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Interval Type-2 Fuzzy Hierarchical Adaptive Cruise Following-control for Intelligent Vehicles

IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1658-1672页

作者： Hong Mo Yinghui Meng Fei-Yue Wang Dongrui Wu the College of Electric and Information Engineering Changsha University of Science and TechnologyChangsha 410114China the State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 Qingdao Academy of Intelligent Industries Qingda 266109 the Center of China Economic and Social Security University of Chinese Academy of SciencesBeijing 100190China the Ministry of Education Key Laboratory on Image Information Processing and Intelligent Control the School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China

Intelligent vehicles can effectively improve traffic congestion and road traffic *** cruise followingcontrol(ACFC)is a vital part of intelligent *** this paper,a new hierarchical vehicle-following control strategy is presented by synthesizing the variable time headway model,type-2 fuzzy control,feedforward+fuzzy proportion integration(PI)feedback(F+FPIF)control,and inverse longitudinal dynamics model of ***,a traditional variable time headway model is improved considering the acceleration of the lead ***,an interval type-2 fuzzy logic controller(IT2 FLC)is designed for the upper structure of the ACFC system to simulate the driver's operating *** reduce the nonlinear influence and improve the tracking accuracy for the desired acceleration,the control strategy of F+FPIF is given for the lower control ***,the lower control method proposed in this paper is compared with the fuzzy PI control and the traditional method(no lower controller for tracking desired acceleration)***,the proportion integration differentiation(PID),linear quadratic regulator(LQR),subsection function control(SFC)and type-1 fuzzy logic control(T1 FLC)are respectively compared with the IT2 FLC in control performance under different ***,the simulation results show the effectiveness of IT2 FLC for the upper structure and F+FPIF control for the lower structure.

关键词： Adaptive cruise following-control(ACFC) feedforward+fuzzy proportion integration(PI)feedback(F+FPIF) type-2 fuzzy control variable time headway

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Infrared Target Detection Based on the Fusion of Mask R-CNN and Image Enhancement Network

Infrared Target Detection Based on the Fusion of Mask R-CNN ...

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2022 Chinese Automation Congress, CAC 2022

作者： Liu, Fang Guan, Song Yu, Kuaikuai Gong, Hua Shengyang Ligong University College of Science Shenyang110159 China Science and Technology on Electro-Optical Information Security Control Laboratory Tianjing300308 China

ISBN: (纸本)9781665465335

In this paper, we focus on the problem of the infrared image detection. Aiming at the problem of the low contrast of the infrared images, an adaptive gamma transformation algorithm (AGT) is established to intelligently improve the contrast of the infrared images. Aiming at the problem of the weak edge information of the infrared images, an improved Sobel operator edge enhancement algorithm (ISOEE) is designed to enrich the edge features of the infrared images. In order to solve the problem that the traditional infrared image detection algorithm relies on expert experience, the fusion infrared images detection model AIE-Mask R-CNN based on Mask R-CNN, AGT algorithm and ISOEE algorithm is proposed. This fusion model can realize accurate and intelligent detection for the infrared images. The experimental results show that the fusion model AIE-Mask R-CNN improves the detection accuracy of the infrared images. © 2022 IEEE.

关键词： Edge detection

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A Passive Navigation Algorithm Based on Derivative Dynamic Time Regularization Geomagnetic Matching 2

A Passive Navigation Algorithm Based on Derivative Dynamic T...

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2021 2nd International Conference on Modeling, Big Data Analytics and Simulation, MBDAS 2021

作者： Wang, Yiteng Bao, Jinhong Li, Zehua Science and Technology on Communication Information Security Control Laboratory China No.36 Research Institute of China Electronics Technology Group Corporation China College of Telecommunication Engineering Hangzhou Dianzi University Hangzhou310018 China

As satellite positioning has shortcomings such as susceptibility to multipath interference, we look forward to using a new algorithm to solve these problems. The method of derivative dynamic time regularization is used as the matching method of geomagnetic navigation. Due to the factors of the inertial device itself, a certain cumulative error will occur in the positioning solution of the inertial navigation (INS). Therefore, an outdoor error model needs to be established, and the positioning error is corrected by filtering technology. To solve this problem, the Unscented Kalman Filter is used to fuse the positioning results of the two to obtain a more accurate positioning, with an average accuracy within 1.5 meters. © Published under licence by IOP Publishing Ltd.

关键词： Kalman filters

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Prompt and Contrastive Learning for Few-shot Sentiment Classification 5

Prompt and Contrastive Learning for Few-shot Sentiment Class...

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5th International Conference on Artificial Intelligence and Pattern Recognition, AIPR 2022

作者： Wang, Fei Chen, Long Huang, Xiaohua Xu, Cai Zhao, Wei Guan, Ziyu Lu, Guangyue Shaanxi Key Laboratory of Information Communication Network and Security Xi'an University of Posts and Telecommunications China School of Information Science and Technology Northwest University China School of Computer Science and Technology Xidian University China

ISBN: (纸本)9781450396899

Sentiment classification is a hot topic in the field of natural language processing. Currently, state-of-the-art classification models follow two steps: pre-training a large language model on upstream tasks, and then using human-labeled data to fine-tune a task-related model. However, there is a large gap between the upstream tasks of the pre-trained model and the downstream tasks being performed, resulting in the need for more labeled data to achieve excellent performance. Manually annotating data is expensive. In this paper, we propose a few-shot sentiment classification method based on Prompt and Contrastive Learning (PCL), which can significantly improve the performance of large-scale pre-trained language models in low-data and high-data regimes. Prompt learning aims to alleviate the gap between upstream and downstream tasks, and the contrastive learning is designed to capture the inter-class and intra-class distribution patterns of labeled data. Thanks to the integration of the two strategies, PCL markedly exceeds baselines with low resources. Extensive experiments on three datasets show that our method has outstanding performance in the few-shot settings. © 2022 ACM.

关键词： Computational linguistics

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News-driven financial warning based on label information attention 5

News-driven financial warning based on label information att...

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5th International Conference on Artificial Intelligence and Pattern Recognition, AIPR 2022

作者： Zhilin, Ren Long, Chen Xiaohua, Huang Wenjing, Wang Cai, Xu Wei, Zhao Ziyu, Guan Shaanxi Key Laboratory of Information Communication Network and Security Xi'an University of Posts and Telecommunications China School of Information Science and Technology Northwest University China School of Computer Science and Technology Xidian University China

ISBN: (纸本)9781450396899

Most existing news-driven stock market prediction methods ignore the potential relationship between financial news and stocks. The complex relationship can help us to improve the accuracy of algorithmic trading systems. Therefore, we propose a deep learning method for financial warning by fusing Stock Label information (SLI). We extract events from news texts and fuse stock information together as feature vectors, using neural networks to model the underlying relationship between news and stocks. Experimental results show that our method outperforms other baseline methods in experiments on TPX500 and TPX100 datasets. CCS CONCEPTS •Computing methodologies •Artificial intelligence •Natural language processing © 2022 ACM.

关键词： Deep learning

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Rotational random extraction of Toeplitz matrix for ghost imaging 4

Rotational random extraction of Toeplitz matrix for ghost im...

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4th International Conference on Optoelectronic science and Materials, ICOSM 2022

作者： Cheng, Zhengdong Sun, Maosheng Chen, Yi Chang, Haikuan Liu, Yanyan State Key Laboratory of Pulsed Power Laser Technology National University of Defense Technology Huangshan Road No.460 HeFei230037 China Science and Technology on Electro-Optical Information Security Control Laboratory Weiwu Road No.9 Tianjin300450 China

ISBN: (纸本)9781510662209

If Toeplitz matrix is used for compression-aware ghost imaging, the imaging quality will be very low. In order to solve the problem, a new experimental scheme for ghost imaging is proposed in this paper. The scheme first extracts the Toeplitz matrix elements randomly and sparsely using a revolving matrix, and then modulates the illumination light field. The sampling is performed by using the Toeplitz matrix as a fixed matrix and another measurement matrix as a revolving matrix. The revolving matrix rotates around its center at a constant angular velocity. The fixed Toeplitz matrix is superimposed with the revolving matrix to form the optical field modulation matrix. The results of simulation experiments show that light field modulation scheme of the rotational random extraction of Toeplitz matrix can modulate the light field with more randomness. The use of this scheme in ghost imaging experiments results in high quality images with low distortion. © 2023 SPIE. All rights reserved.

关键词： Matrix algebra

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Analysis of Attack Effectiveness Evaluation of AD hoc Networks based on Rough Set Theory 17

Analysis of Attack Effectiveness Evaluation of AD hoc Networ...

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17th International Conference on Computational Intelligence and security, CIS 2021

作者： Dai, Jiahao Chen, Yongqun China Electronic Corporation NO.36 Institute Science and Technology on Communication Information Security Control Laboratory Jiaxing China

ISBN: (纸本)9781665494892

This paper mainly studies an attack effectiveness evaluation method for AD hoc networks based on rough set theory. Firstly, we use OPNET to build AD hoc network simulation scenario, design and develop attack module, and obtain network performance parameters before and after the attack. Then the rough set theory is used to evaluate the attack effectiveness. The results show that this method can effectively evaluate the performance of AD hoc networks before and after attacks. © 2021 IEEE.

关键词： Rough set theory

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Direct Position Determination in the Presence of Direction-Dependent Mutual Coupling Using a Moving Array 34

Direct Position Determination in the Presence of Direction-D...

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34th General Assembly and Scientific Symposium of the International Union of Radio science, URSI GASS 2021

作者： Ma, Fei Wang, Yuexian Wang, Ling Gong, Yanyun School of Electronics and Information Northwestern Polytechnical University Xi'an China The Science and Technology on Communication Information Security Control Laboratory Jiaxing China

ISBN: (纸本)9789463968027

In this paper, a new approach without iteration is proposed for direct position determination (DPD) with Doppler shifts in the presence of unknown direction-dependent mutual coupling (DDMC). The special banded symmetric Toeplitz structure of mutual coupling matrix and Doppler shift containing location information can be exploited for constructing a space-time transformation matrix, and the spectral function which is utilized to obtain the locations of sources is established via the orthogonality between space-time transformation matrix and noise subspace. Simulation results show that our solution can accurately determine the emitter position in a single-step without a priori information of the DDMC. © 2021 URSI.

关键词： Electric fields

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The differential fault analysis on block cipher FeW

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Cybersecurity 2023年第2期6卷 62-74页

作者： Haiyan Xiao Lifang Wang Jinyong Chang School of Computer Science Northwestern Polytechnical UniversityXiAn 710055People's Republic of China Engineering University of PAP XiAn 710055People's Republic of China School of Information and Control Engineering XiAn University of Architecture and TechnologyXi'An 710055People's Republic of China State Key Laboratory of Information Security(SKLOIS) Institute of Information EngineeringChinese Academy of SciencesBeijing 100089People's Republic of China

Feather weight(FeW)cipher is a lightweight block cipher proposed by Kumar et *** 2019,which takes 64 bits plaintext as input and produces 64 bits *** Kumar et ***,FeW is a software oriented design with the aim of achieving high efficiency in software based *** seems that FeW is immune to many cryptographic attacks,like linear,impossible differential,differential and zero correlation ***,in recent work,Xie et *** the security of *** precisely,they proved that under the differential fault analysis(DFA)on the encryption states,an attacker can completely recover the master secret *** this paper,we revisit the block cipher FeW and consider the DFA on its key schedule algorithm,which is rather popular cryptanalysis for kinds of block *** particular,by respectively injected faults into the 30th and 29th round subkeys,one can recover about 55/80~69%bits of master *** the brute force searching remaining bits,one can obtain the full master secret *** simulations and experiment results show that our analysis is practical.

关键词： Differential fault analysis Block cipher FeW Side channel attack

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An analysis of network traffic identification based on decision tree 2

An analysis of network traffic identification based on decis...

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2nd International Conference on Artificial Intelligence and Electromechanical Automation, AIEA 2021

作者： Dai, Jiahao Chen, Yongqun Chen, Yucheng Meng, Aodong China Electronic Corporation NO.36 Institute Science and Technology on Communication Information Security Control Laboratory Jiaxing China

ISBN: (纸本)9781665432658

With the strong development momentum of the Internet, network not only brings convenience to our life, but also poses threats to our network security. Users can hide their IP and identity information through encryption algorithm, and carry out various illegal activities and transactions in the network. Therefore, it will be of great value to identify special traffic which impact on network security and exploring abnormal situations in the network. Special traffic is important to the security of the network space. In this paper, we establish a decision tree model based on C4.5 and random forest to compare the accuracy of the two decision tree algorithms in traffic classification. Experimental results show that these two methods can identify traffic effectively. © 2021 IEEE.

关键词： Decision trees

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