• Archives of design research
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• v.19 no.1 s.63
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• pp.79-88
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• 2006

A human face figure is a visual symbol of identity. Each different face per person is a critical information differentiating each person from others and it directly relates to individual identity. When we look back human history, historical change of recognition for a face led to the change of expression and communication media and it in turn caused many changes in expressing a face. However, there has not been no time period when people pay attention to a face more than this time. Technically, the advent of computer graphics opened new turning point in expressing human face figure. Especially, a visual image which can be produced, saved, and transferred in digital has no limitation in time and space, and its importance in communication is getting higher and higher. Among those visual image information, a face image in digital is getting more applications. Therefore, 3d (3-dimensional) expression of a face using computer graphics can be easily produced without any professional techniques, just like assembling puzzle parts composed of the shape of each part ands texture map, etc. This study presents a method with which a general visual designer can effectively express 3d type face by studying each producing step of 3d face expression and by visualizing case study based on the above-mentioned study result.

• Journal of The Korean Association For Science Education
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• v.17 no.1
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• pp.11-19
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• 1997

Students' protocols obtained from think-aloud interviews were analyzed in the aspects of the success at first two problem-solving stages (understanding and planning), the time to complete a problem, the time at each problem-solving stage, the number of transition, and the transition rate. These were compared in the aspects of the context of problem, the success in solving problem, students' logical reasoning ability, spatial ability, and learning approach. The results were as follows:1. Students tended to spend more time in everyday contexts than in scientific contexts, especially at the stages of understanding and reviewing. The transition rate during solving a problem in everyday contexts was greater than that in scientific contexts. 2. Unsuccessful students spent more time at the stage of understanding, but successful students spent more time at the stage of planning. 3. Students' logical reasoning ability, as measured with the Group Assessment of Logical Thinking, was significantly correlated with the success in solving problem. Concrete-operational students spent more time in completing a problem, especially understanding the problem. 4. Students' spatial ability, as measured with the Purdue Visualization of Rotations Test and the Find A Shape Puzzle, was significantly correlated with their abilities to understand a problem and to plan for its solution. 5. Students' learning approach, as measured with the Questionnaire on Approaches to Learning and Studying, was not significantly correlated with the success in solving problem. However, the students in deep approach had more transitions and greater transition rates than the students in surface approach.

• Journal of architectural history
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• v.28 no.1
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• pp.25-34
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• 2019

"Stupa of Buddhist Monk, YeomGeo"(844) is known as the earliest Seon-stupa relic remains in Korean peninsula, from which, during late Silla and ealy Goryeo period, there were more than 30 of stupa was built on such canon. and became the well-known material culture in Seon Buddhism in late Silla period. In $9^{th}$ century, with the JeonDeong(delivering the light of Seon)from Tang to Silla, the culture of "GeonTapIpBi(building the pagoda and erecting stele)" was also moved in. And it was right after the style of monk's stupa had been methodically changed in china, from having the room in stupa for the corpse, named as "QuanShenSheLi", to the lessened stupa that contain the cremated. Analyzing the "Master ChengGuang's stupa"（807）and its stele, it can be found the correspondences of octagonal plan and the subjects of ornamentation to that of Stupas built in Silla, reveals they were made by the same canon. By the document in the stele, surmising the historical cause of alteration in Chan stupa, there was the most famous zen master ShenHui at the time, who has the most important role of making the NanZongChan to get the authenticity in Chan Buddhism. His reliqury was the first ${\acute{s}}ar{\bar{i}}ra$ casket discovered among Chan monks' relics, consequentially it was to influence to Chan cuture and size the monks 'stupa for his ${\acute{s}}ar{\bar{i}}ra$. The stupa of master ChengGuang, by its shape and geological location, is the lost piece in the Puzzle of Chan stupa culture between Silla and Tang.

• Journal of Gifted/Talented Education
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• v.15 no.1
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• pp.67-84
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• 2005

In this study we investigated the adequacy of tools for distinction gifted students through the comparison these mutual relation on the basis of data, like paper test, the depths interview score, and the rest data((TTCT: Torrance Tests of Creative Thinking, IQ test, FASP: Find A Shape Puzzle, V.T: Visualization Tests and Exp: experimental ability test), and analysis data of EEG test for examining the adequacy of tools for identification gifted students. So, we developed Brain Wave gifted Index(G-Index) for finding another distinction ability as using brain waves data. The standard of index development use gifted brain characteristic in closed-eyes rest state which is judged like that characteristic of distinction between gifted and normal students is the most clear and consistence. That is, the degree of unified pattern between each object and gifted PCA pattern was defined by Pearson method which added spatial mutual index to weight concept. This refer to mean number of spatial PCA pattern. Searching for the possibility of distinction gifted gave distinction effect in 76%. The result of regression analysis on the basis of mutual relation between the rest data is . The probability formula for distinct gifted group is as follow. $$P=\frac 1{1+e^{-[-0.018(TTCT)+0.057(IQ)+1.916(FASP)+0.682(V.T)+0.088(Exp.)+0.034(G-Index)-57.510]}}$$ The result of this calculation showed that probability for distinct in gifted group was very good(95.0%). On the basis of upper result, tools for identification gifted students should be estimated as using many-sided estimation data whatever possible. And following study about development, and operation of tools for distinction suitable to gifted student in science should be progressed.