• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.2
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• pp.19-25
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• 2003

For a class of multi-input multi-output nonlinear systems which perform a given task repetitively, an extended type of a direct leaning control (DLC) is proposed using the information on the (vector) relative degree of a multi-input multi-output system. Existing DLC methods are observed to be applied to a limited class of systems with the relative degree one and a new DLC law is suggested which can be applied to systems having higher relative degree. Using the proposed control law, the control input corresponding to the new desired output trajectory is synthesized directly based on the control inputs obtained from the learning process for other output trajectories. To show the validity and the performance of the proposed DLC, simulations are performed for trajectory tracking control of a two-axis SCARA robot.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.711-712
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• 2008

We developed a XMAS (X Multimedia Analysis System) for analyzing the illegal and objectionable multimedia in Internet environment based on Web2.0. XMAS uses the MPEG-7 visual descriptor and multi-class SVM (support vector machine) and its performance (accuracy on precision) is about 91.6% for objectionable multimedia analysis and 99.9% for illegal movie retrieval.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.985-988
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• 1993

An alternative approach to the design of application-driven fuzzy systems is proposed. A broad class of fuzzy systems applications requires a certain fuzzy partition of the input space while it demands for simple numerical quantities. For this class, a dedicated fuzzy system archictecture is presented and a design strategy is proposed. Both the single-input/single-output and multi-input/multi-output cases are considered. Numerical analysis are complete illustrating several aspects of the proposed framework.

• The Journal of the Korean dental association
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• v.13 no.10
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• pp.929-933
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• 1975

A girl aged 15 years 6 months, had a class Ⅲ malocclusion characterized by severe maxillary anterior crowding and a retarded maxilla. Molar relationship was class Ⅲ on both sides, incisor overjet was - 2.9mm. and incisor overbite was 5.5mm. The patient underwent extraction of four first premolars and was trested with a multi-banded light force system. After 13 months, the patient gained a normal verbite-overjet relationship of anterior teeth and a class 1 molar relationship. Superimposition of pretreatment and posttreatment cephalograms upon the line SN registered at S showed backward downward rotation of the mandible.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.1
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• pp.14-32
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• 2022

In this paper, we report the results of a conceptual study to develop of a multi-purpose medium-sized UAV that can safely perform missions in harsh maritime environments. In this study, we focused on developing UAVs capable of performing three maritime missions that urgently require the application of medium-sized UAVs: marine ecosystem management, ocean surveillance system, and response to marine accidents. Furthermore improvement points for the above three naval missions using medium-sized UAVs were derived in preparation for the problems of the existing mission performance. Finally, by developing and analyzing the utilization scenario of the medium-class UAV, the required performance suitable for each mission was defined and assigned to the related mission equipment, A new maritime management plan was proposed using the medium-class UAV system equipped with replaceable mission equipment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.8
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• pp.958-964
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• 2016

In this paper, we propose an i-vector based language recognition system to identify the spoken language of the speaker, which uses multiple discriminative deep neural network (DNN) models analogous to the multi-class support vector machine (SVM) classification system. The proposed model was trained and tested using the i-vectors included in the NIST 2015 i-vector Machine Learning Challenge database, and shown to outperform the conventional language recognition methods such as cosine distance, SVM and softmax NN classifier in open-set experiments.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.4
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• pp.117-124
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• 2015

As recent developing computing environments, service is provided without time or place's limitation, and it is constituted dynamically. Above all, in terms of education supporting system, there is need to conceive user's information and provide optimal service as to right with applying context awareness under Ubiquitous computing environment. It should have groundwork based on user location and time. It is requires service providing based on user location under the condition of class to offer appropriate service with the context. In addition, context information providing technology is needed to offer right education support service in the class, where are different context information. Hence, in this research it is suggested education supporting system to provide context-based for instructor. The framework of this system has a foundation within previous work about Multi-agent based Distributed Framework. To examine implementation of context-based education supporting system in Ubiquitous computing environments suggested by this report, arranging system can fit information relates to instructor's location for service applying in the class.

• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.4
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• pp.11-33
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• 2013

We analyzed the structures and properties of the global financial market networks using social network analysis approach. The Minimum Spanning Tree (MST) lengths and networks of the global financial markets based on the correlation coefficients have been analyzed. Firstly, similar to the previous studies on the global stock indices using MST length, the diversification effects in the global multi-asset portfolio can disappear during the crisis as the correlations among the asset class and within the asset class increase due to the system risks. Second, through the network visualization, we found the clustering of the asset class in the global financial markets network, which confirms the possible diversification effect in the global multi-asset portfolio. Meanwhile, we found the changes in the structure of the network during the crisis. For the last one, in terms of the degree centrality, the stock indices were the most influential to other assets in the global financial markets network, while in terms of the betweenness centrality, Gold, Silver and AUD. In the practical perspective, we propose the methods such as MST length and network visualization to monitor the change of the correlation risk for the risk management of the multi-asset portfolio.

• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.155-167
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• 2008

This paper studies a multiple user class variable demand user equilibrium and system optimal condition, and then establishes solution algorithms for them. The traffic network equilibrium is accomplished with basis on following assumptions. For considering heterogeneous road user, several user classes have discrete set of VOTs and the travel demand of each user classes varies according to generalized travel cost. this paper specifically investigates following question on multi-class variable demand: Are user equilibrium flows pattern dependent on the unit (time or money) perceived by road user classes? What is system optimal condition according to the unit used in measuring the travel cost or disutility? Finally, using this network equilibrium condition, The traffic assignment algorithm of each equilibrium condition are established.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.6
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• pp.33-43
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• 2021

A60 class bulkhead penetration piece is a fire resistance system installed on a bulkhead compartment to protect lives and to prevent flame diffusion in a fire accident on a ship and offshore plant. This study focuses on the approximate optimization of the fire resistance design of the A60 class bulkhead penetration piece using a multi-island genetic algorithm. Transient heat transfer analysis was performed to evaluate the fire resistance design of the A60 class bulkhead penetration piece. For approximate optimization, the bulkhead penetration piece length, diameter, material type, and insulation density were considered discrete design variables; moreover, temperature, cost, and productivity were considered constraint functions. The approximate optimum design problem based on the meta-model was formulated by determining the discrete design variables by minimizing the weight of the A60 class bulkhead penetration piece subject to the constraint functions. The meta-models used for the approximate optimization were the Kriging model, response surface method, and radial basis function-based neural network. The results from the approximate optimization were compared to the actual results of the analysis to determine approximate accuracy. We conclude that the radial basis function-based neural network among the meta-models used in the approximate optimization generates the most accurate optimum design results for the fire resistance design of the A60 class bulkhead penetration piece.