• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.150-150
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• 2018

The Numerical Weather Prediction (NWP) models provide information for weather forecasts. The highly nonlinear and complex interactions in the atmosphere are simplified in meteorological models through approximations and parameterization. Therefore, the simplifications may lead to biases and errors in model results. Although the models have improved over time, the biased outputs of these models are still a matter of concern in meteorological and hydrological studies. Thus, bias removal is an essential step prior to using outputs of atmospheric models. The main idea of statistical bias correction methods is to develop a statistical relationship between modeled and observed variables over the same historical period. The Model Output Statistics (MOS) would be desirable to better match the real time forecast data with observation records. Statistical post-processing methods relate model outputs to the observed values at the sites of interest. In this study three methods are used to remove the possible biases of the real-time outputs of the Weather Research and Forecast (WRF) model in Imjin basin (North and South Korea). The post-processing techniques include the Linear Regression (LR), Linear Scaling (LS) and Power Scaling (PS) methods. The MOS techniques used in this study include three main steps: preprocessing of the historical data in training set, development of the equations, and application of the equations for the validation set. The expected results show the accuracy improvement of the real-time forecast data before and after bias correction. The comparison of the different methods will clarify the best method for the purpose of the forecast skill enhancement in a real-time case study.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.95-99
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• 1999

We proposed a new retrieval method for aerosol's real part of refractive index, optical thickness, and Angstrom exponent using POLDER's directional reflectance and polarization data. We showed that aerosol's real part of refractive index can be retrieved systematically using multi-directional PR(polarization and reflectance) diagrams in a single infrared band by our algorithm for the first time. We examined the retrieved results, by comparing with the simultaneously measured sky observation data at the study site and we obtained a reasonable agreement between them.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.488-491
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• 1988

In this work, we developed a real-time versatile advanced control and supervisory software for a personal computer control. This software, basically, has background and foreground tasks which are performed in parallel at real time. First, background tasks are composed of controls of various kinds, reports and input-ouput of signals etc, which are performed every sampling time. Second, foreground tasks are observation of operation conditions, data search, regulation of controllers and graphical design and display of processes, which are performed by users request. Additionally, this software has the functions of transporting data and composing distributed control systems, and all background tasks are composed of combination of unit function blocks.

• Journal of the Korean earth science society
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• v.30 no.4
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• pp.478-484
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• 2009

A web page was developed to enhance students' learning experience in studying meteorological phenomena. After collecting the meteorological elements observed with automatic weather observation system (AWS), it serve real-time meteorological information on demand. Past meteorological information as well as real-time current information can be retrieved because the web page can save and accumulate observed information in its data base. The completed web page was successfully applied in school settings in teaching students meteorology research sections of earth science. The results show that students experienced authentic and meaningful learning through the real-time meteorological information from the web page. In addition, large scale of time was required to observe meteorological phenomena and it hindered practical meteorological research in earth science classes. However, it is expected that the time limitation can be overcome by utilizing accumulated meteorological information of the web page.

• Korean Journal of Remote Sensing
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• v.28 no.1
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• pp.55-67
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• 2012

Real-time image georeferencing is required to generate spatial information rapidly from the image sequences acquired by multi-sensor systems. To complement the performance of position/attitude sensors and process in real-time, we should employ on-line aerial triangulation based on a sequential estimation algorithm. In this study, we thus attempt to derive an efficient on-line aerial triangulation algorithm for real-time georeferencing of image sequences. We implemented on-line aerial triangulation using the existing Given transformation update algorithm, and a new inverse normal matrix update algorithm based on observation classification, respectively. To compare the performance of two algorithms in terms of the accuracy and processing time, we applied these algorithms to simulated airborne multi-sensory data. The experimental results indicate that the inverse normal matrix update algorithm shows 40 % higher accuracy in the estimated ground point coordinates and eight times faster processing speed comparing to the Given transformation update algorithm. Therefore, the inverse normal matrix update algorithm is more appropriate for the real-time image georeferencing.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.194-198
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• 2005

Although the rainstorm causes local damage on large scale, it is difficult to predict the movement of the rainstorm exactly. In order to reduce the rainstorm damage of the rainstorm, it is necessary to analyze the path of the rainstorm using various statistical methods. In addition, efficient time interval of rainfall observation for the analysis of the rainstorm movement can be derived by applying various statistical methods to rainfall data. In this study, the rainstorm tracking using statistical method is performed for various types of rainfall data. For the tracking of the rainstorm, the methods of temporal distribution, inclined Plane equations, and cross correlation were applied for various types of data including electromagnetic rainfall gauge data and AWS data. The speed and direction of each method were compared with those of real rainfall movement. In addition, the effective time interval of rainfall observation for the analysis of the rainstorm movement was also investigated for the selected time intervals 10, 20, 30, 40, 50, and 60 minutes. As a result, the absolute relative errors of the method of inclined plane equations are smaller than those of other methods in case of electromagnetic rainfall gauges data. The absolute relative errors of the method of cross correlation are smaller than those of other methods in case of AWS data. The absolute relative errors of 30 minutes or less than 30 minutes are smaller than those of other time intervals.

• Publications of The Korean Astronomical Society
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• v.28 no.1
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• pp.1-6
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• 2013

Real-time data reduction pipeline for the Korea Microlensing Telescope Network (KMTNet) was developed by Korea Astronomy and Space Science Institute (KASI). The main goal of the data reduction pipeline is to find variable objects and to record their light variation from the large amount of observation data of about 200 GB per night per site. To achieve the goal we adopt three strategic implementations: precision pointing of telescope using the cross correlation correction for target fields, realtime data transferring using kernel-level file handling and high speed network, and segment data processing architecture using the Sun-Grid engine. We tested performance of the pipeline using simulated data which represent the similar circumstance to CTIO (Cerro Tololo Inter-American Observatory), and we have found that it takes about eight hours for whole processing of one-night data. Therefore we conclude that the pipeline works without problem in real-time if the network speed is high enough, e.g., as high as in CTIO.

• Journal of Korea Foundry Society
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• v.26 no.3
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• pp.129-132
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• 2006

In the present study the new method was proposed by using the real-time X-ray observation and metal die in order to evaluate fluidity and viscosity of the molten metal during pouring into the mold. The special mold for the present experiment was introduced since X-ray could not transmit thick mold wall and scatter the image of the molten metal during pouring. The present study also discussed for evaluation of viscosities by using the flow data from radioscopy images, and the viscosities of six commercial aluminum alloys were evaluated and compared.

• Journal of Information Technology Services
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• v.11 no.sup
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• pp.177-189
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• 2012

We developed the ocean disaster detection system(OD2S) which copes with the occurrences of ocean disasters (e. g. the red and green tide, the oil spill, the typhoon, and the sea ice) by converging and integrating the ocean color remote sensing using the satellite and the information technology exploiting the mass data processing and the pattern recognitions. This system which is based on the cosine similarity detects the ocean disasters in real time. The existing ocean color sensors which are operated in the polar orbit platforms cannot conduct the real time observation of ocean environments because they support the low temporal resolutions of one observation a day. However, geostationary ocean color imager(GOCI), the first geostationary ocean color sensor in the world, produces the ocean color images(e. g. the chlorophyll, the colored dissolved organic matter(CDOM), and the total suspended solid(TSS)), with high temporal resolutions of hourly intervals up to eight observations a day. The evaluation demonstrated that the OD2S can detect the excessive concentration of chlorophyll, CDOM, and TSS. Based on these results, it is expected that OD2S detects the ocean disasters in real time.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.218-225
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• 2020

The purpose of this paper is to establish an IoT-based big data platform that can check the space and form analysis in various play cultures of children. Therefore, to this end, in order to understand the healthy play culture of children, we are going to build a big data platform that allows IoT and smart devices to work together to collect data. Therefore, the goal of this study is to develop a big data platform linked to IoT first in order to collect data related to observation of children's mobile movements. Using the developed big data platform, children's play culture can be checked anywhere through observation and intuitive UI design, quick information can be automatically collected and real-time feedback, data collected through repeaters can be aggregated and analyzed, and systematic database can be utilized in the form of big data.