• 대기
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• 제29권4호
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• pp.439-450
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• 2019

Present weather plays an important role not only for atmospheric sciences but also for public welfare and road safety. While the widely used state-of-the-art visibility and present weather sensor yields present weather, a single type of measurement is far from perfect to replace long history of human-eye based observation. Truly automatic present weather observation enables us to increase spatial resolution by an order of magnitude with existing facilities in Korea. 8 years of human-eyed present weather records in 19 sites over Korea are compared with visibility sensors and auxiliary measurements, such as humidity of AWS. As clear condition agrees with high probability, next best categories follow fog, rain, snow, mist, haze and drizzle in comparison with human-eyed observation. Fog, mist and haze are often confused due to nature of machine sensing visibility. Such ambiguous weather conditions are improved with empirically induced criteria in combination with visibility and humidity. Differences between instrument manufacturers are also found indicating nonstandard present weather decision. Analysis shows manufacturer dependent present weather differences are induced by manufacturer's own algorithms, not by visibility measurement. Accuracies of present weather for haze, mist, and fog are all improved by 61.5%, 44.9%, and 26.9% respectively. The result shows that automatic present weather sensing is feasible for operational purpose with minimal human interactions if appropriate algorithm is applied. Further study is ongoing for impact of different sensing types between manufacturers for both visibility and present weather data.

• 한국기록관리학회지
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• 제3권2호
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• pp.143-155
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• 2003

역사적 사실이나 경험의 중요한 증거자료로서 보존적 가치를 지니는 사진은 보통의 다른 문서들과 달리 빛, 온도, 습도 등의 여러 가지 환경 요인에 따라 매우 쉽게 변형될 수 있기 때문에 보존에 따르는 과학적이고 세밀한 주의가 요구된다. 본 연구에서는 일반적으로 널리 시판되어 사용되고 있는 사진용 필름과 인화지들을 선택하여 노광을 주어 감도를 측정하고, 노화가속장치(Weather-o-meter)에 넣어 인위적으로 변형을 허용한 뒤 다시 감도를 측정하여 비교함으로써 감재의 보존특성을 비교분석 하였다. 실험결과 흑백감재의 보존특성이 컬러의 경우보다 우수했으며, Film보다 인화지의 경우가 노화에 따른 변형이 없는 것으로 나타났다. 그러나 제조회사에 따른 각 제품별 보존특성 차이는 크게 관찰되지 않았다.

• Asian Pacific Journal of Cancer Prevention
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• 제16권2호
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• pp.607-611
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• 2015

Background: Chronic respiratory disease is an important factor for development of lung cancer. To explore the influence of hazy weather on respiratory diseases and its variation the present study was conducted. Materials and Methods: Data from air pollution surveillance from January to October 2014 and case records of visiting patients in the $263^{th}$ Hospital of Chinese PLA in the corresponding period were collected to analyze the relevance between different degrees of air pollution (hazy weather) and the number of visiting patients in Department of Respiratory Disease. Results: Air quality index (AQI) of hazy weather had significantly positive association with particulate matter 2.5 ($PM_{2.5}$) and the number of patients with 5 kinds of respiratory diseases i and different pollutants had distinct influences on various respiratory diseases. Conclusions: The degree of air pollution in Beijing City is in close association with the number of patients with respiratory diseases, in which $PM_{2.5}$ and $SO_2$ are in more significant influences on all respiratory diseases. This could have essential implications for lung cancer development in China.

• 대기
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• 제34권1호
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• pp.1-21
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• 2024

Private companies are increasingly required to take more substantial actions on climate change. This study introduces the principle and cases of climate (physical) risk estimation for 11 private companies in Korea. Climate risk is defined as the product of three major determinants: hazard, exposure, and vulnerability. Hazard is the intensity or frequency of weather phenomena that can cause disasters. Vulnerability can be reflected in the function that explains the relationship between past weather records and loss records. The final climate risk is calculated by multiplying the function by the exposure, which is defined as the area or value of the target area exposed to the climate. Future climate risk is estimated by applying future exposure to estimated future hazard using climate model scenarios or statistical trends based on weather data. The estimated climate risks are developed into three types according to the demand of private companies: i) climate risk for financial portfolio management, ii) climate risk for port logistics management, iii) climate risk for supply chain management. We hope that this study will contribute to the establishment of the climate risk management system in the Korean industrial sector as a whole.

• 한국수자원학회논문집
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• 제43권5호
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• pp.483-493
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• 2010

본 연구에서는 국내 기상관측소 중 관측년수가 30년 이상인 관측소 63개 지점에 대한 5개의 수문기상수문인자 즉, 연강수량, 연강수일수, 연평균기온, 연평균상대습도, 연일조시간 자료를 각 지점별로 수집하고, 통계학적 기법인 Wald-Wolfowitz 검정, Mann-Whitney 검정을 이용하여 변동성 분석과 Wavelet Transform을 이용하여 주기성을 분석하였다. 변동성 분석결과 연평균상대습도, 연평균기온에서 공통적으로 변동성이 나타났으며, 연강수량, 연강수일수, 연일조시간은 지역에 따라 상이한 결과를 보였다. 주기성 분석에서는 연강수량, 연강수일수에서 각 지점별로 주기가 나타났으나, 연평균기온, 연평균상대습도, 연일조시간에서는 뚜렷한 주기가 나타나지 않았다.

• 대한조선학회논문집
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• 제51권2호
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• pp.99-106
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• 2014

Weather routing of a ship provides an optimal route to the destination by using minimal time or fuel in a given sea condition. These days, weather routing came into a spotlight with soaring fuel price and the environmental regulations of IMO and several countries. This study presents three scenarios of voyaging strategies for a ship and compared them in terms of the fuel consumption. The first strategy fixes the speed of a ship as a constant value for entire sailing course, the second fixes the RPM of the ship as constant for entire course, and the third determines the RPMs of the ship for each segment of the course. For each strategy, a ship route is optimized by using the $A^*$ search method. Wind, ocean current and wave are considered as ocean environment factors when seeking the optimal routes. Based on 7000 TEU container ship's sea trial records, simulation has been conducted for three scenarios, and the most efficient routing scenario is determined in the view of fuel consumption.

• 한국농공학회지
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• 제36권1호
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• pp.63-72
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• 1994

The objective of the study is to develop weather generators for daily rainfall and small pan evaporation and to test the applicability with recorded data. Daily rainfall forecasting model(DRFM) was developed that uses a first order Markov chain to describe rainfall seque- nces and applies an incomplete Gamma function to predict the amount of precipitation. Daily evaporation forecasting model(DEFM) that adopts a normal distribution function to generate the evaporation for dry and wet days was also formulated. DRFM and DEFM were tested with twenty year weather data from eleven stations using Chi-square and Kolmogorov and Smirnov goodness of fit tests. The test results showed that the generated sequences of rainfall occurrence, amount of rainfall, and pan evaporation were statistically fit to recorded data from eleven, seven, and seven stations at the 5% level of significance. Generated rainfall data from DRFM were very close in frequency distri- bution patterns to records for stations all over the country. Pan evaporation for rainy days generated were less accurate than that for dry days. And the proposed models may be used as tools to provide many mathematical models with long-term daily rainfall and small pan evaporation data. An example is an irrigation scheduling model, which will be further detailed in the paper.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.150-150
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• 2018

The Numerical Weather Prediction (NWP) models provide information for weather forecasts. The highly nonlinear and complex interactions in the atmosphere are simplified in meteorological models through approximations and parameterization. Therefore, the simplifications may lead to biases and errors in model results. Although the models have improved over time, the biased outputs of these models are still a matter of concern in meteorological and hydrological studies. Thus, bias removal is an essential step prior to using outputs of atmospheric models. The main idea of statistical bias correction methods is to develop a statistical relationship between modeled and observed variables over the same historical period. The Model Output Statistics (MOS) would be desirable to better match the real time forecast data with observation records. Statistical post-processing methods relate model outputs to the observed values at the sites of interest. In this study three methods are used to remove the possible biases of the real-time outputs of the Weather Research and Forecast (WRF) model in Imjin basin (North and South Korea). The post-processing techniques include the Linear Regression (LR), Linear Scaling (LS) and Power Scaling (PS) methods. The MOS techniques used in this study include three main steps: preprocessing of the historical data in training set, development of the equations, and application of the equations for the validation set. The expected results show the accuracy improvement of the real-time forecast data before and after bias correction. The comparison of the different methods will clarify the best method for the purpose of the forecast skill enhancement in a real-time case study.

• 한국게임학회 논문지
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• 제4권3호
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• pp.77-84
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• 2004

게임의 게임성, 재미의 제공, 볼거리 및 배경그래픽 제공하고, 게임플레이의 활동 무대인 배경-맵과 배경그래픽 디자인을 구현하기 위해서는 게임 배경환경은 매우 중요한 요소이다. 본 연구에서는 게임 배경환경의 구성요소를 정의하고, 시대적 및 역사적인 환경요소, 자연적인 환경요소, 인공적인 환경요소, 문화적인 환경요소, 가상적인 환경요소를 문헌과 사료를 통하여 고찰 연구하였으며, 실제 게임 배경맵에 적용할 수 있는 배경그래픽의 환경디자인 모델을 제시한다.

• 대기
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• 제29권5호
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• pp.615-626
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• 2019

To find any effects of precipitation climate on the forecast verification methods, we processed the hourly records of precipitation over South Korea. We examined their relationship between the climate and the methods of verification. Precipitation is an intermittent process in South Korea, generally less than an hour or so. Percentile ratio of precipitation period against the entire period of the records is only 14% in the hourly amounts of precipitation. The value of the forecast verification indices heavily depends on the climate of rainfall. The direct comparison of the index values might force us to have a mistaken appraisal on the level of the forecast capability of a weather forecast center. The size of the samples for verification is not crucial as long as it is large enough to satisfy statistical stability. Our conclusion is still temporal rather than conclusive. We may need the amount of precipitation per minute for the confirmation of the present results.