Mining e-Learning domain concept map from academic articles

Recent researches have demonstrated the importance of concept map and its versatile applications especially in e-Learning. For example, while designing adaptive learning materials, designers need to refer to the concept map of a subject domain. Moreover, concept maps can show the whole picture and core knowledge about a subject domain. Research from literature also suggests that graphical representation of domain knowledge can reduce the problems of information overload and learning disorientation for learners. However, construction of concept maps typically relied upon domain experts in the past; it is a time consuming and high cost task. Concept maps creation for emerging new domains such as e-Learning is even more challenging due to its ongoing development nature. The aim of this paper is to construct e-Learning domain concept maps from academic articles. We adopt some relevant journal articles and conference papers in e-Learning domain as data sources, and apply text-mining techniques to automatically construct concept maps for e-Learning domain. The constructed concept maps can provide a useful reference for researchers, who are new to the e-Leaning field, to study related issues, for teachers to design adaptive learning materials, and for learners to understand the whole picture of e-Learning domain knowledge.     

Detailed Real-Time Urban 3D Reconstruction from Video

The paper presents a system for automatic, geo-registered, real-time 3D reconstruction from video of urban scenes. The system collects video streams, as well as GPS and inertia measurements in order to place the reconstructed models in geo-registered coordinates. It is designed using current state of the art real-time modules for all processing steps. It employs commodity graphics hardware and standard CPU’s to achieve real-time performance. We present the main considerations in designing the system and the steps of the processing pipeline. Our system extends existing algorithms to meet the robustness and variability necessary to operate out of the lab. To account for the large dynamic range of outdoor videos the processing pipeline estimates global camera gain changes in the feature tracking stage and efficiently compensates for these in stereo estimation without impacting the real-time performance. The required accuracy for many applications is achieved with a two-step stereo reconstruction process exploiting the redundancy across frames. We show results on real video sequences comprising hundreds of thousands of frames.     

A neural network-based approach for dynamic quality prediction in a plastic injection molding process

This paper presents an innovative neural network-based quality prediction system for a plastic injection molding process. A self-organizing map plus a back-propagation neural network (SOM-BPNN) model is proposed for creating a dynamic quality predictor. Three SOM-based dynamic extraction parameters with six manufacturing process parameters and one level of product quality were dedicated to training and testing the proposed system. In addition, Taguchi’s parameter design method was also applied to enhance the neural network performance. For comparison, an additional back-propagation neural network (BPNN) model was constructed for which six process parameters were used for training and testing. The training and testing data for the two models respectively consisted of 120 and 40 samples. Experimental results showed that such a SOM-BPNN-based model can accurately predict the product quality (weight) and can likely be used for various practical applications.     

游戏程序设计中若干问题的探讨

游戏编程是当今程序设计的一个热点,开发过程会遇到各种各样的问题。通过限制构造函数和拷贝函数,设计一个单体全局管理类,可以避免不合适的调用。采用分块技术加栽地图,可以在时空性能上优化游戏。阐述了D3D的空间坐标变换。分析了万向节死锁问题发生的原因,并提出了解决办法。     

改进自组织映射神经网络在指纹识别中的应用

改进自组织映射神经网络方法是将常规自组织映射神经网络方法结合确定性水平,对网络的输入矢量进行预处理。通过实验比较了这种改进的自组织映射神经网络识别方法与常规的自组织映射神经网络识别方法的识别效果,在识别性能上有了很大的提高。     

基于复合混沌动力系统的图像加密算法设计

本文通过对部分数字化混沌图像加密算法的分析研究,设计了一个基于复合离散混沌动力系统的对称图像加密算法。该对称图像加密算法充分利用混沌变化的特性,以Logistic映射和Chebyshev映射生成的混沌序列为初始序列,结合对图像的切割、拉伸、折叠变换,充分打乱图像像素间的相关性,使得针对这两个混沌映射的现有分析方法不再有效,并且可以实现较高的加密速度。实验结果证明了算法的有效性和计算速度。     

视频图像在三维模型中的渲染

视频监控是大型安防工作中最重要的一个环节,传统的视频监控系统展示给用户的只是独立的二维平面图像,图像脱离环境,整体性不足,为了解决该问题,提出了将视频图像渲染显示于三维模型的思路.研究了纹理映射技术并结合视频图像渲染的特殊性分析研究了Z缓冲算法、Shadow map算法,根据实际应用提出Extend Shadow map算法以实现将视频图像与三维场景无缝贴合.实验结果表明,视频图像渲染显示于三维模型中所体现的优越性.     

基于近似高斯金字塔的视觉注意模型快速算法

利用输入图像的近似高斯金字塔,将经典的基于显著性的视觉注意模型改造为时空开销更小的版本,从而使其更加适合在嵌入式实时系统中实现.首先采用矩形窗口近似圆形窗口,矩形平均算子近似高斯卷积核;然后采用“先做行累加,再做列累加”的方法来实现矩形平均算子,并直接采样计算出各个特征通道的显著性分布图,该算法关于输入图像像素点个数具有线性时间复杂度;最后,还给出了在显著性分布图中抑制已提取区域显著性的快速算法.在Berkeley分割图像库上的实验结果表明,该方法极大地减小了系统实现的时空开销,且输出结果的误差在可接受范围内.提出的用矩形窗口近似圆形窗口,用矩形平均算子近似高斯卷积核的方法,还适用于其他需要在嵌入式实时系统中实现的图像处理问题.     

彩色扫描军事地形图等高线提取方法

提出了一种基于HSV色彩模型的等高线提取方法.首先去除地形图中的黑色要素,然后选取原图等高线上一像素点色调值作为初值,按一定步长逐步扩大色调阈值,借助对应二值图连通区域数确定阈值区间.该算法无须人为指定聚类中心和类数,初始像素点的选取对提取结果不起决定作用.实验结果验证了算法的鲁棒性,并取得比较理想提取效果.     

离散混沌系统类随机性的符号熵分析法

采用符号熵分析法,分析和讨论了经典的Logistic映射和Henon映射的类随机性强弱.先将离散混沌系统产生的实数序列转化为二进制序列,然后进行编码,计算其符号熵,绘制其符号熵图,并深入讨论了系统参数和初始值对符号熵的影响.数值仿真分析表明,符号熵法能定量区别不同离散混沌系统类随机性的强弱.同时作为随机源,Logistic映射比Henon映射好.