Interactive discovery of sequential patterns in time series of wind data

Wind speed and direction vary over space and time due to the interactions between different pressures and temperature gradients within the atmospheric layers. Near the earth’s surface, these interactions are modulated by topography and artificial structures. Hence, characterizing wind behaviour over large areas and long periods is a complex but essential task for various energy-related applications. In this study, we present a novel approach to discover wind patterns by integrating sequential pattern mining and interactive visualization techniques. The approach relies on the use of the Linear time Closed pattern Miner sequence algorithm in conjunction with a time sliding window that allows the discovery of all sequential patterns present in the data. These patterns are then visualized using integrated 2D and 3D coordinated multiple views and visually explored to gain insight into the characteristics of the wind from a spatial, temporal and attribute (type of wind pattern) point of view. This proposed approach is used to analyse 10 years of hourly wind speed and direction data for 29 weather stations in the Netherlands. The results show that there are 15 main sequential patterns in the data. The spatial task shows that weather stations located in the same region do not necessarily experience similar wind pattern. For within the selected time interval, similar wind patterns can be observed in different stations and in the same station at different times of occurrence. The attribute task discovered that the repetitive occurrences of chosen pattern indicate as regular wind behaviour at different weather stations that persisted continuously over time. The results of these tasks show that the proposed interactive discovery facilitates the understanding of wind dynamics in space and time.     

陕西凤太矿集区多金属成矿作用的构造控制

陕西凤县-太白(简称凤太)矿集区铅、锌、金、银、铜多金属资源丰富,已发现二十余个大中小型矿床。在大地构造位置上,凤太矿集区位于南秦岭造山带北缘,紧邻商丹缝合带。以往的工作缺乏对矿集区整体的构造研究,本次工作通过比较系统的构造测量和解析,提出在南秦岭晚三叠世碰撞造山过程中,凤太矿集区南北两条边界断裂带的左行走滑运动导致在区内衍生了NNE向主压应力场,从而形成了NWW向复式褶皱、脆韧性剪切带、断裂和节理(纵向破裂)、B型线理,以及NNE向断裂和节理(横向破裂)、劈理、张裂隙等一系列构造组合,所有构造形迹都是在统一构造应力场下随着构造层次不断抬升,脆韧性和脆性递进变形叠加的产物,共同构成了一个大型压扭性走滑双重构造变形系统。在构造几何学上,凤太矿集区整体上表现为一个隔档式复式褶皱,由一组NWW向紧闭复背斜和一组相对宽缓复向斜组成。区内的多金属成矿作用、岩浆活动、动力变质变形作用的同位素年龄数据集中于230~190Ma。综合地质演化和成矿作用的研究成果,提出在南秦岭碰撞造山过程中引发的动力变质变形作用和岩浆活动提供了成矿元素和成矿流体,在温压梯度以及浮力效应的驱动下向上运移至走滑双重构造变形系统中的有利扩容空间中发生充填型和交代型矿化,即凤太矿集区多金属矿床是区域大规模变形变质-岩浆活动-流体作用的产物,是在构造作用这一主导因素控制下形成的一个多金属后生热液成矿系统。     

Evaluation of effectiveness of three fuzzy systems and three texture extraction methods for building damage detection from post-event LiDAR data

Building damage maps after disasters can help us to better manage the rescue operations. Researchers have used Light Detection and Ranging (LiDAR) data for extracting the building damage maps. For producing building damage maps from LiDAR data in a rapid manner, it is necessary to understand the effectiveness of features and classifiers. However, there is no comprehensive study on the performance of features and classifiers in identifying damaged areas. In this study, the effectiveness of three texture extraction methods and three fuzzy systems for producing the building damage maps was investigated. In the proposed method, at first, a pre-processing stage was utilized to apply essential processes on post-event LiDAR data. Second, textural features were extracted from the pre-processed LiDAR data. Third, fuzzy inference systems were generated to make a relation between the extracted textural features of buildings and their damage extents. The proposed method was tested across three areas over the 2010 Haiti earthquake. Three building damage maps with overall accuracies of 75.0%, 78.1% and 61.4% were achieved. Based on outcomes, the fuzzy inference systems were stronger than random forest, bagging, boosting and support vector machine classifiers for detecting damaged buildings.     

金沙江白格滑坡残留体稳定性分析与防治对策

金沙江白格滑坡在经历了2018年10月和11月的2次滑动堵江后,在其后缘仍存在K1、K2和K3等3处规模较大的残留崩滑体,并有再次失稳堵江的可能。目前关于残留体稳定性的研究还存在较大争议,多从影响因素及成因机制等方面进行定性分析,其结果依赖于评价者的经验,差异较大。在野外调查的基础上,针对白格滑坡所在区工程地质条件及其残留体变形特征,选取坡高、坡度、坡面形态、临空面、地下水出露、裂缝发育和变形等7个因素作为评价因子,基于模糊综合评判模型,运用层次分析法对白格滑坡残留体进行分区稳定性评价,并提出相应的防治对策。评价结果表明:K1与K2残留体稳定性较差;K3残留体基本稳定,与实际调查状况较吻合。研究结果可为同类型滑坡的评价与防治提供参考。     

渤海湾盆地庙西中南洼围区原油成因类型及分布主控因素

通过原油生物标志化合物参数聚类分析,在对比沙河街组不同层系烃源岩地化特征的基础上,分析了渤海海域庙西中南洼已发现原油的成因类型、来源及其分布规律。结果表明,研究区目前已发现的原油主要有Ⅰ型、Ⅱ型和Ⅲ型3种成因类型,其中：Ⅰ型原油来源于沙三段烃源岩,主要分布在垦利6-4区和蓬莱25区,其进一步可分为Ⅰ₁和Ⅰ₂两个亚类,分别对应中高熟沙三型原油和中低熟沙三型原油;Ⅱ型原油来源于沙三段和沙四段烃源岩,主要分布在蓬莱31区;Ⅲ型原油主要来源于沙四段烃源岩,可能有少量的沙三段烃源岩贡献,主要分布在渤中36区。原油地化特征及分布规律指示研究区为近源成藏特征。综合烃源岩分布特征及断层活动性分析认为蓬莱25区和垦利6-4区原油类型主要受烃源岩控制,而蓬莱31区和渤中36区原油类型和分布受断裂和烃源岩联合控制。     

Landslide susceptibility zonation method based on C5.0 decision tree and K-means cluster algorithms to improve the efficiency of risk management

Machine learning algorithms are an important measure with which to perform landslide susceptibility assessments,but most studies use GIS-based classification methods to conduct susceptibility zonation.This study presents a machine learning approach based on the C5.0 decision tree(DT)model and the K-means cluster algorithm to produce a regional landslide susceptibility map.Yanchang County,a typical landslide-prone area located in northwestern China,was taken as the area of interest to introduce the proposed application procedure.A landslide inventory containing 82 landslides was prepared and subse-quently randomly partitioned into two subsets:training data(70％landslide pixels)and validation data(30％landslide pixels).Fourteen landslide influencing factors were considered in the input dataset and were used to calculate the landslide occurrence probability based on the C5.0 decision tree model.Susceptibility zonation was implemented according to the cut-off values calculated by the K-means clus-ter algorithm.The validation results of the model performance analysis showed that the AUC(area under the receiver operating characteristic(ROC)curve)of the proposed model was the highest,reaching 0.88,compared with traditional models(support vector machine(SVM)=0.85,Bayesian network(BN)=0.81,frequency ratio(FR)=0.75,weight of evidence(WOE)=0.76).The landslide frequency ratio and fre-quency density of the high susceptibility zones were 6.76/km2 and 0.88/km2,respectively,which were much higher than those of the low susceptibility zones.The top 20％interval of landslide occurrence probability contained 89％of the historical landslides but only accounted for 10.3％of the total area.Our results indicate that the distribution of high susceptibility zones was more focused without contain-ing more"stable"pixels.Therefore,the obtained susceptibility map is suitable for application to landslide risk management practices.     

基于模糊熵的GLLE熵阈值分割方法

图像分割是计算机视觉中基础且重要的一个问题.熵阈值图像分割作为一种有效的分割方法,被广泛应用于模式识别和图像处理中.传统的图像分割方法并不能获得足够有效的图像特征.为解决这个问题且进一步探究熵阈值在图像分割中的应用,引入一种GLLE（Gray Level and Local Entropy）二维直方图改进熵阈值图像分割模型,并提出了基于模糊熵的方法计算所建立的二维直方图模型.通过标准实验数据集上的对比实验表明,基于模糊熵的GLLE熵阈值分割方法可以得到更加准确的阈值,提高了分割精度.同时在处理不同类型图像的表现上优于往常的算法,具有更强的鲁棒性.     

THE THEORY OF RESPONSE ANALYSIS OF FUZZY STOCHASTIC DYNAMICAL SYSTEMS WITH A SINGLE DEGREE OF FREEDOM

Most real-life structural/mechanical systems have complex geometrical and material properties and operate under complex fuzzy environmental conditions. These systems are certainly subjected to fuzzy random excitations induced by the environment. For an analytical treatment of such a system subjected to fuzzy random excitations, it becomes necessary to establish the general theory of dynamic response of a system to fuzzy random excitations. In this paper, the theory of response, fuzzy mean response and fuzzy covariance response of a single-degree-of-freedom (sdf) system to fuzzy random excitations in the time domain and frequency domain is put forward. The theory of response analysis of an sdf system to both stationary and non-stationary fuzzy random excitations in the time domain and frequency domain is established. Two examples are considered in order to demonstrate the rationality and validity of the theory, and the models of stationary filtered white noise and non-stationary filtered white noise fuzzy stochastic processes of the earthquake ground motion are set up. Methods of analysis for fuzzy random seismic response of sdf systems are put forward using the principles of response analysis of an sdf fuzzy random dynamic system.     

全球-地方联结与产业集群的技术学习--以河南许昌发制品产业为例

以产业区理论、管制理论和全球生产网络理论为基础,以学习创新为核心,构建了一个融生产体系与社会生产体制、制度与协调机制、地方生产网络、全球生产网络“四位一体”的学习型产业区分析框架;运用该框架,以河南许昌发制品产业集群为案例,研究了全球-地方网络联结的方式、动态及其对技术学习的影响。研究发现,通过全球与地方生产网络的建构和有机联结,传统产业集群的技术学习是可以从“低端道路”迈向“高端道路”的,发展学习型产业区应作为我国经济发展与技术创新的一项重大战略和政策。     

A new load balancing scheme on heterogeneous database cluster

IntroductionAlthoughthe development of cluster has gainedmore and more advantages of low-cost ,high-per-formance and high-availability computing, effi-cient resource usage such as CPU, memory andI/Ois still a keyto achieve better performanceincluster syst…