互联网AS级拓扑中心化度量方法

针对如何能够在规模庞大、结构复杂的互联网AS级中准确而迅速地发现中心节点这一问题,展开对互联网AS级拓扑中心化度量方法的研究.应用三种现在普遍应用的中心化指标——度中心化、紧密度中心化、介数中心化,同时提出一种核中心化的度量法来度量网络中的高核数节点集合.采用节点删除法,通过删除某个节点对网络连通的破坏程度来度量网络中该节点的重要性.经研究发现紧密度中心化在互联网AS级度量上弱于度中心化和介数中心化指标;度中心化和介数中心化在攻击节点数小于0.5%时,有很强的相似性;核中心化度量方法非常适用于查找到网络中度值较高且连接紧密节点所构成的社团.     

一种基于关联规则挖掘的IP定位方法

针对IP定位数据库如何及时更新IP定位数据并同时保证其定位准确率和覆盖率的问题,提出一种基于关联规则挖掘的IP定位方法(IPGEL).首先,结合traceroute网络测量数据和已有IP定位数据库中IP定位数据,获取关联规则挖掘的路由路径数据集.其次,利用国内互联网分层结构的路由特性和关联规则挖掘,在对路由路径数据集进行数据分析的基础上对数据集内的IP分类并定位,同时利用马尔可夫模型对数据集外的IP进行补充定位.最后,使用交叉对比验证和地标验证相结合的方法验证IPGEL方法的准确性.结果表明,IPGEL方法在提高IP定位准确率和覆盖率的同时有效提高了已有IP定位数据库的可信度.     

恐怖网络中基于节点割集分层的组织结构发现方法

“911”等一系列恐怖事件导致越来越多的国家开始重视恐怖组织网络的研究,但社会网络分析中的一些典型度量,如节点的度、介数、接近度等,不能很好地适应具有高度组织性的社会网络.文中针对层次结构性较强的恐怖组织网络,提出了一种新的节点重要性度量,其综合了节点的全局信息与局部信息,利用割集算法对网络节点进行分层获得节点全局信息,局部信息则直接利用了节点的出/入度,并使用BP神经网络方法对综合度量进行参数优化.针对“911”恐怖事件成员网络实际数据的分析结果验证了这种度量的有效性.     

基于复杂网络分析技术的SAP系统迁移

以复杂网络分析技术为基础,利用中心化度量方法与拓扑鲁棒性分析,研究了一个真实企业SAP系统迁移过程的系统设计.提出了基于介数中心性的网络硬件升级规划方案,设计了网络中局部拓扑鲁棒性的度量方法.通过仿真实验验证了相关设计方法的有效性.结论表明,应用复杂网络理论的方法进行实际系统的分析与设计,可以有效地提高SAP系统的鲁棒性和响应时间.     

基于多属性决策的关键蛋白质识别算法研究

关键蛋白质往往通过蛋白质复合物的形式在生物生命活动中扮演着重要作用,在蛋白质互作用(PPI,Protein-Protein Interaction)网络中关键蛋白质对应互作用网络中的重要节点,基于此,提出了一种融合蛋白质拓扑结构属性信息和蛋白质复合物信息的基于多属性决策的关键蛋白质识别算法CBT-Topsis(Topsis based method for Essential Protein Identification on Complex Biological and Topological properties)。该算法采用多属性决策方法TOPSIS将节点局部重要性(LN)、聚集系数(CC)、点介数(BC)和蛋白质复合物内度中心(IDC)进行融合,根据节点重要性对PPI网络中的蛋白质进行排序。在酿酒酵母蛋白质互作用网络中进行关键蛋白质识别的结果表明,CBTTOPSIS算法在F度量、准确率、特异性、敏感度等方面表现了良好的性能。     

基于路网拓扑特性及先验知识的地图匹配算法

基于最大似然估计原理,提出了地图匹配的统一数学模型.将二维地图匹配算法的估计拓展到多维估计,利用道路网络的拓扑特性及先验知识修正前述算法.通过先验知识数字化,用代价函数将基于拓扑特性和先验知识的地图匹配算法纳入统一数学模型中.通过在香港大量的车辆定位实验,及参数修正和模型改进,对前述算法进行验证.实践表明,通过综合利用全球定位系统、航位推算以及数字地图道路网络等多种信息,该地图匹配算法在大规模复杂网络以及高楼环绕的场合可以达到很好的定位效果.     

一种基于加权共同邻居相似度的局部社区发现算法

传统的社区发现算法能够找出网络中所有的社区,其时间复杂度取决于网络的规模.挖掘大网络中的全局社区结构因为时间复杂度高而难以实现,局部社区发现作为一种不需要知道网络的整体结构,从给定的节点逐步向外扩展,寻找该节点所在社区的方法,在大网络时代具有重要的应用意义.目前这方面的研究已经获得广泛关注,并提出了很多局部社区发现算法.针对已有局部社区发现算法需要人工设置参数、准确率低的问题,提出一种新的局部社区发现算法.首先,提出一种加权邻居节点的共同邻居相似度指标,用于计算网络中两个节点间的相似度;然后,基于该相似度指标,给出一种新的局部社区质量度量指标,在保证社区度量指标不下降的前提下,不断选择与当前局部社区嵌入度最大的节点加入到局部社区,逐步找出给定节点所在的社区;最后,在真实网络和仿真网络数据集上进行了实验.实验结果表明,该算法能有效地挖掘出给定节点所在的局部社区,相比具有代表性的Clauset,LWP,GMAC等局部社区发现算法有更高的准确率.     

零售户聚类分析中基于最短主干道距离的差异度计算方法

在研究零售户聚类分析中,地理位置相近且交通方便可达的零售户应被聚为一类.传统的差异度度量方式均未考虑地理与交通的相关信息,不能直接应用到零售户的聚类分析中.提出基于最短主干道距离的零售户差异度度量,有效解决传统差异度度量无法处理地理及交通信息的问题.并给出了利用寻径算法异地计算两点之间的最短主干道距离的一种方法.     

基于拓扑势的局部化重叠社区识别

针对传统社区识别算法中需要根据先验知识设定参数、 社区划分结果具有随机性及复杂度过高的问题, 提出一种基于拓扑势的局部化重叠社区识别算法. 该算法通过引入拓扑势计算节点的影响力, 利用节点间的局部相似性度量指标, 采用标签传播策略进行重叠结构的社区识别. 在真实网络及人工合成网络上与多种经典算法进行对比实验验证了算法的高效性.     

自适应全局—局部集成判别分析

将数据集进行合理的维数约简,对于提高一些机器学习算法的效率起着至关重要的影响.本文提出了一种自适应全局—局部集成判别分析算法(Adaptive integrated global and local discriminant analysis,AIGLD).AILGD利用数据集的全局判别结构和局部判别结构,将线性判别算法(Linear Discriminant Analysis,LDA)与提出的局部判别算法自适应的相结合.在UCI数据库及标准人脸数据库上的识别实验证明,相比于现有算法,AIGLD具有更高的识别准确率及更强的鲁棒性.     

Characterization of Ordovician carbonate reservoirs, southeastern Saskatchewan, Canada

The discovery of the prolific Ordovician Red River reservoirs in 1995 in southeastern Saskatchewan was the catalyst for extensive exploration activity which resulted in the discovery of more than 15 new Red River pools. The best yields of Red River production to date have been from dolomite reservoirs. Understanding the processes of dolomitization is, therefore, crucial for the prediction of the connectivity, spatial distribution and heterogeneity of dolomite reservoirs.The Red River reservoirs in the Midale area consist of 3～4 thin dolomitized zones, with a total thickness of about 20 m, which occur at the top of the Yeoman Formation. Two types of replacement dolomite were recognized in the Red River reservoir: dolomitized burrow infills and dolomitized host matrix. The spatial distribution of dolomite suggests that burrowing organisms played an important role in facilitating the fluid flow in the backfilled sediments. This resulted in penecontemporaneous dolomitization of burrow infills by normal seawater. The dolomite in the host matrix is interpreted as having occurred at shallow burial by evaporitic seawater during precipitation of Lake Almar anhydrite that immediately overlies the Yeoman Formation. However, the low δ18O values of dolomited burrow infills (-5.9‰～ -7.8‰, PDB) and matrix dolomites (-6.6‰～ -8.1‰, avg. -7.4‰ PDB) compared to the estimated values for the late Ordovician marine dolomite could be attributed to modification and alteration of dolomite at higher temperatures during deeper burial, which could also be responsible for its 87Sr/86Sr ratios (0.7084～0.7088) that are higher than suggested for the late Ordovician seawaters (0.7078～0.7080). The trace amounts of saddle dolomite cement in the Red River carbonates are probably related to "cannibalization" of earlier replacement dolomite during the chemical compaction.     

A computer generator for randomly layered structures

AcomputergeneratorforrandomlylayeredstructuresYUJia shun1,2,HEZhen hua2(1.TheInstituteofGeologicalandNuclearSciences,NewZealand;2.StateKeyLaboratoryofOilandGasReservoirGeologyandExploitation,ChengduUniversityofTechnology,China)Abstract:Analgorithmisintrod…     

海南岛地体及其毗邻陆缘晚中生代—新生代古地磁研究和构造演化

本文叙述了对海南岛及其毗邻大陆边缘白垩纪到第四纪地层岩石进行古地磁研究的全部工作过程。通过分析岩石中剩余磁矢量的磁偏角及磁倾角的变化,提出海南岛白垩纪以来经历的构造演化模式如下:早期伴随顺时针旋转而向南迁移,后期伴随逆时针转动并向北运移。联系该地区及邻区的地质、地球物理资料,对海南岛上述的构造地体运动提出以下认识:北部湾内早期有一拉张作用,主要是该作用使湾内地壳显著伸长减薄,形成北部湾盆地。从而导致了海南岛的早期构造运动,而海南岛后期的构造运动则主要是受南海海底扩张的影响。海南地体运动规律的阐明对于了解北部湾油气盆地的形成演化有重要的理论和实际意义。     

Exciton Seebeck in Molecular Systems

Various applications relevant to the exciton dynamics,such as the organic solar cell,the large-area organic light-emitting diodes and the thermoelectricity,are operating under temperature gradient.The potential abnormal behavior of the exicton dynamics driven by the temperature difference may affect the efficiency and performance of the corresponding devices.In the above situations,the exciton dynamics under temperature difference is mixed with     

Achieving Unusual States of Matter Under High Pressure

The elongation method,originally proposed by Imamura was further developed for many years in our group.As a method towards O(N)with high efficiency and high accuracy for any dimensional systems.This treatment designed for one-dimensional(ID)polymers is now available for three-dimensional(3D)systems,but geometry optimization is now possible only for 1D-systems.As an approach toward post-Hartree-Fock,it was also extended to     

《Chinese Science Bulletin》SUBJECT INDEX TO VOLUME 59(2014)

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An on-line scaling method for improving scalability of a database cluster

The explosive growth of the Internet and database applications has driven database to be more scalable and available, and able to support on-line scaling without interrupting service. To support more client's queries without downtime and degrading the response time, more nodes have to be scaled up while the database is running. This paper presents the overview of scalable and available database that satisfies the above characteristics. And we propose a novel on-line scaling method. Our method improves the existing on-line scaling method for fast response time and higher throughputs. Our proposed method reduces unnecessary network use, i.e. , we decrease the number of data copy by reusing the backup data. Also, our on-line scaling operation can be processed parallel by selecting adequate nodes as new node. Our performance study shows that our method results in significant reduction in data copy time.     

An improved R-tree based on childnode''s probability

R-Tree is a good structure for spatial searching. But in this indexing structure,either the sequence of nodes in the same level or sequence of traveling these nodes when queries are made is random. Since the possibility that the object appears in different MBR which have the same parents node is different, if we make the subnode who has the most possibility be traveled first, the time cost will be decreased in most of the cases. In some case, the possibility of a point belong to a rectangle will shows direct proportion with the size of the rectangle. But this conclusion is based on an assumption that the objects are symmetrically distributing in the area and this assumption is not always coming into existence. Now we found a more direct parameter to scale the possibility and made a little change on the structure of R-tree, to increase the possibility of founding the satisfying answer in the front sub trees. We names this structure probability based arranged R-tree (PBAR-tree).     

Integrating GIS Web services based on mediating architecture

The geographic information service is enabled by the advancements in general Web service technology and the focused efforts of the OGC in defining XML-based Web GIS service. Based on these models, this paper addresses the issue of services chaining,the process of combining or pipelining results from several interoperable GIS Web Services to create a customized solution. This paper presents a mediated chaining architecture in which a specific service takes responsibility for performing the process that describes a service chain. We designed the Spatial Information Process Language (SIPL) for dynamic modeling and describing the service chain, also a prototype of the Spatial Information Process Execution Engine (SIPEE) is implemented for executing processes written in SIPL. Discussion of measures to improve the functionality and performance of such system will be included.     

Tracking data management using topology of moving object database system for moving object constrained trajectory in LBS application

Advances in wireless technologies and positioning technologies and spread of wireless devices, an interest in LBS (Location Based Service) is arising. To provide location based service, tracking data should have been stored in moving object database management system (called MODBMS) with proper policies and managed efficiently. So the methods which acquire the location information at regular time intervals then, store and manage have been studied. In this paper, we suggest tracking data management techniques using topology that is corresponding to the moving path of moving object. In our techniques, we update the MODBMS when moving object arrived at a street intersection or a curved road which is represented as the node in topology and predict the location at past and future with attribute of topology and linear function. In this technique, location data that are corresponding to the node in topology are stored, thus reduce the number of update and amount of data. Also in case predicting the location,because topology are used as well as existing location information, accuracy for prediction is increased than applying linear function or spline function.