• 전기학회논문지
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• 제63권10호
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• pp.1423-1427
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• 2014

Quantity of the solar power generation is heavily influenced by weather. In other words, due to difference in insolation, different quantity may be generated. However, it does not mean all areas with identical insolation produces same quantity because of various environmental aspects. Additionally, geographic factors such as altitude, height of plant may have an impact on the quantity. Hence, through this research, we designed a system to predict efficiency of the solar power generation system by applying insolation, weather factor such as duration of sunshine, cloudiness parameter and location. By applying insolation, weather data that are collected from various places, we established a system that fits with our nation. Apart from, we produced a geographic model equation through utilizing generated data installed nationwide. To design a prediction model that integrates two factors, we apply fuzzy algorithm, and validate the performance of system by establishing simulation system.

• 설비공학논문집
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• 제28권12호
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• pp.467-476
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• 2016

As the energy saving issues become one of the important global agenda, the building simulation method is generally used to predict the inside energy usage to establish the power-saving strategies. To foretell an accurate energy usage of a building, proper and typical weather data are needed. For this reason, typical weather data are fundamental in building energy simulations and among the meteorological factors, the solar irradiation is the most important element. Therefore, preparing solar irradiation is a basic factor. However, there are few places where the horizontal solar radiation in domestic weather stations can be measured, so the prediction of the solar radiation is needed to arrive at typical weather data. In this paper, four solar radiation prediction models were analyzed in terms of their applicability for domestic weather conditions. A total of 12 regions were analyzed to compare the differences of solar irradiation between measurements and the prediction results. The applicability of the solar irradiation prediction model for a certain region was determined by the comparisons. The results were that the Zhang and Huang model showed the highest accuracy (Rad 0.87~0.80) in most of the analyzed regions. The Kasten model which utilizes a simple regression equation exhibited the second-highest accuracy. The Angstrom-Prescott model is easily used, also by employing a plain regression equation Lastly, the Winslow model which is known for predicting global horizontal solar irradiation at any climate regions uses a daily integration equation and showed a low accuracy regarding the domestic climate conditions in Korea.

• 한국기후변화학회지
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• 제4권4호
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• pp.317-330
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• 2013

홍수와 가뭄, 고온 등 이상기상의 영향으로 쌀 단수가 감소할 수 있다. 본 연구의 목적은 등숙기 이상기상이 쌀 단수에 미치는 영향을 파악하는 것이며, 이를 위하여 횡단면 자료와 시계열 자료를 모두 이용할 수 있는 패널모형을 이용하였다. 본 연구에서는 기상요소의 평균값을 기준으로 ${\pm}2{\sigma}$의 범위를 벗어날 때를 이상기상으로 정의하였다. 분석결과를 보면, 이상고온이 발생하였을 때 쌀 단수가 5.8~16.3% 감소, 이상고온과 폭우가 동시에 발생하였을 때 8.8~20.8% 감소하는 것으로 나타났다. 이상기상으로 인한 쌀 생산량 감소를 최소화하고, 농가의 소득안정을 위하여 고온과 폭우에 강한 신품종 개발, 농업용 수리시설의 현대화, 농작물보험 채택 등의 적응전략이 필요하다.

• 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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• 제30권3호
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• pp.237-248
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• 2020

In order to effectively prepare for damage caused by weather events, it is important to proactively identify the possible impacts of weather phenomena on the domestic society and economy. Text mining and Network analysis are used in this paper to build a database of damage types and levels caused by heat wave. We collect news articles about heat wave from the SBS news website and determine the primary and secondary effects of that through network analysis. In addition to that, based on the frequency with which each impact keyword is mentioned, we estimate how much influence each factor has. As a result, the types of impacts caused by heat wave are efficiently derived. Among these types of impacts, we find that people in South Korea are mainly interested in algae and heat-related illness. Since this technique of analysis can be applied not only to news articles but also to social media contents, such as Twitter and Facebook, it is expected to be used as a useful tool for building weather impact databases.

• 한국화재소방학회논문지
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• 제15권3호
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• pp.49-54
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• 2001

최근 전 세계적으로 개발을 위한 고의적인 방화와 기상이변에 의한 산림화재의 급증과 피해규모가 증가하는 경향을 보이고 있다. 이와 같은 대형 산림화재는 국내에서도 같은 경향으로 나타나고 있다. 산림화재에 가장 효과적인 대응 방법은 화재발생 후의 진압보다는 화재예방 활동이라고 볼 수 있으며, 우선적으로 시급한 연구과제는 산림화재 예방 시스템에 관한 연구라 할 수 있다. 본 연구에서는 산림화재의 종합적 위험등급 개발을 위해 산림화재에 영향을 미치는 인자들에 대해 실험 및 자료들을 분석·고찰하여 6개 인자에 대한 개별적 위험성을 나타내었으며 각 인자들의 위험성 기여도에 따른 가중치를 적용하여 종합위험 등급을 설정하였다.

• 한국농림기상학회지
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• 제16권4호
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• pp.274-284
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• 2014

농업은 기후 및 환경의 영향을 많이 받는 산업으로 기온, 강수량, 일조시간 등에 따라 재배 가능한 작물 과 품종이 결정된다. 본 연구의 목적은 사과의 생육과정에서 일별로 측정되는 기상변수를 활용하여 기상변수가 사과단수에 미치는 영향을 파악하는 것에 있다. 기상변수는 1) 생육단계를 고려한 자연과학적 접근방법과 2) 통계적 접근방법을 이용한다. 패널분석을 통해 추정된 각각의 결과를 모형적합도와 예측력 비교를 통해 평가한다. 사과단수와 기상변수의 자료는 2006년부터 2013년까지 우리나라 사과주산지 15개지역을 대상으로 수집되었다. 분석 결과, 통계적 접근방법 중요인분석을 이용한 변수 선정 방법이 가장 높은 예측력과 적합도를 보였다. 이는 기상변수와 같이 서로 유사하지만 다양한 설명변수의 사용으로 발생할 수 있는 다중공선성과 낮은 자유도의 문제를 효과적으로 통제하게 될 경우, 보다 많은 기상요인을 회귀분석에 포함하는 것이 적합도와 예측력을 높이는데 기여한 것으로 추정된다. 또한 사과재배에 있어 발아, 개화, 착과, 비대, 성숙, 그리고 착색 및 수확에 이르기까지의 전 생육과정의 기상요인이 단수에 영향력이 있음을 의미한다.

• Agribusiness and Information Management
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• 제6권1호
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• pp.1-11
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• 2014

The purpose of this study is to develop the growth prediction model that can predict growth and development information influencing on the production of citrus fruits. The growth model was developed to predict the floral leaf ratio, number of fruit sets, fruit width, and overweight fruits depending on the main period of growth and development by considering the weather factors because the fruit production is influenced by weather depending on the growth and development period. To predict the outdoor-grown citrus fruit production, the investigation result for the standard farms is used as the basic data; in this study, we also understood that the influence of weather factors on the citrus fruit production based on the data from 2004 to 2013 of the outdoor-grown citrus fruit observation report in which the standard farms were targeted by the Agricultural Research Service and suggested the growth and development information prediction model with the weather information as an independent variable to build the observation model. The growth and development model for outdoor-grown citrus fruits was assumed by using the Ordinary Least Square method (OLS), and the developed growth prediction model can make a prediction in advance with the weather factors prior to the observation investigation for the citrus fruit production. To predict the growth and development information of the production of citrus fruits having a great ripple effect as a representative crop in Jeju agriculture, the prediction result regarding the production applying the weather factors depending on growth and development period could be applied usefully.

• Journal of Multimedia Information System
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• 제5권1호
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• pp.1-8
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• 2018

The coordinate system conversion of weather radar data is a basic and important process because it can be a factor to measure the accuracy of radar precipitation rate by comparison with the ground rain gauge. We proposed a real-time coordinate system conversion method that combines the advantages of the interpolation masks of SPRINT and REORDER to use tables of predetermined radar samples for each interpolated object coordinate and also distance weights for each precomputed sample. Experimental results show that the proposed method improves the computation speed more than 20~30 times compared with the conventional method and shows that the deterioration of image quality is hardly ignored.

• Journal of Advanced Marine Engineering and Technology
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• 제33권5호
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• pp.705-712
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• 2009

The state changes of ocean covered over 70% of earth surface are one of the greatest factor of weather catastrophe. Recently weather extraordinary events are followed by steep increase of sea water temperature and scientists in various fields are studying and warning the weather changes. In this paper, floating buoy is developed to monitor ocean environments via Orbcomm satellite and a method is proposed to increase measurement accuracy of sea water temperature with common low price temperature sensor. Experimental results are presented to illustrate the usability and effectiveness of the developed system. A web-based real time monitoring system is built to monitor ocean environmental information such as sea and air temperature, salinity according to the position of buoy through the internet for user convenience.