检索结果-内蒙古大学图书馆

Physical Layer Authentication Using Ensemble Learning Technique in Wireless Communications

computers, Materials & Continua 2022年第12期73卷 4489-4499页

作者： Muhammad Waqas Shehr Bano Fatima Hassan Shanshan Tu Ghulam Abbas Ziaul Haq Abbas Engineering Research Center of Intelligent Perception and Autonomous Control Faculty of Information TechnologyBeijing University of TechnologyBeijing100124China Faculty of Computer Science and Engineering GIK Institute of Engineering Sciences and TechnologyTopi23460Pakistan School of Engineering Edith Cowan UniversityJoondalup Perth6027WA Australia Faculty of Electrical Engineering GIK Institute of Engineering Sciences and TechnologyTopi23460Pakistan

Cyber-physical wireless systems have surfaced as an important data communication and networking research *** is an emerging discipline that allows effective monitoring and efficient real-time communication between the cyber and physical worlds by embedding computer software and integrating communication and networking *** to their high reliability,sensitivity and connectivity,their security requirements are more comparable to the Internet as they are prone to various security threats such as eavesdropping,spoofing,botnets,man-in-the-middle attack,denial of service(DoS)and distributed denial of service(DDoS)and *** methods use physical layer authentication(PLA),themost promising solution to detect ***,the cyber-physical systems(CPS)have relatively large computational requirements and require more communication resources,thus making it impossible to achieve a low latency *** methods perform well but only in stationary *** have extracted the relevant features from the channel matrices using discrete wavelet transformation to improve the computational time required for data processing by considering mobile *** features are fed to ensemble learning algorithms,such as AdaBoost,LogitBoost and Gentle Boost,to classify *** authentication of the received signal is considered a binary classification *** transmitted data is labeled as legitimate information,and spoofing data is illegitimate ***,this paper proposes a threshold-free PLA approach that uses machine learning algorithms to protect critical data from spoofing *** detects the malicious data packets in stationary scenarios and detects them with high accuracy when receivers are *** proposed model achieves better performance than the existing approaches in terms of accuracy and computational time by decreasing the processing time.

关键词： Physical layer authentication machine learning cyber-physical systems security

来源：评论

学校读者我要写书评

暂无评论

Test-Time Adaptation with Robust Dual-stream Perturbation for Stable Agent Deployment in Dynamic Scenarios

Test-Time Adaptation with Robust Dual-stream Perturbation fo...

引用

International Conference on computer Supported Cooperative Work in Design

作者： Haoyu Xiong Chengfu Yang School of Information Science and Technology Yunnan Normal University Kunming China Department of Education of Yunnan Province Engineering Research Center of Computer Vision and Intelligent Control Technology Kunming China

ISBN: (数字)9798350349184

ISBN: (纸本)9798350349191

Test-Time Adaptation (TTA) aims to provide a deployed agent capable of adapting to the target domain distribution using only unlabeled test data. Most existing TTA methods have achieved success under mild conditions, such as independently sampled data from a single or multiple static domains. However, these attempts may cause the deployed agent to fail in dynamic scenarios, where the test environment undergoes continuous changes over time. Previous TTA methods attempt to improve the quality of pseudo-labels by designing data augmentation strategies based on domain information. However, this violates the TTA paradigm, i.e., no characteristics of the dataset can be known in advance. Motivated by this, we propose a Robust Dual-stream Perturbation Test-time adaptation approach, called RDPT, to further stabilize the deployed agent from two aspects: (1) boost the robustness to noisy samples by encouraging the model to be consistent with its original image-level perturbation samples; (2) dynamically filtering samples with high entropy values, taking into account the discrepancy between the original and perturbation samples. Extensive experiments on the CIFAR10C and CIFAR100C benchmarks demonstrate the effectiveness of our method in dynamic scenarios, which is also easy to implement and deploy. 1

关键词： Adaptation models Filtering Federated learning Perturbation methods Computational modeling Predictive models Data augmentation

来源：评论

学校读者我要写书评

暂无评论

Anomaly-Resistant Decentralized State Estimation Under Minimum Error Entropy With Fiducial Points for Wide-Area Power Systems

引用

IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 74-87页

作者： Bogang Qu Zidong Wang Bo Shen Hongli Dong Hongjian Liu the College of Automation Engineering Shanghai University of Electric PowerShanghai 200090China IEEE the Department of Computer Science Brunel University LondonUxbridgeMiddiesex UB83PHUK the College of Information Science and Technology Donghua UniversityShanghai 200051 the Engineering Research Center of Digitalized Textile and Fashion Technology Ministry of EducationShanghai 201620China the Artificial Intelligence Energy Research Institute Northeast Petroleum UniversityDaqing 163318 the Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast PetroleumDaqing 163318 the Sanya Offshore Oil&Gas Research Institute Northeast Petroleum UniversitySanya 572024China the Key Laboratory of Advanced Perception and Intelligent Control of High-End Equipment Ministry of EducationAnhui Polytechnic UniversityWuhu 2410000 the School of Mathematics and Physics Anhui Polytechnic UniversityWuhu 241000China

This paper investigates the anomaly-resistant decentralized state estimation(SE) problem for a class of wide-area power systems which are divided into several non-overlapping areas connected through transmission lines. Two classes of measurements(i.e., local measurements and edge measurements) are obtained, respectively, from the individual area and the transmission lines. A decentralized state estimator, whose performance is resistant against measurement with anomalies, is designed based on the minimum error entropy with fiducial points(MEEF) criterion. Specifically, 1) An augmented model, which incorporates the local prediction and local measurement, is developed by resorting to the unscented transformation approach and the statistical linearization approach;2) Using the augmented model, an MEEF-based cost function is designed that reflects the local prediction errors of the state and the measurement;and 3) The local estimate is first obtained by minimizing the MEEF-based cost function through a fixed-point iteration and then updated by using the edge measuring information. Finally, simulation experiments with three scenarios are carried out on the IEEE 14-bus system to illustrate the validity of the proposed anomaly-resistant decentralized SE scheme.

关键词： Decentralized state estimation(SE) measurements with anomalies minimum error entropy unscented Kalman filter wide-area power systems

来源：评论

学校读者我要写书评

暂无评论

A Rapid Finger Vein Recognition Approach Based on UNet++ 1

引用

39th CCF National Conference on computer Applications, CCF NCCA 2024

作者： Liu, Peng Jia, Yujiao Cao, Xiaofan Wang, Changjie Fan, Shanshan Institute of Energy and Electrical Engineering Changchun University of Science and Technology Changchun China School of Control and Computer Engineering North China Electric Power University Beijing China Yangzhong Intelligent Electric Research Center North China Electric Power University Beijing China

ISBN: (数字)9789819796748

ISBN: (纸本)9789819796731

With the advancement of biometric technologies, finger vein recognition has garnered widespread attention within the academic community. This paper proposes a method based on the UNet++ model, wherein parameter adjustments are made to the UNet++ architecture to ensure precise pixelwise segmentation of finger vein images. Following the parameter optimization, model compression is applied through structural reparameterization to further increase the recognition speed of the trained model. The approach achieves recognition accuracies of 93.1% on two publicly available finger vein datasets, and it features a feature extraction time of 0.0131 s for a single finger vein image. The recognition time for a single fingerprint vein image is 0.0294 s. The results indicate that the use of the UNet++ model as a framework for finger vein feature extraction and subsequent model compression render it suitable for finger vein recognition tasks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

A Lightweight Model of VGG-U-Net for Remote Sensing Image Classification

引用

computers, Materials & Continua 2022年第12期73卷 6195-6205页

作者： Mu Ye Li Ji Luo Tianye Li Sihan Zhang Tong Feng Ruilong Hu Tianli Gong He Guo Ying Sun Yu Thobela Louis Tyasi Li Shijun College of Information Technology Jilin Agricultural UniversityChangchun130118China Jilin Province Agricultural Internet of Things Technology Collaborative Innovation Center Changchun130118China Jilin Province Intelligent Environmental Engineering Research Center Changchun130118China Jilin Province Information Technology and Intelligent Agriculture Engineering Research Center Changchun130118China College of Engineering and Technology Jilin Agricultural UniversityChangchun130118China Department of Agricultural Economics and Animal Production University of LimpopoSovenga0727PolokwaneSouth Africa College of Information Technology Wuzhou UniversityWuzhou543003China Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou543003China

Remote sensing image analysis is a basic and practical research hotspot in remote sensing *** sensing images contain abundant ground object information and it can be used in urban planning,agricultural monitoring,ecological services,geological exploration and other *** this paper,we propose a lightweight model combining vgg-16 and u-net *** combining two convolutional neural networks,we classify scenes of remote sensing *** ensuring the accuracy of the model,try to reduce the memory of *** to the experimental results of this paper,we have improved the accuracy of the model to 98%.The memory size of the model is 3.4 *** the same time,The classification and convergence speed of the model are greatly *** simultaneously take the remote sensing scene image of 64×64 as input into the designed *** the accuracy of the model is 97%,it is proved that the model designed in this paper is also suitable for remote sensing images with few target feature points and low ***,the model has a good application prospect in the classification of remote sensing images with few target feature points and low pixels.

关键词： VGG-16 U-Net fewer feature points nonlinear correction layer zero padding

来源：评论

学校读者我要写书评

暂无评论

Compactness and Separateness Driven Fuzzy Clustering Validity Index Called TLW 18th

Compactness and Separateness Driven Fuzzy Clustering Validit...

引用

18th CCF Conference on computer Supported Cooperative Work and Social Computing, ChineseCSCW 2023

作者： Tang, Yiming Wang, Xiang Li, Bing Hu, Xianghui Xie, Wenjun Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and Information Hefei University of Technology Anhui Hefei230601 China Engineering Research Center of Safety Critical Industry Measure and Control Technology Ministry of Education Hefei University of Technology Anhui Hefei230601 China

ISBN: (纸本)9789819996391

The design of validity index of fuzzy clustering has always been a historical problem in fuzzy clustering field. When the distribution of cluster centers is very close, it is difficult for the existing fuzzy clustering validity indexes to obtain a reasonable cluster number, and the separation mechanism of these indexes is too simple. In order to solve the above problems, we propose a novel fuzzy clustering validity index called TLW (Tang-Li-Wang) index. Firstly, compactness is expressed as the ratio of the membership weighted distance value to the sample variance of the dataset. Secondly, the sum of the maximum distance between cluster centers and the mean distance is used in separateness, and the sample variance of cluster centers is introduced, and the two are multiplied to describe the separateness. Thirdly, on the basis of considering compactness and separateness, the introduction of cluster number can alleviate the phenomenon that the index value may change monotonically with the increase of cluster number. Finally, the classical FCM (Fuzzy C-Mean) algorithm is used to conduct experiments on indexes. Comparative experiments and analyses were carried out on 17 typical datasets and 12 clustering validity indexes. From the experimental results of normal simple datasets and high-dimensional difficult datasets, the proposed index shows some advantages. All in all, these results verify that the proposed TLW index has better accuracy and stronger stability. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Fuzzy clustering

来源：评论

学校读者我要写书评

暂无评论

Skeleton-based Action Recognition Using Two-stream Graph Convolutional Network with Pose Refinement 41

Skeleton-based Action Recognition Using Two-stream Graph Con...

引用

第41届中国控制会议

作者： Biao Zheng Luefeng Chen Min Wu Witold Pedrycz Kaoru Hirota School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Department of Electrical and Computer Engineering University of Alberta Tokyo Institute of Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

With the development of science and technology,graph convolutional network has made great progress in improving the accuracy of action ***,there still exists some deficiencies in current ***,the human skeleton point coordinates entering into the network are barely refined,which may cause large ***,the second-order information(the length and direction of bones),which can reflect action characteristics discriminatively,is rarely *** solve the above issues,a two stream graph convolutional network with pose refinement for skeleton based action recognition is ***,we use an adaptive block to to help improve the *** test our method on Kinetics dataset and the experiment show it can get better results than some recent methods,which plays a positive role in future research.

关键词： Graph convolutional network Pose refinement Skeleton based action recognition Adaptive block

来源：评论

学校读者我要写书评

暂无评论

SCSegamba: Lightweight Structure-Aware vision Mamba for Crack Segmentation in Structures

arXiv

引用

arXiv 2025年

作者： Liu, Hui Jia, Chen Shi, Fan Cheng, Xu Chen, Shengyong School of Computer Science and Engineering Tianjin University of Technology China Engineering Research Center of Learning-Based Intelligent System Ministry of Education Key Laboratory of Computer Vision and System Ministry of Education

Pixel-level segmentation of structural cracks across various scenarios remains a considerable challenge. Current methods encounter challenges in effectively modeling crack morphology and texture, facing challenges in balancing segmentation quality with low computational resource usage. To overcome these limitations, we propose a lightweight Structure-Aware vision Mamba Network (SCSegamba), capable of generating high-quality pixel-level segmentation maps by leveraging both the morphological information and texture cues of crack pixels with minimal computational cost. Specifically, we developed a Structure-Aware Visual State Space module (SAVSS), which incorporates a lightweight Gated Bottleneck Convolution (GBC) and a Structure-Aware Scanning Strategy (SASS). The key insight of GBC lies in its effectiveness in modeling the morphological information of cracks, while the SASS enhances the perception of crack topology and texture by strengthening the continuity of semantic information between crack pixels. Experiments on crack benchmark datasets demonstrate that our method outperforms other state-of-the-art (SOTA) methods, achieving the highest performance with only 2.8M parameters. On the multi-scenario dataset, our method reached 0.8390 in F1 score and 0.8479 in mIoU. The code is available at https://***/Karl1109/SCSegamba. © 2025, CC BY.

关键词： State space methods

来源：评论

学校读者我要写书评

暂无评论

Multi-branch low-light enhancement algorithm based on spatial transformation

引用

Multimedia Tools and Applications 2024年 1-21页

作者： Wang, Wenlu Sun, Ying Zou, Chunlong Tang, Dalai Fang, Zifan Tao, Bo Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Wuhan430081 China School of Computer Information Management Inner Mongolia University of Finance and Economics Hohhot010051 China College of Mechanical Engineering Hubei University of Automotive Technology Shiyan442000 China Research Center for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan430081 China Precision Manufacturing Research Institute Wuhan University of Science and Technology Wuhan430081 China Hubei Key Laboratory of Hydroelectric Design & amp Maintenance China Three Gorges University Yichang443002 China

Many state-of-the-art low-light image enhancement techniques now suffer from issues like color distortion, detail blurring, and the halo effect, hindering their ability to produce visual effects. This paper presents a multi-branch low-light enhancement algorithm based on spatial transformation to significantly improve the visual impact of images under low-light settings, overcoming the limitations of existing approaches. The process involves dividing the initial low-light picture into three distinct layers. Bootstrap filtering and Contrast Limited Adaptive Histogram Equalization are used to process the main feature layer. Primary feature extraction is used to extract features for the compensation layer, which is then integrated with Contrast Limited Adaptive Histogram Equalization and MSRCR. The auxiliary layer utilizes spatial transformation to apply gamma correction to the V-channel and performs color space transformation and additional processing. Ultimately, these three layers are combined and refined to create the final improved image. Based on the experimental results, the proposed method outperforms the standard MSRCR algorithm by 52.47%, 71.58%, and 12.10%, respectively, on the assessment metrics AG, SD, and IE. LOE declines by 22.3%. The processed image presents a good visual quality, effectively enhancing the image brightness while retaining a large amount of information and improving the image details. This paper proposes an effective method to deal with the problem of low illumination image enhancement, which provides a strong reference for future research and application in related fields. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Image enhancement

来源：评论

学校读者我要写书评

暂无评论

Construction and optimization of a computational holographic lithography system 8

Construction and optimization of a computational holographic...

引用

8th International Conference on Speckle Metrology, Speckle 2023

作者： Chen, Rui Lin, Angyi You, Jianfeng Lin, Huixiang Zhao, Wenqing Zhang, Fucai School of Control and Computer Engineering North China Electric Power University Baoding071003 China The Department of Electrical and Electronic Engineering Southern University of Science and Technology Shenzhen518055 China Engineering Research Center of Intelligent Computing for Complex Energy Systems Ministry of Education North China Electric Power University China

ISBN: (数字)9781510674592

ISBN: (纸本)9781510674585

Traditional lithography techniques are currently facing challenges, including high costs and the susceptibility of mask plates to damage. This research aims to elucidate the feasibility and technical constraints of a novel diffraction lithography approach. This method can reduce the size and cost of lithography machines, break through existing technological barriers, and offer new possibilities for the future development of lithography machines. We have built a basic computational holographic lithography system utilizing a 405nm laser and validated the system using holograms obtained with both classical GS algorithm and a newly proposed method. With the GS holograms, patterns with 700nm features have been successfully exposed on the photoresist. With our new algorithms, multiple holograms for the same target pattern can be generated with different settings in the algorithm. Sequential exposure of those holograms resulted in continuous lines 500 nm wide with reduced speckle artifacts, which was about a 1.4-time improvement over the result from the GS algorithm. Future research will focus on optimizing and enhancing the experimental system and the hologram calculation methods to reduce the line widths further and improve the exposure pattern quality. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Holograms

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：