• Journal of Mechanical Science and Technology
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• 제17권12호
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• pp.1855-1866
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• 2003

This paper discusses an entire procedure for a robust controller design and its implementation of an AMB (active magnetic bearing) spindle, which is part II of the papers presenting details of system modeling and robust control of an AMB spindle. Since there are various uncertainties in an AMB system and reliability is the most important factor for applications, robust control naturally gains attentions in this field. However, tight evaluations of various uncertainties based on experimental data and appropriate performance weightings for an AMB spindle are still ongoing research topics. In addition, there are few publications on experimental justification of a designed robust controller. In this paper, uncertainties for the AMB spindle are classified and described based on the measurement and identification results of part I, and an appropriate performance weighting scheme for the AMB spindle is developed. Then, a robust control is designed through the mixed ${\mu}$ synthesis based on the validated accurate nominal model of part I, and the robust controller is reduced considering its closed loop performance. The reduced robust controller is implemented and confirmed with measurements of closed-loop responses. The AMB spindle is operated up to 57,600 rpm and performance of the designed controller is compared with a benchmark PID controller through experiments. Experiments show that the robust controller offers higher stiffness and more efficient control of rigid modes than the benchmark PID controller.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 D
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• pp.2821-2823
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• 2002

In this paper we propose the Multi-FNN (Fuzzy-Neural Networks) for optimal identification modeling of complex system. The proposed Multi-FNNs is based on a concept of FNNs and exploit linear inference being treated as generic inference mechanisms. In the networks learning, backpropagation(BP) algorithm of neural networks is used to updata the parameters of the network in order to control of nonlinear process with complexity and uncertainty of data, proposed model use a HCM(Hard C-Means)clustering algorithm which carry out the input-output dat a preprocessing function and Genetic Algorithm which carry out optimization of model The HCM clustering method is utilized to determine the structure of Multi-FNNs. The parameters of Multi-FNN model such as apexes of membership function, learning rates, and momentum coefficients are adjusted using genetic algorithms. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization abilities of the model. NOx emission process data of gas turbine power plant is simulated in order to confirm the efficiency and feasibility of the proposed approach in this paper.

• Journal of Multimedia Information System
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• 제3권4호
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• pp.119-128
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• 2016

This study aims to suggest a new algorithm for detecting two-wheelers on road that have various shapes according to the viewing angle for vision based intelligent vehicles. This article describes a new approach to two-wheelers detection algorithm riding on people based on modified Histogram of Oriented Gradients (HOG) using correlation coefficient (CC). The CC between two local area variables, in which one is the person riding a bike and other is its background, can represent correlation relation. First, we extract edge vectors using HOG which includes gradient information and differential magnitude as cell based. And then, the value, which is calculated by the CC between the area of each cell and one of two-wheelers, can be extracted as the weighting factor in process for normalizing the modified HOG cell. This paper applied the Adaboost algorithm to make a strong classification from weak classification. In this experiment, we can get the result that the detection rate of the proposed method is higher than that of the traditional method.

• 한국산학기술학회논문지
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• 제13권7호
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• pp.3224-3231
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• 2012

통합적이고 객관화된 도시압축성 평가방법에 대한 연구가 필요하다. 이를 위하여 압축도시(compact city)와 관련된 문헌 등 선행연구를 통하여 도시압축성 평가요소를 추출하였다. 이렇게 설정된 평가요소는 전문가조사를 통한 객관화 과정과 AHP계층구조모형을 통하여 평가요소별로 가중치를 결정한다. 이러한 평가분석의 틀을 토대로 우리나라 6대 광역시의 도시압축성을 평가하고 표준점수(z-score)화하여 상대적인 차이를 분석하고자 하였다. 이러한 분석결과는 압축도시에 대한 정책 결정에 필요한 기본 자료로서 구도심의 도시재생 등 압축도시계획에 활용될 수 있을 것이다.

• 대한토목학회논문집
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• 제13권4호
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• pp.131-140
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• 1993

기존의 Mualem의 Model III-1에서 공기가 공극으로 진입할 때 이에 대한 공극들의 방해효과를 설명하는 가중치(加重値) $P_a({\theta})$가 무차원 공극반경과 선형적 관계를 가진다는 가정을 바탕으로 하여 모형의 검정을 위하여 한 개의 주곡선이 필요한 새로운 모형을 개발하였다. 개발된 모형은 모형의 검정을 위하여 기존에 제시된 바 있는 한 개의 주곡선이 필요한 모형들보다 실측치를 잘 모의하며, 한쌍의 주곡선이 필요한 영역모형중에서 이력현상을 모형화하는 목적에 가장 부합한 Model III-1과의 비교에서 개발된 모형은 거의 같은 정확성을 가지면서 실측자료를 재현하고 있음을 알 수 있었다. 또한 개발된 모형은 비포화 흐름을 해석할 때 효율적으로 적용될 수 있음을 알 수 있었다.

• 대한설비공학회:학술대회논문집
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• 대한설비공학회 2009년도 하계학술발표대회 논문집
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• pp.148-153
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• 2009

This paper considers the age of air in a ventilated space with multiple supply inlets. The local mean age of air at a point from one supply inlet is different from those from the other supply inlets. It is the purpose of the present paper to investigate theoretically the relations between the LMA's from each supply and overall combined LMA whether or not to trace the origins of supply air. Transient concentration distributions are calculated with a step-up injection of tracer gas at each supply inlet, and at both inlets simultaneously. The steady state concentration with a continuous tracer injection at a supply inlet works as a weighting factor for the corresponding LMA in calculating the average overall LMA from multiple inlets.

• KIEAE Journal
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• 제16권5호
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• pp.13-20
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• 2016

Purpose: The purpose of this study is to provide information on building's energy consumption and efficiency for general building users through a mobile application. Method: This paper presents a mobile application process and building energy assessment models for general users to understand easily. There are two assessment models, one is based on the energy consumption. The other is based on the architectural planning factors of a building. The assessment models are proposed to understand buildings' energy efficiency and to compare the energy consumption level for general users. The applicability of proposed application has been evaluated by conducting a case study. The case study is targeting university buildings. Result: Energy efficiency potentials were proposed using weighting factor which was calculated by the impact on energy consumption of a building according to parameters. The mobile application used the simple energy assessment model by energy efficiency potentials and was developed for a smartphone By using the mobile application, numerous general users of smartphones can easily and conveniently access information pertaining to buildings, energy consumption, and reductions in energy consumption. The proposed application enables user to find more energy efficient buildings by comparing energy status and energy efficiency potential by given information.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2000년도 춘계학술대회 학술발표 논문집
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• pp.47-50
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• 2000

In this paper, an optimal identification method using Multi-FNN(Fuzzy-Neural Network) is proposed for model ins of nonlinear complex system. In order to control of nonlinear process with complexity and uncertainty of data, proposed model use a HCM clustering algorithm which carry out the input-output data preprocessing function and Genetic Algorithm which carry out optimization of model. The proposed Multi-FNN is based on Yamakawa's FNN and it uses simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rules. HCM clustering method which carry out the data preprocessing function for system modeling, is utilized to determine the structure of Multi-FNN by means of the divisions of input-output space. Also, the parameters of Multi-FNN model such as apexes of membership function, learning rates and momentum coefficients are adjusted using genetic algorithms. Also, a performance index with a weighting factor is presented to achieve a sound balance between approximation and generalization abilities of the model, To evaluate the performance of the proposed model, we use the time series data for gas furnace and the numerical data of nonlinear function.

• 한국해안해양공학회지
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• 제15권2호
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• pp.108-115
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• 2003

천수방정식에 기초한 ADCIRC 유한요소모형을 이용하여 지진해일 전파를 수치모의할 때 분산효과를 고려하기 위한 두 가지 일차원 분산보정기법을 개발하였다. 첫 번째 방법은 음해법으로, 각 시간단계의 공간미분항에 부여되는 가중치를 조정함으로써 분산보정을 수행한다. 두 번째는 양해법으로, 유한요소의 크기를 조정하여 분산을 고려한다. 새로운 기법을 이용하여 계산한 수치해와 파의 분산효과를 고려한 해석해의 비교를 통해 본 연구에서 제안한 분산보정기법의 타당성을 확인하였다.

• Journal of Radiation Protection and Research
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• 제46권4호
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• pp.160-169
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• 2021

Background: Dual-energy X-ray images (DEI) can distinguish or improve materials of interest in a two-dimensional radiographic image, by combining two images obtained from separate low and high energies. The concepts of DEI performance describing the performance of double-exposure DEI systems in the Fourier domain been previously introduced, however, the performance of double-exposure DEI itself in terms of various parameters, has not been reported. Materials and Methods: To investigate the DEI performance, signal-difference-to-noise ratio, modulation transfer function, noise power spectrum, and noise equivalent quanta were used. Low- and high-energy were 60 and 130 kVp with 0.01-0.09 mGy, respectively. The energy-separation filter material and its thicknesses were tin (Sn) and 0.0-1.0 mm, respectively. Noise-reduction (NR) filtering used the Gaussian-filter NR, median-filter NR, and anti-correlated NR. Results and Discussion: DEI performance was affected by Sn-filter thickness, weighting factor, and dose allocation. All NR filtering successfully reduced noise, when compared with the dual-energy (DE) images without any NR filtering. Conclusion: The results indicated the significance of investigating, and evaluating suitable DEI performance, for DE images in chest radiography applications. Additionally, all the NR filtering methods were effective at reducing noise in the resultant DE images.