• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.210-210
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• 2000

In this paper, we have investigated the properties of multi-layer perceptron (MLP) for odour patterns classification and concentration estimation simultaneously. When the MLP may be has a fast convergence speed with small error and excellent mapping ability for classification, it can be possible to use for classification and concentration prediction of volatile chemicals simultaneously. However, the conventional MLP, which is back-Propagation of error based on the steepest descent method, was difficult to use for odour classification and concentration estimation simultaneously, because it is slow to converge and may fall into the local minimum. We adapted the Levenberg-Marquardt(LM) algorithm [4,5] having advantages both the steepest descent method and Gauss-Newton method instead of the conventional steepest descent method for the simultaneous classification and concentration estimation of odours. And, We designed the artificial odour sensing system(Electronic Nose) and applied LM-BP algorithm for classification and concentration prediction of VOC gases.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.790-791
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• 2016

The system used in the laboratory of chemistry and medical is management only by measuring the temperature inside the reagent management within and recording in handwriting. When you hold the reagent, it can not recognize in real time the problems that occur in the interior, an accident occurs. you can not find a use record reagent storage, a problem with the management of an efficient reagent can be generated. In this paper, we propose a reagent management system that leverages the embedded boards and sensors in the laboratory reagents effectively manage to resolve it. As a result, Converting the information of the reagent to the data using the NFC, the administrator can identify the reagent user to register and manage hazardous reagents. Converted by using the NFC information of the reagent to the data, the administrator can identify the reagent user to register and manage hazardous reagents, temperature, humidity, so that it can be controlled by utilizing the VOC sensor to. Also it is passes the message to the administrator in the event of a particular risk situation. This is believed to enable the effective administration in a laboratory reagent.

• Journal of Sensor Science and Technology
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• v.22 no.2
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• pp.162-173
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• 2013

The purpose of this paper is to classify VOC gases by emulating the characteristics found in biological olfaction. For this purpose, we propose new signal processing method based a polymeric chemical sensor array consisting of 4096 sensors which is created by NEUROCHEM project. To remove unstable sensors generated in the manufacturing process of very large scaled chemical sensor array, we used discrete wavelet transformation and cosine similarity. And, to remove the supernumerary redundancy, we proposed the method of selecting candidates of representative sensor representing sensors with similar features by Fuzzy c-means algorithm. In addition, we proposed an improved algorithm for selecting representative sensors among candidates of representative sensors to better enhance classification ability. However, Classification for very large scaled sensor array has a great deal of time in process of learning because many sensors are used for learning though a redundancy is removed. Throughout experimental trials for classification, we confirmed the proposed method have an outstanding classification ability, at transient state as well as steady state.

• Journal of Sensor Science and Technology
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• v.20 no.5
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• pp.305-310
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• 2011

This study focuses on the fabrication of $TiO_2$ nanosheets and their gas sensor application. A simple sonochemical method is employed to fabricate the $TiO_2$ nanosheets. The obtained samples were investigated by transmission electron microscope(TEM) and X-ray Diffraction(XRD). The $TiO_2$ nanosheets were coated on substrates by a dropping method followed by heat treatment. The sensor responses to volatile organic compounds(VOCs) such as toluene, benzene, ethanol and acetaldehyde were studied. It was found that the $TiO_2$ nanosheets sensors are able to detect ppb-levels of VOC gases.

• Journal of Sensor Science and Technology
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• v.17 no.1
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• pp.9-14
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• 2008

In this paper, the gas responses of tungsten oxide films prepared by anodic reaction was discussed. Sensing electrodes and heating electrodes were patterned by photolithography method on quartz substrate. Porous tungsten oxide was fabricated in electrolyte solutions of 5 % HF (HF :$C_2H_6OH:H_2O$=3 : 2 : 20) by anodic reaction. The anodic reaction with metal (platinum wire) as a cathode and the sensing device as an anode was conducted under the various reaction times (1-10 min) at 10 mA/$cm^2$ The surface structure and morphology of the fabricated sensor have been analysed by X-ray diffraction (XRD) and field-emission scanning electron microscopy (FE-SEM). All the peaks of XRD results were well indexed to the pure phase pattern. The average diameter of the porous tungsten oxide surface were ranged about 100 nm. The fabricaed sensor showed good sensitivity to 200 ppm toluene at operating temperature of $250^{\circ}C$.

• Journal of Sensor Science and Technology
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• v.11 no.5
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• pp.286-293
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• 2002

We fabricated gas recognition system using conducting polymer sensor array for recognizing and analyzing VOCs(Volatile Organic Compounds) gases. The polypyrrole and polyaniline thin film sensors which were made by chemical polymerization were employed to detect VOCs. The multi-dimensional sensor signals obtained from the sensor array were analyzed using PCA(principal component analysis) technique and RBF(radial basis function) Network. Throughout the experimental trails, we confirmed that RBF Network is effective than PCA technique in identifying VOCs.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.40 no.3
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• pp.149-155
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• 2016

Early detection of toxic gases, such as volatile organic compounds (VOCs), is important for safety and environmental protection. However, the conventional detection methods require long-term measurement times and expensive equipment. In this study, we propose a thin-film-type chemical sensor for VOCs, which consists of self-assembled monosize nanoparticles for 3-D photonic crystal structures and polydimthylsiloxane (PDMS) film. It is operated without any external power source, is truly portable, and has a fast response time. The structure color of the sensor changes when it is exposed to VOCs, because VOCs induce a swelling of the PDMS. Therefore, using this principle of color change, we can create a thin-film sensor for immediate detection of various types of VOCs. The proposed device evidences that a fast response time of just seconds, along with a clear color change, are successfully observed when the sensor is exposed to gas-phase VOCs.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.159-160
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• 2019

일반적인 FOCV MPPT는 VOC와 VMPP와의 관계인 ${\alpha}$를 외부에서 지정해준다. 하지만 외부환경 (조도나 온도)에 따라서 태양전지의 ${\alpha}$값이 변화할 가능성이 있다. 본 논문에서는 저전력 IoT 센서의 구동을 위한 태양열 에너지 하베스팅을 위해 IV Curve를 이용한 태양전지 전력 계싼회로를 제안한다. IV Curve를 이용한 태양전지 전력을 직접 계산하여 FOCV MPPT를 개선함으로써 보다 높은 효율의 MPPT가 가능하고 외부환경의 변화에도 충분히 Maximum Power Point Tracking이 가능해지게 된다.

• Journal of Platform Technology
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• v.9 no.4
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• pp.79-89
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• 2021

In this paper, the fine dust (PM10) and ultrafine dust (PM2.5) measurement platforms are designed to be mobile and fixed using oneM2M, the international standard for IoT. The fine dust measurement platform is composed and designed with a fine dust measurement device, agent, oneM2M platform, oneM2M IPE, and monitoring system. The main difference between mobile and fixed is that the mobile uses the MQTT protocol for interconnection between devices and services without blind spots based on LTE connection, and the fixed uses the LoRaWAN protocol with low power and wide communication range. Not only fine dust, but also temperature, humidity, atmospheric pressure, volatile organic compounds (VOC), carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NO2), and noise data related to daily life were collected. The collected sensor values were managed using the common API provided by oneM2M through the agent and oneM2M IPE, and it was designed into four resource types: AE and container. Six functions of operability, flexibility, convenience, safety, reusability, and scalability were analyzed through the fine dust measurement platform design.

• Journal of Sensor Science and Technology
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• v.27 no.4
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• pp.227-231
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• 2018

Indoor air pollution has become a serious issue, affecting the health and comfort of building occupants. Volatile organic compounds (VOCs) are among the most common indoor contaminants, and are released from numerous indoor emission sources. Among the VOCs, formaldehyde and toluene are toxic chemicals at low levels and are frequently detected indoors. Exposure to formaldehyde and toluene can irritate sensitive tissue and may increase the risk of cancer. Therefore, monitoring formaldehyde and toluene is critical for the health and comfort of residents. In addition, as human indoor activities can generate VOC gases, analysis of their influence on VOCs is needed. In this study, we compared electronic nose (E-Nose) data for formaldehyde and toluene with E-Nose data for indoor mixture gas with consideration for human indoor activities.