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.     

试论新世纪地理信息科学的发展

本文重点分析了当前国内外地理信息科学的形成与发展趋势和地理信息科学不断发展的历程 ,提出近期发展的前沿 ,以及当前地理信息产业化面临的一些重要问题。最后提出对地理信息科学发展的意见。     

广西海洋资源概况及开发刍议

广西海洋资源丰富 ,品种繁多 ,为了更好开发 ,建议从法制、宣传教育、普及海洋资源有关知识 ,提高人们整体素质做起 ,进一步抓住机遇 ,合理开发 ,才能取得良好效益 ,达到预定目标     

双酶法制备低黏度辛烯基琥珀酸淀粉钠的工艺条件

对双酶法制备用作微胶囊壁材的低黏度辛烯基琥珀酸淀粉钠的工艺路线与工艺条件进行了研究。正交实验结果表明 ,在酯化淀粉乳质量浓度 2 0 %、每 g淀粉α 淀粉酶的用量为 6SKBU的条件下 ,影响产品性能的各因素中 ,糖化酶的用量对产品的DE值和流度的影响最大 ,各因素的重要性依次是 :糖化酶的用量、糖化酶作用时间、α 淀粉酶保温作用时间。最佳工艺条件是 :α 淀粉酶保温作用时间 4min ,每 g淀粉糖化酶用量 0 .2GAU ,糖化酶作用时间 2 .5h ,此时产品的DE值为 30 ,流度为 80左右     

小波分析理论在GPS技术中的应用

在GPS数据处理中 ,存在着误差影响、影响波的干扰、周跳和数据量大等问题。误差影响和影响波的干扰实质是在接收卫星信号时受到其它因素的影响 ;周跳是由于卫星信号的失锁而造成信号的不连续 ;数据量大是因为GPS观测需要采样间隔小又连续观测所致。由于小波理论具有时频分析、波形分解、特征提取和快速小波变换等特性 ,应用小波变换和波形分解可以解决误差影响和影响波的干扰的问题 ;应用特征提取可以解决周跳检测问题 ;应用快速小波变换可进行数据压缩     

试论企业组织结构--电子商务企业与传统企业的比较

网络时代的到来，对传统企业的组织结构、运作模式、管理方法均提出了严峻的挑战。传统的企业组织结构是适应大工业生产而形成的等级组织结构形式，它有很大的局限性；电子商务企业的组织结构是适应网络社会而形成扁平化、双向多对多、以信息为基础的新型组织结构形式。电子商务企业以其组织结构扁平化和中空化，决策分散化，运作虚拟化，灵活高效为特点，它将成为传统企业在电子商务发展阶段变革的方向和目标。     

差分法周跳探测与修复方法改进

在目前常用的周跳探测与修复方法基础上 ,提出了首先将观测资料按照观测历元不连续分成若干小弧段 ,然后利用差分法进行周跳探测 ,根据差分后周跳放大的特性判断周跳和野值 ,并确定其位置利用宽带组合和电离层组合的方法解算周跳大小。通过实例验证了其有效性。     

Quantifying hydrogen‐deuterium exchange of meteoritic dicarboxylic acids during aqueous extraction

Abstract— Hydrogen isotope ratios of organic compounds in carbonaceous chondrites provide critical information about their origins and evolutionary history. However, because many of these compounds are obtained by aqueous extraction, the degree of hydrogen‐deuterium (H/D) exchange that occurs during the process needs to be quantitatively evaluated. This study uses compound‐specific hydrogen isotopic analysis to quantify the H/D exchange during aqueous extraction. Three common meteoritic dicarboxylic acids (succinic, glutaric, and 2‐methyl glutaric acids) were refluxed under conditions simulating the extraction process. Changes in δD values of the dicarboxylic acids were measured following the reflux experiments. A pseudo‐first order rate law was used to model the H/D exchange rates which were then used to calculate the isotope exchange resulting from aqueous extraction. The degree of H/D exchange varies as a result of differences in molecular structure, the alkalinity of the extraction solution and presence/absence of meteorite powder. However, our model indicates that succinic, glutaric, and 2‐methyl glutaric acids with a δD of 1800%***_o would experience isotope changes of 38_o, 10_o, and 6_o, respectively during the extraction process. Therefore, the overall change in δD values of the dicarboxylic acids during the aqueous extraction process is negligible. We also demonstrate that H/D exchange occurs on the chiral α‐carbon in 2‐methyl glutaric acid. The results suggest that the racemic mixture of 2‐methyl glutaric acid in the Tagish Lake meteorite could result from post‐synthesis aqueous alteration. The approach employed in this study can also be used to quantify H/D exchange for other important meteoritic compounds such as amino acids.     

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