• Communications for Statistical Applications and Methods
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• v.26 no.3
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• pp.261-272
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• 2019

In this paper, we propose a procedure to build a prediction interval of the sum of dependent binary random variables over a graph to account for the dependence among binary variables. Our main interest is to find a prediction interval of the weighted sum of dependent binary random variables indexed by a graph. This problem is motivated by the prediction problem of various elections including Korean National Assembly and US presidential election. Traditional and popular approaches to construct the prediction interval of the seats won by major parties are normal approximation by the CLT and Monte Carlo method by generating many independent Bernoulli random variables assuming that those binary random variables are independent and the success probabilities are known constants. However, in practice, the survey results (also the exit polls) on the election are random and hardly independent to each other. They are more often spatially correlated random variables. To take this into account, we suggest a spatial auto-regressive (AR) model for the surveyed success probabilities, and propose a residual based bootstrap procedure to construct the prediction interval of the sum of the binary outcomes. Finally, we apply the procedure to building the prediction intervals of the number of legislative seats won by each party from the exit poll data in the $19^{th}$ and $20^{th}$ Korea National Assembly elections.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.4
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• pp.777-790
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• 2001

Theoretical analyses have been tried to design high power and stable operating SLD at 1.55${\mu}{\textrm}{m}$ wavelength range which is the lowest absorption wavelength in optical fiber. The materials of active layer and SCH layer were chosen as conventional In1-xGaxAsyPl-y quaternary composition systems. From the transverse mode and the lateral mode analyses of waveguide, the optical power distributions and the optical confinement factor have been studied for single-mode high power operation. According to these analyses, it was calculated the composition and the thickness of SCH layer to obtain the maximum optical confinement factor. In order to obtain low values of the reflectivity, we used the window region and the lateral tilted angle between tile active region and window region. And the reflectivity of SLD was calculated with the gaussian beam approximation and mode analysis. From these researches, it was confirmed for several results to fabricate the efficient and stable SLD. In case of using $1.3\mum$, InGaAsP SCH layer, the layer thickness was obtained $0.08\mum$, to get the maximum optical confinement factor. Using $0.2\mum$, active layer thickness and $0.08\mum$, SCH layer thickness, the window region length is about $100\mum$ without An coating, $10\mum$ in 1% AR coating to obtain about 10-4 reflectivity. When the tilted angle is about $10~15^{\circ}$, the reflectivity is about 10-3. From these results, if the window region length and tilted angle were controlled appropriately in given device structure, it was confirmed that it is possible to fabricate the stable SLD without AR coating analytically.

• Korean Journal of Materials Research
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• v.8 no.10
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• pp.961-968
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• 1998

In order to investigate the effects of substrate bias voltage on the formation of$ZnS-SiO_2$ protective film in phase change optical disk by R.F. magnetron sputtering method, thin dielectric film was formed on Si wafer and Corning glass by using ZnS(80mol%)-$SiO_2$(20mol%)t arget under argon gas. In this study, the Taguchi experimental method was applied in order to obtain optimum conditions with reduced number of experiments and to control numerous variables effectively. At the same time this method can assure the reproducibility of experiments. Optimum conditions for film formation obtained by above method were target RF power of 200 W. substrate RF power of 20 W, Ar pressure of 5 mTorr. sputtering time of 20 min.. respectively. The phase of specimen was determined by using XRD and TEM. The compositional analysis of specimen was performed by XPS test. In order to measure the thermal resistivity of deposited specimen, annealing test was carried out at $300^{\circ}C$ and $600^{\circ}C$. For the account of void fraction in thin film, the Bruggeman EMA(Effective Medium Approximation) method was applied using the optical data obtained by Spectroscopic Ellipsometry. According to the results of this work, the existence of strong interaction between bias voltage and sputtering time was confirmed for refractive index value. According to XRD and TEM analysis of specimen, the film structure formed in bias voltage resulted in more refined structures than that formed without bias voltage. But excess bias voltage resulted in grain growth in thin film. It was confirmed that the application of optimum bias voltage increased film density by reduction of void fraction of about 3.7%.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.620-626
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• 2004

For general nonlinear processes, it is difficult to control with a linear model-based control method and nonlinear controls are considered. Among the numerous approaches suggested, the most rigorous approach is to use dynamic optimization. Many general engineering problems like control, scheduling, planning etc. are expressed by functional optimization problem and most of them can be changed into dynamic programming (DP) problems. However the DP problems are used in just few cases because as the size of the problem grows, the dynamic programming approach is suffered from the burden of calculation which is called as 'curse of dimensionality'. In order to avoid this problem, the Neuro-Dynamic Programming (NDP) approach is proposed by Bertsekas and Tsitsiklis (1996). To get the solution of seriously nonlinear process control, the interest in NDP approach is enlarged and NDP algorithm is applied to diverse areas such as retailing, finance, inventory management, communication networks, etc. and it has been extended to chemical engineering parts. In the NDP approach, we select the optimal control input policy to minimize the value of cost which is calculated by the sum of current stage cost and future stages cost starting from the next state. The cost value is related with a weight square sum of error and input movement. During the calculation of optimal input policy, if the approximate cost function by using simulation data is utilized with Bellman iteration, the burden of calculation can be relieved and the curse of dimensionality problem of DP can be overcome. It is very important issue how to construct the cost-to-go function which has a good approximate performance. The neural network is one of the eager learning methods and it works as a global approximator to cost-to-go function. In this algorithm, the training of neural network is important and difficult part, and it gives significant effect on the performance of control. To avoid the difficulty in neural network training, the lazy learning method like k-nearest neighbor method can be exploited. The training is unnecessary for this method but requires more computation time and greater data storage. The pH neutralization process has long been taken as a representative benchmark problem of nonlin ar chemical process control due to its nonlinearity and time-varying nature. In this study, the NDP algorithm was applied to pH neutralization process. At first, the pH neutralization process control to use NDP algorithm was performed through simulations with various approximators. The global and local approximators are used for NDP calculation. After that, the verification of NDP in real system was made by pH neutralization experiment. The control results by NDP algorithm was compared with those by the PI controller which is traditionally used, in both simulations and experiments. From the comparison of results, the control by NDP algorithm showed faster and better control performance than PI controller. In addition to that, the control by NDP algorithm showed the good results when it applied to the cases with disturbances and multiple set point changes.