• Title/Summary/Keyword: Automatic Observation

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Quantitative Analysis of Mineral Composition in Porland Cement Clinker by X-ray Diffraction (포틀랜드 시멘트 클린커 광물조성의 X선구절에 의한 정량분석)

  • Chang, Se-Kyung;Rhee, Jhun;Han, Ki-Sung
    • Journal of the Korean Ceramic Society
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    • v.23 no.2
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    • pp.64-70
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    • 1986
  • In this investigation x-ray diffraction method was mainly studied for quantitative analysis of clinker mineral composition. And also optical microscopic observation and Bogue calculation method were applied to compare with the x-ray diffraction method. In the procedure of x-ray diffraction analysis graphite monochromator automatic divergence slit and spinner for sample holder were used for minimizing the error due to the operation of the equipment. Especially the separation of overlapped peaks were proceeded by micro-processor automatically. The results of x-ray diffraction method for synthesized clinker were consistent with the Bogue value and the results of optical microscopic observation. However the results of quantitative analysis of mineral composition or commercial clinker containing solid solution of minor component were different from the Bogue value. On the other hand they agreed reasonably well with results of the optical mic-roscopic observation.

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The Characteristics of Air Temperature according to the Location of Automatic Weather System (AWS 설치장소에 따른 기온 특성)

  • Joo, Hyong-Don;Lee, Mi-Ja;Ham, In-Wha
    • Atmosphere
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    • v.15 no.3
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    • pp.179-186
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    • 2005
  • Due to several difficulties, a number of Automatic Weather Systems (AWS) operated by Korea Meteorological Administration (KMA) are located on the rooftop so that the forming of standard observation environment to obtain the accuracy is needed. Therefore, the air temperature of AWSs on the synthetic lawn and the concrete of the rooftop is compared with the standard observation temperature. The hourly mean temperature is obtained by monthly and hourly mean value and the difference of temperature is calculated according to the location, the weather phenomenon, and cloud amount. The maximum and the minimum temperatures are compared by the conditions, such as cloud amount, the existence of precipitation or not. Consequently, the temperature on the synthetic lawn is higher than it on the concrete so that it is difficult to obtain same effect from ASOS, on the contrary the installation of AWS on the synthetic lawn seem to be inadequate due to heat or cold source of the building.

A Method for Correcting Air-Pressure Data Collected by Mini-AWS (소형 자동기상관측장비(Mini-AWS) 기압자료 보정 기법)

  • Ha, Ji-Hun;Kim, Yong-Hyuk;Im, Hyo-Hyuc;Choi, Deokwhan;Lee, Yong Hee
    • Journal of the Korean Institute of Intelligent Systems
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    • v.26 no.3
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    • pp.182-189
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    • 2016
  • For high accuracy of forecast using numerical weather prediction models, we need to get weather observation data that are large and high dense. Korea Meteorological Administration (KMA) mantains Automatic Weather Stations (AWSs) to get weather observation data, but their installation and maintenance costs are high. Mini-AWS is a very compact automatic weather station that can measure and record temperature, humidity, and pressure. In contrast to AWS, costs of Mini-AWS's installation and maintenance are low. It also has a little space restraints for installing. So it is easier than AWS to install mini-AWS on places where we want to get weather observation data. But we cannot use the data observed from Mini-AWSs directly, because it can be affected by surrounding. In this paper, we suggest a correcting method for using pressure data observed from Mini-AWS as weather observation data. We carried out preconditioning process on pressure data from Mini-AWS. Then they were corrected by using machine learning methods with the aim of adjusting to pressure data of the AWS closest to them. Our experimental results showed that corrected pressure data are in regulation and our correcting method using SVR showed very good performance.

Automatic Thresholding Selection for Image Segmentation Based on Genetic Algorithm (유전자알고리즘을 이용한 영상분할 문턱값의 자동선정에 관한 연구)

  • Lee, Byung-Ryong;Truong, Quoc Bao;Pham, Van Huy;Kim, Hyoung-Seok
    • Journal of Institute of Control, Robotics and Systems
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    • v.17 no.6
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    • pp.587-595
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    • 2011
  • In this paper, we focus on the issue of automatic selection for multi-level threshold, and we greatly improve the efficiency of Otsu's method for image segmentation based on genetic algorithm. We have investigated and evaluated the performance of the Otsu and Valley-emphasis threshold methods. Based on this observation we propose a method for automatic threshold method that segments an image into more than two regions with high performance and processing in real-time. Our paper introduced new peak detection, combines with evolution algorithm using MAGA (Modified Adaptive Genetic Algorithm) and HCA (Hill Climbing Algorithm), to find the best threshold automatically, accurately, and quickly. The experimental results show that the proposed evolutionary algorithm achieves a satisfactory segmentation effect and that the processing time can be greatly reduced when the number of thresholds increases.

Vessel Detection Using Satellite SAR Images and AIS Data (위성 SAR 영상과 AIS을 활용한 선박 탐지)

  • Lee, Kyung-Yup;Hong, Sang-Hoon;Yoon, Bo-Yeol;Kim, Youn-Soo
    • Journal of the Korean Association of Geographic Information Studies
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    • v.15 no.2
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    • pp.103-112
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    • 2012
  • We demonstrate the preliminary results of ship detection application using synthetic aperture radar (SAR) and automatic identification system (AIS) together. Multi-frequency and multi-temporal SAR images such as TerraSAR-X and Cosmo-SkyMed (X-band), and Radarsat-2 (C-band) are acquired over the West Sea in South Korea. In order to compare with SAR data, we also collected an AIS data. The SAR data are pre-processed considering by the characteristics of scattering mechanism as for sea surface. We proposed the "Adaptive Threshold Algorithm" for classification ship efficiently. The analyses using the combination of the SAR and AIS data with time series will be very useful to ship detection or tracing of the ship.

Observation of surface roughness on three types of resin based on grinding time of dental automatic barrel finishing (치과용 자동바렐연마기의 연마시간에 따른 3종 레진의 표면거칠기 관찰)

  • Jung, An-Na;Ko, Hyeon-Jeong;Park, Yu-Jin
    • Journal of Technologic Dentistry
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    • v.43 no.2
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    • pp.56-61
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    • 2021
  • Purpose: This study aimed to produce resin prosthetics using a dental automatic barrel finishing. Surface roughness and surface topography of resins were observed according to the grinding time of the dental automatic barrel finishing. Methods: This study was performed with thermopolymer, autopolymer, and photopolymer resins. The dimensions of the specimen were 10×10×2 mm. Each specimen was polymerized according to the manufacturer's instructions. The polymerized resin was honed for 30 minutes at 5-min intervals in a dental automatic barrel finishing. The specimen was observed using a three-dimensional (3D) optical microscope, and the surface roughness was measured. Results: After the polishing with the dental automatic barrel finishing, the heat-cured (HC) specimen showed the highest and lowest values of Ra after 10 and 15 minutes, respectively. The self-cured (SC) specimen showed the highest and lowest values of Ra after 10 and 25 minutes, respectively. Finally, the 3D specimen showed the highest and lowest values of Ra after 5 and 20 minutes, respectively. Conclusion: After measuring the surface roughness of the three types of resins according to the grinding time of the dental automatic barrel finishing, the lowest Ra values for the HC, SC, and 3D specimens were measured after 15, 25, and 20 minutes, respectively. Therefore, we concluded that a limit on the grinding time of the resin using a dental automatic barrel finishing is needed.

Study on the Impact of Various Observations Data Assimilation on the Meteorological Predictions over Eastern Part of the Korean Peninsula (관측자료별 자료동화 성능이 한반도 동부 지역 기상 예보에 미치는 영향 분석 연구)

  • Kim, Ji-Seon;Lee, Soon-Hwan;Sohn, Keon-Tae
    • Journal of Environmental Science International
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    • v.27 no.11
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    • pp.1141-1154
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    • 2018
  • Numerical experiments were carried out to investigate the effect of data assimilation of observational data on weather and PM (particulate matter) prediction. Observational data applied to numerical experiment are aircraft observation, satellite observation, upper level observation, and AWS (automatic weather system) data. In the case of grid nudging, the prediction performance of the meteorological field is largely improved compared with the case without data assimilations because the overall pressure distribution can be changed. So grid nudging effect can be significant when synoptic weather pattern strongly affects Korean Peninsula. Predictability of meteorological factors can be expected to improve through a number of observational data assimilation, but data assimilation by single data often occurred to be less predictive than without data assimilation. Variation of air pressure due to observation nudging with high prediction efficiency can improve prediction accuracy of whole model domain. However, in areas with complex terrain such as the eastern part of the Korean peninsula, the improvement due to grid nudging were only limited. In such cases, it would be more effective to aggregate assimilated data.