中国海岸带及近海观测数据多维动态表达

基本表达是海洋地理信息系统(MGIS)的首要问题.针对海洋实测数据多源、多格式以及海量等特点,基于大型关系数据库Oracle9i,实现了数据一体化高效组织和管理.基于OCI应用程序接口,设计并开发数据库引擎,实现了数据的高效存储和访问.基于COM技术,开发了CMa3DView等7大可视化组件,并在海洋GIS系统平台软件MaX-plorer中进行集成,实现了海洋实测数据的多维动态表达与分析,包括海洋要素场可视化、海洋要素图可视化以及与其他海洋数据的一体化显示.实际应用表明,本技术方法能有效管理海量实测数据,并能更直观地表达各种复杂的海洋现象,从而为海洋科研工作者揭示抽象数据变化规律以及理解、分析各种复杂海洋现象,提供强有力的辅助工具

A STUDY ON THE MULTI-STRATEGY-BASED INTEGRATION OF POLAR REMOTE SENSING INVERSION MODEL

极地遥感反演模型是极地研究的一种非常重要的工具。遥感反演模型对极地研究具有重要性,分析遥感反演模型的特点,以持续性、业务化、统一调用为目标,提出极地遥感反演模型集成应用架构。基于该集成方案,提出基于多策略的模型改造方法,并从三个方面详细论述模型的集成模式。基于可执行程序的模型改造方法对模型进行改造,采用应用端的模型集成模式构建极地遥感反演模型集成原型系统,通过海冰密集度反演模型验证本研究提出的模型集成方法的正确性。

最优分割尺度下的多层次遥感地物分类实验分析

为了快速、准确地提取我国海岸带地区土地利用及其变化信息,选择高分辨率遥感影像作为数据源,提出了最优分割尺度下的遥感多层次地物识别分类方法。首先,通过改进的局部方差法进行最优分割尺度的确定,建立影像中各对象的方差均值与变化率随分割尺度变化曲线,确定方差均值的峰值,以变化率开始呈现下降趋势时所对应的分割值为最优分割尺度参考;然后,针对地物分类特征差异选取各自适宜的分割尺度,建立多层次地物特征表达与规则,最后,实现最优尺度分割选择下的遥感多层次识别分类,即实现较大尺度下分割形成父对象,而较小尺度下分割出其若干子对象的目标,提出了快速、自动化获取土地利用/覆盖图的策略流程。本文选取了广东省珠海市海岸带地区作为实验区,利用多层次遥感分类方法进行地物识别分类。结果表明,其目视效果以及总体精度、Kappa系数,均优于传统方法和单一分割尺度下的影像分类方法

2.45GHz单电荷态电子回旋共振离子源

描述了一台 2 .4 5GHz单电荷态电子回旋共振 (ECR)离子源的原理、结构与应用。介绍了其微波系统与磁场结构。在微波输入功率约 6 0 0W ,引出高压 2 2kV ,引出孔径为6mm时 ,该离子源的总束流I(H1++H2 ++H3+)可达 90mA

JUNO Sensitivity on Proton Decay p→νˉK+p\to \bar\nu K^+ Searches

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this paper, the potential on searching for proton decay in $p\to \bar\nu K^+$ mode with JUNO is investigated.The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits to suppress the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar\nu K^+$ is 36.9% with a background level of 0.2 events after 10 years of data taking. The estimated sensitivity based on 200 kton-years exposure is $9.6 \times 10^{33}$ years, competitive with the current best limits on the proton lifetime in this channel

JUNO sensitivity on proton decay p → ν K + searches*

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this study, the potential of searching for proton decay in the $p\to \bar{\nu} K^+$ mode with JUNO is investigated. The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits suppression of the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar{\nu} K^+$ is 36.9% ± 4.9% with a background level of $0.2\pm 0.05({\rm syst})\pm$$0.2({\rm stat})$ events after 10 years of data collection. The estimated sensitivity based on 200 kton-years of exposure is $9.6 \times 10^{33}$ years, which is competitive with the current best limits on the proton lifetime in this channel and complements the use of different detection technologies