基于非结构化三角网格的海洋标量数据可视化研究

海洋总体规模庞大,海洋数据具有多源、异构、多维度、多格式、多尺度等特点,如何准确使用数据场精确表达某一环境的时空分布显得尤为重要。为了实现非结构化三角网格数据的可视化,论文采用B/S(浏览器/服务器)架构,设计基于Cesium(开源三维地球框架)的海洋标量数据可视化系统。针对非结构化三角网格数据,提出用无监督分箱的方法进行类别的划分,构建可视化映射标准。用OpenGL图形接口绘制不同的海洋标量要素可视化,对其系统的整体架构、功能和应用进行了详细的阐述:采用三角网格面积基元的可视化方法,利用转换坐标系和无监督聚类分析方法处理数据,并结合层次细节技术和直方图均衡化思想优化可视化效果。论文实验结果表明,该系统对大规模的非结构化三角网格数据有着良好的显示效果。

网络环境下海洋标量场数据三维可视化研究

为了实现多种海洋标量数据在网络环境下的三维可视化,设计基于开源三维地球框架Cesium的海洋标量场数据可视化系统,三维数据可视化系统采用B/S架构。文中对系统整体架构和功能设计进行详细阐述:系统采用瓦片思想,运用层次细节和数据动态调度方法优化数据可视化效果;系统实现数据的时间过程动态可视化、要素点属性查询和点过程曲线查询等功能。实验结果表明,该系统框架方法具有可行性,可在海洋环境分析中起到一定辅助作用。

基于全息时标量测数据挖掘的配电网设备健康状态诊断分析

大数据、数据挖掘等新技术的出现和进步,为建设智能配电网提供了新的技术手段;为实现对配电网运行状态的真实还原、精细分析和精准预测,详实有效的配电网设备运行数据记录和支撑是关键,研究了配电网全息时标量测数据的变化即存储技术,基于全息时标量测数据研究了配电网设备健康状态诊断的方法,对配电网历史数据以及模型信息等进行了深入的数据挖掘,通过聚类分析、线性回归算法、熵权法等建立了设备状态诊断模型和评价体系,实现了对设备故障评估和预警分析等,为及时发现配电网的薄弱环节,保障配电网设备的安全稳定运行提供了有效手段;系统已在地市供电公司的配电网诊断方法研究与实现项目中得到实际应用,很好地满足了地市供电公司的配电网精益化管理需求。

多源异构电网运行时标量测数据接入方案设计

海量准实时数据服务平台是电网运行时标量测数据集中存储的场所;为了满足电网调度自动化、计量自动化等电网运行数据的接入需求,提出一种多源异构电网运行时标量测数据接入方案;该方案综合采用关系数据库和实时数据库存储数据,结合实时数据库存储数据的测点特性定义了电网时标量测数据存储命名规范,通过配置服务实现数据接入任务的启停控制和运行状态监控,使用接入调度器调度接入插件执行接入任务并引入主备冗余技术保证调度器的高可用;方案引入组件化程序设计思想,通过可插拔、易扩展的插件设计满足多源异构数据的接入需求;方案在南方电网公司海量准实时数据服务平台建设项目中得到实际应用,很好地满足了南方电网运行时标量测数据的接入需求。

大规模数据场的并行可视化

大规模数据场的并行可视化一直是科学计算可视化中极具挑战性的一个研究领域 .本文介绍了我们设计与实现的一个面向大规模工程计算的小型并行可视化系统 ,该系统采用了场特征分析技术来提高可视化的质量 .可支持计算和可视化在计算服务器上同时进行 ,并可将可视化结果——可视的图形元素简化后输出到用户端进行显示 .为用户提供了大量的并行可视化算法 ,其中一些是其它商品化软件所未包括的 。

连续框架下二维标量场Morse-Smale复形分割

挖掘拓扑结构是获取数据场关键信息的有效途径,Morse-Smale(MS)复形是二维标量场重要拓扑结构,传统方法均采用分片线性模型,利用离散Morse理论进行MS复形分割,精度较低,积分曲线呈锯齿状,特征冗余信息多,需经过烦琐的删减过程才能得到可用结果.为此提出连续框架下的二维标量场数据MS复形分割的方法.首先为二维标量场数据建立double ZP样条拟插值连续模型;然后利用连续Morse理论,在连续模型上提取临界点、精确计算Hessian矩阵对临界点分类;最后通过精确计算梯度信息构建积分曲线完成MS复形分割.本文采用的double ZP样条具有高阶连续性,满足连续Morse理论至少C2连续的条件,具有数学完备性,其上的各阶微分运算都是精确的,因此能保证提取高精度的特征点、有严格的分类标准和光滑的积分曲线,不需要大量的后处理过程.实验结果表明,与离散框架下的方法相比,该方法流程简单,能得到高精度、平滑性好的MS复形分割结果,能更清晰地呈现数据场蕴含的关键特征结构.

基于多维传输函数的三维医学图像系统研究

传输函数是直接体绘制的基础,传输函数的设计是体视化结果的关键。本文在传输函数的定义上,讨论了将体数据标量值和梯度模值作为定义域的多维传输函数的原理及实现方法。针对传输函数与位置无关,难以提取感兴趣的区域(Region Of Interest简称ROI),提出了基于三切面交互式体数据的切割方法,从而有效的提取感兴趣区域。最后,设计和实现了一个基于多维传输函数的三维医学图像系统,获得了很好的体绘制效果。

高风险隧道施工安全预警管理系统研制与应用

针对高风险隧道施工安全存在的诸多难点,以中川铁路九合二号高风险隧道施工安全管理为平台,应用信息技术和隧道模型仿真技术搭建高风险隧道施工安全预警管理系统,实现隧道的"可视化建造"和"安全风险的可视化预警管理"。在实际应用中,通过地质勘探报告、超前地质预报、监控量测数据的指标化存取和量化分析,融合风险评估报告、现场异常报告、专家远程支持等资源构建风险识别的参数化模型。系统具备开放性工程项目资料管理、多媒体隧道工程知识库等相关的应用性、扩展性和推广性功能。

Full tensor gravity gradiometry data inversion:Performance analysis of parallel computing algorithms

We apply reweighted inversion focusing to full tensor gravity gradiometry data using message-passing interface （MPI） and compute unified device architecture （CUDA） parallel computing algorithms, and then combine MPI with CUDA to formulate a hybrid algorithm. Parallel computing performance metrics are introduced to analyze and compare the performance of the algorithms. We summarize the rules for the performance evaluation of parallel algorithms. We use model and real data from the Vinton salt dome to test the algorithms. We find good match between model efficiency and feasibility of parallel computing gravity gradiometry data. and real density data, and verify the high algorithms in the inversion of full tensor

On Measuring the Privacy of Anonymized Data in Multiparty Network Data Sharing

This paper aims to find a practical way of quantitatively representing the privacy of network data. A method of quantifying the privacy of network data anonymization based on similarity distance and entropy in the scenario involving multiparty network data sharing with Trusted Third Party (TTP) is proposed. Simulations are then conducted using network data from different sources, and show that the measurement indicators defined in this paper can adequately quantify the privacy of the network. In particular, it can indicate the effect of the auxiliary information of the adversary on privacy.

Evaluation of wind vectors observed by HY-2A scatterometer using ocean buoy observations,ASCAT measurements,and numerical model data

The first Chinese microwave ocean environment satellite HY-2A was launched successfully in August, 201 I. This study presents a quality assessment of HY-2A scatterometer （HYSCAT） data based on comparison with ocean buoy data, the Advanced Scatterometer （ASCAT） data, and numerical model data from the National Centers for Environmental Prediction （NCEP）. The in-situ observations include those from buoy arrays operated by the National Data Buoy Center （NDBC） and Tropical Atmosphere Ocean （TAO） project. Only buoys located offshore and in deep water were analyzed. The temporal and spatial collocation windows between HYSCAT data and buoy observations were 30 min and 25 km, respectively. The comparisons showed that the wind speeds and directions observed by HYSCAT agree well with the buoy data. The root-mean-squared errors （RMSEs） of wind speed and direction for the HYSCAT standard wind products are 1.90 m/s and 22.80°, respectively. For the HYSCAT-ASCAT comparison, the temporal and spatial differences were limited to 1 h and 25 km, respectively. This comparison yielded RMSEs of 1.68 m/s for wind speed and 19.1° for wind direction. We also compared HYSCAT winds with reanalysis data from NCEP. The results show that the RMSEs of wind speed and direction are 2.6 m/s and 26°, respectively. The global distribution of wind speed residuals （HYSCAT-NCEP） is also presented here for evaluation of the HYSCAT-retrieved wind field globally. Considering the large temporal and spatial differences of the collocated data, it is concluded that the HYSCAT-retrieved wind speed and direction met the mission requirements, which were 2 rn/s and 20° for wind speeds in the range 2-24 m/s. These encouraging assessment results show that the wind data obtained from HYSCAT will be useful for the scientific community.

Calculation of Significant Wave Height Using the Linear Mean Square Estimation Method

Significant wave height is an important criterion in designing coastal and offshore structures.Based on the orthogonality principle, the linear mean square estimation method is applied to calculate significant wave height in this paper.Twenty-eight-year time series of wave data collected from three ocean buoys near San Francisco along the California coast are analyzed.It is proved theoretically that the computation error will be reduced by using as many measured data as possible for the calculation of significant wave height.Measured significant wave height at one buoy location is compared with the calculated value based on the data from two other adjacent buoys.The results indicate that the linear mean square estimation method can be well applied to the calculation and prediction of significant wave height in coastal regions.

Block-based test data adequacy measurement criteria and test complexity metrics

On the basis of software testing tools we developed for programming languages, we firstly present a new control flowgraph model based on block. In view of the notion of block, we extend the traditional program\|based software test data adequacy measurement criteria, and empirically analyze the subsume relation between these measurement criteria. Then, we define four test complexity metrics based on block. They are J\|complexity 0; J\|complexity 1; J\|complexity \{1+\}; J\|complexity 2. Finally, we show the Kiviat diagram that makes software quality visible.

Relationship between Seed Yield and Yield Chracteristics in Faba Bean （Vicia faba L.） by GGE-Biplot Analysis

Viciafaba L. was domesticated around 8000 BC in the Near East; the crop spread to Central Europe and Russia through Anatolia, the Danube Valley and the Caucasus; to Eastern Mediterranean regions through the Mediterranean coast and the Isles; from Egypt and Arabian Coast （the Arabia Felix） to Abyssinia; through Mesopotamia to India and China probably during the first millennium AD （only land races of major type, the latest in being produced, were known in China until recently）. Faba bean （Vicia faba L.） is grown world-wide as a protein source for food and feed. The importance of nutzients （micro and macro） for human growth is universally recognized. An investigation was camed out to select the most successful faba bean genotypes to estimate for seed yield and some of agro-morphological traits. Effective interpretation of the dataon breeding programes is important at all stages of plant improvment. The GT （genotype by trait） was used for two-way faba bean genotypes with multiple traits. For this purpose, six faba bean genotypes with specific components were tested and the GT biplot for genotype data explained 83% of total variation of the standardized data. The polygon view of GT presented for five traits of faba bean genotypes showed three vertex genotypes as Goryaka, Karcacaoglan and Seher. Genotype G0ryaka had the highest values for most of the traits. It was demonstzaited that the selection of high seed yield will be via hundred seed weight and planth height. These traits should be considered meanwhile as effective selection criteria developing high yielding faba bean genotypes because of their large contibution to grain yield. The genotypes Goryaka and Karacaoglan could be well-considered for improving of desirable candidate in selection of improvement studies.

OceanRoute: Vessel Mobility Data Processing and Analyzing Model Based on MapReduce

The network coverage is a big problem in ocean communication, and there is no low-cost solution in the short term. Based on the knowledge of Mobile Delay Tolerant Network(MDTN), the mobility of vessels can create the chances of end-to-end communication. The mobility pattern of vessel is one of the key metrics on ocean MDTN network. Because of the high cost, few experiments have focused on research of vessel mobility pattern for the moment. In this paper, we study the traces of more than 4000 fishing and freight vessels. Firstly, to solve the data noise and sparsity problem, we design two algorithms to filter the noise and complement the missing data based on the vessel's turning feature. Secondly, after studying the traces of vessels, we observe that the vessel's traces are confined by invisible boundary. Thirdly, through defining the distance between traces, we design MR-Similarity algorithm to find the mobility pattern of vessels. Finally, we realize our algorithm on cluster and evaluate the performance and accuracy. Our results can provide the guidelines on design of data routing protocols on ocean MDTN.

Anisotropic inflation with general potentials

Anomalies in recent observational data indicate that there might be some "anisotropic hair" generated in an inflation period. To obtain general information about the effects of this anisotropic hair to inflation models, we studied anisotropic inflation models that involve one vector and one scalar using several types of potentials. We determined the general relationship between the degree of anisotropy and the fraction of the vector and scalar fields, and concluded that the anisotropies behave independently of the potentials. We also generalized our study to the case of multi-directional anisotropies.

An Isoratio Method and an Isoratio Scaling Phenomenon in Heavy-Ion Collisions

An isoratio method is proposed to study the chemical potential of neutrons(protons) from the yield ratio of isotopes(isotones) differing in neutron-excess(I = N- Z). The measured fragments in the 140 A MeV ^(40),^(48) Ca and^(58),^(64) Ni +~9Be reactions, as well as those in the simulated^(58),^(64) Ni +~9Be reactions by using the antisymmetric molecular dynamics(AMD) model plus the secondary decay model gemini, have been adopted to perform the isoratio analysis.The results of the isoratio method verify that they are similar to that of the well known isoscaling method. The isoratio scaling phenomenon suggested by the isoratio method has also been found in the measured data and the fragments simulated by the AMD + gemini models.