基于MDT重叠覆盖度数据的KNN-DBSCAN参数自适应调优研究

传统网络优化中路测工作存在难以全量测试道路及楼宇、测试工作量大、工作效率低、周期长、受人为因素影响等显性缺点,无法动态关注每个区域网络质量情况,且常规测量报告(measurement report,MR)数据不具备定位信息,无法精确定位如重叠覆盖度问题发生位置。基于最小化路测(minimization drive test,MDT)精准定位系统通过采集底层基站MDT数据,并根据重叠覆盖度算法输出高重叠覆盖度栅格,再通过自适应K最近邻-具有噪声的基于密度的聚类方法(K-nearest neighbor density-based spatial clustering of applica-tions with noise,KNN-DBSCAN)联合算法解决了DBSCAN算法对参数设置敏感性问题,并对问题栅格进行非监督聚类,收敛问题连片区域,通过小区采样贡献度进行栅格区域映射,最终达到精准调整全局最高优先级(TOP)小区,降低小区高重叠覆盖度的目的。     

面向大规模网络的快速重叠社团挖掘算法

重叠社团在社交网络大数据中普遍存在.针对现有重叠社团挖掘算法易将重叠区域错误地划分为独立的社团且计算复杂的问题,提出了一种基于局部信息度量的快速重叠社团挖掘算法（Local information based Fast Overlapped Communities Detection,Li-FOCD）.首先,为节点定义局部信息度量指标——社团连接度和邻居连接度,建模节点与社团的关系,缩小了计算范围;然后,每次并行地迭代执行缩减、扩展、去重等操作,并更新局部度量指标,通过松弛每次迭代的终止条件,发现近似最优社团集合而不是最优社团,最终算法复杂度为O（m+n）.基于真实的大规模社交网络数据的试验分析表明：与当前流行的重叠社团挖掘算法相比,Li-FOCD在不损失检测质量的前提下,大幅提升了计算效率.     

Sizes of atoms and ions and covalency of bonding in molecules and crystals

A new system of atomic radii for the elements up to barium inclusive is constructed. Values of the radii are chosen so as the dependence between the dissociation energy of diatomic homonuclear molecules and a depth of atom overlapping is monotonous, and the scatter of data is minimal. The depth of overlapping is calculated as a difference between the sum of atomic radii and an experimental interatomic distance. Conclusions are made that: the radii of free atoms and ions are determined by the value of the electron density equal to 0.01 au; they considerably change in molecules and crystals only as a result of the charge transfer from cation to anion; covalent bonding is well described by the overlapping of free atoms (ions), confined by the surface of the given radius, and its energy depends upon the depth of overlapping of valence electron densities of atoms. A method of overlapping atoms is proposed for the approximate estimation of ionic sizes and charges in bound systems.     

反相高效液相色谱中复杂体系二元多台阶梯度分离条件快速优化方法

提出了一种反相高效液相色谱中二元多台阶梯度分离条件快速优化方法。通过数次线性梯度初始实验，求得溶质的保留方程。在此基础上，利用重叠分离区域图（OSRM）方法，快速求得复杂样品的最佳多台阶梯度分离条件。该方法只需要几个小时就可以完成对复杂样品分离条件的优化，并通过对中药川芎提取物的分离加以验证，获得了较好的预测精度和分离效果。     

小波变换用于色谱重叠峰的解析

利用小波变换的时频局部化性质，通过对色谱重叠峰信号小波变换后的某些频率段进行放大，使重叠谱峰得到了分离，并将此方法用于苯和甲苯二组分色谱体系的定量分析，重叠峰中各组分均得到了良好的线性关系及令人满意的定量分析。本文还讨论了不同小波基、分解的次数及放大系数在解析结果的影响。     

Application of QR Decomposition Algorithm for Multivariate Calibration in High Overlapping Systems

An accurate and stable algorithm, QR Decomposition Algorithm (QRDA) is initially presented into the chemistry field. The basic principle of QR Multivariate Calibration Algorithm (QRMCA) is investigated, and the complexes system of sodium tripolyphosphate (STPP), sodium sulfate (SS), and sodium Carbonate (SC) with serious overlapping absorption peaks is analyzed by QRMCA. According to our survey, QRDA can avoid matrix inverting, reduce the orders of matrixes, and speed up the operation of matrices. So, it has bright prospects in chemometrics. The process of the QR Decomposition Algorithm (QRDA) was implemented by an orthogonal and upper triangular matrix decomposition that is robust and convenient. Then it was applied to overcome the problem of overlapping spectra of different components in detergent-washing powder.     

基于链接相似性聚类的重叠社区识别

社区结构是社会网络最普遍和重要的拓扑属性之一,提出一种基于链接相似性聚类的重叠社区识别算法.该算法首先根据相邻链接的度分布状态,提出链接间的相似性度量方法;其次以链接相似性矩阵为输入,以链接社区的最优划分为目标,建立链接局部相似性聚类算法,实现了重叠社区的有效识别;然后对链接社区进行优化,解决了可能出现的过度重叠及孤立社区问题;最后在真实网络及人工合成网络上的实验验证了算法的高效性.     

大规模复杂网络下重叠社区的识别

随着网络规模的不断扩大,经典的复杂网络重叠社识别算法已不能高效处理现有的大规模网络图数据.本文在GraphLab并行计算模型上提出了基于重要节点扩展的重叠社区识别算法DOCVN (Detecting the Overlapping Community algorithm based on Vital Node Expanding in GraphLab).算法选取网络中PageRank值大的节点作为重要节点,计算其他节点归属于重要节点的节点归属度,并以重要节点为中心形成核心社区及扩展社区,最后根据重要节点间的连接紧密度合并核心社区及扩展社区,并计算出每个节点在所属社区里的节点重要度,实现了大规模网络的重叠社区识别.实验表明该算法与PD (Propinquity Dynamics)等现有并行算法相比更能有效地识别大规模网络的重叠社区结构.     

Fast bowtie effect elimination for MODIS L1B data

The bowtie effect refers to geometry distortions for the moderate resolution imaging spectrum-radiometer(MODIS) level 1B(L1B) data.Till now,to eliminate the bowtie effect,numerous methods are proposed.However,most of them have limitations in computation efficiency.Through a comparative study of existing methods,this article puts forward a fast method to eliminate the bowtie effect using the ephemeris data.In this method,the rough positions of overlapping data are first detected.Because of the influence caus...     

波动方程单位分解有限元法及收敛性分析

<正>1引言与问题的提出自黄云清和许进超提出基于单位分解技术的重叠型非匹配网格有限元方法以来,这类方法日益引起人们极大的兴趣.这篇文章将这类有限元方法运用到波动方程当中,分别研究了重叠型非匹配网格波动方程半离散和全离散有限元方法,给出了有限元解及其梯度的误差估计.下面先给出模型问题的简单介绍.