基于主动探测的域名解析数据和从公开来源获取的有效数据,通过分析域名(Domain Name)、IP与自治系统号码(Autonomous System Number,ASN)之间的全局关联关系,提出一种基于图数据路径分析的不良网络应用快速发现优化算法。在域名之间建...基于主动探测的域名解析数据和从公开来源获取的有效数据,通过分析域名(Domain Name)、IP与自治系统号码(Autonomous System Number,ASN)之间的全局关联关系,提出一种基于图数据路径分析的不良网络应用快速发现优化算法。在域名之间建立反映其关联强度的关系图谱,并通过调整不同参数配置计算真阳率和假阳率来评估算法的实用性和有效性。实验证明,该算法在保持较低假阳率的同时可以获得较高的真阳率,同时利用少量的已知不良种子域名可以快速发现大量的潜在不良域名,从而具有较好的大规模工程化应用前景。展开更多
Based on the image theory,the analytical solutions of tunneling-induced ground displacement were derived in conjunction with the nonuniform convergence model.The reasonable value of Poisson ratio in the analytical sol...Based on the image theory,the analytical solutions of tunneling-induced ground displacement were derived in conjunction with the nonuniform convergence model.The reasonable value of Poisson ratio in the analytical solution was discussed.The ground settlement width parameter which could reflect the ground condition was introduced to modify the analytical solutions proposed above,and new analytical solutions were presented.To evaluate the validity of the present solutions using the nonuniform convergence model,the results were compared with the observed values for four engineering projects,including 38 measured data of ground settlement.The agreement shows that the present solutions using the nonuniform convergence model are effective for evaluating the tunneling-induced ground displacements.展开更多
DNS(domain name system) query log analysis has been a popular research topic in recent years. CLOPE, the represented transactional clustering algorithm, could be readily used for DNS query log mining. However, the alg...DNS(domain name system) query log analysis has been a popular research topic in recent years. CLOPE, the represented transactional clustering algorithm, could be readily used for DNS query log mining. However, the algorithm is inefficient when processing large scale data. The MR-CLOPE algorithm is proposed, which is an extension and improvement on CLOPE based on Map Reduce. Different from the previous parallel clustering method, a two-stage Map Reduce implementation framework is proposed. Each of the stage is implemented by one kind Map Reduce task. In the first stage, the DNS query logs are divided into multiple splits and the CLOPE algorithm is executed on each split. The second stage usually tends to iterate many times to merge the small clusters into bigger satisfactory ones. In these two stages, a novel partition process is designed to randomly spread out original sub clusters, which will be moved and merged in the map phrase of the second phase according to the defined merge criteria. In such way, the advantage of the original CLOPE algorithm is kept and its disadvantages are dealt with in the proposed framework to achieve more excellent clustering performance. The experiment results show that MR-CLOPE is not only faster but also has better clustering quality on DNS query logs compared with CLOPE.展开更多
文摘基于主动探测的域名解析数据和从公开来源获取的有效数据,通过分析域名(Domain Name)、IP与自治系统号码(Autonomous System Number,ASN)之间的全局关联关系,提出一种基于图数据路径分析的不良网络应用快速发现优化算法。在域名之间建立反映其关联强度的关系图谱,并通过调整不同参数配置计算真阳率和假阳率来评估算法的实用性和有效性。实验证明,该算法在保持较低假阳率的同时可以获得较高的真阳率,同时利用少量的已知不良种子域名可以快速发现大量的潜在不良域名,从而具有较好的大规模工程化应用前景。
基金Project(09JJ1008) supported by Hunan Provincial Science Foundation of China
文摘Based on the image theory,the analytical solutions of tunneling-induced ground displacement were derived in conjunction with the nonuniform convergence model.The reasonable value of Poisson ratio in the analytical solution was discussed.The ground settlement width parameter which could reflect the ground condition was introduced to modify the analytical solutions proposed above,and new analytical solutions were presented.To evaluate the validity of the present solutions using the nonuniform convergence model,the results were compared with the observed values for four engineering projects,including 38 measured data of ground settlement.The agreement shows that the present solutions using the nonuniform convergence model are effective for evaluating the tunneling-induced ground displacements.
基金Project(61103046) supported in part by the National Natural Science Foundation of ChinaProject(B201312) supported by DHU Distinguished Young Professor Program,China+1 种基金Project(LY14F020007) supported by Zhejiang Provincial Natural Science Funds of ChinaProject(2014A610072) supported by the Natural Science Foundation of Ningbo City,China
文摘DNS(domain name system) query log analysis has been a popular research topic in recent years. CLOPE, the represented transactional clustering algorithm, could be readily used for DNS query log mining. However, the algorithm is inefficient when processing large scale data. The MR-CLOPE algorithm is proposed, which is an extension and improvement on CLOPE based on Map Reduce. Different from the previous parallel clustering method, a two-stage Map Reduce implementation framework is proposed. Each of the stage is implemented by one kind Map Reduce task. In the first stage, the DNS query logs are divided into multiple splits and the CLOPE algorithm is executed on each split. The second stage usually tends to iterate many times to merge the small clusters into bigger satisfactory ones. In these two stages, a novel partition process is designed to randomly spread out original sub clusters, which will be moved and merged in the map phrase of the second phase according to the defined merge criteria. In such way, the advantage of the original CLOPE algorithm is kept and its disadvantages are dealt with in the proposed framework to achieve more excellent clustering performance. The experiment results show that MR-CLOPE is not only faster but also has better clustering quality on DNS query logs compared with CLOPE.
