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.     

Overview of In - Situ Biodegradation and Enhancement

Microbial degradation technologies have been developed to restore ground water quality in aquifers polluted by organic contaminants effectively in recent years. However, in course of the degradation, the formation of biofilms in ground water remediation technology can be detrimental to the effectiveness of a ground water remediation project. Several alternatives are available to a remedial design engineer, such as Permeable Reactive Barriers (PRBs) and in -situ bioremediation, Hydrogen Releasing Compounds (HRCs) barrier, Oxygen Releasing Compounds (ORCs) barrier etc. which are efficient and cost- effective technologies. Excessive biomass formation renders a barrier ineffective in degrading the contaminants, Efforts are made to develop kinetics models which accurately determine bio - fouling and bio - filn formation and to control excessive biomass formation.     

ENVIRONMENTAL SUSTAINABILITY AND SCENARIOS OF URBANIZATION IN ARID AREA——A Case Study in Wuwei City of Gansu Province

1IN T R O D U C T IO N The western China isfacinggrowing problems of eco- logicaland economic development. The disparitiebse- tween the socio-economy of the western and eastern China were enlarging, and the major ecologicalprob- lems stilelvolve as past(H…     

Mobile Agent系统结构及其关键技术

Mobile Agent技术是一门新兴的技术,具有移动性、智能性和异步计算的特点,已成为计算机网络和分布式系统最具活力的发展方向.现对Mobile Agent的概念、系统结构及其关键技术进行了分析和探讨.     

MATLAB在运用系统建模处理南海气象数据过程中应用

介绍了MATLAB语言特点和系统建模方法的基本理论.根据南海气象数据的实际建模处理过程,给出了建模的详细步骤及其MATLAB实现过程以及MATLABTM的主要实现程序.试验讨论和结果表明利用MATLAB语言可以方便地对南海气象数据用系统建模方法进行建模和处理,MATLAB在运用系统建模法处理南海气象数据方面具有明显的优越性.     

Observational evidence for solar coronal decimetric radio pulsations with very short periods

Using the decimetric (700–1500 MHz) radio spectrometer and the synchronous observational system with high temporal resolution at four frequencies (1420, 2130, 2840 and 4260 MHz) of Yunnan Observatory, two rare events were observed on 2001 June 24 and 1990 July 30. The former was a small radio burst exhibiting pulsations with short periods (about 29, 40 and 100 ms) in the impulsive phase. The latter was a large radio burst, which at 2840 MHz produced radio pulsations with period of about 30 ms. This paper focuses on pulsations with very short periods in the range of 29–40 ms. The mechanism of generation of such pulsations may be modulation of radio radiation by the periodic trains of whistler packets originating in unstable regions of the corona. Alternatively, these pulsations can be attributed to wave-wave non-linear interactions of electrostatic upper hybrid waves driven by beams of precipitating electrons in flaring loops.     

AR（P）参数估计协方差方法与其改进型方法的对比研究

定性分析协方差方法及其改进型在ＡＲ（Ｐ）参数估计中的应用，提供了一种估计参数的计算机上机流程图，比较了协方差方法及其改进型谱估计结果。     

对地方电视台转播CCTV时延的测定

讲述了同步广播卫星电视时间信号的测量方法和测量结果，获得了CCTV1、CCTV2通过同一颗卫星（亚太－1A）转播的时延差值为16333μs，测量精度在10ns以内；CCTV2、CCTV4分别经两颗卫星（亚太－1A、亚洲－Ⅱ）转播，在陕西天文台卫星地面接收站时延差值为1644．20μs，精度为50μs，并分析了影响时延差值和精度的原因。同时测量了地方电视台转播亚太－1A的CCTV信号与直接接收亚太－1A的CCTV信号的时延差值，其测量精度为0．1μs。这些结果为利用同步广播卫星的电视信号进行高精度的时间服务提供了参考依据。     

蛤蜊科3种贝类16SrRNA基因片段及ITS2核苷酸序列分析

利用PCR技术分别扩增连云港及启东沿海蛤蜊科的西施舌（Coelomactra antiquata）、中国蛤蜊（Mactra chinensis）和四角蛤蜊（Mactra veneriformis）3种双壳贝的16SrRNA基因片段和ITS2核苷酸序列．测序后用DNAstar软件分析了核苷酸差异。结果显示：三种贝类16SrRNA基因片段长度相同，均为306bp（去除引物）．核苷酸存在多态性。共有45个变异位点，54个核苷酸发生了变异。全部为碱基置换。西施舌与中国蛤蜊此片段核苷酸的同源性为88．9％．与四角蛤蜊的同源性为88．6％．中国蛤蜊与四角蛤蜊的同源性为90．6％。三种蛤蜊ITS2序列分别为390bp（西施舌）、441bp（四角蛤蜊）和466bp（中国蛤蜊）。存在长度多态性．ITS2核苷酸差异分析结果显示．西施舌与中国蛤蜊的同源性为70．9％-71．1％，西施舌与四角蛤蜊的为70．5％-71．0％。中国蛤蜊与四角蛤蜊的同源性为88．1％-88．8％。ITS2序列分析结果与16SrRNA基因片段分析结果一致．2种分子分析法均显示中国蛤蜊与四角蛤蜊的亲缘关系近。     

CARBON DYNAMICS OF WETLAND IN THE SANJIANG PLAIN

1INTRODUCTIONWetlandsplayanimportant roleintheprocessofcar-bonstorage.Thetotalcarbonstoredindifferentkindsofwetlandsisabout15%-35%ofthetotalcarboninthegloballandsoils(POSTetal.,1982;GORHAM,1991).Inaddition,wetlandsaresignificantnaturalsources fortheatmospheric CH4 (MOORE,1994).It isestimatedthatabout110×1012gCH4 originates fromanaerobicdecompositioninthenaturalwetlands,CH4 emission fromthenaturalwetlandsis15%-30%oftheglobalCH4 emission andtheCH4 emission from thepeat land at hi…