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Fault-Tolerant Dynamical Consensus of Double-Integrator Multi-Agent Systems in the Presence of Asynchronous Self-Sensing Function Failures

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Journal of Shanghai Jiaotong university(Science) 2024年第4期29卷 613-624页

作者： WU Zhihai XIE Linbo Engineering Research center of internet of Things Technology Applications of the Ministry of Education School of Internet of Things EngineeringJiangnan UniversityWuxiJiangsu214122China

Double-integrator multi-agent systems(MASs)might not achieve dynamical consensus,even if only partial agents suffer from self-sensing function failures(SSFFs).SSFFs might be asynchronous in real engineering *** existing fault-tolerant dynamical consensus protocol suitable for synchronous SSFFs cannot be directly used to tackle fault-tolerant dynamical consensus of double-integrator MASs with partial agents subject to asynchronous *** by these facts,this paper explores a new fault-tolerant dynamical consensus protocol suitable for asynchronous ***,multi-hop communication together with the idea of treating asynchronous SSFFs as multiple piecewise synchronous SSFFs is used for recovering the connectivity of network topology among all normal ***,a fault-tolerant dynamical consensus protocol is designed for double-integrator MASs by utilizing the history information of an agent subject to SSFF for computing its own state information at the instants when its minimum-hop normal neighbor set ***,it is theoretically proved that if the strategy of network topology connectivity recovery and the fault-tolerant dynamical consensus protocol with proper time-varying gains are used simultaneously,double-integrator MASs with all normal agents and all agents subject to SSFFs can reach dynamical ***,comparison numerical simulations are given to illustrate the effectiveness of the theoretical results.

关键词： double-integrator multi-agent systems asynchronous self-sensing function failures fault-tolerant dynamical consensus network topology connectivity recovery

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Gate Feature Interaction Network for Relation Prediction in Knowledge Graph

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Data Intelligence 2024年第3期6卷 749-770页

作者： Jing Wang Shuo Zhang Runzhi Li School of computer and artificial intelligence Zhengzhou UniversityZhengzhou 450001China Cooperative Innovation center of internet Healthcare Zhengzhou UniversityZhengzhou 450052China

Recently,many knowledge graph embedding models for knowledge graph completion have been proposed,ranging from the initial translation-based model such as TransE to recent CNN-based models such as *** models fill in the missing relations between entities by focusing on capturing the representation features to further complete the existing knowledge graph(KG).However,the above KG-based relation prediction research ignores the interaction information among entities in *** solve this problem,this work proposes a novel model called Gate Feature Interaction Network(GFINet)with a weighted loss function that takes the benefit of interaction information and deep expressive features ***,the proposed GFINet consists of a gate convolution block and an interaction attention module,corresponding to catching deep expressive features and interaction information based on these valid features *** method establishes state-of-the-art experimental results on the standard datasets for knowledge graph *** addition,we make ablation experiments to verify the effectiveness of the gate convolution block and the interaction attention module.

关键词： Knowledge graph Relation prediction Gate convolution Expressive feature Interaction information

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A convolutional neural network to detect possible hidden data in spatial domain images

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Cybersecurity 2024年第1期7卷 37-52页

作者： Jean De La Croix Ntivuguruzwa Tohari Ahmad Department of Informatics Institut Teknologi Sepuluh Nopember(ITS)Kampus ITS Keputih SukoliloSurabaya60111Indonesia African center of Excellence in the internet of Things College of Science and TechnologyUniversity of Rwanda3900KigaliRwanda

Hiding secret data in digital multimedia has been essential to protect the ***,attackers with a steganalysis technique may break *** steganalysis methods have good results with conventional Machine Learning(ML)techniques;however,the introduction of Convolutional Neural Network(CNN),a deep learning paradigm,achieved better performance over the previously proposed ML-based *** the existing CNN-based approaches yield good results,they present performance issues in classification accuracy and stability in the network training *** research proposes a new method with a CNN architecture to improve the hidden data detection accuracy and the training phase stability in spatial domain *** proposed method comprises three phases:pre-processing,feature extraction,and ***,in the pre-processing phase,we use spatial rich model filters to enhance the noise within images altered by data hiding;secondly,in the feature extraction phase,we use two-dimensional depthwise separable convolutions to improve the signal-to-noise and regular convolutions to model local features;and finally,in the classification,we use multi-scale average pooling for local features aggregation and representability enhancement regardless of the input size variation,followed by three fully connected layers to form the final feature maps that we transform into class probabilities using the softmax *** results identify an improvement in the accuracy of the considered recent scheme ranging between 4.6 and 10.2%with reduced training time up to 30.81%.

关键词： Information security Spatial domain steganalysis Deep learning Convolutional neural network Infrastructure

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Edge computing oriented virtual optical network mapping scheme based on fragmentation prediction

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High Technology Letters 2024年第2期30卷 158-163页

作者：何烁 BAI Huifeng HUO Chao ZHANG Ganghong China internet Network Information center Beijing 100190P.R.China Beijing SmartChip Microelectronics Technology Company Limited Beijing 100089P.R.China

As edge computing services soar,the problem of resource fragmentation situation is greatly worsened in elastic optical networks(EON).Aimed to solve this problem,this article proposes the fragmentation prediction model that makes full use of the gate recurrent unit(GRU)*** on the fragmentation prediction model,one virtual optical network mapping scheme is presented for edge computing driven *** the minimum of fragmentation degree all over the whole EON,the virtual network mapping can be successively *** results show that the proposed approach can reduce blocking rate,and the supporting ability for virtual optical network services is greatly improved.

关键词： elastic optical networks virtual optical network fragmentation self-awareness edge computing

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Industry-Oriented Detection Method of PCBA Defects Using Semantic Segmentation Models

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1438-1446页

作者： Yang Li Xiao Wang Zhifan He Ze Wang Ke Cheng Sanchuan Ding Yijing Fan Xiaotao Li Yawen Niu Shanpeng Xiao Zhenqi Hao Bin Gao Huaqiang Wu Department of internet of Things Technology and Application China Mobile Research InstituteBeijing 100053China Beijing Advanced Innovation center for Integrated Circuits the School of Integrated CircuitTsinghua UniversityBeijing 100084China SigmaStar Technology Limited Xiamen 361199China IEEE

Automated optical inspection(AOI)is a significant process in printed circuit board assembly(PCBA)production lines which aims to detect tiny defects in *** AOI equipment has several deficiencies including low throughput,large computation cost,high latency,and poor flexibility,which limits the efficiency of online PCBA *** this paper,a novel PCBA defect detection method based on a lightweight deep convolution neural network is *** this method,the semantic segmentation model is combined with a rule-based defect recognition algorithm to build up a defect detection *** improve the performance of the model,extensive real PCBA images are collected from production lines as *** optimization methods have been applied in the model according to production demand and enable integration in lightweight computing *** results show that the production line using our method realizes a throughput more than three times higher than traditional *** method can be integrated into a lightweight inference system and pro-mote the flexibility of *** proposed method builds up a general paradigm and excellent example for model design and optimization oriented towards industrial requirements.

关键词： Automated optical inspection(AOI) deep learning defect detection printed circuit board assembly(PCBA) semantic segmentation.

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Simulation and forecasting of fishery weather based on statistical machine learning

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Information Processing in Agriculture 2024年第1期11卷 127-142页

作者： Xueqian Fu Chunyu Zhang Fuhao Chang Lingling Han Xiaolong Zhao Zhengjie Wang Qiaoyu Ma National Innovation center for Digital Fishery China Agricultural UniversityBeijingChina Key Laboratory of Smart Farming Technologies for Aquatic Animal and Livestock Ministry of Agriculture and Rural AffairsBeijingChina Beijing Engineering and Technology Research center for internet of Things in Agriculture BeijingChina College of Information and Electrical Engineering China Agricultural UniversityBeijingChina

As the new generation of artificial intelligence(AI)continues to evolve,weather big data and statistical machine learning(SML)technologies complement each other and are deeply integrated to significantly improve the processing and forecasting accuracy of fishery *** fishery weather services play a crucial role in fishery production,serving as a great safeguard for economic benefits and personal safety,enabling fishermen to carry out fishery production better,and contributing to the sustainable development of the fishery *** objective of this paper is to offer an understanding of the present state of research and development in SML technology for simulating and forecasting fishery ***,we analyze the current state of research and technical features of SML in weather and summarize the applications of SML in simulation and forecasting of fishery weather,which mainly include three aspects:fishery weather scenario generation,fishery weather forecasting,and fishery extreme weather *** also illustrate the main technical means and principles of SML ***,we summarize the most advanced SML fields and provide an outlook on their application value in the field of fishery weather.

关键词： Fishery weather Statistical machine learning Weather generation Weather forecasting Extreme weather warning

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Crop pest image recognition based on the improved ViT method Author links open overlay panel

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Information Processing in Agriculture 2024年第2期11卷 249-259页

作者： Xueqian Fu Qiaoyu Ma Feifei Yang Chunyu Zhang Xiaolong Zhao Fuhao Chang Lingling Han College of Information and Electrical Engineering China Agricultural UniversityBeijingChina National Innovation center for Digital Fishery China Agricultural UniversityBeijingChina Key Laboratory of Smart Farming Technologies for Aquatic Animal and Livestock Ministry of Agriculture and Rural AffairsBeijingChina Beijing Engineering and Technology Research center for internet of Things in Agriculture BeijingChina

The crop pests and diseases in agriculture is one of the most important reason for the reduction of bulk grain and oil crops and the decline of fruit and vegetable crop quality,which threaten macroeconomic stability and sustainable ***,the recognition method based on manual and instruments has been unable to meet the needs of scientific research and production due to its strong subjectivity and low *** recognition method based on pattern recognition and deep learning can automatically fit image features,and use features to classify and predict *** study introduced the improved Vision Transformer(ViT)method for crop pest image *** them,the region with the most obvious features can be effectively selected by block *** self-attention mechanism of the transformer can better excavate the special solution that is not an obvious lesion *** the experiment,data with 7 classes of examples are used for *** can be illustrated from results that this method has high accuracy and can give full play to the advantages of image processing and recognition technology,accurately judge the crop diseases and pests category,provide method reference for agricultural diseases and pests identification research,and further optimize the crop diseases and pests control work for agricultural workers in need.

关键词： Crop diseases recognition Fruit tree leaf disease Vision Transformer Deep learning Computer Vision

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A Correlation-Based Stochastic Model for Massive MIMO Channel

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China Communications 2024年第1期21卷 175-187页

作者： Yang Liu Gang Li Chengxiang Wang National Mobile Communications Research Laboratory School of Information Science and EngineeringSoutheast UniversityNanjing 211189China School of internet of Things Engineering Jiangnan UniversityWuxi 214122China Pervasive Communication Research center Purple Mountain LaboratoriesNanjing 211111China

In this paper,the channel impulse response matrix(CIRM)can be expressed as a sum of couplings between the steering vectors at the base station(BS)and the eigenbases at the mobile station(MS).Nakagami distribution was used to describe the fading of the coupling between the steering vectors and the *** measurements were carried out to evaluate the performance of this proposed ***,the physical implications of this model were illustrated and the capacities are *** addition,the azimuthal power spectrum(APS)of several models was ***,the channel hardening effect was simulated and *** showed that the proposed model provides a better fit to the measured results than the other CBSM,i.e.,Weichselberger ***,the proposed model can provide better tradeoff between accuracy and complexity in channel *** CIRM model can be used for massive MIMO design in the future communication system design.

关键词： CBSM channel capacity channel hardening channel modeling massive MIMO

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A CELL-centerED GODUNOV METHOD BASED ON STAGGERED DATA DISTRIBUTION,PART Ⅰ:ONE-DIMENSIONAL CASE

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Journal of Computational Mathematics 2024年第4期42卷 1172-1196页

作者： Jiayin Zhai Xiao Li Zhijun Shen Institute of Applied Physics and Computational Mathematics LCPP.O.Box 8009-26Beijing 100088China College of Big Data and internet Shenzhen Technology UniversityShenzhen 518118China center for Applied Physics and Technology HEDPSPeking UniversityChina

This paper presents a cell-centered Godunov method based on staggered data distribu-tion in Eulerian *** motivation is to reduce the intrinsic entropy dissipation of classical Godunov methods in the calculation of an isentropic or rarefaction *** the same time,the property of accurate shock capturing is also *** analyzing the factors that cause nonphysical entropy in the conventional Godunov methods,we introduce two velocities rather than a single velocity in a cell to reduce kinetic energy dissipation.A series of redistribution strategies are adopted to update subcell quantities in order to improve *** examples validate that the present method can dramatically reduce nonphysical entropy *** subject classification:35Q35,76N15,76M12.

关键词： Godunov method Riemann solver Rarefaction wave Nonphysical entropy increase.

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Low-Carbon Dispatching for Virtual Power Plant with Aggregated Distributed Energy Storage Considering Spatiotemporal Distribution of Cleanness Value

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Journal of Modern Power Systems and Clean Energy 2024年第2期12卷 346-358页

作者： Hongchao Gao Tai Jin Guanxiong Wang Qixin Chen Chongqing Kang Jingkai Zhu State Key Laboratory of Power System Operation and Control Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Sichuan Energy internet Research Institute Tsinghua University Chengdu 200016China Power Dispatching and Control center of Shanghai Municipal Electric Power Company Shanghai 200122China IEEE

The scale of distributed energy resources is increasing,but imperfect business models and value transmission mechanisms lead to low utilization ratio and poor *** address this issue,the concept of cleanness value of distributed energy storage(DES)is proposed,and the spatiotemporal distribution mechanism is discussed from the perspectives of electrical energy and *** on this,an evaluation system for the environmental benefits of DES is constructed to balance the interests between the aggregator and the power system ***,an optimal low-carbon dispatching for a virtual power plant(VPP)with aggregated DES is constructed,where-in energy value and cleanness value are both *** achieve the goal,a green attribute labeling method is used to establish a correlation constraint between the nodal carbon potential of the distribution network(DN)and DES behavior,but as a cost,it brings multiple nonlinear ***,a solution method based on the convex envelope(CE)linear re-construction method is proposed for the multivariate nonlinear programming problem,thereby improving solution efficiency and ***,the simulation verification based on the IEEE 33-bus DN is *** simulation results show that the multidimensional value recognition of DES motivates the willingness of resource users to ***,resolving the impact of DES on the nodal carbon potential can effectively alleviate overcompensation of the cleanness value.

关键词： Distributed energy storage virtual power plant(VPP) spatiotemporal distribution low-carbon dispatching

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