• Journal of the Computational Structural Engineering Institute of Korea
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• v.19 no.2 s.72
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• pp.171-185
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• 2006

A sophisticated reliability analysis method is proposed to evaluate the reliability of real nonlinear complicated dynamic structural systems excited by short duration dynamic loadings like earthquake motions by intelligently integrating the response surface method, the finite element method, the first-order reliability method, and the iterative linear interpolation scheme. The method explicitly considers all major sources of nonlinearity and uncertainty in the load and resistance-related random variables. The unique feature of the technique is that the seismic loading is applied in the time domain, providing an alternative to the classical random vibration approach. The four-parameter Richard model is used to represent the flexibility of connections of real steel frames. Uncertainties in the Richard parameters are also incorporated in the algorithm. The laterally flexible steel frame is then reinforced with reinforced concrete shear walls. The stiffness degradation of shear walls after cracking is also considered. The applicability of the method to estimate the reliability of real structures is demonstrated by considering three examples; a laterally flexible steel frame with fully restrained connections, the same steel frame with partially restrained connections with different rigidities, and a steel frame reinforced with concrete shear walls.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.9B
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• pp.1742-1754
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• 1999

In this paper, we propose a rate control scheme, using histogram based rate-distortion (R-D) estimation, which produces a consistent picture quality between consecutive frames. The histogram based R-D estimation used in our rate control scheme offers a closed-form mathematical model that enable us to predict the bits and the distortion generated from an encoded frame at a given quantization parameter (QP) and vice versa. The most attractive feature of the R-D estimation is low complexity of computing the R-D data because its major operation is just to obtain a histogram or weighted histogram of DCT coefficients from an input picture. Furthermore, it is accurate enough to be applied to the practical video coding. Therefore, the proposed rate control scheme using this R-D estimation model is appropriate for the applications requiring low delay and low complexity, and controls the output bit-rate ad quality accurately. Our rate control scheme ensures that the video buffer do not underflow and overflow by satisfying the buffer constraint and, additionally, prevents quality difference between consecutive frames from exceeding certain level by adopting the distortion constraint. In addition, a consistent considering the maximum tolerance BER of the voice service. Also in Rician fading channel of K=6 and K=10, considering CLP=$10^{-3}$ as a criterion, it is observed that the performance improment of about 3.5 dB and 1.5 dB is obtained, respectively, in terms of $E_b$/$N_o$ by employing the concatenated FEC code with pilot symbols.

• Journal of Korea Soil Environment Society
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• v.1 no.1
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• pp.89-102
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• 1996

An integrated model is presented to describe underground flow and mass transport, using a multicomponent multiphase approach. The comprehensive governing equation is derived considering mass and force balances of chemical species over four phases(water, oil, air, and soil) in a schematic elementary volume. Compact and systemati notations of relevant variables and equations are introduced to facilitate the inclusion of complex migration and transformation processes, and variable spatial dimensions. The resulting nonlinear system is solved by a multidimensional finite element code. The developed code with dynamic array allocation, is sufficiently flexible to work across a wide spectrum of computers, including an IBM ES 9000/900 vector facility, SP2 cluster machine, Unix workstations and PCs, for one-, two and three-dimensional problems. To reduce the computation time and storage requirements, the system equations are decoupled and solved using a banded global matrix solver, with the vector and parallel processing on the IBM 9000. To avoide the numerical oscillations of the nonlinear problems in the case of convective dominant transport, the techniques of upstream weighting, mass lumping, and elementary-wise parameter evaluation are applied. The instability and convergence criteria of the nonlinear problems are studied for the one-dimensional analogue of FEM and FDM. Modeling capacity is presented in the simulation of three dimensional composite multiphase TCE migration. Comprehesive simulation feature of the code is presented in a companion paper of this issue for the specific groundwater or flow and contamination problems.

• Proceedings of the Korean Vacuum Society Conference
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• 1999.07a
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• pp.211-211
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• 1999

Titanium nitride (TiN) thin films have useful properties including high hardness, good electrical conductivity, high melting point, and chemical inertness. The applications have included wear-resistant hard coatings on machine tools and bearings, decorative coating making use of the golden color, thermal control coatings for widows, and erosion resistant coatings for spacecraft plasma probes. For all these applications as feature sizes shrink and aspect ratios grow, the issue of good step coverage becomes increasingly important. It is therefore essential to manufacture conformal coatings of TiN. The growth of TiN thin films by chemical vapor deposition (CVD) is of great interest for achieving conformal deposition. The most widely used precursor for TiN is TiCl4 and NH3. However, chlorine impurity in the as-grown films and relatively high deposition temperature (>$600^{\circ}C$) are considered major drawbacks from actual device fabrication. To overcome these problems, recently, MOCVD processes including plasma assisted have been suggested. In this study, therefore, we have doposited Ti(C, N) thin films on Si(100) and D2 steel substrates in the temperature range of 150-30$0^{\circ}C$ using tetrakis diethylamido titanium (TDEAT) and titanium isopropoxide (TIP) by pulsed DC plamsa enhanced metal-organic chemical vapor deposition (PEMOCVD) method. Polycrystalline Ti(C, N) thin films were successfully grown on either D2 steel or Si(100) surfaces at temperature as low as 15$0^{\circ}C$. Compositions of the as-grown films were determined with XPS and RBS. From XPS analysis, thin films of Ti(C, N) with low oxygen concentration were obtained. RBS data were also confirmed the changes of stoichiometry and microhardness of our films. Radical formation and ionization behaviors in plasma are analyzed by optical emission spectroscopy (OES) at various pulsed bias and gases conditions. H2 and He+H2 gases are used as carrier gases to compare plasma parameter and the effect of N2 and NH3 gases as reactive gas is also evaluated in reduction of C content of the films. In this study, we fond that He and H2 mixture gas is very effective in enhancing ionization of radicals, especially N resulting is high hardness. The higher hardness of film is obtained to be ca. 1700 HK 0.01 but it depends on gas species and bias voltage. The proper process is evident for H and N2 gas atmosphere and bias voltage of 600V. However, NH3 gas highly reduces formation of CN radical, thereby decreasing C content of Ti(C, N) thin films in a great deal. Compared to PVD TiN films, the Ti(C, N) film grown by PEMOCVD has very good conformability; the step coverage exceeds 85% with an aspect ratio of more than 3.

• Journal of Korea Multimedia Society
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• v.5 no.5
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• pp.512-522
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• 2002

In this paper, we propose a hybrid method which is mixed with frame selection and weighting model rank method, based on GMM(gaussian mixture model), for real-time text-independent speaker recognition system. In the system, maximum likelihood estimation was used for GMM parameter optimization, and maximum likelihood was used for recognition basically Proposed hybrid method has two steps. First, likelihood score was calculated with speaker models and test data at frame level, and the difference is calculated between the biggest likelihood value and second. And then, the frame is selected if the difference is bigger than threshold. The second, instead of calculated likelihood, weighting value is used for calculating total score at each selected frame. Cepstrum coefficient and regressive coefficient were used as feature parameters, and the database for test and training consists of several data which are collected at different time, and data for experience are selected randomly In experiments, we applied each method to baseline system, and tested. In speaker recognition experiments, proposed hybrid method has an average of 4% higher recognition accuracy than frame selection method and 1% higher than W method, implying the effectiveness of it.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.1
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• pp.15-26
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• 2003

Ultrasonic inspection methods are widely used for detecting flaws in materials. The signal analysis step plays a crucial part in the data interpretation process. A number of signal processing methods have been proposed to classify ultrasonic flaw signals. One of the more popular methods involves the extraction of an appropriate set of features followed by the use of a neural network for the classification of the signals in the feature space. This paper describes an alternative approach which uses the least mean square (LMS) method and expectation maximization (EM) algorithm with the model based deconvolution which is employed for classifying nondestructive evaluation (NDE) signals from steam generator tubes in a nuclear power plant. The signals due to cracks and deposits are not significantly different. These signals must be discriminated to prevent from happening a huge disaster such as contamination of water or explosion. A model based deconvolution has been described to facilitate comparison of classification results. The method uses the space alternating generalized expectation maximization (SAGE) algorithm In conjunction with the Newton-Raphson method which uses the Hessian parameter resulting in fast convergence to estimate the time of flight and the distance between the tube wall and the ultrasonic sensor Results using these schemes for the classification of ultrasonic signals from cracks and deposits within steam generator tubes are presented and showed a reasonable performances.

• Journal of the Korean Society for Nondestructive Testing
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• v.25 no.1
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• pp.27-35
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• 2005

Ultrasonic inspection methods are widely used for detecting flaws in materials. The signal analysis step plays a crucial part in the data interpretation process. A number of signal processing methods have been proposed to classify ultrasonic flaw signals. One of the more popular methods involves the extraction of an appropriate set of features followed by the use of a neural network for the classification of the signals in the feature spare. This paper describes an alternative approach which uses the least mean square (LMS) method and exportation maximization (EM) algorithm with the model based deconvolution which is employed for classifying nondestructive evaluation (NDE) signals from steam generator tubes in a nuclear power plant. The signals due to cracks and deposits are not significantly different. These signals must be discriminated to prevent from happening a huge disaster such as contamination of water or explosion. A model based deconvolution has been described to facilitate comparison of classification results. The method uses the space alternating generalized expectation maximiBation (SAGE) algorithm ill conjunction with the Newton-Raphson method which uses the Hessian parameter resulting in fast convergence to estimate the time of flight and the distance between the tube wall and the ultrasonic sensor. Results using these schemes for the classification of ultrasonic signals from cracks and deposits within steam generator tubes are presented and showed a reasonable performances.

• Journal of Korea Water Resources Association
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• v.49 no.2
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• pp.155-164
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• 2016

Algal blooms not only destroy fish habitats but also diminish biological diversity of ecosystem which results into water quality deterioration of 4 major rivers in South Korea. The relationship between algal bloom and environmental factors had been analyzed through the cross-correlation function between concentration of chlorophyll a and other environmental factors. However, time series of cross-correlations can be affected by the stochastic structure such auto-correlated feature of other controllers. In order to remove external effect in the correlation analysis, the pre-whitening procedure was implemented into the cross correlation analysis. The modeling process is consisted of a series of procedure (e.g., model identification, parameter estimation, and diagnostic checking of selected models). This study provides the exclusive correlation relationship between algae concentration and other environmental factors. The difference between the conventional correlation using raw data and that of pre-whitened series was discussed. The process implemented in this paper is useful not only to identify exclusive environmental variables to model Chl-a concentration but also in further extensive application to configure causality in the environment.

• Journal of Korea Water Resources Association
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• v.47 no.3
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• pp.285-295
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• 2014

We applied the ISPSO-GLUE method, which integrates the Isolated-Speciation-based Particle Swarm Optimization (ISPSO) with the Generalized Likelihood Uncertainty Estimation (GLUE) method, to the uncertainty analysis of the Topography Model (TOPMODEL) and compared its performance with that of the GLUE method. When we performed the same number of model runs for the both methods, we were able to identify the point where the performance of ISPSO-GLUE exceeded that of GLUE, after which ISPSOGLUE kept improving its performance steadily while GLUE did not. When we compared the 95% uncertainty bounds of the two methods, their general shapes and trends were very similar, but those of ISPSO-GLUE enclosed about 5.4 times more observed values than those of GLUE did. What it means is that ISPSOGLUE requires much less number of parameter samples to generate better performing uncertainty bounds. When compared to ISPSO-GLUE, GLUE overestimated uncertainty in the recession limb following the maximum peak streamflow. For this recession period, GLUE requires to find more behavioral models to reduce the uncertainty. ISPSO-GLUE can be a promising alternative to GLUE because the uncertainty bounds of the method were quantitatively superior to those of GLUE and, especially, computationally expensive hydrologic models are expected to greatly take advantage of the feature.

• Analytical Science and Technology
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• v.25 no.5
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• pp.292-299
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• 2012

GC/MS has been utilized for many applications due to great resolution and reproducibility, which made it possible to build up the database of mass spectrum, while HS-SPME has the advantage of solventfree extraction of volatile compounds. The combination of these two methods, HS-SPME GC/MS, enabled many scientific applications with various possibilities. In this study, the analysis of trail pheromone excreted from live Camponotus japonicus with the feature of solvent-free extraction was carried out and the optimization for this analysis was performed. The major compounds detected were n-decane, n-undecane, and n-tridecane. Optimization for the best detection of these hydrocarbons was processed in the point of SPME parameter (selection of fiber, extraction temperature, extraction time, etc.). The advantage of the analysis of live sample is to analyze phenomenon right after it is excreted by ants. But the experimental process has restriction of extraction temperature and time because of the analysis of live ants. Establishing the process of HS-SPME GC/MS applied to live samples shown in this study can be a breakthrough for the ecofriendly and ethical research of live things.