• 한국도로학회논문집
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• 제17권3호
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• pp.117-124
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• 2015

PURPOSES : The purpose of this study is to verify traffic accident injury severity factors for elderly drivers and the relative relationship of these factors. METHODS : To verify the complicated relationship among traffic accident injury severity factors, this study employed a structural equation model (SEM). To develop the SEM structure, only the severity of human injuries was considered; moreover, the observed variables were selected through confirmatory factor analysis (CFA). The number of fatalities, serious injuries, moderate injuries, and minor injuries were selected for observed variables of severity. For latent variables, the accident situation, environment, and vehicle and driver factors were respectively defined. Seven observed variables were selected among the latent variables. RESULTS : This study showed that the vehicle and driver factor was the most influential factor for accident severity among the latent factors. For the observed variable, the type of vehicle, type of accident, and status of day or night for each latent variable were the most relative observed variables for the accident severity factor. To verify the validity of the SEM, several model fitting methods, including ${\chi}^2/df$, GFI, AGFI, CFI, and others, were applied, and the model produced meaningful results. CONCLUSIONS : Based on an analysis of results of traffic accident injury severity for elderly drivers, the vehicle and driver factor was the most influential one for injury severity. Therefore, education tailored to elderly drivers is needed to improve driving behavior of elderly driver.

• 한국과학교육학회지
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• 제17권4호
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• pp.481-492
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• 1997

The purpose of this study is to construct validity of Tripartite model of "Attitudes towards Science" using Exploratory and Confirmatory Factor Analyses. Exploratory and confirmatory factor analyses are two major approaches to factor analysis. The primary goal of factor analysis is to explain the covariances or correlations between many observed variables by means of relatively few underlying latent variables. In exploratory factor analysis, the number of latent variables is not determined before the analysis, all latent variables typically influence all observed variables, the measurement errors(${\delta}$) are not allowed to correlate, and unidentification of parameters is common. Confirmatory factor analysis requires a detailed and identified initial model. Confirmatory factor analysis techniques allow relations between latent and observed variables that are not possible with traditional, exploratory factor analysis techniques. As a result of exploratory factor analysis, tripartite model of "Attitudes towards Science" being composed of affection, behavioral intention and cognition is empirically identified. But attitude of science career being composed of affection and behavioral intention is identified. In validity test using confirmatory factor analysis, measurement structure of Tripartite model of "Attitudes towards Science" is not correspondent to data set. Because it is concluded that the object of attitudes are not specific.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.160-160
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• 2023

Generally, Global Climate Models (GCM) cannot be used directly due to their inherent error arising from over or under-estimation of climate variables compared to the observed data. Several bias correction methods have been devised to solve this problem. Most of the traditional bias correction methods are one dimensional as they bias correct the climate variables separately. One such method is the Quantile Mapping method which builds a transfer function based on the statistical differences between the GCM and observed variables. Laux et al. introduced a copula-based method that bias corrects simulated climate data by employing not one but two different climate variables simultaneously and essentially extends the traditional one dimensional method into two dimensions. but it has some limitations. This study uses objective functions to address specifically, the limitations of Laux's methods on the Quantile Mapping method. The objective functions used were the observed rank correlation function, the observed moment function and the observed likelihood function. To illustrate the performance of this method, it is applied to ten GCMs for 20 stations in South Korea. The marginal distributions used were the Weibull, Gamma, Lognormal, Logistic and the Gumbel distributions. The tested copula family include most Archimedean copula families. Five performance metrics are used to evaluate the efficiency of this method, the Mean Square Error, Root Mean Square Error, Kolmogorov-Smirnov test, Percent Bias, Nash-Sutcliffe Efficiency and the Kullback Leibler Divergence. The results showed a significant improvement of Laux's method especially when maximizing the observed rank correlation function and when maximizing a combination of the observed rank correlation and observed moments functions for all GCMs in the validation period.

• 한국도로학회논문집
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• 제15권5호
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• pp.31-45
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• 2013

PURPOSES : Determination of particle packing model variables that can be used for formulation of new DEM based particle packing model by examining existing particle packing models METHODS : Existing particle packing models are thoroughly examined by analytical reformulation and sensitivity analysis in order to set up DEM based new particle packing model and to determine its variables. All model equations considered in this examination are represented with consistent expressions and are compared to each others to find mathematical and conceptual similarity in expressions. RESULTS : From the examination of existing models, it is observed that the models are very similar in their shapes although the derivation of the models may be different. As well, it is observed that variables used in some existing models are comprehensive enough to estimate particle packing but not applicable to DEM simulation. CONCLUSIONS : A set of variables that can be used in DEM based particle packing model is determined.

• 환경영향평가
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• 제20권6호
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• pp.891-905
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• 2011

Climate vulnerability index is usually defined as a function of the climate exposure, sensitivity, and adaptive capacity, which requires adequate selection of proxy variables of each variable. We selected and used 9 proxy variables related to climate exposure in the literature, and diagnosed the adequacy of them for application in Korean peninsula. The selected proxy variables are: four variables from temperature, three from precipitation, one from wind speed, and one from relative humidity. We collected climate data over both previous year (1981~2010) and future climate scenario (A1B scenario of IPCC SERES) for 2020, 2050, and 2100. We introduced the spatial and temporal diagnostic statistical parameters, and evaluated both spatial and time variabilities in the relative scale. Of 9 proxy variables, effective humidity indicated the most sensitive to climate change temporally with the biggest spatial variability, implying a good proxy variable in diagnostics of climate change vulnerability in Korea. The second most sensitive variable is the frequency of strong wind speed with a decreasing trend, suggesting that it should be used carefully or may not be of broad utility as a proxy variable in Korea. The A1B scenario of future climate in 2020, 2050 and 2100 matches well with the extension of linear trend of observed variables during 1981~2010, indicating that, except for strong wind speed, the selected proxy variables can be effectively used in calculating the vulnerability index for both past and future climate over Korea. Other local variabilities for the past and future climate in association with climate exposure variables are also discussed here.

• 말소리와 음성과학
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• 제8권3호
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• pp.67-78
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• 2016

This study examined the affective prosodic characteristics observed from the children with cochlear implant (CI, hereafter) and normal hearing (NH, hereafter) along with listener's perception on them. Speech samples were acquired from 15 normal and 15 CI children. 8 SLPs(Speech Language Pathologists) perceptually evaluated affective types using Praat's ExperimentMFC. When it comes to the acoustic results, there were statistically meaningful differences between 2 groups in affective types [joy (discriminated by intensity deviation), anger (by intensity-related variables dominantly and duration-related variables partly), and sadness (by all aspects of prosodic variables)]. CI's data are much more louder when expressing joy, louder and slower when expressing anger, and higher, louder, and slower when it comes to sadness than those of NH. The listeners showed much higher correlation when evaluating normal children than CI group(p<.001). Chi-square results revealed that listeners did not show coherence at CI's utterance, but did at those of NH's (CI(p<.01), normal(p=.48)). When CI utterances were discriminated into 3 emotional types by DA(Discriminant Analysis) using 8 acoustic variables, speed related variables such as articulation rate took primary role.

• 대한가정학회지
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• 제37권6호
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• pp.123-138
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• 1999

The purpose of this study was to find out whether home environmental variables had a greater effect on adolescents' violence against parents. The results of self-reporting questionnaires are as follows ; The victims of violence are mainly mothers. The socio-economic status didn't influence on the degree of violence against parents. The adolescents of the extreme family type used more serious violent behavior. The higher the degree of observed and experienced violence is, the higher the degree of violence against parents. Also, the higher the degree of home education is, the lower the degree of violence against parents. Of all variables, the observed violence and structure-environmental variables account for 37.6% of adolescents' violence against parents. The results of in-depth interview showed that birth-order didn't affect violence against parents. The victims of violence were mainly stepmothers and stepfathers. These parents' educational attitudes were disagreement in parents, seriously inflicted corporal punishment and were indifferent to adolescent. Also, interviewed adolescents were observed and experienced violence in home and used violence against others.

• 말소리와 음성과학
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• 제3권4호
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• pp.85-91
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• 2011

Sasang constitution medicine utilizes voice characteristics to diagnose a person's constitution. To classify Sasang constitutional groups using speech information technology, this study aims at establishing the relationship between Sasang constitutional groups and their corresponding voice characteristics by investigating various speech feature variables. The speech variables include features related to speech source and vocal tract filter. Experimental results show that statistically significant correlation between voice characteristics and some speech feature variables is observed.

• Journal of Ecology and Environment
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• 제36권3호
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• pp.193-204
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• 2013

Altitudinal patterns of plant species richness and the effects of area, the mid-domain effect, climatic variables, net primary productivity and latitude on observed richness patterns along the ridge of the Baekdudaegan Mountains, South Korea were studied. Data were collected from 1,100 plots along a 200 to 1,900 m altitudinal gradient on the ridge. A total of 802 plant species from 97 families and 342 genera were recorded. Common and rare species accounted for 91% and 9%, respectively, of the total plant species. The altitudinal patterns of species richness for total, common and rare plants showed distinctly hump-shaped patterns, although the absolute altitudes of the richness peaks varied somewhat among plant groups. The mid-domain effect was the most powerful explanatory variable for total and common species richness, whereas climatic variables were better predictors for rare plant richness. No effect of latitude on species richness was observed. Our study suggests that the mid-domain effect is a better predictor for wide-ranging species such as common species, whereas climatic variables are more important factors for range-restricted species such as rare species. The mechanisms underlying these richness patterns may reflect fundamental differences in the biology and ecology of different plant groups.

• Asian-Australasian Journal of Animal Sciences
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• 제27권12호
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• pp.1678-1683
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• 2014

This study considers a problem of genomic selection (GS) for adjacent genetic markers of Yorkshire pigs which are typically correlated. The GS has been widely used to efficiently estimate target variables such as molecular breeding values using markers across the entire genome. Recently, GS has been applied to animals as well as plants, especially to pigs. For efficient selection of variables with specific traits in pig breeding, it is required that any such variable selection retains some properties: i) it produces a simple model by identifying insignificant variables; ii) it improves the accuracy of the prediction of future data; and iii) it is feasible to handle high-dimensional data in which the number of variables is larger than the number of observations. In this paper, we applied several variable selection methods including least absolute shrinkage and selection operator (LASSO), fused LASSO and elastic net to data with 47K single nucleotide polymorphisms and litter size for 519 observed sows. Based on experiments, we observed that the fused LASSO outperforms other approaches.