BPEL流程监视的可视化实现

When a BPEL process is executed, it is necessary to dynamically monitor the process. BPEL is a executable language, which is not suitable for visual monitoring. On the other hand, BPMN is designed to visually describe business process and is more intuitive for monitoring. To visually monitor a BPEL process, transformation from BPEL to BPMN is necessary. However, current study of transformation from BPEL to BPMN does not support the transformation of "link" activity. Besides, no work has been done to add supplementary information into BPMN during transformation. In this paper, we transform nested BPEL process into a flat BPMN process graph without hierarchy through applying a flattening strategy. Especially, we analyze various scenarios of the transformation of link activity, and provide a method to deal with it. Besides, we analyze the mapping between BPEL activities and BPMN graph, through which we found out that some supplementary information cannot automatically obtained from BPEL process. These supplementary information need to be added during transformation. At the end of this paper, we present the structure of our monitoring tool which is based on our transformation algorithm.     

多数据项广播调度策略

多数据项广播是移动计算环境中一种重要的数据访问方式.为减少用户的平均访问时间和响应最多事务请求,提出了一种新的多数据项广播调度策略.调度策略分为两个阶段,第一阶段根据各事务包含的数据项数目和对重复申请数据项的处理选择事务请求;第二阶段对已选择的事务请求用QEM算法进行调度.实验结果表明,它比现有的QEM算法有更高事务调度成功率和更短的平均访问时间.     

一种特征加权FCM算法的图像重建技术研究

针对传统FCM(Fuzzy C-means)算法中初始聚类中心选取的随机性以及对初始值敏感的问题,提出一种基于进化策略的色彩空间加权的FCM聚类算法.通过在RGB(Red Green Blue)色彩空间矢量中设置加权矩阵来补偿各色彩的非均匀性,并采用一种类内最小距离最大的统计聚类算法来初始化聚类中心.实验结果表明,该算法能有效减少颜色量化后的均方差值,保持重建图像的整体层次和局部特征细节,对研究图像处理技术有较强的实际意义.

Abstract：

Aiming at a defect on randomness of the initial clustering center choosing and sensitivity of initial value in tradition FCM(fuzzy C-means) algorithm, a clustering algorithm about FCM of weighted color space based on evolutionary strategy is proposed. By interposing weighted matrix in RGB(Red Green Blue) color space, the color's inhomogeneous is compensated. And by using a statistics clustering algorithm of minimal maximal distance, clustering center is initiated. The experimental results show that the algorithm can decrease effectively the mean square deviation of color quantization, keep overall arrangement of ideas and part characteristic detail in image reconstruction, and has practical value to the study of the image process technology.     

一种新型套筒天线宽频特性的HFSS仿真分析

针对传统套简单极子天线结构变量复杂、要做到3:1的频带宽度难的问题,利用电抗补偿方法设计了一款位于特殊接地铜管上的双层套筒偶极子天线,并利用HFSS软件对结构进行仿真分析,找到影响频带及反射特性的结构参数,通过软件自带的优化功能,对各个参数进行仿真优化,得到工作在800-960MHz,1710-1920MHz,2400-2483MHz频带范围内驻波系数低于1.5的实用套筒天线结构,包含目前移动通信所用频带:2G、3G和WLAN.天线在同一个结构上实现多频工作,且在各个频段内反射很小,节省了天线资源,利于系统集成.     

基于Delaunay三角剖分的半径补偿新算法

合理的半径补偿算法能有效提高逆向工程的最终精度.在分析了现有半径补偿算法及其相应优缺点的基础上,针对三角网格法,通过Delaunay三角剖分思想的引入,提出了一种基于Delaunay三角剖分的半径补偿新算法,并对其中三角剖分的优化准则、边界点的处理等关键技术进行了详细的阐述,最后以增压器叶轮为例,实现了叶轮叶面测量数据的半径补偿.     

基于模糊理论的非处方药的满意度评价系统

为了帮助顾客从众多对症的非处方药中选出最满意的药品,提出了开发1个基于Web的非处方药满意度评价系统。系统根据顾客提供的典型症状,采用疾病与症状相结合的选药策略,查找出所有对症的非处方药,并以药品安全性、疗效、稳定性、易用性、价格作为评价因素,根据顾客的关注角度和关注程度确定各因素权重,用模型b=W·R对对症药品进行满意度评价,按满意度高低依次推荐。经实际应用,系统推荐准确度在70%以上。     

优势关系粗糙集在RoboCup中的决策分析

截球能力是RoboCup(Robot World Cup)仿真比赛中个体智能体的核心技能之一.为提高截球的成功率,将解析法和经验法相结合,提出了一种基于优势关系粗糙集的截球策略.着重讨论了基于优势关系的知识约简和截球决策规则的提取,研究了RoboCup运动模型中截球点的二分法求解.最后进行了仿真平台中的决策分析,验证了该策略的有效性.     

面向多层次知识表达的贝叶斯分类模型研究

提出多模式贝叶斯分类算法,由变量值之间的条件独立和条件相关性推断因果关系,根据每个完整随机样本而非整个样本空间构造子模式.结合局部计算近似推理进行概率密度和条件概率分布估计,在此基础上采用后离散化策略自动确定连续变量边界.在UCI机器学习数据集上的实验结果证明了该算法的合理性和有效性.     

多普勒频率补偿算法在GPS信号捕获中的应用

在GPS卫星高速运动和地面GPS接收机的移动中,由于卫星和接收机之间的径向速度引起了载波多普勒频移、C/A码的多普勒频移和数据码的多普勒频移,多普勒频移会对GPS接收机的信号捕获产生影响,使其准确度下降。针对上述情况,在常用的相干积分结合非相干积分的GPS信号捕获方案中引入一种多普勒频率补偿算法,并对此算法进行相应的仿真。结果表明该设计方案是可行的,引入的补偿算法能够有效消除多普勒频移对GPS信号捕获的影响,能够实现对GPS卫星信号的多普勒和码相的准确捕获。     

Auto-tuning strategy for evolutionary algorithms: balancing between exploration and exploitation

Genetic Algorithms (GAs) and other Evolutionary Algorithms (EAs), as powerful and broadly applicable stochastic search and optimization techniques have been successfully applied in the area of management science, operations research and industrial engineering. In the past few years, researchers gave lots of great idea for improvement of evolutionary algorithms, which include population initialization, individual selection, evolution, parameter setting, hybrid approach with conventional heuristics etc. However, though lots of different versions of evolutionary computations have been created, all of them have turned most of its attention to the development of search abilities of approaches. In this paper, for improving the search ability, we focus on how to take a balance between exploration and exploitation of the search space. It is also very difficult to solve problem, because the balance between exploration and exploitation is depending on the characteristic of different problems. The balance also should be changed dynamically depend on the status of evolution process. Purpose of this paper is the design of an effective approach which it can correspond to most optimization problems. In this paper, we propose an auto-tuning strategy by using fuzzy logic control. The main idea is adaptively regulation for taking the balance among the stochastic search and local search probabilities based on the change of the average fitness of parents and offspring which is occurred at each generation. In addition, numerical analyses of different type optimization problems show that the proposed approach has higher search capability that improve quality of solution and enhanced rate of convergence.