• Geophysics and Geophysical Exploration
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• v.21 no.2
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• pp.67-81
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• 2018

We acquired the magnetic and bathymetry data around the TA (Tofua Arc) 22 seamount in the Lau Basin for finding submarine hydrothermal deposits. From the data, we estimated the magnetic characteristics in the study area. The bathymetry shows that TA 22 seamount consists of the western and eastern summits. Each summit exhibits a caldera. The western caldera is smaller, but deeper than the eastern caldera. The slope gradients of the TA 22 are steeper around ~1000 m depth range and relatively gentle at the summit areas with the small difference of two calderas. The magnetic properties of TA 22 seamount present high anomalies at the summit and the vicinity of the caldera. Low magnetization zones appear over the outer flanks and center of the calderas. These magnetic patterns are similar to the previous studies which had represented high anomalies and low magnetization zones inside of the summit area or on the flank of the outside of the summit area. The results of the 2D magnetic forward modeling with seismic profiles show about 20 nT of RMSEs (root mean square error) between the modeled and observed values. The low RMSEs proposes a good correlation between the modeled 2D structure and the geophysical observation in this study area. Based on the modeling and magnetization distribution, hydrothermal deposits are predicted to be located at the inner area of the calderas or at small mounds around caldera rims.

• Journal of Korea Water Resources Association
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• v.38 no.7 s.156
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• pp.565-574
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• 2005

It is used water quality data that was measured at Pyeongchanggang real time monitoring stations in Namhan river. These characteristics were analyzed with the water qualify of rainy and nonrainy periods. TOC (Total Organic Carbon) data of rainy periods has correlation with discharge and shows high values of mean, maximum, and standard deviation. DO (Dissolved Oxygen) value of rainy periods is lower than those of nonrainy periods. Input data of the water quality forecasting models that they were constructed by neural network and neuro-fuzzy was chosen as the reasonable data, and water qualify forecasting models were applied. LMNN, MDNN, and ANFIS models have achieved the highest overall accuracy of TOC data. LMNN (Levenberg-Marquardt Neural Network) and MDNN (MoDular Neural Network) model which are applied for DO forecasting shows better results than ANFIS (Adaptive Neuro-Fuzzy Inference System). MDNN model shows the lowest estimation error when using daily time, which is qualitative data trained with quantitative data. The observation of discharge and water quality are effective at same point as well as same time for real time management. But there are some of real time water quality monitoring stations far from the T/M water stage. Pyeongchanggang station is one of them. So discharge on Pyeongchanggang station was calculated by developed runoff neural network model, and the water quality forecasting model is linked to the runoff forecasting model. That linked model shows the improvement of waterquality forecasting.

• Journal of Wetlands Research
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• v.16 no.3
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• pp.441-450
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• 2014

In this study, we consider ability of self-purification for a rational water quality management. And we assess the risk of Alkyl Benzene Sulfonic acid sodium salt(ABS) of harmful ingredients in Anseong Cheon watershed using QUAL2E model. The observations and simulated results were fitted well for BOD and ABS, but even though the trend of DO concentration change was well represented, the error between observation and simulation values was existed. We assessed the Risk assessment by calculating Risk quotient(RQ) by Predicted Exposure Concentration(PEC) and Predicted No-Effect Concentration(PNEC). Results of the impact of ABS on the self-purification of the river were Anseongcheon[0.0003(Bressan), 0.06(Criteria of Ministry of environment)], Jinwicheon[0.0002(Bressan), 0.04(Criteria of Ministry of environment). And result of the impact of ABS on the Aquatic ecosystem of the river were Anseongcheon[0.0667(Bressan), 0.005(Criteria of Ministry of environment)], Jinwicheon[0.1(Bressan), 0.0075(Criteria of Ministry of environment). All of these results were smaller than the 1.0 which is the reference value suggested by Norification No.30 of the National Institute of Environment Research. So, ABS did not affect a self-purification and aquatic ecosystem of the river. The method suggested in the study is a simple one and can provide more information for harmful ingredients than criteria of Ministry of environment.

• Journal of Korea Water Resources Association
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• v.48 no.4
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• pp.245-255
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• 2015

This study used high density network of integrated meteorological sensor, which are operated by SK Planet, with KMA weather stations to estimate the quantitative precipitation field in Seoul area. We introduced SK Planet network and analyzed quality of the observed data for 3 months data from 1 July to 30 September 2013. As the quality analysis result, we checked most SK Planet stations observed similar with previous KMA stations. We developed the real-time quality check and adjustment method to reduce the error effect for hydrological application by missing and outlier value and we confirmed the developed method can be corrected the missing and outlier value. Through this method, we used the 190 stations(KMA 34 stations, SK Planet 156 stations) that missing ratio is less than 20% and the effect of the outlier was the smallest for quantitative precipitation estimation. Moreover, we evaluated reproducibility of rainfall field high density rain gauge network has $3km^2$/gauge. As the result, the spatial relative frequency of rainfall field using SK Planet and KMA stations is similar with radar rainfall field. And, it supplement the blank of KMA observation network. Especially, through this research we will take advantage of the density of the network to estimate rainfall field which can be considered as a very good approximation of the true value.

• Atmosphere
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• v.26 no.1
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• pp.111-126
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• 2016

In the numerical weather model, surface properties can be defined by various parameters such as terrain height, landuse, surface albedo, soil moisture, surface emissivity, roughness length and so on. And these parameters need to be improved in the Seoul metropolitan area that established high-rise and complex buildings by urbanization at a recent time. The surface roughness length map is developed from digital elevation model (DEM) and it is implemented to the high-resolution numerical weather (WISE-WRF) model. Simulated results from WISE-WRF model are analyzed the relationship between meteorological variables to changes in the surface roughness length. Friction speed and wind speed are improved with various surface roughness in urban, these variables affected to temperature and relative humidity and hence the surface roughness length will affect to the precipitation and Planetary Boundary Layer (PBL) height. When surface variables by the WISE-WRF model are validated with Automatic Weather System (AWS) observations, NEW experiment is able to simulate more accurate than ORG experiment in temperature and wind speed. Especially, wind speed is overestimated over $2.5m\;s^{-1}$ on some AWS stations in Seoul and surrounding area but it improved with positive correlation and Root Mean Square Error (RMSE) below $2.5m\;s^{-1}$ in whole area. There are close relationship between surface roughness length and wind speed, and the change of surface variables lead to the change of location and duration of precipitation. As a result, the accuracy of WISE-WRF model is improved with the new surface roughness length retrieved from DEM, and its surface roughness length is important role in the high-resolution WISE-WRF model. By the way, the result in this study need various validation from retrieved the surface roughness length to numerical weather model simulations with observation data.

• Atmosphere
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• v.29 no.5
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• pp.671-687
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• 2019

This study evaluates the long-term seasonal predictability of summer (June, July and August) heatwaves over South Korea using 30-year (1989~2018) Hindcast data of the Pusan National University Coupled General Circulation Model (PNU CGCM)-Weather Research and Forecasting (WRF) chain. Heatwave indices such as Number of Heatwave days (HWD), Heatwave Intensity (HWI) and Heatwave Warning (HWW) are used to explore the long-term seasonal predictability of heatwaves. The prediction skills for HWD, HWI, and HWW are evaluated in terms of the Temporal Correlation Coefficient (TCC), Root Mean Square Error (RMSE) and Skill Scores such as Heidke Skill Score (HSS) and Hit Rate (HR). The spatial distributions of daily maximum temperature simulated by WRF are similar overall to those simulated by NCEP-R2 and PNU CGCM. The WRF tends to underestimate the daily maximum temperature than observation because the lateral boundary condition of WRF is PNU CGCM. According to TCC, RMSE and Skill Score, the predictability of daily maximum temperature is higher in the predictions that start from the February and April initial condition. However, the PNU CGCM-WRF chain tends to overestimate HWD, HWI and HWW compared to observations. The TCCs for heatwave indices range from 0.02 to 0.31. The RMSE, HR and HSS values are in the range of 7.73 to 8.73, 0.01 to 0.09 and 0.34 to 0.39, respectively. In general, the prediction skill of the PNU CGCM-WRF chain for heatwave indices is highest in the predictions that start from the February and April initial condition and is lower in the predictions that start from January and March. According to TCC, RMSE and Skill Score, the predictability is more influenced by lead time than by the effects of topography and/or terrain feature because both HSS and HR varies in different leads over the whole region of South Korea.

• Journal of the Korean earth science society
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• v.38 no.2
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• pp.129-140
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• 2017

Global solar radiation was calculated in this research using ground-base measurement data, meteorological satellite data, and GWNU (Gangneung-Wonju National University) solar radiation model. We also analyzed the accuracy of the GWNU model by comparing the observed solar radiation according to the total cloud cover. Our research was based on the global solar radiation of the GWNU radiation site in 2012, observation data such as temperature and pressure, humidity, aerosol, total ozone amount data from the Ozone Monitoring Instrument (OMI) sensor, and Skyview data used for evaluation of cloud mask and total cloud cover. On a clear day when the total cloud cover was 0 tenth, the calculated global solar radiations using the GWNU model had a high correlation coefficient of 0.98 compared with the observed solar radiation, but root mean square error (RMSE) was relatively high, i.e., $36.62Wm^{-2}$. The Skyview equipment was unable to determine the meteorological condition such as thin clouds, mist, and haze. On a cloudy day, regression equations were used for the radiation model to correct the effect of clouds. The correlation coefficient was 0.92, but the RMSE was high, i.e., $99.50Wm^{-2}$. For more accurate analysis, additional analysis of various elements including shielding of the direct radiation component and cloud optical thickness is required. The results of this study can be useful in the area where the global solar radiation is not observed by calculating the global solar radiation per minute or time.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.5
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• pp.624-630
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• 2012

The peer review learning is a method which improves learning outcome of students through feedback between students and the observation and analysis of other students. One of the important problems in a peer review system is to find proper evaluators to each learner considering characteristics of students for improving learning outcomes. Some of peer review systems randomly assign peer review evaluators to learners, or chose evaluators based on limited strategies. However, these systems have a problem that they do not consider various characteristics of learners and evaluators who participate in peer reviews. In this paper, we propose a novel prediction approach of learning outcomes to apply peer review systems considering various characteristics of learners and evaluators. The proposed approach extracts representative attributes from the profiles of students and predicts learning outcomes using various regression models. In order to verify how much outliers affect on the prediction of learning outcomes, we also apply several outlier removal methods to the regression models and compare the predictive performance of learning outcomes. The experiment result says that the SVR model which does not removes outliers shows an error rate of 0.47% on average and has the best predictive performance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.130-133
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• 2002

As a society advances, an aging phenomenon and many diseases which did not exist in old times are happening. Especially, in case of the aged patient, because we cant know the time the condition of the patients health become worse, the study of the Tele-information system has been actively carried out by the necessity of a persistent observation. A ECG signal a kind of a vital signals has been widely used to the medical information system as an usual clinical diagnosis for the patients who possess heart diseases. BlueTooth is a close range wireless communication technology which uses a wireless frequency 2.4GHz and has a high trust and self - error correction technology according to a low power consumption quality and a high-speed frequency hopping. This makes get a high trust concerning a data transmission than an existing modem. In addition, though wireless modem is restricted by a minimal of a wireless terminal, It will be possible to coincide with the function of the portable with the low power consumption quality by using Bluetooth. And as the system on a chip of module progresses, the possibility of the small size is present According to this, Bluetooth module transmits the medical information, which is input from the outside among the operations that use the Bluetooth to the Bluetooth module that is connected the host PC. And the system that the host PC transmits the medical information from the connected Bluetooth module to the Internet has once embedded. this study let the host PC embedded in advance of the existing system and transmit the medical information by the addition of the Tcp/Ip protocol stark under all embedded environments to internet.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2011.06a
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• pp.27-28
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• 2011

A solar flares have the 11-year cycle and release a large energy which may produce coronal mass ejections (CME). The NOAA (National Oceanic and Atmospheric Administration) predicted that the sun spot activity will be maximized in 2013-2014. A strong solar flare can cause the disturbance of global positioning system including various communication of TV, radio broadcasting. The actual solar storm in 1989 caused power outages in Canada during 9 hours and about 600 million people had experienced a blackout. Such a solar storm can shorten the GPS satellite's life span about 5 to 10 years which can be resulted in economic loss considering the amount of multi-billion won. This paper analyzed the recent solar storm of X-class occurred on 15th of February about 10:45 this year that was reached Korea (Bohyun observatory) on 18th of February about 10:30 (local time), and compared with the data of before and after a week. The proton data of 18th of February considered that the solar strom reached on earth showed a fluctuation compared to the data of before and after a week. The positioning results at Daejeon also showed higher positioning error compared to the data of before and after a week results.