Prediction of three-dimensional ocean temperature in the South China Sea based on time series gridded data and a dynamic spatiotemporal graph neural network

Ocean temperature is an important physical variable in marine ecosystems,and ocean temperature prediction is an important research objective in ocean-related fields.Currently,one of the commonly used methods for ocean temperature prediction is based on data-driven,but research on this method is mostly limited to the sea surface,with few studies on the prediction of internal ocean temperature.Existing graph neural network-based methods usually use predefined graphs or learned static graphs,which cannot capture the dynamic associations among data.In this study,we propose a novel dynamic spatiotemporal graph neural network(DSTGN)to predict threedimensional ocean temperature(3D-OT),which combines static graph learning and dynamic graph learning to automatically mine two unknown dependencies between sequences based on the original 3D-OT data without prior knowledge.Temporal and spatial dependencies in the time series were then captured using temporal and graph convolutions.We also integrated dynamic graph learning,static graph learning,graph convolution,and temporal convolution into an end-to-end framework for 3D-OT prediction using time-series grid data.In this study,we conducted prediction experiments using high-resolution 3D-OT from the Copernicus global ocean physical reanalysis,with data covering the vertical variation of temperature from the sea surface to 1000 m below the sea surface.We compared five mainstream models that are commonly used for ocean temperature prediction,and the results showed that the method achieved the best prediction results at all prediction scales.

A theoretical study of the multigrid three-dimensional variational data assimilation scheme using a simple bilinear interpolation algorithm

In order to solve the so-called ＂bull-eye＂ problem caused by using a simple bilinear interpolation as an observational mapping operator in the cost function in the multigrid three-dimensional variational （3DVAR） data assimilation scheme, a smoothing term, equivalent to a penalty term, is introduced into the cost function to serve as a means of troubleshooting. A theoretical analysis is first performed to figure out what on earth results in the issue of ＂bull-eye＂, and then the meaning of such smoothing term is elucidated and the uniqueness of solution of the multigrid 3DVAR with the smoothing term added is discussed through the theoretical deduction for one-dimensional （1D） case, and two idealized data assimilation experiments （one- and two-dimensional （2D） cases）. By exploring the relationship between the smoothing term and the recursive filter theoretically and practically, it is revealed why satisfied analysis results can be achieved by using such proposed solution for the issue of the multigrid 3DVAR.

Design and Realization of Block Level Augmented Reality Three-Dimensional Map

In response to the construction needs of “Real 3D China”, the system structure, functional framework, application direction and product form of block level augmented reality three-dimensional map is designed. Those provide references and ideas for the later large-scale production of augmented reality three-dimensional map. The augmented reality three-dimensional map is produced based on skyline software. Including the map browsing, measurement and analysis and so on, the basic function of three-dimensional map is realized. The special functional module including housing management, pipeline management and so on is developed combining the need of residential quarters development, that expands the application fields of augmented reality three-dimensional map. Those lay the groundwork for the application of augmented reality three-dimensional map. .

VISUALIZATION OF THREE-DIMENSIONAL DATA FIELD AND ITS APPLICATION IN MACHINE TESTING

In order to realize visualization of three-dimensional data field （TDDF） in instrument, two methods of visualization of TDDF and the usual manner of quick graphic and image processing are analyzed. And how to use OpenGL technique and the characteristic of analyzed data to construct a TDDF, the ways of reality processing and interactive processing are described. Then the medium geometric element and a related realistic model are constructed by means of the first algorithm. Models obtained for attaching the third dimension in three-dimensional data field are presented. An example for TDDF realization of machine measuring is provided. The analysis of resultant graphic indicates that the three-dimensional graphics built by the method developed is featured by good reality, fast processing and strong interaction

Integration system research and development for three-dimensional laser scanning information visualization in goaf

An integration processing system of three-dimensional laser scanning information visualization in goaf was developed. It is provided with multiple functions, such as laser scanning information management for goaf, cloud data de-noising optimization, construction, display and operation of three-dimensional model, model editing, profile generation, calculation of goaf volume and roof area, Boolean calculation among models and interaction with the third party soft ware. Concerning this system with a concise interface, plentiful data input/output interfaces, it is featured with high integration, simple and convenient operations of applications. According to practice, in addition to being well-adapted, this system is favorably reliable and stable.

Three-dimensional visualization interactive system for digital twin workshop

To improve the human-physical-virtual coordination and integration of the digital twin workshop,3D visual monitoring and human-computer interaction of the digital twin workshop was studied.First,a novel 6D model of the 3D visualization interactive system for digital twin workshops is proposed.As the traditional 5D digital twin model ignores the importance of human-computer interaction,a new dimension of the user terminal was added.A hierarchical real-time data-driven mapping model for the workshop production process is then proposed.Moreover,a real-time data acquisition method for the industrial Internet of things is proposed based on OPC UA(object linking and embedding for process control unified architecture).Based on the 6D model of the system,the process of creating a 3D visualization virtual environment based on virtual reality is introduced,in addition to a data-driven process based on the data management cloud platform.Finally,the 6D model of the system was confirmed using the blade rotor test workshop as the object,and a 3D visualization interactive system is developed.The results show that the system is more transparent,real-time,data-driven and more efficient,as well as promotes the coordination and integration of human-physical-virtual,which has practical significance for developing digital twin workshops.

Constructing Three-Dimension Space Graph for Outlier Detection Algorithms in Data Mining

Outlier detection has very important applied value in data mining literature. Different outlier detection algorithms based on distinct theories have different definitions and mining processes. The three-dimensional space graph for constructing applied algorithms and an improved GridOf algorithm were proposed in terms of analyzing the existing outlier detection algorithms from criterion and theory. Key words outlier - detection - three-dimensional space graph - data mining CLC number TP 311. 13 - TP 391 Foundation item: Supported by the National Natural Science Foundation of China (70371015)Biography: ZHANG Jing (1975-), female, Ph. D, lecturer, research direction: data mining and knowledge discovery.

Research on Testing System for Three-dimensional Distribution of Luminous Intensity of LED

In terms of asymmetrical three-dimensional distribution(ID) of luminous intensity(LI) of light-emitting-diode(LED),a testing system was conducted in this study. Design and principle of the testing system were introduced. 31 photometers were placed on a concentric circle,and all of them were used to gather LI data of LED at the same time. The data acquisition card(DAC) was used to gather multichannel data and controlled motor. Experimental results indicated that the testing system had achieved the goal of testing three-dimensional distribution of LI. And each parameter could meet the requirements of industrial production and measurement.

Research and Realization of Medical Image Fusion Based on Three-Dimensional Reconstruction

A new medical image fusion technique is presented.The method is based on three-dimensional reconstruction.After reconstruction,the three-dimensional volume data is normalized by three-dimensional coordinate conversion in the same way and intercepted through setting up cutting plane including anatomical structure,as a result two images in entire registration on space and geometry are obtained and the images are fused at last.Compared with traditional two-dimensional fusion technique,three-dimensional fusion technique can not only resolve the different problems existed in the two kinds of images,but also avoid the registration error of the two kinds of images when they have different scan and imaging parameter.The research proves this fusion technique is more exact and has no registration,so it is more adapt to arbitrary medical image fusion with different equipments.

3D simultaneous seismic data reconstruction and noise suppression based on the curvelet transform

Seismic data contain random noise interference and are affected by irregular subsampling. Presently, most of the data reconstruction methods are carried out separately from noise suppression. Moreover, most data reconstruction methods are not ideal for noisy data. In this paper, we choose the multiscale and multidirectional 2D curvelet transform to perform simultaneous data reconstruction and noise suppression of 3D seismic data. We introduce the POCS algorithm, the exponentially decreasing square root threshold, and soft threshold operator to interpolate the data at each time slice. A weighing strategy was introduced to reduce the reconstructed data noise. A 3D simultaneous data reconstruction and noise suppression method based on the curvelet transform was proposed. When compared with data reconstruction followed by denoizing and the Fourier transform, the proposed method is more robust and effective. The proposed method has important implications for data acquisition in complex areas and reconstructing missing traces.

计数型数据控制图:过去和未来趋势

计数型数据的应用涉及多种制造或服务过程,已引起学界和业界的高度重视.虽然相对计量型数据控制图而言,针对计数型数据控制图的研究较少,但是近二十年也有大量文献涌现.系统回顾和梳理计数型数据控制图的研究进展,以期能为学界和业界工作者提供理论全貌和实践指导.首先,回顾总结了一元计数型数据控制图的相关研究.然后,按照数据复杂程度逐步增加,先后梳理了多元计数型数据控制图、响应为计数型数据的轮廓控制图以及关联关系为计数型数据的网络控制图.最后,综合文献梳理结果,给出未来的研究方向.

基于GMM-Ada-LASSO模型的高维过程统计质量监控方法

针对高维数据往往不服从正态分布导致统计监控模型识别精度低、监控效率差的问题,文章提出一种基于高斯混合模型的变量选择控制图方法。首先,利用高斯混合模型将高维过程分解成若干个服从正态分布的子分布;然后,运用Adaptive LASSO算法识别潜在异常变量;最后,构建多元EWMA控制图实现高维过程统计质量监控。通过仿真实验,在六种不同情形下对所提方法的监控性能进行测试。结果表明,与传统MEW⁃MA和VS-MEWMA控制图相比,所提监控方法对非正态数据具有较强的稳健性,对高维过程具有良好的监控性能。

雅安地区监测井水位预测效能对比研究

为提高监测井水位映震效果的判别准确度并提升预测效能,本文运用不同方法对雅安地区两条断裂附近的6口监测井水位的映震效果开展了对比判别研究。首先,使用差分法对监测井水位数据进行处理和分析。然后,将水位数据与区域地震活动性的两种参数(能级和最大震级)相结合,分析区域地震活动性与水位波动的关系。接着,在时域和频域两个层面对该组合序列进行分析处理。最后,采用Molchan图表法检验5种方法的预测效能,并选出最佳处理方法及断裂附近预测效能最优的监测井。结果表明:水位与地震活动性参数结合处理相比单独使用水位差分法具有优势,前者能够准确排除地震活动性对水位异常的干扰。6口监测井的最优预测方法各不相同,最优预测天数均在60 d内。通过比较监测井水位对地震的预测效能检验结果,确定了两条断裂区域预测效能最优的监测井。虽然水位与地震活动性两种参数结合处理并不适用于所有监测井,但该方法能够体现水位受地震活动性影响的程度。

基于WinHex底层数据恢复的脚本研究与实践

对于被病毒破坏的文件,其数据被修改,目前市面上的数据恢复软件很难进行快速恢复,因此需要基于WinHex底层脚本进行数据恢复。对WinHex模拟文件损坏病毒和脚本病毒进行了分析,对病毒破坏文件的修复流程进行了深层次的研究,对WinHex脚本进行了详细的阐述,并对常见的WinHex脚本进行了实践研究。

基于不同控制图的GNSS异常数据检测方法研究

控制图是一种成熟的突变点检测方法,在全球卫星导航系统坐标序列异常数据检测中得到了广泛的应用。采用3种使用较为广泛的控制图,分别为累计和控制图、休哈特控制图以及指数加权移动平均控制图,通过在GNSS异常数据中加入不同倍数的标准差偏移量进行实验,并进行比较分析。结果表明,CUSUM控制图对于3倍以下标准差偏移量具有较高的准确性,其次是EWMA控制图,但CUSUM控制图最小只能检测到0.5倍的偏移值。对于3倍以上的标准差偏移量,Shewhart控制图和EWMA控制图有类似的效果,而CUSUM控制图会随着偏移量的增大而导致误判的增大。

基于机车运行轨迹的机车调度管理系统设计与应用

为解决机车调度员不能实时准确掌握机车运用情况的问题,设计研发一套基于机车运行轨迹的精细化机车调度管理系统。围绕机车交路、检修、整备等机车运用业务,通过对多源数据进行采集、校验,以及建立机车全生命周期的运行轨迹等技术,实现机车运行轨迹自动生成、周转图自动绘制、机车分布自动推算、超劳预警及机车运用自动统计等功能。应用表明,该系统提高了机车运用效率,为提升铁路运输生产力提供了技术支撑。

基于Web的交互式图表应用于数据分析的研究

本文阐述基于Web的交互式图表应用于数据分析的研究,将HTML5新标准的优势转化为教师平日工作的动能,帮助教师提升工作效率,减轻数据分析工作量。利用该系统可以绘制多样灵动的交互式图表并设计丰富的功能,帮助教师解决日常工作中遇到的数据分析问题,绘制统计图,进行对比分析,从而得到文字统计无法直观反映的数据结果。

JFreeChart在金融数据统计与分析中的应用

阐述了JFreeChart组成及其基本功能,以开发某公司2007年度市场销售数据柱状图为例给出了基于JFreeChart组件进行开发的基本步骤,并给出了部分相关代码,实例应用表明,利用JFreeChart生成图表步骤简洁,可生成类型丰富的专业图表.

An unmanned ground vehicle phenotyping-based method to generate three-dimensional multispectral point clouds for deciphering spatial heterogeneity in plant traits

Fusing three-dimensional(3D)and multispectral(MS)imaging data holds promise for high-throughput and comprehensive plant phenotyping to decipher genome-to-phenome knowledge.Acquiring high-quality 3D MS point clouds(3DMPCs)of plants remains challenging because of poor 3D data quality and limited radiometric calibration methods for plants with a complex canopy structure.Here,we present a novel 3D spatial–spectral data fusion approach to collect high-quality 3DMPCs of plants by integrating the next-best-view planning for adaptive data acquisition and neural reference field(NeREF)for radiometric calibration.This approach was used to acquire 3DMPCs of perilla,tomato,and rapeseed plants with diverse plant architecture and leaf morphological features evaluated by the accuracy of chlorophyll content and equivalent water thickness(EWT)estimation.The results showed that the completeness of plant point clouds collected by this approach was improved by an average of 23.6%compared with the fixed viewpoints alone.The NeREF-based radiometric calibration with the hemispherical reference outperformed the conventional calibration method by reducing the root mean square error(RMSE)of 58.93%for extracted reflectance spectra.The RMSE for chlorophyll content and EWT predictions decreased by 21.25%and 14.13%using partial least squares regression with the generated 3DMPCs.Collectively,our study provides an effective and efficient way to collect high-quality 3DMPCs of plants under natural light conditions,which improves the accuracy and comprehensiveness of phenotyping plant morphological and physiological traits,and thus will facilitate plant biology and genetic studies as well as crop breeding.

A multi-scale second-order autoregressive recursive filter approach for the sea ice concentration analysis

To effectively extract multi-scale information from observation data and improve computational efficiency,a multi-scale second-order autoregressive recursive filter(MSRF)method is designed.The second-order autoregressive filter used in this study has been attempted to replace the traditional first-order recursive filter used in spatial multi-scale recursive filter(SMRF)method.The experimental results indicate that the MSRF scheme successfully extracts various scale information resolved by observations.Moreover,compared with the SMRF scheme,the MSRF scheme improves computational accuracy and efficiency to some extent.The MSRF scheme can not only propagate to a longer distance without the attenuation of innovation,but also reduce the mean absolute deviation between the reconstructed sea ice concentration results and observations reduced by about 3.2%compared to the SMRF scheme.On the other hand,compared with traditional first-order recursive filters using in the SMRF scheme that multiple filters are executed,the MSRF scheme only needs to perform two filter processes in one iteration,greatly improving filtering efficiency.In the two-dimensional experiment of sea ice concentration,the calculation time of the MSRF scheme is only 1/7 of that of SMRF scheme.This means that the MSRF scheme can achieve better performance with less computational cost,which is of great significance for further application in real-time ocean or sea ice data assimilation systems in the future.