• Journal of Korea Water Resources Association
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• v.57 no.2
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• pp.73-85
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• 2024

Predicting water quality of rivers and reservoirs is necessary for the management of water resources. Artificial Neural Networks (ANNs) have been used in many studies to predict water quality with high accuracy. Previous studies have used Gradient Descent (GD)-based optimizers as an optimizer, an operator of ANN that searches parameters. However, GD-based optimizers have the disadvantages of the possibility of local optimal convergence and absence of a solution storage and comparison structure. This study developed improved optimizers to overcome the disadvantages of GD-based optimizers. Proposed optimizers are optimizers that combine adaptive moments (Adam) and Nesterov-accelerated adaptive moments (Nadam), which have low learning errors among GD-based optimizers, with Harmony Search (HS) or Novel Self-adaptive Harmony Search (NSHS). To evaluate the performance of Long Short-Term Memory (LSTM) using improved optimizers, the water quality data from the Dasan water quality monitoring station were used for training and prediction. Comparing the learning results, Mean Squared Error (MSE) of LSTM using Nadam combined with NSHS (NadamNSHS) was the lowest at 0.002921. In addition, the prediction rankings according to MSE and R² for the four water quality indices for each optimizer were compared. Comparing the average of ranking for each optimizer, it was confirmed that LSTM using NadamNSHS was the highest at 2.25.

• Korean Journal of Food Science and Technology
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• v.32 no.1
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• pp.90-96
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• 2000

The optimum cooking conditions for large scale continuous gas cooker were studied with three varieties of rice. Optimum soaking time for the cooker was estimated to be 30 min at cooking temperature above $20{\circ}C$, while 60 min at cooking temperature below $10{\circ}C$. The ratio of water-to-milled rice giving the best eating quality was founded to be $1.41{\sim}1.48$, and corresponding moisture content of cooked rice ranged from 60 to 62% for different rice varieties. The optimum ratio of water to milled rice. (Chucheong) decreased from 1.50 to 1.37 with increase in the amount of milled rice from 4.0 to 6.5 kg in a cooking vessel. However, actual water uptake by rice (g water absorbed per g rice) on cooking was nearly constant value of 1.13, which means that evaporated water during cooking increases with decreasing the amount of rice in a cooking vessel.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.308-323
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• 2021

In this study, we aimed to evaluate the environmental changes in Jinhae Bay caused by cooling water using numerical modeling. Cooling water discharge volume from the results of Case 1 (10 m³ sec^-1) showed that the environmental changes in Jinhae Bay were extremely insignificant throughout the study period. In the simulation conditions of Case 2 (100 m³ sec^-1), there was a decrease in water temperature of approximately 1 - 3℃ within a 5 km radius from the discharge outlet. In Case 3 (1000 m³ sec^-1), a decrease in water temperature of up to 4 - 5℃ was observed within a radius of 8 km from the discharge outlet and cooling water discharge spread throughout the Bay. Growth rate of microalgae decreased by up to 15 % in November, whereas it increased by up to 6 % near the Hangam Bay in Case 3. From the above results, we confirmed that the environmental changes in Jinhae Bay due to cooling water discharged from Tongyeong LNG station are extremely insignificant. Moreover, it is expected that cooling water discharge could be utilized as a counter measure for 'red tide bloom' or 'macroalgae growth'.

• Journal of the Korean earth science society
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• v.40 no.6
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• pp.613-623
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• 2019

Over the past decades, daily sea surface temperature (SST) composite data have been produced using periodically and extensively observed satellite SST data, and have been used for a variety of purposes, including climate change monitoring and oceanic and atmospheric forecasting. In this study, we evaluated the accuracy and analyzed the error characteristic of the SST composite data in the sea around the Korean Peninsula for optimal utilization in the regional seas. We evaluated the four types of multi-satellite SST composite data including OSTIA (Operational Sea Surface Temperature and Sea Ice Analysis), OISST (Optimum Interpolation Sea Surface Temperature), CMC (Canadian Meteorological Centre) SST, and MURSST (Multi-scale Ultra-high Resolution Sea Surface Temperature) collected from January 2016 to December 2016 by using in-situ temperature data measured from the Ieodo Ocean Research Station (IORS). Each SST composite data showed biases of the minimum of 0.12℃ (OISST) and the maximum of 0.55℃ (MURSST) and root mean square errors (RMSE) of the minimum of 0.77℃ (CMC SST) and the maximum of 0.96℃ (MURSST) for the in-situ temperature measurements from the IORS. Inter-comparison between the SST composite fields exhibited biases of -0.38-0.38℃ and RMSE of 0.55-0.82℃. The OSTIA and CMC SST data showed the smallest error while the OISST and MURSST data showed the most obvious error. The results of comparing time series by extracting the SST data at the closest point to the IORS showed that there was an apparent seasonal variation not only in the in-situ temperature from the IORS but also in all the SST composite data. In spring, however, SST composite data tended to be overestimated compared to the in-situ temperature observed from the IORS.

• Korean Journal of Ecology and Environment
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• v.46 no.4
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• pp.488-498
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• 2013

A three-dimensional hydrodynamic model was applied to the Lake Euiam. The lake has three inflows, of which Gongji Stream has the smallest flow rate and poorest water. The dam-storage volume, watershed area, lake shape and discharge type of the Chuncheon Dam and the Soyang Dam are different. Therefore, it is difficult to analyze the water plume and mixing pattern due to the difference of the two dams regarding the amount of outflow and water temperature. In this study, we analyzed the effects of different characteristics on temperature and conductivity using the model appropriate for the Lake Euiam. We selected an integrated system supporting 3-D time varying modeling (GEMSS) to represent large temporal and spatial variations in hydrodynamics and transport of the Lake Euiam. The model represents the water temperature and hydrodynamics in the lake reasonably well. We examined residence time and spreading patterns of the incoming flows in the lake based on the results of the validated model. The results of the water temperature and conductivity distribution indicated that characteristics of upstream dams greatly influence Lake Euiam. In this study, the three-dimensional time variable water quality model successfully simulated the temporal and spatial variations of the hydrodynamics in the Lake Euiam. The model may be used for efficient water quality management.

• Atmosphere
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• v.31 no.2
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• pp.229-240
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• 2021

The Global Ocean Data Assimilation and Prediction System (GODAPS) in operation at the KMA (Korea Meteorological Administration) is introduced. GODAPS consists of ocean model, ice model, and 3-d variational ocean data assimilation system. GODAPS assimilates conventional and satellite observations for sea surface temperature and height, observations of sea-ice concentration, as well as temperature and salinity profiles for the ocean using a 24-hour data assimilation window. It finally produces ocean analysis fields with a resolution of 0.25 ORCA (tripolar) grid and 75-layer in depth. This analysis is used for providing a boundary condition for the atmospheric model of the KMA Global Seasonal Forecasting System version 5 (GloSea5) in addition to monitoring on the global ocean and ice. For the purpose of evaluating the quality of ocean analysis produced by GODAPS, a one-year data assimilation experiment was performed. Assimilation of global observing system in GODAPS results in producing improved analysis and forecast fields with reduced error in terms of RMSE of innovation and analysis increment. In addition, comparison with an unassimilated experiment shows a mostly positive impact, especially over the region with large oceanic variability.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.489-492
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• 2006

Red tide occurred sporadically in early 90s. But It is happening extensively by global warming. So, Airline observation, Red tide buoy development, and Red tide alarm system research is progressing for monitor ring. However, study to early forecast red tide and red tide alarm system did not exist hard. This paper proposed development that design and implementation red tide database of using wireless sensor network. There are GPS, Water Temperature sensor, Oxygen sensor, and Turbidity sensor in each node. And data is stored to red tide database through Ad-hoc network. This data is integrated and analyzed. So, forecast red tide. And red tide database has red tide data that happen at past. This is utilized to comparative analysis data for red tide estimate. Main screen displays position of node and measured value in electron map. Much studies must be backed for this a study. But I think that contribute to analyze red tide data by red tide database construction.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1373-1377
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• 2008

강우-유출에 의해 성층화된 저수지로 유입하는 하천수는 저수지 표층에 비해 낮은 수온과 높은 부유물질(SS) 농도를 가지므로 저수지 표층수보다 상대적으로 높은 밀도를 유지한다. 하천으로부터 유입한 밀도류는 유속에 의한 관성력이 두 수체의 밀도차에 의한 음의 부력보다 큰 구간까지는 저수지 표층을 따라 진행하지만, 두 힘이 같아지는 지점에서 밀도류는 더 이상 진행하지 못하고 저수지 수면 아래로 침강하며 이 과정에서 수체간의 많은 혼합이 일어난다. 따라서 홍수시 유입한 탁수의 침강점에 대한 정확한 예측은 수질관리를 위한 현장조사, 그리고 탁수거동 해석 및 최적관리대책 마련에 중요한 요소이다. 본 연구의 목적은 홍수시 대청호로 유입하는 하천 밀도류의 침강위치를 홍수규모별로 경험식과 수치모델을 통해 산정함으로써 두 방법 간의 장 단점을 비교하고, 탁수 현장조사와 최적관리를 위한 기초정보를 제공하는데 있다. 유입수의 모의조건은 그 동안 대청호에서 발생한 홍수 크기를 기준으로 9개의 등급으로 나누었으며, 저수지 성층조건은 여름철 탁수가 유입되기 전의 발달된 성층구조를 적용하였다. 유입수와 저수지 성층구조의 특성치는 밀도 Froude 수($Fr_i$)로 나타냈으며, $Fr_i$ 조건별로 침강점 위치를 저수지 단면을 삼각형태로 가정한 Hebbert et al.(1979) 경험식과 2차원 수치모델로 산정하여 그 결과를 비교하였다. 대청호로 유입한 탁수는 홍수규모에 따라 대정리 수역에서 회남수역 사이 구간에서 침강하였으며, $Fr_i$ 값이 클수록 침강점 수심이 깊어지는 경향을 보였다. 경험식으로 산정한 침강점 수심은 정상상태 조건을 가정하므로 홍수에 의한 수위변화를 고려하지 못하며, 실제의 불규칙한 하상표고를 일정한 하상경사로 가정하기 때문에 2차원 모델의 결과보다 과대산정하는 경향을 보였다. 따라서 홍수가 연속해서 발생하며 수위변화가 심한 국내 저수지 여건에서 하천 유입 밀도류의 거동을 보다 정확히 예측하기 위해서는 2차원 또는 3차원 수치모델을 적용하는 것이 타당할 것으로 판단된다.

• Journal of Korea Water Resources Association
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• v.33 no.1
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• pp.3-14
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• 2000

The primary objective of this study is to estimate the suitable flow in need for conservation and restoration of the fish habitat in running water ecosystem, which has very important status in the instream flow for stream environment. Year, monthly low flows are estimated to properly maintain the fish habitat. Water depth and velocity are simulated, and also water temperature and Dissolved Oxygen(DO) are predicted at gradually varied flow using estimated low flows. These simulated conditions for each low flow are graphically compared with the requirements to maintain fish habitat at each life stage. These processes were applied to 3 riffle transects located at Dalcheon(Dal stream) in the South Han river. Pirami (Zacco platypus) was selected as a representative fish species in Dalcheon. It was shown that the suitable flow for maintaining the representative fish habitat at each life stage depends on hydraulic conditions rather than water quality conditions, and the flow ranges from the 10-year minimum low flow to consecutive 7-day 2.33-year low flow.w flow.

• Ocean and Polar Research
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• v.43 no.2
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• pp.53-63
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• 2021

Changes in a marine environment have a broad socioeconomic implication on fisheries and their relevant industries so that there has been a growing demand for the medium-range (months to years) prediction of the marine environment Using a medium-range ocean prediction model (Ocean Mid-range prediction System, OMIDAS) for the northwest Pacific, this study attempted to assess seasonal difference in the mid-range predictability of the sea surface temperature (SST), focusing on the Korea seas characterized as a complex marine system. A three-month re-forecast experiment was conducted for each of the four seasons in 2016 starting from January, forced with Climate Forecast System version 2 (CFSv2) forecast data. The assessment using relative root-mean-square-error was taken for the last month SST of each experiment. Compared to the CFSv2, the OMIDAS revealed a better prediction skill for the Korea seas SST, particularly in the Yellow sea mainly due to a more realistic representation of the topography and current systems. Seasonally, the OMIDAS showed better predictability in the warm seasons (spring and summer) than in the cold seasons (fall and winter), suggesting seasonal dependency in predictability of the Korea seas. In addition, the mid-range predictability for the Korea seas significantly varies depending on regions: the predictability was higher in the East Sea than in the Yellow Sea. The improvement in the seasonal predictability for the Korea seas by OMIDAS highlights the importance of a regional ocean modeling system for a medium-range marine prediction.