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    ํ‰์ฐฝ๋™ ์ €์ธต ์ฃผ๊ฑฐ์ง€์—ญ ์žฅ์†Œ์„ฑ์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๋ฌผ๋ฆฌ์  ํ™˜๊ฒฝ ์š”์ธ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ํ™˜๊ฒฝ๋Œ€ํ•™์› : ํ™˜๊ฒฝ๊ณ„ํšํ•™๊ณผ, 2014. 8. ์ด์„์ •.์šฐ๋ฆฌ๋‚˜๋ผ์˜ ์ฃผ๊ฑฐ ๊ณต๊ธ‰ ํŒจ๋Ÿฌ๋‹ค์ž„์ด ์ด์ œ ์•„ํŒŒํŠธ ์ผ๋ณ€๋„๋ฅผ ๋„˜์–ด ๋‹ค์–‘์„ฑ์„ ์ถ”๊ตฌํ•˜๋ ค๋Š” ์›€์ง์ž„์ด ์ผ๊ณ  ์žˆ๋‹ค. ์•„ํŒŒํŠธ๋„ ์—ฌ์ „ํžˆ ์ธ๊ธฐ๊ฐ€ ์žˆ์ง€๋งŒ, ์ตœ๊ทผ์—๋Š” ์—ฌ๋Ÿฌ ๊ฐ€์ง€ ์ด์œ ๋กœ ์ €์ธต ์ฃผ๊ฑฐ์ง€์—ญ๋„ ์ฃผ๊ฑฐ์ง€๋กœ์„œ์˜ ๊ฐ€์น˜์— ๋งŽ์€ ์ด๋“ค์ด ์ฃผ๋ชฉํ•˜๊ณ  ์žˆ๋‹ค. ํ•˜์ง€๋งŒ ์šฐ๋ฆฌ๋‚˜๋ผ์˜ ๋งŽ์€ ์ €์ธต ์ฃผ๊ฑฐ์ง€์—ญ์ด ์ฒ˜ํ•œ ๋น„ํšจ์œจ์  ๊ณต๊ฐ„ ํ™œ์šฉ๊ณผ ์–‘์งˆ์˜ ์ฃผ๊ฑฐ ์‹œ์„ค ๋ถ€์กฑ ๋“ฑ์˜ ๋ฌธ์ œ๋Š” ์ €์ธต ์ฃผ๊ฑฐ์ง€์—ญ์˜ ์–ด๋– ํ•œ ๋ฌผ๋ฆฌ์  ํ™˜๊ฒฝ์ด ํ•„์š”ํ•œ๊ฐ€์— ๋Œ€ํ•œ ์˜๋ฌธ์„ ๋‚ณ๊ณ  ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” 5์ธต ์ด๋‚ด์˜ ๋‹จ๋…โ€ข๋‹ค์„ธ๋Œ€โ€ข๋‹ค๊ฐ€๊ตฌ ์ฃผํƒ์ด ๋ฐ€์ง‘ํ•œ ์ €์ธต์ฃผ๊ฑฐ์ง€์—ญ์—์„œ ๊ฑฐ์ฃผ์ž๋“ค์—๊ฒŒ ํ•ด๋‹น ์ฃผ๊ฑฐ์ง€์— ๋Œ€ํ•ด ๊ธ์ •์ ์ธ ์ธ์‹์ด๋‚˜ ๊ฐ์ •์„ ๋Š๋ผ๊ฒŒ ํ•˜๋Š” ๋ฌผ๋ฆฌ์ ์ธ ํ™˜๊ฒฝ์š”์†Œ(๊ฑฐ๋ฆฌ, ๊ฒฝ๊ด€, ๊ทผ๋ฆฐ์ƒ์—…์‹œ์„ค, ์ฃผํƒ ๋‚ด ์‹œ์„ค, ๊ฑด์ถ•๋ฌผ์˜ ์™ธ๊ด€ ๋“ฑ)๊ฐ€ ๋ฌด์—‡์ธ์ง€๋ฅผ ๋ฐํžˆ๊ณ  ๊ทธ๊ฒƒ์ด ์–ด๋–ค ๊ณผ์ •์„ ํ†ตํ•ด ๊ฑฐ์ฃผ์ž์—๊ฒŒ ๊ธ์ •์ ์ธ ์žฅ์†Œ์„ฑ์„ ํ˜•์„ฑํ•˜๊ฒŒ ํ•˜๋Š”๋ฐ ์˜ํ–ฅ์„ ์ฃผ๋Š”์ง€๋ฅผ ๋ฐํžˆ๋Š”๋ฐ ๊ทธ ๋ชฉ์ ์ด ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์œ„์™€ ๊ฐ™์€ ์—ฐ๊ตฌ ๋ชฉ์ ์˜ ๋‹ฌ์„ฑ์„ ์œ„ํ•ด ํ‰์ฐฝ๋™ ์ง€์—ญ์„ ๋Œ€์ƒ์œผ๋กœ ์งˆ์ ๋ฐฉ๋ฒ•๋ก ์„ ๋„์ž…ํ•˜์—ฌ ์ž๋ฃŒ๋ฅผ ์ˆ˜์ง‘ํ•˜๊ณ  ๋ถ„์„ํ•˜์˜€๋‹ค. ํ‰์ฐฝ๋™์— ๊ฑฐ์ฃผํ•˜์˜€๊ฑฐ๋‚˜ ํ•˜๊ณ  ์žˆ๋Š” ์ฃผ๋ฏผ๋“ค์„ ๋Œ€์ƒ์œผ๋กœ ์ฃผ๋ฏผ๋“ค์ด ํ‰์ฐฝ๋™ ์ง€์—ญ์˜ ์–ด๋–ค ๋ฌผ๋ฆฌ์  ํ™˜๊ฒฝ์—์„œ ๋ฌด์Šจ ๊ฐ์ •์„ ๋Š๋ผ๊ณ  ์–ด๋–ค ๊ฒฝํ—˜์„ ํ•˜์˜€๋Š”์ง€๋ฅผ ์ค‘์ ์ ์œผ๋กœ ์งˆ๋ฌธํ•˜์˜€๋‹ค. ๋˜ํ•œ ๋งตํ•‘์„ ํ†ตํ•ด ์ฃผ๋ฏผ๋“ค์ด ํ‰์ฐฝ๋™์˜ ๋ฒ”์œ„๋ฅผ ์–ด๋–ป๊ฒŒ ์ธ์‹ํ•˜๊ณ  ์–ด๋– ํ•œ ๋ฌผ๋ฆฌ์  ์š”์†Œ๋ฅผ ํ†ตํ•ด ์ธ์‹ํ•˜๊ณ  ์žˆ๋Š”์ง€๋ฅผ ์กฐ์‚ฌํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ๊ฒฐ๊ณผ ๊ฑฐ์ฃผ์ž๋“ค์€ ์ƒ๋Œ€์ ์œผ๋กœ ์ €๋ฐ€๋„์™€ ์ €์ธต, ๋„“์€ ์ธ๋™ ๊ฐ„๊ฒฉ ๋“ฑ์˜ ๊ฑด์ถ•๋ฌผ์˜ ๋ฌผ๋ฆฌ์  ํ˜•ํƒœ์™€ ๋ชจํ˜ธํ•œ ์„ฑ๊ฒฉ์„ ๊ฐ€์ง€๋Š” ์ ˆ์ถฉ์  ๊ณต๊ฐ„์˜ ์กด์žฌ, ๊ทธ๋ฆฌ๊ณ  ์ง€์—ญ์˜ ๊ฐœ์„ฑ์žˆ๋Š” ๊ฑฐ๋ฆฌ ๊ฒฝ๊ด€, ์‹ฌ๋ฆฌ์  ์•ˆ์ •๊ฐ์„ ๋Š๋ผ๋Š” ์ฐจ๋Ÿ‰๊ณผ ์œ ๋™์ธ๊ตฌ ํ†ตํ–‰์„ ํ†ตํ•ด ํ‰์ฐฝ๋™์˜ ์žฅ์†Œ์„ฑ์„ ๊ฐ•ํ™”ํ•˜๊ณ  ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ์กฐ์‚ฌ๋๋‹ค. ๊ฐ๊ฐ์˜ ์š”์†Œ๋“ค์€ ์ง‘ํ•ฉ์ ์ธ ์„ฑ๊ฒฉ์„ ๋Œ ๋•Œ ๊ฑฐ๋ฆฌ ๊ฒฝ๊ด€์— ์˜ํ–ฅ์„ ์ฃผ๋Š” ๋“ฑ ์ƒํ˜ธ ์—ฐ๊ด€์„ฑ์„ ๋ณด์˜€๊ณ  ๊ฑฐ์ฃผ์ž๋“ค ์—ญ์‹œ ์ด๋Ÿฌํ•œ ๋ถ€๋ถ„์„ ํ‰์†Œ์— ์‚ฐ์ฑ…์ด๋‚˜ ์ง‘ ์•ˆ์—์„œ์˜ ๊ฒฝ๊ด€ ์ „๋ง ๋“ฑ์„ ํ†ตํ•ด ์ง๊ฐ„์ ‘์ ์œผ๋กœ ๋Š๋ผ๊ณ  ์žˆ์Œ์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋ฐ˜๋ฉด ๊ทผ๋ฆฐ์ƒ์—…์‹œ์„ค์€ ๋žœ๋“œ๋งˆํฌ์  ์š”์†Œ๋กœ์„œ๋งŒ ๊ธฐ๋Šฅํ•  ๋ฟ ๊ฑฐ์ฃผ์ž ๋“ค์€ ์žฅ์†Œ์„ฑ์„ ๊ฐ•ํ™”ํ•˜๋Š” ์š”์†Œ๋กœ์„œ ์ธ์‹ํ•˜๊ณ  ์žˆ์ง€ ์•Š๋Š” ๊ฒฝํ–ฅ์„ ๋ณด์˜€๋‹ค. ๊ทธ ๋ฐ–์— ๊ณต์› ๋“ฑ์€ ๊ฑฐ์ฃผํ•˜๋Š” ์ฃผํƒ ์œ ํ˜•๊ณผ ์—ฐ๋ น๋Œ€์— ๋”ฐ๋ผ ์žฅ์†Œ์„ฑ์„ ํ˜•์„ฑํ•˜๋Š” ์š”์ธ์ด ๋˜์—ˆ์ง€๋งŒ ๋‹จ๋…์ฃผํƒ์— ๊ฑฐ์ฃผํ•˜๋Š” ๊ฒฝ์šฐ ์ฃผํƒ ๋‚ด๋ถ€์— ์ •์› ๋“ฑ์˜ ๋…น์ง€ ๊ณต๊ฐ„์ด ์œ„์น˜ํ•œ ํŠน์ˆ˜์„ฑ์œผ๋กœ ์ธํ•ด ๋Œ€๋ถ€๋ถ„์˜ ์ฃผ๋ฏผ๋“ค์—๊ฒŒ ๊ฑฐ์˜ ๊ณ ๋ ค๋˜์ง€ ์•Š๊ณ  ์žˆ์—ˆ๋‹ค. ๋”ฐ๋ผ์„œ ํ–ฅํ›„ ์ฃผ๊ฑฐ์ง€๋ฅผ ๊ณ„ํšํ•˜๊ณ  ์„ค๊ณ„ํ•˜๋Š”๋ฐ ์žˆ์–ด ์ ˆ์ถฉ์  ๊ณต๊ฐ„, ์ฆ‰ ์™ธ๋ถ€์™€ ๋‚ด๋ถ€ ์‚ฌ์ด์˜ ๊ณต๊ฐ„์ธ ํ…Œ๋ผ์Šค๋‚˜ ๋ฐœ์ฝ”๋‹ˆ์˜ ๊ณต๊ธ‰๊ณผ ํ™•์žฅ ์ œํ•œ ๋“ฑ์„ ํ†ตํ•ด ์ฃผํƒ ๊ฑฐ์ฃผ์ž ๊ฐœ์ธ์  ์ธก๋ฉด์—์„œ์˜ ์ด์ ๊ณผ ๋”๋ถˆ์–ด ๋„์‹œ ๊ฒฝ๊ด€ ์ธก๋ฉด์—์„œ ์ฃผ๊ฑฐ ๊ฑด๋ฌผ ๋“ค์˜ ๋‹ค์–‘์„ฑ์„ ๊พ€ํ•ด์•ผ ํ•  ํ•„์š”๊ฐ€ ์žˆ์œผ๋ฉฐ, ์ ‘๊ทผ ์„ฑ์ด ์ข‹์€ ์ค‘์ •์ด๋‚˜ ์˜ฅ์ƒ ๋“ฑ ์ฃผํƒ ๋‚ดโ€ข์™ธ๋ถ€์— ๋…น์ง€๋ฅผ ๊ณต๊ธ‰ํ•˜๊ณ  ์ˆ˜๊ณต๊ฐ„์„ ์ ‘ํ•˜๋Š” ์ฃผํƒ์„ ๋ณด๊ธ‰ํ•˜์—ฌ ๋‹ค์–‘ํ•œ ์ข…๋ฅ˜์˜ ์ž์—ฐํ™˜๊ฒฝ์„ ์ฃผ๊ฑฐ์ง€ ๊ฐ€๊นŒ์ด์—์„œ ์ ‘ํ•  ์ˆ˜ ์žˆ๋„๋ก ๊ณ„ํšํ•ด์•ผ ํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ๋ฌผ๋ฆฌ์  ํ™˜๊ฒฝ์„ ์กฐ์„ฑํ•˜๋Š” ๋ฐ ์žˆ์–ด ๋‹จ์ˆœํžˆ ์ „๋ฌธ๊ฐ€์  ์‹œ์„ ์—์„œ์˜ ํ•˜ํ–ฅ์  ์ ‘๊ทผ์„ ๋ฒ—์–ด๋‚˜ ์‚ฌ์šฉ์ž ๋“ค์ด ๋Š๋ผ๋Š” ๋ฐ”๋ฅผ ์ธ์‹ํ•ด ์ƒํ–ฅ์‹ ์ ‘๊ทผ์„ ํ•˜๋Š”๋ฐ ๋„์›€์„ ์ค„ ๊ฒƒ์œผ๋กœ ๋ณด์ธ๋‹ค. ๋˜ํ•œ ์ •์„ฑ์  ๋ฐฉ๋ฒ•๋ก ์ด ์ˆ˜์ง‘ํ•  ์ˆ˜ ์—†๋Š” ๋ฏธ๋ฌ˜ํ•œ ๊ฐ์„ฑ์ด๋‚˜ ๋‹จ์‹œ๊ฐ„ ๋ฉด์ ‘์œผ๋กœ ์–ป์„ ์ˆ˜ ์—†๋Š” ์˜์—ญ์˜ ์ •๋ณด๊นŒ์ง€ ์Šต๋“ํ•˜์—ฌ ๊ทธ๋™์•ˆ ์šฐ๋ฆฌ ๋„์‹œ๊ณ„ํš์ด ์†Œํ™€ํ–ˆ๋˜ ์ƒํ™œ๊ณต๊ฐ„์œผ๋กœ์„œ์˜ ๋„์‹œ๋ฅผ ์‹คํ˜„ํ•˜๋Š”๋ฐ ๋„์›€์ด ๋  ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€ํ•œ๋‹ค.๋ชฉ ์ฐจ ์ œ 1 ์žฅ ์„œ๋ก  1 1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์  1 2. ์—ฐ๊ตฌ์˜ ๋ฒ”์œ„ 3 1) ๋ฌธํ—Œ์  ๋ฒ”์œ„ 3 2) ๊ณต๊ฐ„์  ๋ฒ”์œ„ 4 3) ๋ฌผ๋ฆฌ์  ์š”์†Œ์˜ ๋ฒ”์œ„ 5 3. ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• 5 1) ๋ฌธํ—Œ ๋ถ„์„ 7 2) ์‹ฌ์ธต ์ธํ„ฐ๋ทฐ 7 4. ๋Œ€์ƒ์ง€ ๊ฐœ๊ด€ 17 1) ํ‰์ฐฝ๋™์˜ ํ˜•์„ฑ ์—ญ์‚ฌ 17 2) ํ˜„ํ™ฉ 17 ์ œ 2 ์žฅ ์ด๋ก ์  ๋ฐฐ๊ฒฝ ๋ฐ ์„ ํ–‰์—ฐ๊ตฌ ๊ณ ์ฐฐ 24 1. ์žฅ์†Œ์„ฑ์— ๊ด€ํ•œ ์—ฐ๊ตฌ 24 2. ์ฃผ๊ฑฐ์ง€ ์žฅ์†Œ์„ฑ์— ๊ด€ํ•œ ์—ฐ๊ตฌ 25 3. ์žฅ์†Œ์˜ ์ธ์‹๊ณผ ์ด๋ฏธ์ง€์— ๊ด€ํ•œ ์—ฐ๊ตฌ 31 4. ์žฅ์†Œ์„ฑ๊ณผ ๋ฌผ๋ฆฌ์  ์š”์†Œ์— ๊ด€ํ•œ ์—ฐ๊ตฌ 33 5. ์†Œ๊ฒฐ 34 ์ œ 3 ์žฅ ์ผ์ƒ์ƒํ™œ๊ณผ ๊ณต๊ฐ„์˜ ๊ด€๊ณ„ 36 1. ๊ณต๋™ ์ฃผํƒ ๊ฑฐ์ฃผ์ž์˜ ์ผ์ƒ์ƒํ™œ๊ณผ ๊ณต๊ฐ„ ์ด์šฉ 37 1) ์ผ์ƒ์ƒํ™œ 37 2) ๊ณต๊ฐ„์ด์šฉ ํ˜„ํ™ฉ 38 2. ๋‹จ๋… ์ฃผํƒ ๊ฑฐ์ฃผ์ž์˜ ์ผ์ƒ์ƒํ™œ๊ณผ ๊ณต๊ฐ„ ์ด์šฉ 41 1) ์ผ์ƒ์ƒํ™œ 41 2) ๊ณต๊ฐ„์ด์šฉ ํ˜„ํ™ฉ 44 3) ์š”์•ฝ 46 3. ์†Œ๊ฒฐ 46 ์ œ 4 ์žฅ ์žฅ์†Œ์„ฑ์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๋ฌผ๋ฆฌ์  ํ™˜๊ฒฝ ์š”์†Œ 48 1. ์žฅ์†Œ์„ฑ์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ํ™˜๊ฒฝ์  ์š”์†Œ ๋ถ„์„ 48 1) ์ €์ธตโ€ข์ €๋ฐ€๋„์˜ ๊ฑด์ถ•๋ฌผ ํ˜•ํƒœ 48 2) ์ ˆ์ถฉ์  ์„ฑ๊ฒฉ์˜ ๊ณต๊ฐ„ 51 3) ํŠน์ƒ‰ ์žˆ๋Š” ๊ฑด์ถ•๋ฌผ ๋””์ž์ธ 55 4) ํ†ต๊ณผ ๊ตํ†ต ๋ฐ ์œ ๋™์ธ๊ตฌ์˜ ์ ์ •์„ฑ 59 2. ์†Œ๊ฒฐ 62 ์ œ 5 ์žฅ ๋ฌผ๋ฆฌ์  ์š”์†Œ์˜ ๋„์‹œ ์ฃผ๊ฑฐ ์ธก๋ฉด์—์„œ์˜ ํ•ด์„ 64 1. ๊ฑฐ์ฃผ์ž๊ฐ€ ์œ ์—ฐํ•˜๊ฒŒ ํ™œ์šฉํ•  ์ˆ˜ ์žˆ๋Š” ์™ธ๋ถ€๊ณต๊ฐ„์˜ ์ค‘์š”์„ฑ 64 1) ์ •์› 64 2) ํ˜„๊ด€โ€ขํ…Œ๋ผ์Šคโ€ข์ค‘์ • ๋“ฑ 66 2. ๊ฐ€๋กœ๊ฒฝ๊ด€๊ณผ ๊ณต๊ณต ๊ณต๊ฐ„ 66 1) ๋‹ค์–‘ํ•œ ์ฃผํƒ์œ ํ˜• 73 2) ๋‹ค์–‘ํ•œ ์ฃผํƒ์™ธ๊ด€ ๋””์ž์ธ 74 3. ๋„์‹œ ์ฃผ๊ฑฐ ์ง€์—ญ์˜ ๋„์‹œ์„ฑ๊ณผ ์ž์—ฐ์„ฑ์˜ ๊ณต์กด 75 1) ๋„์‹œ ๊ฑฐ์ฃผ์ง€์—์„œ ์ž์—ฐ์˜ ๊ฐ€์น˜ 76 ์ œ 6 ์žฅ ๊ฒฐ๋ก  83 1. ํ‰์ฐฝ๋™ ๋ฌผ๋ฆฌ์  ๊ฒฝ๊ด€์˜ ์•ˆ์ •์„ฑ๊ณผ ๊ฑฐ์ฃผ์ž๋“ค์˜ ์žฅ์†Œ์„ฑ ํ˜•์„ฑ 83 2. ๋ฏธ๋ž˜ ๋„์‹œ ์ฃผ๊ฑฐ ์ง€ํ–ฅ์ ์œผ๋กœ์„œ์˜ ํ‰์ฐฝ๋™ ์žฅ์†Œ์„ฑ๊ณผ ์˜์˜ 85 ์ฐธ ๊ณ  ๋ฌธ ํ—Œ 88 Abstract 90 ํ‘œ ๋ชฉ์ฐจ [ํ‘œ 1 1] ์ธํ„ฐ๋ทฐ ๋Œ€์ƒ์ž ์ •๋ณด 8 [ํ‘œ 1 2] ์ˆ˜์ • ์ „ ์งˆ๋ฌธ์ง€ 11 [ํ‘œ 1 3] ์ˆ˜์ • ํ›„ ์งˆ๋ฌธ์ง€ 13 [ํ‘œ 1 4] ํ‰์ฐฝ๋™ ์ฃผ๊ฑฐ ์œ ํ˜•๋ณ„ ์„ธ๋Œ€ ํ˜„ํ™ฉ 21 [ํ‘œ 1 5] ํ‰์ฐฝ๋™ ์ธ๊ตฌ ํ˜„ํ™ฉ 21 [ํ‘œ 3 1] ๊ณต๋™์ฃผํƒ ๊ฑฐ์ฃผ์ž N์”จ์˜ ์ผ์ƒ์ƒํ™œ 37 [ํ‘œ 3 2] ๋‹จ๋…์ฃผํƒ ๊ฑฐ์ฃผ์ž E์”จ์˜ ํ‰์ฐฝ๋™์—์„œ์˜ ์ผ์ƒ์ƒํ™œ 42 โ€ƒ ๊ทธ๋ฆผ ๋ชฉ์ฐจ [๊ทธ๋ฆผ 1 1] ํ‰์ฐฝ๋™์˜ ์šฉ๋„์ง€์—ญ ํ˜„ํ™ฉ 19 [๊ทธ๋ฆผ 1 2] ํ‰์ฐฝ๋™ ๊ฐ€๋กœ ํ˜„ํ™ฉ 20 [๊ทธ๋ฆผ 1 3] ํ‰์ฐฝ๋™ ์ง€์—ญ ๊ฑด์ถ•๋ฌผ์˜ ์šฉ๋„ ํ˜„ํ™ฉ 23 [๊ทธ๋ฆผ 3 1] ๊ณต๋™์ฃผํƒ ๊ฑฐ์ฃผ์ž N์”จ์˜ ํ‰์ฐฝ๋™ ๋‚ด ์ด๋™ ๋™์„  40 [๊ทธ๋ฆผ 3 2] ๊ณต๋™์ฃผํƒ ๊ฑฐ์ฃผ์ž E์”จ์˜ ํ‰์ฐฝ๋™ ๋‚ด ์ด๋™ ๋™์„  45 [๊ทธ๋ฆผ 3 3] ๊ณต๋™์ฃผํƒ ๊ฑฐ์ฃผ์ž์™€ ๋‹จ๋…์ฃผํƒ ๊ฑฐ์ฃผ์ž์˜ ์ƒํ™œ ๊ณต๊ฐ„ ๋ฐ ํ™œ๋™ ๋น„๊ต 47 [๊ทธ๋ฆผ 5 1] ํ‰์ฐฝ๋™์˜ ์ฃผํƒ ์œ ํ˜•๋ณ„ ๋‹ค์–‘ํ•œ ์ •์› 65 [๊ทธ๋ฆผ 5 2] ํ‰์ฐฝ๋™์˜ ๋‹ค์–‘ํ•œ ์ฃผํƒ ์œ ํ˜• 65 [๊ทธ๋ฆผ 5 3] ์ค‘์ • ๋ฐ ํ…Œ๋ผ์Šค 66 [๊ทธ๋ฆผ 5 4] ์ธํ„ฐ๋ทฐ ๋Œ€์ƒ์ž ๋“ค์˜ ์‚ฐ์ฑ… ๋™์„  68 [๊ทธ๋ฆผ 5 5] ๋†’์€ ๋‹ด์žฅ์œผ๋กœ ์ธํ•ด ๊ฒฝ๊ด€์— ๋ถ€์ •์ ์ธ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๊ฒฝ์šฐ 73 [๊ทธ๋ฆผ 5 6] ํ‰์ฐฝ๋™์˜ ๋‹ค์–‘ํ•œ ์ฃผํƒ์œ ํ˜• 73 [๊ทธ๋ฆผ 5 7] ์ฃผ๊ฑฐ์ง€ ์„ ํƒ์— ๋Œ€ํ•œ ์ด๋ก  82 [๊ทธ๋ฆผ 6 1] ํ‰์ฐฝ๋™ ์ฃผ๊ฑฐ์ง€์—ญ ์žฅ์†Œ์„ฑ ํ˜•์„ฑ ๊ณผ์ • 84Maste

    ๋™์ธ์ง€ <๋ฐฑ์กฐ>์˜ ๋ฌธํ•™์‚ฌ์  ์„ฑ๊ฒฉ

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    The association of mdtabolic syndrome and glaucoma in Korean adults : the 5th (2010-2012) Korea national health and nutrition examination survey

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    Background: Metabolic sundrome(MetS) and glaucoma are becoming public health challenge individually. In this study, we aimed to investigate the relationship between MetS and Glaucoma risk through its components in Korean adults. Methods: This study was based on the data obtained from 5th(2015) Korea National Health and Nutrition Examination Survey(KNHANES). It is a nationwide cross-sectional survey of nationally representative civilians in the Republic of Korea. From upper 19-year-old subjects, this study selected a total of 11,972 subjects(5,144 men, 6,828 women), excluding people who have some missing data for study, have been diagnosed or treated glaucoma, fasted under 8 hours for the blood test and have any disease which affects intraocular pressure. This study conducted logistic regression analysis, chi-square analysis. Results: Prevalences of metabolic syndrome and glaucoma was 12.1%m 2.27% respectively. After adjustment for confounding factors, women who satisfied with combination of 2~3 components of metabolic syndrome have high odds ratios for glaucoma risk. And women who have high blood pressure and impaired glucose fasting had high odds ratios for glaucoma according to Model โ… (adjusted age and BMI), โ…ก(adjusted Model โ…  plus health behavioral factors), โ…ข(Model โ…ก plus socioeconomic factors) at 3.15(OR=3.15, 95% CI 1.41-7.01), 4.02(OR=4.02, 95% CI 1.78-9.07), 3.82(OR=3.82, 95% CI 1.69-8.66) respectively. Conclusions: These study showed that women who have metabolic syndrome suspect had high risk for developing glaucoma. If additional follow up studies are conducted, the findings can be used as an indicator for predicting glaucoma risk in patients with metabolic syndrome. ๋…น๋‚ด์žฅ์€ ์‹œ์‹ ๊ฒฝ์œ„์ถ•๊ณผ ์‹œ์•ผ์†์ƒ์„ ํŠน์ง•์œผ๋กœ ํ•˜๋Š” ์งˆํ™˜์œผ๋กœ ์กฐ๊ธฐ ๋ฐœ๊ฒฌํ•˜์—ฌ ์ ์ ˆํžˆ ์น˜๋ฃŒํ•˜์ง€ ์•Š์œผ๋ฉด ์‹ฌํ•œ ๊ฒฝ์šฐ ์‹ค๋ช…์— ์ด๋ฅด๋Š” ์งˆํ™˜์ด๋‹ค. ๊ตญ๋ฏผ๊ฑด๊ฐ•๋ณดํ—˜๊ณต๋‹จ ํ‘œ๋ณธ ์ฝ”ํ˜ธํŠธ ์ž๋ฃŒ๋ฅผ ์ด์šฉํ•œ ์—ฐ๊ตฌ์— ๋”ฐ๋ฅด๋ฉด 2008๋…„๋ถ€ํ„ฐ 2013๋…„๊นŒ์ง€ ๋…น๋‚ด์žฅ ํ™˜์ž๋Š” ๋งค๋…„ 9%์ฆ๊ฐ€ํ•˜์˜€๊ณ  ๋…น๋‚ด์žฅ ํ™˜์ž์˜ ์‚ฌํšŒ์  ๋น„์šฉ์€ ์ง€์†์ ์œผ๋กœ ๋Š˜์–ด๋‚  ๊ฒƒ์œผ๋กœ ๋ณด์ธ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ํ•œ๊ตญ์ธ์˜ ํŠน์„ฑ์„ ๋Œ€ํ‘œํ•˜๋Š” ๊ตญ๋ฏผ๊ฑด๊ฐ•์˜์–‘์กฐ์‚ฌ ์ œ5๊ธฐ(2010-2012) ์ž๋ฃŒ๋ฅผ ์ด์šฉํ•˜์—ฌ ๋Œ€์‚ฌ์ฆํ›„๊ตฐ๊ณผ ๋…น๋‚ด์žฅ๊ณผ์˜ ๊ด€๋ จ์„ฑ์„ ๋ณด๊ณ ์ž ํ•˜์˜€๋‹ค. ๋Œ€์‚ฌ์ฆํ›„๊ตฐ ์ง„๋‹จ์€ NCEP ATP III์— ๋”ฐ๋ผ ์ •์˜ํ•˜์˜€๊ณ , ์ด ์ค‘ ๋ณต๋ถ€๋น„๋งŒ์€ ๋Œ€ํ•œ๋น„๋งŒํ•™ํšŒ์—์„œ ์ œ์‹œํ•œ ํ—ˆ๋ฆฌ๋‘˜๋ ˆ ๊ธฐ์ค€์„ ๊ทผ๊ฑฐํ•˜์—ฌ ์ •์˜ํ•˜์˜€๋‹ค. ๋…น๋‚ด์žฅ์˜ ์ง„๋‹จ์€ International Society of Geographical and Epidemiological Ophthalmology (ISGEO) ์ง„๋‹จ ๊ธฐ์ค€์„ ์‚ฌ์šฉํ•˜์˜€์œผ๋ฉฐ ๋Œ€์‚ฌ์ฆํ›„๊ตฐ์˜ ์œ ๋ณ‘๋ฅ ์€ ์ „์ฒด ์—ฐ๊ตฌ๋Œ€์ƒ์ž 11,972๋ช… ์ค‘ 1,446๋ช…์œผ๋กœ 12.1%, ๋…น๋‚ด์žฅ์˜ ์œ ๋ณ‘๋ฅ ์€ 272๋ช…์œผ๋กœ 2.27%๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋Œ€์‚ฌ์ฆํ›„๊ตฐ๊ณผ ๋…น๋‚ด์žฅ์˜ ๊ด€๋ จ์„ฑ ํ™•์ธ์„ ์œ„ํ•ด ์„ฑ์ธ ๋‚จ๋…€๋กœ ๋‚˜๋ˆ„์–ด ๋กœ์ง€์Šคํ‹ฑ ํšŒ๊ท€๋ถ„์„์„ ์‹ค์‹œํ•˜์˜€๋‹ค. ๋จผ์ € ์—ฐ๋ น์„ ํ†ต์ œํ•˜์—ฌ ๋Œ€์‚ฌ์ฆํ›„๊ตฐ๊ณผ ๋…น๋‚ด์žฅ ๊ด€๋ จ์„ฑ ํ™•์ธ์„ ์œ„ํ•œ ๋กœ์ง€์Šคํ‹ฑ ํšŒ๊ท€๋ถ„์„์„ ์‹ค์‹œํ•˜์˜€๊ณ , Model โ… (์—ฐ๋ น๊ณผ ์ฒด์งˆ๋Ÿ‰์ง€์ˆ˜ ๋ณด์ •), โ…ก(Model โ… ์— ๊ฑด๊ฐ•ํ–‰ํƒœ์  ํŠน์„ฑ ์ถ”๊ฐ€), โ…ข(Model โ…ก์— ์‚ฌํšŒ์ธ๊ตฌํ•™์  ํŠน์„ฑ ์ถ”๊ฐ€)๋กœ ํ˜ผ๋ž€๋ณ€์ˆ˜๋ฅผ ํ†ต์ œํ•œ ์ƒํƒœ์—์„œ ์ถ”๊ฐ€์ ์ธ ๋ถ„์„์„ ์‹ค์‹œํ•˜์˜€๋‹ค. ์—ฐ๋ น์„ ํ†ต์ œํ•œ ๋กœ์ง€์Šคํ‹ฑ ํšŒ๊ท€๋ถ„์„ ๊ฒฐ๊ณผ ์„ฑ์ธ ๋‚จ๋…€ ๋ชจ๋‘์—์„œ ๋…น๋‚ด์žฅ์— ๋Œ€ํ•œ ๋Œ€์‚ฌ์ฆํ›„๊ตฐ์˜ ์˜ค์ฆˆ๋น„๋Š” ์œ ์˜ํ•˜์ง€ ์•Š์•˜๋‹ค(๋‚จ๋…€ ๊ฐ๊ฐ 0.84(OR=0.84, 95% CI 0.52-1.35, 1.37(OR=1.37, 95% CI 0.85-2.21)). ๋Œ€์‚ฌ์ฆํ›„๊ตฐ ์ง„๋‹จ ๊ธฐ์ค€์„ ๋งŒ์กฑํ•˜๋Š” ์ˆซ์ž๋กœ ๋ถ„๋ฅ˜ํ•œ ํšŒ๊ท€๋ถ„์„, ๋Œ€์‚ฌ์ฆํ›„๊ตฐ ์ง„๋‹จ์˜ ์กฐํ•ฉ์œผ๋กœ ๋ถ„๋ฅ˜ํ•œ ํšŒ๊ท€๋ถ„์„ ๊ฒฐ๊ณผ ์„ฑ์ธ ๋‚จ์„ฑ์—์„œ๋Š” ๋ชจ๋‘ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•˜์ง€ ์•Š์•˜๋‹ค. ์„ฑ์ธ ์—ฌ์„ฑ์—์„œ๋Š” ๋Œ€์‚ฌ์ฆํ›„๊ตฐ ์ง„๋‹จ ๊ธฐ์ค€์„ 2๊ฐœ ๋งŒ์กฑํ•˜๋Š” ๋Œ€์‚ฌ์ฆํ›„๊ตฐ ์œ„ํ—˜๊ตฐ์˜ ๊ฒฝ์šฐ Model โ…ก์™€ Model โ…ข์—์„œ ๊ฐ๊ฐ ์˜ค์ฆˆ๋น„ 2.30(OR=2.30, 95% CI 2.28-2.32), 1.73(OR=1.73, 95% CI 1.72-1.75)๋กœ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•˜์˜€๊ณ , ๋Œ€์‚ฌ์ฆํ›„๊ตฐ ์ค‘ ์ง„๋‹จ๊ธฐ์ค€ 3๊ฐœ๋ฅผ ๋งŒ์กฑํ•˜๋Š” ๊ทธ๋ฃน์—์„œ Model โ…ก, Model โ…ข์—์„œ ๊ฐ๊ฐ ์˜ค์ฆˆ๋น„ 3.43(OR=3.43, 95% CI 3.43-3.50), 2.43(OR=2.43, 95% CI 2.43-2.46)๋กœ ์œ ์˜ํ•˜์˜€๋‹ค. ์—ฌ์„ฑ์—์„œ ์ด์ƒ์ง€์งˆํ˜ˆ์ฆ์„ ๊ฐ€์ง„ ๊ฒฝ์šฐ ๋…น๋‚ด์žฅ์— ๊ด€ํ•œ ์˜ค์ฆˆ๋น„๋Š” Model โ…ก์—์„œ 1.64(OR=1.64, 95% CI 1.00-2.69)๋กœ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•˜์˜€์œผ๋ฉฐ, ๋†’์€ ํ˜ˆ์••๊ณผ ๋‹น๋‡จ์ „๋‹จ๊ณ„์˜ ๊ฒฝ์šฐ Model โ… ~โ…ข์—์„œ ๊ฐ๊ฐ ์˜ค์ฆˆ๋น„ 3.15(OR=3.15, 95% CI 1.41-7.01), 4.02(OR=4.02, 95% CI 1.78-9.07), 3.82(OR=3.82, 95% CI 1.69-8.66)๋กœ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•˜์˜€๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ ์—ฌ์„ฑ์—์„œ ๋†’์€ ํ˜ˆ์••, ๋‹น๋‡จ ์ „๋‹จ๊ณ„, ์ด์ƒ์ง€์งˆํ˜ˆ์ฆ์„ ๋ชจ๋‘ ๊ฐ€์ง„ ๊ฒฝ์šฐ Model โ…ก, Model โ…ข์—์„œ ๊ฐ๊ฐ ์˜ค์ฆˆ๋น„ 2.70(OR=2.70, 95% CI 1.07-6.81), 2.78(OR=2.78, 95% CI 1.09-7.04)๋กœ ์œ ์˜ํ•˜์˜€๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ๋งŒ 19์„ธ ์ด์ƒ 80์„ธ ์ดํ•˜ ์„ฑ์ธ์—์„œ ๋Œ€์‚ฌ์ฆํ›„๊ตฐ๊ณผ ๋…น๋‚ด์žฅ์˜ ๊ด€๋ จ์„ฑ์„ ์•Œ์•„๋ณด๋Š” ์—ฐ๊ตฌ์ด๋‹ค. ๋น„๋งŒ์ธ๊ตฌ๊ฐ€ ์ฆ๊ฐ€ํ•˜๋ฉด์„œ ๋Œ€์‚ฌ์ฆํ›„๊ตฐ๋„ ์ฆ๊ฐ€ํ•˜๊ณ  ์žˆ๋Š” ์ถ”์„ธ๋กœ ๋Œ€์‚ฌ์ฆํ›„๊ตฐํ™˜์ž์—์„œ ๋…น๋‚ด์žฅ์— ๋Œ€ํ•œ ์ „ํ–ฅ์  ์—ฐ๊ตฌ๊ฐ€ ํ•„์š”ํ•  ๊ฒƒ์œผ๋กœ ๋ณด์ธ๋‹ค.prohibition์„

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    Thesis(master`s)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์ œ์•ฝํ•™๊ณผ,2007.Maste

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    Dept. of Medical Science/๋ฐ•์‚ฌRecent studies have shown that motor imagery training improves the actual performance of motor skills, which are involved in an intentional movement to perform a specific task. The effect of training is related to the plasticity of neural activity of motor intentions. However, it is still unknown how we practice motor imagery in order to make our desired activity patterns. Here, we first report real-time fMRI classification system can classify brain states related to motor intentions during motor imagery and give feedback about imagery to subjects. To generate accurate feedback, we propose a novel detrending for improving classification performance. Motor imagery training also has showed the stability of neural activity patterns related to motor intentions during motor imagery. Motor execution and motor imagery classification using simulated MVPA revealed the representation of motor information as well as the feasibility of real-time classification. After feedback training, increased motor information and motor network showed that real-time classification of fMRI signals and feedback could be helpful to self-regulation of activity patterns for consistency. Unlike previous studies, we could classify brain states during complex movements imagery. These results indicate that our system could be a useful tool in certain applications including rehabilitation and fMRI-BCI for the improvement of motor skills as well as function.restrictio

    Precise Measurement of Reactor Antineutrino Oscillation Parameters and Fuel-dependent Variation of Antineutrino Yield and Spectrum

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ž์—ฐ๊ณผํ•™๋Œ€ํ•™ ๋ฌผ๋ฆฌยท์ฒœ๋ฌธํ•™๋ถ€(๋ฌผ๋ฆฌํ•™์ „๊ณต), 2019. 2. ๊น€์ˆ˜๋ด‰.The reactor experiment for neutrino oscillation (RENO) ๋Š” 2011๋…„ 8์›”๋ถ€ํ„ฐ ์˜๊ด‘ ์›์ž๋ ฅ๋ฐœ์ „์†Œ ๊ทผ์ฒ˜์— ์œ„์น˜ํ•œ ๋‘๊ฐœ์˜ ๋™์ผํ•œ ๊ฒ€์ถœ๊ธฐ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ์ „์ž ๋ฐ˜์ค‘์„ฑ๋ฏธ์ž์˜ ๋ฐ์ดํ„ฐ๋ฅผ ๋ฐ›๊ธฐ ์‹œ์ž‘ํ–ˆ๋‹ค. ๋Œ€๋žต 2,200์ผ์˜ ๋ฐ์ดํ„ฐ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ, ๊ทผ๊ฑฐ๋ฆฌ์—์„œ๋Š” 850\,666 ์›๊ฑฐ๋ฆฌ์—์„œ๋Š” 103\,212 ๊ฐœ์˜ ์ค‘์„ฑ๋ฏธ์ž ์ด๋ฒคํŠธ ํ›„๋ณด๋ฅผ ๊ณจ๋ผ๋‚ด์—ˆ์œผ๋ฉฐ, ๊ทธ ์ค‘ ๊ทผ๊ฑฐ๋ฆฌ์—์„œ๋Š” 2.0\%, ์›๊ฑฐ๋ฆฌ์—์„œ๋Š” 4.7\%์˜ ๋น„์œจ์œผ๋กœ ๋ฐฑ๊ทธ๋ผ์šด๋“œ๊ฐ€ ํฌํ•จ๋˜์–ด์žˆ๋‹ค. 5MeV ๋ถ€๊ทผ์—์„œ ์ธก์ •๋œ ์ค‘์„ฑ๋ฏธ์ž์˜ ์„ ํ–‰์ด๋ฒคํŠธ ์ŠคํŽ™ํŠธ๋Ÿผ๊ณผ ์ตœ์‹ ์˜ ์ด๋ก ์„ ์‚ฌ์šฉํ•˜์—ฌ ์˜ˆ์ธกํ•œ ์„ ํ–‰ ์ด๋ฒคํŠธ ์ŠคํŽ™ํŠธ๋Ÿผ์— ์ฐจ์ด๊ฐ€ ์žˆ๋Š” ๊ฒƒ์„ ๋ฐœ๊ฒฌํ•˜์˜€๋‹ค. ์›๊ฑฐ๋ฆฌ์™€ ๊ทผ๊ฑฐ๋ฆฌ์˜ ๋น„์œจ์„ ๊ธฐ์ค€์œผ๋กœ ๋ถ„์„ํ•˜์—ฌ ๊ฑฐ๋ฆฌ์™€ ์ค‘์„ฑ๋ฏธ์ž์˜ ์—๋„ˆ์ง€์— ๋”ฐ๋ผ ์ค‘์„ฑ๋ฏธ์ž๊ฐ€ ์‚ฌ๋ผ์ง€๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๊ณ , ๊ทธ ์—๋„ˆ์ง€ ์ŠคํŽ™ํŠธ๋Ÿผ๊ณผ ์–‘์œผ๋กœ๋ถ€ํ„ฐ sinโก22ฮธ13=0.0896ยฑ0.0048(stat.)ยฑ0.0047(syst.)\sin^2 2 \theta_{13} = 0.0896 \pm 0.0048({\rm stat.}) \pm 0.0047({\rm syst.}) and ฮ”mee2=[2.68ยฑ0.12(stat.)ยฑ0.07(syst.)]ร—10โˆ’3\Delta m_{ee}^2= [2.68\pm0.12({\rm stat.})\pm0.07({\rm syst.})]\times 10^{-3}~eV2^2 ๋ฅผ ์ธก์ •ํ•˜์˜€๋‹ค. ํ•œํŽธ, 6๊ฐœ ์›์ž๋กœ๊ฐ€ ์ž‘๋™ํ•˜๋Š” ์‚ฌ์ดํด์˜ ๊ธฐ๊ฐ„์ด ์„œ๋กœ ์กฐ๊ธˆ์”ฉ ๋‹ฌ๋ผ ์›์ž๋กœ์˜ ์—ฐ๋ฃŒ์ธ 235^{235}U, 238^{238}U, 239^{239}Pu ๊ทธ๋ฆฌ๊ณ  235^{235}Pu์˜ ๋น„์œจ์ด ๊ณ„์†์ ์œผ๋กœ ๋ณ€ํ•˜๊ณ  ์žˆ์œผ๋ฉฐ, ์ด๋ฅผ ํ†ตํ•˜์—ฌ ์—ฐ๋ฃŒ ๋น„์œจ์— ๋”ฐ๋ผ IBD ์ƒ์‚ฐ๋Ÿ‰์˜ ๋ณ€ํ™”๋ฅผ ์‚ดํŽด๋ณด์•˜๋‹ค. ์ด๋กœ๋ถ€ํ„ฐ 235^{235}U ์— ๋Œ€ํ•œ IBD ์ƒ์‚ฐ๋Ÿ‰ (6.15 ยฑ\pm 0.19) ร—\times 104310^{43} cm2cm^{2}/fission, 239^{239}Pu ์— ๋Œ€ํ•œ IBD ์ƒ์‚ฐ๋Ÿ‰ (4.18 ยฑ\pm 0.26) ร—\times 104310^{43} cm2cm^{2}/fission, ๊ทธ๋ฆฌ๊ณ  ์ „์ฒด IBD ์ƒ์‚ฐ๋Ÿ‰ (5.84 ยฑ\pm 0.13) ร—\times 104310^{43} cm2cm^{2}/fission ์„ ์ธก์ •ํ•˜์˜€๋‹ค. ์ด๋Ÿฌํ•œ ์ธก์ •์œผ๋กœ๋ถ€ํ„ฐ, 4๊ฐ€์ง€ ์—ฐ๋ฃŒ์˜ ๋ฒ ํƒ€ ๋ถ•๊ดด๋กœ๋ถ€ํ„ฐ ๋ฐœ์ƒํ•˜๋Š” ์ค‘์„ฑ๋ฏธ์ž์˜ ์ŠคํŽ™ํŠธ๋Ÿผ์ด ์„œ๋กœ ๊ฐ™์ง€ ์•Š์Œ์„ 6.6 ฯƒ\sigma๋กœ์„œ ํ™•์ธํ•˜๊ณ  ์žˆ๋‹ค.์ธก์ •๋œ ๊ฐ 4๊ฐ€์ง€ ์—ฐ๋ฃŒ์˜ IBD ์ƒ์‚ฐ๋Ÿ‰์ค‘ 235^{235}U์˜ ๊ฒฝ์šฐ๊ฐ€ ์ด๋ก ์œผ๋กœ๋ถ€ํ„ฐ ์˜ˆ์ƒ๋œ ๊ฒƒ์— ๋น„ํ•ด ๊ฐ€์žฅ ๋งŽ์ด ์ ๊ฒŒ ๋‚˜ํƒ€๋‚˜๊ณ  ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ 4๊ฐ€์ง€ ์—ฐ๋ฃŒ์ค‘ 235^{235}U์˜ IBD ์ƒ์‚ฐ๋Ÿ‰์„ ๋‹ค์‹œ ๊ณ„์‚ฐํ•˜๋Š” ๊ฒƒ์ด ์›์ž๋กœ ๋ฐ˜์ค‘์„ฑ๋ฏธ์ž์˜ ๋ณ€์น™์„ ๊ฐ€์žฅ ์ž˜ ํ•ด๊ฒฐํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์ด๋‹ค. ๋˜ํ•œ, 5MeV ๋ถ€๊ทผ์—์„œ ์ธก์ •๋œ ์ค‘์„ฑ๋ฏธ์ž ์ด๋ฒคํŠธ์˜ ์ŠคํŽ™ํŠธ๋Ÿผ๊ณผ ์ด๋ก ์œผ๋กœ๋ถ€ํ„ฐ ์˜ˆ์ƒํ•œ ์ŠคํŽ™ํŠธ๋Ÿผ์˜ ์ฐจ์ด๊ฐ€ ์›์ž๋กœ ๋‚ด๋ถ€์˜ 235^{235}U์˜ ๋น„์œจ๊ณผ๋„ ์ƒ๊ด€๊ด€๊ณ„๊ฐ€ ์žˆ๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค.The reactor experiment for neutrino oscillation (RENO) since August 2011 has been extracting electron antineutrino (\nueb) data from two identical detectors located near the Yonggwang nuclear reactors in Korea. Using roughly 2,200 live days of data, we observed 850\,666 (103\,212) reactor \nuebS candidate events with 2.0\%(4.7)\% background in the near (far) detector. A discrepancy of approximately 5 MeV between the measured positron spectra of the reactor \nuebS events and the predicted positron spectra of the current reactor \nuebS model was observed. A far-to-near ratio measurement was conducted using the spectral and rate information, which gave sinโก22ฮธ13=0.0896ยฑ0.0048(stat.)ยฑ0.0047(syst.)\sin^2 2 \theta_{13} = 0.0896 \pm 0.0048({\rm stat.}) \pm 0.0047({\rm syst.}) and =[2.68ยฑ0.12(stat.)ยฑ0.07(syst.)]ร—10โˆ’3= [2.68\pm0.12({\rm stat.})\pm0.07({\rm syst.})]\times 10^{-3}~eV2^2. On the other hand, we observed from the multiple fuel cycles a fuel-dependent variation in an inverse beta decay (IBD) yield of (6.15 ยฑ\pm 0.19) ร—\times 104310^{43} cm2cm^{2}/fission for 235^{235}U and (4.18 ยฑ\pm 0.26) ร—\times 104310^{43} cm2cm^{2}/fission for 239^{239}Pu, and measured a total average IBD yield per fission of (5.84 ยฑ\pm 0.13) ร—\times 104310^{43} cm2cm^{2}/fission. This observation rejects the hypothesis of fuel-independent IBD yield or identical fuel-isotope spectra at 6.6 ฯƒ\sigma. The measured IBD yield per fission for 235^{235}U shows the largest deficit relative to a reactor model prediction. Re-evaluation of the 235^{235}U IBD yield per fission could solve the reactor antineutrino anomaly. We also report a correlation between the 5 MeV discrepancy in the observed IBD spectrum and 235^{235}U reactor fuel isotope fraction.List of Figures v List of Tables xi 1 Introduction 1 1.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Neutrino Oscillation . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.3 Reactor Neutrino Experiment . . . . . . . . . . . . . . . . . . . . . 3 1.3.1 Reactor Neutrino Production . . . . . . . . . . . . . . . . . 5 1.3.2 Reactor Neutrino Detection . . . . . . . . . . . . . . . . . . 6 1.3.3 Neutrino Oscillation in Reactor Experiments . . . . . . . . 8 1.3.4 Determination of Mixing Angle theta13 . . . . . . . . . . . . . . 10 1.3.5 Determination of Mass Squared Difference 1.4 The RENO Experiment . . . . . . . . . . . . . . . . . . . . . . . . 12 1.5 Fuel-dependent Variation of Antinetrino Yield and Spectrum . . . 12 2 Setup of the RENO Experiment 15 2.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 2.2 Experimental Arrangement . . . . . . . . . . . . . . . . . . . . . . 18 2.2.1 Hanbit Nuclear Power Plant . . . . . . . . . . . . . . . . . . 18 2.2.2 Near and Far detectors . . . . . . . . . . . . . . . . . . . . 18 2.2.3 Underground Facility and Experiment Halls . . . . . . . . . 20 2.3 Detector Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 2.3.1 Target and Gamma Catcher . . . . . . . . . . . . . . . . . . 21 2.3.2 Buffer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 2.3.3 Veto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 2.3.4 PMT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 2.4 Liquid Scintillator . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 2.4.1 Optimization for Liquid Scintillator . . . . . . . . . . . . . 30 2.4.2 Gd-loaded Liquid Scintillator . . . . . . . . . . . . . . . . . 32 2.4.3 Long-term Stability of the Liquid Scintillator . . . . . . . . 34 2.5 DAQ and Monitoring System Setup . . . . . . . . . . . . . . . . . 35 2.5.1 Front-End Electronics . . . . . . . . . . . . . . . . . . . . . 35 2.5.2 Qbee Board . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 2.5.3 DAQ System . . . . . . . . . . . . . . . . . . . . . . . . . . 38 2.5.4 Slow Control and Monitoring system . . . . . . . . . . . . . 42 3 Expected Reactor Antineutrino Flux and Spectrum 47 3.1 Production of Reactor Neutrino . . . . . . . . . . . . . . . . . . . . 47 3.2 Calculation of Reactor Neutrino Flux . . . . . . . . . . . . . . . . 50 3.3 Expected Interaction Antineutrino Spectrum . . . . . . . . . . . . 56 3.4 Systematic Uncertainties of Expected Reactor Neutrino Flux and Spectrum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 3.5 Monte Carlo Simulation . . . . . . . . . . . . . . . . . . . . . . . . 60 3.5.1 Detector Simulation . . . . . . . . . . . . . . . . . . . . . . 60 3.5.2 Monte-Carlo Event Reconstruction . . . . . . . . . . . . . . 64 4 Event Reconstruction 71 4.1 Energy Reconstruction . . . . . . . . . . . . . . . . . . . . . . . . . 71 4.2 Muon Energy Reconstruction . . . . . . . . . . . . . . . . . . . . . 73 4.3 Vertex Reconstruction . . . . . . . . . . . . . . . . . . . . . . . . . 73 5 Energy Calibration 81 5.1 Radioactive Sources . . . . . . . . . . . . . . . . . . . . . . . . . . 81 5.2 Source Driving System . . . . . . . . . . . . . . . . . . . . . . . . . 83 5.3 Energy Conversion Function . . . . . . . . . . . . . . . . . . . . . . 85 5.4 Energy Scale . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 5.5 Energy Resolution . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 6 Event Selection for IBD Candidates 93 6.1 Data Sample . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 6.2 Backgrounds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 6.2.1 Accidental Background . . . . . . . . . . . . . . . . . . . . 95 6.2.2 Fast Neutron Background . . . . . . . . . . . . . . . . . . . 95 6.2.3 Cosmogenic 9Li=8He Background . . . . . . . . . . . . . . 96 6.2.4 252Cf Contamination Background . . . . . . . . . . . . . . 97 6.3 IBD Selection Requirements . . . . . . . . . . . . . . . . . . . . . . 98 6.3.1 Removal of -Rays from Radioactivity, Noise and Flashers . 99 6.3.2 Removal of Accidental Background . . . . . . . . . . . . . . 103 6.3.3 Removal of Cosmogenic 9Li=8He Background . . . . . . . . 108 6.3.4 Removal of Fast Neutron Background . . . . . . . . . . . . 113 6.3.5 Further Removal of 252Cf Contamination Background . . . 118 6.4 Signal Loss due to Selection Requirements . . . . . . . . . . . . . . 122 6.4.1 Timing Veto with Muon or Trigger Information . . . . . . . 122 6.4.2 Remval of Flasher Events . . . . . . . . . . . . . . . . . . . 122 6.4.3 Removal of 252Cf Contamination Background . . . . . . . . 123 6.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 7 Estimation of Remaining Backgrounds 127 7.1 Accidental Background . . . . . . . . . . . . . . . . . . . . . . . . . 127 7.2 Fast Neutron Background . . . . . . . . . . . . . . . . . . . . . . . 130 7.3 Cosmogenic 9Li=8He Background . . . . . . . . . . . . . . . . . . . 133 7.4 252Cf Contamination Background . . . . . . . . . . . . . . . . . . 137 7.5 Summary of Backgrounds and Background Reduction since 500 live-day Result . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139 7.5.1 Background Reduction since 500 live-day Result . . . . . . 140 8 Systematic Uncertainty 143 8.1 Detector Related Uncertainties . . . . . . . . . . . . . . . . . . . . 143 8.1.1 Detection Efficiecny . . . . . . . . . . . . . . . . . . . . . . 143 8.1.2 IBD Selection Efficiency . . . . . . . . . . . . . . . . . . . . 147 8.1.3 Summary of Detection and IBD Selection Efficiencies . . . 154 8.2 Reactor Related Uncertainty . . . . . . . . . . . . . . . . . . . . . 155 8.3 Energy Scale Uncertainty . . . . . . . . . . . . . . . . . . . . . . . 156 8.4 Background Uncertainty . . . . . . . . . . . . . . . . . . . . . . . . 157 8.5 Summary of Systematic Uncertainty . . . . . . . . . . . . . . . . . 159 9 Results of theta13 and Measurement 161 9.1 Observed and Expected IBD Rates . . . . . . . . . . . . . . . . . . 161 9.2 Comparison of Observed and Expected IBD Spectra . . . . . . . . 163 9.3 Rate Only Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 163 9.3.1 2 Fitting of Rate Only Analysis . . . . . . . . . . . . . . . 165 9.4 Rate and Spectrum Analysis . . . . . . . . . . . . . . . . . . . . . 167 9.4.1 2 Fitting of Rate and Spectrum Analysis . . . . . . . . . . 167 9.5 Energy and Baseline-dependent Reactor neutrino Disappearance . . . . . 169 10 Fuel-dependent Variation of Antineutrino Yield and Spectrum 173 11 Summary and Discussion 179 iii A Muon Energy Correction 183 A.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183 A.2 New Muon Energy Correction . . . . . . . . . . . . . . . . . . . . . 183 A.3 Result of New Muon Energy Correction . . . . . . . . . . . . . . . 185 B Charge Correction 189 B.1 Temporal and Spatial Variation of Raw Charge . . . . . . . . . . . 189 B.2 Making Charge Correction . . . . . . . . . . . . . . . . . . . . . . . 189 B.3 Stability Check after Applying Charge Correction . . . . . . . . . . 193 C Development of Flasher Cut 197 C.1 Finding highly flashing QmaxPMT . . . . . . . . . . . . . . . . . . 197 C.1.1 Condition on Qmax/Qtot and Qave/Qmax . . . . . . . . . . . 197 C.1.2 Condition on Large R . . . . . . . . . . . . . . . . . . . . 198 C.1.3 Condition on Accidental Background Rate . . . . . . . . . . 199 C.1.4 Development of Flasher Cut . . . . . . . . . . . . . . . . . . 200 D More Details of Signal Loss due to IBD Selection Requirements203 D.1 Timing Veto with Muon or Trigger Information . . . . . . . . . . . 203 D.2 Removal of Adjacent IBD Pairs . . . . . . . . . . . . . . . . . . . . 207 D.3 Removal of Flasher Events . . . . . . . . . . . . . . . . . . . . . . . 208 D.4 Removal of 252Cf Contamination Background . . . . . . . . . . . . 209 D.4.1 Removal of Hotspot . . . . . . . . . . . . . . . . . . . . . . 209 D.4.2 252Cf background Removal by Temporal and Spatial Cor- relation with Prompt Candidates . . . . . . . . . . . . . . . 209 Bibliography 213Docto

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    ๋ณธ ๋ฐœ๋ช…์€ RF ํƒœ๊ทธ๋ฅผ ์ด์šฉํ•œ ์Šค๋งˆํŠธ ๋ฌผํ’ˆ ๊ด€๋ฆฌ ์žฅ์น˜ ๋ฐ ๊ทธ ๋ฐฉ๋ฒ•์— ๊ด€ํ•œ ๊ฒƒ์œผ๋กœ, ๋ณธ ๋ฐœ๋ช…์˜ ์ผ ์‹ค์‹œ์˜ˆ์— ๋”ฐ๋ฅธ RF ํƒœ๊ทธ๋ฅผ ์ด์šฉํ•œ ์Šค๋งˆํŠธ ๋ฌผํ’ˆ ๊ด€๋ฆฌ ์žฅ์น˜๋Š”, RF ๋ฆฌ๋”๊ธฐ๋ฅผ ํ†ตํ•ด ๋ณต์ˆ˜์˜ ์œ„์น˜ ์‹๋ณ„ RF ํƒœ๊ทธ๊ฐ€ ๊ตฌ์—ญ๋ณ„๋กœ ์„ค์น˜๋œ RF ์„ ๋ฐ˜ ๋ฐ ๋ฌผํ’ˆ ์‹๋ณ„ RF ํƒœ๊ทธ๊ฐ€ ๋ถ€์ฐฉ๋œ ๋ณต์ˆ˜์˜ RF ๋ฌผํ’ˆ๊ณผ RF ํ†ต์‹ ํ•˜๋Š” ์Šค๋งˆํŠธ ๋ฌผํ’ˆ ๊ด€๋ฆฌ ์žฅ์น˜์— ์žˆ์–ด์„œ, ์ƒ๊ธฐ RF ์„ ๋ฐ˜ ๋ฐ ์ƒ๊ธฐ ๋ณต์ˆ˜์˜ RF ๋ฌผํ’ˆ์„ ํฌํ•จํ•˜๋Š” ์˜์—ญ์— ๊ธฐ ์„ค์ •๋œ ์ฃผ๊ธฐ๋งˆ๋‹ค ์ „์†ก๋œ ํ˜ธ์ถœ์‹ ํ˜ธ์— ๋Œ€์‘ํ•œ ์‘๋‹ต์‹ ํ˜ธ์˜ ๊ฐ•๋„๋ฅผ ์ธก์ •ํ•˜๋Š” ์‘๋‹ต์‹ ํ˜ธ ๊ฐ•๋„ ์ธก์ •๋ถ€์™€, ์ƒ๊ธฐ ์‘๋‹ต์‹ ํ˜ธ์— ๊ธฐ ์„ค์ •๋œ ์‹ ํ˜ธ ๊ฐ•๋„ ๋ฒ”์œ„๋ฅผ ์ดˆ๊ณผํ•˜๋Š” ๊ฐ„์„ญ์‹ ํ˜ธ์˜ ๋ฐœ์ƒ ์—ฌ๋ถ€ ๋ฐ ์ƒ๊ธฐ ์‘๋‹ต์‹ ํ˜ธ๋ฅผ ๊ธฐ ์„ค์ •๋œ RF ๋ฌผํ’ˆ์˜ ์‹๋ณ„ ์ •๋ณด์™€ ๋น„๊ตํ•˜์—ฌ ์ƒˆ๋กœ์šด RF ๋ฌผํ’ˆ์— ๋Œ€ํ•œ ์‹๋ณ„ ์ •๋ณด์˜ ํฌํ•จ ์—ฌ๋ถ€๋ฅผ ํŒ๋‹จํ•˜๋Š” ํŒ๋‹จ๋ถ€์™€, ์ƒ๊ธฐ ์‘๋‹ต์‹ ํ˜ธ์— ์ƒ๊ธฐ ์‹ ํ˜ธ ๊ฐ•๋„ ๋ฒ”์œ„๋ฅผ ์ดˆ๊ณผํ•˜๋Š” ๊ฐ„์„ญ์‹ ํ˜ธ๊ฐ€ ๋ฐœ์ƒํ•˜๊ณ , ์ƒˆ๋กœ์šด RF ๋ฌผํ’ˆ์˜ ์‹๋ณ„ ์ •๋ณด๊ฐ€ ํฌํ•จ๋˜๋Š” ๊ฒฝ์šฐ, ์ƒ๊ธฐ ๋ณต์ˆ˜์˜ RF ๋ฌผํ’ˆ ๊ฐ„์— ๊ฐ„์„ญ์‹ ํ˜ธ ๊ทธ๋ฃน์„ ์„ค์ •ํ•˜๋Š” ๊ฐ„์„ญ์‹ ํ˜ธ ๊ทธ๋ฃน ์„ค์ •๋ถ€์™€, ์ƒ๊ธฐ ์ƒ์„ฑ๋œ ๊ฐ„์„ญ์‹ ํ˜ธ ๊ทธ๋ฃน์— ํฌํ•จ๋˜๋Š” ๋ณต์ˆ˜์˜ RF ๋ฌผํ’ˆ์— ๋ถ€์—ฌ๋œ ๊ฐ€์ค‘์น˜ ์ •๋ณด ๋ฐ ์ƒ๊ธฐ RF ์„ ๋ฐ˜์˜ ์œ„์น˜ ์‹๋ณ„ ์ •๋ณด๋ฅผ ์ด์šฉํ•˜์—ฌ ์ƒ๊ธฐ ์ƒˆ๋กœ์šด RF ๋ฌผํ’ˆ์˜ ์œ„์น˜๋ฅผ ์ถ”์ •ํ•˜๋Š” ์œ„์น˜ ์ถ”์ •๋ถ€๋ฅผ ํฌํ•จํ•œ๋‹ค. ์ด์— ๋”ฐ๋ผ, RF ํƒœ๊ทธ๊ฐ€ ๋ถ€์ฐฉ๋œ ๋ฌผํ’ˆ ๊ฐ„์˜ ๊ฐ„์„ญ์‹ ํ˜ธ์˜ ๋ณ€ํ™” ๊ฐ•๋„๋ฅผ ์ด์šฉํ•จ์œผ๋กœ์จ ๋ฌผํ’ˆ์˜ ์œ„์น˜๋ฅผ ๋ณด๋‹ค ์ •ํ™•ํ•˜๊ฒŒ ์ถ”์ •ํ•  ์ˆ˜ ์žˆ๋‹ค.RF ๋ฆฌ๋”๊ธฐ๋ฅผ ํ†ตํ•ด ๋ณต์ˆ˜์˜ ์œ„์น˜ ์‹๋ณ„ RF ํƒœ๊ทธ๊ฐ€ ๊ตฌ์—ญ๋ณ„๋กœ ์„ค์น˜๋œ RF ์„ ๋ฐ˜ ๋ฐ ๋ฌผํ’ˆ ์‹๋ณ„ RF ํƒœ๊ทธ๊ฐ€ ๋ถ€์ฐฉ๋œ ๋ณต์ˆ˜์˜ RF ๋ฌผํ’ˆ๊ณผ RF ํ†ต์‹ ํ•˜๋Š” ์Šค๋งˆํŠธ ๋ฌผํ’ˆ ๊ด€๋ฆฌ ์žฅ์น˜์— ์žˆ์–ด์„œ,์ƒ๊ธฐ RF ์„ ๋ฐ˜ ๋ฐ ์ƒ๊ธฐ ๋ณต์ˆ˜์˜ RF ๋ฌผํ’ˆ์„ ํฌํ•จํ•˜๋Š” ์˜์—ญ์— ๊ธฐ ์„ค์ •๋œ ์ฃผ๊ธฐ๋งˆ๋‹ค ์ „์†ก๋œ ํ˜ธ์ถœ์‹ ํ˜ธ์— ๋Œ€์‘ํ•œ ์‘๋‹ต์‹ ํ˜ธ์˜ ๊ฐ•๋„๋ฅผ ์ธก์ •ํ•˜๋Š” ์‘๋‹ต์‹ ํ˜ธ ๊ฐ•๋„ ์ธก์ •๋ถ€;์ƒ๊ธฐ ์‘๋‹ต์‹ ํ˜ธ์— ๊ธฐ ์„ค์ •๋œ ์‹ ํ˜ธ ๊ฐ•๋„ ๋ฒ”์œ„๋ฅผ ์ดˆ๊ณผํ•˜๋Š” ๊ฐ„์„ญ์‹ ํ˜ธ์˜ ๋ฐœ์ƒ ์—ฌ๋ถ€ ๋ฐ ์ƒ๊ธฐ ์‘๋‹ต์‹ ํ˜ธ๋ฅผ ๊ธฐ ์„ค์ •๋œ RF ๋ฌผํ’ˆ์˜ ์‹๋ณ„ ์ •๋ณด์™€ ๋น„๊ตํ•˜์—ฌ ์ƒˆ๋กœ์šด RF ๋ฌผํ’ˆ์— ๋Œ€ํ•œ ์‹๋ณ„ ์ •๋ณด์˜ ํฌํ•จ ์—ฌ๋ถ€๋ฅผ ํŒ๋‹จํ•˜๋Š” ํŒ๋‹จ๋ถ€;์ƒ๊ธฐ ์‘๋‹ต์‹ ํ˜ธ์— ์ƒ๊ธฐ ์‹ ํ˜ธ ๊ฐ•๋„ ๋ฒ”์œ„๋ฅผ ์ดˆ๊ณผํ•˜๋Š” ๊ฐ„์„ญ์‹ ํ˜ธ๊ฐ€ ๋ฐœ์ƒํ•˜๊ณ , ์ƒˆ๋กœ์šด RF ๋ฌผํ’ˆ์˜ ์‹๋ณ„ ์ •๋ณด๊ฐ€ ํฌํ•จ๋˜๋Š” ๊ฒฝ์šฐ, ์ƒ๊ธฐ ๋ณต์ˆ˜์˜ RF ๋ฌผํ’ˆ ๊ฐ„์— ๊ฐ„์„ญ์‹ ํ˜ธ ๊ทธ๋ฃน์„ ์„ค์ •ํ•˜๋Š” ๊ฐ„์„ญ์‹ ํ˜ธ ๊ทธ๋ฃน ์„ค์ •๋ถ€; ๋ฐ์ƒ๊ธฐ ์„ค์ •ํ•œ ๊ฐ„์„ญ์‹ ํ˜ธ ๊ทธ๋ฃน์— ํฌํ•จ๋˜๋Š” ๋ณต์ˆ˜์˜ RF ๋ฌผํ’ˆ์— ๋ถ€์—ฌ๋œ ๊ฐ€์ค‘์น˜ ์ •๋ณด ๋ฐ ์ƒ๊ธฐ RF ์„ ๋ฐ˜์˜ ์œ„์น˜ ์‹๋ณ„ ์ •๋ณด๋ฅผ ์ด์šฉํ•˜์—ฌ ์ƒ๊ธฐ ์ƒˆ๋กœ์šด RF ๋ฌผํ’ˆ์˜ ์œ„์น˜๋ฅผ ์ถ”์ •ํ•˜๋Š” ์œ„์น˜ ์ถ”์ •๋ถ€๋ฅผ ํฌํ•จํ•˜๋Š” RF ํƒœ๊ทธ๋ฅผ ์ด์šฉํ•œ ์Šค๋งˆํŠธ ๋ฌผํ’ˆ ๊ด€๋ฆฌ ์žฅ์น˜

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