ID 原文 译文
58528 仿真结果证明，在远近功率差为 10 dB，过载为 150% 时，小规模的 LDSM 方案和大规模 LDSM 方案较 SCMA 方案的整体用户性能分别能获得 2. Simulation results show that when power difference is10 dB and overloading is 150% ，small dimensional and large dimensional LDSM can get 2.
58529 3 dB 和 2. 3 dB and2.
58530 46 dB 的增益. 46 dB SNＲ gains over SCMA for overall performance. Both theoretic analysis and simulation resultsprove the performance of LDSM outperforms that of SCMA.
58531 针对机械臂工作场景复杂、任务需求多样的特点，提出了一种基于改进图规划的机械臂任务规划方法. In order to deal with the complex work scene and diverse task demands of manipulator task，amanipulator task planning method based on improved graph planning is proposed.
58532 首先建立针对机械臂任务规划的通用数学表征模型;其次结合机械臂的任务特性与改进模拟退火算法，提出一种基于图规划的改进任务规划算法，将传统算法单一的规划结果拓展为任务动作序列集合; Firstly a common math?ematical model of manipulator task planning is established，and then combined with the task characteris?tics of manipulator and the improved simulated annealing algorithm，an improved task planning algorithmbased on graph planning is proposed，which extends the single planning result of traditional algorithm tothe set of task action sequences. Finally，the task execution strategy is solved by fusion of different tar?gets.
58533 最后，基于该集合求解融合不同目标的机械臂任务执行策略，并以七自由度机械臂为仿真对象对该方法的正确性和有效性进行了验证. A simulation of 7-degree of freedom manipulator verifies the correctness and effectiveness of the pro?posed method.
58534 结果表明，与传统规划方式相比，提出的方法具备优先考虑不同目标任务执行策略的能力，同时可以有效缩短规划时间 The results show that compared with the traditional task planning algorithm，the proposedmethod has the ability to prioritize tasks with different targets and can shorten plan time.
58535 针对无线传感器网络( WSN) 中数据计算需求和由簇首负载过重引起的热点问题和能量空洞问题，提出基于计算节点和转发节点的自组织聚簇算法( SCATN) ，对簇首功能进行分解，以计算节点满足数据计算需求，以转发节点进行数据转发，并通过分布控制解决热点问题和能量空洞问题. A self-organized clustering algorithm based on computation node and transmission node( SCATN) for wireless sensor network ( WSN) was proposed to satisfy computation requirement and solvethe problem of hot spot and energy hole caused by cluster head overload. SCATN employs computationnode and transmission node to undertake the cluster head’s function data computation and transmission. The distribution probability of functional nodes is controlled to tackle with the problems raised. The gen?eration and distribution of functional node is controlled by self-organized manner to solve the problem ofdistribution and connection.
58536 聚簇过程采用自组织方式控制功能节点的生成、分布，从而解决分布不均匀和连接性问题.同时，普通节点自主更换归属簇，以及时、细粒度地调整计算节点负载. The ordinary nodes choose its belonged cluster to adjust the computationnode’s load.
58537 仿真实验结果表明，与现有几种聚簇算法相比，SCATN 算法可有效地提高网络生存时间，增加基站的吞吐量，降低丢包率. Simulation indicates that SCATN can effectively extend the network lifetime，improve thethroughput at the sink and decrease the packet loss rate in comparison with several existing clusteringalgorithms.