Orientation-based unique representation for planar curves and shapes

This paper presents an orientation-based representation for planar curves and shapes. The new representation can uniquely represent all types, of planar shapes, be it convex, nonconvex, polygonal, smoothly curved, or piecewise smooth shapes. It is based on a new parameterization, theabsolute integral orientation. This representation is invariant under translation and rotation. The absolute integral orientation is a parameter invariant under scaling. As a result, matching of similar shapes (i.e., determination of the relative orientation and the scaling factor) using the absolute integral orientation as the parameter is easier than using the arclength as the parameter. In addition, the new representation has the feature of adaptive sampling, making it more compact and efficient than arc-length-based representations.     

微机传真系统

本文介绍了集传真技术、通信技术、微型计算机技术于一体的微机传真系统，提出了微机传真系统在硬件接口及报表识别上的实现方法。     

韶钢第五轧钢厂自动分槽器的设计与应用

介绍了韶钢第五轧钢厂自动分槽器的设计与应用．     

图像匹配中噪声分析和预处理

提出和证明了在三坐标测量机单镜头三维视觉系统中的图像噪声主要有三种：（1）电磁干扰噪声；（2）季节、气候和时间变化引起的噪声；（3）物体的位置和视角变化引起的噪声。相应地提出了一种基于优化图像搜索模块的有效减少和消除噪声的预处理方法。理论分析和实验均表明，该方法具有简便、可靠和速度快的优点。     

复杂系统建模——高维特征空间变量法

本文运用模式识别技术提出了一种分析和选择复杂系统变量的方法.运用该方法使得系 统的建模和控制简化.本文以复杂碳化过程作为实例,用模式识别技术对其内在规律进行分 析,找出了温度分布与结晶质量的定量关系.在此基础上,建立了碳化过程的动态模型.实践 表明,该模型与实际过程基本吻合,并已取得明显经济效益.     

模式识别催化剂生产调优

本文介绍如何将模式识别应用于生产调优,着重讨论了多指标(优化目标)因素的分级,提出了用模糊综合评价度量和依有序聚类最小损失函数准则划类,并相继进行变量与样本筛选、信息压缩、特征提取和模拟仿真获得优区操作条件,实施效果显著。     

人类HLA-DRB1基因型与民族和人群的神经网络无监督模式分类

HLA-DRB1等位基因主要参与人类的抗原免疫功能,对其进行比较研究,有助于追溯人类的进化迁移史,开发类群特异性药物.本研究以Matlab为平台,用自组织竞争网络(Self-Organizing Competitive Neural Network),对世界54个民族和人群、14个HLA-DRB1等位基因,进行了无监督模式分类.结果表明,各民族之间存在差异性,同民族的各人群之间有相似性.西伯利亚各人群,澳洲各土著人群,黑人各人群,南美印第安各人群,犹太族各人群,日本各人群,及欧美白人各人群有相对独立性:南美印第安人与西伯利亚人有高度相似性;中国民族在南方人群和北方人群间存在较大差异;中国汉族中,广东汉族地位特殊,与少数民族如拉祜族、瑶族关系密切.     

Class normalization in centroid-based text categorization

Centroid-based categorization is one of the most popular algorithms in text classification. In this approach, normalization is an important factor to improve performance of a centroid-based classifier when documents in text collection have quite different sizes and/or the numbers of documents in classes are unbalanced. In the past, most researchers applied document normalization, e.g., document-length normalization, while some consider a simple kind of class normalization, so-called class-length normalization, to solve the unbalancedness problem. However, there is no intensive work that clarifies how these normalizations affect classification performance and whether there are any other useful normalizations. The purpose of this paper is three folds; (1) to investigate the effectiveness of document- and class-length normalizations on several data sets, (2) to evaluate a number of commonly used normalization functions and (3) to introduce a new type of class normalization, called term-length normalization, which exploits term distribution among documents in the class. The experimental results show that a classifier with weight-merge-normalize approach (class-length normalization) performs better than one with weight-normalize-merge approach (document-length normalization) for the data sets with unbalanced numbers of documents in classes, and is quite competitive for those with balanced numbers of documents. For normalization functions, the normalization based on term weighting performs better than the others on average. For term-length normalization, it is useful for improving classification accuracy. The combination of term- and class-length normalizations outperforms pure class-length normalization and pure term-length normalization as well as unnormalization with the gaps of 4.29%, 11.50%, 30.09%, respectively.     

A reconfigurable VLSI-based double-lens tracking camera

Watching and tracking an object while seeing a much wider view is one of advantages of the eye system. We proposed and developed a tracking camera system that mimics the eyes by using double-lens modules. In the system, a wide view is captured through the wide-lens module, while the target in it is tracked and magnified through the telescopic lens module. Electronic circuits for tracking control are implemented onto the reconfigurable VLSI or FPGA in order to embed the parallelism in the tracking algorithm into the hardware. A successfully developed FPGA-based prototype performs high-speed tracking at the video-rate. This work was present in part at the 12th International Symposium on Artificial Life and Robotics, Oita, Japan, January 25–27, 2007