检索结果-内蒙古大学图书馆

Current Bioinformatics 2014年第3期9卷 218-227页

作者： Chen, Xiao-Su Yu, Zu-Guo Zheng, Juan Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Hunan411105 China School of Mathematical Sciences Queensland University of Technology GPO Box 2434 BrisbaneQ 4001 Australia School of Information and Engineering Xiangtan University Hunan411105 China

Whole genome sequences are generally accepted as excellent tools for studying evolutionary relationships. Due to the problems caused by the uncertainty in alignment, existing tools for phylogenetic analysis based on multiple alignments could not be directly applied to the whole-genome comparison and phylogenomic studies. There has been a growing interest in alignment-free methods for phylogenetic analysis using complete genome data. The "distances" used in these alignment-free methods are not proper distance metrics in the strict mathematical sense. In this study, we first review them in a more general frame — dissimilarity. Then we propose some new dissimilarities for phylogenetic analysis. Last three genome datasets are employed to evaluate these dissimilarities from a biological point of view. © 201. Bentham science Publishers.

关键词： Alignment

来源：评论

学校读者我要写书评

暂无评论

Gradient Recovery-Type a Posteriori Error Estimates for Steady-State Poisson-Nernst-Planck Equations

引用

Advances in Applied Mathematics and Mechanics 2020年第6期12卷 1353-1383页

作者： Ruigang Shen Shi Shu Ying Yang Mingjuan Fang School of Mathematics and Computational Science Hunan Key Laboratory for Computation and Simulation in Science and EngineeringXiangtan UniversityXiangtanHunan 411105China School of Mathematics and Computational Science Guangxi Colleges and Universities Key Laboratory of Data Analysis and ComputationGuilin University of Electronic TechnologyGuilinGuangxi 541004China School of Mathematics and Computational Science Guilin University of Electronic TechnologyGuilinGuangxi 541004China

In this article,we derive the a posteriori error estimators for a class of steadystate Poisson-Nernst-Planck *** the gradient recovery operator,the upper and lower bounds of the a posteriori error estimators are established both for the electrostatic potential and *** is shown by theory and numerical experiments that the error estimators are reliable and the associated adaptive computation is efficient for the steady-state PNP systems.

关键词： Poisson-Nernst-Planck equations gradient recovery a posteriori error estimate

来源：评论

学校读者我要写书评

暂无评论

Mathematical simulation of Cloaking Metamaterial Structures

引用

Advances in Applied Mathematics and Mechanics 2012年第1期4卷 93-101页

作者： Jichun Li Yunqing Huang Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan UniversityXiangtan 411105China Department of Mathematical Sciences University of Nevada Las VegasLas VegasNevada 89154-4020USA

In this paper we present a rigorous derivation of the material parameters for both the cylinder and rectangle cloaking *** results using these material parameters are presented to demonstrate the cloaking effect.

关键词： Maxwell’s equations metamaterial finite element method cloaking structures

来源：评论

学校读者我要写书评

暂无评论

Some applications of nonlinear science methods and support vector machine methods to protein problems

引用

Mini-Reviews in Organic Chemistry 2015年第6期12卷 493-505页

作者： Hana, Guo Sheng Yu, Zu-Guo Zhao, Zhi-Qin Hunan Key Laboratory for Computation and Simulation in Science and Engineering and Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University XiangtanHunan411105 China School of Mathematical Sciences Queensland University of Technology GPO Box 2434 BrisbaneQ4001 Australia

Protein folding, prediction of protein structure and functions are most important problems in bioinformatics. The protein fold process mainly reflects in the kinetic order of folding. Predicting the structural classes of low-homology protein is a difficult problem in the prediction of protein structure. In order to understanding the mechanism of programmed cell death, it is very necessary to obtain the information about subcellular locations and functions of apoptosis proteins. Predicting protein subnuclear localizations is a challenging problem which is harder than predicting protein subcellular locations. Predicting membrane protein types is related to the structure and function of proteins. In this review, we introduce some applications of nonlinear science methods and support vector machine methods to the above protein problems. The nonlinear science methods including the horizontal visibility network, kernel method, recurrence quantification analysis, global descriptor, Lempel-Ziv complexity, and Hilbert-Huang transform are used to extract features in these approaches. © 201. Bentham science Publishers.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

TWO-GRID ALGORITHM OF H^(1.-GALERKIN MIXED FINITE ELEMENT METHODS FOR SEMILINEAR PARABOLIC INTEGRO-DIFFERENTIAL EQUATIONS

引用

Journal of computational Mathematics 2022年第5期40卷 667-685页

作者： Tianliang Hou Chunmei Liu Chunlei Dai Luoping Chen Yin Yang School of Mathematics and Statistics Beihua UniversityJilin 132013China College of Science Hunan University of Science and EngineeringYongzhou 425199China School of Mathematics Southwest Jiaotong UniversityChengdu 611756China 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

In this paper,we present a two-grid discretization scheme for semilinear parabolic integro-differential equations by H1.Galerkin mixed finite element *** use the lowest order Raviart-Thomas mixed finite elements and continuous linear finite element for spatial discretization,and backward Euler scheme for temporal ***,a priori error estimates and some superclose properties are ***,a two-grid scheme is presented and its convergence is *** the proposed two-grid scheme,the solution of the nonlinear system on a fine grid is reduced to the solution of the nonlinear system on a much coarser grid and the solution of two symmetric and positive definite linear algebraic equations on the fine grid and the resulting solution still maintains optimal ***,a numerical experiment is implemented to verify theoretical results of the proposed *** theoretical and numerical results show that the two-grid method achieves the same convergence property as the one-grid method with the choice h=H^(2).

关键词： Semilinear parabolic integro-differential equations H^(1.-Galerkin mixed finite element method A priori error estimates Two-grid Superclose.

来源：评论

学校读者我要写书评

暂无评论

Secondary structure element alignment kernel method for prediction of protein structural classes

引用

Current Bioinformatics 2014年第3期9卷 253-257页

作者： Han, Guo-Sheng Yu, Zu-Guo Anh, Vo Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Hunan 411105 China School of Mathematical Sciences Queensland University of Technology GPO Box 2434 Brisbane Q 4001 Australia

In this paper, we aim at predicting protein structural classes for low-homology data sets based on predicted secondary structures. We propose a new and simple kernel method, named as SSEAKSVM, to predict protein structural classes. The secondary structures of all protein sequences are obtained by using the tool PSIPRED and then a linear kernel on the basis of secondary structure element alignment scores is constructed for training a support vector machine classifier without parameter adjusting. Our method SSEAKSVM was evaluated on two low-homology datasets 25PDB and 1.89 with sequence homology being 25% and 40%, respectively. The jackknife test is used to test and compare our method with other existing methods. The overall accuracies on these two data sets are 86.3% and 84.5%, respectively, which are higher than those obtained by other existing methods. Especially, our method achieves higher accuracies (88.1. and 88.5%) for differentiating the α+ β class and the α/β class compared to other methods. This suggests that our method is valuable to predict protein structural classes particularly for low-homology protein sequences. The source code of the method in this paper can be downloaded at http://***/myphp/math/research/source/SSEAK_source_***. © 201. Bentham science Publishers.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Space-time finite element adaptive AMG for multi-term time fractional advection diffusion equations

Space-time finite element adaptive AMG for multi-term time f...

引用

作者： Yue, Xiaoqiang Liu, Menghuan Shu, Shi Bu, Weiping Xu, Yehong School of Mathematics and Computational Science Xiangtan University Hunan China Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan University Hunan China

In this study, we construct a space-time finite element (FE) scheme and furnish cost-efficient approximations for one-dimensional multi-term time fractional advection diffusion equations on a bounded domain Ω. Firstly, a fully discrete scheme is obtained by the linear FE method in both temporal and spatial directions, and many characterizations on the resulting matrix are established. Secondly, the associated condition number estimation (Formula presented.) is derived, where τn and h, respectively, are the current time and space step sizes. Next, we propose a lossless in robustness and adaptive algebraic multigrid (AMG) with (Formula presented.) computational cost and (Formula presented.) matrix-free storage, in contrast to classical AMG with (Formula presented.), where M is the number of spatial segments. Meanwhile, uniform convergence analyses on the two-level V(0,1.-cycle of classical and adaptive AMGs are provided. Finally, we demonstrate the optimal error order of space-time FE approximations in the L2(Ω) norm sense, present theoretical confirmations and predictable behaviors of the proposed algorithm in numerical experiments. © 201. John Wiley & Sons, Ltd.

关键词： Matrix algebra

来源：评论

学校读者我要写书评

暂无评论

IMPLICIT-EXPLICIT RUNGE-KUTTA-ROSENBROCK METHODS WITH ERROR ANALYSIS FOR NONLINEAR STIFF DIFFERENTIAL EQUATIONS

引用

Journal of computational Mathematics 2021年第4期39卷 599-620页

作者： Bin Huang Aiguo Xiao Gengen Zhang School of Mathematics and Computational Science&Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan UniversityXiangtan 411105China South China Research Center for Applied Mathematics and Interdisciplinary Studies South China Normal UniversityGuangzhou 510631China

Implicit-explicit Runge-Kutta-Rosenbrock methods are proposed to solve nonlinear sti ordinary di erential equations by combining linearly implicit Rosenbrock methods with explicit Runge-Kutta ***,the general order conditions up to order 3 are ***,for the nonlinear sti initial-value problems satisfying the one-sided Lipschitz condition and a class of singularly perturbed initial-value problems,the corresponding errors of the implicit-explicit methods are *** last,some numerical examples are given to verify the validity of the obtained theoretical results and the e ectiveness of the methods.

关键词： Sti di erential equations Implicit-explicit Runge-Kutta-Rosenbrock method Order conditions Convergence

来源：评论

学校读者我要写书评

暂无评论

Analysis theory of random energy of train derailment in wind

引用

science China(Physics,Mechanics & Astronomy) 2010年第4期53卷 751-757页

作者： CHEN RuiLin 1.2,3 , ZENG QingYuan 3 , HUANG YunQing 1., XIANG Jun 3 , WEN Ying 3 , GUO XiaoGang 2 , YIN ChangJun 2 , DONG Hui 2 & ZHAO Gang 4 1.hunan {1. laboratory for computation and simulation in science and engineering, Xiangtan University, Xiangtan 41.1.5, China 2 School of Civil engineering & Mechanics, Xiangtan University, Xiangtan 41.1.5, China 3 School of Civil Architecture, Central South University, Changsha 41.075, China 4 AMEC, Toronto M5A5G7, Canada 1. Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan University Xiangtan 411105 China2. School of Civil Engineering & Mechanics Xiangtan University Xiangtan 411105 China3. School of Civil Architecture Central South University Changsha 410075 China4. AMEC Toronto M5A5G7 Canada

Based on the analysis theory of random energy of train derailment, an analysis theory of random energy of train derailment in wind is suggested. Two methods are proposed -the time domain method and the frequency domain method of analysis theory of random energy of train derailment in wind. The curves of σ pw -v under various wind speeds are obtained through the computation. The original curve of σ p -v is expanded, which turns the analysis theory of random energy of train derailment into the all-weather theory. Train derailment condition has been established under wind action. The first and second criterions of train derailment have been proposed in light of wind action. The analysis of train derailment cases at home or abroad is made, in- cluding the first analysis of Xinjiang train derailment case encountered 1.-level of gale, which explained the inevitability of train derailment. The analysis theory of random energy of train derailment in wind shows its validity and accuracy. The input energy σ pw of the transverse vibration of train-track(bridge)-wind system is linked to train speed. With the establishment of the analysis theory of random energy of train derailment in wind, It is likely to initiate an all-weather speed limit map for a train or any high-speed train.

关键词： train derailment analysis theory of random energy of train derailment analysis theory of random energy of train de- railment in wind train derailment condition in wind the criterion of train derailment in wind train derailment case

来源：评论

学校读者我要写书评

暂无评论

An Iterative Discontinuous Galerkin Method for Solving the Nonlinear Poisson Boltzmann Equation

引用

Communications in computational Physics 2014年第7期16卷 491-515页

作者： Peimeng Yin Yunqing Huang Hailiang Liu Hunan Key Laboratory for Computation and Simulation in Science and Engineering School of Mathematics and Computational ScienceXiangtan UniversityXiangtan 411105P.R.China Iowa State University Mathematics DepartmentAmesIA 50011USA.

An iterative discontinuous Galerkin(DG)method is proposed to solve the nonlinear Poisson Boltzmann(PB)*** first identify a function space inwhich the solution of the nonlinear PB equation is iteratively approximated through a series of linear PB equations,while an appropriate initial guess and a suitable iterative parameter are selected so that the solutions of linear PB equations are monotone within the identified solution *** the spatial discretization we apply the direct discontinuous Galerkin method to those linear PB *** precisely,we use one initial guess when the Debye parameter l=O(1.,and a special initial guess for l≪1.to ensure *** iterative parameter is carefully chosen to guarantee the existence,uniqueness,and convergence of the *** particular,iteration steps can be reduced for a variable iterative *** one and two-dimensional numerical results are carried out to demonstrate both accuracy and capacity of the iterative DG method for both cases of l=O(1.and l≪***(m+1.th order of accuracy for L2 and mth order of accuracy for H1.for Pm elements are numerically obtained.

关键词： Poisson-Boltzmann equation nonlinear existence uniqueness DDG methods numerical flux.

来源：评论

学校读者我要写书评

暂无评论

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

请选择保存的检索档案：

请选择收藏分类：

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

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

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：