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Peer-to-Peer (P2P) technologies are considered as one of the fundamental technologies for the next generation Internet. P2P systems are classified into unstructured P2P systems or structured P2P systems depending on their topological structure of network. Most structured P2P systems are based on Chord protocol that is designed by using Distributed Hash Tables (DHTs). However, some issues have not...
A water quality comprehensive evaluation was taken for the water in water supply network. It was on the basis of water supply network microcosmic model. The water quality indicators, by which the state of water quality was expressed, were chosen as the input vector for the comprehensive evaluation model. The self-organizing feature map and k-means arithmetic were taken in the model. As a result, a...
Track initiation is an important part in multi-target tracking, especially for the lower observable targets under the condition of heavy clutter. Multi-Hough transform track initiation for detecting target with constant acceleration in heavy clutter environment is proposed. In this algorithm, standard Hough transform is used to filter clutter first. Then sift the candidate tracks by using randomized...
Incorporating knowledge into a statistical unsupervised model, an approach of semantic dependency analysis on Chinese is presented. Semantic units and part dependency relationships are identified based on knowledge first, and then analysis is given by training the unsupervised model with extended inside-outside algorithm. Despite F1 of the experiments is not better than that of supervised approach,...
Clustering is one of the important means of Intrusion detection. In order to overcome the disadvantages of fuzzy C-means algorithm, this paper presents a kind of improved fuzzy C-means algorithm (IFCM for short). IFCM algorithm reduces the infection of isolated point by means of weighting the degree of membership for objects to be clustered, and avoids the subjectivity in choosing the number of clustering...
On the base of NS-IMMC, this paper propose a new method of generating the cause-and-effect of news topic. The new method choose representative sentences for news documents according to the specialty of news structure (NS, News structure), and then utilizes IMMC (Improved Min-Max clustering) to classify these representative sentences to generate multi-documents summary which represents the topic cause-and-effect...
A numerical optimization method for module identification based on particle swarm optimization (PSO) algorithm is proposed. A series of property correlations facing the product lifecycle are divided into functional, geometrical, physical and auxiliary ones, and the synthesis design structure matrix (DSM) is obtained. The optimization function for module identification is then established based on...
This paper introduces an image segmentation algorithm of weighted with neighborhood gray difference fuzzy c-means clustering (WFCM) and experiments with the samples on two-dimensional histogram between the original image and its median filter image. Experimental results demonstrate that this scheme can not only effectively segment the low contrast object, but also reduce the noise from the background.
One of the key problems for wireless sensor networks (WSNs) is how to make the best of limited energy. The conventional clustering method has the unique potential to be the framework for energy-conserving wireless sensor networks .In this paper, a novel dynamic clustering algorithm based on geographical location information(GL-DC)is proposed for WSNs. Comparing with other algorithms, GL-DC has two...
A variety of cluster analysis techniques exist to group objects having similar characteristics. While there have been recent advances in algorithms for clustering data, some are unable to handle uncertainty in the clustering process while others have stability issues. This paper proposes a new algorithm for clustering data based on rough set theory, which has the ability to handle the uncertainty...
Based on Discovery Feature Sub-space Model (DFSSM), this paper proposes a new web text clustering algorithm which characterizes self-stability and powerful antinoise ability. The definitions of cluster and distance measures in the concept space being given. It can distinguishes the most meaningful features from the Concept Space without the evaluation function. The application in the modern long-distance...
The data stream problem has been studied extensively in recent years. This is because the great in collection of the nature of data stream. The nature of stream data makes it essential to use algorithms which require only one pass over the data. And single-scan, stream analysis methods have been proposed in this context. However, clustering is still a challenging task since many published algorithms...
This paper proposed a comprehensive color feature vector for tile online color consistency inspection. Non-uniform color quantitative method that was based on main color and human vision was put forward and the result accord with the human vision and the speed meet the requirement of tile online inspection. In order to synchronously meet the demand of tile global and local color difference inspection,...
XML has become a de facto standard for data representation and exchange over the Internet. With the emergence of more and more XML documents, the clustering of XML documents has become an active research area. XML documents lie between structured data and unstructured data which describe both content and structure, so how to effectively cluster XML documents is a huge challenge. However, most of existing...
Intrusion detection has become the important component of the network security. Many intelligent intrusion detection models are proposed, but the performance and efficiency are not satisfied to real computer network system. This paper extends these works by applying a new high efficient technique, named twin support vector machines (TWSVM), to intrusion detection. Using the KDD'99 data set collected...
Classification of intrusion attacks and normal network traffic is a challenging and critical problem in network security. Many classification methods for intrusion detection have been proposed, but there are few algorithms that are capable of distinguishing among the various attacks and normal connections effectively. This paper presents an effective intrusion detection algorithm based on conscientious...
This paper proposed an adaptive shadows detection algorithm based on Gaussian Mixture Model to improve the performance of video object segmentation. This method takes advantage of luminance weight to model the background of the image and obtains a primary segmentation in CIE Luv color space. In this way, it improves the real-time ability of detection. It also becomes more efficient, comparing with...
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