探析新时代背景下中国家具设计的走向

本文阐述了我国前一时期家具行业存在的弊端,分析了我国家具业弊端的缘由及解决的方法,提出了中国家具业要告别依靠高投入、粗放式外延扩张来实现产业增长的方式。论述了今后的增长将主要依靠技术进步来实现,首先要更新设计理念,走出有中国特色的家具业之路,对中国现代家具设计方法、设计元素、设计观点进行了详细的论述并对未来中国家具业的进行展望。     

图像置乱效果评价算法综述

图像置乱技术通过对图像矩阵的重排操作,破坏图像矩阵的相关性,从而实现信息加密。图像置乱效果评价方法是对图像置乱程度的客观评价,目前涌现的图像置乱方法都从各个方面验证其自身的优越性,但仍没有一种通用的评判方法。该文根据最优置乱效果的定义,讨论了一些现有的图像置乱效果评判方法,在深入研究这些方法的原理后,对各置乱性能评判方法的客观性进行了深入分析和讨论。     

Localized relaxation theory of circuits and its applications in electro-thermal analyses

In the high-performance IC design with increasing design complexity,it is a very important design content to efficiently analyze IC parameters.Thus,the electro-thermal (ET) analyses including power/ground (P/G) analysis and thermal analysis are hot topics in today’s IC research.Since ET analysis equation has a sparse,positive definite and strictly diagonally dominant coefficient-matrix,we prove that the ET analysis has the advantage of locality.Owing to this advantage,localized relaxation method is formally proposed,which has the same accuracy as the global relaxation done with the constraint of the same truncation error limitation.Based on the localized relaxation theory,an efficient and practical localized successive over-relaxation algorithm (LSOR2) is introduced and applied to solve the following three ET analysis problems.(1) Single-node statistical voltage analysis for over-IR-drop nodes in P/G networks;(2) single-node statistical temperature analysis for hot spots in 3D thermal analysis;(3) fast single open-defect analysis for P/G networks.A large amount of experimental data demonstrates that compared with the global successive over-relaxation (SOR) algorithm,LSOR2 can speed up 1-2 orders of magnitudes with the same accuracy in ET analyses.     

Personalized course generation and evolution based on genetic algorithms

Online learners are individuals,and their learning abilities,knowledge,and learning performance differ substantially and are ever changing.These individual characteristics pose considerable challenges to online learning courses.In this paper,we propose an online course generation and evolution approach based on genetic algorithms to provide personalized learning.The courses generated consider not only the difficulty level of a concept and the time spent by an individual learner on the concept,but also the changing learning performance of the individual learner during the learning process.We present a layered topological sort algorithm,which converges towards an optimal solution while considering multiple objectives.Our general approach makes use of the stochastic convergence of genetic algorithms.Experimental results show that the proposed algorithm is superior to the free browsing learning mode typically enabled by online learning environments because of the precise selection of learning content relevant to the individual learner,which results in good learning performance.     

跳数加权DV-Hop定位算法

针对DV-Hop定位算法中距离估计误差对定位结果的影响,提出了一种信标节点优选方案和跳数加权DV-Hop定位算法。首先通过设定跳数阈值,保留跳数较少的信标节点,然后剔除近似在一条直线上的信标节点,完成信标节点优选,避免未知节点无法定位的情形。此外,利用Friis模型推导出距离估计误差与信号传播跳数之间的映射关系,采用传播跳数作为加权因子对定位结果进行了修正。仿真结果表明该算法降低了距离估计误差对定位精度的影响,提高了定位精度。     

基于半定规划的无线传感器网络定位算法性能分析

基于测距的定位方法是无线传感器网络节点定位中一种常见的方法。测距定位方法往往将定位过程转化为数学优化问题。介绍了实现测距定位下的LS-SDR与SAL-SDR两种半定规划定位算法,并同时介绍了LS-LM、SLS-LM、SLS-US与SLS-S等4种定位算法。仿真实验分析和比较了6种不同定位算法的平均RMS定位误差,结果表明相对于其他4种定位算法,LS-SDR和LS-LM算法的定位误差较小。在信标节点数量较少的情况下,LS-LM算法的定位结果有可能发生奇异,造成定位结果的严重失真。而LS-SDR算法对于奇异的发生具有较好的抵抗能力,此时LS-SDR算法的平均RMS定位误差将优于LS-LM算法。     

基于Android的多功能文件管理系统的设计与实现

文章所涉内容是一款基于Android的多功能文件管理系统的设计与实现。该设计以Android系统为开发平台,其目的是开发出一种方便用户使用的管理软件,使其具有文件浏览、文件权限的修改、添加文件到文件库、文件历史记录浏览、文件压缩以及文件加密等功能。     

浅析数据挖掘在CRM中的应用

电子商务加速发展,吸引了众多企业进军电商行业,加剧了企业对客户的竞争。因此,做好客户关系管理就显得非常重要。在简要描述数据挖掘和CRM（客户关系管理）的基础上,重点分析数据挖掘在CRM中的具体应用．包括如何获取新客户和如何提升客户的价值。这对电子商务企业的客户关系管理有参考价值。