• Ecology and Resilient Infrastructure
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• 제3권3호
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• pp.189-200
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• 2016

종분포 모델은 어떤 지역에서 침입외래종이 어떻게 확장되고 어떤 환경 요인이 이들의 분포에 영향을 미치는지를 이해하는데 매우 유용한 도구이다. 본 연구에서는 한반도에서 두 침입외래종인 돼지풀 (Ambrosia artemisiifolia)과 물참새피 (Paspalum distichum)의 분포에 대하여 연구하였다. 이 두 종의 현재의 분포지에서 기후환경 요인을 분석하고 이 두 종의 분포를 예측하기 위하여 Maxent (the maximum entropy) 모델을 이용하였다. 이 두 종의 출현 자료는 Global Biodiversity Information Facility와 우리나라의 식물종 데이터베이스에서, 생물기후 자료는 WorldClim 자료로부터 얻었다. 모델을 수행한 결과, 자생지 위치자료를 이용한 예측 결과보다 전지구 위치자료를 이용한 예측이 연구 대상종의 잠재적 분포지를 잘 설명하였다. 이들 종의 분포에 기여한 기후환경 요인으로서 돼지풀에서는 최건월의 강수량과 연평균온도가, 물참새피에서는 연평균온도와 최한사분기의 평균온도가 선정되었다. Maxent 종분포 모델은 외래종의 침입을 예측하고 이들의 확산을 관리하는데 유용한 도구가 될 것으로 생각된다.

• 대기
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• 제19권2호
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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.

• 한국농공학회지
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• 제26권2호
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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.

• 한국수자원학회논문집
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• 제55권10호
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• pp.723-736
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• 2022

본 연구에서는 금강권역을 대상으로 최대 12개월까지 선행예측이 가능한 월 강수량 예측모형을 구축하였으며, 예측모형 구축에는 다중회귀분석과 인공신경망의 두 가지 통계적 기법을 적용하였다. 예측인자 후보로 NOAA에서 제공하는 글로벌 기후패턴 39종과 금강권역에 대한 기상인자 8종 등 총 47종의 기후지수를 활용하였다. 예측대상월을 기준으로 과거 40년간의 월 강수량과 기후지수와의 지연상관성 분석을 통해 상관도가 높은 기후지수를 예측인자로 활용하여 다중회귀모형 및 인공신경망 모형을 구축하였다. 1991~2021년에 대해 매월 예측결과의 평균값과 관측값과의 적합도를 분석한 결과, 다중회귀모형은 PBIAS -3.3~-0.1%, NSE 0.45~0.50, r 0.69~0.70으로 분석되었으며, 인공신경망모형은 PBIAS -5.0~+0.5%, NSE 0.35~0.47, r 0.64~0.70로, 다중회귀모형에 의해 도출된 예측치의 평균값이 인공신경망모형보다 관측치에 좀 더 근접한 것으로 나타났다. 각 월의 예측범위 안에 관측치가 포함될 확률을 분석한 결과에서는 다중회귀모형이 57.5~83.6%(평균 72.9%), 인공신경망모형의 경우에는 71.5~88.7%(평균 81.1%)로 인공신경망모형 결과가 우수한 것으로 나타났다. 3분위 예측확률을 비교한 결과는 다중회귀모형의 경우에는 25.9~41.9%(평균 34.6%), 인공신경망모형은 30.3~39.1%(평균 34.7%)로 비슷하며, 두 모형 모두 평균 33.3% 이상으로 월 강수량에 대한 장기예측성을 확인 할 수 있었다. 이상과 같이 두 모형의 예측성 차이는 비교적 크지 않은 것으로 나타났으나, 예측범위에 대한 적중률이나 3분위 예측확률로부터 판단할 때 예측성에 대한 월별 편차는 인공신경망모형의 결과가 상대적으로 작게 나타났다.

• 한국환경생태학회지
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• 제25권6호
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• pp.903-910
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• 2011

본 연구는 기후변화에 따른 한반도 후박나무의 분포를 규정하는 기후요인과 현재기후와 미래기후에서의 잠재 생육지를 CT모델을 이용하여 예측하였다. 모델 구축을 위한 4개 독립변수로는 최한월최저기온(TMC), 온량지수(WI), 하계강수량(PRS), 동계강수량(PRW)을 사용하였다. CT분석을 통해 구축된 후박나무 분포 모델(Mth-model)에서 TMC(최한월최저기온)가 분포를 규정하는 주요요인으로 작용하였으며, TMC(최한월최저기온) $-3.3^{\circ}C$이상인 지역에서 후박나무의 높은 출현확률을 나타냈다. 현재기후에서 한반도 후박나무의 잠재 생육지(PH)는 $9,326km^2$로 예측되었으며, 3종류 미래기후 시나리오(CCCMA-A2, CSIRO-A2, HADCM3-A2)에서 $61,074{\sim}67,402km^2$(남한: $58,419{\sim}61,137km^2$, 북한:$2,655{\sim}6,542km^2$)로 예측되었다. 미래기후에서 잠재 생육지는 49~51%(남한: 49~51%, 북한: 2~5%) 증가된 면적이 예측되었다. 기후변화에 따라 한반도 후박나무의 잠재 생육지의 확대는 난온대 낙엽활엽수림과 경쟁이 예상된다. 후박나무는 한반도 기후변화 지표종으로 유효하다고 판단되며 잠재 생육지에 대한 지속적인 모니터링이 중요하다.

• 간호행정학회지
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• 제20권5호
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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.

• 대한치과교정학회지
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• 제6권1호
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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.

• 터널과지하공간
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• 제13권4호
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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.

• 한국임상수의학회지
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• 제21권4호
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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.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2016년도 추계학술대회
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• pp.893-895
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• 2016

데이터센터는 지속적으로 IT 서버의 안정적 운영을 위해 실내 환경을 관리하고 있다. 서버가 과열로 동작영향을 받지 않도록 많은 에너지를 항온항습 기능에 투자하고 있다. 기축 데이터센터들은 건축 특징, 운영 방법에 따라 에너지 효율 격차가 크게 발생한다. 본 논문에서는 IoT 기술을 이용하여 기축 데이터센터의 현재 에너지 사용효율을 확인하고, 교체, 업그레이드 필요성을 판단하는 진단시스템 기술을 구현하였다. 해당 측정 정보는 IoT 센서를 통해 수집되며, 수집된 데이터는 클라우드 시스템에서 다양한 머신러닝 알고리즘에 입력되어, 에너지 비즈니스에 지표를 도출한다. IoT를 이용하여 구현한 진단 시스템은 설치, 데이터 수집, 분석에 3주이내의 시간 소요로, 기축 데이터센터의 에너지 효율향상에 많은 기여를 제공할 수 있다.