Shareability-Exclusivity Representation on Product Grassmann Manifolds for Multi-camera video clustering

With the rapid popularity of multi-camera networks, one human action is usually captured by multiple cameras located at different angles simultaneously. Multi-camera videos contain the distinct perspectives of one action, therefore multiple views can overcome the impacts of illumination and occlusion. In this paper, we propose a novel multi-camera video clustering model, named Shareability-Exclusivity Representation on Product Grassmann Manifolds (PGM-SER), to address two key issues in traditional multi-view clustering methods (MVC): (1) Most MVC methods directly construct a shared similarity matrix by fusing multi-view data or their corresponding similarity matrices, which ignores the exclusive information in each view; (2) Most MVC methods are designed for multi-view vectorial data, which cannot handle the nonlinear manifold structure hidden in multi-camera videos. The proposed PGM-SER firstly adopts Product Grassmann Manifolds to represent multi-camera videos, then simultaneously learn their shared and exclusive information in global structures to achieve multi-camera video clustering. We provide an effective optimization algorithm to solve PGM-SER and present the corresponding convergence analysis. Finally, PGM-SER is tested on three multi-camera human action video datasets and obtain satisfied experimental results.     

受蚁群分类行为启发的环形结构构建稳定性分析

 群集智能由简单个体之间的相互作用涌现出来,这种涌现出来的智能可以解决许多复杂的问题.首先,从环形分类结构和群体集聚行为结果的相似之处出发,在物体聚集的过程中引入了物体间的引力场和斥力场,对多种物体的环形分类结构的形成进行研究.然后,采用Lyapunov稳定性理论分析了同类物体在引力和斥力的平衡下,最终会稳定的被聚集在一定范围内,并且所有物体最终形成稳定的环形结构.最后,通过仿真实验对上述理论进行了验证.     

A Fault Detection Method for Electrohydraulic Switch Machine Based on Oil-Pressure-Signal-Sectionalized Feature Extraction

A turnout switch machine is key equipment in a railway, and its fault condition has an enormous impact on the safety of train operation. Electrohydraulic switch machines are increasingly used in high-speed railways, and how to extract effective fault features from their working condition monitoring signal is a difficult problem. This paper focuses on the sectionalized feature extraction method of the oil pressure signal of the electrohydraulic switch machine and realizes the fault detection of the switch machine based on this method. First, the oil pressure signal is divided into three stages according to the working principle and action process of the switch machine, and multiple features of each stage are extracted. Then the max-relevance and min-redundancy (mRMR) algorithm is applied to select the effective features. Finally, the mini batch k-means method is used to achieve unsupervised fault diagnosis. Through experimental verification, this method can not only derive the best sectionalization mode and feature types of the oil pressure signal, but also achieve the fault diagnosis and the prediction of the status of the electrohydraulic switch machine.     

基于因子和聚类分析的全国科普示范县（市、区）科普综合实力评价研究

如何对创建单位进行有效的管理是全国科普示范县(市、区)活动目前面临的问题之一。以2011—2015年全国科普示范县(市、区)为样本,设计评价指标,应用因子分析和聚类分析方法对我国32个省级行政单位的全国科普示范县(市、区)的科普综合实力进行分析,得出基于因子分析的全国科普示范县(市、区)科普综合实力评价体系和基于全国科普示范县(市、区)科普综合实力的分类标准。应用该结论能够对全国科普示范县(市、区)进行评价和分类,为全国科普示范县(市、区)管理提供一种可以量化的参考。     

H.264压缩域中mean-shift聚类运动目标分割算法

针对视频监控、检索,提出了一 种在H.264压缩域下运动对象分 割的新算法。根据实际监控应用特点,算法主要利用H.264码流中提 取的运动矢量(MV)、分块尺寸信息对原始的MV场(MVF)进 行可靠性分析以及空间滤波、mean-shift聚类处理,从而得到可信度较高的 MVF场。首先,从H.264码流中获取原 始MV 并进行归一化处理,同时对原始MVF进行两步空间滤波;其次,对不同的块大 小分配相应的权值作为每个样本 的权重系数,将处理之后的MVF作为样本空间,利用mean-shift聚类获取 真实的MVF;最后,根据可靠的MVF 标记运动目标。实验结果表明,本文提出的mean-shift聚类运动目标分割算 法可以获得有效并可靠的分割结果。     

基于影响力形成的论坛意见领袖识别

为了在网络论坛中提取意见领袖,文中通过抽象模拟论坛舆论意见领袖影响力的形成过程,建立了影响力向量模型,进而提出了可以利用影响力向量的模和方向这对参数来筛选意见领袖,并以天涯论坛某日的一个话题为研究个案,阐述了该参数的选择依据。再通过聚类分析比较不同类型的论坛舆论参与者的特点,将分析结果与提出模型筛选的结果相比对,论证文中方法结果的有效性和准确性,反应出文中提出参数的优越性。     

基于改进SSA优化WSN分簇协议

无线传感器网络(Wireless Sensor Networks,WSN)的路由协议是无线传感器网络领域中的一个研究热点.针对LEACH协议的不足,提出一种基于自适应t分布改进麻雀搜索算法(Improved Sparrow Search Algorithm,ISSA)的改进LEACH协议(LEACH?ISSA),以解决...     

一种T-S型动态模糊推理模型的建模算法研究

以一种进化聚类算法（ECM）为基础,提出了一种新的T-S型动态模糊推理模型的建模算法.以往许多神经模糊模型都不适用于自适应在线学习,而文章模型能够实时地调整模糊规则库及规则参数,具有较强的在线学习能力.仿真结果表明,该方法是有效的.     

基于二分网络的用户聚类电影推荐系统构建

针对已经存在的推荐算法中数据的稀疏性问题,提出一种基于聚类算法的二分图信任网络构造算法,通过聚类技术把项目评分相似的用户聚集起来,形成若干个用户群组,在每个群组内部通过二分图建立连接,利用信任机制在群组内部和群组间建立连接,进而构造出推荐系统.实验是在MovieLens数据集上进行的,采用平均绝对误差(MAE)为评测指标,验证了方法的有效性,从而得出该系统使得数据稀疏性对最终推荐结果的负面影响变小.     

一种多媒体传感器网络低能耗分簇协议

多媒体传感器网络面临的主要挑战是在能量受限的情况下传输大量数据。在经典分簇协议LEACH的基础上,提出一种考虑数据量的多媒体传感器网络低能耗分簇协议。在簇头选举阶段,选择剩余能量多和数据量大的节点作为簇头;在成簇阶段,同时考虑节点到簇头的通信距离和节点的数据量让节点加入簇。仿真结果表明,提出的协议能有效提高网络的生命周期。