Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach

Mining frequent patterns in transaction databases, time-series databases, and many other kinds of databases has been studied popularly in data mining research. Most of the previous studies adopt an Apriori-like candidate set generation-and-test approach. However, candidate set generation is still costly, especially when there exist a large number of patterns and/or long patterns.In this study, we propose a novel frequent-pattern tree (FP-tree) structure, which is an extended prefix-tree structure for storing compressed, crucial information about frequent patterns, and develop an efficient FP-tree-based mining method, FP-growth, for mining the complete set of frequent patterns by pattern fragment growth. Efficiency of mining is achieved with three techniques: (1) a large database is compressed into a condensed, smaller data structure, FP-tree which avoids costly, repeated database scans, (2) our FP-tree-based mining adopts a pattern-fragment growth method to avoid the costly generation of a large number of candidate sets, and (3) a partitioning-based, divide-and-conquer method is used to decompose the mining task into a set of smaller tasks for mining confined patterns in conditional databases, which dramatically reduces the search space. Our performance study shows that the FP-growth method is efficient and scalable for mining both long and short frequent patterns, and is about an order of magnitude faster than the Apriori algorithm and also faster than some recently reported new frequent-pattern mining methods.     

Visibility threshold in sharpness for people with different regional backgrounds

Abstract— The influence of regional background on the visibility of sharpness differences has been investigated by blurring various still images to different extents. The assessment of sharpness has been performed both in China by Chinese people and in the Netherlands by European people. The results showed that both Chinese characters and Roman text were clearly more critical image material for judging sharpness than natural images. Independent on whether the image contained Chinese characters or Roman text, the visibility threshold for a difference in sharpness was the same for both the Chinese and European people. When related to a diagonal step response, the threshold on average equaled an angular resolution of 5 arcsec.     

基于知识的装配序列规划方法研究

为了解决装配序列规划的计算机辅助生成问题,对产品的装配CAD模型进行了分析,得到与装配规划相关的几个重要信息,并对其进行知识表示。通过建立产品的装配特征矩阵,确定了装配零、部件在各个方向的自由度。根据从CAD模型中得到的信息和零、部件的自由度信息,制定了产品拆卸序列规划的推理规则和求解算法;按照“可拆即可装”的原则,倒置拆卸序列得到产品的装配序列。以球阀产品为例,详细介绍了本文提出的装配序列规划方法的应用。     

基于OpenGL的3DS图形文件中模型数据的获取

介绍了在OpenGL绘图环境下，从3DS文件中读取数据的方法，减少了复杂形体建模的工作量。     

周期余数法与智能测速系统

本文介绍了周期余数法测速的原理，分析了其性能。采用周期余数法的智能测速系统具有相对分辨率高、动态范围宽的特点，可用于各种实时控制系统。     

一种开关稳压电源电路

分析一种开关稳压电源的基本原理，介绍了它的电路结构及稳压过程。     

基于磁阻原理非接触式位移测量的非线性方法

针对低功耗和非接触式位移测量的应用需求，利用磁阻传感器，本文在传统的线性测量方法的基础上，提出了一种非线性的测量方法。设计了一个测量系统，实测结果表明该方法测量精度高、测量范围广、简单易用，也节省了成本。     

浅谈农机的信息化

通过对农机信息网现状的调查分析,指出农机网站存在的突出问题,提出解决农机信息网站建设的主要措施.     

基于Matlab 的链传动寿命计算及仿真

根据摩擦学原理，对多从动轮链传动的磨损使用寿命进行了研究，结合Matlab软件编程运算，构建了滚子链磨损使用寿命的计算模块，给出了多从动轮滚子链传动磨损寿命的计算公式，并进行了仿真计算。在已知工况下，仿真系统可以准确求解各段链条的磨损使用寿命及链条总预期磨损使用寿命。     

基于进化神经网络的电火花铣削加工电极损耗预测

针对电火花铣削加工的时变非线性特性,提出基于神经网络的电火花铣削加工电极损耗预测模型,利用该网络预测加工速度和工具的相对损耗,从而可在加工中实时计算出工具实际损耗量,为实现电极损耗的在线动态补偿打下基础。针对神经网络传统训练算法-BP算法的不足,提出了一种自适应调节变异率和变异量的进化算法来优化网络权值和网络结构,提高了网络的逼近精度和进化速度。