• The Journal of the Korea Contents Association
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• v.6 no.7
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• pp.58-68
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• 2006

There are two traditional scheduling methods known as PQ and WRR in the DiffServ network, however, these two scheduling methods have some drawbacks. In this paper, we propose an algorithm that can be adopted in WRR scheduler with making up for weak points of PQ and WRR. The proposed algorithm produces the control discipline by the fuzzy theory to dynamically assign the weight of WRR scheduler with checking the Queue status of each class. To evaluate the performance of the proposed algorithm, We accomplished a computer simulation using NS-2. From simulation results, the proposed algorithm improves the packet loss rate of the EF class traffic to 6.5% by comparison with WRR scheduling method and that of the AF4 class traffic to 45% by comparison with PQ scheduling method.

• Journal of Technology Innovation
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• v.19 no.3
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• pp.85-114
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• 2011

This paper aims at developing a new index that represents the Korean new growth industries, which is named the Korea Future Technology Index(KOFTI). The KOFTI is designed to provide a reliable and econometric index based on which the Korean government searches for new growth engines. The KOFTI is composed of three individual indexes such as the Economic Impact Index, the Future Strategy Index, and the Technological Influence Index. The KOFTI is applied for 62 star brands, which have been promoted by the Korean government for the korean future industrial competitiveness. The top 13 leading industries are drawn from the calculation of the KOFTI for 62 star brands.

• Journal of Advanced Navigation Technology
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• v.14 no.4
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• pp.553-561
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• 2010

This paper proposed the face tracking method which can be effectively applied to the robot's vision system. The proposed algorithm tracks the facial areas after detecting the area of video motion. Movement detection of video images is done by using median filter and erosion and dilation operation as a method for removing noise, after getting the different images using two continual frames. To extract the skin color from the moving area, the color information of sample images is used. The skin color region and the background area are separated by evaluating the similarity by generating membership functions by using MIN-MAX values as fuzzy data. For the face candidate region, the eyes are detected from C channel of color space CMY, and the mouth from Q channel of color space YIQ. The face region is tracked seeking the features of the eyes and the mouth detected from knowledge-base. Experiment includes 1,500 frames of the video images from 10 subjects, 150 frames per subject. The result shows 95.7% of detection rate (the motion areas of 1,435 frames are detected) and 97.6% of good face tracking result (1,401 faces are tracked).

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.10
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• pp.59-68
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• 2009

The field oriented control of induction motors is widely used in high performance applications. However, detuning caused by parameter disturbance still limits the performance of these drives. In order to accomplish variable speed operation, conventional PI-like controllers are commonly used. These controllers provide limited good performance over a wide range of operation, even under ideal field oriented conditions. This paper is proposed high performance control of induction motor drive using multi adaptive fuzzy controller. This controller has been performed for speed control with fuzzy adaptation mechanism (FAM)-PI, current control with model reference adaptive fuzzy control(MFC) and estimation of speed using ANN. The proposed control algorithm is applied to induction motor drive system using FAM-PI, MFC and ANN controller. The performance of proposed controller is evaluated by analysis for various operating conditions using parameters of induction motor drive. Also, this paper is proposed the analysis results to verify the effectiveness of this controller.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.139-145
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• 2018

An outrigger system is used widely to increase the lateral stiffness of high-rise buildings, resulting in reduced dynamic responses to seismic or wind loads. Because the dynamic characteristics of earthquake or wind loads are quite different, a smart vibration control system associated with an outrigger system can be used effectively for both seismic and wind excitation. In this study, an adaptive smart structural control system based on an outrigger damper system was investigated for the response reduction of multi-hazards, including seismic and wind loads. A MR damper was employed to develop the smart outrigger damper system. Three cities in the U.S., L.A., Charleston, and Anchorage, were used to generate multi-hazard earthquake and wind loads. Parametric studies on the MR damper capacity were performed to investigate the optimal design of the smart outrigger damper system. A smart control algorithm was developed using a fuzzy controller optimized by a genetic algorithm. The analytical results showed that an adaptive smart structural control system based on an outrigger damper system can provide good control performance for multi-hazards of earthquake and wind loads.

• Proceedings of the Korea Contents Association Conference
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• 2006.05a
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• pp.128-131
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• 2006

There are two traditional scheduling methods known as PQ and WRR in the DiffServ network, however, these two scheduling methods have some drawbacks. In this paper, we propose an algorithm that can be adopted in WRR scheduler with making up for weak points of PQ and WRR. The proposed algorithm produces the control discipline by the fuzzy theory to dynamically assigns the weight of WRR scheduler with checking the Queue status of each class. To evaluate the performance of the proposed algorithm, We accomplished a computer simulation using NS-2. In result, the proposed algorithm enhances the packet discard rate at the EF class than WRR scheduling method and the AF4 class than PQ scheduling method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.1
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• pp.14-22
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• 2001

Off-line handwritten numeral recognition is a very difficult task and hard to achieve high recognition results using a single feature and a single classifier, since handwritten numerals contain many pattern variations which mostly depend upon individual writing styles. In this paper, we propose handwritten numeral recognition system using hybrid features and combined classifier. To improve recognition rate, we select mutually helpful features -directional features, crossing point feature and mesh features- and make throe new hybrid feature sets by using these features. These hybrid feature sets hold the local and global characteristics of input numeral images. And we implement combined classifier by combining three neural network classifiers to achieve high recognition rate, where fuzzy integral is used for multiple network fusion. In order to verify the performance of the proposed recognition system, experiments with the unconstrained handwritten numeral database of Concordia University, Canada were performed. As a result, our method has produced 97.85% of the recognition rate.

• The Journal of the Korea Contents Association
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• v.18 no.5
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• pp.280-291
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• 2018

Recently, various interactions have been actively conducted through sharing and expressing opinions among users in social networks. In this process, since malicious users and fault information spread misinformation, trust is reduced irrespective of their will. To solve this problem, studies have been conducted to determine the trust of a user through direct-connected users. In this paper, we propose a enhanced user indirect trust discrimination scheme considering the connection relation and influence of users. The proposed indirect trust computation scheme derives the user's area of interest through user interaction and reconstructs the existing network considering the user connection relationship. The final indirect trust is also detected by determining whether the user is a malicious user through the influence of the user. Through various performance evaluations, we show that the proposed scheme achieves better performance than the existing method.

• Journal of Soil and Groundwater Environment
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• v.23 no.4
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• pp.26-41
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• 2018

The purpose of this study is to improve the Original DRASTIC Model (ODM) for the assessment of groundwater contamination vulnerability on the GIS platform. Miryang City of urban and rural features was selected for the study area to accomplish the research purpose. Advanced DRASTIC Model (ADM) was developed adding two more DRASTIC factors of lineament density and landuse to ODM. The fuzzy logic was also applied to ODM and ADM to improve their ability in evaluating the groundwater contamination vulnerability. Although the vulnerability map of ADM was a little simpler than that of ODM, it increased the area of the low vulnerability sector. The groundwater vulnerability maps of ODM and ADM using DRASTIC Indices represented the more detailed descriptions than those from the overlap of thematic maps, and their qualities were improved by the application of fuzzy technique. The vulnerability maps of ODM, ADM and FDM was evaluated by NO3-N concentrations in the study area. It was proved that ADM including lineament density and landuse factors produced a more reliable groundwater vulnerability map, and fuzzy ADM (FDM) made the best detailed groundwater vulnerability map with the significant statistical results.

• The Journal of Society for e-Business Studies
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• v.20 no.2
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• pp.125-140
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• 2015

It is general that the impact of supply chain risk spread out to the whole network along the connected structure. Due to the risk propagation the probability to exposure a certain risk is affected by not only the characteristics of each risk factor but also network structure. It means that the structural connectivity among vertices should be considered while designing supply chain network in order to minimize disruption cost. In this research, the betweenness centrality has been utilized to quantitatively assess the structural vulnerability. The betweenness centrality is interpreted as the index which can express both the probability of risk occurrence and propagation of risk impact. With the structural vulnerability index, it is possible to compare the stability of each alternative supply chain structure and choose the better one.