• Child Health Nursing Research
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• v.7 no.1
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• pp.118-140
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• 2001

The purpose of this study was to measure the effect of safety education program in preschool children for accident prevention and improve their health through more systematic method. Data were collected from 584 preschoolers(247 preschooler are assigned to experimental group and 337 preschoolers are assinged to control group) from 4 to 6 years old using APP paper test which consists of questions and drawings. To experimental group, safety education were done 4 times within the time of 30 minutes per 1 time using education books, drawings, OHP. The findings of this study are as follows: 1. There were significant difference in movement(χ²=18.732, p=.0000), behavioral character(χ²=27.785, p=.000), synthetic judgement(χ²=12.02, p=0.002). So, safety education program have effect on preschooler. 2. In the accident proneness on preschooler between experimental group and control group according to general characteristics, it proved significant difference in the case of accident prevention education were done, reasoning power(χ²=10.48, p=.005), movement speed(χ²=7.341, p=.025) and behavioral character(χ²=18.86, p=.000), in the case of housing pattern is private house(individual house, yard?), reasoning power(χ²=6.683, p=.035), movement speed(χ²=12.76, p= .002) and behavioral character(χ²=12.24, p=.002), in the case of housing pattern is mixed-type, movement speed(χ²=6.935, p= .031) and behavioral character(χ²=10.816, p=.004), in the case of housing pattern is over six stories, movement speed(χ²=7.543, p=.023), in the case of subjects' age is 4 years old, movement speed(χ²=16.5, p= .000) and behavioral character(χ²=12.18, p=.002), in the case of subjects' age is 5 years old, movement speed(χ²=7.519, p= .023), watchfulness(χ²=6.372, p=.041), behavioral character(χ²=14.74, p=0.001) and synthetic judgement(χ²=14.5, p=.001), in the case of subjects' sex is male, life safety(χ²=6.406, p=.041), movement speed(χ²=22.86, p= .000), behavioral character(χ²=13.72, p= .001) and synthetic judgement(χ²=13.82, p=.001), in the case of subjects' sex is female, reasoning power(χ²=12.57, p=.002) and behavioral character(χ²=13.16, p= .001), in the case of childrens have past accidental experience, traffic safety(χ²= 6.683, p=.035), in the case of childrens have no past accidental experience, reasoning power(χ²=8.384, p=.015), movement speed(χ²=20.6, p=.000), behavioral character(χ²=25.1, p=.000) and synthetic judgement(χ² =10.79, p=.005), in the case of children's order is first, reasoning power(χ²=11.15, p=.004), movement speed(χ²=11.92, p= .003) and behavioral character(χ²=7.003, p=.030), in the case of children's order is second, movement speed(χ²=6.694, p= .035), behavioral character(χ²=26.9, p= .000) and synthetic judgement(χ²=14.3, p= .001), in the case of nuclear family, reasoning power(χ²=8.777, p=.012), movement speed(χ²=19.0, p=.000), behavioral character (χ²=26.4, p=0.000) and synthetic judgement (χ²=9.999, p=.007), in the case of mothers' school career is under high school graduate, life safety(χ²=8.023, p=.018), movement speed(χ²=10.99, p=.004) and behavioral character(χ²=6.777, p=.034), in the case of mothers' school career is beyond college graduate, reasoning power(χ²=6.717, p= .035), movement speed(χ²=8.963, p=.011), behavioral character(χ²=25.03, p=.000) and synthetic judgement(χ²=15.19, p=.001), in the case of mothers' age ranged 31-34, movement speed(χ²=12.29, p=.002) and behavioral character(χ²=14.17, p=.001), in the case of mothers' age ranged 35-39, movement speed(χ²=9.859, p=.007), behavioral character(χ²=9.095, p=.011) and synthetic judgement(χ²=7.810, p=.020), in the case of mothers' age is over 40, life safety(χ² =5.593, p=.025), in the case of mothers' job is full-time, traffic safety(χ²=6.032, p=.049) and reasoning power(χ²=8.502, p= .014), in the case of mothers' job is part- time., movement speed(χ²=10.99, p=.004) and behavioral character(χ²=7.895, p= .019), in the case of mothers have no job, movement speed(χ²=6.410, p=.041), movement stability(χ²=6.879, p=.032), behavioral character(χ²=27.72, p=.000) and synthetic judgement(χ²=18.11, p=.000). The difference of accident proneness between experimental group and control group according to general characterists, it also showed that there were significant difference in behavioral character compared to other area.. From this findings, we can guess that safety education program change and guide preschoolers' behavioral character to desirable direction.

• Journal of Korea Game Society
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• v.9 no.1
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• pp.127-134
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• 2009

This paper presents a motion generation technique for arbitrary morphologies with the user defined correspondences between joints. Users can define the controlling part in the source character and the part to be controlled in the target character in our system. To remove the restriction in the morphology of the target character, we use the pair of example posture sets. In our system, in order to provide the correspondence regardless of the number of joints, the deformed part in the target character is simplified into the direction vector. The final postures are then generated with the weighted sum of the examples. Our experimental results demonstrate that our approach can generate motions for various target characters and can control the user defined joints in real-time.

• Journal of the Korea Computer Graphics Society
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• v.13 no.4
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• pp.1-6
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• 2007

In this paper we describe the method of controlling the animation of 3D characters according to ISO/IEC 19774 (H-Anim) specification, which has been released by Wed3D Consortium and ISO/IEC SC24 WG6. The animation structure of the H-Anim character can be defined and modified in our H-Anim editor program. Our H-Anim animator generates the character's motion automatically according to the input of motion parameters at the character's joints interactively. This paper is focused on the development of a motion generation tool for human-like characters defined by H-Anim structures.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.9
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• pp.1547-1553
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• 2008

This paper presents a method that generates various facial expressions of vector graphic character by using the simplified principle component vector. First, we analyze principle components to the nine facial expression(astonished, delighted, etc.) redefined based on Russell's internal emotion state. From this, we find principle component vector having the biggest effect on the character's facial feature and expression and generate the facial expression by using that. Also we create natural intermediate characters and expressions by interpolating weighting values to character's feature and expression. We can save memory space considerably, and create intermediate expressions with a small computation. Hence the performance of character generation system can be considerably improved in web, mobile service and game that real time control is required.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.413-435
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• 2018

Although the accuracy of handwritten character recognition based on deep networks has been shown to be superior to that of the traditional method, the use of an overly deep network significantly increases time consumption during parameter training. For this reason, this paper took the training time and recognition accuracy into consideration and proposed a novel handwritten character recognition algorithm with newly designed network structure, which is based on an extended nonlinear kernel residual network. This network is a non-extremely deep network, and its main design is as follows:(1) Design of an unsupervised apriori algorithm for intra-class clustering, making the subsequent network training more pertinent; (2) presentation of an intermediate convolution model with a pre-processed width level of 2;(3) presentation of a composite residual structure that designs a multi-level quick link; and (4) addition of a Dropout layer after the parameter optimization. The algorithm shows superior results on MNIST and SVHN dataset, which are two character benchmark recognition datasets, and achieves better recognition accuracy and higher recognition efficiency than other deep structures with the same number of layers.

• Journal of Digital Convergence
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• v.14 no.3
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• pp.361-372
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• 2016

The purpose of this study was to examine the mediating effect of moral elevation and self control on the relationship between moral identity, character strengths, family strengths, and altruistic behavior in the times of convergence. The collected data were analyzed by SEM. The results of this study were as follows: First, moral self has indirect effect on altruistic behavior through moral elevation and self control in turn, and character strengths, have indirect effect on altruistic behavior through moral elevation and self control and moral elevation, self control in turn, and family strengths have indirect effect on altruistic behavior through self control. Second, it was found that there was a significant gender difference in the structural weights of character strengths and moral elevation.

• Journal of Digital Convergence
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• v.13 no.11
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• pp.481-491
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• 2015

This research has verified the efficacy of character education course in Liberal Art Curriculum in accordance with the objective of K Women's University of which is the 'mind sharing through mindfulness, SMART human resources development'. Most of the content of character education is organized aiming to promote values of "appreciation". The subjects are experimental group and control group, of which are 229. Research methods were t-test of between groups. The effects of the course have shown that the experimental group students were higher on the level of connectedness sub-scale in Gestalt Contact Boundary Scale than those of the control group students(t=2.323, p = .021). Although the 'character education' course increased connectedness, but it no positive effect on mindfulness skill and self-esteem. This results showed that character education course is effective to promote mind sharing and connectedness in part. It was discussed about a way of further refining course contents and the need to reflect educational philosophy of the K Women's University.

• Proceedings of the KAIS Fall Conference
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• 2009.12a
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• pp.630-632
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• 2009

The parameters of PID controller should be readjusted whenever system character change. In spite of a rapid development of control theory, this work needs much time and effort of expert. In this paper, to resolve this defect, after the sample of parameters in the changeable limits of system character is obtained, these parametrs are used as desired values of back propagation learning algorithm, also neural network auto tuner for PID controller is proposed by determing the optimum structure of neural network. Simulation results demonstrate that auto-tuning proper to system character can work well.

• KIEE International Transaction on Systems and Control
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• v.12D no.1
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• pp.27-32
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• 2002

In this paper, we would study the applicability of neural networks to the recognition process of Korean stenographic character image, applying the classification function, which is the greatest merit of those of neural networks applied to the various parts so far, to the stenographic character recognition, relatively simple classification work. Korean stenographic recognition algorithms, which recognize the characters by using some methods, have a quantitative problem that despite the simplicity of the structure, a lot of basic characters are impossible to classify into a type. They also have qualitative one that It Is not easy to classify characters fur the delicacy of the character farms. Even though this is the result of experiment under the limited environment of the basic characters, this shows the possibility that the stenographic characters can be recolonized effectively by neural network system. In this system, we got 90.86% recognition rate as an average.

• Journal of Intelligence and Information Systems
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• v.8 no.2
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• pp.105-115
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• 2002

This paper proposed a recognition method of english calling card using both 4-directed contour tracking algorithm and enhanced ART1 algorithm. After we extract candidate character string region using horizontal smearing and 4-directed contour tracking method, we extract character string region through comparison of character region and non-character region using horizontal and vertical ratio and area in english calling card. In extracted character string region, we extract each character using horizontal smearing and contour tracking algorithm, and recognize each character by enhanced ART1 algorithm. The proposed ART1 algorithm is enhanced by dynamic control of similarity using fuzzy sum connective operator. The result indicate that the proposed method is superior in performance.