A machine learning approach for predicting computational intensity and domain decomposition in parallel geoprocessing

ABSTRACT

High performance computing is required for fast geoprocessing of geospatial big data. Using spatial domains to represent computational intensity (CIT) and domain decomposition for parallelism are prominent strategies when designing parallel geoprocessing applications. Traditional domain decomposition is limited in evaluating the computational intensity, which often results in load imbalance and poor parallel performance. From the data science perspective, machine learning from Artificial Intelligence (AI) shows promise for better CIT evaluation. This paper proposes a machine learning approach for predicting computational intensity, followed by an optimized domain decomposition, which divides the spatial domain into balanced subdivisions based on the predicted CIT to achieve better parallel performance. The approach provides a reference framework on how various machine learning methods including feature selection and model training can be used in predicting computational intensity and optimizing parallel geoprocessing against different cases. Some comparative experiments between the approach and traditional methods were performed using the two cases, DEM generation from point clouds and spatial intersection on vector data. The results not only demonstrate the advantage of the approach, but also provide hints on how traditional GIS computation can be improved by the AI machine learning.     

ECOLOGICAL SERIES OF SOIL ANIMALS IN DARLIDAI MOUNTAIN

The ecological series of soil animals under the broad-leaved and pine mixed forest in Darlidai Mountainwas studied. Seven sample plots were selected according to different altitude gradients, which belong to different vegeta-tion types. By investigating and analyzing soil animals in every sample plot it is found that there are 45 groups and 1956individuals, which axe involved in 3 phylums, 7 classes, 16 orders, respectively. The altitude is a key factor which af-fects ecological series of soil animals. Both the groups and individuals of soil animals increase with altitude increasingunder certain conditions, which contrastes with ordinary cases, resulting from special micro-climate in studied area. Thegroups and individuls of soil animals are the most under the broad-leaved and pine forest on the top of the mountain, andthe least under Picea-Abies forest in the foot of the mountain.     

Wavelet Analysis of Space Solar Telescope Images

The scientific satellite SST (Space Solar Telescope) is an important research project strongly supported by the Chinese Academy of Sciences. Every day, SST acquires 50 GB of data (after processing) but only 10GB can be transmitted to the ground because of limited time of satellite passage and limited channel volume. Therefore, the data must be compressed before transmission. Wavelets analysis is a new technique developed over the last 10 years, with great potential of application. We start with a brief introduction to the essential principles of wavelet analysis, and then describe the main idea of embedded zerotree wavelet coding, used for compressing the SST images. The results show that this coding is adequate for the job.     

单片机控制的电子显示屏

本文介绍了由８０３１单片机控制的ＬＥＤ发光二极管阵列构成的电子显示屏显示原理、显示屏数据锁存、驱动接口电路、键盘接口电路、字模存放电路及软件框图。     

广西老厂铅锌矿床地质特征及其成因探讨

本文是在专题研究基础上,探讨广西老厂铅锌矿床地质特征和矿床成因。该矿床位于海洋山复式背斜南段的老厂穹窿构造核部,铅锌矿化受构造、地层和岩性控制。矿体呈脉状,产于NE向组张扭性断裂构造中;围岩为寒武系白云岩,板岩、砂岩;矿石类型以锌为主,矿物成分简单,以闪锌矿、方铅矿与石英、白云石为主,具充填、交代矿石结构、构造,矿石平均品位含Zn9.94%、Pb1.50%;围岩蚀变主要为硅化、绢云母化和碳酸盐化。据地层岩石元素丰度值、稀土元素配分和稳定同位素数据、资料,探讨了成矿物质来源于围岩,热液主要来自大气降水。因此,认为本矿床实属产于寒武系轻变质岩中的层控矿型大气降水热液铅锌矿床。     

APPLICATION OF ANALYTIC HIERARCHY PROCESS TO ASSESSING THE ECOLOGICAL VULNERABILITY OF WETLANDS IN THE JIANGHAN PLAIN

Wetlands in the Jianghan Plain are important components of wetland types in lake area in the middle and lower reaches the Changjiang (Yangtze) River and they fulfill many uses and functions related to hydrology,waste assimilation, ecosystem productivity and biodiversity. Owing to natural factors and human activities, especially excessive reclamation from lakes, the shrinking process of the lakes has been accelerated. Wetland ecosystem has shown the characteristics of vulnerability. According to the analysis of wetland ecological function in the Jianghan Plain, this paper presented an index system related to productivity, stability and environmental capacity. By using the method of Analytic Hierarchy Process, we computed the values of the relative weights of the indexes, and evaluated the vulnerability level of the wetland ecosystem by the method of multi-indexes. The case study showed that the fragile extent of wetland ecosystem in the Jianghan Plain is 5.6. This means that the wetland ecosystem in the Jiang-han Plain is laid to the state of middle vulnerability. Therefore, the wetland conservation and eco-rehabilitation in the JiangJaan Plain should be paid attention to.     

富氏谱分析法模拟地壳垂直运动的地学依据及其策应力模型

应用地壳波浪与镶嵌构造学说对富氏谱分析法提取地壳垂直形变信息的科学性做了地质学意义上的阐释 ,并提出了根据多期形变资料提取特定波段上构造策应力的数学模型     

Optical Flash of GRB 990123: Constraints on the Physical Parameters of the Reverse Shock

The optical flash accompanying GRB 990123 is believed to be powered by the reverse shock of a thin shell. With the best-fit physical parameters for GRB 990123 and the assumption that the parameters in the optical flash are the same as in the afterglow, we show that: 1) the shell is thick rather than thin, and we have provided the light curve for the thick shell case which coincides with the observation; 2) the theoretical peak flux of the optical flash accounts for only 3×10~-4 of the observed. In order to remove this discrepancy, the physical parameters, the electron energy and magnetic ratios, εe and εB, should be 0.61 and 0.39, which are very different from their values for the late afterglow.     

Silicon limitation on primary production and its destiny in Jiaozhou Bay, China——Ⅳ：Study on cross-bay transect from estuary to ocean

The authors analyzed the data collected in the Ecological Station Jiaozhou Bay from May 1991 to November 1994, including 12 seasonal investigations, to determine the characteristics, dynamic cycles and variation trends of the silicate in the bay. The results indicated that the rivers around Jiaozhou Bay provided abundant supply of silicate to the bay. The silicate concentration there depended on river flow variation. The horizontal variation of silicate concentration on the transect showed that the silicate concentration decreased with distance from shorelines. The vertical variation of it showed that silicate sank and deposited on the sea bottom by phytoplankton uptake and death, and zooplankton excretion. In this way, silicon would endlessly be transferred from terrestrial sources to the sea bottom. The silicon took up by phytoplankton and by other biogeochemical processes led to insufficient silicon supply for phytoplankton growth. In this paper, a 2D dynamic model of river flow versus silicate concentration was established by which silicate concentrations of 0.028–0.062 μmol/L in seawater was yielded by inputting certain seasonal unit river flows (m³/s), or in other words, the silicate supply rate; and when the unit river flow was set to zero, meaning no river input, the silicate concentrations were between 0.05–0.69 μmol/L in the bay. In terms of the silicate supply rate, Jiaozhou Bay was divided into three parts. The division shows a given river flow could generate several different silicon levels in corresponding regions, so as to the silicon-limitation levels to the phytoplankton in these regions. Another dynamic model of river flow versus primary production was set up by which the phytoplankton primary production of 5.21–15.55 (mgC/m²·d)/(m³/s) were obtained in our case at unit river flow values via silicate concentration or primary production conversion rate. Similarly, the values of primary production of 121.98–195.33 (mgC/m²·d) were achieved at zero unit river flow condition. A primary production conversion rate reflects the sensitivity to silicon depletion so as to different phytoplankton primary production and silicon requirements by different phytoplankton assemblages in different marine areas. In addition, the authors differentiated two equations (Eqs. 1 and 2) in the models to obtain the river flow variation that determines the silicate concentration variation, and in turn, the variation of primary production. These results proved further that nutrient silicon is a limiting factor for phytoplankton growth. This study was funded by NSFC (No. 40036010), and the Director's Fund of the Beihai Sea Monitoring Center, the State Oceanic Administration.     

复杂模型重力位场快速正反演方法及应用

提要 本文详细讨论了一种三维重力位场快速正反演方法。作者在前人工作的基础上,对算法作了行之有效的改进,通过对反演中的不稳定因素进行各种理论模型试算,得出保证迭代反演稳定收敛的准则,编制出可在微型机IBM—PC上运行的人机对话式自动正反演程序。本文还对各种不均质模型进行了模似计算并将该方法应用于某含油气沉积盆地的双层界面构造研究,揭示出了储油有利地段。