检索结果-内蒙古大学图书馆

2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Wang, Bingshu Lin, Jia Zhuang, Xiaodong Zhang, Guanghui Chen, C.L. Philip School of Software Northwestern Polytechnical University Xi'an China Shenzhen University Guangdong Key Lab. of Intelligent Info. Processing and Shenzhen Key Laboratory of Media Security Shenzhen China School of Computer Science and Technology Shandong University Qingdao China School of Computer Science and Engineering South China University of Technology Guangzhou China

ISBN: (纸本)9781665410205

Concrete structural crack damage classification is of importance for road safety. This paper proposes a new method based on broad neural network for crack damage classification in concrete structures. It includes three stages. Firstly, a pre-trained deep neural network is used to extract the features from crack images. Secondly, principal component analysis is used to project the retrieved features from high dimensions to low dimensions. Thirdly, broad learning system is employed to predict the classification using the low-dimensional features. Experimental results demonstrate that this method reduces the model's training time and improves classification accuracy. © 2024 IEEE.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Electric Energy Trading Mechanism of Distributed Electric Vehicles in Smart Grid 38

Electric Energy Trading Mechanism of Distributed Electric Ve...

引用

38th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2023

作者： Hu, Chunlin An, Dou Xi'an Jiaotong University Faculty of Electronic and Information Engineering Xian710049 China Xi'an Jiaotong University Fac. of Electron. and Info. Eng. and the Moe Key Lab. for Intelligent Networks and Network Security Xian710049 China

ISBN: (纸本)9798350303636

With the continuous development of the smart grid and the increasing number of electric vehicles (EVs), the power transaction in the smart grid has become increasingly important in our daily life. This paper studies the distributed trading mechanism of electric vehicle energy in a smart grid. First, a non-cooperative game model is established among EV users. Each user can buy and sell power to both the central grid and other EV users. EV owners may act as buyers or sellers in the transaction according to their power availab.lity. Next, this paper calculates the optimal utility function for EV users and obtains the optimal decision. The expression of the Nash equilibrium solution and the optimal user utility function are given. Then the efficiency of Nash equilibrium is analyzed. Finally, demand response management is carried out under the model. This paper designs two groups of comparative experiments. The first experiment compared daily electricity consumption and electricity charges of users before and after demand response management. The second experiment showed how the sum of electricity bills changed with the number of users who don't change their habits. © 2023 IEEE.

关键词： demand response management electricity transaction Nash equilibrium non-cooperative game

来源：评论

学校读者我要写书评

暂无评论

Research and Implementation of a Fast Fault Location Algorithm for Distribution network Equipment 5

Research and Implementation of a Fast Fault Location Algorit...

引用

5th International Conference on Applied Machine Learning, ICAML 2023

作者： Qiao, Junfeng Zhou, Aihua Peng, Lin Shen, Xiaofeng Pan, Sen Chen, Jingde State Grid Key Lab. of Info. Network Security of State Grid Smart Grid Research Institute Co. Ltd Jiangsu Nanjing210003 China Qingpu Power Supply Company State Grid Shanghai Municipal Electric Power Company. Shanghai201799 China

ISBN: (纸本)9798350341416

The new distribution network management system is mainly a system that integrates automation and intelligent data acquisition technology, computer technology and business management system, and manages all aspects of the electric distribution grid. The traditional fault analysis of electric distribution grid equipment is to judge the relative position relationship between the widely distributed switches and segmented switch-gear in the electric distribution grid, which can find out the real location of equipment fault through section analysis. This method has a low degree of automation. Later, through the design and development of intelligent computer programs, feeder terminal components are integrated into the conventionalizing switch in the network, through which the state data of the switch is collected, and then the collected data is transmitted to the central controller, which is identified and analyzed by the computer system. After receiving the collected data, after judgment and analysis, specific instructions are issued to operate the switch accordingly, Isolate the faulty equipment in a specific area to ensure that it does not affect other non faulty areas. In the article, a method of fault identification is proposed, which integrates the geographic location info.mation into the computer program, and then performs signal dispatching through instruction analysis to realize the operation monitoring, data signal acquisition, equipment fault location, load control, etc. of the distribution network equipment. © 2023 IEEE.

关键词： Electric power distribution

来源：评论

学校读者我要写书评

暂无评论

Control Technology of Kernel Resource Isolation for Power Intelligent IoT Terminal Operating System 4

Control Technology of Kernel Resource Isolation for Power In...

引用

4th IEEE International Conference on Renewable Energy and Power Engineering, REPE 2021

作者： Jiaxuan, Fei Xiangqun, Wang Qigui, Yao Nuannuan, Li Cen, Chen Global Ener. Interconnection Res. Inst. Co. Ltd. State Grid Key Lab. of Info. and Network Security Nanjing China State Grid Henan Elec. Power Research Institute Henan Laboratory OfInformation and Network Security Zhengzhou China

ISBN: (纸本)9781665443715

With the development of electric smart Internet of Things, electric smart Internet of Things terminals are widely used, and higher requirements are put forward for the safety of electric smart Internet of Things terminals. This paper studies the current research status of using container technology for kernel resource isolation control, and proposes a comprehensive container resource isolation protection scheme. The resource isolation and protection module of the electric supply IoT terminal container is realized through two ways of kernel security lab.l and path matching. We reported the experimental results to verify the proposed methods and demonstrated the effectiveness. © 2021 IEEE.

关键词： Containers

来源：评论

学校读者我要写书评

暂无评论

Towards Harnessing Feature Embedding for Robust Learning with Noisy lab.ls

arXiv

引用

arXiv 2022年

作者： Zhang, Chuang Shen, Li Yang, Jian Gong, Chen Pca Lab The Key Lab. of Intelligent Percept. and Syst. for High-Dimensional Info. of Ministry of Education School of Computer Science and Engineering Nanjing University of Science and Technology China Jiangsu Key Lab of Image and Video Understanding for Social Security China Jd Explore Academy China College of Computer Science Nankai University China

The memorization effect of deep neural networks (DNNs) plays a pivotal role in recent lab.l noise learning methods. To exploit this effect, the model prediction-based methods have been widely adopted, which aim to exploit the outputs of DNNs in the early stage of learning to correct noisy lab.ls. However, we observe that the model will make mistakes during lab.l prediction, resulting in unsatisfactory performance. By contrast, the produced features in the early stage of learning show better robustness. Inspired by this observation, in this paper, we propose a novel feature embedding-based method for deep learning with lab.l noise, termed lab.l NoiseDilution (LEND). To be specific, we first compute a similarity matrix based on current embedded features to capture the local structure of training data. Then, the noisy supervision signals carried by mislab.led data are overwhelmed by nearby correctly lab.led ones (i.e., lab.l noise dilution), of which the effectiveness is guaranteed by the inherent robustness of feature embedding. Finally, the training data with diluted lab.ls are further used to train a robust classifier. Empirically, we conduct extensive experiments on both synthetic and real-world noisy datasets by comparing our LEND with several representative robust learning approaches. The results verify the effectiveness of our LEND. © 2022, CC BY.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

WISERNet: Wider Separate-then-reunion network for Steganalysis of Color Images

arXiv

引用

arXiv 2018年

作者： Zeng, Jishen Tan, Shunquan Liu, Guangqing Li, Bin Huang, Jiwu Guangdong Key Laboratory of Intelligent Information Processing National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen518060 China College of Computer Science and Software Engineering Shenzhen University Guangdong Key Lab. of Intelligent Info. Processing and Shenzhen Key Laboratory of Media Security Shenzhen University Shenzhen518060 China Peng Cheng Laboratory Shenzhen518052 China

Until recently, deep steganalyzers in spatial domain have been all designed for gray-scale images. In this paper, we propose WISERNet (the wider separate-then-reunion network) for steganalysis of color images. We provide theoretical rationale to claim that the summation in normal convolution is one sort of "linear collusion attack" which reserves strong correlated patterns while impairs uncorrelated noises. Therefore in the bottom convolutional layer which aims at suppressing correlated image contents, we adopt separate channel-wise convolution without summation instead. Conversely, in the upper convolutional layers we believe that the summation in normal convolution is beneficial. Therefore we adopt united normal convolution in those layers and make them remarkably wider to reinfo.ce the effect of "linear collusion attack". As a result, our proposed wide-and-shallow, separate-then-reunion network structure is specifically suitable for color image steganalysis. We have conducted extensive experiments on color image datasets generated from BOSSBase raw images and another large-scale dataset which contains 100,000 raw images, with di_erent demosaicking algorithms and downsampling algorithms. The experimental results show that our proposed network outperforms other state-of-the-art color image steganalytic models either hand-crafted or learned using deep networks in the literature by a clear margin. Specifically, it is noted that the detection performance gain is achieved with less than half the complexity compared to the most advanced deeplearning steganalyzer as far as we know, which is scarce in the literature. Copyright © 2018, The Authors. All rights reserved.

关键词： Steganography

来源：评论

学校读者我要写书评

暂无评论

Robust Multi-Exposure Image Fusion: A Structural Patch Decomposition Approach

Robust Multi-Exposure Image Fusion: A Structural Patch Decom...

引用

作者： Ma, Kede Li, Hui Yong, Hongwei Wang, Zhou Meng, Deyu Zhang, Lei Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada Department of Computing Hong Kong Polytechnic University Hong Kong Hong Kong Department of Computing. Hong Kong Polytechnic University Hong Kong Hong Kong Institute for Information and System Sciences and Ministry of Education Key Laboratory of Intelligent Networks and Network Security Xi'an Jiaotong University Xi'an710049 China Inst. for Info. and Syst. Sci. and Min. of Educ. Key Lab. of Intelligent Networks and Netwk. Secty. Xi'an Jiaotong University Xi'an710049 China

We propose a simple yet effective structural patch decomposition approach for multi-exposure image fusion (MEF) that is robust to ghosting effect. We decompose an image patch into three conceptually independent components: signal strength, signal structure, and mean intensity. Upon fusing these three components separately, we reconstruct a desired patch and place it back into the fused image. This novel patch decomposition approach benefits MEF in many aspects. First, as opposed to most pixel-wise MEF methods, the proposed algorithm does not require post-processing steps to improve visual quality or to reduce spatial artifacts. Second, it handles RGB color channels jointly, and thus produces fused images with more vivid color appearance. Third and most importantly, the direction of the signal structure component in the patch vector space provides ideal info.mation for ghost removal. It allows us to reliably and efficiently reject inconsistent object motions with respect to a chosen reference image without performing computationally expensive motion estimation. We compare the proposed algorithm with 12 MEF methods on 21 static scenes and 12 deghosting schemes on 19 dynamic scenes (with camera and object motion). Extensive experimental results demonstrate that the proposed algorithm not only outperforms previous MEF algorithms on static scenes but also consistently produces high quality fused images with little ghosting artifacts for dynamic scenes. Moreover, it maintains a lower computational cost compared with the state-of-The-Art deghosting schemes.11The MATlab.code of the proposed algorithm will be made availab.e online. Preliminary results of Section III-A [1] were presented at the IEEE International Conference on Image Processing, Canada, 2015. © 1992-2012 IEEE.

关键词： Image fusion

来源：评论

学校读者我要写书评

暂无评论

Feature selection based on particle swarm optimal with multiple evolutionary strategies

Feature selection based on particle swarm optimal with multi...

引用

15th International Conference on info.mation Fusion, FUSION 2012

作者： Zhao, Jing Han, Chongzhao Wei, Bin Zhao, Qi Xiao, Peng Zhang, Kedai MOE Key Lab. for Intelligent Networks and Network Security School of Elect. and Info. Engineering Xi'an Jiaotong University Xi'an China System Engineering Institute Electronic and Information Engineering School Xi'an Jiaotong University Xi'an China Beijing Institute of Graphics Beijing China

ISBN: (纸本)9780982443859

Feature selection is an effective data preprocessing step to reduce the dimension of feature space and save storage space. Binary particle swarm optimization (BPSO) has been applied successfully to solve feature selection problem. But it was easy to fall into local optimal point. M2BPSO was an improved BPSO algorithm. The particles of M2BPSO were updated by using various evolutionary strategies according to the performance of them, in addition, the mutation was used to overcome premature. In this paper, we adopted M2BPSO to solve feature selection problem. To test the validity of the algorithm, we compared it with various versions of BPSO methods. Experimental results showed that M2BPSO could effectively solve the feature selection problem. © 2012 ISIF (Intl Society of info.mation Fusi).

关键词： Feature Selection

来源：评论

学校读者我要写书评

暂无评论

Distributed lite CA key management scheme in mobile Ad Hoc networks

引用

Sichuan Daxue Xuebao (Gongcheng Kexue Ban)/Journal of Sichuan University (Engineering Science Edition) 2011年第6期43卷 133-139页

作者： Han, Lei Liu, Ji-Qiang Zhao, Jia Wei, Xue-Ye School of Electronics and Info. Eng. Beijing Jiaotong Univ. Beijing 100044 China School of Computer and Info. Technol. Beijing Jiaotong Univ. Beijing 100044 China Key Lab. of Network Security and Cryptology Fujian Normal Univ. Fuzhou 35007 China

In order to solve the problem of asymmetric key management in mobile ad hoc networks, a new distributed asymmetric key management scheme based on lite CA public key authentication framework and Shamir secret sharing scheme was presented. The public key could be certified locally by the mechanism of distributed lite CA certification authentication and so the certification management was not need in the scheme. It also avoided the inherent key escrow problem in identity-based cryptography to combine with the advantages of certificateless public key cryptography and provided the ability to resist the public key substitution attacks. security analysis and experiment results showed that the scheme is secure and efficient in implementation.

关键词： Mobile ad hoc networks

来源：评论

学校读者我要写书评

暂无评论

Detection model for multi-stage attacks based on WOWA-FCM

引用

Sichuan Daxue Xuebao (Gongcheng Kexue Ban)/Journal of Sichuan University (Engineering Science Edition) 2008年第1期40卷 122-126页

作者： Lu, Zhen-Bang Zhou, Li-Hua Key Lab. for Computer Networks and Info. Security Xidian Univ. Xi'an 710071 China

In order to handle the uncertainties and complexities of multi-stage attack detection effectively, a novel detection model for multi-stage attacks based on Weighted Ordered Weighted Averaging (WOWA) and Fuzzy Cognitive Maps (FCM) was proposed. Based on Attack Intention Analysis, the WOWA-FCM detection model implemented the Cause-Effect correlation of the primary intrusion alerts along with the vulnerability and configuration info.mation of the target system utilizing Fuzzy Cognitive Maps, and implemented the effects fusion via WOWA aggregation operators. The WOWA-FCM approach was not only able to recognize the individual stages of a multi-stage attack, construct the whole attack scenario, but also able to evaluate the global attack process and the security states of the target system dynamically. The WOWA-FCM model simplified the conventional multi-stage attack detection process, and provided with a better adaptability. The effectiveness of this approach was verified by the Mstream DDoS detection experimental results.

关键词： Intrusion detection

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：