• The Korean Journal of Applied Statistics
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• v.9 no.1
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• pp.139-152
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• 1996

In this paper we propose nonparametric tests using optimal weights for umbrella alternatives in a randomized block design. We obtain the optimal weights by maximizing the asymptotic relative efficiency of the proposed test statistics with respect to Mack and Wolf(1981) type test statistic, and investigate asymptotic relative efficiencies of the proposed test statistics using these optimal weights relative to Mack and Wolfe type statistics and linear rank statistic. Throughout simulations for small samples, the proposed test statistic has good powers rather than the other two tests when the block sizes are different.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.575-591
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• 2006

In a previous research, we presented the Grid Method and confirmed it as a systematic and efficient problem formulation method for the task-oriented design of robot kinematics. However, our previous research was limited in two ways. First, it gave only a local optimum due to its use of a local optimization technique. Second, it used constant weights for a cost function chosen by the manual weights tuning algorithm, thereby showing low efficiency in finding an optimal solution. To overcome these two limitations, therefore, this paper presents a global optimization technique and an adaptive weights tuning algorithm to solve a formulated problem using the Grid Method. The efficiencies of the proposed algorithms have been confirmed through the kinematic design examples of various robot manipulators.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.36
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• pp.1-11
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• 1995

Manual lifting, as a part of manual materials handling activities, is recognized by authorities in the fields of occupational health and safety as a major hazards to industrial workers. In order to minimize the injuries caused by manual material handling activities as well as maximize job productivity, it is important to determine the maximum weights. This paper presents the optimal combination of membership functions according to the high lifting frequency and determines the safe maximum acceptable weights in manual lifting activities through the actual experiment.

• Journal of the East Asian Society of Dietary Life
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• v.11 no.3
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• pp.219-224
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• 2001

This study was conducted to investigate the optimal conditions for the growth of soybean sprouts by ozone water watering. Optimal conditions for ozone water watering of soybean sprouts during cultivation at 2$0^{\circ}C$ were evaluated with ozone concentration(0.1~O.5 ppm) and watering frequency(1~9 times) by response surface methodology. The optimal conditions for growth of soybean sprouts were ozone concentrations of 0.20~0.32 ppm, ozone treatment frequency of 3.0~4.4 times. Germination rates, hypocotyl weights and hypocotyl lengths in the soybean sprouts cultivated under the optimal conditions increased by 13.3, 10.1 and 11.9%, respectively, whereas root weights decreased by 89.0%.

• The Mathematical Education
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• v.55 no.2
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• pp.147-169
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• 2016

This study analyzes the mathematical creativity test as an illustrative example with scoring domains of fluency, flexibility and originality in order to make suggestions for obtaining maximum reliability based on a composite score depending on combinations of each scoring domain weights. This is done by performing a multivariate generalizability analysis on the test scores, which were allowed to access publicly, of 30 mathematically gifted elementary school students, and therefore error variances, generalizability coefficients, and effective weights have been calculated. The main results were as follows. First, the optimal weights should adjust to .5, .4, and .1 based on the maximum generalizability coefficient even though the original weights in the mathematical creativity test were equal for each scoring domain with fluency, flexibility and originality. Second, the mathematical creativity test using the three scoring domains of fluency, flexibility, and originality showed higher reliability than using one scoring domain such as fluency. These results are limited to the mathematical creativity test used in this study. However, the methodology applied in this study can help determine the optimal weights depending on each scoring domain when the tests constructed in various researchers or educational fields are composed of multiple scoring domains.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1406-1420
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• 2017

Artificial neural networks (ANNs) play an important role in the fields of function approximation, prediction, and classification. ANN performance is critically dependent on the input parameters, including the number of neurons in each layer, and the optimal values of weights and biases assigned to each neuron. In this study, we apply the particle swarm optimization method, a popular optimization algorithm for determining the optimal values of weights and biases for every neuron in different layers of the ANN. Several regression models, including general linear regression, Fourier regression, smoothing spline, and polynomial regression, are conducted to evaluate the proposed method's prediction power compared to multiple linear regression (MLR) methods. In addition, residual analysis is conducted to evaluate the optimized ANN accuracy for both training and test datasets. The experimental results demonstrate that the proposed method can effectively determine optimal values for neuron weights and biases, and high accuracy results are obtained for prediction applications. Evaluations of the proposed method reveal that it can be used for prediction and estimation purposes, with a high accuracy ratio, and the designed model provides a reliable technique for optimization. The simulation results show that the optimized ANN exhibits superior performance to MLR for prediction purposes.

• IE interfaces
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• v.22 no.3
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• pp.223-233
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• 2009

In this paper we developed a method for an optimal planning to reorganize Dong offices to enhance the administrative efficiency. First we defined a mathematical model for the optimal planning problem of reorganizing Dong office and developed a genetic algorithm to solve the problem. For the purpose of minimizing standard deviation of population, area and distance among reorganized offices, the constraints such as allocation, distance, area, population, etc. are considered and weights are applied to Dong offices in the downtown and shopping area. The developed algorithm was applied for reorganizing Dong offices in Jongro Gu, Seoul. The results showed that the developed algorithm could be applied for the real world problem. This study may be applied to the optimal decision of reorganization of offices in the similar reorganization or company M&A situations by changing constraints and weights.

• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.1
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• pp.25-36
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• 2003

Unlike the mean-variance approach, the stochastic dominance approach Is to form a portfolio that first-degree stochastically dominates a predetermined benchmark portfolio, e.g. KOSPI. Analytically defining the first derivative of the objective function, an optimal algorithm of nonlinear programming was developed to search a set of optimal weights systematically and tested with promising results against veal data sets from Korean stock market.

• Communications for Statistical Applications and Methods
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• v.9 no.3
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• pp.765-774
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• 2002

Suppose one is given a vector X of a finite set of quantities $X_i$ which are independent Poisson random variables. A null hypothesis $H_0$ about E(X) is to be tested against an alternative hypothesis $H_1$. A quantity $\sum\limits_{i}w_ix_i$ is to be computed and used for the test. The optimal values of $W_i$ are calculated for three cases: (1) signal to noise ratio is used in the test, (2) normal approximations with unequal variances to the Poisson distributions are used in the test, and (3) the Poisson distribution itself is used. The above three cases are considered to the situations that are without background noise and with background noise. A comparison is made of the optimal values of $W_i$ in the three cases for both situations.

• Journal of the Korean Data and Information Science Society
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• v.13 no.2
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• pp.307-315
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• 2002

Suppose one is given a vector X of a finite set of quantities $X_i$ which are independent Poisson signals. A null hypothesis $H_0$ about E(X) is to be tested against an alternative hypothesis $H_1$. A quantity $$\sum\limits_{i}\omega_ix_i$$ is to be computed and used for the test. The optimal values of $\omega_i$ are calculated for three cases : (1) signal to noise ratio is used in the test, (2) normal approximations with unequal variances to the Poisson distributions are used in the test, and (3) the Poisson distribution it self is used. A comparison is made of the optimal values of $\omega_i$ in the three cases as parameter goes to infinity.