如何运用微博发展电视新闻

利用微博发布新闻已成为当今社会信息发布的一个平台,由于微博新闻有着信息短小、快捷、图片资料真实,话语权公开可信,与政府、媒体沟通及时,迅速等特点,利用微博发展电视新闻,愈来愈受到各主流媒体的重视.通过运用微博发展电视新闻的阐述,不仅进一步确立了电视新闻的主流媒体地位,而且会拥有巨大的发展空间和庞大的受众.     

大学英语大班教学方法探索

大班教学已是我国大学英语公共外语教学的普遍形式,而班级规模的扩大给英语教学带来了许多新的问题。为了培养合格的英语人才,适应新形势下社会的需求,详细地、有针对性地做了一系列研究,提出解决的对策和建议。     

Chang’E-1 precision orbit determination and lunar gravity field solution

In this paper we present results assessing the role of Very Long Baseline Interferometry (VLBI) tracking data through precision orbit determination (POD) during the check-out phase for Chang’E-1, and the lunar gravity field solution CEGM-01 based on the orbital tracking data acquired during the nominal phase of the mission. The POD of Chang’E-1 is performed using S-band two-way Range and Range Rate (R&RR) data, together with VLBI delay and delay rate observations. The role of the VLBI data in the POD of Chang’E-1 is analyzed, and the resulting orbital accuracies are estimated for different solution strategies. The final orbital accuracies proved that the VLBI tracking data can improve the Chang’E-1 POD significantly. Consequently, CEGM-01 based on six-month tracking data during Chang’E-1 nominal mission phase is presented, and the accuracy of the model is assessed by means of the gravity field power spectrum, admittance and coherence between gravity and topography, lunar surface gravity anomaly and POD for both Chang’E-1 and Lunar Prospector (LP). Our analysis indicates that CEGM-01 has significant improvements over a prior model (i.e. GLGM-2), and shows the potential of Chang’E-1 tracking data in high resolution lunar gravity field model solution by combining with SELENE and LP tracking data.     

Near lossless data compression onboard a hyperspectral satellite

To deal with the large volume of data produced by hyperspectral sensors, the Canadian Space Agency (CSA) has developed and patented two near lossless data compression algorithms for use onboard a hyperspectral satellite: successive approximation multi-stage vector quantization (SAMVQ) and hierarchical self-organizing cluster vector quantization (HSOCVQ). This paper describes the two compression algorithms and demonstrates their near lossless feature. The compression error introduced by the two compression algorithms was compared with the intrinsic noise of the original data that is caused by the instrument noise and other noise sources such as calibration and atmospheric correction errors. The experimental results showed that the compression error was not larger than the intrinsic noise of the original data when a test data set was compressed at a compression ratio of 20:1. The overall noise in the reconstructed data that contains both the intrinsic noise and the compression error is even smaller than the intrinsic noise when the data is compressed using SAMVQ. A multi-disciplinary user acceptability study has been carried out in order to evaluate the impact of the two compression algorithms on hyperspectral data applications. This paper briefly summarizes the evaluation results of the user acceptability study. A prototype hardware compressor that implements the two compression algorithms has been built using field programmable gate arrays (FPGAs) and benchmarked. The compression ratio and fidelity achieved by the hardware compressor are similar to those obtained by software simulation     

SPATIAL REGULARIZATION OF CANONICAL CORRELATION ANALYSIS FOR LOW-RESOLUTION FACE RECOGNITION

Canonical correlation analysis ( CCA ) based methods for low-resolution ( LR ) face recognition involve face images with different resolutions ( or multi-resolutions ), i.e.LR and high-resolution ( HR ) .For single-resolution face recognition , researchers have shown that utilizing spatial information is beneficial to improving the recognition accuracy , mainly because the pixels of each face are not independent but spatially correlated.However , for a multi-resolution scenario , there are no related works.Therefore , a method named spatial regularization of canonical correlation analysis ( SRCCA ) is developed for LR face recognition to improve the performance of CCA by the regularization utilizing spatial information of different resolution faces.Furthermore , the impact of LR and HR spatial regularization terms on LR face recognition is analyzed through experiments.     

薄膜反射面结构新型折展方案设计

基于薄膜结构模拟方式的对比分析,选用VUMAT子程序修改了考虑褶皱问题的膜单元的本构关系,解决了膜单元不能承受压应力的问题。采用三维数字图像相关（3D-DIC）方法对聚酰亚胺薄膜材料进行性能测试,试验表明带折痕的薄膜材料的等效模量比无折痕的薄膜材料低15%左右。在考虑折痕弹性模量差异的基础上采用显式计算方法对Miura折纸的展开过程进行了仿真,并基于平面度和最大应力2个指标对不同数量加载点的情况进行了对比,结果表明,加载点数量增多对结构的平面度和最大应力指标均是有利的。最后,基于薄膜结构找形和Miura折纸概念提出一种新的薄膜折叠方案。     

飞翼式客机机翼气动/结构综合优化方法研究

针对目前在飞翼客机机翼优化过程中对气动弹性效应考虑不充分、气动/结构耦合不充分的问题,分别对飞翼客机机翼的CFD（Computational Fluid Dynamics,简称CFD）气动模型、平板气动模型和三维板杆模型进行参数化建模,开展了针对飞翼布局客机机翼的气动/结构综合优化设计的研究,搭建了一套基于Kriging模型的前瞻性设计方法,获得了机翼最优的气动外形和结构构型,在有效降低机翼结构重量的同时,显著地减少了气动阻力。在满足精度及效率的前提下,气动子学科选用亚声速偶极子格网法以及基于Euler方程的CFD方法,结构子学科选用有限元分析方法,优化算法采用遗传算法。     

航天器电缆网快速协同设计方法及关键技术

以航天器电缆网传统研制模式的局限性为出发点,提出了电缆网全息模型的概念及其通用模型体系,实现了包含全要素设计信息的完整产品数字化定义;基于先"修路"后布线的设计理念,系统地提出了导航式电缆网快速协同设计方法及其相关算法,建立了航天器整器级统一的电缆网络通道"地图",有效增强了电缆网的顶层设计,减少了每束电缆并行设计时路径统筹规划不够和走向不优化的问题;构建了电缆网机电一体化协同模式和面向研制全周期的一体化业务流程,建立了跨型号跨专业的通用模型库、参数库、算法与规则库,完善了电缆网系统级设计和底层数据模型,实现了不同专业间的并行协同;开发了导航式电缆网快速协同设计系统,实现了基于参数驱动的复杂电缆网快速三维布线,提升了设计效率效益,并在以空间站为代表的载人航天型号中开展了应用,为复杂电缆网的研制提供了一种有效方法和手段。     

激光干涉仪远程触发功能及其在工作台运动性能评估中的应用

本文介绍了激光干涉仪远程触发端口的应用方法.根据测试要求,将实际触发信号经过分频,以满足激光干涉仪所能接受的频率;同时设计了移位叠加的方法完成全行程的小间隔的自动测量,为工作台运动评估和控制性能的改善提供了依据.     

应用于轴对称流的流图变换中的两个问题

本文导得了轴对称流的位函数φ与流函数ψ的偏导数之间的一个关系式,此式与平面流的关系式是类似的,它是Molenbroek-Chaplygin变换式的推广。本文还导得了轴对称流中的导数的表达式。该式虽然与平面流的形式不一样,但也可以统一起来,它也是平面特征线关系式的推广。