ID 原文 译文
44996 50 组对比实验表明 ES-MOAC 算法在求解该问题上得到的能量利用率的平均值比 NSGA-II 算法增加了 4.53%， 50 groups of contrastive experiments show that the average number of energy utilization obtained by ES-MOACalgorithm is 4.53% higher than that of NSGA-II algorithm.
44997 网络中所有节点数据传输的平均时延的平均值比 NSGA-II 算法缩短了 5.12%。 The average number of average delay of all node data transmission obtained by ES-MOAC algorithm is 5.12% lower than that of NSGA-II algorithm.
44998 为了解决分布式云计算存储的数据窃取检测中，出现数据量大、内部窃取难以检测的问题，以 hadoop分布式文件系统（HDFS, hadoop distributed file system）为检测对象，提出了一种基于 MapReduce 的数据窃取随机检测算法。 To address the problems of big data efficient analysis and insider theft detection in the data theft detection of distributed cloud computing storage, taking HDFS (hadoop distributed file system) as a case study, a stochastic algorithm for HDFS data theft detection based on MapReduce was proposed.
44999 分析 HDFS 文件夹复制产生的 MAC 时间戳特性，确立复制行为的检测与度量方法，确保能够检测包括内部窃取的所有窃取模式。 By analyzing the MAC time stamp features of HDFS generated by folder replication, the replication behavior’s detection and measurement method was established to detect all data theft modes including insider theft.
45000 设计适合于 MapReduce 任意的任务划分，同时记录 HDFS 层次关系的输入数据集，实现海量时间戳数据的高效分析。 The data set which is suitable for MapReduce task partition and maintains the HDFS hierarchy was designed to achieve efficient analysis of large-volume timestamps.
45001 实验结果表明，该算法能够通过分段检测策略很好地控制漏检率和误检文件夹数量， The experimental results show that the missed rate and the number of mislabeled folders could be kept at a low level by adopting segment detection strategy.
45002 并且具有较高的执行效率和良好的可扩展性。 The algorithm was proved to be efficient and had good scalability under the Map Reduce framework.
45003 社交影响力是驱动信息传播的关键因素，基于在线社交网络数据，可以对社交影响力进行建模和分析。 Social influence is the key factor to drive information propagation in online social networks and can be modeled and analyzed with social networking data.
45004 针对一种经典的个体影响力计算方法，介绍了该算法的 2 种并行化实现， As a kind of classical personal influence algorithm, two parallel implementation versions of a Page Rank based method were introduced.
45005 并在真实大规模在线社交网络数据集上进行了性能测试。 Furthermore, extensive experiments were conducted on a large-scale real dataset to test the performance of these parallel methods in a distributed environment.