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Bayesian Filtering for High-Dimensional State-Space Models With State Partition and Error Compensation

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1239-1249页

作者： ke Li Shunyi Zhao Biao Huang Fei Liu key Laboratory of Advanced Process Control for Light Industry(Ministry of Education) Institute of AutomationJiangnan UniversityWuxi 214122China Department of Chemical and Materials Engineering University of AlbertaEdmonton AB T6G 2G6Canada

In the era of exponential growth of data availability,the architecture of systems has a trend toward high dimensionality,and directly exploiting holistic information for state inference is not always computationally *** paper proposes a novel Bayesian filtering algorithm that considers algorithmic computational cost and estimation accuracy for high-dimensional linear *** high-dimensional state vector is divided into several blocks to save computation resources by avoiding the calculation of error covariance with immense *** that,two sequential states are estimated simultaneously by introducing an auxiliary variable in the new probability space,mitigating the performance degradation caused by state ***,the computational cost and error covariance of the proposed algorithm are analyzed analytically to show its distinct features compared with several existing *** results illustrate that the proposed Bayesian filtering can maintain a higher estimation accuracy with reasonable computational cost when applied to high-dimensional linear systems.

关键词： filtering estimation error

Analyzing topics in social media for improving digital twinning based product development

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Digital Communications and Networks 2024年第2期10卷 273-281页

作者： Wenyi Tang Ling Tian Xu Zheng ke Yan School of Computer Science and Engineering University of Electronic Science and Technology of ChinaChengdu611731China

Digital twinning enables manufacturers to create digital representations of physical entities,thus implementing virtual simulations for product *** efforts of digital twinning neglect the decisive consumer feedback in product development stages,failing to cover the gap between physical and digital *** work mines real-world consumer feedbacks through social media topics,which is significant to product *** specifically analyze the prevalent time of a product topic,giving an insight into both consumer attention and the widely-discussed time of a *** primary body of current studies regards the prevalent time prediction as an accompanying task or assumes the existence of a preset ***,these proposed solutions are either biased in focused objectives and underlying patterns or weak in the capability of generalization towards diverse *** this end,this work combines deep learning and survival analysis to predict the prevalent time of *** propose a specialized deep survival model which consists of two *** first module enriches input covariates by incorporating latent features of the time-varying text,and the second module fully captures the temporal pattern of a rumor by a recurrent network ***,a specific loss function different from regular survival models is proposed to achieve a more reasonable *** experiments on real-world datasets demonstrate that our model significantly outperforms the state-of-the-art methods.

关键词： Digital twinning Product development Topic analysis Social media

Photoinduced superlubricity on TiO_(2) surfaces

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Friction 2024年第3期12卷 428-438页

作者： ke HAN Liran MA Yu TIAN Jianbin LUO State key Laboratory of Tribology in Advanced Equipment Tsinghua UniversityBeijing 100084China Received:16 September 2022/Revised:28 October 2022/Accepted:27 December 2022The author(s)2022.

Superlubricity control is of great interest in both industry and scientific research,and several methods have been proposed to achieve this *** this work,ultraviolet(UV)light was introduced into titanium dioxide(TiO_(2))and silicon nitride(Si_(3)N_(4))tribosystems to accomplish photoinduced *** friction coefficients(COFs)between Si_(3)N_(4) balls and TiO_(2) plates in the mixtures of sulfuric acid(H^(2)SO_(4))solution and glycerol solution were obviously reduced,and the system entered the superlubricity region(COFkey to the photoinduced superlubricity in this *** findings showed one method for achieving superlubricity by introducing a light field that could be further applied to special working conditions.

关键词： light control friction superlubricity glycerol titanium dioxide(TiO_(2))

A quantum-enhanced magnetometer using a single high-spin nucleus in silicon

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Chinese Physics B 2024年第9期33卷 110-115页

作者： Tao Xin ke Zhang Jun Li Shenzhen Institute for Quantum Science and Engineering Southern University of Science and TechnologyShenzhen 518055China Guangdong Provincial key Laboratory of Quantum Science and Engineering Southern University of Science and TechnologyShenzhen 518055China Physikalisch-Technische Bundesanstalt Bundesallee 10038116 BraunschweigGermany Institute of Quantum Precision Measurement State Key Laboratory of Radio Frequency Heterogeneous IntegrationShenzhen UniversityShenzhen 518060China College of Physics and Optoelectronic Engineering Shenzhen UniversityShenzhen 518060China

Quantum enhanced metrology has the potential to go beyond the standard quantum limit and eventually to the ultimate Heisenberg *** particular,quantum probes prepared in nonclassical coherent states have recently been recognized as a useful resource for ***,there has been considerable interest in constructing magnetic quantum sensors that combine high resolution and high ***,we explore a nanoscale magnetometer with quantum-enhanced sensitivity,based on 123Sb(I=7/2)nuclear spin doped in silicon,that takes advantage of techniques of spin-squeezing and coherent *** the optimal squeezed initial state,the magnetic field sensitivity may be expected to approach 6 aT·Hz^(−1/2)·cm^(−3/2) and 603 nT·Hz^(−1/2) at the single-spin *** magnetic sensor may provide a novel sensitive and high-resolution route to microscopic mapping of magnetic fields as well as other applications.

关键词： quantum magnetometer silicon quantum qubit nuclear electrical resonance

Multi-Perspective Data Fusion Framework Based on Hierarchical BERT: Provide Visual Predictions of Business Processes

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Computers, Materials & Continua 2024年第1期78卷 1227-1252页

作者： Yongwang Yuan Xiangwei Liu ke Lu School of Mathematics and Big Data Anhui University of Science and TechnologyHuainan232001China School of Economics and Management Anhui University of Science and TechnologyHuainan232001China The key Laboratory of Embedded System and Service Computing Ministry of Education Tongji UniversityShanghai201804China

Predictive Business Process Monitoring(PBPM)is a significant research area in Business Process Management(BPM)aimed at accurately forecasting future behavioral *** present,deep learning methods are widely cited in PBPM research,but no method has been effective in fusing data information into the control flow for multi-perspective process ***,this paper proposes a process prediction method based on the hierarchical BERT and multi-perspective data ***,the first layer BERT network learns the correlations between different category attribute ***,the attribute data is integrated into a weighted event-level feature vector and input into the second layer BERT network to learn the impact and priority relationship of each event on future predicted ***,the multi-head attention mechanism within the framework is visualized for analysis,helping to understand the decision-making logic of the framework and providing visual ***,experimental results show that the predictive accuracy of the framework surpasses the current state-of-the-art research methods and significantly enhances the predictive performance of BPM.

关键词： Business process prediction monitoring deep learning attention mechanism BERT multi-perspective

Byzantine Robust Federated Learning Scheme Based on Backdoor Triggers

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Computers, Materials & Continua 2024年第5期79卷 2813-2831页

作者： Zheng Yang ke Gu Yiming Zuo School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China

Federated learning is widely used to solve the problem of data decentralization and can provide privacy protectionfor data owners. However, since multiple participants are required in federated learning, this allows attackers tocompromise. Byzantine attacks pose great threats to federated learning. Byzantine attackers upload maliciouslycreated local models to the server to affect the prediction performance and training speed of the global model. Todefend against Byzantine attacks, we propose a Byzantine robust federated learning scheme based on backdoortriggers. In our scheme, backdoor triggers are embedded into benign data samples, and then malicious localmodels can be identified by the server according to its validation dataset. Furthermore, we calculate the adjustmentfactors of local models according to the parameters of their final layers, which are used to defend against datapoisoning-based Byzantine attacks. To further enhance the robustness of our scheme, each localmodel is weightedand aggregated according to the number of times it is identified as malicious. Relevant experimental data showthat our scheme is effective against Byzantine attacks in both independent identically distributed (IID) and nonindependentidentically distributed (non-IID) scenarios.

关键词： Federated learning Byzantine attacks backdoor triggers

VKFQ:A Verifiable keyword Frequency Query Framework with Local Differential Privacy in Blockchain

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Computers, Materials & Continua 2024年第3期78卷 4205-4223页

作者： Youlin Ji Bo Yin ke Gu School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China

With its untameable and traceable properties,blockchain technology has been widely used in the field of data *** to preserve individual privacy while enabling efficient data queries is one of the primary issues with secure data *** this paper,we study verifiable keyword frequency(KF)queries with local differential privacy in *** the numerical and the keyword attributes are present in data objects;the latter are sensitive and require privacy ***,prior studies in blockchain have the problem of trilemma in privacy protection and are unable to handle KF *** propose an efficient framework that protects data owners’privacy on keyword attributes while enabling quick and verifiable query processing for KF *** framework computes an estimate of a keyword’s frequency and is efficient in query time and verification object(VO)size.A utility-optimized local differential privacy technique is used for privacy *** data owner adds noise locally into data based on local differential privacy so that the attacker cannot infer the owner of the keywords while keeping the difference in the probability distribution of the KF within the privacy *** propose the VB-cm tree as the authenticated data structure(ADS).The VB-cm tree combines the Verkle tree and the Count-Min sketch(CM-sketch)to lower the VO size and query *** VB-cm tree uses the vector commitment to verify the query *** fixed-size CM-sketch,which summarizes the frequency of multiple keywords,is used to estimate the KF via hashing *** conduct an extensive evaluation of the proposed *** experimental results show that compared to theMerkle B+tree,the query time is reduced by 52.38%,and the VO size is reduced by more than one order of magnitude.

关键词： Security data sharing blockchain data query privacy protection

ProNet Adaptive Retinal Vessel Segmentation Algorithm Based on Improved UperNet Network

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Computers, Materials & Continua 2024年第1期78卷 283-302页

作者： Sijia Zhu Pinxiu Wang ke Shen CW Chu College Jiangsu Normal UniversityXuzhou221000China Biomedical Engineering College Southern Medical UniversityGuangzhou510080China

This paper proposes a new network structure,namely the ProNet *** medical image segmentation can help clinical diagnosis of related eye diseases and is essential for subsequent rational *** baseline model of the ProNet network is UperNet(Unified perceptual parsing Network),and the backbone network is ConvNext(Convolutional Network).A network structure based on depth-separable convolution and 1×1 convolution is used,which has good performance and *** further optimise ProNet mainly in two *** is data enhancement using increased noise and slight angle rotation,which can significantly increase the diversity of data and help the model better learn the patterns and features of the data and improve the model’s ***,it can effectively expand the training data set,reduce the influence of noise and abnormal data in the data set on the model,and improve the accuracy and reliability of the *** is the loss function aspect,and we finally use the focal loss *** focal loss function is well suited for complex tasks such as object *** function will penalise the loss carried by samples that the model misclassifies,thus enabling better training of the model to avoid these errors while solving the category imbalance problem as a way to improve image segmentation density and segmentation *** the experimental results,the evaluation metrics mIoU(mean Intersection over Union)enhanced by 4.47%,and mDice enhanced by 2.92% compared to the baseline *** generalization effects and more accurate image segmentation are achieved.

关键词： Retinal segmentation multifaceted optimization cross-fusion data enhancement focal loss

Is Yang-Mills theory unitary in fractional spacetime dimensions?

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Science China(Physics,Mechanics & Astronomy) 2024年第7期67卷 59-64页

作者： Qingjun Jin ke Ren Gang Yang Rui Yu Graduate School of China Academy of Engineering Physics Beijing 100193China School of Physics and Astronomy Sun Yat-Sen UniversityZhuhai 519082China CAS key Laboratory of Theoretical Physics Institute of Theoretical PhysicsChinese Academy of SciencesBeijing 100190China School of Fundamental Physics and Mathematical Sciences Hangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesHangzhou 310024China International Centre for Theoretical Physics Asia-Pacific Hangzhou 310024China School of Physical Science and Technology Inner Mongolia UniversityHohhot 010021China Beijing Computational Science Research Center Beijing 100193China

We present concrete evidence that Yang-Mills theory exhibits non-unitarity in non-integer spacetime *** violation of unitarity stems from evanescent operators that,while vanishing in four dimensions,are non-zero in general d *** demonstrate that these evanescent operators lead to the emergence of both negative-norm states and complex anomalous dimensions.

关键词： gauge field theories field theories in dimensions other than four renormalization