In this paper, we propose a novel speed and service-sensitive handoff algorithm and analytical model for hierarchical cellular networks.First, we use the Gauss-Markov mobility model to predict the speeds of mobile sta...In this paper, we propose a novel speed and service-sensitive handoff algorithm and analytical model for hierarchical cellular networks.First, we use the Gauss-Markov mobility model to predict the speeds of mobile stations, and divide mobile stations into three classes based on the predicted speeds: fast, medium-speed, and slow.Then, according to the mobility classification,network conditions, and service types, mobile stations will be handoff to the proper target networks prior to the deterioration of the currently operating channel. We further develop an analytical model to evaluate the performance of such a hierarchical system with different speed classes and service types. Simulations and analytical results show that the proposed handoff algorithm can significantly improve the network performance in terms of the handoff failure probability, unnecessary handoff probability, and network throughput, comparing with the traditional algorithms.展开更多
Aim To analyze the traditional hierarchical Kalman filtering fusion algorithm theoretically and point out that the traditional Kalman filtering fusion algorithm is complex and can not improve the tracking precision we...Aim To analyze the traditional hierarchical Kalman filtering fusion algorithm theoretically and point out that the traditional Kalman filtering fusion algorithm is complex and can not improve the tracking precision well, even it is impractical, and to propose the weighting average fusion algorithm. Methods The theoretical analysis and Monte Carlo simulation methods were ed to compare the traditional fusion algorithm with the new one,and the comparison of the root mean square error statistics values of the two algorithms was made. Results The hierarchical fusion algorithm is not better than the weighting average fusion and feedback weighting average algorithm The weighting filtering fusion algorithm is simple in principle, less in data, faster in processing and better in tolerance.Conclusion The weighting hierarchical fusion algorithm is suitable for the defective sensors.The feedback of the fusion result to the single sersor can enhance the single sensorr's precision. especially once one sensor has great deviation and low accuracy or has some deviation of sample period and is asynchronous to other sensors.展开更多
Purpose： To discuss the problems arising from hierarchical cluster analysis of co-occurrence matrices in SPSS, and the corresponding solutions. Design/methodology/approach： We design different methods of using the S...Purpose： To discuss the problems arising from hierarchical cluster analysis of co-occurrence matrices in SPSS, and the corresponding solutions. Design/methodology/approach： We design different methods of using the SPSS hierarchical clustering module for co-occurrence matrices in order to compare these methods. We offer the correct syntax to deactivate the similarity algorithm for clustering analysis within the hierarchical clustering module of SPSS. Findings： When one inputs co-occurrence matrices into the data editor of the SPSS hierarchical clustering module without deactivating the embedded similarity algorithm, the program calculates similarity twice, and thus distorts and overestimates the degree of similarity. Practical implications： We offer the correct syntax to block the similarity algorithm for clustering analysis in the SPSS hierarchical clustering module in the case of co-occurrence matrices. This syntax enables researchers to avoid obtaining incorrect results. Originality/value： This paper presents a method of editing syntax to prevent the default use of a similarity algorithm for SPSS＇s hierarchical clustering module. This will help researchers, especially those from China, to properly implement the co-occurrence matrix when using SPSS for hierarchical cluster analysis, in order to provide more scientific and rational results.展开更多
Entity relation is an essential component of some famous knowledge bases,such as Freebase,Yago and Knowledge Graph,while the hyponymy plays an important role in entity relations that show the relationship between the ...Entity relation is an essential component of some famous knowledge bases,such as Freebase,Yago and Knowledge Graph,while the hyponymy plays an important role in entity relations that show the relationship between the more general terms(hypernyms)and the more specific instances of the terms(hyponyms).In this paper,we present a comprehensive scheme of open-domain Chinese entity hypernym hierarchical construction.Some of the most important unsupervised and heuristic approaches for building hierarchical structure are covered in sufficient detail along with reasonable analyses.We experimentally evaluate the proposed methods and compare them with other baselines.The result shows high precision of our method and the proposed scheme will be further improved with larger scale corpora.展开更多
为维护网络运行安全,保证网络信息安全存储,提出基于多源数据挖掘的网络安全态势评估系统。首先建立以应用层、控制层、数据转发层为核心的3层网络安全态势系统架构,为保证应用层与网络设备之间信息有效传输,利用OSGi(Open Service Gate...为维护网络运行安全,保证网络信息安全存储,提出基于多源数据挖掘的网络安全态势评估系统。首先建立以应用层、控制层、数据转发层为核心的3层网络安全态势系统架构,为保证应用层与网络设备之间信息有效传输,利用OSGi(Open Service Gateway Initiative)设计模式对控制层的ONOS(Open Network Operating System)控制器实施5层平行建构,以保障网络安全态势的决策响应。利用流量探测模块内多探测器的部署,实现网络多源数据的深度挖掘;引入LEACH(Low Energy Adaptive Clustering Hierarchy)算法,在网络簇首实现多源数据融合。通过安全态势评估模块对网络入侵因子威胁等级进行分析后,结合权系数理论对网络态势威胁因子进行威胁度赋值,并结合网络层次划分法对运行网络服务层、主机层、网络层安全态势实施分层评估。实验表明,所提方法对网络数据运行状态分析能力较高,面对多类型网络威胁因子的攻击行为能做到精准识别,为网络安全运行提供重要保障。展开更多
针对采用分布式并行方法仿真WLAN(wireless local area network)场景时存在的随终端节点个数增加而效率降低的问题,提出了一种面向WLAN的分布式分层并行仿真方法。基于WLAN的星状网络拓扑结构,令仿真接入节点的进程为主进程,负责WLAN全...针对采用分布式并行方法仿真WLAN(wireless local area network)场景时存在的随终端节点个数增加而效率降低的问题,提出了一种面向WLAN的分布式分层并行仿真方法。基于WLAN的星状网络拓扑结构,令仿真接入节点的进程为主进程,负责WLAN全网中其他仿真节点的时间同步;将所有仿真终端节点的进程均匀分为若干组,由组长负责该组内进程的同步。在主进程广播仿真开始事件后,组长进程先收集本组组员终端节点推进结束消息,当收齐后再向主进程汇报。形成“主进程-组长进程-组员进程”的3层分层结构。在不同计算负荷下,仿真分析并得到了分层仿真方法的时间增益因子闭合表达式。仿真结果表明,与现有不分层的仿真方法相比,当平均计算负荷为1.2倍单位时长、节点个数为100时,所提分层仿真方法的增益可达50%。展开更多
在学术和工程领域,如何在带宽严重受限的水声信道中获取具有一定可用性的彩色图像一直是一个备受关注的问题。文章提出了一种新的水下彩色图像传输方法,利用基于分级树集合分裂(Set Partitioning in Hierarchical Trees,SPIHT)算法的图...在学术和工程领域,如何在带宽严重受限的水声信道中获取具有一定可用性的彩色图像一直是一个备受关注的问题。文章提出了一种新的水下彩色图像传输方法,利用基于分级树集合分裂(Set Partitioning in Hierarchical Trees,SPIHT)算法的图像渐进传输和视觉显著性检测,在复杂多变、带宽严重受限的水声信道中获得可用性较好的水下彩色图像。该方法根据信噪比动态调整数据传输方案,并使用红色通道补偿来提高频域中显著性检测的准确性。然后使用SPIHT渐进传输图像,并在接收端通过导向滤波解决高降采样率引起的块效应,以获得高质量的水下图像。实验结果表明,所提出的方法在压缩水下彩色图像方面具有一定的适用性。展开更多
基金supported by Natural Science Foundation of China(61372125)973 project(2013CB329104)+1 种基金the National High-Tech R&D Program(863 Program 2015AA01A705)the open research fund of National Mobile Communications Research Laboratory,Southeast University(2013D01)
文摘In this paper, we propose a novel speed and service-sensitive handoff algorithm and analytical model for hierarchical cellular networks.First, we use the Gauss-Markov mobility model to predict the speeds of mobile stations, and divide mobile stations into three classes based on the predicted speeds: fast, medium-speed, and slow.Then, according to the mobility classification,network conditions, and service types, mobile stations will be handoff to the proper target networks prior to the deterioration of the currently operating channel. We further develop an analytical model to evaluate the performance of such a hierarchical system with different speed classes and service types. Simulations and analytical results show that the proposed handoff algorithm can significantly improve the network performance in terms of the handoff failure probability, unnecessary handoff probability, and network throughput, comparing with the traditional algorithms.
文摘Aim To analyze the traditional hierarchical Kalman filtering fusion algorithm theoretically and point out that the traditional Kalman filtering fusion algorithm is complex and can not improve the tracking precision well, even it is impractical, and to propose the weighting average fusion algorithm. Methods The theoretical analysis and Monte Carlo simulation methods were ed to compare the traditional fusion algorithm with the new one,and the comparison of the root mean square error statistics values of the two algorithms was made. Results The hierarchical fusion algorithm is not better than the weighting average fusion and feedback weighting average algorithm The weighting filtering fusion algorithm is simple in principle, less in data, faster in processing and better in tolerance.Conclusion The weighting hierarchical fusion algorithm is suitable for the defective sensors.The feedback of the fusion result to the single sersor can enhance the single sensorr's precision. especially once one sensor has great deviation and low accuracy or has some deviation of sample period and is asynchronous to other sensors.
文摘Purpose： To discuss the problems arising from hierarchical cluster analysis of co-occurrence matrices in SPSS, and the corresponding solutions. Design/methodology/approach： We design different methods of using the SPSS hierarchical clustering module for co-occurrence matrices in order to compare these methods. We offer the correct syntax to deactivate the similarity algorithm for clustering analysis within the hierarchical clustering module of SPSS. Findings： When one inputs co-occurrence matrices into the data editor of the SPSS hierarchical clustering module without deactivating the embedded similarity algorithm, the program calculates similarity twice, and thus distorts and overestimates the degree of similarity. Practical implications： We offer the correct syntax to block the similarity algorithm for clustering analysis in the SPSS hierarchical clustering module in the case of co-occurrence matrices. This syntax enables researchers to avoid obtaining incorrect results. Originality/value： This paper presents a method of editing syntax to prevent the default use of a similarity algorithm for SPSS＇s hierarchical clustering module. This will help researchers, especially those from China, to properly implement the co-occurrence matrix when using SPSS for hierarchical cluster analysis, in order to provide more scientific and rational results.
基金supported by ZTE Industry-Academia-Research Cooperation Funds
文摘Entity relation is an essential component of some famous knowledge bases,such as Freebase,Yago and Knowledge Graph,while the hyponymy plays an important role in entity relations that show the relationship between the more general terms(hypernyms)and the more specific instances of the terms(hyponyms).In this paper,we present a comprehensive scheme of open-domain Chinese entity hypernym hierarchical construction.Some of the most important unsupervised and heuristic approaches for building hierarchical structure are covered in sufficient detail along with reasonable analyses.We experimentally evaluate the proposed methods and compare them with other baselines.The result shows high precision of our method and the proposed scheme will be further improved with larger scale corpora.
文摘针对采用分布式并行方法仿真WLAN(wireless local area network)场景时存在的随终端节点个数增加而效率降低的问题,提出了一种面向WLAN的分布式分层并行仿真方法。基于WLAN的星状网络拓扑结构,令仿真接入节点的进程为主进程,负责WLAN全网中其他仿真节点的时间同步;将所有仿真终端节点的进程均匀分为若干组,由组长负责该组内进程的同步。在主进程广播仿真开始事件后,组长进程先收集本组组员终端节点推进结束消息,当收齐后再向主进程汇报。形成“主进程-组长进程-组员进程”的3层分层结构。在不同计算负荷下,仿真分析并得到了分层仿真方法的时间增益因子闭合表达式。仿真结果表明,与现有不分层的仿真方法相比,当平均计算负荷为1.2倍单位时长、节点个数为100时,所提分层仿真方法的增益可达50%。
文摘在学术和工程领域,如何在带宽严重受限的水声信道中获取具有一定可用性的彩色图像一直是一个备受关注的问题。文章提出了一种新的水下彩色图像传输方法,利用基于分级树集合分裂(Set Partitioning in Hierarchical Trees,SPIHT)算法的图像渐进传输和视觉显著性检测,在复杂多变、带宽严重受限的水声信道中获得可用性较好的水下彩色图像。该方法根据信噪比动态调整数据传输方案,并使用红色通道补偿来提高频域中显著性检测的准确性。然后使用SPIHT渐进传输图像,并在接收端通过导向滤波解决高降采样率引起的块效应,以获得高质量的水下图像。实验结果表明,所提出的方法在压缩水下彩色图像方面具有一定的适用性。
