Scalable classification by clustering： Hybrid can be better than Pure

The problem of scalable classification by clustering in large databases was discussed. Clustering based classification method first generates clusters using clustering algorithms. To classify new coming da-ta points, it finds the κ nearest clusters of the data point as neighbors, and assign each data point to the dominant class of these neighbors. Existing algorithms incorporated class information in making clustering decisions and produced pure clusters （each cluster associated with only one class）. We presented hybrid cluster based algorithms, which produce clusters by unsupervised clustering and allow each cluster associ- ated with multiple classes. Experimental results show that hybrid cluster based algorithms outperform pure ones in both classification accuracy and training soeed.     

Efficient storage and retrieval of clustering results using relational database

The problem of how to efficiently store and query the clustering results was considered. Three different storage schemas for clustering results using relational database were proposed, namely, full schema (f-schema), partial schema (p-schema) and compressed schema (c-schema). At the same time, a classification for queries issued to the clustering results was also presented. Finally, we empirically studied the performance of proposed queries on different storage schemas. To our knowledge, this is the first work to address the problem.     

氯苯基三唑硅化合物的合成及其生物活性测定

采用新的合成法，对三唑有机硅化合和进行了合成，中间体及产物的结构得到了ＩＲ，１ＨＮＭＲ及元素分析的证实；讨论了影响气相光氯化反应、格氏反应及缩合反应的反应条件，测定了ＰＳＴ１，ＰＳＴ２的生物活性。     

基于混合方法的室内毫米波传播特性研究

为了研究室内毫米波的传播特性,结合射线跟踪法(ray tracing, RT)和时域有限差分法(finite difference time domain, FDTD)各自的优点,提出了一种基于射线跟踪法和时域有限差分法的混合方法。介绍了混合方法的基本思想,给出了混合方法建模步骤,利用射线跟踪法分析较为空旷的区域,而对于射线跟踪法不能准确预测的含有复杂间断点区域,用时域有限差分法进行了分析。探讨了发射信号频率为60 GHz,室内和室外到室内2种仿真环境下接收信号场强随距离变化的分布以及某一定点接收信号的时延信息。仿真结果可知,复杂环境下混合方法比射线跟踪法的精度高;在接收点的计算量上,混合方法比时域有限差分方法的计算量少。由此表明,混合方法是一种行之有效的方法,能够准确地预测毫米波的传播特性。