• The KSFM Journal of Fluid Machinery
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• v.2 no.3 s.4
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• pp.52-58
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• 1999

The leakage and rotordynamic coefficients of see-through type gas labyrinth seals are determined using a two-control-volume-model analysis with Moody's wall-friction-factor formula which is defined with a large range of Reynolds number and relative roughness. Jet flow theory are used for the calculation of the recirculation velocity in the cavity. For the reaction force from the labyrinth seal, linearized zeroth-order and the first-order perturbation equations are developed for small motion about a centered position. The leakage and rotordynamic coefficient results of the present analysis are compared with Scharrer's theoretical analysis using Blasius' wall-friction-factor formula and Pelletti's experimental results. The comparison shows that the present analysis using Moody's wall-friction-factor formula and Scharrer's theoretical analysis using Blasius' wall-friction-factor formula give the same results for a smooth seal surface and the range of Reynolds number less than $10^5$.

• Journal of Korean Society for Quality Management
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• v.30 no.2
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• pp.118-129
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• 2002

A multiple test of a mean parameter, λ, in the Poisson model is considered using the Bayes factor. Under noninformative improper priors, the intrinsic Bayes factor(IBF) of Berger and Pericchi(1996) and the fractional Bayes factor(FBF) of O'Hagan(1995) called as the default or automatic Bayes factors are used to select one among three models, M$_1$: λ< $λ_0, M$_2$: λ= $λ_0, M$_3$: λ> $λ_0. Posterior probability of each competitive model is computed using the default Bayes factors. Finally, theoretical results are applied to simulated data and real data.

• Explosives and Blasting
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• v.22 no.4
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• pp.1-6
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• 2004

In this study, dimension and scale factor of explosives were calculated. Proper dimension and scale factor were considered. Scale factor of 1/256 was obtained when scaled factor of the length was l/4. This value is similar to the ratio of explosives of model test and demolition structure. It seemed that scale factor of length should be larger than 1/4.

• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.211-216
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• 2021

This study intended to test the structure of the latent factor of a subjective happiness scale and the stability of invariance across groups of students' classifications (gender and students' status). In the large, non-clinical sample (619), students completed the subjective happiness scale. The (CFA) confirmatory factor analysis was used to investigate the factor-structure of the measure, and multiple-group confirmatory factor analysis (MGCFA) model was used to test the stability of invariance across groups of students classifications. The findings of the CFA indicated support for the original one-factor model. Additional analyses of the MGCFA method support the measurement (configural, metric and strong) invariant and practical invariant components of this model. There was an invariant across gender. There was partially invariant across groups of students' statuses. The scale exists in both groups to assess the same concepts of (single and married), excluding Items 3 and 4. Given that this study is the first investigation for the structure of the subjective happiness scale.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.149-156
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• 2021

This study intended to test the structure of the latent factor of an effectiveness scale and the stability of invariance across groups of students' classifications (gender and levels of education). In the large, non-clinical sample (850), students completed the effectiveness scale. The (CFA) confirmatory factor analysis was used to investigate the factor-structure of the measure, and multiple-group confirmatory factor analysis (MGCFA) model was used to test the stability of invariance across groups of students' classifications. The findings of the CFA indicated support for the original four-factor model. Additional analyses of the MGCFA method support the measurement (configural, metric and strong) invariant and practical invariant components of this model. There was an invariant across gender. There was partially invariant across groups of levels of education. The scale exists in groups of levels of education assess the same concepts of, excluding Items 15 and 10. Given that this study is the first investigation for the structure of the effectiveness scale.

• The Korean Journal of Applied Statistics
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• v.25 no.4
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• pp.553-561
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• 2012

Various statistical models to Estimate GDP (measured as a nation's economic situation) have been developed. In this paper an autoregressive distributed lag model, factor model, and a Bayesian VAR model estimate quarterly GDP as a single model; the combined estimates were evaluated to compare a single model. Subsequently, we suggest that some combined models are better than a single model to estimate quarterly GDP.

• Journal of Korean Society of Transportation
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• v.10 no.2
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• pp.25-42
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• 1992

The purpose of this paper is to construct a model to compute a progression adjustment factor on a signalized network. In a way to construct the model, a simulation method is introduced and the TRAF-NETSIM is used as a tool of simulation. The structure of the network chooses an urban arterial network so as to measure the effect of progression and compute average stopped delay on each link. A regression model is constructed by using the results of the simulation. The stepwise variable selection in the regression model in used. The findings of this paper are as follows: i)The secondary queue and platoon ratio are sensitive to the values of the progression adjustment factor ii) The continuous model can practically reflect on various situations in the real world. The platoon adjustment factor can be computed by this model and the data required for this model can be easily obtained in the field.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.847-855
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• 2009

While many studies on feasibility analysis for housing projects have been released, the main focus was on economic feasibility and factors related to developers were not clearly identified enough to be used in practice. In order to establish a feasibility analysis model for apartment development projects requested by developers in Korea, 31 driving factors behind projects' success were identified under seven different categories. Criterions of the each factor were also developed, and weight of each factor was assigned by applying the Analytical Hierarchy Process(AHP). Finally, based on the Monte Carlo simulation, the feasibility analysis model was established, providing probability distribution of project's grade. The model was applied to 12 housing projects to verify its reliability, and found that the model properly filtered projects that are unlikely to be profitable, indicating reasonable reliability of the model. The model can be a useful tool for contractors, especially with less experience in analyzing project development feasibility.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.6
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• pp.55-65
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• 2019

Universal Soil Loss Equation (USLE) is to estimate potential soil loss and has benefit in use with its simplicity. The equation is composed of five factors, one of the factors is the slope length and steepness factor (LS factor) that is for topographic property of fields to estimate potential soil loss. Since the USLE was developed, many equations to compute LS was suggested with field measurement. Nowadays the factor is often computed in GIS software with digital elevation model, however it was reported that the factor is very sensitive to the resolution of digital elevation model. In addition, the digital elevation model of high resolution less than 3 meter is required in small field application, however these inputs are not associate with the empirical models' backgrounds since the empirical models were derived in 22.1 meter field measurements. In the study, four equation to compute LS factor and two approaches to determine slope length and steepness were examined, and correction factor was suggested to provide reasonable precision in LS estimations. The correction factor is computed with field area and cell size of digital elevation model, thus the correction factor can be adapted in any USLE-based models using LS factor at field level.

• The Journal of Information Systems
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• v.30 no.3
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• pp.159-175
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• 2021

Purpose The purpose of this study was to find the effect of the determinants on the Big data utilization in industry. The determinants of Big data utilization were deduced by reviewing theoretical background and discussions on Big data related researches. Research model and proposed hypothesis were constructed from TOE framework and UTAUT model. Design/methodology/approach The research was conducted to collect a sample data from the experts involved in the Big data projects in industry. In addition, interviews and online survey were performed to get sample data. Exploratory factor analysis was conducted to verify the grouping of these questionnaire items and confirmatory factor analysis was done to verify the validity and reliability of the measurement model. Finally, research hypothesis was verified and theoretical and practical implications were proposed for further studies. Findings The results show that the technical factor have a significant effect on the expectancy factor and the behavioral factor. The organizational factor have a significant effect on the behavioral factor. In addition, the expectancy factor was significant on the behavioral factor and the intention-to-use of Big data system.