• Korean Journal of Construction Engineering and Management
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• v.7 no.4 s.32
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• pp.100-108
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• 2006

Non-working days affected by weather conditions of the construction-sites have been estimated without proper data. They are usually estimated based on project engineer's own experience and intuition. As a result, they cause not only economic loss to time-adjustment but also conflicts among project participants. It becomes more difficult to predict the weather nowadays than before due to tendency of recently weather change. Therefore, this paper presents an improved estimation method for non-working days, which could minimize estimation errors. The estimation method is developed based on analysis of regional characteristics and weather conditions which affect project duration.

• Fire Science and Engineering
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• v.29 no.5
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• pp.88-95
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• 2015

We propose a weather-related service for fire risk assessment in order to increase fire safety awareness in everyday life. The proposed service offers a fire risk assessment level according to weather forecasts and a degree of fire risk according to fire factors under certain weather conditions. In order to estimate the fire risk, we produced a risk matrix through data mining with a decision tree using investigation data and weather data. Through the proposed service, residents can calculate the degree of fire risk under certain weather conditions using the fire factors around them. In addition, they can choose from various solutions to reduce fire risk. In order to demonstrate the feasibility of the proposed services, we developed a system that offers the services. Whenever weather forecasting is carried out by the Korea Meteorological Administration, the system produces the fire risk assessment levels for seven major cities and nine provinces of South Korea in an online process, as well as the fire risk according to fire factors for the weather conditions in each region.

• The Plant Pathology Journal
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• v.39 no.6
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• pp.548-565
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• 2023

Armillaria root disease affects forests around the world. It occurs in many habitats and causes losses in the infested stands. Weather conditions are important factors for growth and development of Armillaria species. Yet, the relation between occurrence of damage caused by Armillaria disease and weather variables are still poorly understood. Thus, we used generalized linear mixed models to determine the relationship between weather conditions of current and previous year (temperature, precipitation and their deviation from long-term averages, air humidity and soil temperature) and the incidence of Armillaria-induced damage in young (up to 20 years old) and older (over 20 years old) coniferous stands in selected forest districts across Poland. We used unique data, gathered over the course of 23 years (1987-2009) on tree damage incidence from Armillaria root disease and meteorological parameters from the 24-year period (1986-2009) to reflect the dynamics of damage occurrence and weather conditions. Weather parameters were better predictors of damage caused by Armillaria disease in younger stands than in older ones. The strongest predictor was soil temperature, especially that of the previous year growing season and the current year spring. We found that temperature and precipitation of different seasons in previous year had more pronounced effect on the young stand area affected by Armillaria. Each stand's age class was characterized by a different set of meteorological parameters that explained the area of disease occurrence. Moreover, forest district was included in all models and thus, was an important variable in explaining the stand area affected by Armillaria.

• Korean Journal of Construction Engineering and Management
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• v.11 no.3
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• pp.89-96
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• 2010

Construction industry try to use weather information because construction is much influenced by weather conditions. However, the researches, how to use the weather information in construction fields at present state, are not sufficient. Therefore, the purpose of this study is to present the methods for improving weather information application by analysis the present state in building construction fields. The results show that educations about application of weather information are poorly conducted though the construction engineers know that weather information is helpful to improve the performance and that weather information serviced is not suitable to apply their field's work. Based on the results, for improving the application of weather information, the construction engineers are structurally educated about applying weather information and the weather information system is developed to specialize the building construction projects. Additionally, construction companies have a long term plan to cultivate the experts who equally have a good knowledge and experience of weather information and construction technologies. These proposed methods help to decrease the influence of weather conditions and finally to improve the performance in building construction projects.

• Journal of the Korean Institute of Navigation
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• v.11 no.1
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• pp.107-144
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• 1987

In cold season, ice accretion on ship, drift ice, NW winter monsoon, developed extratropical cyclones and associated cold fronts, in warm season, tropical cyclones and dense sea fogs, are encountered very frequently in the North Pacific, especially in the northwest part of it. The two areas, namely, the northwest part of the North Pacific and Burmuda Triangle in the North Atlantic are generally known as most dangerous areas in the world because its high incidence of sea cascualities. In recent years, the small fisherboats operating in the northern seas were frequently sunk in a group as they encountered ice accretion or drift ice. And ocean going vessels were also sunk frequently due to strong winds and very high seas in winter monsoon or developed cyclones and cold fronts. The purpose of this paper is to analyze the real state of heavy weather conditions such as ice accretion on ship drift, ice, typhoons and sea fogs, and also to analyse the effect of these heavy weather phenomena on the vessels at sea, thus helping mariners operate in such heavy weather conditions.

• Journal of Sericultural and Entomological Science
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• v.36 no.2
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• pp.110-114
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• 1994

Abnormally cool and wet weather conditions during the summer of 1993 offered an opportunity to evaluate the effects of abnormal weather conditions on mulberry growth and to develop cultivation practicies to reduce leaf yield loss under the similar abnormal weather conditions. Different methods of nutrient supplementation were evaluated in Suwon and Kongju. Nitrogen was supplemented by foliar spray of urea(1.7%) or composite chemical fertilizer Jamsibiryo #8, or by the application of ammonium sulfate(60kg/ha) to the soil. During the period between the late June and the early September which corresponds to the mulberry growing season after summer pruning, mean temperature was 1.4$^{\circ}C$ lower and precipitation 83mm higher than normal year. This weather condition in 1993 caused reduction in leaf yield by 16.4% than common year. Soil nitrogen content decreased due to higher precipitation. Leaf yield loss was reduced by the supplementation of nitrogen to the soil. Leaf nitrogen content increased with the foliar urea spray and nitrogen supplementation to the soil.

• Journal of the Society of Naval Architects of Korea
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• v.52 no.2
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• pp.110-118
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• 2015

Weather routing method is one of the best practices of SEEMP (Ship Energy Efficiency Management Plan) for fuel-efficient operation of ship. KR is carrying out a basic research for development of the weather routing algorithm and making a monitoring system by FOC (Fuel Oil Consumption) analysis compared to the reference, which is the great circle route. The added resistances applied global sea/weather data can be calculated using ship data, and the results can be corrected to ship motions. The global sea/weather data such as significant wave height, ocean current and wind data can be used to calculate the added resistances. The reference route in a usual navigation is the great circle route, which is the shortest distance route. The global sea/weather data can be divided into grids, and the nearest grid data from a ship's position can be used to apply a ocean going vessel's sea conditions. Powell method is used as an optimized routing technique to minimize FOC considered sea/weather conditions, and FOC result can be compared with the great circle route result.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.6_2
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• pp.1025-1032
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• 2020

In this paper, we propose a method to classify road weather conditions into rain, fog, and sun using a SVM (Support Vector Machine) classifier after extracting weather features from images acquired in real time using an optical sensor installed on a roadside post. A multi-dimensional weather feature vector consisting of factors such as image sharpeness, image entropy, Michelson contrast, MSCN (Mean Subtraction and Contrast Normalization), dark channel prior, image colorfulness, and local binary pattern as global features of weather-related images was extracted from road images, and then a road weather classifier was created by performing machine learning on 700 sun images, 2,000 rain images, and 1,000 fog images. Finally, the classification performance was tested for 140 sun images, 510 rain images, and 240 fog images. Overall classification performance is assessed to be applicable in real road services and can be enhanced further with optimization along with year-round data collection and training.

• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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• v.14 no.4
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• pp.322-356
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• 1985

The outdoor design conditions for summer and winter are basic data required for determining the heating and cooling loads and HVAC equipment capacity. The latest study reported was based on the 1960's weather data, which is widely used by HVAC design engineers in Korea. The purpose of this paper is to update the outdoor design conditions for HVAC loads and equipments based on the weather data for the 1970's. The weather conditions of 24 sites, namely Sokcho, Chuncheon, Gangreung, Seoul, Inchon, Ulreungdo, Suweon, Seosan, Cheongju, Daejeon, Chupungryeong, Pohang, Gunsan, Daegu, Jeonju, Ulsan, Kwangju, Busan, Chungmu, Mokpo, Yeosu, Jeju, Seogwipo, and Jinju have been analyzed to calculate the outdoor design conditions. This analys is performed on the basis of TAC $1\%,\;TAC\;2.5\%,\;and\;TAC\;5\%$.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.28 no.12
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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.