• Journal of Korean Society of Forest Science
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• v.105 no.1
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• pp.139-148
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• 2016

The purpose of this study was to evaluate critically the effects of forest experience on young children using meta-analysis. To test this, a total 30 studies were identified, and mean effect size of variables was calculated by applying Fixed-effect model. As a result, the overall effect size of forest experience on young children was 0.797. The effect sizes of daily type as a program type had an effect than experience type at the level of .939. And also the effect sizes of period program (more 4month), number of participants (10-20people), program time (180minute), dependant variables (multiple intelligence) yield effects 0.972, 0.980, 1.138 and 0.957 respectively. As the result, this study implies a way which is to derive effectively further studies on the forest experience on young children.

• The Journal of the Korea Contents Association
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• v.17 no.4
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• pp.606-620
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• 2017

The purpose of this study was to develop and validate a Children's Play Disposition Scale(CPDS) which could be used to evaluate children's play patterns and preferences. The participants of this study were parents of 437 5-7-year-old children (age range from 51months to 106months). Preliminary items were developed through a review of relevant research, multiple intelligence theory and scales, confirmation of item adequacy and content validity. After the content validity was confirmed by experts, these items were edited down to a final list of 27 items representing 6 factors identified by exploratory factor analysis. The 6 factors of the scale consists of initiative, linguistic activity, logical-mathematical activity, art and craft, physical activity, and sensitivity respectively. Concurrent validity was established by using correlations between each factor of the CPDS and sub-factors and the total scores of Multiple Intelligence Checklist for preschoolers (Multiple Intelligence Institute Co., Ltd, 2008) and Multiple Intelligence Checklist for elementary schoolers (Multiple Intelligence Institute Co., Ltd, 2007). In addition, the reliability of each factor, as measured by Cronbach's ${\alpha}$, ranged from .53 to .79. The CPDS provides the developmental and educational information for strengthening children's developmental forte and for supporting children's developmental weakness. This scale can be used on developing children's play contents and guiding play methods in the future.

• Journal of Digital Contents Society
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• v.19 no.5
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• pp.845-852
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• 2018

This study has developed a preventive launcher from smartphone addiction for the digital generation and the contents recommendation based on machine learning which used multiple and collective intelligence. This could provide convenient digital nurturing experience for the parents who fear their children's over use of digital devices and also suggest individually adaptive digital learning methods that enhance the learning efficiency and pleasurable and safe learning environment for the children. Suggested application is a kind of gamification launcher that protects children from harmful contents and from smartphone addiction with time limit settings. For parents who find difficulty choosing from various kinds of contents and applications for education, this suggested system could provide a learning analytic report based on big data after collecting and analyzing the data of their children's learning and activities and recommend contents necessary for their kids using recommended algorithm by collective intelligence.

• Journal of the Institute of Convergence Signal Processing
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• v.21 no.4
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• pp.183-194
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• 2020

Recently, the number of hip dysplasia (DDH) that occurs during infant and child growth has been increasing. DDH should be detected and treated as early as possible because it hinders infant growth and causes many other side effects In this study, two modelling techniques were used for multiple training techniques. Based on the results after the first transformation, the training was designed to be possible even with a small amount of data. The vertical flip, rotation, width and height shift functions were used to improve the efficiency of the model. Adam optimization was applied for parameter learning with the learning parameter initially set at 2.0 x 10e-4. Training was stopped when the validation loss was at the minimum. respectively A novel image overlay system using 3D laser scanner and a non-rigid registration method is implemented and its accuracy is evaluated. By using the proposed system, we successfully related the preoperative images with an open organ in the operating room