检索结果-南通市图书馆

A Novel Locomotion Rule Rmbedding Long Short-Term Memory Network with Attention for Human Locomotor Intent Classification Using Multi-Sensors Signals

引用

Computers, Materials & Continua 2024年第6期79卷 4349-4370页

作者： Jiajie Shen Yan Wang Dongxu Zhang key laboratory of Symbol computation and knowledge engineering Ministry of EducationColleague of Computer Science and TechnologyJilin UniversityChangchun130012China College of Software and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of EducationJilin UniversityChangchun130012China

Locomotor intent classification has become a research hotspot due to its importance to the development of assistive robotics and wearable *** work have achieved impressive performance in classifying steady locomotion ***,it remains challenging for these methods to attain high accuracy when facing transitions between steady locomotion *** to the similarities between the information of the transitions and their adjacent steady ***,most of these methods rely solely on data and overlook the objective laws between physical activities,resulting in lower accuracy,particularly when encountering complex locomotion modes such as *** address the existing deficiencies,we propose the locomotion rule embedding long short-term memory(LSTM)network with Attention(LREAL)for human locomotor intent classification,with a particular focus on transitions,using data from fewer sensors(two inertial measurement units and four goniometers).The LREAL network consists of two levels:One responsible for distinguishing between steady states and transitions,and the other for the accurate identification of locomotor *** classifier in these levels is composed of multiple-LSTM layers and an attention *** introduce real-world motion rules and apply constraints to the network,a prior knowledge was added to the network via a rule-modulating *** method was tested on the ENABL3S dataset,which contains continuous locomotion date for seven steady and twelve transitions *** results showed that the LREAL network could recognize locomotor intents with an average accuracy of 99.03%and 96.52%for the steady and transitions states,*** is worth noting that the LREAL network accuracy for transition-state recognition improved by 0.18%compared to other state-of-the-art network,while using data from fewer sensors.

关键词： Lower-limb prosthetics deep neural networks motion classification

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

NADARAYA-WATSON ESTIMATORS FOR REFLECTED STOCHASTIC PROCESSES

引用

Acta Mathematica Scientia 2024年第1期44卷 143-160页

作者：韩月才张丁文 School of Mathematics Jilin UniversityChangchun130012China key laboratory of symbolic computation and knowledge engineering of ministry of education Jilin UniversityChangchun130012China

We study the Nadaraya-Watson estimators for the drift function of two-sided reflected stochastic differential *** estimates,based on either the continuously observed process or the discretely observed process,are *** certain conditions,we prove the strong consistency and the asymptotic normality of the two *** method is also suitable for one-sided reflected stochastic differential *** results demonstrate that the performance of our estimator is superior to that of the estimator proposed by Cholaquidis et al.(Stat Sin,2021,31:29-51).Several real data sets of the currency exchange rate are used to illustrate our proposed methodology.

关键词： reflected stochastic differential equation discretely observed process continuously observed process Nadaraya-Watson estimator asymptotic behavior

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

A novel graph oversampling framework for node classification in class-imbalanced graphs

引用

Science China(Information Sciences) 2024年第6期67卷 214-229页

作者： Riting XIA Chunxu ZHANG Yan ZHANG Xueyan LIU Bo YANG key laboratory of symbolic computation and knowledge engineering of ministry of education Jilin University College of Artificial Intelligence Jilin University College of Computer Science and Technology Jilin University College of Communication engineering Jilin University

Graph neural network(GNN) is a promising method to analyze graphs. Most existing GNNs adopt the class-balanced assumption, which cannot deal with class-imbalanced graphs well. The oversampling technique is effective in alleviating class-imbalanced problems. However, most graph oversampling methods generate synthetic minority nodes and their edges after applying GNNs. They ignore the problem that the representations of the original and synthetic minority nodes are dominated by majority nodes caused by aggregating neighbor information through GNN before oversampling. In this paper, we propose a novel graph oversampling framework, termed distribution alignment-based oversampling for node classification in classimbalanced graphs(named Graph-DAO). Our framework generates synthetic minority nodes before GNN to avoid the dominance of majority nodes caused by message passing in GNNs. Additionally, we introduce a distribution alignment method based on the sum-product network to learn more information about minority nodes. To our best knowledge, it is the first to use the sum-product network to solve the class-imbalanced problem in node classification. A large number of experiments on four real datasets show that our method achieves the optimal results on the node classification task for class-imbalanced graphs.

关键词： graph neural network class-imbalanced graphs sum-product network oversampling node classification

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

DeciLS-PBO: an effective local search method for pseudo-Boolean optimization

引用

Frontiers of Computer Science 2024年第2期18卷 239-241页

作者： Luyu JIANG Dantong OUYANG Qi ZHANG Liming ZHANG College of Computer Science and Technology Jilin UniversityChangchun 130012China key laboratory of symbolic computation and knowledge engineering(ministry of education) Jilin UniversityChangchun 130012China

1 Introduction Local search method is a rising star for solving combinatorial optimization problems in recent years,and the state-of-the-art local search-based incomplete Maximum Satisfiability(MaxSAT)solversshowpromi... 详细信息

关键词： Max optimization local

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Measuring drug similarity using drug–drug interactions

引用

Quantitative Biology 2024年第2期12卷 164-172页

作者： Ji Lv Guixia Liu Yuan Ju Houhou Huang Ying Sun College of Computer Science and Technology Jilin UniversityChangchunChina key laboratory of symbolic computation and knowledge engineering of ministry of education Jilin UniversityChangchunChina Sichuan University Library Sichuan UniversityChengduChina College of Chemistry Jilin UniversityChangchunChina Department of Respiratory Medicine The First Hospital of Jilin UniversityChangchunChina

Combination therapy is a promising approach to address the challenge of antimicrobial resistance,and computational models have been proposed for predicting drug–drug *** existing models rely on drug similarity measures based on characteristics such as chemical structure and the mechanism of *** this study,we focus on the network structure itself and propose a drug similarity measure based on drug–drug interaction *** explore the potential applications of this measure by combining it with unsupervised learning and semi-supervised learning *** unsupervised learning,drugs can be grouped based on their interactions,leading to almost monochromatic group–group *** addition,drugs within the same group tend to have similar mechanisms of action(MoA).In semi-supervised learning,the similarity measure can be utilized to construct affinity matrices,enabling the prediction of unknown drug–drug *** method exceeds existing approaches in terms of ***,our experiments demonstrate the effectiveness and practicability of the proposed similarity *** the one hand,when combined with clustering algorithms,it can be used for functional annotation of compounds with unknown *** the other hand,when combined with semi-supervised graph learning,it enables the prediction of unknown drug–drug interactions.

关键词： drug similarity drug–drug interactions drug combinations synergy effect clustering semi-supervised learning

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Rational surface charge engineering of haloalkane dehalogenase for boosting the enzymatic performance in organic solvent solutions

引用

Chinese Journal of Chemical engineering 2024年第1期65卷 276-285页

作者： Yin Wu Yan Sun Department of Biochemical engineering School of Chemical Engineering and Technology and Key Laboratory of Systems Bioengineering and Frontiers Science Center for Synthetic Biology(Ministry of Education)Tianjin UniversityTianjin 300350China

Biocatalysis in organic solvents(OSs)has numerous important applications,but native enzymes in OSs often exhibit limited catalytic ***,we proposed a computation-aided surface charge engineering strategy to improve the catalytic performance of haloalkane dehalogenase DhaA in OSs based on the energetic analysis of substrate binding to the DhaA *** variants with enhanced OS resistance were obtained by replacing negative charged residues on the surface with positive charged residue(Arg).Particularly,a four-substitution variant E16R/E93R/E121R/E257R exhibited the best catalytic performance(five-fold improvement in OS resistance and seven-fold half-life increase in 40%(vol)dimethylsulfoxide).As a result,the overall catalytic performance of the variant could be at least 26 times higher than the wild-type *** spectroscopy and molecular dynamics simulation studies revealed that the residue substitution mainly enhanced OS resistance from four aspects:(a)improved the overall structural stability,(b)increased the hydrophobicity of the local microenvironment around the catalytic triad,(c)enriched the hydrophobic substrate around the enzyme molecule,and(d)lowered the contact frequency between OS molecules and the catalytic *** findings validate that computationaided surface charge engineering is an effective and ingenious rational strategy for tailoring enzyme performance in OSs.

关键词： Surface charge engineering Organic solvent resistance Molecular dynamics simulation Haloalkane dehalogenase

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

CONVERGENCE ANALYSIS OF SOME FINITE ELEMENT PARALLEL ALGORITHMS FOR THE STATIONARY INCOMPRESSIBLE MHD EQUATIONS

引用

Journal of computational Mathematics 2024年第1期42卷 49-70页

作者： Xiaojing Dong Yinnian He Hunan key laboratory for computation and Simulation in Science and engineering Key Laboratory of Intelligent Computing&Information Processing of Ministry of EducationSchool of Mathematics and Computational ScienceXiangtan UniversityXiangtan 411105China Institute of Applied Physics and computational Mathematics Beijing 100088China School of Mathematics and Statistics Xi'an Jiaotong UniversityXi'an 710049China

By combination of iteration methods with the partition of unity method(PUM),some finite element parallel algorithms for the stationary incompressible magnetohydrodynamics(MHD)with different physical parameters are presented and *** algorithms are highly *** first,a global solution is obtained on a coarse grid for all approaches by one of the iteration *** parallelized residual schemes,local corrected solutions are calculated on finer meshes with overlapping *** subdomains can be achieved flexibly by a class of *** proposed algorithm is proved to be uniformly stable and ***,one numerical example is presented to confirm the theoretical findings.

关键词： Partition of unity method Local and parallel algorithm Finite element method Iteration methods Magnetohydrodynamics

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

ZnO-ITO/WO_(3-x)heterojunction structured memristor for optoelectronic co-modulation neuromorphic computation

引用

Science China Materials 2024年第9期67卷 2838-2847页

作者： Jianyong Pan Tong Wu Wenhao Yang Yang Li Jiaqi Zhang Hao Kan Shandong Provincial key laboratory of Network Based Intelligent Computing School of Information Science and EngineeringUniversity of JinanJinan250022China School of Integrated Circuits Shandong UniversityJinan250101China key laboratory of Automobile Materials ministry of education College of Materials Science and EngineeringJilin UniversityChangchun130012China

Traditional transistors confront severe challenges of insufficient computing capability and excessive power consumption in large-scale neuromorphic *** address these critical bottlenecks,we propose an optoelectronic memristor based on zinc oxide-indium tin oxide/tungsten oxide(ZnO-ITO/WO_(3-x))heterojunctions as a promising *** applying different types of electrical and optical signals,the device successfully emulates diverse synaptic functions including short-term/long-term synaptic plasticity,alongside short-term and long-term *** the ZnO-ITO functional layer enhances the photoresponse of the WO_(3-x)-based memristor and demonstrates“learning-forgetting-relearning”behavior under optical ***,based on the photoelectric cooperative memristor array,a convolutional neural network for vehicle type recognition is constructed,which solves the problem of zero weight and negative weight *** regard to energy efficiency,the neural network built with this device operates at a power level of only 10^(-3)W,representing a reduction of more than 4 orders of magnitude compared with a standard central ***,the photoelectric memristor proposed in this work provides a new idea for neuromorphic computing and is expected to promote the development of energy-efficient brain-like computing.

关键词： ZnO-ITO/WO_(3-x)heterojunction optoelectronic memristor synaptic plasticity neuromorphic computing convolutional neural network

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Multi-party privacy-preserving decision tree training with a privileged party

引用

Science China(Information Sciences) 2024年第8期67卷 253-268页

作者： Yiwen TONG Qi FENG Min LUO Debiao HE key laboratory of Aerospace Information Security and Trusted Computing ministry of education School of Cyber Science and Engineering Wuhan University Shanghai Technology Innovation Centre of Distributed Privacy-Preserving Artificial Intelligence Matrix Elements Technologies key laboratory of Computing Power Network and Information Security Ministry of EducationShandong Computer Science Center Qilu University of Technology(Shandong Academy of Sciences)

Currently, a decision tree is the most commonly used data mining algorithm for classification tasks. While a significant number of studies have investigated privacy-preserving decision trees, the methods proposed in these studies often have shortcomings in terms of data privacy breach or efficiency. Additionally,these methods typically only apply to symmetric frameworks, which consist of two or more parties with equal privilege, and are not suitable for asymmetric scenarios where parties have unequal privilege. In this paper,we propose SecureCART, a three-party privacy-preserving decision tree training scheme with a privileged party. We adopt the existing pMPL framework and design novel secure interactive protocols for division,comparison, and asymmetric multiplication. Compared to similar schemes, our division protocol is 93.5–560.4× faster, with the communication overhead reduced by over 90%; further, our multiplication protocol is approximately 1.5× faster, with the communication overhead reduced by around 20%. Our comparison protocol based on function secret sharing maintains good performance when adapted to pMPL. Based on the proposed secure protocols, we implement SecureCART in C++ and analyze its performance using three real-world datasets in both LAN and WAN environments. he experimental results indicate that SecureCART is significantly faster than similar schemes proposed in past studies, and that the loss of accuracy while using SecureCART remains within an acceptable range.

关键词： decision trees privacy protection privileged party secret sharing secure multi-party computation

来源：

同方期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

UAV-assisted cooperative offloading energy efficiency system for mobile edge computing

引用

Digital Communications and Networks 2024年第1期10卷 16-24页

作者： Xue-Yong Yu Wen-Jin Niu Ye Zhu Hong-Bo Zhu Jiangsu key laboratory of Wireless Communications Nanjing University of Posts and Telecommunications Nanjing210003China engineering Research Centerof Health Service System Based on Ubiquitous Wireless Networks Ministry of EducationNanjng Universityof Posts and Telecommunications Nanjing210003China

Reliable communication and intensive computing power cannot be provided effectively by temporary hot spots in disaster areas and complex terrain ground *** this has greatly developed the application and integration of UAV and Mobile Edge Computing(MEC)to the Internet of Things(loT).However,problems such as multi-user and huge data flow in large areas,which contradict the reality that a single UAV is constrained by limited computing power,still *** to allowing UAV collaboration to accomplish complex tasks,cooperative task offloading between multiple UAVs must meet the interdependence of tasks and realize parallel processing,which reduces the computing power consumption and endurance pressure of *** the computing requirements of the user terminal,delay constraint of a computing task,energy constraint,and safe distance of UAV,we constructed a UAV-Assisted cooperative offloading energy efficiency system for mobile edge computing to minimize user terminal energy ***,the resulting optimization problem is originally nonconvex and thus,difficult to solve *** tackle this problem,we developed an energy efficiency optimization algorithm using Block Coordinate Descent(BCD)that decomposes the problem into three convex ***,we jointly optimized the number of local computing tasks,number of computing offloaded tasks,trajectories of UAV,and offloading matching relationship between multi-UAVs and multiuser *** results show that the proposed approach is suitable for different channel conditions and significantly saves the user terminal energy consumption compared with other benchmark schemes.

关键词： computation offloading Internet of things(IoT) Mobile edge computing(MEC) Block coordinate descent(BCD)

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：