• School Mathematics
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• v.15 no.4
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• pp.975-994
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• 2013

In this paper, we analyzed the utilization trend of technology in the secondary mathematics textbooks based on the 6th, 7th and 2007 revised mathematics curriculums in Korea. We analyzed 30, 60 and 90 mathematics books based on the 6th, 7th and 2007 revised mathematics curriculums respectively. The analysis focused on three aspects of using technology, i.e., contents areas in which technology used, technological tools and programs used, and methods of using technology in teaching and learning mathematics. The results shows that the frequency of using technology in mathematics books has been increased as mathematics curriculum has been revised. In the mathematics books based on th 6th curriculum, only 25 scenes were found, but in 7th and 2007 revised curriculum 248 and 355 scenes were found. In the 6th curriculum, calculators and graphing calculators were used mainly, but in the 7th and 2007 revised curriculum many kinds of technological tools and softwares were used including CAS, dynamic geometry software, spreadsheets, programming language, and the Internet. Especially the internet was used frequently in the 7th curriculum. And the methods of using technology has been diversified as time passed. In the 6th curriculum, the technology mainly used for introducing technology and simple calculation, but in the 7th and 2007 revised curriculum the technologies and software were also used for understanding mathematical laws, principles and concepts and students-centered exploring the mathematical properties.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.11
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• pp.465-472
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• 2022

In this paper, the style synthesis network is trained to generate style-synthesized video through the style synthesis through training Stylegan and the video synthesis network for video synthesis. In order to improve the point that the gaze or expression does not transfer stably, 3D face restoration technology is applied to control important features such as the pose, gaze, and expression of the head using 3D face information. In addition, by training the discriminators for the dynamics, mouth shape, image, and gaze of the Head2head network, it is possible to create a stable style synthesis video that maintains more probabilities and consistency. Using the FaceForensic dataset and the MetFace dataset, it was confirmed that the performance was increased by converting one video into another video while maintaining the consistent movement of the target face, and generating natural data through video synthesis using 3D face information from the source video's face.