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A randomised prospective study to assess the analgesic efficacy of peripheral nerve block using ropivacaine with dexamethasone vs. dexmedetomidine for postoperative analgesia in lower limb surgeries
Volume -12 | Special Issue-13
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Performance Evaluation of popular pre-trained CNN Models on Plant Disease Detection: A Case Study on Mango, Guava, Black Gram, and Sugarcane Datasets
Volume -12 | Special Issue-13
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Automated Capuchinbird Call Detection with CNN Based Audio Classifier
Volume -12 | Special Issue-13
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A cross sectional study on assessment of nutritional status of patients with tuberculosis and associated factors in a tertiary care Hospital, Hyderabad, Telangana, India
Volume -12 | Special Issue-13
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SYNTHESIS OF QUINAZOLIN-4-ONE DERIVATIVES AND EVALUATE THEIR ANTI-INFLAMMATORY ACTIVITIES
Volume -12 | Special Issue-13
INDENTIFICATION OF CHICKEN IN CHICKEN, BEEF AND LAMB EXPERIMENTS USING CONDUCTING POLYMER SENSOR SERIES AND KOHONEN ALGORITHM METHOD
Main Article Content
Abstract
In a classifications of meat types circuit, the chicken, beef and lamb are based on the aroma of each type of meat. This principle is similar to the human nose and the principle is known as an electronic nose, using a Conductive Polymer sensor array consisting of 6 (six) pieces and using an Artificial Neural Network (NN) as pattern recognition and an ATMega16 microcontroller as data acquisition. Neural Network trained using Kohonen. In this paper, the chicken, beef and mutton were taken as test samples and placed in a closed container at room temperature. Tests were carried out 10 times to ensure the circuit could determine the type of chicken meat. The percentage of system success was 100%.
