集群式软件平台敏捷测试

在敏捷开发模式的环境下,对以集群存储业务为导向的集群平台的测试与其他产品的测试有很多不同的地方,需要采用有效的策略和方法。首先介绍了敏捷测试的理论和敏捷测试传统的增量模型,在此基础上结合集群平台敏捷开发中实际的问题提出了适合平台敏捷测试的增量模型和对集群平台用户故事测试时用到的仿真环境的搭建和有效的测试方法。     

采用增量型非负矩阵分解建模的目标跟踪算法

建立鲁棒的外观模型是目标跟踪中的关键问题,为此提出一种基于增量型非负矩阵分解的目标跟踪算法.首先根据转移概率模型在当前帧中预测得到一组图像样本;随后利用非负矩阵分解获取样本在子空间中的坐标向量;在此基础上计算样本与前一帧视频中目标图像在低维坐标向量上的相关性,以具有最大相关性的图像样本作为目标在当前帧中的图像区域;最后以增量的方式完成子空间的在线更新,提高了外观模型的更新效率,且所要求的存储空间大小恒定.实验结果表明,该算法对目标物的外观变化具有良好的自适应性,能够在视频序列中对目标进行稳定的跟踪.     

增量式精确多面体可见外壳

提出一种新的增量式计算精确多面体可见外壳的算法IEPVH。首先,在新视图的图像平面,计算旧可见外壳的边被新光椎切割得到的交点。然后,恢复旧可见外壳的边上交点的局部方向信息并同时获得新光椎边上的交点。接着,恢复新光椎边上交点的局部方向信息。最后,新可见外壳的多边形面片通过一次遍历网格的边的过程被识别出来,并为了便于显示而被划分为三角面片。与EPVH等其他算法相比,IEPVH不但能够让用户更多地参与基于图像3维重建的过程,而且具有空间计算复杂度小。实验证明此算法的高效和鲁棒性。IEPVH的特点使其更易于在移动设备中得到应用。     

概念格的渐进式维护算法

由二元关系导出的概念格是一种非常有用的形式化工具,也很适合于发现数据中潜在的概念。概念格的算法一直是数据挖掘领域研究的热点。本文根据需要对概念格的结构进行一定的修改,采用一个带头、尾指针的链表作为整个算法的数据结构,提出概念格的渐进式维护算法,该算法中包含两个算法,即渐进式构造算法和渐进式删除算法。最后,通过将该算法和其他算法进行比较,得出较好的时间和空间效率。     

基于增量学习SVM的人脸识别

为了提高人脸识别率,本文提出了一种增量学习支持矢量机(SVM)人脸识别方法,有效地对SVM的参数进行更新。提出的方法采用高斯概率模型描述SVM的参数统计特征,在无需额外存储训练数据的前提下,采用增量学习SVM的方式实现参数的更新;并通过最小化分类误差准则最大化SVM两类输出值概率分布间的距离。详细的实验以及与现有方法的比较结果表明,提出的识别方法具有更好的识别性能。     

可增量学习的水下航行器噪声源识别中聚类算法研究

水下航行器的噪声源识别具有训练样本有限,存在偶发或突变噪声源等特点。本文针对这些特点,在具有增量学习能力的水下航行器的噪声源识别系统架构下,提出了一种参数自适应可调的基于密度的聚类算法。实验表明,该算法可以有效避免基于密度的聚类算法的参数敏感性对聚类结果的不良影响,在无监督情况下对水下航行器的机械噪声源样本进行有效聚类。通过该聚类算法标注后的样本可直接作为具有增量学习结构的分类器的训练样本,节省了时间和系统开销。     

Lagrangean relaxation with clusters for point-feature cartographic label placement problems

This paper presents two new mathematical formulations for the point-feature cartographic label placement problem (PFCLP) and a new Lagrangean relaxation with clusters (LagClus) to provide bounds to these formulations. The PFCLP can be represented by a conflict graph and the relaxation divides the graph in small subproblems (clusters) that are easily solved. The edges connecting clusters are relaxed in a Lagrangean way and a subgradient algorithm improves the bounds. The LagClus was successfully applied to a set of instances up to 1000 points providing the best results of those reported in the literature.     

Development of a genetic algorithm for component placement sequence optimization in printed circuit board assembly

This paper describes the development and evaluation of a custom application exploring the use of genetic algorithms (GA) to solve a component placement sequencing problem for printed circuit board (PCB) assembly. In the assembly of PCB’s, the component placement process is often the bottleneck, and the equipment to complete component placement is often the largest capital investment. The number of components placed on a PCB can range from few to hundreds. As a result, developing an application to determine an optimal or near-optimal placement sequence can translate into reduced cycle times for the overall assembly process and reduced assembly costs. A custom application was developed to evaluate the effectiveness of using GA’s to solve the component placement sequencing problem. A designed experiment was used to determine the best representation and crossover type, crossover rate, and mutation rate to use in solving a component sequencing problem for a PCB consisting of 10 components being placed on a single-headed placement machine. Three different representations (path, ordinal, and adjacency) and six appropriate crossover types (partially mapped, ordered, cycle, classical, alternating edges, and heuristic) were evaluated at three different mutation rates and at 11 crossover rates. Two algorithm response variables, the total distance traveled by the placement head and the algorithm solution efficiency (measured as number of generations and algorithm solution time) were used to evaluate the different GA applications. The combination of representation and crossover type along with mutation rate were found to be the most significant parameters in the algorithm design. In particular, path representation with order crossover was found to produce the best solution as measured by the total distance traveled as well as the solution generation efficiency. Increasing the mutation rate led to slightly improved solutions in terms of head travel, but also resulted in increased solution time.     

Optimal replica placement in hierarchical Data Grids with locality assurance

In this paper, we address three issues concerning data replica placement in hierarchical Data Grids that can be presented as tree structures. The first is how to ensure load balance among replicas. To achieve this, we propose a placement algorithm that finds the optimal locations for replicas so that their workload is balanced. The second issue is how to minimize the number of replicas. To solve this problem, we propose an algorithm that determines the minimum number of replicas required when the maximum workload capacity of each replica server is known. Finally, we address the issue of service quality by proposing a new model in which each request must be given a quality-of-service guarantee. We describe new algorithms that ensure both workload balance and quality of service simultaneously.     

渐近跟踪鲁棒控制的混沌同步

对混沌系统同步控制中的控制器进行了研究,因其实际应用受限大等因素而要求系统具有较好的鲁棒性.把渐近跟踪作为系统同步的推广,从控制方法的角度设计一个混沌同步控制器,运用极点配置法求出控制器的增益参数并从控制理论上证明了该思路的可行性.通过对Lorenz系统的数值仿真试验,验证了该方法在控制混沌同步方面的有效性.为混沌控制中设计耐受性高的控制器提供了依据.