• Journal of Environmental Health Sciences
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• v.33 no.5
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• pp.365-371
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• 2007

To evaluate the effect of air pollution on respiratory health in children, We conducted a longitudinal study in which children were asked to record their daily levels of Peak Expiratory Flow Rate(PEFR) using potable peak flow meter(mini-Wright) for 4 weeks. The relationship between daily PEFR and ambient air particle levels was analyzed using a mixed linear regression models including gender, age in year, weight, the presence of respiratory symptoms, and relative humidity as an extraneous variable. The daily mean concentrations of $PM_{10}$ and $PM_{2.5}$ over the study period were $64.9{\mu}g/m^3$ and $46.1{\mu}g/m^3$, respectively. The range of daily measured PEFR in this study was $182{\sim}481\;l/min$. Daily mean PEFR was regressed with the 24-hour average $PM_{10}(or\;PM_{2.5})$ levels, weather information such as air temperature and relative humidity, and individual characteristics including sex, weight, and respiratory symptoms. The analysis showed that the increase of air particle concentrations was negatively associated with the variability in PEFR. We estimated that the IQR increment of $PM_{10}$ or $PM_{2.5}$ were associated with 1.5 l/min (95% Confidence intervals -3.1, 0.1) and 0.8 l/min(95% CI -1.8, 0.1) decline in PEFR. Even though this study showed negative findings on the relationship between respiratory function and air particles, it was worth noting that the findings must be interpreted cautiously because exposure measurement based on monitoring of ambient air likely resulted in misclassification of true exposure levels and this was the first Korean study that $PM_{2.5}$ measurement was applied as an index of air quality.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.3
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• pp.119-123
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• 2012

The duration of low temperature in winter season is one of the important agrometeorological characteristics in crop growing fields. This study was conducted to develop a method to estimate the duration of low-temperature with monthly meteorological data. Using daily meteorological data from 61 observation sites from 1981 to 2010, we analyzed the relationships between the averages of monthly temperature minima and the durations of low-temperature ranging from -15 to $5^{\circ}C$, The monthly mean of the January minimum air temperature was appropriate for theestimation of the durations of lowtemperature below $0^{\circ}C$. We tested a simple second order equation to predict durations of low-temperature. To apply the equation to various temperature ranges, we suggested two different equations for the estimation of coefficients a and b, which are dependent on the base temperatures from -15 to $0^{\circ}C$. Thevalidation of the equations using other daily meteorological datasets from 1971 to 2000 showed that they were appropriate for the range from -10 to $0^{\circ}C$, but underestimated at $-15^{\circ}C$.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.25-30
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• 2016

It is critical to forecast the maximum daily and monthly demand for power with as little error as possible for our industry and national economy. In general, long-term forecasting of power demand has been studied from both the consumer's perspective and an econometrics model in the form of a generalized linear model with predictors. Time series techniques are used for short-term forecasting with no predictors as predictors must be predicted prior to forecasting response variables and containing estimation errors during this process is inevitable. In previous researches, seasonal exponential smoothing method, SARMA (Seasonal Auto Regressive Moving Average) with consideration to weekly pattern Neuron-Fuzzy model, SVR (Support Vector Regression) model with predictors explored through machine learning, and K-means clustering technique in the various approaches have been applied to short-term power supply forecasting. In this paper, SARMA and intervention model are fitted to forecast the maximum power load daily, weekly, and monthly by using the empirical data from 2011 through 2013. $ARMA(2,\;1,\;2)(1,\;1,\;1)_7$ and $ARMA(0,\;1,\;1)(1,\;1,\;0)_{12}$ are fitted respectively to the daily and monthly power demand, but the weekly power demand is not fitted by AREA because of unit root series. In our fitted intervention model, the factors of long holidays, summer and winter are significant in the form of indicator function. The SARMA with MAPE (Mean Absolute Percentage Error) of 2.45% and intervention model with MAPE of 2.44% are more efficient than the present seasonal exponential smoothing with MAPE of about 4%. Although the dynamic repression model with the predictors of humidity, temperature, and seasonal dummies was applied to foretaste the daily power demand, it lead to a high MAPE of 3.5% even though it has estimation error of predictors.

• Korean Journal of Ichthyology
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• v.24 no.2
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• pp.110-117
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• 2012

Hatching date and early growth of Pacific cod Gadus macrocephalus were estimated by examination of otolith microstructure of Pacific cod juveniles collected in Jinhae Bay of Korea from May to June, 2008. Water temperature during the main spawning time ranged from 7 to $9^{\circ}C$ according to the geographic distribution of temperature measured from November to May between 2006 and 2009. The spawners were collected from December to February between 2006 and 2008, and the gonadosomatic index of spawners was larger in females than in males, showing a peak in January. Total length of juveniles ranged from 37.5 to 94.9 mm ($63.2{\pm}11.0mm$; mean${\pm}$SD). The number of daily growth increments in juvenile otoliths were on average $102{\pm}15$ in May 17 samples, $119{\pm}16$ in May 29 ones and $116{\pm}18$ in June 3 ones. Hatching dates estimated from the number of daily growth increments ranged from late December to mid-March, showing the peak between late January and mid-February. Daily growth in total length (TL, mm) can be adjusted to the Gompertz curve: $TL_t=123.2{\exp}\{-{\exp}[-0.0165(t-81.8)]\}$ ($r^2$=0.93, n=273).

• Journal of Environmental Health Sciences
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• v.43 no.6
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• pp.478-490
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• 2017

Objectives: The association of air pollution levels and land-use types with changes in the prevalence of allergic diseases (allergic conjunctivitis, allergic rhinitis, asthma, and atopic dermatitis) was investigated for seven metropolitan cities in Korea Methods: Data on daily hospital visits and admissions (of those under 19 years old) for 2003-2012 were obtained from the National Health Insurance Cooperation. Meteorological data on daily mean temperature, humidity, and air pressure were obtained from the Korea Meteorological Administration. Daily mean or maximum concentration data for five pollutants ($PM_{10}$, $O_3$, $NO_2$, $SO_2$, and CO) as measured at air quality monitoring sites operated by the Ministry of Environment were used. We estimated excess risk and 95% confidence intervals for the increasing interquatile range (IQR) of each air pollutant using Generalized Additive Models (GAM) appropriate for time series analysis. Results: In this study, we observed a significant association between the IQR increases of air pollutants and the prevalence risk of allergic diseases (allergic conjunctivitis, allergic rhinitis, asthma, and atopic dermatitis) in all metropolitan cities after adjusting for temperature, humidity, and air pressure at sea level. Among the air pollutants, $NO_2$ and $PM_{10}$ were associated with the prevalence of asthma, and $O_3$ was associated with only allergic conjunctivitis in regression analysis. However, in GAM analysis considering land-use, $O_3$ and $SO_2$ were associated with allergic conjunctivitis, PM10, O3, NO2, and CO were associated with allergic rhinitis, and $PM_{10}$, $O_3$ and $NO_2$ were associated with asthma in industrial area. Conclusion: This study found a significant association between air pollution and the prevalence of allergic related diseases in industrial areas. More detailed research considering mixed traffic-related air pollution (TRAP) and conducting meta-analyses combining data of the all cities is required.

• Journal of the Korean Institute of Landscape Architecture
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• v.14 no.2
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• pp.81-90
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• 1986

The full grasp of recreation demand and factors affecting on recreation demand can be very important information for park planning and management. The object-tives of this study are to investigate factors affecting the fluctuation of urban park visitors and to analyze the relationship between these factors and the daily parti-cipations. The results were as follows; 1) The peak of monthly participations comes on May, April, August and October in order. And these months are specified as school picnic period and vacation of school children. 2) In correlation analysis, the variables such as ‘Day of a week(D)’, ‘Monthly mean temp.(T)’and ‘Monthly character(M)’have high correlations with ‘No. of visitors’in order. And it is better to categorize months by its charater(picnic period in school, vacation etc) than by seasons. 3) Candidate regression model were established, as for 1984 log U= 1.51 + 0.64D1 + 0.02T + 0.36W1 - 0.23M4 + 0.003SS + 0.24Ml($R^2$=0.5326) where, U=no. of daily visitors D1 = sunday.ho1iday(1), weekday(0) T=monthly mean temperature($^{\circ}C$) W1= weather (sunny.cloudy(1) , rainy (>5mm)(0)> M4=non vacations and non school picnic period(1) , if not (0) SS=monthly sunshining hours M1=summer vacation(1), if not(0) 4) The most important variable was ‘Day of a week’(sunday.holiday or not). And temperature, weather and monthly charcter(especially picnic period of school and vacation) were in turn, hence ‘Children's grand park’shows the use pattern of park.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.1
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• pp.34-45
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• 2021

Weather is one of the important factors in the agricultural industry as it affects the price, production, and quality of crops. Upland crops are directly exposed to the natural environment because they are mainly grown in mountainous areas. Therefore, it is necessary to provide accurate weather for upland crops. This study examined the effectiveness of 12 forest soil factors to interpolate the weather in mountainous areas. The daily temperature and precipitation were collected by the Korea Meteorological Administration between January 2009 and December 2018. The Generalized Additive Model (GAM), Kriging, and Random Forest (RF) were considered to interpolate. For evaluating the interpolation performance, automatic weather stations were used as training data and automated synoptic observing systems were used as test data for cross-validation. Unfortunately, the forest soil factors were not significant to interpolate the weather in the mountainous areas. GAM with only geography aspects showed that it can interpolate well in terms of root mean squared error and mean absolute error. The significance of the factors was tested at the 5% significance level in GAM, and the climate zone code (CLZN_CD) and soil water code B (SIBFLR_LAR) were identified as relatively important factors. It has shown that CLZN_CD could help to interpolate the daily average and minimum daily temperature for upland crops.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.55 no.3
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• pp.214-219
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• 2010

In order to evaluate the benefits of global warming on the double cropping with staple crops in North-Korea, four aspects such as the increasing rate of air temperature, the wintering temperatures for winter crops, the causing temperature of cool injury to rice and the securing of accumulated temperature for the double cropping in the different agricultural climate zones were analyzed by comparing the differences between the past 22 years from 1973 to 1994 and the recent 5 years from 2002 to 2006. The warming rate in recent daily mean air temperature of $8.96^{\circ}C$ in North Korea was higher by $0.64^{\circ}C$ than that in the past with large regional variations ranging from $1.06^{\circ}C$ in Samjiyeon of northern inland semi-alpine zone to $12.26^{\circ}C$ in Jangjeon of east central coastal zone. With the accumulated temperatures of more than $3,150^{\circ}C$ and $2,650^{\circ}C$, it was possible to apply the double cropping patterns with winter wheat and for cropping patterns with spring potato, respectively, to the whole region except for the northern inland semi-alpine zone. However, the wintering temperature higher than $-15^{\circ}C$ of average daily minimum air temperature of January, cropping patterns were impossible to northern inland semi-alpine zone and most regions of the northern mountainous zone. The days passed by below $17^{\circ}C$ in daily mean air temperature, causing the spikelet sterility at meiotic stage of rice in July, were a lot recorded from 21 to 29 days in northern inland semi-alpine zone and from 2 to 10 days in east-northern coastal zone, respectively. Therefore, a reasonable utilization of heat / temperature resources would relieve the limiting factors in double cropping for stable production of staple crops in North-Korea.

• New & Renewable Energy
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• v.8 no.2
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• pp.14-23
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• 2012

The TMY (Typical Meteorological Year) for the solar energy study is generated using observation data with 22 solar sites from KMA (Korea Meteorological Administration) during 11 years (2000-2010). The meteorological data for calculation the TMY are used solar radiation, temperature, dew point temperature, wind speed and humidity data. And the TMY is calculated to apply the FS (Finkelstein and Schafer) statistics and RMSE (Root Mean Squared Error) methods. FS statistics performed with each point and each variable and then selected top five candidate TMM months with statistical analysis and normalization. Finally TMY is generated to select the highest TMM score with evaluation the average errors for the 22 whole points. The TMY data is represented average state and long time variations with 22 sites and meteorological data. When TMY validated with the 11-year daily solar radiation data, the correlation coefficient was about 0.40 and the highest value is 0.57 in April and the lowest value is 0.23 in May. Mean monthly solar radiation of TMY is 411.72 MJ which is 4 MJ higher than original data. Average correlation coefficient is 0.71, the lowest correlation is 0.43 in May and the highest correlation is 0.90 in January. Accumulated annual solar radiation by TMY have higher value in south coast and southwestern region and have relatively low in middle regions. And also, differences between TMY and 11-year mean of is distributed lower 100 MJ in Kyeongbuk, higher 200 MJ in Jeju and higher 125 MJ in Jeonbuk and Jeonnam, respectively.

• Journal of the Korean Wood Science and Technology
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• v.38 no.1
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• pp.66-74
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• 2010

This study was carried out to investigate the optimum condition for sap exudation of Acer mono Max. tree in a site of Mt. Baekun, Kwangyang city, Korea. Amount of sap exudation, air temperature, relative air humidity and tree diameter at breast height (DBH) were monitored for the period of January 5 through March 28, 2008, and correlation analysis of several factors affecting on sap exudation was carried out. As the diameter of Acer mono at breast height increased, the amount of sap was linearly proportional. Sap exudation initiated at February 18, and occurred intensively in the period of February 28 through March 10, resulting in 84% of total sap amount by volume. During sap exudation, the minimum temperature was averaged at $-2.4{\pm}1.5^{\circ}C$ and the maximum at $6.0{\pm}1.8^{\circ}C$, while there was no sap exudation whenever temperature was below or above $0^{\circ}C$ all the day long. The maximum temperature, range of temperature and the maximum, minimum and mean humidities in air were significant factors affecting on amount of sap. The maximum air temperature had the highest correlation coefficient with 0.768 (P < 0.01) and was also considered as the principal factor by partial-correlation analysis. These results showed that sap exudation required daily air-temperature fluctuation from below to above $0^{\circ}C$, and the amount of sap was strongly dependent on the highest daily-temperature and DBH of tree.