• Journal of the Korean Society of Safety
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• v.29 no.2
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• pp.98-105
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• 2014

Biosafety has become quite sensitive issues according to dramatic development of biotechnology and LMO(Living Modifying Organism) is one of the key issue in biosafety. This study is an exploratory research for investigating the activation strategy of biosafety training management in LMO research field. Based on the survey data, main results are derived through various statistical analysis methodology such as descriptive analysis, factor analysis, reliability analysis, analysis of variance and regression analysis. According to the analysis results, some activation strategies are required to reach the target such as extension of specialized biosafety training program, enhancement of safety consciousness from the undergraduate courses, introduction of appropriate safety regulations, unification of safety management and establishment of safety management system.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.1
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• pp.53-67
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• 1996

The dynamic characteristics of mechanical structure are strongly affected by the properties of joint parameters. In this study, the test structures are constructed with two beams which are clamped by bolts, and a bolted joint which is modelled as a lumped stiffness element. To idientify the dynamic joint parameters with variance of clamping torque of bolts, the sensitivity analysis and the mode energy analysis methods are investigated experimentally. As a reult of these two methods, stiffnesses of bolted joint are experimentally found to increase as the clamping torque increases. These stiffnesses identified from the sensitivity analysis and the mode energy analysis method have some difference.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.477-481
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• 2007

The purpose of this study is to provide the ideal forecasting model of cadastral survey work load through the Economeatric Analysis of Time Series, Granger Causality and VAR Model Analysis, it suggested the forecasting reference materials for the total amount of cadastral survey general work load. The main result is that the derive of the environment variables which affect cadastral survey general work load and the outcome of VAR(vector auto regression) analysis materials(impulse response function and forecast error variance decomposition analysis materials), which explain the change of general work load depending on altering the environment variables. And also, For confirming the stability of time series data, we took a unit root test, ADF(Augmented Dickey-Fuller) analysis and the time series model analysis derives the best cadastral forecasting model regarding on general cadastral survey work load. And also, it showed up the various standards that are applied the statistical method of econometric analysis so it enhanced the prior aggregate system of cadastral survey work load forecasting.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.7
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• pp.3145-3149
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• 2014

Gene expression profiling facilitates the understanding of biological characteristics of gliomas. Previous studies mainly used regression/variance analysis without considering various background biological and environmental factors. The aim of this study was to investigate gene expression differences between grade III and IV gliomas through partial least squares (PLS) based analysis. The expression data set was from the Gene Expression Omnibus database. PLS based analysis was performed with the R statistical software. A total of 1,378 differentially expressed genes were identified. Survival analysis identified four pathways, including Prion diseases, colorectal cancer, CAMs, and PI3K-Akt signaling, which may be related with the prognosis of the patients. Network analysis identified two hub genes, ELAVL1 and FN1, which have been reported to be related with glioma previously. Our results provide new understanding of glioma pathogenesis and prognosis with the hope to offer theoretical support for future therapeutic studies.

• Journal of the Korean Society for Railway
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• v.11 no.6
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• pp.543-549
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• 2008

The ride comfort is more important according to train speedup. Generally it is defined as the vehicle vibration. There are many studies on evaluation method of ride comfort for railway. But the ride comfort for Korean high speed train (HSR 350x) has been assessed by statistical method according to UIC 5l3R. In this paper, the ride indices, which were measured in the Korean high speed train. have been analyzed and reviewed by using the inferential statistics such as t-test, variance analysis (ANOVA) and regression analysis.

• Fashion & Textile Research Journal
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• v.10 no.4
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• pp.499-505
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• 2008

The Purpose of this study is to research the relations between brand attachment and brand loyalty depending on symbolic consumption propensity toward fashion goods. Subjects were 391 women in their twenties to fifties who live in Gyungsang Province and have purchased the fashion goods. Frequency analysis, reliability analysis, factor analysis, multiple regression analysis, and one-way layout variance analysis were conducted using SPSS 13.0 as data analysis. The findings from the analysis are described in the following: Uniqueness and materialism out of the symbolic consumption propensity toward fashion goods had positive effects on the elements of brand attachment such as love, care, and knowledge. Brand loyalty was influenced positively by social face sensitivity and materialism among symbolic consumption toward fashion goods.

• International Commerce and Information Review
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• v.12 no.1
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• pp.153-175
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• 2010

This study conducts an analysis to verify an existence of co-movement among the exchange rates of Yuan-Dollar, Yen-Dollar and Won-Dollar by using time series data. An analysis period is divided into two periods. Therefore the first analysis period is from Dec. 17, 1997 to Jul. 21th. 20, 2005 and the second analysis period is from Jul. 25th, 2005 to Nov. 20th. 2009. This paper uses VAR model and daily data of exchange rates during the period. According to the result of an empirical analysis, yuan-dollar exchange rate has affected by th other variables ; yen-dollar exchange rate. It can be proved by result of an impulse response test and variance decomposition test in the second period. Therefore the won-dollar, yen-dollar, and Yen-dollar exchange rate has been influenced each other and the relationship will be maintained.

• Communications for Statistical Applications and Methods
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• v.31 no.1
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• pp.1-35
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• 2024

The assumption of homoscedasticity is one of the most crucial assumptions for many parametric tests used in the biological sciences. The aim of this paper is to compare the empirical probability of type I error and the power of ten parametric and two non-parametric tests for homoscedasticity with simulations under different types of distributions, number of groups, number of samples per group, variance ratio and significance levels, as well as through empirical data from an agricultural experiment. According to the findings of the simulation study, when there is no violation of the assumption of normality and the groups have equal variances and equal number of samples, the Bhandary-Dai, Cochran's C, Hartley's Fmax, Levene (trimmed mean) and Bartlett tests are considered robust. The Levene (absolute and square deviations) tests show a high probability of type I error in a small number of samples, which increases as the number of groups rises. When data groups display a nonnormal distribution, researchers should utilize the Levene (trimmed mean), O'Brien and Brown-Forsythe tests. On the other hand, if the assumption of normality is not violated but diagnostic plots indicate unequal variances between groups, researchers are advised to use the Bartlett, Z-variance, Bhandary-Dai and Levene (trimmed mean) tests. Assessing the tests being considered, the test that stands out as the most well-rounded choice is the Levene's test (trimmed mean), which provides satisfactory type I error control and relatively high power. According to the findings of the study and for the scenarios considered, the two non-parametric tests are not recommended. In conclusion, it is suggested to initially check for normality and consider the number of samples per group before choosing the most appropriate test for homoscedasticity.

• Structural Monitoring and Maintenance
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• v.6 no.4
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• pp.317-346
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• 2019

Performance assessment of pavements proves useful, in terms of handling the ride quality, controlling the travel time of vehicles and adequate maintenance of pavements. Roughness profiles provide a good measure of the deteriorating condition of the pavement. For the accurate estimates of pavement roughness from dynamic vehicle responses, vehicle parameters should be known accurately. Information on vehicle parameters is uncertain, due to the wear and tear over time. Hence, condition monitoring of pavement requires the identification of pavement roughness along with vehicle parameters. The present study proposes a scheme which estimates the roughness profile of the pavement with the use of accurate estimates of vehicle parameters computed in parallel. Pavement model used in this study is a two-layer Euler-Bernoulli beam resting on a nonlinear Pasternak foundation. The asphalt topping of the pavement in the top layer is modeled as viscoelastic, and the base course bottom layer is modeled as elastic. The viscoelastic response of the top layer is modeled with the help of the Burgers model. The vehicle model considered in this study is a half car model, fitted with accelerometers at specified points. The identification of the coupled system of vehicle-pavement interaction employs a coupled scheme of an unbiased minimum variance estimator and an optimization scheme. The partitioning of observed noisy quantities to be used in the two schemes is investigated in detail before the analysis. The unbiased minimum variance estimator (MVE) make use of a linear state-space formulation including roughness, to overcome the linearization difficulties as in conventional nonlinear filters. MVE gives estimates for the unknown input and fed into the optimization scheme to yield estimates of vehicle parameters. The issue of ill-posedness of the problem is dealt with by introducing a regularization equivalent term in the objective function, specifically where a large number of parameters are to be estimated. Effect of different objective functions is also studied. The outcome of this research is an overall measure of pavement condition.

• Journal of Korean Academy of Nursing
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• v.27 no.4
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• pp.901-911
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• 1997

The purpose of this study is to provide a basis for nursing intervention strategies to promote quality of life in cancer patients. Therefore the study is designed to evaluate the effectiveness of perceived health status, self-esteem, health locus of control, self-efficacy, perceived susceptibility /severity, health promoting behaviors, and hope for quality of life. The sample was composed of 164 stomach cancer patients who visited outpatient clinics at a university hospital in Seoul. The following instruments were used in the study after some adaptation : Lawstone and others' Health Self-rating Scale, Rosenberg's Self-esteem Scale, Wallston and others 'Multidimensional Health Locus of Control Scale, Sherer & Maddux's Self-efficacy Scale, Moon's Health Beliefs Scale, Walker and others' Health Promoting Lifestyle Profile, Nowotney's Hope scale and Noh's Quality of Life Scale. Data were analyzed using a SAS program for Pearson correlation coefficients, descriptive correlational statistics and stepwise multiple regression. The results are as follows : 1. The scores on the quality of life scale ranged from 115 to 243 with a mean of 177.84(SD : 25.35). The mean scores(range 1-5) on the different dimensions were : emotional state 3.37 : economic life 3.47 : physical state & function 3.52 : self-esteem 3.66 : relationship with neighbors 3.37 ; family relationships 3.80. 2. There was a significant correlation between all the predictive variables and the quality of life (r=.20-.65, p<.01). 3. Stepwise multiple regression analysis showed that : 1) Self-esteem was the main predictor of quality of life and accounted for 46.9% of the variance in quality of life. 2) Perceived health status, hope and perceived susceptibility/severity accounted for 11.8%, 8.3%, 1.5% of the variance in quality of life, respectively. 3) Self-esteem, perceived health status, hope & perceived susceptibility /severity combined accounted for 68.5% of the variance in quality of life. In conclusion, self-esteem, perceived health status, hope and perceived susceptibility / severity were identified as important variables in the quality of life of cancer patients.