• Journal of Integrative Natural Science
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• v.11 no.3
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• pp.154-160
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• 2018

Consider the problem of estimating a $p{\times}1$ mean vector ${\theta}(p-r{\geq}3)$, r = rank(K) with a projection matrix K under the quadratic loss, based on a sample $Y_1$, $Y_2$, ${\cdots}$, $Y_n$. In this paper a James-Stein type estimator with shrinkage form is given when it's variance distribution is specified and when the norm ${\parallel}{\theta}-K{\theta}{\parallel}$ is constrain, where K is an idempotent and symmetric matrix and rank(K) = r. It is characterized a minimal complete class of James-Stein type estimators in this case. And the subclass of James-Stein type estimators that dominate the sample mean is derived.

• Analytical Science and Technology
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• v.15 no.2
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• pp.108-114
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• 2002

The new system using a glow discharge atomic emission spectrometer for the direct analysis of solid samples has been developed and characterized. The system was consisted of new glow discharge cell improved previous gas-jet boosted nozzle and radio-frequency power supply. In the case of previous type glow discharge chamber, it had been fitted trace analysis of low alloy steel with low discharge power, because it was to decrease redeposition and increase sample weight loss. But it had a problem that plasma becomes unstale due to increased sample weight loss and redeposition resulting from the high discharge power. Because of being problem of previous glow discharge, it is impossible to analyze using high power. The modified gas-jet boosted glow discharge to solve this problem would improve to be less sample loss rate of modified nozzle than sample loss rate of previous nozzle on the equal discharge condition, and improve to increase stability of plasma. The effect of discharge parameters such as discharge pressure, gas flow rate and power on the sample loss rate, emission intensity has been studied to find optimum discharge conditions. The calibration curves of Fe were obtained with 3 low-alloy samples.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1117-1119
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• 1999

This paper presents a new approach for the optimal routing problem of distribution system planning using the well known Hopfield Neural Network(HNN) method. The optimal routing problem(ORP) in distribution system planning(DSP) is generally formulated as combinational mixed integer problem with various equality and inequality constraints. For the exceeding nonlinear characteristics of the ORP most of the conventional mathematical methods often lead to a local minimum. In this paper, a new approach was made using the HNN method for the ORP to overcome those disadvantages. And for this approach, a appropriately designed energy function suited for the ORP was proposed. The proposed algorithm has been evaluated through the sample distribution planning problem and the simulation results are presented.

• Journal of Families and Better Life
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• v.29 no.4
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• pp.161-174
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• 2011

The purpose of this study was to investigate the structural relationships among different variables related to school adjustment. 601 elementary school students residing in Pohang-City in Korea completed questionnaires about school adjustment, internal problem behavior, external problem behavior, family adaptability and family cohesion. A variance-covariance matrix of this sample was analyzed using AMOS 19.0, and the maximum likelihood minimization function. The goodness of fit was evaluated via SRMR, RMSEA with a 90% confidence interval, CFI, and TLI. The results were as follows: First, family adaptability, family cohesion, internal problem behavior and external problem behavior were all found to have a significant direct effect how the children adjusted to their school. Second, family adaptability, and family cohesion had a direct effect on internal problem behavior. Third, family cohesion had a direct effect on external problem behavior, but family adaptability had a substantial indirect effect on the children's external problem behavior that was mediated by their internal problem behavior. Fourth, internal problem behavior had a direct effect on external problem behavior.

• Journal of Korean Clinical Nursing Research
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• v.18 no.3
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• pp.402-412
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• 2012

Purpose: The purpose of this study was to explore influencing factors of dysfunctional beliefs and emotion regulation strategy for nurses' problem solving ability. Methods: This study was a cross-sectional design with a sample of 745 nurses from 1 university hospital located in Gyeonggido. The scales were Dysfunctional Beliefs Test (70 items), Emotion Regulation Strategy Questionnaire (25 items) and Social Problem Solving Inventory (52 items). The data were analyzed using SPSS 17.0 employing ANOVA, pearson correlation coefficients and multiple regression analysis. Results: The mean score for problem solving ability was 11.26 points. Influencing factors for nurses' problem solving ability were identified as 'active regulation style' in emotion regulation strategy and 'negative concept of social self' in dysfunctional beliefs. Conclusion: It is plausible to assume that dysfunctional beliefs which are vulnerability factors in cognitive variables and emotion regulation strategy affect nurses' problem solving ability.

• Journal of Magnetics
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• v.8 no.4
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• pp.160-163
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• 2003

In magnetic flux measurement, output voltage drift of electronic integrator is an essential problem. In this work, we have developed a new kind of Miller type integrator using a sample and hold amplifier. Input bias current was measured and this value was hold in the sample and hold amplifier, after that input bias current of Miller integrator was compensated automatically using the value which holds in the sample and hold amplifier. Developed flux-meter shows the drift of flux-meter are smaller than 10$^{-5}$ Wb/min in full scale of 10$^{-2}$, and we could also measure multi-channel magnetic flux simultaneously.

• Journal of the Korean Statistical Society
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• v.36 no.2
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• pp.299-320
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• 2007

We introduce a high breakdown point estimator referred to as data partitioning robust regression estimator (DPR). Since the DPR is obtained by partitioning observations into a finite number of subsets, it has no computational problem unlike the previous robust regression estimators. Empirical and extensive simulation studies show that the DPR is superior to the previous robust estimators. This is much so in large samples.

• Management Science and Financial Engineering
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• v.6 no.2
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• pp.29-45
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• 2000

We consider the design of a two-level telecommunication network having logical full-mesh/star topology, with the implementation of conduit systems taken together. The design problem is then viewed as consisting of three subproblems: locating hub facilities, placing a conduit network, and installing cables therein to configure the logical full-mesh/star network. Without partitioning into subproblems as done in the conventional approach, the whole problem is directly dealt with in a single integrated framework, inspired by some recent successes with the approach. We successfully formulate the problem as a variant of the classical multicommodity flow model for the fixed charge network design problem, aided by network augmentation, judicious commodity definition, and some flow restrictions. With our optimal model, we solve some randomly generated sample problems by using CPLEX MIP program. From the computational experiments, it seems that our model can be applied to the practical problem effectively.

• Research in Mathematical Education
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• v.17 no.3
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• pp.199-220
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• 2013

The main objective of this study is to explore the relationship between psychological factors (i.e. math anxiety, attention, attitude, Working Memory Capacity (WMC), and Field dependency) and students' mathematics problem solving based on Revised Bloom Taxonomy. A sample of 169 K11 school girls were tested on (1) The Witkin's cognitive style (Group Embedded Figure Test). (2) Digit Span Backwards Test. (3) Mathematics Anxiety Rating Scale (MARS). (4) Modified Fennema-Sherman Attitude Scales. (5) Mathematics Attention Test (MAT), and (6) Mathematics questions based on Revised Bloom Taxonomy (RBT). Results obtained indicate that the effect of these items on students mathematical problem solving is different in each cognitive process and level of knowledge dimension.

• Proceedings of the KIEE Conference
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• 1999.11b
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• pp.232-235
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• 1999

This paper presents a HNN(Hopfield Neural Network) model to solve the ORP(Optimal Routing Problem) in DSP(Distribution System Planning). This problem is generally formulated as a combinatorial optimization problem with various equality and inequality constraints. Precedent study[3] considered only fixed cert, but in this paper, we proposed the capability of optimization by fixed cost and variable cost. And suggested the corrected formulation of energy function for improving the characteristics of convergence. The proposed algorithm has been evaluated through the sample distribution planning problem and the simmulation results are presented.