• The Korean Journal of Applied Statistics
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• v.25 no.1
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• pp.15-27
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• 2012

We have studied the realized variance(RV) of intra-day returns and market microstructure noise based on high-frequency stock transaction data for the four largest companies in terms of market capitalization in the KOSPI. First, non-negligible biases are observed for the RV and for the bias-corrected realized variance($RV_{AC_1}$) which is constructed by adjusting RV for the first order autocorrelation in intra-day returns. Bias is more obvious for the RV and the $RV_{AC_1}$ when intra-day returns are sampled more frequently than every 2 minutes. Transaction Time Sampling(TTS) is shown to be better than Calendar Time Sampling(CTS) in terms of biases of the RV and the $RV_{AC_1}$ for the 4 companies. The analysis reveals that market microstructure noise is temporally dependent. Second, by using the Noise-to-Signal Ratio(NSR), we estimate sampling frequencies that are optimal in terms of the Mean Square Errors(MSE) of the RV and the $RV_{AC_1}$. The optimal sampling frequencies are around 200 for RV and is around 5000 for the $RV_{AC_1}$ for all the four stock prices. For the 6 hour transaction period of the Korean stock trading, these correspond to about 2 minutes and 6 seconds.

• Structural Engineering and Mechanics
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• v.21 no.3
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• pp.255-273
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• 2005

Based on the random vibration theory, a response spectrum method is developed for seismic response analysis of linear, multi-degree-of-freedom structures under multi-support excitations is developed. Various response quantities, including the mean and variance of the peak response, the response mean frequency, are obtained from proposed combination rules in terms of the mean response spectrum. This method makes it possible to apply the response spectrum to the seismic reliability analysis of structures subjected to multi-support excitations. Considering that the tedious numerical integration is required to compute the spectral parameters and correlation coefficients in above combination rules, this paper further offers simplified procedures for their computation, which enhance dramatically the computational efficiency of the suggested method. The proposed procedure is demonstrated for tow numerical examples: (1) two-span continuous beam; (2) two-tower cabled-stayed bridge by using Monte Carlo simulation (MC). For this purpose, this paper also presents an approach to simulation of ground motions, which can take into account both mean and variation properties of response spectrum. Computed results based on the response spectrum method are in good agreement with Monte Carlo simulation results. And compared with the MSRS method, a well-developed multi-support response spectrum method, the proposed method has an incomparable computational efficiency.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.225-228
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• 2007

This paper presents a geostatistical methodology to model local uncertainty in spatial estimation of sediment grain size with high-resolution remote sensing imagery. Within a multi-Gaussian framework, the IKONOS imagery is used as local means both to estimate the grain size values and to model local uncertainty at unsample locations. A conditional cumulative distribution function (ccdf) at any locations is defined by mean and variance values which can be estimated by multi-Gaussian kriging with local means. Two ccdf statistics including condition variance and interquartile range are used here as measures of local uncertainty and are compared through a cross validation analysis. In addition to local uncertainty measures, the probabilities of not exceeding or exceeding any grain size value at any locations are retrieved and mapped from the local ccdf models. A case study of Baramarae beach, Korea is carried out to illustrate the potential of geostatistical uncertainty modeling.

• The Korean Journal of Rehabilitation Nursing
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• v.13 no.2
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• pp.123-131
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• 2010

Purpose: This study was aimed at identifying the levels of parenting stress among mothers of children with cerebral palsy and factors influencing parenting stress. Method: The research design was cross-sectional survey. Data were collected from 122 mothers of hospitalized children (under 15 years of age) with cerebral palsy at the Y medical center using the questionnaires. The data were analyzed using one way analysis of variance with Scheffe test for post-hoc analysis or t-test, Pearson correlation, and stepwise multiple regression. Results: The mean score of parenting stress was 2.52 (SD=0.79; range: 1~4). The father's participation, mother's parenting hours, self-esteem and social support were significant predictors of parenting stress, significantly accounting for the 33.3% variance (F=16.118, p<.001). Conclusion: It is essential for health professionals to consider the aforementioned four factors when developing interventions to reduce parenting stress for mothers of children with cerebral palsy.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2733-2746
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• 2018

The two inverse regression estimation methods, SIR and SAVE to estimate the central space are computationally easy and are widely used. However, SIR and SAVE may have poor performance in finite samples and need strong assumptions (linearity and/or constant covariance conditions) on predictors. The two non-parametric estimation methods, MAVE and dMAVE have much better performance for finite samples than SIR and SAVE. MAVE and dMAVE need no strong requirements on predictors or on the response variable. MAVE is focused on estimating the central mean subspace, but dMAVE is to estimate the central space. This paper explores and compares four methods to explain the dimension reduction. Each algorithm of these four methods is reviewed. Empirical study for simulated data shows that MAVE and dMAVE has relatively better performance than SIR and SAVE, regardless of not only different models but also different distributional assumptions of predictors. However, real data example with the binary response demonstrates that SAVE is better than other methods.

• Journal of Korean Society on Water Environment
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• v.39 no.4
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• pp.261-268
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• 2023

The benthic macroinvertebrates index (BMI) was developed based on the 5-day biochemical oxygen demand (BOD₅), which is the amount of biodegradable organic matter in stream water. However, benthic macroinvertebrates mainly live in the streambed substrate and are affected by the interaction of water quality and substrate. This study was conducted to examine the interactive relationship between water quality items (BOD₅, total phosphorus (TP), total suspended solids (TSS)) and substrate with BMI by performing statistical analyses (four-way analysis of variance, Pearson's correlation analysis, partial correlation analysis and multiple regression analysis). The data used in the analyses were collected from 19,915 sampling units at 1,937 sites in South Korea from 2010 to 2020. The interaction effect between BOD₅ and substrate types was confirmed through a four-way analysis of variance. Partial correlation analysis and multiple regression analysis estimated the degree of influence on the change in BMI value in the order of mean grain size of the substrate as (𝜱_m) > BOD₅ > TP > TSS. BMI can be regarded as an index that evaluates the comprehensive effects of water quality and streambed status, although it is an index that was developed based on the amount of biodegradable organic matter in a water column.

• Journal of Nutrition and Health
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• v.37 no.10
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• pp.917-927
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• 2004

This study was performed to examine component of variance in nutrient intakes and to estimate the level of accuracy with varying degree of precision in order to achieve estimates of usual nutrient intakes. Three-day dietary records including both weekdays and weekends were collected every 4 season over a I-year period from 36 males and 93 females aged 40 - 65 y. For each nutrient, we partitioned total intake variance into weekly (weekday vs weekend), seasonal, within- and between- individual variation as components of variance, using analysis of variance. It was found that major components of variance were within- and between-individual variation. Particularly, within-individual variation (57.2 - 87.1 %) was greater than between-individual variation (12.2 - 37.4%) for all nutrients. Weekly and seasonal variation contributed small components of variance for most nutrients. For protein, fat and carbohydrate, there were a little significant weekly variation (0.00 - 1.35%) in females but not in males. For some micronutrients, there were moderately significant seasonal variation (0.15 - 5.48%) in both sexes. Ratio of within- to between- individual variation ranged 1.4 (vitamin B$_2$) -4.5 (vitamin B$_1$) in males and 1.6 (carbohydrate) -2.9 (fat) in females. With total 12-day dietary records data, the maximum percentage deviation of observed intakes from usual (true) intakes ranged 12-37%. To estimate usual individual intakes within 20% of the true mean with 90% confidence level, 3 - 9 days of dietary survey were required for energy, protein, carbohydrate, phosphorus and iron, 13 - 19 days for fat and calcium, 25 - 29 days for vitamin A and vitamin C. Correlation coefficients between observed and true nutrient intakes were 0.71 - 0.91 for males, 0.81-0.91 for females. In conclusion, mean intakes of several nutrients can be reliably measured with the record method, using a limited number of days. Both nutrients of interest and the primary objectives should be taken account when planning method of assessment and number of replicates.

• Journal of Chest Surgery
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• v.27 no.10
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• pp.833-837
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• 1994

Lung contusion due to blunt chest trauma is the most common lung injury and correlated with the clinical course and prognosis. Its diagnosis by CT[Computerized Tomogram] gives a more clear and understandable three dimensional view, by which we are able to measure the volume of the contused and entire lung. Other variables are arterial blood gas, number of rib fracture, presence of hemopneumothorax, sternal fracture and clavicle fracture, number of associated non-thoracic injuries, ventilator time and presence of pulmonary complication. Percentage[%] of lung contusion are expressed as mean $\pm$ standard deviation and data analysis was performed by means of multivariate repeated measures analysis of variance to detect significant differences in variables between positive thoracic injury group and negative group. The paired t-test was used. Differences of percentage of lung contusion between groups were assessed by one-way analysis of variance. Simple linear regression was used to perform correlation analysis in the number of rib fracture and ventilator time. A p value less than 0.05 was considered statistically significant. Pneumothorax and the number of associated other injuries affect the amount of lung contusion and pulmonary complication group has more contused lung volume. Arterial blood gas study shows no correlation with the amount of lung contusion statistically. The number of rib fracture correlated with the amount of lung contusion, which also correlated with ventilator time[r=0.56, p<0.05]. In conclusion, quantitative anlysis of lung contusion by CT predicts the clinical course and treatment such as ventilator care.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.3
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• pp.263-274
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• 2020

In the Southeast Sea of Korea, a cold water mass is formed intensively in summer every year, causing frequent abnormal sea conditions. In order to analyze the spatial changes of sea surface temperature distribution in this area, ocean fields buoy data observed at Gori and Jeongja and reanalyzed sea surface temperature(SST) data from GHRSST Level 4 were used from June to September 2018. The buoy data were used to analyze the time-series water temperature changes at two stations, and the GHRSST data were used to calculate the daily SST variance and weighted mean center(WMC) across the study area. When the buoy's water temperature was lowered, the variance of SST in the study area trend to increase, but it did not appear consistently for the entire period. This is because GHRSST is a reanalysis data that does not reflect sensitive changes in water temperature along the coast. As such, there is a limit to grasping the local small-scale water temperature change in the coast or detecting the location and extent of the cold water zone only by the statistical variance representing the SST change in the entire sea area. Therefore, as a result of using WMC to quantitatively determine the spatial location of the cold water mass, when the cold water zone occurred, WMC was located in the northwest sea area from the mean center(MC) of the study area. This means that it is possible to quantitatively identify where and to what extent the distribution of cold surface water temperature appears through SST's WMC location information, and we could see the possibility of WMC's use in detecting the scale of cold water zones and the extent of regional spread in the future.

• Journal of Environmental Science International
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• v.15 no.12
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• pp.1125-1139
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• 2006

The cluster analysis of diurnal precipitation patterns is performed by using daily precipitation of 59 stations in South Korea from 1973 to 1996 in four seasons of each year. Four seasons are shifted forward by 15 days compared to the general ones. Number of clusters are 15 in winter, 16 in spring and autumn, and 26 in summer, respectively. One of the classes is the totally dry day in each season, indicating that precipitation is never observed at any station. This is treated separately in this study. Distribution of the days among the clusters is rather uneven with rather low area-mean precipitation occurring most frequently. These 4 (seasons)$\times$2 (wet and dry days) classes represent more than the half (59 %) of all days of the year. On the other hand, even the smallest seasonal clusters show at least $5\sim9$ members in the 24 years (1973-1996) period of classification. The cluster analysis is directly performed for the major $5\sim8$ non-correlated coefficients of the diurnal precipitation patterns obtained by factor analysis In order to consider the spatial correlation. More specifically, hierarchical clustering based on Euclidean distance and Ward's method of agglomeration is applied. The relative variance explained by the clustering is as high as average (63%) with better capability in spring (66%) and winter (69 %), but lower than average in autumn (60%) and summer (59%). Through applying weighted relative variances, i.e. dividing the squared deviations by the cluster averages, we obtain even better values, i.e 78 % in average, compared to the same index without clustering. This means that the highest variance remains in the clusters with more precipitation. Besides all statistics necessary for the validation of the final classification, 4 cluster centers are mapped for each season to illustrate the range of typical extremities, paired according to their area mean precipitation or negative pattern correlation. Possible alternatives of the performed classification and reasons for their rejection are also discussed with inclusion of a wide spectrum of recommended applications.