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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Sun, Lei Ju, Dongjie Ke, Shi School of Electrical Engineering and Automation Binshui Xidao Extension 391 Tianjin300384 China Tianjin University of Technology Tianjin Key Laboratory for Control Theory and Complicated Industry Systems Binshui Xidao Extension 391 Tianjin300384 China

ISBN: (纸本)9798350320831

Image colorization has always been a hot topic in computer vision. Since the emergence of deep learning and its excellent performance in many image-processing tasks, image colorization methods based on convolutional neural networks (CNN) emerge in an endless stream, including automatic colorization methods and A coloring method based on a reference image. In the coloring method based on the reference image, an existing problem is that an algorithm for calculating the similarity between the grayscale image and the reference image needs to be designed to map the color blocks in the reference image to the grayscale image. And we use the attention mechanism to spread color implicitly, and propose an attention-guided image colorization network, which extracts features and corresponding color information from the reference image through a reference encoding sub-network, and simultaneously passes a target encoding sub-network The network extracts grayscale features from grayscale images, uses attention to calculate the correlation between the two types of features, and then restores the features and reconstructs colors through the decoding network. Our method can quickly capture the color of the reference feature, accurately transfer it to the target feature, and effectively solve the problem of small target loss during downsampling. By validating on multiple datasets, the results show that our method is effective, outperforming multiple state-of-the-art image colorization algorithms. © 2023 IEEE.

关键词： Color

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Named Entity Recognition in Chinese Medical Texts Based on RoBERTa-WWM-IDCNN-CRF

Named Entity Recognition in Chinese Medical Texts Based on R...

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System Simulation Technology and its Application (CCSSTA), IEEE China Conference on

作者： Lan Tang Jie Kong Liang Xu School of Computer Xi‘an Shiyou University Xi‘an China Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems and School of Electrical Engineering and Automation Tianjin University of Technology Tianjin China

ISBN: (数字)9798350366600

ISBN: (纸本)9798350366617

Electronic medical records and doctor-patient conversations contain a wealth of useful information, such as disease symptoms, drug names, and cure cycles. Traditional deep learning approaches utilize bidirectional recurrent neural networks to encode text, which cannot effectively capture long-distance dependencies in text. In order to identify medical entity types in various texts more accurately, a named entity recognition approach based on RoBERTa-WWM-IDCNN-CRF is proposed. This approach introduces the RoBERTa-WWM pre-trained model, in order to improve the overall understanding of long Chinese texts for the first time. The model generates semantic representations containing prior knowledge. Then, the generated semantic representations are feed to the IDCNN to extract sentence level characteristics. Finally, the global optimal solution is obtained and the results of the named entity are produced through the CRF. The experiment indicates that the improvement of $F_{1}$ score, accuracy, and recall of RoBERTa-WWM-IDCNN-CRF model are 7.94%, 4.52% and 10.02% comparing with the classical BiLSTM-CRF model.

关键词： Drugs Recurrent neural networks Semantics Named entity recognition Oral communication Medical services systems simulation Feeds Electronic medical records Diseases

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Simultaneous displacement measurement method of multiple targets based on laser self-mixing interference

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Optoelectronics Letters 2021年第3期17卷 165-169页

作者： ZHAO Yan ZHANG Ai-ling ZHANG Hai-wei School of Electrical and Electronic Engineering Tianjin University of TechnologyTianjin 300384China Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems Tianjin 300384China Tianjin Key Laboratory of Film Electronic and Communication Device Tianjin 300384China

In order to simultaneously measure the displacements of multiple targets, the laser self-mixing interference(SMI) measurement method based on variational mode decomposition(VMD) is proposed. The SMI signal containing the motion information of the external targets is detected by a photodiode. The VMD can non-recursively decompose the mixed SMI signal into SMI signals corresponding to different external targets. The displacement signals can be reconstructed by fringe counting method and interpolation method. The experimental results show that the displacement signals of different external targets can be reconstructed with half wavelength accuracy, which verifies the correctness and feasibility of this method. This method can improve the measurement efficiency, which offers an effective method for the multi-channel displacement measurement.

关键词： measurement. displacement mixing

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Linear active disturbance rejection control of phase-shifted full-bridge converter based on improved particle swarm optimization algorithm

Linear active disturbance rejection control of phase-shifted...

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IEEE International Conference on Mechatronics and Automation

作者： HongSen Wang YanJuan Wu Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems Tianjin Key Laboratory of New Energy Power Conversion Transmission and Intelligent Control Tianjin University of Technology Binshui Xidao 391 Tianjin China

In order to improve the dynamic performance and disturbance suppression ability of conventional PID control phase shift full-bridge converter, LADRC based on improved particle swarm optimization is proposed. The voltage loop transfer function of phase-shifted full-bridge converter is derived based on the state space average method. Secondly, LESO and LSEF are designed to estimate and compensate the external disturbance and internal uncertainty in real time. Finally, the advantages of linear active disturbance rejection controller are verified by simulation experiments. The experimental results show that the controller has better disturbance suppression performance and dynamic performance than the traditional PID controller.

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Image Enhancement Method for Arc Welding Process Monitoring in the Present of Strong Arc Light Interference 7th

Image Enhancement Method for Arc Welding Process Monitoring ...

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7th International Conference on Nanomanufacturing, nanoMan2021

作者： He, Xinxin Liu, Bin Yang, Fan Wang, Zhongya Wen, Yaxin Zhang, Baofeng School of Electrical and Electronic Engineering Tianjin University of Technology Tianjin China Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems Tianjin China Co. Ltd. Tianjin China University of Technology Tianjin China

ISBN: (纸本)9789811919176

The application of vision technology plays a significant role in the development of intelligent automatic welding. However, the welding process would produce strong arc light. The arc light seriously reduces the imaging quality of the vision system. In this case, the function of vision auxiliary would fail. The operation of a suitable image enhancement algorithm is capable of solving the problems caused by the strong arc light, such as nonuniform brightness, the loss of edges and low signal-to-noise. In this paper, image enhancement algorithm was studied to solve the imaging interference caused by the strong arc light. According to the characteristic of captured image, the advantage of LIME algorithm was analyzed. Then suitable filtering method was introduced into LIME to improve the enhancement. Experimental results showed that the algorithm could balance the global brightness and suppress the intensity of the strong light area. Furthermore, the original object contour details could be restored to optimize the visual effect. By investigating the effect of various low-light image enhancement algorithms from both subjective and objective aspects, the combined algorithm was proved to be effective. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Image enhancement

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Research on conducted emi characteristics of sic mosfet considering temperature effect

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Progress In Electromagnetics Research C 2021年 112卷 69-82页

作者： Du, Mingxing Bian, Weiguo Wang, Hongbin Dai, Qiqi Ouyang, Ziwei Tianjin Key Laboratory of Control Theory & Applications in Complicated System Tianjin University of Technology Tianjin300384 China State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin300130 China

—The junction temperature change of SiC MOSFET will change its switching process, and then affect the electromagnetic interference (EMI) characteristics of the system where the device is located and the safe operation of the surrounding equipment. Therefore, it is of great significance to research the temperature dependence of its EMI characteristics. In this paper, a buck converter composed of SiC MOSFET is taken as the research object to study the temperature variation characteristics of the conducted EMI spectrum during the switching process. Combined with the specific circuit connection form of the buck converter, the coupling paths of the conducted EMI are determined, and then the influence mechanisms of temperature change on the differential mode (DM) interference and common mode (CM) interference are analyzed. The theoretical analysis and experimental results show that the DM interference of the buck converter composed of SiC MOSFET increases with the increase of temperature, and the CM interference is almost unaffected by temperature. When the working temperature increases from 25◦C to 145◦C, the peak value of DM voltage increases by 6.7 dBµV, and the peak value of CM voltage changes less than 1.4 dBµV. © 2021, Electromagnetics Academy. All rights reserved.

关键词： Temperature distribution

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Real-time scheduling strategy for electric vehicles based on sliding window transmission optimization

Real-time scheduling strategy for electric vehicles based on...

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IEEE International Conference on Mechatronics and Automation

作者： Peizhi Cong Yanjuan Wu Caiwei Wang Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems Tianjin Key Laboratory of New Energy Power Conversion Transmission and Intelligent Control Tianjin University of Technology Binshui Xidao 391 Tianjin China

In order to reduce the impact of electric vehicle(EV) charging load on the power grid, a real-time optimal scheduling scheme for charging and discharging Evs is proposed. Firstly, the objective is to reduce charging costs and network loss costs, aiming to minimize the total cost of EVs at the current time. An EV dispatching model is established, the grid node acceptance capacity performance is analyzed by constructing a network loss sensitivity index, and the EV charging and discharging strategy is obtained in real time based on the time-of-use tariff of the grid load by means of a tide calculation and a sliding window variable speed optimization algorithm as well as a second-order convex optimization calculation method. Finally, the proposed strategy is verified to be effective in reducing the charging cost and network loss cost, and has good real-time flexible dispatching performance, using an improved IEEE 39-node distribution network as an example.

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Based on Hybrid Densenet-121 with Support Vector Machine Algorithm for Lettuce and Chili

Based on Hybrid Densenet-121 with Support Vector Machine Alg...

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IEEE International Conference on Mechatronics and Automation

作者： Yuzhe He Yanjuan Wu Caiwei Wang Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems Tianjin Key Laboratory of New Energy Power Conversion Transmission and Intelligent Control Tianjin University of Technology Binshui Xidao 391 Tianjin China

In this paper, to improve the recognition accuracy of Densenet-121, we combine Densenet-121 with SVM to generate a new network Densenet-121-SVM. In this paper, the two datasets are combined to generate a new dataset named Mixed-dataset, which has four plants, namely: Lettuce, Chili, Chinee apple, and Lantana, and this dataset is used to train the network. Finally, the recognition accuracies of SVM, Densenet121 and Densenet-121-SVM are 84.144%, 96.211% and 98.181%, respectively, and it can be seen that the accuracy of Densenet-121-SVM is improved by 14% and 1.97% compared to SVM and Densenet-121, respectively.

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DH Detector: One-stage detection model with double-head detector and efficient convolution

DH Detector: One-stage detection model with double-head dete...

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IEEE International Conference on Mechatronics and Automation

作者： Ziyuan Feng Lei Sun School of Electrical Engineering and Automation Tianjin Key Laboratory for Control Theory and Complicated Industry Systems Tianjin University of Technology Tianjin China

ISBN: (数字)9798350388077

ISBN: (纸本)9798350388084

This article explores advanced techniques to build a network model, including the use of a double-head(DH) detector: one section of which is responsible for performing classification and the other for object prediction. This is followed by information stitching, which allows the model to learn more appropriate parameters. Subsequently, a CSP structure incorporating an attention mechanism is used to improve the feature extraction capabilities of the model. Finally, dynamic convolution is added to enhance the feature representation. Our model is trained from scratch on the COCO Dataset without taking a pre-trained model, the results of which are listed below. Based on 300 epochs of training, the mAP values for the four versions of DH Detector (s, m, l, x, the network model becomes larger in turn) are 40.8, 46.1, 48, and 49.8(100 epoch), respectively. The experiment results show that this method outperforms other competing methods in terms of both quantity and quality. In addition, the mAP of DH-s and DH-l reached 43.0 and 50.1 at an input image size of 960. A comparison of DH Detector with other algorithms is provided in Figure 1.

关键词： YOLO Training Solid modeling Attention mechanisms Convolution Computational modeling Detectors

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Uncertainty Treatment of Integrated Energy System Based on Scenario Reduction Method

Uncertainty Treatment of Integrated Energy System Based on S...

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IEEE International Conference on Mechatronics and Automation

作者： Caiwei Wang Yanjuan Wu Peizhi Cong Yuzhe He Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems Tianjin Key Laboratory of New Energy Power Conversion Transmission and Intelligent Control Tianjin University of Technology Binshui Xidao 391 Tianjin China

In the context of high permeability of renewable energy, a large number of uncertain energy sources, such as scenery, have brought a huge impact on the security and stability of the comprehensive energy system. In order to reduce the impact of renewable energy on the new power system and improve the system stability, In this paper, a comprehensive energy system of the park is set up, which consists of three kinds of energy loads including source side electricity, heat, gas and scenery, and electric heat. On this basis, Monte Carlo method is adopted to simulate multiple sets of scenes respectively for the scenery output. On this basis, scene reduction method is adopted to reduce them to obtain the final equivalent force diagram, so as to reduce the influence of the uncertainty of scenery on the system stability. Finally, the effectiveness of the proposed method is verified by simulation analysis.

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