• Journal of Navigation and Port Research
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• v.41 no.3
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• pp.109-118
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• 2017

The key word (KW) is a set of words to clearly express the important causations of marine accidents; they are determined by a judge in a Korean maritime safety tribunal. The selection of KW currently has two main issues: one is maintaining consistency due to the different subjective opinion of each judge, and the second is the large number of KW currently in use. To overcome the issues, the systematic framework used to construct KW's needs to be optimized with a minimal number of KW's being derived from a set of Common Words (CW). The purpose of this study is to identify a set of CW to develop the systematic KW construction frame. To fulfill the purpose, the word reduction method to find minimum number of CW is proposed using P areto distribution function and Pareto index. A total of 2,642 KW were compiled and 56 baseline CW were identified in the data sets. These CW, along with their frequency of use across all KW, are reported. Through the word reduction experiments, an average reduction rate of 58.5% was obtained. The estimated CW according to the reduction rates was verified using the Pareto chart. Through this analysis, the development of a systematic KW construction frame is expected to be possible.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.2
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• pp.455-461
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• 2008

Enhanced Distributed Channel Access (EDCA) is a channel access scheme adopted by the IEEE 802.11e draft standard for QoS-enabled wireless local area networks. It classifies traffic into separate Access Categories (ACs) and achieves service differentiation by allowing each AC to have its own values of channel access parameters. This paper proposes a scheme to dynamically adapt the EDCA parameters to traffic environment so that they both maximize the throughput of non real-time traffics and meet the delay and throughput constraints of real-time traffics. For this purpose, we develop a design algorithm for efficient exploration of the EDCA parameter space. Using the algorithm, we derive a Pareto curve fur delay-throughput trade-off in each anticipated traffic environment. The Pareto database can then be used to optimally adjust the parameter according to the traffic environment and administrative policies. Simulation results show that compared with the default parameter configuration, the proposed scheme is better for delay, throughput guarantee and can improve the throughput of non real-time traffics by 12% on average.

• Journal of computational fluids engineering
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• v.19 no.4
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• pp.14-19
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• 2014

This study conducts shape optimization of rib turbulator on the internal cooling passage that has triangular cross-section of high pressure turbine nozzle. During optimization, various types of rib turbulator including angled, V-shaped, A-shaped and angled rib with intersecting rib are considered. Each type of rib turbulator is parameterized with attack angle(s), rib height, spacing ratio and bending/intersecting location. For optimization, Design of Experiment (DOE) and Kriging surrogate model are used to utilize computational resource more efficiently and Genetic Algorithm (GA) is used to search the optimum points. As a result, Pareto front of each type of rib turbulator with friction factor that relates to pressure drop in cooling passage and spatially averaged Nusselt number that relates to heat transfer on the wall is drawn and optimum points on the Pareto front are suggested.

• Journal of KIISE:Information Networking
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• v.37 no.4
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• pp.312-316
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• 2010

In this paper, we propose a game theoretic channel sharing model that allocates resources of a base station between MNO(Mobile Network Operator) and MVNO(Mobile Virtual Network Operator) in a fair and efficient manner. Considering the input traffic loads of MNO and MVNO, the proposed model uses the bargaining game theory to allocate channel resources between MNO and MNVO. When the input loads of the carriers are asymmetric, the proposed model increases the resource utilization by allocating more channel resources to the operator with high input load. In addition, the proposed model prevents the quality of service of an operator from degrading even if the input load of the other operators increases excessively.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.6
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• pp.507-514
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• 2022

This study proposes an optimal design process for a high-frequency transformer that has a large leakage inductance for dual-active-bridge converters. Notably, conventional design processes have large errors in designing leakage transformers because mathematically modeling the leakage inductance of such transformers is difficult. In this work, the geometric parameters of a shell-type transformer are identified, and finite element analysis(FEA) simulation is performed to determine the magnetization inductance, leakage inductance, and copper loss of various shapes of shell-type transformers. Regression models for magnetization and leakage inductances and copper loss are established using the simulation results and the machine learning technique. In addition, to improve the regression models' performance, the regression models are tuned by adding featured parameters that consider the physical characteristics of the transformer. With the regression models, optimal high-frequency transformer designs and the Pareto front (in terms of volume and loss) are determined using NSGA-II. In the Pareto front, a desirable optimal design is selected and verified by FEA simulation and experimentation. The simulated and measured leakage inductances of the selected design match well, and this result shows the validity of the proposed design process.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.6
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• pp.56-66
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• 1998

This paper investigates a neuro-controller combined in parallel with a conventional linear controller of PID type in order to control nonminimum phase systems more efficiently. The objective is to minimize overall position errors as well as to maintain small undershooting. A costfunction is proposed with two conflict objectives. The neuro-controller is trained off-line with evolutionary programming(EP) in such a way that it becomes optimal by minimizing the given cost function through global evaluation based on desired control performance during the whole training time interval. However, it is not easy to find an optimal solution which satisfies individual objective simultaneously. With the concept of Pareto optimality and EP, we train the proposed controller more effectively and obtain a valuable set of optimal solutions. Simulation results show the efficacy of the proposed controller in a viewpoint of improvement of performance of a step response like fast settling time and small undershoot or overshoot compared with that of a conventional linear controller.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.11
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• pp.1106-1110
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• 2010

This paper proposes a method of optimizing a stacking strategy for an automated container terminal using multi-objective evolutionary algorithms (MOEAs). Since the yard productivities of seaside and landside are conflicting objectives to be optimized, it is impossible to maximize them simultaneously. Therefore, we derive a Pareto optimal set instead of a single best solution using an MOEA. Preliminary experiments showed that the population is frequently stuck in local optima because of the difficulty of the given problem depending on the yard occupancy rate. To cope with this problem, we propose another method of simultaneously optimizing two problems with different difficulties so that diverse solutions can be preserved in the population. Experimental results showed the proposed method can derive better stacking policies than the compared method solving a single problem given the same computational costs.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.332-332
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• 2023

농업용 저수지는 농촌유역의 홍수조절에 핵심적인 역할을 하지만 기본적인 기능은 이수 기능이기 때문에 농업용수 수량을 충분하게 확보하면서 동시에 홍수에도 대비할 수 있도록 저수지를 적절히 운영하는 것이 중요하다. 이에 농업용 저수지마다 홍수기 제한수위를 설정하여 홍수조절용량과 농업용수를 적절하게 확보하도록 하고 있으나, 현재 홍수기 제한수위는 저수지별 특성을 고려하지 않고 70% 정도의 저수율 기준이 일괄적으로 적용된 경우가 대부분이며 시기별 농업용수공급 특성을 고려하지 못한다. 이에 본 연구에서는 농업용 저수지의 이수안전도 및 치수안전도를 이용하여 이·치수 기능을 모두 고려한 홍수기 제한수위 설정 방안을 제시하였다. 홍수기 제한수위는 초기 (6/21~7/20), 중기 (7/21~8/20), 후기 (8/21~9/20)에 대해 각각 설정하였고, 오봉저수지와 묘곡저수지에 대해 1973~2022년의 기상자료를 이용하여 이·치수를 모의하였다. 관개기 최저저수량 및 이듬해 4월의 저수량을 기준으로 이수안전도를 산정하고, 재현기간 100년/200년/500년 홍수에 대해 저수지 운영을 모의하여 최고저수량을 기준으로 치수안전도를 산정하였다. 초기/중기/후기 제한수위 조합에 대한 이수안전도 및 치수안전도 값을 좌표공간에 점으로 도시하고 Pareto front를 도시하여 최적의 제한수위 범위를 도출하였다. 분석 결과, 오봉저수지의 이수안전도는 후기 제한수위에 의해 대부분 결정되며, 초기/중기 제한수위는 큰 영향을 주지 못하는 것으로 나타났다. 반면 묘곡저수지의 이수안전도는 초기 제한수위에 의해 크게 영향을 받으며, 그 영향이 이듬해까지 이어지는 것으로 나타났다. 이를 토대로 최적의 제한수위를 도출한 결과, 오봉저수지의 경우 초기 65%, 중기 65~80%, 후기 95% (유효저수량에 대한 비율)로 시기별 수문 운영이 필요한 것으로 나타났고, 묘곡저수지의 경우 초기 100%, 중기 95%, 후기 65~80%로 취수 구조물 또는 비상수문 설치를 통한 방류가 필요한 것으로 나타났다. 본 연구에서 제시한 방법을 통해 저수지별 특성을 고려하여 홍수기 제한수위를 설정함으로써 효율적인 저수지 운영이 가능할 것으로 기대된다.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.4
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• pp.1-7
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• 2009

This paper presents a process routing (PR) algorithm with multiple objectives. PR determines the optimum sequence of operations for transforming a raw material into a completed part within the available machining resources. In any computer aided process planning (CAPP) system, selection of the machining operation sequence is one of the most critical activities for manufacturing a part and for the technical specification in the part drawing. Here, the goal could be to generate the sequence that optimizes production time, production cost, machine utilization or with multiple these criteria. The Pareto Stratum Niche Cubicle (PS NC) GA has been adopted to find the optimum sequence of operations that optimize two conflicting criteria; production cost and production quality. The numerical analysis shows that the proposed PS NC GA is both effective and efficient to the PR problem.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.284-288
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• 2005

본 연구에서는 낙동강수계 일별 운영 계획 수립을 위한 저수지군 최적 연계운영 모형(CoMOM, Coordinated Multiple Reservoir Operating Model)을 개발하였다. 이를 위하여 동적 네트워크 흐름 모형을 기반으로 한 다중목적 혼합 정수 목표계획 모형 (MOMIGP, Multiple Objective Mixed Integer Goal-Programming)을 수립하였다. 이 모형은 월말 목표 수위 및 운영 제약 등을 목표 계획법으로 구성하였으며, 일별 운영의 특성을 고려하여 하도추적의 효과를 반영하였고, 선형화된 발전함수를 이용하여 발전량을 최대화 하도록 한 후 정확한 발전량을 사후에 산정하였다. 이와 같이 수립된 수학 모형을 GUI를 비롯한 프로그램(CoMOM)으로 개발하여 사용자가 편리하게 수행 할 수 있도록 하였다. 이 프로그램은 의사결정자의 운영 목표와 의도를 효과적으로 반영할 수 있도록 대화형 목표 계획법을 구현하였으며, 상충되는 여러 목적에 대하여 가능한 파래토(Pareto) 최적해를 제시하고 의사결정자가 가장 선호하는 해를 선택하도록 대화형 다중목적 계획법 CBITP(Convex hull of individual maxima Based Interactive Tchebycheff Procedure)를 활용하여 구현하였다. 한편 객체지항적 프로그램 기법을 활용하여 수계 내의 노드(저수지, 수요지, 발전소 등)를 추가 하거나 삭제 할 수 있도록 하여, 다른 수계로의 확장이 용이하도록 개발하였다.