• Science of Emotion and Sensibility
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• v.1 no.1
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• pp.213-221
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• 1998

현대의 시스템들이 가지는 고기능화와 자동화로 인하여 인간의 운용 능력이 점점 더 중요한 능력으로 부각되고 있으며, 이는 사용자가 경험하게 되는 인지넉 복잡도를 제어하는 것을 요구한다. 본 연구에서는 사용자 인터페이스에서 사용자가 경험해야 하는 인지적 복잡도를 스키마 구조를 반영하여 정량화하는 엔트로피 모형(윤완철, 1992)을 적용하여 사용자가 겪게 될 인지적 복잡도를 예측하는 척도가 제안되었으며 실험적으로 검증되었다. 엔트로피와 시스템 크기-조작의 수와 상태의 수-가 각각 다른 세 가지 인터페이스 (엔트로피가 낮고 작은 크기의 인터페이스, 엔트로피가 높고 작은 크기의 인터페이스, 엔트로피가 높고 큰 크기의 인티페이스) 중의 하나를 사용하는 것을 피험자이 학습하고, 이에 대해 검사를 받았다. 제안된 척도인 시스템 엔트로피는 사용자 수행도를 잘 설명하였지만, 시스템의 크기는 그러하지 않았다. 본 연구는 사용자가 겪게 될 인지적 복잡도를 평가자의 주관이 개입하지 않는 방법을 통하여 평가할 수 있음을 보인 것으로 가전제품이나 스프트웨어의 디자인의 평가와 개선 등 인간의 인지적 복잡도가 사용성에 중요한 영향을 미치는 분야에서 유용하리라 여겨진다.

• Proceedings of KOSOMES biannual meeting
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• 2018.06a
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• pp.22-22
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• 2018

• Journal of Digital Convergence
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• v.12 no.12
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• pp.293-301
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• 2014

In this paper, we propose a new measure based on the confidence of Bayesian posterior probability so as to reduce unimportant information in the clustering process. Because the performance of clustering is up to selecting the important degree of attributes within the databases, the concept of information entropy is added to posterior probability for attributes discernibility. Hence, The same value of attributes in the confidence of the proposed measure is considerably much less due to the natural logarithm. Therefore posterior probability-based clustering algorithm selects the minimum of attribute reducts and improves the efficiency of clustering. Analysis of the validation of the proposed algorithms compared with others shows their discernibility as well as ability of clustering to handle uncertainty with ACME categorical data.

• The Korean Journal of Applied Statistics
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• v.26 no.4
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• pp.611-622
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• 2013

Mudholkar and Tian (2002) proposed an entropy-based test of fit for the inverse Gaussian distribution; however, the test can be applied to only the composite hypothesis of the inverse Gaussian distribution with an unknown location parameter. In this paper, we propose an entropy-based goodness-of-fit test for an inverse Gaussian distribution that can be applied to the composite hypothesis of the inverse Gaussian distribution as well as the simple hypothesis of the inverse Gaussian distribution with a specified location parameter. The proposed test is based on the probability integration transformation. The critical values of the test statistic estimated by simulations are presented in a tabular form. A simulation study is performed to compare the proposed test under some selected alternatives with Mudholkar and Tian (2002)'s test in terms of power. The results show that the proposed test has better power than the previous entropy-based test.

• Journal of Korea Game Society
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• v.18 no.1
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• pp.105-114
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• 2018

Various data analysis methods used for customer type analysis are very important for game companies to understand their type and characteristics in an attempt to plan customized content for our customers and to provide more convenient services. In this paper, we propose a k-mode cluster analysis algorithm that uses information uncertainty by extending information entropy to reduce information loss. Therefore, the measurement of the similarity of attributes is considered in two aspects. One is to measure the uncertainty between each attribute on the center of each partition and the other is to measure the uncertainty about the probability distribution of the uncertainty of each property. In particular, the uncertainty in attributes is taken into account in the non-probabilistic and probabilistic scales because the entropy of the attribute is transformed into probabilistic information to measure the uncertainty. The accuracy of the algorithm is observable to the result of cluster analysis based on the optimal initial value through extensive performance analysis and various indexes.

• Communications for Statistical Applications and Methods
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• v.17 no.4
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• pp.591-598
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• 2010

A questionnaire may consist of duplicated or similar items. This study finds the duplicated or similar items by using the MDS and the cluster analysis of response patterns. By identifying the characteristics of the cluster, those items are combined into a representative item. The similarity of items is measured by the mutual information.

• Journal of Korea Society of Industrial Information Systems
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• v.4 no.1
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• pp.52-57
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• 1999

In this paper, the methods which calculate the tuple membership values in a vague model of the fuzzy databases are analyzed A method among them is proposed to offer the effective solutions to the users. Also an information theory is studied to calculate the entropy of the results of a fuzzy query and an algorithm is proposed to control the size of the entropy.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.6
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• pp.47-54
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• 2014

Based on the indiscernible relation of rough set, the inevitability of superposition and inconsistency of data makes the reduction of attributes very important in information system. Rough set has difficulty in the difference of attribute reduction between consistent and inconsistent information system. In this paper, we propose the new uncertainty measure and attribute reduction algorithm by Bayesian posterior probability for correlation analysis between condition and decision attributes. We compare the proposed method and the conditional information entropy to address the uncertainty of inconsistent information system. As the result, our method has more accuracy than conditional information entropy in dealing with uncertainty via mutual information of condition and decision attributes of information system.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.399-402
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• 2001

본 논문에서는 항공 영상에서 직선 성분을 강건하게 추출하기 위한 새로운 영상 필터링 기법을 제안한다. 제안하는 기법은 지상 구조물의 추출에 유용한 직선 특징을 이루는 에지와 비직선 특징을 이루는 에지의 대비도를 증가시키기 위하여 비선형, 비등방 확산 기법 [2]을 영상에 적응적으로 적용한다. 이를 위하여 확산 매개변수를 제안하는 새로운 직선성 척도로 설정하고 영상의 각 점에서의 직선성 값에 따라 적응적으로 확산을 시킴으로써 확산 과정에서 직선 특징을 잘 보존하고 비직선 특징을 효과적으로 제거한다. 본 논문에서는 직선성 척도로서 에지 체인 위의 점들의 방향성 엔트로피를 제안하고 다양한 영상에 대한 실험을 통해서 엔트로피 척도가 영상에서의 직선 특징을 추출하는데 효율적임을 보인다.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.9
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• pp.1112-1118
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• 2014

In this paper, we propose a local descriptor and a similarity measure that is robust to radiometic variations. The proposed local descriptor is made up Haar wavelet filter and it can contain frequency informations about the feature point and its surrounding pixels in fixed region, and it is able to describe feature point clearly under ununiform illumination condition. And a proposed similarity measure is combined with conventional entropy-based similarity and another similarities that is generated by local descriptor. It can reflect similarities between image regions accurately under radiometic illumination variations. We validate with experimental results on some images and we confirm that the proposed algorithm is more superior than conventional algorithms.