Analysis of Heat Environment Indexes Using Integrated Remote Sensing and Site Measurement Techniques in a Community

Remote sensing and on？site measurement are used to determine the heat environment within a community, and are compared the differences for heat analysis. The two methods perform differently for various underlying surfaces. The individual methods can detect different aspects of the heat environment, which used in combination are useful for heat island research. The differences in estimated air and surface temperatures are smaller in open space and more obvious for vegetated surfaces. Ventilation does not affect the difference between air and surface temperature in open areas, and the vegetation surface and shading moderates surface temperature more effectively than the water surface; The forest is a type of underlying surface with heat comfortable, in which the feeling of air temperature is much difference to the structure of heat environment that should be survey and detected separately. The two methods can be used to study different aspects of the heat environment, thus forming a comprehensive approach for planners in urban and rural spaces.     

Spatio-temporal succession of iron and manganese microbial community in biological filter layer

This paper studied the structure and dynamic change of microbial communities in bio-reactor for treating ground water which contained high concentration of iron and manganese.In this study,polymerase chain reaction(PCR) denaturing gradient gel electrophoresis(DGGE) was used to evaluate the bacterial diversity.Different samples in spatio-temporal of bacterial community suceession in sands were analyzed,and the removal of iron and manganese were discussed.The results showed that a significant change in the community structure was observed during running time and the bio-reactor which designed by ourselves:the removal rate of iron and manganese could achieve 88.93%.The mass of microrganisms was decreasing,and the type of micro-organisms tended to stable with the increase of operating time.Besides,the change of mass and types of micro-organisms in sands was related to temperature.Along the depth of filter layer,the mass and types of micro-organisms were gradually decreasing.Further,pseudomonas were found to be the main microbiology by recycling the band sequencing and phylogenetic analysis.And with time increasing the mass and kind of bacteria were growing from less to more,finally to be stable.     

Application of multi-stage bio-filtration system for sewage treatment and analysis of the microbial community

The conventional fixed-bed biofilm process has disadvantages of easily blocked,high headloss and short operation cycle.For overcoming these disadvantages,a multi-stage biofilm reactor(MSBFR),in which the lightweight floating filter was dominant,was set up and operated.For detail investigation of the system when treating municipal wastewater,the succession characteristic of microbial community was analyzed by polymerase chain reaction(PCR)-Denaturing Gradient Gel Electrophoresis(DGGE)method.The results showed that the process had high efficiency to removal COD,SS and NH4+-N.The concentration of COD,SS and NH4-N in effluent were maintained lower than 40 mg/L,5 mg/L and 2 mg/L even though the concentration of COD,SS and NH4+-N in influent were 232-663 mg/L,105-245 mg/L and 23.7-62.7 mg/L,respectively,and the empty bed retention time was 3 h.Furthermore,biofilm samples taken from the column 2nd in height were analyzed by PCR-DGGE.The result of PCR-DGGE analysis showed that the microbial community had a little change in height and the dominant groups were Paracoccus sp.,Lactobacillus delbrueckii,Pseudomonas sp.and Bacteroidetes bacterium.     

Community discovery method with uncertainty measure of overlappingnodes based on topological potential

Community discovery of complex networks,esp.of social networks,has been a hotly debated topic in academic circles in recent years.Since actual networks usually contain some overlapping nodes that are d...     

Impact of Online Community Structure on Information Propagation: Empirical Analysis and Modeling

Online social networking sites (OSNS), as a popular social media platform, have been developed massively for business and research purposes. In this paper, it investigated the impact of community structure in online social network on information propagation. A SI (Susceptible-Infected) model based on community structure was proposed. In the SI model, the heterogeneity of user’s active time was taken into account. From the results, it was found that the number of links among communities determines the fraction of infected nodes. With the increase of the number of groups G, however, the fraction of infected nodes remains approximately constant. The simulation results will be of great significance: the information will last relatively short for group networks which have either a small or a large number of groups. The results can be useful for optimizing or controlling information, such as propagating rumors in online social networks.     

VisQAC: Visual Analytics for Online Q&A Communities

Online question and answer (Q&A) communities, which allow users to exchange knowledge by asking and answering questions, have become increasingly popular. As a result of user active participation, these communities store overwhelming volumes of information. However, existing related methods are unable to meet community operators'' needs for analyzing multi-dimensional Q&A sequences and understanding user behavior. In this paper, collaborating with domain experts in online community,we present a system, VisQAC, which explores the patterns of Q&A sequence and user behavior. In the system,a novel visual design is proposed, which is combined with flexible mapping measures for analyzing critical characteristics of sequence data. Moreover, a timeline visualization method is designed to visualize data with categorical attributes and its correlation can be displayed flexibly by choosing time mode and time granularity. The usefulness and effectiveness of the system are demonstrated with several case studies of VisQAC with community operators based on the Zhihu dataset. Our evaluation shows that VisQAC is beneficial to the understanding of Q&A sequence and associated user behavior.     

Effect of deteriorated microstructures on stress corrosion cracking of X70 pipeline steel in acidic soil environment

In order to investigate stress corrosion cracking (SCC) of X70 pipeline steel and its weld joint area in acidic soil environ-ment in China, two simulating methods were used: one was to obtain bad microstructures in heat affected zone by annealing at 1300°C for 10 min and then, quenching in water; the other was to get different simulating solutions of acidic soil in Yingtan in south-east China. The SCC susceptibilities of X70 pipeline steel before and after quenching in the simulating solutions were analyzed...     

A Scheme on the Integration of VPN and PKI

A Scheme is introduced in this paper on integration of VPN and PKI. Techniques concerning authentication and data package in VPN, and cross-certification in PKI are described. With the employment of PKI and CA, the network security and key management in VPN are improved. The integration is transparent to the users and cost-effective in setting up and maintaining a VPN.     

Human Capital Investment and an Analysis of Its Progressive Profit

Skilled labor force cultivated through putting in funds and time in their education are undoubtedly essential in the operation of sophisticated machines in production, but it is so also in the creation of new ideas and methods in production and other economic activities, and ultimately in the promotion of the progressive increase of material capital. Thus strengthening the investment of human capital and enriching the stock of human capital is of primary importance, especially for China, in the 21st century.     

Transgression regression event element geochemistry records of southwestern Fujian in Late Triassic-Middle Jurassic

Southwest Fujian area has experienced a large-scale transgression regression cycle in Late Triassic-Middle Jurassic and the maximum transgression has taken place in Early Jurassic. The migration and enrichment of geochemical element in the continuous fine-grained sediments in the basin recorded the paleosalinity and the paleodepth. The changes of paleosalinity and paleodepth indicate the sea(lake) level relative change in every period of Late Triassic-Middle Jurassic in southwestern Fujian. The relative change curve of sea(lake) level in southwestern Fujian is established based on the m value(m=100×w(MgO)/w(Al2 O3)) and the ratios of w(B)/w(Ga), w(Sr)/w(Ba) and w(Ca)/w(Mg). The curve indicates that level I sea-level relative change in southwestern Fujian is composed of the transgression in Late Triassic-Early Jurassic and the regression in the late period of Early Jurassic-Middle Jurassic. The level III sea-level relative change is frequent, which is composed by the lake level descent lake level rise lake level descent of Wenbin Shan formation in Late Triassic, the regression transgression regression of Lishan formation in Early Jurassic and the lake level rise lake level descent-lake level rise lake level descent of Zhangping formation in Middle Jurassic. The transgression regression cycle in southwestern Fujian is significantly controlled by the sea-level change in the north of South China Sea. The relative change curve trends of the level I sea-level in the north of South China Sea and the one in southwestern Fujian are the same. The maximum transgressions both occur in Early Jurassic. The level III sea-level curve reflects the fluctuation of a transgression and two regressions in the early period of Early Jurassic.     

基于拓扑势的网络社区结点重要度排序算法

针对经典网络社区划分方法存在的划分结果难以理解的问题,基于源自物理学中核子场的拓扑势理论,提出针对具有聚类效应的社会网络和复杂网络的社区结点重要度排序算法.在算法中,首先利用NSP方法(network soft partition based on topological potential)依据结点在社区中所起的作用将其分为内部结点和边界结点,其次分别对内部结点和边界结点的重要性进行量化并排序,最后将2个排序结果进行拼接以构成最终的排序结果.实验表明,文中算法不但可以解决前述问题,而且具有和快速排序算法同样的时间复杂度.     

基于局部模块度的社区层次结构发现方法

为了发现复杂网络中社区之间的层次关系,提出了一种基于局部模块度的社区层次结构发现方法。文章方法克服了多分辨率方法无法给出整个网络的层次划分以及无法直接定位造成社区层次变化的分辨率等方面不足,选取网络中的大度数节点基于R公式进行社区层次结构探测,根据局部模块度值变化过程中产生的极大值和极小值定义了社区层次区分度来判断是否到达层次边界。并对网络进行裁剪,从不同的大度数节点出发来发现网络中的全部层次结构。在经典数据集和人工生成网络上进行了实验,并与现有算法进行比较。实验结果证明章算法的有效性。     

基于改进卡尔曼滤波目标跟踪分簇方法研究

针对现有的目标跟踪分簇算法没有从根本上解决参与跟踪的节点数量过多,导致整个无线传感器网络(WSN)能耗的增加问题,提出一种基于Fisher信息矩阵的改进卡尔曼滤波的目标跟踪分簇方法 (Fisher Matrix for Kalman Filter,FMKF),用于针对性的选择节建立跟踪簇。该算法利用随机矢量估计的克拉美罗下界获得未知噪声的统计特性,优化卡尔曼滤波器的误差协方差。在无线传感器网络动态分簇时,创新的使用信息判据作为标准,并且加入节点剩余能量判据。仿真结果显示,FMKF算法与控制簇的激活半径算法和无分簇算法相比,FMKF算法可以在减少跟踪节点的数量的同时提高跟踪精度。     

基于聚类的超闭球CMAC神经网络改进算法

针对CMAC神经网络的网络节点随输入维数的增大呈几何级数增加的问题,提出了基于模糊聚类的超闭球CMAC神经网络改进算法。该算法通过对输入数据进行模糊聚类确定网络节点数和节点值,并根据输入输出数据通过模糊推理优化算法计算神经网络初始权值。与原算法比较,该算法可有效降低神经网络节点数,提高系统的学习精度。对一个多步时延的非线性系统的辨识仿真结果表明了该算法的可行性与有效性。     

集合扩充的社团分解算法

社团结构是复杂网络的重要特征之一,寻找网络中的社团对于分析整个网络的结构和功能都有非常重要的意义.综述了一些经典的复杂网络社团结构划分的算法,提出了一种基于集合扩充的社团结构划分的新算法.该算法以网络中相邻的两个节点构成的集合为起点,用社团同外部联系的边的数目与社团内部边的数目的比值作为度量指标,通过计算将某一个邻居节点加入该集合后度量指标值的变化情况来判断某个邻居节点是否加入该集合,若度量指标值变小则将该邻居节点加入该集合,若度量指标值变大则不将该邻居节点加入该集合,直到不再有新的邻居节点加入时,一个社团就被划分出来.在剩下的网络中重复这个过程直到网络中的节点完全被划分.用社团结构分解中的两个经典例子测试了该算法,从测试结果来看,用该方法能够合理地划分网络中的社团结构,且运算量小,运行效率高,达到了预期目标.该社团结构的划分方法对于规模较大的复杂网络也具有普遍意义.     

基于Rough set理论的无线传感器网络节点故障

提出了一种无线传感器网络（WSN）节点故障诊断的新方法，首先基于粗糙集理论中改进的可辨识矩阵算法得到故障诊断决策的属性约简；然后通过属性匹配的故障分类算法，建立一套WSN节点故障诊断方法，对WSN节点的各个模块分别进行具体的故障诊断和定位. 仿真实验表明，该方法在WSN节点故障诊断时通信代价小、能量消耗低、诊断准确率高，因而具有在能量有限的WSN节点中应用的可能性.     

基于混合蒙特卡罗算法的网络隐式节点监测方法研究

为了提高动态分簇传感网络的节点转发能力,提出了一种基于混合蒙特卡罗算法的网络隐式节点监测方法.首先,采用分布式均衡控制方法进行网络节点优化设计,构建动态分簇传感网络的输出信道模型.其次,利用自适应链路转发协议进行网络的路由探测设计,构建动态分簇传感网络的隐式节点路由均衡控制模型,提取隐式节点输出信息的关联特征量.最后,利用混合蒙特卡罗算法进行特征检测和信息提取,根据网络隐式节点的特征规律性分布对网络隐式节点信息进行监测.仿真结果表明,本文方法对网络隐式节点具有较好的监测效果,对网络隐式节点监测的最高丢包率仅为0.05,显著低于蚁群算法(0.29)与PEAS算法(0.48).     

基于种子节点集的社区层次结构发现算法

针对多分辨率方法无法直接给定社区层次结构的问题,提出一种基于种子节点集的社区层次结构发现算法。该算法通过选取种子节点,并根据余弦相似度的大小添加其最近邻节点共同构成种子节点集;再由种子节点集出发,基于分辨率公式进行社区层次结构探测,根据节点加入社区的度值比来判断是否到达层次边界;最后在已发现完毕的社区外选取新的种子节点集,并由此出发直到全网络的社区层次结构发现完毕。将该算法分别应用于人工网络和真实社会网络,实验表明,相较于其它算法,该算法能够更好地发现网络中全部的社区层次结构。     

基于PSNodeRank算法的电力系统关键节点辨识方法

电力系统中的某些关键节点在系统发生大规模连锁故障的时候可能会对故障的扩大起着推动的作用。为了提高关键节点辨识的速度和准确性,该文通过对Google公司提出的PageRank算法进行改进,提出基于PSNodeRank算法的电网关键节点辨识方法。该方法选取电网关键节点的重要评价指标,建立电力系统有向加权网络模型。考虑电力系统网络的网络链接方向和权值的特性,该文提出PSNodeRank值对节点进行评估,并具体描述每个节点的重要性,再利用电力系统分区特点,对大电网节点重要性的复杂计算过程进行改进,大大提高了运算速度,减少了运算所需存储容量。最后,通过对IEEE 39节点系统进行仿真,所得结果表明:该文所提方法计算的指标可以有效、准确地辨识出电网中的关键节点,判断它们在交直流电网自组织临界演化过程中的作用。对预防系统向连锁故障临界状态演化有着重要的意义。