土壤容重对土壤物理性状和小麦生长的影响

以黑土和自浆土为试材,进行筒栽试验.结果表明,适宜小麦生长的容重范围分别为1.15～1 30g/cm3和0.9～1.05g/cm3.     

河北省土壤容重的传递函数研究

由于非破坏性取样测定土壤容重是一项困难、昂贵、费时和不符合实际的工作.为克服这些困难,国外学者已经研究出多种与土壤有机质或有机碳含量和土壤质地有关的传递函数去估计其研究范围内的土壤容重.本文利用河北省第二次土壤普查资料中的土壤有机质和质地数据,对已有的13种土壤传递函数模拟的结果进行对比,确定最佳传递函数形式后,用SPSS统计分析软件进行回归分析,求得适宜河北省土壤容重的传递函数表达式.     

荠菜根系的计算机模拟

针对荠菜根系的形态特征和生长特点,提出一种基于几何模型的荠菜根系三维建模方法：根据荠菜根系的拓扑几何结构,应用根系几何模型SimRoot,基于Visual C++平台并采用OpenGL图形库,建立能较真实再现荠菜根系动态生长过程的可视化模拟系统。模拟结果表明该方法是可行有效的。     

基于DLA的虚拟植物根系模拟方法研究

传统的根系研究模型注重于根系外观形态的模拟,而将根系的生理生态结合起来的模拟方法则较少。对于农业信息技术而言,根系生理生态的研究模型能更好地服务于农林业领域。文中在研究了DLA模型的特点及其应用的基础上,分析了基本DLA模型的不足并提出了一种改进的DLA模型,用于植物须根系的向水性模拟。该模型结合参数可控方法体现了植物须根系向水性的动态生长过程,一定程度上符合实际植物的生长机理,并在VC＋＋6.0上给出了模拟效果图。模拟结果显示,改进的模型能够逼真、细腻地模拟须根系的向水性生长形态。最后指出了改进DLA算法关于根系建模进一步的研究方向。     

基于L-系统的落叶松根系生长模拟模型研究

根据落叶松根系动态分布参数与生长规律,基于L-系统理论构建落叶松根系生长模拟模型.以落叶松根系微观上的自相似性为依据,建立适合描述落叶松根系生长参数的数据结构,以应用随机生成技术,在数据结构中引入生长控制参数以实现动态可控性.     

龙须草对土壤理化性状的影响研究

通过定位试验方法,从定量的角度研究与探讨种植龙须草对土壤理化性状的影响。研究结果表明,龙须草能降低土壤容重,提高土壤总孔隙度、非毛管孔隙度和毛管孔隙度,适当增加土壤中粘粒、粉粒含量、减少砂粒含量,改善土壤通气透水性能,提高土壤肥力,改善土壤化学性状,从而达到改良土壤耕性的效果。     

土壤Nmin在南疆棉花氮肥推荐中的应用研究

结合6个施氮水平下土壤Nmin速测值分析了土壤Nmin与施肥量和棉花产量关系,对应用土壤Nmin进行棉花氮肥推荐进行了研究。分析结果表明:土壤Nmin与棉花产量和施氮量均呈正相关关系,与土壤深度呈负相关关系;其中0~20cm土层土壤与施氮量和棉花产量相关性最强,可以很好的表征土壤初始供氮能力,因而可以利用它作为棉花氮肥推荐的指标。在考虑土壤初始供氮能力下,供试棉花品种达到最高产量时的最佳施肥量为226kghm-2,此时0~20cm土层土壤Nmin临界值为为20mgkg-1,并结合最佳施肥量和0~20cm土层土壤Nmin临界值计算出了棉花苗期、蕾期、花铃期的氮肥追施量。     

籽粒苋根际土壤及根系分泌物对矿物态钾的活化作用

通过大田和模拟试验等方法 ,研究了籽粒苋根际土壤及根系分泌物对矿物态钾的活化作用 ,研究结果表明 :(1)籽粒苋根际土壤的速效钾含量较非根际土增加了 1.7倍 ,缓效钾 (K)的含量也提高了 5 5 .9% ;(2 )用籽粒苋根际土壤处理后的花岗岩粉末 ,其速效钾和缓效钾含量均较对照有所增加 ,增幅分别为 2 .8%～ 2 4.7%和 15 .7%～ 44 .7% ;用籽粒苋根际土壤处理后的紫色土 ,其速效钾和缓效钾含量较对照分别增加了 18.5 %和 11.1% ;(3 )通过对y值的综合贡献率计算可知 ,不同籽粒苋模拟根系分泌物对花岗岩粉末中矿物态钾的活化能力大小依次为 :草酸 >蔗糖 >核酸 >乳酸 >柠檬酸。     

知识管理研究

通过对知识管理内容、过程、人和技术等方面的研究，提出今后知识管理研究在这些方面的重点。     

图书馆知识管理创新研究

本文分析了图书馆知识管理所存在的一些问题,提出了加强图书馆管理理念创新,注重人力资开发管理,用知识管理理念创新图书馆服务,提高图书馆知识创新能力,组建知识型决策团队和塑造适应知识管理的图书馆组织文化等对策促进图书馆知识管理创新的发展以便于更好的为人们服务。     

知识管理在化工企业中的应用

知识已成为企业重要的生产投入要素，知识管理能将企业战略、信息系统和企业核心能力知识有机结合起来，而成为新的研究热点。当前国际管理信息发展的三个趋势是：从信息管理走向知识管理，从信息资源开发走向知识资源开发，由C／S(Client／Server)结构走向B／S(Browser／Server)结构。企业实施知识管理是当前现代管理的发展方向。该文分析了化工企业实施知识管理的必要性，介绍了知识管理的基本概念，提出了知识管理系统的分层框架，以及企业实施知识管理的原则和步骤。     

面向课程的知识管理系统研发

为了有效地将教育资源的建设和使用融入到日常的教学工作中,并使教育资源能为学生终生服务,深入研究了应用型本科院校对知识管理系统的需求,提出了以课程知识体(Course Knowledgebody,CK)进行信息集成设计理念,建立了知识管理系统的业务模型和信息模型,进而开发了面向整个课程生命周期知识管理系统,该系统已在攀枝花学院实施应用,效果良好。     

Generation of crown bulk density for Pinus sylvestris L. from lidar

The use of lidar data to estimate critical variables needed for modeling wildfire behavior was tested on a Scots pine forest (Pinus sylvestris L.) in central Spain. Lidar data accurately estimated crown bulk density at the plot level (r²=0.80). Lidar data could be used to directly estimate crown volume (r²=0.92) and foliage biomass (r²=0.84), which together produced better results than directly fitting the lidar data to crown bulk density. Incorporating equations that relate tree diameter at breast height and other forest parameters improved estimates of foliage biomass. Individual tree level analyses were not completely successful due to difficulty in accurately assigning laser pulses to the correct tree (r²=0.14).     

Back to the future: from knowledge management to the management of information and data

This paper argues for a return to fundamentals and for a balanced assessment of the contribution that Information Technology can make as we enter the new millennium. It argues that the field of Information Systems should no longer be distracted from its natural locus of concern and competence, or claim more than it can actually achieve. More specifically, and as a case in point, we eschew IT-enabled Knowledge Management, both in theory and in practice. We view Knowledge Management as the most recent in a long line of fads and fashions embraced by the Information Systems community that have little to offer. Rather, we argue for a refocusing of our attention back on the management ofdata, since IT processes data-notinformation and certainly notknowledge. In so doing, we develop a model that provides a tentative means of distinguishing between the terms. This model also forms the basis for on-going empirical research designed to test the efficacy of our argument in a number of case companies currently implementing ERP and Knowledge Management Systems.     

人工智能在解决知识管理难题中的应用

在知识经济社会中，企业的价值创造极大地依赖于知识，知识管理日益受到重视。随着Internet的飞速发展，知识管理面临信息过载、非结构化以及隐性知识的三大难题。人工智能在知识信息处理方面具有很大的优势，有助于解决知识管理中的难题，实现知识自动获取以及知识的自动分类。人工智能在知识管理中的应用虽然存在一定的局限性，但它促进了知识管理的智能化，提高了知识管理的效率和质量。     

Ajax技术在KMS系统中的设计与应用

Ajax是JavaScritp、XML等多种技术的集合,介绍了如何将Ajax技术应用到KMS系统中。主要包括Ajax技术工作原理及其如何提升KMS系统的性能,给出了系统应用的关键代码和最终效果。结果表明,应用Ajax技术提高了KMS系统的响应速度和用户友好度。     

ERP Simulation Effects on Knowledge and Attitudes of Experienced Users

ABSTRACT

Best-in-class organizations recognize that knowledge management provides a competitive advantage. Opportunities to share knowledge enhance knowledge sharing attitudes. Organizations use training to facilitate knowledge and acclimate novice employees to Enterprise Resource Planning (ERP) systems. Most ERP functional training leverages explicit codified knowledge. Without collaborative opportunities between departments, allowing users to interact and exchange internalized knowledge and skills, information remains untapped. Prior research explored the impact of ERPsim on knowledge, skills, and attitudes, but failed to model construct relationships. This work assesses if a business simulation can be used to mimic Social Cognition Theory and enhance knowledge and attitude among experienced employees. Paired sample T-tests confirmed significant differences in means across constructs. Additionally, PLS Path Modeling investigated and confirmed a relationship between knowledge and skills constructs with attitude. Findings suggest ERPsim might be beneficial to diffuse knowledge and skills among experienced users in the workplace, while positively influencing attitudes.     

仿真生命周期管理在现实仿真工作中的意义

仿真生命周期的管理不仅仅实现对仿真具体工作细节的再现和数据对象的管理,还将仿真工作形成全方位的五维立体形式.这种革新方式,以数据、流程、管理、知识和安全5个维度,将现实中的仿真工作提升到真正的信息化高度.达索公司的仿真生命周期管理系统(Simulation Lifecycle Management,SLM)的架构符合这种立体模式,可将理论上的仿真生命周期管理成为现实.     

基于Web2.0环境的复杂性转向——以个人知识管理为例

Web2.0环境带给整个学习群体的不仅是技术的革新,更重要的是理念的转变。从复杂性理论的角度出发,对Web2.0环境下的个人知识管理技术支持平台,如Blog、wiki、RSS、TAG、SNS等应用后所应具有的复杂性进行分析,并力图从个人知识管理学习群及个人知识管理帮助者两个角度促进个人知识管理。     

The impact of simulated soil temperatures on the estimation of snow depth over Siberia from SSM/I compared to a multi-model climatology

The snowpack is a key variable of the hydrological cycle. In recent years, numerous studies have demonstrated the importance of long-term monitoring of the Siberian snowpack on large spatial scales owing to evidence of increased river discharge, changes in snow fall amount and alterations with respect to the timing of ablation. This can currently only be accomplished using remote sensing methods. The main objective of this study is to take advantage of a new land surface forcing and simulation database in order to both improve and evaluate the snow depths retrieved using a dynamic snow depth retrieval algorithm. The dynamic algorithm attempts to account for the spatial and temporal internal properties of the snow cover. The passive microwave radiances used to derive snow depth were measured by the Special Sensor Microwave/ Imager (SSM/I) data between July 1987 and July 1995.The evaluation of remotely sensed algorithms is especially difficult over regions such as Siberia which are characterized by relatively sparse surface measurement networks. In addition, existing gridded climatological snow depth databases do not necessarily correspond to the same time period as the available satellite data. In order to evaluate the retrieval algorithm over Siberia for a recent multi-year period at a relatively large spatial scale, a land surface scheme reanalysis product from the Global Soil Wetness Project-Phase 2 (GSWP-2) is used in the current study. First, the high quality GSWP-2 input forcing data were used to drive a land surface scheme (LSS) in order to derive a climatological near-surface soil temperature. Four different snow depth retrieval methods are compared, two of which use the new soil temperature climatology as input. Second, a GSWP-2 snow water equivalent (SWE) climatology is computed from 12 state-of-the-art LSS over the same time period covered by the SSM/I data. This climatology was compared to the corresponding fields from the retrievals. This study reaffirmed the results of recent studies which showed that the inclusion of ancillary data into a satellite data-based snow retrieval algorithm, such as soil temperatures, can significantly improve the results. The current study also goes a step further and reveals the importance of including the monthly soil temperature variation into the retrieval, which improves results in terms of the spatial distribution of the snowpack. Finally, it is shown that further improved predictions of SWE are obtained when spatial and temporal variations in snow density are accounted for.