基于网格相邻关系的离异点识别算法

离异点是偏离部分观察对象的数据点,根据离异点所在单元的密度与相邻单元的密度相比可能偏高或偏低的特点,本文提出了基于网格相邻关系的离异点识别算法GAO。该算法用单元间的相对密度和单元质心距离来衡量单元间的离异度,根据离异度确定离异单元和离异点。实验结果表明,该算法能有效地识别出多密度数据集的离异点,算法的效率优于Cell-based算法,且适合大数据集的离异点识别。     

磁悬浮通信系统的误码性能分析及改进

磁悬浮车地通信系统承担着在高速列车和地面之间传输监控信息的重要任务,因此对误码率要求较高。在某一确定的信道条件下,决定误码率的主要因素是调制和编码,本文在对传统车地无线通信系统的误码性能做出定量分析的基础上,提出以正交振幅调制（QAM）和卷积码相结合的方案替代传统的频移键控（FSK）和循环码,仿真证明,改进方案将误码率提高了3到5个数量级。     

基于自适应灰色模型的路面使用性能预测

在灰色理论建模的基础上,通过采用预测的最新数据替代最老数据这种方式,建立了自适应灰色模型,并将其应用于路面使用性能预测。能够克服缺少历史数据的不足,同时,与以往的预测模型相比,更加准确,更加符合路面使用性能的变化规律。通过MATLAB编程实现,使得预测更加简便易行。     

一种新的动态网页程序的防篡改系统

动态网页技术越来越多地应用于互联网,确保动态网页脚本的安全性的需求与日俱增,该文实现了一种新的基于脆弱性数字水印技术的动态网页应用程序防篡改系统,阐明了能够应用在动态网页防篡改系统中的脆弱性数字水印提取算法应该具有的特性,评估了系统运行的效率,证明了该系统嵌入水印和检测水印的过程的高效性,还对比证明了该系统相对于入侵检测系统有着更广泛的保护范围。     

基于模式搜索的连续函数寻优

模式搜索方法是求解最优化问题的一种直接搜索方法,它只根据函数值信息来进行求优。但模式搜索对起始点非常敏感,对好的起始点,模式搜索可以搜索到全局最优点,但对某些起始点,模式搜索只能搜索到局部极值点。本文提出基于模式搜索的一个新方法,实验证明,它能搜索到全局最优。     

战略网络形成动因之制造模式篇

本研究目的在于探究战略网络生成中制造模式的推动作用。文章首先分析了制造模式在技术经济范式变迁中扮演的角色,总结出制造模式与技术经济范式之间的关系,接着运用数学抽象和哲学思辨的方法,提炼出人类历史上三次制造模式对技术经济范式的价值实现函数。基于该函数研究发现:精益生产中目的在于充分调动人的主观能动性,以实现人的解放的复合机制——现场管理、劳工关系管理和知识管理等体系是制造模式未来的发展方向;战略网络的演进服务于制造模式的价值实现功能,它的生成是为了弥补制造模式柔性不足的缺陷。     

多平台下动态采集税控数据的技术研究

在商业税收领域中,不同的行业、商家,可能会采用不同的系统平台来完成他们各自的销售任务,这就给国家税收时获取税控数据带来了一定的挑战。本文基于国家信息化标准委员会针对税控收款机的国家标准,提出并实现了一种在多平台下动态采集税控数据的解决方案。     

On fuzzy boundary value problems

The statement that a two-point boundary value problem of fuzzy differential equation is equivalent to a fuzzy integral equation was pointed out by Lakshmikantham et al. and O’Regan et al. Recently Bede gave a counterexample to show that this statement does not hold and he also argued that in many cases two-point boundary value problems have no solutions. Under a new structure and certain conditions we show that a two-point boundary value problem is equivalent to a fuzzy integral equation. We also prove the existence of solutions to the two-point boundary value problem. In some sense, this is an amendment to results of Lakshmikantham et al. and O’Regan et al., and it is an answer to one of Bede’s problems.     

A rough margin based support vector machine

By introducing the rough set theory into the support vector machine (SVM), a rough margin based SVM (RMSVM) is proposed to deal with the overfitting problem due to outliers. Similar to the classical SVM, the RMSVM searches for the separating hyper-plane that maximizes the rough margin, defined by the lower and upper margin. In this way, more data points are adaptively considered rather than the few extreme value points used in the classical SVM. In addition, different support vectors may have different effects on the learning of the separating hyper-plane depending on their positions in the rough margin. Points in the lower margin have more effects than those in the boundary of the rough margin. From experimental results on six benchmark datasets, the classification accuracy of this algorithm is improved without additional computational expense compared with the classical ν-SVM.     

An extensible and lightweight architecture for adaptive server applications

Server applications augmented with behavioral adaptation logic can react to environmental changes, creating self‐managing server applications with improved quality of service at runtime. However, developing adaptive server applications is challenging due to the complexity of the underlying server technologies and highly dynamic application environments. This paper presents an architecture framework, the Adaptive Server Framework (ASF), to facilitate the development of adaptive behavior for legacy server applications. ASF provides a clear separation between the implementation of adaptive behavior and the business logic of the server application. This means a server application can be extended with programmable adaptive features through the definition and implementation of control components defined in ASF. Furthermore, ASF is a lightweight architecture in that it incurs low CPU overhead and memory usage. We demonstrate the effectiveness of ASF through a case study, in which a server application dynamically determines the resolution and quality to scale an image based on the load of the server and network connection speed. The experimental evaluation demonstrates the performance gains possible by adaptive behavior and the low overhead introduced by ASF. Copyright © 2007 John Wiley & Sons, Ltd.