ID	原文	译文
46096	在无线传感器网络中，节点所在环境复杂多变导致其通信链路质量的不可靠，	The link quality was vulnerable to the complexity environment in wireless sensor network.
46097	若能提前感知链路质量信息，则能很大程度上降低网络中节点的额外能量消耗。	Obtaining link quality information in advance could reduce energy consumption of nodes.
46098	在分析现有链路质量预测方法的基础上，提出基于 AdaBoost的链路质量预测机制。	After analyzing the existing link quality predication methods, AdaBoost-based link quality prediction mechanism was put forward.
46099	通过收集多个实验场景下的链路质量样本，	Link quality samples in different scenarios were collected.
46100	采用基于密度的无监督聚类算法对训练样本划分链路质量等级；	Density-based unsupervised clustering algorithm was employed to classify training samples into different link quality levels.
46101	采用以支持向量机为弱分类器的 AdaBoost 算法，构建链路质量预测机制。	The AdaBoost with SVM-based component classifiers was adopted to build link quality predication mechanism.
46102	实验结果表明，所提预测机制具有较高的预测精度。	Experimental results show that the proposed mechanism has better prediction precision.
46103	随着基于位置服务的广泛使用，用户请求查询过程中真实位置信息泄露会产生严重的安全问题。	With location-based services worldwide used, private location data appealed easily in query process which caused serious security problems.
46104	为此引入 SpaceTwist 增量近邻查询算法，提出一种结合锚点优选算法改进的 SpaceTwist 位置隐私保护方法。	So the introduction of SpaceTwist incremental nearest neighbor query algorithm,proposes protection of privacy method combined with improved SpaceTwist location optimization algorithm.
46105	在分布式系统结构下增加了认证服务器，用户根据自身隐私偏好同时结合实际环境生成 k 匿名区，并且使用锚点优选算法生成锚点；	The anchor point authentication server added to distributed system structure, user generate a k anonymous area according to their privacy preference and actual environment, using optimization algorithm to generate the anchor point.