• Ecology and Resilient Infrastructure
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• v.3 no.3
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• pp.189-200
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• 2016

The species distribution model would be a useful tool for understanding how invasive alien species spread over the country and what environmental variables contribute to their distributions. This study is focused on the potential distribution of two invasive alien species, the common ragweed (Ambrosia artemisiifolia) and knotgrass (Paspalum distichum) in the Korean Peninsula. The maximum entropy (Maxent) model was used for the prediction of their distribution by inferring their climatic environmental requirements from localities where they are currently known to occur. We obtained their presence data from the Global Biodiversity Information Facility and the Korean plant species databases and bioclimatic data from the WorldClim dataset. As a results of the modelling, the potential distribution predicted by global occurrence data was more accurate than that by native occurrence data. The variables determining the common ragweed distribution were precipitation of the driest month and annual mean temperature. Both annual and the coldest quarter mean temperatures were critical factors in determining the knotgrass distribution. The Maxent model could be a useful tool for the prediction of alien species invasion and the management of their expansion.

• Atmosphere
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• v.19 no.2
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• pp.127-143
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• 2009

This study investigates characteristics of wintertime simulation conducted by METRI AGCM utilizing new radiation parameterization scheme. New radiation scheme is based on the method of Chou et al., and is utilized in the METRI AGCM recently. In order to analyze characteristics of seasonal simulation in boreal winter, hindcast dataset from 1979 to 2005 is produced in two experiments - control run (CTRL) and new model's run (RADI). Also, changes in performance skill and predictability due to implementation of new radiation scheme are examined. In the wintertime simulation, the RADI experiment tends to reduce warm bias in the upper troposphere probably due to intensification of longwave radiative cooling over the whole troposphere. The radiative cooling effect is related to weakening of longitudinal temperature gradient, leading to weaker tropospheric jet in the upper troposphere. In addition, changes in vertical thermodynamic structure have an influence on reduction of tropical precipitation. Moreover, the RADI case is less sensitive to variation of tropical sea surface temperature than the CTRL case, even though the RADI case simulates the mean climate pattern well. It implies that the RADI run does not have significant improvement in seasonal prediction point of view.

• 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.

• Journal of Korea Water Resources Association
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• v.55 no.10
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• pp.723-736
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• 2022

In this study, monthly precipitation forecasting models that can predict up to 12 months in advance were constructed for the Geum River basin, and two statistical techniques, multiple linear regression (MLR) and artificial neural network (ANN), were applied to the model construction. As predictor candidates, a total of 47 climate indices were used, including 39 global climate patterns provided by the National Oceanic and Atmospheric Administration (NOAA) and 8 meteorological factors for the basin. Forecast models were constructed by using climate indices with high correlation by analyzing the teleconnection between the monthly precipitation and each climate index for the past 40 years based on the forecast month. In the goodness-of-fit test results for the average value of forecasts of each month for 1991 to 2021, the MLR models showed -3.3 to -0.1% for the percent bias (PBIAS), 0.45 to 0.50 for the Nash-Sutcliffe efficiency (NSE), and 0.69 to 0.70 for the Pearson correlation coefficient (r), whereas, the ANN models showed PBIAS -5.0~+0.5%, NSE 0.35~0.47, and r 0.64~0.70. The mean values predicted by the MLR models were found to be closer to the observation than the ANN models. The probability of including observations within the forecast range for each month was 57.5 to 83.6% (average 72.9%) for the MLR models, and 71.5 to 88.7% (average 81.1%) for the ANN models, indicating that the ANN models showed better results. The tercile probability by month was 25.9 to 41.9% (average 34.6%) for the MLR models, and 30.3 to 39.1% (average 34.7%) for the ANN models. Both models showed long-term predictability of monthly precipitation with an average of 33.3% or more in tercile probability. In conclusion, the difference in predictability between the two models was found to be relatively small. However, when judging from the hit rate for the prediction range or the tercile probability, the monthly deviation for predictability was found to be relatively small for the ANN models.

• Korean Journal of Environment and Ecology
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• v.25 no.6
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• pp.903-910
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• 2011

The research was carried out in order to find climate factors which determine the distribution of Machilus thunbergii, and the potential habitats under the current climate and three climate change scenario by using classification tree (CT) model. Four climate factors; the minimum temperature of the coldest month (TMC), the warmth index (WI), summer precipitation (PRS), and winter precipition (PRW) : were used as independent variables for the model. The model of distribution for Machilus thunbergii (Mth-model) constructed by CT analysis showed that minimum temperature of the coldest month (TMC) is a major climate factor in determining the distribution of M. thunbergii. The area above the $-3.3^{\circ}C$ of TMC revealed high occurrence probability of the M. thunbergii. Potential habitats was predicted $9,326km^2$ under the current climate and $61,074{\sim}67,402km^2$(South Korea: $58,419{\sim}61,137km^2$, North Korea: $2,655{\sim}6,542km^2$) under the three climate change scenarios (CCCMA-A2, CSIRO-A2, HADCM3-A2). The Potential habitats was to predicted increase by 51~56%(South Korea: 49~51%, North Korea: 2~5%) under the three climate change scenarios. The potential expand of M. thunbergii habitats has been expected that it is competitive with warm-temperate deciduous broadleaf forest. M. thunbergii is evaluated as the indicator of climate change in Korea and it is necessary for M. thunbergii to monitor of potential habitats.

• Journal of Korean Academy of Nursing Administration
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• v.20 no.5
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• pp.558-566
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• 2014

Purpose: This study was done to measure the level of social support, self-esteem, and empowerment and to identify any effect of social support and self-esteem on the empowerment of nurses. Methods: The study design was a descriptive survey using questionnaires which were given to 381 nurses in C province. The collected data were analyzed using descriptive analysis, t-test, ANOVA, Pearson correlation coefficient, and multiple regressions. Results: The mean score for nurses' empowerment was $2.83{\pm}0.66$. Seven individual characteristics, social support(family, meaningful persons, supervisors, and co-workers) and self-esteem accounted for 23.3% of the variance in nurses' empowerment. Prediction elements influencing empowerment of nurses were salary per month, self-esteem, and social support(supervisors). Conclusion: The results indicate that it is necessary to increase nurses' empowerment. Social support by supervisors and self-esteem were confirmed as important factors to increase nurses' empowerment. In addition, raising the monthly average income would increase empowerment of nurses.

• The korean journal of orthodontics
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• v.6 no.1
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• pp.7-15
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• 1976

The author have studied the relationship between the maximum puberal growth stage in body height and the appearance of the adductor sesamoid of the thumb with wrist x-ray films. In addition to this, it has been investigated the age at which pubic hair appeared in boys, and the age at menarche in girls. The results were as follows: 1) The ossification of the adductor sesamoid of the thumb occured at 13-years-o-month in boys and 10-years-8-months in girls. 2) There was a close association between the age at maximum puberal growth in body height and the age when ossification of the adductor sesamoid of the thumb occured, and also in girls, the age at the menarche. 3) Appearance of the adductor sesamoid of the thumb indicated that maximum puberal growth in body height is imminent or has been reached. 4) The maximum puberal growth in body height occured 23 months earlier in girls than in boys, and ossification of the adductor sesamoid of the thumb 28 months earlier in girls. 5) Appearance of the pubic hair in boys was of no value for prediction of maximum puberal growth in body height. 6) Menarche is a reliable indication that the maximum puberal growth in body height has been reached or passed.

• Tunnel and Underground Space
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• v.13 no.4
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• pp.260-269
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• 2003

In order to introduce to engineers the suitable calculation techniques of TBM advance rate (ad.) and ultimately promote to understand the designing process, this study was carried out. We analyzed the 17 bored data of TBM which applied to the roadway and water supply tunnels in Korea. From this analysis, it was able to how that the average utilization is 30.83% md the correlation equation of Ad and TBM´s diameter (D) is Ad(m/month) = 506.05ㆍ $e^{-0.1162}$$\times$D than the correlation coefficient ($R^2$) is 0.76. In the object of the W tunnel of Seoul-Busan highspeed railway, the Ad of TBM 5.0mø was analyzed by the variety of empirical models and upper correlation equation. Average Ad of the empirical models was calculated to be larger than one of the upper equations. But considering only the results of 3.0~5.0mø TBM in the 17 bored data, the average Ad by the models belongs to the similar range of bored data. Therefore, when the reliability and representative of parameters are decreased, a reliability test should be carried out through the comparison a variety of empirical models with the upper correlation equation.

• Journal of Veterinary Clinics
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• v.21 no.4
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• pp.355-362
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• 2004

The purpose of this study was to herd management and control of dairy cows by milk components analysis in Gyeongsangnamdo. Milk components analysis were carried out milk yield (MY), milk fat (MF), milk protein (MP), milk urea nitrogen (MUN) and somatic cell count (SCC) but, milk solid (MS), day of non-pregnant condition (DNPC), and days of primipara (DPRI) involved in report. Dairy farms were divided high group, middle group, low group according to the standard records for milk components. Examination records were divided by farm, parity, year, season and month, the number of samples were 28,957. Feeding management practice and the prediction for the risk possibility of productive disease such as reproductive and metabolic disorders by evaluating fat, protein, solids. Determination of MY, MF, MP, MS were Milkoscan 4,000~5,000 Serier (FOSS Electric Co., Copenhagen, Denmark). Correlation coefficient of milk protein (MP) and milk solid (MS) was ascertain r=0.759. SCC was ascertain 372.8$\pm$11.34 (thousand unit) and DNPC was ascertain 155.3$\pm$5.15 (days) in seven parity.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.893-895
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• 2016

Data center has a lot of management efforts for the facility, energy, and efficient usage monitoring. Data center power management is important to make the data center have reliable service and cost-effective business. In this paper, IoT based energy measurements monitoring which gives support to energy consumption analysis including indoor, outdoor temperature condition. This converged information for energy analysis gives various aspects of energy consumption effects. With IoT big data, energy machine learning system can give the relation of energy components and measurements, it is the key information of the quick energy analysis in the just one month data trend for the prediction and estimation.