• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.2
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• pp.64-70
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• 2011

Portable artificial electronic nose (E-nose) system suffers from noisy fluctuation in surroundings such as temperature, vapor concentration, and gas flow, because its measuring condition is not controled precisely as in the laboratory. It is important to develop a simple and robust vapor recognition technique applicable to this uncontrolled measurement, especially for the portable measuring and diagnostic system which are expanding its area with the improvements in micro bio sensor technology. This study used a PDA-based portable E-nose to collect the uncontrolled vapor measurement signals, and applied the image matching algorithm developed in the previous study on the measured signal to verify its robustness and improved accuracy in portable vapor recognition. The results showed not only its consistent performance under noisy fluctuation in the portable measurement signal, but also an advanced recognition accuracy for 2 similar vapor species which have been hard to discriminate with the conventional maximum sensitivity feature extraction method. The proposed method can be easily applied to the data processing of the ubiquitous sensor network (USN) which are usually exposed to various operating conditions. Furthermore, it will greatly help to realize portable medical diagnostic and environment monitoring system with its robust performance and high accuracy.

• Food Engineering Progress
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• v.13 no.4
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• pp.275-281
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• 2009

Sesame oils are partially mixed with other vegetable oils due to high price in a Korean market. To find out authentic sesame oil, a mass spectrometer-based electronic nose (MS-based E-nose) was used. Sesame oil (Se) was blended with soybean oil (So) or corn oil (Co) at the ratio (Se:So, Se:Co) of 97:3, 94:6, 91:9, 88:12 and 85:15, respectively. Intensities of each fragment from sesame oil by MS-based E-nose were completely different from those of soybean oil or corn oil. The obtained results were used for discriminant function analysis (DFA). Volatile organic components (VOC) of soybean oil or corn oil were similar to those of fresh air and DFA plot indicated a significant separation of pure sesame oil and pure other oil. The group of the mixed oil was seperated with that of sesame oil in DFA plot and the added amount of soybean oil to sesame oil was correlated with discriminant function first score (DF1). MS based E-nose system could be used as an efficient method to investigate the purity of sesame oil.

• Korean Journal of Food Science and Technology
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• v.45 no.2
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• pp.142-147
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• 2013

This study was conducted to evaluate and compare new beer (NB) with market beers, e.g., New castle brown ale (NC), Victoria bitter (VB), and Coopers pale ale (CP) using physicochemical parameters. In addition, pattern recognition analyses were carried out using an electronic nose based on mass spectrometry (MS-E nose) and an electronic tongue (E-tongue) for differentiation of the different types of beer. The measured alcohol content of NB was 4.37%. NB was not significantly different compared with other types of beer with regard to bitterness unit, color, and polyphenol content (p<0.05). On the basis of the flavor pattern determined by the MS-E nose, NB was separated by DF1 (first score from discriminant function analysis), while NC, VB, and CP were located in the same group. The result of the E-tongue showed that the different samples could be clearly discriminated; NB was less sour. It was suggested that the discriminant function analysis (DFA) given by the MS-E nose and E-tongue could be used for evaluations during new product development. Furthermore, because of its simplicity, it might be possible to use the validated method for the evaluation of beer.

• Journal of the Korean Applied Science and Technology
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• v.37 no.1
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• pp.38-48
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• 2020

The aroma pattern was analyzed using electronic nose to examine the possibility of origin discrimination according to the mixing ratio of Chinese and Korean red ginseng concentrates. The origin of Chinese red ginseng concentrate and Korea red ginseng concentrate could be distinguished and the pattern of aroma component detected decreased as the mixing ratio of Chinese red ginseng concentrate increased. Cultivar and habitat of Korean red ginseng concentrated was remarkably distinguished by the chromatogram of frequency pattern, derivative pattern and visual pattern using olfactory images known as vapor print^TM.

• ETRI Journal
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• v.32 no.3
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• pp.440-446
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• 2010

Array-based gas sensors now offer the potential of a robust analytical approach to odor measurement for medical use. We are developing a fast reliable method for detection of microbial infection by monitoring the headspace from the infected wound. In this paper, we present initial results obtained from wound-state monitoring for burn patients using an electronic nose incorporating an automated solid-phase microextraction (SPME) desorption system to enable the system to be used for clinical validation. SPME preconcentration is used for sampling of the headspace air and the response of the sensor module to variable concentrations of volatiles emitted from SPME fiber is evaluated. Gas chromatography-mass spectrometry studies prove that living bacteria, the typical infectious agents in clinical practice, can be distinguished from each other by means of a limited set of key volatile products. Principal component analysis results give the first indication that infected patients may be distinguished from uninfected patients. Microbial laboratory analysis using clinical samples verifies the performance of the system.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2007.11a
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• pp.364-364
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• 2007

This paper presents characteristics of surface acoustic wave (SAW) gas sensor for detecting volatile gases such as ethanol gas by measuring phase shift of output signal. A delay-line with a center frequency of 400MHz was fabricated on 128o Y-Z $LiNbO_3$ substrates. Experimental results, which show the phase change of output signal under the absorption of volatile gas on sensor surface, were presented. The sensitivities of SAW delay lines coated with polyurethane films are greatly increased compared to those for uncoated devices. This SAW gas sensor system may be well suited for a high sensitivity electronic nose system.

• Bulletin of the Korean Chemical Society
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• v.31 no.11
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• pp.3084-3092
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• 2010

This paper describes the development of an automated, hand-held sensor for the fast assessment of seafood freshness. The sensor developed here combined: an array-based chemical sensor, composed of incrementally different conducting polymer elements deposited on a small chip; a highly sensitive, custom-made electronics for the detection of very small signal changes; precise temperature control of the sensor chamber; and an on-board microcontroller for data collection, storage, automation, and analysis. The instrument was used to successfully test seafood samples with different degree of freshness and spoilage. A linear relationship between microbiological count and e-Nose signal for three different fish fillet was developed. Once the linear relationship is included into the hand-held unit software, the e-Nose signal can be used for assessment of seafood freshness without performing the microbiological count technique.

• Proceedings of the IEEK Conference
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• 2002.06b
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• pp.297-300
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• 2002

Application of electronic nose and PLD chip design was developed to be used in gas discrimination system for limited kinds of gas. An array of 4 metal oxide gas sensors with different selectivity patterns were used in order to measure gases. BP(Back Propagation) algorithm was designed and implemented on CPLD of two hundred thousand gate level chips by VHDL language for processing input signals from 4 kinds of gas sensors. This module successfully discriminated 4 kinds of gases and displayed the results on LCD and LED. The developed module could be used for various applications in the field of food process control and alcohol judgment.

• Proceedings of the IEEK Conference
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• 2001.06b
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• pp.309-312
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• 2001

A primitive gas classification system which can classify limited species of gas was designed and simulated. The 'electronic nose' consists of an array of 4 metal oxide gas sensors with different selectivity patterns, signal collecting unit and a signal pattern recognition and decision Part in PLD(programmable logic device) chip. Sensor array consists of four commercial, tin oxide based, semiconductor type gas sensors. BP(back propagation) neutral networks with MLP(Multilayer Perceptron) structure was designed and implemented on CPLD of fifty thousand gate level chip by VHDL language for processing the input signals from 4 gas sensors and qualification of gases in air. The network contained four input units, one hidden layer with 4 neurons and output with 4 regular neurons. The 'electronic nose' system was successfully classified 4 kinds of industrial gases in computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.210-210
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• 2000

In this paper, we have investigated the properties of multi-layer perceptron (MLP) for odour patterns classification and concentration estimation simultaneously. When the MLP may be has a fast convergence speed with small error and excellent mapping ability for classification, it can be possible to use for classification and concentration prediction of volatile chemicals simultaneously. However, the conventional MLP, which is back-Propagation of error based on the steepest descent method, was difficult to use for odour classification and concentration estimation simultaneously, because it is slow to converge and may fall into the local minimum. We adapted the Levenberg-Marquardt(LM) algorithm [4,5] having advantages both the steepest descent method and Gauss-Newton method instead of the conventional steepest descent method for the simultaneous classification and concentration estimation of odours. And, We designed the artificial odour sensing system(Electronic Nose) and applied LM-BP algorithm for classification and concentration prediction of VOC gases.