• 한국수자원학회논문집
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• 제41권7호
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• pp.681-692
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• 2008

본 연구에서는 자료동화 기법의 가장 간단한 방법이라 할 수 있는 연속수정법(successive correction method)을 이용한 레이더 강우자료와 지상 강우자료의 합성방법에 대한 적용성을 검토하였다. 우선 연속수정법의 적용 시 고려해야 할 사항인 반복계산 횟수 및 영향 반경의 규모를 민감도 분석을 통해 결정하였다. 또한 자료 합성에 대한 정량적인 평가를 위해 밀도 있는 지상 강우자료를 공간분포시켜 실제 강우장을 가정하였다. 최근 자료 합성에 많이 이용되고 있는 co-Kriging을 이용하여 두 자료를 합성하여 연속수정법에 의한 자료 합성 결과를 정량적으로 분석하였다. 그 결과 간단하고 경제적인 자료동화 기법인 연속수정법으로도 co-Kriging을 이용하는 경우의 통계적 특성 및 정확도를 확보할 수 있다는 것을 알 수 있었다.

• 대기
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• 제20권3호
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• pp.287-306
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• 2010

An ensemble Kalman filter (EnKF) with Weather Research and Forecasting (WRF) Model is applied for Typhoon Wukong (200610) to investigate the performance of ensemble forecasts depending on experimental configurations of the EnKF. In addition, the ensemble sensitivity analysis is applied to the forecast and analysis ensembles generated in EnKF, to investigate the possibility of using the ensemble sensitivity analysis as the adaptive observation guidance. Various experimental configurations are tested by changing model error, ensemble size, assimilation time window, covariance relaxation, and covariance localization in EnKF. First of all, experiments using different physical parameterization scheme for each ensemble member show less root mean square error compared to those using single physics for all the forecast ensemble members, which implies that considering the model error is beneficial to get better forecasts. A larger number of ensembles are also beneficial than a smaller number of ensembles. For the assimilation time window, the experiment using less frequent window shows better results than that using more frequent window, which is associated with the availability of observational data in this study. Therefore, incorporating model error, larger ensemble size, and less frequent assimilation window into the EnKF is beneficial to get better prediction of Typhoon Wukong (200610). The covariance relaxation and localization are relatively less beneficial to the forecasts compared to those factors mentioned above. The ensemble sensitivity analysis shows that the sensitive regions for adaptive observations can be determined by the sensitivity of the forecast measure of interest to the initial ensembles. In addition, the sensitivities calculated by the ensemble sensitivity analysis can be explained by dynamical relationships established among wind, temperature, and pressure.

• 한국수산과학회지
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• 제46권3호
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• pp.287-295
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• 2013

The growth, respiration, ingestion, and ecological efficiencies of Hexagrammos otakii larvae and juveniles reared on different diets and temperatures were estimated. A factorial experiment using two diets [non-enriched hatched Artemia nauplii (NEA) and enriched Artemia nauplii (EA)] crossed with two temperatures [natural seawater temperature (NT, $5.1-8.5^{\circ}C$) and heated seawater (HT, $13{\pm}0.5^{\circ}C$)] was conducted to investigate growth and energy budgets of Hexagrammos otakii larvae and juveniles. The energy used by larvae and juveniles for 6 weeks was calculated using data on ingestion, growth, respiration, excretion, and egestion. In the NT trials, the energy used for growth by larvae and juveniles was 0.121 and 0.129 Kcal in the NEA and EA treatments, respectively. Assimilation efficiency at NT were 78.0% and 80.2% in the NEA and EA trials, respectively. Gross growth efficiency ($K_1$) were 60.5% and 62.3% and net growth efficiency ($K_2$) was 77.56% and 77.71% in the NEA and EA trials, respectively. In the HT trials, the energy used for growth by juveniles was 0.189 and 0.212 Kcal in the NEA and EA trials, respectively. Assimilation efficiency at HT was 86.4% and 95.1% in the NEA and EA trials, respectively. Values of $K_1$ and $K_2$ at HT were 69.5% and 80.43%, respectively, in the NEA trials, and 73.9% and 77.66%, respectively, in the EA trials. These results suggest that enriched Artemia nauplii and higher temperatures ($13{\pm}0.5^{\circ}C$) are effective for rearing larvae and juveniles of H. otakii.

• International Journal of Computer Science & Network Security
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• 제23권3호
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• pp.177-186
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• 2023

Hyperspectral imaging technology is one of the most efficient and fast-growing technologies in recent years. Hyperspectral image (HSI) comprises contiguous spectral bands for every pixel that is used to detect the object with significant accuracy and details. HSI contains high dimensionality of spectral information which is not easy to classify every pixel. To confront the problem, we propose a novel RGB channel Assimilation for classification methods. The color features are extracted by using chromaticity computation. Additionally, this work discusses the classification of hyperspectral image based on Domain Transform Interpolated Convolution Filter (DTICF) and 3D-CNN with Bi-directional-Long Short Term Memory (Bi-LSTM). There are three steps for the proposed techniques: First, HSI data is converted to RGB images with spatial features. Before using the DTICF, the RGB images of HSI and patch of the input image from raw HSI are integrated. Afterward, the pair features of spectral and spatial are excerpted using DTICF from integrated HSI. Those obtained spatial and spectral features are finally given into the designed 3D-CNN with Bi-LSTM framework. In the second step, the excerpted color features are classified by 2D-CNN. The probabilistic classification map of 3D-CNN-Bi-LSTM, and 2D-CNN are fused. In the last step, additionally, Markov Random Field (MRF) is utilized for improving the fused probabilistic classification map efficiently. Based on the experimental results, two different hyperspectral images prove that novel RGB channel assimilation of DTICF-3D-CNN-Bi-LSTM approach is more important and provides good classification results compared to other classification approaches.

• 대기
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• 제26권3호
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• pp.387-400
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• 2016

In this study, the atmospheric $CO_2$ concentrations estimated by CT2013B, a recent version of CarbonTracker, are compared with $CO_2$ measurements from the Comprehensive Observation Network for Trace gases by Airliner (CONTRAIL) project during 2010-2011. CarbonTracker is an inversion system that estimates surface $CO_2$ fluxes using atmospheric $CO_2$ concentrations. Overall, the model results represented the atmospheric $CO_2$ concentrations well with a slight overestimation compared to observations. In the case of horizontal distribution, variations in the model and observation difference were large in northern Eurasia because most of the model and data mismatch were located in the stratosphere where the model could not represent $CO_2$ variations well enough due to low model resolution at high altitude and existing phase shift from the troposphere. In addition, the model and observation difference became larger in boreal summer. Despite relatively large differences at high latitudes and in boreal summer, overall, the modeled $CO_2$ concentrations fitted well to observations. Vertical profiles of modeled and observed $CO_2$ concentrations showed that the model overestimates the observations at all altitudes, showing nearly constant differences, which implies that the surface $CO_2$ concentration is transported well vertically in the transport model. At Narita, overall differences were small, although the correlation between modeled and observed $CO_2$ concentrations decreased at higher altitude, showing relatively large differences above 225 hPa. The vertical profiles at Moscow and Delhi located on land and at Hawaii on the ocean showed that the model is less accurate on land than on the ocean due to various effects (e.g., biospheric effect) on land compared to the homogeneous ocean surface.

• 한국물환경학회지
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• 제36권5호
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• pp.353-363
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• 2020

Hydrologic models can be classified into two types: those for understanding physical processes and those for predicting hydrologic quantities. This study deals with how to use the model to predict today's stream flow based on the system's knowledge of yesterday's state and the model parameters. In this regard, for the model to generate accurate predictions, the uncertainty of the parameters and appropriate estimates of the state variables are required. In this study, a relatively simple hydrologic partitioning model is proposed that can explicitly implement the hydrologic partitioning process, and the posterior distribution of the parameters of the proposed model is estimated using the Markov chain Monte Carlo approach. Further, the application method of the ensemble Kalman filter is proposed for updating the normalized soil moisture, which is the state variable of the model, by linking the information on the posterior distribution of the parameters and by assimilating the observed steam flow data. The stochastically and recursively estimated stream flows using the data assimilation technique revealed better representation of the observed data than the stream flows predicted using the deterministic model. Therefore, the ensemble Kalman filter in conjunction with the Markov chain Monte Carlo approach could be a reliable and effective method for forecasting daily stream flow, and it could also be a suitable method for routinely updating and monitoring the watershed-averaged soil moisture.

• 한국수자원학회논문집
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• 제52권1호
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• pp.61-70
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• 2019

실제증발산 자료를 융합하기 위한 Modified Kling-Gupta efficiency Fusion (KGF)방법을 제시하였고, 인공위성 및 재분석 증발산 자료인 Global Land Data Assimilation System (GLDAS), Global Land Evaporation Amsterdam Model (GLEAM), MODIS Global Evapotranspiration Project (MOD16)를 활용하여 Simple Taylor skill's Score (STS)와 비교하였다. 한반도와 중국의 세가지 land cover type(i.e., cropland, grassland, forest)을 가진 flux tower에서 비교 검증을 실시하였다. 실제증발산의 융합 방법인 STS와 KGF로 계산된 가중치의 결과를 확인하면, cropland와 grassland에서 재분석 자료(GLDAS, GLEAM)가 높은 가중치 영향을 나타내지만, forest에서 융합 방법에 따라 가중치 영향이 다르게 나타났다. 전반적으로 실제증발산 융합 방법 적용 결과의 비교에서는 cropland에서는 융합에 사용된 자료에 비하여 높은 개선이 이뤄지지 않았지만, grassland와 forest 에서는 개선이 이뤄졌다. 두 방법 중 KGF의 결과가 STS의 결과에 비하여 약간 개선되는 결과를 나타내었다.

• 한국초지조사료학회지
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• 제12권4호
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• pp.226-231
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• 1992

This experiment was carried out to estimate the dry matter accumulation using growth analysis in spring growth of perennial ryegrass varieties grown under space planting conditions, based on the data of previous paper9'. The results obtained were as follows: 1. Growth parameters of leaf area ratio(LAR), specific leaf area(SLA) and leaf weight ratio(LWR) were recognized siginificant differences between varieties. But, specific leaf area(SLA), leaf weight ratio (LWR) and relative tiller appearance rate(RTAR) were recognized significant differences between growth stages. Specific leaf area(SLA) was significant difference for the interaction of variety Xgrowth stage. 2. The relative growth rate of biological yields(BYRGR) indicated significantly positive correlations with relative growth rate of shoot(RGR) and root(RWGR), and net assimilation rate(NAR) as affected by the varieties and growth stages. 3. The relative growth rate of biological yields(BYRGR) indicated significantly positive correlation with nct assimilation rate(NAR) in all varieties. Leaf area ratio(LAR) had significantly positive correlation with specific leaf area(SLA) in all varieties, but shows a significant negative correlation with leaf weight ratio(LWR) of Maprima variety. 4. The relative growth rate of biological yields(BYRGR) indicated significantly positive correlations with the absolute growth rates of yield components.

• Fisheries and Aquatic Sciences
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• 제12권4호
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• pp.331-338
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• 2009

This study presents physiological rates of respiration and excretion, clearance rate, and assimilation efficiency of the ark shell Scapharca broughtonii, determined during 2007 from specimens collected in Gamak Bay on the south coast of Korea. Physiological parameters were measured monthly under static, laboratory controlled conditions with ambient conditions, and measurements were performed seasonally in order to estimate scope for growth and its probable sources of variation. Temperature directly influenced respiration and excretion. Clearance rates showed a tendency to be low during May-August, which is a period of gametogenesis. Assimilation efficiency was not significantly different seasonally and was independent of the concentration of chlorophyll a. The scope for growth was negative during high-temperature months (July-August), reflecting the high temperature and low clearance rate, and had its highest positive values during spring and autumn. The energy budget or growth potential of bivalves has been applied to other economically important species. Data on the physiological parameters and scope for growth of S. broughtonii obtained in this study will be used to assess the carrying capacity for ark shell cultivation.

• 한국농림기상학회지
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• 제17권2호
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• pp.165-172
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• 2015

지구 온난화와 연관된 기후 변화는 악기상 현상의 발생 빈도 및 강도를 증가시킨다. 따라서 산불, 산사태 등 산림 재해의 예방 및 대응을 위한 정밀한 산림 미기상 예측 시스템의 개발이 필요하다. 본 연구에서는 2013년 3월 봉화와 강릉에서 발생한 산불을 WRF와, 3D-var로 모의 하였다. WRF에서 나온 Output 자료를 이용하여 MUKLIMO 모형을 기반으로 산림 미기상 해석 및 모의를 위한 예측 시스템의 구축과 최적화를 이루었다. 이를 위해 3차원 변분 자료 동화 방법을 사용하여 기상청 AWS 관측 자료를 동화하였고, WRF의 예보에 MUKLIMO 모형을 결합하여 100m의 고해상도 바람장을 산출하였다. 자료동화를 수행하지 않은 CNTL 실험에 비해 자료 동화를 수행한 KMA 혹은 KMA_KFRI실험의 모의 결과가 관측과 가까워짐을 확인하였다. MUKLIMO에서 산출된 바람장 자료를 이용하여 보다 정확한 산림 미기상 예측 시스템을 구축할 수 있었다.