检索结果-内蒙古大学图书馆

8th Symposium on Novel Photoelectronic Detection technology and Applications

作者： Fu, Luhua Hu, Yutong Pang, Jiaming Dong, Liu Shuai, Jia Ma, Baoqiang Key Laboratory of Photoelectric Control Technology Tianjin300072 China Science and Technology on Electro-Optical Information Security Control Laboratory Tianjin300308 China Tianjin University Tianjin300072 China

ISBN: (数字)9781510653122

ISBN: (纸本)9781510653115

This paper studies a method of detecting the position of crankshaft flange hole group based on vision measurement, and sets up the position detection system of crankshaft flange hole group. The relative measurement model of hole group position is established by using the standard crankshaft information, and the system calibration method is studied. In this paper, a multi-camera calibration method based on polynomial fitting two-dimensional image mapping model is adopted. In addition, the image processing technology of hole group is studied. The improved Canny edge detection method is used to extract the contour of the hole group. Redundant edge filtering algorithm is used to eliminate unreliable edges. Then use the gradient interpolation method to extract sub-pixel edges. The measurement results show that the single-direction measurement error of the central coordinate of the crankshaft flange hole group is less than 0.07mm, and the repeatability error is less than 0.009mm, which provides a basis for the realization of industrial online efficient detection. © 2022 SPIE

关键词： Calibration

来源：评论

学校读者我要写书评

暂无评论

Defense of Signal Modulation Classification Attack Based on GAN 7th

Defense of Signal Modulation Classification Attack Based on ...

引用

7th China National Conference on Big Data and Social Computing, BDSC 2022

作者： Zhu, Jiawei Liu, Yuhang Xu, Dongwei Yang, Hao Xuan, Qi Wang, Shunling Science and Technology on Communication Information Security Control Laboratory Jiaxing314033 China Institute of Cyberspace Security Zhejiang University of Technology Hangzhou310023 China College of Information Engineering Zhejiang University of Technology Hangzhou310023 China

ISBN: (纸本)9789811975318

Although deep learning has been broadly used in all kinds of domains and has also achieved very good performance, it is obvious that deep learning is very vulnerable to be attacked shown by extensive researches (e.g. even a very small perturbation is added to the raw signal data, the result of the modulation classification of the signal by the deep neural network will be wrong), which will cause serious consequences. Thus, it is necessary to find some ways to defense this attack. As a new deep learning model in recent years, Generative Adversarial Network (GAN) has been applied to the field of radio communication, which can encrypt the signal data, so as to ensure the reliable transmission of the signal. In this paper, a defense method against signal modulation classification attack based on GAN is developed, which is used to utilize generator to reconstruct the signal sample to improve the classification accuracy of the model, while the defense ability of the model against adversarial samples is improved. It has been shown that the method achieved good results in experiments. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Fake News Detection Across Multiple Domains Using Fuzzy Association Rules 24th

Fake News Detection Across Multiple Domains Using Fuzzy Asso...

引用

24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

作者： Xu, Xiaofeng Zhang, Weisha Huang, Yuanyuan Lu, Hongyu Lu, Jiazhong School of Cybersecurity Xin Gu Industrial College Chengdu University of Information Technology Chengdu610225 China Advanced Cryptography and System Security Key Laboratory of Sichuan Province Chengdu610225 China SUGON Industrial Control and Security Center Chengdu610225 China School of Foreign Languages University of Electronic Science and Technology of China Chengdu611731 China

ISBN: (纸本)9789819615247

The detection of fake news is not confined to a single domain, and due to domain transfer, the reliance on detection methods specific to a single domain becomes inadequate when dealing with multi-domain issues. When a multi-domain detection occurs, labels from one domain focus exclusively on the news characteristics of that particular domain, ignoring the possibility that part of the news may include functions from more than one domain. To address these challenges, we propose a multi-domain fake news detection model based on fuzzy rules, incorporating a fuzzy mechanism and an optimization module for fuzzy association rules. In this model, we first introduce a fuzzy mechanism that applies fuzzy processing to domains through neural networks, constructing fuzzy domain labels for each news domain. Subsequently, we incorporate fuzzy association rules to extract a broader range of sample features, thereby enhancing detection effectiveness. Experiments conducted on a fake news dataset demonstrate that our model achieves commendable detection performance with a relatively low training cost, reaching an F1 score of over 97.13% for sample detection. This model successfully overcomes the limitations of single-domain detection in fake news identification and improves the precision of feature extraction through fuzzy rules, showing superior performance in handling multi-domain fake news detection. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： fake news detection fuzzy rules multi-domain social media

来源：评论

学校读者我要写书评

暂无评论

Data-Driven Active Power Dispatch for Wind Farms 13

Data-Driven Active Power Dispatch for Wind Farms

引用

13th IEEE Data Driven control and Learning Systems Conference, DDCLS 2024

作者： Jiao, Xuguo Zhang, Daoyuan Wang, Xin Ma, Zhaoxing Zhang, Zhenyong Liu, Wenfeng School of Information and Control Engineering Qingdao University of Technology Qingdao266520 China College of Control Science and Engineering Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou310027 China Ministry of Education Shandong Computer Science Center Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Jinan250014 China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan250014 China College of Computer Science and Technology Guizhou University State Key Laboratory of Public Big Data Guiyang550025 China School of Civil Engineering Qingdao University of Technology Qingdao266520 China

ISBN: (纸本)9798350361674

Active power dispatch of wind farms plays an important role in power grid scheduling. In this paper, a data-driven active power dispatch strategy for wind farms is proposed, which uses the key point of minimizing the standard deviation of wind turbines' output power series to reduce their fluctuations. First, to build the optimization problem, the historical active power output data of each wind turbine is collected from the Supervisory control And Data Acquisition (SCADA) system. Then, the objective function is developed based on the idea of minimizing the standard deviation of the output power time series. Meanwhile, considering the constraints of wind turbines' output power and active power balance of the grid, the feasible domain of the cost function is constructed. Further, to solve the proposed nonlinear optimization problem with equality and inequality constraints, the trust region interior point method (TRIPM) is employed to explore optimal solution within the feasible domain. Finally, actual data collected from wind farms is used to test effectiveness of the designed approach and experimental results show that our method can achieve better output power smoothing performance than conventional Proportional Dispatch (PD) method. © 2024 IEEE.

关键词： Cost functions

来源：评论

学校读者我要写书评

暂无评论

Multi-view infrared small target recognition based on YOLOv5

Multi-view infrared small target recognition based on YOLOv5

引用

2022 Chinese Automation Congress, CAC 2022

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

ISBN: (纸本)9781665465335

In order to improve the recognition accuracy of small infrared targets in complex environment, a SyluInfrared dataset is built by taking multi-view infrared images with the Frock TiX600 infrared thermal imager. Seven image enhancement algorithms including image brightening, contrast adjustment, image blurring, image flipping and image scaling are designed to improve the image quality of small infrared targets. The YOLOv5 deep learning model is used to identify small infrared targets with multiple views to improve the recognition accuracy of small infrared targets. The experimental results show that the accuracy of multi-view infrared small target recognition model for YOLOv5 deep network is 97.7%, which is 6.6% higher than that of single-view infrared small target recognition model based on YOLOv5. The multi-view target recognition strategy significantly improves the infrared small target recognition performance. © 2022 IEEE.

关键词： Image enhancement

来源：评论

学校读者我要写书评

暂无评论

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

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 ...

引用

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

来源：评论

学校读者我要写书评

暂无评论

Signals of Opportunity Navigation Using LTE Downlink Signals 22

Signals of Opportunity Navigation Using LTE Downlink Signals

引用

22nd IEEE International Conference on Communication technology, ICCT 2022

作者： Wang, Yiteng Zhu, Huijie Liang, Tianyi Qian, Jiachuan The 36th Research Institute of China Electronics Technology Group Corporation Science and Technology on Communication Information Security Control Laboratory Jiaxing China

ISBN: (纸本)9781665470674

For the global navigation satellite system (GNSS) cannot meet the positioning requirements under occlusion or malicious interference, this paper proposes a receiver self-localization method using long-term evolution (LTE) downlink signals. The method is based on the multi-station time difference location mechanism. The signal acquisition of multi-base stations (BSs) is realized by signal demodulation. The transmission time difference calibration is used to solve the asynchronous problem among BSs. The synchronous signal and cell-specific reference signal are comprehensively detected to extract high-precision time difference parameters. The receiver can calculate and obtain its own position by using these timing parameters. Finally, a software-defined receiver is built to carry out experiments in the outdoor environment. Experimental results show that the positioning distance and moving direction are basically consistent with the actual situation. The root mean square error (RMSE) is less than 5m, which fully verifies the feasibility of LTE as an opportunity signal for navigation. © 2022 IEEE.

关键词： Navigation

来源：评论

学校读者我要写书评

暂无评论

Rotational random extraction of Toeplitz matrix for ghost imaging 4

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

Phased Array Full-Duplex for Concurrent Multifunction: Architecture and Implementation 13

Phased Array Full-Duplex for Concurrent Multifunction: Archi...

引用

13th International Conference on Microwave and Millimeter Wave technology, ICMMT 2021

作者： Chen, Shunyang Chen, Jiarui Huang, Xiaoguo Chen, Linglu Zhang, Qi Chen, Binhui Zhu, Menglei Science And Technology On Communication Information Security Control Laboratory Jiaxing China

ISBN: (纸本)9781665434379

In this article, the realization of concurrent multifunction in phased array full-duplex platforms is discussed. For modern complex electromagnetic environment, an efficient architecture is needed to accomplish the concurrent working of several different functions, such as communication, radar, spectrum sensing and so on. First, we establish a novel architecture based on the phased array system to effectively incorporate current approaches useful for realizing concurrent multifunction. Then, a prototype implementation based on multi-objective beamforming is proposed to demonstrate the role of digital methods in cancelling self-interferenc. Finally, simulation and experimental results are exhibited to prove the result of the proposed method. © 2021 IEEE.

关键词： Architecture

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：