HiSC:A Hybrid XML Index Composing Structure-Encoded with Cluster

A new way of indexing and processing twig patterns in an XML documents is proposed in this paper. Every path in XML document can be transformed into a sequence of labels by Structure-Encoded that constructs a one-to-one correspondence between XML tree and sequence. Base on identifying characteristics of nodes in XML tree, the elements are classified and clustered. During query proceeding, the twig pattern is also transformed into its Structure-Encoded. By performing subsequence matching on the set of sequences in XML documents, all the occurrences of path in the XML documents are refined. Using the index, the numbers of elements retrieved are minimized. The search results with pertinent format provide more structure information without any false dismissals or false alarms. The index also supports keyword search Experiment results indicate the index has significantly efficiency with high precision.

Application of Principal Component Analysis, Cluster Analysis, Pollution Index and Geoaccumulation Index in Pollution Assessment with Heavy Metals from Gold Mining Operations, Tanzania

Gold mining is now widely acknowledged as one of the significant sources of soil pollution in developed countries. In developing countries, the sources and levels of soil contamination have not been thoroughly addressed. Thus, this study was intended to determine the source of soil pollution and the level of contamination in the active and closed gold mining areas. The research paper presents the pollution load of heavy metals (lead-Pb, chromium-Cr, cadmium-Cd, copper-Cu, arsenic-As, manganese-Mn, and nickel-Ni) in 90 soil samples collected from the studied sites. Multivariate statistical analysis, including Principal Component Analysis (PCA) and Cluster Analysis (CA), coupled with correlation coefficient analysis, was performed to determine the possible sources of pollution in the study areas. The results indicated that Pb, Cr, Cu and Mn come from different sources than Cd, As and Ni. The results obtained from the metal pollution assessment using the Pollution Index (PI) and the Geoaccumulation Index (Igeo) confirmed that soils in the mining areas were contaminated in the range from moderately through strongly to highly contaminated soils. This study verified that soil contamination in the gold mining areas results from natural and anthropogenic processes. The current study findings would enhance our knowledge regarding the soil contamination level in the mining areas and the source of contamination. It is recommended to use PCA, CA, PI and Igeo to assess and monitor the heavy metal contaminated soil in gold mining areas.

AN ANALYSIS OF THE APPLICABILITY OF FUZZY CLUSTERING IN ESTABLISHING AN INDEX FOR THE EVALUATION OF METEOROLOGICAL SERVICE SATISFACTION

An evaluation index is a prerequisite for the scientific evaluation of a public meteorological service.This paper aims to explore a technical method for determining and screening evaluation indicators.Based on public satisfaction survey data obtained in Wafangdian,China in 2010,this study investigates the suitability of fuzzy clustering analysis method in establishing an evaluation index.Through quantitative analysis of multilayer fuzzy clustering of various evaluation indicators,correlation analysis indicates that if the results of clustering were identical for two evaluation indicators in the same sub-evaluation layer,then one indicator could be removed,or the two indicators merged.For evaluation indicators in different sub-evaluation layers,although clustering reveals attribute correlations,these indicators may not be substituted for one another.Analysis of the applicability of the fuzzy clustering method shows that it plays a certain role in the establishment and correction of an evaluation index.

CDV Index: A Validity Index for Better Clustering Quality Measurement

In this paper, a cluster validity index called CDV index is presented. The CDV index is capable of providing a quality measurement for the goodness of a clustering result for a data set. The CDV index is composed of three major factors, including a statistically calculated external diameter factor, a restorer factor to reduce the effect of data dimension, and a number of clusters related punishment factor. With the calculation of the product of the three factors under various number of clusters settings, the best clustering result for some number of clusters setting is able to be found by searching for the minimum value of CDV curve. In the empirical experiments presented in this research, K-Means clustering method is chosen for its simplicity and execution speed. For the presentation of the effectiveness and superiority of the CDV index in the experiments, several traditional cluster validity indexes were implemented as the control group of experiments, including DI, DBI, ADI, and the most effective PBM index in recent years. The data sets of the experiments are also carefully selected to justify the generalization of CDV index, including three real world data sets and three artificial data sets which are the simulation of real world data distribution. These data sets are all tested to present the superior features of CDV index.

Detection and Mapping of Water Quality Variation in the Godavari River Using Water Quality Index, Clustering and GIS Techniques

The objective of this research is to develop a tool for planning and managing the water quality of River Godavari. This is achieved by classifying the pollution levels of Godavari River into several categories using water quality index and a clustering approach that ensure simple but accurate information about the pollution levels and water characteristics at any point in Godavari River in Maharashtra. The derived water quality indices and clusters were then visualized by using a Geographical Information System to draw thematic maps of Godavari River, thus making GIS as a decision support system. The obtained maps may assist the decision makers in managing and controlling pollution in the Godavari River. This also provides an effective overview of those spots in the Godavari River where intensified monitoring activities are required. Consequently, the obtained results make a major contribution to the assessment of the State’s water quality monitoring network. Three significant groups (less polluted, moderately and highly polluted sites) were detected by Cluster Analysis method. The results of Discriminant Analysis revealed that five parameters?i.e.?pH, Dissolved Oxygen (DO), Faecal Coliform (FC), Total Coliform (TC) and Ammonical Nitrogen (NH3-N) were necessary for analysis in spatial variation. Using discriminant function developed in the analysis, 100% of the original sites were correctly classified.

Presentation of a multi-index clustering technique for the mathematical programming of block-cave scheduling

Long-term planning is one of the most important stages that determines the distribution of cash flows over the mine life and the feasibility of the project. However, it is not feasible in block caving to generate a production schedule that will provide optimal operating strategies without considering geotechnical constraints. This paper develops a mixed-integer linear programming(MILP) model to optimize the extraction sequence of drawpoints over multiple time horizons of block-cave mines with respect to the draw control systems. A multi-similarity index clustering technique to solve the MILP model in a reasonable time is also presented. Application and comparison of production scheduling based on the draw control system and clustering technique are illustrated using 325 drawpoints over 15 periods. The results show a significant reduction in the size of the MILP model, and in the time required to solve it.

NEW SHADOWED C-MEANS CLUSTERING WITH FEATURE WEIGHTS

Partition-based clustering with weighted feature is developed in the framework of shadowed sets. The objects in the core and boundary regions, generated by shadowed sets-based clustering, have different impact on the prototype of each cluster. By integrating feature weights, a formula for weight calculation is introduced to the clustering algorithm. The selection of weight exponent is crucial for good result and the weights are updated iteratively with each partition of clusters. The convergence of the weighted algorithms is given, and the feasible cluster validity indices of data mining application are utilized. Experimental results on both synthetic and real-life numerical data with different feature weights demonstrate that the weighted algorithm is better than the other unweighted algorithms.

基于Multi-index LQ与CIC指数的集成评估框架

将多指标区位商计算和工业集群竞争力评价相结合,生成集成的工业集群竞争力评估框架,运用统计数据,可对我国区域工业集群现状及工业集群竞争力水平进行分析。结果表明,区域工业经济存在4种类型,即集聚的竞争优势产业、集聚的竞争劣势产业、非集聚的竞争优势产业和非集聚的竞争劣势产业;据此,我国区域工业经济的支柱产业和主导产业可以被确定。

Cluster乘积图的点PI和Szeged指标

连通图G的点PI和Szeged指标分别定义为PIv(G)=∑e=uv∈E(G)[nu(e G)+nv(e G)]和Sz(G)=∑e=uv∈E(G)nu(e G)nv(e G),其中nu(e G)表示图G中到点u的距离小于到点v的距离的点的个数,nv(e G)表示图G中到点v的距离小于到点u的距离的点的个数.设G{H}和GoH分别表示两个图G和H的cluster乘积和corona乘积.利用因子图的相关拓扑指标分别给出计算G{H}和GoH的点PI和Szeged指标的精确表达式.

The characteristics of clusters of weather and extreme climate events in China during the past 50 years

The pick-up algorithm by the k-th order cluster for the closest distance is used in the fields of weather and climactic events, and the technical terms clustered index and high clustered region are defined to investigate their temporal and spatial distribution characteristics in China during the past 50 years. The results show that the contribution of extreme high-temperature event clusters changed in the period from the 1960s to the 1970s, and its strength was enhanced. On the other hand, the decreasing trend in the clusters of low-temperature extremes can be taken as a signal for warmer winters to follow in the decadal time scale. Torrential rain and heavy rainfall clusters have both been lessened in the past 50 years, and have different cluster characteristics because of their definitions. Regions with high clustered indexes are concentrated in southern China. The spatial evolution of the heavy rainfall clusters reveals that clustered heavy rainfall has played an important role in the rain-belt pattern over China during the last 50 years.

Improved method for the feature extraction of laser scanner using genetic clustering

Feature extraction of range images provided by ranging sensor is a key issue of pattern recognition. To automatically extract the environmental feature sensed by a 2D ranging sensor laser scanner, an improved method based on genetic clustering VGA-clustering is presented. By integrating the spatial neighbouring information of range data into fuzzy clustering algorithm, a weighted fuzzy clustering algorithm （WFCA） instead of standard clustering algorithm is introduced to realize feature extraction of laser scanner. Aimed at the unknown clustering number in advance, several validation index functions are used to estimate the validity of different clustering algorithms and one validation index is selected as the fitness function of genetic algorithm so as to determine the accurate clustering number automatically. At the same time, an improved genetic algorithm IVGA on the basis of VGA is proposed to solve the local optimum of clustering algorithm, which is implemented by increasing the population diversity and improving the genetic operators of elitist rule to enhance the local search capacity and to quicken the convergence speed. By the comparison with other algorithms, the effectiveness of the algorithm introduced is demonstrated.

基于K-means聚类方法和Ⅰ Index聚类有效性检验指标的岩体结构面自动分组及应用

岩体结构面产状数据的统计分组是工程地质、水文地质工作中基础但十分重要的环节。常用的倾向、走向玫瑰花图和极点等密度图人为主观因素大,需借助合适的数学手段对结构面产状数据进行客观划分。基于Kmeans聚类方法和Ⅰ Index聚类有效性检验指标,提出了一种岩体结构面自动分组方法,并开发了岩体结构面自动分组程序RDAP。通过与经典文献进行对比,验证了所提分组方法的可靠性。最后,以某工程为例,使用RDAP对实测涌水裂隙资料进行了预处理,初步计算了灌浆钻孔的最佳方位,为工程涌水的防治提供了依据。

The concept and statistical method of drought resistance index in crops

There is evindence showing that stress susceptibility index(SSI)(1一Yd/Yp)/(1—(?)d/(?)p)used as a measure of drought resistance of crop on the field is an altered form of droughtresistance coefficient(DRC)(Yd/Yp).The correlative coefficient SSI and DRC is r=-1.Therefore,the SSI doesn’t improve the defect of the DRC.After two years experiments per-formed by using thirty winter wheat varieties as trial materials,the concept of drought resistanceindex in crops was put forward.Its expressing equation is:the yield in drylan×drought resis-tance coefficient/average yield in dryland.It makes the drought resistance coefficient(physicalindex)correlate well with the yield in dryland(agronomy index)and is suitable for breeder.

CLASSIFYING WESTERN NORTH PACIFIC TROPICAL CYCLONES BY PHYSICAL INDEX SYSTEM

The classification of tropical cyclones(TCs) is significant to obtaining their temporal and spatial variation characteristics in the context of dramatic-changing global climate. A new TCs clustering method by using K-means clustering algorithm with nine physical indexes is proposed in the paper. Each TC is quantified into an 11-dimensional vector concerning trajectory attributes, time attributes and power attributes. Two recurving clusters(cluster A and E)and three straight-moving clusters(cluster B, C and D) are categorized from the TC best-track dataset of the western North Pacific(WNP) over the period of 1949-2013, and TCs' properties have been analyzed and compared in different aspects. The calculation results of coefficient variation(CV) and Nash-Sutcliffe efficiency(NSE) reveal a high level of intra-cluster cohesiveness and inter-cluster divergence, which means that the physical index system could serve as a feasible method of TCs classification. The clusters are then analyzed in terms of trajectory, lifespan, seasonality, trend,intensity and Power Dissipation Index(PDI). The five classified clusters show distinct features in TCs' temporal and spatial development discipline. Moreover, each cluster has its individual motion pattern, variation trend, influence region and impact degree.

基于大数据聚类的通信网络安全态势预测技术

传统通信网络安全态势预测技术缺乏大数据支撑,难以对发生的攻击进行详细分类和追踪,导致在进行长时间的态势预测中收敛过慢,准确度降低.提出一种基于大数据聚类的通信网络安全态势预测技术.分析通信网络的属性以及特点,选择安全态势描述一级指标,将数据标准化处理之后,细分出二级指标;优化大数据聚类算法,计算最优聚类数量、确定聚类中心,建立关联规则库并优化预测流程,完成基于大数据聚类的通信网络安全态势预测技术的设计.通过实验结果表明,与两种传统的安全态势预测技术相比,设计的技术收敛速度更快,全体数据点没有出现残差扩散的现象,并且数据完整度较高.

“油-稻-稻”三熟制早熟冬油菜氮高效基因型及鉴定指标筛选

【目的】旨在筛选适宜“油-稻-稻”三熟制的氮高效早熟冬油菜基因型及其简易筛选指标。【方法】利用田间小区试验,选用了生育期185 d以下的的适宜“油-稻-稻”三熟制种植的14种早熟冬油菜基因型,进行正常施氮(N_(1))和不施氮(N_(0))处理。根据不同冬油菜基因型氮肥利用率(NUE)的差异,利用树状聚类分析进行分类,形成高、中、低3种氮效率基因型。同时通过逆向溯源的方法,观察分析3种氮效率基因型在不同氮水平条件下的产量构成、主要农艺性状、干物质积累及氮素吸收等方面的表现特征。总结分析出氮高效冬油菜基因型的一些简易判断的指标。【结果】不同氮效率基因型冬油菜在产量形成、主要农艺性状等方面存在显著差异。N1处理下成熟期早熟冬油菜的主要农艺性状的表型值和变异系数基本表现大于N0处理。因此,以N1处理下不同基因型的农艺性状表现作为不同氮效率基因型的鉴别标准。N1处理下,氮高效基因型比氮中效和氮低效基因型产量高、单株角果数多、每角粒数多、株高高、主花序长、一级分枝数多、角果密度高、各部位干物质积累量高、籽粒中氮含量高、氮肥偏生产力、氮肥农学效率、氮肥生理利用率和氮收获指数均较高。【结论】沣油737是适合南方“油-稻-稻”三熟制的氮高效早熟冬油菜;正常施氮条件下,成熟期较多的单株角果数与每角粒数,以及较高株高是判断早熟冬油菜氮高效基因型的简易指标。

Classification of Hourly Clearness Index of Solar Radiation in the District of Yamoussoukro

The exploitation of systems using solar energy as a source of energy is not fluctuations free because of short passage of clouds on solar radiation. The amplitude, the persistence and the frequency of these fluctuations should be analyzed with appropriate tools, instead of focusing on their location over time. The analysis of these fluctuations should use the instantaneous clearness index whose distribution is given as a first approximation which is independent not only of the season but also of the site. It is important to evaluate the potential solar energy in a region. Indeed such evaluation helps the decision-makers in their reflections on agricultural or photovoltaic solar projects. Then this study was conducted for a predictive purpose. The method used in our work combines the classification method which is the hierarchical ascending classification and two partitioning methods, the principal component?analysis and the K-means method. The partitioning method enabled to?achieve a number of well-known situations (in advance) that are representative of the day. The study was based on the data of a climatic weather station in the district of Yamoussoukro located in the center region of Côte d’Ivoire during the 2017 year. Using the clearness index, the study allowed the classification of the solar radiation in the region. Thus, it showed that only 346 days of the 365 days in 2017 were classified (95%). We identified three clusters of days, the cloudy sky (29%), the partly cloudy sky?(32%) and the clear sky (39%). The statistical tests used for the characterization?of these clusters will be detailed in a future study.

Clusterization of Surface Water Quality and Its Relation to Climate and Land Use/Cover

The quality of surface water is rapidly changing due to climatic variations, natural processes, and anthropogenic activities. The objectives of this study were to classify and analyze the surface water quality of 12 major rivers of Alberta on the basis of 17 parameters during the period of five years (i.e., 2004-2008) using principal component analysis (PCA), total exceedance model and clustering technique. Seven major principal components (PCs) with variability of about 89% were identified. These PCs were the indicators of watershed geology, mineralization and anthropogenic activities related to land use/cover. The seven dominant parameters revealed from the seven PCs were total dissolved solids (TDS), true color (TC), pH, iron (Fe), fecal coliform (FC), dissolved oxygen (DO), and turbidity (TUR). The normalized data of dominant parameters were used to develop a model for obtaining total exceedance. The exceedance values acquired from the total exceedance model were used to determine the patterns for the development of five clusters. The performance of the clusters was compared with the classes obtained in Canadian Water Quality Index (CWQI). Cluster 1, cluster 2, cluster 3, cluster 4 and cluster 5 showed agreements of 85.71%, 83.54%, 90.22%, 80.74%, and 83.40% with their respective CWQI classes on the basis of the data for all rivers during 2004-2008. The water quality was deteriorated in growing season due to snow melting. This methodology could be applied to classify the raw surface water quality, analyze the spatio-temporal trends and study the impacts of the factors affecting the water quality anywhere in the world.

贝塞尔涡旋光束经水下气泡幕传输衰减特性研究

利用涡旋光束与水下气泡的相互作用,可以实现对水下航行体的快速、准确探测和跟踪,基于贝塞尔涡旋光束经过球形粒子散射Mie理论,并通过等效折射率的方法,研究了贝塞尔涡旋光束与微小气泡的相互作用规律。在考虑洁净水的吸收、散射作用以及水下气泡散射作用的基础上,分析了不同光源参数下贝塞尔涡旋光束在水下气泡环境中的传输功率衰减。