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Data aggregation is a promising way to reduce the redundant data communication in wireless sensor networks and hence improves the network lifetime. Among the various data aggregation protocols, it is reported that PEGASIS is better than LEACH and HEED. PEGASIS is a chain based aggregation protocol, where each node communicates only with its closest neighbour and on its turn to become a leader, transmits...
Optical Character Recognition alludes to the methodology of taking images or photos of letters or typewritten content and changing over them into information that a machine can easily interpret, e.g. organizations and libraries taking physical duplicates of books, magazines, or other old printed material and utilizing OCR to put them into computers. Segmentation is the indispensable and most difficult...
Wireless sensor networks are currently being employed in a variety of applications ranging from medical to military and from home to industry. In military areas highly confidential information are being exchanged between the sensor nodes. Wireless Sensor Networks being mobile in nature are prone to various kinds of attacks. An open problem today is to design a secured routing. This paper aims in providing...
Many real time applications, they are generated continues flow of data streams have became more popular now a days. Therefore many researches attracted clustering data streams. Most of data stream clustering algorithms based on distance function which find out clusters with spiracle of shape clusters and unable to deal noisy data. Therefore density based clustering algorithms substitute remarkable...
In Wireless Sensor Networks, directly sending large amount of data to the sink node may cause several problems. So, the data aggregation is a basic task in wireless sensor network. Certain application needs approximate data collection. In this paper, we focus on to collect a data approximately and efficiently with limited energy. So, we propose a technique called ADC (Approximate Data Collection),...
There are various data mining techniques that are frequently used for the mining of vital patterns embedded within bulk data. These techniques include neural network, regression analysis, rough set theory, Bayesian network, decision trees, and so on. In this research, a novel data mining technique, genetically guided cluster based fuzzy decision tree (GCFDT), is introduced for the mining task. In...
Data mining techniques have increasingly been studied specifically in their application in real-world databases. One typical problem is that databases tend to be very large, and these techniques often repeatedly scan the entire set. Sampling has been used for a long time, but subtle differences among sets of objects become less evident. This paper aims to bring attention to some of the fundamental...
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