• International Journal of Highway Engineering
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• v.11 no.4
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• pp.17-23
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• 2009

Deformational characteristics of subgrade soils are very important input parameters for pavement design. It is necessary to make an amount of effort to estimate experimentally the modulus of subgrade soils. In case of designing simple (or lower level) pavement section, the estimation of the modulus based on experiments must cause an excessive cost. It has proposed various empirical correlation models to estimate the modulus from basic properties of the materials or more simple alternative tests. Seven subgrade soils in Korea were tested in this study. It was founded that the deformational characteristics of subgrade soils in Korea has a close relation to strength characteristics, the empirical correlation model was proposed. There was a close relation between cohesion value and modulus at low confining stress ($r^2=0.93$). By comparing with the measured modulus and the modulus determined by proposed correlation model from strength characteristics, the value of the coefficient of determination ($r^2$) is 0.75.

• ETRI Journal
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• v.30 no.6
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• pp.765-773
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• 2008

Spatial correlation is a result of insufficient antenna spacing among multiple antenna elements, while temporal correlation is caused by Doppler spread. This paper compares the effect of spatial and temporal correlation in order to investigate the performance of multiuser scheduling algorithms in multiple-input multiple-output (MIMO) broadcast channels. This comparison includes the effect on the ergodic capacity, on fairness among users, and on the sum-rate capacity of a multiuser scheduling algorithm utilizing statistical channel state information in spatio-temporally correlated MIMO broadcast channels. Numerical results demonstrate that temporal correlation is more meaningful than spatial correlation in view of the multiuser scheduling algorithm in MIMO broadcast channels. Indeed, the multiuser scheduling algorithm can reduce the effect of the Doppler spread if it exploits the information of temporal correlation appropriately. However, the effect of spatial correlation can be minimized if the antenna spacing is sufficient in rich scattering MIMO channels regardless of the multiuser scheduling algorithm used.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.3
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• pp.681-689
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• 1994

A model to predict the onset of significant void (OSV) in vertical flow between parallel plates has been developed. The model was compared to the experimental data of Whittle and Forgan (1967) and Dougherty et al. (1990), showing excellent agreement. The model was also compared with the Saha-Zuber(1974) correlation, which has been widely used in computer codes for nuclear safety analysis. The present theory is more conservative than this correlation, and further shows that, contrary to this correlation, the Stanton number is not solely related to the Peclet number. This may explain the large error margins required for the Saha-Zuber correlation, and also the scatter beyond the error margins specified by the authors. The steady-state OSV heat fluxes for equal and unequal heating cases between parallel plates were compared. The arithmetic mean of heat fluxes for unequal heating cases is less than the heat flux for equal heating cases. The result may imply that OSV is controlled by local thermal parameters rather than bulk parameters.

• Proceedings of the Safety Management and Science Conference
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• 2009.11a
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• pp.187-201
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• 2009

Semiconductor industry is based on equipment industry and timing industry. In particular, semiconductor process is very complex and as semiconductor-chip width tails and is becoming equipment gradually more as a high technology. Equipment operation is primarily engaged in semiconductor manufacturing (engineers and operator) of being conducted by, equipment errors have also been raised. Equipment operational data related to the error of korea occupational safety and health agency were based on data and production engineers involved in the operator's questionnaire was drawn through the error factor. Equipment operating in the error factor of 9 big item and 36 detail item detailed argument based on the errors down, and 9 big item the equipment during operation of the correlation error factor was conducted. Each of the significance level was correlated with the tabulation and analysis. Using the maximum correlation coefficient, the correlation between the error factors to derive the relationship between factors were analyzed. Facility operating with the analysis of error factors (big and detail item) derive a relationship between the model saw. The end of the operation of the facility in operation on the part of the two factors appeared as prevention. Safety aspects and ergonomics aspects of the approach should be guided to the conclusion.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.461-470
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• 2014

This paper presents a probabilistic power flow (PPF) analysis method for distribution network incorporating the randomness and correlation of photovoltaic (PV) generation. Based on the multivariate kernel density estimation theory, the probabilistic model of PV generation is proposed without any assumption of theoretical parametric distribution, which can accurately capture not only the randomness but also the correlation of PV resources at adjacent locations. The PPF method is developed by combining the proposed PV model and Monte Carlo technique to evaluate the influence of the randomness and correlation of PV generation on the performance of distribution networks. The historical power output data of three neighboring PV generators in Oregon, USA, and 34-bus/69-bus radial distribution networks are used to demonstrate the correctness, effectiveness, and application of the proposed PV model and PPF method.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.585-594
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• 2003

It has been generally recognized that conventional binomial or Poisson model provides poor fits to the actual correlated binary data due to the extra-binomial variation. A number of generalized statistical models have been proposed to account for this additional variation. Among them, beta-binomial, correlated-binomial, and modified-binomial models are binomial-related models which are frequently used in modeling the sum of n correlated binary data. In many situations, it is reasonable to assume that n correlated binary data are exchangeable, which is a special case of correlated binary data. The sum of n exchangeable correlated binary data is modeled relatively well when the above three binomial-related models are applied. But the estimation results of correlation coefficient turn to be quite different. Hence, it is important to identify which model provides better estimates of model parameters(success probability, correlation coefficient). For this purpose, a small-scale simulation study is performed to compare the behavior of above three models.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.1
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• pp.1-10
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• 2001

As computer power is increased, refined finite element models are employed for structural analysis. However, it is difficult and expensive to use refined models in the design stage. The refined models especially cause problems in the preliminary design where the design is frequently changed. Therefore, simplified models are needed. The simplification process is regarded as an empirical technique. Simplified and equivalent finite element model of a structure has been studied and used in the preliminary design. A general approach to establish the simplified and equivalent model is presented. The generated simple model has satisfactory correlation with the corresponding refined finite element model. An optimization method, the Goal Programming algorithm is used to make the simple model. The simplified model is used for the design change and the changed design is recovered onto the original design. The presented method was verified with three examples.

• Journal of the Korean Chemical Society
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• v.57 no.3
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• pp.370-376
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• 2013

A back propagation artificial neural network model with one hidden layer is established to correlate the liquid-liquid equilibrium data of hydrocarbon-water systems. The model has four inputs and two outputs. The network is systematically trained with 48 data points in the range of 283.15 to 405.37K. Statistical analyses show that the optimised neural network model can yield excellent agreement with experimental data(the average absolute deviations equal to 0.037% and 0.0012% for the correlated mole fractions of hydrocarbon in two coexisting liquid phases respectively). The comparison in terms of average absolute deviation between the correlated mole fractions for each binary system and literature results indicates that the artificial neural network model gives far better results. This study also shows that artificial neural network model could be developed for the phase equilibria for a family of hydrocarbon-water binaries.

• Journal of the Society of Naval Architects of Korea
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• v.43 no.1 s.145
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• pp.50-58
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• 2006

Free running model tests gives us only maneuvering indices not hydrodynamic derivatives. For this reason, system identification method has been applied to the measured data to identify mathematical model describing hydrodynamic force. However It is difficult to obtain complete set of maneuvering derivatives because of strong correlation of sway velocity and yaw rate. Therefore, in this paper, we assumed that sway velocity related coefficients would be obtained by oblique towing test. and then proposed new procedure to estimate yaw related coefficients. To do this, correlation and regression analyses were carried out to establish modified model and estimate maneuvering derivatives. Also D-optimal rudder input scenario was found based on the modified model and confirmed the validity of its sufficient richness as a input scenario.

• Korean Business Review
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• v.20 no.2
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• pp.15-27
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• 2007

This paper analyzed the relationship between Housing Purchase Price volatility of Seoul and Housing Purchase Price volatility of local large city. Other studies investigates the effect on the observed volatility Observed volatility consists of fundamental volatility and transitory volatility. Fundamental volatility is caused by information arrival and transitory volatility is caused by noise trading. Fundamental volatility is trend component and is modelled as a random walk with drift. Transitory volatility is cyclical component and is modelled as a stationary process. In contrast to other studies, this study investigates the effect on the fundamental volatility and transitory volatility individually. Observed volatility is estimated by GJR GARCH(1,1) model. We find that GJH GARCH model is superior to GARCH model and good news is more remarkable effect on volatility than bad news. This study decomposes the observed volatility into fundamental volatility and transitory volatility using Kalman filtering method. The findings in this paper is as follows. The correlation between Seoul housing price volatility and Busan housing price volatility is high. But, the correlation between Seoul and Daejeon is low. And the correlation between Daejeon and Busan is low. As a distinguishing feature, the correlation between fundamental volatilities is high in the case of all pairs. But, the correlation between transitory volatilities turns out low. The reason is as follows. When economic information arrives, Seoul, Daejeon, and Busan housing markets, all together, are affected by this information.