• Magazine of the Korean Society of Agricultural Engineers
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• v.26 no.2
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• pp.106-124
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• 1984

Monthly streanflow of watersheds is one of the most important elements for the planning, design, and management of water resources development projects, e.g., determination of storage requirement of reservoirs and control of release-water in lowflow rivers. Modeling of longterm runoff is theoretically based on water-balance analysis for a certain time interval. The effect of the casual factors of rainfall, evaporation, and soil-moisture storage on streamflow might be explained by multiple regression analysis. Using the basic concepts of water-balance and regression analysis, it was possible to develop a generalized model called the Regionalized Regression Model for Monthly Streamflow in Korean Watersheds. Based on model verification, it is felt that the model can be reliably applied to any proposed station in Korean watersheds to estimate monthly streamflow for the planning, design, and management of water resources development projects, especially those involving irrigation. Modeling processes and properties are summarized as follows; 1. From a simplified equation of water-balance on a watershed a regression model for monthly streamflow using the variables of rainfall, pan evaporation, and previous-month streamflow was formulated. 2. The hydrologic response of a watershed was represented lumpedly, qualitatively, and deductively using the regression coefficients of the water-balance regression model. 3. Regionalization was carried out to classify 33 watersheds on the basis of similarity through cluster analysis and resulted in 4 regional groups. 4. Prediction equations for the regional coefficients were derived from the stepwise regression analysis of watershed characteristics. It was also possible to explain geographic influences on streamflow through those prediction equations. 5. A model requiring the simple input of the data for rainfall, pan evaporation, and geographic factors was developed to estimate monthly streamflow at ungaged stations. The results of evaluating the performance of the model generally satisfactory.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.1
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• pp.169-178
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• 2019

Now a day, we can perform various predictions by applying machine learning, which is a field of artificial intelligence; however, the finding of best algorithm in the field is always the problem. This paper predicts monthly power trading amount, monthly power trading amount of money, monthly index of production extension, final consumption of energy, and diesel for automotive using machine learning supervised algorithms. Then, we find most fit algorithm among them for each case. To do this we show the probability of predicting the value for monthly power trading amount and monthly power trading amount of money, monthly index of production extension, final consumption of energy, and diesel for automotive. Then, we try to average each predicting values. Finally, we confirm which algorithm is the most superior algorithm among them.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.1
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• pp.21-30
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• 2017

Soil erosion has been issued in many countries since it causes negative impacts on ecosystem at the receiving water bodies. Therefore best management practices to resolve the problem in a watershed have been developed and implemented. As a prior process, there is a need to define soil erosion level and to identify the area of concern regarding soil erosion so that the practices are effective as they are designed. Universal Soil Loss Equation (USLE) were developed to estimate potential soil erosion and many Geographic Information System (GIS) models employ USLE to estimate soil erosion. Sediment Assessment Tool for Effective Erosion Control (SATEEC) is one of the models, the model provided several opportunities to consider various watershed peculiarities such as breaking of slope length, monthly variation of rainfall, crop growth at agricultural fields, etc. SATEEC is useful to estimate soil erosion, however the model can be implemented with ArcView software that is no longer used or hard to use currently. Therefore SATEEC based on ArcView was rebuild for the ArcGIS software with all modules provided at the previous version. The rebuilt SATEEC, ArcSATEEC, was programmed in ArcPy and works as ArcGIS Toolset and allows considering monthly variations of rainfall and crop growth at any watershed in South-Korea. ArcSATEEC was applied in Daecheong-dam watershed in this study, monthly soil erosion was estimated with monthly rainfall and crop growth variation. Annual soil erosion was computed by summing monthly soil erosion and was compared to the conventional approach to estimate annual soil erosion. The annual soil erosion estimated by the conventional approach and by summing monthly approach did not display much differences, however, ArcSATEEC was capable to provide monthly variation of soil erosion.

• The Korean Journal of Malacology
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• v.27 no.1
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• pp.43-53
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• 2011

The gametogenic cycle and the spawning season in female and male Cyclina sinensis were investigated by quantitative statistical analysis using an image analyzer system, and the biological minimum size (the size at 50% of sexual maturity) was calculated by combination of quantitative data by size and von Bertalanffy's equation. Compared the gametogenic cycle by quantitative statistical analysis with the previous qualitative results in female and male C. sinensis, monthly changes in female and male gametogenic cycles calculated by quantitative statistical analysis showed similar patterns to the gonadal stages in female and male reproductive cycles by qualitative histological analysis. Comparisons of monthly changes in the portions (%) of each area to eight kinds of areas by quantitative statistical analysis in the gonads in female and male C. sinensis are as follows. Monthly changes in the portions (%) of the ovary areas to total tissue areas in females and also monthly changes in the portions of the testis areas to total tissue areas in males increased in March and reached the maximum in May, and then showed a rapid decrease from June to October. Monthly changes in the portions (%) of oocyte areas to ovarian tissue areas in females and also monthly changes in the portions of the areas of the spermatogenic stages to testis areas in males began to increase in March and reached the maximum in June in females and males, and then rapidly dropped from July to October in females and males when spawnig occurred. From these data, it is apparent that the number of spawning seasons in female and male C. sinensis occurred once per year, from July to October. Monthly changes in the number of the oocytes per mm2 and in the mean diameter of the oocyte in captured image which were calculated for each female slide showed a maximum in May and reached the minimum from December to February. Therefore, C. sinensis in both sexes showed a unimodal gametogenic cycle during the year. The percentage of sexual maturity of female and male clams ranging from 25.1 to 30.0 mm in length was over 50% and 100% for clams over 40.1 mm length. In this study, the biological minimum size (sexually mature shell lengths at 50% of sexual maturity) in females and males were 26.85 and 26.28 mm, respectively.

• Transactions of the Korean hydrogen and new energy society
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• v.25 no.5
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• pp.541-549
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• 2014

The monthly-average meteorological data, in particular, the monthly average daily terrestrial horizontal insolation are required for designing solar thermal energy systems. In this paper, the dynamic thermal performance of a flat plate solar collector system is numerically investigated through a year from the monthly average insolation data in Seoul. For a specified data set of solar collector system, the dynamic behaviors of total solar radiation on the tilted collector surfaces, heat loss from the collector system, useful energy and collector efficiency are analyzed from January to December by a mathematical simulation model. In addition, the monthly average daily total solar radiation, useful energy, and daily collector efficiencies through a year are estimated. The simulated results show that the average total radiation is highest in March and the useful energy is highest in October, while the total radiation and the collector efficiency are lowest in July.

• The Korean Journal of Health Service Management
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• v.9 no.3
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• pp.95-106
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• 2015

Objectives : The purpose of this study was to identify levels of turnover intention of nurses in long-term care hospitals, and to explore influential factors on turnover intention. Methods : Data were collected with a structured questionnaires from 165 nurses. The data were analyzed with SPSS/WIN 21.0. Results : First, the average score for the practice environment cognition, job satisfaction, reward importance, and turnover intention were $3.14{\pm}0.21$, $3.18{\pm}0.32$, $4.02{\pm}0.53$, and $3.29{\pm}0.67$, respectively. Second, there were significant differences in the turnover intention according to the average monthly wage, total clinical career, present clinical career, work form, average monthly night shift and turnover experience. Third, the significant predictors of turnover intention were monthly salary, practice environment cognition, reward importance, monthly night shift and type of work explaining 67.0%. of the variance. Conclusions : It is necessary to conduct continuous and systematic research and to find ways that can prevent the resignation of nurses and improve cognition in the practice environment in long-term hospitals nurses.

• The Research Journal of the Costume Culture
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• v.6 no.4
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• pp.50-61
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• 1998

This study aims to make clear how consumer's characteristic and involvement in infant's clothing effect on the purchasing behavior. Using questionnaire as a researching tool, I collected the date from 366 housewives who live in Seoul and have kids aged from two to six year-old. The results of the study were as follows : First, they showed a significance on the correlation between sub-variants of involvement in their child's clothing like interest, importance and cognition of danger and those of purchasing behavior like directions to trademark, beauty and practicality, and so that, ti was realized that the involvement have a great effect on their purchasing behavior like. This was of the same opinion that when they think economic significance seriously, they also think practical function importantly. It seems that such a result derived from the fact that infant's clothing is most involved in practicality and economy rather than in trademark, beauty and popularity which are important on adult's clothing because infant's growth is so rapid that it requires to change sooner. Second, as for the correlation between the involvement in their child's clothing and the purchasing behavior according with the consumer's characteristics, they showed a significant correlation according with the consumer's characteristics like husband's profession, average monthly income and monthly expense to purchase infant's clothing. I found, therefore, economic factors like husband's profession, average monthly income and monthly expense to purchase infant's clothing were of most important. It suggests that the higher the consumer's income is, the grater it have an effect on the purchasing behavior.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.1612-1615
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• 2009

Water supply reliability indexes (WSRI) is estimated for assessment of water supply capacity in the downstream for parallel reservoir system in Nakdong River, South Korea, using allocation rule (AR) according to the water supply capacity of each reservoir and the characteristic of parallel reservoir system. The result of the analyzing parallel reservoir system for Andong and Imha reservoir in Nakdong River does not include evidences available enough to decide whether the results of water supply analysis are excellent in the current reliability evaluation or not. However, AR (C) shows a good result in the water supply capacity for each reservoir based on the connected operation system and the total water supply capacity at the control point of downstream by the average water supply capacity and possible range of water supply capacity suggested by this study. The average water supply capacity is analyzed by the reliability of monthly average water supply capacity. Furthermore, the possible range of water supply capacity is estimated by the standard deviation when water deficit occurs. Therefore, AR (C) is useful to establish and estimate the planning water supply capacity according to the monthly water supply condition and the possible range of water supply capacity when the water supply capacity deficit occurs, South Korea.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.1
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• pp.63-75
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• 2002

To improve the efficiency of the electric power generation, monthly maximum electric power consumptions for a next one year should be forecasted in advance and used as the fundamental input to the yearly electric power-generating master plan, which has a greatly influence upon relevant sub-plans successively. In this paper, we analyze the past 22-year hourly maximum electric load data available from KEPCO(Korea Electric Power Corporation) and select necessary data from the raw data for our model in order to reflect more recent trends and seasonal components, which hopefully result in a better forecasting model in terms of forecasted errors. After analyzing the selected data, we recommend to KEPCO the Winters' multiplicative model with decomposition and exponential smoothing technique among many candidate forecasting models and provide forecasts for the electric power consumptions and their 95% confidence intervals up to December of 1999. It turns out that the relative errors of our forecasts over the twelve actual load data are ranged between 0.1% and 6.6% and that the average relative error is only 3.3%. These results indicate that our model, which was accepted as the first statistical forecasting model for monthly maximum power consumption, is very suitable to KEPCO.

• Journal of the Korean Society of Hazard Mitigation
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• v.1 no.2 s.2
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• pp.115-121
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• 2001

The purpose of the synthetic generation of monthly river flows based on the short term observed data by means of stochastic models is to provide abundant input data to the water resources systems of which the system performance and operation policy are to be determined beforehand. In this study, a multivariate autoregressive model has been applied to generate monthly flows of the multi sites considering the correlations between each site. The model performance was examined using statistical comparisons between the historical and generated monthly series such as mean, variance, skewness and correlation coefficients. The results of this study showed that the modeled generated flows were statistically similar to the historical flows.