• The Korean Journal of Financial Management
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• v.21 no.1
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• pp.231-253
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• 2004

We examine hedge strategies that use Won-dollar futures to hedge the price risk of the Won-dollar exchange rate. We employ the naive hedge model, minimum variance hedge model and bivariate ECT-ARCH(1) model as hedge instruments, and analyze their hedge performances. The sample period covers from January 2, 2001 to December 31, 2002 with sub-samples such as daily, weekly, bi-weekly prices of the Won-dollar futures and cash. The important findings may be summarized as follows. First, there is no significant difference in hedge ratio between the risk minimum variance model and bivariate ECT-ARCH(1) model that controls for the cointegration relationship of the Won-dollar futures and cash. Second, hedge performance of the naive model and minimum variance model with constant hedge ratios is not far behind that of bivariate ECT-ARCH(1) model with time-varying hedge ratios. This results imply that investors are encouraged to use the minimum variance hedge model to hedge Won-dollar exchange rate with Won-dollar futures. Third, hedge performance and effectiveness of each model is also analyzed with respect to hedge period appear to be greater over long than over the short period. This evidence supports the hypothesis that futures prices would have more time to respond to the greater cash price changes over the longer holding period, leading to an improved hedge performance.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.6
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• pp.1-8
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• 2002

This paper presents a generalized minimum-variance self-tuning controller with a PID structure using neural network which adapts to the changing parameters of the nonlinear system with nonminimum phase behavior and time delays. The neural network is used to estimate the controller parameters, and the control output is obtained through estimated controller parameter. In order to demonstrate the effectiveness of the proposed algorithm, the computer simulation is done to adapt the nonlinear nonminimum phase system with time delays and changed system parameter after a constant time. The proposed method compared with direct adaptive controller using neural network.

• Communications for Statistical Applications and Methods
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• v.15 no.6
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• pp.925-937
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• 2008

In this study, we considered the clustering analysis for stock return traded in the stock market. Most of financial time-series data, for instance, stock price and exchange rate have conditional heterogeneous variability depending on time, and, hence, are not properly applied to the autoregressive moving-average(ARMA) model with assumption of constant variance. Moreover, the variability is font and center for stock investors as well as academic researchers. So, this paper focuses on the generalized autoregressive conditional heteroscedastic(GARCH) model which is known as a solution for capturing the conditional variance(or volatility). We define the metrics for similarity of unconditional volatility and for homogeneity of model structure, and, then, evaluate the performances of the metrics. In real application, we do clustering analysis in terms of volatility and structure with stock return of the 11 Korean companies measured for the latest three years.

• The KIPS Transactions:PartB
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• v.13B no.3 s.106
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• pp.245-254
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• 2006

In this work, a new rate control algorithm for transmission of H.264/AVC video bit stream through CBR(constant bit rate) channel is proposed. The proposed algorithm predicts target bit rate and MAD(mean of absolute difference) for current frame considering image complexity variance between neighboring backward and current images. In details, respective linear regression analysis for MAD and encoded bit rate against image complexity variance produce correlation parameters. Additionally, it uses frame skip technique to maintain bit stream within a manageable range and protect buffer from overflow or underflow. Implementation and experimental results show that the proposed algorithm can provide accurate bit allocation, and can effectively visual degradation after scene changes. Also our proposed algorithm encodes the video sequences with less frame skipping compared to the existing rate control for H.264/AVC.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.5
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• pp.25-34
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• 2008

By comparing two images, which are captured with the same scene at different time, we can detect a set of outliers, such as occluding objects due to moving vehicles. To reduce the influence from the different intensity properties of the images, an intensity compensation scheme, which is based on the polynomial regression model, is employed. For an accurate detection of outliers alleviating the influence from a set of outliers, a simple technique that reruns the regression is employed. In this paper, an algorithm that iteratively reruns the regression is theoretically analyzed by observing the convergence property of the estimates of the noise variance. Using a correction constant for the estimate of the noise variance is proposed. The correction enables the detection algorithm robust to the choice of thresholds for selecting outliers. Numerical analysis using both synthetic and Teal images are also shown in this paper to show the robust performance of the detection algorithm.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.9 no.3
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• pp.115-124
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• 1997

We measured the variance of eddy diffusion and associated ‘diffusion coefficients’ in coastal regions of Korea by observing the separation distances among multiple drifters deployed simultaneously at the same initial position. The variance of eddy diffusion was found to be proportional to $t^m$, where t is the time and m is a non-integer scaling exponent between 1.5 and 3.5. The observed scaling exponent of eddy diffusion cannot be reproduced by diffusion models employing constant eddy diffusivity. In this study, we applied fractal theory in simulating exponential increase of variance of eddy diffusion. We employed the fGn(fractional Gaussian noise) as a ‘modified’ random walks corresponding to the oceanic eddy diffusion. The variance of eddy diffusion, which corresponds to the fBm(fractional Brown motion) of our diffusion model, is proportional to $t^{2H}$, where H is Hurst scaling exponent. The temporal increase of the variance. with scaling exponent between 1 and 2, was successfully reproduced by our fractal diffusion model. However, our model cannot reproduce scaling exponent greater than 2. The scaling exponents greater than 2 are associated with the velocity shear of the mean flow.

• Journal of computational fluids engineering
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• v.17 no.2
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• pp.42-52
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• 2012

Direct Numerical Simulation(DNS) of turbulent mass transfer in fully developed turbulent pipe flow has been performed to study the effect of wall boundary conditions on the concentration fields at $Re_{\tau}$=180 based on friction velocity and pipe radius. Fully developed turbulent pipe flows for Sc=0.71 are studied with two different wall boundary conditions, namely, constant mass flux and constant wall concentration. The mean concentration profiles and turbulent mass fluxes obtained from the present DNS are in good agreement with the previous numerical results currently available. To investigate the effects of wall boundary condition on the turbulent mass transfer, the mean concentration profile, root-mean-square of concentration fluctuation, turbulent mass fluxes and higher-order statistics(Skewness and Flatness factor) are compared for the two cases. Furthermore, the budgets of turbulent mass fluxes and concentration variance were computed and analyzed to elucidate the effects of wall boundary conditions on the turbulent mass transfer.

• Reproductive and Developmental Biology
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• v.31 no.1
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• pp.15-20
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• 2007

To search of a new porcine pheromonal odorant for biostimulation control system technologies to offer a potentially useful and practical way to improve reproductive efficiency in livestock species, the two dimensional quantitative structure-activity relationship (QSAR) models between physicochemical parameters as descriptors of 2-cyclohexyloxytetrahydrofurane (A), 2-phenoxytetrahydrofurane (B) analogues and binding affinity constant ($p[Od.]_{50}$) for porcine odorant-binding protein (pOBP) as receptor of pig pheromones were derived and disscused. The statistical quality of the optimized 2D-QSAR model is good ($r^{2}=0.964$) and accounts for 96.4% of the variance in the binding affinity constants. It was found that the binding affinity constants were dependent upon the optimal value, $(SL)_{opt.}=1.418$ of substituent lipole (SL) in molecules. Therefore, the SL constant was very important factor for binding affinity.

• Environmental Engineering Research
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• v.22 no.4
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• pp.339-346
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• 2017

The objective of this study is the evaluation of the performance of a large-scale respirometer (LSR) of 17.7 L in the determination of the methane generation rate constant (k) values. To achieve this objective, a comparison between anaerobic (GB21) and LSR tests was conducted. The data were modeled using a linear function, and the resulting correlation coefficient ($R^2$) of the linear regression is 0.91. This result shows that despite the aerobic conditions, the biodegradability values that were obtained from the LSR test produced results that are similar to those from the GB21 test. In this respect, the LSR test can be an indicator of the anaerobic biodegradability for landfill waste. In addition, the results show the high repeatability of the tests with an average coefficient of variance (CV) that is lower than 10%; furthermore, the CV for the LSR is lower than that of the GB21, which indicates that the LSR-test method could provide a better representation of waste samples. Therefore, the LSR method allows for both the prediction of the long-term biodegradation potential in a shorter length of time and the reduction of the sampling errors that are caused by the heterogeneity of waste samples. The k values are $0.156y^{-1}$ and $0.127y^{-1}$ for the cumulative biogas production (GB21) and the cumulative oxygen uptake for the LSR, respectively.

• Journal of Advanced Navigation Technology
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• v.16 no.5
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• pp.846-852
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• 2012

The result of imaging segmentation becomes different with the parameters involved in the segmentation algorithms; therefore, the parameters for the optimal segmentation have been found through a try and error. In this paper, we propose the method to find the best values of parameters involved in the area-based active contour method using three-way ANOVA. The segmentation result applied by three-way ANOVA is compared with the optimal segmentation which is drawn by user. We use the global consistency rate for comparing two segmentations. Finally, we estimate the main effects and interactions between each parameter using three-way ANOVA, and then calculate the point and interval estimate to find the best values of three parameters. The proposed method will be a great help to find the optimal parameters before working the motion segmentation using piecewise constant model.