• Journal of Sensor Science and Technology
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• v.27 no.2
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• pp.118-125
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• 2018

An evaluation system for an electronic-nose concept using three types of metal oxide gas sensors that react similarly to the human olfactory cells was constructed for the quantitative and qualitative evaluation of aroma fragrances. Four types of aroma fragrances (lavender, orange, jasmine, and Roman chamomile), which are commonly used in aromatherapy, were evaluated. All the gas sensors reacted remarkably to the aroma fragrances and the good correlation of r=0.58-0.88 with the aromatic odor intensities by olfaction was confirmed. From the results of the analysis of an electronic-nose concept for classifying the characteristics of aroma oil fragrances, aroma oils could be classified using the fragrance characteristics and oil extraction methods with the cumulative variability contribution rate of 95.65% (F1: 69.65%, F2: 26.03%) by principal component analysis. In the pattern recognition based on the artificial neural network, the four aroma fragrances were 100% recognized through the training data of 56 cases (70%) out of 80 cases, and the pattern recognition rate was 57.1%-71.4% through the validation and testing data of 24 cases (30%). The pattern recognition success rate through all confusion matrices was 82.1%, indicating that the classification of aroma oil fragrances using the three types of gas sensors was successful.

• 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 the Korea Academia-Industrial cooperation Society
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• v.5 no.1
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• pp.1-6
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• 2004

Air qualify monitoring if a primary activity for industrial and social environment. Especially, the VOCs(Volatile Organic Compounds) are very harmful for human and environment. Throughout this research. we designed sensor array with various kinds of gas sensor, and the recognition algorithm with ANN(Artificial Neural Network : BP), respectively. We have designed system to recognize various kinds and quantities of VOCs, such as benzene, tolylene, and xylene.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.3
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• pp.419-426
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• 2018

An useful and effective design method for the gas identification system is presented in this paper. The proposed gas identification system adopts hierarchical structure with two level rule base combining fuzzy sets with rough sets. At first, a hybrid genetic algorithm is used in grouping the array sensors of which the measured patterns are similar in order to reduce the dimensionality of patterns to be analyzed and to make rule construction easy and simple. Next, for low level identification, fuzzy inference systems for each divided group are designed by using TSK fuzzy rule, which allow handling the drift and the uncertainty of sensor data effectively. Finally, rough set theory is applied to derive the identification rules at high level which reflect the identification characteristics of each divided group. Thus, the proposed method is able to accomplish effectively dimensionality reduction as well as accurate gas identification. In simulation, we demonstrated the effectiveness of the proposed methods by identifying five types of gases.

• Journal of Sensor Science and Technology
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• v.6 no.6
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• pp.476-482
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• 1997

A portable electronic nose system has been fabricated and characterized using an oxide semiconductor gas sensor array and pattern recognition techniques such as principal component analysis 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 $SnO_{2}$, $TiO_{2}-Sb_{2}O_{5}-Pd$-doped $SnO_{2}$, $TiO_{2}-Sb_{2}O_{5}-Pd$-doped $SnO_{2}$ + Pd coated layer, $Al_{2}O_{3}$-doped ZnO and $PdCl_{2}$-doped $SnO_{2}$. The portable electronic nose system consists of an 16bit Intel 80c196kc as CPU, an EPROM for storing system main program, an EEPROM for containing optimized connection weights of artificial neural network, an LCD for displaying gas concentrations. As an application the system has been used to identify 26 carbon monoxide/hydrocarbon (CO/HC) car exhausting gases in the concentration range of CO 0%/HC 0 ppm to CO 7.6%/HC 400 ppm and the identification has been successfully demonstrated.

• Journal of Sensor Science and Technology
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• v.24 no.6
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• pp.379-384
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• 2015

An infrared image sensor is a core device in a thermal imaging system. The fabrication method of a focal plane array (FPA) is a key technology for a high resolution infrared image sensor. Each pixels in the FPA have $Si_3N_4/SiO_2$ membranes including legs to deposit bolometric materials and electrodes on Si readout circuits (ROIC). Instead of polyimide used to form a sacrificial layer, the feasibility of an amorphous silicon (${\alpha}-Si$) was verified experimentally in a $8{\times}8$ micro-bolometer array with a $50{\mu}m$ pitch. The elimination of the polyimide sacrificial layer hardened by a following plasma assisted deposition process is sometimes far from perfect, and thus requires longer plasma ashing times leading to the deformation of the membrane and leg. Since the amorphous Si could be removed in $XeF_2$ gas at room temperature, however, the fabricated micro-bolomertic structure was not damaged seriously. A radio frequency (RF) sputtered nickel oxide film was grown on a $Si_3N_4/SiO_2$ membrane fabricated using a low stress silicon nitride (LSSiN) technology with a LPCVD system. The deformation of the membrane was effectively reduced by a combining the ${\alpha}-Si$ and LSSiN process for a nickel oxide micro-bolometer.

• 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.

• 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.

• Journal of Sensor Science and Technology
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• v.20 no.3
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• pp.151-155
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• 2011

A variety of pattern recognition algorithms including neural networks may be applicable to the identification of odors. In this paper, an identification technique for an electronic odor sensing system applicable to wound state monitoring is presented. The performance of the radial basis function(RBF) network is highly dependent on the choice of centers and widths in basis function. For the fine tuning of centers and widths, those parameters are initialized by an ill-conditioned genetic fuzzy c-means algorithm, and the distribution of input patterns in the very first stage, the stochastic gradient(SG), is adapted. The adaptive RBF network with singular value decomposition(SVD), which provides additional adaptation capabilities to the RBF network, is used to process data from array-based gas sensors for early detection of wound infection in burn patients. The primary results indicate that infected patients can be distinguished from uninfected patients.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.1 s.307
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• pp.21-30
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• 2006

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 may sensors. In this paper, a solution to standardize sensors for electronic nose systems is presented.