• 대한원격탐사학회지
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• 제24권2호
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• pp.107-115
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• 2008

최근에 개체의 경계가 분명하게 나타나는 고해상도 위성영상을 분석하는 연구가 활발히 이루어지고 있다. 고해상도 영상을 이용해 도시지역을 세분화하여 연구하려고 할 때 분석의 범위는 임의로 결정되는 경우가 많다. 연구지역에 대한 사전정보가 충분하다면 임의로 결정하는 것이 가능하지만 그렇지 않을 경우 영상만을 이용해 연구 지역의 최적 분석범위를 결정하는 것은 쉽지 않다. 이 연구에서는 실제 위성 영상에 적용하기에 앞서 간단한 가상 모델의 베리오그램을 분석하였다. 모델 테스트 결과, 문턱값은 개체들의 밀도에 영향을 주고 개체의 크기와 간격은 상관거리에 영향을 준다. 이 모델 테스트의 결과를 도시지 역을 촬영한 실제 위성영상의 베리오그램에 반영하여 분석하고 이론적 베리오그램의 상관거리를 이용해 최적의 분석 단위를 결정하였다. 이 연구는 베리오그램이 연구지역에 대한 사전자료가 없는 경우 효과적으로 기본 분석단위를 결정하는데 도움을 줄 수 있을 것이라는 것을 보여주었다. 또한 베리오그램은 기존의 전통적인 크리깅이나 시뮬레이션뿐만 아니라 도시 영상의 특성을 정의하는 정보로 활용 가능할 것으로 기대된다.

• Journal of Electrical Engineering and Technology
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• 제11권6호
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• pp.1628-1633
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• 2016

This paper derives an effective shape of the ferromagnetic pole pieces (low-speed rotor) for the reduction of transmission torque ripple in a magnetic-geared machine based on a Box-Behnken design (BBD). In particular, using a non-linear finite element method (FEM) based on 2-D numerical analysis, we conduct a numerical investigation and analysis between independent variables (selected by the BBD) and reaction variables. In addition, we derive a regression equation for reaction variables according to the independent variables by using multiple regression analysis and analysis of variance (ANOVA). We assess the validity of the optimized design by comparing characteristics of the optimized model derived from a response surface analysis and an initial model.

• Composites Research
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• 제18권4호
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• pp.52-58
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• 2005

사이클로콥터는 회전축에 평행하게 회전하는 블레이드로 구성된 사이클로이드 블레이드 시스템으로부터 추력을 얻는 수직이착륙 무인기이다. 본 논문에서는 공기역학을 고려한 최적 설계를 통해 결정된 형상을 갖는 사이글로콥터 로터에 대해서 구조적 관점에서 최적 설계를 수행하였다. 복합재료 블레이드의 적층각, 적층수와 스파 위치 등을 설계 변수로 하여 MSC/NASTRAN을 이용한 해석을 통해 데이터베이스를 구축하고, 반응면 기법 등에 의해서 최적의 조합을 결정하였다. 최적 설계된 블레이드와 복합재료로 구성된 허브암을 포함하는 로터에 대해, 정적 해석을 수행하여 각 요소가 허용 응력 이내의 값을 가짐을 확인하였고, 동적 해석을 통해 주요 저차 모드가 로터 회전과 불일치하게 함으로써 공진의 가능성을 없앴다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1505-1509
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• 2005

This paper introduces a new architecture of genetically optimized self-organizing fuzzy polynomial neural networks by means of information granulation. The conventional SOFPNNs developed so far are based on mechanisms of self-organization and evolutionary optimization. The augmented genetically optimized SOFPNN using Information Granulation (namely IG_gSOFPNN) results in a structurally and parametrically optimized model and comes with a higher level of flexibility in comparison to the one we encounter in the conventional FPNN. With the aid of the information granulation, we determine the initial location (apexes) of membership functions and initial values of polynomial function being used in the premised and consequence part of the fuzzy rules respectively. The GA-based design procedure being applied at each layer of genetically optimized self-organizing fuzzy polynomial neural networks leads to the selection of preferred nodes with specific local characteristics (such as the number of input variables, the order of the polynomial, a collection of the specific subset of input variables, and the number of membership function) available within the network. To evaluate the performance of the IG_gSOFPNN, the model is experimented with using gas furnace process data. A comparative analysis shows that the proposed IG_gSOFPNN is model with higher accuracy as well as more superb predictive capability than intelligent models presented previously.

• 한국도로학회논문집
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• 제12권2호
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• pp.123-127
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• 2010

본 논문에서는 최소단면 보수가 완료된 아스팔트 콘크리트 포장의 평탄성 평가를 위하여 경량 프로파일러를 이용하여 측정하였으며 평탄성 분석을 실시하였다. 측정 프로파일러의 정확도를 검토하기 위하여 2회 측정한 프로파일을 이용하여 반복성(repeatability) 검증을 수행하였다. Cross-Corelation 함수를 이용하여 측정치간의 일치를 검증하였다. 최소단면 보수가 이루어진 아스팔트 콘크리트 포장 부분과 기존 포장의 평탄성을 국제평탄성지수와 PrI 지수를 비교 분석하였으며, 최소단면 보수가 이루어진 차선의 평탄성이 대체적으로 좋지 않았다. 향후 최소단면 보수 지역의 평탄성 평가에 대한 기초자료로 사용할 수 있다고 판단된다.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권8호
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• pp.551-560
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• 2004

In this paper, we propose a new architecture of Self-Organizing Fuzzy Polynomial Neural Networks (SOFPNN) that is based on a genetically optimized multilayer perceptron with fuzzy polynomial neurons (FPNs) and discuss its comprehensive design methodology involving mechanisms of genetic optimization, especially genetic algorithms (GAs). The proposed SOFPNN gives rise to a structurally optimized structure and comes with a substantial level of flexibility in comparison to the one we encounter in conventional SOFPNNs. The design procedure applied in the construction of each layer of a SOFPNN deals with its structural optimization involving the selection of preferred nodes (or FPNs) with specific local characteristics (such as the number of input variables, the order of the polynomial of the consequent part of fuzzy rules, and a collection of the specific subset of input variables) and addresses specific aspects of parametric optimization. Through the consecutive process of such structural and parametric optimization, an optimized and flexible fuzzy neural network is generated in a dynamic fashion. To evaluate the performance of the genetically optimized SOFPNN, the model is experimented with using two time series data(gas furnace and chaotic time series), A comparative analysis reveals that the proposed SOFPNN exhibits higher accuracy and superb predictive capability in comparison to some previous models available in the literatures.

• 제어로봇시스템학회논문지
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• 제11권2호
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• pp.127-136
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• 2005

In this paper, a new architecture and comprehensive design methodology of genetically optimized Rule-based Fuzzy Polynomial Neural Networks(gRFPNN) are introduced and a series of numeric experiments are carried out. The architecture of the resulting gRFPNN results from asynergistic usage of the hybrid system generated by combining rule-based Fuzzy Neural Networks(FNN) with polynomial neural networks (PNN). FNN contributes to the formation of the premise part of the overall rule-based structure of the gRFPNN. The consequence part of the gRFPNN is designed using PNNs. At the premise part of the gRFPNN, FNN exploits fuzzy set based approach designed by using space partitioning in terms of individual variables and comes in two fuzzy inference forms: simplified and linear. As the consequence part of the gRFPNN, the development of the genetically optimized PNN dwells on two general optimization mechanism: the structural optimization is realized via GAs whereas in case of the parametric optimization we proceed with a standard least square method-based learning. To evaluate the performance of the gRFPNN, the models are experimented with the use of several representative numerical examples. A comparative analysis shows that the proposed gRFPNN are models with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• 대한토목학회논문집
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• 제33권5호
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• pp.1935-1946
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• 2013

본 연구에서는 변단면 단일 현장타설말뚝의 거동 특성을 평가하고자 현장재하시험 사례를 분석하였으며, 또한 3차원 유한요소해석을 이용하여 말뚝 내부에서 발생하는 응력을 통해 심도별 휨응력을 산정하였다. 분석 결과, 단일 현장타설말뚝의 변단면 부근에서 휨응력이 집중되어 재료파괴가 발생하기 가장 쉬운 것을 알 수 있었다. 이를 토대로, 단일 현장타설말뚝의 기둥-말뚝 직경비와 수평 균열하중비 관계를 통해 최적의 기둥-말뚝 직경비를 제안하였다. 연구 결과, 최적의 기둥-말뚝 직경비는 기둥-말뚝 직경비와 수평 균열하중비 관계 곡선의 변곡점 부근에서 산정되었으며, 단일 현장타설말뚝 설계에 최적 변단면 특성을 고려한다면 개선된 설계가 이루어질 수 있을 것으로 판단되었다.

• Journal of Microbiology and Biotechnology
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• 제17권1호
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• pp.89-95
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• 2007

Improvements in the dissolution of proteins in two-dimensional gel electrophoresis have greatly advanced the ability to analyze the proteomes of microorganisms under a wide variety of physiological conditions. This study examined the effect of various combinations of chaotropic agents, a reducing agent, and a detergent on the dissolution of the Streptomyces peucetius cytosolic proteins. The use of urea alone in a rehydration buffer as a chaotropic agent gave the proteome a higher solubility than any of the urea and thiourea combinations, and produced the highest resolution and clearest background in two-dimensional gel electrophoresis. Two % CHAPS, as a detergent in a rehydration buffer, improved the protein solubility. After examining the effect of several concentrations of reducing agent, 50 mM DTT in a rehydration buffer was found to be an optimal condition for the proteome analysis of Streptomyces. Using this optimized buffer condition, more than 2,000 distinct and differentially expressed soluble proteins could be resolved using two-dimensional gel electrophoresis with a pI ranging from 4-7. Under this optimized condition, 15 novel small proteins with low-level expression, which could not be analyzed under the non-optimized conditions, were identified. Overall, the optimized condition helped produce a better reference gel for Streptomyces peucetius.

• 환경생물
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• 제22권2호
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• pp.329-335
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• 2004

To develop a biomarker for the monitoring of the contamination of estrogenic endocrine disrupters in the aquatic environment, reverse transcription -polymerase chain reaction (RT-PCR) analysis of vitellogenin (Vg) mRNA expression was optimized in Bombina orientalis, a Korean red bellied toad species. Based on partial cDNA sequences of both Vg and beta actin genes of B. orientalis, specific primers for RT-PCR of Vg and beta actin mRNAs were developed. Semiquantitative RT-PCR of the Vg mRNA in liver was optimized using a beta actin mRNA as an internal control in both sexes. In female RT-PCR using $1\;\mu{g}$ of the liver cDNA resulted in a linear increment in the PCR product of Vg from 18 to 34 cycles of amplification. In male, on the contrary, the RT- PCR product was first detected at 30 cycles of amplification and a linear increment was observed from 30 to 40 cycles of amplification, suggesting that male B. orientalis expresses minute amount of Vg mRNA which is a $2^{-12}$ equivalent of female. In conclusion, the optimized protocol for semiquantitative RT-PCR analysis of Vg mRNA level in B. orientalis male liver will be useful for the environmental monitoring the xenoestrogen contamination in the freshwater environment in Korea.