基于本体的语义信息检索的研究

针对传统信息检索在查询准确度方面的问题,在信息检索中引入了语义网的思想,对网络信息的进行语义描述,从而出现了语义信息检索。该文提出了一种语艾信息检索的框架,弃针对该框架结构,给出了实现语义检索的算法,可以实现对信息的精确检索。     

Constructing the Bayesian network structure from dependencies implied in multiple relational schemas

Relational models are the most common representation of structured data, and acyclic database theory is important in relational databases. In this paper, we propose the method for constructing the Bayesian network structure from dependencies implied in multiple relational schemas. Based on the acyclic database theory and its relationships with probabilistic networks, we are to construct the Bayesian network structure starting from implied independence information instead of mining database instances. We first give the method to find the maximum harmoniousness subset for the multi-valued dependencies on an acyclic schema, and thus the most information of conditional independencies can be retained. Further, aiming at multi-relational environments, we discuss the properties of join graphs of multiple 3NF database schemas, and thus the dependencies between separate relational schemas can be obtained. In addition, on the given cyclic join dependency, the transformation from cyclic to acyclic database schemas is proposed by virtue of finding a minimal acyclic augmentation. An applied example shows that our proposed methods are feasible.     

基于ECC的广义门限签密方案设计

为了满足群组之间相互通信时同时需要加密和认证的要求,设计了一个基于椭圆曲线密码体制的广义门限签密方案,该方案能够同时实现,门限签密和,门限共享解签密。在门限共享解签密阶段,利用Chaum-Pedersen离散对数等式知识证明协议的思想实现了对群组成员中恶意成员的检测。通过对该方案进行的安全性分析和效率分析结果表明,该方案可以用较小的计算代价和通信代价安全地实现群组通信中的保密和认证。     

Necessary conditions of optimality for a class of optimal control problems on time scales

A class of optimal control problems of a system governed by linear dynamic equations on time scales with quadratic cost functional is considered. By the Lebesgue Δ-integral theory and the Sobolev-type space H¹ on time scales the weak solution of linear dynamic equations on time scales for both initial value problem and backward problem are introduced, therefore the necessary conditions of optimality are presented. Some typical examples are given for demonstration.     

Boosting k-nearest neighbor classifier by means of input space projection

The k-nearest neighbors classifier is one of the most widely used methods of classification due to several interesting features, such as good generalization and easy implementation. Although simple, it is usually able to match, and even beat, more sophisticated and complex methods. However, no successful method has been reported so far to apply boosting to k-NN. As boosting methods have proved very effective in improving the generalization capabilities of many classification algorithms, proposing an appropriate application of boosting to k-nearest neighbors is of great interest.Ensemble methods rely on the instability of the classifiers to improve their performance, as k-NN is fairly stable with respect to resampling, these methods fail in their attempt to improve the performance of k-NN classifier. On the other hand, k-NN is very sensitive to input selection. In this way, ensembles based on subspace methods are able to improve the performance of single k-NN classifiers. In this paper we make use of the sensitivity of k-NN to input space for developing two methods for boosting k-NN. The two approaches modify the view of the data that each classifier receives so that the accurate classification of difficult instances is favored.The two approaches are compared with the classifier alone and bagging and random subspace methods with a marked and significant improvement of the generalization error. The comparison is performed using a large test set of 45 problems from the UCI Machine Learning Repository. A further study on noise tolerance shows that the proposed methods are less affected by class label noise than the standard methods.     

随机正则(k,r)-SAT问题的可满足临界

研究k-SAT问题实例中每个变元恰好出现r=2s次,且每个变元对应的正、负文字都出现s次的严格随机正则（k,r）-SAT问题.通过构造一个特殊的独立随机实验,结合一阶矩方法,给出了严格随机正则（k,r）-SAT问题可满足临界值的上界.由于严格正则情形与正则情形的可满足临界值近似相等,因此得到了随机正则（k,r）-SAT问题可满足临界值的新上界.该上界不仅小于当前已有的随机正则（k,r）-SAT问题的可满足临界值上界,而且还小于一般的随机k-SAT问题的可满足临界值.因此,这也从理论上解释了在相变点处的随机正则（k,r）-SAT问题实例通常比在相应相变点处同规模的随机k-SAT问题实例更难满足的原因.最后,数值分析结果验证了所给上界的正确性.     

基于索引视图实现动态数据仓库的实时数据加载

随着数据仓库技术的不断普及,基于数据仓库技术的决策支持系统在企业得到了广泛应用,同时出现了动态数据仓库。随着动态数据仓库在决策支持领域扮演的角色越来越重要,企业利用决策支持系统从辅助进行战略决策开始向战术决策转变。而要进行战术性的分析,数据仓库中必须有动态变化的最新数据,实现数据仓库的“动态”特性的关键又在于实现“动态数据获取”,即实现实时数据捕获加载。提出了基于索引视图实现动态数据仓库的实时数据加载,并通过实验验证了其可行性。该方法对进一步深入研究实时数据捕获技术有一定的借鉴作用。     

基于Adams/Car的汽车前悬架仿真分析及优化设计

针对某车型的麦弗逊前悬架系统,用车辆多体动力学仿真软件Adams/Car建立该悬架的虚拟样机模型,对其进行双轮同向跳动激振仿真分析,并综合评价该悬架的车轮定位参数、主销后倾拖距和转向角随轮跳的响应特性.在仿真分析的基础上,针对不合理的结构设计参数,利用Adams/Insight模块进行基于设计变量灵敏度分析的优化设计.优化后的悬架参数能很好地满足设计要求,从而达到提高该悬架系统整体性能的目的.     

基于位图生成三维地形的设计与实现

地形模型的建立是地理信息系统GIS中三维地形仿真研究的重要部分。地形位图建立地形模型的方法是生成地形模型的其中之一,易于实现,位图的灰度值转换成可用高程值,实现三维地形的生成。阐述了该算法的程序流程,使用Visual Studio2008和OpenGL编程实现该算法,具有效率高、运行速度快的特点,特别适合虚拟场景和虚拟三维地形的生成。