基于ODMG Java绑定的面向对象数据库 存储管理①

针对面向对象数据库(OODB)的存储管理进行研究,依照ODMG3.0标准,并以Java绑定方式提供实现方案。通过对典型对象存储结构的研究,给出一种兼顾各种类型数据特点的分层对象存储结构。结合这里使用的体系结构,给出一种基于分槽页结构的改进文件存储结构,将存储单位由页面替换成数据库文件。分析OODB中引入的索引,给出一种基于B+-Tree,结合继承层次和聚集层次的综合索引策略。     

基于Hyperion数据的铜矿信息直接和间接提取方法研究

针对不同的地表覆盖条件,研究基于Hyperion星载高光谱数据的砂页岩型铜矿信息提取方法。首先对Hyperion L1级数据进行波段筛选、坏线修复、大气纠正和几何纠正等预处理,然后分别针对不同的植被覆盖情况使用不同的信息提取方法。在岩石裸露区,直接使用光谱角制图法;在植被覆盖区,使用铜金属离子的积累导致的植被生理异常作为间接标志来识别铜矿信息,生理异常使用高光谱植被指数来计算。结果表明,综合使用这两种方法的互补信息能够便于提取复杂地表覆盖情况下的铜矿信息。     

提高分类准确率的诊断性测验的研究

传统的纸笔测验只给被试提供一个测验分数,计算机化自适应测验（CAT）不仅给出了被试的测验分数,还估计了被试的能力。但这两种方法都没有对学生的认知结构进行探索,认知诊断评价（CDA）的优势就在于能够揭示个人在所测知识领域的详细信息,对个体进行补救,教师也可以针对学生的知识状态改进教学,对教、学双方都有指导作用。传统的测验构建方法没有考虑可达矩阵,导致分类准确率不高,本文提出将可达矩阵与认知诊断信息指标相结合的选题策略,模拟实验结果表明,模式判准率和平均边际判准率都有所提高。     

窄带宽网络环境下的快速文件备份方法

提出一种窄带宽网络环境下的快速文件备份方法,该方法在差异备份过程中使用一种新的校验和数据管理方式,减少了客户端和服务器端之间数据的传输,可以在窄带宽的网络环境下快速备份文件。     

Vegetation water content during SMEX04 from ground data and Landsat 5 Thematic Mapper imagery

Vegetation water content is an important parameter for retrieval of soil moisture from microwave data and for other remote sensing applications. Because liquid water absorbs in the shortwave infrared, the normalized difference infrared index (NDII), calculated from Landsat 5 Thematic Mapper band 4 (0.76-0.90 μm wavelength) and band 5 (1.55-1.65 μm wavelength), can be used to determine canopy equivalent water thickness (EWT), which is defined as the water volume per leaf area times the leaf area index (LAI). Alternatively, average canopy EWT can be determined using a landcover classification, because different vegetation types have different average LAI at the peak of the growing season. The primary contribution of this study for the Soil Moisture Experiment 2004 was to sample vegetation for the Arizona and Sonora study areas. Vegetation was sampled to achieve a range of canopy EWT; LAI was measured using a plant canopy analyzer and digital hemispherical (fisheye) photographs. NDII was linearly related to measured canopy EWT with an R² of 0.601. Landcover of the Arizona, USA, and Sonora, Mexico, study areas were classified with an overall accuracy of 70% using a rule-based decision tree using three dates of Landsat 5 Thematic Mapper imagery and digital elevation data. There was a large range of NDII per landcover class at the peak of the growing season, indicating that canopy EWT should be estimated directly using NDII or other shortwave-infrared vegetation indices. However, landcover classifications will still be necessary to obtain total vegetation water content from canopy EWT and other data, because considerable liquid water is contained in the non-foliar components of vegetation.     

Use of a dark object concept and support vector machines to automate forest cover change analysis

An automated method was developed for mapping forest cover change using satellite remote sensing data sets. This multi-temporal classification method consists of a training data automation (TDA) procedure and uses the advanced support vector machines (SVM) algorithm. The TDA procedure automatically generates training data using input satellite images and existing land cover products. The derived high quality training data allow the SVM to produce reliable forest cover change products. This approach was tested in 19 study areas selected from major forest biomes across the globe. In each area a forest cover change map was produced using a pair of Landsat images acquired around 1990 and 2000. High resolution IKONOS images and independently developed reference data sets were available for evaluating the derived change products in 7 of those areas. The overall accuracy values were over 90% for 5 areas, and were 89.4% and 89.6% for the remaining two areas. The user's and producer's accuracies of the forest loss class were over 80% for all 7 study areas, demonstrating that this method is especially effective for mapping major disturbances with low commission errors. IKONOS images were also available in the remaining 12 study areas but they were either located in non-forest areas or in forest areas that did not experience forest cover change between 1990 and 2000. For those areas the IKONOS images were used to assist visual interpretation of the Landsat images in assessing the derived change products. This visual assessment revealed that for most of those areas the derived change products likely were as reliable as those in the 7 areas where accuracy assessment was conducted. The results also suggest that images acquired during leaf-off seasons should not be used in forest cover change analysis in areas where deciduous forests exist. Being highly automatic and with demonstrated capability to produce reliable change products, the TDA-SVM method should be especially useful for quantifying forest cover change over large areas.     

Optimal Trajectory Planning for Wheeled Mobile Robots Based on Kinematics Singularity

This research introduces a new optimality criterion for motion planning of wheeled mobile robots based on a cost index that assesses the nearness to singularity of forward and inverse kinematic models. Slip motions, infinite estimation error and impossible control actions are avoided escaping from singularities. In addition, high amplification of wheel velocity errors and high wheel velocity values are also avoided by moving far from the singularity. The proposed cost index can be used directly to complement path-planning and motion-planning techniques (e.g. tree graphs, roadmaps, etc.) in order to select the optimal collision-free path or trajectory among several possible solutions. To illustrate the applications of the proposed approach, an industrial forklift, equivalent to a tricycle-like mobile robot, is considered in a simulated environment. In particular, several results are validated for the proposed optimality criterion, which are extensively compared to those obtained with other classical optimality criteria, such as shortest-path, time-optimal and minimum-energy.     

Improvements of nonlinear dynamic modeling of hot-film MAF sensor

The operating procedure of engine requires that the mass air flow (MAF) sensor can measure the pulsation air flow accurately. Therefore the MAF sensor must possess fast response speed. It is necessary to study the dynamic characteristic of the MAF sensor. Both the experimental equipments and method used by authors previously are improved to obtain the sensor response data accurately in this paper. The static and dynamic separable modeling method is adopted to build the uniform nonlinear dynamic model of the hot-film MAF sensor in the Hammerstein and Wiener forms, which can describe the large/small flow-rate and positive/negative step responses. The performance indexes are calculated by the actual and model responses.     

P2P系统中基于副本链的一致性维护算法

提出一种无结构纯P2P的副本一致性维护算法。利用副本节点发起的第一次更新消息在P2P网络中的广播,由其他收到消息的副本节点给出响应,构建副本链。副本链建立后,更新消息在副本节点间进行传播,不再在网络中洪泛。副本链的维护通过记录首次发起更新的副本节点IP地址完成。仿真试验证明该算法是简单有效的。     

基于社区分析的网络分割

在并行计算中,网络分割的质量会极大地影响并行计算的效率,然而在网络分割时并没有一个统一的质量评价指标,因此网络分割评价指标的定义以及最佳网络分割方法的构造,成为大规模网络中并行计算的一个核心问题.根据对影响并行计算效率的各种因素的分析,给出了一个网络分割评价指数的定义,并利用并行最短路径的计算验证了该评价指数的定义的正确性;并且基于社区分析,给出了一个全新的网络分割方法,理论分析表明:该网络分割方法是最优的.