Index-adaptive Triangle-Based Graph Local Clustering

Motif-based graph local clustering(MGLC)algorithms are gen-erally designed with the two-phase framework,which gets the motif weight for each edge beforehand and then conducts the local clustering algorithm on the weighted graph to output the result.Despite correctness,this frame-work brings limitations on both practical and theoretical aspects and is less applicable in real interactive situations.This research develops a purely local and index-adaptive method,Index-adaptive Triangle-based Graph Local Clustering(TGLC+),to solve the MGLC problem w.r.t.triangle.TGLC+combines the approximated Monte-Carlo method Triangle-based Random Walk(TRW)and deterministic Brute-Force method Triangle-based Forward Push(TFP)adaptively to estimate the Personalized PageRank(PPR)vector without calculating the exact triangle-weighted transition probability and then outputs the clustering result by conducting the standard sweep procedure.This paper presents the efficiency of TGLC+through theoretical analysis and demonstrates its effectiveness through extensive experiments.To our knowl-edge,TGLC+is the first to solve the MGLC problem without computing the motif weight beforehand,thus achieving better efficiency with comparable effectiveness.TGLC+is suitable for large-scale and interactive graph analysis tasks,including visualization,system optimization,and decision-making.

Index-free triangle-based graph local clustering

Motif-based graph local clustering(MGLC)is a popular method for graph mining tasks due to its various applications.However,the traditional two-phase approach of precomputing motif weights before performing local clustering loses locality and is impractical for large graphs.While some attempts have been made to address the efficiency bottleneck,there is still no applicable algorithm for large scale graphs with billions of edges.In this paper,we propose a purely local and index-free method called Index-free Triangle-based Graph Local Clustering(TGLC^(*))to solve the MGLC problem w.r.t.a triangle.TGLC^(*)directly estimates the Personalized PageRank(PPR)vector using random walks with the desired triangleweighted distribution and proposes the clustering result using a standard sweep procedure.We demonstrate TGLC^(*)’s scalability through theoretical analysis and its practical benefits through a novel visualization layout.TGLC^(*)is the first algorithm to solve the MGLC problem without precomputing the motif weight.Extensive experiments on seven real-world large-scale datasets show that TGLC^(*)is applicable and scalable for large graphs.

Unveiling the early stage evolution of local atomic structures in the crystallization process of a metallic glass

The early stage evolution of local atomic structures in a multicomponent metallic glass during its crystallization process has been investigated via molecular dynamics simulation.It is found that the initial thermal stability and earliest stage evolution of the local atomic clusters show no strong correlation with their initial short-range orders,and this leads to an observation of a novel symmetry convergence phenomenon,which can be understood as an atomic structure manifestation of the ergodicity.Furthermore,in our system we have quantitatively proved that the crucial factor for the thermal stability against crystallization exhibited by the metallic glass is not the total amount of icosahedral clusters,but the degree of global connectivity among them.

A Dark Matter Theory by Quantum Gravitation for Galaxies and Clusters

This paper develops an original theory of dark matter in the current ΛCDM framework, whose main hypothesis is that DM is generated by the own gravitational field, according to an unknown quantum gravitational phenomenon. This work is the best version of the theory, which I have been developing and publishing since 2014. The hypothesis of DM by quantum gravitation, DMbQG hereafter, has two main consequences: the first one is that the law of DM generation has to be the same, in the halo region, for all the galaxies and the second one is that the haloes are unbounded, so the total DM goes up without limit as the gravitational field is unbounded as well. The first one consequence is backed by the fact that M31 and MW has a fitted function with the same power exponent for the rotation curve at the halo region and both giant galaxies are the only ones whose rotation curves at the halo region may be studied with accuracy. This paper is firstly developed all the theory with M31 rotation curve data up to Chapter 9. The most important formula of the theory is the called Direct mass, which calculates the total mass at a specific radius into the halo region. Chapter 10 is dedicated to apply the theory to Milky Way, it is calculated its total mass at different radius into the halo and such results have been validated successfully using the data of masses at different radius published by two researcher teams. In Chapter 11, it is calculated the direct mass for the Local Group, and it is shown how the DMbQG theory is able to calculate the total mass at 770 kpc, that the dynamical methods estimate to be 5×1012MΘ. In Chapter 12, it is shown a method to estimate the Direct mass formula for a cluster of galaxies, using only its virial mass and virial radius. By this method, it is estimated the parameter a2 of the Local Group, which match with the one calculated in previous chapter by a different method. Also are calculated the parameters a2 associated to Virgo and Coma clusters. In Chapter 13, it is demonstrated how the DE is able to counterbalance the DM at cluster scale, as the Direct mass grows up with the square root of radius whereas the DE grows up with the cubic power. The chapter is an introduction to the DMbQG theory for cluster of galaxies, which has been developed fully by the author in other works. This theory aims to be a powerful method to study DM in the halo region of galaxies and cluster of galaxies and conversely the measures in galaxies and clusters offer the possibility to validate the theory.

A Hierarchical Clustering and Fixed-Layer Local Learning Based Support Vector Machine Algorithm for Large Scale Classification Problems

It is a challenging topic to develop an efficient algorithm for large scale classification problems in many applications of machine learning. In this paper, a hierarchical clustering and fixed- layer local learning （HCFLL） based support vector machine（SVM） algorithm is proposed to deal with this problem. Firstly, HCFLL hierarchically dusters a given dataset into a modified clustering feature tree based on the ideas of unsupervised clustering and supervised clustering. Then it locally trains SVM on each labeled subtree at a fixed-layer of the tree. The experimental results show that compared with the existing popular algorithms such as core vector machine and decision.tree support vector machine, HCFLL can significantly improve the training and testing speeds with comparable testing accuracy.

A LOCAL DYNAMIC CLUSTER SELF-ORGANIZATION ALGORITHM IN WIRELESS SENSOR NETWORKS FOR RAINFALL MONITORING

Wireless Sensor Networks for Rainfall Monitoring (RM-WSNs) is a sensor network for the large-scale regional and moving rainfall monitoring,which could be controlled deployment. Delivery delay and cross-cluster calculation leads to information inaccuracy by the existing dynamic collabo-rative self-organization algorithm in WSNs. In this letter,a Local Dynamic Cluster Self-organization algorithm (LDCS) is proposed for the large-scale regional and moving target monitoring in RM-WSNs. The algorithm utilizes the resource-rich node in WSNs as the cluster head,which processes target information obtained by sensor nodes in cluster. The cluster head shifts with the target moving in chance and re-groups a new cluster. The target information acquisition is limited in the dynamic cluster,which can reduce information across-clusters transfer delay and improve the real-time of information acquisition. The simulation results show that,LDCS can not only relieve the problem of "too frequent leader switches" in IDSQ,also make full use of the history monitoring information of target and con-tinuous monitoring of sensor nodes that failed in DCS.

The impact of spatial scale on local Moran's I clustering of annual fishing effort for Dosidicus gigas offshore Peru

The spatial scale(?shing grid) of ?sheries research af fects the observed spatial patterns of?sheries resources such as catch-per-unit-ef fort(CPUE) and ?shing ef fort. We examined the scale impact of high value(HH) clusters of the annual ?shing ef fort for Dosidicus gigas of fshore Peru from 2009 to 2012.For a multi-scale analysis, the original commercial ?shery data were tessellated to twelve spatial scales from 6′ to 72′ with an interval of 6′. Under these spatial scales, D. gigas clusters were identi?ed using the Anselin Local Moran's I. Statistics including the number of points, mean CPUE, standard deviation(SD),skewness, kurtosis, area and centroid were calculated for these HH clusters. We found that the z-score of global Moran's I and the number of points for HH clusters follow a power law scaling relationship from2009 to 2012. The mean ef fort and its SD also follow a power law scaling relationship from 2009 to 2012.The skewness follows a linear scaling relationship in 2010 and 2011 but ?uctuates with spatial scale in2009 and 2012; kurtosis follows a logarithmic scale relationship in 2009, 2011 and 2012 but a linear scale relationship in 2010. Cluster area follows a power law scaling relationship in 2010 and 2012, a linear scaling relationship in 2009, and a quadratic scaling relationship in 2011. Based on the peaks of Moran's I indices and the multi-scale analysis, we conclude that the optimum scales are 12′ in 2009 ? 2011 and 6′ in 2012, while the coarsest allowable scales are 48′ in 2009, 2010 and 2012, and 60′ in 2011. Our research provides the best spatial scales for conducting spatial analysis of this pelagic species, and provides a better understanding of scaling behavior for the ?shing ef fort of D. gigas in the of fshore Peruvian waters.

Quasi-aromaticity in Cluster Chemistry Ⅱ. Localized Molecular Orbital Studies on Co_6 (CO)_(14)^(4-) and Ni_2Co_4 (CO)_(14)^(2-) Cluster Anions

The energy-localized CNDO/2 molecular orbitals have been calculated for the cluster anions of [Co_6 (CO)_(14)]￣(4-) and [Ni_2Co_4 (CO)_(14)]￣(2-)in order to get a deeper insight into the nature of their skeletal bonding. The bonding characteristics of these hexanuclear carbonyl cobaltates are described from a localization bonding viewpoint. There are two typical M-CO bondings, one of which is formed by electron donation from the terminal and capping carbonyl ligands into the vacant hybrid orbitals on the metal atoms , leading to formation ofσ(C_t→Co) and σ(C_b→{Co_3})bonds. The other typical M-CO bonding is back donation of the lone d-electron pairs on the metal atoms into the carbonyl ligands, forming π(Co→C_t) bonds, σ(Co→{C_(b2)}) bonds and π(Co→{C_(b4)} ) bonds. It is found that there are no direct metalmetal bondings in the skeletons of these two cluster anions.The delocalization situation of the skeletal bonding electrons is briefly discussed.

The Assessment of Localized Clustering of Photovoltaic Plants in Italy: The Role of Financial Incentives

In recent years, the rapid growth of renewable energy sources (photovoltaic, biomass, geothermal, wind and hydroelectricity) constitutes a feasible solution for environmental problems created by the present production-consumption energy model. Photovoltaic (PV) is one of the most promising, renewable energy sources with great potential for development. Over the last decade, the diffusion of photovoltaic installations in Italy has recorded a considerable increase, displaying at the same time substantial regional dissimilarities. In this paper, we sustain the hypothesis that the installation of PV plants is first of all driven by the financial incentives granted. Using data for Italian provinces, derived under two different editions of the Energy Account, which represents the current Italian financing mechanism, we apply a statistical cluster detection method (the spatial elliptic scan statistics) to identify differences in the spatial distribution of PV plants, in terms of most concentration, throughout the Italian territory. The focus is on mapping the clusters and checking their spatial stability over time, when different subsidy schemes have been adopted. The evidence shows that in the latest detected clusters there are many Northern Italian provinces, with adverse climate conditions (low global irradiance level, low annual temperatures), which have rapidly taken advantage of incentives for solar energy installations.

Quasi-aromaticity in Cluster Chemistry Ⅲ. Localized Molecular Orbital Study on Electron-rich Cobalt-sulfur Cluster Compounds[Co_6(μ_3-X)_8L_6]￣(n+)(X=S,Se;L=PPh_3,PEt_3,CO;n=0,1)

The localized molecular orbitals and energy levels for [Co_6 (μ_3-S)_8 (PH_3)_6]￣(n+)(n=0, 1) as model molecules of the electron-rich [Co_6 (μ_3-S)_8 (PPh_3)_6]￣(n+) (n=0,1) cluster compounds have been calculated by using Edmiston-Ruedenberg energy localization scheme under the spin-unrestricted CNDO/2 approximation. It is shown that the cluster skeletons of these two isostructural molecules consist of the edge-localized two-centered two-electron (Co-S) bonds plus a pair of the skeleton electrons delocalized on the whole cluster core,leading an extra stability of the cluster core.The one-electron oxidation for the neutral molecule gives rise to a one-electron σ (Co-Co) bond.which further resonates among the three diagonal lines of the {Co_6} octahedron. The comparison between [Co_6 (μ_3-S)_8(PPh_3)_6] and [Co_6(μ_3-CO)_8(CO)_6]￣(4-) indicates that the latter possesses face-localized bridging-bonds which are further delocalized on the whole surface of the cluster octahedron by the back-donation bonds from the lone electron pairs on the Co atoms to the capping carbonyl CO ligands. The structural features of the series of the [Co6(μ_3-X)_8L_6]￣(n+)(X =S, Se; L=PPh_3,PEt_3, CO;n=0, 1) cluster compounds are briefly rationalized on the basis of the localization description as well.

Winding sense of galaxies around the local supercluster

We present an analysis of the winding sense（S and Z-shapes） of 1 621 field galaxies that have radial velocity between 3 000 km s-1 and 5 000 km s-1.The preferred alignments of S-and Z-shaped galaxies are studied using chi-square,autocorrelation and Fourier series tests.We classify all the galaxies into 32 subsamples and notice a good agreement between the position angle（PA） distribution of the S-and Zshaped galaxies.The homogeneous distribution of the S-and Z-shaped galaxies is more noticeable for the late-type spirals（Sc,Scd,Sd and Sm） than for the early-types（Sa,Sab,Sb and Sbc） .A significant dominance of S-mode galaxies is apparent in the barred spirals.A random alignment is evident in the PA-distribution of Z-and S-mode spirals.In addition,a homogeneous distribution of the S-and Z-shaped galaxies is found to be invariant under global expansion.The PA-distribution of the total S-mode galaxies is found to be random,whereas a preferred alignment is clear for all the Zmode galaxies.It is found that the galactic planes of Z-mode galaxies tend to lie in the equatorial plane.

基于局部密度聚类的WSN多Sink节点部署研究

针对无线传感器网络中传感器节点能量受限,网络生命周期短的问题,在考虑网络成本的情况下,提出一种基于节点局部密度聚类的多Sink节点优化部署算法。首先,基于多属性因子构建聚类决策函数确定Sink节点部署位置,完成传感器节点聚类;然后,根据下一跳节点与Sink节点间距离最短准则搜索并形成数据传输路径;最后,以网络生命周期成本比最大化为依据确定最优的Sink节点数目,实现多Sink节点优化部署。仿真结果表明:与已有算法相比,所提算法能够有效延长网络生命周期,具有较高的网络生命周期能效比。

Outlier detection based on multi-dimensional clustering and local density

Outlier detection is an important task in data mining. In fact, it is difficult to find the clustering centers in some sophisticated multidimensional datasets and to measure the deviation degree of each potential outlier. In this work, an effective outlier detection method based on multi-dimensional clustering and local density(ODBMCLD) is proposed. ODBMCLD firstly identifies the center objects by the local density peak of data objects, and clusters the whole dataset based on the center objects. Then, outlier objects belonging to different clusters will be marked as candidates of abnormal data. Finally, the top N points among these abnormal candidates are chosen as final anomaly objects with high outlier factors. The feasibility and effectiveness of the method are verified by experiments.

地方智慧旅游公共服务平台持续使用意愿研究

地方智慧旅游公共服务平台的建设和运营已经成为各地全域旅游建设与发展的重要组成部分,但是平台的持续使用一直是学术和行业界讨论的重点。文章以“游云南”平台为案例,基于刺激-机体-反应理论框架,运用混合研究方法对地方智慧旅游公共服务平台的持续使用意愿进行研究,并提出“因素-感知-使用”地方智慧旅游公共服务平台持续使用意愿综合分析模型,得到如下研究结果。1)在地感知、地方依恋均能够显著提高游客对地方智慧旅游公共服务平台的感知信任和情感依恋,进而提高满意度。其中,平台情感依恋在提高平台持续使用意愿方面具有显著正向作用。具体而言,在地感知会通过信息拓展、形象匹配之机制,地方依恋会通过情感外溢、期待满足之机制促进平台情感依恋和信任的产生,并最终提高持续使用意愿。2)功能集群、享乐体验均能够显著提高游客对地方智慧旅游公共服务平台的感知有用性、感知易用性和感知信任,进而提高游客使用满意度,最终提高持续使用意愿。功能集群通过“信息全面、减少成本”之机制,享乐体验通过“逃离惯常、精美设计”之机制影响游客对平台的积极感知。

局部线性下的函数型主成分聚类算法

函数型聚类分析在统计学领域被广泛关注,其分析过程通常在降维目标实现后进行。为了有效解决函数型主成分聚类问题,文章结合局部线性嵌入算法(Locally Linear Embedding,LLE)在非线性空间下的适用性,提出了一种局部线性下的函数型主成分分析模型(LLE Function Principle Component Analysis,LFPCA)。首先,采用函数型主成分分析法作为降维目标方法,改进了FPCA的算法模型,通过将LLE算法的权重系数矩阵与函数型主成分定义相结合,构建出一个适用于非线性空间下的聚类算法;其次,在求解算法的过程中定义了函数型主成分得分,并结合EM算法构建出GMM模型来近似函数型算法的概率密度函数,使模型更高效且适用性更强;最后,通过随机模拟实验及应用分析验证了LFPCA算法模型在真实数据集上具有良好的聚类效能。

Controlling optical responses through local dielectric resonance in nanometre metallic clusters

Optical responses in dilute composites are controlled through the local dielectric resonance of metallic clusters. We consider two located metallic clusters close to each other with admittances ε1 and ε2. Through varying the difference admittance ratio η[= （ε2 - ε0）/（ε1 - ε0）], we find that their optical responses are determined by the local resonance. There is a blueshift of absorption peaks with the increase of η- Simultaneously, it is known that the absorption peaks will be redshifted by enlarging the cluster size. By adjusting the nano-metallic cluster geometry, size and admittances, we can control the positions and intensities of absorption peaks effectively. We have also deduced the effective linear optical responses of three-component composites εe=ε0 （1＋∑^n n=1[（γn1＋ηγn2）/（ε0（s-sn））]） and the sum rule of cross sections：∑^n n=1（γn1＋ηγn2）=Nh1＋Nh2,, where Nh1and Nh2 are the numbers of εl and ε2 bonds along the electric field, respectively. These results may be beneficial to the study of surface plasmon resonances on a nanometre scale.

局部标准差优化的密度峰值聚类算法

密度峰值聚类(clustering by fast search and find of density peaks,DPC)算法是一种基于密度的聚类算法,它可以发现任意形状和维度的类簇,是具有里程碑意义的聚类算法。然而,DPC算法的样本局部密度定义不适用于同时发现数据集的稠密簇和稀疏簇;此外,DPC算法的一步分配策略使得一旦有一个样本分配错误,将导致更多样本的错误分配,产生“多米诺骨牌效应”。针对这些问题,提出一种新的样本局部密度定义,采用局部标准差指数定义样本局部密度,克服DPC的密度定义缺陷;采用两步分配策略代替DPC的一步分配策略,克服DPC的“多米诺骨牌效应”,得到ESDTS-DPC算法。与DPC及其改进算法KNN-DPC、FKNN-DPC、DPC-CE和经典密度聚类算法DBSCAN的实验比较显示,提出的ESDTS-DPC算法具有更好的聚类准确性。

Quasi-aromaticity in Cluster Chemistry Ⅱ. Localized Molecular Orbital Studies on Co6 （CO）14 ￣（4-） and Ni2Co4 （CO）14 ￣（2-） Cluster Anions

The energy-localized CNDO/2 molecular orbitals have been calculated for the cluster anions of [Co6 （CO）14]￣（4-） and [Ni2Co4 （CO）14]￣（2-）in order to get a deeper insight into the nature of their skeletal bonding. The bonding characteristics of these hexanuclear carbonyl cobaltates are described from a localization bonding viewpoint. There are two typical M-CO bondings, one of which is formed by electron donation from the terminal and capping carbonyl ligands into the vacant hybrid orbitals on the metal atoms , leading to formation ofσ（Ct→Co） and σ（Cb→{Co3}）bonds. The other typical M-CO bonding is back donation of the lone d-electron pairs on the metal atoms into the carbonyl ligands, forming π（Co→Ct） bonds, σ(Co→{Cb2}) bonds and π(Co→{Cb4} ) bonds. It is found that there are no direct metalmetal bondings in the skeletons of these two cluster anions.The delocalization situation of the skeletal bonding electrons is briefly discussed.

面向密度分布不均数据的混合近邻密度峰值聚类算法

密度峰值聚类算法(DPC)的局部密度忽略了密度分布不均数据的疏密差异,易导致类簇中心聚集在密集区域;其分配策略在分配剩余样本时,易将稀疏区域样本错误分配到密集区域,致使聚类效果不佳.为克服上述缺陷,本文提出了面向密度分布不均数据的混合近邻密度峰值聚类(MN-DPC)算法.首先,利用自然近邻信息定义样本的局部密度,平衡稀疏区域与密集区域样本之间的密度差异,从而正确找到稀疏区域的类簇中心;其次,利用样本之间的共享及自然近邻信息对样本相似度进行加权处理,加强了同一类簇样本间的相似度,有效的避免稀疏区域样本被错误分配.本文将MN-DPC算法与IDPC-FA,DPC-DBFN,DPCSA,FNDPC,FKNN-DPC,DPC算法进行对比.实验结果表明,MN-DPC算法能有效聚类密度分布不均及UCI数据集.

71份广西豌豆地方种质资源农艺性状遗传多样性分析

【目的】分析广西豌豆地方种质资源农艺性状的遗传多样性并筛选优异种质,为其高效利用提供参考依据。【方法】以71份广西豌豆地方种质资源为材料,测定其农艺性状(10个质量性状和16个数量性状),分析其遗传变异情况,并进行相关性分析、主成分分析和聚类分析。【结果】10个质量性状的变异系数变化范围为13.07%~47.71%,平均29.16%,所有质量性状变异系数均大于10.00%;遗传多样性指数变化范围为0.13~1.26,平均值为0.62。16个数量性状变异系数变化范围为5.78%~61.75%,平均24.07%,多数性状变异系数大于10.00%;遗传多样性指数变化范围为1.73~2.07,平均1.93。相关性分析结果表明,在26个农艺性状中,大部分性状间存在不同程度的相关性。主成分分析表明,26个农艺性状前7个主成分的累计贡献率为75.621%,主要与生育期、产量、籽粒外观、株型、荚果外观有关。聚类分析结果表明,71份广西豌豆地方种质资源主要分为2个类群(I类群和Ⅱ类群),其中I类群又分为2个次级类群(Ia和Ib类群),Ia类群属于高秆、蔓生、迟熟、较高产、较抗白粉病的材料,Ib类群属于荚较多且较大,产量较高,籽粒较小,较感白粉病的材料,Ⅱ类群属于较早熟,矮秆,直立,长荚,产量较低,较感白粉病的材料。筛选出14份具有优异农艺性状的豌豆种质资源,其中,2、40、61和67号高产、抗白粉病、综合性状较优异的种质可直接推广应用;3、5、14、15、41、57、59、66、68和71号具有某个(些)优异农艺性状的种质可作为后续创制豌豆优良新种质的亲本。【结论】71份广西豌豆地方种质资源农艺性状遗传多样性较丰富,具有分枝多、节数多、果荚较长、籽粒较多且大的特点。