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Adaptively secure key-policy ABE scheme with fast decryption

Tongxin Xuebao/Journal on Communications 2014年 35卷 26-32页

作者： Li, Qi Ma, Jian-Feng Xiong, Jin-Bo Liu, Xi-Meng School of Computer Science and Technology Xidian University Xi'an710071 China Shaanxi Key Laboratory of Network and System Security Xidian University Xi'an710071 China Science and Technology on Communication Information Security Control Laboratory Jiaxing314033 China Faculty of Software Fujian Normal University Fuzhou350108 China School of Telecommunication Engineering Xidian University Xi'an710071 China

In the existing adaptively secure ABE (attribute-based encryption) schemes, the decryption cost goes linearly with the number of attributes that are used in decryption. An adaptively secure key-policy ABE (FKP-ABE) scheme with fast decryption is proposed, where constant size of computation overhead is implemented in decryption. This scheme is constructed on composite order bilinear groups and supports any monotonic access structure that can be expressed by LSSS (linear secret sharing schemes). The proposed scheme is proved to be adaptively secure in the standard model. ©, 2014, Editorial Board of Journal on Communications. All right reserved.

关键词： Cryptography

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Tensor and Minimum Connected Dominating Set based Confident Information Coverage Reliability Evaluation for IoT

IEEE Transactions on Sustainable Computing

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IEEE Transactions on Sustainable Computing 2024年

作者： Xiao, Ziheng Zhu, Chenlu Feng, Wei Liu, Shenghao Deng, Xianjun Lu, Hongwei Yang, Laurence T. Park, Jong Hyuk Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Hubei Wuhan430074 China Artificial Intelligence and Intelligent Transportation Joint Technical Center of HUST and Hubei Chutian Intelligent Transportation Company Ltd United States Network and Industrial Control Information Security Technology Department China Nuclear Power Operation Technology Company Ltd. 1011 Xiongchu Avenue Hubei Wuhan430070 China The Department of Computer Science and Engineering Seoul National University of Science and Technology Seoul01811 Korea Republic of

Internet of Things (IoT) reliability evaluation contributes to the sustainable computing and enhanced stability of the network. Previous algorithms usually evaluate the reliability of IoT by enumenating the states of nodes and networks, which are difficult to handle IoT with hundreds of nodes because the computational cost. In this paper, a novel algorithm, TMCRA, is proposed to evaluate the reliability of IoT in complex network environment, which consider both coverage and connectivity. For coverage, TMCRA employs the Confident Information Coverage (CIC) model to divide the target area into independent grids and calculates the coverage rate. In terms of connectivity, TMCRA forming the Virtual Backbone network (VBN) based on two proposed methods: TMA and MGIN, and evaluate connectivity by analyzing the VBN rather than the whole network. The TMA and MGIN are two algorithms for constructing Minimum Connected Dominant Sets (MCDS), which are suitable for different scale networks. Finally, based on the data of coverage and connectivity, TMCRA utilizes tensors for the unified modeling and representation of network structure, and calculates IoT reliability based on the tensors. Simulations are carried out for various sizes of IoT to show the advantages and effectiveness of the proposed approach in reliability evaluation. © 2016 IEEE.

关键词： Data reliability

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HRTS: Hierarchical Rauch-Tung-Striebel Smoother With Online Learning Priors for EEG Denoising

Journal of Network Intelligence

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Journal of network Intelligence 2024年第2期9卷 673-688页

作者： Wang, Chuan-Sheng Zhang, Ling Fu, Tian-Lin Chen, Zhao-Qi Zhang, Fu-Quan Department of Automatic Control Technical Polytechnic University of Catalonia Autonomous Region of Catalonia Barcelona Spain School of Computer and Data Science Minjiang University No.200 Xiyuangong Road Fuzhou University Town Fujian Province Fuzhou City China College of Computer and Big Data Fuzhou University No.2 Wulongjiang North Road Fuzhou University Town Fujian Province Fuzhou City China Digital Media Art Key Laboratory of Sichuan Province Sichuan Conservatory of Music Fuzhou Technology Innovation Center of Intelligent Manufacturing Information System Minjiang University No.200 Xiyuangong Road Fuzhou University Town Fujian Province Fuzhou City China Fujian Province University No.1 Campus New Village Longjiang Street Fujian Province Fuqing City China

Electroencephalogram (EEG) is a nonlinear signal that reflects the physio-logical state of the brain at different times, containing rich information. However, the possible interference during the collection and transmission process often leads to a large amount of unnecessary noise in the EEG signal. Traditional denoising methods may face difficulties in high-dimensional data processing and the inability to effectively handle different types of Gaussian white noise. To better eliminate the interference of Gaussian white noise, this article specifically adopts the Hierarchical Rauch-Tung-Striebel Smoother (HRTS) method. This method can effectively integrate the learned structural prior EEG signals into the state space model, thereby describing the relationship between EEG signals and noise. Capture the spatiotemporal characteristics of EEG signals through hierarchical modeling, and optimize the components of EEG signals through estimation and prediction of hidden variables. Finally, the mean square error (MSE) is used as an evaluation indicator to compare and evaluate the denoising results. Empirical research has shown that the HRTS algorithm can not only effectively reduce runtime and better process high-dimensional data, but also significantly improve the quality of EEG signals, effectively suppress noise interference, and more accurately reflect the characteristics of brain activity. Compared to denoising algorithms such as Kalman filtering and Kalman wavelet filtering, the HRTS algorithm has more advantages in denoising EEG signals. © 2024, J. network Intell. All rigjts reserved.

关键词： Electroencephalography

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Robotic Trajectory Planning for Non-Destructive Testing Based on Surface 3D Point Cloud Data

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Journal of Physics: Conference Series 2021年第1期1965卷

作者： Zhen Zhang Hualiang Zhang Xiaolong Yu Yongsheng Deng Zheng Chen School of mechanical engineering and automation Northeastern University Shenyang China Key laboratory of industrial control network and system Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Hangzhou innovation institute Beihang University Hangzhou China School of information engineering Shenyang University of Chemical Technology Shenyang China

Robotics has been widely used in the field of non-destructive testing in recent years. However, for complex surfaces, manual teaching or offline programming is time-consuming and difficult to ensure high precision for non-destructive testing robot trajectory planning. Therefore, this work proposes a new method to generate non-destructive testing trajectory of the robot based on the pre-processed point cloud data. The workpiece surface is measured by 3D sensor to obtain the point cloud data. The trajectory line on workpiece surface is obtained by slicing pre-processed point cloud data. The dense trajectory points are obtained by isometric discretizing trajectory lines, and then they are compressed by Douglas-Peucker algorithm. The Principal Component Analysis (PCA) method is used to estimate the normal vector of the optimized trajectory points and unify their orientation. The pose of non-destructive testing robot can be obtained by biasing the trajectory points along their normal vectors finally.

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Analysis of Electricity Loss and Electricity Consumption Law in low-Voltage Areas: A Case Study

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Journal of Physics: Conference Series 2021年第1期2022卷

作者： Xi Chen Chunhe Song Tianran Wang Key Laboratory of Network Control System Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang 110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang 110016 China University of Chinese Academy of Sciences Beijing 100049 China

Electric power is an important resource in energy. With the development of society, the consumption of electric power is more and more. Research on electricity consumption and power loss has become a hot *** this paper, we conduct statistical analysis on the power supply, power consumption and line loss rate of 395 power supply *** loss rate is an indicator to describe electricity *** found that the line loss rate decreased over the course of a *** overall distribution of line loss rate is approximately lognormal distribution. Total daily electricity supply and electricity consumption in the power supply area approximately obey exponential *** terms of electricity consumption, a statistical analysis was made on the daily electricity consumption of 100, 000 users in three years, and it was found that the electricity distribution of users was in line with the power law distribution.

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Coalition game based user association for mmWave mobile relay systems in rail traffic scenarios

arXiv

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arXiv 2021年

作者： Chen, Chen Niu, Yong Mao, Shiwen Zhang, Xiaodan Han, Zhu Ai, Bo Gao, Meilin Xiao, Huahua Wang, Ning The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-Speed Railway System Beijing Jiaotong University Beijing100044 China The National Mobile Communications Research Laboratory Southeast University Nanjing211189 China The Department of Electrical and Computer Engineering Auburn University AuburnAL36849-5201 United States The School of Management Shenzhen Institute of Information Technology Shenzhen518172 China The Department of Electrical and Computer Engineering The University of Houston HoustonTX77004 United States The Department of Computer Science and Engineering Kyung Hee University Seoul446-701 Korea Republic of The Beijing Engineering Research Center of High-Speed Railway Broadband Mobile Communications Beijing Jiaotong University Beijing100044 China The Tsinghua Space Center Tsinghua University Beijing100091 China The ZTE Corporation State Key Laboratory of Mobile Network Mobile Multimedia Technology Shenzhen518057 China The School of Information Engineering Zhengzhou University Zhengzhou450001 China

Rail transportation, especially, high-speed rails (HSR), is an important infrastructure for the development of national economy and the promotion of passenger experience. Due to the large bandwidth, millimeter wave (mmWave) communication is regarded as a promising technology to meet the demand of high data rates. However, since mmWave communication has the characteristic of high attenuation, mobile relay (MR) is considered in this paper. Also, full-duplex (FD) communications have been proposed to improve the spectral efficiency. However, because of the high speed, as well as the problem of penetration loss, passengers on the train have a poor quality of service. Consequently, an effective user association scheme for HSR in mmWave band is necessary. In this paper, we investigate the user association optimization problem in mmWave mobile relay systems where the MRs operate in the FD mode. To maximize the system capacity, we propose a cooperative user association approach based on coalition formation game, and develop a coalition formation algorithm to solve the challenging NP-hard problem. We also prove the convergence and Nash-stable property of the proposed algorithm. Extensive simulations are done to show the system performance of the proposed scheme under various network settings. It is demonstrated that the proposed distributed low complexity scheme achieves a near-optimal performance and outperforms two baseline schemes in terms of average system throughput. Copyright © 2021, The Authors. All rights reserved.

关键词： Game theory

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The design of 1553b relay circuit based on FPGA

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IOP Conference Series: Materials Science and Engineering 2020年第1期740卷

作者： Zhonghua Han Chengcheng Huang Jiayu Peng Shuai Wang Faculty of Information and Control Engineering Shenyang Jianzhu University Shenyang 110168 China Department of Digital Factory Shenyang Institute of Automation the Chinese Academy of Sciences (CAS) Shenyang 110016 China Key Laboratory of Network Control System Chinese Academy of Sciences Shenyang 110016 Liaoning China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang 110016 Liaoning China

On the basis of increasing the transmission distance of the 1553B bus, in order to maintain the simplicity and stability of the bus and improve its anti-jamming ability, the 1553B signal relay circuit based on FPGA is designed in this paper. The signal transmission part is consists of the software and the hardware, and the chip of ZYNQ series is used in the FPGA. Firstly, the transmitted signal oscillation is transformed into a group of positive and negative differential signals, which are realized by transformer (pmdb25). Secondly, the signal is sent to the main control chip of ZYNQ series through signal acquisition chip and level conversion chip. Finally, the data is processed by software program and forwarded to the receiver. The specific experiments have been done on the 1553B signal transmission platform, which significantly show that the proposed scheme is reasonable and reliable.

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Photo-Based Monitoring of Particulate Matter in the Campus: A New Strategy for Student Health

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IOP Conference Series: Earth and Environmental Science 2020年第1期555卷

作者： Yonghui Zhang Ke Gu Zhifang Xia Junfei Qiao Faculty of Information Technology Beijing University of Technology 100124 Beijing China Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education 100124 Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligent System 100124 Beijing China Beijing Artificial Intelligence Institute 100124 Beijing China State Information Center 100045 Beijing China

It is imperative for the students' future health to ensure the students in good physical levels. Recent years have witnessed the increasingly serious harm to student health caused by the continually growing concentration of Particulate Matters (PMs). Consequently, the task of preventing and controlling PM concentrations in the campus is eagerly required. A well-designed model for the monitoring of PM (as the basis for PM prevention and control) has posed a big challenge. Prior works have revealed that photo-based methods are available for the monitoring of PM. Towards validating the effectiveness of existing methods for PM monitoring in the campus, we construct a novel dataset that involves 1,500 photos collected in the Beijing University of Technology. Results confirm that stated-of-the-art methods are far from ideal for the monitoring of PM in the campus. To solve the aforesaid issue, this paper further proposes a novel photo-based PM monitoring model by using the weighted average method solved by LASSO regression to fuse the above methods' outputs tested to infer the PM values. Results demonstrate the superiority of our proposed model as compared to state-of-the-art methods on the large-scale AQPDBJUT dataset.

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2-D GCANet Applied to Denoise 1-D EEG Signals in Online Remote Teaching Scenarios

Journal of Network Intelligence

引用

Journal of network Intelligence 2023年第4期8卷 1289-1302页

作者： Huang, Ting-Qing Wang, Chuan-Sheng Chen, Zhao-Qi Zhang, Fu-Quan Meng, Xiang-Long Grau, Antoni Chen, Yang Huang, Jing-Wei College of Computer and Control Engineering Minjiang University Fuzhou University Town No. 200 Xiyuangong Road Fuzhou China Department of Automatic Control Technical Polytechnic University of Catalonia Autonomous Region of Catalonia Barcelona Spain College of Computer and Big Data Fuzhou University Fuzhou University Town No. 2 Wulong Jiangbei Avenue Fuzhou China Digital Media Art Key Laboratory of Sichuan Province Sichuan Conservatory of Music No. 2 Wannianchang Street Chenghua District Sichuan Province Chengdu City China Fuzhou Technology Innovation Center of intelligent Manufacturing information System Minjiang University Fuzhou University Town NO. 200 Xiyuangong Road Fuzhou China Fujian Province University No. 599 Quanxiu Road Juyuanzhou Ecological Civilization District Fujian Province Fuzhou City China College of Electronic Engineering Shandong University of Science and Technology No. 579 Qianwangang Road Huangdao District Qingdao China School of Mechanical and Automotive Engineering Fujian University of Technology No. 33 Xuefu South Road University New District Fujian Province Fuzhou City China

When EEG signals are used to assess the level of student engagement in online teaching tasks, they are often interfered by noise. It is a challenge to effectively remove these noises. Currently, deep learning methods have been applied to the field of EEG denoising. However, existing methods still have some problems. The denoised signals still have obvious noise residue, or the original EEG signals are damaged, and the model fitting speed is too slow. Image dehazing, as a typical denoising task in the field of image enhancement, has achieved great success in recent years. Therefore, inspired by advanced models in this field, we introduce CNN into EEG denoising tasks. In this paper, we take GCANet, an excellent image enhancement model, as an example. The dilated convolutions and gate fusion subnetworks included in GCANet enable more efficient EEG signal denoising. The results demonstrate that the proposed model effectively reduces noise while preserving essential features. Furthermore, in comparison to other state-of-the-art models, our proposed model exhibits enhanced robustness and faster convergence, as evidenced by achieving lower loss values after five epochs. Its good performance provides a new development idea for the field of EEG denoising. © 2023, Taiwan Ubiquitous Information CO LTD. All rights reserved.

关键词： Image enhancement

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Application of BIM coding and example modelling for typical asphalt pavement diseases based on Omni Class

引用

Journal of Physics: Conference Series 2021年第1期2044卷

作者： Xian Tong Li Hong Wei Zhang Zhen Zheng Liu Wan Ying Qu Zhao Hui Wu Liang Wang China Academy of Transportation Sciences Beijing 100029 China Inner Mongolia Autonomous Region Traffic Construction Engineering Quality Supervision Bureau Hohhot 0110051 China Key laboratory of Transport Industry of Management Control and Cycle Repair Technology for Traffic Network Facilitates in Ecological Security Barrier Area Hohhot 0110051 China Changchun Municipal Engineering Design & Research Institute Changchun 130000 China

With the widespread application of BIM technology in highway engineering, the practice of coding asphalt pavement diseases and integrating it with BIM models in the highway management and maintenance stage can contribute to the clarity of data collection and source-tracing of the disease and strengthening the circulation of disease data in the whole life cycle of highway engineering. This paper compares the coding methods of construction and infrastructure coding at home and abroad, and identifies the disease of asphalt pavement according to existing norms and clarifies the rules for formulating disease coding in the aim of producing a unified coding method of asphalt pavement disease. At the same time, based on the establishment of the disease model, the coding information is integrated with the BIM model to fill in the gaps in the coding work in the management and maintenance of highway engineering to improve the circulation of code-integrated BIM disease model in the maintenance phase.

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