• Korean Journal of Childcare and Education
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• v.11 no.2
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• pp.201-220
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• 2015

The purpose of this study is to analyse the effects of teachers'personal background (academic, education career) and institutional characteristic factors(founded facility type, class size, and curriculum organization type) on the quality of the classroom in early childhood education and care(ECEC) fields. This study is to explore the conditions for improving the quality of ECEC, looking back on a traditional paradigm focused on teacher education and qualifications. The hierarchical regression analysis was conducted through a survey as a research method. The results indicated that the effects of institutional characteristics were more influential than teachers' education on classroom quality. Public kindergartens and child care centers were reported to have higher effects than the private ones on classroom quality. Based on these results, policy implications and future research plans were suggested in perspective of improving the publicness of ECEC services.

• Current Photovoltaic Research
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• v.2 no.1
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• pp.1-7
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• 2014

We developed a method of growing thin Si film at $600^{\circ}C$ by hot wire CVD using a very thin large-grained poly-Si seed layer for thin-film Si solar cells. The seed layer was prepared by crystallizing an amorphous Si film by vapor-induced crystallization using $AlCl_3$ vapor. The average grain size of the p-type epitaxial Si layer was about $20{\mu}m$ and crystallographic defects in the epitaxial layer were mainly low-angle grain boundaries and coincident-site lattice boundaries, which are special boundaries with less electrical activity. Moreover, with a decreasing in-situ boron doping time, the mis-orientation angle between grain boundaries and in-grain defects in epitaxial Si decreased. Due to fewer defects, the epitaxial Si film was high quality evidenced from Raman and TEM analysis. The highest mobility of $360cm^2/V{\cdot}s$ was achieved by decreasing the in-situ boron doping time. The performance of our preliminary thin-film solar cells with a single-side HIT structure and $CoSi_2$ back contact was poor. However, the result showed that the epitaxial Si film has considerable potential for improved performance with a reduced boron doping concentration.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.2
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• pp.70-77
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• 2019

Breast ultrasound readings are very important to diagnose early breast cancer. In Ultrasonic inspection, it shows a significant difference in image quality depending on the ultrasonic equipment, and there is a large difference in diagnosis depending on the experience and skill of the inspector. Therefore, objective criteria are needed for accurate diagnosis and treatment. In this study, we analyzed texture characteristics by applying GLCM (Gray Level Co-occurrence Matrix) algorithm and extracted characteristic parameters and diagnosed breast cancer using neural network classifier. Breast ultrasound images were classified into normal, benign and malignant tumors and six texture parameters were extracted. Fourteen cases of normal, malignant and benign tumor diagnosed by mammography were studied by using the extracted six parameters and learning by multi - layer perceptron neural network back propagation learning method. As a result of classification using 51 normal images, 62 benign tumor images, and 74 malignant tumor images of the learned model, the classification rate was 95.2%.

• Journal of the Korean Society for Railway
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• v.19 no.3
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• pp.314-323
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• 2016

Overhead line voltage of DC railway traction substations has rising or falling characteristics depending on the acceleration and regenerative braking of the subway train loads. The suppression of this irregular fluctuation of the line voltage gives rise to improved energy efficiency of both the railway substation and the trains. This paper presents parameter estimation schemes using the RC circuit model for an overhead line voltage at a 1500V DC electric railway traction substation. A linear artificial neural network with a back-propagation learning algorithm was trained using the measurement data for an overhead line voltage and four feeder currents. The least square estimation method was configured to implement batch processing of these measurement data. These estimation results have been presented and performance analysis has been achieved through raw data simulation.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2007.11a
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• pp.313-318
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• 2007

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. This paper proposes maximum torque control of IPMSM drive using adaptive fuzzy neural network controller and artificial neural network(ANN). This control method is applicable over the entire speed range which considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using Adaptive-FNN controller and ANN controller. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper reposes speed control of IPMSM using Adaptive-FNN and estimation of speed using ANN controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is a lied to IPMSM drive system controlled Adaptive-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper proposes the analysis results to verify the effectiveness of the Adaptive-FNN and ANN controller.

• Journal of the Korean Society of Costume
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• v.56 no.7 s.107
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• pp.33-45
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• 2006

This study was to provide the fundamental data for a scientific and rational clothing construction by investigating the length variation of the upper arm surface, using the method of surgical tape, and to understand the expansion and contraction of parts of body for the making of clothing adaptable to movement. The subjects were li early elementary schoolgirls in Busan area classified with three somatotypes, and arm-movements consisted of 6 types. The statistical analyses used in this study were mean, standard deviation and the ANOVA and LSD procedure. The results of the analysis of the length of the upper arm surface are as follows: By arm-movements, in the items of horizontal, upper arm length changed more in the front than in the back, and in the items of vertical, represented the opposite of horizontal items. In the items of upper arm, the anterior-posterior axilla length and under arm length were influenced by arm-movements, and the under length of the upper arm represented the maximum rate increase of 74.59%(3.20cm)$\sim$138.72%(4.28cm). In the somatotypes of early elementary schoolgirls, type II was more influenced by arm-movements, and for the making of clothing adaptable to movement, type III needed to reflect more surplus length(2cm) than the other types.

• Transactions of the Korean Society of Mechanical Engineers
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• v.15 no.6
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• pp.1919-1932
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• 1991

Experimental studies are conducted to investigate the Flow-Induced Vibration mechanism for cantilever plate model with the angle of attack (.alpha.=10.deg., 20.deg., 30.deg.). Research is divided into two parts. First, the flow fields around two dimensional flat plate model are investigated using LDV system. Second, the vortex shedding frequency and response spectra of cantilever plate are obtained experimentally using gap sensor and hot wire anemometer. Finite element method program was used in order to predict the flow field and pressure field around thin flat plate. And some predicted results were compared with the experimental data. The aspect ration of test model is d/t=25 (d; width, t; thickness). From the measurement of the flow field it was found that in the case of small inclined (.alpha.=10.deg., 20.deg.) relatively, the separated boundary layer at sharp leading edge developed smoothly downstream. With increasing the angle of attack of the plate, stagnation region was appeared on the back side of the plate and separated boundary layer was extended downstream. These trends are a good agreement with the computational results. It was found by analysis of response spectra of cantilever plate that the influences of vortex shedding frequency were important at the large of attack (.alpha.=30.deg.), and two peak values appear in entire test model at 24Hz, 150Hz.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.37 no.1
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• pp.1-8
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• 2001

This study deals with the experimental and numerical investigations to design the high performance otter board. Experiment was carried out to determine the most effective slot size of single-slot cambered otter board in the circulation water channel of BAEK KYUNG IND. Co. LTD. Numerical analysis was done by the commercial CFD code, FLUENT, to provide some valuable physical interpretations and finally to design the otter board section by numerical method. The major results are as follows ; 1. In experiment, the maximum lift and drag coefficients of simple cambered type otterboard were 1.41, 0.55, respectively, at the angle of attack $28^\circ$, while those of slot one with slot size 0.02C (C denotes the chord length) were 1.72, 0.42 at the angle of attack $24^\circ$. 2. The hydrodynamic characteristics depending upon slot size shows the greatest at 0.02C of the slot size. 3. Numerical results well visualized the streamlines, pressure fields, and speed vectors of a simple cambered and slot cambered otter board with slot size 0.02C. The slot cambered one with slot size 0.02C was shown that pressure field was distributed moderately on front and back side of otter board. And, the delay and decrease of separation were favorably achieved by flow through slot. 4. Computed result on the pattern of hydrodynamic field and the values of $C_L$ and $C_D$ by the commercial CFD code, FLUENT, show almost the same as those of the experimental result.

• Korean Journal of Applied Biomechanics
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• v.15 no.2
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• pp.119-127
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• 2005

The purpose of this research helps to make full use for perfect performance by grasping the defects of Ropez motion performed by athlete CSM who was under the training for the 28th 2004 Athene Olympic Garnes, and by presenting complementary methods. For the better Ropez motion which had been performed by CSM for the 1st dispatch selection test and the final for the 28th Athene Olympic Game was analyzed with 3-dimensional cinematographic method. Here are the conclusions: 1. During the board contact phase, powerful kicking and rapid forward flexion motion of upper body make increasing vertical velocity of C. O. G and enlarging body angle. 2. It was indicated that rapid forward flexion motion of upper body during the board contact phase get a large body angle in horse take-off. 3. rapid forward flexion motion of upper body during the board contact phase makes a longer time at horse contacting phase. It showed that this result increased velocity of horse take-off causing by powerful blocking motion. 4. Increasing of air-borne height during pre- flight phase, makes a higher C. O. G; and larger angle of hip, angle of knee and body angle in the landing phase. And it revealed that these results have a stable landing.

• Journal of Korean Society of Steel Construction
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• v.17 no.6 s.79
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• pp.661-672
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• 2005

For the efficient stochastic optimization of steel structures for which a large number of analyses is required, artificial neural networks,which have emerged as a powerful tool that could have been used to replace time-consuming procedures in many scientific or engineering applications, are applied. They are utilized for the solution of the equilibrium equations resulting from the application of the finite element method in connection with the reanalysis type of problem, for which a large number of finite element analyses are required in this study. As such, the use of artificial neural networks to predict finite element analysis outputs simplifies and facilitates the performance of the stochastic optimal design of structural systems where a trained neural network is used to replace the structural reanalysis phase. Moreover, to improve efficiency of used artificial neural networks, genetic algorithm is utilized. The stochastic optimizer used in this study is an algorithm based on the evolution theory. The efficiency of the proposed procedure is examined in problems with both volume (weight) functions and real-world cost functions