• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.18 no.3
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• pp.111-121
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• 2013

Accurate prediction of sea water temperature has been emphasized to make precise local weather forecast and to understand change of ecosystem. The Yellow Sea, which has turbid water and strong tidal current, is an unique shallow marginal sea. It is essential to include the effects of the turbidity and the strong tidal mixing for the realistic simulation of temperature distribution in the Yellow Sea. Evaluation of ocean circulation model response to vertical mixing scheme and turbidity is primary objective of this study. Three-dimensional ocean circulation model(Regional Ocean Modeling System) was used to perform numerical simulations. Mellor- Yamada level 2.5 closure (M-Y) and K-Profile Parameterization (KPP) scheme were selected for vertical mixing parameterization in this study. Effect of Jerlov water type 1, 3 and 5 was also evaluated. The simulated temperature distribution was compared with the observed data by National Fisheries Research and Development Institute to estimate model's response to turbidity and vertical mixing schemes in the Yellow Sea. Simulations with M-Y vertical mixing scheme produced relatively stronger vertical mixing and warmer bottom temperature than the observation. KPP scheme produced weaker vertical mixing and did not well reproduce tidal mixing front along the coast. However, KPP scheme keeps bottom temperature closer to the observation. Consequently, numerical ocean circulation simulations with M-Y vertical mixing scheme tends to produce well mixed vertical temperature structure and that with KPP vertical mixing scheme tends to make stratified vertical temperature structure. When Jerlov water type is higher, sea surface temperature is high and sea bottom temperature is low because downward shortwave radiation is almost absorbed near the sea surface.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.8 no.3
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• pp.165-177
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• 2013

The purpose of this study was to examine the efficiency of senior welfare centers and the cause of differences among senior welfare centers in that regard, and to investigate influential factors for the differences in efficiency and the size of the influence of the factors. What methods would be effective at assessing the efficiency of senior welfare centers by taking into account their circumstances was reviewed, andpost-hoc analyses were made by using data envelopment analysis(DEA) and DAE/AP Modified prosthetic which were useful tools to evaluate relative efficiency. After 20 senior welfare centers located in Gyeonggi-do were selected, their yearly operating data of 2009 were utilized. The purpose of this study was to examine the efficiency of senior welfare centers. The evaluation data released by the Gyeonggi Welfare Foundation were analyzed by DEA, which is one of nonparametric statistics, and it was possible to obtain significant results on the regional operating efficiency of social welfare centers in 14 metropolitan cities and provinces, the causes and degree of their inefficiency and what areas one could refer to. As the data for the counties were utilized in this study, it's not quite possible to produce accurate results on the relative efficiency of senior welfare centers, but this study could be said to be of significance in that it suggested how to evaluate the overall operating efficiency of senior welfare centers in the counties involving the degree of their operating inefficiency, what improvements should be made and what reference groups there might be and provided information on the usefulness of the DEA model.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.3
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• pp.164-178
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• 2022

Uncertainties in weather forecasts would affect the reliability of yield prediction using crop models. The objective of this study was to compare uncertainty in crop yield prediction caused by the use of the weather forecast data. Daily weather data were produced at 10 km spatial resolution using W eather Research and Forecasting (W RF) model. The nearest neighbor method was used to downscale these data at the resolution of 5 km (W RF5K). Parameter-elevation Regressions on Independent Slopes Model (PRISM) was also applied to the WRF data to produce the weather data at the same resolution. W RF5K and PRISM data were used as inputs to the CROPGRO-SOYBEAN model to predict crop yield. The uncertainties of the gridded data were analyzed using cumulative growing degree days (CGDD) and cumulative solar radiation (CSRAD) during the soybean growing seasons for the crop of interest. The degree of agreement (DOA) statistics including structural similarity index were determined for the crop model outputs. Our results indicated that the DOA statistics for CGDD were correlated with that for the maturity dates predicted using WRF5K and PRISM data. Yield forecasts had small values of the DOA statistics when large spatial disagreement occured between maturity dates predicted using WRF5K and PRISM. These results suggest that the spatial uncertainties in temperature data would affect the reliability of the phenology and, as a result, yield predictions at a greater degree than those in solar radiation data. This merits further studies to assess the uncertainties of crop yield forecasts using a wide range of crop calendars.