• Journal of the Korea Convergence Society
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• v.4 no.2
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• pp.35-41
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• 2013

Data management with fuzzy entropy and similarity measure were discussed and verified by applying reliable data selection problem. Calculation of certainty or uncertainty for data, fuzzy entropy and similarity measure are designed and proved. Proposed fuzzy entropy and similarity are considered as dissimilarity measure and similarity measure, and the relation between two measures are explained through graphical illustration.Obtained measures are useful to the application of decision theory and mutual information analysis problem. Extension of data quantification results based on the proposed measures are applicable to the decision making and fuzzy game theory.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.1
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• pp.141-153
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• 2009

There have been a lot of researches about KM(knowledge management) in domestic and foreign countries since 1990. Especially, there have been a lot of researches about enabler of KM, knowledge asset etc. but these are insufficient researches about performance measure of knowledge management considering maturity of KM. In addition, performance measure and maturity considering enabler to manage successful knowledge as well as knowledge asset which can be the following result are not the sufficient situation. Therefore, this study makes developmental levels of the inside and outside of the corporate by observing previous studies about the maturity of knowledge management and classifies enabler of knowledge management and measure item about knowledge asset by level, considering the features of each developmental level. And it is designed to propose maturity measure methods considering maturity level of actual knowledge management item by drawing indicator to measure classified items.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.4
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• pp.275-280
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• 2010

Verification of efficiency in data management fuzzy entropy and similarity measure were discussed and verified by applying reliable data selection problem and numerical data similarity evaluation. In order to calculate the certainty or uncertainty fuzzy entropy and similarity measure are designed and proved. Designed fuzzy entropy and similarity are considered as dissimilarity measure and similarity measure, and the relation between two measures are explained through graphical illustration. Obtained measures are useful to the application of decision theory and mutual information analysis problem. Extension of data quantification results based on the proposed measures are applicable to the decision making and fuzzy game theory.

• Bulletin of the Korean Mathematical Society
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• v.55 no.2
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• pp.561-572
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• 2018

In this paper we consider the concept of statistical causality in continuous time between flows of information, represented by filtrations. Then we relate the given concept of causality to the equivalent change of measure that plays an important role in mathematical finance. We give necessary and sufficient conditions, in terms of statistical causality, for extremality of measure in the set of martingale measures. Also, we have considered the extremality of measure which involves the stopping time and the stopped processes, and obtained similar results. Finally, we show that the concept of unique equivalent martingale measure is strongly connected to the given concept of causality and apply this result to the continuous market model.

• Journal of applied mathematics & informatics
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• v.29 no.3_4
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• pp.987-1000
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• 2011

We show how the dynamic optimization problem with the capital constraint can be reduced to the problem to find an optimal modified claim $\tilde{\psi}H$ where $\tilde{\psi}$ is a randomized test in the static problem. Coherent risk measure is used as risk measure in the $L^{\infty}$ random variable spaces. The paper is written in expository style to some degree. We use an average risk of measure(AVaR), which is a special coherent risk measure, to see how to hedge the modified claim in a complete market model.

• Fire Science and Engineering
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• v.10 no.3
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• pp.19-28
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• 1996

This paper present the way the fire detector determines whether a fire has broken out or not using the fuzzy measure. This method is based on Dempster's combination rule using the belief measure. The detector indicate a 'Fire'(F) or 'Nonfire'(N) when it determines whether a fire has broken out or not. To determine this, the fuzzy rule is applied in the setting value for the heat and smoke detector which is used. As a result, It is proved that the final decision can be determined more exactly whether a fire has broken out or not in proportion to the frequency of the fuzzy measure and the value of Bel (F).

• Journal of Korean Institute of Industrial Engineers
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• v.29 no.1
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• pp.41-48
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• 2003

In this paper, we present a new measure to evaluate the interestingness of association rules. Ultimately. to evaluate whether a rule is interesting or not is subjective. However, an interestingness measure is useful in that it shows the cause for pruning uninteresting rules statistically or logically. Some interestingness measures have been developed in association rules mining. We present an overview of interestingness measures and propose a new measure. A comparative study of some interestingness measures is made on an example dataset and a real dataset. Our experiments show that the new measure can avoid the discovery of misleading rules.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.5
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• pp.518-528
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• 2001

In this paper, we firstly define a new combined segmentation measure and propose a segmentation algorithm using this measure. The combined segmentation measure is a weighted sum of intensity, motion, and a change segmentation measure that is extracted from the resulting image of the proposed change detector. The change segmentation measure is defined as an absolute change value difference between an pixel and its neighboring region from the eroded image, which results from morphological erosion filtering to eliminate many inaccurate components included in the resulting image of a conventional change detector. The change segmentation measure can be used as an efficient segmentation measure for the accurate segmentation of neighboring moving objects and static background regions. Therefore, the proposed combined segmentation measure can determine exact boundaries in the segmentation process of region-based coding even though the estimated motion vectors around the boundaries of moving objects and static background regions are inaccurate and the intensities around the boundaries are similar.

• ETRI Journal
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• v.18 no.1
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• pp.29-41
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• 1996

This paper describes a method to select a suitable feature for speech recognition using information theoretic measure. Conventional speech recognition systems heuristically choose a portion of frequency components, cepstrum, mel-cepstrum, energy, and their time differences of speech waveforms as their speech features. However, these systems never have good performance if the selected features are not suitable for speech recognition. Since the recognition rate is the only performance measure of speech recognition system, it is hard to judge how suitable the selected feature is. To solve this problem, it is essential to analyze the feature itself, and measure how good the feature itself is. Good speech features should contain all of the class-related information and as small amount of the class-irrelevant variation as possible. In this paper, we suggest a method to measure the class-related information and the amount of the class-irrelevant variation based on the Shannon's information theory. Using this method, we compare the mel-scaled FFT, cepstrum, mel-cepstrum, and wavelet features of the TIMIT speech data. The result shows that, among these features, the mel-scaled FFT is the best feature for speech recognition based on the proposed measure.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.19 no.2
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• pp.16-22
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• 2011

It is recognized that the control surface fault is detected by monitoring the value of the coefficients due to the control surface deviation. It is found out the control surface stuck position by comparing the trim value with the reference value. To detect and isolate the fault, two mixed methods apply to the real-time parameter estimation and similarity measure. If the scatter of aerodynamic coefficients for the fault and normal are closing nearly, fault decision is difficult. Applying similarity measure to decide for fault or not, it makes a clear and easy distinction between fault and normal. Low power processor is applied to the real-time parameter estimator and computation of similarity measure.