Snow and sea ice thermodynamics in the Arctic:Model validation and sensitivity study against SHEBA data

Evolution of the Arctic sea ice and its snow cover during the SHEBA year were simulated by applying a high-resolution thermodynamic snow/ice model （HIGHTSI）. Attention was paid to the impact of albedo on snow and sea ice mass balance, effect of snow on total ice mass balance, and the model vertical resolution. The SHEBA annual simulation was made applying the best possible external forcing data set created by the Sea Ice Model Intercomparison Project. The HIGHTSI control run reasonably reproduced the observed snow and ice thickness. A number of albedo schemes were incorporated into HIGHTSI to study the feedback processes between the albedo and snow and ice thickness. The snow thickness turned out to be an essential variable in the albedo parameterization. Albedo schemes dependent on the surface temperature were liable to excessive positive feedback effects generated by errors in the modelled surface temperature. The superimposed ice formation should be taken into account for the annual Arctic sea ice mass balance.

ESTIMATORS AND SOME BEHAVIORS FORA PARTIALLY LINEAR MODEL WITH CENSORED DATA

This paper considers the local linear regression estimators for partially linear model with censored data. Which have some nice large-sample behaviors and are easy to implement. By many simulation runs, the author also found that the estimators show remarkable in the small sample case yet.

The Importance of Integrating Geological Mapping Information with Validated Assay Data for Generating Accurate Geological Wireframes in Orebody Modelling of Mineral Deposit in Mineral Resource Estimation: A Case Study in AngloGold Ashanti, Obuasi Mine

The basis of accurate mineral resource estimates is to have a geological model which replicates the nature and style of the orebody. Key inputs into the generation of a good geological model are the sample data and mapping information. The Obuasi Mine sample data with a lot of legacy issues were subjected to a robust validation process and integrated with mapping information to generate an accurate geological orebody model for mineral resource estimation in Block 8 Lower. Validation of the sample data focused on replacing missing collar coordinates, missing assays, and correcting magnetic declination that was used to convert the downhole surveys from true to magnetic, fix missing lithology and finally assign confidence numbers to all the sample data. The missing coordinates which were replaced ensured that the sample data plotted at their correct location in space as intended from the planning stage. Magnetic declination data, which was maintained constant throughout all the years even though it changes every year, was also corrected in the validation project. The corrected magnetic declination ensured that the drillholes were plotted on their accurate trajectory as per the planned azimuth and also reflected the true position of the intercepted mineralized fissure(s) which was previously not the case and marked a major blot in the modelling of the Obuasi orebody. The incorporation of mapped data with the validated sample data in the wireframes resulted in a better interpretation of the orebody. The updated mineral resource generated by domaining quartz from the sulphides and compared with the old resource showed that the sulphide tonnes in the old resource estimates were overestimated by 1% and the grade overestimated by 8.5%.

Latest Progress of the Chinese Meteorological Satellite Program and Core Data Processing Technologies

In this paper,the latest progress,major achievements and future plans of Chinese meteorological satellites and the core data processing techniques are discussed.First,the latest three FengYun(FY)meteorological satellites(FY-2H,FY-3D,and FY-4A)and their primary objectives are introduced Second,the core image navigation techniques and accuracies of the FY meteorological satellites are elaborated,including the latest geostationary(FY-2/4)and polar-orbit(FY-3)satellites.Third,the radiometric calibration techniques and accuracies of reflective solar bands,thermal infrared bands,and passive microwave bands for FY meteorological satellites are discussed.It also illustrates the latest progress of real-time calibration with the onboard calibration system and validation with different methods,including the vicarious China radiance calibration site calibration,pseudo invariant calibration site calibration,deep convective clouds calibration,and lunar calibration.Fourth,recent progress of meteorological satellite data assimilation applications and quantitative science produce are summarized at length.The main progress is in meteorological satellite data assimilation by using microwave and hyper-spectral infrared sensors in global and regional numerical weather prediction models.Lastly,the latest progress in radiative transfer,absorption and scattering calculations for satellite remote sensing is summarized,and some important research using a new radiative transfer model are illustrated.

IEC 61850 SCL Validation Using UML Model in Modern Digital Substation

The IEC 61850 standard stipulates the Substation Configuration Description Language (SCL) file as a means to define the substation equipment, IED function and also the communication mechanism for the substation area network. The SCL is an eXtensible Markup Language (XML) based file which helps to describe the configuration of the substation Intelligent Electronic Devices (IED) including their associated functions. The SCL file is also configured to contain all IED capabilities including data model which is structured into objects for easy descriptive modeling. The effective functioning of this SCL file relies on appropriate validation techniques which check the data model for errors due to non-conformity to the IEC 61850 standard. In this research, we extend the conventional SCL validation algorithm to develop a more advanced validator which can validate the standard data model using the Unified Modeling Language (UML). By using the Rule-based SCL validation tool, we implement validation test cases for a more comprehensive understanding of the various validation functionalities. It can be observed from the algorithm and the various implemented test cases that the proposed validation tool can improve SCL information validation and also help automation engineers to comprehend the IEC 61850 substation system architecture.

The Proposal of Data Warehouse Validation

The analysis of relevant standards and guidelines proved the lack of information on actions and activities concerning data warehouse testing. The absence of the complex data warehouse testing methodology seems to be crucial particularly in the phase of the data warehouse implementation. The aim of this article is to suggest basic data warehouse testing activities as a final part of data warehouse testing methodology. The testing activities that must be implemented in the process of the data warehouse testing can be split into four logical units regarding the multidimensional database testing, data pump testing, metadata and OLAP （Online Analytical Processing） testing. Between main testing activities can be included： revision of the multidimensional database scheme, optimizing of fact tables number, problem of data explosion, testing for correctness of aggregation and summation of data etc.

Variance Estimation for High-Dimensional Varying Index Coefficient Models

This paper studies the re-adjusted cross-validation method and a semiparametric regression model called the varying index coefficient model. We use the profile spline modal estimator method to estimate the coefficients of the parameter part of the Varying Index Coefficient Model (VICM), while the unknown function part uses the B-spline to expand. Moreover, we combine the above two estimation methods under the assumption of high-dimensional data. The results of data simulation and empirical analysis show that for the varying index coefficient model, the re-adjusted cross-validation method is better in terms of accuracy and stability than traditional methods based on ordinary least squares.

基于DEA和熵权TOPSIS模型比较的高校科技创新效率分析

高校是国家创新体系的重要组成部分,为深入分析新形势下高校科技创新效率,完善高校科技创新效率评价方法,综合运用数据包络分析(data envelopment analysis,DEA)模型和基于信息熵法的理想点模型(technique for order preference by similarity to an ideal solution model,TOPSIS),以天津市区域14所高校为例,对比分析了新形势下高校科技创新效率。基于DEA模型的分析结果表明,14所高校科技创新效率总体呈不规律波动趋势,即使继续加大投入力度,也仅能获得科技成果产出规模有限的增加;基于TOPSIS模型的分析结果表明,14所高校科技创新效率总体呈上升发展趋势,可继续加大投入力度,以促进科技成果更大规模地产出。通过两个模型的综合运用,实现了评价结果的交叉验证,为新形势下高校科技创新效率评价提供了新思路。

基于分段特征提取的仿真模型结果验证方法

校核、验证与确认(verification,validation,and accreditation,VV&A)是保证仿真模型可信度的关键手段,其中模型验证是核心环节。针对导弹飞行仿真模型结果验证存在的参考数据不可获得、参考数据来源多样、专家验证主观性强等问题,提出一种基于时间序列分段特征提取的导弹飞行仿真模型结果验证方法。提出了一种综合的时间序列分段线性方法,由基于二阶导数提取趋势边缘点的线性分段算法和基于极值点优化的Top-Down线性分段算法两部分组成,以实现对导弹飞行仿真数据和参考数据进行有效的线性分段表示。基于上述分段结果,对各段时间序列的均值、方差、斜率等特征进行提取,以辅助专家进行验证,从而降低验证中的主观性;或者直接利用TIC系数法、动态时间规整(dynamic time warping,DTW)等方法进行客观的相似性分析。通过充分利用时间序列的分段特征,可实现各种情形下的导弹飞行仿真模型结果验证。通过一个导弹模型结果验证案例演示了所提方法的可行性和有效性。

基于真实世界数据研究注射用伏立康唑致急性肾损伤的危险因素建立预测模型及验证

目的 基于真实世界数据,分析注射用伏立康唑发生急性肾损伤(AKI)的危险因素,建立预测模型并进行内部验证和外部验证,为临床安全用药提供参考。方法 收集2020年1月1日至2023年6月30日在某院注射用伏立康唑治疗≥3 d,且年龄≥18岁患者的病历资料。其中2023年1月1日之前出院的患者作为建模组,之后的患者作为验证组。提取患者的基本信息、实验检查指标、临床诊断、联合用药等数据。根据是否发生AKI将患者分为AKI组和非AKI组。采用多因素Logistic回归法分析注射用伏立康唑致AKI的危险因素,并建立预测模型。通过受试者工作特征(ROC)、ROC曲线下面积(AUC)及Hosmer-Lemeshow检验(H-L检验)评估区分度和校准度,并进行内部验证和外部数据验证检验该模型的价值。结果 共625例(男性371例,女性254例)患者纳入研究。其中建模组489例(男性296例,女性193例),发生AKI 87例;验证组136例(男性75例,女性61例),发生AKI 32例。建模组多因素Logistic回归分析显示血流感染、肾脏疾病、心血管疾病、使用利尿剂是发生AKI危险因素,肌酐清除率(CrCl)和血清白蛋白(Alb)是保护因素。用上述影响因素建立Logistic回归方程,经变换后得到预测因子Y=0.735X_(1)+0.707X_(2)+0.701X_(3)+0.683X_(4)-0.062 X_(5)-0.008X_(6)。X_(1)~X_(6)分别表示使用利尿剂、心血管疾病、肾脏疾病、血流感染、Alb、CrCl。经ROC曲线分析验证,模型组AUC为0.750(95%CI:0.692~0.808,P<0.0 01),H-L检验χ^(2)值为7.535,P=0.480;验证组AUC为0.821(95%CI:0.749~0.893,P<0.001),H-L检验χ^(2)值为13.924,P=0.084,提示该模型具有较好的区分度。模型的约登指数最大值为0.389,对应ROC曲线切点最佳值为-0.976,敏感度为56.3%,特异度为82.6%。k折交叉验证提示该模型的准确率较好(Accuracy=0.823),一致性较低(Kappa=0.191)。结论 CrCl、Alb、血流感染、肾脏疾病、心血管疾病、利尿剂是注射用伏立康唑发生AKI的独立影响因素。基于这6个变量建立AKI的预测模型具有一定的区分度,可在一定程度上辅助临床治疗决策,有利于临床安全用药。

小样本飞机生产质量偏差数据分析与预测方法研究

随着现代工业水平和对飞机精度要求的不断提升,对飞机生产质量的分析和管控方法越来越受到各大航空企业的重视。当前阶段,针对飞机装配偏差存在可参考样本数据少、不确定性大、非线性、多层级装配等固有特征,传统的分析方法难以准确地构建飞机生产偏差分析模型。因此,以飞机生产过程的偏差为研究目标,对飞机生产质量偏差数据分析与预测方法展开系统研究。首先分析各个零件之间的偏差关系,基于主成分分析法识别对总偏差影响最大的关键零件,找到重点预测的目标;接着从实际生产的类正态数据出发,重点关注关键零件,实现了基于正态云模型的偏差数据预测、生成与验证,得到更多样本的飞机生产质量偏差数据及其隶属度,一定程度上缓解了“小样本”的问题,并基于k-折交叉验证对预测模型进行了评估;最后构建了基于改进的灰色预测模型的多源数据融合的装配偏差波动区间协同预测模型,“小样本”问题的缓解使得区间预测更加精细、科学,在公差数据的参考下,预测飞机生产质量偏差所在的区间范围,为实际生产和制定公差修正机制提供指导。

Direct Pointwise Comparison of FE Predictions to StereoDIC Measurements:Developments and Validation Using Double Edge-Notched Tensile Specimen

To compare finite element analysis(FEA)predictions and stereovision digital image correlation(StereoDIC)strain measurements at the same spatial positions throughout a region of interest,a field comparison procedure is developed.The procedure includes(a)conversion of the finite element data into a triangular mesh,(b)selection of a common coordinate system,(c)determination of the rigid body transformation to place both measurements and FEA data in the same system and(d)interpolation of the FEA nodal information to the same spatial locations as the StereoDIC measurements using barycentric coordinates.For an aluminum Al-6061 double edge notched tensile specimen,FEA results are obtained using both the von Mises isotropic yield criterion and Hill’s quadratic anisotropic yield criterion,with the unknown Hill model parameters determined using full-field specimen strain measurements for the nominally plane stress specimen.Using Hill’s quadratic anisotropic yield criterion,the point-by-point comparison of experimentally based full-field strains and stresses to finite element predictions are shown to be in excellent agreement,confirming the effectiveness of the field comparison process.

激光雷达在森林资源本底调查中的应用探讨

森林资源本底调查的目的是全面掌握森林资源现状与动态变化情况。文章采用高分遥感、机载激光雷达遥感与少量地面调查结合的方法,利用航空数字正射影像或高分辨率卫星遥感正射影像(Digital Orthophoto Map,DOM)进行小班区划和基本属性(地类和树种)识别,通过机载LiDAR点云数据和地面建模样地数据进行林分调查因子测算,从而得到统一标准、相同尺度的小班区划图、立地因子、管理因子和林分因子等,形成高质量的调查结果,为森林资源本底调查提供技术及方法参考。

基于差异化估计模型的航电系统地面验证飞参数据预处理方法

飞机航电系统地面验证,是航电系统设计完成后和交付装机前的重要检验环节,需要通过数据激励航电设备模拟飞行过程中多种使用场景,从而验证设备级、系统级、全机级的功能响应正确与否。通过飞参数据挖掘和深度分析,实现飞参数据在航电系统地面验证中的利用,是改进飞机性能提高飞机设计水平,探索航电系统验证专业的目标和方向。文章结合飞参数据在航电系统近地告警子系统地面验证中的实践,介绍基于差异化估计模型的飞参数据预处理方法,包括特征数据筛选、冗余数据清理、缺失数据插补等系列流程,经过数据分析、数据预处理、模型校验、整合输出,获得可用、完整、简洁的高质量验证激励数据,有效提升航电系统验证的质量和效率。

基于水动力模型与大数据分析的污水干线优化调度策略

随着我国城市化的快速发展与国家污水处理要求的逐渐提高,城市的污水排水系统越来越复杂。单纯依靠人工经验来进行污水系统的运维与优化调度的难度逐渐越大。文章以上海市白龙港片区污水主干系统为案例,创新性地提出了通过水动力模型耦合历史大数据分析来进行污水干线系统优化调度的技术方案:该方案通过历史大数据挖掘出各个泵站在污水厂不发生溢流情况下的启闭策略,并将此策略放入经过严格率定验证的排水模型中进行评估。目前得到的优化方案通过模拟可以将2021年的白龙港污水厂的旱天溢流天数从现状的58 d降低至50 d。该优化方案于2022年进行了试运行:相比2021年,在试运行的两个月内将旱天溢流总量降低了13%。基于此案例分析,最终总结出一种城市污水主干系统获取优化调度策略的方法。

利用预训练模型提升光谱特征提取性能的有效性研究

观测技术的发展带来了海量的光谱数据。如何对这些数据进行自动分类受到广大研究人员的关注,其关键是光谱数据的特征提取。鉴于人工处理方式的局限性,主流研究大多采用机器学习算法进行光谱数据的特征提取。然而,这些机器学习算法由于时空复杂度过高无法处理海量光谱数据。近年来涌现的预训练模型具有优良的特征提取能力,但目前鲜有文献对该模型对光谱数据有效性问题进行探讨。因此,将恒星光谱数据作为研究对象,分别引入BERT、ALBERT、GTP等预训练模型和卷积神经网络(CNN)来对恒星光谱数据进行特征提取和分类处理,通过比较实验结果来检验这几类预训练模型在恒星光谱特征提取方面的有效性。利用Python编程语言编写光谱分类程序。在预训练模型特征提取的基础上,利用TensorFlow1.14中的CNN模型进行光谱类型判定。实验用到的数据集是SDSS DR10恒星光谱数据集,包括K型、F型、G型。利用网格搜索和5倍交叉验证法获得实验最优参数。在相同训练数据集条件下,与ALBERT、GPT相比,BERT模型的分类正确率均最高。从平均正确率看,在K型、F型、G型恒星数据集上,BERT模型的平均正确率比ALBERT分别高0.0251、0.0215和0.0225,比GPT分别高0.0497、0.0424和0.0432。分析实验结果可以得出如下结论:(1)恒星光谱分类正确率随训练数据规模的增大而提高;(2)在训练数据规模占比相同的情况下,同一模型在K型恒星数据集上的分类正确率最高,其次是F型恒星数据集,G型恒星数据集最低;(3)与ALBERT、GPT相比,BERT模型具有具有更优的特征提取能力。

飞控系统多元数据融合虚拟试验仿真模型验证

为提高飞控系统虚拟试验仿真模型的有效性与可信性,解决虚拟试验中多元冗余与强耦合数据的问题,提出了一种基于多元数据融合的仿真模型验证方法。首先,通过多元仿真数据融合,减少噪声和误差;其次,运用皮尔逊相关系数分析多元输出数据的相关性,并结合时域卷积神经网络-长短期记忆(TCN-LSTM)方法融合数据特征,深入挖掘数据的时空关联性;最后,通过概率分布分析评估仿真数据与参考数据的差异,转化为可信度等级,实现仿真模型的有效验证。实验结果表明,80%的输出数据达到仿真模型可信标准,其中有50%的输出数据达到完全可信标准,该方法显著提升了仿真模型的验证精度与可靠性。

基于姿态估计的输电线路带电作业的人体数字孪生研究

带电作业是保证电网安全可靠运行的重要内容,而带电作业又充满危险。为了能够对人体面临的风险进行评估,可以将数字孪生理念引入输电线路带电作业中,构建人体数字孪生体对人体进行风险评估,在虚拟空间中完成对现实世界的映射。采用姿态估计、模型重构和模拟仿真构建高压输电线路带电作业人体数字孪生体,能够对危险状况进行预警,评估人身安全。首先运用POSIT算法得到现实世界和图像坐标系的转换矩阵,结合二维三维转换技术将后续的二维坐标点转换为三维坐标点,即能得到人体的姿态数据。然后利用人体姿态数据进行人体的模型重构论述和现场仿真进行风险评估,并且通过实时工作指南规则进行人员的潜在风险评估。该研究实现了三维模型随着姿态数据的改变而模型重构,继而随着人体模型的改变,系统将在仿真中自动计算电场,并利用风险评估显示危险。此技术能够为现场作业人员安全评估提供一种新的思路,为数字化电网发展提供基础。

基坑开挖引起周边建筑物变形简化预测模型研究

基于武汉某综合性办公建筑项目,建立基坑开挖对周边建筑物影响数值分析模型,利用现场实测数据验证其准确性;分析基坑开挖深度、围护结构水平位移、基坑与建筑物相对位置等因素对既有建筑物变形的影响,形成建筑物变形数据库;建立简化的半经验预测模型,评估基坑邻近建筑物的变形,并通过既有工程的实测数据,验证该理论计算模型的准确性。

滑坡风险评估实践中的难点与对策

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