外向型汉语学习词典编纂与研究综述

外向型汉语学习词典是为母语非汉语的学习者编纂的学习汉语用的词典。20世纪80年代以来,词典编纂成果数量较多,品种较全,类型意识在逐渐增强,培育出了几部品牌产品;但在类型定位、用户意识、编纂技术、品牌观念等方面仍需加强。在研究方面,出现了一批较有分量的论文和专著,研究内容不断深入,研究队伍不断壮大;但与国外发达水平相比,仍有较大差距,主要表现在理论研究滞后于编纂实践、学科仍不成熟、学术流派尚未形成等。     

Does the Social Capital in Networks of “Fish and Fire” Scientists and Managers Suggest Learning?

Patterns of social interaction influence how knowledge is generated, communicated, and applied. Theories of social capital and organizational learning suggest that interactions within disciplinary or functional groups foster communication of knowledge, whereas interactions across groups foster generation of new knowledge. We used social network analysis to examine patterns of social interaction reported in survey data from scientists and managers who work on fish and fire issues. We found that few fish and fire scientists and managers interact with one another, suggesting low bridging social capital and thus, limited opportunity for generation of new knowledge. We also found that although interaction occurs among scientists—suggesting modest bonding social capital—few managers interact with other managers, indicating limited opportunity for communication of scientific knowledge for the purposes of application. We discuss constraints and opportunities for organizational learning evident in these patterns of social interaction among fish and fire scientists and managers.     

Research Approaches for Understanding,Enhancing, and Monitoring Community Resilience

The growing interest in the understanding of community resilience suggests a need for improving research approaches. This article reviews methods used to date, and suggests opportunities for expanding the range and efficacy of approaches used to understand, improve, and monitor the coupled social and ecological aspects of community resilience. We explore three potential foci: research approaches that enhance understanding of community resilience; those that help to improve community resilience through the research process; and the further development of methods to guide monitoring. Most studies have relied on mixed and multistaged methods, including in-depth interviews and case studies. We comment on the wide range of approaches used, and suggest others that could be valuable. There is particular scope for greater use of cumulative studies, historical or retrospective studies, participatory methods, and systems approaches, and a need for more methods that explore the coupling of social and ecological dimensions.     

Domain adaptation for land use classification: A spatio-temporal knowledge reusing method

Land use classification requires a significant amount of labeled data, which may be difficult and time consuming to obtain. On the other hand, without a sufficient number of training samples, conventional classifiers are unable to produce satisfactory classification results. This paper aims to overcome this issue by proposing a new model, TrCbrBoost, which uses old domain data to successfully train a classifier for mapping the land use types of target domain when new labeled data are unavailable. TrCbrBoost adopts a fuzzy CBR (Case Based Reasoning) model to estimate the land use probabilities for the target (new) domain, which are subsequently used to estimate the classifier performance. Source (old) domain samples are used to train the classifiers of a revised TrAdaBoost algorithm in which the weight of each sample is adjusted according to the classifier’s performance. This method is tested using time-series SPOT images for land use classification. Our experimental results indicate that TrCbrBoost is more effective than traditional classification models, provided that sufficient amount of old domain data is available. Under these conditions, the proposed method is 9.19% more accurate.     

Web 2.0环境下测绘实践个性化平台的构建

随着教育信息化的快速发展,网络个性化学习越来越普遍。提升大学生的网络学习能力成为一个重要的研究课题。本文结合Web 2.0技术的特点和优势,以学生学习的个性化、自主性为基础,以测绘专业实践教学改革为依托,探讨了利用Web 2.0技术进行个性化学习测绘实践教学平台建设的意义、可行性和技术路线。     

自定义扩展AutoCAD属性信息的实现

为了更灵活方便地对AutoCAD图形数据对象添加自定义的属性信息,针对AutoCAD中存在的自定义扩展CAD属性信息的问题进行了分析研究,并在.NET环境下借助ObjectARX的开发组件,分别使用了XData扩展方式和扩展词典方式来实现AutoCAD属性信息的自定义扩展功能,并以在CAD图形文件中扩展GIS属性数据为例进行实践应用,展示了应用的实践效果。     

基于影像交叉学习的CBERS CCD波段模拟

与TM/ETM+相比,CBERS CCD缺少2个红外波段(波段5和波段7),这便导致了许多针对TM/ETM+数据的图像处理方法难以直接应用于CBERS CCD图像.为此,采用基于影像交叉学习的波段模拟方法,即以ETM+数据作为先验知识,通过支持向量回归( Support Vector Regression,SVR),拟...     

基于认知风格的遥感导论实验教学体系的建立与实践

从认知风格理论出发,顺应学习者的认知风格差异,建立多层次、一体化的实验教学体系,并从实验教学的内容、过程、环境与考核出发,构建个性化的学习平台,以培养学习者的实践能力与创新精神。     

通用型森林资源调查GIS系统设计与实现

本文分析了PDA森林资源调查采集软件的应用现状,针对现有开发模式和系统框架重用度低、通用性差、难于维护扩展的问题,提出了基于“数据字典”的通用型森林资源调查GIS系统软件的开发方案.采用相关开发工具,进行了系统实现;实践证明,该系统具有良好的通用性和可扩展性.     

Can we improve the spatial predictions of seabed sediments? A case study of spatial interpolation of mud content across the southwest Australian margin

Spatially continuous data of environmental variables is often required for marine conservation and management. However, information for environmental variables is usually collected by point sampling, particularly for the marine region. Thus, methods generating such spatially continuous data by using point samples to estimate values for unknown locations become essential tools. Such methods are, however, often data- or even variable-specific and it is difficult to select an appropriate method for any given dataset. In this study, 14 methods (37 sub-methods) are compared using samples of mud content with five levels of sample density across the southwest Australian margin. Bathymetry, distance-to-coast, slope and geomorphic province were used as secondary variables. Ten-fold cross validation with relative mean absolute error (RMAE) and visual examination were used to assess the performance of these methods. A total of 1850 prediction datasets are produced and used to assess the performance of the methods and the effects of other factors considered. Considering both the accuracy and the visual examination, we found that a combined method (i.e., random forest and ordinary kriging: RKrf) is the most robust method. This method is novel, with a RMAE up to 17% less than that of the control. No threshold in sample density was detected in relation to prediction accuracy. No consistent patterns are observed between the performance of the methods and data variation. The RMAE of three most accurate methods is about 30% lower than that of the best methods in previous publications, highlighting the robustness of the methods selected in this study. The implications and limitations of this study are discussed and a number of suggestions are provided for further studies.