373 research outputs found

    The Educational Life Histories on High School Admission Experience of Students of Science Gifted Education Institute Affiliated with University

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์‚ฌ๋ฒ”๋Œ€ํ•™ ๊ณผํ•™๊ต์œก๊ณผ(ํ™”ํ•™์ „๊ณต), 2020. 8. ํ™ํ›ˆ๊ธฐ.๋ณธ ์—ฐ๊ตฌ๋Š” ๊ณผํ•™์˜์žฌ๊ต์œก์› ์ˆ˜๋ฃŒ ๊ฒฝ๋ ฅ์ด ๊ณ ๋“ฑํ•™๊ต ์ž…์‹œ์— ์‹ค์งˆ์ ์œผ๋กœ ๋„์›€์ด ๋˜์ง€ ์•Š๋Š”๋‹ค๋Š” ํ†ต๋…์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ , ์ž…์‹œ ์ค€๋น„ ๊ธฐ๊ฐ„์— ์ ๊ทน์ ์œผ๋กœ ๊ณผํ•™์˜์žฌ๊ต์œก์›์—์„œ ํ™œ๋™ํ•œ ํ•™์ƒ๋“ค์— ๋Œ€ํ•œ ํ˜ธ๊ธฐ์‹ฌ์—์„œ ์ถœ๋ฐœํ–ˆ๋‹ค. ๊ทธ๋“ค์˜ ๊ฒฝํ—˜์œผ๋กœ๋ถ€ํ„ฐ ๊ณ ๋“ฑํ•™๊ต ์ž…์‹œ ์ƒํ™ฉ์„ ์ฒด๊ณ„์ ์œผ๋กœ ์ดํ•ดํ•˜๊ณ , ๊ณ ๋“ฑํ•™๊ต ์ž…์‹œ์™€ ๊ณผํ•™์˜์žฌ๊ต์œก์›์˜ ๊ต์œก์ด ๊ต์ฐจํ•˜๋Š” ์žฅ๋ฉด์„ ์žฌ๊ตฌ์„ฑํ•จ์œผ๋กœ์จ ๋” ๋‚˜์€ ๊ณผํ•™์˜์žฌ๊ต์œก์„ ์œ„ํ•œ ์‹œ์‚ฌ์ ์„ ์ฐพ๋Š” ๊ฒƒ์ด ๋ณธ ์—ฐ๊ตฌ์˜ ๋ชฉ์ ์ด๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ์—ฐ๊ตฌ์ฐธ์—ฌ์ž ๊ฐœ์ธ์˜ ์ƒ์•  ๊ฒฝํ—˜์„ ๊ต์œก์˜ ๋งฅ๋ฝ์—์„œ ์ถฉ์‹คํžˆ ๊ธฐ์ˆ ํ•˜๊ณ , ๊ฑฐ์‹œ์  ๊ด€์ ์—์„œ ์‚ฌํšŒ๋ฌธํ™”์  ๋ฐ ์—ญ์‚ฌ์  ๋งฅ๋ฝ์„ ํ•จ๊ป˜ ๋ณด์—ฌ์ฃผ๋Š” ๊ต์œก์ƒ์• ์‚ฌ ์—ฐ๊ตฌ๋ฅผ ์ˆ˜ํ–‰ํ–ˆ๋‹ค. ์—ฐ๊ตฌ์— ์ฐธ์—ฌํ•œ ๊ณผํ•™์˜์žฌ๋“ค์€ 2015, 2016๋…„์— ์„œ์šธ๋Œ€ํ•™๊ต ๊ณผํ•™์˜์žฌ๊ต์œก์› ํ™”ํ•™๋ถ„๊ณผ์—์„œ ๊ต์œก์„ ๋ฐ›์€ 5๋ช…์˜ ํ•™์ƒ์ด๋‹ค. ์ด๋“ค์€ ์˜์žฌ๊ณ , ๊ณผํ•™๊ณ , ์ž์‚ฌ๊ณ  ๋“ฑ์˜ ์ž…์‹œ๋ฅผ ์ค€๋น„ํ•˜๋Š” ์™€์ค‘์—๋„ ๊ณผํ•™์˜์žฌ๊ต์œก์›์—์„œ ํ™œ๋™ํ–ˆ์œผ๋ฉฐ, ํŠนํžˆ ์ž…์‹œ๊ฐ€ ์ง„ํ–‰๋˜๋Š” ์ค‘ํ•™๊ต 3ํ•™๋…„ ๋‹น์‹œ ์ „๊ตญ ์‚ฌ์‚ฌ๊ณผ์ • ์—ฐ๊ตฌ์„ฑ๊ณผ ๋ฐœํ‘œ๋Œ€ํšŒ์—์„œ ๊ฐ€์žฅ ์šฐ์ˆ˜ํ•œ ์„ฑ๊ณผ๋ฅผ ๊ฑฐ๋‘˜ ๋งŒํผ ์ ๊ทน์ ์œผ๋กœ ๊ณผํ•™์˜์žฌ๊ต์œก์›์˜ ํƒ๊ตฌ ํ™œ๋™์— ์ฐธ์—ฌํ–ˆ๋‹ค๋Š” ๊ณตํ†ต์ ์ด ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์šฐ์„ , ๋Œ€ํ•™๋ถ€์„ค ๊ณผํ•™์˜์žฌ๊ต์œก์› ํ•™์ƒ๋“ค์˜ ๊ณ ๋“ฑํ•™๊ต ์ž…์‹œ ๊ณผ์ •์˜ ํŠน์ง•์„ ๊ฐœ๋ณ„์ ์œผ๋กœ ์‚ดํŽด๋ณด์•˜๋‹ค. ์ฒซ ๋ฒˆ์งธ ์—ฐ๊ตฌ์ฐธ์—ฌ์ž ๊น€๋ฆฌ์˜จ์€ ์ดˆ๋“ฑํ•™๊ต ์ €ํ•™๋…„ ๋•Œ๋ถ€ํ„ฐ ์˜์žฌ๊ต์œก ์ „๋ฌธํ•™์›์— ๋‹ค๋‹ˆ๋ฉฐ ๊ณ ๋“ฑํ•™๊ต ์ž…์‹œ๋ฅผ ์ค€๋น„ํ–ˆ๊ณ , ์˜๋Œ€ ์ง„ํ•™์„ ๋ชฉํ‘œ๋กœ ๊ณผํ•™๊ณ ์— ์ง€์›ํ•  ๊ณ„ํš์„ ์„ธ์› ๋‹ค. ํ•˜์ง€๋งŒ ๊ทธ๋…€๋Š” ์‹œํ—˜ ์‚ผ์•„ ๋„์ „ํ•œ ์˜์žฌ๊ณ  ์ž…์‹œ์—๋Š” ํ•ฉ๊ฒฉํ•˜์ง€ ๋ชปํ–ˆ๊ณ , ๋’ค์ด์–ด ์ง„ํ–‰๋œ ๊ณผํ•™๊ณ  ์ž…์‹œ์—์„œ๋„ 1์ฐจ ์ „ํ˜•์—์„œ ํƒˆ๋ฝํ•˜๋ฉฐ ํฐ ์ถฉ๊ฒฉ์„ ๋ฐ›์•˜๋‹ค. ๋‘ ๋ฒˆ์งธ ์—ฐ๊ตฌ์ฐธ์—ฌ์ž ๋ฐ•์žฌํ˜์€ ๊ณผํ•™ํ•™์›์„ ํ•จ๊ป˜ ๋‹ค๋…”๋˜ ์นœ๊ตฌ๋“ค์ด ์˜์žฌ๊ณ  ์ž…์‹œ ์ค€๋น„๋ฅผ ์‹œ์ž‘ํ•˜์ž ๋ณธ์ธ๋„ ๋ง‰์—ฐํ•˜๊ฒŒ๋‚˜๋งˆ ์˜์žฌ๊ณ ์— ์ง„ํ•™ํ•˜๊ธธ ํฌ๋งํ–ˆ๋‹ค. ํ•˜์ง€๋งŒ ์•„๋“ค์ด ์‚ฌ๊ต์œก์˜ ๋„์›€ ์—†์ด ๊ณต๋ถ€ํ•˜๊ธธ ์›ํ–ˆ๋˜ ๋ถ€๋ชจ๋‹˜์˜ ๊ต์œก ๋ฐฉ์นจ์œผ๋กœ ์ธํ•ด ๋‹ค๋ฅธ ์นœ๊ตฌ๋“ค๊ณผ๋Š” ๋‹ฌ๋ฆฌ ์ž…์‹œ ์ „๋ฌธํ•™์›์— ๋‹ค๋‹ ์ˆ˜ ์—†์–ด ์‹ฌ๋ฆฌ์  ๊ฐˆ๋“ฑ์„ ๊ฒช๊ธฐ๋„ ํ–ˆ๋‹ค. ๊ทธ๋Š” ์˜์žฌ๊ณ  ์ž…์‹œ์—์„œ ํƒˆ๋ฝํ–ˆ์œผ๋‚˜, ์ดํ›„ ์ž์‚ฌ๊ณ ์— ์ง€์›ํ•˜์—ฌ ํ•ฉ๊ฒฉํ–ˆ๋‹ค. ์„ธ ๋ฒˆ์งธ ์—ฐ๊ตฌ์ฐธ์—ฌ์ž ์ตœ์ธ๊ทœ๋Š” ์ž์‹ ์ด ๋‹ค๋‹ˆ๋Š” ๊ตญ์ œ์ค‘์˜ ๋…ํŠนํ•œ ๊ต์œก๊ณผ์ •์— ๋งค์šฐ ๋งŒ์กฑํ•˜์—ฌ, ๊ณ ๋“ฑํ•™๊ต์— ์ง„ํ•™ํ•ด์„œ๋„ ํŠน๋ณ„ํ•œ ๊ต์œก๊ณผ์ •์— ๋”ฐ๋ผ ๊ณต๋ถ€ํ•˜๊ธธ ์›ํ–ˆ๋‹ค. ํ•œ๊ตญ์ค‘๋“ฑ์˜ฌ๋ฆผํ”ผ์•„๋“œ์—์„œ ์šฐ์ˆ˜ํ•œ ์„ฑ๊ณผ๋ฅผ ๊ฑฐ๋‘” ๊ทธ๋Š” ์ž์‹ ๊ฐ์„ ์–ป์–ด ์˜์žฌ๊ณ  ์ž…์‹œ์— ๋„์ „ํ–ˆ์œผ๋‚˜ ํƒˆ๋ฝํ–ˆ๋‹ค. ์˜์žฌ๊ณ  ํƒˆ๋ฝ ์ดํ›„ ๋ถ€๋ชจ๋‹˜์ด ์‚ฌ๊ต์œก์„ ๊ฐ•๋ ฅํ•˜๊ฒŒ ๊ถŒํ•˜๊ฒŒ ๋˜๋ฉด์„œ ๋ถ€๋ชจ๋‹˜๊ณผ ๊ฐˆ๋“ฑ์„ ๋นš์—ˆ์œผ๋ฉฐ, ์ž์‚ฌ๊ณ ์— ํ•ฉ๊ฒฉํ•œ ๋’ค์—๋„ ์ด๋Ÿฌํ•œ ๊ฐˆ๋“ฑ์€ ์ด์–ด์กŒ๋‹ค. ๋„ค ๋ฒˆ์งธ ์—ฐ๊ตฌ์ฐธ์—ฌ์ž ์•ˆ์„ฑ๋ฏผ์€ ์•„๋ฒ„์ง€๊ฐ€ ์ถ”์ฒœํ•œ ๊ตญ์ œ์ค‘์— ๋‹ค๋‹ˆ๋ฉฐ ์—ฌ๋Ÿฌ ๊ณผํ•™ ๊ด€๋ จ ๋Œ€ํšŒ์—์„œ ์ˆ˜์ƒ๊ฒฝ๋ ฅ์„ ์Œ“์•˜๋‹ค. ์ž…์‹œ ์ „๋ฌธํ•™์›์—์„œ ์˜ฌ๋ฆผํ”ผ์•„๋“œ๋ฅผ ์ค€๋น„ํ•˜๋ฉฐ ์ˆ˜ํ•™ยท๊ณผํ•™์„ ๊นŠ์ด ์žˆ๊ฒŒ ๊ณต๋ถ€ํ–ˆ๊ณ , ์˜ฌ๋ฆผํ”ผ์•„๋“œ ์ข…๋ฃŒ ํ›„์—๋Š” ์˜์žฌ๊ณ  ์ž…์‹œ์— ๋งค์ง„ํ•˜์—ฌ ์ตœ์ข…์ ์œผ๋กœ ์˜์žฌ๊ณ ์— ํ•ฉ๊ฒฉํ–ˆ๋‹ค. ๋‹ค์„ฏ ๋ฒˆ์งธ ์—ฐ๊ตฌ์ฐธ์—ฌ์ž ์•ˆ์˜์šฐ๋Š” ์–ด๋ ค์„œ๋ถ€ํ„ฐ ํŠน๋ชฉ๊ณ ๋ฅผ ๊ฑฐ์ณ ๋ช…๋ฌธ๋Œ€์— ์ง„ํ•™ํ•œ ๋‘ ๋ˆ„๋‚˜์—๊ฒŒ ํ•™์—…์ ์ธ ๋„์›€์„ ๋งŽ์ด ๋ฐ›์•˜๋‹ค. ๊ทธ๋Š” ํ•™๊ต์—์„œ ๋ฐฐ์šธ ์ˆ˜ ์—†๋Š” ๋„์ „์ ์ธ ๋‚ด์šฉ์„ ์ง‘๊ณผ ํ•™์›์—์„œ ๋Šฅ๋™์ ์œผ๋กœ ํ•™์Šตํ–ˆ๊ณ , ๋น„๊ต์  ์งง์€ ๊ธฐ๊ฐ„ ์ž…์‹œ ์ „๋ฌธํ•™์›์—์„œ ์˜์žฌ๊ณ  ์ž…์‹œ๋ฅผ ์ค€๋น„ํ•˜์—ฌ ์ตœ์ข…์ ์œผ๋กœ ์˜์žฌ๊ณ ์— ์šฐ์„ ์„ ๋ฐœ๋กœ ํ•ฉ๊ฒฉํ–ˆ๋‹ค. ๋‘˜์งธ๋กœ, ์—ฐ๊ตฌ์ฐธ์—ฌ์ž๋“ค์˜ ๊ณ ๋“ฑํ•™๊ต ์ž…์‹œ ๊ตฌ์กฐ๋ฅผ ์ฒด๊ณ„์ ์œผ๋กœ ์ดํ•ดํ•˜๊ธฐ ์œ„ํ•ด ์†Œ์ƒํ™ฉ-(๋งค๊ฐœ์ƒํ™ฉ)-๋Œ€์ƒํ™ฉ ๋ถ„์„ํ‹€์— ๋”ฐ๋ผ ๊ณ ๋“ฑํ•™๊ต ์ž…์‹œ์˜ ์ƒํ™ฉ์  ๊ตฌ์กฐ๋ฅผ ์‚ดํŽด๋ณด์•˜๋‹ค. ์—ฐ๊ตฌ์ฐธ์—ฌ์ž๋“ค์˜ ์†Œ์ƒํ™ฉ์  ์š”์†Œ๋กœ๋Š” ๊ฐœ์ธ์  ํŠน์„ฑ์œผ๋กœ ๋†’์€ ํ•™์Šต ๋Šฅ๋ ฅ๊ณผ ํ•™๊ตฌ์—ด, ๋ฐฐ๊ฒฝ์  ํŠน์„ฑ์œผ๋กœ ๊ณ ํ•™๋ ฅ ๋ถ€๋ชจ์˜ ์กด์žฌ, ์‹œ๊ฐ„์  ํŠน์„ฑ์œผ๋กœ ์ƒ๊ฐ์ด ๋งŽ์•„์ง€๋Š” ์‚ฌ์ถ˜๊ธฐ๋ฅผ ์ถ”์ถœํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์—ฐ๊ตฌ์ฐธ์—ฌ์ž ๊ฐœ์ธ์˜ ํ–‰์œ„ ์ด๋ฉด์— ์ž‘์šฉํ•˜๊ณ  ์žˆ๋Š” ์ถ”์ƒ์ , ๋ณดํŽธ์ , ๋น„๊ฐ€์‹œ์ , ๋น„์ผ์ƒ์ , ์ด๋ก ์  ์ƒํ™ฉ์— ํ•ด๋‹นํ•˜๋Š” ๋Œ€์ƒํ™ฉ์  ์š”์†Œ๋กœ๋Š” ๋Œ€ํ•™์˜ ์œ„๊ณ„์„œ์—ด์ด ๊ณ ๋“ฑํ•™๊ต ๊ธ‰๊นŒ์ง€ ํ™•์‚ฐ๋˜๋Š” ํ•™๋ฒŒ์ฃผ์˜, ๊ฐœ์ธ์˜ ์‹ค๋ ฅ์— ๋”ฐ๋ฅธ ๊ธฐํšŒ ๋ฐฐ๋ถ„๊ณผ ๋…ธ๋ ฅ์„ ์ค‘์‹œํ•˜๋Š” ์‹ค๋ ฅ์ฃผ์˜, ๊ต์œก์˜ ๋งฅ๋ฝ์—์„œ ๊ณ ๊ต๋‹ค์–‘ํ™”์™€ ์ˆ˜๋Ÿ‰ํ™”์˜ ์ง€๋ฐฐ๋ฅผ ๋ถˆ๋Ÿฌ์˜จ ์‹ ์ž์œ ์ฃผ์˜๋ฅผ ์ถ”์ถœํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์†Œ์ƒํ™ฉ๊ณผ ๋Œ€์ƒํ™ฉ์„ ์—ฐ๊ฒฐํ•˜๋Š” ํ•ด์„์  ๋ฉ”ํƒ€-์ปค๋ฎค๋‹ˆ์ผ€์ด์…˜ ์ƒํ™ฉ์— ํ•ด๋‹นํ•˜๋Š” ๋งค๊ฐœ์ƒํ™ฉ์œผ๋กœ๋Š” ์„ฑ์ ๊ณผ ์„ฑ๊ณผ๊ฐ€ ๊ถŒ๋ ฅ์œผ๋กœ ์ž‘๋™ํ•˜๋Š” ํ•™๊ต, ๋ถˆ์•ˆ๊ฐ์„ ์ž๊ทนํ•จ๊ณผ ๋™์‹œ์— ํ•ด์†Œํ•ด์ฃผ๋Š” ํ•™์›, ๋ช…์‹œ์ /์•”๋ฌต์ ์œผ๋กœ ํ•™๋ฒŒ์„ ๋น„๊ตํ•˜๋Š” ๊ฐ€์กฑ, ์ฐจ๋ณ„ํ™”์™€ ๋™์งˆํ™”์˜ ์ด์ค‘์  ๋˜๋ž˜ ๊ด€๊ณ„๋ฅผ ์ถ”์ถœํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ด๋Ÿฌํ•œ ์ƒํ™ฉ์  ๊ตฌ์กฐ๋Š” ์—ฐ๊ตฌ์ฐธ์—ฌ์ž๋“ค์—๊ฒŒ ๋Œ€๋ถ€๋ถ„ ๊ณตํ†ต์ ์œผ๋กœ ์ถ”์ถœํ•  ์ˆ˜ ์žˆ๋Š” ์š”์†Œ์ด๊ธด ํ–ˆ์ง€๋งŒ, ๊ตฌ์ฒด์ ์ธ ์–‘์ƒ์€ ์ œ๊ฐ๊ฐ ์ฐจ์ด๊ฐ€ ์žˆ์—ˆ๋‹ค. ์…‹์งธ๋กœ, ๊ณ ๋“ฑํ•™๊ต ์ž…์‹œ ๊ณผ์ •์—์„œ ๊ณผํ•™์˜์žฌ๊ต์œก์›์€ ์—ฐ๊ตฌ์ฐธ์—ฌ์ž๋“ค์—๊ฒŒ ์–ด๋–ค ์—ญํ• ์„ ๋‹ด๋‹นํ–ˆ๋Š”์ง€ ๋ถ„์„ํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ์ฐธ์—ฌ์ž๋“ค์—๊ฒŒ ๊ณผํ•™์˜์žฌ๊ต์œก์›์€ ์ง€์  ๋„์ „์„ ํ•˜๊ธฐ ์–ด๋ ค์šด ํ•™๊ต๋‚˜ ์ง€๋‚˜์น˜๊ฒŒ ์น˜์—ดํ•œ ๊ฒฝ์Ÿ์ด ๋ฒŒ์–ด์ง€๋Š” ํ•™์›์—์„œ ๋ฒ—์–ด๋‚˜, ๊ด€์‹ฌ์‚ฌ๋ฅผ ๊ณต์œ ํ•  ์ˆ˜ ์žˆ๋Š” ์นœ๊ตฌ๋“ค๊ณผ ๋งˆ์Œ ํŽธํžˆ ํ™œ๋™ํ•  ์ˆ˜ ์žˆ๋Š” ์‰ผํ„ฐ์˜ ์—ญํ• ์„ ํ–ˆ๋‹ค. ๋˜ํ•œ, ์ž์‹ ์ด ๋ฐฐ์šด ๊ณผํ•™ ์ง€์‹์„ ์‹ค์ œ ์„ธ๊ณ„์™€ ์—ฐ๊ฒฐํ•ด๋ณด๋Š” ์‹คํ—˜์„ ๊ฒฝํ—˜ํ•  ์ˆ˜ ์žˆ๊ณ , ์ด๋ฅผ ํ†ตํ•ด ๊ณผํ•™์ž๋กœ์„œ์˜ ์ •์ฒด์„ฑ์„ ํ‚ค์›Œ๊ฐˆ ์ˆ˜ ์žˆ๋Š” ์‹คํ—˜์‹ค์˜ ์—ญํ• ์„ ๋‹ด๋‹นํ–ˆ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, ๋Œ€ํ•™๊ต์ˆ˜์™€ ์กฐ๊ต๋กœ๋ถ€ํ„ฐ ์ฒด๊ณ„์ ์œผ๋กœ ํƒ๊ตฌ ํ™œ๋™์„ ์ง€๋„๋ฐ›์Œ์œผ๋กœ์จ ์ง€ํ•„๊ณ ์‚ฌ ์ค€๋น„์—๋งŒ ๋ชฐ๋‘ํ•˜๋Š” ๋‹ค๋ฅธ ๊ฒฝ์Ÿ์ž๋“ค๊ณผ๋Š” ์ฐจ๋ณ„ํ™”๋œ ์ŠคํŽ™์„ ์Œ“์„ ์ˆ˜ ์žˆ๋Š” ๊ต์œก๊ธฐ๊ด€์˜ ์—ญํ• ์„ ๋‚˜ํƒ€๋‚ด๊ธฐ๋„ ํ–ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋ถ„์„ ๊ฒฐ๊ณผ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ์—ฐ๊ตฌ์ฐธ์—ฌ์ž๋“ค์˜ ์‚ฌ๋ก€๊ฐ€ ๊ณผํ•™์˜์žฌ๊ต์œก์— ์–ด๋– ํ•œ ์‹œ์‚ฌ์ ์„ ์ œ๊ณตํ•˜๋Š”์ง€ ๋…ผ์˜ํ•ด๋ณด์•˜๋‹ค. ์ฒซ์งธ, ํ˜„์žฌ์˜ ๊ณ ๋“ฑํ•™๊ต ์ž…์‹œ๋Š” ์‹œํ—˜์—์„œ ๊ฐ€์žฅ ์šฐ์ˆ˜ํ•œ ์„ฑ์ ์„ ๊ฑฐ๋‘” ์‹ค๋ ฅ ์žˆ๋Š” ํ•™์ƒ์„ ์„ ๋ฐœํ•˜๋Š” ๊ฒฝํ–ฅ์ด ํฌ๋‹ค. ์ด๋Ÿฌํ•œ ์‹ค๋ ฅ์ฃผ์˜ ํŒจ๋Ÿฌ๋‹ค์ž„์—์„œ ๋ฒ—์–ด๋‚˜ ๊ฐ ์˜์žฌ๊ต์œก ๊ธฐ๊ด€์ด ์ œ๊ณตํ•˜๋Š” ๊ฐ€๋ฅด์นจ๊ณผ ๊ธ์ •์ ์œผ๋กœ ์ƒํ˜ธ์ž‘์šฉํ•  ์ˆ˜ ์žˆ๋Š” ํ•™์ƒ์„ ์„ ์ •ํ•˜๋ ค๋Š” ์‹œ๋„๊ฐ€ ์š”๊ตฌ๋œ๋‹ค. ๋‘˜์งธ, ๊ณ ๋“ฑํ•™๊ต ์ž…์‹œ ๊ณผ์ •์—์„œ๋„ ๋“œ๋Ÿฌ๋‚˜๋“ฏ ์ง€๊ธˆ๊นŒ์ง€ ์˜์žฌ๊ต์œก์€ ๊ฐœ์ธ ์ฐจ์›์˜ ์ด๋ก ์ , ์ถ”์ƒ์  ์‚ฌ๊ณ ๋ฅผ ์ค‘์‹œํ–ˆ๋‹ค. ํ•˜์ง€๋งŒ ์—ฐ๊ตฌ์ฐธ์—ฌ์ž๋“ค์˜ ๊ฒฝํ—˜์„ ํ†ตํ•ด ํ˜„์ƒ์„ ์ฐฝ์กฐํ•˜๋Š” ๊ด€์ฐฐ๊ณผ ์‹คํ—˜ ๋“ฑ์ด ํ•จ๊ป˜ ํ•˜๋Š” ๊ณต๋ถ€๋ฅผ ์ด‰์ง„ํ•  ์ˆ˜ ์žˆ์Œ์„ ์•Œ ์ˆ˜ ์žˆ๋‹ค. ์…‹์งธ, ์ง€๊ธˆ๊นŒ์ง€ ๊ณผํ•™์˜์žฌ๊ต์œก ๋งฅ๋ฝ์—์„œ ์—ฐ๊ตฌ์ฐธ์—ฌ์ž๋“ค์€ ์“ธ๋ชจ์žˆ๋Š” ๊ฒฐ๊ณผ๋ฅผ ๋‚ด์•ผ ํ•œ๋‹ค๋Š” ์••๋ฐ•์— ์‹œ๋‹ฌ๋ฆฌ๋ฉฐ ์ž์‹ ์˜ ๋ฌธ์ œ ํ•ด๊ฒฐ ์—ญ๋Ÿ‰์„ ๋ฐœํœ˜ํ•˜๋Š” ํ™œ๋™์—๋งŒ ๋งค๋‹ฌ๋ ค ์™”๋‹ค. ์žฅ์ฐจ ๊ณผํ•™ ๋ถ„์•ผ๋ฅผ ์„ ๋„ํ•ด์•ผ ํ•  ๊ณผํ•™์˜์žฌ ํ•™์ƒ๋“ค์—๊ฒŒ๋Š” ์™ธ๋ถ€๋กœ๋ถ€ํ„ฐ ์ฃผ์–ด์ง„ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ๋ณด๋‹ค๋Š” ์Šค์Šค๋กœ ๋…์ฐฝ์ ์ธ ๋ฌธ์ œ๋ฅผ ์ƒ์„ฑํ•˜๋Š” ๊ฒฝํ—˜์ด ์ค‘์š”ํ•˜๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ๊ณผํ•™์˜์žฌ๊ต์œก์€ ์“ธ๋ชจ์— ๋Œ€ํ•œ ์ง‘์ฐฉ์—์„œ ๋ฒ—์–ด๋‚˜ ํ•™์ƒ๋“ค์ด ๋ถˆํ™•์‹ค์„ฑ์„ ์ฆ๊ธธ ์ˆ˜ ์žˆ๋Š” ๊ต์œก์  ํ™˜๊ฒฝ ์กฐ์„ฑ์— ๊ด€์‹ฌ์„ ์Ÿ์„ ํ•„์š”๊ฐ€ ์žˆ๋‹ค.This study started as a curiosity about students who actively participated in Science Gifted Education Institute(SGEI) during the preparation period for admission, despite the notion that completing SGEI does not really help with high school admissions. The purpose of this study is to systematically understand the high school admissions situation from their experience and to find suggestions for better science gifted education by reconstructing the intersection of high school admissions and the SGEI education. To this end, we researched educational life history that faithfully describes the life experiences of each research participant in the context of education and shows macroscopic socio-cultural and historical contexts together. There were five science gifted students who participated in the study who trained in the Seoul National University SGEI Chemistry Division in 2015 and 2016. These students participated in Science Gifted Education Institute training while preparing for admissions to the Science Academy, Science High School, and Autonomous Private High School. In particular, they were actively involved in SGEI's inquiry activities when they were in the ninth grade when high school admission was being conducted, so that they achieved the best results in the national research achievement presentation contest. The characteristics of SGEI students' high school admissions processes were examined individually. The first participant, Rion, went to cram school since elementary school to prepare for high school admissions. He wished to go to medical school in the future, but she did not pass the Science Academy admissions and subsequently shocked everyone by dropping out of the first screening at the Science High School admissions. The second participant, Jaehyeok, hoped that he would attend the Science Academy as his SGEI friends were preparing for that school. His parents believed that their son wanted to study without the help of private tutoring, which was incorrect as he suffered psychological stress when he could not attend cram school like his other friends. He dropped out of Science Academy admissions, but later applied and passed the exam for the Autonomous Private High School. The third participant, Ingyu, wanted to study according to a special curriculum even when he entered high school, just as at his international middle school. With a good performance at the Olympiad, he gained enough confidence to apply for Science Academy admissions, but did not make it. Afterwards, his parents strongly urged private tutoring, which caused conflict in their relationship. The conflict continued even after he passed the Autonomous Private High School admissions. The fourth participant, Seongmin, attended an international middle school recommended by his father where he won several science related competitions. At the cram school, he studied mathematics and science in depth while preparing for the Olympiad. After the Olympiad, he achieved admissions to the Science Academy. The fifth participant, Youngwoo, received a lot of academic help since he had two older sisters who went to prestigious universities. He actively studied at home and at cram school for challenging content that could not be learned at school. He gained admissions to the Science Academy by preparing at cram school for a relatively short period of time. In order to systematically understand the high school admissions structure, the situational structure was examined according to the analysis framework of "micro situation-(mediated situation)-macro situation". In the micro situation, study participants had 'high learning ability and academic enthusiasm,' 'highly-educated parents,' and 'puberty.' In the macro situation, study participants had 'sectarianism,' 'meritocracy,' and 'neoliberalism'. In addition, mediated situations include 'schools where test scores and outcomes work as power,' 'cram schools that stimulate and relieve anxiety at the same time,' 'families that emphasize sectarianism explicitly and implicitly,' and 'dual peer relationship between differentiation and homogenization.' Although this situational structure was a factor that can be extracted most commonly for research participants, specific aspects were different. Furthermore, in the high school admissions process, SGEI analyzed what it meant to study participants as it acted as a 'shelter' for students to share their interests with ease, away from cramped schools where it is difficult to achieve intellectual stimulation or cram schools with intense competition. In addition, they were able to experience experiments that connect the science knowledge they learned with the real world. Through this, SGEI played the role of a 'laboratory' that can develop scientific identity. Lastly, by systematically directing inquiry activities from university professors and assistants, it also showed the role of an 'educational institute' to build a specification that is different from other competitors who are also preparing for the written exam. Finally, we discuss the implications of these analyses for science gifted education. The current high school admissions selects skilled students who have achieved the best grades on the test by moving out of this meritocracy paradigm and selecting students who can positively interact with the teaching provided by each gifted education institute. Additionally, as revealed in the high school admissions process, gifted education has so far emphasized theoretical and abstract thinking at the individual level. However, from the experience of research participants, we can see that observations and experiments that create phenomenon can promote 'studying together.' Until now, in the context of science gifted education, research participants have been forced to tackle problem solving activities under pressure to produce useful results. For science gifted students who need to lead the field of science in the future, it is important to create original problems on their own rather than solving existing problems. To this end, science gifted education needs to focus on creating an educational environment where students can enjoy uncertainty rather than obsess over usefulness.โ… . ์„œ๋ก  1 1. ์—ฐ๊ตฌ์˜ ํ•„์š”์„ฑ ๋ฐ ๋ชฉ์  1 2. ์—ฐ๊ตฌ ๋ฌธ์ œ 8 3. ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• 9 1) ๊ต์œก์ƒ์• ์‚ฌ ์—ฐ๊ตฌ 9 2) ์—ฐ๊ตฌ์ฐธ์—ฌ์ž 11 3) ์ž๋ฃŒ ๊ตฌ์„ฑ ๋ฐ ๋ถ„์„ 14 4) ์—ฐ๊ตฌ์˜ ๋ฒ”์œ„์™€ ํ•œ๊ณ„ 15 โ…ก. ์ด๋ก ์  ๋ฐฐ๊ฒฝ ๋ฐ ์„ ํ–‰์—ฐ๊ตฌ 17 1. ๊ณ ๋“ฑํ•™๊ต ์ฒด์ œ ๋ณ€์ฒœ๊ณผ ์ง„ํ•™ ๊ฒฐ์ •์š”์ธ 17 1) ๊ณ ๋“ฑํ•™๊ต ์ฒด์ œ์™€ ์ž…ํ•™์ „ํ˜•์˜ ๋ณ€์ฒœ 17 2) ๊ณ ๋“ฑํ•™๊ต ์ง„ํ•™์— ์˜ํ–ฅ์„ ์ฃผ๋Š” ์š”์ธ 23 2. ์˜์žฌ์„ฑ ๊ฐœ๋…๊ณผ ์šฐ๋ฆฌ๋‚˜๋ผ ๊ณผํ•™์˜์žฌ๊ต์œก 30 1) ์˜์žฌ์„ฑ ๊ฐœ๋…์˜ ๋ณ€์ฒœ 30 2) ์šฐ๋ฆฌ๋‚˜๋ผ ๊ณผํ•™์˜์žฌ๊ต์œก์˜ ์—ญ์‚ฌ 35 3. ์˜์žฌ์˜ ์‚ถ์— ๊ด€ํ•œ ์งˆ์ ์—ฐ๊ตฌ ๊ฐœ๊ด€ 40 1) ์˜๋ฏธ๊ถŒ ์˜์žฌ์˜ ์‚ถ์— ๊ด€ํ•œ ์งˆ์ ์—ฐ๊ตฌ 40 2) ์šฐ๋ฆฌ๋‚˜๋ผ ๊ณผํ•™์˜์žฌ์˜ ์‚ถ์— ๊ด€ํ•œ ์งˆ์ ์—ฐ๊ตฌ 44 โ…ข. ๊ณผํ•™์˜์žฌ๋“ค์˜ ๊ณ ๋“ฑํ•™๊ต ์ž…์‹œ ๊ณผ์ • 49 1. ์—ฐ๊ตฌ์ฐธ์—ฌ์ž๋“ค์˜ ์ž…์‹œ ๊ณผ์ • ๊ฐœ๊ด€ 49 2. ์—ฐ๊ตฌ์ฐธ์—ฌ์ž๋“ค์˜ ๊ณผํ•™์˜์žฌ๊ต์œก์› ํ™œ๋™ 55 1) 2015ํ•™๋…„๋„ ์‹ฌํ™”๊ณผ์ •: ์ค‘ํ•™๊ต 2ํ•™๋…„ ์‹œ๊ธฐ 55 1) 2016ํ•™๋…„๋„ ์‚ฌ์‚ฌ๊ณผ์ •: ์ค‘ํ•™๊ต 3ํ•™๋…„ ์‹œ๊ธฐ 66 3. ๊น€๋ฆฌ์˜จ ์ด์•ผ๊ธฐ: ์ธ์ƒ์˜ ๋งˆ์ง€๋ง‰์€ ๋Œ€ํ•™์ด๋‹ค 70 4. ๋ฐ•์žฌํ˜ ์ด์•ผ๊ธฐ: ํŠน๋ชฉ๊ณ ๊ฐ€ ๋ฉ‹์ ธ ๋ณด์ผ ๊ฒƒ ๊ฐ™์•„์„œ 82 5. ์ตœ์ธ๊ทœ ์ด์•ผ๊ธฐ: ๋‚ด ํ•  ์ผ์€ ๋‚ด๊ฐ€ ํ•˜๊ฒŒ ์ข€ ๋†”๋‘ฌ๋ผ 94 6. ์•ˆ์„ฑ๋ฏผ ์ด์•ผ๊ธฐ: ๋ญ”๊ฐ€ ์‚ฌ๊ธฐ๋ฅผ ๋‹นํ•œ ๊ธฐ๋ถ„์ด์—์š” 105 7. ์•ˆ์˜์šฐ ์ด์•ผ๊ธฐ: ํ•™๊ต์—์„œ ๋ชป ๋ฐฐ์šฐ๋Š” ๊ฒŒ ๋” ์žฌ๋ฐŒ์ฃ  116 โ…ฃ. ๊ณผํ•™์˜์žฌ๋“ค์˜ ๊ณ ๋“ฑํ•™๊ต ์ž…์‹œ ๊ตฌ์กฐ 127 1. ๊ณ ๋“ฑํ•™๊ต ์ž…์‹œ์˜ ์ƒํ™ฉ์  ๊ตฌ์กฐ 127 1) ์†Œ์ƒํ™ฉ 127 (1) ๋†’์€ ํ•™์Šต ๋Šฅ๋ ฅ๊ณผ ํ•™๊ตฌ์—ด 128 (2) ๊ณ ํ•™๋ ฅ ๋ถ€๋ชจ์˜ ์กด์žฌ 132 (3) ์ƒ๊ฐ์ด ๋งŽ์•„์ง€๋Š” ์‚ฌ์ถ˜๊ธฐ 136 2) ๋Œ€์ƒํ™ฉ 139 (1) ํ•™๋ฒŒ์ฃผ์˜: ์œ„๊ณ„์„œ์—ด์˜ ํ™•์‚ฐ 139 (2) ์‹ค๋ ฅ์ฃผ์˜: ์‹ค๋ ฅ์— ๋”ฐ๋ฅธ ๊ธฐํšŒ ๋ฐฐ๋ถ„๊ณผ ๋…ธ๋ ฅ ์ค‘์‹œ 143 (3) ์‹ ์ž์œ ์ฃผ์˜: ๊ณ ๊ต๋‹ค์–‘ํ™”์™€ ์ˆ˜๋Ÿ‰ํ™”์˜ ์ง€๋ฐฐ 146 3) ๋งค๊ฐœ์ƒํ™ฉ 150 (1) ์„ฑ์ ๊ณผ ์„ฑ๊ณผ๊ฐ€ ๊ถŒ๋ ฅ์œผ๋กœ ์ž‘๋™ํ•˜๋Š” ํ•™๊ต 150 (2) ๋ถˆ์•ˆ๊ฐ์„ ์ž๊ทนํ•จ๊ณผ ๋™์‹œ์— ํ•ด์†Œํ•ด์ฃผ๋Š” ํ•™์› 154 (3) ๋ช…์‹œ์ /์•”๋ฌต์ ์œผ๋กœ ํ•™๋ฒŒ์„ ๋น„๊ตํ•˜๋Š” ๊ฐ€์กฑ 161 (4) ์ฐจ๋ณ„ํ™”์™€ ๋™์งˆํ™”์˜ ์ด์ค‘์  ๋˜๋ž˜ ๊ด€๊ณ„ 164 2. ๊ณ ๋“ฑํ•™๊ต ์ž…์‹œ ๊ณผ์ •์—์„œ ๊ณผํ•™์˜์žฌ๊ต์œก์›์˜ ์—ญํ•  169 1) ์ง€์นœ ๋ชธ๊ณผ ๋งˆ์Œ์„ ๋‹ฌ๋ž  ์ˆ˜ ์žˆ๋Š” ์‰ผํ„ฐ 169 2) ์‹ค์ œ ์„ธ๊ณ„๋ฅผ ํƒ๊ตฌํ•  ์ˆ˜ ์žˆ๋Š” ์‹คํ—˜์‹ค 173 3) ์ŠคํŽ™์„ ์Œ“์„ ์ˆ˜ ์žˆ๋Š” ๊ต์œก๊ธฐ๊ด€ 177 โ…ค. ํ•ด์„ ๋ฐ ๋…ผ์˜ 181 1. ์‹œํ—˜์— ์ข…์†๋œ ํ‰๊ฐ€ vs. ๊ต์œก์ด ์‚ด์•„์žˆ๋Š” ํ‰๊ฐ€ 182 2. ์ทจ๋“์„ ์œ„ํ•œ ๊ณต๋ถ€ vs. ์ฒด๋“์„ ํ–ฅํ•œ ๊ณต๋ถ€ 187 3. ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๋Š” ๊ต์œก vs. ๋ฌธ์ œ๋ฅผ ์ƒ์„ฑํ•˜๋Š” ๊ต์œก 192 โ…ฅ. ์š”์•ฝ ๋ฐ ๊ฒฐ๋ก  198 1. ์š”์•ฝ 198 2. ๊ฒฐ๋ก  209 ์ฐธ๊ณ ๋ฌธํ—Œ 212 Abstract 223 ๋ถ€๋ก 228Docto

    3D Numerical Analysis Algorithm for Dam Break Flood Wave

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๋†์—…์ƒ๋ช…๊ณผํ•™๋Œ€ํ•™ ์ƒํƒœ์กฐ๊ฒฝยท์ง€์—ญ์‹œ์Šคํ…œ๊ณตํ•™๋ถ€, 2020. 8. ์ตœ์›.2018๋…„ ๊ธฐ์ค€์œผ๋กœ ๊ตญ๋‚ด 17,240๊ฐœ์˜ ์ €์ˆ˜์ง€ ์ค‘ 81.2%๊ฐ€ ์ถ•์กฐ ํ›„ 50๋…„์ด ์ง€๋‚œ ๋…ธํ›„ํ™” ์‹œ์„ค๋ฌผ์ด๋ฉฐ, ์ตœ๊ทผ ๊ธฐํ›„๋ณ€ํ™”๋กœ ์ธํ•ด ๊ธฐ์ƒ์žฌํ•ด๊ฐ€ ์ฆ๊ฐ€ํ•˜๋ฉด์„œ ์ €์ˆ˜์ง€์˜ ๋ถ•๊ดด ์‚ฌ๊ณ ๊ฐ€ ๋นˆ๋ฒˆํžˆ ๋ฐœ์ƒํ•˜๊ณ  ์žˆ๋‹ค. ํ˜„์žฌ ์ €์ˆ˜์ง€์˜ ๋ถ•๊ดด๋กœ ์ธํ•œ ํ”ผํ•ด๋ฅผ ์‚ฌ์ „์— ์˜ˆ์ธกํ•˜๊ณ , ๋น„์ƒ๋Œ€์ฒ˜๊ณ„ํš ์ˆ˜๋ฆฝ์„ ์œ„ํ•ด ์ผ๋ถ€ ํฐ ๊ทœ๋ชจ์˜ ์ €์ˆ˜์ง€์— ํ•œํ•ด ํ™์ˆ˜์œ„ํ—˜์ง€๋„๊ฐ€ ๊ตฌ์ถ•๋˜์–ด ๊ด€๋ฆฌ๋˜๊ณ  ์žˆ์œผ๋‚˜ ์‹ค์ œ ์ง€ํ˜•ํŠน์„ฑ๊ณผ ์œ ์ฒด์˜ ๋‚œ๋ฅ˜ ํŠน์„ฑ์„ ์ถฉ๋ถ„ํžˆ ๋ฐ˜์˜ํ•˜์ง€ ๋ชปํ•˜๊ณ  ์žˆ๋‹ค. ํŠนํžˆ, ํ™์ˆ˜ํŒŒ ํ•ด์„ ์‹œ ์ง€ํ˜•์กฐ๊ฑด์— ๋”ฐ๋ฅธ ์œ ์ฒด์˜ ๋™์—ญํ•™์  ๋ณ€ํ™”๋Š” ํ™์ˆ˜ํŒŒ ๋„๋‹ฌ ๋ฒ”์œ„ ์‚ฐ์ •์— ์ง€๋Œ€ํ•œ ์˜ํ–ฅ์„ ๋ฏธ์น˜๊ธฐ์—, ์ด๋ฅผ ๊ณ ๋ คํ•œ ํ™์ˆ˜์œ„ํ—˜์ง€๋„ ๊ตฌ์ถ•์ด ์ ˆ์‹คํžˆ ์š”๊ตฌ๋œ๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ €์ˆ˜์ง€์˜ ๋ถ•๊ดด๋กœ ์ธํ•ด ๋ฐœ์ƒํ•˜๋Š” ํ•˜๋ฅ˜๋ถ€์˜ ํ™์ˆ˜ํŒŒ ๋„๋‹ฌ ๋ฒ”์œ„๋ฅผ ์ •๋ฐ€ํ•˜๊ฒŒ ์˜ˆ์ธกํ•˜๋„๋ก UAV-SfM ๊ธฐ๋ฒ•๊ณผ 3์ฐจ์› ์ˆ˜์น˜ํ•ด์„์„ ์—ฐ๊ณ„ํ•œ ํ™์ˆ˜ํŒŒ ํ•ด์„ ๋ฐฉ๋ฒ•์„ ๊ฐœ๋ฐœํ•˜๊ณ , ์ด๋ฅผ ์ด์šฉํ•œ ๊ฒฐ๊ณผ์™€ ์‹ค์ œ ํ™์ˆ˜ํŒŒ ๋„๋‹ฌ ๋ฒ”์œ„๋ฅผ ๋Œ€์กฐํ•˜์—ฌ ์˜ˆ์ธก ์ •ํ™•์„ฑ์„ ํ‰๊ฐ€ํ•˜์˜€๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ์ฒซ์งธ, 2์ฐจ์› ์—ฐ์† ์ด๋ฏธ์ง€์—์„œ 3์ฐจ์› ๊ตฌ์กฐ๋ฅผ ์ถ”์ •ํ•˜๋Š” SfM ๊ธฐ๋ฒ•๊ณผ ์ง€ํ˜•์˜ ๊ทผ์ ‘ ์ด๋ฏธ์ง€ ํš๋“์— ํšจ๊ณผ์ ์ธ UAV ํ•ญ๊ณต์ดฌ์˜ ๋ฐฉ๋ฒ•์„ ์—ฐ๊ณ„ํ•œ ์ง€ํ˜•์ž๋ฃŒ ๊ตฌ์ถ•๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•˜์˜€๋‹ค. UAV ์ดฌ์˜ ์กฐ๊ฑด์— ๋”ฐ๋ฅธ ์ ๊ตฐ ๋ชจ๋ธ์˜ ์ง€ํ˜• ์žฌํ˜„์œจ์ด ๋ถ„์„๋˜์—ˆ์œผ๋ฉฐ, ์ดฌ์˜๋ฉด์ ๊ณผ ์ˆ˜์น˜๋ชจ๋ธ์˜ ์ˆ˜๋ ด์„ฑ์„ ๊ณ ๋ คํ•˜์˜€์„ ๋•Œ, 2.5 cm/pixel ๊ณต๊ฐ„ํ•ด์ƒ๋„ ๋ฐ ์ข…์ค‘๋ณต๋„ 80%, ํšก์ค‘๋ณต๋„ 72% ์กฐ๊ฑด์—์„œ 55ยฐ ์ดฌ์˜ ๊ฐ ์กฐ๊ฑด์ผ ๋•Œ ์ตœ์  ์ดฌ์˜ ์กฐ๊ฑด์ธ ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ์œผ๋ฉฐ, ์ด๋ฅผ ํ†ตํ•ด ๊ตฌ์ถ•๋œ ์ง€ํ˜•์ž๋ฃŒ๋Š” ๊ฐ ํ™์ˆ˜ํŒŒ ํ•ด์„ ๋ชจ๋ธ์˜ ์ง€ํ˜•์ž๋ฃŒ๋กœ ์ž…๋ ฅ๋˜์—ˆ๋‹ค. ๋‘˜์งธ, ๋ถ•๊ดด ์ง์ „์˜ ์ €์ˆ˜์ง€ ์ˆ˜์œ„์™€ ํ•˜์ฒœ์˜ ๊ธฐ์ €์ˆ˜์œ„๋ฅผ ๊ณ ๋ คํ•˜๊ธฐ ์œ„ํ•ด ํ•˜๋„ ๊ตฌ๊ฐ„๋ณ„ ์œ ์ž…๋Ÿ‰์„ ์‚ฐ์ •ํ•˜๊ณ  ์ด๋ฅผ ์ง€์ ๋ณ„ ๊ฒฝ๊ณ„์กฐ๊ฑด์œผ๋กœ ์„ค์ •ํ•˜์˜€๋‹ค. ์…‹์งธ, ์ €์ˆ˜์ง€ ๋ถ•๊ดด ์›์ธ, ๋ถ•๊ดด ์ง€์†์‹œ๊ฐ„ ๋ฐ ํ˜•์ƒ ๋“ฑ์˜ ๋ถ•๊ดด ํŠน์„ฑ์„ ๊ฒ€ํ† ํ•˜์—ฌ, ๋ถ•๊ดด์— ๋”ฐ๋ฅธ ๋ฐฉ๋ฅ˜๋Ÿ‰์„ ๊ฒ€ํ† ํ•˜์˜€๊ณ , ์ €์ˆ˜์ง€ ๋ถ•๊ดด ์ง์ „ ์ˆ˜์œ„์— ๋”ฐ๋ฅธ ๋ชจ๋ธ๋ณ„ ํ™์ˆ˜ํŒŒ ํ•ด์„ ๊ฒฐ๊ณผ๋ฅผ ๋น„๊ตํ•˜์˜€๋‹ค. ๊ทธ ๊ฒฐ๊ณผ, 1์ฐจ์› ๋ชจ๋ธ์€ ํ™์ˆ˜ํŒŒ ๋„๋‹ฌ ๋ฒ”์œ„๊ฐ€ ๊ณผ๋„ํ•˜๊ฒŒ ์‚ฐ์ •๋˜์—ˆ์œผ๋ฉฐ, ์ด๋Š” ์œ ์ฒด์˜ ์ˆ˜์œ„ ์ƒ์Šน์ด ํšก๋‹จ๋ฉด๋„๋ณ„ ๋‹จ๋ฐฉํ–ฅ์œผ๋กœ๋งŒ ํ•ด์„๋˜๋Š” ํ•œ๊ณ„์  ๋•Œ๋ฌธ์ธ ๊ฒƒ์œผ๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ์ด์— ๋”ฐ๋ผ 1์ฐจ์› ๋ชจ๋ธ์€ ์‹œ๊ฐ„์— ๋”ฐ๋ฅธ ์žฌ๋‚ด์ง€์˜ ํ™์ˆ˜ํŒŒ ๋„๋‹ฌ ํ”์  ํ™•์ธ์ด ๋ถˆ๊ฐ€๋Šฅํ•˜๋‹ค๊ณ  ํŒ๋‹จ๋˜์—ˆ๋‹ค. 2์ฐจ์› ๋ชจ๋ธ์˜ ๊ฒฝ์šฐ 2์ฐจ์› ํ”ฝ์…€์— ์ตœ์ƒ๋‹จ ๊ณ ๋„๊ฐ’์ด ์ž…๋ ฅ๋œ ์ˆ˜์น˜ํ‘œ๋ฉด๋ชจ๋ธ์„ ์ง€ํ˜•์ž๋ฃŒ๋กœ ์‚ฌ์šฉํ•˜๊ณ  ์žˆ์–ด, ์œ ์ฒด ํ๋ฆ„์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์ˆ˜๋กœ์˜ ๋ณด์ •์ž‘์—…์ด ๋ฐ˜๋“œ์‹œ ํ•„์š”ํ•˜์˜€์œผ๋ฉฐ, ์œ„์–ด ๊ณ„์ˆ˜์˜ ๊ฒฝ์šฐ๋Š” ๊ฒฝํ—˜์ ์ธ ์ž…๋ ฅ๊ฐ’์ด ์š”๊ตฌ๋˜์–ด ์ •ํ™•ํ•œ ๋ชจ์˜๋ฅผ ์œ„ํ•ด์„œ๋Š” ์ˆ˜์ฐจ๋ก€ ๋ฐ˜๋ณตํ•ด์„์ด ์š”๊ตฌ๋˜์—ˆ๋‹ค. ์ตœ์ข… ์‚ฐ์ •๋œ ํ™์ˆ˜ํŒŒ ํ•ด์„ ๊ฒฐ๊ณผ๋Š” ์‹ค์ œ ๋Œ€๋น„ 57%์˜ ์œ ์‚ฌ๋„๋ฅผ ๋ณด์˜€์œผ๋ฉฐ, ์ด๋Š” 2์ฐจ์› ๋‚œ๋ฅ˜ ๊ทผ์‚ฌ ๋ชจ๋ธ์˜ ๋™์—ญํ•™์  ํ•ด์„ ํ•œ๊ณ„๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. 3์ฐจ์› ๋ชจ๋ธ์˜ ๊ฒฝ์šฐ ์ง€ํ˜•์˜ ๋ณด์ •์ž‘์—…์ด ์ตœ์†Œํ™”๋˜๊ณ , 2์ฐจ์› ๋ชจ๋ธ๊ณผ ๋‹ฌ๋ฆฌ ๊ณ„์ˆ˜ ๊ฒฐ์ •์„ ์œ„ํ•œ ๋ฐ˜๋ณตํ•ด์„๋„ ๋ถˆํ•„์š” ํ•˜์˜€์œผ๋ฉฐ, ์‹ค์ œ ํ™์ˆ˜ํŒŒ ๋„๋‹ฌ ๋ฒ”์œ„ ๋Œ€๋น„ 95%์˜ ์œ ์‚ฌ๋„๋ฅผ ๋ณด์—ฌ ๋ชจ๋ธ์˜ ํ•ด์„ ์ •ํ™•์„ฑ์ด ๋†’๊ฒŒ ํ‰๊ฐ€๋˜์—ˆ๋‹ค. ์ถ”๊ฐ€๋กœ ์ œ์ฒด์˜ ํŒŒ์ดํ•‘ ๋ถ•๊ดด ์‹œ๋‚˜๋ฆฌ์˜ค ์ˆ˜ํ–‰ ๊ฒฐ๊ณผ๋Š” ์ฆ‰์‹œ ๋ถ•๊ดด ์‹œ์™€ ๋น„๊ตํ•˜์—ฌ ํ™์ˆ˜ํŒŒ ํ•ด์„ ์ •ํ™•์„ฑ์ด ๋‚ฎ๊ฒŒ ๋‚˜ํƒ€๋‚ฌ์œผ๋ฉฐ, ์ด๋ฅผ ํ†ตํ•ด ์—ฐ๊ตฌ๋Œ€์ƒ ์ €์ˆ˜์ง€์˜ ์ œ์ฒด๋Š” ์ฆ‰์‹œ ๋ถ•๊ดด๋ฅผ ์ผ์œผ์ผฐ์„ ๊ฒƒ์œผ๋กœ ์ถ”์ •๋˜์—ˆ๋‹ค. ๋˜ํ•œ ์ถ”ํ›„ ๋” ํฐ ๊ทœ๋ชจ์˜ ์ €์ˆ˜์ง€์— ๋Œ€ํ•œ ๋ถ•๊ดด ํ™์ˆ˜ํŒŒ ํ•ด์„ ์‹œ ๊ธฐ์กด ๋ชจ๋ธ๊ณผ ๋” ํฐ ์ฐจ์ด๋ฅผ ๋ณด์ผ ๊ฒƒ์œผ๋กœ ์‚ฌ๋ฃŒ๋œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๊ฒฐ๊ณผ๋ฅผ ํ† ๋Œ€๋กœ ๊ธฐ์กด ์ˆ˜์น˜๋ชจ๋ธ์˜ ํ•œ๊ณ„์ ์„ ๊ตฌ๋ช…ํ•˜์˜€๊ณ , ์ƒˆ๋กœ์šด ํ•ด์„ ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•˜์—ฌ ์ €์ˆ˜์ง€ ๊ด€๋ฆฌ ์šฐ์„ ์ˆœ์œ„๋ฅผ ์œ„ํ•œ ์ •ํ™•ํ•œ ํ™์ˆ˜์œ„ํ—˜์ง€๋„ ๊ตฌ์ถ• ๋ฐฉ์•ˆ ๋งˆ๋ จ์— ๊ธฐ์—ฌํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ์‚ฌ๋ฃŒ๋œ๋‹ค.As of 2018, 81.2% of the 17,240 reservoirs in Korea are aging facilities which are 50 years after construction. Reservoir failure often occurs since climate change and meteorological disasters recently have increased. For that reason, the flood hazard maps were developed for some enormous dams to rank maintenance priority, but they reflect few geological characteristics and fluid dynamic attributes. When the flood is numerically analyzed, dynamic changes of fluids by geological characteristics have enormous impacts on estimating wave travels. Therefore, new reservoir failure model was conducted in this study to precisely predict downstream flood damage due to the failure of agricultural reservoirs. The prediction accuracy of the model was assessed by comparing the actual wave travel domain with the result. Limits of the previous model and novel flood wave analysis prediction method were presented by comparing the new model with the previous model. First, Structure from Motion (SfM) method, getting the 3D structure from 2D continuous images, and Unmanned Aerial Vehicle (UAV) method effective to gain close-up images were combined to develop topological data. The topological reproducibility rate of point cloud model according to photographing condition was examined. The optimum photography was gained when the resolution was 2.5 cm/pixel, the frontal overlap was 80%, side overlap was 72%, and the photography angle was 55ยฐ. Second, the inflow hydrograph of each stream section was estimated and set as boundary conditions of each point, to compare reservoir water level about to failure with the baseflow of the stream. Third, reservoir failure cause, failure duration, and breach shape were examined to analyze breach discharge hydrograph. Flood wave travels of each model according to reservoir water level about to failure were compared. The 1D model estimated the overrated flood wave travel domain calculated because the flood wave was interpreted only 1D propagation. Therefore, the 1D model could not calculate the flood wave travel domain in receptors. The 2D model used the digital surface model as topological data, combined 2D pixels and the highest elevation of each points, so streamline calibration was required. Several calculations were required to precisely make model, due to weir coefficient was empirical value. The 2D model result was 57% similar to the actual flood wave travel domain, which represents the dynamic analysis limit of the 2D model. 3D model required a few calibration tasks for some area and no repetitive calculation to set coefficients. The 3D model result was 95% similar to the actual flood wave travel domain, which represents the great accuracy of the model. Piping breach scenario result of the dam was less similar to the actual flood wave travel domain, so it could be assumed that the dam was breached immediately. In addition, it is considered that the analysis of the dam break flood wave for a large reservoir will show a greater difference from the existing model. Limits of the previous numerical models were determined to base on this study, and a new methodology was presented to make precise flood risk maps to rank reservoir maintenance priority.์ œ 1 ์žฅ ์„œ ๋ก  1 1.1. ์—ฐ๊ตฌ๋ฐฐ๊ฒฝ ๋ฐ ํ•„์š”์„ฑ 1 1.2. ์—ฐ๊ตฌ๋ชฉ์  3 ์ œ 2 ์žฅ ์—ฐ๊ตฌ์‚ฌ 5 2.1. ์ €์ˆ˜์ง€ ๋ถ•๊ดด ์›์ธ ๋ฐ ํ”ผํ•ด 5 2.2. ์ €์ˆ˜์ง€ ๊ด€๋ฆฌ๋ฅผ ์œ„ํ•œ ํ™์ˆ˜์œ„ํ—˜์ง€๋„ ์ž‘์„ฑ 8 2.3. ์ง€ํ˜•์ž๋ฃŒ ๊ตฌ์ถ• 11 2.4. 3์ฐจ์› ์ˆ˜์น˜์œ ๋™ํ•ด์„ 13 ์ œ 3 ์žฅ ์žฌ๋ฃŒ ๋ฐ ๋ฐฉ๋ฒ• 15 3.1. ์—ฐ๊ตฌ ๋Œ€์ƒ 16 3.2. ์‹ค์ œ ํ™์ˆ˜ํŒŒ ํ˜„์žฅ ์กฐ์‚ฌ 18 3.3. ์ง€ํ˜•์ž๋ฃŒ ๊ตฌ์ถ• 21 3.3.1. ์ง€ํ˜•์ž๋ฃŒ ๊ตฌ์ถ• ๊ธฐ๋ฒ• 23 3.3.2. ํ™์ˆ˜ํŒŒ ํ•ด์„์„ ์œ„ํ•œ ์ตœ์  ์ง€ํ˜•์ž๋ฃŒ ๊ตฌ์ถ• 27 3.4. ํ™์ˆ˜ํŒŒ ํ•ด์„์กฐ๊ฑด ์„ค์ • 33 3.4.1. ์œ ์—ญ ์œ ์ถœ๋Ÿ‰ ์‚ฐ์ • 33 3.4.2. ์ œ์ฒด ์›”๋ฅ˜ ์œ ๋ฌด ๊ฒ€ํ†  38 3.4.3. ๋ถ•๊ดด ์ง€์†์‹œ๊ฐ„ ๋ฐ ์ œ์ฒด ๋ถ•๊ดด ํ˜•์ƒ ์„ค์ • 38 3.4.4. ๋ถ•๊ดด ์‹œ๋‚˜๋ฆฌ์˜ค ์„ค์ • 42 3.5. ํ™์ˆ˜ํŒŒ ํ•ด์„ 44 3.5.1. 1์ฐจ์› ๋ชจ์˜ 44 3.5.2. 2์ฐจ์› ๋ชจ์˜ 48 3.5.3. 3์ฐจ์› ๋ชจ์˜ 53 ์ œ 4 ์žฅ ๊ฒฐ๊ณผ ๋ฐ ๊ณ ์ฐฐ 59 4.1. ์‹ค์ œ ํ™์ˆ˜ํŒŒ ๋„๋‹ฌ ํ”์  ์ง€๋„ ๊ตฌ์ถ• 59 4.2. ์ง€ํ˜•์ž๋ฃŒ ๊ตฌ์ถ• ๊ฒฐ๊ณผ 61 4.2.1. ์ตœ์  ์ดฌ์˜ ์กฐ๊ฑด ์„ ์ • 61 4.2.2. ๋Œ€์ƒ์ง€์—ญ ํ•ญ๊ณต์ดฌ์˜ ๋ฐ ์ ๊ตฐ ๋ชจ๋ธ ๊ตฌ์ถ• 69 4.2.3. ์ˆ˜์น˜๋ชจ๋ธ๋ณ„ ์ง€ํ˜•์ž๋ฃŒ ๊ตฌ์ถ• ๋ฐ ๋ณด์ • 71 4.3. ์ €์ˆ˜์ง€ ๋ถ•๊ดด ํ™์ˆ˜ํŒŒ ํ•ด์„์กฐ๊ฑด ๊ตฌ์ถ• 79 4.3.1. ๊ฒฝ๊ณ„์กฐ๊ฑด ์„ค์ • 79 4.3.2. ์ œ์ฒด ๋ถ•๊ดด ํŠน์„ฑ ๊ฒฐ์ • 84 4.3.3. ํ™์ˆ˜ํŒŒ ํ•ด์„ ์‹œ๋‚˜๋ฆฌ์˜ค 93 4.4. ์ €์ˆ˜์ง€ ๋ถ•๊ดด ํ™์ˆ˜ํŒŒ ํ•ด์„ ๊ฒฐ๊ณผ 95 4.4.1. 1์ฐจ์› ํ•ด์„ ๊ฒฐ๊ณผ 95 4.4.2. 2์ฐจ์› ํ•ด์„ ๊ฒฐ๊ณผ 97 4.4.3. 3์ฐจ์› ํ•ด์„ ๊ฒฐ๊ณผ 102 4.4.4. ๋ชจ๋ธ๋ณ„ ํ•ด์„ ์ •ํ™•๋„ ํ‰๊ฐ€ 104 ์ œ 5 ์žฅ ์š”์•ฝ ๋ฐ ๊ฒฐ๋ก  113 ์ฐธ ๊ณ  ๋ฌธ ํ—Œ 117 Abstract 129Maste

    Spin wave modes excited along magnetic domain walls and its application to magnetic logic operations

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์žฌ๋ฃŒ๊ณตํ•™๋ถ€, 2019. 2. ๊น€์ƒ๊ตญ.๋งˆ๊ทธ๋…ธ๋‹‰์Šค(Magnonics) ๋ถ„์•ผ์—์„œ, ์Šคํ•€ํŒŒ(spin-wave)๋Š” ์ •๋ณด ์ „๋‹ฌ์ฒด๋กœ ์‚ฌ์šฉ๋˜๋ฉฐ ํŒŒ๋™ ํŠน์„ฑ์„ ๊ธฐ๋ฐ˜์œผ๋กœ ์ž‘๋™ํ•  ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€๋˜์–ด ์™”๋‹ค. ํŠนํžˆ, ์Šคํ•€ํŒŒ์˜ ํŒŒ๋™ ํŠน์„ฑ์€ ์œ ๋งํ•˜์—ฌ ์Šคํ•€ํŒŒ ๋…ผ๋ฆฌ ๊ฒŒ์ดํŠธ๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•˜๋Š” ์žฅ์น˜(device)๋Š” ์ •๋ณด ์ฒ˜๋ฆฌ์— ์ ์šฉํ•˜๋Š”๋ฐ ์žˆ์–ด์„œ ๊ด€์‹ฌ์˜ ๋Œ€์ƒ์ด๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” 2 ์ฐจ์› ๋‚˜๋…ธ ํฌ๊ธฐ์˜ ๋„ํŒŒ๊ด€(waveguide)์—์„œ ์Šคํ•€ํŒŒ ์ „ํŒŒ(propagation)์˜ ์—๋„ˆ์ง€ ํšจ์œจ์ ์ธ ์ œ์–ด๋ฅผ ์œ„ํ•œ ์ƒˆ๋กœ์šด ๊ธฐ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค. ์ž๊ตฌ๋ฒฝ(magnetic domain wall)์— ๊ตญํ•œ๋œ ์Šคํ•€ํŒŒ ์ „ํŒŒ๋ฅผ ์œ ๋„ํ•˜์—ฌ ์Šคํ•€ํŒŒ๊ฐ€ ๋‹ค๋ฅธ ์ฑ„๋„(channel)๋กœ ์ „ํŒŒ๋  ์ˆ˜ ์žˆ์Œ์„ ๋ณด์ธ๋‹ค. ๋˜ํ•œ ๊ฐ•์ž์„ฑ(ferromagnetic) ํฌ๋กœ์Šค(cross) ๋„ํŒŒ๊ด€์„ ๊ธฐ๋ฐ˜์œผ๋กœ ์Šคํ•€ํŒŒ ๊ฐ„์˜ ์ค‘์ฒฉ ๋ฐ ๊ฐ„์„ญ ํ˜„์ƒ์„ ์ด์šฉํ•˜์—ฌ ๋‹ค์ˆ˜ ๊ฒŒ์ดํŠธ(majority gate) ๋™์ž‘์„ ๊ตฌํ˜„ํ•˜๋ฉฐ ์ž๊ธฐ์†Œ์šฉ๋Œ์ด(vortex)์˜ ๋น„์„ ํ˜• ํšŒ์ „ ์šด๋™(nonlinear gyration motion)์— ์˜ํ•œ ์Šคํ•€ํŒŒ ์‚ฐ๋ž€(scattering)์„ ์ดํ•ดํ•œ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ ์ž๊ธฐ์†Œ์šฉ๋Œ์ด์˜ ํšŒ์ „ ์šด๋™์„ ๊ณ ๋ คํ•˜์—ฌ ๊ฐ ๋„ํŒŒ๊ด€์œผ๋กœ ์‚ฐ๋ž€๋˜๋Š” ์Šคํ•€ํŒŒ ๊ฐ„์˜ ์œ„์ƒ ์ฐจ๋ฅผ ์กฐ์ ˆํ•จ์œผ๋กœ์จ, ๋‹ค์ˆ˜ ๊ฒŒ์ดํŠธ ๋™์ž‘์„ ๊ตฌํ˜„ํ•œ๋‹ค.In the field of magnonics, devices based on spin-wave logic gates are of considerable interest, as the wave character of spin waves holds promise for application to information-processing and high-efficiency computing platforms. In this study, a magnetic logic operation is presented along with an approach by which the spin wave can be propagated in a nano-sized magnonic waveguide. It is shown through micromagnetic simulation that the channeling of the localized spin wave in domain walls is realized in a specific type of nano-magnonic waveguide, which fact allows for the spatial superposition and interference of the confined spin-wave modes. The dynamics of the vortex generated in the proposed structure and the interaction of the spin wave with it are analyzed, and the scattering of the spin wave into the magnonic waveguide is demonstrated. The proposed concept features the utilization of the Damon-Eshbach spin-wave mode in modern wave-based logic devices and suggests a route by which the limitations of the previous approaches can be overcome. The present study not only proposes the operation mechanism underlying a majority gate function encoded in the phase of the transmitted spin waves, but also presents a library of logic gates as a function of amplitude.์ œ 1์žฅ ์„œ๋ก  1 ์ œ 2์žฅ ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ 4 2.1 ์ž๊ตฌ์™€ ์ž๊ตฌ๋ฒฝ 4 2.1.1 ์ž๊ตฌ์™€ ์ž๊ตฌ๋ฒฝ 4 2.1.2 ์ž๊ตฌ๋ฒฝ์˜ ์ข…๋ฅ˜ ๋ฐ ๊ตฌ์กฐ 7 2.2 ์Šคํ•€ํŒŒ 11 2.2.1 ์Šคํ•€ํŒŒ์˜ ๊ฐœ๋… ๋ฐ ์ข…๋ฅ˜ 13 2.2.2 ์Šคํ•€ํŒŒ์˜ ๋ฐœ์ƒ 16 2.2.3 ์Šคํ•€ํŒŒ์˜ ํŒŒ๋™์  ํŠน์„ฑ 18 2.2.4 ์Šคํ•€ํŒŒ์˜ ์‘์šฉ-๋…ผ๋ฆฌ ์—ฐ์‚ฐ 21 2.3 ๋ฏธ์†Œ์ž๊ธฐ ์ „์‚ฐ๋ชจ์‚ฌ 24 ์ œ 3์žฅ ์ž๊ตฌ๋ฒฝ์—์„œ์˜ ์Šคํ•€ํŒŒ ์ „๋‹ฌ 30 3.1 ๋‹จ์ž๊ตฌ์—์„œ์˜ ์Šคํ•€ํŒŒ ์ „๋‹ฌ 30 3.1.1 ์ „์‚ฐ๋ชจ์‚ฌ ์กฐ๊ฑด 30 3.1.2 ์Šคํ•€ํŒŒ ๋ชจ๋“œ 32 3.2 ์ž๊ตฌ๋ฒฝ์—์„œ์˜ ์Šคํ•€ํŒŒ ์ „๋‹ฌ 36 3.2.1 ์ „์‚ฐ๋ชจ์‚ฌ ์กฐ๊ฑด 36 3.2.2 ์Šคํ•€ํŒŒ ๋ชจ๋“œ 38 3.3 ์ž๊ตฌ๋ฒฝ ๊ธฐ๋ฐ˜ ํฌ๋กœ์Šค ๊ตฌ์กฐ์—์„œ ์Šคํ•€ํŒŒ ์ „๋‹ฌ 43 3.3.1 ์ „์‚ฐ๋ชจ์‚ฌ ์กฐ๊ฑด 43 3.3.2 ์Šคํ•€ํŒŒ ๋ชจ๋“œ 45 3.3.3 ์Šคํ•€ํŒŒ์™€ ์ž๊ธฐ์†Œ์šฉ๋Œ์ด ์ƒํ˜ธ์ž‘์šฉ 54 3.4 ์ž๊ตฌ๋ฒฝ ๊ธฐ๋ฐ˜ ํฌ๋กœ์Šค ๊ตฌ์กฐ์—์„œ์˜ ์‘์šฉ-๋…ผ๋ฆฌ ์—ฐ์‚ฐ 67 3.4.1 ๋‹ค์ˆ˜๊ฒŒ์ดํŠธ 67 3.4.2 ์ „์‚ฐ๋ชจ์‚ฌ ์กฐ๊ฑด 70 3.4.3 ๋‹ค์ˆ˜ ๊ฒŒ์ดํŠธ ๋™์ž‘ 73 ์ œ 4์žฅ ๊ฒฐ๋ก  75Maste

    5mm ์ดํ•˜์˜ ๊ณ ํ˜• ์„ฑ๋ถ„์„ ๊ฐ€์ง€๋Š” ์ง€์†์ ์ธ ํ ์•„๊ณ ํ˜• ๊ฒฐ์ ˆ

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ž„์ƒ์˜๊ณผํ•™๊ณผ, 2017. 2. ๊ตฌ์ง„๋ชจ.๋ชฉ์  : ์ด ์—ฐ๊ตฌ์˜ ๋ชฉ์ ์€ ๊ณ ํ˜• ์„ฑ๋ถ„์ด 5mm ์ดํ•˜์ธ ํ ์•„๊ณ ํ˜• ๊ฒฐ์ ˆ์˜ ์ž์—ฐ๊ฒฝ๊ณผ ํ™•์ธ๊ณผ, 5mm ์ดํ•˜์˜ ๊ณ ํ˜• ์„ฑ๋ถ„์„ ์ง€๋‹ˆ๋Š” ๋ถ€๋ถ„ ๊ณ ํ˜• ๊ฒฐ์ ˆ์— ๋Œ€ํ•˜์—ฌ ์„ฑ์žฅ์„ ๋ณด์ผ ๋•Œ๊นŒ์ง€ ๊ธฐ๋‹ค๋ฆฐ ํ›„ ์ˆ˜์ˆ ์  ์น˜๋ฃŒ๋ฅผ ํ•˜๋Š” ๊ฒƒ์ด ํ™˜์ž์˜ ์˜ˆํ›„์— ๋‚˜์œ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š”์ง€ ํ™•์ธํ•˜๋Š” ๊ฒƒ์ด๋‹ค. ๋ฐฉ๋ฒ• : 2005๋…„๋ถ€ํ„ฐ 2013๋…„๊นŒ์ง€ 213๋ช…์˜ ํ™˜์ž์—๊ฒŒ์„œ ์–ป์€ 5mm ์ดํ•˜์˜ ๊ณ ํ˜• ์„ฑ๋ถ„์„ ์ง€๋‹ˆ๋Š” ์•„๊ณ ํ˜• ๊ฒฐ์ ˆ๋“ค์„ ๋Œ€์ƒ์œผ๋กœ ๊ทธ ์ž์—ฐ๊ฒฝ๊ณผ๋ฅผ ํ™•์ธํ•˜๊ณ ์ž ํ•˜๋ฉฐ, ์ด์™€๋Š” ๋ณ„๊ฐœ๋กœ, 125๋ช…์˜ ํ™˜์ž์—๊ฒŒ์„œ ์–ป์€ 125๊ฐœ์˜ ๋ถ€๋ถ„ ๊ณ ํ˜• ๊ฒฐ์ ˆ์„ ๋Œ€์ƒ์œผ๋กœ ์„ฑ์žฅ์„ ๋ณด์ผ ๋•Œ๊นŒ์ง€ ๊ธฐ๋‹ค๋ฆฐ ํ›„ ์ˆ˜์ˆ ํ•˜๋Š” ๊ฒƒ์ด ์˜ˆํ›„์— ์–ด๋–ค ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š”์ง€ ์•Œ์•„๋ณด๊ณ ์ž ํ•œ๋‹ค. ์ด๋Š” Kaplan-Meier, Cox proportional hazard regression, ๊ทธ๋ฆฌ๊ณ  Cox-regression analysis๋ฅผ ์ด์šฉํ•˜์—ฌ ์ฆ๋ช…ํ•˜๊ณ ์ž ํ•œ๋‹ค. ๊ฒฐ๊ณผ : 213๊ฐœ์˜ ํ ์•„๊ณ ํ˜• ๊ฒฐ์ ˆ ์ค‘, 136๊ฐœ๋Š” ๊ฐ„์œ ๋ฆฌ์Œ์˜ ๊ฒฐ์ ˆ (์„ฑ์žฅ: 18๊ฐœ๋น„์„ฑ์žฅ: 118๊ฐœ)์ด์—ˆ๊ณ , 77๊ฐœ๋Š” 5mm์ดํ•˜์˜ ๊ณ ํ˜• ์„ฑ๋ถ„์„ ๊ฐ€์ง€๋Š” ๋ถ€๋ถ„ ๊ณ ํ˜• ๊ฒฐ์ ˆ (์„ฑ์žฅ: 24๊ฐœ๋น„์„ฑ์žฅ: 53๊ฐœ)์ด์—ˆ๋‹ค. ์ „์ฒด ํ™˜์ž๊ตฐ์—์„œ๋Š” ํ์•”์˜ ๋ณ‘๋ ฅ (p=0.001), ๊ณ ํ˜• ์„ฑ๋ถ„์˜ ์—ฌ๋ถ€ (p<0.001), ๊ฒฐ์ ˆ ํฌ๊ธฐ (p<0.001)๊ฐ€ ์„ฑ์žฅ์„ ์˜ˆ์ธกํ•˜๋Š” ์œ ์˜ํ•œ ์ธ์ž๋กœ ๋ฐํ˜€์กŒ๋‹ค. ๊ฒฐ์ ˆ์˜ ํฌ๊ธฐ๋Š” ๊ฐ„์œ ๋ฆฌ์Œ์˜ ๊ฒฐ์ ˆ (p<0.001)๊ณผ ๋ถ€๋ถ„ ๊ณ ํ˜• ๊ฒฐ์ ˆ (p=0.037)๋“ค์„ ๋‚˜๋ˆˆ ์ถ”๊ฐ€ ์—ฐ๊ตฌ์—์„œ๋„ ์œ ์˜ํ•œ ์„ฑ์žฅ์ธ์ž๋กœ ํŒ๋ช…๋˜์—ˆ๊ณ , ํ์•”์˜ ๋ณ‘๋ ฅ์€ ๋ถ€๋ถ„ ๊ณ ํ˜• ๊ฒฐ์ ˆ์—์„œ๋งŒ ๋˜ ๋‹ค๋ฅธ ์œ ์˜ํ•œ ์ธ์ž๋กœ ํŒ๋ช…๋˜์—ˆ๋‹ค (p=0.002). 10mm ์ด์ƒ์˜ ๊ฐ„์œ ๋ฆฌ์Œ์˜ ๊ฒฐ์ ˆ๋“ค๊ณผ 8mm ์ด์ƒ์˜ ๋ถ€๋ถ„ ๊ณ ํ˜• ๊ฒฐ์ ˆ๋“ค์€ 10mm ๋ฏธ๋งŒ์˜ ๊ฐ„์œ ๋ฆฌ์Œ์˜ ๊ฒฐ์ ˆ๋“ค๊ณผ 8mm ๋ฏธ๋งŒ์˜ ๋ถ€๋ถ„ ๊ณ ํ˜• ๊ฒฐ์ ˆ์— ๋น„ํ•ด ์œ ์˜ํ•˜๊ฒŒ ๋†’์€ ์„ฑ์žฅ ๋นˆ๋„๋ฅผ ๋ณด์˜€๋‹ค. ์˜ˆํ›„ ๊ด€๋ จ ์—ฐ๊ตฌ์— ์žˆ์–ด์„œ 5mm ๋ฏธ๋งŒ์˜ ๊ณ ํ˜• ์„ฑ๋ถ„์„ ๊ฐ€์ง€๋Š” 125๊ฐœ์˜ ๋ถ€๋ถ„ ๊ณ ํ˜• ๊ฒฐ์ ˆ ์ค‘์— 5๊ฐœ์˜ ์žฌ๋ฐœ์ด ์˜์‹ฌ๋˜๋Š” ์ฆ๋ก€๊ฐ€ ์žˆ์—ˆ์œผ๋‚˜, ์ด๋ฅผ ์‹ค์ œ ์žฌ๋ฐœ์ด๋ผ๊ณ  ํ•˜๋”๋ผ๋„ ๋ถ€๋ถ„ ๊ณ ํ˜• ๊ฒฐ์ ˆ์ด ์„ฑ์žฅ์„ ๋ณด์ธ ํ›„ ์ˆ˜์ˆ ์  ์ ˆ์ œ๋ฅผ ํ•˜๋Š” ๊ฒƒ์ด ๋ฐ”๋กœ ์ ˆ์ œ๋ฅผ ํ•˜๋Š” ๊ฒƒ์— ๋น„ํ•ด ๋ฌด์žฌ๋ฐœ ์ƒ์กด (p=0.485)๊ณผ ์ตœ์ข… ์ƒ์กด์œจ (p=0.185)์— ์žˆ์–ด์„œ ์˜๋ฏธ ์žˆ๋Š” ์ฐจ์ด๋ฅผ ๋ณด์ด์ง€ ์•Š์•˜๋‹ค. ๊ฒฐ๋ก  : 5mm ์ดํ•˜์˜ ๊ณ ํ˜• ์„ฑ๋ถ„์„ ๊ฐ€์ง€๋Š” ํ ์•„๊ณ ํ˜• ๊ฒฐ์ ˆ์˜ ์ž์—ฐ๊ฒฝ๊ณผ๋Š” ๊ณ ํ˜• ์„ฑ๋ถ„์˜ ์—ฌ๋ถ€, ๊ฒฐ์ ˆ์˜ ํฌ๊ธฐ์— ๋”ฐ๋ผ ์˜๋ฏธ ์žˆ๊ฒŒ ๋‹ฌ๋ž์œผ๋ฉฐ, ์ด๋ฅผ ์ด์šฉํ•˜์—ฌ ์ถ”์ ๊ฒ€์‚ฌ์˜ ๋ฐฉํ–ฅ์„ ๋‚˜๋ˆŒ ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€ํ•œ๋‹ค. ๋˜ํ•œ 5mm ์ดํ•˜์˜ ๊ณ ํ˜• ์„ฑ๋ถ„์„ ๊ฐ€์ง€๋Š” ๋ถ€๋ถ„ ๊ณ ํ˜• ๊ฒฐ์ ˆ์˜ ๊ฒฝ์šฐ, ์„ฑ์žฅ์„ ๋ณด์ธ ํ›„ ์ˆ˜์ˆ ์  ์ ˆ์ œ๋ฅผ ํ•˜๋”๋ผ๋„ ํ™˜์ž์˜ ์˜ˆํ›„์—๋Š” ๋‚˜์œ ์˜ํ–ฅ์„ ๋ผ์น˜์ง€ ์•Š๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค.Introduction 1 Materials and methods 3 Results 10 Discussion 16 References 22 Table and figures 26 Abstract in Korean 38Maste

    Hierarchical Subtopic Mining for Topic Annotation

    No full text
    1

    POSTECH at NTCIR-6: English Patent Retrieval Subtask

    No full text
    1
    • โ€ฆ
    corecore