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.     

5个新发现的X选BL Lac天体

利用ＲＯＳＡＴＶＬＡ方法筛选，从ＲＯＳＡＴＸ射线源中选出了一批新的ＢＬＬａｃ天体和类星体的候选体．１９９６年１２月８日至１７日，利用北京天文台２．１６ｍ望远镜和新从美国引进的ＯＭＲ摄谱仪，对这批新候选体进行了光谱认证．经ＳＵＮ工作站处理，又发现了５个新的Ｘ选ＢＬＬａｃ天体．此外，还对去年作者在ＯＭＲ引进之前发现的ＢＬＬａｃ天体进行了检验，结果发现，去年发现的７个ＢＬＬａｃ天体中，２３２２＋３４３的ＣａＩＩＨ＆Ｋ“Ｂｒｅａｋｓｔｒｅｎｇｔｈ”为２６．９％，稍大于判据２５％，因此，２３２２＋３４３到底是ＢＬＬａｃ天体还是射电星系还有待于进一步测光及偏振观测的验证．     

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.     

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.     

利用MC-ICPMS对水样中硼同位素比值的测定

采用Amberlite IRA-743硼特效树脂进行水溶液中硼的分离,对洗脱液温度、体积以及树脂动态交换容量等进行了实验.它的动态交换容量为4.2 mg/g,在室温条件下,用5 mL 2%HNO3可定量从树脂柱上洗脱被吸附的硼.采用Neptune型MC-ICPMS进行硼同位素组成的测定,1 μg/g浓度的硼标准溶液获得放大的信号强度约为0.7V,硼的化学分离过程有效避免了质量歧视效应.实验结果表明,MC-ICPMS对硼存在严重的记忆效应,通过采用5%HNO3-(1%HNO3 0.1%HF)-H2O-20%NH3H2O-H2O的交替清洗方法,可在约1 h内消除硼的记忆效应.在最佳仪器条件下,对含有250 ng硼的水样,可以快速测定硼的同位素组成,占δ11B测定的绝对偏差为0.4‰-0.5‰(SD).     

内蒙阿右旗铁板井镍矿矿床特征及成因探讨

铁板井绦矿床赋存于辉橄岩体中,辉橄岩体具有全岩矿化的特点,岩体及镍矿体的形成经历了三种不同的成矿过程:首先是岩浆深源液态重力分异作用,而后发生岩浆深源熔离-贯入(成岩、成矿)作用,形成岩体和镍矿体,最后在岩浆期后热液作用的叠加下完成整个成矿过程.该矿床是典型的主要由岩浆熔离作用形成的岩浆矿床.     

基于呼叫中心的防伪识别系统的设计与实现

呼叫中心系统是综合利用先进的通信及计算机技术,对信息和物资流程优化处理和管理,集中实现沟通、服务和生产指挥的系统.介绍了呼叫中心系统的历史、发展过程、意义等,阐明了论文的研究背景和主要的研究工作.论述了呼叫中心的基本原理,以及本系统总体方案的确定和相关技术,并详细阐述了系统的具体实现方法.本系统结合实际需求,采用板卡实现方案,有效地提高了系统的性能价格比,解决了呼叫中心在电话防伪识别系统中所涉及的相关问题.通过实践运行该电话防伪识别系统,证实了该系统的实用性和有效性.     

全球地球化学填图——历史发展与今后工作之建议

区域性与国家性的地球化学填图已取得进展,如何在可期待的未来以极低密度采样获得周期表内大多数元素在全球的分布,有赖于对填图理念的更新及采样介质、采样部署与采样方法研究的进展。英国Webb等发现在数平方千米至数十平方千米汇水盆地之河口采集水系沉积物样品,其分析结果可大致逼近其上游汇水盆地内土壤中元素之平均值。挪威及中国的研究工作表明在更大河流(其汇水盆地达数百、数千以至数万平方千米)的河口采样,这一规律依旧适用。看来,这种分形规律还可进一步延展至世界上一些汇水盆地达数十万至百万以上平方千米的主要入海河口,但这方面尚需作更多的研究。在这种新的填图理念指导下,提出了为实现全球地球化学填图的短期研究与试点计划和长期全面实现之规划。     

ECOLOGICAL DISTRIBUTION OF HYDROCARBON-DEGRADATION BACTERIA IN XIAMEN HARBOR

The ecology of hydrocarbon-degrading bacteria were investigated during five cruises in Xiamen Harbor. The results demonstrated that number of hydrocarbon-degrading bacteria were 2.1×102-7.5×106 cell/1 and 1.7×102-1.5×106 ceil/g dry and hetcrotrophic bacteria were 3.0× 104-5.9× 109 cell/1 and 2.53× 103-5.0× 103 cell/g dry in seawater and sediment respectively. The isolated strains which can degrade the petroleum belong to fifteen genera. Most, strains can only degsade one kind of hydro- carbon or petroleum. The results showed that the population and the species-composition of hydro carbon-degrading microorganisms were positively correlated with existing level of oil pollution and with water temperature, but independent of total microbtat count.