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2009 First Asian Conference on Intelligent Information and Database Systems最新文献

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A Data Management System for Distributed Real-Time Emissions and Air Pollutants Monitoring System 分布式实时排放和空气污染物监测系统的数据管理系统
Pub Date : 2009-04-01 DOI: 10.1109/ACIIDS.2009.84
Junghee Kim, Youlin Jin, S. Lim, Karpjoo Jeong, J. Woo, Eun Yi Kim
Many people want to feel safe and secure by monitoring events and changes surrounding them that affect their quality of life. This concern prompted the development of the environment monitoring system. Among the many research groups, sensors and sensor network are their choice of tool for environment monitoring system. Data management is the most challenging issue when we are using sensor networks. To compose sensor network environment need various kind of sensors which does not have standard way to describe sensors and sensor data. In this paper, we will discuss the data management system for the Distributed Real-time Emissions Air pollutants Monitoring System (DREAM). In this system, we will discuss sensor data modeling and usage of those data.
许多人希望通过监控周围影响他们生活质量的事件和变化来获得安全感。这种关注促使了环境监测系统的发展。在众多的研究小组中,传感器和传感器网络是他们选择的环境监测系统的工具。当我们使用传感器网络时,数据管理是最具挑战性的问题。组成传感器网络环境需要各种各样的传感器,而这些传感器和传感器数据没有标准的描述方式。在本文中,我们将讨论分布式实时排放空气污染物监测系统(DREAM)的数据管理系统。在本系统中,我们将讨论传感器数据建模和这些数据的使用。
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引用次数: 1
Implicit Camera Calibration Using MultiLayer Perceptron Type Neural Network 基于多层感知器型神经网络的隐式摄像机标定
Pub Date : 2009-04-01 DOI: 10.1109/ACIIDS.2009.11
Dong-Min Woo, Dong-Chul Park
This paper suggest a new camera calibration approach based on the neural network model. The proposed approach is shown to be very accurate because the neural network model implicitly contains all the physical parameters, some of which are very difficult to be estimated in the conventional explicit calibration methods. As the first step of this approach, this paper presents the camera calibration process which enables the coordinate transformation between 2D image points and points of a certain space in 3D real world. However, this approach is currently extended to be a general 3D camera calibration method in terms of 2 plane method. Experimental comparison of our method with well-known Tsai's 2 stage method is made to verify the accuracy of the proposed method.
提出了一种基于神经网络模型的摄像机标定方法。由于神经网络模型隐式地包含了常规显式校准方法难以估计的所有物理参数,因此该方法具有很高的精度。作为该方法的第一步,本文给出了实现二维图像点与三维真实世界中一定空间点之间坐标转换的摄像机标定过程。然而,该方法目前被扩展为一种通用的2平面三维摄像机标定方法。将本文方法与蔡氏二阶段法进行了实验比较,验证了本文方法的准确性。
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引用次数: 6
Dynamic Packet Balancing Agent in MANETs Based on AOMDV 基于AOMDV的manet动态包均衡代理
Pub Date : 2009-04-01 DOI: 10.1109/ACIIDS.2009.50
Chen Ni, Hyeon-Cheol Zin, Bokman Lee, D. Hwang, Chonggun Kim
A MANET comprises a set of mobile devices which are capable of communicating with others. Despite its flexibility and portability, it suffers from energy limitation. If the energy consumption of the nodes in the MANET cannot be balanced efficiently, some nodes will die in an early stage due to the energy depletion, which in turn partitions the whole network and leads to the communication failure. To balance the energy consumption, we propose the dynamic packet balancing agent for MANETs. The agent utilizes the HELLO packets to update energy information along a path, which enables the dynamic update of the energy information of each path, and sends packets via the path with the best energy condition. The agent is further applied to AOMDV, a well-known multipath protocol. Simulation result generated by NS2(Network Simulator version 2) shows that our proposal outperforms AOMDV in balancing energy consumption.
MANET包括一组能够与其他人通信的移动设备。尽管它具有灵活性和便携性,但它受到能量限制。如果不能有效地平衡MANET中节点的能量消耗,一些节点会因为能量耗尽而过早死亡,从而导致整个网络被分割,导致通信失败。为了平衡能量消耗,我们提出了动态分组平衡代理。agent利用HELLO报文沿着一条路径更新能量信息,实现了每条路径能量信息的动态更新,并在能量状态最佳的路径上发送报文。该代理进一步应用于著名的多路径协议AOMDV。NS2(Network Simulator version 2)的仿真结果表明,我们的方案在平衡能耗方面优于AOMDV。
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引用次数: 5
An Approach to Identity Theft Detection Using Social Network Analysis 基于社会网络分析的身份盗窃检测方法
Pub Date : 2009-04-01 DOI: 10.1109/ACIIDS.2009.44
G. Kolaczek
The paper presents a method of automatic detection of identity theft related event. The method is based on the social network analysis. The protection of electronic identity in contemporary information society is one of the greatest challenge in security research. The main idea about method of identity theft detection described in the paper is that identity theft events are related to change of the subject’s behavior as the node of the social network (or several different networks). In consequence identity theft may be detected similarly as the other types of malicious activities by analyzing the change of observed behavior patterns.
提出了一种身份盗窃相关事件的自动检测方法。该方法基于社会网络分析。在当代信息社会中,电子身份的保护是安全研究的最大挑战之一。本文所描述的身份盗窃检测方法的主要思想是身份盗窃事件与作为社会网络(或几个不同网络)节点的主体的行为变化有关。因此,通过分析观察到的行为模式的变化,可以像检测其他类型的恶意活动一样检测身份盗窃。
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引用次数: 5
Leader Election for Multi-channel Radio Networks - Dependent versus Independent Trials 多信道无线网络的领导人选举——依赖与独立试验
Pub Date : 2009-04-01 DOI: 10.1109/ACIIDS.2009.29
Z. Golebiewski, Michal Koza, M. Klonowski, Mirosław Kutyłowski
We consider access scheduling to a shared radio channel in networks where a set of stations tries to get exclusive rights to transmit over a shared radio channel. A frequent strategy to solve this problem is that each station independently tosses an asymmetric coin and transmits in case of tails. The trials are executed some number of times and the first station that sends alone in a trial gets the right to broadcast over the shared channel. We consider here a multi-channel case: during onetime slot a station may transmit on k different channels.In this case trials can be arranged in two slightly different ways. The first method is that in each trial a station decides whether to participate in it; if it is so, then the station decides independently for each channel whether to transmit on it. According to the second method a station makes one decision whether to send and if the decision is positive it chooses a single channel for transmission. The second method guarantees a limited energy cost for each station but,as we show, turns out to be inferior regarding success probability. We consider these algorithms for a realistic number of stations. We analyze subtle differences between both algorithms regarding success probability.
我们考虑在网络中对共享无线信道的访问调度,其中一组电台试图获得通过共享无线信道的独家传输权。解决这个问题的一个常用策略是,每个站点独立地投掷一枚非对称硬币,并在反面的情况下进行传输。试验执行若干次,并且在试验中单独发送的第一个站获得在共享频道上广播的权利。我们在这里考虑一个多信道的情况:在一个时隙中,一个电台可以在k个不同的信道上传输。在这种情况下,审判可以以两种略有不同的方式安排。第一种方法是在每次试验中由一个工作站决定是否参加试验;如果是这样,那么电台独立决定是否在每个频道上传输。根据第二种方法,站做出是否发送的决定,如果决定是肯定的,则选择单个信道进行传输。第二种方法保证每个站点的能源成本有限,但正如我们所示,其成功概率较低。我们将这些算法考虑为实际数量的站点。我们分析了两种算法在成功率方面的细微差异。
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引用次数: 2
Intelligent Distributed Intrusion Detection Systems of Computer Communication Systems 计算机通信系统的智能分布式入侵检测系统
Pub Date : 2009-04-01 DOI: 10.1109/ACIIDS.2009.87
A. Grzech
The paper is devoted to present various intelligent, distributed network-based intrusion detection systems architectures and quality measures. Moreover an impact of network and their intrusion detection system architectures parameters on the intrusion detection systems quality is discussed.
本文介绍了各种基于分布式网络的智能入侵检测系统的体系结构和质量措施。讨论了网络及其入侵检测系统体系结构参数对入侵检测系统质量的影响。
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引用次数: 2
Short-Term Load Forecasting Using Support Vector Regression Based on Pattern-Base 基于模式基的支持向量回归短期负荷预测
Pub Date : 2009-04-01 DOI: 10.1109/ACIIDS.2009.52
Yingchun Guo, D. Niu
A new idea is proposed that preprocessing is the key to improving the precision of short-term load forecasting (STLF). This paper presents a new model of STLF which is using support vector regression (SVR) based on pattern-base. Our model can be described as follows: firstly, it recognizes the different patterns of daily load according such features as weather and date type by means of data mining technology of classification and regression tree (CART); secondly, it sets up pattern-bases which are composed of daily load data sequence with highly similar features; thirdly, it establishes SVR forecasting model based on the pattern-base which matches to the forecasting day. Since the patterns of daily load are treated beforehand, the rule of the historical data sequence is more obvious. The model has many advantages: first, since the training data has similar pattern to the forecasting day, the model reflects the rule of daily load accurately and improves forecasting precision accordingly; second, as the pattern variables need not to be input into model, the mapping of the categorical variables is solved; third, as inputs are reduced, the model is simplified and the runtime is lessened. The simulation indicates that the new method is feasible and the forecasting precision is greatly improved.
提出了预处理是提高短期负荷预测精度的关键思想。本文提出了一种基于模式基的支持向量回归(SVR)的STLF模型。我们的模型可以描述为:首先,利用分类回归树(CART)的数据挖掘技术,根据天气、日期类型等特征识别出日负荷的不同模式;其次,建立由特征高度相似的日负荷数据序列组成的模式库;第三,建立了与预测日匹配的基于模式库的支持向量回归预测模型。由于对日负荷模式进行了预先处理,因此历史数据序列的规律更为明显。该模型具有以下优点:第一,由于训练数据与预测日的模式相似,模型能准确反映日负荷规律,提高预测精度;其次,由于模式变量不需要输入到模型中,解决了分类变量的映射问题;第三,随着输入的减少,模型得到简化,运行时间也缩短了。仿真结果表明,新方法是可行的,预测精度大大提高。
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引用次数: 4
Fuzzy Classification of Incomplete Data with Adaptive Volume 不完全数据的自适应模糊分类
Pub Date : 2009-04-01 DOI: 10.1109/ACIIDS.2009.58
L. Yao, Kuei-Sung Weng, Ren-Wei Chang
For solving the incomplete data problem of missing feature values in prototype data, various strategies were proposed. In this paper, two improved approaches are proposed to estimate the missing values of incomplete data. The two approaches are based on combining the adaptive volume Gustafson-Kessel algorithm (GKA) and the nearest vector features under the distance norm evaluated by complete data. The GKA with adaptive volume is applied for clustering and classifying the results. At last, compared the result with other strategies, and the computer simulations show that the improved strategies provide superior effects.
针对原型数据中缺失特征值的不完全数据问题,提出了多种策略。本文提出了两种估计不完全数据缺失值的改进方法。这两种方法都是基于自适应体积Gustafson-Kessel算法(GKA)和在完整数据评估的距离范数下的最近向量特征相结合。采用具有自适应体积的GKA对结果进行聚类和分类。最后,将改进后的策略与其他策略进行了比较,并进行了计算机仿真,结果表明改进后的策略具有较好的效果。
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引用次数: 1
Extensions to the Relational Paths Based Learning Approach RPBL 基于关系路径学习方法RPBL的扩展
Pub Date : 2009-04-01 DOI: 10.1109/ACIIDS.2009.40
Zhiqiang Gao, Zhizheng Zhang, Zhisheng Huang
In this paper we extend RPBL, a Relational Paths Based Learning approach for first order theories in three directions. We apply domain theories to expand structured instance space, learn recursive theories by an example of learningmember relationship of lists, and analyze the performance as well as time complexity theoretically. In addition, we give the details of our experimental results.
本文从三个方面扩展了基于关系路径的一阶理论学习方法RPBL。应用域理论扩展结构化实例空间,以学习列表的成员关系为例学习递归理论,并从理论上分析了性能和时间复杂度。此外,我们给出了我们的实验结果的细节。
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引用次数: 6
An Information Extraction Approach to English-Vietnamese Weather Bulletins Machine Translation 英越天气预报机器翻译中的信息提取方法
Pub Date : 2009-04-01 DOI: 10.1109/ACIIDS.2009.90
S. Pham, G. Tran, Dang Duc Pham, Kien Chi Phung, Kien Trung Nguyen
In this paper, we present our method of using Information Extraction techniques to tackle the task of automatically translating English weather bulletins to Vietnamese. It is simple yet effective in satisfying the constraints of low processing power and storage space for the deployment on an embedded system. Experimental results are very promising with the F-measure going up to 96% for extracting relevant information from the weather bulletins.
在本文中,我们提出了一种使用信息提取技术来解决英语天气公报自动翻译成越南语的任务的方法。它简单而有效地满足了嵌入式系统部署的低处理能力和低存储空间的限制。实验结果表明,从天气预报中提取相关信息的f值高达96%。
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引用次数: 2
期刊
2009 First Asian Conference on Intelligent Information and Database Systems
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