• Geophysics and Geophysical Exploration
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• v.16 no.3
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• pp.131-138
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• 2013

We developed a method for inverting magnetic data to image 2D susceptibility models. The major difficulty in the inversion of the potential data is the nonuniqueness. Furthermore, generally the number of inversion blocks are greater than the number of the magnetic data available, and thus the magnetic inversion leads to under-determined problem, which aggravates the nonuniqueness. When the magnetic data were inverted by the general least-squares method, the anomalous susceptibility would be concentrated near the surface in the inverted section. To overcome this nonuniqueness problem, we propose a new resolution model constraint that is calculated from the parameter resolution. The model constraint imposes large penalty on the model parameter with good resolution, on the other hand small penalty on the model parameter with poor resolution. Thus, the deep-seated model parameter, generally having poor resolution, can be effectively resolved. The developed inversion algorithm is applied to the inversion of the synthetic data for typical models of magnetic anomalies and is tested on real airborne data obtained at the Okcheon belt of Korea.

• Journal of the Korean GEO-environmental Society
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• v.18 no.2
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• pp.47-51
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• 2017

In this study, the optimization algorithm by inverse analysis that is the core of the adaptive management technique was adopted to update the soil engineering properties based on the ground response during the construction. Adaptive management technique is the framework wherein construction and design procedures are adjusted based on observations and measurements made as construction proceeds. To evaluate the performance of the adaptive management technique, the numerical simulation for the triaxial tests and the synthetic deep excavation were conducted with the Hardening Soil model. To effectively conduct the analysis, the effective parameters among the parameters employed in the model were selected based on the composite scaled sensitivity analysis. The results from the undrained triaxial tests performed with soft Chicago clays were used for the parameter calibration. The simulation for the synthetic deep excavation were conducted assuming that the soil engineering parameters obtained from the triaxial simulation represent the actual field condition. These values were used as the reference values. The observation for the synthetic deep excavation simulations was the horizontal displacement of the support wall that has the highest composite scaled sensitivity among the other possible observations. It was found that the horizontal displacement of the support wall with the various initial soil properties were converged to the reference displacement by using the adaptive management technique.

• Journal of the Korean earth science society
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• v.37 no.5
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• pp.277-285
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• 2016

We introduce a depth scaling strategy to improve the accuracy of frequency-domain elastic full waveform inversion (FWI) using the new pseudo-Hessian matrix for seismic data without low-frequency components. The depth scaling strategy is based on the fact that the damping factor in the Levenberg-Marquardt method controls the energy concentration in the gradient. In other words, a large damping factor makes the Levenberg-Marquardt method similar to the steepest-descent method, by which shallow structures are mainly recovered. With a small damping factor, the Levenberg-Marquardt method becomes similar to the Gauss-Newton methods by which we can resolve deep structures as well as shallow structures. In our depth scaling strategy, a large damping factor is used in the early stage and then decreases automatically with the trend of error as the iteration goes on. With the depth scaling strategy, we can gradually move the parameter-searching region from shallow to deep parts. This flexible damping factor plays a role in retarding the model parameter update for shallow parts and mainly inverting deeper parts in the later stage of inversion. By doing so, we can improve deep parts in inversion results. The depth scaling strategy is applied to synthetic data without lowfrequency components for a modified version of the SEG/EAGE overthrust model. Numerical examples show that the flexible damping factor yields better results than the constant damping factor when reliable low-frequency components are missing.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.5 s.305
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• pp.19-26
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• 2005

In this paper, a new method for obtaining three-dimensional shape of an object by measuring relative blur between images using wavelet analysis has been described. Most of the previous methods use inverse filtering to determine the measure of defocus. These methods suffer from some fundamental problems like inaccuracies in finding the frequency domain representation, windowing effects, and border effects. Besides these deficiencies, a filter, such as Laplacian of Gaussian, that produces an aggregate estimate of defocus for an unknown texture, can not lead to accurate depth estimates because of the non-stationary nature of images. We propose a new depth from defocus (DFD) method using wavelet analysis that is capable of performing both the local analysis and the windowing technique with variable-sized regions for non-stationary images with complex textural properties. We show that normalized image ratio of wavelet power by Parseval's theorem is closely related to blur parameter and depth. Experimental results have been presented demonstrating that our DFD method is faster in speed and gives more precise shape estimates than previous DFD techniques for both synthetic and real scenes.

• Journal of the Mineralogical Society of Korea
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• v.16 no.2
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• pp.125-133
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• 2003

Saponite was synthesized from talc by hydrothermal method. The starting material was prepared by adding ($NO_3$)$Al_3$$.$$9H_2$O and Mg($NO_3$)$_2$$.$$6H_2$O solution to the talc powder. which was previously activated in air at 800 $^{\circ}C$ together with $Na_2$$CO_3$. The alkalinity of the solution was controlled by $NH_4$OH solution. The autoclaving was carried out in the closed stainless steel vessel (about 1 liter) for 40 hours under the pressure of 25 kgf/$\textrm{cm}^2$ at $ 230^{\circ}C$ The characterization of the reaction product shows that saponite was crystallized successfully. After the experimental results, pressure was not sensitive parameter in the range of 25 ∼ 75 kgf/$\textrm{cm}^2$, but longer reaction time results in better crystallinity.

• The KIPS Transactions:PartB
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• v.9B no.5
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• pp.563-570
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• 2002

Robust extraction of 3D facial features and global motion information from 2D image sequence for the MPEG-4 SNHC face model encoding is described. The facial regions are detected from image sequence using multi-modal fusion technique that combines range, color and motion information. 23 facial features among the MPEG-4 FDP (Face Definition Parameters) are extracted automatically inside the facial region using color transform (GSCD, BWCD) and morphological processing. The extracted facial features are used to recover the 3D shape and global motion of the object using paraperspective camera model and SVD (Singular Value Decomposition) factorization method. A 3D synthetic object is designed and tested to show the performance of proposed algorithm. The recovered 3D motion information is transformed into global motion parameters of FAP (Face Animation Parameters) of the MPEG-4 to synchronize a generic face model with a real face.

• The KIPS Transactions:PartC
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• v.11C no.5
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• pp.621-632
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• 2004

Recent measurement studies of real teletraffic data in modern telecommunication networks have shown that self-similar (or fractal) processes may provide better models of teletraffic in modern telecommunication networks than Poisson processes. If this is not taken into account, it can lead to inaccurate conclusions about performance of telecommunication networks. Thus, an important requirement for conducting simulation studies of telecommunication networks is the ability to generate long synthetic stochastic self-similar sequences. A new generator of pseu-do-random self-similar sequences, based on the fractional Gaussian nois and a wavelet transform, is proposed and analysed in this paper. Specifically, this generator uses Daubechies wavelets. The motivation behind this selection of wavelets is that Daubechies wavelets lead to more accurate results by better matching the self-similar structure of long range dependent processes, than other types of wavelets. The statistical accuracy and time required to produce sequences of a given (long) length are experimentally studied. This generator shows a high level of accuracy of the output data (in the sense of the Hurst parameter) and is fast. Its theoretical algorithmic complexity is 0(n).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.1
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• pp.1-8
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• 2014

The positions, attitudes, and internal orientation parameters of three line scanners are critical factors in order to acquire the accurate location of objects on the ground. Based on the assumption that positions and attitudes of the sensors are derived either from direct geo-referencing which of using Global Positioning Systems (GPS) and Inertial Navigation Systems (INS), or from indirect geo-referencing which of using Ground Control Points (GCPs), this paper describes on biased effects of Internal Orientation Parameter (IOP) on the ground. The research concentrated on geometrical explanations of effects from different focal length biases on the ground. The Synthetic data was collected by reasonable flight trajectories and attitudes of three line scanners. The result of experiments demonstrated that the focal length bias in case of indirect geo-referencing does not have critical influences on the quality of reconstructed ground space. Also, the relationships between IO parameters and EO parameters were found by the correlation analysis. In fact, the focal length bias in case of the direct geo-referencing caused significant errors on coordinates of reconstructed objects. The RMSE values along the vertical direction and the amount of focal length bias turned out to be almost perfect linear relationship.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.6
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• pp.547-555
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• 2015

The vegetation index is a crucial parameter in many biophysical studies of vegetation, and is also a valuable content in ecological processes researching. The OVIs (Optical Vegetation Index) that of using multispectral and hyperspectral data have been widely investigated in the literature, while the RVI (Radar Vegetation Index) that of considering volume scattering measurement has been paid relatively little attention. Also, there was only some efforts have been put to fuse the OVI with the RVI as an integrated vegetation index. To address this issue, this paper presents a novel FVI (Fusion Vegetation Index) that uses multispectral and full-PolSAR (Polarimetric Synthetic Aperture Radar) data. By fusing a NDVI (Normalized Difference Vegetation Index) of RapidEye and an RVI of C-band Radarsat-2, we demonstrated that the proposed FVI has higher separability in different vegetation types than only with OVI and RVI. Also, the experimental results show that the proposed index not only has information on the vegetation greenness of the NDVI, but also has information on the canopy structure of the RVI. Based on this preliminary result, since the vegetation monitoring is more detailed, it could be possible in various application fields; this synergistic FVI will be further developed in the future.

• Journal of Computing Science and Engineering
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• v.6 no.3
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• pp.219-226
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• 2012

Recently, shape analysis of human organs has achieved much attention, owing to its potential to localize structural abnormalities. For a group-wise shape analysis, it is important to accurately restore the shape of a target structure in each subject and to build the inter-subject shape correspondences. To accomplish this, we propose a shape modeling method based on the Laplacian deformation framework. We deform a template model of a target structure in the segmented images while restoring subject-specific shape features by using Laplacian surface representation. In order to build the inter-subject shape correspondences, we implemented the progressive weighting scheme for adaptively controlling the rigidity parameter of the deformable model. This weighting scheme helps to preserve the relative distance between each point in the template model as much as possible during model deformation. This area-preserving deformation allows each point of the template model to be located at an anatomically consistent position in the target structure. Another advantage of our method is its application to human organs of non-spherical topology. We present the experiments for evaluating the robustness of shape modeling against large variations in shape and size with the synthetic sets of the second cervical vertebrae (C2), which has a complex shape with holes.