基于修正πHW变分的板非协调动态有限元法

本文本文讨论了基于修正πＨＷ变分的杂交应变板弯曲非协调动态有限元的分析列式,建立了四节点单元,进行了特征分析。算例表明,该单元是简单、有效的。     

一种大区域地貌矢量数据的DEM快速生成与粗差检测算法

本文论述了一种大区域范围从矢量化地貌数据中快速形成ＤＥＭ以及可视化粗差检测与修正的方法。实践表明，该算法具有实用、直观、快速等特点，可获得稳定而可靠的计算结果。     

关于一行《大衍历》的插值法

论证一行《大衍历》（Ａ．Ｄ．７２９）的二次不等间距插值法和刘焯《皇极历》（Ａ．Ｄ．６０４）的二次等间距插值法的实质完全相同，并没有一般所说的推广意义；否定了以往人们关于一行有意识地应用了三次插值法近似公式的说法．     

基于卷积神经网络的智能化地震数据插值技术

地震数据通常存在数据缺失问题,严重影响地震数据各个处理环节,需采用适当的手段对其重构.本文提出了一种基于深度学习卷积神经网络(CNN)的智能化地震数据插值技术.算法的关键在于构建一个适用于地震资料插值的CNN模型,该技术以缺失地震数据作为输入层,由卷积算法提取地震数据的特征信息,并通过池化层实现数据压缩降维,同时引入修正线性函数(ReLU)提高模型的非线性表达能力,再通过反卷积层恢复数据尺寸,最终搭建卷积自编码器模型(CAE),实现数据-数据的映射关系.该模型通过残差学习获得缺失数据特征并实现重构数据输出,与现有技术相比,该方法采用自监督学习方式,利用大量数据训练卷积自编码器模型,通过所得模型实现缺失地震道的数据重构.分别利用CAE模型及POCS插值技术对模型资料和实际数据进行插值,测试结果表明,CAE能有效实现地震数据插值,且与POCS方法相比具有更高的精度,验证了算法的可行性和有效性.     

西门子多排螺旋CT新技术

多排螺旋CT的推出使得CT临床应用能力大大提高,CT扫描仪进入了一个快速发展的时期。本文通过介绍双向飞焦点Z-Sharp技术、自由螺旋SureView等技术,比较各种螺旋重建算法,以及剂量调节方案CAREDose4D等新的西门子CT技术,呈现西门子在CT革新中所作的努力,Sensation64排CT在市场上大受欢迎证明了这些技术的优越性。     

Geostatistics applied to best-fit interpolation of orientation data

Automatic methods used in geosciences to interpolate between orientation data have often limited applicability and strength, in particular where large ranges of orientations occur. In this paper, we show that geostatistical methods yield rather strong and powerful results when applied to directional data. The procedure involves the calculation of variograms, followed by a kriging interpolation of the data. In order to free from the circular property of directional data, the treatment of initial angular data sets is performed using scalar values provided by the direction cosines of double-angle values. The strength and application of the method are demonstrated by the analysis of theoretical and natural data sets. Natural examples are focused on the calculation and the analysis of cleavage trajectory maps.     

Comparative analysis of different techniques for spatial interpolation of rainfall data to create a serially complete monthly time series of precipitation for Sicily,Italy

The availability of good and reliable rainfall data is fundamental for most hydrological analyses and for the design and management of water resources systems. However, in practice, precipitation records often suffer from missing data values mainly due to malfunctioning of raingauge for specific time periods. This is an important issue in practical hydrology because it affects the continuity of rainfall data and ultimately influences the results of hydrologic studies which use rainfall as input. Many methods to estimate missing rainfall data have been proposed in literature and, among these, most are based on spatial interpolation algorithms.     

Performance of geostatistical interpolation methods for modeling sampled data with non-stationary mean

The measured ozone pollution peak in the atmosphere of Mexico City region was considered in order to study the effect of a non-stationary mean of the sampled data in geostatistics interpolation methods. With this objective the local mean value of the sampled data was estimated through a linear regression analysis of their values on the monitoring station’s coordinates. The residuals obtained by removing the data trend are considered as a set of stationary random variables. Several interpolation methods used in geostatistics, such as inverse distance weighted, kriging, and artificial neural networks techniques were considered. In an effort to optimize and evaluate its performance, we fit interpolated values to sampled data, obtaining optimal values for the parameters defining the used model, that means, the values of the parameters that give the lowest mean RMSE between the interpolated value and measured data at 20 stations at 1500 hours for a set of 21 days of December 2001, which was chosen as the training set. The training set is conformed by all the days in December 2001 excepting the days (3,6,9,12,...,27,30) which were considered as the testing set. Once the optimal model is obtained, it is used to interpolate the values at the stations at 1500 hours for the testing days. The RMSE between interpolated and measured values at monitoring stations was also evaluated for these testing values and is shown as a percentage in Table 2. These values and the defined generalization parameter G, can be used to evaluate the performance and the ability of the models to predict and reproduce the peak of ozone concentrations. Scatter plots for testing data are presented for each interpolation method. An interpretation of the ozone pollution levels obtained at 1500 hours at December 21 was given using the wind field that prevailed in the region 1 h before the same day.     

Mapping crop phenology using NDVI time-series derived from HJ-1 A/B data

With the availability of high frequent satellite data, crop phenology could be accurately mapped using time-series remote sensing data. Vegetation index time-series data derived from AVHRR, MODIS, and SPOT-VEGETATION images usually have coarse spatial resolution. Mapping crop phenology parameters using higher spatial resolution images (e.g., Landsat TM-like) is unprecedented. Recently launched HJ-1 A/B CCD sensors boarded on China Environment Satellite provided a feasible and ideal data source for the construction of high spatio-temporal resolution vegetation index time-series. This paper presented a comprehensive method to construct NDVI time-series dataset derived from HJ-1 A/B CCD and demonstrated its application in cropland areas. The procedures of time-series data construction included image preprocessing, signal filtering, and interpolation for daily NDVI images then the NDVI time-series could present a smooth and complete phenological cycle. To demonstrate its application, TIMESAT program was employed to extract phenology parameters of crop lands located in Guanzhong Plain, China. The small-scale test showed that the crop season start/end derived from HJ-1 A/B NDVI time-series was comparable with local agro-metrological observation. The methodology for reconstructing time-series remote sensing data had been proved feasible, though forgoing researches will improve this a lot in mapping crop phenology. Last but not least, further studies should be focused on field-data collection, smoothing method and phenology definitions using time-series remote sensing data.     

Evaluation of Diverse Geometric and Geostatistical Estimation Methods Applied to Annual Precipitation in Asturias (NW Spain)

Several alternative estimation and interpolation methods for making annual precipitation maps of Asturias are analysed. The data series in this study corresponds to the year 2003. There exists an evident relationship between precipitation and altitude, with a high correlation coefficient of 0.70, that reflects the hillside effect; that is, the increase in the amount of precipitation in more mountainous areas. The direct spatial variability of precipitation and of altitude and the cross variability of precipitation–altitude are defined by two exponential variogram models: one with a short-range structure (15–30 km) that reflects the control exerted by the lesser, local mountain ranges over the amount of precipitation; and another with a long-range structure (80 km) that supposes the influence over precipitation of the major mountainous alignments of the inland areas of the Cantabrian Mountain Range (Cordillera Cantábrica) situated between 60 and 90 km from the coastline. These variogram models had to be validated for coregionalization by the Pardo-Igúzquiza and Dowd method so as to be able to make the cokriging map. The geometric estimation methods employed were triangulation and inverse distance. The geostatistical estimation methods developed were simple kriging, ordinary kriging, kriging with a trend model (universal kriging), lognormal kriging, and cokriging. In all of these methods, a 3 × 3 km² grid was selected with a total of 2580 points to estimate, a circular search window of 60 km, and a relatively small number of samples with the aim of highlighting the local features and variations on isohyet maps. The kriging methods were implemented using the WinGslib software, incorporating two specific programs, Prog2 and Fichsurf, so as to be able then to make isohyet maps using the Surfer software. All the methods employed, apart from triangulation, rendered realistic maps with good fits to the values of the original data (precipitation) of the sample maps. The problem with triangulation lies not in the reliability of the estimates but in the fact that it gives rise to contrived maps because of the tendency of isohyets to present abundant triangular facets. The reliability of the methods was based on cross-validation analysis and on evaluation of the different types of errors, both in their values and in their graphical representations. Substantial differences were not found in the values of the errors that might discriminate some methods from others in an evident way. Bearing the aforesaid in mind, should we have to make an evaluation of the different estimation methods in decreasing order of acceptance, this would be: kriging with a trend model, inverse distance, cokriging, lognormal kriging, ordinary kriging, simple kriging, and triangulation. The application of other estimation methods such as colocated cokriging, kriging with an external drift, and kriging of variable local means (residual kriging) is dependent on the availability of a digital model of the terrain with an altitude grid of the region.