• Science of Emotion and Sensibility
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• v.7 no.3
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• pp.15-25
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• 2004

The regression analysis and Adaptive -Network based Fuzzy-inference system (ANFIS) were applied to the explanation on human's visual texture of cotton fabrics with 7 mechanical properties. The ANFIS uses the structure with fuzzy membership function and neural network. The results obtained by the statistical analysis through the coefficient of correlation and regression analysis showed that subjective texture had a linear relationship with mechanical properties. But It had a relatively low coefficient of determination and was difficult that the statistical analysis explained other relationship with the exception of a lineality and interaction among mechanical properties. Comparing the statistical analysis, the ANFIS was an effective tool to explain human's non-linear perceptions and their interactions. But to apply ANFIS to human's perceptions more effectively, it is necessary to discriminate effective input variables through controlling the properties of samples.

• Journal of the Korean Society for Railway
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• v.12 no.6
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• pp.921-926
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• 2009

The RPN provides information which includes the risk level and the priority order of maintenance tasks for components. However, if there is no sufficient historical failure data, the historical failure data from other sources can be applied to the target system. And if we use historical data from other sources without any process, there will be concomitant problems according to a discord of each system characteristic, a difference between the present and the date of failure data, etc. In this paper, a new methodology is proposed to model the failure rate as a fuzzy function to resolve these problems. Taking advantage of this result, the RPN can be calculated by using the fuzzy operation. The proposed method is applied to the substation system.

• The Journal of the Korea Contents Association
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• v.11 no.9
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• pp.1-8
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• 2011

A fuzzy inference technique for real-time textile animation without integration at textile model based Mass-Spring model is introduced. Until now many techniques have used the Mass-Spring model to describe elastically deformable objects like textile. A textile object is able to represent as a deformable surface composed of spring and masses, the movement of textile surface which is analysed through the numerical integration by the fundamental law of dynamics such as Hooke's law. However, the integration methods have 'instability problems' if the explicit Euler's method is applied or 'large amounts of calculation' if the implicit Euler's method is applied. A simple and fast animation technique for Mass-Spring model of a textile with fuzzy inference is proposed. The stabilized simulation result is obtained the state of each mass-point in real-time for the n of mass-points by a relatively simple calculation.

• Journal of the Korea Society for Simulation
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• v.23 no.4
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• pp.1-8
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• 2014

Cloud computing helps big data processing to make various information using IT resources. The government has to start the RPS(Renewable Portfolio Standard) and induce the production of electricity using renewable energy equipment. And the government manages system to gather big data that is distributed geographically. The companies can purchase the REC(Renewable Energy Certificate) to other electricity generation companies to fill shortage among their duty from the system. Because of the RPS use voluntary competitive market in REC trade and the prices have the large variation, RPS is necessary to predict the equitable REC price using RPS big data. This paper proposed REC price prediction method base on fuzzy logic using the price trend and trading condition infra in REC market, that is modeled in cloud computing environment. Cloud computing helps to analyze correlation and variables that act on REC price within RPS big data and the analysis can be predict REC price by simulation. Fuzzy logic presents balanced REC average trading prices using the trading quantity and price. The model presents REC average trading price using the trading quantity and price and the method helps induce well-converged price in the long run in cloud computing environment.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.3
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• pp.95-103
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• 1998

This paper deals with a problem occuring in recognition of tactile images due to the effects of imposed force at a me urement moment. Tactile image of a contact surface, used for recognition of the surface type, varies depending on the forces imposed so that a false recognition may result in. This paper fuzzifies two parameters of the contour of a tactile image with the membership function formed by considering the imposed force. Two fuzzifed paramenters are fused by the average Minkowski's dist; lnce. The proposed algorithm was implemented on the multisensor system cnmposed of an optical tact le sensor and a 6 axes forceltorque sensor. By the experiments, the proposed algorithm has shown average recognition ratio greater than 869% over all imposed force ranges and object models which is about 14% enhancement comparing to the case where only the contour information is used. The pro- ~oseda lgorithm can be used for end-effectors manipulating a deformable or fragile objects or for recognition of 3D objects by implementing on multi-fingered robot hand.

• Journal of Internet Computing and Services
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• v.12 no.5
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• pp.87-100
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• 2011

In this paper, we address a video summarization task as generating both visually salient and semantically important video segments. In order to find salient data points, one can use the OC-SVM (One-class Support Vector Machine), which is well known for novelty detection problems. It is, however, hard to incorporate into the OC-SVM process the importance measure of data points, which is crucial for video summarization. In order to integrate the importance of each point in the OC-SVM process, we propose a fuzzy version of OC-SVM. The Importance-based Fuzzy OC-SVM weights data points according to the importance measure of the video segments and then estimates the support of a distribution of the weighted feature vectors. The estimated support vectors form the descriptive segments that best delineate the underlying video content in terms of the importance and salience of video segments. We demonstrate the performance of our algorithm on several synthesized data sets and different types of videos in order to show the efficacy of the proposed algorithm. Experimental results showed that our approach outperformed the well known traditional method.

• Journal of the Korea Society for Simulation
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• v.15 no.4
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• pp.29-39
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• 2006

Sensor networks consist of small nodes with sensing, computation, and wireless communications capabilities. A number of routing protocols to transmit the data between the base station and sensor nodes have been proposed. Intanagonwiwat et al. proposed the directed diffusion in which the base station sends interest messages and waits for data from the nodes in the specific regions. Since the directed diffusion propagates every interest message to whole nodes in the network, it causes energy dissipation of nodes. In this paper, we propose a novel data propagation method, which limits the data transmission area according to a threshold value for reducing the energy consumption in the network. A fuzzy logic is exploited to determine the threshold value by considering the energy and density of all the deployed nodes. The simulation models are designed and implemented based on DEVS formalism which is theoretically well grounded means of expressing discrete event simulation models.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.5
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• pp.645-652
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• 2011

The present study investigated the tracking system of a reflector to trace the movement of sun. The system was designed to minimize the error between the vertical vector of reflector and the position of sun. The proposed system was able to collect the sun lights at a point as a useful source of light energy and transmit the collected light to a remote area through optical fibers. Also the study successfully solved the controller design problem due to the complexity of modeling of the sun tracking system using a fuzzy logic controller which mimics human reasoning.

• KSBB Journal
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• v.15 no.1
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• pp.14-21
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• 2000

In this study, algae cultivation using the photobioreactor has been applied to remove the nitrogen and phosphorus compounds in the wastewater of the livestock industry. The optimal ratio of nitrate and ortho-phosphate concentration was found for the enhancement of removal efficiency. To achieve the high density culture of algae, the photobioreactor consisted of optical fibers wes developed to get the sufficient light intensity. The light could be illuminated uniformly from light source to the entire reactor by the optical fibers. The structured kinetic model was proposed to describe the growth rate, consumption rate of nitrates and ortho-phosphates in algae culture. The self-organizing fuzzy logic controller incorporated with genetic algorithm was constructed to control the semi-continuous wastewater treatment system. The proposed fuzzy logic controller was applied to maintain the nitrated concentration at the given set-point with the control of wastewater feeding rate. The experimental results showed that the self-organizing fuzzy logic controller could keep the nitrate concentration and enhance algae growth.

• The Journal of the Korea Contents Association
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• v.17 no.5
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• pp.574-590
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• 2017

The purpose of this paper is the provision of a decision-making tool for developers to identify the project risks for under-consideration overseas independent power projects (IPPs), and to analyze the priority and importance weights of the risks through the employment of a fuzzy multi-criteria decision-making (MCDM) approach. A fuzzy MCDM is the calculation method for which the imprecision of each respondent's unique opinion is considered. Through the extensive literature surveys that were conducted for this paper, eight major project finance (PF) risks have been derived credit risk, completion risk, market risk, fuel risk, operating risk, financial risk, environmental risk, and force majeure. The empirical results show that the market risk is the most important risk factor in terms of overseas IPPs, thereby confirming that the long-term power purchase agreement (PPA) guarantee of the host country is one of the most important corresponding factors for the PF.