• Atmosphere
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• v.19 no.4
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• pp.309-318
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• 2009

Vulnerability to heat was examined for populations of 6 major cities in South Korea (Seoul, Incheon, Daejeon, Gwangju, Daegu, and Busan). Daily excess mortality and maximum temperature from 1991 to 2005 were employed in this study. The results show that the standardized mortality increase associated with a $1^{\circ}C$ increase in daily maximum temperature above the city-specific threshold explains the heat acclimatization effect better than the threshold temperature itself. The estimated increase in mortality (standardized per 10 million population) associated with a $1^{\circ}C$ increase in temperature above the threshold is 4.8 in Incheon, 4.7 in Seoul, 4.3 in Daejeon, 2.8 in Gwangju, 2.4 in Daegu, and 1.5 in Busan, well reflecting the latitudinal locations and local climates of each city. Climate models project more frequent, more intense, and longer lasting heat waves in most land areas in both hemispheres in the 21st century under increasing greenhouse gas concentrations. In order to mitigate the adverse human health impacts due to excess heat, more detailed characteristics of acclimatization to heat need to be understood and quantified.

• Korean Journal of Otorhinolaryngology-Head and Neck Surgery
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• v.62 no.2
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• pp.75-81
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• 2019

The objective of this study was to perform a systematic review of the literature for application of intranasal sodium citrate in the patients with olfactory dysfunction to help determine the sodium citrate treatments for this condition. Two authors independently searched the data base (Medline, Scopus, and the Cochrane database) for relevant studies from inception to January 2018. Included studies were randomized controlled studies published in English comparing topical sodium citrate application (treatment group) with saline (control group) in patients who had olfactory dysfunction. Outcomes of interest included the change of olfactory identification and threshold during 2 hours post-treatment. Three studies were enrolled in the meta-analysis. Compared with control group, treatment group did not increase posttreatment score of olfactory identification [standardized mean difference (SMD)=-0.03; 95% confidence interval (CI)=-0.29-0.24; I²=0%] and olfactory threshold (SMD=0.18; 95% CI=-0.09-0.45; I²=0%) significantly. In the degree of pre-post improvement of two outcomes, although treatment group statistically showed the significant improvement in olfactory threshold (SMD=0.30; 95% CI=0.05-0.55; I²=17%), the clinical significance of this outcome was meaningless. Similarly, there was no significant difference in olfactory identification between two groups (SMD=0.17; 95% CI=-0.11-0.45; I²=22%). Unlike the recent favorable results, our summated results presented the uselessness for the local application of sodium citrate in improving patient's olfactory function. However, we also had some limitation such as small sample size and inconsistent application methods. Therefore, larger trials and standardized methodology are needed to reach more stronger and exact results.

• Journal of Environmental Science International
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• v.18 no.7
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• pp.767-780
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• 2009

This study investigates the standard, duration period and excess mortality of extreme heat using the standardized daily mortality data from 1991 to 2004, establishing a standard threshold Criteria for Heat Health Watch Warning System in Korea. It ultimately aims to provide the guidance in building up Heat Health Watch Warning System for Korea by suggesting the standard to quantify thermal stress from heat. The standard threshold Criteria for Heat Health Watch Warning System for Seoul metropolitan city takes into account both daily maximum temperature and daily maximum heat index(HI) and consists of four phases; caution, extreme caution, danger, and extreme danger. Extreme caution phase and danger phase are used as the advisory and warning of extreme heat, respectively. Since the nationwide distribution of the frequency of extreme heat day and the excess mortality rate shows little difference across regions, the standard threshold Criteria for Heat Health Watch Warning System for Seoul metropolitan city can be used for other regions.

• Journal of Korean Society for Quality Management
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• v.33 no.3
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• pp.126-134
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• 2005

This paper proposes a selectively cumulative sum(S-CUSUM) control chart for detecting shifts in the process mean. The basic idea of the S-CUSUM chart is to accumulate previous samples selectively in order to increase the sensitivity. The S-CUSUM chart employs a threshold limit to determine whether to accumulate previous samples or not. Consecutive samples with control statistics out of the threshold limit are to be accumulated to calculate a standardized control statistic. If the control statistic falls within the threshold limit, only the next sample is to be used. During the whole sampling process, the S-CUSUM chart produces an 'out-of-control' signal either when any control statistic falls outside the control limit or when L -consecutive control statistics fall outside the threshold limit. The number L is a decision variable and is called a 'control length'. A Markov chain approach is employed to describe the S-CUSUM sampling process. Formulae for the steady state probabilities and the Average Run Length(ARL) during an in-control state are derived in closed forms. Some properties useful for designing statistical parameters are also derived and a statistical design procedure for the S-CUSUM chart is proposed. Comparative studies show that the proposed S-CUSUM chart is uniformly superior to the CUSUM chart or the Exponentially Weighted Moving Average(EWMA) chart with respect to the ARL performance.

• Journal of The Korean Society of Agricultural Engineers
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• v.46 no.7
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• pp.15-21
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• 2004

This study is to present a standardized agricultural land use classification scheme at various spatial resolution (from 1 m to 30 m) of satellite images including Landsat TM, KOMPSAT-1 EOC, ASTER VNIR and IKONOS panchromatic (PAN) and multi-spectral (MS) images. The satellite images were interpreted especially for identifying agricultural land use, crop types, agricultural facilities and structures of 18 items. It was found that there is a threshold spatial resolution between 4 m and 6.6 m to identify the full items. Thus it is suggested that IKONOS fusion image (MS enhanced by PAN) is required to produce land use map for agricultural purpose.

• Proceedings of the KSRS Conference
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• v.1
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• pp.200-203
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• 2006

Cloud detection algorithm is being developed as major one of the 16 baseline products of CMDPS (COMS Meteorological Data Processing System), which is under development for the real-time application of data will be observed from COMS Meteorological Imager. For cloud detection from satellite data, we studied two different algorithms. One is threshold technique based algorithm, which is traditionally used, and another is artificial neural network model. MPEF scene analysis algorithm is the basic idea of threshold cloud detection algorithm, and some modifications are conducted for COMS. For the neural network, we selected MLP with back-propagation algorithm. Prototype software of each algorithm was completed and evaluated by using the MTSAT-1R and GOES-9 data. Currently the software codes are standardized using Fortran90 language. For the preparation as an operational algorithm, we will setup the validation strategy and tune up the algorithm continuously. This paper shows the outline of the two cloud detection algorithm and preliminary test result of both algorithms.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.367-372
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• 2006

Cloud detection algorithm is being developed as primary one of the 16 baseline products of CMDPS (COMS Meteorological Data Processing System), which is under development for the real-time application of data will be observed from COMS Meteorological Imager. For cloud detection from satellite data, we studied two different algorithms. One is threshold technique based algorithm, which is traditionally used, and another is artificial neural network model. MPEF scene analysis algorithm is the basic idea of threshold cloud detection algorithm, and some modifications are conducted for COMS. For the neural network, we selected MLP with back-propagation algorithm. Prototype software of each algorithm was completed and evaluated by using the MTSAT-IR and GOES-9 data. Currently the software codes are standardized using Fortran90 language. For the preparation as an operational algorithm, we will setup the validation strategy and tune up the algorithm continuously. This paper shows the outline of the two cloud detection algorithms and preliminary test results of both algorithms.

• Journal of Korea Water Resources Association
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• v.49 no.10
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• pp.877-885
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• 2016

In this study, the Standard Precipitation Index(SPI), meteorological drought index, was used to evaluate the temporal and spatial assessment of drought forecasting results for all cross Korea. For the drought forecasting, the Multi Layer Perceptron-Artificial Neural Network (MLP-ANN) was selected and the drought forecasting was performed according to different forecasting lead time for SPI (3) and SPI (6). The precipitation data observed in 59 gaging stations of Korea Meteorological Adminstration (KMA) from 1976~2015. For the performance evaluation of the drought forecasting, the binary classification confusion matrix, such as evaluating the status of drought occurrence based on threshold, was constituted. Then Receiver Operating Characteristics (ROC) score and F score according to conditional probability are computed. As a result of ROC analysis on forecasting performance, drought forecasting performance, of applying the MLP-ANN model, shows satisfactory forecasting results. Consequently, two-month and five-month leading forecasts were possible for SPI (3) and SPI (6), respectively.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.4
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• pp.457-468
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• 2007

This paper proposes an adaptive moving average (A-MA) control chart with variable sampling intervals (VSI) for detecting shifts in the process mean. The basic idea of the VSI A-MA chart is to adjust sampling intervals as well as to accumulate previous samples selectively in order to increase the sensitivity. The VSI A-MA chart employs a threshold limit to determine whether or not to increase sampling rate as well as to accumulate previous samples. If a standardized control statistic falls outside the threshold limit, the next sample is taken with higher sampling rate and is accumulated to calculate the next control statistic. If the control statistic falls within the threshold limit, the next sample is taken with lower sampling rate and only the sample is used to get the control statistic. The VSI A-MA chart produces an 'out-of-control' signal either when any control statistic falls outside the control limit or when L-consecutive control statistics fall outside the threshold limit. The control length L is introduced to prevent small mean shifts from being undetected for a long period. A Markov chain model is employed to investigate the VSI A-MA sampling process. Formulae related to the steady state average time-to signal (ATS) for an in-control state and out-of-control state are derived in closed forms. A statistical design procedure for the VSI A-MA chart is proposed. Comparative studies show that the proposed VSI A-MA chart is uniformly superior to the adaptive Cumulative sum (CUSUM) chart and to the Exponentially Weighted Moving Average (EWMA) chart, and is comparable to the variable sampling size (VSS) VSI EWMA chart with respect to the ATS performance.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.560-570
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• 2006

This paper proposes a selectively cumulative sum (S-CUSUM) control chart with variable sampling intervals (VSI) for detecting shifts in the process mean. The basic idea of the VSI S-CUSUM chart is to adjust sampling intervals and to accumulate previous samples selectively in order to increase the sensitivity. The VSI S-CUSUM chart employs a threshold limit to determine whether to increase sampling rate as well as to accumulate previous samples or not. If a standardized control statistic falls outside the threshold limit, the next sample is taken with higher sampling rate and is accumulated to calculate the next control statistic. If the control statistic falls within the threshold limit, the next sample is taken with lower sampling rate and only the sample is used to get the control statistic. The VSI S-CUSUM chart produces an 'out-of-control' signal either when any control statistic falls outside the control limit or when L-consecutive control statistics fall outside the threshold limit. The number L is a decision variable and is called a 'control length'. A Markov chain model is employed to describe the VSI S-CUSUM sampling process. Some useful formulae related to the steady state average time-to signal (ATS) for an in-control state and out-of-control state are derived in closed forms. A statistical design procedure for the VSI S-CUSUM chart is proposed. Comparative studies show that the proposed VSI S-CUSUM chart is uniformly superior to the VSI CUSUM chart or to the Exponentially Weighted Moving Average (EWMA) chart with respect to the ATS performance.