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.

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.

基于Bullet物理引擎的机器人仿真实验平台设计

为适应新时代工业机器人实验教学的蓬勃发展,设计了一种基于Bullet物理引擎的机器人仿真实验平台。该平台使用Bullet作为仿真引擎,具备运动学解算、碰撞检测与轨迹可视化的功能,使用Lua脚本作为主逻辑控制语言,调用仿真引擎功能函数。使用基于数据流的节点图作为主实验交互平台,将计算模块和通信模块封装为功能节点,通过图形连接定义运算逻辑。应用实例表明,该平台功能完善,可扩展性强,兼具脚本语言的灵活性与图形化语言的便捷性,适用于机器人的多种实验场景。

Application of oblique photogrammetry technique in geological hazard identification and decision management

With the continuous development of the oblique photography technique, it has been used more and more widely in the field of geological disasters. It can quickly obtain the three-dimensional(3D) real scene model of dangerous mountainous areas under the premise of ensuring the safety of personnel while restoring the real geographic information as much as possible. However, geological disaster areas are often accompanied by many adverse factors such as cliffs and dense vegetation. Based on this, the paper introduced the flight line design of oblique photogrammetry, analyzed the multi-platform data fusion processing, studied the multi-period data dynamic evaluation technology and proposed the application methods of data acquisition, early warning, disaster assessment and decision management suitable for geological disaster identification through the analysis of actual cases, which will help geologists to plan and control geological work more scientifically and rationally, improve work efficiency and reduce the potential personnel safety hazards in the process of geological survey, to offer technical support to the application of oblique photogrammetry in geological disaster identification and decision making and provide the scientific basis for personal and property safety protection and later-stage geological disaster management in disaster areas.

An Analysis of Policy Ecology of Scientific Data under the Dual Three-dimensional Framework

The analysis of the current big data policy for scientific research can promote the ecological optimization of big data policy,and is a positive response to the national big data strategy.This paper constructs a“dual three-dimensional framework”to analyze the central and local science data policies from 2013 to 2022.With the dissemination and popularization of the concept of scientific data sharing,policies and regulations related to scientific data management have been issued,which promotes the emergence of scientific data policy ecology.The scientific data policy ecology is a complex and multicollaborative dynamic system composed of policy text,policy environment and related personnel,the core of which lies in the policy itself,aiming to ensure the security of scientific data and promote the development of science.There are the following problems in the scientific data policy ecology:In terms of policy text,the policy effectiveness is low and the use of policy tools is uneven.In terms of relevant personnel,the cooperation network density among various subjects is low and there is a lack of highquality talents.In terms of policy environment,there is an imbalance of regional funding support.It also puts forward some optimization strategies,such as strengthening the systematization of policy texts,improving the degree of coordination of policy subjects to form a long-term cooperation network,and improving the degree of compatibility between environment,personnel and policies.

Evaluation of Two Momentum Control Variable Schemes and Their Impact on the Variational Assimilation of Radar Wind Data:Case Study of a Squall Line

Different choices of control variables in variational assimilation can bring about different influences on the analyzed atmospheric state. Based on the WRF model＇s three-dimensional variational assimilation system, this study compares the be- havior of two momentum control variable options-streamfunction velocity potential （ψ-χ） and horizontal wind components （U-V）-in radar wind data assimilation for a squall line case that occurred in Jiangsu Province on 24 August 2014. The wind increment from the single observation test shows that the ψ-χ control variable scheme produces negative increments in the neighborhood around the observation point because streamfunction and velocity potential preserve integrals of velocity. On the contrary, the U-V control variable scheme objectively reflects the information of the observation itself. Furthermore, radial velocity data from 17 Doppler radars in eastern China are assimilated. As compared to the impact of conventional observation, the assimilation of radar radial velocity based on the U-V control variable scheme significantly improves the mesoscale dynamic field in the initial condition. The enhanced low-level jet stream, water vapor convergence and low-level wind shear result in better squall line forecasting. However, the ψ-χ control variable scheme generates a discontinuous wind field and unrealistic convergence/divergence in the analyzed field, which lead to a degraded precipitation forecast.

Impacts of XBT,TAO,Altimetry and ARGO Observations on the Tropical Pacific Ocean Data Assimilation

This study aims at assessing the relative impacts of four major components of the tropical Pacific Ocean observing system on assimilation of temperature and salinity fields. Observations were collected over a period between January 2001 through June 2003 including temperature data from the expendable bathythermographs （XBT）, thermistor data from the Tropical Ocean Global Atmosphere Tropical Atmosphere-Ocean （TOGA-TAO） mooring array, sea level anomalies from the Topex/Poseidon and Jason-1 altimetry （T/P-J）, and temperature and salinity profiles from the Array for Real-time Geostrophic Oceanography （ARGO） floats. An efficient three-dimensional variational analysis-based method was introduced to assimilate the above data into the tropical-Pacific circulation model. To evaluate the impact of the individual component of the observing system, four observation system experiments were carried out. The experiment that assimilated all four components of the observing system was taken as the reference. The other three experiments were implemented by withholding one of the four components. Results show that the spatial distribution of the data influences its relative contribution. XBT observations produce the most distinguished effects on temperature analyses in the off-equatorial region due to the large amount of measurements and high quality. Similarly, the impact of TAO is dominant in the equatorial region due to the focus of the spatial distribution. The Topex/Poseidon-Jason-1 can be highly complementary where the XBT and TAO observations are sparse. The contribution of XBT or TAO on the assimilated salinity is made by the model dynamics because no salinity observations from them are assimilated. Therefore, T/P-J, as a main source for providing salinity data, has been shown to have greater impacts than either XBT or TAO on the salinity analysis. Although ARGO includes the subsurface observations, the relatively smaller number of observation makes it have the smallest contribution to the assimilation system.

Research and application on integration modeling of 3D bodies in coal mine with blended data model based on TIN and ARTP

Data modeling is the foundation of three-dimensional visualization technology. First the paper proposed the 3D integrated data model of stratum, laneway and drill on the basic of TIN and ARTP, and designed the relevant conceptual and logical model from the view of data model, and described the data structure of geometric elements of the model by adopting the object-oriented modeling idea. And then studied the key modeling technology of stratum, laneway and drill, introduced the ARTP modeling process of stratum, laneway and drill and studied the 3D geometric modeling process of different section laneways. At last, the paper realized the three-dimensional visualization system professionally coalmine-oriented, using SQL Server as background database, Visual C＋＋6.0 and OpenGL as foreground development tools.

A novel trilinear decomposition algorithm:Three-dimension non-negative matrix factorization

Non-negative matrix factorization （NMF） is a technique for dimensionality reduction by placing non-negativity constraints on the matrix. Based on the PARAFAC model, NMF was extended for three-dimension data decomposition. The three-dimension nonnegative matrix factorization （NMF3） algorithm, which was concise and easy to implement, was given in this paper. The NMF3 algorithm implementation was based on elements but not on vectors. It could decompose a data array directly without unfolding, which was not similar to that the traditional algorithms do, It has been applied to the simulated data array decomposition and obtained reasonable results. It showed that NMF3 could be introduced for curve resolution in chemometrics.

An Improved Data Exchange Method Between Pro/E and ADAMS

According to the question of how to transfer data between Pro/E and ADAMS correctly, the paper gives an improved importing solution, which combines the interface and the Standard Data Format（SDF） files. It settles the problems caused by improper geometry during the import conducted by the interface software. With the solution ,fea- ture points can be conveniently picked to build kinematic constraints are the preparation of the model will be simpli- fied. An example is given for the method, and corresponding simulations are conducted. The results of the simula- tions verify the validity of the solution.

枪用计数器的加速度感应开关仿真

枪支射击时,需要对其射弹数量进行统计,但是现有的统计方式大多还停留在手工阶段,因此需要一种能自动计数的枪用计数器;使用计数器完成枪支射击次数统计,既能帮助射手评估枪支的剩余寿命,也能防止射手私自截留子弹,对提高武器保养质量、提升靶场枪弹智能管理效率具有重要价值;结合自动步枪的结构特点以及枪械射击时有两次较大的向后冲击的特征,根据机械振动感应识别技术来统计枪支的击发弹药次数,设计了一种惯性式加速度感应开关,将前两较大加速度值的160 g, 70 g作为电路导通的加速度阈值;通过测试工装发现其单发和连发的采集的信号可以满足要求;通过Adams动力学仿真,对加速度感应开关进行动态响应分析,发现加速度感应开关能够有效的提取出枪支射击时的特征;通过Ansys有限元分析,对加速度感应开关的结构强度进行了校核,选用的材料均满足强度要求;通过实弹射击检验其计数的准确率,现场一共发射630发子弹,一共可靠记录了627次射击动作,总的计数准确率为99.5%,可以满足日常的使用要求。