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An important class of community-based activities of mobile users is searching and querying for common locations to visit or come together for a specific task. For this purpose, Group Nearest-Neighbor (GNN) queries are used a generalization of nearest-neighbor queries where the goal is to find one or more points from a set of destination points that have the smallest total distance from all query points...
Clustering sensor nodes is an effective topology control for increasing network lifetime and scalability. It also, balances the load on the sensor nodes. HEED is a well known distributed clustering protocol that uses both energy and communication cost to elect Cluster Heads (CHs) in a probabilistic way. This paper improves HEED protocol using fuzzy logic and a non probabilistic approach for CH election...
The ultimate goal in a multiple classifier system (MCS) is to obtain a global and more accurate model through the combination of several base learners. Among the popular combining rules, averaging has been emphasized as a well qualified option. The averaging rule can be applied with equal (simple averaging) or non-equal (weighted averaging) weights vector for the linear combination. When the formed...
Web services are the most important event in distributed computing today and have achieved great popularity among software developers. A critical step in the process of developing applications based on web services is web service discovery, i.e., the identification of existing web services that can potentially be used in the context of a new web application. We have proposed a novel method based on...
This paper describes the blind speech target sources using Independent Component Analysis in the frequency domain. Mixtures are convolutive and the target sources are assumed to be close to sensors and to have non-gaussianity and also we do not have any information about the position and active time of each source. We are going to determine the number of target sources and solving the permutation...
In this paper a hierarchical structure is proposed for automatic gender identification (AGI). In this structure two clustering techniques are used. The first technique is divisive clustering for dividing speakers from each gender to some classes of speakers. The second clustering technique is agglomerative clustering for creating a hierarchical structure. Feature reduction is done by SOAP feature...
In the field of pattern recognition, combination of different classifiers is a common method to improve classification accuracy. Recently, tendency to improve the function of clustering methods, specifically partitional clustering methods, is being increased. Generally, hierarchical clustering is preferred to partitional clustering when the number of exact clusters is undetermined or when we are interested...
Data clustering has been applied in multiple fields such as machine learning, data mining, wireless sensor networks and pattern recognition. One of the most famous clustering approaches is K-means which effectively has been used in many clustering problems, but this algorithm has some problems such as local optimal convergence and initial point sensitivity. Artificial fishes swarm algorithm (AFSA)...
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