信息检索中的广义作用效应链应用研究

广义作用句和广义效应句的划分是作用效应链思想在句类体系中的体现.这一划分是对自然语言语句的一个最基本的分类.如果结合信息检索中采取的统计学办法,在检索结果的基础上进行二次精筛选,则提供给查询用户的结果必将更符合实际需求,能更有效提高信息检索的正确率.从人为数据统计结果来看,这一思路有效地把统计方·法和基本规则方法结合起来,提高了信息检索的检索准确率.     

一种改进的基于时空混沌系统的Hash函数构造方法

首先介绍了一种以时空混沌为基础的构造Hash函数的典型方案,并分析了它的不足和安全性问题.在此基础上提出了一种改进的Hash函数构造方法.理论和仿真实验分析表明,该算法具有更好的统计特性和更高的效率,有效地弥补了原算法中存在的碰撞漏洞.     

一种新颖隶属度函数的模糊支持向量机

传统的支持向量机(SVM)训练含有外部点或噪音数据时,容易产生过拟合(over-fitting)。通过模糊隶属度函数来降低外部点或被污染数据的选择。本文提出了一种新的核隶属度函数,这种新的隶属度函数不仅依赖于每个样本点到类型中心的距离,还依赖于该样本点最邻近的K个其他样本点的距离。实验结果表明了具有该隶属度函数的模糊支持向量机的有效性。     

Pi演算对图灵机的表达

为了研究Pi演算的表达能力,我们试着用它来表达图灵机。研究结果表明,只要对Pi演算进行一定的的扩展,即引入某些函数符号,允许对发送的名字作一定的运算,就可以用Pi演算的规约来表达图灵机的运算过程。     

Hierarchical classification of protein function with ensembles of rules and particle swarm optimisation

This paper focuses on hierarchical classification problems where the classes to be predicted are organized in the form of a tree. The standard top-down divide and conquer approach for hierarchical classification consists of building a hierarchy of classifiers where a classifier is built for each internal (non-leaf) node in the class tree. Each classifier discriminates only between its child classes. After the tree of classifiers is built, the system uses them to classify test examples one class level at a time, so that when the example is assigned a class at a given level, only the child classes need to be considered at the next level. This approach has the drawback that, if a test example is misclassified at a certain class level, it will be misclassified at deeper levels too. In this paper we propose hierarchical classification methods to mitigate this drawback. More precisely, we propose a method called hierarchical ensemble of hierarchical rule sets (HEHRS), where different ensembles are built at different levels in the class tree and each ensemble consists of different rule sets built from training examples at different levels of the class tree. We also use a particle swarm optimisation (PSO) algorithm to optimise the rule weights used by HEHRS to combine the predictions of different rules into a class to be assigned to a given test example. In addition, we propose a variant of a method to mitigate the aforementioned drawback of top-down classification. These three types of methods are compared against the standard top-down hierarchical classification method in six challenging bioinformatics datasets, involving the prediction of protein function. Overall HEHRS with the rule weights optimised by the PSO algorithm obtains the best predictive accuracy out of the four types of hierarchical classification method.     

A new adaptive backstepping Coulomb friction compensator for servo control systems

A new Coulomb friction compensator is proposed for servo control systems in this paper. The novelty of the new approach lies in its capability of assigning the eigenvalues of the resulting closed loop system while attacking the problem. First, based on the standard backstepping methodology, an implicit Lyapunov function, with part of the components being only symbolically constructed at the very beginning, is utilized. To increase the robustness of the system against disturbance and model inaccuracy, an integral term is employed in the design. Using part of the variable gradient method, we are able to turn the implicit Lyapunov function into an explicit one, which is positive definite, and whose time‐derivative is negative definite. Second, it will be shown that the resulting closed loop error system is a switched linear system with two possible active modes that share the same set of eigenvalues, which is at our disposal. Unlike the common adaptive control design methods, such as the Control Lyapunov Function approach, in which the gains are typically positive but otherwise arbitrary, and are hence difficult to choose and have a lack of connection with the system's performance, our new scheme imposes two further constraints on the gains. It turns out that we can then match these gains with the coefficients of the desired characteristic equation of the closed loop system. In this respect, the gains are linked to the system's overall performance, which is a new and very appealing feature for such a scheme. Finally, a procedure of constructing a common Lyapunov function is provided to prove exponential stability of the aforementioned switched linear system. In addition, using the invariance principle, we will show the convergence of the estimated Coulomb friction coefficient to its real value. Numerical simulations are given to validate the effectiveness of the design and its robustness against friction time‐variations. Compared to existing results, the proposed scheme is much simpler, hence, much more advantageous computationally. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

建筑美学

把建筑定义为美学带有主观随意性,局限性,除了形式美,建筑还具有实用,经济,技术等价值。本文分别从建筑的形式美,使用功能,先进技术、环境特色等方面具体阐述建筑美学,对大多数人关心的建筑美学做一个冷静而深入的思考,探究这样一种美从何而来。     

图像边缘检测在DM642上的应用研究

采用TMS320DM642EVM作为数字图像处理硬件平台,利用CCS开发环境来构建程序并对其进行优化;通过对改进后的Log算子和小波多尺度方法提取到的边缘图像进行数据融合,得到一幅新的边缘图像。实验结果表明,该方法提高了边缘检测的运算速度,满足了实时性要求;并能有效地抑制噪声的影响,保留了图像边缘细节。     

基于惩罚函数的演化测试优化方法研究

演化测试是一种有效的测试用例自动生成技术。它将测试用例的生成的过程转化为一个利用遗传算法进行数值优化的问题,可以自动生成高质量的测试用例。目前,演化测试技术已经在许多测试领域被广泛地研究。研究发现,演化测试过程中无效解和局部最优解的存在扰乱了演化正常进行,降低了演化测试的性能。针对演化测试中存在的问题,提出基于惩罚函数的适应值函数F（x）,对无效解和局部最优解进行惩罚,有助于演化过程中根据适应值选择更合适的个体进行遗传操作,提高演化测试的性能。实验结果表明,F（x）有效降低了无效解和局部最优解的适应值,提高了演化测试的性能。     

固态功率组件热耦合效应研究

文中基于热叠加原理研究了固态功率组件中多个离散分布的集中热源的热耦合效应,并证明强迫对流下应用热叠加原理计算的温度场与整场系统数值模拟的结果相当吻合,用它来进行热耦合效应的分析研究是有效的.