利用多频多系统GNSS OEM板卡实现高精度变形监测

针对近年来被广泛应用的多频多系统GNSS OEM板卡,设计并实现了一套基于多频多系统OEM板卡的低成本变形监测系统,包括数据解码、基线处理、网平差和坐标转换等,能够实时获取测站点高精度空间坐标。以某高层建筑形变监测为例,通过串口通信获取板卡多频多系统观测信息,并经过该系统解算,实现了监测点实时定位,且系统成本相比市场上测量型GNSS接收机系统下降了约40%。实验结果表明,该系统解码精度可达0.2 mm,静态模式定位精度可达到平面2 mm以内,高程5 mm以内,动态模式定位精度可达到平面5 mm以内,高程10 mm以内,验证了该系统的可靠性和适用性。     

基于多元线性回归分析的页岩气有利区评价新方法 ——以上扬子地区五峰组—龙马溪组海相页岩为例

本文以四川盆地及其周缘五峰组—龙马溪组页岩气评价为例,总结了页岩气有利区优选的储层参数、保存参数和压力系数等参数,量化了各关键参数平面分布,运用多元线性回归分析方法计算了参数权重,通过多参数加权叠加公式建立了多元线性回归模型:有利区=-0.317+0.75×埋深+0.285×TOC+0.148×RO+0.093×孔隙度...     

具有不同到达率的带有启动时间及不耐烦策略的多级适应性休假M^X/G/1排队

研究了具有不同到达率的带有启动时间及不耐烦策略的多级适应性休假M^X/G/1排队模型,通过嵌入马尔可夫链方法推导出稳态队长的母函数、等待时间的LST（先到先服务规则）,并验证了稳态队长和稳态等待时间具有随机分解性,而且给出了忙期、全忙期及在线期均值。     

动态多地图服务负载平衡设计及实现

文章针对在于WebGIS应用中,服务器需要海量生成地图服务时,服务器常处于瘫痪状态的问题,提出建立基于ArcGIS Server的多地图服务对象的管理方案,客户端发出新的地图请求时,需通过多地图服务管理对象检验,由地图服务管理对象控制向ArcGIS Server发出的请求,从而解决服务器经常处于瘫痪的问题。基于此研究,作者设计并实现了B/S模式的以工代赈信息管理系统,在实际应用中取得了较好的效果。     

Dominant climate factors influencing the Arctic runoff and association between the Arctic runoff and sea ice

By using the Arctic runoff data from R-ArcticNET V4.0 and ArcticRIMS, trends of four major rivers flowing into the Arctic Ocean, whose climate factor plays an important role in determining the variability of the Arctic runoff, are investigated. The results show that for the past 30 years, the trend of the Arctic runoff is seasonally dependent. There is a significant trend in spring and winter and a significant decreasing trend in summer, leading to the reduced seasonal cycle. In spring, surface air temperature is the dominant factor influencing the four rivers. In summer, precipitation is the most important factor for Lena and Mackenzie, while snow cover is the most important factor for Yenisei and Ob. For Mackenzie, atmospheric circulation does play an important role for all the seasons, which is not the case for the Eurasian rivers. The authors further discuss the relationships between the Arctic runoff and sea ice. Significant negative correlation is found at the mouth of the rivers into the Arctic Ocean in spring, while significant positive correlation is observed just at the north of the mouths of the rivers into the Arctic in summer. In addition, each river has different relationship with sea ice in the eastern Greenland Sea.     

多种模式降水预报的稳定性特征研究

预报的稳定性是指对同一时段在不同时间发布的多时效预报结论的一致性,是模式预报质量的一个重要方面,较大的不稳定性会给使用者造成困扰。为深入了解业务常用模式的稳定性,使用相对标准偏差指标计算不同时效预报的降水量波动大小,并改进了Flip-Flop指数（改进后简称FFnorm）,计算多时效降水量预报变化趋势的翻转程度,衡量预报变化趋势的稳定性,对2种全球模式（ECMWF、NCEP-GFS）、3种区域模式（CMA-MESO、CMA-SH9、HHUPS-ST）,在中国6个气候分区中降水预报的稳定性进行对比分析,分为实况有降水和暴雨及以上降水2种情况进行了讨论。结果表明：实况有降水时,相对区域模式来说,全球模式的多时效降水预报的相对标准偏差较小,即模式降水量预报的波动较小;各模式对西南区的西部、东北区的东部以及华南区的南部预报的波动性相对较小,西北区的西部波动性较大。就多时效降水量预报变化趋势而言,2种情况下均为CMA-MESO、NCEP-GFS和 ECMWF的稳定性较好,其FFnorm指数小于HHUPS-ST和CMA-SH9模式,其中CMA-MESO对西南区、华南部分地区降水量预报变化趋势的稳定性较为突出;CMA-SH9的指数最大,多时效降水量预报变化趋势稳定性较差;各模式对长江中下游地区的FFnorm指数相对较大,多时效预报趋势的稳定性较差。有降水时,CMA-MESO随时效临近的降水量预报变化趋势稳定（单调递增、单调递减或不变）的频次最多,其次是NCEP-GFS,2种降水情况下,该2种模式的降水量预报均为随时效临近单调递增次数大于递减次数,且CMA-MESO单调递增特征尤其显著。以上特征能够为模式调试和预报决策提供参考。     

Spatial and multivariate analysis of geochemical data from metavolcanic rocks in the Ben Nevis area, Ontario

A study of the lithogeochemistry of metavolcanics in the Ben Nevis area of Ontario, Canada has shown that factor analysis methods can distinguish lithogeochemical trends related to different geological processes, most notably, the principal compositional variation related to the volcanic stratigraphy and zones of carbonate alteration associated with the presence of sulphides and gold. Auto- and cross-correlation functions have been estimated for the two-dimensional distribution of various elements in the area. These functions allow computation of spatial factors in which patterns of multivariate relationships are dependent upon the spatial auto- and cross-correlation of the components. Because of the anisotropy of primary compositions of the volcanics, some spatial factor patterns are difficult to interpret. Isotropically distributed variables such as CO ₂ are delineated clearly in spatial factor maps. For anisotropically distributed variables (SiO ₂ ), as the neighborhood becomes smaller, the spacial factor maps becomes better. Interpretation of spatial factors requires computation of the corresponding amplitude vectors from the eigenvalue solution. This vector reflects relative amplitudes by which the variables follow the spatial factors. Instability of some eigenvalue solutions requires that caution be used in interpreting the resulting factor patterns. A measure of the predictive power of the spatial factors can be determined from autocorrelation coefficients and squared multiple correlation coefficients that indicate which variables are significant in any given factor. The spatial factor approach utilizes spatial relationships of variables in conjunction with systematic variation of variables representing geological processes. This approach can yield potential exploration targets based on the spatial continuity of alteration haloes that reflect mineralization.List of symbols c _i Scalar factor that minimizes the discrepancy between andU _i - D Radius of circular neighborhood used for estimating auto- and cross-correlation coefficients - d Distance for which transition matrixU is estimated - d _ij Distance between observed valuesi andj - E Expected value - E _i Row vector of residuals in the standardized model - F(d _ij) Quadratic function of distanced _ij F(d _ij)=a+bd _ij+cd _ij ² - L Diagonal matrix of the eigenvalues ofU - _i Eigenvalue of the matrixU;ith diagonal element ofL - N Number of observations - p Number of variables - Q Total predictive power ofU - R Correlation matrix of the variables - R _0j Variance-covariance signal matrix of the standardized variables at origin;j is the index related tod andD (e.g.,j=1 ford=500 m,D=1000 m) - R _1j Matrix of auto- and cross-correlation coefficients evaluated at a given distance within the neighborhood - R _m ² Multiple correlation coefficient squared for themth variable - S _i Column vectori of the signal values - s _k ² Residual variance for variablek - T _i Amplitude vector corresponding toV _i;ith row ofT=V ^–1 - T Total variation in the system - U Nonsymmetric transition matrix formed by post-multiplyingR ₀₁ ^–1 byR _ij - U _i Componenti of the matrixU, corresponding to theith eigenvectorV _i;U _i= _iV_iT_i - U* _i ComponentU _i multiplied byc _i - U _ij Sum of componentsU _i+U _j - V _i Eigenvector of the matrixU;ith column ofV withUV=VL - w Weighting factor; equal to the ratio of two eigenvalues - X _i Random variable at pointi - x _i Value of random variable at pointi - y _i Residual ofx _i - Z _i Row vectori for the standardized variables - z _i Standardized value of variable     

The Zoulang Nanshan Caledonian Subduct ion Complex in the Northern Qilian Mountains and Its Dynamics

The front of the Zoulang Nanshan Caledonian volcanic island arc zone in the northern Qilian Mountains is a forearc accretionary terrane, composed of multiple accretionary volcanic island arcs, flysch accretionary wedges,high-pressure metamorphosed detachment zones and remnants of ophiolites. It resulted from the northeastward subduction of the Early Palaeozoic Qilan oceanic crust beneath the Alxa block. High-pressure metamorphism, which occurred during the subduction, progressed through three stages: the initial stage of medium T-high P,the main stage of temperature decrease and pressure increase, and the lag stage of pressure decrease and temperature increase. Finally the paper presents a retrotrench subduction dynamic model indicative of northward subduction of the central Qilian block and southward accretion of the Alxa block during the period of 450-500 Ma.     

中国主要自然致灾因子的区域分异

依据１０２种自然致灾因子分布图，以县域为统计单元，建立了全国自然致灾因子数据库。在此基础上，绘制出中国自然致灾因子多度、相对强度、被灾指数图，进而分析了它们的区域分异，为进行中国自然灾害区划提供依据。