Research on Algorithm for Generating Min-Area Rectangle Encasing Box for Closed Contour

Encasingboxisoneofthebasicproblemsincom putinggeometry .ItiswidelyusedinmanyengineeringapplicationssuchasimageprocessingpatternrecognitionandCAD .Theproblemofcomputingthemin arearect angleencasingboxforclosedcontourisaspecialcaseofencasingboxproblem .Thisproblemisinvestigatedforpracticalapplication ,especiallyindesigningpath ,colli siondetectionandreal timeroaming (Day ,1988;PreprataandShamos ,1985 ) .ThecommonapproachisAABB (axis alignedboundingboxes)whenfindingrectangleencasingboxnow ,wh…     

地面γ能谱测量影响因素初探

由于地面γ能谱测量所反映的是表层土壤中的情况，因此地表影响因素，如介质的粒度、湿度及环境温度等成为不可忽视的干扰因素。经试验的数据曲线分析表明，介质粒度越大，其γ场降低，衰减率高；而介质的湿度越大，介质对射线的吸收量增高，衰减率增高。选择适当的季节，进行γ能谱测量也是很重要的。     

Scientific objectives and payloads of Chang’E-1 lunar satellite

China plans to implement its first lunar exploration mission Chang’E-1 by 2007. The mission objectives are

Cytochalasin B induced triploidy in Penaeus chinensis

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The Transient Solution of Plane Progressive Waves

- Generated by an ideal sinusoidal motion of the vertical plate, the simplest linear solution in time domain for two-dimensional regular waves is derived. The solution describes the propagation process of the plane progressive wave with a front, and will approach the linear steady- state solution as the oscillation time of the plate approaches infinity. The solution presented in this paper can be used to provide an incident wave model with analytical expression for solving the problems of diffraction and response of floating bodies in time domain.     

地籍数据共享应用系统设计与实现

近年来国家开展了全国土地调查,查清了全国各类土地资源底数,形成了国土资源核心数据库.这些地籍数据具有巨大的利用价值,但是不同部门之间的数据资源难以充分利用和共享.为了打破国土资源部和其他部门之间的信息孤岛,本文通过SOA技术与B/S架构建立了地籍数据共享应用系统,实现了国土资源部内部、相关事业单位和不同部委之间的地籍数据共享和应用,提高数据应用的深度和广度.     

微生物岩研究的发展与展望

概述了微生物岩的定义、研究范围和实用意义；划分了早期启蒙阶段、古生物学派与现实主义（沉积）学派对立阶段、比较现实主义（沉积学）阶段和微生物沉积学阶段等４个研究发展阶段（涉及微生物岩的岩石、微生物、生态系、环境、分类和演化）；介绍了微生物礁丘、热泉沉积和磷铁锰微生物岩等研究热点；指出在构造类型、沉积环境、组成岩石和成因标志等方面的发展趋势；提出当前任务是要分析鉴定微生物岩的细菌化石，微生物成因的结构构造和矿物，标志元素、同位素和生物标志物，以及微生物生态系统和成岩成矿机理.     

Modeling Groundwater in Multimodal Porous Media with Localized Decompositions

In the present paper, a new stochastic framework is introduced to decompose random variables. This decomposition method is shown to better capture and reflect the medium heterogeneity for multimodal porous media than the classical Reynolds decomposition does. In particular, with this decomposition method, the variance of log conductivity is decomposed into two parts. The first one measures the mean differences of log conductivity across different units having high contrasting conductivity. The second part measures the variation of log conductivity arisen within individual units. Based on this localized decomposition, a new stochastic model is proposed for flow in a highly heterogeneous porous media. This stochastic model shall produce much sharper approximations under the assumption that only the second part of the variance of log conductivity is small. Therefore, the proposed model can partially overcome the assumption of small composite variance for log conductivity in current theory for both flow and transport.