ID 原文 译文
25595 文件格式信息的缺失会影响符号执行的效率以及测试用例生成，该方法通过分析程序代码自动分析程序读取的格式文件数据块之间的依赖关系并建立相关约束，随后使用这些约束引导符号执行更关注于核心功能代码区域。 FFCBSE analyzed program source code to extract file structure constraints automatically． FFCBSE then used these structure constraints to guide symbolic execution to focus on core functions．
25596 在 KLEE 中实现了上述优化框架，并对 Tcpdump、Readelf、Elfdump、File、Zlib 等 7 个常用文件处理程序做了检测。 This architecture was implemented in KLEE, and it was evaluated on seven file processing applications, such as Tcpdump, Readelf, File, Zlib.
25597 和 KLEE 以及 DASE 相比，FFCBSE 发现了 13 个之前未知的缺陷，在指令覆盖率和分支覆盖率有 10% ～ 225% 不同程度的提升。 Compare with KLEE and DASE, FFCBSE detects thirteen previously unknown bugs. In addition, FFCBSE increases instruction line coverage/branch coverage by 10% ～ 225% ．
25598 为了提高多传感器系统的目标跟踪精度，且解决传感器数量多导致的耗时长的问题，提出了一种复合量测 IMM-EKF(Interacting Multiple Model-Extended Kalman Filter)融合算法。 In order to improve the target tracking accuracy of multi-sensor system as well as solve the problem of long processing time due to the multiple sensors, a composite measurement IMM-EKF (Interacting Multiple Model-Extended Kal-man Filter) data fusion algorithm is proposed．
25599 该算法根据各传感器的测量精度，对各传感器关于同一目标的量测点迹进行加权融合，再将融合后的点迹进行 IMM-EKF 滤波处理。 According to the measurement accuracy of each sensor, the algorithm weights and fuses the measurement of all sensors with respect to the same target, and performs the IMM-EKF filtering process on the merged measurement．
25600 通过仿真及实验数据处理，将复合量测 IMM-EKF 融合算法与加权 IMM-EKF 融合算法、扩维 IMM-EKF 融合算法进行了对比分析，比较了三种算法的跟踪精度及耗时长度。 The composite measurement IMM-EKF algorithm is compared with the weighted IMM-EKF algorithm and the extended dimension IMM-EKF algorithm in tracking accuracy and processing time through simulation and experiment data processing.
25601 结果表明，扩维 IMM-EKF 融合算法具有最优的跟踪精度，复合量测 IMM-EKF 融合算实时性最好。 The result shows that the extended dimension IMM-EKF algorithm has the best tracking accuracy while the composite measurement IMM-EKF algorithm needs the shortest processing time．
25602 最后分别给出了三种算法的适用场合。 The adapted occasions of the three fusion algorithms are given in the end．
25603 数据存储是无线传感器网络中数据管理的基础操作。 Data storage is a basic operation of data management in wireless sensor networks．
25604 在移动低占空比传感网中，由于节点的移动性，每个节点需要频繁更新邻居节点集合，使得节点能量消耗过大。 In mobile low-duty-cyclesensor networks, due to the mobility of the nodes, each node needs to frequently update the set of its neighbor nodes, which making energy consumption of the node too large．