浅析展示空间界面的导向设计

文章基于视知觉及环境心理学的理论平台,从参观者对空间的形状、色彩、光照等方面的知觉体验入手,进而对空间界面的各个元素可产生的导向性加以逐步论述,得出了展示空间界面导向设计的原理和方法,表明空间层面导向系统的建立,将有效的促进整个展示空间中参观者路线的条理化,完善现今展示空间中标牌加文字来表现导向的单一形式,提高人们对展示内容的接受度。     

基于MP-BGP扩展的4over6隧道技术的实现

随着IPv4地址资源的日益枯竭,互联网从IPv4向IPv6过渡势在必行。为了进一步推动该校IPv4向IPv6的平稳过渡,文章经过技术论证后,采用MP-BGP扩展的4over6隧道技术,构建了一个IPv4over IPv6实验网络平台,使运行IPv4单协议栈的网络能够跨越IPv6骨干网络实现互联互通。     

一种自适应的仿生图像增强方法:LDRF算法

为了研究基于人类视觉系统特性(亮度自适应特性和视网膜神经元感受野非经典侧抑制特性)的仿生图像处理方法,增强仿生图像增强算法的自适应性,提出了一种新的自适应仿生图像增强算法——LDRF算法.LDRF算法首先建立参数对数模型对图像全局亮度进行自适应调整,然后采用三高斯动态滤波进行局部细节增强,引入Wal-lis算子建立增益因子模型,使局部细节增强具有自适应性,最后通过线性变换恢复图像彩色信息.在大量图像上进行对比实验和分析.实验结果证明,LDRF算法能够避免过增强现象,并且针对不同大小、不同内容的图像能够自适应地进行图像增强,取得了较好的效果,提高了仿生图像增强算法的实用性.     

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。     

网络环境下计算机信息安全分析

随着网络信息技术的不断发展,人们对于网络信息的需求与依赖性逐渐增强。然而,网络在带给人们便利的同时,也带来了很多的不安全因素,主要表现在信息泄露、信息篡改、非法占有网络信息与网络资源等。因计算机信息安全隐患的存在,个人、企业遭受"攻击"的计算机信息安全事件时有发生,并造成了巨大的经济损失。因此,加强网络环境下的计算机信息安全管理工作就显得很有必要。本文就网络环境下计算机信息安全问题展开探讨。     

引入蜜罐技术的局域网安全研究

由于网络攻击行为的日益复杂多样,传统的网络安全系统无法全面有效地对局域网进行防护。本文介绍了蜜罐技术的运行机制,并将之引入局域网安全体系,扬长补短,提出了更为积极主动的局域网安全防御思路。     

基于XML异构数据库数据转换技术的研究

文章是对数据共享和同步技术的研究,主要是针对不同部门数据库之间的数据转换技术,采用系统服务组件的设计理念,耦合程度低。主要实现方式是采用XML文件格式来描述异构数据库的结构信息,然后采用模糊匹配的方式计算两个数据库的异构程度,抽象出符合目标数据库的表结构。最后按照这个结构抽取源数据库的有用数据,导入目标数据库中。     

A new intelligent prediction system model-the compound pyramid model

A current development trend in research on intelligent systems is to optimize a general intelligent prediction system into an individuation intelligent prediction system that is applied in specialized fields. Protein structure prediction is a challenging international issue. In this paper, we propose a new intelligent prediction system model, designed as a multi-layer compound pyramid model, for predicting secondary protein structure. The model comprises four independent intelligent interfaces and several knowledge discovery methods. The model penetrates throughout the domain knowledge, with the effective attributes chosen by Causal Cellular Automata. Furthermore, a high pure structure database is constructed for training. On the RS126 dataset, the overall state per-residue accuracy, Q3, reached 83.99%, while on the CB513 dataset, Q3 reached 85.58%. Meanwhile, on the CASP8 sequences, the results are superior to those produced by other methods, such as Psipred, Jpred, APSSP2 and BehairPred. These results confirm that our method has a strong generalization ability, and that it provides a model for the construction of other intelligent systems.     

基于游程编码思想的条码定位与识别方法

在复杂背景中的定位条码是图像式条码识别系统中的一个关键步骤,如何在复杂的背景中快速、白动地检测出条形码是该文的主要研究内容。首先介绍了条型码的编码结构,然后提出了一种基于游程编码思想的条码定位与识别方法,最后通过给出相关实验结果,验证了该算法的可行性和实用性。     

An incentive scheduling mechanism for peer-to-peer video streaming

P2P video streaming networks are found as a scalable solution and an alternative for traditional client–server based video streaming over the Internet. One of the significant issues affecting the success of any P2P streaming network is cooperation between peers. Practical observations have proved the prevalence of free riders in P2P networks that degrade their performance. To solve this problem, using incentive mechanisms, which encourage peers to contribute more in the network, is necessary. In this paper, we designed and proposed a distributed and scalable incentive mechanism for mesh based P2P video streaming networks. In the proposed approach the contribution of the peers is measured and maintained in a distributed fashion. Furthermore, we proposed an incentive sending side scheduler in which peers are served based on their contribution in the network. Our simulation evaluations show the efficiency of the proposed approach in improving the overall perceived video quality by the non-free rider nodes and consequently in the whole network.