• ETRI Journal
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• v.27 no.5
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• pp.585-594
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• 2005

A small electronic nose (E-Nose) system has been developed using an 8-channel vapor detection array and personal digital assistant (PDA). The sensor array chip, integrated on a single microheater-embedded polyimide substrate, was made of carbon black-polymer composites with different kinds of polymers and plasticizers. We have successfully classified various volatile organic compounds such as methanol, ethanol, i-propanol, benzene, toluene, n-hexane, n-heptane, and c-hexane with the aid of the sensor array chip, and have evaluated the resolution factors among them, quantitatively. To achieve a PDA-based E-Nose system, we have also elaborated small sensor-interrogating circuits, simple vapor delivery components, and data acquisition and processing programs. As preliminary results show, the miniaturized E-Nose system has demonstrated the identification of essential oils extracted from mint, lavender, and eucalyptus plants.

• Journal of Sensor Science and Technology
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• v.23 no.5
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• pp.320-325
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• 2014

Volatile flavor compounds from milk were analyzed and identified by using the analysis methods of headspace solid phase microextraction gas chromatography/mass spectrometry (HSPME-GC/MS) and electronic nose (E-Nose) system. About 30 volatile compounds were identified by HSPME-GC/MS for the fresh and off-flavor milk samples. Also, the correlation between rancidity and ageing days of milk was obtained by the aid of principal component analysis algorithm. It shows that the E-Nose system can identify the various types of milk flavor. These results imply that the analysis method based on the E-nose system can apply to the quality control of milk flavor and the rancidity.

• Journal of Sensor Science and Technology
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• v.13 no.6
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• pp.454-461
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• 2004

We have designed a portable electronic nose (e-nose) system using an array of commercial gas sensors and personal digital assistants (PDA) for the recognition and analysis of volatile organic compounds (VOC) in the field. Field screening of pollutants has been a target of instrumental development during the past years. A portable e-nose system was advantageous to localize the special extent of a pollution or to find pollutants source. The employment of PDA improved the user-interface and data transfer by Internet from on-site to remote computer. We adapted the Lavenberg-Marquardt algorithm based on the back-propagation and proposed the method that could predict the concentration levels of VOC gases after classification by separating neural network into two parts.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.39-42
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• 2004

We have designed a portable electronic nose(e-nose) system using an array of commercial gas sensors for recognition and analyzing the various odours. In this paper, we have implemented a portable e-nose system using an array gas sensors and personal digital assistants(PDA) for recognizing and analyzing volatile organic compounds(VOCs) in the field. Field screening for pollutants has been a target of instrumental development for number of year. A portable e-nose system can be substantial benefit to rapidly localize the spacial extent of a pollution or to find pollutants source. And, by using PDA, E-nose have a better function such as the easy user-interface and data transfer by internet from on- site to remote computer. We adapted the Levenberg-Marquardt algorithm based on the back-propagation and proposed the method that could be predicted concentration levels of VOCs gases after classification by separating neural network into two parts.

• Journal of Sensor Science and Technology
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• v.14 no.2
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• pp.69-77
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• 2005

The electronic nose (e-nose) has been used in food industry and quality controls in plastic packaging. Recently it finds its applications in medical diagnosis, specifically on detection of diabetes, pulmonary or gastrointestinal problem, or infections by examining odors in the breath or tissues with its odor characterizing ability. Moreover, the use of portable e-nose enables the on-site measurements and analysis of vapors without extra gas-sampling units. This is expected to widen the application of the e-nose in various fields including point-of-care-test or e-health. In this study, a PDA-based portable e-nose was developed using micro-machined gas sensor array and miniaturized electronic interfaces. The rich capacities of the PDA in its computing power and various interfaces are expected to provide the rapid and application specific development of the diagnostic devices, and easy connection to other facilities through information technology (IT) infra. For performance verification of the developed portable e-nose system, Six different vapors were measured using the system. Seven different carbon-black polymer composites were used for the sensor array. The results showed the reproducibility of the measured data and the distinguishable patterns between the vapor species. Additionally, the application of two typical pattern recognition algorithms verified the possibility of the automatic vapor recognition from the portable measurements. These validated the portable e-nose based on PDA developed in this study.

• Journal of Sensor Science and Technology
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• v.24 no.6
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• pp.368-372
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• 2015

In this paper, we proposed a post-processing technique for improving classification performance of electronic nose (E-Nose) system which may be occurred drift signals from sensor array. An adaptive radial basis function network using stochastic gradient (SG) and singular value decomposition (SVD) is applied to process signals from sensor array. Due to drift from sensor's aging and poisoning problems, the final classification results may be showed bias and fluctuations. The predicted classification results with drift are quantized to determine which identification level each class is on. To mitigate sharp fluctuations moving-averaging (MA) technique is applied to quantized identification results. Finally, quantization and some edge correction process are used to decide levels of the fluctuation-smoothed identification results. The proposed technique has been indicated that E-Nose system was shown correct odor identification results even if drift occurred in sensor array. It has been confirmed throughout the experimental works. The enhancements have produced a very robust odor identification capability which can compensate for decision errors induced from drift effects with sensor array in electronic nose system.

• Journal of Biomedical Engineering Research
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• v.25 no.5
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• pp.329-334
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• 2004

The electronic nose (E-nose) recently finds its applications in medical diagnosis, specifically on detection of diabetes, pulmonary or gastrointestinal problem, or infections by examining odors in the breath or tissues with its odor characterizing ability. The odor recognition performance of E-nose can be improved by manipulating the sensor array responses of vapors in time-profile forms. The different chemical interactions between the sensor materials and the volatile organic compounds (VOC's) leave unique marks in the signal profiles giving more information than collection of the conventional piecemal features, i.e., maximum sensitivity, signal slopes, rising time. In this study, to use them in vapor recognition task conveniently, a novel time-profile method was proposed, which is adopted from digital image pattern matching. The degrees of matching between 8 different vapors were evaluated by using the proposed method. The test vapors are measured by the silicon-based gas sensor array with 16 CB-polymer composites installed in membrane structure. The results by the proposed method showed clear discrimination of vapor species than by the conventional method.

• Journal of Ginseng Research
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• v.41 no.1
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• pp.85-95
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• 2017

Background: American ginseng (Panax quinquefolius L.) and Asian ginseng (Panax ginseng Meyer) products, such as slices, have a similar appearance, but they have significantly different prices, leading to widespread adulteration in the commercial market. Their aroma characteristics are attracting increasing attention and are supposed to be effective and nondestructive markers to determine adulteration. Methods: The aroma characteristics of American and Asian ginseng were investigated using gas chromatography-mass spectrometry(GC-MS) and an electronic nose (E-nose). Their volatile organic compounds were separated, classified, compared, and analyzed with different pattern recognition. Results: The E-nose showed a good performance in grouping with a principle component analysis explaining 94.45% of variance. A total of 69 aroma components were identified by GC-MS, with 35.6% common components and 64.6% special ingredients between the two ginsengs. It was observed that the components and the number of terpenes and alcohols were markedly different, indicating possible reasons for their difference. The results of pattern recognition confirmed that the E-nose processing result is similar to that of GC-MS. The interrelation between aroma constituents and sensors indicated that special sensors were highly related to some terpenes and alcohols. Accordingly, the contents of selected constituents were accurately predicted by corresponding sensors with most $R^2$ reaching 90%. Conclusion: Combined with advanced chemometrics, the E-nose is capable of discriminating between American and Asian ginseng in both qualitative and quantitative angles, presenting an accurate, rapid, and nondestructive reference approach.

• Journal of the Korean Society of Tobacco Science
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• v.35 no.1
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• pp.20-27
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• 2013

An Electronic Nose(E-Nose) and Gas Chromatography/Mass Spectroscopy (GC/MS) are meanwhile conventional technique to analyze volatile materials in many industries (e.g., food, medicine, environment) and have broad acceptance in the analysis of tobacco products. In this study, an experiment where tin oxide gas sensor array responses and GC/MS profiles are used to characterize the volatile compounds of different cigarettes at the same time is performed and the measurements of two instruments are compared for cigarette samples with a known chemical information. E-Nose and GC/MS were employed to differentiate and match flavored cigarettes with commercial tobacco flavoring agents (lavender, vanilla, peppermint, orange, star anise). For verifying reliability of two systems, the analyses were conducted in terms of amount of flavors in each cigarettes using partial least squares (PLS) and with the principal components analysis (PCA). Various chemical sensors and GC/MS data was reduced into two principal factors (PC1, PC2) for being distinguished with visualized regions. Both systems provided adequate results for odor characteristics of cigarettes in this study with each instrument having its own advantages and disadvantages.

• Electrical & Electronic Materials
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• v.8 no.4
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• pp.509-517
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• 1995