• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.7
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• pp.3245-3250
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• 2011

This study introduces a threat level assessment model adapting Fuzzy theories in order to help make decisions for better covering quantitative factors and qualitative ones together. The threat is classified into three major categories - one resulting from navigational condition, another from target vessel specification and the other from external decision environment. The threat levels by each category are examined by a fuzzy inference, and its corresponding weights are assigned via fuzzy measures. Finally the high level threat measures become integrated via a Choquet Fuzzy Integral method into ultimate threat level indicators.

• The KIPS Transactions:PartD
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• v.17D no.1
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• pp.1-8
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• 2010

Association rule mining techniques enable us to acquire knowledge concerning sales patterns among individual items from voluminous transactional data. Certainly, one of the major purposes of association rule mining is utilizing the acquired knowledge to provide marketing strategies such as catalogue design, cross-selling and shop allocation. However, this requires too much time and high cost to only extract the actionable and profitable knowledge from tremendous numbers of discovered patterns. In currently available literature, a number of interest measures have been devised to accelerate and systematize the process of pattern evaluation. Unfortunately, most of such measures, including support and confidence, are prone to yielding impractical results because they are calculated only from the sales frequencies of items. For instance, traditional measures cannot differentiate between the purchases in a small basket and those in a large shopping cart. Therefore, some adjustment should be made to the size of market baskets because there is a strong possibility that mutually irrelevant items could appear together in a large shopping cart. Contrary to the previous approaches, we attempted to consider market basket's size in calculating interest measures. Because the devised measure assigns different weights to individual purchases according to their basket sizes, we expect that the measure can minimize distortion of results caused by accidental patterns. Additionally, we performed intensive computer simulations under various environments, and we performed real case analyses to analyze the correctness and consistency of the devised measure.

• Journal of Families and Better Life
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• v.24 no.4 s.82
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• pp.11-24
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• 2006

The purpose of this study was to determine if expectation, performance, and disconfirmation are related to consumer satisfaction and behavioral intention. The major findings were as follows: First, among the four dimensions of the medical services, the level of consumer satisfaction was highest with 'doctors' and lowest with 'facilities' while the level of importance was highest with 'doctors' and lowest with 'medical systems' Second, ability to predict behavioral intention can best be improved with regression coefficient weights among the six measures of consumer satisfaction. Third, greater satisfaction was significantly associated with performance and disconfirmation while behavioral intention was significantly associated with expectations, performance, and discoufirmation.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.2
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• pp.1-16
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• 2008

The purpose of this paper is to propose a new binary classification method for predicting corporate failure based on genetic algorithm, and to validate its prediction power through empirical analysis. Establishing virtual companies representing bankrupt companies and non-bankrupt ones respectively, the proposed method measures the similarity between the virtual companies and the subject for prediction, and classifies the subject into either bankrupt or non-bankrupt one. The values of the classification variables of the virtual companies and the weights of the variables are determined by the proper model to maximize the hit ratio of training data set using genetic algorithm. In order to test the validity of the proposed method, we compare its prediction accuracy with ones of other existing methods such as multi-discriminant analysis, logistic regression, decision tree, and artificial neural network, and it is shown that the binary classification method we propose in this paper can serve as a premising alternative to the existing methods for bankruptcy prediction.

• Journal of the military operations research society of Korea
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• v.17 no.1
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• pp.84-104
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• 1991

Up to the present, the evaluation measures in the production and inventory management have been studied under the pre-condition that the costs for major factors(e.g,. cost of carrying inventory, cost of demand shortage) are given easily, although in practice, it is difficult. The case in which multiple participants have a different viewpoints in production and inventory management has not been studied, in spite of its frequent occurrence. This study suggests a production and inventory model with multiple objectives corresponding to major factors and the related interactive algorithm based on the preference structures of participants. The problem can be solved through a weighting vector generated by an interaction with participants. The concept of equity is also used in order to guarantee the reasonable distribution of group utility in determining the individual relative weights of participants. This study includes the reality of the model and the decision process in the production and inventory management.

• Nuclear Engineering and Technology
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• v.51 no.2
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• pp.453-462
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• 2019

Mental workload (MWL) is a major consideration for the user interface design in nuclear power plants (NPPs). However, each MWL evaluation method has its advantages and limitations, thus the evaluation and control methods based on multi-index methods are needed. In this study, fuzzy comprehensive evaluation (FCE) theory was adopted for assessment of interface designs in NPP based on operators' MWL. An evaluation index system and membership functions were established, and the weights were given using the combination of the variation coefficient and the entropy method. The results showed that multi-index methods such as performance measures (speed of task and error rate), subjective rating (NASA-TLX) and physiological measure (eye response) can be successfully integrated in FCE for user interface design assessment. The FCE method has a correlation coefficient compared with most of the original evaluation indices. Thus, this method might be applied for developing the tool to quickly and accurately assess the different display interfaces when considering the aspect of the operators' MWL.

• Korean Journal of Food Science and Technology
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• v.37 no.4
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• pp.685-694
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• 2005

Korean practices in tolerance setting of pesticide residues on food crops were compiled with an effort to harmonize with international standards. Based on scientific data including historical background, limit setting protocols, adoption of ADI values, food factors, nation's body weights, and regulatory margins which are required for the setting of maximum residue limits, necessary measures to be taken by Korean regulatory authorities were proposed.

• The Journal of Korea Robotics Society
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• v.2 no.1
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• pp.29-39
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• 2007

We present an implementation of particle filter algorithm for global localization and kidnap recovery of mobile robot. Firstly, we propose an algorithm for efficient particle initialization using sonar line features. And then, the average likelihood and entropy of normalized weights are used as a quality measure of pose estimation. Finally, we propose an active kidnap recovery by adding new particle set. New and independent particle set can be initialized by monitoring two quality measures. Added particle set can re-estimate the pose of kidnapped robot. Experimental results demonstrate the capability of our global localization and kidnap recovery algorithm.

• Journal of the Korea Safety Management & Science
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• v.5 no.4
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• pp.229-243
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• 2003

This paper suggests the process of performance measurement system development for B2B e-Marketplace using BSC (Balanced Scorecard). As the first step, main features and factors affecting performance of e-Business company and especially of B2B e-Marketplaces were derived based on the literatures. For the 2nd step, the nonnative performance measurement model for B2B e-Marketplace was suggested. Especially, the research range that the model covers is restricted to the neutral and systematic sourcing B2B e-Marketplace. And, the performance measurement model was based on BSC, for the BSC is very powerful and sound tool among all the available performance measurement systems. Also, the model was based on the AHP (Analytic Hierarchy Process) to make the model more structured, and to draw weights of performance measures from experts

• Journal of the Korea Society of Computer and Information
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• v.7 no.3
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• pp.49-55
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• 2002

This paper proposes speaker recognition algorithm which includes both the pitch parameter and the fuzzy. This study proposes a pitch detection method for the peak and valley pitch detection function by means of comparing spectra which utilizes the transform characteristics between time and frequency. It measures the similarity to the original spectrum while arbitrarily varying the period in the time domain. It heavily weights the error due to the changing characteristics of the phonemes, while it is strong against noise. In this paper, makes reference pattern using membership function and performs vocal track recognition of common character using fuzzy pattern matching in odor to include time variation width for non-linear utterance time.