• Proceedings of the Zoological Society Korea Conference
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• 2001.10a
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• pp.233.1-233
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• 2001

No Abstract, See Full Text

• Proceedings of the Korean Society of Plant Pathology Conference
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• 2002.11a
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• pp.74.2-75
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• 2002

• Proceedings of the Korean Society of Life Science Conference
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• 2006.09a
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• pp.63.2-63.2
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• 2006

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2006.06a
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• pp.236-237
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• 2006

• Proceedings of the Korean Radioactive Waste Society Conference
• /
• 2006.06a
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• pp.238-239
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• 2006

• Proceedings of the Zoological Society Korea Conference
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• 2000.10a
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• pp.264.1-264
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• 2000

No Abstract, See Full Text

• Proceedings of the Zoological Society Korea Conference
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• 2003.08a
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• pp.192.3-192
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• 2003

No Abstract, See Full Text

• Proceedings of the Korean Society of Life Science Conference
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• 2007.10a
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• pp.117.2-117.2
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• 2007

See Full Text

• East Asian mathematical journal
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• v.25 no.3
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• pp.279-297
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• 2009

This paper discusses the key differences and common themes among three major assessments of pre-college mathematics learning: Program for International Student Assessment (PISA), Third International Mathematics and Science Study Repeat (TIMSS-R), and National Assessment of Educational Progress (NAEP).

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.3
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• pp.215-221
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• 2016

This paper describes an automatic vowel sequence reproduction system for a talking robot built to reproduce the human voice based on the working behavior of the human articulatory system. A sound analysis system is developed to record a sentence spoken by a human (mainly vowel sequences in the Japanese language) and to then analyze that sentence to give the correct command packet so the talking robot can repeat it. An algorithm based on a short-time energy method is developed to separate and count sound phonemes. A matching template using partial correlation coefficients (PARCOR) is applied to detect a voice in the talking robot's database similar to the spoken voice. Combining the sound separation and counting the result with the detection of vowels in human speech, the talking robot can reproduce a vowel sequence similar to the one spoken by the human. Two tests to verify the working behavior of the robot are performed. The results of the tests indicate that the robot can repeat a sequence of vowels spoken by a human with an average success rate of more than 60%.