Treatment of Hydrodynamic Loading for Random Sea State

- In order to employ cost effective frequency domain analysis for off-shore structures treatment of hydrodynamic loading is essential. Drag and inertia dominated, resonating and antiresonating cases under random sea states are analyzed to highlight the implications and relative merits of four salient linearization techniques.     

Freshening of the Intermediate Waters in the Northern South China Sea over the PastSix Decades

The properties of salinity in the South China Sea (SCS), a significant marginal sea connecting the Pacific andIndian Oceans, are greatly influenced by the transport of fresh water flux between the two oceans. However, the long-termchanges in the intermediate water in the SCS have not been thoroughly studied due to limited data, particularly in relationto its thermodynamic variations. This study utilized reanalysis data products to identify a 60-year trend of freshening in theintermediate waters of the northern South China Sea (NSCS), accompanied by an expansion of low-salinity water. Thestudy also constructed salinity budget terms, including advection and entrainment processes, and conducted an analysis ofthe salinity budget to understand the impacts of external and internal dynamic processes on the freshening trend of theintermediate water in the NSCS. The analysis revealed that the freshening in the northwest Pacific Ocean and theintensification of intrusion through the Luzon Strait at intermediate levels are the primary drivers of the salinity changes inthe NSCS. Additionally, a weakened trend in the intensity of vertical entrainment also contributes to the freshening in theNSCS. This study offers new insights into the understanding of regional deep sea changes in response to variations in boththermodynamics and oceanic dynamic processes.     

Evaluation of gas production rates in some comets

Emission fluxes of CN, C₂ and C₃ carbon-bearing molecular species observed in the coma of comets Bennett (1969i 1970II), West (1975n 1976VI), P Halley (1982i), Hartley-Good (19851) and Bradfield (1987s) are analysed in the framework of Haser model. CN, C₂ and C₃ production rates are determined using recently derived fluorescence efficiencies. The dependence of CN, C₂ and C₃ production rates on the heliocentric distance and the possible correlations among these radicals is studied and briefly discussed.     

频率域电磁法中视电阻率全区定义

视电阻率定义在电法勘探中得到广泛的应用。目前在频率域电磁法中常常采用远区视电阻率定义。由于在频率域中收发距并非足够大,以致在低频段远区定义视电阻率往往不能反映地下电阻率值。我们定义全区电阻率及引入校正系数K,经二层三层模型及野外实测资料的计算,证明了方法的有效性。     

基于GIS的区域经济统计分析系统的设计与实现

随着经济的发展,区域间经济相互作用和影响的关系越来越密切,忽略空间相互作用的传统区域经济分析手段和方法开始显现出一些明显的不足。而GIS在处理和分析区域地理数据上具有强大的空间分析能力,为此我们引入GIS工具对区域经济进行分析,相较于传统的分析手法有了很大改善。本文以江西省区域经济数据为例,设计了一个基于GIS的区域经济统计分析系统,并利用Arcob-jects二次开发控件结合VB可视化编程语言,实现了大部分区域经济统计分析功能,最后并将结果进行网络发布。研究结果表明将GIS引入到区域经济统计分析中,更能正确、有效的揭示区域经济发展在空间上的联系,为区域经济研究决策提供服务。     

区域似大地水准面确定的最小二乘支持向量机方法

支持向量机(SVM)是近年来发展起来的机器学习的新方法,它较好地解决小样本、非线性、高维数、局部极小点等实际问题.文中研究支持向量机的拓展算法--最小二乘支持向量机(LSSVM),并将其应用于确定大面积复杂似大地水准面.通过工程实例并与神经网络模型和二次曲面多项式拟合模型相比较,验证确定区域似大地水准面的LSSVM方法的有效性.     

Automated Target Detection and Discrimination Using Constrained Kurtosis Maximization

Exploiting hyperspectral imagery without prior information is a challenge. Under this circumstance, unsupervised target detection becomes an anomaly detection problem. We propose an effective algorithm for target detection and discrimination based on the normalized fourth central moment named kurtosis, which can measure the flatness of a distribution. Small targets in hyperspectral imagery contribute to the tail of a distribution, thus making it heavier. The Gaussian distribution is completely determined by the first two order statistics and has zero kurtosis. Consequently, kurtosis measures the deviation of a distribution from the background and is suitable for anomaly/target detection. When imposing appropriate inequality constraints on the kurtosis to be maximized, the resulting constrained kurtosis maximization (CKM) algorithm will be able to quickly detect small targets with several projections. Compared to the widely used unconstrained kurtosis maximization algorithm, i.e., fast independent component analysis, the CKM algorithm may detect small targets with fewer projections and yield a slightly higher detection rate.     

RUSLE及其影响因子的快速计算分析

RUSLE是目前应用最广泛的土壤侵蚀模型。虽然是一种经验模型,但是其影响因子计算仍然非常复杂,满足不了区域土壤侵蚀的快速提取要求。针对这种状况,文章在介绍RUSLE手册中每个影响因子计算方式基础上,分析总结了可进行快速计算的方法,实验表明,采用文章推荐的因子计算方式,可达到快速有效的目的。