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.     

An approximate method for evaluating the shear band thickness in saturated soils

A formula for the thickness of a shear band formed in saturated soils under a simple shear or a combined stress state has been proposed. It is shown that the shear band thickness is dependent on the pore pressure properties of the material and the dilatancy rate, but is independent of the details of the combined stress state. This is in accordance with some separate experimental observations. Copyright © 2004 John Wiley & Sons, Ltd.     

一种基于自证明公钥的可公开验证的认证加密方案

针对现有的基于证书的认证加密方案通信量和计算量大的缺点,提出了基于自证明公钥的可公开验证的认证加密方案。详细阐述了方案的系统初始化、签名生成、消息恢复验证以及公开验证4个阶段,方案的安全性是基于求解离散对数的困难性(DLP)和强单向hash函数(OWFH)的不可逆。该方案在没有签名者的协作下,任何验证者都可验证签名者的诚实性,在验证签名的同时可认证签名者的公钥,因而减少了存储空间、通信量和计算量。     

基于蚁群算法的城市可持续发展综合评价

在可持续发展体系分类的基础上，应用蚁群算法对可持续发展各分类指数公式和综合指数公式进行优化，建立可持续发展评价模型。将该模型应用于乌鲁木齐市可持续发展水平评价，评价结果与现状分析一敛。结果表明该模型简单适用、有良好的通用性。     

地倾斜台站数字化、模拟观测数据频率特性研究

分析了四川、云南的部分地倾斜数字化观测与模拟观测资料的特性，从频率范围，周期10天以上的FFT谱特性，固体潮波振幅，相位特征值等方面，论述了地倾斜数字化资料较模拟记录资料的信息组成变化，并对资料的分析与应用进行了初步探讨。     

Neutrino mass,luminosity variation,and spectrum of SN1987A

In this paper, the neutrino mass has been determined from SN1987a observation in a manner that the simultaneity of neutrino emission is not regarded as the starting point, but is itself defined through the analysis by Monte-Carlo simulation. The result is that the neutrino mass lies in 3–4 eV, possiblym _v 3.6 eV. Neutrino luminosity variation and neutrino spectrum are also obtained. Comparison with theories gives further support to the mass determination, and also predicts the mass of progenitor star of SN1987a to be in the range of 12–25M .The project supported by the National Natural Science Foundation of China.     

A model of the galactic centre with magnetic monopoles

A model of the galactic centre with magnetic monopole has been presented here. The positron can be produced continuously through magnetic monopoles to induce baryon decay (Rubakov catalytic reaction) and a lot of energy can be released as well. The calculation results show that even if the galactic center contains only a few magnetic monopoles (=N _M/N_B10^–24), this massive object can not collapse into a black hole. This model can explain the observed intensities of the annihilation line and higher energy photons ofE >511 keV from the galactic centre.Paper presented at the IAU Third Asian-Pacific Regional Meeting, held in Kyoto, Japan, between 30 September–6 October, 1984.     

Possible chemical structures and biological precursors of different vitrinites in coal measure in Northwest China

Chemical structure of Jurassic vitrinites isolated from the coals in basins in NW China have been checked using solid state ¹³C NMR and flash pyrolysis-GC/MS. Study shows some Jurassic collodetrinites are rich in aliphatic products in pyrolysates, consisting with the high amount of methylene carbon in ¹³C NMR spectra. In contrast, pyrolysates of Jurassic collotelinites are rich in phenols and alkylbenzenes. Also one Pennsylvanian and one Permian vitrinite selected from the Ordos basin, NW China have been checked for comparison. The proportion of aliphatics is low in pyrolysates, and aliphatic carbon peak in ¹³C NMR spectrum of Permian vitrinite is mostly composed of gas-prone carbons compared with collodetrinites in those Jurassic basins. But both pyrolysis and ¹³C NMR data shows the Pennsylvanian vitrinite is not only gas-prone but also oil-prone. Relatively high proportion of long chain aliphatic structure of some Jurassic vitrinite in Junggar, Turpan-Hami basins may be due to the contribution of liptodetrinites, which may be included during the formation of vitrinites. And it seems that suberinite is the most possible precursor of long chain aliphatics in the structure of Jurassic collodetrinite.     

东秦岭二郎坪群中火山成因块状硫化物矿床地质地球化学特征及其成因讨论

二郎坪群是东秦岭造山带重要的组成部分,其火山建造中广泛发育有火山成因块状硫化物(VMS)矿床.文章总结并分析了南阳盆地东、西两侧二郎坪群中3个典型矿床(刘山岩、水洞岭和上庄坪)的研究资料,把二郎坪群VMS矿床分为3类:Zn-Cu型矿床(刘山岩矿床);Zn-Cu型与Zn-Pb-Cu型矿床(水洞岭矿床);Zn-Pb-Cu型矿床(上庄坪矿床).从刘山岩矿床到水洞岭矿床,再到上庄坪矿床,铜的含量减少,铅的含量增多.二郎坪群VMS矿床矿石富集LREE、Ce负异常及Eu正异常,说明矿床为热液成因.石英和重晶石中流体包裹体的氢氧同位素特征表明,成矿流体主要来自建造水,南阳盆地以西,矿床成矿流体中伴有较多古大气降水.矿石的硫同位素特征说明,二郎坪群VMS矿床中的硫可能为地幔岩浆硫和海水硫的混合硫.围岩与矿石的铅同位素组成基本一致,说明矿石和围岩可能来源于相似的物源区,成矿元素主要来源于地幔或下地壳深源物质,而水洞岭矿床明显有上地壳浅源物质的混染.研究表明,南阳盆地以西的水洞岭和上庄坪矿床可能形成于大陆边缘海环境,盆地规模较小,受陆源物质影响较大;而南阳盆地以东的刘山岩矿床可能形成于远洋盆地,盆地到达成熟阶段.用地震泵模式可解释二郎坪群VMS矿床的成因机制.     

Identification of sources and causes of leakage on a zoned earth dam in northern Taiwan: Hydrological and isotopic evidence

Seepage through an earth dam body must be regulated as a well–planned process, if it is not properly managed, the abnormal seepage may cause dam failure. This study employed stable isotopic and statistical methods to identify the source and cause of an abnormal leakage on the zoned earth dam of the Xin–Shan reservoir located in northern Taiwan. Water samples from the dam area over a 2-a period were collected and analyzed for their stable O and H isotope compositions. In addition, a 4-a period of hydrological data, including rainfall, reservoir level, well level, seepage of filter drainage and leakage, were statistically analyzed with a stepwise multiple regression approach. Both the stable isotopic and hydrological results indicate that the abnormal leakage on the dam shell comes from the filter drainage in the dam. The reason for abnormal leakage is due to unexpected and significant precipitation–sourced water flowing into the dam’s body. The dam filter fails to drain out the incoming water sufficiently, thus generating the abnormal seepage. In addition, the defect in the dam filter may also cause the drainage filter to drain off reservoir seepage inadequately. Therefore, it is suggested that checking the filter function and preventing excessive precipitation–sourced water from flowing into the dam are the two top priorities for the follow-up remedial strategy of the dam.