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4th International Conference on Electronic information engineering and Computer Communication, EIECC 2024

作者： Ju, Alei Zheng, Jianming Jilin Institute of Chemical Technology School of Information and Control Engineering Jilin Province Jilin City China

ISBN: (纸本)9798331534622

Ground penetrating radar (GPR) images are often affected by Gaussian noise, which reduces their clarity. While traditional filtering methods can mitigate noise to some extent, they often struggle to preserve image details simultaneously. Deep learning-based Denoising Convolutional Neural Network (DNCNN) has demonstrated notable performance in image denoising, yet its effectiveness in handling Gaussian noise in GPR images leaves room for improvement. This study enhances the DNCNN model by integrating a Bottleneck Attention Module (BAM) module, enabling the network to better identify and focus on both noise and image details, thereby improving denoising performance. Experimental results show that the modified DNCNN model not only surpasses traditional techniques but also outperforms the original DNCNN in GPR image denoising. The improvements in PSNR and SSIM metrics confirm the effectiveness of the proposed approach[3] © 2024 IEEE.

关键词： Convolutional neural networks

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Attentional SoftLexicon for Chinese named entity recognition 3

Attentional SoftLexicon for Chinese named entity recognition

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3rd International Conference on Machine Vision, Automatic Identification, and Detection, MVAID 2024

作者： Liu, Dongsheng Peng, Zhiping He, Jieguang Liang, Zhushen Qiu, Jinbo Cui, Delong School of Information and Control Engineering Jilin Institute of Chemical Technology Jilin132022 China School of Electronic and Information Engineering Guangdong University of Petrochemical Technology Maoming525000 China

ISBN: (纸本)9781510681880

Some effective word embeddings have been proposed by researchers and acted in NER (Named Entity Recognition) tasks, but these embeddings often suffer from under-utilization, resulting in poorly characterized word vectors encoded. Driven by the lack of entity information, I perform lexical enhancement techniques at the input layer of the NER model for Chinese. Roughly speaking, we introduce an attention mechanism to the Softlexicon approach, which makes the embedded entity information more complete. We conducted experiments. On all four Chinese NER datasets, the performance of the improved Softlexicon is improved compared to the original one. In addition to using different datasets, we also embedded the improve d Softlexicon in combi nation with different pre-trained models, and the attention mechanism still led to good performance. © 2024 SPIE.

关键词： Embeddings

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Timeliness optimization of unmanned aerial vehicle lossy communications for internet-of-things

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Chinese Journal of Aeronautics 2023年第6期36卷 249-255页

作者： Wensheng LIN Lixin LI Yun LIU Yixuan HE Ying LIU School of Electronics and Information Northwestern Polytechnical UniversityXi'an 710129China Southwest China Institute of Electronic Technology Chengdu 610036China Xi'an Modern Control Technology Research Institute Xi'an 710065China Shanghai Institute of Satellite Engineering Shanghai 201109China

information freshness is a key factor for Internet-of-Things(IoT)to make appropriate decisions and *** paper proposes an analytical framework for evaluating the timeliness performance of the IoT system based on Unmanned Aerial Vehicle(UAV)lossy *** performance analysis consists of the outage probability analysis and the Age-of-information(AoI)analysis with *** begin with,we solve a lossy coding problem formulated from the UAV communication system,and derive a closed-form expression of the outage probability based on Shannon's lossy source-channel separation ***,we characterize the Peak AoI(PAoI)for the considered system,and further minimize the PAoI by deriving the optimal rate for generating ***,we analyze the system performance through theoretical calculations and *** results indicate that the optimal server utilization ratio is always no larger than *** practical applications,we can utilize the proposed analytical framework to determine the system parameters which guarantee the timeliness performance of UAV lossy communications.

关键词： Age-of-information information freshness Lossy communications Unmanned aerial vehicle Outage probability

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Fuzzing:Progress,Challenges,and Perspectives

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Computers, Materials & Continua 2024年第1期78卷 1-29页

作者： Zhenhua Yu Zhengqi Liu Xuya Cong Xiaobo Li Li Yin Institute of Systems Security and Control College of Computer Science and TechnologyXi'an University of Science and TechnologyXi'an710054China School of Mathematics and Information Science Baoji University of Arts and SciencesBaoji721013China Institute of Systems Engineering Macao University of Science and TechnologyTaipaMacaoChina

As one of the most effective techniques for finding software vulnerabilities,fuzzing has become a hot topic in software *** feeds potentially syntactically or semantically malformed test data to a target program to mine vulnerabilities and crash the *** recent years,considerable efforts have been dedicated by researchers and practitioners towards improving fuzzing,so there aremore and more methods and forms,whichmake it difficult to have a comprehensive understanding of the *** paper conducts a thorough survey of fuzzing,focusing on its general process,classification,common application scenarios,and some state-of-the-art techniques that have been introduced to improve its ***,this paper puts forward key research challenges and proposes possible future research directions that may provide new insights for researchers.

关键词： Fuzzing vulnerability software testing software security

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ViT lightweight training at IoT edge based on transfer learning

ViT lightweight training at IoT edge based on transfer learn...

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2024 International Conference on Optics, Electronics, and Communication engineering, OECE 2024

作者： Li, Zhixin Long, Yang Miao, Jiahao School of Computer Technology and Engineering Changchun Institute of Technology Jilin Changchun130012 China School of Information and Control Engineering Jilin Institute of Chemical Technology Jilin Jilin132022 China

ISBN: (纸本)9781510685437

Recently, the vision transformer (ViT) model of deep learning has achieved surprising performance in the field of computer vision and has been widely used in IoT edge devices. However, the training of ViT models requires a large amount of data and computing resources, which is a challenge for resource-constrained edge IoT devices. To solve the above problems, this paper proposed a lightweight ViT method based on transfer learning. The primary concept of this method is to train large-scale ViT models in the cloud (CloudViT) and deploying small-scale ViT models at the edge (EdgeViT). Firstly, through the method of transfer learning, some underlying parameters of CloudViT were utilized to construct EdgeViT. The purpose is to enable EdgeViT to learn from CloudViT, acquiring knowledge and improving its performance. Secondly, adding a randomly initialized LayerNorm layer before the MLPHead during the training process of EdgeViT, it can improve further model performance. Finally, Experiment results demonstrated that EdgeViT could achieve 91.3% of CloudViT’s performance with only half the parameters and floating-point operations (FLOPs). Moreover, finetuning EdgeViT with a 60% reduction in training time still allows it to achieve 81.3% of CloudViT’s performance. Relevant conclusions can provide technical support for the proposed method. © 2024 SPIE.

关键词： Data modeling Clouds Internet of things Performance modeling Instrument modeling Neural networks Head Visual process modeling Image classification

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Active Magnetic Compensation Based on Parametric Resonance Magnetometer

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Journal of Shanghai Jiaotong university(Science) 2024年第2期29卷 280-289页

作者：郭阳李绍良黄艺明骆曼箬刘华 School of Electronic Information and Electrical Engineering Shanghai Jiao Tong UniversityShanghai 200240China Shanghai Institute of Spacefight Control Technology Shanghai Key Laboratory of Space Intelligent Control TechnologyShanghai Engineer Research Center of InertiaShanghai 201109China

Based on the parametric resonance magnetometer(PRM)theory,this paper establishes an experimen-tal system of *** experimental results are consistent with the theoretical predictions.A PRM has been developed with sensitivity of 0.5 pT/Hz^(1/2),which can detect the magnitude of residual magnetic field;furthermore,a proportion-integration-differentiation(PID)closed-loop magnetic compensation system of the residual magnetic field also has been *** with open-loop compensation,the PID closed-loop compensation reduces the average value of the residual magnetic field in the z-axis direction from 0.0244nT to-0.0023nT,and the mean-square error from 0.2083 nT to 0.0691 *** the same way,the average value of the residual magnetic field in the y-axis direction is reduced from 0.0816nT to-0.0042nT,and the mean-square error from 0.1316nT to 0.0461 *** magnitude of residual magnetic fields in both directions is decreased to the order of picotesla(pT).In addition,based on the signal waveforms of the magnetometer,a method of verifying the effect of magnetic compensation is proposed.

关键词： magnetometer parametric resonance nuclear magnetic resonance gyroscope magnetic compensa-tion proportion-integration-differentiation(PID)

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A Finite-time Distributed Cooperative control Approach for Microgrids

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CSEE Journal of Power and Energy Systems 2022年第4期8卷 1194-1206页

作者： Jiancheng Zhang Xinsheng Wang Lingyu Ma Department of Control Science and Engineering Harbin Institute of TechnologyHarbin 150006China Department of Information Engineering Shandong Management UniversityJinan 250100China

Reactive power sharing cannot be achieved using many existing microgrid(MG)control methods,but the convergence speed of these methods is *** solve these problems,a finite-time distributed control approach is proposed in this paper,which is based on the hierarchical control *** hierarchical control structure consists of a dual loop control,a droop control used as a primary control and a secondary ***,the secondary controller is modeled,and the MG system composed of distributed generators(DGs)is considered as a multi-agent *** secondary controller consists of a frequency regulator,voltage regulator and power ***,the adaptive virtual impedance module is established,using the output of the reactive power regulator as its ***,a dual loop controller is combined with a primary controller and secondary controller to generate a pulse width modulation(PWM)signal to control the power and voltage of the *** order to reduce the fluctuation of the MG,a damping module is introduced when the structure of the system ***,the stability of the proposed control strategy is proved by the related theorems.A simulation system is established in the Matlab environment,and the simulation results show that the proposed method is effective.

关键词： Consensus droop control finite-time microgrid power sharing virtual impedance

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Research on tree barrier measurement method based on monocular image depth estimation 3

Research on tree barrier measurement method based on monocul...

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3rd International Conference on Signal Image Processing and Communication, ICSIPC 2023

作者： Mu, Xiaofei Liu, Hongxi Fang, Jun School of Information and Control Engineering Jilin Institute of Chemical Technology Jilin China School of Electrical and Information Engineering Changchun Institute of Engineering Changchun China

ISBN: (纸本)9781510670945

Tree barrier plays a vital role in transmission lines, and its existence directly affects the stable supply of electricity. Therefore, it is necessary to measure and inspect the tree barrier. For this purpose, this paper proposes a measurement method based on monocular image depth estimation. In this method, the LSD (Line Segment Detector) algorithm is used to detect the straight line, and the RANSAC (RANdom SAmple Consensus) algorithm is used to iteratively detect the vanishing point, and the vanishing point coordinates are successfully obtained. The camera calibration is carried out to determine the pixel coordinates of the object in the image and to obtain the internal and external parameters and rotation matrix of the camera. Through coordinate system transformation, the depth estimation of the target in the world coordinate system and the distance between any tree lines can be accurately calculated. Finally, the height of the camera is used as the reference height to complete the measurement of the tree barrier around the wire, and the experimental results show that the method has certain feasibility and the error is controlled within a reasonable range. © 2023 SPIE.

关键词： Electric lines

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Drug-Target Interactions Prediction Based on Signed Heterogeneous Graph Neural Networks

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Chinese Journal of Electronics 2024年第1期33卷 231-244页

作者： Ming CHEN Yajian JIANG Xiujuan LEI Yi PAN Chunyan JI Wei JIANG College of Information Science and Engineering Hunan Normal University School of Computer Science Shaanxi Normal University Faculty of Computer Science and Control Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of Sciences Computer Science Department BNU-HKBU United International College

Drug-target interactions(DTIs) prediction plays an important role in the process of drug *** computational methods treat it as a binary prediction problem, determining whether there are connections between drugs and targets while ignoring relational types information. Considering the positive or negative effects of DTIs will facilitate the study on comprehensive mechanisms of multiple drugs on a common target, in this work, we model DTIs on signed heterogeneous networks, through categorizing interaction patterns of DTIs and additionally extracting interactions within drug pairs and target protein pairs. We propose signed heterogeneous graph neural networks(SHGNNs), further put forward an end-to-end framework for signed DTIs prediction, called SHGNN-DTI,which not only adapts to signed bipartite networks, but also could naturally incorporate auxiliary information from drug-drug interactions(DDIs) and protein-protein interactions(PPIs). For the framework, we solve the message passing and aggregation problem on signed DTI networks, and consider different training modes on the whole networks consisting of DTIs, DDIs and PPIs. Experiments are conducted on two datasets extracted from Drug Bank and related databases, under different settings of initial inputs, embedding dimensions and training modes. The prediction results show excellent performance in terms of metric indicators, and the feasibility is further verified by the case study with two drugs on breast cancer.

关键词： Drug-target interactions Signed heterogeneous network Link sign prediction Graph neural networks

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Chinese Address Named Entity Recognition Based on BERT-BiLSTM-ATT-CRF Model 43

Chinese Address Named Entity Recognition Based on BERT-BiLST...

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43rd Chinese control Conference, CCC 2024

作者： Chang, Yunshui Zhang, Zhengteng Du, Yaxun Jilin Institute of Chemical Technology College of Information and Control Engineering Jilin132022 China Beihua University College of Electrical and Information Engineering Jilin132013 China

ISBN: (纸本)9789887581581

With the rapid development of the Internet, Chinese addresses are widely present online. However, their complexity and diversity make traditional methods challenging for accurate identification. To address this issue, this paper proposes a Chinese address named entity recognition method based on the BERT-BiLSTM-ATT-CRF model. This model combines BERT's contextual understanding, BiLSTM's sequence modeling, Attention's emphasis focus, and CRF's sequence labeling capabilities, enabling more accurate identification of address entities from Chinese text. Experimental results demonstrate significant progress of the model in Chinese address named entity recognition tasks, improving accuracy, recall, and F1 score for address information identification. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： BERT BiLSTM Chinese address Named Entity Recognition

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