文化嵌入与集群发展的共演机制研究

作为影响集群发展的重要"软环境",文化嵌入通过影响集群创新系统的结构和行为进而影响集群的竞争优势。从动态视角看,这些关系之间存在着共演,共演可能出现耦合或锁定两种不同结果,共演耦合一般出现在集群发展初期;而共演锁定则更可能在集群发展的后期出现,即最初导致集群发展的文化因素也往往是集群衰亡的原因。共演锁定表明了文化过度嵌入,从内在根源分析,文化的过度嵌入来自于文化功能和性质形成的路径依赖导致的锁定。因此,为了保持集群长期可持续发展,必须实现文化的适度嵌入。     

Variable selection in clustering

Standard clustering algorithms can completely fail to identify clear cluster structure if that structure is confined to a subset of the variables. A forward selection procedure for identifying the subset is proposed and studied in the context of complete linkage hierarchical clustering. The basic approach can be applied to other clustering methods, too.     

由Al12C原子集团构造晶体的理论探讨

使用基于混合基表示的第一原理赝势法,研究了由Ａｌ１２Ｃ原子集团立方密堆积构造而成的晶体的电子和几何结构．对所构成的晶体的晶格常数和集团中各原子在晶体场下的位置改变都进行了没有可调参数的从头计算．结果表明,这样构成的晶体将是金属而非半导体,Ａｌ１２Ｃ原子集团之间在构成晶体时有较强的相互作用,晶场中的集团不再具有类似惰性原子的性质．     

利用ISSR分析野生蘑菇与双孢蘑菇的遗传多样性

摘要：利用Inter- Simple Sequence Repeat ,简单序列重复区间扩增(ISSR )分子标记对一批野生蘑菇进行分子鉴别,在选用的60 个ISSR 引物中,从中筛选出11 个引物,能对供试的14个菌株基因组DNA 进行扩增,获得的指纹图谱清晰稳定、多态性强。结果表明,在获得的116个条带中,74.1％是多态性条带,相似系数从0.32到0.72.用NTSYS 软件进行聚类分析,野生蘑菇与双孢蘑菇的相似系数有较低,最高的仅在0.7的水平上。研究结果表明,该批野生蘑菇有明显的遗传多样性,可以作为蘑菇杂交育种的资源。     

Cluster based hierarchical resource searching model in P2P network

For the problem of large network load generated by the Gnutella resource-searching model in Peer to Peer (P2P) network, a improved model to decrease the network expense is proposed, which establishes a cluster in P2P network, auto-organizes logical layers, and applies a hybrid mechanism of directional searching and flooding. The performance analysis and simulation results show that the proposed hierarchical searching model has availably reduced the generated message load and that its searching-response time performance is as fairly good as that of the Gnutella model.     

基于TCT的平面交叉口灰色聚类评价方法

交通冲突技术是一种非事故统计评价方法,是以大样本、快速、定量研究评价交通安全现状与改善效果的特点而异于传统的事故统计评价方法.本文应用交通冲突技术,引入交通冲突与混合当量交通量的比值(TC/MPCU)作为评价指标,提出对以时均交通冲突和交通量数据为依据的交叉口进行安全评价的交通冲突灰色聚类评价法.并以某市5个相似交叉口的实测TC/MPCU值加以验证.     

Weight constrained maximum split clustering

ConsiderN entities to be classified, with given weights, and a matrix of dissimilarities between pairs of them. The split of a cluster is the smallest dissimilarity between an entity in that cluster and an entity outside it. The single-linkage algorithm provides partitions intoM clusters for which the smallest split is maximum. We consider the problems of finding maximum split partitions with exactlyM clusters and with at mostM clusters subject to the additional constraint that the sum of the weights of the entities in each cluster never exceeds a given bound. These two problems are shown to be NP-hard and reducible to a sequence of bin-packing problems. A (N ²) algorithm for the particular caseM =N of the second problem is also presented. Computational experience is reported.Acknowledgments: Work of the first author was supported in part by AFOSR grants 0271 and 0066 to Rutgers University and was done in part during a visit to GERAD, Ecole Polytechnique de Montréal, whose support is gratefully acknowledged. Work of the second and third authors was supported by NSERC grant GP0036426 and by FCAR grant 89EQ4144. We are grateful to Silvano Martello and Paolo Toth for making available to us their program MTP for the bin-paking problem and to three anonymous referees for comments which helped to improve the presentation of the paper.