• Journal of the Korean Mathematical Society
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• v.32 no.1
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• pp.109-114
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• 1995

Before state precisely our main theorem, we want to make some brief historical comment.

• Archives of Craniofacial Surgery
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• v.16 no.2
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• pp.102-103
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• 2015

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.11 no.2
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• pp.1-2
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• 2007

• Journal of the Korean Ceramic Society
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• v.28 no.1
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• pp.86-89
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• 1991

• Journal of the Korean Ceramic Society
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• v.27 no.5
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• pp.702-704
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• 1990

• Archives of Plastic Surgery
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• v.48 no.2
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• pp.237-238
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• 2021

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.49 no.1
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• pp.55-56
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• 2023

• Journal of Astronomy and Space Sciences
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• v.40 no.2
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• pp.89-90
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• 2023

• The Journal of the Korea Contents Association
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• v.14 no.12
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• pp.1100-1116
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• 2014

The purpose of this study is to investigate how children use the PAIR strategy for their audiences in the writing on the screen and how the comments play a role to communicate between an author and audiences. In order to perform this research, 7 elementary school students(4th-6th grade) participated in the literary education program designed to promote to write on the screen. As a result, 42 body texts(635 sentences) and 424 comments of children's writing on the screen were collected and analyzed according to the PAIR strategies and performance behaviour. The findings are as follows: first, 'attracting' is used the most among PAIR strategies and second, the most frequent performance behavior of comment is 'expression'. These findings indicate that children's writing strategy considering audiences tends to be emotionally appealing and performance behavior of comment is likely to focus on affective expression.

• Journal of Korea Game Society
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• v.18 no.5
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• pp.83-92
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• 2018

Many studies in deep learning show results as good as human's decision in various fields. And importance of activation of online-community and SNS grows up in game industry. Even it decides whether a game can be successful or not. The purpose of this study is to construct a system which can read texts and create comments according to schedule in online-community and SNS using deep learning. Using recurrent neural network, we constructed models generating a comment and a schedule of writing comments, and made program choosing a news title and uploading the comment at twitter in calculated time automatically. This study can be applied to activating an online game community, a Q&A service, etc.