The evaluation of cluster policy by fuzzy MCDM: Empirical evidence from HsinChu Science Park

In the recent years, industrial clusters have received considerable attention from economists and industrial analysts, because they are seen as the main reason for economic growth and success of certain economic region. This study systematically reviews past researches of industrial cluster. The purpose of this paper is to contribute to the understanding of this issue regarding the driving forces for the growth of industrial cluster and find out the priority among these cluster policies. Taiwan HsinChu Science Park is a prime example for this paper, and its connection with the innovative participators. We begin with an examination of the literature on cluster about its driving forces and policies upon which we propose a conceptual framework. In doing so, we explore the cluster-based industrial system. Then this research adopts the Fuzzy Analytic Hierarchy Process as the analytical tool. The Fuzzy Analytic Hierarchy Process method is used to determine the weightings for evaluation dimension among decision makers. From our research results, the Factor Conditions is the most important driving force for advancing the industrial cluster performance. Moreover, the promotion of international linkages policy and broader framework policies rank the first two priorities for cluster policy. Overall, this paper concludes with some simulations of cluster policy alternatives confronting the industry and the Taiwanese government.     

风机流场并行数值模拟在集群系统上的应用

介绍集群系统的特点及其软硬件配置环境。利用计算流体力学商用软件Fluent对一种新型垂直轴风力机风轮在曙光天潮超级服务器4000A集群上进行数值模拟及并行计算,得到风轮内外部的三维流场,实现该软件在高性能并行计算机上的应用,为并行有限元分析提供一个基础计算平台。     

移动Sinks无线传感器网络的能量效率分析

能量效率是无线传感器网络的关键性问题,无线传感器网络通过移动sinks节点延长了网络的生命周期。讨论一些关键性要素对能量效率的影响,如簇的大小、移动sinks的速度、数量和数据包生命周期等。分析基于能量效率的单跳、多跳路由模式,提出最优跳数的簇路由模式,并以仿真实验验证移动sinks无线传感器网络的系统性能。     

一种伪随机自治服务可生存调度算法

可生存调度算法是服务可生存性研究中的重要内容,在服务器集群系统中引入随机策略,使服务在各个服务器之间的轮转产生不确定效果,可增加攻击者攻击系统的难度,增强系统可生存性。介绍可生存性研究的层次划分,指出可生存调度算法在可生存性研究中的作用,分析现有可生存调度算法的优缺点,提出一种伪随机自治服务可生存调度算法,并分析算法的性能。     

集群系统中的FP-Growth并行算法

针对FP-Growth算法面临大规模数据库时空效率不高的问题,提出一种面向计算机集群的并行算法。采用投影方法直接寻找频繁项的条件数据库,将挖掘条件数据库的工作分化成若干独立的子任务,分配到集群中的节点上并行实现,由中央节点汇总结果并输出。结果证明,该算法不仅能够提高计算速度,解决数据库规模过大时内存溢出的情况,且具有良好的延展性。     

一种低功耗自适应集簇分层协议的优化算法

针对低功耗自适应集簇分层(LEACH,low energy adaptive clustering hierarchy)协议在簇头(CH,cluster head)选择和能量消耗方面的缺陷,提出了改进的LEACH协议,记为LEACH-Ⅰ(LEACH-improved)协议.LEACH-Ⅰ协议利用节点离基站的位置和剩余能量选择簇头,使得CH均匀分布.同时,减轻CH负担,从簇内选择剩余能量最大的节点作为数据融合节点,分担原本由CH完成的数据融合任务,平衡了节点间的能量消耗问题.实验结果表明,提出的LEACH-Ⅰ协议有效地延长网络生存时间,比LEACH、DDEEC的网络生存时间分别提高了60％、43％.     

基于改进蛙跳算法的WSNs路由协议

在分析已有的各类分簇方法后,提出了一种改进蛙跳算法的无线传感器网络(WSNs)路由协议.将模拟退火(SA)算法的Metropolis判别准则引入到蛙跳算法中,改进蛙跳算法的局部搜索能力.该协议结合传感器节点本身剩余能量和位置建立适应度函数,通过改进蛙跳算法实现适应度函数的最优求解,从而获得合适的分簇,并在簇头节点数据传输时采用新的路由方式.仿真实验表明:该方法在降低网络能耗,延长网络的生存周期方面有明显的优势.     

迁移近邻传播聚类算法

在目标域可利用数据匮乏的场景下,传统聚类算法的性能往往会下降.在该场景下,通过抽取源域中的有用知识用于指导目标域学习以得到更为合适的类别信息和聚类性能,是一种有效的学习策略.借此提出一种基于近邻传播的迁移聚类（transfer affinity propagation,简称TAP）算法,在源域和目标域数据分布相似的情况下,通过引入迁移学习机制来改善近邻传播聚类（affinity propagation,简称AP）算法在数据匮乏场景下的聚类性能.为保证迁移的有效性,TAP在综合考虑源域和目标域的统计特性及几何特征的基础上改进AP算法中的消息传递机制使其具备迁移能力,从而达到辅助目标域学习的目的.此外,通过TAP对应的因子图,亦可说明TAP可以以类似AP的消息传递机制,在目标域数据匮乏的情况下进行高效的知识迁移,为最终所获得的聚类结果提供了保证.在模拟数据集和真实数据集上的仿真实验结果显示,所提出的算法较之经典AP算法在处理非充分数据聚类任务时具有更佳的性能.     

An Objective Deghosting Quality Metric for HDR Images

Reconstructing high dynamic range (HDR) images of a complex scene involving moving objects and dynamic backgrounds is prone to artifacts. A large number of methods have been proposed that attempt to alleviate these artifacts, known as HDR deghosting algorithms. Currently, the quality of these algorithms are judged by subjective evaluations, which are tedious to conduct and get quickly outdated as new algorithms are proposed on a rapid basis. In this paper, we propose an objective metric which aims to simplify this process. Our metric takes a stack of input exposures and the deghosting result and produces a set of artifact maps for different types of artifacts. These artifact maps can be combined to yield a single quality score. We performed a subjective experiment involving 52 subjects and 16 different scenes to validate the agreement of our quality scores with subjective judgements and observed a concordance of almost 80%. Our metric also enables a novel application that we call as hybrid deghosting, in which the output of different deghosting algorithms are combined to obtain a superior deghosting result.