• Proceedings of the Computational Structural Engineering Institute Conference
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• 2005.04a
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• pp.55-62
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• 2005

In this paper, a CAB/CAE integrated optimal design system is developed, in which design and analysis process is automated using CAD/CAE softwares, for a complicated model for which parametric modeling provided by CAD software is not possible. CAD modeling process is automated by using UG/OPEN API function and UG/Knowledge Fusion provided by Unigraphics. The generated model is transferred to the analysis code ANSYS in parasolid format. Visual DOC software is used for optimization. The system is developed for PLS(Plasma Lighting System), which is a next generation illumination system that is used to illuminate stadium or outdoor advertizing panel. The PLS system consists of more then 20 components, which requires a lot of human efforts in modeling and analysis. The analysis for PLS includes static load, wind load and impact load analysis. As a result of analysis, it is found that the most critical component is a tilt assembly, which links lower & upper body assembly. For more reliable analysis, experiment is conducted using MTS and compared with the Finite element analysis result. The objective in the optimization is to minimize the material volume under allowable stresses. The design variables are three parameters in the tilt assembly that are chosen to be the most sensitive in stress values of twelve parameters. Gradient based method and RSM(Response Surface Method) are used for the algorithm and the results are compared. As a result of optimization, the maximum stress is reduced by 57%.

• The Korea Journal of Herbology
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• v.22 no.2
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• pp.97-102
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• 2007

Objectives : This study presents a high performance liquid chromatography - electrospray ionization-mass spectrometer (HPLC-MS/MS) methods for the quantitative and qualitative analysis of various active components in Samul-tang, which is composed of four crude herbs. Methods : HPLC-ESI-MS/MS for the determinations of paeoniflorin and 5-HMF (5-hydroxymethyl 2-furaldehyde) in the Samul-tang, the separation method was performed on an COSMOS1L 5C18-AR-Il (2.0 X 150 mm I.D.) column by gradient elution with 0.1% acetic acid and 5% CH3CN in water (A)-0.1% acetic acid and 5% H20 in CH3CN (B) as the mobile phase at a flow-rate of 300 ${\mu}L/min$ with detection at quadrupole mass spectrometer. The all marker substances were always detected as the base peaks in the positive ion mode. Results : The paeoniflorin of Paeoniae Radix in Samul-tang showed a strong base peak [M+H2O]+ in the positive detection mode to give the following as; paeoniflorin (498.109 [M+H2O]+, 479.8 [M]+, 301 [M-glucose]+, 179.3 [glucose]+). Based on the HPLC retnetion time and MS of standard compounds confirmed the identity of active compounds in Rehmanniae Radix Preparata as follows; 5-HMF (127.0[M+H]+, 109.3 [M-OH]+) in the positive ion mode. Conclusion : According to the above results, HPLC-ESI-MS method permits assignment of tentative structures such as paeoniflorin and 5-HMF in the Samul-tang.

• Transactions of the Korean Society of Mechanical Engineers
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• v.15 no.6
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• pp.2109-2124
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• 1991

A simulation program is developed to analyse the performance of an axial flow turbine stage based on the meanline prediction method. The gradient projection method is utilized to minimize the aerodynamic losses under the specified constraints on such as flow coefficient, total pressure ratio, stage power and blade loading coefficient. After obtaining the optimum point for minimizing the stage loss, a sensitivity analysis is carried out ground the optimum point to find the effects of the design variables and the design constraints on the stage performance. The result of the senitivity analysis under a constant blade loading coefficient shows that the total loss is more sensitive to the mean diameter, the absolute flow angle at nozzle outlet, the relative flow angle at rotor outlet and the axial mean velocity compared to the chords and the pitches. Moreover, the design constraints on the degree of reaction at root and the blade length-to-diameter ratio are found to be most influencial on the maximization of the overall aerodynamic efficiency.

• Journal of Broadcast Engineering
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• v.21 no.1
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• pp.66-75
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• 2016

In this paper, we present a new method to reduce crosstalk of a glasses-free three-dimensional (3D) display using a multi-view image processing technique. Since crosstalk makes the current view image mixed with its neighboring ones, the output 3D image becomes severely blurred. We apply adaptive depth retargeting and view gradient-based crosstalk inverse filtering onto a multi-view image to minimize crosstalk of the glasses-free 3D display. In addition, overflow and underflow pixels are compensated by epipolar image pixel interpolation so that visual artifacts are minimized. Experimental results show that the proposed method reduces crosstalk more efficiently than the previous work while improving 3D image quality.

• Journal of Broadcast Engineering
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• v.21 no.1
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• pp.24-35
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• 2016

By estimating environment light distribution, we can generate realistic shadow images in AR(augmented reality). When we estimate light distribution without sensing equipment, environment light model, geometry of virtual object, and surface reflection property are needed. Previous study using 3D marker builds surrounding light environment with a geodesic dome model and analyzes shadow images. Because this method employs candidate shadow maps in initial scene setup, however, it is difficult to estimate precise light information. This paper presents a novel light estimation method based on hierarchical light distribution model subdivision. By using an overlapping area ratio of the segmented shadow and candidate shadow map, we can make hierarchical subdivision of light geodesic dome.

• Korean Journal of Remote Sensing
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• v.33 no.4
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• pp.423-436
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• 2017

This paper presents a deep learning-based road segmentation framework from very high-resolution orthophotos. The proposed method uses Deep Convolutional Autoencoders for end-to-end mapping of orthophotos to road segmentations. In addition, a set of post-processing steps were applied to make the model outputs GIS-ready data that could be useful for various applications. The optimization of the model's parameters is explained which was conducted via grid search method. The model was trained and implemented in Keras, a high-level deep learning framework run on top of Tensorflow. The results show that the proposed model with the best-obtained hyperparameters could segment road objects from orthophotos at an average accuracy of 88.5%. The results of optimization revealed that the best optimization algorithm and activation function for the studied task are Stochastic Gradient Descent (SGD) and Exponential Linear Unit (ELU), respectively. In addition, the best numbers of convolutional filters were found to be 8 for the first and second layers and 128 for the third and fourth layers of the proposed network architecture. Moreover, the analysis on the time complexity of the model showed that the model could be trained in 4 hours and 50 minutes on 1024 high-resolution images of size $106{\times}106pixels$, and segment road objects from similar size and resolution images in around 14 minutes. The results show that the deep learning models such as Convolutional Autoencoders could be a best alternative to traditional machine learning models for road segmentation from aerial photographs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.3
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• pp.405-417
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• 2001

In this paper, since we currently using surveillance system of analog type bring about waste of resource and efficiency deterioration problems, we describe new solution that design and implementation to the digital surveillance system of new type applying compression techniques and encoding techniques of image data using MPEG-2 international standard. Also, we proposed fast motion estimation algorithm requires much less than the convectional digital surveillance camera system. In this paper a fast motion estimation algorithm is proposed the MPEG-2 video encoding. This algorithm is based on a hybrid use of the block matching technique and gradient technique. Also, we describe a method of moving object extraction directly using MPEG-2 video data. Since proposed method is very simple and requires much less computational power than the conventional object detection methods. In this paper we don't use specific H/W and this system is possible only software encoding, decoding and transmission real-time for image data.

• Proceedings of the KSRS Conference
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• v.2
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• pp.831-835
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• 2006

NOAA/AVHRR data were used to analyze sea surface temperatures (SSTs) and thermal fronts (TFs) in the Korean seas. Temporal and spatial analyses were based on data from 1993 to 2000. Harmonic analysis revealed mean SST distributions of $10{\sim}25^{\circ}C$. Annual amplitudes and phases were $4{\sim}11^{\circ}C$ and $210{\sim}240^{\circ}$, respectively. Inverse distributions of annual amplitudes and phases were found for the study seas, with the exception of the East China Sea, which is affected by the Kuroshio Current. Areas with high amplitudes (large variations in SSTs) showed 'low phases' (early maximum SST); areas with low amplitudes (small variations in SSTs) had 'high phases' (late maximum SST). Empirical orthogonal function (EOF) analyses of SSTs revealed a first-mode variance of 97.6%. Annually, greater SST variations occurred closer to the continent. Temporal components of the second mode showed higher values in 1993, 1994, and 1995. These phenomena seemed to the effect of El $Ni{\tilde{n}}o$. The Sobel edge detection method (SEDM) delineated four fronts: the Subpolar Front (SPF) separating the northern and southern parts of the East Sea; the Kuroshio Front (KF) in the East China Sea, the South Sea Coastal Front (SSCF) in the South Sea, and a tidal front (TDF) in the West Sea. Thermal fronts generally occurred over steep bathymetric slopes. Annual amplitudes and phases were bounded within these frontal areas. EOF analysis of SST gradient values revealed the temporal and spatial variations in the TFs. The SPF and SSCF were most intense in March and October; the KF was most significant in March and May.

• The Journal of the Acoustical Society of Korea
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• v.22 no.2
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• pp.145-152
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• 2003

In this paper, assuming that the score of speech utterance is the product of HMM log likelihood and HMM weight, we propose a new method that HMM weights are adapted iteratively like the general MCE training. The proposed method adjusts HMM weights for better performance using delta coefficient defined in terms of misclassification measure. Therefore, the parameter estimation and the Viterbi algorithms of conventional 1:.um can be easily applied to the proposed model by constraining the sum of HMM weights to the number of HMMs in an HMM set. Comparing with the general segmental MCE training approach, computing time decreases by reducing the number of parameters to estimate and avoiding gradient calculation through the optimal state sequence. To evaluate the performance of HMM-based speech recognizer by weighting HMM likelihood, we perform Korean isolated digit recognition experiments. The experimental results show better performance than the MCE algorithm with state weighting.

• 한국전산유체공학회:학술대회논문집
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• 2008.03a
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• pp.177-180
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• 2008

The objective of this study is to get simulation data about pulsatile flow of a non-Newtonian fluid through a bifurcated tube. All the process was based on CFD method, with a commercial FVM code, SC/Tetra ver. 6.0 for solving, and with CATIA R16 for generating geometries. To define a non-Newtonian fluid, the following viscous models are used; the Powell-Eyring model, the modified Powell-Eyring model, the Cross model, the modified Cross model, the Carreau model, the Carreau-Yasuda model and the modified Power Law model. The flow calculation data using each model were compared with the other data of a existing paper. Finally, the Carreau model was recognized to give the best result with the SC/Tetra code, and the succeeding simulations are made with the model. For the pulsating flow condition, the sine wave type velocity profile is given as the inlet boundary condition. To investigate the effect of geometries and mesh, the pre-test is carried out with various curvature conditions of the bifurcated corner, and then with various mesh conditions. The final process is to calculate flow variables such as the wall shear stress (WSS) and the wall shear stress gradient (WSSG). To validate all the result, the simulation is compared with the existing data of the other papers. Generally speaking, there is a noticeable difference in the maximum and minimum value of WSS. It is not sure that the values in each data are on the exactly same location. However, the overall trend is similar. The next study needs to investigate the same situation by experimental method. Furthermore, if the flow is simulated with more pulsatile conditions, more data of flow field through a bifurcated tube could be achieved.