基于内容的网络异常信息过滤

虽然网络促进社会经济的发展与进步,但是在互联网规模的不断扩大下,恶意邮件和不良网络,以及不健康网络内容的传播等都将严重影响网络健康运行。因此,对内容的网络异常信息过滤的安全保护成为人们关注的焦点。通过简要介绍网络异常信息过滤,对网络异常信息过滤模型进行分析,并设计基于内容的网络异常信息过滤系统,同时通过试验与分析证明其实用的价值。     

基于行为模式进行网络搜索信息过滤

在网络信息搜索过程中会经常出现大量垃圾信息,这些垃圾信息,提高了用户查询有效信息的难度,浪费了用户查询有效信息的时间。本文提出一种利用行为模式识别技术,对网络搜索引擎获得信息结果进行过滤的方式,通过这种方式来提高网络搜索信息的准确率。     

手机上网文本信息过滤系统的设计与实现

随着手机上网业务的发展,手机网络的不良信息逐渐增多,引发很多社会问题,基于手机端的不良信息过滤软件又有很大的局限性,难以普及,基于服务器端,提出一种运用关键字过滤技术的手机上网文本信息过滤系统,实现不良文本信息的过滤。     

具有字符过滤功能的包过滤防火墙的设计研究

一、绪论传统的包过滤防火墙系统主要是包过滤规则以IP信息包为基础,对IP源地址、IP目标地址、封装协议(TCP/UDP)、端口号等进行筛选。只有符合访问条件的数据包才被转发,其它包被丢弃。其功能设计主要是为在IP层和传输层上进行过滤的,而内容过滤在传统的包过滤防火墙上是难     

中文新词提取与过滤研究综述

新词识别是中文信息处理领域的关键技术,而候选新词提取与垃圾串过滤是新词识别的必经阶段。中文文本不以特定的符号标志词的边界,因此任何相邻字符都有成词的可能性,这给新词提取与过滤带来了很大困难,先验知识与统计数据的缺乏使得新词提取成为中文词性标注的技术瓶颈。文章深入研究了中文新词识别技术中新词提取与过滤技术的研究现状,分析了新词提取与过滤技术中存在的问题,并对新词提取与过滤技术的研究方向进行了展望。     

基于多信息的柴油机缸套磨损故障诊断研究

采用了模糊神经网络模型，对柴油机缸套磨损故障以及缸套破坏性磨损故障进行了诊断研究．通过缸套磨损故障的模拟实验，获取柴油机机身振动和铁谱分析等多源多雏故障信息，并对融合故障信息进行预处理，解决了模糊神经网络输入矢量的模糊特性化、输出矢量的隶属函数及网络的学习训练问题，对缸套不同磨损故障进行了诊断．研究表明，这种基于多信息的诊断方法减小了故障诊断的不确定性，提高了诊断精度．     

对工程机械液压油过滤技术的研究

如今我们的企业所使用的工程机械多数都采用了机、电、液一体化的技术,而液压系统的技术状况的好坏是整个工程机械技术状况好坏的关键。液压系统的作用是通过压强的改变增大作用力。一个完整的液压系统是由五个部分构成,即执行元件、动力元件、辅助元件、控制元件和液压油。系统设计合理性、系统污染处理与防护、系统元件性能优劣决定了一个液压系统的好坏。而系统污染处理与防护尤为重要。近年来我国国内的液压技术已经有了很大的提高,不再是使用国外的液压技术完成工程机械的加工。本文将针对工程机械液压油污染问题的来源和危害．对液压油过滤技术展开探讨。     

垃圾短信的现状及过滤技术研究

随着通讯时代的到来,短信已成为人们生活中必不可少的工具之一,但是随之而来的垃圾短信,给人们的生活、工作带来一定烦恼,垃圾短信逐渐成为社会公害,需引起关注,将对当前垃圾短信的现状进行分析,并提出垃圾短信的过滤技术与解决方案,以净化通讯环境。     

活性炭过滤技术的变革

目前，90％的医药产品生产厂商都要利用活性炭清除杂质和异昧。但与此同时，如何将这些极为细小的活性炭粉末从最终成品中清理出去则成为一个生产过程的遗留问题。本文将向您介绍一种以深层过滤为基础的活性炭过滤方法，为您解决生产中的难题。     

基于多Agent混合智能实现个性化信息推荐

在基于Agent的个性化网页推荐中,目前主要有两种过程方法：基于内容的过滤和基于多Agent合作的过滤。本文分析了单独使用这两种方法存在的不足,给出了结合两种方法优点的混合智能过滤虎法,并通过网络Bookmark服务,给出了该算法的一个实际应用系统,最后对该系统的运行结果进行了定性分析。     

一种自适应的图像双边滤波方法

提出一种利用双边滤波的图像平滑滤波方法,即在滤除图像中高频噪声的同时,按照图像亮度变化保持图像中处于高频部分的边缘信息的自适应滤波过程。该滤波方法将传统的Gauss滤波器的权系数优化成Gauss函数和图像的亮度信息乘积的形式,优化后的权系数再与图像作卷积运算。这样,滤波时就可以考虑到图像的亮度信息,在滤除图像噪声的同时尽量保持了图像的边缘。由于双边滤波的方法可以使滤波器的权系数随着图像的亮度变化而改变,所以在滤波过程中能达到自适应滤波的目的。     

Information sharing in supply chains: Incentives for information distortion

The existing literature on supply chain information sharing assumes that information is shared truthfully. Unless each party can verify the authenticity of the other party's information, manufacturers and retailers may divulge false information for their own benefit. These information distortions may reduce the benefit levels or even stop information sharing in supply chains. We analyze the incentives for manufacturers and retailers within a supply chain to distort information when they share it and propose a mechanism that results in truthful information sharing. We consider a make-to-order supply chain consisting of a single manufacturer and a single retailer. The manufacturer and the retailer set prices based on their private forecasts of uncertain demand. If both parties share their forecasts truthfully, the manufacturer always benefits; however, the retailer benefits only if the manufacturer sets a lower wholesale price when information is shared compared to when information is not shared. However, we show that the manufacturer and the retailer, respectively, have an incentive to overstate and understate their forecasts while sharing information. The information distortion phenomenon is the direct result of each party exploiting its private information to appropriate the gains from information sharing. We show that the incentives to distort information are eliminated and both parties benefit from information sharing if the manufacturer and the retailer can agree on their relative profit margins prior to information sharing.     

中国标准信息服务网站比较分析

本文利用网站调研法和文献计量学方法,对200个提供标准信息服务的门户网站进行了全方位、多角度,深入细致的比较分析。提出各类型网站存在从资源检索,到结果展示等各种问题,凸显了国家技术标准资源服务平台共建共享的重要意义。     

Application of stochastic filtering for lifetime prediction

This paper introduces a stochastic filtering modeling approach for predicting the remaining lifetime of a component based on information on the stochastic degradation process and uncertain condition monitoring measurements. The model is illustrated by a case study, where the degradation is assumed to be a simplified fatigue crack growth process. The model accounts for uncertainties in both degradation process and condition measurements in a sound way. If completed with information on costs of monitoring, failure and replacement, such model could be used in optimizing both the condition monitoring intervals and, e.g. the replacement time for the component.     

国外网络空间不良信息管理与趋势

针对网络空间内容安全中各种不良信息(包括恐怖、谣言、诈骗、暴力、色情和颠覆等)的治理需求,本文综述了国外网络空间不良信息的管理情况。首先,对国外网络空间不良信息进行了定义和分类;其次,梳理了国外网络空间不良信息监管的法律法规,阐述了一些国家在立法中普遍采取的做法;再次,从网络数据监听、网络不良信息过滤与舆论对抗入手,着重介绍了世界主要国家对网络不良信息的治理技术与手段;最后,总结了近年来全球范围内部分互联网不良信息治理专项行动等。     

小波滤波在Shack-Hartmann传感器上的应用

在使用Shack-Hartmann传感器进行大口径非球面镜面检测中,外部环境的各种振动影响以及气流、温差的干扰都会使检测精度下降。针对这个问题,提出了一种新的时域小波滤波技术。这项技术可以对传感器的信号干扰在时间域上进行不同层次的小波分析,提取干扰信号的先验特征,对测量数据进行有效的滤波,减小波前的扰动起伏,以更准确地探测质心。实验结果表明,采用这种技术后,Shack-Hartmann波前传感器对光学镜面检测的静态测量精度提高了50%以上,离散性减少到原来的20%-30%。     

非线性结构系统识别的自组织蒙特卡洛滤波方法

摘 要：提出一种对扩展的非线性状态空间模型进行识别的自组织序贯蒙特卡洛滤波方法. 通过在原始状态空间模型中增加未知待识别参数来定义扩展的状态空间模型,该模型为自组织非线性状态空间模型,适用于解决噪声分布的自校正问题;同时该系统识别方法通过引入局部似然函数,可以从有限的有效数据中进行最优参数选取.给出了Bouc-Wen滞回系统识别的数值算例,证明了该方法的有效性.     

Particle filtering based pitch sequence correction for monaural speech segregation

This article proposes a novel speech and sound segregation framework incorporating a technique for correcting a series of pitch periods based on particle filtering. The conventional pitch track correction method finds the peak locations of the autocorrelation functions to estimate the pitch period, and only the longest reliable pitch streak is used to correct unreliable pitch tracks. Especially in noisy environments, it is hard to find long and reliable pitch streaks, resulting in the degradation of the speech segregation performance. The proposed algorithm based on particle filtering considers all the reliable pitch streaks rather than the longest one and smoothly connects the scattered pitch streaks. To apply the particle filtering algorithm to pitch track correction, the importance weight computation to account for the degree of matchness of the found pitch to the individual spectro‐temporal components is also proposed. The performance of the proposed method is evaluated by the results of speech segregation experiments for the mixtures of speech and various noise sources in various mixing signal‐to‐noise ratios (SNRs). The evaluation measures were SNR, energy loss ratio, and noise residue ratio of the segregated speech, and all these measures showed that the proposed segregation method achieved superior performance compared to the conventional approach. © 2013 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 23, 64–70, 2013.     

Bilateral filtering for structural topology optimization

Filtering has been a major approach used in the homogenization‐based methods for structural topology optimization to suppress the checkerboard pattern and relieve the numerical instabilities. In this paper a bilateral filtering technique originally developed in image processing is presented as an efficient approach to regularizing the topology optimization problem. A non‐linear bilateral filtering process leads to a suitable problem regularization to eliminate the checkerboard instability, pronounced edge preserving smoothing characteristics to favour the 0–1 convergence of the mass distribution, and computational efficiency due to its single pass and non‐iterative nature. Thus, we show that the application of the bilateral filtering brings more desirable effects of checkerboard‐free, mesh independence, crisp boundary, computational efficiency and conceptual simplicity. The proposed bilateral technique has a close relationship with the conventional domain filtering and range filtering. The proposed method is implemented in the framework of a power‐law approach based on the optimality criteria and illustrated with 2D examples of minimum compliance design that has been extensively studied in the recent literature of topology optimization and its efficiency and accuracy are highlighted. Copyright © 2005 John Wiley & Sons, Ltd.     

小波变换与卡尔曼滤波结合的RLG降噪方法

针对激光陀螺随机游走噪声其非平稳和非正态分布的特性,提出了基于小波变换的卡尔曼滤波的RLG降噪方法,该方法既具有小波变换对自相似过程的去相关作用和多分辨分析的功能,同时又保持了卡尔曼滤波器对未知信号的线性无偏最小方差估计的特点,实现了激光陀螺随机游走噪声的实时多尺度分解和最优估计。实测激光陀螺零偏信号去噪的结果表明,基于小波变换的卡尔曼滤波器使随机游走噪声的标准差降低了10.3%,降噪效果优于传统的卡尔曼滤波器。