基于.NET的研究生管理信息系统的设计与实现

随着我国的研究生教育规模不断扩大,迫切需要科学化、信息化的管理。针对研究生管理现状,建立一个适应研究生管理规律的基于Web的研究生管理信息系统,规范研究生教育教学过程,对提高研究生教育管理水平和工作效率有很好的促进作用,同时,也有利于提高研究生的教育教学质量。     

警用脉冲防暴水炮管外动力过程数值模拟

为研究脉冲防暴水炮发射后在管外的动力过程,在Open FOAM软件上利用LES和VOF相耦合的方法对脉冲防暴水炮气液两相流流动过程作数值模拟。对水炮发射过程及其在距端口1.5m范围内的压力分布和速度分布做了分析。用SAMPLE软件对流场数据进行了采样,得到了用其它手段难以获得的数据。模拟表明,液柱形状急剧变化,首先形成蘑菇形,接着被压缩成半球形,在球形内部压力的作用下,半球形液弹被压缩成弧形。压力的作用距离集中在距端口300mm范围内,并很快降到了0.4MPa以下,其间因为压力有一个二次突然释放的过程,造成了二次喷射现象。速度是一个急剧先增加后减小的过程。所采用的圆柱式喷嘴使压力和速度下降太快,不利于提高水炮射程,需要改用其它类型的喷嘴。     

一种内容完整的视频稳定算法

设计了一种基于可靠特征集合匹配的内容完整的视频稳定算法。为了避免运动前景上的特征点参与运动估计,由经典的KLT(Kanade-Lucas-Tomasi)算法提取特征点,而后基于特征有效性判定规则对特征点集合进行有效性验证以提高特征点的可靠性。利用通过验证的特征点对全局运动进行估计,得到精确的运动参数并据此对视频图像进行运动补偿。对于运动补偿造成的无定义区,首先计算当前帧的定义区与相邻帧的光流,以此为向导腐蚀无定义区;利用拼接的方法,填充仍为无定义区的像素。实验结果表明该算法对于前景物体运动具有较好的鲁棒性并能够生成内容完整的稳定视频序列。     

基于SAIL模型的HJ-1卫星LAI反演算法研究

基于辐射传输模型和人工神经网络算法,研究出适用于环境一号卫星CCD相机数据的叶面积指数反演算法针对环境一号卫星CCD相机的波段特征,设计出一种新的植被指数HJVI,有效的避免了数据饱和现象,提高了算法的精度。     

Binary-image comparison with local-dissimilarity quantification

In this paper, we present a method for binary image comparison. For binary images, intensity information is poor and shape extraction is often difficult. Therefore binary images have to be compared without using feature extraction. Due to the fact that different scene patterns can be present in the images, we propose a modified Hausdorff distance (HD) locally measured in an adaptive way. The resulting set of measures is richer than a single global measure. The local HD measures result in a local-dissimilarity map (LDMap) including the dissimilarity spatial layout. A classification of the images in function of their similarity is carried out on the LDMaps using a support vector machine. The proposed method is tested on a medieval illustration database and compared with other methods to show its efficiency.     

Image categorization: Graph edit distance+edge direction histogram

This paper presents a novel algorithm for computing graph edit distance (GED) in image categorization. This algorithm is purely structural, i.e., it needs only connectivity structure of the graph and does not draw on node or edge attributes. There are two major contributions: (1) Introducing edge direction histogram (EDH) to characterize shape features of images. It is shown that GED can be employed as distance of EDHs. This algorithm is completely independent on cost function which is difficult to be defined exactly. (2) Computing distance of EDHs with earth mover distance (EMD) which takes neighborhood bins into account so as to compute distance of EDHs correctly. A set of experiments demonstrate that the newly presented algorithm is available for classifying and clustering images and is immune to the planar rotation of images. Compared with GED from spectral seriation, our algorithm can capture the structure change of graphs better and consume 12.79% time used by the former one. The average classification rate is 5% and average clustering rate is 25% higher than the spectral seriation method.     

Generating CAM aspect-oriented architectures using Model-Driven Development

Aspect-Oriented Software Development promotes the separation of those concerns that cut across several components and/or are tangled with the base functionality of a component, through all phases of the software lifecycle. The benefit of identifying these crosscutting concerns (aspects) at the architectural level in particular is to improve the architecture design and its subsequent evolution, before moving onto detailed design and implementation. However, software architects are not usually experts on using specific AO architecture notations. Therefore, the aim of this paper is to provide support to define and specify aspect-oriented (AO) architectures using non-AO ones as the source. We will use the Model-Driven Development approach to transform a component-based architecture model into an AO architecture model. The CAM (component and aspect model) model and the DAOP–ADL language are the proposals used for modelling and specifying AO architectures. We will show how we automated part of the process and the tool support.     

A framework to analyze information systems as knowledge flow facilitators

This paper presents a framework which can be used to analyze information systems as knowledge flow facilitators in organizational processes. This framework may be useful, particularly to small organizations, for two main reasons: it can help them to start seeing the implications of KM in their current technical infrastructure, and as a result, they should be in a better position to know how to include their current working tools in part of a KM strategy, thus facilitating the alignment of such a strategy to the daily work of the organization. Second, identifying the role that their current tools play in the flow of knowledge should help such organizations to identify means by which to improve such tools as KM enablers, before becoming engaged in costly KM efforts that could require the acquisition of new tools and often also big changes in their current work processes. The applicability of the framework is illustrated with a case study conducted in a software development environment in which it was successfully applied.     

基于序列聚类的事件流数据特征分析

事件流是近年来兴起的一种对实时进入系统的海量数据进行分析查询的应用,而数据特征是评价系统所需要的负载模型的重要部分。以网络安全监控为背景,提出一种将事件流聚集成时间序列并进行相似性聚类来分析数据特征的方法。通过适当的粒度聚合,将事件流转化成时间序列,选取周期性的时间序列作为代表消除随机干扰,给出基于序列线性相似性的聚类算法。聚类试验表明,具有相似时间特征的事件流可以被有效地聚集到同一类中。     

基于直接估计梯度思想的数据降维算法

高维非线性数据的降维处理对于计算机完成高复杂度的数据源分析是非常重要的。从拓扑学角度分析,维数约简的过程是挖掘嵌入在高维数据中的低维线性或非线性的流形。该文在局部嵌入思想的流形学习算法的基础上,提出直接估计梯度值的方法,从而达到局部线性误差逼近最小化,实现高维非线性数据的维数约简,并在Swiss roll曲线上采样测试取得了良好的降维效果。