• Progress in Superconductivity
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• v.13 no.2
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• pp.85-89
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• 2011

Using the density functional theory and its combination to the dynamical mean field theory (DMFT), we have studied the electronic and magnetic structures of Fe-based superconductors, $AFe_2As_2$ (A=Ca, Sr, Ba). Our results for the electronic structure agree well with existing angle resolved photoemission spectroscopy (ARPES) data. The temperature dependent magnetization has been calculated using DMFT, and the magnetic transition temperatures are reasonably consistent with the experimentally observed trend for three compounds.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3630-3656
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• 2018

Degree distribution can provide basic information for structural characteristics and internal relationship in social network. It is a critical procedure for social network topology analysis. In this paper, based on the mean-field theory, we study a special type of social network with exponential distribution of time intervals. First of all, in order to improve the accuracy of analysis, we propose a spreading coefficient algorithm based on intimate relationship, which determines the number of the joined members through the intimacy among members. Then, simulation show that the degree distribution of follows the power-law distribution and has small-world characteristics. Finally, we compare the performance of our algorithm with the existing algorithms, and find that our algorithm improves the accuracy of degree distribution as well as reducing the time complexity significantly, which can complete 29.04% higher precision and 40.94% lower implementation time.

• ETRI Journal
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• v.14 no.3
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• pp.67-74
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• 1992

Discrete variable을 갖는 Mean Field Theory(MFT) neural network은 이미 많은 combinatorial optimization 문제에 적용되어져 왔다. 본 논문에서는 이를 확장하여 continuous variable을 갖는 mean field annealing을 제안하고, 이러한 network에서 integral로 표현되는 spin average를 mean field에 기초하여 어렵지 않게 구할 수 있는 one-variable stochastic simulated annealing을 제안하였다. 이런 방법으로 multi-body problem을 single-body problem으로 바꿀 수 있었다. 또한 이 방법을 이용한 응용으로서 통계학에서 잘 알려진 문제중의 하나인 quantification analysis 문제에 적용하여 타당성을 보였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.206-211
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• 2006

The quantification analysis problem is that how the m entities that have n characteristics can be linked to p-dimension space to reflect the similarity of each entity In this paper, the optimization approach for the quantification analysis problem using neural networks is suggested, and the performance is analyzed The computation of average variation volume by mean field theory that is analytical approximated mobility of a molecule system and the annealed mean field neural network approach are applied in this paper for solving the quantification analysis problem. As a result, the suggested approach by a mean field annealing neural network can obtain more optimal solution than the eigen value analysis approach in processing costs.

• 한국초전도학회:학술대회논문집
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• v.12
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• pp.13-13
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• 2002

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2000.05a
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• pp.122-126
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• 2000

In particle or short-fiber reinforced composites cracking of the reinforcements is a significant damage mode because the broken reinformcements lose load carrying capacity . The average stress in the inhomogeneity represents its load carrying capacity and the difference between the average stresses of the intact and broken inhomogeneities indicates the loss of load carrying capacity due to cracking damage. The composite in damage process contains intact and broken reinforcements in a matrix, An incremental constitutive relation of particle or short-fiber reinforced composites including the progressive cracking damage of the reinforcements have been developed based on the Eshelby's equivalent inclusion method and Mori-Tanaka's mean field concept. influence of the cracking damage on the Eshelby's equivalent inclusion method and Mori-Tanaka's mean field concept. Influence of the cracking damage on the stress-strain response of the composites is demonstrated.

• Journal of the Korean Mathematical Society
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• v.53 no.5
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• pp.1077-1100
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• 2016

We develop an invariant local theory of Lorentz surfaces in pseudo-Euclidean 4-space by use of a linear map of Weingarten type. We find a geometrically determined moving frame field at each point of the surface and obtain a system of geometric functions. We prove a fundamental existence and uniqueness theorem in terms of these functions. On any Lorentz surface with parallel normalized mean curvature vector field we introduce special geometric (canonical) parameters and prove that any such surface is determined up to a rigid motion by three invariant functions satisfying three natural partial differential equations. In this way we minimize the number of functions and the number of partial differential equations determining the surface, which solves the Lund-Regge problem for this class of surfaces.

• The Transactions of the Korea Information Processing Society
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• v.2 no.3
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• pp.417-424
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• 1995

This paper describes MFT(Mean Field Theory) neural network with continuous with continuous variables is applied to quantification analysis problem. A quantification analysis problem, one of the important problems in statistics, is NP complete and arises in the optimal location of objects in the design space according to the given similarities only. This paper presents a MFT neural network with continuous variables for the quantification problem. Starting with reformulation of the quantification problem to the penalty problem, this paper propose a "one-variable stochastic simulated annealing(one-variable SSA)" based on the mean field approximation. This makes it possible to evaluate of the spin average faster than real value calculating in the MFT neural network with continuous variables. Consequently, some experimental results show the feasibility of this approach to overcome the difficulties to evaluate the spin average value expressed by the integral in such models.ch models.

• Journal of Ocean Engineering and Technology
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• v.33 no.3
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• pp.229-235
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• 2019

In this study, a two-dimensional oscillating foil with forward speed in a propagating wave flow field was considered. The time-mean power to maintain the heaving and pitching motions of the foil was analyzed using the perturbation theory in an ideal fluid. The power, which was a non-linear quantity of the second-order, was expressed in terms of the quadratic transfer functions related to the mutual product of the heaving and pitching motions and incoming vertical flow. The effects of the pivot point and phase difference among the disturbances were studied. The negative power, which indicates energy extraction from the fluid, is shown as an example calculation.

• Proceedings of the Korean Magnestics Society Conference
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• 2004.12a
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• pp.1-1
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• 2004