基于小波的全局多源遥感图像信息融合方法

提出的图像信息融合方法用于解决传统方法在空间分辨率等方面的不足。原始图像经过小波变换，分解成子图像，再进行分块处理，高、低分辨率图像根据全局方差准则分别计算融合的权值系数，进行图像融合重建，然后，对图像采用全局法进行信息融合，实验表明，方法切实可行，能使低分辨率图像接近于高分辨率图像。     

新型动态汽车衡称重系统的设计与实现

针对目前现有动态汽车衡称重误差大等问题，提出了一种新型动态汽车衡称重系统的实现方法，该称重系统在基于Intel x86硬件平台和linux操作系统的基础上设计实现的。同时分析了产生称重误差的根本原因。采用了数字信号处理手段来提高动态汽车衡的称重精度。现场测试数据分析表明，该新型动态汽车衡称重系统技术指标优于国家动态衡标准。     

Comparing interpolation techniques for monthly rainfall mapping using multiple evaluation criteria and auxiliary data sources: A case study of Sri Lanka

Interpolating climatic variables such as rainfall is challenging due to the highly variable nature of meteorological processes, the effects of terrain and geography, and the difficulty in establishing a representative network of stations. While interpolation models are being adapted to include these effects, often the rainfall data contain significant gaps in coverage. In this paper, we evaluated rainfall data from an agro-ecological monitoring network for producing maps of total monthly rainfall in Sri Lanka. We compared four spatial interpolation techniques: inverse distance weighting, thin-plate splines, ordinary kriging, and Bayesian kriging. Error metrics were used to validate interpolations against independent data. Satellite data were used to assess the spatial pattern of rainfall. Results indicated that Bayesian kriging and splines performed best in low and high rainfall, respectively. Rainfall maps generated from the agro-ecological network were found to have accuracies consistent with previous studies in Sri Lanka.     

Enhancing self-scheduling algorithms via synchronization and weighting

Existing dynamic self-scheduling algorithms, used to schedule independent tasks on heterogeneous clusters, cannot handle tasks with dependencies because they lack the support for internode communication. To compensate for this deficiency we introduce a synchronization mechanism that provides inter-processor communication, thus, enabling self-scheduling algorithms to handle efficiently nested loops with dependencies. We also present a weighting mechanism that significantly improves the performance of dynamic self-scheduling algorithms. These algorithms divide the total number of tasks into chunks and assign them to processors. The weighting mechanism adapts the chunk sizes to the computing power and current run-queue state of the processors. The synchronization and weighting mechanisms are orthogonal, in the sense that they can simultaneously be applied to loops with dependencies. Thus, they broaden the application spectrum of dynamic self-scheduling algorithms and improve their performance. Extensive testing confirms the efficiency of the synchronization and weighting mechanisms and the significant improvement of the synchronized–weighted versions of the algorithms over the synchronized-only versions.     

基于加权模糊支持向量描述的旋转机械故障分类

基于支持向量数据描述良好的分类性能,针对旋转机械故障诊断中故障样本获取的特点,提出了基于正负类样本的加权模糊支持向量数据描述多类分类器,不仅考虑了正类样本,而且也充分考虑了负类样本对分类结果的影响.利用模拟故障样本对系统进行了实验,结果表明提出的方法在系统中具有良好的分类能力.     

数据融合技术在消防车检测系统中的研究

文中主要研究消防车检测系统中温度工作状态参数,给出了基于DSP TMS320LF2407为核心的硬件构成,提出了基于多传感器数据检测与数据融合技术的温度采集方法。在多传感器采集数据基础上,采用分布图法去除疏失误差,同时采用自适应加权数据融合算法的方法对采集的数据进行融合。实测表明,采用这种方法可以提高温度采集的精度,同时有效地解决了由于传感器失效引起的误差和单点采集温度的不足。有效地保证了消防车检测系统的实时性和准确性。有一定良好的应用前景。     

Using Similarity Analyses to Scale Out Research Findings Across Andean Watershed Basins

Abstract

Strategic research in agriculture and natural resources carried out by international research centers is deemed a public good and should, sooner or later, be put into the hands of development, governmental and non-governmental organizations. However, this research is usually done at specific pilot sites; there is a greater need to know how representative those sites are in relation to the diversity of contexts in other locations. Such is the case with the Challenge Program on Water and Food (CPWF), a global initiative in water research promoted by the Consultative Group on International Agricultural Research (CGIAR), which is developing and implementing strategic research in nine basins located in the tropics of Africa, Asia and South America. Given that resources are not available to collect data from the whole of the region, pilot sites are needed. It is hoped that research outputs obtained in the selected pilot sites can be the basis for scaling out solutions to similar situations in neighbouring or adjacent areas in same or different basins.

In order to contribute to the scaling-out process, different classification methodologies were applied to determine how specific watershed basins are representative of larger areas. The Andean eco-region served as a case study but the methods can easily be applied in other regions. The spatial diversity of biophysical and social conditions across the Andes requires careful site selection. Two methods, a combination of Weight of Evidence (WofE) and Logistic Regression (LR) methods and Fast Cluster analysis, were used to determine the similarity of selected sites with those excluded. A 1-km study resolution covering most of the Andes eco-region included annual rainfall, elevation, length of growing period, land cover, roads and population density as the key variables. Results showed complementarities between the two methods in presenting a probability surface of similarity across the Andes and a clustering of similar sites inside and outside the pilot basins. The output information forms a strong basis for devising plans to scale out research findings from the pilot basins to the whole region.     

辐射防护的生物学基础--辐射生物效应

人类必须研究电离辐射的生物效应，以保护其自身及其它物种免受电离辐射的有害影响，同时在应用中最大限度地获取利益，辐射生物效应，作为辐射防护的生物学基础，一直受到国内外辐射防护界的极大关注。本文就辐射防护密切相关的辐射随机效应，辐射致癌概率，小剂量照射效应及组织权重因子等进行简要讨论。     

纤维缠绕外压容器稳定性最佳铺层分析

在纤维缠绕压力容器设计中，纤维缠绕的方向及各方向纤维用量配比是关键问题。过去的研究中，这一问题一直没能得到很好地解决，特别是各方向纤维用量问题。本文在文献［１～４］的基础上，以加权因子和铺设角为参量给出了对称多层正交各向异性外压容器筒体失稳的最佳铺层理论值。得出了加权因子ｓ取最佳值的范围为０＜ｓ＜０．２５的结论。文中算例表明，按最佳取值给出的临界压力较其它情况有较大幅度的提高。     

A combination model for orientation field of fingerprints

Orientation field is a global feature of fingerprints that is very important in automatic fingerprint identification systems (AFIS). Establishing an accurate and concise model for orientation fields will not only improve the performance of orientation estimation, but also make it feasible to apply orientation information in the matching process. In this paper, a novel model for the orientation field of fingerprints is proposed. We use a polynomial model to approximate the orientation field globally and a point-charge model at each singular point to improve the approximation locally. These two models are combined together by a weight function. Experimental results are provided to illustrate the fact that this combination model is more accurate and robust with respect to noise compared with the previous works. The application of the model is discussed at the end.