The home network technologies are taking advantage of the increasingly promising market prospect, thank to the popularity of digital home appliances. To enable control and data transfer among interconnected home netwo...The home network technologies are taking advantage of the increasingly promising market prospect, thank to the popularity of digital home appliances. To enable control and data transfer among interconnected home network devices, it is necessary to adopt the Universal Plug and Play (UPnP) technology. This technology leverages the Internet technical standards including the Internet Protocol (IP), the Transmission Control Protocol (TCP), the User Datagram Protocol (UDP), the Hypertext Transfer Protocol (HTTP), and the Extensible Markup Language (XML) to provide the automatic across-platform service discovery and the remote control. In addition to the control and the data transfer among networked devices, the UPnP provides the flexible and robust service discovery ability to change the complex network device drive into a simple remote network control.展开更多
【目的】应用线粒体DNA条形码技术对尤犀金龟属(Eupatorus Burmeister,1847)昆虫物种界定进行探索,以解决该属物种形态鉴定困难的问题。【方法】基于尤犀金龟属物种线粒体cox1和cox2基因序列数据集,使用Automatic Barcode Gap Discovery...【目的】应用线粒体DNA条形码技术对尤犀金龟属(Eupatorus Burmeister,1847)昆虫物种界定进行探索,以解决该属物种形态鉴定困难的问题。【方法】基于尤犀金龟属物种线粒体cox1和cox2基因序列数据集,使用Automatic Barcode Gap Discovery(ABGD)和Bayesian Poisson Tree Processes(bPTP)对3个形态种进行分子物种界定,并与形态学鉴定结果进行比较。【结果】使用ABGD方法时,cox1数据集的界定结果与形态学鉴定结果一致,cox2数据集的界定结果与形态学鉴定结果存在差异;使用bPTP方法时,2种数据集的界定结果均远高于形态学鉴定结果,且均存在不同程度的过度划分。【结论】cox1是更适合用于鉴定尤犀金龟属昆虫的DNA条形码,使用ABGD方法时,其数据集界定结果与形态学鉴定结果一致。利用分子界定与形态特征鉴定相结合,可极大地提高鉴定效率和准确性。展开更多
The rapid development of network technology and its evolution toward heterogeneous networks has increased the demand to support automatic monitoring and the management of heterogeneous wireless communication networks....The rapid development of network technology and its evolution toward heterogeneous networks has increased the demand to support automatic monitoring and the management of heterogeneous wireless communication networks.This paper presents a multilevel pattern mining architecture to support automatic network management by discovering interesting patterns from telecom network monitoring data.This architecture leverages and combines existing frequent itemset discovery over data streams,association rule deduction,frequent sequential pattern mining,and frequent temporal pattern mining techniques while also making use of distributed processing platforms to achieve high-volume throughput.展开更多
文摘The home network technologies are taking advantage of the increasingly promising market prospect, thank to the popularity of digital home appliances. To enable control and data transfer among interconnected home network devices, it is necessary to adopt the Universal Plug and Play (UPnP) technology. This technology leverages the Internet technical standards including the Internet Protocol (IP), the Transmission Control Protocol (TCP), the User Datagram Protocol (UDP), the Hypertext Transfer Protocol (HTTP), and the Extensible Markup Language (XML) to provide the automatic across-platform service discovery and the remote control. In addition to the control and the data transfer among networked devices, the UPnP provides the flexible and robust service discovery ability to change the complex network device drive into a simple remote network control.
文摘【目的】应用线粒体DNA条形码技术对尤犀金龟属(Eupatorus Burmeister,1847)昆虫物种界定进行探索,以解决该属物种形态鉴定困难的问题。【方法】基于尤犀金龟属物种线粒体cox1和cox2基因序列数据集,使用Automatic Barcode Gap Discovery(ABGD)和Bayesian Poisson Tree Processes(bPTP)对3个形态种进行分子物种界定,并与形态学鉴定结果进行比较。【结果】使用ABGD方法时,cox1数据集的界定结果与形态学鉴定结果一致,cox2数据集的界定结果与形态学鉴定结果存在差异;使用bPTP方法时,2种数据集的界定结果均远高于形态学鉴定结果,且均存在不同程度的过度划分。【结论】cox1是更适合用于鉴定尤犀金龟属昆虫的DNA条形码,使用ABGD方法时,其数据集界定结果与形态学鉴定结果一致。利用分子界定与形态特征鉴定相结合,可极大地提高鉴定效率和准确性。
基金funded by the Enterprise Ireland Innovation Partnership Programme with Ericsson under grant agreement IP/2011/0135[6]supported by the National Natural Science Foundation of China(No.61373131,61303039,61232016,61501247)+1 种基金the PAPDCICAEET funds
文摘The rapid development of network technology and its evolution toward heterogeneous networks has increased the demand to support automatic monitoring and the management of heterogeneous wireless communication networks.This paper presents a multilevel pattern mining architecture to support automatic network management by discovering interesting patterns from telecom network monitoring data.This architecture leverages and combines existing frequent itemset discovery over data streams,association rule deduction,frequent sequential pattern mining,and frequent temporal pattern mining techniques while also making use of distributed processing platforms to achieve high-volume throughput.
