPEC 2023

作者： Ranjit, Sorra Arya, Avinash Saha, Biswajit Kumar, Sumit Singh, Bhim Indian Institute of Technology Delhi Department of Electrical Engineering Hauz Khas New Delhi110016 India

ISBN: (纸本)9798350304732

The incorporation of power factor correction (PFC) is a crucial element in the design of home appliances. Power Factor Correction (PFC) is a technique employed to enhance the efficiency of power utilization from the grid to the appliance. This is achieved by reducing the harmonic content of reactive power and improving the power factor. PFC rectifiers featuring current inputs have gained popularity due to their boost topology. Nonetheless, two-stage topologies exhibit reduced output voltages, increased component count, and substantial losses. In this study, a PFC boost rectifier incorporating a hybrid switched capacitor is employed to ensure power quality at the forefront of the brushless DC motor (BLDCM) based air conditioner (AC) compressor drive. The BLDCM is powered by the grid to the DC link via PFC frontend converter, enabling an uninterrupted power supply to the motor. The front-end converter is functioning at continuous conduction mode (CCM) while ensuring a power factor of unity at the AC mains grid side. The speed of a BLDC motor is controlled through the DC link voltage regulation. The estimation of the rotor position is achieved through the utilization of the motor's terminal voltages. A fully functional power factor corrected BLDC motor drive without the use of position sensors is developed specifically for AC compressor drive applications. The system under consideration is subjected to simulation and thorough analysis. © 2023 ieee.

关键词： air-conditioner BLDC motor drive home appliances power factor correction sensorless drive

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Remaining Useful Life Prediction Based On Causal Inference and Deep Learning 14

Remaining Useful Life Prediction Based On Causal Inference a...

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14th International conference on Reliability, Maintainability and Safety, ICRMS 2023

作者： Wang, Jiayi Li, Yiming Xu, Jia Li, Li Yu, Qingyun Zhao, Hui Gong, Wei Department of Control Science & Engineering Tongji University Shanghai201804 China

ISBN: (纸本)9798350329988

To address the challenge associated with high feature dimensionality in remaining useful life (RUL) prediction, this paper proposes a prediction method based on causal inference and deep learning. First, the causal relationships among the data are determined using a causal discovery algorithm named Peter-Clark momentary conditional independence. Subsequently, feature dimensionality is reduced based on these relationships. The RUL is predicted based on the reduced-dimensional data combined with deep learning techniques, such as convolutional neural networks and gated recurrent units. In addition, the C-MAPSS dataset is used for experimental validation. The results demonstrated that the proposed method exhibits excellent prediction accuracy while affording interpretability, thereby providing reliable guidance for engineering applications. © 2023 ieee.

关键词： Prediction models

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DC-DC converter with reduced voltage stress for electric vehicle low voltage application 2

DC-DC converter with reduced voltage stress for electric veh...

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2nd International conference on Advancements in Electrical, Electronics, Communication, Computing and Automation, ICAECA 2023

作者： Maithili, P. Kavitha, R. Shanthi, T. Dhurga, Sri S Jayanthish, M.J. Balaji, R. Kumaraguru College of Technology Electrical and Electronics Engineering Coimbatore India

ISBN: (纸本)9798350306811

The study presents a closed loop DC-DC converter for hybrid E-vehicle based on the Zeta converter architecture. It standardizes the voltages to connect to the traction applications. This converter has merits such as the properties of both buck and boost converters, simple design, high voltage gain, low ripple, better feedback control and increased efficiency compared to that of the conventional converters in existence. A PID controller has been implemented into the Arduino Uno microcontroller board that provides closed loop control. The hardware has been tested, and results are provided. © 2023 ieee.

关键词： Three term control systems

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A Comprehensive Study of AI-Powered Writing Assistance Tools and Content Spinning applications 7

A Comprehensive Study of AI-Powered Writing Assistance Tools...

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7th International conference on Electronics, Communication and Aerospace technology, ICECA 2023

作者： Tamilselvi, C. Dhanasakkaravarthi, B. Devi, R. Ebenezer, A.Shamila Dhanwanth, Batini Mohanaprakash, T.A. Dr. MGR Educational and Research Institute Department of IT Chennai India Agni College of Technology Department of Mechanical Engineering Chennai India Sree Sastha Institute of Engineering and Technology Department of CSE Chennai India Karunya Institute of Technology and Sciences Department of CSE Coimbatore India Panimalar Institute of Technology Department of CSE Tamil Nadu Chennai India Panimalar Engineeering College Department of CSE Chennai India

ISBN: (纸本)9798350340600

This study delves into an in-depth examination of AI-powered writing assistance tools, including Quillbot, Grammarly, and Wordtune, alongside an exploration of content spinning applications, encompassing WordAi, Spin Rewriter, Chimp Rewriter, Rephrase, and SpinBot. By scrutinizing their features, functionalities, advantages, disadvantages, and overall utility, this study offers an extensive analysis of how these tools contribute to improving writing quality and efficiency. Furthermore, a comparative evaluation sheds light on their distinct attributes and target user base. Throughout this study, the evolving landscape of writing enhancement and content creation tools is considered, keeping in mind the potential updates or changes that may have occurred beyond the scope of this analysis. This research serves as a valuable resource for individuals seeking to optimize their writing process and generate engaging, polished content. © 2023 ieee.

关键词： Quality control

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Center of Excellence for control and Automation in the Context of ASEAN Factori 4.0 Project 8

Center of Excellence for Control and Automation in the Conte...

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Joint 8th International conference on Digital Arts, Media and technology and 6th ECTI Northern Section conference on Electrical, Electronics, Computer and Telecommunications Engineering, ECTI DAMT and NCON 2023

作者： Thourn, Kosorl Kim, Bunthern Eng, Samphors Vai, Vannak Chou, Koksal Thiriet, Jean-Marc Lubineau, Denis Yahoui, Hamed Institute of Technology of Cambodia Dept. Telecom. and Network Eng. Phnom Penh Cambodia Institute of Technology of Cambodia Dept. Elec. and Energy Eng. Phnom Penh Cambodia Univ. Grenoble Alpes Gipsa-Lab Grenoble France Univ. Claude Bernard Lyon 1 Dépt Mécanique Lyon France

ISBN: (纸本)9798350396546

The innovative learning laboratory based on an industrial Programmable Logic controller (PLC) is very important allowing students to perform practices under actual industrial conditions. In the ASEAN Factori 4.0 Erasmu+ project, each Asian partner university will have its own center of excellence with the PLC platform for industrial automation applications developed by the EU partner universities. This paper presents the elements of the center of excellence in conjunction with the existing pedagogical platforms in the department of Electrical and Energy Engineering at the Institute of technology of Cambodia. © 2023 ieee.

关键词： Programmable logic controllers

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Analysis of Electrical Energy Consumption Efficiency Trends Using Visualization Tools 8

Analysis of Electrical Energy Consumption Efficiency Trends ...

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8th International conference on Power Energy Systems and applications, ICoPESA 2024

作者： Ratsame, Priyaporn Chansri, Pakpoom King Mongkut's University of Technology Thonburi Division of Electrical Technology Education Faculty of Industrial Education and Technology Bangkok Thailand

ISBN: (纸本)9798350351668

Industrial factories tend to use more power. Resulting studying the application of energy efficiency, leading to energy conservation. Through the analysis of the cumulative sum of energy differences Cumulative Sum control Chart (CUSUM), it is possible to know the trends in energy use of industrial plants. Energy analysis using Visualization Tools for data analysis A case study of a pineapple processing factory To find the efficiency of energy use. The advantage is that you can identify correlations between operations and results faster, and can provide real-time system information for users to make decisions. Therefore, in the research, Analysis of Electrical Energy Consumption Efficiency Trends using Visualisation Tools, using the Power BI program to display the results on the dashboard page on Power BI, which can display the results of energy consumption in real time and can analyze complex data. Using Power BI displays the Dashboard page. It was found that in Phase 1, during weeks 1-54, there were no energy conservation measures, with a value of Productive Dependent Energy Consumption (PEC), equal to 18.32 kWh Unproductive Energy Consumption (UEC), equal to 308.14 kWh. And in Phase 2, during weeks 54-108, measures were set. Energy conservation has a PEC value of 9.27 kWh and a UEC value of 117.75 kWh, resulting in a PEC reduction of 49.40%. By following these steps and leveraging Power BI's capabilities, you can gain valuable insights into your electrical energy use, forecast future trends, and identify areas for significant efficiency improvements. © 2024 ieee.

关键词： CUSUM Electrical Energy Consumption Power BI Visualization Tools

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Enhanced Speed control of Aviation PMSM Drives by a Proportional Resonant-Based ADRC With Adaptive Frequency Identification 49

Enhanced Speed Control of Aviation PMSM Drives by a Proporti...

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49th Annual conference of the ieee Industrial Electronics Society, IECON 2023

作者： Li, Jincheng Chen, Peiyang Zhao, Xiaopeng Zhang, Mengbo Luo, Guangzhao Chen, Zhe School of Automation Northwestern Polytechnical University Xi'an China Xi'an Flight Automatic Control Research Institute Avic Xi'an China

ISBN: (纸本)9798350331820

The accurate speed control is significant for PMSM in aircraft flap-slat elctromechanical actuator, which serves as the key motion unit of aircraft high-lift system. However, the speed controller suffers from internal and external periodical disturbances due to current sampling and scaling errors and aerodynamic load. The periodical disturbance estimation in extended state observer is done by a proportional resonant scheme to enhance the disturbance rejection ability of speed control loop [1]. This paper proposes an adaptive sinusoidal frequency observer(ASFO)to expand the applicability of proportional resonant-based active disturbance rejection control(PRADRC) technique to applications where periodic and aperiodic disturbances exist. The resonant frequency is adaptively estimated through the ASFO whose input is the speed tracking error. The performance analysis of proposed method is proved theoretically and then validated by experiments. © 2023 ieee.

关键词： Electromechanical actuators

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