this paper compares clusters of aligned persian and english texts obtained from k-means method. text clustering has many applications in various fields of natural language processing. so far, much english documents clustering research has been accomplished. now this question arises, are the results of them extendable to other languages? since the goal of document clustering is grouping of docum...

A mobile ad-hoc network (MANET) faces various challenges including limited energy, limited communication bandwidth, computation constraint and cost. Therefore, clustering of sensor nodes is adopted which involves selection of cluster-heads for each cluster. This enhances system performance by enabling bandwidth reuse, better resource allocation and improved power control. The various existing c...

This research work intends to propose a system with Improved Ant Colony Optimization (IACO) based on enhanced preprocessing method for enzyme clustering. A powerful optimization system is proposed in this research work initially deals with the enhanced principal component analysis. At that point the target function for the co-clustering troupe towards application to enzyme clustering is present...

A combinatorial random variable is a discrete random variable defined over a combinatorial set (e.g., a power set of a given set). In this paper we introduce combinatorial Markov random fields (Comrafs), which are Markov random fields where some of the nodes are combinatorial random variables. We argue that Comrafs are powerful models for unsupervised and semi-supervised learning. We put Comraf...

Data mining techniques, such as clustering, have become a mainstay in many applications such as bioinformatics, geographic information systems, and marketing. Over the last decade, due to new demands posed by these applications, clustering techniques have been significantly adapted and extended. One such extension is the idea of finding clusters in a dataset that preserve information about some...

In wireless sensor network (WSN), many novel architectures, protocols, algorithms and applications have been proposed and implemented for energy efficiency. The efficiency of these networks is highly dependent on routing protocols which directly affecting the network life-time. Cluster formation in sensor network is one of the most popular technique for reducing the energy consumption and expan...

Wireless sensor network a powerful network contains many wireless sensors with limited power resource, data processing, and transmission abilities. Wireless sensor capabilities including computational capacity, radio power, and memory capabilities are much limited. Moreover, to design a hierarchy topology, in addition to energy optimization, find an optimum clusters number and best location of ...

Energy efficiency is the main challenge in wireless sensor network. Many routing protocols have been designed to face this challenge. Hierarchical cluster-based routing is one of the efficient techniques to route the sensed data from source node to sink node. The proposed algorithm deals with cluster formation based on different events, cluster head selection, aggregation of the sensed data wit...

WSN has been directed from military applications to various civil applications. However, many applications are not ready for real world deployment. Most challenging issues are still unresolved. The main challenge facing the operation of WSN is saving energy to prolong the network lifetime. Clustering is an efficient technique used for managing energy consumption. However, clustering is an NP ha...

Abstract:In image analysis techniques, image segmentation takes a major role for analyzing any type of image. The Kmeans clustering algorithm is one of the widely used algorithm in image segmentation system. This paper proposes the colour data base image segmentation using the L*a*b* colour space and K-means clustering. This work presents a data base image segmentation based on colour features ...