• Proceedings of the Korean Magnestics Society Conference
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• 1991.05a
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• pp.97-98
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• 1991

• Proceedings of the Korean Magnestics Society Conference
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• 1996.10a
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• pp.104-105
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• 1996

• Proceedings of the Korean Information Science Society Conference
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• 2007.10a
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• pp.209-210
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• 2007

• Proceedings of the Korean Information Science Society Conference
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• 2007.10a
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• pp.68-69
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• 2007

• Proceedings of the Korean Magnestics Society Conference
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• 1995.10a
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• pp.38-39
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• 1995

• Economic and Environmental Geology
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• v.27 no.1
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• pp.41-47
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• 1994

A fast Hankel transform (FHT) algorithm (Anderson, 1982) is applied to numerical evaluation of many Green's tensor integrals encountered in three-dimensional electromagnetic modeling using integral equations. Efficient computation of Hankel transforms is obtained by a combination of related and lagged convolutions which are available in the FHT. We express Green's tensor integrals for a layered half-space, and rewrite those to a form of related functions so that the FHT can be applied in an efficient manner. By use of the FHT, a complete or full matrix of the related Hankel transform can be rapidly and accurately calculated for about the same computation time as would be required for a single direct convolution. Computing time for a five-layer half-space shows that the FHT is about 117 and 4 times faster than conventional direct and multiple lagged convolution methods, respectively.

• Journal of the Korean Society of Hazard Mitigation
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• v.1 no.3 s.3
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• pp.123-136
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• 2001

The purpose of application of moment tensor inversion method is to determine source parameters, such as, focal mechanism, seismic moment and source depth. This paper presents results of focal mechanism solutions of 14 recent events with magnitudes ranging from M3.3 to M4.8 by using moment tensor inversion method called TDMT_INV. The strike of faults is in the direction of NE-SW and NW-SE with the movement of strike-slip or strike-slip of minor reverse component. The compressional axis of the stress field is predominantly E-W or ENE-WSW except for some faults, which are distributed at Ryongnam Massif and Wonsan, they have a compressional axis of N-S or NNW-SSE.

• Journal of Advanced Navigation Technology
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• v.21 no.6
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• pp.674-679
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• 2017

As the importance of the 4th industrial revolution and ICT technology increased, it became a software centered society. Existing software training was limited to the composition of the learning environment, and a lot of costs were incurred early. In order to solve these problems, a learning method using a web compiler was developed. The web compiler supports various software languages and shows compilation results to the user via the web. However, Web compilers that support artificial intelligence technology are missing. In this paper, we designed and implemented a tensor flow based web compiler, Google's artificial intelligence library. We implemented a system for learning artificial intelligence by building a meteorJS based web server, implementing tensor flow and tensor flow serving, Python Jupyter on a nodeJS based server. It is expected that it can be utilized as a tool for learning artificial intelligence in software centered society.

• KIISE Transactions on Computing Practices
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• v.23 no.11
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• pp.625-631
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• 2017

The stock price prediction for stock markets remains an unsolved problem. Although there have been various overtures and studies to predict the price of stocks scientifically, it is impossible to predict the future precisely. However, stock price predictions have been a subject of interest in a variety of related fields such as economics, mathematics, physics, and computer science. In this paper, we will study fluctuation patterns of stock prices and predict future trends using the Deep learning. Therefore, this study presents the three deep learning models using Tensorflow, an open source framework in which each learning model accepts different input features. We expand the previous study that used simple price data. We measured the performance of three predictive models increasing the number of priced-based input features. Through this experiment, we measured the performance change of the predictive model depending on the price-based input features. Finally, we compared and analyzed the experiment result to evaluate the impact of the price-based input features in stock price prediction.

• Progress in Medical Physics
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• v.18 no.4
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• pp.214-220
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• 2007

Diffusion tensor tractorgraphy which is based on line propagation method with brute force approach is implemented and the vector correlation function is proposed in addition to the conventional fractional anisotrophy value as a criterion to select seed points. For the whole tractography, the proposed method used 41 % less seed points than the conventional brute force approach for $FA{\geq}0.3$ and most of the fiber tracks in the outer region of white matter were removed. For the corticospinal tract passing through region of interest, the proposed method has produced similar results with 50% less seed points than conventional one.