QFD质量职能扩展简介

介绍ＱＦＤ（质量职能扩展）的发展历史及其具体的操作过程。     

Image segmentation towards new image representation methods

Very low bit-rate video coding has recently become one of the most important areas of image communication and a large variety of applications have already been identified. Since conventional approaches are reaching a saturation point, in terms of coding efficiency, a new generation of video coding techniques, aiming at a deeper “understanding” of the image, is being studied. In this context, image analysis, particularly the identification of objects or regions in images (segmentation), is a very important step. This paper describes a segmentation algorithm based on split and merge. Images are first simplified using mathematical morphology operators, which eliminate perceptually less relevant details. The simplified image is then split according to a quad tree structure and the resulting regions are finally merged in three steps: merge, elimination of small regions and control of the number of regions.     

An approach to automatic display layout using combinatorial optimization algorithms

The introduction of automatic display layout (ADL), i.e. the automatic placing and sizing of windows in a window-oriented graphical user interface, is a major contribution towards an improved user interface. Our approach to ADL is to treat this problem as a combinatorial optimization problem. In this article we describe the concepts we used for implementing an experimental system which controls the computer screen contents and its layout. We give two examples of different standard applications into which we included ADL successfully, namely hypertext for a window layout problem and graph-browser for a hierarchical graph layout problem within a particular window. The results show that automatic (and tool independent) display layout will be possible in the near future even in an interactive environment.     

基于进化计算的兴趣建模

为实现对个体的兴趣建模,提出基于进化计算的建模(Evolutionary Computation Based Modeling,ECBM)方法。该方法采用定性和定量相结合的方式对个体的兴趣系统进行建模,首先通过定性分析构建个体的兴趣模型框架,然后通过进化计算(Evolutionary Computation)方法对模型参数自动进化。实验结果表明,ECBM能够通过数据驱动模式优化模型参数,并利用更新信息进化模型,使其不断逼近真实系统。     

恶意软件鉴别技术及其应用

随着互联网技术的发展和安全形势的变化,恶意软件的数量呈指数级增长,恶意软件的变种更是层出不穷,传统的鉴别方法已经不能及时有效的处理这种海量数据,这使得以客户端为战场的传统查杀与防御模式不能适应新的安全需求,各大安全厂商开始构建各自的"云安全"计划。在这种大背景下,研究恶意软件检测关键技术是非常必要的。针对恶意软件数量大、变化快、维度高与干扰多的问题,我们研究云计算环境下的软件行为鉴别技术,探讨海量软件样本数据挖掘新方法、事件序列簇类模式挖掘新模型和算法及在恶意软件鉴别中的应用,并构建面向云安全的恶意软件智能鉴别系统原型以及中文钓鱼网站检测系统架构。     

兴趣和蚁群相结合的非结构化P2P搜索算法

针对传统flooding搜索算法面临的效率低下和网络流量过大等问题,提出了一种改进的基于兴趣和蚁群相结合的资源搜索算法（IASA）。该算法将TTL机制加以改进,并将兴趣相似度引入到蚁群算法的路径概率选择中,同时结合信息素的多样性和正反馈机制,积累历史搜索经验,获得路由指引信息,从而有效地指导查询请求消息的转发,将请求消息尽量发往资源可能存在的节点上。仿真实验表明：该算法能有效地指导资源搜索的方向,提高查询命中率,减少冗余消息包,其整体搜索效果较好。     

基于用户兴趣度的校园网带宽管理策略应用研究

针对校园网出口拥塞问题,提出一种基于行为分析的用户兴趣建模方法,通过用户参与时间来衡量并计算不同种类应用的用户访问兴趣度,在用户兴趣度的基础上结合通道管理技术进行带宽管理策略研究,实现动态带宽管理。实施结果表明,该方法能够有效地提高用户的网络满意度。     

基于知识图谱的互补项目推荐

在缺乏用户交互互补项目方面数据的情况下,将用户对项目的偏好融合到只考虑项目关系的互补项目推荐中,提高推荐模型的性能。提出一种基于知识图谱的互补项目推荐方法,在用户历史交互项目集中推测用户交互的互补项目,基于知识图谱提取用户对互补项目的偏好,利用图像与文本学习项目之间的互补关系,最后基于神经网络实现二者的共同学习。提出的方法在Amazon数据集上与次优的基线方法相比,ACC提升了7%,precision提升了3%,这说明提出的方法性能优异。该算法共同学习用户对项目的偏好与项目之间的互补关系,提升了推荐性能。     

DETECTOR: A knowledge-based system for injection molding diagnostics

A knowledge-based system (KBS) for diagnosis of multiple defects in injection molding is presented. The general scheme for knowledge representation based on fuzzy set theory has been shown useful in representing inexact and incomplete information for developing the KBS. An optimality criterion is created for selecting a simple and best cover to explain the given problem. An efficient search algorithm for finding such cover is also discussed.