• Korean Journal of Materials Research
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• v.12 no.9
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• pp.718-723
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• 2002

$Ti_{1-x}$ $Al_{ x}$N thin films as barrier layer for memory devices application were deposited by reactive magnetron sputtering. The crystallinity, micro-structure, oxidation resistance and oxidation mechanism of films were investigated as a function of Al content. Lattice parameter and grain size of thin films were decreased with increasing the Al content Oxidation of the film with higher Al content is slow and then, total oxide thickness is thinner than that of lower Al content film. Oxide layer formed on the surface is AlTiNO layer. Oxidation of $Ti_{1-x}$ /$Al_{x}$ N barrier layer is diffusion limited process and thickness of oxide layer with oxidation time increased with a parabolic law. The activation energy of oxygen diffusion, Ea and diffusion coefficient, D of $Ti_{0.74}$ /X$0.74_{0.26}$N film is 2.1eV and $10^{-16}$ ~$10^{-15}$ $\textrm{cm}^2$/s, respectively. $_Ti{1-x}$ /$Al_{x}$ XN barrier layer showed good oxidation resistance.

• Journal of Ocean Engineering and Technology
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• v.35 no.5
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• pp.336-346
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• 2021

The prediction of wave conditions is crucial in the field of marine and ocean engineering. Hence, this study aims to predict the significant wave height through machine learning (ML), a soft computing method. The adopted metocean data, collected from 2012 to 2020, were obtained from the Korea Institute of Ocean Science and Technology. We adopted the feedforward neural network (FNN) and long-short term memory (LSTM) models to predict significant wave height. Input parameters for the input layer were selected by Pearson correlation coefficients. To obtain the optimized hyperparameter, we conducted a sensitivity study on the window size, node, layer, and activation function. Finally, the significant wave height was predicted using the FNN and LSTM models, by varying the three input parameters and three window sizes. Accordingly, FNN (W48) (i.e., FNN with window size 48) and LSTM (W48) (i.e., LSTM with window size 48) were superior outcomes. The most suitable model for predicting the significant wave height was FNN(W48) owing to its accuracy and calculation time. If the metocean data were further accumulated, the accuracy of the ML model would have improved, and it will be beneficial to predict added resistance by waves when conducting a sea trial test.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.205-205
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• 2021

Surface soil moisture, which governs the partitioning of precipitation into infiltration and runoff, plays an important role in the hydrological cycle. The assimilation of satellite soil moisture retrievals into a land surface model or hydrological model has been shown to improve the predictive skill of hydrological variables. This study aims to improve streamflow prediction with Weather Research and Forecasting model-Hydrological modeling system (WRF-Hydro) by assimilating Soil Moisture Active and Passive (SMAP) data at 3 km and analyze its impacts on hydrological components. We applied Cumulative Distribution Function (CDF) technique to remove the bias of SMAP data and assimilate SMAP data (April to July 2015-2019) into WRF-Hydro by using an Ensemble Kalman Filter (EnKF) with a total 12 ensembles. Daily inflow and soil moisture estimates of major dams (Soyanggang, Chungju, Sumjin dam) of South Korea were evaluated. We investigated how hydrologic variables such as runoff, evaporation and soil moisture were better simulated with the data assimilation than without the data assimilation. The result shows that the correlation coefficient of topsoil moisture can be improved, however a change of dam inflow was not outstanding. It may attribute to the fact that soil moisture memory and the respective memory of runoff play on different time scales. These findings demonstrate that the assimilation of satellite soil moisture retrievals can improve the predictive skill of hydrological variables for a better understanding of the water cycle.

• The Korean Journal of Applied Statistics
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• v.36 no.6
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• pp.529-545
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• 2023

This paper introduces the Banded-VHAR model suitable for high-dimensional long-memory time series with band structure. The Banded-VHAR model has nonignorable correlations only with adjacent dimensions due to data features, for example, geographical information. Row-wise estimation method is adapted for fast computation. Also, two estimation methods, namely BIC and ratio methods, are proposed to estimate the width of band. We demonstrate asymptotic consistency of our proposed estimation methods through simulation study. Real data applications to pm2.5 and apartment trading volume substantiate that our Banded-VHAR model outperforms traditional sparse VHAR model in forecasting and easy to interpret model coefficients.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.13 no.2
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• pp.99-107
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• 2003

The finite element method(FEM) is the most widely used and powerful method for structural analysis. In general, in order to analyze complex and large structures, we have used the FEM. However, it is necessary to use a large amount of computer memory and computation time for solving accurately by the FEM the dynamic problem of a system with many degree-of-freedom, because the FEM has to deal with very large matrices in this case. Therefore, it was very difficult to analyze the vibration for plate structures with a large number of degrees of freedom by the FEM on a personal computer. For overcoming this disadvantage of the FEM without the loss of the accuracy, the finite element-transfer stiffness coefficient method(FE-TSCM) was developed. The concept of the FE-TSCM is based on the combination of modeling technique in the FEM and the transfer technique in the transfer stiffness coefficient method(TSCM). The merit of the FE-TSCM is to take the advantages of both methods, that is, the convenience of the modeling in the FEM and the computation efficiency of the TSCM. In this paper, the forced vibration analysis algorithm of plate structures is formulated by the FE-TSCM. In order to illustrate the accuracy and the efficiency of the FE-TSCM, results of frequency response analysis for a rectangular plate, which was adopted as a computational model, were compared with those by the modal analysis method and the direct analysis method which are based on the FEM.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.16 no.1
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• pp.9-18
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• 2003

In static analysis of a variety of structures, the matrix method of structural analysis is the most widely used and powerful analysis method. However, this method has drawback requiring high-performance computers with many memory units and fast processing units in the case of analyzing accurately structures with a large number of degrees-of- freedom. Therefore, it's very difficult to analyze these structures accurately in personal computers. For overcoming the drawback of the matrix method of structural analysis, authors suggest the transfer stiffness coefficient method(TSCM). The TSCM is very suitable to a personal computer because the concept of the TSCM is based on the transfer of the stiffness coefficient for an analytical structure. In this paper, the static analysis algorithm for frame structures is formulated by the TSCM. We confirm the validity of the TSCM through the comparison of computation results by the TSCM, the NASTRAN, the matrix method of structural analysis and the analytical solution.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.48 no.1
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• pp.39-44
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• 1999

The dielectric layers in AC plasma display panel(PDP) are essential to the discharge cell structure, because they protect metal electrodes from sputtering by positive ion bombarding in discharge plasma and form a sheath of wall charges which are essential to memory function of AC PDP. This layer should have high dielectric breakdown voltage, and also be transparent because the luminance of PDP is strongly correlated this layer. In this paper, we discussed the dielectric breakdown voltage and transparency of the dielectric layer under various conditions. As a result, on the $15\mum$ thickness, the minimum dielectric breakdown voltage was 435V and the transmission coefficient was about 80% after $570^{\circ}C$ firing process. It can be proposed that the resonable dielectric thickness in AC PDP is $15\mum$ because it has about 75V margin on the maximum applied voltage.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.4B
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• pp.377-384
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• 2009

In order to reduce computing time significantly for a large matrix in EFEM of linear waves propagation over ripple beds, each of which is approximated to a multi-step topography, a partition method is presented to calculate reflection coefficients. By use of 10 evanescent modes in the model, the most accurate numerical solutions have been obtained up to date, which show different behaviors of computed reflection coefficient in some cases against the existing results. Both computing time and memory of the present partition model for solving a large matrix are still so much demanding that it is needed to develop an efficient method.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.8
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• pp.79-85
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• 2009

In this paper, an accurate current reference using temperature and process compensation current mirror (TPC-CM) is proposed. The temperature independent reference current is generated by summing a proportional to absolute temperature (PTAT) current and a complementary to absolute temperature (CTAT) current. However, the temperature coefficient and magnitude of the reference current are influenced by the process variation. To calibrate the process variation, the proposed TPC-CM uses two binary weighted current mirrors which control the temperature coefficient and magnitude of the reference current. After the PTAT and CTAT current is measured, the switch codes of the TPC-CM is fixed in order that the magnitude of reference current is independent to temperature. And, the codes are stored in the non-volatile memory. In the simulation, the effect of the process variation is reduced to 0.52% from 19.7% after the calibration using a TPC-CM in chip-by-chip. A current reference chip is fabricated with a 3.3V 0.35um CMOS process. The measured calibrated reference current has 0.42% variation for $20^{\circ}$C${\sim}$100$^{\circ}$C.

• KIISE Transactions on Computing Practices
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• v.22 no.5
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• pp.201-208
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• 2016

Collection and storing of multiple time series data in real time requires large memory space. To solve this problem, the usage of varying sample size is proposed in the compression scheme using discrete cosine transform technique. Time series data set has characteristics such that a higher compression ratio can be achieved with smaller amount of value changes and lower frequency of the value changes. The coefficient of variation and the variability of the differences between adjacent data elements (VDAD) are presumed to be very good measures to represent the characteristics of the time series data and used as key parameters to determine the varying sample size. Test results showed that both VDAD-based and the coefficient of variation-based scheme generate excellent compression ratios. However, the former scheme uses much simpler sample size decision mechanism and results in better compression performance than the latter scheme.