• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1995년도 추계학술대회
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• pp.247-249
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• 1995

A new localized imaging technique of reduced imaging time using a locally-linear gradient is proposed. Since most fast MR imaging methods need the whole k-space data corresponding to the whole imaging area, there are limitations in reducing the minimum imaging time. The imaging method proposed in this paper uses a specially-made gradient coil generating a local ramp-shape field and uniform field outside of the imaging area. Conventional imaging sequences can be used without any RF/gradient pulse sequence modifications. The proposed localized imaging technique has been implemented on a 2.0 Tesla whole-body system at KAIST and the imaging results show the utility of the proposed technique.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 추계학술대회 논문집
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• pp.612-615
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• 2002

The objective of this study is to develop an integrated process planning system which can flexibly cope with the status changes in a shop floor by utilizing the concept of Non-Linear and Closed-Loop Process Planning(NCPP). In this paper, Genetic Algorithm(GA) is employed in order to quickly generate feasible setup sequences for minimizing the makespan and tardiness under an NCPP. The genetic algorithm developed in this study for getting the machine load utilizes differentiated mutation rate and method in order to increase the chance to avoid a local optimum and to reach a global optimum. Also, it adopts a double gene structure for the sake of convenient modeling of the shop floor. The last step in this system is a simulation process which selects a proper process plan among alternative process plans.

• Structural Engineering and Mechanics
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• 제43권2호
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• pp.163-177
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• 2012

This paper presents a LMI(linear matrix inequality)-based fuzzy approach of modeling and active vibration control of geometrically nonlinear flexible plates with piezoelectric materials as actuators and sensors. The large-amplitude vibration characteristics and dynamic partial differential equation of a piezoelectric flexible rectangular thin plate structure are obtained by using generalized Fourier series and numerical integral. Takagi-Sugeno (T-S) fuzzy model is employed to approximate the nonlinear structural system, which combines the fuzzy inference rule with the local linear state space model. A robust fuzzy dynamic output feedback control law based on the T-S fuzzy model is designed by the parallel distributed compensation (PDC) technique, and stability analysis and disturbance rejection problems are guaranteed by LMI method. The simulation result shows that the fuzzy dynamic output feedback controller based on a two-rule T-S fuzzy model performs well, and the vibration of plate structure with geometrical nonlinearity is suppressed, which is less complex in computation and can be practically implemented.

• 한국자동차공학회논문집
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• 제1권1호
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• pp.131-139
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• 1993

Low cycle fatigue characteristics of cast aluminum alloy A356 with a yield strength and ultimate strength of 229 and 283 MPa respectively was evaluated using smooth axial specimen under strain controlled condition. Reversals to failure ranged from 16 to 107. The cast aluminum alloy exhibited cyclically strain-gardening behavior. The results of low cycle fatigue tests indicated that the conventional low cycle fatigue tests indicated that the conventional low cycle fatigue life model was not a satisfactory representation of the data. This occurred because the elastic strain-life curve was not-log-log linear and this phenomena caused a nonconservative and unsafe fatigue life prediction at both extremes of long and short lives. A linear log-log total strain-life model and a bilinear log-log elastic strain-life model were proposed in order to improve the representation of data compared to the conventional low cycle fatigue life model. Both proposed fatigue life models were statistically analyzed using F tests and successfully satisfied. However, the low cycle fatigue life model generated by the bilinear log-log elastic strain-life equation yielded a discontinuous curve with nonconservatism in the region of discontinuity. Among the models examined, the linear log-log total strain-life model provided the best representation of the low cycle fatigue data. Low cycle fatigue life prediction method based on the local strain approach could conveniently incorporated both proposed fatigue life models.

• Journal of Advanced Marine Engineering and Technology
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• 제32권8호
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• pp.1215-1220
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• 2008

To obtain the shape of the free surface more accurately, computations are carried out by a finite volume method using unstructured meshes and an interface capturing method. Free-surface flow, which is very important in the fields of ship and marine engineering, is numerically simulated for flows of both water and air. Control volumes are used with an arbitrary number of faces and allows a local mesh refinement. The integration is of second order, with a midpoint rule integration and linear interpolation. The method is fully implicit and uses quadratic interpolation. The solution method of pressure-correction type solves sequentially equations of momentum, continuity, conservation, and two-equations turbulence model. Comparison are quantitatively made between the computation and experiment in order to confirm the solution method.

• 한국해양공학회지
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• 제9권1호
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• pp.22-35
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• 1995

A simplified numerical procedure have proposed to trace the dynamic behaviour of offshore tubulars subjected to lateral collision impacts. The local denting and overall bending deformation of the struck tubular are represented by a non-linear spring and an elastic visco-plastic beam respectively. In this method a temporal finite difference method and a spacial finite element method are employed. Using this method various boundary conditions are able to considered and their effects on the extent of damage can be quantified. The extent of damage due to collision can be obtained as results of the dynamic analysis. The predictions using the proposed method have been correlated with existing test results and then the reliability of the procedure has been substantiated. The characteristics of the dynamic response of tubulars under lateral impacts are compared for simply supported roller and fixed end conditions and their effects on the extent of damage are specfied.

• 한국정밀공학회지
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• 제12권2호
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• pp.69-78
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• 1995

Nonlinear analysis methods are developed which will enable the reliable prediction of the dynamic behavior of the space shuttle main engine(SSME) turbopumps in the presence of bearing clearances and other local nonlinearities. A computationally efficient convolution method, based on discretized Duhamel and transition matrix integral formulations, is developed for the transient analysis. In the formulation, the coupling forces due to the onlinearities are treated as external forces acting on the coupled subsystems. Iteration is utilized to determine their magnitudes at each time increament. The method is applied to a nonlinear generic model of the high pressure oxygen turthods, the convolution approach proved to be more accurate and highly more efficient. For determining the nonlinear, steady-state periodic responses, an incremental harmonic balance(IHB) method was also developed. The method was successfully used to determine dominantly harmonic and subharmonic(subsynchronous) responses of the HPOTP generic model with bearing clearances. A reduction method similar to the impedance formulation utilized with linear systems is used to reduce the housing-totor models to their coordinates at the bearing clearances.

• 한국지능시스템학회논문지
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• 제16권5호
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• pp.608-615
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• 2006

본 논문에서는 퍼지 클러스터 기법을 이용하여 구간 분할된 퍼지 모델트리의 제안과 이를 이용한 데이터 모델링 기법을 다룬다. 제안된 방법은 먼저 입력과 출력변수의 속성을 고려한 퍼지 클러스터링에 의해 중심벡터를 계산한 후, 중심벡터들과 입력속성간의 소속도를 이용하여 구간 분할된 영역별로 각각의 선형모델을 구축한다. 노드의 확장은 부모노드(parent node)에서 만들어진 모델에서 계산된 오차값과 자식노드(child node)에서 계산된 오차값을 비교하여 이루어진다. 출력값 예측 단계에서는 입력된 데이터와 잎노드에서 계산된 클러스터 중심값과 비교하여 소속도가 높은 선형모델을 선택하여 데이터에 대한 출력값을 예측하게 된다. 제안된 방법의 우수성을 보이기 위해 다양한 데이터를 대상으로 실험한 결과, 기존의 모델트리방식 및 뉴럴 네트워크 기반의 신경회로망 보다 향상된 성능을 보임을 알 수 있었다.

• 농업과학연구
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• 제41권3호
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• pp.169-175
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• 2014

Objective of this study was to investigate effects of pre-processing method and number of sampling leaves on stability of the reflectance measurement for Chinese cabbage and kale leaves. Chinese cabbage and kale were transplanted and cultivated in a plant factory. Leaf samples of the kale and cabbage were collected at 4 weeks after transplanting of the seedlings. Spectra data were collected with an UV/VIS/NIR spectrometer in the wavelength region from 190 to 1130 nm. All leaves (mature and young leaves) were measured on 9 and 12 points in the blade part in the upper area for kale and cabbage leaves, respectively. To reduce the spectral noise, the raw spectral data were preprocessed by different methods: i) moving average, ii) Savitzky-Golay filter, iii) local regression using weighted linear least squares and a $1^{st}$ degree polynomial model (lowess), iv) local regression using weighted linear least squares and a $2^{nd}$ degree polynomial model (loess), v) a robust version of 'lowess', vi) a robust version of 'loess', with 7, 11, 15 smoothing points. Effects of number of sampling leaves were investigated by reflectance difference (RD) and cross-correlation (CC) methods. Results indicated that the contribution of the spectral data collected at 4 sampling leaves were good for both of the crops for reflectance measurement that does not change stability of measurement much. Furthermore, moving average method with 11 smoothing points was believed to provide reliable pre-processed data for further analysis.

• International Journal of Control, Automation, and Systems
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• 제1권3호
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• pp.289-300
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• 2003

In this paper, we introduce an identification method in Fuzzy Relation-based Fuzzy Neural Networks (FRFNN) through a hybrid identification algorithm. The proposed FRFNN modeling implement system structure and parameter identification in the efficient form of "If...., then... " statements, and exploit the theory of system optimization and fuzzy rules. The FRFNN modeling and identification environment realizes parameter identification through a synergistic usage of genetic optimization and complex search method. The hybrid identification algorithm is carried out by combining both genetic optimization and the improved complex method in order to guarantee both global optimization and local convergence. An aggregate objective function with a weighting factor is introduced to achieve a sound balance between approximation and generalization of the model. The proposed model is experimented with using two nonlinear data. The obtained experimental results reveal that the proposed networks exhibit high accuracy and generalization capabilities in comparison to other models.er models.