• Journal of Korea Multimedia Society
• /
• v.8 no.6
• /
• pp.783-789
• /
• 2005

This paper is proposed a watermarking technique for copyright protection of multimedia contents. We proposed adaptive watermark detection algorithm using stochastic perceptual model and statistical decision method in DMWT(discrete multi wavelet transform) domain. The stochastic perceptual model calculates NVF(noise visibility function) based on statistical characteristic in the DMWT. Watermark detection algorithm used the likelihood ratio depend on Bayes' decision theory by reliable detection measure and Neyman-Pearson criterion. To reduce visual artifact of image, in this paper, adaptively decide the embedding number of watermark based on DMWT, and then the watermark embedding strength differently at edge and texture region and flat region embedded when watermark embedding minimize distortion of image. In experiment results, the proposed statistical decision method based on multiwavelet domain could decide watermark detection.

• International Journal of Quality Innovation
• /
• v.8 no.2
• /
• pp.100-114
• /
• 2007

Decision makers in the service industry must effectively cope with queuing problems, service capacity optimization, service efficiency and service quality problems. This study proposes a computer simulation-enabled MCDM framework that integrates computer simulation analysis, Taguchi method, expert opinion and multiple criteria decision making (MCDM) to assist decision makers in coping with decision problems. In this framework, Taguchi method is adopted to reduce the time required for the simulation experiment. Computer simulation analysis is adopted to obtain useful information for rapid decision-making without interrupting actual production. MCDM is used to select the optimal alternative. The illustrative result is extremely promising.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.14 no.24
• /
• pp.7-13
• /
• 1991

Recently, in FMS composing of various automatic equipments, the machines with lower operating costs, and with higher operating costs and replacement costs resulting from deterioration have been appearing successively as a result of rapidly advances in technology. "Control Limit Policy" [1] by using Markov decision policy, a kind of optimal economic replacement decision, well reflects and represents this environment. In this paper, it is reviewed that the decision method of the forecasted replacement alternatives in planning horizon under technological advances is derived. The proposed method is applied to a numerical example and some characteristics are examined by sensitivity. It is clarified that the method is relatively insensitive to changes of parameters at the present decision. decision.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2006.10a
• /
• pp.144-153
• /
• 2006

In order to take TC forecasts from different observatories into consideration, and make quantitative assessment and analysis for avoiding TC routes from the view of safety and cost, a new safe-economic decision making method of TC avoidance routing on ocean was put forward. This model is based on combining forecast of TC trace based on neural networks, technical method to determine the future TC wind and wave fields, technical method of fuzzy information optimization, risk analysis theory, and meteorological-economic decision making theory. It has applied to the simulation of MV Tianlihai's shipping on ocean. The result shows that the model can select the optimum plan from 7 plans, the selected plan is in accordance with the one selected by experienced captains.

• Journal of KIISE:Software and Applications
• /
• v.29 no.3
• /
• pp.156-166
• /
• 2002

Decision tree induction is a kind of useful machine learning approach for extracting classification rules from a set of feature-based examples. According to the partitioning style of the feature space, decision trees are categorized into univariate decision trees and multivariate decision trees. Due to observation error, uncertainty, subjective judgment, and so on, real-world data are prone to contain some errors in their feature values. For the purpose of making decision trees robust against such errors, there have been various trials to incorporate fuzzy techniques into decision tree construction. Several researches hove been done on incorporating fuzzy techniques into univariate decision trees. However, for multivariate decision trees, few research has been done in the line of such study. This paper proposes a fuzzy decision tree induction method that builds fuzzy multivariate decision trees named fuzzy oblique decision trees, To show the effectiveness of the proposed method, it also presents some experimental results.

• Asia pacific journal of information systems
• /
• v.7 no.1
• /
• pp.99-111
• /
• 1997

This paper presents an application of an artificial neural net to the implementation of decision class analysis (DCA), together with the generation of a decision model influence diagram. The diagram is well-known as a good tool for knowledge representation of complex decision problems. Generating influence diagram model is known to in practice require much time and effort, and the resulting model can be generally applicable to only a specific decision problem. In order to reduce the burden of modeling decision problems, the concept of DCA is introduced. DCA treats a set of decision problems having some degree of similarityz as a single unit. We propose a method utilizing a feedforward neural net with supervised learning rule to develop DCA based on influence diagram, which method consists of two phases: Phase l is to search for relevant chance and value nodes of an individual influence diagram from given decision and specific situations and Phase II elicits arcs among the nodes in the diagram. We also examine the results of neural net simulation with an example of a class of decision problems.

• ETRI Journal
• /
• v.24 no.4
• /
• pp.323-327
• /
• 2002

In this study, we propose a novel mobile tracking method based on Multi-Criteria Decision Making (MCDM), in which uncertain parameters-the received signal strength, the distance between the mobile and the base station, the moving direction, and the previous location-are used in the decision process using the aggregation function in the fuzzy set theory. Through numerical results, we show that our proposed mobile tracking method provides a better performance than the conventional method using the received signal strength.

• Communications of the Korean Mathematical Society
• /
• v.32 no.4
• /
• pp.1077-1097
• /
• 2017

In this research article, we introduce certain concepts, including domination, total domination, strong domination, weak domination, edge domination and total edge domination in m-polar fuzzy graphs. We describe these concepts by several examples. We investigate some related properties of certain dominations in m-polar fuzzy graphs. We also present a decision making method based on domination in m-polar fuzzy graphs.

• Journal of Power Electronics
• /
• v.8 no.1
• /
• pp.101-107
• /
• 2008

In this paper, the features extracted from vibration time signals are used to detect the bearing fault condition. The decision tree is applied to diagnose the bearing status, which has the benefits of being an expert system that is based on knowledge history and is simple to understand. This paper also suggests a genetic algorithm (GA) as a method to reduce the number of features. In order to show the potentials of this method in both aspects of accuracy and simplicity, the reduced-feature decision tree is compared with the non reduced-feature decision tree and the PCA-based decision tree.

• Computers and Concrete
• /
• v.9 no.2
• /
• pp.99-118
• /
• 2012

Marine Structures are very costly and need a continuous inspection and maintenance routine. The most effective way to control the structural health is the application of an expert system that can evaluate the importance of any distress on the structure and provide a maintenance program. An extensive literature review, interviews with expert supervisors and a national survey are used to build a decision support system for concrete structures in sea environment. Decision trees are the main rules in this system. The system input is inspection information and the system output is the main cause(s) of distress(es) and the best repair method(s). Economic condition, severity of distress, distress situation, and new technologies and the most repeated classical methods are considered to choose the best repair method. A case study demonstrates the application of the developed decision support system for a type of marine structure.