• Transactions on Control, Automation and Systems Engineering
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• 제3권4호
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• pp.223-228
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• 2001

We have been developed an intelligent mobile robot with an artificial olfactory function to recognize odours and to track odour source location. This mobile robot also has ben installed an engine for speech recognition and synthesis and is controlled by wireless communication. An artificial olfactory system based on array of 7 gas sensors has been installed in the mobile robot for odour recognition, and 11 gas sensors also are located in the obttom of robot to track odour sources. 3 optical sensors are also in cluded in the intelligent mobile robot, which is driven by 2 D. C. motors, for clash avoidance in a way of direction toward an odour source. Throughout the experimental trails, it is confirmed that the intelligent mobile robot is capable of not only the odour recognition using artificial neural network algorithm, but also the tracking odour source using the step-by-step approach method. The preliminary results are promising that intelligent mobile robot, which has been developed, is applicable to service robot system for environmental monitoring, localization of odour source, odour tracking of hazardous areas etc.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.405-405
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• 2000

We designed the artificial olfactory sensing system (Electronic Nose) using MOS type sensor array fur recognizing and analyzing odour. The response of individual sensors of sensor array, each processing a slightly different response towards the sample volatiles, can provide enough information to discriminate between sample odours. In this paper, we applied clustering algorithm for dimension reduction, such as linear projection mapping (PCA method), nonlinear mapping (Sammon mapping method) and the combination of PCA and Sammon mapping having a better discriminating ability. The odours used are VOC (Volatile chemical compound) and Toxic gases.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 1997년도 춘계학술대회 논문집
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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.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.137.2-137
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• 2001

We have been developed an intelligent mobile robot with an artificial olfactory function to recognize odours and to track odour source location. This mobile robot also has been installed an engine for speech recognition and synthesis, and is controlled by wireless communication. An artificial olfactory system based on array of 7 gas sensors has been installed in the mobile robot for odour recognition, and 11 gas sensors also are located in the bottom of robot to track odour sources. 3 optical sensors are also included in the intelligent mobile robot, which is driven by 2 D.C. motors, for clash avoidance in a way of direction toward an odour source. Throughout the experimental trails, it is confirmed that the intelligent mobile robot is capable of not only the odour recognition using artificial neural network algorithm, but also the tracking odour source using the step-by-step approach method ...

• 산업기술연구
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• 제31권B호
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• pp.45-50
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• 2011

Recently, machine olfactory systems that have been proposed as an artificial substitute of the human olfactory system are being studied by many researchers because they can scent dangerous gases and identify the type of gases in contamination areas instead of the human. In this paper, we present an effective design method for the gas identification system. The design method adopted the sequential combination between genetic algorithms and TSK fuzzy logic system. First, the proposed method allowed the designed gas identification system effectively performing the pattern analysis because it was able to avoid the curse of dimensionality caused by use of a large number of sensors. Secondly, the method led the gas identification system to good performance because it was able to deal with drift characteristics of the sensor data by using description ability of the fuzzy system for nonlinear data. In simulation, we demonstrated the effectiveness of the designed gas identification system by using the simulation results of five types of gases.

• 전기학회논문지
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• 제61권8호
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• pp.1164-1171
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• 2012

Recently, machine olfactory systems as an artificial substitute of the human olfactory system are being studied actively because they can scent dangerous gases and identify the type of gases in contamination areas instead of the human. In this paper, we present an effective design method for the gas identification system. Even though dimensionality reduction is the very important part, in pattern analysis, We handled effectively the dimensionality reduction by grouping the sensors of which the measured patterns are similar each other, where genetic algorithms were used for combination optimization. To identify the gas type, we constructed the hierarchical rule base with two frames by using rough set theory. The first frame is to accept measurement characteristics of each sensor and the other one is to reflect the identification patterns of each group. Thus, the proposed methods was 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.

• 감성과학
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• 제21권4호
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• pp.11-24
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• 2018

본 연구는 사회적 배제가 물리적 따뜻함을 추구하게 만든다는 선행연구에 기초하여 사회적 배제가 감성적 따뜻함을 추구하게 만들고, 감성적 차가움을 회피하게 만들 것이라는 예측을 향 감성을 사용하여 검증하기 위해 이루어졌다. 이를 위해 차가운 감성으로 지각되는 향과 따뜻한 감성으로 지각되는 향을 선정하기 위한 사전조사를 실시한 후, 사회적 배제를 지각한 집단과 통제 집단의 향 선호도에 차이가 있는지 확인하기 위한 두 가지 실험을 진행하였다. 결과적으로 사회적 배제를 경험한 사람은 그렇지 않은 사람보다 따뜻한 향에 대한 선호가 강한 반면, 차가운 향에 대한 선호는 약했다. 본 연구는 사회적 배제가 물리적 따뜻함을 추구하게 만드는 현상을 감성적 차원으로 확장했다는 측면과 선행연구에서 간과해 왔던 차가움을 회피하게 하는 현상까지 관찰했다는 측면에서 이론적으로 중요하다. 또한 컴포트 푸드, 인물 감성, 공간 감성 디자인, 인공지능 채팅봇의 감성 등에도 실용적 시사점을 가진다.

• 센서학회지
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• 제27권2호
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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.

• 감성과학
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• 제13권1호
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• pp.235-242
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• 2010

최근 학제간 교류가 빈번해지고 그 경계마저도 무너지고 있는 추세에서 감성과학에 대한 연구범위는 그 어느 때보다도 넓어지고 있다. 과거 심리학, 환경디자인, 두뇌 신경학 중심의 학제연구를 넘어서 인류학, 사회학, 문화 역사학, 예술, 공학 등 모든 분야에 걸쳐 감성에 대한 관심이 높아지고, 또 이들 간의 견고한 학제연구의 필요성이 제기되고 있다. 본 논문에서는 일차적으로 감성연구의 각 분과학문의 지평 확대를 위해 동물모델을 이용한 감성기법, 인공 후각센서와 뉴런 칩 기술의 적용가능, 감성과학을 이용한 인간 대사조절 등의 연구 가능성을 타진해 보고 향후 감성연구가 심리학이나 의학, 이공계학은 물론 철학, 역사 문화, 사회학 등의 전방위적 학제간 연구로 확장될 필요성을 제시한다. 동물 모델을 이용한 감성측정기법에서는 주로 감성의 근원지를 뇌로 규정하고 뇌신경을 자극했을 때 나타나는 현상 등을 모니터링하는 기법등을 소개한다. 인공후각센서와 뉴런칩에 관한 내용은 최근의 첨단 나노/마이크로 응용기술을 감성과학분야에 적용하려는 사례를 소개하는 것으로 반도체 공정으로 만든 칩위에 후각세포나 신경세포를 키우면서 전기적 신호를 읽는 신기술을 소개한다. 마지막으로 소리를 감성의 한 자극체로 보고 인간의 생리대사, 특히 비만 관리에 있어 감성과학을 응용한 사례를 자세히 보고한다.