ID 原文 译文
47476 采用属性加密和对称加密的方法分别对密钥信息和位置信息进行加密，在社交网络上发布。 The location information was divided into three parts according to a close friend of grade, then the key infor-mation and position information was encrypted with attribute-based encryption and symmetric encryption method respec-tively and the ciphertext was published to the social network.
47477 对方案的安全性进行分析，表明方案具有用户属性信息机密性、数据机密性和可抵抗合谋攻击的优点。 The security of the scheme is analyzed, which shows that thescheme has the advantage of user attribute information confidentiality, data confidentiality and can resist the collusion attack.
47478 为了研究在无线通信环境中如何选择满足用户需求的无线信道连接系统的问题，首先根据用户数目利用爱尔兰呼叫损失关系，估计出满足用户需要所应提供的信道数目； In order to study the problem of how to choose the wireless channel connection system to meet the needs ofusers in the wireless communication environment, according to the number of users using the Irish call loss, the estimatednumber of users need to meet the channel should be provided.
47479 其次利用信道数目建立用户需求和系统容量之间的关系模型，引入综合评价因子对频分多址、时分多址和码分多址通信系统进行评价； Followed by the number of channels to establish the rela-tion model between user requirements and system capacity, introducing comprehensive evaluation factors to evaluateFDMA, TDMA and CDMA communication system.
47480 最后提出了满足用户需求的最佳决策方案。 Finally a solution was put forward to meet the optimal decision theneeds of users.
47481 该方案不仅实现了信道的有效利用，而且使信道有一定冗余，避免了因未来用户增长所引起的系统重建、资金浪费等问题，为不同用户数的通信系统选择提供了双赢的衡量方法。 This scheme not only realizes the effective utilization of the channel, and the channel has certain redun-dancy, avoid the system reconstruction caused by future user growth, capital waste, provides a measure of win-win choicefor different number of users of the communication system.
47482 无线传感器网络中数据具有较强联合稀疏特性，应用压缩感知理论，通过联合编码压缩数据，再使用联合解码进行还原，可实现低采样代价收集传感数据。 The data of wireless sensor network has strong joint sparse characteristics, by utilizing compressed sensingtheory, compressed data by joint encoding, and then reconstructed the data by joint decoding, the sensed data can be ga-thered with low computational cost.
47483 提出了一种基于联合稀疏模型与压缩感知理论的同步子空间追踪算法，以稀疏特性为先验知识， A synchronous subspace pursuit algorithm based on joint sparse model and com-pressed sensing theory was proposed.
47484 通过回溯迭代方式，判断并选取合适的联合子空间，用更少量观测值实现原始传感数据的精确重构。 By utilizing the sparsity of the sensed data, it selected the correct joint subspaceand reconstruct the original signal group accurately with fewer observations in a backtracking iterative manner.
47485 与 SCoSaMP 算法、SP 算法在不同稀疏特性和不同采样率下相比较，同步子空间追踪算法具有较好的恢复性能。 Com-pared with SCoSaMP algorithm and SP algorithm, the proposed algorithm presents better data reconstruction perfor-mance under the conditions of different sparsity and sampling rate.