• Korean Journal of Construction Engineering and Management
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• v.5 no.6 s.22
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• pp.80-89
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• 2004

Among the various factors influencing construction productivity, weather conditions or elements become very important factors in planning and executing construction project. It is especially true in Korea where the weather changes dramatically through few seasons. In this study, relationship between construction productivity of the reinforced concrete structure we for the high-rise apartment buildings and 5 weather elements including temperature, humidity, day time, rainfall, and wind velocity have been analyzed The results trough regression analysis showed that weather elements explain $58.8\%$ of productivity in total and temperature and day time were more important factors among them.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.4
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• pp.274-284
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• 2014

Crops and varieties are mostly affected by temperature, the amount of precipitation, and duration of sunshine. This study aims to identify the weather factors that directly influence to apple yield among the series of daily measured weather variables during growing seasons. In order to identify them, 1) a priori natural scientific knowledge with respect to the growth stage of apples and 2) pure statistical approaches to minimize bias due to the subject selection of variables are considered. Each result estimated by the Panel regression using fixed/random effect models is evaluated through suitability (i.e., Akaike information criterion and Bayesian information criterion) and predictability (i.e., mean absolute error, root mean square error, mean absolute percentage). The Panel data of apple yield and weather factors are collected from fifteen major producing areas of apples from 2006 to 2013 in Korea for the case study. The result shows that variable selection using factor analysis, which is one of the statistical approaches applied in the analysis, increases predictability and suitability most. It may imply that all the weather factors are important to predict apple yield if statistical problems, such as multicollinearity and lower degree of freedom due to too many explanatory variables used in the regression, can be controlled effectively. This may be because whole growth stages, such as germination, florescence, fruit setting, fatting, ripening, coloring, and harvesting, are affected by weather.

• Research in Plant Disease
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• v.8 no.4
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• pp.199-206
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• 2002

It was investigated on the relationship of the rice blast epidemics and the real-time meteorological factors, at the experimental paddy field in 1997. Weather factors(temperature, relative humidity, irradiation, precipitation, the direction of wind, wind speed, soil temperature and leaf-wetness, etc) were measured by using the automated weather station. The most influenced weather factor to blast epidemics, was the average max-temp($R^2$= 0.95) during 10 days before leaf blast epidemics, while the least thing was wind speed($R^2$= 0.24). The most potential weather factors correlated with the blast epidemics were T-ave(average temperature), T-max(maximum temperature), RH(Relative Humidity) and RD(Relative Humidity > 90% hrs). A statistics model(the regression equation) of the blast epidemics with the potential weather factors, was established as tallows ; Y = -3410.91 - 23.91 $\times$ T-ave ＋ 28.56 $\times$ T-max ＋ 41.0 $\times$ RH - 3.75 $\times$ RD, ($R^2$= 0.99). (T-ave >= 19$^{\circ}C$, T-max - T-ave >= 5.2$^{\circ}C$ and RH% >= 90.4%). According to the fitness test($\chi$$^2$) of the model, the observed blast disease severity was quite close to those expected.

• Journal of Climate Change Research
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• v.4 no.4
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• pp.317-330
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• 2013

The yield of rice production is affected severely by abnormal weather events, such as flood, drought, high temperature etc. The objective of this paper is to assess impacts of abnormal weather events on rice production, using a panel model which analyzes both cross-section data and ti- me series data. Abnormal weather is defined as the weather event which goes beyond the range of ${\pm}2{\sigma}$ from the average of a weather factor. The result of an analysis on impacts of high temperature on rice production showed that the yield of rice was decreased 5.8% to 16.3% under the conditions of extremely high temperature, and it was decreased 8.8 to 20.8% under the conditions of both extremely high and heavy rain. Adaptation strategies, development of new varieties enduring high temperature and heavy rain, adaptation of crop insurance, modernization of irrigation facilities are needed to minimize the impacts of abnormal weather on rice production, and to stabilize farmers' income.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.969-980
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• 2017

Galloping is one of the most serious vibration problems in transmission lines. Power lines can be extensively damaged owing to aerodynamic instabilities caused by ice accretion. In this study, the accident probability induced by galloping phenomenon was analyzed using logistic regression analysis. As former studies have generally concluded, main factors considered were local weather factors and physical factors of power delivery systems. Since the number of transmission towers outnumbers the number of weather observatories, interpolation of weather factors, Kriging to be more specific, has been conducted in prior to forming galloping accident estimation model. Physical factors have been provided by Korea Electric Power Corporation, however because of the large number of explanatory variables, variable selection has been conducted, leaving total 11 variables. Before forming estimation model, with 84 provided galloping cases, 840 non-galloped cases were chosen out of 13 billion cases. Prediction model for accidents by galloping has been formed with logistic regression model and validated with 4-fold validation method, corresponding AUC value of ROC curve has been used to assess the discrimination level of estimation models. As the result, logistic regression analysis effectively discriminated the power lines that experienced galloping accidents from those that did not.

• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.1
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• pp.153-181
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• 2013

Weather is an influential factor to sales of companies. There have been growing attempts with which companies apply weather to developing their strategic marketing plans. By executing weather marketing activities, companies minimize risks (or negative impacts) of weather to their business and increase sales revenues. In spite of managerial importance of weather management, there are scarce empirical studies that comprehensively investigate its impact and present an efficient method that optimally allocates marketing budget. Our research was conducted in two parts. In the first part, we investigated influences of weather on sales based on real-world daily sales data. We specifically focused on the contextual factors that were less focused in the weather related research. In the second part, we propose an optimization model that can be utilized to efficiently allocate weather marketing budget across various regions (or branches) and show how it can be applied to real industry cases. The results of our study are as follow. Study 1 investigated the impact of weather on sales using store sales data of a family restaurant company and an outdoor fashion company. Results represented that the impacts of weather are context-dependent. The impact of weather on store sales varies across their regional and location characteristics when it rains. Based on the results derived from Study 1, Study 2 proposes a method on how optimally companies allocate their weather marketing budgets across each region.

• International Journal of Concrete Structures and Materials
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• v.7 no.2
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• pp.165-174
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• 2013

Portland cement concrete exposed to high temperatures during mixing, transporting, casting, finishing, and curing can develop undesirable characteristics. Applicable requirements for such the hot weather concrete differ from country to country and government agencies. The current study is an attempt at evaluating the hardened properties of the concrete exposed to hot weather in fresh state. First of all, this study reviews the current state of understanding and practice for hot weather concrete placement in US and then roadway sites with suspected hot weather concrete problems were investigated. Core samples were obtained from the field locations and were analyzed by standard resonance frequency analysis and the boil test. Based on the results, there does not appear to be systematic evidence of frequent cracking problems related to high temperature placement. Thus, the suspicious deteriorations which are referable to hot weather concreting would be due to other factors.

• Journal of Korean Society of Rural Planning
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• v.24 no.3
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• pp.25-31
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• 2018

This study analyzed factors influencing cultivation area of two major apple cultivars, Fuji and Hongro, applying the panel SUR model to survey data from farms. Characteristics of farms, distribution factors, and weather factors were the independent variables of the model. The analysis indicated that characteristics of farms, distribution factors, and weather factors influence the cultivation area of Hongro and Fuji. The independent variables were also found to have different levels of influence on increase and decrease of the cultivated area. Helping predict changes in cultivation area of Hongro and Fuji, the research results can be used as primary data to support efforts to prevent price fluctuations due to changes in supply.

• Preventive Nutrition and Food Science
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• v.7 no.1
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• pp.88-94
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• 2002

The purpose of this study was to identify factors influencing the consumption of calcium-rich foods among adolescents. A total of 96 adolescents divided into twelve focus groups were investigated during April to May 2000 in Busan. Focus group discussions were audio-taped, transcribed and analyzed using a grounded theory approach. Key factors influencing the consumption of calcium-rich foods were taste, food type, body image, and family. Motivators among the factors were taste, flood type, body image, health, family and perception, and barriers were taste, flood type, location, friends, price, weather and lactose intolerance. Taste, flood type, location and weather were found to be both motivators and barriers of consumption of calcium-rich floods according to circumstances. Some of these factors varied in importance by gender and age. Younger adolescents were more strongly influenced by taste and family than older ones. Older adolescents were strongly influenced by body image, convenience and perception. These findings could be used as a guideline for adolescents to consume calcium-rich foods.

• Journal of the Korea Convergence Society
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• v.5 no.1
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• pp.9-15
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• 2014

Traffic accidents are caused by a variety of factors. Among the factors that cause traffic accidents are weather conditions at the time. There is a difference in the percentage of deaths according to traffic accidents, due to the weather conditions. In order to reduce the number of deaths due to traffic accidents, to predict the incidence of traffic accidents that occur in response to weather conditions is required. In this paper, it propose a model to predict the incidence of traffic accidents caused by weather conditions. Predictive modeling was applied to the theory of Markov processes. By applying the actual data for the proposed model, to predict the incidence of traffic accidents, it was compared with the number of occurrences in practice. In this paper, it is to support the development of traffic accident policy with the change of weather.