• Proceedings of the KSME Conference
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• 2008.11a
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• pp.424-429
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• 2008

Aircraft flutter analysis model consists of dynamic FE model and aerodynamic model. Dynamic FE model is composed of stiffness and mass model, and is used for the prediction of normal mode characteristics of the structure. Since aircraft flutter analysis is normally performed in the modal domain, dynamic FE model shall be constructed to describe the modal characteristics of the structure with sufficient accuracy. In this study, dynamic FE modeling method was described using full airframe FE model and structural and system weight data for aircraft flutter analysis. In addition, full airframe dynamic FE model for composite small aircraft was constituted for normal mode and flutter analysis, and the mass modeling results were compared with the target weight data to validate the mass modeling method proposed. Finally, full airframe flutter analysis of composite small aircraft was performed with the dynamic FE model and the aerodynamic model composed.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.701-705
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• 2008

Design analysis and computer experiments (DACE) model is widely used to express efficiently the nonlinear responses in the field of engineering design. Kriging model, a DACE model, can approximately replace a simulation model that is very expensive or highly nonlinear. The kriging model is composed of the summation of a global model and a local model representing deviation from global model. The local model is determined by correlation coefficient of the pre-sampled points, where determination of the correct correlation coefficient has an effect on accuracy and robustness of the kriging model. Therefore, robustness of the correlation coefficient is explored with respect to degrees of the global model. Then we propose the range of correlation coefficient to make correct and robust kriging model and the influence of the correlation coefficients on the degrees of global model with respect to the nonlinearity of the pre-sampled responses.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.4
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• pp.83-92
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• 2022

Due to the uncertainty in the order of the integrated model, the SARIMA-LSTM model, SARIMA-SVR model, LSTM-SARIMA model, and SVR-SARIMA model are constructed respectively to determine the best-combined model for forecasting the China-Russia trade turnover. Meanwhile, the effect of the order of the combined models on the prediction results is analyzed. Using indicators such as MAPE and RMSE, we compare and evaluate the predictive effects of different models. The results show that the SARIMA-LSTM model combines the SARIMA model's short-term forecasting advantage with the LSTM model's long-term forecasting advantage, which has the highest forecast accuracy of all models and can accurately predict the trend of China-Russia trade turnover in the post-epidemic period. Furthermore, the SARIMA - LSTM model has a higher forecast accuracy than the LSTM-ARIMA model. Nevertheless, the SARIMA-SVR model's forecast accuracy is lower than the SVR-SARIMA model's. As a result, the combined models' order has no bearing on the predicting outcomes for the China-Russia trade turnover time series.

• Journal of Korean Society for Quality Management
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• v.42 no.2
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• pp.221-234
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• 2014

Purpose: The Purpose of this study is to develop a model for predicting agent churn group in the cosmetics industry. We develope two models, pattern model and matrix model, which are compared regarding the prediction accuracy of churn agents. Finally, we try to conclude if there is statistically significant difference between two models by empirical study. Methods: We develop two models using the part of RFM(Recency, Frequency, Monetary) method which is one of customer segmentation method in traditional CRM study. In order to ensure which model can predict churn agents more precisely between two models, we used CRM data of cosmetics company A in China. Results: Pattern model and matrix model have been developed. we find out that there is statistically significant differences between two models regarding the prediction accuracy. Conclusion: Pattern model and matrix model predict churn agents. Although pattern model employed the trend of monetary mount for six months, matrix model that used the amount of sales per month and the duration of the employment is better than pattern model in prediction accuracy.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.12 no.4
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• pp.69-74
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• 2013

According to the axial torsion applied at power transmission and the vibration from the roughness of road surface, this paper analyzes the stresses on two kinds of universal joint model. As stress and deformation at model 2 becomes smaller than model 1 on structural analysis, model 2 is more stabilized than model 1. The natural frequencies at model 1 and 2 are 7,040 and 9,540 Hz respectively. As the natural frequency range of model 2 becomes higher than model 1, model 2 becomes safer than model 1. Critical frequencies at these models are calculated through harmonic response analyses. On critical frequencies at model 1 and 2, the stress at model 2 becomes lower than 2 times as much as model 1 and the deformation at model 2 becomes lower than 4 times as much as model 1. Model 2 on durability is thought to become better than model 1. This study result is applied with the design of safe universal joint and it can be useful to improve the durability by predicting prevention against the deformation due to its vibration.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.05a
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• pp.75-80
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• 1999

As current manufacturing processes require high spindle speed and precise machining, increasing accuracy by reducing volumetric errors of the machine itself, particularly thermal errors, is very important. Thermal errors can be estimated by many empirical models, for example, an FEM model, a neural network model, a linear regression model, an engineering judgment model etc. This paper discusses to make a modeling of thermal errors efficiently through backward elimination and fuzzy logic strategy. The model of a thermal error using fuzzy logic strategy overcome limitation of accuracy in the linear regression model or the engineering judgment model. And this model is compared with the engineering judgment model. It is not necessary complex process such like multi-regression analysis of the engineering judgment model. A fuzzy model does not need to know the characteristics of the plant, and the parameters of the model can be mathematically calculated. Like a regression model, this model can be applied to any machine, but it delivers greater accuracy and robustness.

• The Journal of Fisheries Business Administration
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• v.44 no.1
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• pp.59-70
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• 2013

The purpose of this paper is to integrate various models of price formation and let the data choose the most proper model. After the data choose the proper model, one can analyze the price formation process and demand structures for fishery resources under the restriction of Korean fisheries regulations. This study suggests the integrated model including quasi-linear price formation model, Translog price formation model, AIDS price formation model and Lewbel price formation model as level variables. It also suggests another integrated model including AIDS price formation model, Rotterdam price formation model, Latinen-Theil price formation model and Neves price formation model as difference variables. The empirical results show that the AIDS price formation model is the most preferred in both level and difference variables of fishery resources. The estimated parameters show that all sample species have (-) sign of price flexibilities, thus following the law of demand. The scale flexibilities of all species are estimated as (-) sign, thus being adapted to the theory. The contribution and results are summarized as follows. First, the integrated model of fishery market demand has been developed and the data can choose the proper model without arbitrary choice of the researcher. Second, the fishery market demand structure could be analyzed in a way different from the ordinary demand analysis, which is based upon price flexibility and scale flexibility. Third, the integrated model for fishery resources can be used easily when catching restrictions are imposed by policies.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.10
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• pp.831-841
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• 1991

A combined model of probabilistic and MLP(multi layer perceptron) model is proposed for the pattern classification of EMG( electromyogram) signals. The MLP model has a problem of not guaranteeing the global minima of error and different quality of approximations to Bayesian probabilities. The probabilistic model is, however, closely related to the estimation error of model parameters and the fidelity of assumptions. A proper combination of these will reduce the effects of the problems and be robust to input variations. Proposed model is able to get the MAP(maximum a posteriori probability) in the probabilistic model by estimating a priori probability distribution using the MLP model adaptively. This method minimize the error probability of the probabilistic model as long as the realization of the MLP model is optimal, and this is a good combination of the probabilistic model and the MLP model for the usage of MLP model reliability. Simulation results show the benefit of the proposed model compared to use the Mlp and the probabilistic model seperately and the average calculation time fro classification is about 50ms in the case of combined motion using an IBM PC 25 MHz 386model.

• Journal of the Society of Naval Architects of Korea
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• v.57 no.1
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• pp.15-22
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• 2020

Understanding the strength characteristics of model ice is an important issue for model testing in an ice model basin to estimate the ship performance in ice. In particular, the mechanical properties of the model ice including elastic modulus, flexural strength and compressive strength are key consideration factors. In order to understand the characteristics of the model ice during warm-up phase at KRISO's ice model basin, the strength properties are tested in this study. The infinite plate-bending method, in-situ cantilever beam test and ex-situ uniaxial compressive test are conducted to determine the strength properties of model ice. The strength characteristics of the model ice are then analyzed in terms of the warm-up phase and seasonality. These results could be valuable to quality control of the model ice characteristics in KRISO's ice model basin and to better understand the variations in strength properties during the ice model tests.

• International journal of advanced smart convergence
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• v.11 no.3
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• pp.1-6
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• 2022

In this paper, we estimate the mean number of objects in the M/H₂/1 model for web service when the mean object size in the M/H₂/1 model is equal to that of the M/G/1/PS and M/BP/1 models. To this end, we use the mean object size obtained by assuming that the mean latency of deterministic model is equal to that of M/H₂/1, M/G/1/PS, and M/BP/1 models, respectively. Computational experiments show that if the shape parameter of the M/BP/1 model is 1.1 and the system load is greater than 0.35, the mean number of objects in the M/H₂/1 model when mean object size of M/H₂/1 model is the same as that of M/G/1/PS model is almost equal to the mean number of objects in the M/H₂/1 model when the mean object size of M/H₂/1 model is the same as that of M/BP/1 model. In addition, as the upper limit of the M/BP/1 model increases, the number of objects in the M/H₂/1 model converges to one, which increases latency. These results mean that it is efficient to use small-sized objects in the web service environment.