增强式网络考试系统设计

网络考试系统是当前计算机应用的热门研究课题之一．从单一学科、简单题型、随机算法组卷的简单网络考试系统逐渐向多学科,多题型,智能组卷的增强式网络考试系统发展．通过对目标系统进行需求分析,了解其功能需求,设计一个完善的增强式网络考试系统,为最终实现该类型考试系统打下基础．     

An extension of an over-dispersion test for count data

While over-dispersion in capture-recapture studies is well known to lead to poor estimation of population size, current diagnostic tools to detect the presence of heterogeneity have not been specifically developed for capture-recapture studies. To address this, a simple and efficient method of testing for over-dispersion in zero-truncated count data is developed and evaluated. The proposed method generalizes an over-dispersion test previously suggested for un-truncated count data and may also be used for testing residual over-dispersion in zero-inflation data. Simulations suggest that the asymptotic distribution of the test statistic is standard normal and that this approximation is also reasonable for small sample sizes. The method is also shown to be more efficient than an existing test for over-dispersion adapted for the capture-recapture setting. Studies with zero-truncated and zero-inflated count data are used to illustrate the test procedures.     

Patterns for multigrid equidistributed functions: Application to general parabolas and length estimation

We show that for some special functions (called k-multigrid equidistributed functions), we can compute the limit of the frequency of patterns in the discretization of their graph, when the resolution tends to zero. This result is applied to parabolas. We deduce also that local length estimators almost never converge to the length for the parabolas.     

An enhanced error estimator on the constitutive relation for plasticity problems

This paper presents an extension to plasticity problems of a new error estimator on the constitutive relation which was introduced by P. Ladevèze in a recent paper. Numerical experiments show that this enhanced error estimator can lead to a significant improvement in the effectivity indexes in the case of anisotropic meshes, or when perfect plasticity is approached.     

Industrial Robot Navigation and Obstacle Avoidance Employing Fuzzy Logic

This paper proposes a novel conceptual approach based on fuzzy logic to solve the local navigation and obstacle avoidance problem for industrial 3-dof robotic manipulators. The proposed system is divided into separate fuzzy units, which control individually each manipulator link. The fuzzy rule-base of each unit combines a repelling influence, which is related to the distance between the manipulator and the nearby obstacles, with the attracting influence produced by the angular difference, between the actual and the final manipulator configuration, to generate a new actuating command for each link. It can be considered as an on-line local navigation method for the generation of instantaneous collision-free trajectories. The strategy has been successfully applied to manipulators in different simulated workspace environments providing collision-free paths. Some of the simulation results obtained are included.     

基于J2EE的网上商城系统的设计

采用J2EE体系结构,构建一个安全高效的网上商城系统,并对主要模块设计和重要的流程处理作了详细介绍。     

Relative Loss Bounds for On-Line Density Estimation with the Exponential Family of Distributions

We consider on-line density estimation with a parameterized density from the exponential family. The on-line algorithm receives one example at a time and maintains a parameter that is essentially an average of the past examples. After receiving an example the algorithm incurs a loss, which is the negative log-likelihood of the example with respect to the current parameter of the algorithm. An off-line algorithm can choose the best parameter based on all the examples. We prove bounds on the additional total loss of the on-line algorithm over the total loss of the best off-line parameter. These relative loss bounds hold for an arbitrary sequence of examples. The goal is to design algorithms with the best possible relative loss bounds. We use a Bregman divergence to derive and analyze each algorithm. These divergences are relative entropies between two exponential distributions. We also use our methods to prove relative loss bounds for linear regression.     

改进的选择神经网络结构的方法

有关人工神经网络作为在线状态估计器组成基于神经网络的传感器故障检测的研究已有报导。但是这些文章中没有提到如何选择神经网络的结构。神经网络的输入延迟数和隐基单元数影响其对系统的拟合精度,从而影响故障检测的灵敏度。研究了一些现有的选择神经网络结构的方法,以系统化的交叉证实法为基础,经过改进,提出了针对作为在线状态估计器的神经网络选择输入延迟数和隐层单元数的系统化的方法,并用某船在试验场中航行时平台罗经输出的一段数据作了仿真,结果证明该法可行,具有工程实用意义。     

基于图象集似然度的人脸识别

根据人的认识规律,提出了基于图象集的似然度人脸识别方法。该方法把图象集中的各幅图象的信息矩阵的奇异值向量作为矩阵中的一列而构成的图象集特征矩阵。然后,把测试样本的图象集特征矩阵与图象集库中的训练样本图象集的特征矩阵相比较找出它们的相似程序－－图象集的似然度,从而进行人睑图象识别。     

循环冷却水综合在线监控记录系统

在分析当前循环冷却水处理方法的基础上,提出了设计循环冷却水综合在线监控记录系统的必要性。本系统利用多种专用传感器,配合控制电路,实现了循环冷却水的多参数实时测量。并根据参数值分析水质情况,实现了加药的剂量自动控制。本系统还配以上位机,实时显示参数测量值与测量值的存储和导出。经实践证明:本系统功能全,可靠性好,实时性高。