• Journal of Sensor Science and Technology
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• v.13 no.1
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• pp.41-46
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• 2004

There is currently much interest in the development of instruments that emulate the senses of humans. Increasingly, there is demand for mimicking the human sense of smell, which is a sophisticated chemosensory system. An electronic nose system is applicable to a large area of industries including environmental monitoring. We have designed a protable electronic nose system using an array of commercial chemical gas sensors for recognizing and analyzing the various odours. In this paper, we have implemented a portable electronic nose system using an array of gas sensors for recognizing and analyzing VOCs (Volatile Organic Compounds) in the field. The accuracy of a portable electronic nose system may be lower than an instrument such as GC/MS (Gas Chromatography/Mass Spectrometer). However, a portable electronic nose system could be used on the field and showed fast response to pollutants in the field. Several different algorithms for odours recognition were used such as BP (Back-Propagation) or LM-BP (Levenberq-Marquardt Back-Propagation). We applied RBF (Radial Basis Function) Network for recognition and quantifying of odours, which has simpler and faster compared to the previously used algorithms such as BP and LM-BP.

• Journal of Sensor Science and Technology
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• v.22 no.4
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• pp.276-280
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• 2013

The purpose of this paper is to diagnose osmidrosis visually and quantify the extent of osmidrosis. To achieve this, we designed the diagnosis method of osmidrosis using electronic nose system. The developed electronic nose system use principal component analysis for visualization of osmidrosis and fuzzy c-means algorithm for quantification. To confirm the efficiency of electronic nose system for osmidrosis diagnosis, we obtained samples from 34 volunteers and compared our experiment results with the doctor's diagnosis, and we met with successful results.

• Journal of Biosystems Engineering
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• v.34 no.6
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• pp.462-469
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• 2009

The aim of this study was to develop a portable electronic nose system for freshness measurement of stored pork. An electronic nose system was constructed using seven different MOS sensor array. To determine the quality change of pork with storage time, the samples were divided into ten groups in terms of storage time with an increment of 2 day up to 19 storage days. GC-MS, total bacteria's count (TBC), thiobarbituric acid reactive substance (TBARS), and pH analyses as well as the analysis of the electronic nose system measurement were performed to monitor the freshness change of the samples. To investigate the performance of the electronic nose system for detecting the change of freshness of pork, the acquired signal values of the system were compared with those of GC-MS, TBC, TBARS, and pH analysis values. According to principal component analysis (PCA) and linear discriminant analysis (LDA) with the signals of the electronic nose system for the pork samples, the sample groups were clearly separated into two groups of 1-9 days and 11-19 days, and four groups of 1-3 days, 5-9 days, 11 days, and 13-19 days respectively. The results show that the electronic nose system has potential for evaluating freshness of pork.

• Korean Journal of Agricultural Science
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• v.38 no.3
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• pp.525-532
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• 2011

The aim of this study was to develop a portable electronic nose system for freshness measurement of meats, which could be an alterative of subjective measurements of human nose and time-consuming measurements of conventional gas chromatograph methods. The portable electronic system was o optimized by comparing the measurement sensitivity and hardware efficiency, such as power consumption and dimension reduction throughout two stages of the prototypes. The electronic nose systems were constructed using an array of four different metal oxide semiconductor sensors. Two different configurations of sensor array with dimension were designed and compared the performance respectively. The final prototype of the system showed much improved performance on saving power consumption and dimension reduction without decrease of measurement sensitivity of pork freshness. The results show the potential of constructing a portable electronic system for the measurement of meat quality with high sensitivity and energy efficiency.

• Journal of Sensor Science and Technology
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• v.28 no.1
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• pp.7-12
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• 2019

Significant progress has been made recently in detection of highly sensitive volatile organic compounds (VOCs) using chemical sensors. Combined with the progress in design of micro sensors array and electronic nose systems, these advances enable new applications for detection of extremely low concentrations of breath-related VOCs. State of the art detection technology in turn enables commercial sensor systems for health care applications, with high detection sensitivity and small size, weight and power consumption characteristics. We have been developing an intelligent electronic nose system for detection of VOCs for healthcare breath analysis applications. This paper reviews our contribution to monitoring of respiratory diseases and to diabetic monitoring using an intelligent electronic nose system for detection of low concentration VOCs using breath analysis techniques.

• Proceedings of the Korean Society of Crop Science Conference
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• 2006.04a
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• pp.40-54
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• 2006

It's not easy to detect the high quality and functional compounds for control quality of food materials. The electronic nose was an instrument, which comprised of an array of electronic chemical sensors with partial specificity and an appropriate pattern recognition system, capable of recognizing simple or complex odors. It can conduct fast analysis and provide simple and straightforward results and is best suited for quality control and process monitoring in the field of functional foods. Numbers of applications of an electronic nose in the functional food industry include discrimination of habitats for medicinal food materials, monitoring storage process, lipid oxidation, and quality control of food and/or processing with principal component analysis, neural network analysis and the electronic nose based on GC-SAW sensor. The electronic nose would be possibly useful for a wide variety of quality control in the functional food and plant cultivation when correlating traditional analytical instrumental data with sensory evaluation results or electronic nose data.

• 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.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1997.04a
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• pp.99-102
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• 1997

An electronic nose system is an instrument designed far mimicking human olfactory system. It consists generally of gas (odor) sensor array corresponding to olfactory receptors of human nose and artificial neural network pattern recognition technique based on human biological odor sensing mechanism. Considerable attempts to develop the electronic nose system have been made far applications in the fields of floods, drinks, cosmetics, environment monitoring, etc. A portable electronic nose system has been fabricated by using oxide semiconductor gas sensor array and pattern recognition technique such as principal component analysis (PCA) and back propagation artificial neural network The sensor array consists of six thick film gas sensors whose sensing layers are Pd-doped WO$_3$ Pt-doped SnO$_2$ TiO$_2$-Sb$_2$O$_3$-Pd-doped SnO$_2$ TiO$_2$-Sb$_2$O$_{5}$-Pd-doped SnO$_2$+Pd filter layer, A1$_2$O$_3$-doped ZnO and PdCl$_2$-doped SnO$_2$. As an application the system has been used to identify CO/HC car exhausting gases and the identification has been successfully demonstrated.d.

• Journal of Biosystems Engineering
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• v.33 no.5
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• pp.333-339
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• 2008

The purpose of this study was to develop a portable electronic nose system to measure volatile components of agricultural and food products. Also, a graphical operating software to control the electronic nose system and to acquire signals through the Internet was developed. An array of five commercial metal oxide gas sensors was used to detect various volatile gas components of target samples. Transient and steady state signals were analyzed to extract variables related to sample states, To find optimal operating conditions of the system, several experiments were performed with different gas chambers, vacuum pumps, gas sampling temperatures, and sample container sizes. The patterns of gas sensor signals were analysed to find effects of the various conditions.