• Journal of the Korean Society for Precision Engineering
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• v.15 no.1
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• pp.78-86
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• 1998

This paper presents a numerical method of the minimum-time trajectory planning for a robot manipulator amid obstacles. Each joint displacement is represented by the linear combination of the finite-term quintic B-splines which are the known functions of the path parameter. The time is represented by the linear function of the same path parameter. Since the geometric path is not fixed and the time is linear to the path parameter, the coefficients of the splines and the time-scale factor span a finite-dimensional vector space, a point in which uniquely represents the manipulator motion. The displacement, the velocity and the acceleration conditions at the starting and the goal positions are transformed into the linear equality constraints on the coefficients of the splines, which reduce the dimension of the vector space. The optimization is performed in the reduced vector space using nonlinear programming. The total moving time is the main performance index which should be minimized. The constraints on the actuator forces and that of the obstacle-avoidance, together with sufficiently large weighting coefficients, are included in the augmented performance index. In the numerical implementation, the minimum-time motion is obtained for a planar 3-1ink manipulator amid several rectangular obstacles without simplifying any dynamic or geometric models.

• Earthquakes and Structures
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• v.21 no.6
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• pp.627-639
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• 2021

Fragility curves are being more significant as a useful tool for evaluating the relationship between the earthquake intensity measure and the effects of the engineering demand parameter on the buildings. In this paper, the effect of different site conditions on the vulnerability of the structures was examined through the fragility curves taking into account different strength capacities of the precast columns. Thus, typical existing single-story precast RC industrial buildings which were built in Turkey after the year 2000 were examined. The fragility curves for the three typical existing industrial structures were derived from an analytical approach by performing non-linear dynamic analyses considering three different soil conditions. The Park and Ang damage index was used in order to determine the damage level of the members. The spectral acceleration (Sa) was used as the ground motion parameter in the fragility curves. The results indicate that the fragility curves were derived for the structures vary depending on the site conditions. The damage probability of exceedance values increased from stiff site to soft site for any Sa value. This difference increases in long period in examined buildings. In addition, earthquake demand values were calculated by considering the buildings and site conditions, and the effect of the site class on the building damage was evaluated by considering the Mean Damage Ratio parameter (MDR). Achieving fragility curves and MDR curves as a function of spectral acceleration enables a quick and practical risk assessment in existing buildings.

• Journal of Korea Multimedia Society
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• v.11 no.4
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• pp.462-470
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• 2008

This study applies fuzzy functions to improve image quality under the assumption that uncertainty of image information due to low contrast is based on vagueness and ambiguity of the brightness pixel values. To solve the problem of low contrast images whose brightness distribution is inclined, we use the k-means algorithm as a parameter of the fuzzy function, through which automatic critical points can be found to differentiate objects from background and contrast between bright and dark points can be improved. The fuzzy function is presented at the three main stages presented to improve image quality: fuzzification, contrast enhancement and defuzzification. To measure improved image quality, we present the fuzzy index and entropy index and in comparison with those of histogram equalization technique, it shows outstanding performance.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.6
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• pp.106-118
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• 1998

The study concerns a design procedure of rule-based systems. The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient from of "IF..., THEN..." statements, and exploits the theory of system optimization and fuzzy implication rules. The method for rule-based fuzzy modeling concerns the from of the conclusion part of the the rules that can be constant. Both triangular and Gaussian-like membership function are studied. The optimization hinges on an autotuning algorithm that covers as a modified constrained optimization method known as a complex method. The study introduces a weighted performance index (objective function) that helps achieve a sound balance between the quality of results produced for the training and testing set. This methodology sheds light on the role and impact of different parameters of the model on its performance. The study is illustrated with the aid of two representative numerical examples.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2911-2913
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• 1999

This paper suggest an optimal identification method to complex and nonlinear system modeling that is based on Fuzzy-Neural Network(FNN). The FNN modeling implements parameter identification using HCM algorithm and optimal identification algorithm structure combined with two types of optimization theories for nonlinear systems, we use a HCM Clustering Algorithm to find initial parameters of membership function. The parameters such as parameters of membership functions, learning rates and momentum coefficients are adjusted using optimal identification algorithm. The proposed optimal identification algorithm is carried out using both a genetic algorithm and the improved complex method. Also, an aggregate objective function(performance index) with weighted value is proposed 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, the data of sewage treatment process and traffic route choice process.

• Industrial Engineering and Management Systems
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• v.4 no.1
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• pp.68-74
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• 2005

Among many dimensional and dimensionless amplitude parameters, kurtosis (4-th normalized moment of probability density function) is generally regarded as a sensitive good parameter for machine diagnosis. However, higher order moment may be supposed to be much more sensitive. Bicoherence is an absolute deterioration factor whose range is 1 to 0. The theoretical value of n-th moment divided by n-th moment calculated by measured data would behave in the same way. We propose a simplified calculation method for an absolute index of n-th moment and name this as simplified absolute index of n-th moment. Some favorable results are obtained.

• The Korean Journal of Applied Statistics
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• v.29 no.3
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• pp.463-470
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• 2016

In analysing a time series on the frequency domain, the spectral estimator (or periodogram) is a very useful statistic to identify the periods of a time series. However, the spectral estimator is very sensitive in nature to outliers, so that the spectral estimator in terms of M-estimation has been studied by some researchers. Pak (2001) proposed an empirical method to choose a tuning parameter for the Huber's M-estimating function. In this article, we try to implement Pak's estimation proposal in the spectral estimator. We use the Korean housing price index as an example data set for comparing various M-estimating results.

• Journal of Korean Society for Quality Management
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• v.42 no.4
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• pp.747-756
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• 2014

Purpose: The purpose of this study is to apply the Bayesian estimation methodology for producing 'Korean Standard -Quality Excellence Index' model and prove the effectiveness of the new approach based on survey data by comparing the current index with the new index produced by Bayesian estimation method. Methods: The 'Korean Standard -Quality Excellence Index' was produced through the collected survey data by Bayesian estimation method and comparing the deviation with two results for confirming the effectiveness of suggested application. Results: The statistical analysis result shows that suggested estimator, that is, empirical Bayes estimator improves the effectiveness of the index with regard to reduce the error under specific loss function, which is suggested for checking the goodness of fit. Conclusion: Considering the Bayesian techniques such as empirical Bayes estimator for producing the quality excellence index reduces the error for estimating the parameter of interest and furthermore various Bayesian perspective approaches seems to be meaningful for producing the corresponding index.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.96-101
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• 2007

A new metallic sandwich panel with a quasi-Kagome truss core subjected to bending load has been analyzed. First, equations of the failure loads corresponding to the eight failure modes are presented. Then, non-dimensional forms of the equations are derived as functions of three geometric variables, one material parameter (yield strain), one load index and one weight index. Failure maps are presented for a given weight index. By using the dimensionless forms of equations as the design constraints, two kinds of optimization are performed. One is based on the weight, that is, the objective function, namely, the dimensionless load is to be maximized for a given weight. Another is based on the load, that is, the dimensionless weight is to be minimized for a given load. The results of the two optimization processes are found to agree each other. The optimized geometric variables are derived as a function of given weights or failure loads. The performance of the quasi-Kagome truss as the core of a sandwich panel is evaluated by comparison with those of honeycomb cored and octet truss cored panels

• Journal of Biosystems Engineering
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• v.36 no.5
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• pp.348-354
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• 2011

Various crop spacing methods have been implemented so far for the greenhouse and plant factory applications. However, there is no generally accepted parameter for evaluation of plant spacing efficiency in plant production system. In this study, 'Planted Area Index' (PAI) of a spacing method is defined as the ratio of the planted area in the field to required planted area using the spacing method when no transplanting operation is assumed. Three common types of spacing methods for plane placement of the plants were modeled mathematically. For calculating the planted area, an optimal growth radius function (R(t)) is needed. Function of the days after transplanting stage gives a radius of an optimal circle area for the living plants. A computer simulation was developed to calculate the PAI, based on three crop spacing methods and four optimal growth radius functions. In general, the 1-D zigzag spacing showed the best PAI. Moreover, it gives an example on how to apply the PAI for the design.