• Journal of Korean Society of Transportation
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• v.35 no.6
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• pp.481-498
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• 2017

Travel time reduction benefit is the most important benefit item in the feasibility study of transportation infrastructure investment projects and calculated by using the value of travel time. The current feasibility study guideline (5th edition) calculate the value of non-business ravel time in a metropolitan area, using the ratio of the value of non-business travel time to business travel time calculated based on the nationwide inter-regional traffic survey data of 1999. The characteristics of metropolitan trips are different from those of nationwide regional trips. Metropolitan trips have frequent transfers between multiple public transits and long-time commuter trips. Therefore, this research aims to calculate the value of travel time reflecting traffic characteristics in a metropolitan area by improving the limitation of current calculation methods. To reflect these characteristics, this research extracts commuter trips from non-business trips and calculates the value of travel time for commuter trips. The results of the likelihood ratio test for the commuter trip model and the non-business trip model are found to be statistically significant. An integrated public transportation model was also estimated in this study to reflect the trip conditions of the Seoul metropolitan area integrated fare system. The results of comparing coefficients between bus and subway in the integrated public transit model indicated that there were no statistically significant differences between the two modes.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.543-546
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• 2000

Static and dynamic experiments were done to study on the restitution behaviors of strings. The elastic and viscoelastic model were compared. To apply a linear viscoelastic model (Kelvin model) to longitudinal behaviors of strings, static and dynamic tensile tests were done. Using their results, it should be intended to acquire damped stress (Stress related to velocity), and to calculate the viscoelastic coefficient. Fixing both ends, string was pushed by the loadcell attached to the tensile tester. The experimental results were in accordance with the calculated results using the Kelvin model acquired from the results of longitudinal tensile test. But the results of falling mass experiments, the behaviors of strings were near to elastic model. The clamping condition of strings in both sides has an effected on the value of COR. The smaller contact area, the grower the value of COR.

• Journal of computational fluids engineering
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• v.2 no.2
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• pp.1-8
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• 1997

Two versions of anisotropic k-ε turbulence model are incorporated in the modified k-ε model of Sohn et al. to avoid the need for the experimental normal stress value in the model and applied to convergent and divergent flows with strong and adverse pressure gradients in the plane of symmetry of a body of revolution. The models are the nonlinear k-ε model of Speziale and the anisotropic model of Nisizima & Yoshizawa. All of the models yield satisfactory results for relatively complex flow on a plane-of-symmetry boundary layer. The results of the models are compared with those results of experimental normal stress value.

• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.11
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• pp.1482-1494
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• 2004

This study identified convergent validity and discriminant validity of measurement variables by factor analysis using Spss program and tested covariance measurement model including latent variables such as the website attributes (interactivity, search and visual information of website), shopping values(utilitarian and hedonic value) and attitude toward website by AMOS program. The data were collected from a sample of 271 internet shopper of university students(male: 82, female: 189). They visited the website for apparel shopping and, after searching a casual clothing which they wanted to buy, requested to answer the questionnaire. The results were as follows: Variables that reduce validity were deleted in the several steps of factor analysis and initial measurement model testing. Final measurement model was constructed by valid variables was accepted. This measurement model will be input for testing causal research model that can explain how attributes of the website influences on consumer attitude toward the website.

• Health Policy and Management
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• v.12 no.3
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• pp.54-76
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• 2002

This study investigated how much EVA which evaluate firm's value can explain hospital bankruptcy prediction as a explanatory variable including financial indicators in Korea. In this study, artificial neural network and logit regression which are traditional statistical were used as the model for bankruptcy prediction. Data used in this study were financial and economic value added indicators of 34 bankrupt and -:4 non-bankrupt hospitals from the Database of Korean Health Industry Development Institute. The main results of this study were as follows: First, there was a significant difference between the financial variable model including EVA and the financial variable model excluding EVA in pre-bankruptcy analysis. Second, EVA could forecast bankruptcy hospitals up to 83% by the logistic analysis. Third, the EVA model outperformed the financial model in terms of the predictive power of hospital bankruptcy. Fourth, The predictive power of neural network model of hospital bankruptcy was more powerful than the legit model. After all the result of this study will be useful to future study on EVA to evaluate bankruptcy hospitals forecast.

• Journal of the Korean Institute of Landscape Architecture
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• v.24 no.4
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• pp.96-111
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• 1997

This study was carried out to identify users' choice behavior of theme parks. overland. Lotte World, Seoul Land, Dreamland and Children's Grand Park were selected as study areas. Both multinomial logic model(MNL), nested logic model(NMNL) and joint logit model wet$.$e test using a choice-based sample collected on study areas. Hausman-McFadden test showed that the MNL is not appropriate because the IIA assumption is violated. To avoid the problematic IIA assumption, the NMNL was tested. It splits similar alternatives into groups and nests separate decisions into hierarchical order to avoid the IIA assumption. Cluster analysis and discriminant analysis were conducted to find applicable nest structures. The inclusive value coefficient was 0.7788. It meant that sufficient condition of this model is met and users' choice behavior can be better understood by NMNL than MNL. The $\rho$2 value and accuracy of prediction of this model were 0.402 and 46.33% , respectively. Several comments were suggested to make the NMNL to be more reliable for future research on users' choice behavior of theme park.

• Journal of Korea Water Resources Association
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• v.33 no.2
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• pp.159-167
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• 2000

The purpose of this study is to estimate the stochastic monthly runoff model for the Kunwi south station of Wi-stream basin in Nakdong river system. This model was based on the theory of Box-Jenkins multiplicative ARlMA and the state-space model to simulate changes of monthly runoff. The forecasting monthly runoff from the pair of estimated effective rainfall and observed value of runoff in the uniform interval was given less standard error then the analysis only by runoff, so this study was more rational forecasting by the use of effective rainfall and runoff. This paper analyzed the records of monthly runoff and effective rainfall, and applied the multiplicative ARlMA model and state-space model. For the P value of V AR(P) model to establish state-space theory, it used Ale value by lag time and VARMA model were established that it was findings to the constituent unit of state-space model using canonical correction coefficients. Therefore this paper confirms that state space model is very significant related with optimization factors of VARMA model.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.73-95
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• 2021

This study uses Node2vec graph embedding method and Light GBM link prediction to explore undeveloped export candidate countries in Korea's food and beverage industry. Node2vec is the method that improves the limit of the structural equivalence representation of the network, which is known to be relatively weak compared to the existing link prediction method based on the number of common neighbors of the network. Therefore, the method is known to show excellent performance in both community detection and structural equivalence of the network. The vector value obtained by embedding the network in this way operates under the condition of a constant length from an arbitrarily designated starting point node. Therefore, it has the advantage that it is easy to apply the sequence of nodes as an input value to the model for downstream tasks such as Logistic Regression, Support Vector Machine, and Random Forest. Based on these features of the Node2vec graph embedding method, this study applied the above method to the international trade information of the Korean food and beverage industry. Through this, we intend to contribute to creating the effect of extensive margin diversification in Korea in the global value chain relationship of the industry. The optimal predictive model derived from the results of this study recorded a precision of 0.95 and a recall of 0.79, and an F1 score of 0.86, showing excellent performance. This performance was shown to be superior to that of the binary classifier based on Logistic Regression set as the baseline model. In the baseline model, a precision of 0.95 and a recall of 0.73 were recorded, and an F1 score of 0.83 was recorded. In addition, the light GBM-based optimal prediction model derived from this study showed superior performance than the link prediction model of previous studies, which is set as a benchmarking model in this study. The predictive model of the previous study recorded only a recall rate of 0.75, but the proposed model of this study showed better performance which recall rate is 0.79. The difference in the performance of the prediction results between benchmarking model and this study model is due to the model learning strategy. In this study, groups were classified by the trade value scale, and prediction models were trained differently for these groups. Specific methods are (1) a method of randomly masking and learning a model for all trades without setting specific conditions for trade value, (2) arbitrarily masking a part of the trades with an average trade value or higher and using the model method, and (3) a method of arbitrarily masking some of the trades with the top 25% or higher trade value and learning the model. As a result of the experiment, it was confirmed that the performance of the model trained by randomly masking some of the trades with the above-average trade value in this method was the best and appeared stably. It was found that most of the results of potential export candidates for Korea derived through the above model appeared appropriate through additional investigation. Combining the above, this study could suggest the practical utility of the link prediction method applying Node2vec and Light GBM. In addition, useful implications could be derived for weight update strategies that can perform better link prediction while training the model. On the other hand, this study also has policy utility because it is applied to trade transactions that have not been performed much in the research related to link prediction based on graph embedding. The results of this study support a rapid response to changes in the global value chain such as the recent US-China trade conflict or Japan's export regulations, and I think that it has sufficient usefulness as a tool for policy decision-making.

• Journal of Environmental Health Sciences
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• v.46 no.5
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• pp.576-587
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• 2020

Objectives: This study calculated local residents exposures to VOCs (Volatile Organic Compounds) released into the atmosphere using the CalTOX model and carried out uncertainty analysis and sensitivity analysis. The model validity was analyzed by comparing the predicted and the actual atmospheric concentrations. Methods: Uncertainty was parsed by conducting a Monte Carlo simulation. Sensitivity was dissected with the regression (coefficients) method. The model validity was analyzed by applying r² (coefficient of determination), RMSE (root mean square error), and the Nash-Sutcliffe EI (efficiency index) formula. Results: Among the concentrations in the atmosphere in this study, benzene was the highest and the lifetime average daily dose of benzene and the average daily dose of xylene were high. In terms of the sensitivity analysis outcome, the source term to air, exposure time, indoors resting (ETri), exposure time, outdoors at home (ETao), yearly average wind speed (v_w), contaminated area in ㎡ (Area), active breathing rate (BRa), resting breathing rate (BRr), exposure time, and active indoors (ETai) were elicited as input variables having great influence upon this model. In consequence of inspecting the validity of the model, r² appeared to be a value close to 1 and RMSE appeared to be a value close to 0, but EI indicated unacceptable model efficiency. To supplement this value, the regression formula was derived for benzene with y=0.002+15.48x, ethylbenzene with y ≡ 0.001+57.240x, styrene with y=0.000+42.249x, toluene with y=0.004+91.588x, and xylene with y=0.000+0.007x. Conclusions: In consequence of inspecting the validity of the model, r² appeared to be a value close to 1 and RMSE appeared to be a value close to 0, but EI indicated unacceptable model efficiency. This will be able to be used as base data for securing the accuracy and reliability of the model.

• Proceedings of the Society of Korea Industrial and System Engineering Conference
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• 2002.05a
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• pp.19-24
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• 2002

The result of management profits create to manufacturing activity. The gross sale profits must be maximum thraw spend of economic value. The profit maximum have to management based key value driver of manufacturing activity. The important factors of the study model are manufacturing value driver(MVD) and manufacturing value added(MVA). We show necessity of management based value by means of a case study.