• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.7
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• pp.1038-1046
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• 2004

In order to acquire high-speed and high-precision performances in servomechanisms, an integrated design method have been proposed. Based on strict mathematical modeling and analysis of system performance according to design and operating parameters, a nonlinear constrained optimization problem including the relevant subsystem parameters of the servomechanism is formulated. Optimum design results of mechanical and electrical parameters are obtained according to the design parameters specified by designers through the integrated design processes. Motors are optimally selected from the servo motor database. Both the geometric errors referring to Abbe offset and the contour errors are minimized while required constraints such as stability conditions and saturated conditions are satisfied. This design methodology both offers the improved possibility to evaluate and optimize the dynamic motion performance of the servomechanism and improves the quality of the design process to achieve the required performance for high-speed/precision servomechanisms.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.3
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• pp.273-283
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• 2000

In this paper we suggest an optimal design method of Fuzzy-Neural Networks(FNN) model for complex and nonlinear systems. The FNNs use the simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. And we use a HCM(Hard C-Means) Clustering Algorithm to find initial parameters of the membership function. The parameters such as parameters of membership functions learning rates and momentum weighted value is proposed to achieve a sound balance between approximation and generalization abilities of the model. According to selection and adjustment of a weighting factor of an aggregate objective function which depends on the number of data and a certain degree of nonlinearity (distribution of I/O data we show that it is available and effective to design and optimal FNN model structure with a mutual balance and dependency between approximation and generalization abilities. This methodology sheds light on the role and impact of different parameters of the model on its performance (especially the mapping and predicting capabilities of the rule based computing). To evaluate the performance of the proposed model we use the time series data for gas furnace the data of sewage treatment process and traffic route choice process.

• Journal of the Earthquake Engineering Society of Korea
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• v.21 no.6
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• pp.303-310
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• 2017

The coupled shear wall system with coupling beams is an efficient structural system for high-rise buildings because it can provide excellent ductility and energy dissipation to the buildings. The objective of this study is to simulate the hysteretic behavior of diagonally reinforced concrete coupling beams including pinching and cyclic deteriorations in strength and stiffness using a numerical model. For this purpose, coupling beams are modeled with an elastic beam element and plastic spring element placed at the beam ends. Parameters for the analytical model was calibrated based on the test results of 6 specimens for diagonally reinforced concrete coupling beams. The analytical model with calibrated model parameters is verified by comparing the hysteretic curves obtained from analysis and experimental tests.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.8
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• pp.1353-1362
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• 2003

This paper considers a simultaneous optimization problem of structure and control systems. The problem is generally formulated as a non-convex optimization problem for the design parameters of mechanical structure and controller. Therefore, it is not easy to obtain the global solutions for practical problems. In this paper, we parameterize all design parameters of the mechanical structure such that the parameters work in the control system as decentralized static output feedback gains. Using this parameterization, we have formulated a simultaneous optimization problem in which the design specification is defined by the Η$_2$and Η$\_$$\infty$/ norms of the closed loop transfer function. So as to lead to a convex problem we approximate the nonlinear terms of design parameters to the linear terms. Then, we propose a convex optimization method that is based on linear matrix inequality (LMI). Using this method, we can surely obtain suboptimal solution for the design specification. A numerical example is given to illustrate the effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.292-292
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• 2000

Since high-power CO$_2$ Laser can be make a high densed energy to Local processing area, manufacturing processes using the laser can be processed for very Localized areas at a very fast rate with minimal or no distortion. Accordingly, the laser has been widely used in the fields of thermal manufacturing processes such as welding, fusion cutting, grooving, and heat treatment of metals. In particular, interest in the laser heat treatment process has grown tremendously in the past few years. In this process, maintaining the uniform hardening depth is important problem to obtain good quality products and to reduce heat induced distortion and residual stress. For achieving this objective, we introduced a new design technique of a fuzzy logic controller that greatly simplified the design procedure by defining several simplified design parameters. In the design procedure, the major design parameters of the controller are characterized by identifying several common aspects. From a series of simulation results, we found that the proposed design technique can be effectively used to design of a fuzzy logic controller for the LASER surface hardening process.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.5
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• pp.1990-1995
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• 2012

This paper presents design methodology to determine the design parameters that affect the manufacture of aluminum forging piston using the FE simulation and the Taguchi method. Maximum forging load is used as the objective function, and preform, material temperature and draft angle are selected as the design parameters. Their combinations are implemented by orthogonal array, and forging load is evaluated through the simulation. From the analytic results of design parameters to minimize the load using signal to noise ratio, their optimal combinations are proposed. The proposed design methodology will be able to help in selecting proper preform among preforms and to be used in determining the optimal combination of the parameters in metal forming process.

• Earthquakes and Structures
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• v.7 no.5
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• pp.817-842
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• 2014

ASCE/SEI 41-13 provides modeling parameters and numerical acceptance criteria for various types of members that are useful for evaluating the seismic performance of reinforced concrete (RC) building structures. To accurately evaluate the global performance of a coupled wall system, it is crucial to first properly define the component behaviors (i.e., force-displacement relationships of shear walls and coupling beams). However, only a few studies have investigated on the modeling of RC coupling beams subjected to earthquake loading to date. The main objective of this study is to assess the reliability of ASCE 41-13 modeling parameters specified for RC coupling beams with various design details, based on a database compiling almost all coupling beam tests available worldwide. Several recently developed coupling beam models are also reviewed. Finally, a rational method is proposed for determining the chord yield rotation of RC coupling beams.

• Journal of Korean Biological Nursing Science
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• v.15 no.2
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• pp.43-53
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• 2013

Purpose: This study was intended to analyze the types and measurement parameters of non-pharmacological interventional studies for nonalcoholic fatty liver disease (NAFLD). Methods: NAFLD related literatures were systematically reviewed. The existing literatures were searched electronically using the data base of PubMed, a Medline data base of the National Library of Medicine with the key words of nonalcoholic fatty liver disease, NAFLD, nonalcoholic steatohepatitis, and NASH. The criteria for inclusion in this review were 1) non-pharmacological intervention, 2) human, 3) English. Finally, 20 articles were included in the review. Results: The major findings of this study were as follows: 1) the types of non-pharmacological intervention were exercise (35%), caloric restriction (30%), and lifestyle modification with combination both of exercise and caloric restriction (35%), 2) Almost all studies adopted various measurement parameters derived from pathophysiological mechanism-based biomarkers such as anthropometric indices, biochemical parameters, body fat mass, and liver biopsy results. Conclusion: Non-pharmacological interventions have been reported to be effective to improve NAFLD status, and many objective biomarkers confirmed supported these findings. Therefore, the development of nursing interventions for NAFLD subjects is needed and the consideration of using mechanism-based biomarkers is suggested to verify nursing outcomes objectively.

• Advances in materials Research
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• v.5 no.2
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• pp.67-80
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• 2016

The objective of the present work is to optimize process parameters namely, cutting speed, feed rate, and depth of cut in milling of AISI 304 stainless steel. In this work, experiments were carried out as per the Taguchi experimental design and an $L_{27}$ orthogonal array was used to study the influence of various combinations of process parameters on surface roughness (Ra) and material removal rate (MRR). As a dynamic approach, the multiple response optimization was carried out using grey relational analysis (GRA) and desirability function analysis (DFA) for simultaneous evaluation. These two methods are considered in optimization, as both are multiple criteria evaluation and not much complicated. The optimum process parameters found to be cutting speed at 63 m/min, feed rate at 600 mm/min, and depth of cut at 0.8 mm. Analysis of variance (ANOVA) was employed to classify the significant parameters affecting the responses. The results indicate that depth of cut is the most significant parameter affecting multiple response characteristics of GFRP composites followed by feed rate and cutting speed. The experimental results for the optimal setting show that there is considerable improvement in the process.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1248-1250
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• 1996

The objective of camera calibration is to obtain the correlation between camera image coordinate and 3-D real world coordinate. Most calibration methods are based on the camera model which consists of physical parameters of the camera like position, orientation, focal length, etc and in this case camera calibration means the process of computing those parameters. In this research, we suggest a new approach which must be very efficient because the artificial neural network(ANN) model implicitly contains all the physical parameters, some of which are very difficult to be estimated by the existing calibration methods. Implicit camera calibration which means the process of calibrating a camera without explicitly computing its physical parameters can be used for both 3-D measurement and generation of image coordinates. As training each calibration points having different height, we can find the perspective projection point. The point can be used for reconstruction 3-D real world coordinate having arbitrary height and image coordinate of arbitrary 3-D real world coordinate. Experimental comparison of our method with well-known Tsai's 2 stage method is made to verify the effectiveness of the proposed method.