Electronic tongue mimics human gustatory sensation and is used to characterize and discriminate beverages and foods. Feature extraction plays a key role in improving the classification accuracy by preserving the distinct characteristics while reducing high dimensionality of data generated from electronic tongue. This paper presents a new feature extraction method based on stationary wavelet singular entropy for a developed electronic tongue system to classify pasteurized cow milk. The electronic tongue consists of an array of five working electrodes along with a reference and a counter electrode to characterize milk sample. The feature extraction of acquired data is done by computing stationary wavelet transform to obtain detail and approximate coefficients at different level of decomposition. These coefficients are processed using singular value decomposition followed by calculation of entropy to obtain stationary wavelet singular entropy values. These values form the feature set and feed to two classifiers, k-nearest neighbor and back propagation artificial neural network, and their classification accuracy is evaluated with variation in their model parameters. The proposed method is compared with other wavelet transform-entropy methods in terms of classification accuracy, which indicates that the proposed method is more effective in discriminating milk samples.

Human breath is largely composed of oxygen, carbon dioxide, water vapor, nitrogen and numerous compounds in trace concentration. Exhaled Breath analysis is non-invasive, real-time and low cost technique which can be applied in medicine field both as a diagnostic tool and as a way to monitor the progress of therapies. This paper proposes a pellet sensor which responds to the exposure of exhaled breath. A proportion of zinc oxide and tin oxide nanopowder was used to fabricate gas sensor in the form of pellet. The pellet sensor response for asthmatic exhaled breath varies from normal exhaled breath response. The electrical conductivity, sensitivity, response time and recovery time of pellet sensor with asthmatic exhaled breath exposure has been studied and compared to the normal response. As a part of standard data collection, a spirometer apparatus for differentiating normal person and asthmatic patient is used. The response of pellet sensor is different for normal and asthmatic subjects with stable and repeated response. Characterization of pellet sensor is done for both normal and diseased case. The comparison between normal and asthmatic pellet sensor response can be used as an assistive tool for asthma disease detection.

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In the present study to mask the unpleasant taste of chloroquine phosphate, hot melt coating technique was used as a taste masking tool. Hot melt coating is a solvent free technology grants rapid, additionally economical coating process with reduced risk of dissolving drug during process and provide uniform application rate of coating agent. Precirol ATO 5 was used as hot melt coating material for taste masking. Tablets were prepared by wet granulation method and coated using hot melt coating technique. Coated tablets exhibited good uniformity of drug content. Amount of drug release from all batches were evaluated. Taste evaluation of hot melt coated tablets was done by using electronic tongue.PrecirolATO5 was found to be a better taste masking agent when used by hot melt coating technique. Keywords: Precirol ATO 5, Hot melt coating, taste masking.