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An efficient wear-leveling-aware multi-grained allocator for persistent memory file systems

Frontiers of Information technology & Electronic Engineering 2023年第5期24卷 688-702页

作者： Zhiwang YU Runyu ZHANG Chaoshu YANG Shun NIE Duo LIU State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang 550000China College of Computer Science Chongqing UniversityChongqing 404100China

Persistent memory(PM)file systems have been developed to achieve high performance by exploiting the advanced features of PMs,including nonvolatility,byte addressability,and dynamic random access memory(DRAM)like ***,these PMs suffer from limited write *** space management strategies of PM file systems can induce a severely unbalanced wear problem,which can damage the underlying PMs *** this paper,we propose a Wear-leveling-aware Multi-grained Allocator,called WMAlloc,to achieve the wear leveling of PMs while improving the performance of file *** adopts multiple min-heaps to manage the unused space of *** heap represents an allocation ***,WMAlloc allocates less-worn blocks from the corresponding min-heap for allocation ***,to avoid recursive split and inefficient heap locations in WMAlloc,we further propose a bitmap-based multi-heap tree(BMT)to enhance WMAlloc,namely,*** implement WMAlloc and WMAlloc-BMT in the Linux kernel based on NOVA,a typical PM file *** results show that,compared with the original NOVA and dynamic wear-aware range management(DWARM),which is the state-of-the-art wear-leveling-aware allocator of PM file systems,WMAlloc can,respectively,achieve 4.11×and 1.81×maximum write number reduction and 1.02×and 1.64×performance with four workloads on ***,WMAlloc-BMT outperforms WMAlloc with 1.08×performance and achieves 1.17×maximum write number reduction with four workloads on average.

关键词： File system Persistent memory Wear-leveling Multi-grained allocator

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Design of Wrist Rehabilitation Robot 12

Design of Wrist Rehabilitation Robot

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12th International Conference on Information technology in Medicine and Education, ITME 2022

作者： Zhenfeng, Wang Key Laboratory of Big Data and Artificial Intelligence in University of Fujian Province MinNan Science and Technology University Quanzhou China

ISBN: (纸本)9798350310153

We have developed a wrist rehabilitation manipulator to help patients with wrist injuries during exercise achieve sustained and standardized rehabilitation. Based on the theory of rehabilitation medicine, a 3RRP spherical parallel three-dimensional exoskeleton repair manipulator was developed. According to the principle of ergonomics, the shape safety of the robot was optimized. The virtual prototype system is used to simulate the rehabilitation manipulator and MATLAB is used to operate the recovery manipulator. The simulation results show that the designed manipulator has three degrees of freedom, which can meet our needs. The working area is part of the spherical area, and there is no cavity. The appearance, color and humanistic dimension can enable patients to obtain better treatment experience. Conclusion: It provides some basis for the industrial design of manipulator. © 2022 IEEE.

关键词： Manipulators

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Enclosing control of heterogeneous multi-agent systems

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Kongzhi yu Juece/Control and Decision 2024年第7期39卷 2267-2274页

作者： Jia, Ya-Peng Zhao, Qi Zheng, Yuan-Shi School of Mechanical and Electrical Engineering Xidian University Xi’an710071 China College of Big Data Qingdao University of Science and Technology Qingdao266061 China

We investigate the enclosing control problem of heterogeneous multi-agent systems composed of first-order and second-order dynamical agents in fixed directed topologies. Firstly, four effective control protocols are proposed for the two cases in which the system contains both first-order dynamical leaders and second-order dynamical followers, second-order dynamical leaders and first-order dynamical followers, respectively. Then, by using algebraic graph theory, matrix theory and stability analysis tools, the criteria for the above two types of heterogeneous multi-agent systems to achieve enclosing control are obtained through the system transformation method or the error vector construction method. Finally, the effectiveness of the proposed protocols is further verified by simulations. © 2024 Northeast University. All rights reserved.

关键词： Multi agent systems

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Source Camera Identification Algorithm Based on Multi-Scale Feature Fusion

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Computers, Materials & Continua 2024年第8期80卷 3047-3065页

作者： Jianfeng Lu Caijin Li Xiangye Huang Chen Cui Mahmoud Emam School of Computer Science and Technology Hangzhou Dianzi UniversityHangzhou310018China Shangyu Institute of Science and Engineering Hangzhou Dianzi UniversityShaoxing312300China Key Laboratory of Public Security Information Application Based on Big-Data Architecture Ministry of Public SecurityZhejiang Police CollegeHangzhou310000China Faculty of Artificial Intelligence Menoufia UniversityShebin El-Koom32511Egypt

The widespread availability of digital multimedia data has led to a new challenge in digital *** source camera identification algorithms usually rely on various traces in the capturing ***,these traces have become increasingly difficult to extract due to wide availability of various image processing *** Neural Networks(CNN)-based algorithms have demonstrated good discriminative capabilities for different brands and even different models of camera ***,their performances is not ideal in case of distinguishing between individual devices of the same model,because cameras of the same model typically use the same optical lens,image sensor,and image processing algorithms,that result in minimal overall *** this paper,we propose a camera forensics algorithm based on multi-scale feature fusion to address these *** proposed algorithm extracts different local features from feature maps of different scales and then fuses them to obtain a comprehensive feature *** representation is then fed into a subsequent camera fingerprint classification *** upon the Swin-T network,we utilize Transformer Blocks and Graph Convolutional Network(GCN)modules to fuse multi-scale features from different stages of the backbone ***,we conduct experiments on established datasets to demonstrate the feasibility and effectiveness of the proposed approach.

关键词： Source camera identification camera forensics convolutional neural network feature fusion transformer block graph convolutional network

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Message Verification Protocol Based on Bilinear Pairings and Elliptic Curves for Enhanced Security in Vehicular Ad Hoc Networks

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Computers, Materials & Continua 2024年第10期81卷 1029-1057页

作者： Vincent Omollo Nyangaresi Arkan A.Ghaib Hend Muslim Jasim Zaid Ameen Abduljabbar Junchao Ma Mustafa A.Al Sibahee Abdulla J.Y.Aldarwish Ali Hasan Ali Husam A.Neamah Department of Computer Science and Software Engineering Jaramogi Oginga Odinga University of Science and TechnologyBondo40601Kenya Department of Applied Electronics Saveetha School of EngineeringSIMATSChennaiTamilnadu602105India Information Technology Department Management Technical CollegeSouthern Technical UniversityBasrah61004Iraq Department of Computer Science College of Education for Pure SciencesUniversity of BasrahBasrah61004Iraq College of Big Data and Internet Shenzhen Technology UniversityShenzhen518118China Huazhong University of Science and Technology Shenzhen InstituteShenzhen518000China National Engineering Laboratory for Big Data System Computing Technology Shenzhen UniversityShenzhen518060China Computer Technology Engineering Department Iraq University CollegeBasrah61004Iraq Department of Mathematics College of Education for Pure SciencesUniversity of BasrahBasrah61004Iraq Institute of Mathematics University of DebrecenDebrecenH-4002Hungary Department of Electrical Engineering and Mechatronics Faculty of EngineeringUniversity of DebrecenDebrecen4028Hungary

Vehicular ad hoc networks(VANETs)provide intelligent navigation and efficient route management,resulting in time savings and cost reductions in the transportation ***,the exchange of beacons and messages over public channels among vehicles and roadside units renders these networks vulnerable to numerous attacks and privacy *** address these challenges,several privacy and security preservation protocols based on blockchain and public key cryptography have been proposed ***,most of these schemes are limited by a long execution time and massive communication costs,which make them inefficient for on-board units(OBUs).Additionally,some of them are still susceptible to many *** such,this study presents a novel protocol based on the fusion of elliptic curve cryptography(ECC)and bilinear pairing(BP)*** formal security analysis is accomplished using the Burrows–Abadi–Needham(BAN)logic,demonstrating that our scheme is verifiably *** proposed scheme’s informal security assessment also shows that it provides salient security features,such as non-repudiation,anonymity,and ***,the scheme is shown to be resilient against attacks,such as packet replays,forgeries,message falsifications,and *** the performance perspective,this protocol yields a 37.88%reduction in communication overheads and a 44.44%improvement in the supported security ***,the proposed scheme can be deployed in VANETs to provide robust security at low overheads.

关键词： Attacks bilinear elliptic curve cryptography(ECC) privacy security vehicular ad hoc network(VANET)

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Optimal Structure Exploration of Bayesian Network Based on Dealing with the Route Choice Model 6

Optimal Structure Exploration of Bayesian Network Based on D...

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6th International Conference on Computer Information science and Application technology, CISAT 2023

作者： Wang, Ziyi Zeng, Yufei Wang, Rui College of Big Data and Intelligent Engineering Southwest Forestry University Kunming China College of Computer Science and Technology Harbin Institute of Technology Yichun China Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China

ISBN: (纸本)9781510668546

Route selection in residents' travel is a key link in travel decision-making in transportation systems. In existing studies, discrete choice models are often used to describe residents' travel path choices. However， with today's highly developed big data, the traditional discrete choice model is too simple to represent residents' travel path choices, ignoring the connection between various factors. Therefore, a big data-driven approach is proposed to solve this problem in this paper. Driven by research data and with the introduction of the Bayesian network model, the paper adopts a hill-climbing search strategy to improve the search efficiency, uses a variety of scoring functions to train data, which optimizes the Bayesian network structure. The experimental results show that the model fully considers the causation between the independent variables, which is more logical and makes the construction of the resident travel route selection model more accurate and efficient. © 2023 SPIE.

关键词： Bayesian networks

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Knowledge Distillation Facilitates the Lightweight and Efficient Plant Diseases Detection Model

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Plant Phenomics 2023年第3期5卷 501-519页

作者： Qianding Huang Xingcai Wu Qi Wang Xinyu Dong Yongbin Qin Xue Wu Yangyang Gao Gefei Hao State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang 550025China Text Computing&Cognitive Intelligence Engineering Research Center of National Education Ministry Guizhou UniversityGuiyang 550025China National Key Laboratory of Green Pesticide Guizhou UniversityGuiyang 550025China

Plant disease diagnosis in time can inhibit the spread of the disease and prevent a large-scale drop in production,which benefits food *** detection-based plant disease diagnosis methods have attracted widespread attention due to their accuracy in classifying and locating ***,existing methods are still limited to single crop disease *** importantly,the existing model has a large number of parameters,which is not conducive to deploying it to agricultural mobile ***,reducing the number of model parameters tends to cause a decrease in model *** solve these problems,we propose a plant disease detection method based on knowledge distillation to achieve a lightweight and efficient diagnosis of multiple diseases across multiple *** detail,we design 2 strategies to build 4 different lightweight models as student models:the YOLOR-Light-v1,YOLOR-Light-v2,Mobile-YOLOR-v1,and Mobile-YOLOR-v2 models,and adopt the YOLOR model as the teacher *** develop a multistage knowledge distillation method to improve lightweight model performance,achieving 60.4%mAP@.5 in the PlantDoc dataset with small model parameters,outperforming existing ***,the multistage knowledge distillation technique can make the model lighter while maintaining high *** only that,the technique can be extended to other tasks,such as image classification and image segmentation,to obtain automated plant disease diagnostic models with a wider range of lightweight applicability in smart *** code is available at https://***/QDH/MSKD.

关键词： Plant diagnosis image

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Explore augmented reality and deep feature learning to visual field operation and maintenance for electric power equipment

Explore augmented reality and deep feature learning to visua...

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2024 International Conference on Automation Control, Algorithm, and Intelligent Bionics, ACAIB 2024

作者： Yuan, Qi Feng, Jianfeng Yan, Nannan Xue, Xiangyang Shen, Bin Yang, Yongcheng Liu, Ziqi Zhou, Yunjie Yuan, Jialiang State Grid Shanghai Electric Power Company Shanghai200122 China School of Big Data Institute of Brain-Like Intelligence Science and Technology Fudan University Shanghai200433 China Institute of Brain and Intelligence Science and Technology School of Computer Science Fudan University Shanghai200433 China

ISBN: (纸本)9781510682597

This work mainly studies the visual field operation and maintenance method based on human-computer interaction, and establishes the field operation and maintenance management module through the deep image feature analysis method to realize the operation and maintenance function of augmented reality (AR) intelligent devices. For the on-site electricity inspection, the visual image feature mining model based on deep convolutional neural network is established. The basic information, operation condition, box condition, etc. of the field collection and metering equipment for regular inspection needs to be recorded and uploaded to the deep network model for analysis. The experimental results show that the proposed method has high efficiency in equipment operation and maintenance. © 2024 SPIE.

关键词： Inspection equipment

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Face anti-spoofing based on multi-modal and multi-scale features fusion

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The Journal of China Universities of Posts and Telecommunications 2022年第6期29卷 73-82页

作者： Kong Chao Ou Weihua Gong Xiaofeng Li Weian Han Jie Yao Yi Xiong Jiahao School of Big Data and Computer Science Guizhou Normal UniversityGuiyang 550025China Special Key Laboratory of Artificial Intelligence and Intelligent Control of Guizhou Province Guizhou Institute of TechnologyGuiyang 550003China Guizhou Science and Technology Information Center Department of Science and Technology of Guizhou ProvinceGuiyang 550002China

Face anti-spoofing is used to assist face recognition system to judge whether the detected face is real face or fake face. In the traditional face anti-spoofing methods, features extracted by hand are used to describe the difference between living face and fraudulent face. But these handmade features do not apply to different variations in an unconstrained environment. The convolutional neural network(CNN) for face deceptions achieves considerable results. However, most existing neural network-based methods simply use neural networks to extract single-scale features from single-modal data, while ignoring multi-scale and multi-modal information. To address this problem, a novel face anti-spoofing method based on multi-modal and multi-scale features fusion(MMFF) is proposed. Specifically, first residual network(Resnet)-34 is adopted to extract features of different scales from each modality, then these features of different scales are fused by feature pyramid network(FPN), finally squeeze-and-excitation fusion(SEF) module and self-attention network(SAN) are combined to fuse features from different modalities for classification. Experiments on the CASIA-SURF dataset show that the new method based on MMFF achieves better performance compared with most existing methods.

关键词： face anti-spoofing multi-modal fusion multi-scale fusion self-attention network(SAN) feature pyramid network(FPN)

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Inductive Relation Prediction with Logical Reasoning Using Contrastive Representations

Inductive Relation Prediction with Logical Reasoning Using C...

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2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022

作者： Pan, Yudai Liu, Jun Zhang, Lingling Zhao, Tianzhe Lin, Qika Hu, Xin Wang, Qianying School of Computer Science and Technology Xi'an Jiaotong University China National Engineering Lab for Big Data Analytics China Shaanxi Provincial Key Laboratory of Big Data Knowledge Engineering China Lenovo Research Beijing China

Relation prediction in knowledge graphs (KGs) aims at predicting missing relations in incomplete triples, whereas the dominant embedding paradigm has a restriction on handling unseen entities during testing. In the real-world scenario, the inductive setting is more common because entities in the training process are finite. Previous methods capture an inductive ability by implicit logic in KGs. However, it would be challenging to preciously acquire entity-independent relational semantics of compositional logic rules and to deal with the deficient supervision of logic caused by the scarcity of relational semantics. To this end, we propose a novel graph convolutional network (GCN)-based model LogCo with logical reasoning by contrastive representations. LogCo firstly extracts enclosing subgraphs and relational paths between two entities to supply the entity-independence. Then a contrastive strategy for relational path instances and the subgraph is proposed for the issue of deficient supervision. The contrastive representations are learned for a joint training regime. Finally, prediction results and logic rules for reasoning are attained. Comprehensive experiments on twelve inductive datasets show that LogCo achieves outstanding performance comparing with SOTA inductive baselines. © 2022 Association for Computational Linguistics.

关键词： Forecasting

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