• 한국군사과학기술학회지
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• 제17권2호
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• pp.189-196
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• 2014

Automated design program using commercial process integration and optimization program was developed for conceptual design of fighter-class aircraft. Wind tunnel test data and performance analysis results were compared for the verification of analysis tool of this program, and the usefulness of the tool was found. After integration with radar cross section analysis tool, the correlation with configuration design variables of wing, tail and performance parameters was identified by design of experiment, and the optimized configuration for weight and RCS was derived from optimization of empty weight and average frontal RCS value. After parameter definition of fuselage, the program can be implemented for full aircraft configuration.

• 대한조선학회논문집
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• 제53권2호
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• pp.108-114
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• 2016

Recently, there has been a growing interest in marine leisure sports and high speed power boat for fishing. The prototype of 20 feet class power boat was developed and authors are joined in this government-led project. The research was performed to evaluate the optimal structure and design of the structural strength necessary to ensure the structural safety of the power boat. A new material ROCICORE fiber added to the mat and roving was adopted for high-power tenacity. ANSYS Workbench has been used to make the structural model, evaluate the strength and optimize the structural design. The response of the structure to quasi-static slamming loads according to the rules and regulations of ISO 12215-5, Lloyd’s Register of Shipping and Korean Register has been implemented and studied. An optimization study for the structural response is carried out by changing the plate thickness and section modulus of stiffeners. The power boat structure derived fuel efficiency is optimized by performing the best possible structural design to minimize the hull weight.

• Current Optics and Photonics
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• 제7권4호
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• pp.435-442
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• 2023

These days, the size of a reflective telescope has been increasing for astronomical observation. An additional optical system usually assists a large ground telescope for image analysis or the compensation of air turbulence. To guide collimated light to the external optical system through a designated path, a coudé mirror is usually adopted. Including a collimator, a coudé mirror of a ground telescope is affected by gravity, depending on the telescope's pointing direction. The mirror surface is deformed by the weight of the mirror itself and its mount, which deteriorates the optical performance. In this research, we propose an optimization method for the coudé mirror assembly for a 1-m class ground telescope that minimizes the gravitational surface error (SFE). Here the mirror support positions and the sizes of the mount structure are optimized using finite element analysis and the response surface optimization method in both the horizontal and vertical directions, considering the telescope's altitude angle. Throughout the whole design process, the coefficients of the Zernike polynomials are calculated and their amplitude changes are monitored to determine the optimal design parameters. At the same time, the design budgets for the thermal SFE and the mass and size of the mount are reflected in the study.

• 한국초전도ㆍ저온공학회논문지
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• 제7권4호
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• pp.24-27
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• 2005

Development of a 600 kJ class Superconducting Magnetic Energy Storage (SMES) system is being in progress by Korea Electrotechnology Research Institute(KERI). High temperature superconducting (HTS) wires are going to be used for the windings for the SMES system is presented in this paper. We considered BSCCO-2223 wire for the HTS windings and the operating temperature of the winding was decided to be 20 K which will be accomplished by conduction cooling method using cyro-coolers. Auto-Tuning Niching Genetic Algorithm was adopted for an optimization method of the HTS magnets in the SMES system. The objective function of the optimal process was minimizing total amount of the HTS wire. As a result, we obtained output parameters for optimization design of 600 kJ class SMES under several constrained conditions. These HTS windings are going to be applied to the SMES system whose purpose is stabilization of the power grid.

• 해양환경안전학회지
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• 제1권2호
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• pp.69-82
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• 1995

This study is concerned with developing a heuristic algorithm for solving a class of ninlinear integer programs(NLIP). Exact algrithm for solving a NLIP either may not exist, or may take an unrealistically large amount of computing time. This study develops a new heuristic, the Excursion Algorithm(EA), for solving a class of NLIP's. It turns out that excursions over a bounded feasible and/or infeasible region is effective in alleviation the risks of being trapped at a lical optimum. The developed EA is applied to the redundancy optimization problems for improving the system safety, and is compared with other existing heuristic methods. We also include simulated annealing(SA) method in the comparision experiment due to ist populatrity for solving complex combinatorial problems. Computational results indicate that the proposed EA performs consistently better than the other in terms of solution quality, with moderate increase in computing time. Therefore, the proposed EA is believed to be an attractive alternative to other heuristic methods.

• 대한수학교육학회지:수학교육학연구
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• 제20권2호
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• pp.185-202
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• 2010

본 연구는 중등수학교육에서 도구화된 CAS에 기반한 최적화 문제해결 활동을 통해 CAS가 교육과정 내용제시 순서에 영향을 줄 수 있는지를 분석하기 위해 설계되었다. 이를 위하여 본 연구자는 CAS를 활용한 최적화 문제해결 활동을 구안하였으며 3개월간의 CAS 활용 수업 경험이 있으나 아직 미적분학을 접해 본 적이 없는 고등학교 2학년 7명을 선정하여 총 9차시의 수업을 실시하고, 수업녹화자료와 면담을 통해 학생들의 활동을 분석하였다. 분석 결과, 학생들은 CAS를 이용하여 미 학습된 교육내용인 미분과 삼차방정식, 무리방정식의 해구하기와 그래프 분석이 포함된 최적화 문제해결활동을 수준 높게 다룰 수 있는 것으로 나타나 CAS가 교육과정 내용제시 순서에 영향을 줄 수 있음을 확인할 수 있었다.

• 한국해안·해양공학회논문집
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• 제26권6호
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• pp.359-366
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• 2014

본 연구에서는 버터플라이밸브의 고유 유량 특성을 개선하기 위해 회색 관계분석을 이용한 디스크 형상 최적화 방안을 도입하였다. Class 150의 200A 버터플라이밸브에 대해 적용하여 그 유용성을 확인하였다. 부가물 형상 파라미터의 영향 분석을 위해 직교 배열을 이용한 실험계획법을 실시하였으며, 파라미터의 영향을 회색 관계 분석과 평균 분석을 이용하여 분석하였다. 최적화를 위한 목적함수는 유량 계수를 선정하였으며, 기존 디스크 모델과 부가물 부착 모델에 대해 유동 해석을 수행하였다. 회색 관계 등급을 이용하여 평균 분석을 실시하였으며, 그 결과를 토대로 최적 형상을 결정하였다.

• 가정과삶의질연구
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• 제21권2호
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• pp.131-144
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• 2003

Selective Optimization with Compensation (SOC), a concept defined by Baltes and Baltes, is known to predict successful aging. This study was conducted to find out which factors affect Korean elderly people SOC The data for this study were obtained from a survey conducted between March and May 2001, on a sample of middle-class male and female participants over 60 years old. Two hundred and fifty four completed questionnaires were used for final analyses. Descriptive statistics, t-test, ANOVA, Duncan test, Pearson correlations, multiple regressions, multiple response frequencies and sequential threshold methods were used to analyze the data. In order to measure successful aging, the Selective Optimization with Compensation Scale developed by Baltes, Baltes, Freud, and Lang (1996) was used. The SOC scale consists of four subscales, Elective Selection, Loss-based Selection, Optimization, and Compensation. The major findings are summarized in the following. First, the level of SOC by various socio-demographic variables was examined. It tuned out that health status is the most important variable in predicting SOC. Also important was satisfaction with family life. Second, significant correlations were found between SOC and duration of the marriage (negative), practicing a religion, health, and economic stability (all positive). Third, religion and health status affected SOC, but health was a stronger predictor Those who practiced a religion and were healthy had a higher score in SOC as a whole. Fourth, the participants were divided into three groups by their SOC score, and their idea.; of successful aging were compared. The top- and middle-score groups considered satisfaction with family life to be more important, whereas the bottom-score group regarded the social status as more important.

• International Journal of Computer Science & Network Security
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• 제23권11호
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• pp.21-31
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• 2023

In this paper, we focused on the problem of evaluating multi-class classification accuracy and simulation of multiple classifier performance metrics. Multi-class classifiers for sentiment analysis involved many challenges, whereas previous research narrowed to the binary classification model since it provides higher accuracy when dealing with text data. Thus, we take inspiration from the non-linear Support Vector Machine to modify the algorithm by embedding dynamic hyperplanes representing multiple class labels. Then we analyzed the performance of multi-class classifiers using macro-accuracy, micro-accuracy and several other metrics to justify the significance of our algorithm enhancement. Furthermore, we hybridized Enhanced Convolution Neural Network (ECNN) with Dynamic Support Vector Machine (DSVM) to demonstrate the effectiveness and efficiency of the classifier towards multi-class text data. We performed experiments on three hybrid classifiers, which are ECNN with Binary SVM (ECNN-BSVM), and ECNN with linear Multi-Class SVM (ECNN-MCSVM) and our proposed algorithm (ECNNDSVM). Comparative experiments of hybrid algorithms yielded 85.12 % for single metric accuracy; 86.95 % for multiple metrics on average. As for our modified algorithm of the ECNN-DSVM classifier, we reached 98.29 % micro-accuracy results with an f-score value of 98 % at most. For the future direction of this research, we are aiming for hyperplane optimization analysis.

• 전기학회논문지P
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• 제67권3호
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• pp.143-148
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• 2018

In this paper, the optimal fuzzy logic controller(FLC) for a hybrid renewable energy system(HRES) is proposed. Generally, hybrid renewable energy systems can consist of wind power, solar power, fuel cells and storage devices. The proposed FLC can effectively control the entire HRES by determining the output power of the fuel cell or the absorption power of the electrolyzer. In general, fuzzy logic controllers can be optimized by classical optimization algorithms such as genetic algorithms(GA) or particle swarm optimization(PSO). However, these FLC have a disadvantage in that their performance varies greatly depending on the control parameters of the optimization algorithms. Therefore, we propose a method to optimize the fuzzy logic controller using the teaching-learning based optimization(TLBO) algorithm which does not have the control parameters of the algorithm. The TLBO algorithm is an optimization algorithm that mimics the knowledge transfer mechanism in a class. To verify the performance of the proposed algorithm, we modeled the hybrid system using Matlab Tool and compare and analyze the performance with other classical optimization algorithms. The simulation results show that the proposed method shows better performance than the other methods.