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FL-EASGD:Federated Learning Privacy Security Method Based on Homomorphic Encryption

Computers, Materials & Continua 2024年第5期79卷 2361-2373页

作者： Hao Sun Xiubo Chen Kaiguo yuan Information Security Center State Key Laboratory ofNetworking and Switching TechnologyBeijing University of Posts and TelecommunicationsBeijing100876China

Federated learning ensures data privacy and security by sharing models among multiple computing nodes instead of plaintext ***,there is still a potential risk of privacy leakage,for example,attackers can obtain the original data through model inference ***,safeguarding the privacy of model parameters becomes *** proposed solution involves incorporating homomorphic encryption algorithms into the federated learning ***,the existing federated learning privacy protection scheme based on homomorphic encryption will greatly reduce the efficiency and robustness when there are performance differences between parties or abnormal *** solve the above problems,this paper proposes a privacy protection scheme named Federated Learning-Elastic Averaging Stochastic Gradient Descent(FL-EASGD)based on a fully homomorphic encryption ***,this paper introduces the homomorphic encryption algorithm into the FL-EASGD scheme to preventmodel plaintext leakage and realize privacy security in the process ofmodel ***,this paper designs a robust model aggregation algorithm by adding time variables and constraint coefficients,which ensures the accuracy of model prediction while solving performance differences such as computation speed and node anomalies such as downtime of each *** addition,the scheme in this paper preserves the independent exploration of the local model by the nodes of each party,making the model more applicable to the local data ***,experimental analysis shows that when there are abnormalities in the participants,the efficiency and accuracy of the whole protocol are not significantly affected.

关键词： Federated learning homomorphic encryption privacy security stochastic gradient descent

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A New Method for Deriving High-Vertical-Resolution Wind Vector Data from the L-Band Radar Sounding System in China

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Advances in Atmospheric Sciences 2024年第11期41卷 2192-2202页

作者： Fang yuan Zijiang ZHOU Jie LIAO National Meteorological Information Center China Meteorological AdministrationBeijing 100081China

High-vertical-resolution radiosonde wind data are highly valuable for describing the dynamics of the meso-and microscale atmosphere. However, the current algorithm used in China's L-band radar sounding system for calculating highvertical-resolution wind vectors excessively smooths the data, resulting in significant underestimation of the calculated kinetic energy of gravity waves compared to similar products from other countries, which greatly limits the effective utilization of the data. To address this issue, this study proposes a novel method to calculate high-vertical-resolution wind vectors that utilizes the elevation angle, azimuth angle, and slant range from L-band radar. In order to obtain wind data with a stable quality, a two-step automatic quality control procedure, including the RMSE-F(root-mean-square error F) test and elemental consistency test are first applied to the slant range data, to eliminate continuous erroneous data caused by unstable signals or radar malfunctions. Then, a wind calculation scheme based on a sliding second-order polynomial fitting is utilized to derive the high-vertical-resolution radiosonde wind vectors. The evaluation results demonstrate that the wind data obtained through the proposed method show a high level of consistency with the high-resolution wind data observed using the Vaisala Global Positioning System and the data observed by the new Beidou Navigation Sounding System. The calculation of the kinetic energy of gravity waves in the recalculated wind data also reaches a level comparable to the Vaisala observations.

关键词： L-band radar sounding system upper air high-vertical-resolution radiosonde wind vectors quality control polynomial fitting

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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

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Effect of the grain boundary character distribution on the sulfur corrosion behaviour and mechanisms of copper windings under different high temperatures

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HIGH VOLTAGE 2024年第3期9卷 566-580页

作者： Dai, Xu yuan, yuan Zhou, Jiang Liu, Guoyong Zhu, Tao Xiang, Huiying Yu, Qi Gao, Xue Liao, Ruijin Chongqing Univ State Key Lab Power Transmiss Equipment & Syst Sec Chongqing Peoples R China Chongqing Univ Coll Mat Sci & Engn Chongqing Peoples R China Dongfang Elect Machinery Co Ltd Deyang Peoples R China

As a typical failure phenomenon in transformers, sulfur corrosion has garnered significant attention in the field of high-voltage engineering. Grain boundary character distribution (GBCD) copper windings have been introduced to enhance sulfur corrosion resistance by slowing down intergranular corrosion. In this study, the sulfur corrosion behaviour and mechanisms of the GBCD copper windings under various temperatures were experimentally and theoretically studied. Results show that GBCD can enhance the corrosion resistance of copper in liquid environments. With the increase in temperatures, the insulating properties of oil and papers in traditional copper windings experience notable degradation, while GBCD copper windings show more stable insulating behaviours. In addition, modelling of grain boundary energy indicates that the grain boundary structure of GBCD copper windings has a lower average interface energy of 0.170 eV/angstrom 2. Calculations of reaction thermodynamics show that GBCD copper windings possess a higher failure temperature (135.2 degrees C) and inhibition degree (activation energy) of the sulfur corrosion (32,557.62 J/mol), revealing the stability and enhanced sulfur corrosion resistance at elevated temperatures.

关键词： OIL-PAPER INSULATION DIBENZYL DISULFIDE POWER TRANSFORMERS STAINLESS-STEEL STRENGTH

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Ghost Module Based Residual Mixture of Self-Attention and Convolution for Online Signature Verification

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Computers, Materials & Continua 2024年第4期79卷 695-712页

作者： Fangjun Luan Xuewen Mu Shuai yuan Department of Computer Technology School of Computer Science and EngineeringShenyang Jianzhu UniversityShenyang110168China Liaoning Province Big Data Management and Analysis Laboratory of Urban Construction Shenyang Jianzhu UniversityShenyang110168China Shenyang Branch of National Special Computer Engineering Technology Research Center Shenyang Jianzhu UniversityShenyang110168China

Online Signature Verification (OSV), as a personal identification technology, is widely used in various ***, it faces challenges, such as incomplete feature extraction, low accuracy, and computational heaviness. Toaddress these issues, we propose a novel approach for online signature verification, using a one-dimensionalGhost-ACmix Residual Network (1D-ACGRNet), which is a Ghost-ACmix Residual Network that combines convolutionwith a self-attention mechanism and performs improvement by using Ghost method. The Ghost-ACmix Residualstructure is introduced to leverage both self-attention and convolution mechanisms for capturing global featureinformation and extracting local information, effectively complementing whole and local signature features andmitigating the problem of insufficient feature extraction. Then, the Ghost-based Convolution and Self-Attention(ACG) block is proposed to simplify the common parts between convolution and self-attention using the Ghostmodule and employ feature transformation to obtain intermediate features, thus reducing computational ***, feature selection is performed using the random forestmethod, and the data is dimensionally reducedusing Principal Component Analysis (PCA). Finally, tests are implemented on the MCYT-100 datasets and theSVC-2004 Task2 datasets, and the equal error rates (EERs) for small-sample training using five genuine andforged signatures are 3.07% and 4.17%, respectively. The EERs for training with ten genuine and forged signaturesare 0.91% and 2.12% on the respective datasets. The experimental results illustrate that the proposed approacheffectively enhances the accuracy of online signature verification.

关键词： Online signature verification feature selection ACG block ghost-ACmix residual structure

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Current status of early gastric cancer screening research

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Cancer Biology & Medicine 2024年第3期21卷 218-222页

作者： Can Hu Li yuan Xiangdong Cheng Department of Gastric surgery Zhejiang Cancer HospitalHangzhou Institute of Medicine(HIM)Chinese Academy of SciencesHangzhouZhejiang 310022China Key Laboratory of Prevention Diagnosis and Therapy of Upper Gastrointestinal Cancer of Zhejiang ProvinceHangzhou 310022China Zhejiang Provincial Research Center for Upper Gastrointestinal Tract Cancer Zhejiang Cancer HospitalHangzhou 310022China

Gastric cancer is a predominant threat to the health and well-being of China's residents. Data from the World Health Organization(WHO) in 2020 revealed that gastric cancer in China notably accounted for 44.0% of new c... 详细信息

关键词： cancer Gastric gastric

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Methane activation by[LnO]^(+):the 4f orbital matters

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Science China Chemistry 2024年第1期67卷 330-335页

作者： Bowei yuan Jingxiang Zou Mincheng Yu Shaodong Zhou College of Chemical and Biological Engineering Zhejiang Provincial Key Laboratory of Advanced Chemical Engineering Manufacture TechnologyZhejiang UniversityHangzhou 310027China Zhejiang Provincial Innovation Center of Advanced Chemicals Technology Institute of Zhejiang University–QuzhouQuzhou 324000China Laboratory for Sciences and Technologies of Energy Materials of Fujian Province(IKKEM) Xiamen 361005China

Gas-phase reactions of[LnO]^(+)with methane have been studied by using inductively coupled plasma-mass spectrometer(ICP-MS)combined with quantum chemical *** indicate that the[LnO]^(+)(Ln=Sm-Lu)ions are able to activate methane to generate methyl *** particular,[EuO]^(+)and[YbO]^(+)exhibit the highest ***,ab initio computations reveal a novel HAT process operating in the absence of a terminal oxygen radical,as mediated by[EuO]^(+)and[YbO]^(+).Such a process diverges from previous findings on the methane activation by metal oxide clusters,not only on the electronic pattern during the course of hydrogen transfer,but also on the important role that 4f electrons *** associated electronic origins have been discussed,and the well-designed 4f electron occupation may turn to be a promising approach in constructing lanthanide involved catalysts.

关键词： lanthanide oxides methane activation 4f orbitals quantum chemical calculation ion-molecule reaction

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Chiral thermally activated delayed fluorescence materials for circularly polarized organic light-emitting diodes

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Science China Chemistry 2024年第4期67卷 1097-1116页

作者： Li yuan Yi-Pin Zhang You-Xuan Zheng State Key Laboratory of Coordination Chemistry Collaborative Innovation Center of Advanced MicrostructuresJiangsu Key Laboratory of Advanced Organic MaterialsSchool of Chemistry and Chemical EngineeringNanjing UniversityNanjing 210023China

Chirality is an important natural characteristic of organic molecules,and chiral organic molecules have shown extensive application in areas such as pharmaceutical development and material *** from the ability to achieve circularly polarized luminescence(CPL),chiral luminescent materials have shown potential applications in anti-glare display,optical communication and,3D display,*** to the ability to harvest both singlet and triplet excitons by a fast reverse intersystem crossing process without involving noble metals,chiral thermally activated delayed fluorescence(TADF)materials with point chirality,axial chirality,planar chirality and helical chirality are regarded as the state-of-the-art materials for circularly polarized organic light-emitting diodes(CP-OLEDs).In recent years,the chiral TADF materials and CP-OLEDs have rapidly developed,but unfortunately,the dissymmetry factors(g)are far from the requirement of practical *** ideal emitters and devices should have both high efficiency and a g factor,or at least a balance between these two *** review gives an overview of recent progress in chiral TADF materials,with a particular focus on the chiral skeleton,CPL property and device ***,the molecular design concept,device structure and methods to improve the g factors of chiral materials and CP-OLEDs are also discussed.

关键词： chiral thermally activated delayed fluorescence material chiral skeleton circularly polarized luminescence circularly polarized organic light-emitting diodes dissymmetry factor

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Metarelation2vec:A Metapath-Free Scalable Representation Learning Model for Heterogeneous Networks

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Tsinghua Science and Technology 2024年第2期29卷 553-575页

作者： Lei Chen yuan Li Yong Lei Xingye Deng School of Information and Electrical Engineering Hunan University of Science and TechnologyXiangtan 411201China School of Computer Science and Engineering Hunan University of Science and TechnologyXiangtan 411201China

Metapaths with specific complex semantics are critical to learning diverse semantic and structural information of heterogeneous networks(HNs)for most of the existing representation learning ***,any metapaths consisting of multiple,simple metarelations must be driven by domain *** sensitive,expensive,and limited metapaths severely reduce the flexibility and scalability of the existing models.A metapath-free,scalable representation learning model,called Metarelation2vec,is proposed for HNs with biased joint learning of all metarelations in a bid to address this ***,a metarelation-aware,biased walk strategy is first designed to obtain better training samples by using autogenerating cooperation probabilities for all metarelations rather than using expert-given ***,grouped nodes by the type,a common and shallow skip-gram model is used to separately learn structural proximity for each node ***,grouped links by the type,a novel and shallow model is used to separately learn the semantic proximity for each link ***,supervised by the cooperation probabilities of all meta-words,the biased training samples are thrown into the shallow models to jointly learn the structural and semantic information in the HNs,ensuring the accuracy and scalability of the *** experimental results on three tasks and four open datasets demonstrate the advantages of our proposed model.

关键词： metarelation random walk heterogeneous network metapath representation learning

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All-inorganic ultrathin high-sensitivity transparent temperature sensor based on a Mn-Co-Ni-O nanofilm

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Microsystems & Nanoengineering 2024年第3期10卷 195-205页

作者： yuanyuan Cui Mengwei Sun Changbo Liu yuan Deng Research Institute for Frontier Science Beihang UniversityBeijing 100191China School of Materials Science and Engineering Beihang UniversityBeijing 100191China Key Laboratory of Intelligent Sensing Materials and Chip Integration Technology of Zhejiang Province Hangzhou Innovation Institute of Beihang UniversityHangzhou 310051China

The demand for optically transparent temperature sensors in intelligent devices is ***,the performance of these sensors,particularly in terms of their sensitivity and resolution,must be further *** study introduces a novel transparent and highly sensitive temperature sensor characterized by its ultrathin,freestanding design based on a Mn-Co-Ni-O *** Mn-Co-Ni-O-based sensor exhibits remarkable sensitivity,with a temperature coefficient of resistance of−4%℃^(−1),and can detect minuscule temperature fluctuations as small as 0.03℃.Additionally,the freestanding sensor can be transferred onto any substrate for versatile application while maintaining robust structural stability and excellent resistance to interference,indicating its suitability for operation in challenging *** practical utility in monitoring the surface temperature of optical devices is demonstrated through vertical integration of the sensor and a micro light-emitting diode on a polyimide ***,an experiment in which the sensor is implanted in rats confirms its favorable biocompatibility,highlighting the promising applications of the sensor in the biomedical domain.

关键词： transparent sensor versatile

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