• Feed Journal
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• v.2 no.4
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• pp.72-74
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• 2004

농림부는 지난달 축산법 제 20조의 5 및 동법 시행규칙 제25조의 2제3호의 규정에 의하여 가축사육시설 단위면적당 적정 가축사육기준과 축산법 제2조1호 및 동법 시행 규칙 제2조제4호의 규정에 의하여 사육하는 동물중 가축의 범위에 해당하는 기타 동물을 고시했다. 다음은 고시된 내용을 정리한 것이다.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.19 no.1
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• pp.68-76
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• 2007

As an alternative approach to evaluate the unit heating load for apartment houses, we newly developed and proposed unit building method. The new method, which calculates the heating load of an apartment building as a whole, conceptually corresponds to integral analysis of building heat loss, while the existing unit apartment method to differential analysis. Four typical building models of Korean-style apartment house and two dynamic load calculation programs were selected to validate the present method under realistically imposed conditions. Eight sets of unit heating load calculated respectively by unit building and unit apartment methods showed excellent agreements regardless of building model and simulation program. It is expected that the unit building method can take the place of the unit apartment method due to fewer modeling assumptions as well as less computational efforts. Additional calculations to investigate the effects of various parameters on unit heating load yield good consistencies with known facts, and re-confirm the validity.

• Proceedings of the SAREK Conference
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• 2004.11a
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• pp.53-53
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• 2004

• Journal of the Korean Geographical Society
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• v.49 no.3
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• pp.371-389
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• 2014

This study aims to analyze the redistricting problems in non-autonomous Gu. Although non-autonomous Gu is a just local administrative district, it has been regarded as an important and basic spatial unit in electoral redistricting. By the reform of Public Official Election Act in 2012, however, non-autonomous Gu is distinguished from local governments like Si, Gun and autonomous Gu, in boundary delimitation for the 19th National Assembly election, and some are divided into a part of another constituency. About these background, this study points out the following problems. First, in national scale, the reform of Act made the malapportionment in constituencies of non-autonomous Gus, comparing with those of local governments. Second, there was the discriminative application of Act in each non-autonomous Gu and it will make the malapportionment worse in next election, considering the reorganization of local administrative system. Finally, this study propose that it is necessary to select one from a variety of redistricting principles, especially between the prevention of gerrymandering, the representativeness of local government and the apportionment, prior to another amendment of redistricting system and the debate about political reform.

• Journal of Korea Water Resources Association
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• v.53 no.11
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• pp.929-938
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• 2020

In this study, we estimated missing evapotranspiration (ET) data at a eddy-covariance flux tower in the Cheongmicheon farmland site using the Artificial Neural Network (ANN). The ANN showed excellent performance in numerical analysis and is expanding in various fields. To evaluate the performance the ANN-based gap-filling, ET was calculated using the existing gap-filling methods of Mean Diagnostic Variation (MDV) and Food and Aggregation Organization Penman-Monteith (FAO-PM). Then ET was evaluated by time series method and statistical analysis (coefficient of determination, index of agreement (IOA), root mean squared error (RMSE) and mean absolute error (MAE). For the validation of each gap-filling model, we used 30 minutes of data in 2015. Of the 121 missing values, the ANN method showed the best performance by supplementing 70, 53 and 84 missing values, respectively, in the order of MDV, FAO-PM, and ANN methods. Analysis of the coefficient of determination (MDV, FAO-PM, and ANN methods followed by 0.673, 0.784, and 0.841, respectively.) and the IOA (The MDV, FAO-PM, and ANN methods followed by 0.899, 0.890, and 0.951 respectively.) indicated that, all three methods were highly correlated and considered to be fully utilized, and among them, ANN models showed the highest performance and suitability. Based on this study, it could be used more appropriately in the study of gap-filling method of flux tower data using machine learning method.