• The Journal of the Korea Contents Association
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• v.17 no.3
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• pp.189-198
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• 2017

This study examined how adolescents make a decision on a company's unethical viral and what factors influenced their decision. There were three independent variables, self-interest, sense of rivalry, and monetary attitude, considered for affecting adolescents' ethical decision. The ethical decision as the dependent variable has two perspectives such as deontology and relativism. The findings showed that sense of rivalry was only significant factor influencing relativism and deontology of adolescents' ethical decision. Self-interest and monetary attitude were not significant, but when eliminating sense of rivalry due to multicollinearity in regression model, monetary attitude significantly influenced their ethical decision.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.3
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• pp.77-82
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• 2018

This paper is concerned with the performance analysis of a modified stop-and-go generalized multi-modulus algorithm (MSAG-GMMA) adaptive blind equalization algorithm with variable step size. The proposed algorithm multiplies the fixed step size by the error signal of the decision-oriented algorithm in the equalization coefficient update equation, and changes the step size according to the error size. Also, the MSAG-GMMA having a fixed step size is operated so as to maintain a fast convergence speed from a certain threshold to a steady state by determining the error signal size of the decision-directed algorithm, and when the MSAG-GMMA to work To evaluate the performance of the proposed algorithm, we use the ensemble ISI, ensemble-averaged MSE, and equalized constellation obtained from the output of the equalizer as the performance index. Simulation results show that the proposed algorithm has faster convergence speeds than MMA, GMMA, and MSAG-GMMA and has a small residual error in steady state.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.4
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• pp.275-285
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• 2003

The now video coding standard H.264 employs variable block size motion compensation, multiple references, and quarter-pel motion vector accuracy. These techniques are key features to accomplish higher coding gain, however, at the same time main factors that increase overall computational complexity. Therefore, in order to apply H.264 to many applications, key techniques are requested to improve their speed. For this reason, we propose a fast motion estimation which is suited for variable block size motion communication. In addition, we propose a fast mode decision method to choose the best mode at early stage. Experimental results show the reduction of the number of SAT SATD calculations by a factor of 4.5 and 2.6 times respectively, when we compare the proposed fast motion estimation and the conventional MVFAS $T^{［8-10］}$. Besides, the number of RDcost computations is reduced by about 45%. Therefore, the proposed methods reduces significantly its computational complexity without noticeable coding loss.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.89-95
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• 2016

In this paper, we propose a dual-mode blind equalization algorithm that two of the blind equalization algorithm using the size of the decision-directed error signal is automatically switched. The proposed algorithm has a faster convergence speed due to operation of the MSAGF-SMMA with large fixed step-size mainly in the initial equalization. After the equalization has been made to some extent, the proposed algorithm has a smaller residual error in the steady- state by operation of the MSAGF-SMMA with a variable step-size mainly. The variable step-size is determined by multiplying the size of the decision-directed error signal of a fixed step-size. In this paper, we analyze the performance of the proposed algorithm. The computer simulation results demonstrate that the proposed algorithm has a significantly improved performance in terms of a residual inter-symbol interference and residual error in the steady-state compared with the MMA, SMMA, and MSAGF-SMMA.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.9
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• pp.759-767
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• 2000

OPKFDD(Ordered Pseudo-Kronecker Functional Decision Diagram)는 각 노드에서 다양한 decomposition을 취할 수 있는 Ordered-DD(Decision Diagram)의 한 종류이다. OBDD(Ordered Binary Decision Diagram)에서 각 노드는 Shannon decomposition 만을 이용하는 반면, OPKFDD는 각 노드마다 Shannon, positive Davio, negative Davio decomposition 중의 하나를 사용하도록 하며 많은 경우 매우 적은 수의 노드로 함수를 표현할 수 있다. 그러나 각 노드마다 각기 다른 확장 방법을 선택할 수 있는 특징 때문에 입력 노드에 대한 확장 방밥과 입력 변수 순서의 결정에 의해서 OPKFDD의 크기가 좌우되며 이에 대한 최적의 해를 구하는 것은 매우 어려운 문제로 알려져 있다. 본 논문에서는 DD 크기를 기준을 노드 수로 하여 기존의 BDD(Binary Decision Diagram) 자료구조에서 OPKFDD를 효율적으로 유도해내는 방법을 제시하고 complex term을 이용하여 이를 최소화하는 알고리즘을 제시한다. 그리고 입력변수 순서 결정을 위하여 다출력함수의 경우 함수간의 포함관계를 고려한 그룹-sifting과 각 노드의 확장 방법을 제안하고 실험 결과를 제시한다.

• Journal of the Korean Home Economics Association
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• v.38 no.5
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• pp.41-54
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• 2000

While equity theory started as a theory focusing upon the relationship between employee and employer, over the years the theory has been expanded to various other types of relationships including marital relationships. The present research among 251 housewives examines the perception of equity and the decision-making styles from the perspective of equity theory. The perception of equity was measured by the revised TUW scales and the Walster's global measure. Also, decision-making styles was assessed by means of the 'final-say' scale In line with the predictions, the results clearly showed that the perception of equity was a strong predictor variable to the joint decision-making.

• Proceedings of the Technology Innovation Conference
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• 2003.02a
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• pp.191-199
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• 2003

It is critical to select an appropriate technology valuation method when the characteristics of a technology and valuation environment are variable. To ensure high quality decision making when selecting a technology valuation method, it is necessary to understand the principles of a good technology valuation method, and define and apply a decision making theory for selecting an optimal method. The authors propose that Axiomatic Design Principles can be applied as a decision making theory. In order to apply Axiomatic Design for this problem, this paper describes four domains(customer, functional, physical, and process domain) and four axioms(independence, information, cost, time axiom) for the decision making process for the optimal technology valuation method. The result of this study will contribute flexibility to the dynamic technology valuation process.

• Journal of IKEEE
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• v.3 no.2 s.5
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• pp.295-304
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• 1999

This paper presents a method of constructing the Multiple-Valued Logic Systems(MVLS) over Finite Fields(FF) using by Decision Diagram(DD) that is based on Graph Theory. The proposed method is as following. First, we derivate the Ordered Multiple-Valued Logic Decision Diagram(OMVLDD) based on the multiple-valued Shannon's expansion theorem and we execute function decomposition using by sub-graph. Next, we propose the variable selecting algorithm and simplification algorithm after apply the each isomorphism and reodering vertex. Also we propose MVLS design method.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.2
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• pp.285-291
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• 2010

In this paper, we propose an induced linguistic ordered weighted harmonic mean(ILOWHM) operator. The ILOWHM operator is more general type of aggregation operator, which is based on the LHM and LOWHM operators. Based on the LOWHM and ILOWHM operator, we develop an approach to group decision making with linguistic preference relations. Finally, an application of the approach to group decision making problem with linguistic preference relations is pointed out.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.243-246
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• 2003

Data mining is a process of discovering useful patterns for decision making from an amount of data. It has recently received much attention in a wide range of business and engineering fields Classifying a group into subgroups is one of the most important subjects in data mining Tree-based methods, known as decision trees, provide an efficient way to finding classification models. The primary concern in tree learning is to minimize a node impurity, which is evaluated using a target variable in the data set. However, there are situations where multiple target variables should be taken into account, for example, such as manufacturing process monitoring, marketing science, and clinical and health analysis. The purpose of this article is to present several methods for measuring the node impurity, which are applicable to data sets with multiple target variables. For illustrations, numerical examples are given with discussion.