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              <text>A novel automated method for coconut grading based on audioception</text>
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              <text>Coconut grading; Dagging; Fast Fourier Transform; Naive bayes; Sequential minimal optimization (SMO); Sound processing</text>
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              <text>The quality of the coconuts used for various purposes is of utmost importance. Demand for better quality products is constantly on the rise due to the improvements in the standard of living of people. There is a possibility that a bad coconut goes unnoticed by the traders, as it is hard to decide if a coconut is good or bad by relying only on its external appearance. Traditionally, quality assessment is carried out manually with the help of three senses; sight, hearing and smell. In the proposed work, a sound processing technique is used in an attempt to automate this process which overcomes the drawbacks of manual processing, which can be used in large godowns and warehouses. This proposed method provides the quality assessment of the coconut purely based on audioception. While creating the database, coconuts varying in size, shape, color and water content were taken from several places as a source for the dataset. Features are extracted from the sound pattern produced by the dropped coconut, which forms the basis for classification. Sequential Minimal Optimization (SMO), Dagging and Naive Bayes classifiers were used and the results obtained were found to be encouraging.  2005  ongoing JATIT &amp;amp; LLS.</text>
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              <text>Thomas P.; Anita H.B.</text>
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              <text>Journal of Theoretical and Applied Information Technology, Vol-95, No. 10, pp. 2265-2273.</text>
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              <text>Asian Research Publishing Network</text>
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              <text>2017-01-01</text>
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              <text>Restricted Access</text>
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              <text>ISSN: 19928645</text>
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              <text>Thomas P., Department of Computer Science, Christ University, Bengaluru, Karnataka, India; Anita H.B., Department of Computer Science, Christ University, Bengaluru, Karnataka, India</text>
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