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  <title>DSpace Collection:</title>
  <link rel="alternate" href="http://localhost:8080/xmlui/handle/123456789/2339" />
  <subtitle />
  <id>http://localhost:8080/xmlui/handle/123456789/2339</id>
  <updated>2026-06-23T06:33:47Z</updated>
  <dc:date>2026-06-23T06:33:47Z</dc:date>
  <entry>
    <title>Liquid Identification Using e Tongue</title>
    <link rel="alternate" href="http://localhost:8080/xmlui/handle/123456789/2340" />
    <author>
      <name>Sharma, Prerna</name>
    </author>
    <author>
      <name>Ugale, Dr. Sunita</name>
    </author>
    <id>http://localhost:8080/xmlui/handle/123456789/2340</id>
    <updated>2019-08-19T10:28:44Z</updated>
    <published>2015-03-01T00:00:00Z</published>
    <summary type="text">Title: Liquid Identification Using e Tongue
Authors: Sharma, Prerna; Ugale, Dr. Sunita
Abstract: Tongue is one of the most important sensory organs of our system. With the help of&#xD;
tongue, we are able to distinguish between the various food items which we eat or drink. The&#xD;
sensors on the tongue identify the tastes which are classified as bitter, sour, salty, sweet, umami&#xD;
(delicious). These are the parameters that help in determining and distinguishing the liquids like&#xD;
beer, tea, coffee, honey, milk etc. The present work describes an efficient way of identifying&#xD;
liquids- an electronic tongue. The electronic tongue consists of an array of sensors immersed in&#xD;
the liquids to identify them. The sensors generate the data in the form of electrical signals. These&#xD;
electrical signals are then processed. For pattern recognition, Linear Vector Quantization (LVQ)&#xD;
algorithm of artificial neural networks (ANN) is used.</summary>
    <dc:date>2015-03-01T00:00:00Z</dc:date>
  </entry>
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