Titlebook: Data Engineering and Intelligent Computing; Proceedings of IC3T Suresh Chandra Satapathy,Vikrant Bhateja,B. Janaki Conference proceedings

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https://doi.org/10.1007/978-1-4419-6297-3for binary and character information. Mining information form images is a challenge today for many researchers. Creating of images and videos is easy as it does not require any domain knowledge, but extracting the required knowledge is difficult. For this reason, today video data mining is an intere

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Laurie K. McLay,Amarie Carnett,Mandy Rispolias become a common means for people to express their impressions on any product, while serving as a recommendation for others. To enhance customer satisfaction and buying experience, often the sellers provide a platform for the customers to express their views. Due to the explosion of these opinion

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Laurie K. McLay,Amarie Carnett,Jeff Sigafoos is a vital step for performing accurate texture classification. The research area of texture classification is widely investigated in several computer vision and pattern recognition problems. In this paper, texture descriptors applied for the texture classification in the literature are summarized.

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Neville M. Blampied,Jenna van DeursMCPC) signal has fluctuations in amplitude because it is the sum of carriers with different frequency. To avoid non linear working of power amplifiers at transmitter, it is desirable to reduce Peak to Mean Envelope Power Ratio (PMEPR) of the signal. We have tried two algorithms to reduce PMEPR and s

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Ritu Grewal MD,Karl Doghramji MD opinion mining. In this paper we focus on identifying ‘the most influential sentiment’ for topics extracted from tweets using Latent Dirichlet Allocation (LDA) method. The most influential twitterers for various topics are identified using the TwitterRank algorithm. Then a SentiCircle based approac

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