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ON SEVERAL NEW METHODS TO POLAR DECOMPOSITION COMPUTATION

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Acta Mechanica Solida Sinica 1998年第4期11卷 329-340页

作者： huang, MJ Li, M Fu, mf Nanchang Univ Inst Engn Mech Nanchang 330029 Peoples R China

In this paper, the polar decomposition of a deformation gradient tensor is analyzed in detail. The four new methods for polar decompositioncomputation are given: (1) the iterated method, (2) the principal invariant's method, (3) the principal rotation axis' s method, (4) the coordinate transformation's method. The iterated method makes it possible to establish the nonlinear finite element method based on polar decomposition. Furthermore, the material time derivatives of the stretch tensor and the rotation tensor are obtained by explicit and simple expressions.

关键词： polar decomposition deformation gradient stretch tensor rotation tensor large deformation and large rotation

Memory-based adaptive event-triggered secure control of Markovian jumping neural networks suffering from deception attacks

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Science China(Technological Sciences) 2023年第2期66卷 468-480页

作者： YAO Lan huang Xia College of Electrical Engineering and Automation Shandong University of Science and TechnologyQingdao 266590China

In this article,we study the secure control of the Markovian jumping neural networks(MJNNs)subject to deception *** the limitation of the network bandwidth and the impact of the deception attacks,we propose two memory-based adaptive event-trigger mechanisms(AETMs).Different from the available event-trigger mechanisms,these two memory-based AETMs contain the historical triggered data not only in the triggering conditions,but also in the adaptive *** can adjust the data transmission rate adaptively so as to alleviate the impact of deception attacks on the controlled system and to suppress the peak of the system *** view of the proposed memory-based AETMs,a time-dependent Lyapunov functional is constructed to analyze the stability of the error *** sufficient conditions to ensure the asymptotical synchronization of master-slave MJNNs are obtained,and two easy-to-implement co-design algorithms for the feedback gain matrix and the trigger matrix are ***,a numerical example is given to verify the feasibility and superiority of the two memory-based AETMs.

关键词： secure control memory-based adaptive event-trigger mechanism globally asymptotical synchronization deception attacks

Modulating the electrode–electrolyte interface enables switchable selectivity in electrocatalytic furfural reduction

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Science China Chemistry 2024年第10期67卷 3193-3194页

作者： Jingfang Zhang Yi huang Engineering Research Center of Phosphorus Resources Development and Utilization of Ministry of Education School of Chemical Engineering&PharmacyWuhan Institute of TechnologyWuhan 430205China College of Chemistry Central China Normal UniversityWuhan 430079China

Furfural(FF),an important bio-based platform molecule,can be valorized to high-value-added chemicals(e.g.,furfuryl alcohol(FA)or 2-methylfuran(mf))through catalytic hydrogenation[1].The traditional thermocatalytic transformation of FF always requires high-temperature and highpressure conditions[2].Accordingly,electrocatalytic hydrogenation is emerging as a promising approach for the selective reduction of FF to FA or mf under environmentally friendly and benign conditions.

关键词： hydrogenation electrolyte selectivity

A Mean-Field Optimal Control for Fully Coupled Forward-Backward Stochastic Control Systems with Lévy Processes

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Journal of Systems Science & Complexity 2022年第1期35卷 205-220页

作者： huang Zhen WANG Ying WANG Xiangrong College of Mathematics and Systems Science Shandong University of Science and TechnologyQingdao 266590China.

This paper is concerned with a class of mean-field type stochastic optimal control systems,which are governed by fully coupled mean-field forward-backward stochastic differential equations with Teugels martingales associated to Lévy *** these systems,the coefficients contain not only the state processes but also their marginal distribution,and the cost function is of mean-field type as *** necessary and sufficient conditions for such optimal problems are ***,the applications to the linear quadratic stochastic optimization control problem are investigated.

关键词： Adjoint equation Lévy processes mean-field forward-backward stochastic differential equations stochastic maximum principle Teugels martingales

Dual-domain and Multiscale Fusion Deep Neural Network for PPG Biometric Recognition

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Machine Intelligence Research 2023年第5期20卷 707-715页

作者： Chun-Ying Liu Gong-Ping Yang Yu-Wen huang Fu-Xian huang School of computer Heze UniversityHeze 274015China School of Software Shandong UniversityJinan 250101China

Photoplethysmography(PPG)biometrics have received considerable *** deep learning has achieved good performance for PPG biometrics,several challenges remain open:1)How to effectively extract the feature fusion representation from time and frequency PPG signals.2)How to effectively capture a series of PPG signal transition information.3)How to extract timevarying information from one-dimensional time-frequency sequential *** address these challenges,we propose a dual-domain and multiscale fusion deep neural network(DmfDNN)for PPG biometric *** DmfDNN is mainly composed of a two-branch deep learning framework for PPG biometrics,which can learn the time-varying and multiscale discriminative features from the time and frequency ***,we design a multiscale extraction module to capture transition information,which consists of multiple convolution layers with different receptive fields for capturing multiscale transition *** addition,the dual-domain attention module is proposed to strengthen the domain of greater contributions from time-domain and frequency-domain data for PPG *** on the four datasets demonstrate that DmfDNN outperforms the state-of-the-art methods for PPG biometrics.

关键词： Photoplethysmography(PPG)signal biometric recognition multiple scale deep neural network dual-domain attention.

SnapshotPrune: A Novel Bitcoin-Based Protocol Toward Efficient Pruning and Fast Node Bootstrapping

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Tsinghua Science and Technology 2024年第4期29卷 1037-1052页

作者： Pengfei huang Xiaojun Ren Teng huang Arthur Sandor Voundi Koe Duncan S Wong Hai Jiang Institute of Artificial Intelligence and Blockchain Guangzhou UniversityGuangzhou 510006China Institute of Artificial Intelligence and Blockchain Guangzhou UniversityGuangzhou 510006Chinaand also with Pazhou LabGuangzhou 510330China

Node synchronization is essential for the stability of the Bitcoin network. Critics have raised doubts about the ability of a new node to quickly and efficiently synchronize with the Bitcoin network and alleviate the storage pressure from existing full nodes to stockpile new data. Basic pruning and other techniques have been explored to address these concerns but have been insufficient to reduce node synchronization delay and effectively suppress the growth of synchronized data. In this study, we propose SnapshotPrune, a novel pruning and synchronization protocol that achieves fast node bootstrapping in the Bitcoin blockchain. Real Bitcoin historical data are leveraged to measure the synchronization time and monitor the network traffic during node bootstrapping. The protocol requires data downloads that are 99.70% less than Bitcoin Core, 81% less than CoinPrune, and 60% less than SnapshotSave, thereby saving 97.23% of download time. Findings show that the proposed design enhances the storage efficiency and reduces the node synchronization delay compared with existing techniques. We hypothesize that the efficiency of this protocol increases with the block height.

关键词： synchronization blockchain Unspent Transaction Output(UTXO)pruning snapshot fast bootstrapping

Information mining and similarity computation for semi-/un-structured sentences from the social data

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Digital Communications and Networks 2021年第4期7卷 518-525页

作者： Peiying Zhang Xingzhe huang Lei Zhang College of Computer Science and Technology China University of Petroleum(East China)Qingdao266580China Petroleum Engineering Technology Research Institute Shengli OilfieldSinopecDongying257000China

In recent years,with the development of the social Internet of Things(IoT),all kinds of data accumulated on the *** data,which contain a lot of social information and ***,these data are rarely fully analyzed,which is a major obstacle to the intelligent development of the social *** this paper,we propose a sentence similarity analysis model to analyze the similarity in people’s opinions on hot topics in social media and news *** of these data are unstructured or semi-structured sentences,so the accuracy of sentence similarity analysis largely determines the model’s *** the purpose of improving accuracy,we propose a novel method of sentence similarity computation to extract the syntactic and semantic information of the semi-structured and unstructured *** mainly consider the subjects,predicates and objects of sentence pairs and use Stanford Parser to classify the dependency relation triples to calculate the syntactic and semantic similarity between two ***,we verify the performance of the model with the Microsoft Research Paraphrase Corpus(MRPC),which consists of 4076 pairs of training sentences and 1725 pairs of test sentences,and most of the data came from the news of social *** simulations demonstrate that our method outperforms other state-of-the-art methods regarding the correlation coefficient and the mean deviation.

关键词： Sentence similarity computation Information mining and computation Social data Internet of things Type of sentence pairs

Joint Sample Position Based Noise Filtering and Mean Shift Clustering for Imbalanced Classification Learning

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Tsinghua Science and Technology 2024年第1期29卷 216-231页

作者： Lilong Duan Wei Xue Jun huang Xiao Zheng School of Computer Science and Technology Anhui University of TechnologyMaanshan 243032China Institute of Artificial Intelligence Hefei Comprehensive National Science CenterHefei 230088China

The problem of imbalanced data classification learning has received much *** classification algorithms are susceptible to data skew to favor majority samples and ignore minority *** weighted minority oversampling technique(MWMOTE)is an effective approach to solve this problem,however,it may suffer from the shortcomings of inadequate noise filtering and synthesizing the same samples as the original minority *** this end,we propose an improved MWMOTE method named joint sample position based noise filtering and mean shift clustering(SPMSC)to solve these ***,in order to effectively eliminate the effect of noisy samples,SPMsC uses a new noise filtering mechanism to determine whether a minority sample is noisy or not based on its position and distribution relative to the majority *** that MWMOTE may generate duplicate samples,we then employ the mean shift algorithm to cluster minority samples to reduce synthetic replicate ***,data cleaning is performed on the processed data to further eliminate class *** on extensive benchmark datasets demonstrate the effectiveness of SPMsC compared with other sampling methods.

关键词： imbalanced data classification oversampling noise filtering clustering

Upper and Lower Bounds of the α-Universal Triple I Method for Unified Interval Implications

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Computers, Materials & Continua 2024年第4期79卷 1063-1088页

作者： Yiming Tang Jianwei Gao Yifan huang School of Computer and Information Hefei University of TechnologyHefei230601China Department of Electrical and Computer Engineering University of AlbertaEdmontonAB T6R 2V4Canada

Theα-universal triple I(α-UTI)method is a recognized scheme in the field of fuzzy reasoning,whichwas proposed by our research group *** robustness of fuzzy reasoning determines the quality of reasoning algorithms to a large extent,which is quantified by calculating the disparity between the output of fuzzy reasoning with interference and the output without ***,in this study,the interval robustness(embodied as the interval stability)of theα-UTI method is explored in the interval-valued fuzzy *** begin with,the stability of theα-UTI method is explored for the case of an individual rule,and the upper and lower bounds of its results are estimated,using four kinds of unified interval implications(including the R-interval implication,the S-interval implication,the QL-interval implication and the interval t-norm implication).Through analysis,it is found that theα-UTI method exhibits good interval stability for an individual ***,the stability of theα-UTI method is revealed in the case of multiple rules,and the upper and lower bounds of its outcomes are *** results show that theα-UTI method is stable for multiple rules when four kinds of unified interval implications are used,***,theα-UTI reasoning chain method is presented,which contains a chain structure with multiple *** corresponding solutions and their interval perturbations are *** is found that theα-UTI reasoning chain method is stable in the case of chain *** application examples in affective computing are given to verify the stability of theα-*** summary,through theoretical proof and example verification,it is found that theα-UTImethod has good interval robustness with four kinds of unified interval implications aiming at the situations of an individual rule,multi-rule and reasoning chain.

关键词： Fuzzy reasoning the CRI method the triple I method fuzzy implication interval robustness