ID 原文 译文
18875 该文以虚拟空域密集干扰为切入点，推导并提出一种可用于旁瓣对消器的自适应零陷优化设计算法。 An adaptive null broadening algorithm forsidelobe canceller is proposed based on dense disturbance in virtual airspace.
18876 该算法通过对辅助阵列数据的自协方差矩阵和主辅阵列数据的互协方差矩阵同时进行重构实现零陷区域的自适应控制，锥削矩阵只与阵元位置和展宽宽度有关，无需干扰信息，可以离线生成，不占用系统运算资源。 The algorithm reconstructs the self-covariance matrix of the auxiliary array data and the co-covariance matrix of the main and auxiliary array data at the same time to realize the adaptive control of the null region. The taper matrix is only related to theposition and width of the array elements, and it can be generated offline without disturbing information andoccupying no computing resources of the system.
18877 仿真结果表明，该方法可以实现零陷区域的自适应展宽，提高非平稳干扰抑制的稳健性。 The simulation results show that this method can achieveadaptive broadening of the null region and improve the robustness of non-stationary interference suppression.
18878 针对现有兴趣点(POI)推荐算法对不同签到特征的用户缺乏自适应性问题，该文提出一种基于用户签到活跃度(UCA)特征和时空(TS)概率模型的自适应兴趣点推荐方法UCA-TS。 Existing Point-Of-Interest (POI) recommendation algorithms lack adaptability for users withdifferent check-in features. To solve this problem, an adaptive POI recommendation method UCA-TS based onUser Check-in Activity (UCA) feature and Temporal-Spatial (TS) probabilistic models is proposed.
18879 利用概率统计分析方法提取用户签到的活跃度特征，给出一种用户不活跃和活跃的隶属度计算方法。 The user check-in activity is extracted using a probabilistic statistical analysis method, and a calculation method of user's inactive and active membership is given.
18880 在此基础上，分别采用结合时间因素的1维幂律函数和2维高斯核密度估计来计算不活跃和活跃特征的概率值，同时融入兴趣点流行度来进行推荐。 On this basis, one-dimensional power law function and two-dimensional Gaussian kernel density estimation combined with time factor are used to calculate the probability for inactive and active features respectively, and the popularity of POI is incorporated to recommend.
18881 该方法能自适应用户的签到特征，并能更准确体现用户签到的时间和空间偏好。 This method can adapt to the users' check-in features and reflect the users' check-in temporal-spatial preferences more accurately.
18882 实验结果表明，该方法能够有效提高推荐精度和召回率。 The experiments show that the proposed method can effectively improve the recommendation precision and recall.
18883 针对5G网络切片架构下业务请求动态性引起的虚拟网络功能(VNF)迁移优化问题，该文首先建立基于受限马尔可夫决策过程(CMDP)的随机优化模型以实现多类型服务功能链(SFC)的动态部署， In order to solve the Virtual Network Function (VNF) migration optimization problem caused by the dynamicity of service requests on the 5G network slicing architecture, firstly, a stochastic optimization model based on Constrained Markov Decision Process (CMDP) is established to realize the dynamic deployment of multi-type Service Function Chaining (SFC).
18884 该模型以最小化通用服务器平均运行能耗为目标，同时受限于各切片平均时延约束以及平均缓存、带宽资源消耗约束。 This model aims to minimize the average sum operating energyconsumption of general servers, and is subject to the average delay constraint for each slicing as well as theaverage cache, bandwidth resource consumption constraints.