空间数据库中一种自适应的缓存替换策略

随着近年来空间数据库研究和应用的不断深入,针对空间数据库中数据组织和查询的特征来设计缓存页面替换策略成为一个新的研究问题.Voronoi图是一种重要的空间数据库组织技术,在处理kNN查询时具有非常好的性能.针对Voronoi图组织的空间数据库,首先利用空间局部性提出了一种基于欧氏距离的替换策略,在发生页面失效时选择距离上一次访问页面欧氏距离最远的页面进行替换;进一步,针对不同kNN查询的搜索空间大小差异非常大的特点,在LIRS替换策略基础上提出一种自适应替换策略,通过对HIR页面占缓存比例自动调整来适应不同的查询.综合两者,形成基于欧氏距离的自适应缓存页面替换算法AELIRS.大量实验表明,在缓存大小与搜索空间大范围变动中,AELIRS始终优于其他替换策略.     

基于粗糙集与粗糙元神经网络的三峡库区水质评价模型

粗糙集和粗糙元神经网络相结合进行三峡库区水质评价.针对评价因子较多,通过粗糙集进行数据预处理,降低模型的复杂性.对于库区数据非精确值或范围值时,采用粗糙元神经网络建立评价模型,提高了系统的正确性和可理解性,并将其应用在三峡库区水环境安全系统中.     

一种改进的证据理论C均值分割方法

证据理论C均值(ECM)作为传统聚类方法的一种改进仍然存在着对噪声敏感和易于陷入局部极小值的缺点,鉴于此,提出一种遗传算法(GA)和证据理论C均值相结合的分割方法,并且在分类过程中引入了位置信息。遗传算法具有全局搜索的能力,很好地克服了证据理论C均值结果局部最优的缺点,而位置信息的引入则解决了对噪声敏感的问题。实验结果证明,该方法收敛速度快,迭代步数少,分割精度高。     

Identifying mislabeled training data with the aid of unlabeled data

This paper presents a new approach for identifying and eliminating mislabeled training instances for supervised learning algorithms. The novelty of this approach lies in the using of unlabeled instances to aid the detection of mislabeled training instances. This is in contrast with existing methods which rely upon only the labeled training instances. Our approach is straightforward and can be applied to many existing noise detection methods with only marginal modifications on them as required. To assess the benefit of our approach, we choose two popular noise detection methods: majority filtering (MF) and consensus filtering (CF). MFAUD/CFAUD is the new proposed variant of MF/CF which relies on our approach and denotes majority/consensus filtering with the aid of unlabeled data. Empirical study validates the superiority of our approach and shows that MFAUD and CFAUD can significantly improve the performances of MF and CF under different noise ratios and labeled ratios. In addition, the improvement is more remarkable when the noise ratio is greater.     

Face recognition based on extreme learning machine

Extreme learning machine (ELM) is an efficient learning algorithm for generalized single hidden layer feedforward networks (SLFNs), which performs well in both regression and classification applications. It has recently been shown that from the optimization point of view ELM and support vector machine (SVM) are equivalent but ELM has less stringent optimization constraints. Due to the mild optimization constraints ELM can be easy of implementation and usually obtains better generalization performance. In this paper we study the performance of the one-against-all (OAA) and one-against-one (OAO) ELM for classification in multi-label face recognition applications. The performance is verified through four benchmarking face image data sets.     

CropStraw Fire Remote Sensing Monitoring and Its Algorithm Implementation

in order to obtain the information and achieve the effective control of crop straw fire spatial distribution in Central China Region.The MODIS L1B remote sensing datasets during 2014 for the main data source in this article,and combined with land use data,the farmland of Central China Region was taken as study region.Based on the enhanced contextual fire remote sensing detection algorithm,and make full use of the theoretical knowledge of quantitative remote sensing and Geospatial Data Abstraction Library (GDAL)and other technical means,to achieve the crop straw fire recognition in Central China Region.Using Ministry of Environmental Protection of the People’s Republic of China release the daily newspaper of crop straw fire in China and the standard fire products (MYD14)of MODIS for the comparative analysis of the quantitative and spatial.The results indicate that the algorithmof this paper can achieve crop straw fire remote sensing monitoring of this study region effectively,and the parameters can be adjusted in real time based on the characteristic of the study region,and improve the automation and working efficiency of crop straw fire monitoring.     

HIMAC协处理器流量控制设计与实现

为了防止非法的业务流消耗系统过多的资源,并且控制每个端口占用的带宽,需要对进入HINOC系统的业务流流量进行限制.本文提出了HINOC MAC (HIMAC)的流量控制方案.本设计的特别之处在于,它允许根据各个端口业务量的大小,动态地调整分配给它们的带宽,并且设计方案简单可行.     

Discriminative Sketch‐based 3D Model Retrieval via Robust Shape Matching

We propose a sketch‐based 3D shape retrieval system that is substantially more discriminative and robust than existing systems, especially for complex models. The power of our system comes from a combination of a contour‐based 2D shape representation and a robust sampling‐based shape matching scheme. They are defined over discriminative local features and applicable for partial sketches; robust to noise and distortions in hand drawings; and consistent when strokes are added progressively. Our robust shape matching, however, requires dense sampling and registration and incurs a high computational cost. We thus devise critical acceleration methods to achieve interactive performance: precomputing kNN graphs that record transformations between neighboring contour images and enable fast online shape alignment; pruning sampling and shape registration strategically and hierarchically; and parallelizing shape matching on multi‐core platforms or GPUs. We demonstrate the effectiveness of our system through various experiments, comparisons, and user studies.     

基于SoPC的SD卡控制器IP核的设计

针对目前在嵌入式平台中使用SD卡控制器专用芯片价格昂贵、软件模拟SPI时序控制读写速度较慢的问题,提出了一种基于SoPC技术的SD卡控制器IP核设计的架构方案.采用VHDL语言设计SD卡控制器IP核,利用自定义模块技术将其添加到SoPC中,利用Nios Ⅱ IDE编写SD卡的基础读写驱动软件并移植μC/FS文件系统,实...     

基于语法树的批价优惠研究与设计

以中国电信行业计费系统为研究对象,从批价优惠业务需求层面进行分析,提出了基于语法树的批价优惠方法,并在理论和实践上给出了一个电信行业中应用的解决方案。