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23rd IEEE International Conference on Communication technology, ICCT 2023

作者： Hu, Yanzhe Feng, Chenyuan Jiang, Wei Shi, Wenzhe Feng, Daquan Shenzhen University Shenzhen Key Laboratory of Digital Creative Technology Guangdong-Hong Kong Joint Laboratory for Big Data Imaging and Communication Shenzhen China College of Information Engineering Zhejiang University of Technology Zhejiang Hangzhou China Zte Corporation State Key Laboratory of Mobile Network and Mobile Multimedia Technology China

ISBN: (纸本)9798350325959

The service time of Road-Side Units (RSUs) for vehicle users will directly affect the Quality of Service (QoS) in the Internet of Vehicles (IoV), and it is related to the traffic flow and service decisions. Consequently, a sophisticated service decision mechanism based on the traffic flow prediction is necessary beforehand in order to optimize QoS. In this work, we propose a service decision based on traffic flow prediction to reduce the service waiting time of vehicles. Firstly, we propose a traffic flow prediction model based on deep learning. Convolutional Neural network (CNN) is used to capture spatial data in order to handle the complicated road network layout in metropolitan roads. First, to reveal people's travel patterns, temporal features are captured by two different models. While short-term features are captured from historical data by Auto-Encoder, daily period feature as well as weekly period feature are captured from bi-directional data by Bidirectional Long Short-Term Memory (Bi-LSTM). Second, by simulating the process of RSUs serving vehicles using a queuing theory model, we propose a service decision mechanism based on the anticipated traffic flow. The proposed service decision mechanism aims to reduce the average waiting time of vehicles for service. Particularly, the RSUs will ask the Macro Base Station (MBS) for assistance when there are too many vehicles traveling through the RSUs. Finally, we conduct comprehensive experiments using real data to evaluate the model performance, and it is demonstrated that our proposed scheme outperforms other benchmarks. © 2023 IEEE.

关键词： Internet of Vehicles queuing theory service decision mechanism traffic flow prediction

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Differentially Private and Heterogeneity-Robust Federated Learning With Theoretical Guarantee

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第12期5卷 6369-6384页

作者： Wang, Xiuhua Wang, Shuai Li, Yiwei Fan, Fengrui Li, Shikang Lin, Xiaodong Huazhong University of Science and Technology Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Wuhan430074 China University of Electronic Science and Technology of China National Key Laboratory of Wireless Communications Chengdu611731 China Xiamen University of Technology Fujian Key Laboratory of Communication Network and Information Processing Xiamen361024 China University of Guelph School of Computer Science GuelphONN1G 2W1 Canada

Federated learning (FL) is a popular distributed paradigm where enormous clients collaboratively train a machine learning (ML) model under the orchestration of a central server without knowing the clients' private raw data. The development of effective FL algorithms faces multiple practical challenges including data heterogeneity and clients' privacy protection. Despite that numerous attempts have been made to deal with data heterogeneity or rigorous privacy protection, none have effectively tackled both issues simultaneously. In this article, we propose a differentially private and heterogeneity-robust FL algorithm, named DP-FedCVR to mitigate the data heterogeneity by following the client-variance-reduction strategy. Besides, it adopts a sophisticated differential privacy (DP) mechanism where the privacy-amplified strategy is applied, to achieve a rigorous privacy protection guarantee. We show that the proposed DP-FedCVR algorithm maintains its heterogeneity-robustness though DP noises are incorporated, while achieving a sublinear convergence rate for a nonconvex FL problem. Numerical experiments based on image classification tasks are presented to demonstrate that DP-FedCVR provides superior performance over the benchmark algorithms in the presence of data heterogeneity and various DP privacy budgets. © 2020 IEEE.

关键词： Federated learning

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Unveiling the corrosion evolution and pitting mechanism of X70 pipeline steel in typical near-neutral/bentonite soil environment

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Journal of Materials Science & technology 2025年

作者： Guangming Yang Lulu Zeng Hua Shen Huaiyun Cui Tianqi Chen Zengyao Chen Chengwei Xu Chao Liu Feng Huang Zhiyong Liu Zhichao Che Cuiwei Du Xiaogang Li Key Laboratory for Corrosion and Protection (MOE) Institute of Advanced Materials and Technology University of Science and Technology Beijing Beijing 100083 China National Materials Corrosion and Protection Scientific Data Center University of Science and Technology Beijing Beijing 100083 China Jilin Oilfield Company China National Petroleum Corporation Songyuan 138000 China Corrosion and control Research Center Branch of Science and Technology Research Institute of National Oil and Gas Pipeline Network Group Co Tianjin 300457 China The State Key Laboratory of Refractories and Metallurgy Wuhan University of Science and Technology Wuhan 430081 China School of Metallurgical and Ecological Engineering University of Science and Technology Beijing Beijing 100083 China

This work investigated the effect of dissolved oxygen (DO) on the corrosion behavior and pitting mechanism of X70 pipeline steel in near-neutral soil-bentonite simulated environment. The localized corrosion evolution to uniform corrosion was quantitatively analyzed using statistical methods. In situ characterization reveals that the localized corrosion mechanism is induced by core-shell inclusions. The microcracks occur between MnS and core oxides, the galvanic effect exists between MnS and matrix, and the high distortion region of the matrix promotes the localized corrosion initiation, while the galvanic effect between ferrite and pearlite aids propagation. Interestingly, the pitting growth rates are higher at low DO concentrations. Furthermore, the lower DO and longer immersion time enhance rust layer protection and reduce the corrosion rate of X70 pipeline steel.

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Microbiologically Influenced Corrosion Behavior of Fe_(40)(CoCrMnNi)_(60) and Fe_(60)(CoCrMnNi)_(40) Medium Entropy Alloys in the Presence of Pseudomonas Aeruginosa

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Acta Metallurgica Sinica(English Letters) 2023年第3期36卷 379-390页

作者： Weiwei Chang Yangyang Li Huaibei Zheng Hongchang Qian Dawei Guo Shuyuan Zhang Yuntian Lou Chi Tat Kwok Lap Mou Tam Dawei Zhang National Materials Corrosion and Protection Data Center Institute for Advanced Materials and TechnologyUniversity of Science and Technology BeijingBeijing 100083China BRI Southeast Asia Network for Corrosion and Protection(MOE) Shunde Graduate School of University of Science and Technology BeijingFoshan 528399China State Key Laboratory of Metal Material for Marine Equipment and Application Anshan 114002China Department of Electromechanical Engineering University of MacaoMacao 999078China Institute for the Development and Quality Macao 999078China

In this work,the microbiologically influenced corrosion(MIC)of Fe_(40)(CoCrMnNi)_(60) and Fe_(60)(CoCrMnNi)_(40) medium entropy alloys(MEAs)induced by Pseudomonas aeruginosa(***)was *** behaviors during 14 days of immersion in sterile and ***-inoculated culture media are *** sterile conditions,both MEAs exhibited good corrosion resistance against the culture medium *** the presence of ***,the pitting corrosion of MEAs was *** results of inductively coupled plasma‒mass spectrometry(ICP‒MS)and potentiodynamic polarization tests showed that the presence of *** promoted the selective dissolution of passive film and accelerated the corrosion of *** results of X-ray photoelectron spectroscopy(XPS)and Mott-Schottky measurements further demonstrated the degradation effect of *** on the passive *** with Fe_(60)(CoCrMnNi)_(40),Fe_(40)(CoCrMnNi)_(60) manifested better resistance to the MIC caused by ***,which may be attributed to more Cr oxides and fewer Fe oxides of the passive film.

关键词： Microbiologically influenced corrosion Medium entropy alloys Pseudomonas aeruginosa

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Efficient and random oracle-free conditionally anonymous ring signature

Efficient and random oracle-free conditionally anonymous rin...

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6th International Conference on Provable Security, ProvSec 2012

作者： Zeng, Shengke Qin, Zhiguang Lu, Qing Li, Qinyi School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu 611731 China Network and Data Security Key Laboratory of Sichuan Province China Shanghai Key Laboratory of Integrate Administration Technologies for Information Security China

ISBN: (纸本)9783642332715

Compared to conventional ring signature schemes, conditionally anonymous ring signatures allow to revoke the anonymity of actual signer without the group manager's help if necessary. When the actual signer intends to confirm his role, it can be proved by a confirmation algorithm. In addition, any user, who is in a ring but not signer, can claim this through a disavowal algorithm. There were several proposals which were proved secure in random oracles. In other words, the security of such schemes depends on the randomness of hash functions. Recently, Zeng et al. proposed a generic construction of conditionally anonymous ring signature scheme without random oracles. Their scheme relies on NIZKs and pseudorandom functions, which render it to be inefficient. This paper proposes a practical ring signature scheme with traceability without random oracles in the common reference string model. © 2012 Springer-Verlag.

关键词： Hash functions

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A feature extraction with pose-auxiliary method for Person Reidentification 2

A feature extraction with pose-auxiliary method for Person R...

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2nd International Conference on Advanced Algorithms and Signal Image Processing, AASIP 2022

作者： Ma, ZePing Network and Data Security Key Laboratory of Sichuan Province University of Electronic Science and Technology of China Sichuan Chengdu610054 China School of Information and Software Engineering University of Electronic Science and Technology of China Sichuan Chengdu610054 China

ISBN: (纸本)9781510660571

Person re-identification is widely considered as a sub problem of image retrieval. It is a technology that uses computer vision technology to determine whether there is a specific pedestrian in an image or video, given a monitored pedestrian image, the pedestrian image under the cross device is retrieved. Many researches have been made to study how to match one people from two picture, but how to locating proper body parts has become a problem which could lead to misalign and wrongly divided sample. To solve this problem, we introduce a pose-auxiliary network to extract the position feature of pedestrian. We use a post estimation network to estimate the person's body location, then we decide whether it's a body part or a static obstacle by using a separated trained classifier. Then we compare these features from two picture and calculate their loss. Meanwhile, we use a graph-matching strategy to compare two pedestrians pose structure, which is also used into jugging the match problem. By using a multi-verification strategy, our method has some improvement than some previous study using Market-1501 and DukeMTMC-Reid datasets, but still remains room for improvement. © 2022 SPIE.

关键词： Image retrieval

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Recent advances in ethanol gas sensors based on metal oxide semiconductor heterojunctions

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Rare Metals 2022年第6期41卷 1818-1842页

作者： Ling-Yun Gai Run-Ping Lai Xian-Hui Dong Xing Wu Qiao-Tong Luan Jue Wang Hao-Feng Lin Wen-Hao Ding Guang-Lei Wu Wan-Feng Xie Big Data and Network Management Center Qingdao Agricultural UniversityQingdao 266109China School of Mechanical Electronic and Information Engineering China University of Mining and Technology-BeijingBeijing 10083China School of Material Science and Engineering State Key Laboratory of Bio-Fibers and Eco-TextilesQingdao UniversityQingdao 266071China School of Electronics and Information State Key Laboratory of Bio-Fibers and Eco-TextilesQingdao UniversityQingdao 266071China Shanghai Key Laboratory of Multidimensional Information Processing School of Communication and Electronic EngineeringEast China Normal UniversityShanghai 200241China

Metal oxide semiconductor heterojunctions(MOSHs)can enhance the performance of ethanol gas sen-sors *** gas sensors based on MOSHs are cost-effective and have excellent sensing response,good selectivity,fast response and recovery,long-term stability or repeatability,a low operating temperature,a facile fabrica-tion process,and versatile *** paper reviews the recent advances in gas sensors that are based on MOSHs and the advantages of using them to detect ethanol *** to the literature,compared with ethanol gas sen-sors that use single-component sensing materials,the MOSHs exhibit superior performance due to the synergy between the different components,which can amplify the reception and transduction components of the sensor *** the best of our knowledge,heterojunctions can be grouped into four main categories as metal oxide/metal oxide,metal oxide/metal sulfide,metal oxide/noble metal,and metal oxide/other materials,including rare-earth metals,g-C_(3)N_(4),and graphene,*** future trends and challenges that would be faced in the development of ethanol gas sensors based on MOSHs are discussed in ***,critical ideas and thinking regarding the future progress of MOSH-based gas sensors are presented.

关键词： Metal oxides Heterojunction Chemiresistori Ethanol sensor Synergistic behavior

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Recent advances on environmental corrosion behavior and mechanism of high-entropy alloys

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Journal of Materials Science & technology 2021年第21期80卷 217-233页

作者： Yu Fu Jun Li Hong Luo Cuiwei Du Xiaogang Li Institute for Advanced Materials and Technology University of Science and Technology BeijingBeijingJ 00083China Key Laboratory for Corrosion and Protection of The Ministry of Education(MOE) Beijing100083China Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology BeijingBeijing100083China National Materials Corrosion and Protection Scientific Data Center Institute for Advanced Materials and TechnologyUniversity of Science and Technology BeijingBeijing100083China BRI Southeast Asia Network for Corrosion and Protection(MOE) Shunde Graduate School of University of Science and Technology BeijingFoshan528000China

In the past decade, the sudden rise of high-entropy alloys(HEAs) has become a research hotspot in the domain of metal materials. HEAs break through the design concept of traditional single-principal element alloys, and the four core effects, especially the high entropy and cocktail effects, make HEAs exhibit much better corrosion resistance than traditional corrosion-resistant metal materials, e.g., stainless steels, copper-nickel alloys, and high-nickel alloys. Currently, the corrosion resistance of HEAs causes great concern in the field of corrosion research. This article reviews the corrosion behavior and mechanism of HEAs in various aqueous solutions, revealing the correlation among the composition, microstructure and corrosion resistance of HEAs, and elaborates the influence of heat treatment, anodizing treatment and preparation methods on the corrosion behavior of HEAs. This knowledge will benefit the on-demand design of corrosion-resistant HEAs, which is an important trend of future development. Finally, perspectives regarding the corrosion research of HEAs are outlined to guide future studies.

关键词： High-entropy alloys Corrosion behavior Corrosion mechanism Passive film Alloy design

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Secure real-time image protection scheme with near-duplicate detection in cloud computing

Secure real-time image protection scheme with near-duplicate...

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作者： Liu, Dengzhi Shen, Jian Wang, Anxi Wang, Chen Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing210044 China State Key Laboratory of Cryptology Beijing100878 China Guizhou Provincial Key Laboratory of Public Big Data Guiyang550025 China

With advancements in technologies of the Internet and multi-media, various images need to be generated and transmitted anytime. Restricted by local constrained storage space, users can store their images with the assist of the cloud. However, the cloud is a remote semi-trusted party that may extract stored images for adversaries due to monetary reasons. In this paper, a secure real-time image protection scheme is proposed, which can be used to enhance the security of the stored images in cloud computing. Moreover, the convergent encryption is used to construct our scheme, which can provide functionalities of image deduplication checking and near-duplicate detection for the image owner. To improve the efficiency of the near-duplicate detection, deep learning is exploited in our scheme to extract images. Security analysis indicates that the proposed scheme can meet the security requirements of correctness and security. Performance analysis shows that the proposed scheme can be performed with low computational cost. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Cloud computing

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Memory-efficient GPU-based exact and parallel triangle counting in large graphs 21

Memory-efficient GPU-based exact and parallel triangle count...

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21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on data Science and Systems, HPCC/SmartCity/DSS 2019

作者： Ouyang, Zhiyou Wu, Shanni Zhao, Tongtong Yue, Dong Zhang, Tengfei Institute of Advanced Technology School of Automation Nanjing University of Posts and Telecommunications Nanjing210003 China School of Computer Nanjing University of Posts and Telecommunications Nanjing China Institute of Advanced Technology School of Automation Jiangsu Engineering Laboratory of Big Data Analysis and Control for Active Distribution Network Nanjing University of Posts and Telecommunications Nanjing China School of Automation Jiangsu Engineering Laboratory of Big Data Analysis and Control for Active Distribution Network Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9781728120584

Triangle counting is one of the basic research topics in many practical problems, such as clustering coefficients, transitivity ratio and traffic network complexity, etc., all of which can be converted into triangle counting issues. In this paper, a memory efficient GPU-based parallel triangle counting algorithm is proposed for large undirected graphs, which based on Polak's parallel forward triangle counting algorithm and improved the algorithm flow, edges sorting and triangle counting kernel function to increase the memory usage efficiency and run time performance. Algorithm comparison with the description of proposed algorithm steps and the implementation details is also introduced in the paper. Performance evaluations show that the proposed algorithm achieves 5 to 10 times speedup over the existing parallel forward algorithm, moreover, the GPU memory usage is reduced to a maximum of 50% compared to the existing algorithm. © 2019 IEEE.

关键词： Graphics processing unit

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