Implementation of high-order implicit runge-kutta methods

In this paper, we develop single-Newton iterative schemes for the solution of the stage equations of some implicit Runge-Kutta methods such as the four-stage Gauss and Radau IIA methods and the five-stage Lobatto IIIA formula. We also compare the implementation cost of these schemes with the simplified-Newton iteration and we present some numerical experiments on some well-known stiff test problems to show that the proposed iterations are reliable and efficient.     

Convergence of memory gradient methods

In this paper we present a new class of memory gradient methods for unconstrained optimization problems and develop some useful global convergence properties under some mild conditions. In the new algorithms, trust region approach is used to guarantee the global convergence. Numerical results show that some memory gradient methods are stable and efficient in practical computation. In particular, some memory gradient methods can be reduced to the BB method in some special cases.     

Finite difference methods and group analysis for a class of quasilinear-hyperbolic equations ∗

In this paper we consider the theory of finite difference methods which find application in numerical solution of hyperbolic nonlinear problems.

We first introduce a class of quasilinear-hyperbolic mathematical models. Thus we consider some finite difference methods for these models and we give a conditioned stability criterion. In closing we report some experience of numerical tests performed by applying discrete perturbation stability analysis, for which we check the validity of the given stability condition.     

On computing logic programs

In this paper we present and compare some classical problem-solving methods for computing the stable models of logic programs with negation. Using a graph theoretic representation of logic programs and their stable models, we discuss and compare linear programming, propositional satisfiability, constraint satisfaction, and graph methods.     

视频显著性检测研究进展

视频显著性检测是计算机视觉领域的一个热点研究方向,其目的在于通过联合空间和时间信息实现视频序列中与运动相关的显著性目标的连续提取.由于视频序列中目标运动模式多样、场景复杂以及存在相机运动等,使得视频显著性检测极具挑战性.本文将对现有的视频显著性检测方法进行梳理,介绍相关实验数据集,并通过实验比较分析现有方法的性能.首先,本文介绍了基于底层线索的视频显著性检测方法,主要包括基于变换分析的方法、基于稀疏表示的方法、基于信息论的方法、基于视觉先验的方法和其他方法五类.然后,对基于学习的视频显著性检测方法进行了总结,主要包括传统学习方法和深度学习方法,并着重对后一类方法进行了介绍.随后,介绍了常用的视频显著性检测数据集,给出了四种算法性能评价指标,并在不同数据集上对最新的几种算法进行了定性和定量的比较分析.最后,对视频显著性检测的关键问题进行了总结,并对未来的发展趋势进行了展望.     

具有最大代数免疫度的布尔函数的构造

系统地总结了现有的具有最大代数免疫度的布尔函数的构造方法,将现有各种构造方法按其构造思想的不同分为有代表性的几类,并分别介绍了基于这几类方法的一些结果和进展,其中包括作者自己在该方面的研究结果。     

The numerical solution of linear fuzzy Fredholm integral equations of the second kind by using finite and divided differences methods

In recent years, many numerical methods have been proposed for solving fuzzy linear integral equations. In this paper, we use the divided differences and finite differences methods for solving a parametric of the fuzzy Fredholm integral equations of the second kind with arbitrary kernel and present some examples to illustrate this method.     

Applying abstract acceleration to (co-)reachability analysis of reactive programs

Acceleration methods are commonly used for computing precisely the effects of loops in the reachability analysis of counter machine models. Applying these methods on synchronous data-flow programs, e.g. Lustre programs, requires to deal with the non-deterministic transformations due to numerical input variables. In this article, we address this problem by extending the concept of abstract acceleration of Gonnord et al. to numerical input variables. Moreover, we describe the dual analysis for co-reachability. We compare our method with some alternative techniques based on abstract interpretation pointing out its advantages and limitations. At last, we give some experimental results.     

Characterizing Strong Stability Preserving Additive Runge-Kutta Methods

Space discretization of some time dependent partial differential equations give rise to ordinary differential equations containing additive terms with different stiffness properties. In these situations, additive Runge-Kutta (additive RK) methods are used. For additive RK methods the curve of absolute monotonicity gives stepsize restrictions for monotonicity. Necessary conditions for nontrivial curves of absolute monotonicity are the nonnegativity of the additive RK coefficients and some inequalities on some incidence matrices. In this paper we characterize strong stability preserving additive Runge-Kutta methods giving some order barriers and structural properties. Research supported by the Ministerio de Educación y Ciencia, Project MTM2005-03894.     

数据开采与统计学

数据开采是利用现代统计学知识和计算知识从大型数据库中发现潜在的有用模式的学科。可以说,数据开采的目的和数据开采中使用的方法,覆盖了古典的统计学应用范畴。然而,统计学和数据开采在哲学上和使用方法上都有许多的差别。文中描述统计学和数据开采方法在知识发现上的差异,指出统计学和数据开采可通过彼此学习和互相使用来得到发展。     

网络扫描隐蔽性分析

各种不同的网络扫描方法,其隐蔽性和效率根据不同的原理而各不相同。同种扫描也可以采用不同的使用策略和芳法而改变其隐蔽性。分析了各种网络扫描的隐蔽性,提出了对付隐蔽扫描可以采取的一些通用策略,并针对不同的扫描方式给出相应的对策。     

基于VB的分形图形实现方法

本文阐述了使用Visual Basic的可视化编程方法进行分形图形程序设计的通用方法和注意事项,并给出了一些具体例程加以说明。     

Functionally based augmented sculpting

In this paper we describe an approach to computer‐aided sculpting concerned with the creation and modification of digital models based on physical abstract sculptures. We begin by presenting a survey of current methods for the creation of computer‐aided sculptured artefacts. Then we proceed to present some original methods and tools based on the function representation of geometric models. We introduce a specialized computer language, named HyperFun, which facilitates the modelling of complex objects. As well as presenting computer‐generated animated models of pre‐existing sculptures by Russian artist Igor Seleznev, we also show how some interesting novel shapes can be generated using the HyperFun system. Finally we outline two advanced projects concerned with creating a sculpture‐based augmented reality which allows for the interactive participation of the observer. In this paper, we present experimental results, which hopefully have some artistic appeal. These results were produced by an international team of researchers and students collaborating through the Internet. Copyright © 2005 John Wiley & Sons, Ltd.     

A hybrid recommendation approach for a tourism system

Many current e-commerce systems provide personalization when their content is shown to users. In this sense, recommender systems make personalized suggestions and provide information of items available in the system. Nowadays, there is a vast amount of methods, including data mining techniques that can be employed for personalization in recommender systems. However, these methods are still quite vulnerable to some limitations and shortcomings related to recommender environment. In order to deal with some of them, in this work we implement a recommendation methodology in a recommender system for tourism, where classification based on association is applied. Classification based on association methods, also named associative classification methods, consist of an alternative data mining technique, which combines concepts from classification and association in order to allow association rules to be employed in a prediction context. The proposed methodology was evaluated in some case studies, where we could verify that it is able to shorten limitations presented in recommender systems and to enhance recommendation quality.     

软件多进程结构改造为多线程结构的方法研究

将软件的某些进程结构改造为多线程结构，可以解决逻辑并发性、物理并行性等问题，显著提高运行效率。但如何改造(特别是大型软件)是一个比较困难的事情，方法不当很容易造成系统不稳定。该文针对目前该领域研究多局限于理论分析，缺少具体实施方法的问题，提出了一套在Linux环境下将软件的多进程结构改造成多线程结构的具体方案，并围绕改造信号量、信号处理和全局变量等几个难点，提出合理的解决方法。最后，应用此方法成功地将一个著名开放源代码数据库(Poatgre SQL)改造为多线程结构数据库。性能得到显著提高。     

Opinion summarization methods: Comparing and extending extractive and abstractive approaches

In the last years, the opinion summarization task has gained much importance because of the large amount of online information and the increasing interest in learning the user evaluation about products, services, companies, and people. Although there are many works in this area, there is room for improvement, as the results are far from ideal. In this paper, we present our investigations to generate extractive and abstractive summaries of opinions. We study some well-known methods in the area and compare them. Besides using these methods, we also develop new methods that consider the main advantages of the ones before. We evaluate them according to three traditional summarization evaluation measures: informativeness, linguistic quality, and utility of the summary. We show that we produce interesting results and that our methods outperform some methods from literature.     

A recent survey on computational techniques for solving singularly perturbed boundary value problems

This survey paper contains a surprisingly large amount of material and indeed can serve as an introduction to some of ideas and methods of singular perturbation theory. In continuation of a survey performed earlier, this paper limits its coverage to some standard numerical methods developed by numerous researchers between 2000 and 2005. A summary of the results of some recent methods is presented and this leads to conclusions and recommendations regarding methods to use on singular perturbation problems. Because of space constraints, we considered one-dimensional singularly perturbed boundary value problems only.     

移动IP切换对TCP性能影响的分析

介绍了移动IP切换的发展过程及原理,描述了切换造成TCP性能下降原因和一些实验验证数据。说明为了更好地满足用户需求,移动IP和TCP需要作进一步改进,并提出了相应的解决办法。     

Solving Electrical Distribution Problems Using Hybrid Evolutionary Data Analysis Techniques

Real-world electrical engineering problems can take advantage of the last Data Analysis methodologies. In this paper we will show that Genetic Fuzzy Rule-Based Systems and Genetic Programming techniques are good choices for tackling with some practical modeling problems. We claim that both evolutionary processes may produce good numerical results while providing us with a model that can be interpreted by a human being. We will analyze in detail the characteristics of these two methods and we will compare them to the some of the most popular classical statistical modeling methods and neural networks.     

Some fourth-order nonlinear solvers with closed formulae for multiple roots

In this paper, we present six new fourth-order methods with closed formulae for finding multiple roots of nonlinear equations. The first four of them require one-function and three-derivative evaluation per iteration. The last two require one-function and two-derivative evaluation per iteration. Several numerical examples are given to show the performance of the presented methods compared with some known methods.