• Korea Trade Review
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• v.44 no.1
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• pp.31-44
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• 2019

This study examines the normalization of Korean GM management between the Korean government and GM in terms of external negotiation game and internal negotiation game using Putnam's Two-Level Games. In addition, GM's Win-set change and negotiation strategy were analyzed. This analysis suggested implications for the optimal negotiation strategy for mutual cooperation between multinational corporations and local governments in the global business environment. First, the negotiation strategy for Korea's normalization of GM management in Korea can be shifted to both the concession theory and the opposition theory depending on the situation change and the government policy centered on the cautious theory. Second, GM will maximize its bargaining power through 'brink-end tactics' by utilizing the fact that the labor market is stabilized, which is the biggest weakness of the Korean government, while maintaining a typical Win-set reduction strategy. GM will be able to restructure at any time in terms of global management strategy, and if the financial support of the Korean government is provided, it will maintain the local factory but withdraw the local plant at the moment of stopping the support. In negotiations on the normalization of GM management in Korea, it is necessary to prepare a problem and countermeasures for various scenarios and to maintain a balance so that the policy does not deviate to any one side.

• Journal of the Korean School Mathematics Society
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• v.6 no.1
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• pp.27-43
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• 2003

This paper introduces some theories that can be effectively applied for the development of teaching and learning mathematics using fuzzy theory developed by Zadeh who defined fuzzy set and knowledge space by Doignon and Falmagne. Especially, we expect that two theories mentioned above are expected to solve the situation that could not be taken care of the present evaluation method.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.9
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• pp.1055-1063
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• 1999

This paper present a conceptual possibilistic approach using fuzzy set theory to manage the uncertainties in the given reliability input date of the practical power system. In this paper, an algorithm is introduced to calculate the possibilstic reliability indices according to the degree of uncertainty in the given data. The probability distribution function can be transformed into an appropriate possibilstic representation using the probability-Possibility Consistency principle(PPCP) algorithm. In this the algorithm, the transformation is performation by making a compromise between the transformation consistency and the human updating experience. Fuzzy classifcation theory is applied to reduced the number of load data. The fuzzy classification method determines the closeness of load data points by assigning them to various clusters and then determening the distance between the clusters. The IEEE-RTS with 32-generating units is used to demonstrate the capability of the proposed algorithm.

• The Mathematical Education
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• v.12 no.2
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• pp.1-4
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• 1974

Matroid theory, which was first introduced in 1935 by Whitney (2), is a branch of combinational mathematics which has some very much to the fore in the last few years. H. Whitney had just spent several years working in the field of graph theory, and had noticed several similarities between the ideas of independence and rank in graph theory and those of linear independence and dimension in the study of vector spaces. A matroid is essentially a set with some kind of 'independence structure' defined on it. There are several known results concerning how matroids can be induced from given matroid by a digraph. The purpose of this note is to show that, given a matroid M$_{0}$ (N) and a digraph $\Gamma$(N), then a new matroid M(N) is induced, where A⊆N is independent in M(N) if and only if A is the set of initial vertices of a family of pairwise-vertex-disjoint paths with terminal vertices independent in M$_{0}$ (N).(N).

• Coupled systems mechanics
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• v.6 no.3
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• pp.369-376
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• 2017

Intermolecular interaction energies and conformer geometries of the hydrogen bonded acrylamide dimers have been studied by using the second-order Møller-Plesset (MP2) perturbation theory and the density functional theory (DFT) with 17 density functionals. Dunning's correlation consistent basis sets (up to aug-cc-pVTZ) have been used to study the basis set effects. The DFT calculated interaction energies are compared to the reference energy data calculated by the MP2 method and the coupled cluster method at the complete basis set (CCSD(T)/CBS) limit in order to determine the relative performance of the studied density functionals. Overall, dispersion-energy-corrected density functionals outperform uncorrected ones. The ${\omega}B97XD$ density functional is particularly effective in terms of both accuracy and computational cost in estimating the reference energy values using small basis sets and is highly recommended for similar calculations for larger systems.

• Korean Journal of Logic
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• v.19 no.1
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• pp.83-106
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• 2016

We compare the approaches to natural numbers and the induction principles in Frege's Grundgesetze and in systems thereafter. We start with an illustration of Frege's approach and then explain the use of induction principles in Zermelo-Fraenkel set theory and in modern type theories such as Calculus of Inductive Constructions. A comparison among the different approaches to induction principles is also given by analyzing them in respect of predicativity and impredicativity.

• Bulletin of the Korean Mathematical Society
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• v.54 no.4
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• pp.1173-1183
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• 2017

We give some sufficient conditions for the null and infinite derivatives of the $Riesz-N{\acute{a}}gy-Tak{\acute{a}}cs$ (RNT) singular function. Using these conditions, we show that the Hausdorff dimension of the set of the infinite derivative points of the RNT singular function coincides with its packing dimension which is positive and less than 1 while the Hausdorff dimension of the non-differentiability set of the RNT singular function does not coincide with its packing dimension 1.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1163-1166
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• 1993

This paper studies the evaluation of mechanical design plans through fuzzy cluster. Plans are classified into two sets, 'good' and 'bad'. The membership of a plan to the 'good' set is numerically equal to the distance to the 'bad' set. The central parameter of the 'good' set is defined as '1', and that of the 'bad' set '0'. This will greatly simplify calculations. The result of the calculating example proves the method available.

• Journal of Intelligence and Information Systems
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• v.4 no.1
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• pp.133-147
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• 1998

Recently, many researchers have been involved in finding deterministic equations which can accurately predict future event, based on chaotic theory, or fractal theory. The theory says that some events which seem very random but internally deterministic can be accurately predicted by fractal equations. In contrast to the conventional methods, such as AR model, MA, model, or ARIMA model, the fractal equation attempts to discover a deterministic order inherent in time series data set. In discovering deterministic order, researchers have found that neural networks are much more effective than the conventional statistical models. Even though prediction accuracy of the network can be different depending on the topological structure and modification of the algorithms, many researchers asserted that the neural network systems outperforms other systems, because of non-linear behaviour of the network models, mechanisms of massive parallel processing, generalization capability based on adaptive learning. However, recent survey shows that prediction accuracy of the forecasting models can be determined by the model structure and data structures. In the experiments based on actual economic data sets, it was found that the prediction accuracy of the neural network model is similar to the performance level of the conventional forecasting model. Especially, for the data set which is deterministically chaotic, the AR model, a conventional statistical model, was not significantly different from the MLP model, a neural network model. This result shows that the forecasting model. This result shows that the forecasting model a, pp.opriate to a prediction task should be selected based on characteristics of the time series data set. Analysis of the characteristics of the data set was performed by fractal analysis, measurement of Hurst index, and measurement of Lyapunov exponents. As a conclusion, a significant difference was not found in forecasting future events for the time series data which is deterministically chaotic, between a conventional forecasting model and a typical neural network model.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.734-737
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• 2004

When the margin level is set relatively low, margin violation probability increases and the default probability of the futures market rises. On the other hand, if the margin level is set high, the margin violation probability decreases, but the futures market becomes less attractive to hedgers as the investor's opportunity cost increases. In this paper, we investigate whether the movement of KOSPI200(Korea Composite Stock Price Index 200) futures daily prices can be modeled with the extreme value theory. Base on this investigation, we examine the validity of the margin level set by the extreme value theory. Computational results are presented to compare the extreme value distribution and the empirical distribution of margin violation in KOSPI200. Some observations and implications drawn from the computational experiment are also discussed.