• 농업과학연구
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• 제38권3호
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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.

• 농업과학연구
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• 제38권4호
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• pp.761-767
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• 2011

The objective of this study was to predict total bacteria count of pork meats by using the portable electronic nose systems developed throughout two stages of the prototypes. Total bacteria counts were measured for pork meats stored at $4^{\circ}C$ for 21days and compared with the signals of the electronic nose systems. PLS(Partial least square), PCR (Principal component regression), MLR (Multiple linear regression) models were developed for the prediction of total bacteria count of pork meats. The coefficient of determination ($R_p{^2}$) and root mean square error of prediction (RMSEP) for the models were 0.789 and 0.784 log CFU/g with the 1st system for the pork loin, 0.796 and 0.597 log CFU/g with the 2nd system for the pork belly, and 0.661 and 0.576 log CFU/g with the 2nd system for the pork loin respectively. The results show that the developed electronic system has potential to predict total bacteria count of pork meats.

• 센서학회지
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• 제28권1호
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.123-126
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• 2005

The IEEE 1451.4 standards defines an architectural model for interfacing smart transducers for sensors & actuators. This standard allows analogue transducers to communicate their identification and calibration data in a digital format. A digital format is called TEDS(transducer electronic data sheet). However, the standard template of IEEE 1451.4 TEDS do not supports gas sensors to use in electronic nose system, such as array sensors. In this paper, a solution to standardize sensors for electronic nose systems is presented.

• 한국연초학회지
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• 제35권1호
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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.

• 전자공학회논문지SC
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• 제43권1호
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• pp.21-30
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• 2006

IEEE 1451.4는 센서 및 액츄에이터를 위한 스마트트랜스듀서의 연결 표준안으로 정의되었다. 이 표준은 아날로그 트랜스듀서의 정보를 디지털 형태로 전송한다 이 디지털 형태의 정보를 TEDS(transducer electronic data sheet)라고 부른다. IEEE 1451.4 TEDS는 전자코 시스템에서의 어레이 센서에 대해서는 이용하기가 어렵다. 본 논문은 전자코 시스템에서 센서 인터페이스의 대한 표준화에 대해 분석해보고 새로운 방안을 제안한다.

• Journal of Biosystems Engineering
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• 제27권3호
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• pp.241-248
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• 2002

An electronic noses system including six metal oxide sensors was used to predict the characteristics of shelf-life of soybean curd. Soybean curd was stored at two different temperatures defined as low temperature(5$\^{C}$) and high temperature(25$\^{C}$). Resistance changes of the sensors were measured 13 times for 19 days at low temperature and 19 times for 120 hours at high temperature. Three different analytical methods such as graphical analysis(GA), principal component analysis(PCA), and cluster analysis(CA) were used to analyze sensors outputs. The ratio of resistance was decreased according to increasement of shelf-life. Using PCA it was possible to predict freshness and shelf-life time of soybean curds. Also, using CA it was possible to simplify an electronic nose system. Electronic nose system could be an efficient method to predict shelf-life and to evaluate quality in foods.

• 한국작물학회지
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• 제41권6호
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• pp.672-677
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• 1996

전자코를 이용하여 향미품종에 대한 방향성 성분함량비율을 조사한 결과를 요약하면 다음과 같다. 1. 작용기별로는 polar compound계열과 aldehydes compounds계열이 apolar compounds 계열과 sulphur compounds, aminated com-pounds계열에 비해 약 3배정도 높은 함량 비율을 보였다. 2. 백미와 취반상태에 있어서 방향성 성분 함량변화는 대부분 0.02에서 0.1수준으로 증가하는 경향을 보였으나, 찰성을 가진 밀양 14006의 경우는 취반 상태에서 방향성 성분의 함량이 오히려 감소하는 경향을 보였다. 3. 향기와 amylose함량 관계에서는 Japonica와 Indica계열 모두 아밀로스함량이 높을수록 방향성 성분의 함량이 증가하는 경향을 보였다. 4. Headspace 진행 후 센서에 감지되는 시간대는 대부분의 품종에서 30～35초에서 가장 많은 향기성분의 양을 검출할 수 있었으나, 이리 41003의 경우는 방향성성분의 검출이 30초대 이후에 급격히 감소하였다.

• 센서학회지
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• 제32권1호
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• pp.1-9
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• 2023

Recently, the digital healthcare technologies including non-invasive diagnostics based on Internet of Things (IOT) are getting attention. Human exhaled breath contains a variety of volatile organic compounds (VOCs), which can provide information of malfunctions of the body and presence of a specific disease. Detection of VOCs in exhaled breath using gas sensors are easy to use, safe, and cost-effective. However, accurate diagnosis of diseases is challenging because changes in concentration of VOCs are extremely small and lots of body factors directly or indirectly influence to the conditions. To overcome the limitations, highly selective nanosensors and artificial intelligent electronic nose (E-nose) systems have been mainly researched in recent decades. This review provides brief reviews of the recent studies for diabetes and lung cancer diagnosis using nanosensors and E-nose systems.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.61.3-61
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• 2001

Field screening for pollutants has been a target of instrumental development for number of years. An electronic nose can be of substantial benefit to rapidly localize the spatial extent of a pollution or to find pollutant source. Although an electronic nose cannot separate complex composition into the whole spectrum of present volatile organic compound(VOC) in pollutants such as Gas chromatography(GC), qualitative and semi-quantitative chemical characterizations are rapidly available on site at a low cost using the optimum sensory system and pattern recognition algorithm based on neural network.