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2009 Ninth International Conference on Hybrid Intelligent Systems最新文献

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A Novel Method to Detect Junk Mail Traffic 一种检测垃圾邮件的新方法
Pub Date : 2009-08-12 DOI: 10.1109/HIS.2009.239
Qiang Li, Baoliang Mu
This paper proposes a junk mail or spam detection technique called ASCI (Abnormal SMTP Command Identification), which allows network administrators to cut off some spam traffic on email delivery. Our insight is that spamware usually generate special or abnormal packets deviating SMTP protocol for high throughout, while good users never do it. This characterization can be used to detect spam. ASCI is applied to two different volumes of email traffic data captured respectively near an email gateway and at a country-edged core router of a large commercial Internet Service Provider in China. Experimental results indicate that the method is effective and practical, with at least 11.4% reduction of email traffic for unwanted traffic
本文提出了一种称为ASCI(异常SMTP命令识别)的垃圾邮件或垃圾邮件检测技术,它允许网络管理员在电子邮件发送时切断一些垃圾邮件流量。我们的见解是,垃圾软件通常会在高流量时生成偏离SMTP协议的特殊或异常数据包,而好的用户从不这样做。这种特征可以用来检测垃圾邮件。ASCI应用于在中国一家大型商业互联网服务提供商的电子邮件网关附近和国家边缘核心路由器上捕获的两种不同数量的电子邮件流量数据。实验结果表明,该方法是有效和实用的,减少了至少11.4%的邮件流量
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引用次数: 2
Robust Image Hash Based on Cyclic Coding the Distributed Features 基于循环编码的分布式特征鲁棒图像哈希
Pub Date : 2009-08-12 DOI: 10.1109/HIS.2009.204
Sun-Woo Yang
Robust hash measure the similarity between two images by matching their short hash vectors. For its advantages of efficiency and versatility, robust hash has become a promising technology in image authentication and identification. Different to the traditional watermarking method, robust hash does not need to embed information into the host image. Therefore, it is promising to provide more robustness to geometrical distortions by robust hash. In this paper, a novel robust image hash algorithm is addressed on the issue of image rotation, which coding the distributed image features in cyclic manner, and the performance is discussed by an illustrative experiment.
鲁棒哈希通过匹配两个图像的短哈希向量来度量它们之间的相似性。鲁棒哈希以其高效、通用性强等优点,已成为图像认证和识别领域的一种很有前途的技术。与传统的水印方法不同,鲁棒哈希算法不需要在宿主图像中嵌入信息。因此,鲁棒哈希算法有望为几何畸变提供更强的鲁棒性。本文针对图像旋转问题,提出了一种新的鲁棒图像哈希算法,该算法以循环的方式对分布式图像特征进行编码,并通过一个说明性实验讨论了算法的性能。
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引用次数: 2
A Virtual Community Building Platform Based on Google Earth 基于Google Earth的虚拟社区建设平台
Pub Date : 2009-08-12 DOI: 10.1109/HIS.2009.183
Xu Huaiyu, Ni Qing, Su Ruidan, Hou Xiaoyu, Xiao Chao
Virtual community performs more and more important role for online users. Many tools for virtual community design, implementation and management have been developed, such as Virtual Reality (VR). On the other hand, few popular technologies have received frequent usage because of cost and time consuming. In this study, a platform for building virtual community more easily and quickly is proposed, which is called E-Life Platform (ELP) in our paper. ELP is based on Google Earth (GE) which provides high resolution global geographic information. The architecture of ELP system based on SketchUp is discussed in this paper. The detailed implementation of ELP is presented. Moreover, how to build a virtual community by using ELP is also described in this paper. Experimental results have shown the efficiency and low cost of ELP system.
虚拟社区在网络用户中扮演着越来越重要的角色。许多用于虚拟社区设计、实施和管理的工具已经被开发出来,例如虚拟现实(VR)。另一方面,由于成本和时间的原因,很少有流行的技术得到经常使用。本文提出了一种更方便、更快捷地构建虚拟社区的平台,即电子生活平台(E-Life platform, ELP)。ELP基于谷歌Earth (GE),提供高分辨率的全球地理信息。讨论了基于SketchUp的ELP系统的体系结构。给出了ELP的具体实现。此外,本文还介绍了如何利用ELP构建虚拟社区。实验结果表明,该系统效率高,成本低。
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引用次数: 1
Individual Cognitive Parameter Setting Based on Black Stork Foraging Process 基于黑鹳觅食过程的个体认知参数设置
Pub Date : 2009-08-12 DOI: 10.1109/HIS.2009.80
Z. Cui
Cognitive learning factor is an important parameter in particle swarm optimization algorithm(PSO). Although many selection strategies have been proposed, there is still much work need to do. Inspired by the black stork foraging process, this paper designs a new cognitive selection strategy, in which the whole swarm is divided into adult and infant particle, and each kind particle has its special choice. Simulation results show this new strategy is superior to other two previous modifications.
认知学习因子是粒子群优化算法中的一个重要参数。虽然已经提出了许多选择策略,但仍有许多工作需要做。受黑鹳觅食过程的启发,设计了一种新的认知选择策略,将整个群体分为成虫和幼虫,每一种幼虫都有其特殊的选择。仿真结果表明,该方法优于前两种改进方法。
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引用次数: 2
bSpace: A Data Cleaning Approach for RFID Data Streams Based on Virtual Spatial Granularity 基于虚拟空间粒度的RFID数据流数据清洗方法
Pub Date : 2009-08-12 DOI: 10.1109/HIS.2009.266
Baoyan Song, Pengfei Qin, Hao Wang, Weihong Xuan, Ge Yu
RFID holds the promise of real-time identifying, locating, tracking and monitoring physical objects without line of sight, and can be used for a wide range of pervasive computing applications. To achieve these goals, RFID data have to be collected, filtered, and transformed into semantic application data. RFID data, however, contain false readings and duplicates. Such data cannot be used directly by applications unless they are filtered and cleaned. To compensate for the inherent unreliability of RFID data streams, most RFID middleware systems employ a “smoothing filtering”. In this paper, a new “smoothing filtering” approach named bSpace is proposed, which is based on the concept of virtual spatial granularity. For providing accurate RFID data to applications, bSpace uses a Bayesian estimation algorithm to fill up false negatives, and uses the rules which we define to solve false positives.
RFID具有实时识别、定位、跟踪和监控无视线物理对象的前景,可用于广泛的普适计算应用。为了实现这些目标,必须收集、过滤RFID数据并将其转换为语义应用程序数据。然而,RFID数据包含错误读数和重复。这些数据不能被应用程序直接使用,除非它们经过过滤和清理。为了补偿RFID数据流固有的不可靠性,大多数RFID中间件系统采用“平滑过滤”。本文基于虚拟空间粒度的概念,提出了一种新的“平滑滤波”方法——bSpace。为了向应用程序提供准确的RFID数据,bSpace使用贝叶斯估计算法来填补假阴性,并使用我们定义的规则来解决假阳性。
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引用次数: 11
The Netlogo-Based Dynamic Model for the Teaching 基于网络语言的动态教学模型
Pub Date : 2009-08-12 DOI: 10.1109/HIS.2009.121
Longbin Jiang, Chun-xiao Zhao
This paper is to understand the dynamics of teaching behaviors based on complex adaptive system theory and methods of modeling. Due to the complexity and indetermination of complex systems, it is difficult to study the complex systems with the traditional reductive theory. The agent-based computer simulation is approved in the paper. Because classical interactions only among pre-set behavioral models may limit the capability to explore all possible evolution patterns, to tackle this issue, we introduce participating method to the MAS model, propose participator MAS(P-MAS)modeling method. In order to support this new approach, we introduce the concept and framework of artificial classroom (AC) for the first time by employing artificial societies. By adopting the bottom-up modeling technique and MAS model, the innovative dynamic model of AC is built. We have given a system structure of AC, design and implement an AC based on TCP/IP. The AC is currently being developed in NetLogo/HubNet. It provides a good tool to study classroom behaviors.
本文是基于复杂适应系统理论和建模方法来理解教学行为的动态性。由于复杂系统的复杂性和不确定性,用传统的还原理论来研究复杂系统是很困难的。本文对基于智能体的计算机仿真进行了验证。由于传统的行为模型之间的相互作用限制了探索所有可能的进化模式的能力,为了解决这一问题,我们将参与方法引入到MAS模型中,提出了参与者MAS(P-MAS)建模方法。为了支持这种新方法,我们首次引入了人工课堂(AC)的概念和框架。采用自底向上建模技术和MAS模型,建立了交流系统的创新动态模型。给出了交流系统的系统结构,设计并实现了一个基于TCP/IP的交流系统。AC目前正在NetLogo/HubNet中开发。它为研究课堂行为提供了一个很好的工具。
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引用次数: 1
A New Scan-Line Algorithm Using Clustering Approach 一种新的聚类扫描线算法
Pub Date : 2009-08-12 DOI: 10.1109/HIS.2009.129
Xiaoguang Tian, Yuke Ma, X. Hou
Correct recognition of the lines is essential for technical drawing understanding. Automation solution is quite difficult due to the limitations of machine vision algorithm. In order to promote development of better technology, according to the fast and high-quality clustering algorithm Particle Swarm Optimization (PSO), a new fast and high-quality line clustering algorithm present in this paper, that consisting of one scan-line connected components processing are clustered and an appropriate measure to recognize the pattern of every line including the dash-line in the drawing paper. The underlying mechanisms are excluding isolated components, a sequential stepwise recovery of components that meet certain continuity conditions and the results presented the node-tree structure that can enhance efficiency of computer. The performance of the algorithm is better in our experiment
对线条的正确认识对于理解技术图纸是至关重要的。由于机器视觉算法的限制,自动化解决相当困难。为了促进更好的技术发展,根据快速、高质量的聚类算法粒子群优化(Particle Swarm Optimization, PSO),本文提出了一种新的快速、高质量的直线聚类算法,该算法由一条扫描线相连的组件处理聚类,并采取适当的措施来识别图纸上包括虚线在内的每条直线的模式。其基本机制是排除孤立组件,对满足一定连续性条件的组件进行顺序逐步恢复,并给出了提高计算机效率的节点树结构。在我们的实验中,该算法的性能较好
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引用次数: 2
Simulation Study of AC Motor Speed Sensorless Vector Control System Based on SVPWM 基于SVPWM的交流电机无速度传感器矢量控制系统仿真研究
Pub Date : 2009-08-12 DOI: 10.1109/HIS.2009.108
Hui Jin, Yue-ling Zhao, Da-zhi Wang
The paper applies the Space Vector Pulse Width Modulation (SVPWM) algorithm to speed sensorless vector control system according to the theory of Space Vector Pulse Width Modulation, so as to enhance the stability and the performance of speed sensorless drives. The vector control strategy of the SVPWM voltage source inverter fed induction motor is studied. To testify the correctness and feasibility of the scheme, the simulation method is proposed to estimate the motor speed and realize a simple and high performance speed sensorless system. This system has been implemented on dynamic simulated tool SIMULINK of MATLAB software in AC motor. The simulation results show that the method gives satisfying estimation of stator flux and rotor speed in the whole speed range and can improve the control precision.
本文根据空间矢量脉宽调制理论,将空间矢量脉宽调制(SVPWM)算法应用于无速度传感器矢量控制系统,以提高无速度传感器驱动器的稳定性和性能。研究了SVPWM电压源逆变式异步电动机的矢量控制策略。为了验证该方案的正确性和可行性,提出了一种估算电机转速的仿真方法,实现了一种简单、高性能的无速度传感器系统。该系统已在MATLAB软件中的动态仿真工具SIMULINK上在交流电机上实现。仿真结果表明,该方法能在全转速范围内对定子磁链和转子转速进行较好的估计,提高了控制精度。
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引用次数: 11
Efficient k-Dominant Skyline Processing in Wireless Sensor Networks 无线传感器网络中有效的k-Dominant Skyline处理
Pub Date : 2009-08-12 DOI: 10.1109/HIS.2009.273
Jianmei Huang, Junchang Xin, Guoren Wang, Miao Li
Wireless sensor network amalgamates sensing, computing and communication technologies. Because of the energy limitation of sensor nodes, how to manage the data collected by the sensor nodes energy-efficiently becomes the focus of the research recently. As the main mean of multi-decision and data mining, skyline query plays a more and more important role in sensing applications. However, as the increase of data dimensionality, skyline query results extend greatly, which not only obstacles the decision, but also costs most of the energy of the nodes. In this article, k-dominant skyline query is researched deeply to deal with the above problem. An energy-efficient $k$-dominant skyline query algorithm (EKS) is proposed to calculate the $k$-dominant skyline of the wireless sensor network. The experimental results show that EKS could reduce the communication cost of the sensor network,while it calculates the k-dominant skyline, therefore, prolong the life-span of it.
无线传感器网络融合了传感、计算和通信技术。由于传感器节点的能量有限,如何对传感器节点采集到的数据进行高效的能量管理成为当前研究的热点。天际线查询作为多决策和数据挖掘的主要手段,在传感应用中发挥着越来越重要的作用。然而,随着数据维数的增加,skyline查询结果的扩展很大,这不仅阻碍了决策,而且耗费了节点的大部分能量。本文对k-显性天际线查询进行了深入研究,以解决上述问题。为了计算无线传感器网络的k主导天际线,提出了一种高效的k主导天际线查询算法(EKS)。实验结果表明,EKS可以降低传感器网络的通信成本,同时计算k-dominant skyline,从而延长传感器网络的寿命。
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引用次数: 4
A Classification Algorithm Based on an Association Rule of Multiple Frequent Item-Sets 基于多频繁项集关联规则的分类算法
Pub Date : 2009-08-12 DOI: 10.1109/HIS.2009.271
Zhiheng Liang
It is necessary to discrete datasets firstly if you want to data mining an association rule of datasets consisting of many categorical and numeric attributes by a traditional algorithm. However, in view of the versatility, the applications of the traditional algorithm are limited. This paper propose a new algorithm called ARMFI(Association Rule of Multiple Frequent Item-sets) which can data mining an Association Rule from datasets consisting of many categorical and numeric attributes directly and completely, and overcome disadvantage of the traditional algorithm. The result has been proofed that the ARMFI shows better performances than the traditional algorithm¿
如果要用传统的算法对由许多分类属性和数值属性组成的数据集进行关联规则挖掘,首先需要对离散数据集进行挖掘。然而,由于其通用性,传统算法的应用受到了限制。本文提出了一种新的算法ARMFI(Multiple frequency item -set Association Rule of Multiple frequency item -set),该算法可以直接完整地从由许多分类属性和数字属性组成的数据集中挖掘出关联规则,克服了传统算法的缺点。实验结果表明,该算法比传统算法具有更好的性能
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引用次数: 0
期刊
2009 Ninth International Conference on Hybrid Intelligent Systems
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