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2023 2nd International Conference on Mechanical, Aerospace Technology and Materials Application, MATMA 2023

作者： Zhang, Tianzhi Bing, Zhigang Chen, Biao Xu, Yu Ming, Rui School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin Key Laboratory of Information Sensing & Intelligent Control Tianjin GongJiang Double Carbon Research Institute Tianjin300384 China

When it comes to the virtual machine tool assembly process, there are problems such as assembly errors. Based on the general idea of correct assembly, it is proposed to innovate the assembly process by utilizing the enclosing box and separating axis theorem and GJK algorithm, so as to monitor the state of the detection process, which verifies the effective feasibility of the monitoring method and provides a new idea for the assembly process of virtual CNC machine tools. © Published under licence by IOP Publishing Ltd.

关键词： Assembly

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Privacy protection oriented on data stream computing

Privacy protection oriented on data stream computing

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2022 International Conference on Computer Application and information Security, ICCAIS 2022

作者： He, Renjie Zheng, Xianghan Wang, Gong School of Computer and Big Data Fuzhou University Fujian Fuzhou China The Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fujian Fuzhou China

ISBN: (纸本)9781510663459

Data security has always been one of the public concerns, and homomorphic encryption technology, as one of the effective means to ensure data security, has always been a hot topic of academic research. Traditional machine learning is trained in a batch environment. In practice, data owners tend to outsource data and model training tasks to third-party clouds with huge computing resources, but data outsourcing carries the risk of privacy leakage. Therefore, in order to prevent this situation, an effective method is to encrypt the data before the outsourcing, and the third-party cloud trains the machine model of the ciphertext data. This method has special requirements for encryption algorithms which should support computation directly on the ciphertext data. This paper presents a novel data flow computing privacy protection framework based on the homomorphic encryption algorithm CKKS and the flow data processing engine Flink, called SDPPF (Streaming Data Privacy Protection on Flink). The proposed framework supports the functions of data stream encryption, decryption and ciphertext computing, and expands the functions of vector point multiplication and array sum operation on the basic simultaneous operation supported by the original CKKS algorithm. This paper also selects a classical machine learning algorithm: KNN algorithm, combined with the homomorphic encryption algorithm CKKS to realize the privacy protection machine learning algorithm. © 2023 SPIE.

关键词： Cryptography

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Emotion Classification and Recognition based on facial EMG 2022

Emotion Classification and Recognition based on facial EMG

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7th International Conference on Multimedia and Image processing, ICMIP 2022

作者： Zhang, Zhiwen Zhao, Li He, Xinglin Meng, Tongning Key Laboratory of Information Sensing and Intelligent Control Tianjin University of Technology and Education Tianjin300222 China

ISBN: (纸本)9781450387408

Study emotion classification recognition individual difference is big, dispersion characteristics of rule, the problem of insufficient accuracy, based on the physiological signal acquisition device collected 12 subjects zygomatic muscle and brow muscle two channels of electromyography data, from the time domain feature extraction, using support vector machine (SVM) and the method of extreme learning machine(ELM) to classify positive, negative and neutral moods,Compare the classification accuracy and find out the algorithm with higher classification accuracy. The results showed that the zygomatic muscle activity increased significantly and the frowning muscle activity decreased significantly in positive emotions, while the frowning muscle activity increased significantly and the zygomatic muscle activity decreased in negative *** with the 50% average classification accuracy of support vector machine classifier, the average classification efficiency of extreme learning machine classifier is better, and the average classification accuracy can reach 60.08%.In practical applications, the extreme learning machine has a better classification effect and provides a certain technical foundation for modern human-computer interaction. © 2022 Association for Computing Machinery. All rights reserved.

关键词： Support vector machines

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Prediction of Heat Load of Thermal Station Based on Neural Network 24

Prediction of Heat Load of Thermal Station Based on Neural N...

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6th International Conference on control and Computer Vision, ICCCV 2024

作者： Zhu, Xinying Geng, Liqing Yang, Genghuang Huo, Yang Xu, Shiyuan Tianjin Key Laboratory of Information Sensing & Intelligent Control Tianjin University of Technology and Education School of Automation and Electrical Engineering Tianjin University of Technology and Education China Co. Ltd China

ISBN: (纸本)9798400718045

To solve the problem of improving the prediction accuracy of thermal station, multi-strategy fusion Sparrow Search Algorithm to optimize the Neural Network prediction method. First, the acquired data is preprocessed to ensure the continuity of the data;second, the Pearson Correlation Coefficient method is used to determine the input feature variables and construct the data set through the data;and finally, Sparrow Search Algorithm and multi-strategy fusion Sparrow Search Algorithm respectively optimizes Back Propagation Neural Network and Long Short-Term Memory Neural Network models for heat supply prediction. After example verification and comparison, the multi-strategy fusion Sparrow Search Algorithm optimizes the Back Propagation Neural Network model with the minimum prediction error, which effectively improves the prediction accuracy. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Prediction models

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Two-Stage OD Flow Prediction for Emergency in Urban Rail Transit

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IEEE Transactions on intelligent Transportation Systems 2024年第1期25卷 920-928页

作者： Zhu, Guangyu Ding, Jiacun Wei, Yun Yi, Yang Xu, Sendren Sheng-Dong Wu, Edmond Q. Beijing Jiaotong University Key Lab. of Transport Industry of Big Data Application Technologies for Comprehensive Transport The Beijing Research Center of Urban Traffic Information Sensing and Service Technologies Beijing100044 China Beijing Mass Transit Railway Operation Corporation Ltd. Beijing100014 China Yangzhou University College of Information Engineering Yangzhou225127 China National Taiwan University of Science and Technology Automation and Control Center The Graduate Institute of Automation and Control Taipei106335 Taiwan Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China The Shanghai Engineering Research Center of Intelligent Control and Management Department of Automation Shanghai200240 China

Urban rail transit (URT) is vulnerable to natural disasters and social emergencies including fire, storm and epidemic (such as COVID-19), and real-time origin-destination (OD) flow prediction provides URT operators with important information to ensure the safety of URT system. However, hindered by the high dimensionality of OD flow and the lack of supportive information reflecting the real-time passenger flow changes, study in this area is at the beginning stage. A novel model consisting of two stages is proposed for OD flow prediction. The first stage predicts the inflows of all stations by Long Short-Term Memory (LSTM) in real time, where the dimension is reduced compared with predicting OD flows directly. In the second stage, the notion of separation rate, namely, the proportion of inbound passengers bounding for another station, is estimated. Finally, The OD flow is predicted by multiplying the inflow and separation rate. Experiments based on Hangzhou Metro dataset show the proposed model outperforms the contrast model in weighted mean average error (WMAE) and weighted mean square error (WMSE). Results also suggest that the proposed prediction model performs better on weekdays than on weekends, and with greater accuracy on larger OD flows. © 2000-2011 IEEE.

关键词： Forecasting

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POSITION SYNCHRONOUS control OF DUAL PMSM SYSTEM BASED ON PDFF+COMPOSITE control WITH PARAMETER ADAPTIVE ADJUSTMENT

POSITION SYNCHRONOUS CONTROL OF DUAL PMSM SYSTEM BASED ON PD...

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2024 CSAA/IET International Conference on Aircraft Utility Systems, AUS 2024

作者： Jiang, Zifeng Zhang, Xiuyun Xu, Runfei Wang, Zhiqiang Geng, Liqing Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin University of Technology and Education Tianjin300222 China School of Automobile and Transportation Tianjin University of Technology and Education Tianjin300222 China

To improve the tracking and synchronous performance of the dual PMSM system, this paper proposes a position synchronous control of dual PMSM system based on PDFF+composite control with parameter adaptive adjustment. Firstly, a mathematical model of the dual PMSM system is established. Then, the advantages, disadvantages, and limitations of the traditional cross coupling+single axis three loop control structure, PDFF based control structure, and PDFF based feedforward proportional composite control structure are analyzed. Then, a PDFF+composite control structure based on parameter adaptive adjustment is proposed, and it can improve the system's motion control and synchronous control effect by adaptively adjusting the velocity loop PDFF feedforward coefficient and cross coupling coefficient. Finally, the effectiveness of the proposed position synchronous control strategy is verified through Matlab/Simulink simulation. © The Institution of Engineering & Technology 2024.

关键词： Permanent magnets

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Unified convergence analysis of a second-order method of multipliers for nonlinear conic programming

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Science China Mathematics 2022年第11期65卷 2397-2422页

作者： Liang Chen Junyuan Zhu Xinyuan Zhao School of Mathematics Hunan UniversityChangsha 410082China Hunan Provincial Key Laboratory of Intelligent Information Processing and Applied Mathematics Changsha 410082China School of Mathematics Beijing University of TechnologyBeijing 100124China

In this paper,we accomplish the unified convergence analysis of a second-order method of multipliers(i.e.,a second-order augmented Lagrangian method)for solving the conventional nonlinear conic optimization ***,the algorithm that we investigate incorporates a specially designed nonsmooth(generalized)Newton step to furnish a second-order update rule for the *** first show in a unified fashion that under a few abstract assumptions,the proposed method is locally convergent and possesses a(nonasymptotic)superlinear convergence rate,even though the penalty parameter is fixed and/or the strict complementarity ***,we demonstrate that for the three typical scenarios,i.e.,the classic nonlinear programming,the nonlinear second-order cone programming and the nonlinear semidefinite programming,these abstract assumptions are nothing but exactly the implications of the iconic sufficient conditions that are assumed for establishing the Q-linear convergence rates of the method of multipliers without assuming the strict complementarity.

关键词： second-order method of multipliers augmented Lagrangian method convergence rate generalized Newton method second-order cone programming semidefinite programming

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Competition on robust deep learning

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National Science Review 2023年第6期10卷 13-15页

作者： Yinpeng Dong Chang Liu Wenzhao Xiang Hang Su Jun Zhu Department of Computer Science and Technology Institute for AI Tsinghua-Bosch Joint ML Center THBI Lab BNRist Center Tsinghua University Institute of Image Communication and Networks Engineering in the Department of Electronic Engineering (EE) Shanghai Jiao Tong University Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology CAS Peng Cheng Laboratory Pazhou Laboratory (Huangpu)

PROBLEM In recent years,the rapid development of artificial intelligence (AI) technology,especially machine learning and deep learning, is profoundly changing human production and *** various fields,such as robotics,face recognition,autonomous driving and healthcare,AI is playing an important ***,although AI is promoting the technological revolution and industrial progress,its security risks are often *** studies have found that the wellperforming deep learning models are extremely vulnerable to adversarial examples [1-3].The adversarial examples are crafted by applying small,humanimperceptible perturbations to natural examples,but can mislead deep learning models to make wrong *** vulnerability of deep learning models to adversarial examples can raise security and safety threats to various realworld applications.

关键词： robustness adversarial example adversarial training deep learning

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Three-Way Decision-Making Based on Incomplete information System and Its Application 9

Three-Way Decision-Making Based on Incomplete Information Sy...

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9th International Conference on Fuzzy Systems and Data Mining, FSDM 2023

作者： Xu, Changlin Mao, Songqian School of Mathematics and Information Science North Minzu University Yinchuan750021 China The Key Laboratory of Intelligent Information and Big Data Processing of Ningxia Province North Minzu University Ningxia Yinchuan750021 China

ISBN: (纸本)9781643684703

In order to avoid decision makers from making wrong decisions as much as possible and reduce the losses caused by wrong decisions, a new aggregation method of interval loss function is proposed based on incomplete information system. Firstly, the missing values are filled according to their characteristics and combined with probability, and on this basis, the measurement method of similarity is given, and the horizontal similarity class of each object is obtained according to the similarity between objects. Secondly, according to the number of times each object in the similar class appears in its corresponding horizontal similar class, the corresponding weight is obtained;Then the interval loss function of similar class is defined as the aggregation of interval loss functions of all objects in similar class, and each interval is weighted according to the weight, so that multiple intervals in similar class are aggregated into an interval, and then the aggregated interval is converted into a single value by using the conversion function. Finally, according to the aggregation method, three decision rules are given to make decisions, and the effectiveness of the method is verified by a case. © 2023 The authors and IOS Press.

关键词： Decision making

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Efficient DOA Estimation Based on Cauchy Loss Variable Step Size Algorithm 6

Efficient DOA Estimation Based on Cauchy Loss Variable Step ...

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6th IEEE International Conference on Electronic information and Communication Technology, ICEICT 2023

作者： Xu, Xingchao Li, Yingsong College of Information and Communications Engineering Harbin Engineering University Harbin150001 China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei China

ISBN: (纸本)9798350399059

The Cauchy loss function is robust to large outliers and has successful applications in signal processing. In this paper, a DOA estimation algorithm based on adaptive zero technology is proposed, which updates the weight of the filter by applying the Cauchy loss function, and further improves the algorithm performance by using the variable step size method. The algorithm step size is adjusted by accumulating errors and establishing a nonlinear function with instantaneous errors. The DOA estimation ability, estimation error and accuracy of the improved Cauchy algorithm in the impulse noise environment are analyzed. The algorithm is verified by simulation experiments. © 2023 IEEE.

关键词： Impulse noise

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