• 제목/요약/키워드: Hybrid sensing

검색결과 149건 처리시간 0.025초

R.F 마그네트론 스퍼트링으로 작성된 $TiO_2$박막의 $NO_x$ 감지 특성 ($NO_x$ Sensing Characteristic of $TiO_2$ Thin Film Deposited by R.F Magnetron Sputtering)

  • 고희석;박재윤;박상현
    • 대한전기학회논문지:전기물성ㆍ응용부문C
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    • 제51권12호
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    • pp.567-572
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    • 2002
  • In these days, diesel vehicle or power plant emits $NO_X\; and SO_2$ which cause air pollution like acid-rain, ozone layer destroy and optical smoke, therefore there are many kinds of methods considered for removing them such as SCR, catalyst, plasma process, and plasma-catalyst hybrid process. T$TiO_2$ is commonly used as catalyst to remove $NO_X$ gas because it have very excellent chemical characteristic as photo catalyst. In this paper, $NO_X$ sensing characteristic of $TiO_2$ thin film deposited by R.F Magnetron sputtering is investigated. A finger shaped electrode on $Al_2$O$_3$ substrate is designed and $TiO_2$ is deposited on the electrode by the magnetron sputtering deposition system. Chemical composition of the deposited $TiO_2$ thin film is $TiO_{1.9}$ by RBS analysis. When the UV is irradiated on it with flowing air, capacitance of $TiO_2$ thin film increases, however, when NO gas is put into the system with air, it immediately decreases because of photo chemical reaction. and it monotonously decreases with increasing NO concentration.

Pan-sharpening Effect in Spatial Feature Extraction

  • Han, Dong-Yeob;Lee, Hyo-Seong
    • 대한원격탐사학회지
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    • 제27권3호
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    • pp.359-367
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    • 2011
  • A suitable pan-sharpening method has to be chosen with respect to the used spectral characteristic of the multispectral bands and the intended application. The research on pan-sharpening algorithm in improving the accuracy of image classification has been reported. For a classification, preserving the spectral information is important. Other applications such as road detection depend on a sharp and detailed display of the scene. Various criteria applied to scenes with different characteristics should be used to compare the pan-sharpening methods. The pan-sharpening methods in our research comprise rather common techniques like Brovey, IHS(Intensity Hue Saturation) transform, and PCA(Principal Component Analysis), and more complex approaches, including wavelet transformation. The extraction of matching pairs was performed through SIFT descriptor and Canny edge detector. The experiments showed that pan-sharpening techniques for spatial enhancement were effective for extracting point and linear features. As a result of the validation it clearly emphasized that a suitable pan-sharpening method has to be chosen with respect to the used spectral characteristic of the multispectral bands and the intended application. In future it is necessary to design hybrid pan-sharpening for the updating of features and land-use class of a map.

The Detection of Yellow Sand with Satellite Infrared bands

  • Ha, Jong-Sung;Kim, Jae-Hwan;Lee, Hyun-Jin
    • 대한원격탐사학회지
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    • 제22권5호
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    • pp.403-406
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    • 2006
  • An algorithm for detection of yellow sand aerosols has been developed with infrared bands. This algorithm is a hybrid algorithm that has used two methods combined. The first method used the differential absorption in brightness temperature difference between $11{\mu}m\;and\;12{\mu}m\;(BTD1)$. The radiation at $11{\mu}m$ is absorbed more than at $12{\mu}m$ when yellow sand is loaded in the atmosphere, whereas it will be the other way around when cloud is present. The second method uses the brightness temperature difference between $3.7{\mu}m\;and\;11{\mu}m(BTD2)$. This technique is sensitive to dust loading, which the BTD2 is enhanced by reflection of $3.7{\mu}m$ solar radiation. First the Principle Component Analysis (PCA), a form of eigenvector statistical analysis from the two methods, is performed and the aerosol pixel with the lowest 10% of the eigenvalue is eliminated. Then the aerosol index (AI) from the combination of BTD 1 and 2 is derived. We applied this method to Multi-functional Transport Satellite-l Replacement (MTSAT-1R) data and obtained that the derived AI showed remarkably good agreements with Ozone Mapping Instrument (OMI) AI and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth.

Rockfall Source Identification Using a Hybrid Gaussian Mixture-Ensemble Machine Learning Model and LiDAR Data

  • Fanos, Ali Mutar;Pradhan, Biswajeet;Mansor, Shattri;Yusoff, Zainuddin Md;Abdullah, Ahmad Fikri bin;Jung, Hyung-Sup
    • 대한원격탐사학회지
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    • 제35권1호
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    • pp.93-115
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    • 2019
  • The availability of high-resolution laser scanning data and advanced machine learning algorithms has enabled an accurate potential rockfall source identification. However, the presence of other mass movements, such as landslides within the same region of interest, poses additional challenges to this task. Thus, this research presents a method based on an integration of Gaussian mixture model (GMM) and ensemble artificial neural network (bagging ANN [BANN]) for automatic detection of potential rockfall sources at Kinta Valley area, Malaysia. The GMM was utilised to determine slope angle thresholds of various geomorphological units. Different algorithms(ANN, support vector machine [SVM] and k nearest neighbour [kNN]) were individually tested with various ensemble models (bagging, voting and boosting). Grid search method was adopted to optimise the hyperparameters of the investigated base models. The proposed model achieves excellent results with success and prediction accuracies at 95% and 94%, respectively. In addition, this technique has achieved excellent accuracies (ROC = 95%) over other methods used. Moreover, the proposed model has achieved the optimal prediction accuracies (92%) on the basis of testing data, thereby indicating that the model can be generalised and replicated in different regions, and the proposed method can be applied to various landslide studies.

유무기 페로브스카이트 나노입자의 휘발성 유기화합물 감응특성 (Detection of Volatile Organic Compounds (VOCs) using Organic-Inorganic Hybrid Perovskite Nanoparticles)

  • 최한솔;최지훈
    • 한국재료학회지
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    • 제30권10호
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    • pp.515-521
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    • 2020
  • Organic-inorganic hybrid perovskite nanocrystals have attracted a lot of attention owing to their excellent optical properties such as high absorption coefficient, high diffusion length, and photoluminescence quantum yield in optoelectronic applications. Despite the many advantages of optoelectronic materials, understanding on how these materials interact with their environments is still lacking. In this study, the fluorescence properties of methylammonium lead bromide (CH3NH3PbBr3, MAPbBr3) nanoparticles are investigated for the detection of volatile organic compounds (VOCs) and aliphatic amines (monoethylamine, diethylamine, and trimethylamine). In particular, colloidal MAPbBr3 nanoparticles demonstrate a high selectivity in response to diethylamine, in which a significant photoluminescence (PL) quenching (~ 100 %) is observed at a concentration of 100 ppm. This selectivity to the aliphatic amines may originate from the relative size of the amine molecules that must be accommodated in the perovskite crystals structure with a narrow range of tolerance factor. Sensitive PL response of MAPbBr3 nanocrystals suggests a simple and effective strategy for colorimetric and fluorescence sensing of aliphatic amines in organic solution phase.

Robust Extraction of Lean Tissue Contour From Beef Cut Surface Image

  • Heon Hwang;Lee, Y.K.;Y.r. Chen
    • 한국농업기계학회:학술대회논문집
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    • 한국농업기계학회 1996년도 International Conference on Agricultural Machinery Engineering Proceedings
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    • pp.780-791
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    • 1996
  • A hybrid image processing system which automatically distinguished lean tissues in the image of a complex beef cut surface and generated the lean tissue contour has been developed. Because of the in homegeneous distribution and fuzzy pattern of fat and lean tissue on the beef cut, conventional image segmentation and contour generation algorithm suffer from a heavy computing requirement, algorithm complexity and poor robustness. The proposed system utilizes an artificial neural network enhance the robustness of processing. The system is composed of pre-network , network and post-network processing stages. At the pre-network stage, gray level images of beef cuts were segmented and resized to be adequate to the network input. Features such as fat and bone were enhanced and the enhanced input image was converted tot he grid pattern image, whose grid was formed as 4 X4 pixel size. at the network stage, the normalized gray value of each grid image was taken as the network input. Th pre-trained network generated the grid image output of the isolated lean tissue. A training scheme of the network and the separating performance were presented and analyzed. The developed hybrid system showed the feasibility of the human like robust object segmentation and contour generation for the complex , fuzzy and irregular image.

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SOG(Silicon On Glass)공정을 이용한 수평형 미소가속도계의 제작에 관한 연구 (A Study on the Fabrication of the Lateral Accelerometer using SOG(Silicon On Glass) Process)

  • 최범규;장태하;이창길;정규동;김종팔
    • 센서학회지
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    • 제13권6호
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    • pp.430-435
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    • 2004
  • The resolution of the accelerometer, fabricated with MEMS technology is mainly affected by mechanical and electrical noise. To reduce mechanical noise, we have to increase mass of the structure part and quality factor related with the degree of vacuum packaging. On the other hand, to increase mass of the structure part, the thickness of the structure must be increased and ICP-RIE is used to fabricate the high aspect ratio structure. At this time, footing effect make the sensitivity of the accelerometer decreasing. This paper presents a hybrid SOG(Silicon On Glass) Process to fabricate a lateral silicon accelerometer with differential capacitance sensing scheme which has been designed and simulated. Using hybrid SOG Process, we could make it a real to increase the structural thickness and to prevent the footing effect by deposition of metal layer at the bottom of the structure. Moreover, we bonded glass wafer to structure wafer anodically, so we could realize the vacuum packaging at wafer level. Through this way, we could have an idea of controlling of quality factor.

D-space-controlled graphene oxide hybrid membrane-loaded SnO2 nanosheets for selective H2 detection

  • Jung, Ji-Won;Jang, Ji-Soo
    • 센서학회지
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    • 제30권6호
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    • pp.376-380
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    • 2021
  • The accurate detection of hydrogen gas molecules is considered to be important for industrial safety. However, the selective detection of the gas using semiconductive metal oxides (SMOs)-based sensors is challenging. Here, we describe the fabrication of H2 sensors in which a nanocellulose/graphene oxide (GO) hybrid membrane is attached to SnO2 nanosheets (NSs). One-dimensional (1D) nanocellulose fibrils are attached to the surface of GO NSs (GONC membrane) by mixing GO and nanocellulose in a solution. The as-prepared GONC membrane is employed as a sacrificial template for SnO2 NSs as well as a molecular sieving membrane for selective H2 filtration. The combination of GONC membrane and SnO2 NSs showed substantial selectivity to hydrogen gas (Rair / Rgas > 10 @ 0.8 % H2, 100 ℃) with noise level responses to interfering gases (H2S, CO, CH3COCH3, C2H5OH, and NO2). These remarkable sensing results are attributed mainly to the molecular sieving effect of the GONC membrane. These results can facilitate the development of a highly selective H2 detector using SMO sensors.

KOMPSAT-3·3A 위성영상 글로벌 융합활용을 위한 다중센서 위성영상과의 정밀영상정합 (Fine-image Registration between Multi-sensor Satellite Images for Global Fusion Application of KOMPSAT-3·3A Imagery)

  • 김태헌;윤예린;이창희;한유경
    • 대한원격탐사학회지
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    • 제38권6_4호
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    • pp.1901-1910
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    • 2022
  • 뉴스페이스(new space) 시대가 도래함에 따라 국내 KOMPSAT-3·3A 위성영상과 해외 위성영상과의 글로벌 융합활용 기술확보가 대두되고 있다. 일반적으로 다중센서 위성영상은 취득 당시의 다양한 외부요소로 인해 영상 간 상대적인 기하오차(relative geometric error)가 발생하며, 이로 인해 위성영상 산출물의 품질이 저하된다. 따라서 본 연구에서는 KOMPSAT-3·3A 위성영상과 해외 위성영상 간 존재하는 상대기하오차를 최소화하기 위한 정밀영상정합(fine-image registration) 방법론을 제안한다. KOMPSAT-3·3A 위성영상과 해외 위성영상 간 중첩영역을 선정한 후 두 영상 간 공간해상도를 통일한다. 이어서, 특징 및 영역 기반 정합기법을 결합한 형태의 하이브리드(hybrid) 정합기법을 이용하여 정합점(tie-point)을 추출한다. 그리고 피라미드(pyramid) 영상 기반의 반복적 정합을 수행하여 정밀영상정합을 수행한다. KOMPSAT-3·3A 위성영상과 Sentinel-2A 및 PlanetScope 영상을 이용하여 제안기법의 정확도 및 성능을 평가하였다. 그 결과, Sentienl-2A 영상 기준 평균 Root Mean Square Error (RMSE) 1.2 pixels, PlanetScope 영상 기준 평균 RMSE 3.59 pixels의 정확도가 도출되었다. 이를 통해 제안기법을 이용하여 효과적으로 정밀영상정합을 수행할 수 있을 것으로 사료된다.

태양광/디젤 하이브리드 시스템 기반 센서 구동 및 환경 모니터링 컨테이너 하우스 개발 (Development of Container House Equipped with Sensing and Environmental Monitoring System Based on Photovoltaic/Diesel Hybrid System)

  • 박미정;주종율;김응곤
    • 한국전자통신학회논문지
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    • 제18권3호
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    • pp.459-464
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    • 2023
  • 본 논문은 태양광을 이용하여 에너지를 발전하여 생성되는 전력으로 각종 센서 및 환경 모니터링이 가능하도록 계통 독립형 전력을 공급한다. 생산된 잉여 전력은 리튬 배터리에 저장시켜 태양광이 없는 환경에서도 컨테이너 하우스가 원활한 구동이 가능하도록 설계하였다. 긴 장마나 폭설로 인하여 태양광 생성이 어려우면 디젤발전으로 시스템이 멈추지 않고 구동할 수 있도록 하였다. 태양광 및 전력 관리를 위해 BMS(Battery Management System)를 구축하여 태양광 방/충전 및 사용량을 모니터링한다. 각종 센싱 데이터를 자동으로 기록하고 전송되며, 컴퓨터 및 스마트폰 앱을 통해 무선 모니터링이 가능하도록 설계하였다. 본 연구에서 제안하는 컨테이너 하우스는 계통 전원이 없는 오지, 공원, 행사장, 공사현장 등에서 최적의 에너지 운영을 수행함으로써 효율적인 에너지 관리가 가능하다.