Typology of teacher perception toward distance education issues – A study of college information department teachers in Taiwan

The popularity of distance education has grown rapidly over the last decade in Taiwan’s higher education, yet many fundamental teaching–learning issues are still in debate. While teacher–student interaction is a key success factor in distance education, little work has been done on the teachers. The intent of this research was to clarify teacher’s perceptions on key distance education issues and to develop a discernible typology of different groups of teachers based on their perceptions. Because there may be a gulf between teachers and the technology used in distance education, the target of this study was teachers in information related departments in Taiwan’s colleges, who were more familiar with current technology. Factor analysis and cluster analysis were used to derive the typology. Five higher-level issue constructs emerged from the factor analysis: learning effect, customization, administrative challenges, geographic and resource integration, and instructional design challenges. Four groups of teachers, namely the skeptics, the optimists, the mild-promising group, and the outlier, were identified using cluster analysis of teachers’ perceptions on these five higher-level issue constructs. The profiles of the four groups of teachers were summarized and implications were discussed, which should provide useful insights to the policy makers of higher education on distance education decisions.     

Analyzing the performance of a cluster-based architecture for immersive visualization systems

Cluster computing has become an essential issue for designing immersive visualization systems. This paradigm employs scalable clusters of commodity computers with much lower costs than would be possible with the high-end, shared memory computers that have been traditionally used for virtual reality purposes. This change in the design of virtual reality systems has caused some development environments oriented toward shared memory computing to require modifications to their internal architectures in order to support cluster computing. This is the case of VR Juggler, which is considered one of the most important virtual reality application development frameworks based on open source code.     

Design and Implementation of an Agent Home Scheme Strategy for Prefetch-Based DSM Systems

In recent years, cluster computing has been widely investigated and there is no doubt that it can provide a cost-effective computing infrastructure by aggregating computational power, communication, and storage resources. Moreover, it is also considered to be a very attractive platform for low-cost supercomputing. Distributed shared memory (DSM) systems utilize the physical memory of each computing node interconnected in a private network to form a global virtual shared memory. Since this global shared memory is distributed among the computing nodes, accessing the data located in remote computing nodes is an absolute necessity. However, this action will result in significant remote memory access latencies which are major sources of overhead in DSM systems. For these reasons, in order to increase overall system performance and decrease this overhead, a number of strategies have been devised. Prefetching is one such approach which can reduce latencies, although it always increases the workload in the home nodes. In this paper, we propose a scheme named Agent Home Scheme. Its most noticeable feature, when compared to other schemes, is that the agent home distributes the workloads of each computing nodes when sending data. By doing this, we can reduce not only the workload of the home nodes by balancing the workload for each node, but also the waiting time. Experimental results show that the proposed method can obtain about 20% higher performance than the original JIAJIA, about 18% more than History Prefetching Strategy (HPS), and about 10% higher than Effective Prefetch Strategy (EPS).     

ER-TCP: an efficient TCP fault-tolerance scheme for cluster computing

This paper proposes a novel scheme, named ER-TCP, which transparently masks the failures happened on the server nodes of a cluster from clients at TCP connection granularity. In this scheme, TCP connections at the server side are actively and fully replicated to remain consistency so as to be transplanted over healthy parts during failure. A log mechanism is designed to cooperate with the replication to achieve small sacrifice on the performance of communication and makes the scheme scales beyond a few nodes, even when they have different processing capacities. We built a prototype system at a four-node cluster with ER-TCP, and conducted a series of experiments on that. The experimental result told us that ER-TCP has relatively small penalty on the communication performance, especially when it is used to synchronize multiple replicas. The results of real applications show that ER-TCP will incur small sacrifice on performance of web server at light load, and it can be used to distribute files very efficiently and reliably.

Multi-core CPUs,Clusters, and Grid Computing: A Tutorial

The nature of computing is changing and it poses both challenges and opportunities for economists. Instead of increasing clock speed, future microprocessors will have “multi-cores” with separate execution units. “Threads” or other multi-processing techniques that are rarely used today are required to take full advantage of them. Beyond one machine, it has become easy to harness multiple computers to work in clusters. Besides dedicated clusters, they can be made up of unused lab computers or even your colleagues’ machines. Finally, grids of computers spanning the Internet are now becoming a reality.     

蓝鲸集群文件系统中资源交互一致性协议

在蓝鲸集群文件系统中,分布式资源交互在系统异常的情况下会出现资源状态不一致的情况,为解决这一问题,该文提出分布式资源交互一致性协议S2PC-RT。S2PC-RT引入资源交互序号保证一致性,通过增加资源申请空间减少消息等待。证明协议的正确性,并在蓝鲸集群文件系统中实现了协议。测试结果表明,S2PC-RT能够保证资源的一致性,有效提高分布式资源的交互性能。     

数据挖掘在仓库物资补给预测中的应用研究

介绍使用数据挖掘工具SQL Server 2005 Data Mining、SPSS／Clementine进行仓库物资补给预测的方法和步骤并就使用两种教据挖掘工具,利用不同的挖掘算法进行物资补给预测的结果进行比对分析,以便使库存数量和成本之间取得平衡。     

一种含影响力因子的自适应C均值算法

含影响力因子的硬聚类算法(HCMef)在对多于两类规模不均的样本进行聚类时,影响力因子指数对聚类结果影响很大,取值不当会引起类消失.影响力因子指数在0附近穷举,并利用影响力因子指数较大时类规模会在较少训练次数内消失的现象,降低计算量.提出了含影响力因子的自适应C均值聚类策略(AHCMef),并介绍了两阶段聚类方法,进一步提高聚类成功率和执行效率.结果显示,最佳影响力因子指数出现在成功聚类时的较大值附近,聚类效果从该点起随影响力因子指数的减小而降低.对HCMef算法应用于多类规模不均样本情况时,影响力因子指数的选取具有指导意义.     

无线传感网络中基于综合因素的分布式路由算法

近年来由于在多方面的广泛应用,无线传感器网络受到了越来越多的关注.然而限于无线传感器网络自身的限制,如何更好地节省能量,仍为无线传感器路由协议设计中面临的主要问题之一.LEACH等基于分簇的路由协议通过成簇来减少能量消耗,但是成簇过程却带来额外消耗以及冗余.对LEACH协议中簇头生成算法进行了研究并提出了改进,提出了基于节点能量、节点距离以及节点度的分布式优化算法,并对优化算法进行分析与仿真.仿真试验表明,基于综合因素的分布式簇头选举算法优化了簇头选举方式和簇头的分布,从而节省了能量消耗,延长了网络生存周期.