• International Journal of Automotive Technology
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• v.6 no.6
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• pp.571-577
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• 2005

Combustion of turbulent sprays in a direct injection diesel engine is modeled by the conditional moment closure (CMC) model. The CMC routines are combined with the KIVA code to provide conditional flame structures to determine mean state variables, instead of mean reaction rates. An independent transport equation is solved for each flame group with equal mass of sequentially evaporating fuel vapor. CMC calculation begins as the fuel mass for each flame group begins to evaporate with corresponding initialization conditions. Comparison is made with measured pressure traces for four operating conditions at different rpm's and injection conditions. Results show that the CMC model with multiple flame histories can successfully be applied to ignition and mixing-controlled combustion phases of a diesel engine.

• The Korean Journal of Financial Management
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• v.26 no.3
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• pp.199-226
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• 2009

We examine the intertemporal relation between risk and return in the Korean stock market and foreign exchange market based on the two factor ICAPM framework. The standard GARCH model and the GJR(1993) model are employed to estimate conditional variances of the stock returns and foreign exchange rates. The covariance between the rates of stock returns and changes in the exchange rates are estimated by the constant conditional correlation model of Bollerslev(1990) and the dynamic conditional correlation model of Engle(2002). The multivariate GARCH in mean model and quasi-maximum likelihood estimation method, consequently, are applied to investigate riskreturn relation jointly. We find that the estimated coefficient of relative risk aversion is negative and statistically significant in the post-financial crisis sample period in the Korean stock market. We also show that the expected stock returns are negatively related to the dynamic covariance with foreign exchange rates. Both estimated parameters of conditional variance and covariance in the foreign exchange market, however, are not statistically significant. The GJR model is better than the standard GARCH model to estimate the conditional variances. In addition, the dynamic conditional correlation model has higher explanatory power than the constant correlation model. The empirical results of this study suggest following two points to investors and risk managers in hedging and diversifying strategies for their portfolios in the Korean stock market: first, the variability of foreign exchange rates should be considered, and second, time-varying correlation between stock returns and changes in foreign exchange rates supposed to be considered.

• 한국연소학회:학술대회논문집
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• 2002.11a
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• pp.11-17
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• 2002

The first-order conditional moment closure (CMC) model is applied to $CH_4$/Air turbulent jet diffusion flames(Sandia Flame D, E and F). The flow and mixing fields are calculated by fast chemistry assumption and a beta function pdf for mixture fraction. Reacting scalar fields are calculated by elliptic CMC formulation. The results for Flame D show reasonable agreement with the measured conditional mean temperature and mass fractions of major species, although with discrepancy on the fuel rich side. The discrepancy tends to increase as the level of local extinction increases. Second-order CMC may be needed for better prediction of these near-extinction flames.

• Journal of Communications and Networks
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• v.13 no.6
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• pp.621-624
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• 2011

With the rapid growth of internet traffic, accurate and reliable prediction of internet traffic has been a key issue in network management and planning. This paper proposes an autoregressive-generalized autoregressive conditional heteroscedasticity (AR-GARCH) error model for forecasting internet traffic and evaluates its performance by comparing it with seasonal autoregressive integrated moving average (ARIMA) models in terms of root mean square error (RMSE) criterion. The results indicated that the seasonal AR-GARCH models outperformed the seasonal ARIMA models in terms of forecasting accuracy with respect to the RMSE criterion.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.28 no.12
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• pp.1616-1624
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• 2004

The conditional moment closure(CMC) model has been implemented in context with the unstructured-grid finite-volume method which efficiently handle the physically and geometrically complex turbulent reacting flows. The validation cases include a turbulent nonpremixed CO/$H_2$/$N_2$ Jet flame and a turbulent nonpremixed $H_2$/CO flame stabilized on an axisymmetric bluff-body burner. In terms of mean flame field, minor species and NO formation, numerical results has the overall agreement with expermental data. The detailed discussion has been made for the turbulence-chemistry interaction and NOx formation characteristics as well as the comparative performance for CMC and flamelet model.

• Korea Trade Review
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• v.47 no.3
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• pp.211-232
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• 2022

Due to the impact of the public health event COVID-19 epidemic, the Chinese futures market showed "Black Swan". This has brought the unpredictable into the economic environment with many commodities falling by the daily limit, while gold performed well and closed in the sunshine(Yan-Li and Rui Qian-Wang, 2020). Volatility is integral part of financial market. As an emerging market and a special precious metal, it is important to forecast return of gold futures price. This study selected data of the SHFE gold futures returns and conducted an empirical analysis based on the generalised autoregressive conditional heteroskedasticity (GARCH)-type model. Comparing the statistics of AIC, SC and H-QC, ARMA (12,9) model was selected as the best model. But serial correlation in the squared returns suggests conditional heteroskedasticity. Next part we established the autoregressive moving average ARMA-GARCH-type model to analysis whether Volatility Clustering and the leverage effect exist in the Chinese gold futures market. we consider three different distributions of innovation to explain fat-tailed features of financial returns. Additionally, the error degree and prediction results of different models were evaluated in terms of mean squared error (MSE), mean absolute error (MAE), Theil inequality coefficient(TIC) and root mean-squared error (RMSE). The results show that the ARMA(12,9)-TGARCH(2,2) model under Student's t-distribution outperforms other models when predicting the Chinese gold futures return series.

• 한국연소학회:학술대회논문집
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• 2001.11a
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• pp.35-41
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• 2001

A second-order conditional moment closure(CMC) model is applied to the prediction of local extinction in a turbulent hydrocarbon diffusion flame and compared with direct numerical simulation(DNS) results for the flame. Combustion of a hydrocarbon fuel is described by a simple two-step mechanism. A second-order correction for conditional mean reaction rate terms is made by the assumed pdf method. The results show that the second-order closure is necessary for accurate prediction of intermediate species, while first-order CMC gives good predictions for fuel, oxidant, product and temperature. Conditional variances and covariances are well predicted during an extinction process while they are overpredicted during a reignition process.

• The Journal of the Acoustical Society of Korea
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• v.29 no.1
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• pp.76-81
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• 2010

In this paper, we propose a novel approach to improve the performance of a statistical model-based voice activity detection (VAD) which is based on the second-order conditional maximum a posteriori (CMAP). In our approach, the VAD decision rule is expressed as the geometric mean of likelihood ratios (LRs) based on adapted threshold according to the speech presence probability conditioned on both the current observation and the speech activity decisions in the pervious two frames. Experimental results show that the proposed approach yields better results compared to the statistical model-based and the CMAP-based VAD using the LR test.

• Transactions of the Korean Society of Mechanical Engineers
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• v.12 no.5
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• pp.1175-1188
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• 1988

Linear estimation in isotropic turbulence is examined to approximate conditional averages in the form of fluctuating velocity fields conditioned on local velocity. The conditional flow fields and their associated vorticity field are computer using experimental data [Van Atta and Chen] and energy spectrum model [Driscoll and Kennedy]. It appears that ring vorticies could be the dominant structure. Due to the extremely large vorticity in the viscous region of a conditional ring vortex, the energy spectrum model can be used appropriately by changing the Reynolds number. The hairpin vortex could be detected by combining vorticies in isotropic field with an anisotropic orientation imbedded in uniform mean shear flow and this is consistent with other studies [Kim and Moin].

• The Journal of the Acoustical Society of Korea
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• v.30 no.6
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• pp.324-329
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• 2011

In this paper, we propose a novel approach to improve the performance of a statistical model-based voice activity detection (VAD) which is based on the conditional maximum a posteriori (CMAP) with deviation. In our approach, the VAD decision rule is expressed as the geometric mean of likelihood ratios (LRs) based on adapted threshold according to the speech presence probability conditioned on both the speech activity decisions and spectral deviation in the pervious frame. Experimental results show that the proposed approach yields better results compared to the CMAP-based VAD using the LR test.