• Journal of Wellbeing Management and Applied Psychology
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• v.6 no.2
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• pp.27-31
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• 2023

Purpose: Establishment of a real-time monitoring system for odor control in traditional markets in Gangwon-do and a system for linking prevention facilities. Research design, data and methodology: Build server and system logic based on data through real-time monitoring device (sensor-based). A temporary data generation program for deep learning is developed to develop a model for odor data. Results: A REST API was developed for using the model prediction service, and a test was performed to find an algorithm with high prediction probability and parameter values optimized for learning. In the deep learning algorithm for AI modeling development, Pandas was used for data analysis and processing, and TensorFlow V2 (keras) was used as the deep learning library. The activation function was swish, the performance of the model was optimized for Adam, the performance was measured with MSE, the model method was Functional API, and the model storage format was Sequential API (LSTM)/HDF5. Conclusions: The developed system has the potential to effectively monitor and manage odors in traditional markets. By utilizing real-time data, the system can provide timely alerts and facilitate preventive measures to control and mitigate odors. The AI modeling component enhances the system's predictive capabilities, allowing for proactive odor management.

• Journal of Biosystems Engineering
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• v.29 no.4
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• pp.317-322
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• 2004

This study was conducted to evaluate the feasibility of identifying freshness of beef using a surface acoustic wave (SAW) sensor based electronic nose. The beef was stored at 5$^{\circ}C$ and aroma was measured with the passage of time. Chromatographic analysis of the odor showed that number of volatile components and their amounts were rapidly increased after 19 days of storage. Classifying beefs according to their storage days was possible using principle component analysis (PCA). Classifying beefs processed from four different origins was also possible with PCA analysis of odor. This study shows that electronic nose can be applied to beef freshness evaluation and classification of its origin.

• Journal of Korean Society for Atmospheric Environment
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• v.20 no.6
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• pp.783-792
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• 2004

In this study, a thick-film semiconductor odor gas sensor for the detection of $CH_3$SH was developed using SnO$_2$ as the main substrate and was investigated in terms of its sensitivity and reaction time. In the process of manufacturing the sensor, Taguchi's design of experiment (DOE) was applied to analyze the effects of a variety of parameters, including the substrate, the additives and the fabrication conditions, systematically and effectively. Eight trials of experiments could be possible using the 27 orthogonal array for the seven factors and two levels of condition, which originally demands 128 trials of experiments without DOE. The additives of Sb$_2$O$_{5}$ and PdCl$_2$ with the H$_2$PtCl$_{6}$ ㆍ6$H_2O$ catalyst were appeared to be important factors to improve the sensitivity, and CuO, TiO$_2$, V$_2$O$_{5}$ and PdO were less important. In addition, TiO$_2$, V$_2$O$_{5}$ and PdO would improve the reaction time of a sensor, and CuO, Sb$_2$O$_{5}$, PdCl$_2$ and H$_2$PtCl$_{6}$ㆍ6$H_2O$ were negligible. Being evaluated simultaneously in terms of both sensitivity and reaction time, the sensor showed the higher performance with the addition of TiO$_2$ and PdO, but the opposite results with the addition of CuO, V$_2$O$_{5}$, Sb$_2$O$_{5}$ and PdCl$_2$. The amount of additives were superior in the case of 1% than 4%. H$_2$PtCl$_{6}$ㆍ6$H_2O$ would play an important role for the increase of sensor performance as a catalyst.nce as a catalyst.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.7
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• pp.616-623
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• 2007

A dual micro gas sensor array was fabricated using nano sized $SnO_2$ thin films which had good sensitivities to CO and combustible gases, or $H_2S$ gas for air quality sensors in automobile. The already existed air quality sensor detects oxidizing gases and reducing gases, the air quality sensor(AQS), located near the fresh air inlet detected the harmful gases, the fresh air inlet door/ventilation flap was closed to reduce the amount of pollution entering the vehicle cabin through HVAC(heating, ventilating, and air conditioning) system. In this study, to make $SnO_2$ thin film AQS sensor, thin tin metal layer between 1000 and $2000{\AA}$ thick was oxidized between 600 and $800^{\circ}C$ by thermal oxidation. The gas sensing layers such as $SnO_2$, $SnO_2$(pt) and $SnO_2$(+CuO) were patterned by metal shadow mask for simple fabrication process on the silicon substrate. The micro gas sensors with $SnO_2$(+Pt) and $SnO_2$(CuO) showed good selectivity to CO gas among reducing gases and good sensitivity to $H_2S$ that is main component of bad odor, separately.

• International Journal of Advanced Culture Technology
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• v.11 no.1
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• pp.325-331
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• 2023

In this paper, we propose a mixed neural network structure of CNN and LSTM that can be used to detect or predict odor occurrence, which is most required in manufacturing industry or real life, using odor complex sensors. In addition, the proposed learning model uses a complex odor sensor to receive four types of data such as hydrogen sulfide, ammonia, benzene, and toluene in real time, and applies this data to an inference model to detect and predict odor conditions. The proposed model evaluated the prediction accuracy of the learning model through performance indicators according to accuracy, and the evaluation result showed an average performance of 94% or more.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.8
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• pp.1679-1686
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• 2009

Odor sensing system that is electronic nose device and its signal processing technique has potential to become a critical service for the people who require tangibility of sense of smell in the multimedia communication. PCA(Principal Component Analysis) have been used for dimensionality reduction and visualization of multivariate measurement data. PCA is good for estimating importance value by variance of data but, have some limitation for getting meaningful representation from odor sensing system. This paper explain about how to analyze the data of odor sensing system by ICA(Independent Component Analysis). We show that ICA can give better result like sensor drift analysis, dimensionality reduction and data representation by improved discrimination.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.464-469
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• 2023

As modern society develops, the number of diseases caused by bad smells is increasing. As it can harm people's health, it is important to predict in advance the extent to which bad smells may occur, inform the public about this, and take preventive measures. In this paper, we propose a hybrid neural network structure of CNN and LSTM that can be used to detect or predict the occurrence of odors, which are most required in manufacturing or real life, using odor complex sensors. In addition, the proposed learning model uses a complex odor sensor to receive four types of data, including hydrogen sulfide, ammonia, benzene, and toluene, in real time, and applies this data to the inference model to detect and predict the odor state. The proposed model evaluated the prediction accuracy of the training model through performance indicators based on accuracy, and the evaluation results showed an average performance of more than 94%.

• 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.

• Fire Science and Engineering
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• v.23 no.2
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• pp.1-5
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• 2009

We studies wish to investigated establishment form of cabinet board, and confirm possibility of electrical disaster prevention through reappearance experiment of odor detection system. Established breaker consists of MCCB, RCD order in cabinet board for house, but industry is used together with. When imposed shock using shaker to terminal block that contact becomes in appropriate, flame was made sure. According to result that experiment attaching odor capsule in terminal block, capsule commissioned exactly by occurred heat. According to establishment position of sensor, difference of inspection time was about 10 seconds. Estimate odor inspection system by thing which electrical device accident prevention is available. When there is abnormal generated heat in connection of electric wire, accident prevention estimates that is possible by giving an alarm state of overheat to administrator.

• Journal of Sensor Science and Technology
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• v.21 no.4
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• pp.249-255
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• 2012

Among the human senses, olfactory information still does not have a proper data presentation method unlike that regarding vision and auditory information. It makes presenting the sense of smell into multimedia information impossible, which may be an exploratory field in human computer interaction. In this paper, we propose an olfactory information presentation method, which is a way to use smell as multimedia information, and show an application for scent generation and odor display using a web service. The olfactory information can present smell characteristics such as intensity, persistence, hedonic tone, and odor description. The structure of data format based on olfactory information can also be organized according to data types such as integer, float, char, string, and bitmap. Furthermore, it can be used for data transmitting via a web service and for odor display using a scent generator. The scent generator, which can display information of smell, is developed to generate 6 odors using 6 aroma solutions and a diluted solution with 14 micro-valves and a micropump. Throughout the experiment, we confirm that the remote user can grasp information of smell transmitted by messenger service and request odor display to the computer controlled scent generator. It contributes to enlarge existing virtual reality and to be proposed as a standard reference method regarding olfactory information presentation for future multimedia technology.