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    ๊ณ ์œ ๋Ÿ‰๋น„๊ฐ•์บ๋‰ผ๋ผ๋ฅผ ์ ์šฉํ•˜๋Š” ์†Œ์•„ ํ™˜์ž์—์„œ ๋น„์นจ์Šต์  ์ง€ํ‘œ๋ฅผ ์ด์šฉํ•œ ํ˜ธํก๋ถ€์ „ ๊ฒฝ๊ณผ ์˜ˆ์ธก์— ๋Œ€ํ•œ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ์˜๊ณผ๋Œ€ํ•™ ์˜ํ•™๊ณผ, 2023. 2. ์„œ๋™์ธ.์—ฐ๊ตฌ๋ฐฐ๊ฒฝ: ๊ณ ์œ ๋Ÿ‰๋น„๊ฐ•์บ๋‰ผ๋ผ๋Š” ํ˜ธํก๋ถ€์ „ ์†Œ์•„์—์„œ ์œ ์šฉํ•œ ํ˜ธํก ๋ณด์กฐ ์žฅ์น˜์ด์ง€๋งŒ ๊ธฐ๊ด€ ์‚ฝ๊ด€๊ณผ ๊ฐ™์€ ์นจ์Šต์  ๊ธฐ๋„ ํ™•๋ณด์˜ ์‹œ์ ์„ ๋Šฆ์ถœ ์ˆ˜ ์žˆ๋‹ค๊ณ  ์•Œ๋ ค์ ธ ์žˆ๋‹ค. ์ตœ๊ทผ์—๋Š” ๊ณ ์œ ๋Ÿ‰๋น„๊ฐ•์บ๋‰ผ๋ผ์˜ ์‹คํŒจ๋ฅผ ์กฐ๊ธฐ์— ์˜ˆ์ธกํ•˜๊ธฐ ์œ„ํ•ด ๊ฒฝํ”ผ์  ์‚ฐ์†Œ ํฌํ™”๋„, ์‚ฐ์†Œ๋ถ„์••๊ณผ ํ˜ธํก์ˆ˜๋ฅผ ์ด์šฉํ•œ ์—ฌ๋Ÿฌ ์ง€ํ‘œ๊ฐ€ ์ œ์‹œ๋˜์–ด ์™”๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ๊ณ ์œ ๋Ÿ‰๋น„๊ฐ•์บ๋‰ผ๋ผ๋ฅผ ์ ์šฉํ•˜๋Š” ํ™˜์ž์—์„œ ํ˜ธํก๋ถ€์ „์„ ์˜ˆ์ธกํ•˜๊ธฐ ์œ„ํ•œ ๋‹ค์–‘ํ•œ ๋น„์นจ์Šต์  ์ง€ํ‘œ๋ฅผ ํ‰๊ฐ€ํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ๋ฐฉ๋ฒ•: ๊ณ ์œ ๋Ÿ‰๋น„๊ฐ•์บ๋‰ผ๋ผ์—์„œ ์ถ”๊ฐ€ ํ˜ธํก ๋ณด์กฐ๋ฅผ ํ•„์š”๋กœ ํ–ˆ๋˜ ํ™˜์ž๋“ค์€ ๊ธฐ๊ด€์‚ฝ๊ด€์˜ ์›์ธ์— ๋”ฐ๋ผ hypoxic respiratory failure (HRF)์™€ non-HRF (NHRF)๋กœ ๋ถ„๋ฅ˜๋˜์—ˆ๋‹ค. ๊ฒฝํ”ผ์  ์‚ฐ์†Œํฌํ™”๋„๋ฅผ ์‚ฐ์†Œ๋ถ„์œจ๋กœ ๋‚˜๋ˆˆ ๋น„(S/F), S/F๋ฅผ RR๋กœ ๋‚˜๋ˆˆ ๋น„ (ROX), S/F๋ฅผ ํ˜ธํก์ˆ˜์˜ ์ค‘๊ฐ„๊ฐ’ ๋Œ€๋น„ ํ™˜์ž์˜ ํ˜ธํก์ˆ˜๋กœ ๋‚˜๋ˆˆ ๋น„ (ROX-M), S/F๋ฅผ ํ™˜์ž ํ˜ธํก์ˆ˜์˜ z score๋กœ ๋‚˜๋ˆˆ ๋น„๋ฅผ ๊ณ„์‚ฐํ•˜์—ฌ ์ง€ํ‘œ๋กœ์„œ์˜ ๊ฐ€์น˜๋ฅผ ๋น„๊ตํ•˜์˜€๋‹ค. ๊ณ ์œ ๋Ÿ‰๋น„๊ฐ•์บ๋‰ผ๋ผ๋Š” ์ œ๊ฑฐํ•œ ๊ตฐ, HRF, NHRF ๊ตฐ ์‚ฌ์ด์— ๋‚˜ํƒ€๋‚œ ๊ฐ ์ง€ํ‘œ์˜ ์ฐจ์ด๋ฅผ ๋น„๊ตํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ๊ฒฐ๊ณผ: 152๋ช…์˜ ์ฆ๋ก€๋ฅผ ์ˆ˜์ง‘ํ•˜์˜€๋Š”๋ฐ ์ด์ค‘ 45๋ช…(29.6%0)๋Š” ๊ณ ์œ ๋Ÿ‰๋น„๊ฐ•์บ๋‰ผ๋ผ๋ฅผ ์ œ๊ฑฐํ•˜์ง€ ๋ชปํ•˜์˜€๋‹ค. ์ด ์ค‘ 21๋ช…(46.7%)๋Š” HRF์— ์†ํ•˜์˜€๊ณ , 24๋ช…(53.3%)๋Š” NHRF์˜€๋‹ค. 3์‹œ๊ฐ„๊ณผ 6์‹œ๊ฐ„์— ์ธก์ •๋œ S/F์™€ ROX-M ๊ฐ’์€ ๋†’์€ AUC ๊ฐ’์„ ๋ณด์—ฌ ๊ฐ๊ฐ HRF๋ฅผ ์˜ˆ์ธกํ•˜๋Š” ์ข‹์€ ์ง€ํ‘œ๋กœ ์ œ์‹œ๋˜์—ˆ๋‹ค. ๋ฐ˜๋ฉด ์ดˆ๊ธฐ์˜ ๊ณ ํƒ„์‚ฐํ˜ˆ์ฆ๊ณผ ์ €์ฒด์ค‘์ด ๊ฐ๊ฐ NHRF์˜ ์œ„ํ—˜ ์š”์†Œ๋กœ ์ œ์‹œ๋˜์—ˆ๋‹ค. ๊ฒฐ๋ก : ๊ณ ์œ ๋Ÿ‰๋น„๊ฐ•์บ๋‰ผ๋ผ๋ฅผ ์ ์šฉํ•˜๋Š” ์†Œ์•„์—์„œ ๊ธฐ๊ด€์‚ฝ๊ด€์„ ์กฐ๊ธฐ์— ๊ฒฐ์ •ํ•˜๋Š”๋ฐ ์žˆ์–ด 65mmHg ์ด์ƒ์˜ ๊ณ ํƒ„์‚ฐํ˜ˆ์ฆ ์œ ๋ฌด์™€ ์ €์ฒด์ค‘ ์—ฌ๋ถ€, ๊ทธ๋ฆฌ๊ณ  S/F, ROX-M ๋“ฑ์„ ๋ชจ๋‹ˆํ„ฐํ•˜๋Š” ๊ฒƒ์€ ์œ ์šฉํ•œ ์˜ˆ์ธก ์ง€ํ‘œ๋กœ ์‚ฌ์šฉ๋  ์ˆ˜ ์žˆ๋‹ค.Background: High-flow nasal cannula (HFNC) is a useful respiratory support for children with respiratory distress; however, it elevates the risk of belated intubation. Recently, indices based on percutaneous oxygen saturation (SpO2),a fraction of inspired oxygen (FiO2), and respiratory rate (RR) have been suggested for predicting HFNC failure. We aimed to evaluate various indices predicting HFNC failure in children who started receiving HFNC at this tertiary center for 27months. Methods: Cases of HFNC failure were classified as hypoxic respiratory failure (HRF) or non-HRF (NHRF) according to the cause of intubation. Ratio of SpO2 by FiO2 (S/F), ratio of S/F by RR (ROX), ratio of S/F by RR/median RR (ROX-M), and ratio of S/F by z-score of RR (ROX-Z) were calculated and compared between groups. Results: Of the 152 cases, 45 (29.6%) failed to wean off the HFNC support, of which 21 (46.7%) were HRFs and 24 (53.3%) were NHRFs. S/F and ROX-M at 6 and 3 hours, respectively, showed good predictability for predicting HRF with high area under the curve. Whereas initial hypercapnia and low weight were good predictors for NHRF. Conclusions: For the management of children with HFNC, these risk factors and indicators should be monitored to make an early decision of intubation.Chapter 1. Introduction 1 Chapter 2. Methods 3 Chapter 3. Results 8 Chapter 4. Discussion 28 Chapter 5. Conclusions 33 Bibliography 34 Abstract in Korean 39์„

    ์ง€๊ตฌ์  ํ•ด์–‘๋ณด์ „์—์„œ ๋‚˜ํƒ€๋‚˜๋Š” ์กด์žฌ๋“ค์˜ ์—ฐํ•ฉ๊ณผ ๋ถ„์—ด

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ํ™˜๊ฒฝ๋Œ€ํ•™์› ํ™˜๊ฒฝ๊ณ„ํšํ•™๊ณผ, 2022. 8. ์œค์ˆœ์ง„.ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ๋Š” ์ธ๊ณต๋ฌผ์ด ํ•ด์–‘๊นŒ์ง€ ์ ๋ นํ•ด๋ฒ„๋ฆฐ ์ƒํ™ฉ์„ ๋ณด์—ฌ์คŒ์œผ๋กœ์จ, ์ธ๋ฅ˜์„ธ(Anthropocene)์—์„œ ๋‚˜ํƒ€๋‚˜๋Š” โ€˜์ธ๊ฐ„ ํ™œ๋™์— ์˜ํ•œ ์ž์—ฐ ํŒŒ๊ดดโ€™์˜ ๋Œ€ํ‘œ์ ์ธ ์˜ˆ์‹œ๋กœ ํ‘œ์ƒ๋˜๊ณ  ์žˆ๋‹ค. ์ด์ œ ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ์˜ ์‹ฌ๊ฐ์„ฑ์ด๋‚˜ ๋ฌธ์ œ์˜์‹์— ๊ณต๊ฐํ•˜๊ธฐ๋ž€ ์–ด๋ ต์ง€ ์•Š์œผ๋ฉฐ, ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ๋Š” ์‘๋‹น ์ œ๊ฑฐ๋˜์–ด์•ผ ํ•  ์‚ฌ๋ฌผ๋กœ ์ทจ๊ธ‰๋ฐ›๋Š”๋‹ค. ๊ตญ์ œ๊ธฐ๊ตฌ, ์ •๋ถ€, ํ™˜๊ฒฝ๋‹จ์ฒด, ๊ฐœ์ธ, ๊ธฐ์—…์— ์ด๋ฅด๊ธฐ๊นŒ์ง€ ์„œ๋กœ ๋‹ค๋ฅธ ํ–‰์œ„์ž๋“ค์€ ๊ฐ์ž์˜ ๋ฐฉ์‹์œผ๋กœ ํ˜น์€ ๊ทธ ๊ฒฝ๊ณ„๋ฅผ ๋„˜๋‚˜๋“ค๋ฉฐ ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ๋ฅผ ์ œ๊ฑฐํ•˜๊ธฐ ์œ„ํ•ด ๋…ธ๋ ฅํ•œ๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ๋ฐ”๋กœ ์ด๋Ÿฌํ•œ ์ƒํ™ฉ ์ธ์‹์—์„œ ์ถœ๋ฐœํ•œ๋‹ค. ์ฆ‰, ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ๋Š” โ€˜๋‹น์—ฐํžˆโ€™ ๋‚˜์œ ์‚ฌ๋ฌผ์ด๋ฉฐ, ํ•ด์–‘์€ ๊ทธ๋Ÿฌํ•œ ์‚ฌ๋ฌผ๋กœ๋ถ€ํ„ฐ โ€˜๋ณดํ˜ธโ€™๋ฐ›์•„์•ผํ•  ๊ณต๊ฐ„์ด๋ผ๋Š” ๋ช…์ œ์—์„œ ๋ง์ด๋‹ค. ์ด๋Ÿฌํ•œ ๋ช…์ œ๋Š” ๋„ˆ๋ฌด๋„ ๋‹น์—ฐํ•ด์„œ ์˜์‹ฌํ•  ์—ฌ์ง€์—†์ด โ€˜์‚ฌ์‹คโ€™๋กœ์„œ ์ทจ๊ธ‰๋˜๋ฉฐ, ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ์— ๋Œ€ํ•œ ์‚ฌํšŒ๊ณผํ•™ ์—ฐ๊ตฌ ์—ญ์‹œ๋„ ๊ทธ ์‚ฌ์‹ค์— ์ž…๊ฐํ•˜์—ฌ ์—ฐ๊ตฌ๋ฅผ ์ˆ˜ํ–‰ํ•ด์™”๋‹ค. ์š”์ปจ๋Œ€ ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ๋ฅผ ๋น„๋กฏํ•œ ํ™˜๊ฒฝ๋ฌธ์ œ์— ๋Œ€ํ•œ ์‚ฌํšŒ๊ณผํ•™์ ์ธ ์—ฐ๊ตฌ์˜ ๋Œ€๋ถ€๋ถ„์—์„œ ์‚ฌ๋ฌผ์˜ ์กด์žฌ ๋ฐฉ์‹์€ ๋„ˆ๋ฌด๋‚˜ ๋‹น์—ฐํ•ด์„œ ๋‹จ์ง€ ๋ฐฐ๊ฒฝ์ด ๋  ๋ฟ, ๊ถ๊ทน์ ์œผ๋กœ๋Š” ์‚ฌ๋žŒ๋“ค์˜ ์ธ์‹, ํ–‰๋™, ์ œ๋„, ๊ตฌ์กฐ ๋“ฑ, ์ธ๊ฐ„์ ์ธ ๊ฒƒ๋งŒ์ด ๊ด€์‹ฌ์˜ ๋Œ€์ƒ์ด ๋˜์—ˆ๋‹ค. ์ด๋•Œ ์—ฐ๊ตฌ๋“ค์€ ์ฃผ๋กœ ์‚ฌ๋ฌผ์˜ ๋ถ€์ •์„ฑ์„ ํ™•๊ณ ๋ถ€๋™ํ•œ ์œ„์น˜์— ๋†“์Œ์œผ๋กœ์จ ์—ฐ๊ตฌ์˜ ์ •๋‹น์„ฑ์„ ๋งˆ๋ จํ•ด์™”๋‹ค. ์ด๋Ÿฌํ•œ ํƒœ๋„๋Š” ์‚ฌ์‹ค์— ๋Œ€ํ•œ ํƒ๊ตฌ๋ฅผ ์ž์—ฐ๊ณผํ•™์˜ ์˜์—ญ์— ๋ฐฐ๋‹นํ•˜๊ณ , ์‚ฌํšŒ๊ณผํ•™์˜ ์—ญํ• ์„ ์ธ๊ฐ„์ ์ธ ๊ฒƒ, ์ด๋ฅผํ…Œ๋ฉด, ์‚ฌํšŒ, ์ •์น˜, ๋ฌธํ™” ๋“ฑ์— ๋Œ€ํ•œ ๋ถ„์„์œผ๋กœ๋งŒ ํ•œ์ •์‹œ์ผฐ๋˜ ๊ทผ๋Œ€์˜ ์ด๋ถ„๋ฒ•์„ ๋ฐ˜๋ณต์ ์œผ๋กœ ๋ณด์—ฌ์ค€๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ด ์—ฐ๊ตฌ๋Š”, ์‚ฌ์‹ค์„ ํ† ๋Œ€๋กœ ์—ฐ๊ตฌ๋ฅผ ์ˆ˜ํ–‰ํ•˜๊ธฐ๋ณด๋‹ค๋Š”, ์‚ฌ์‹ค์˜ ์ƒ์‚ฐ ๊ทธ ์ž์ฒด๋ฅผ ์—ฐ๊ตฌ์˜ ์ผ๋ถ€๋กœ ๋‹ค๋ฃฌ๋‹ค. ๊ทธ๋ฆฌํ•˜์—ฌ, ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ์™€ ํ•จ๊ป˜, ํ˜น์€ ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ๋ฅผ ํ†ตํ•ด ๋ณ€ํ™”ํ•˜๋Š” ์กด์žฌ๋“ค์„ ํ™˜๊ฒฝ์‚ฌํšŒํ•™์˜ ๋ณธ๊ฒฉ์ ์ธ ๋ฌธ์ œ๋กœ์„œ ๋‹ค๋ฃจ๊ณ ์ž ์‹œ๋„ํ•˜์˜€๋‹ค. ๋”ฐ๋ผ์„œ ์ด ์—ฐ๊ตฌ๋Š” ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ์— ๋Œ€ํ•œ ์„ ์•…์˜ ํŒ๋‹จ๊ณผ ๋‹น์œ„์— ์˜ํ•œ ํ–‰๋™์„ ์ด‰๊ตฌํ•˜๊ธฐ ์ด์ „์—, ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ์™€ ์šฐ๋ฆฌ๊ฐ€ ํ•จ๊ป˜ ์‚ด์•„๊ฐ€๋Š” ๋ฐฉ์‹์— ๋Œ€ํ•ด ํƒ๊ตฌํ•œ๋‹ค. ๊ณผ์—ฐ ์šฐ๋ฆฌ๋Š” ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ๋ฅผ ์–ด๋–ป๊ฒŒ ๋ณด์•„์™”์œผ๋ฉฐ, ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ๋ฅผ ํ†ตํ•ด ๋ฌด์—‡์„ ๋ณผ ์ˆ˜ ์žˆ์—ˆ์œผ๋ฉฐ, ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ์™€ ํ•จ๊ป˜ ํ™œ์„ฑํ™”๋˜๋Š”(animated) ๊ฒƒ๋“ค์€ ๋ฌด์—‡์ด์—ˆ๋Š”๊ฐ€? ์ด๋Ÿฌํ•œ ์งˆ๋ฌธ๋“ค์„ ํ†ตํ•ด ์ด ์—ฐ๊ตฌ๋Š” ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ์™€ ํ•จ๊ป˜ ๋งŒ๋“ค์–ด๊ฐ€๋Š” ์„ธ๊ณ„์˜ ์˜๋ฏธ์— ๋Œ€ํ•ด ํƒ๊ตฌํ•˜๋ฉฐ, ์šฐ๋ฆฌ ์‚ถ๊ณผ ์œ ๋ฆฌ๋œ ์ดˆ์›”์ ์ธ ์œค๋ฆฌ๊ฐ€ ์•„๋‹ˆ๋ผ ์‚ถ ์†์— ๋ฟŒ๋ฆฌ๋ฐ•ํ˜€ ์žˆ๋Š” ์œค๋ฆฌ์™€ ์‹ค์ฒœ์„ ๋ฐฐ์šฐ๊ณ ์ž ํ•˜์˜€๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ์ด๋Ÿฌํ•œ ์ดํ•ด๋ฅผ ์œ„ํ•˜์—ฌ ์šฐ์„  ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ๋ฅผ ์—ฐ๊ตฌ์˜ ์ฐธ์—ฌ์ž๋กœ ์—ฌ๊ธธ ์ˆ˜ ์žˆ๋Š” ์ด๋ก ์ ์ธ ํ† ๋Œ€๋ฅผ ํ˜•์„ฑํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ๊ธฐ์กด์— ํ™˜๊ฒฝ์‚ฌํšŒํ•™์—์„œ ๋…ผ์˜๋˜์–ด์™”๋˜ ์ž์—ฐ-์‚ฌํšŒ ๊ด€๊ณ„๋ก ์„ ์ ๊ฒ€ํ•˜๊ณ , ํŽ˜๋ฏธ๋‹ˆ์ŠคํŠธ ๊ณผํ•™๊ธฐ์ˆ ํ•™์ž์ธ ํ•ด๋Ÿฌ์›จ์ด์˜ ์ž์—ฐ๋ฌธํ™”(naturecultures) ๋…ผ์˜๋ฅผ ํ†ตํ•ด ๊ด€์ฐฐ ์˜์กด์ ์ธ ๋ณต์ˆ˜์˜ ์ž์—ฐ๊ณผ ์‚ฌํšŒ์— ๋Œ€ํ•ด ๋…ผํ•˜์˜€์œผ๋ฉฐ, ์ด๋•Œ ์ž์—ฐ๊ณผ ์‚ฌํšŒ ํ˜น์€ ์ž์—ฐ๊ณผ ๋ฌธํ™”๋ผ๋Š” ์ด ํ•ญ๋“ค์€ ๊ตฌ๋ณ„๋จ์œผ๋กœ์จ ์„œ๋กœ๋ฅผ ์ง€ํƒฑํ•˜๋ฉฐ ์„ธ๊ณ„๋ฅผ ๊ตฌ์„ฑํ•œ๋‹ค. ๋˜ํ•œ ๊ด€์ฐฐ์˜ ์กฐ๊ฑด์ธ ๊ด€์ฐฐ์ž์™€ ๊ด€์ฐฐ์ž์˜ ์„ธ๊ณ„๋ฅผ ๋…ผ์˜ํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์„ธ๊ณ„์ง“๊ธฐ(worlding)๋ผ๋Š” ๊ฐœ๋…์„ ๋„์ž…ํ•˜์˜€๋‹ค. ์„ธ๊ณ„์ง“๊ธฐ๋ž€ ์„ธ๊ณ„ ์†์˜ ์กด์žฌ์ž๋“ค์ด ์„ธ๊ณ„๋ฅผ ๋งŒ๋“ค์–ด๋‚˜๊ฐ€๋Š” ๊ณผ์ •์œผ๋กœ์„œ, ์ด๋•Œ ์„ธ๊ณ„๋Š” ์ดˆ์›”์ ์ธ ์„ค๊ณ„์ž์— ์˜ํ•ด ์ง€์–ด์ง„ ๊ณ ์ •๋œ ์šฉ๊ธฐ๊ฐ€ ์•„๋‹ˆ๋ผ ๋Š์ž„์—†์ด ํ˜•์„ฑ๋˜๋Š” ์‹œ๊ณต๊ฐ„์œผ๋กœ์„œ ๊ฐ€์ •๋œ๋‹ค. ์„ธ๊ณ„๋ฅผ ํ•จ๊ป˜ ์ง“๋Š” ์กด์žฌ๋“ค์€ ์ธ๊ฐ„์— ํ•œ์ •๋  ์ˆ˜ ์—†์œผ๋ฉฐ, ์กด์žฌ(์‚ฌ๋ฌผ ํ˜น์€ ๊ฐ์ฒด)์€ ์กด์žฌํ•œ๋‹ค๋Š” ์ธก๋ฉด์—์„œ ๋™์ผํ•œ ์œ„์ƒ์„ ์ง€๋‹ˆ๊ณ  ์žˆ๋‹ค๊ณ  ๋ณด์•˜๋‹ค. ๋˜ํ•œ ๊ฐ์ฒด-์ง€ํ–ฅ ์กด์žฌ๋ก ์—์„œ ์–ธ๊ธ‰๋˜๋Š” ์ดˆ๊ณผ๊ฐ์ฒด(hyperobject)๋ผ๋Š” ๊ฐœ๋…์ด ์ง€๋‹Œ ์œ ์šฉ์„ฑ์„ ํƒ๊ตฌํ•˜๋ฉด์„œ ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ๋ผ๋Š” ์‚ฌ๋ฌผ์„ ์ดˆ๊ณผ๊ฐ์ฒด๋กœ์„œ ๋ฐ”๋ผ๋ณด๊ธฐ ์œ„ํ•œ ํ† ๋Œ€๋ฅผ ๋งˆ๋ จํ•˜์˜€๋‹ค. ์ด ์—ฐ๊ตฌ์—์„œ ์ดˆ๊ณผ๊ฐ์ฒด๋ž€ ์‹œ๊ณต๊ฐ„์ ์œผ๋กœ ์œก์ค‘ํ•˜๊ฒŒ ๋‚˜ํƒ€๋‚˜๋Š” ์‚ฌ๋ฌผ์„ ์ผ์ปซ๋Š”๋‹ค(Morton, 2013). ์ž์—ฐ๊ณผ ์‚ฌํšŒ์˜ ๊ด€๊ณ„์™€ (์„ธ๊ณ„ ์†) ์„ธ๊ณ„์ง“๊ธฐ ๋…ผ์˜๋ฅผ ์‚ดํŽด๋ณด๋ฉด, โ€œ์ž์—ฐ ๋ณด์ „โ€์ด๋ž€ ๊ฐœ๋…์€ ๋ชจ์ˆœ์ ์ด๋‹ค. ์ž์—ฐ์˜ ์˜์—ญ๊ณผ ์ธ๊ฐ„์˜ ์˜์—ญ์„ ์ž„์˜์ ์œผ๋กœ ๊ตฌ๋ถ„ํ•จ์—๋„ ๊ทธ๊ฒƒ์ด ์ž„์˜์ ์ธ์ง€ ์•Œ์ง€ ๋ชปํ•˜๋Š” ๋งน๋ชฉ์„ฑ์„ ์ง€๋‹ˆ๊ณ  ์žˆ์œผ๋ฉฐ, ์ˆ˜๋™์ ์ธ ์ž์—ฐ๊ณผ ๋ณดํ˜ธ์ž ์ธ๊ฐ„์„ ๊ฐ€์ •ํ•  ๋ฟ๋”๋Ÿฌ ์ž์—ฐ์˜ ๋ณ€ํ™”์™€ ๋ณต์ˆ˜์„ฑ์„ ๊ฐ€๋ ค๋ฒ„๋ฆฌ๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ๊ทธ๋ ‡๊ธฐ์— ๋ผํˆฌ๋ฅด๋‚˜ ๋ชจํ„ด๊ณผ ๊ฐ™์€ ์—ฐ๊ตฌ์ž๋“ค์€ ์ž์—ฐ ๊ฐœ๋…์„ ํ๊ธฐํ•  ๊ฒƒ์„ ๊ถŒํ•˜๊ธฐ๋„ ํ•˜์˜€๋‹ค(Morton, 2007; Latour, 2017). ๊ทธ๋Ÿฌ๋‚˜ ํ˜„์‹ค์—์„œ ์‚ฌ์šฉ๋˜๋Š” ๊ฐœ๋…์„ ํ๊ธฐํ•  ๊ถŒ๋ฆฌ๋Š” ๋ˆ„๊ตฌ์—๊ฒŒ๋„ ์—†์œผ๋ฉฐ, ์ž์—ฐ ๋ณด์ „์˜ ์‹ค์ฒœ์€ ์ด๋ฏธ ์šฐ๋ฆฌ๋“ค์˜ ์„ธ๊ณ„ ์†์—์„œ ๊ณ ์œ ํ•œ ์˜๋ฏธ๋ฅผ ์—ฎ์–ด๊ฐ€๊ณ  ์žˆ๋‹ค. โ€˜์ž์—ฐ ๋ณด์ „โ€™์„ ๋ถ€์ •ํ•˜๋Š” ๊ฒƒ์€ ์ž์—ฐ ๋ณด์ „์— ๋Œ€ํ•œ ์‰ฌ์šด ๋น„ํŒ์ด๋ฉฐ, ์‚ฌ๋ฌผ์ด ์•ผ๊ธฐํ•˜๋Š” ์œ„ํ—˜๊ณผ ํ”ผํ•ด์— ๋ˆˆ ๊ฐ์•„ ๋ฒ„๋ฆฌ๊ฒŒ๋” ๋งŒ๋“œ๋Š” ํšจ๊ณผ๋ฅผ ๊ฐ€์ ธ์˜ฌ ์ˆ˜ ์žˆ๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ๊ทธ๋Ÿฌํ•œ ์‰ฌ์šด ๋น„ํŒ์„ ํ”ผํ•œ๋‹ค. ๋Œ€์‹ ์— ์šฐ๋ฆฌ์˜ ์‚ถ์ด ์ด๋ฏธ ํ—ˆ๊ตฌ์™€ ์‹ค์žฌ์˜ ์–ฝํž˜์ด๋ผ๋Š” ๋ชจ์ˆœ ์†์—์„œ ์กด์žฌํ•œ๋‹ค๋Š” ํ•ด๋Ÿฌ์›จ์ด(Haraway, 1997)์˜ ์ด์•ผ๊ธฐ๋ฅผ ๊ธฐ์–ตํ•˜๋ฉด์„œ, ์ž์—ฐ ๋ณด์ „์˜ ์ง‘ํ•ฉ์ฒด๊ฐ€ ์–ด๋–ค ์„ธ๊ณ„ ์†์— ์žˆ๊ณ , ๋ˆ„๊ตฌ์™€ ํ•จ๊ป˜ ์„ธ๊ณ„๋ฅผ ๋งŒ๋“ค์–ด ๊ฐ€๋Š”์ง€, ๊ทธ ์„ธ๊ณ„์ง“๊ธฐ์˜ ๊ณผ์ •์„ ์„ฌ์„ธํ•˜๊ฒŒ ์‚ดํŽด๋ณด๊ณ ์ž ํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ์ž๋Š” ์ด๋ฅผ ์œ„ํ•˜์—ฌ ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ์— ๋Œ€ํ•ด ํ™œ๋™ํ•˜๊ณ  ์—ฐ๊ตฌํ•˜๋Š” ๋น„์˜๋ฆฌํ™˜๊ฒฝ๋‹จ์ฒด์™€ ์ •๋ถ€์ถœ์—ฐ์—ฐ๊ตฌ์†Œ์—์„œ 13๊ฐœ์›” ๊ฐ„ ํ˜„์žฅ ์—ฐ๊ตฌ๋ฅผ ์ˆ˜ํ–‰ํ•˜์˜€๊ณ , ์ด๋ฅผ ํ† ๋Œ€๋กœ ๋ฏผ์กฑ์ง€(ethnography)๋ฅผ ์ž‘์„ฑํ•˜์˜€๋‹ค. ์ด๋•Œ ๋ฏผ์กฑ์ง€๋Š” ํŠน์ •ํ•œ ํŽธ์„ ๋ฏธ๋ฆฌ ๋“ค์ง€ ์•Š์œผ๋ฉด์„œ๋„ ๊ด€์‹ฌ ๊ฐ–๋Š” ์„ธ๊ณ„์— ๊นŠ๊ฒŒ ๊ฐœ์ž…ํ•˜๋Š” ๋ฐฉ์‹์˜ ์—ฐ๊ตฌ ๋ฐฉ๋ฒ•๋ก ์œผ๋กœ ์‚ฌ์šฉ๋˜์—ˆ๋‹ค. ์ด ์—ฐ๊ตฌ์—์„œ๋Š” ํฌ๊ฒŒ ๋„ค ๊ฐ€์ง€ ํ๋ฆ„ ์†์—์„œ ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ์™€ ํ•จ๊ป˜ ์ง“๋Š” ์„ธ๊ณ„๋ฅผ ํƒ๊ตฌํ•˜์˜€๋‹ค. ๋จผ์ € ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ์˜ ํƒ„์ƒ๊ณผ ํฌ์ฐฉ, ๋“œ๋Ÿฌ๋‚จ์— ๋Œ€ํ•ด ์‚ดํŽด๋ณด์•˜๋‹ค. ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ๋Š” ๋‹ค๋ฅธ ์‚ฌ๋ฌผ๋“ค๊ณผ ๊ตฌ๋ณ„๋˜๊ธฐ ์‹œ์ž‘ํ•  ๋•Œ๋ถ€ํ„ฐ ์ง€๊ตฌ์ ์ธ ๋ฌธ์ œ๋กœ ๋“ฑ์žฅํ–ˆ๋‹ค. ์ด๋•Œ ์‹œ๊ฐ์ด๋ผ๋Š” ํฌ์ฐฉ์˜ ๊ณผ์ •์€ ์œ„์น˜ ์ง€์–ด์ง„ ๋ชธ์— ์˜ํ•œ ๊ณผ์ •์œผ๋กœ์„œ ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ ๋ณด๊ธฐ๋Š” ์ œ๋„, ๋™๋ฌผ๊ณผ ๊ณผํ•™ ๋„๊ตฌ, ์‚ฌ๋ฌผ, ์ด๋ฏธ์ง€, ์ˆซ์ž ๋“ฑ์„ ํ†ตํ•ด ๊ฐ€์‹œํ™”๋˜์—ˆ๋‹ค. ํŠนํžˆ ๋ฏธ์„ธํ”Œ๋ผ์Šคํ‹ฑ์€ ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ๊ฐ€ ์‰ฝ๊ฒŒ ๋ณผ ์ˆ˜ ์žˆ๋Š” ์‚ฌ๋ฌผ์ด๋ผ๋Š” ๋ช…์ œ๋ฅผ ๋’ค์ง‘์œผ๋ฉด์„œ, ์‚ฌ๋ฌผ์„ ์ดํ•ดํ•˜๋Š” ์ƒˆ๋กœ์šด ๋ฐฉ์‹์„ ์—ฐ๊ฒฐ์‹œ์ผœ์ฃผ์—ˆ๋‹ค. ๋งจ๋ˆˆ์œผ๋กœ๋Š” ๋ณด๊ธฐ ํž˜๋“  ๋ฏธ์„ธํ”Œ๋ผ์Šคํ‹ฑ์˜ ์กด์žฌ๋Š” ์˜คํžˆ๋ ค ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ๋ฅผ ๊ณผํ•™์˜ ์žฅ์— ํŽธ์ž…๋  ์ˆ˜ ์žˆ๋„๋ก ํ—ˆ๋ฝํ•˜์˜€์œผ๋ฉฐ, ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ์— ๋Œ€ํ•œ ๋ณด์ „ ์‹ค์ฒœ์˜ ๋ฐฉ์‹ ์—ญ์‹œ๋„ ๋ฐ”๊พธ์—ˆ๋‹ค. ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ๋Š” ๋ฒˆ์—ญ์˜ ๊ณผ์ •์„ ๊ฑฐ์น˜๋ฉด์„œ ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ ๊ทธ ์ž์ฒด๋ณด๋‹ค ๋” ๋งŽ์€ ์˜๋ฏธ๋ฅผ ๋‹ด์ง€ํ•œ๋‹ค๋Š” ์˜๋ฏธ์—์„œ ๊ณผ์ž‰๋œ๋‹ค. ๋ฒˆ์—ญ๋œ ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ๋Š” ํ—ˆ๊ตฌ์„ฑ์œผ๋กœ๋ถ€ํ„ฐ ์ž์œ ๋กœ์šธ ์ˆ˜ ์—†๊ฒŒ ๋˜์ง€๋งŒ, ๋™์‹œ์— ๋ฐ”๋กœ ๊ทธ ์  ๋•Œ๋ฌธ์— ํ’๋ถ€ํ•œ ์˜๋ฏธ๋ฅผ ์ง€๋‹ ์ˆ˜ ์žˆ๊ฒŒ ๋œ๋‹ค. ๋˜ํ•œ ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ๋Š” ๋ฒˆ์—ญ๋  ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ๋‹ค๋ฅธ ์กด์žฌ๋“ค์„ ๋งค๊ฐœํ•˜๋ฉฐ, ํŠนํžˆ ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ ๊ด€์ฐฐ์ž์— ํŠน์ •ํ•œ ์„ธ๊ณ„๋ฅผ ๋ณผ ์ˆ˜ ์žˆ๋„๋ก ํ—ˆ์šฉํ•œ๋‹ค. ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ๋Š” ์ดˆ๊ณผ๊ฐ์ฒด๋กœ์„œ, ์‹œ๊ณต๊ฐ„์„ ์ดˆ์›”ํ•˜์—ฌ ์—ฌ๋Ÿฌ ์ง€์—ญ์˜ ํ•ด์–‘์„ ํ•˜๋‚˜์˜ ํ•ด์–‘์œผ๋กœ ๋ฌถ๊ณ  ๊ณผ๊ฑฐ์™€ ๋ฏธ๋ž˜์˜ ์‹œ๊ฐ„์„ ์—ฐ๊ฒฐํ•˜๋ฉด์„œ ๊ณต๊ฐ„์ ์œผ๋กœ ๊ท ์งˆํ•˜์ง€๋งŒ ์‹œ๊ฐ„์ ์œผ๋กœ๋Š” ๋‹จ์ ˆ๋œ ์„ธ๊ณ„๋ฅผ ์ƒ์ƒํ•˜๊ฒŒ ํ•œ๋‹ค. ์—ฌ๊ธฐ์—์„œ ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ๊ฐ€ ์ง€๊ตฌ๋ฅผ ํ•˜๋‚˜์˜ โ€˜๊ธ€๋กœ๋ฒŒ ๊ณต๊ฐ„โ€™์œผ๋กœ ๋งŒ๋“œ๋Š” ๋ฐ์— ๊ฒฐ์ •์ ์ธ ์—ญํ• ์„ ํ•˜๋Š” ๊ฒƒ์€ ํ•ด๋ฅ˜์ด๋‹ค. ํ•ด๋ฅ˜๋Š” ์ธ๊ฐ„์ด ์˜๋„ํ•˜์ง€ ์•Š์€ ์ธ๊ณต๋ฌผ์˜ ์ˆœํ™˜์„ ์•ผ๊ธฐํ•˜์˜€์œผ๋ฉฐ, ํŠนํžˆ ๋™์•„์‹œ์•„์˜ ํ•ด๋ฅ˜ ๋•๋ถ„์— ์ผ๋ณธ-ํ•œ๊ตญ-์ค‘๊ตญ์˜ ์ธ๊ฐ„๋“ค์ด ์ˆœํ™˜์ ์œผ๋กœ ๊ด€๊ณ„ ๋งบ์„ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋”๋ถˆ์–ด ์ง€๊ตฌ, ์ธ๊ฐ„, ํ”Œ๋ผ์Šคํ‹ฑ์ด๋ž€ ๊ฐ์ฒด๋“ค ๊ฐ„์˜ ์‹œ๊ฐ„ ์ฐจ์ด๋Š” ํšก๋‹จํ•˜๋Š” ๋ชธ๋“ค์˜ ์—ฐ๊ฒฐ์„ ์œ„ํ—˜์˜ ๊ด€์ ์—์„œ ์žฌ์ƒ์‚ฐํ•œ๋‹ค. ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ ๋•๋ถ„์— ๊ทธ์™€ ์—ฐ๊ฒฐ๋œ ์ธ๊ฐ„๋“ค์€ ์„ธ๊ณ„์˜ ํ˜ผ์ข…์„ฑ์„ ์ง์‹œํ•˜๊ฒŒ ๋˜๋ฉฐ ํ”Œ๋ผ์Šคํ‹ฑ์„ธ(Plasticocene)๋ฅผ ์„ ์–ธํ•˜๊ธฐ์— ์ด๋ฅธ๋‹ค. ์ด๋•Œ ํ”Œ๋ผ์Šคํ‹ฑ์„ธ๋Š” ํ˜ผ์ข…์„ฑ์ด ์•ผ๊ธฐํ•˜๋Š” ์œ„ํ—˜์˜ ์‹ ํ˜ธ๋กœ ๋‹ค๊ฐ€์˜ค๊ธฐ ๋•Œ๋ฌธ์—, ํ˜ผ์ข…์„ฑ์œผ๋กœ๋ถ€ํ„ฐ ํ•ด์–‘์„ ์ง€ํ‚ค๋ ค๋Š” ์‚ฌ๋žŒ๋“ค์€ ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ์™€์˜ โ€œ์ „์Ÿโ€์„ ์„ ํฌํ•˜๊ธฐ์— ์ด๋ฅธ๋‹ค. ์ด ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ์™€์˜ ์ „์Ÿ์€ ์ง€๊ตฌ์  ํ•ด์–‘๋ณด์ „์˜ ๋‹ค๋ฅธ ์ด๋ฆ„์œผ๋กœ, ๊ณผํ•™์—์˜ ์ˆœ์ข…์ด ๊ฐ•์กฐ๋œ๋‹ค. ๊ณผํ•™์€ ์‹ค์ฒœ์˜ ๊ทผ๊ฑฐ์ด์ž ์ „๋žต์ด ๋˜๋ฉฐ, ๊ณผํ•™์  ์ง€์‹์„ ํš๋“ํ•œ โ€˜์ „๋ฌธ๊ฐ€โ€™๋“ค์ด ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ ๋ฌธ์ œ์˜ ๋Œ€ํ‘œ์ž๊ฐ€ ๋˜์—ˆ๋‹ค. ๋˜ํ•œ ์ „๋ฌธ๊ฐ€๋Š” ๊ณผํ•™์„ ๋‹ด์ง€ํ•˜๋Š” ํˆฌ๋ช…ํ•œ ์กด์žฌ๋กœ ์—ฌ๊ฒจ์ง€๊ณ , ๊ณผํ•™ ์—ญ์‹œ ์ž์—ฐ์„ ์žˆ๋Š” ๊ทธ๋Œ€๋กœ ๋ณด์—ฌ์ฃผ๋Š” ์œ ์ผํ•œ ์ง€์‹ ํ˜•ํƒœ๋กœ ๊ฐ„์ฃผ๋œ๋‹ค. ์ด ๊ณผํ•™์„ ์ˆœ์ข…ํ•˜๋Š”์ง€, ๋ถˆ๋ณต์ข…ํ•˜๋Š”์ง€์— ๋”ฐ๋ผ ์˜ณ๊ณ  ๊ทธ๋ฆ„์ด ๋‚˜๋‰˜๊ธฐ ๋•Œ๋ฌธ์—, ์ด๋“ค์€ ๊ณผํ•™์„ ๋ฏฟ๋Š”๋‹ค๋ฉด ์‚ฌ์‹ค์ƒ ๋ˆ„๊ตฌ์™€๋„ ์‹ธ์šธ ํ•„์š”๊ฐ€ ์—†์–ด์ง„๋‹ค. ๋”ฐ๋ผ์„œ ์ด ์ „์Ÿ์€ ๋ˆ„๊ตฌ๋„ ๋น„ํŒ๋ฐ›์ง€ ์•Š๊ณ  ์˜ค์ง ํ˜‘๋ ฅ๋งŒ์„ ์š”์ฒญํ•˜๋Š” ๊ต์œก์˜ ํ˜•ํƒœ๊ฐ€ ๋˜์—ˆ๋‹ค. ํ•˜์ง€๋งŒ ์ด ๋ชจ์ˆœ๋œ ์ „์Ÿ์ด ์ง€๋‹Œ ํ•œ๊ณ„์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ , ์ƒˆ๋กœ์šด ์„ธ๊ณ„๋ฅผ ์ง์กฐํ•  ๊ฐ€๋Šฅ์„ฑ์€ ์ „์Ÿ ์•ˆ์— ์žˆ์—ˆ๋‹ค. ์ ์„ ์•Œ์•„๊ฐ€๊ณ  ์ดํ•ดํ•ด๊ฐ€๋Š” ๊ณผํ•™์  ํƒ๊ตฌํ™œ๋™์˜ ์ˆ˜ํ–‰ ์†์—์„œ, ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ๋ผ๋Š” ์ดˆ๊ณผ๊ฐ์ฒด๋Š” ๋ถ„๋ฅ˜๋จ์œผ๋กœ์จ ์ชผ๊ฐœ์ง€๊ณ  ๋‹ค๋ฅธ ์กด์žฌ๋“ค์ด ๋ถ€์ƒํ•˜๊ฒŒ ๋˜๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ์ด๋•Œ ๋ถ„๋ฅ˜๋Š” ์•Ž์˜ ๊ธฐ๋ณธ์ ์ธ ํ–‰์œ„์ด์ž ๋‹ค๋ฅธ ์‹ค์ฒœ์„ ์œ ๋„ํ•˜๋Š” ์ •์น˜์ ์ธ ํ–‰์œ„์ด๋ฉฐ, ์ž…์žฅ์— ๋”ฐ๋ผ ๋‹ค๋ฅธ ๋ถ„๋ฅ˜๋ฅผ ์„ ํ˜ธํ•˜๊ฒŒ ๋œ๋‹ค. ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ์˜ ๋ถ€๋ถ„๋“ค์ด ๊ด€์‹ฌ์˜ ๋Œ€์ƒ์ด ๋จ์œผ๋กœ์จ, ๊ฐ€๋ น ์Šคํ‹ฐ๋กœํผ ๋ถ€์ž๋‚˜ ์–ด๊ตฌ, ์‚ฌํƒ• ๊ป์งˆ ๋“ฑ์ด ์ฃผ๋ชฉ๋จ์œผ๋กœ์จ, ํ˜น์€ ํ•ด์ƒ๊ธฐ์ธ๊ณผ ์œก์ƒ๊ธฐ์ธ ์“ฐ๋ ˆ๊ธฐ๋ผ๋Š” ์ด๋ฆ„์„ ํš๋“ํ•จ์œผ๋กœ์จ ์ธ๊ฐ„์€ ๊ฒฐ์ฝ” ํ•˜๋‚˜์˜ ์ธ๊ฐ„์ด ์•„๋‹ˆ๋ผ ์ž…์žฅ์„ ๋‹ฌ๋ฆฌํ•˜๋Š” ์ธ๊ฐ„๋“ค์ด ๋˜๋ฉฐ, ๊ทธ๋“ค๊ณผ ์—ฐํ•ฉํ•˜๋Š” ๋น„์ธ๊ฐ„ ์—ญ์‹œ ๋น„์ธ๊ฐ„โ€˜๋“คโ€™์ด ๋œ๋‹ค. ์ด์— ๋”ฐ๋ผ ์‚ฌ๋ฌผ ์ •์น˜๋Š” ์ธ๊ฐ„ ๋Œ€ ๋น„์ธ๊ฐ„์˜ ์ •์น˜๊ฐ€ ์•„๋‹ˆ๋ผ {๋น„์ธ๊ฐ„-์ธ๊ฐ„}์˜ ์—ฐํ•ฉ๋“ค ๊ฐ„์˜ ์ •์น˜์ด๋ฉฐ, ์ด ์—ฐํ•ฉ๋“ค์€ ํƒ€ํ˜‘๊ณผ ์ ๋Œ€, ๋ถ„์—ด๊ณผ ์žฌ๊ฒฐํ•ฉ์„ ๋ฐ˜๋ณตํ•œ๋‹ค. ๊ทธ ๊ณผ์ •์—์„œ ์‚ฌ๋ฌผ๊ณผ์˜ ์ „์Ÿ์€ ํŒจ๋ฐฐ๋ฅผ ์˜ˆ๊ฒฌํ•จ์—๋„ ์ ˆ๋งํ•˜์ง€ ์•Š์„ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ด๋กœ์จ ๊ณผํ•™์€ ๊ทธ ์ž์ฒด๋กœ ์˜ˆ์ฐฌ๋˜๊ฑฐ๋‚˜ ๋ถ€์ •๋  ๊ฒƒ์ด ์•„๋‹ˆ๋ผ ์ˆœ์ข…์„ ์š”๊ตฌํ•˜๋Š” ๊ทœ๋ฒ”์ด ์•„๋‹ˆ๋ผ ์ •๋‹ต์ด ์—†๋Š” ์ •์น˜๋ฅผ ์‹คํ˜„ํ•˜๊ธฐ ์œ„ํ•œ ๋„๊ตฌ๋กœ์„œ ์ดํ•ด๋˜์—ˆ๋‹ค. ์„ธ๊ณ„์˜ ๋™์  ๊ฐ€๋Šฅ์„ฑ์€ ์ž์นซํ•˜๋ฉด ๋ฌดํ•œํ•œ ๋‹ค์ค‘์„ฑ๊ณผ ์šฐ์—ฐ์„ฑ์˜ ์˜ˆ์ฐฌ์œผ๋กœ ์ •๋ฆฌ๋˜๊ธฐ ์‰ฝ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์กด์žฌ์˜ ๊ตฌ์กฐ์ ์ธ ์ œ์•ฝ์€ ๊ฒฐ์ฝ” ์šฐ๋ฆฌ์—๊ฒŒ ์ฑ…์ž„์„ ๋ฐฉ๊ธฐํ•˜๋„๋ก ๋‚ด๋ฒ„๋ ค๋‘์ง€ ์•Š๋Š”๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ์™€ ์ธ๊ฐ„์˜ ๊ด€๊ณ„๊ฐ€ ๋ฌดํ•œํ•œ ๊ฐ€๋Šฅ์„ฑ์˜ ์ง€ํ‰์— ์žˆ๋‹ค๊ณ  ์ด์•ผ๊ธฐํ•˜๋ฉด์„œ๋„, ๋™์‹œ์— ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ์˜ ํ”ผํ•ด๊ฐ€ ์‹ฌ๊ฐํ•˜๋ฉฐ ์šฐ๋ฆฌ๊ฐ€ ๋ฌด์–ธ๊ฐ€๋ฅผ ํ•ด์•ผ ํ•œ๋‹ค๋Š” ๊ฒƒ์„ ๊ฒฐ์ฝ” ๋ถ€์ •ํ•˜์ง€ ์•Š๋Š”๋‹ค. ์—ฌ๊ธฐ์—์„œ ์ œ๊ธฐํ•˜๋Š” ๋ฌธ์ œ๋Š” ์˜คํžˆ๋ ค ๊ด€๊ณ„ ๋งบ์Œ์˜ ํƒœ๋„์ธ๋ฐ, ์–ด๋–ค ๋ชจ์Šต์œผ๋กœ ๋‚˜ํƒ€๋‚ ์ง€ ๋ชจ๋ฅด๋Š” ํƒ€์ž๋ฅผ ํ–ฅํ•œ โ€˜์ธ๊ฐ„โ€™์˜ ํƒœ๋„์—๋Š” ์˜ค๋งŒํ•จ์ด ๋‚ด์žฌ๋˜์–ด ์žˆ๋‹ค๋Š” ์ ์ด๋‹ค. ๊ทธ๋Š” ์„ธ๊ณ„๋ฅผ ์ด๊ด„ํ•˜๋ ค๋Š” ์•ผ์‹ฌ์— ์„ธ๊ณ„๋ฅผ ๊ท ์งˆํ•˜๊ฒŒ ๋งŒ๋“ค์–ด๋ฒ„๋ฆฐ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์šฐ๋ฆฌ๋Š” ๊ทธ ์˜ค๋งŒํ•จ์˜ ๋‚ด๋Ÿฌํ‹ฐ๋ธŒ๋ฅผ ์ชผ๊ฐค ๋•Œ, ์ „์ฒด๋ณด๋‹ค ํฐ ๋ถ€๋ถ„๋“ค์„ ๋งŒ๋‚˜๊ฒŒ ๋˜๋ฉฐ, ๋ถ€๋ถ„์„ฑ์œผ๋กœ๋ถ€ํ„ฐ ๊ฒธ์†ํ•จ์„ ๋˜์ฐพ๋Š”๋‹ค. ๊ทธ๋•Œ ์ธ๊ฐ„์€ ์ธ๊ฐ„โ€˜๋“คโ€™์ด ๋œ๋‹ค. ์ž‘์€ ์ธ๊ฐ„๋“ค์€ ์ž‘์€ ๋น„์ธ๊ฐ„๋“ค๊ณผ ์—ฐํ•ฉ๊ณผ ๋ถ„์—ด์„ ๋ฐ˜๋ณตํ•˜๋Š” ๊ณผ์ • ์†์—์„œ ์„ธ๊ณ„์˜ ๋ณต์žก์„ฑ๊ณผ ์šฐ์—ฐ์„ฑ์„ ๊ฐ๋‚ดํ•  ์ค„ ์•Œ๊ฒŒ ๋˜๋ฉฐ, ์ƒˆ๋กญ๊ฒŒ ์ถœํ˜„ํ•˜๋Š” ์˜๋ฏธ๋“ค ์†์—์„œ ์ฒœ์ƒ์˜ ์œค๋ฆฌ๊ฐ€ ์•„๋‹ˆ๋ผ ์ง€์ƒ์˜ ์œค๋ฆฌ๋ฅผ ์ฐพ์•„๋‚ผ ์ˆ˜ ์žˆ๋‹ค. ๊ทธ๋•Œ ๋น„๋กœ์†Œ ํ•œ ์„ธ๊ณ„๋Š” ๋‹ค๋ฅธ ์„ธ๊ณ„๋กœ ๋˜์–ด๊ฐˆ ๊ฐ€๋Šฅ์„ฑ์„ ์ง€๋‹Œ๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ์ด์ฒ˜๋Ÿผ ํ˜„์‹ค์— ๋ฐ•ํ˜€์žˆ์œผ๋ฉด์„œ๋„ ๋‹ค๋ฅธ ์„ธ๊ณ„์˜ ๊ฐ€๋Šฅ์„ฑ์„ ์ฃผ์‹œํ•˜๋Š” ๊ฒธ์†ํ•จ์— ๋Œ€ํ•œ ์—ด๋ง์œผ๋กœ ์“ฐ์˜€๋‹ค.Marine debris is represented as an example of "destruction of nature by human activity" in the Anthropocene by showing the situation in which man-made objects have occupied the ocean. Now, it is not difficult to sympathize with the seriousness or recognize problems of marine debris, and marine debris is treated as an object that should be removed. As such, various agents, from international organizations, governments, environmental groups, individuals to corporations, work in their own way or across borders to remove marine debris. This study starts with situational awareness. In other words, it begins with the point that marine debris is a bad thing "of course", and that the ocean is a space that needs to be protected from such things. These propositions seem so natural that they are undoubtedly treated as "facts". Similarly, most social science research on marine debris has also been conducted based on these facts. In short, in most social scientific studies on environmental problems, including that on marine debris, the way things exist is considered a given, so it only serves as a background and only "human things", such as people's perceptions, actions, institutions, and social structures, have become the subjects of these disciplines. Such studies have found legitimacy in their research by placing the negativity of things in a firm and fixed position. This attitude repeatedly shows the modern dichotomy that assigned the search for facts to the realm of the natural sciences and limited the role of social sciences only to the analysis of exclusive realms of human beings, such as society, politics, and culture. However, rather than conducting research on the basis of facts, this research treats the production of facts itself as a part of the research. Thus, it tries to deal with changes of beings with or through marine debris as a problem of Environmental Sociology. Therefore, this study explores the way we live together with marine debris before judging the value of the thing or urging actions against marine debris. How have we looked at marine debris? What could we see through it? What is "animated" with marine debris? Through these questions, this study explores the meaning of worlds created with marine debris and seeks to learn the ethics and practices rooted in our lives, not transcendental ethics separated from our lives. In order to answer these questions, this paper tries to form a theoretical foundation for considering marine debris as a "participant" in the study. The nature-society relationship theories that have been traditionally discussed in Environmental Sociology and Political Ecology are reviewed, and in order to sophisticate the theory of the relation, this study suggests the observation-dependent differentiation of nature and society through discussing on Actor-Network Theory in Science and Technology Studies (STS) and the concept of natureculture(s) coined by Haraway, a Feminist STS scholar. At this point, two terms (nature and culture) are dependent on each other but distinguished and constitute worlds together. This study also introduces the concept of worlding to discuss the relation between an observer seeing a world and the world which regulates the observer. Worlding is a process in which beings in a world make the world, where the world is assumed not as a fixed container built by a transcendental designer, but as a space-time that is constantly formed by beings in the world. The beings who build a world together cannot be limited to humans. In addition, this study refers to the "hyperobject" concept, as mentioned in Object-Oriented Ontology, an ontology which advocates for the equality of beings in terms of existence to explain marine debris. A hyperobject, in this study, refers to an object that appears massively in space and time (Morton, 2013). Looking at naturecultures and worlding, the concept of "conservation of nature" is contradictory. This is because, even when arbitrarily dividing the realm of nature and the realm of humans, it has the blindness of not knowing whether it is arbitrary, and it not only assumes a passive nature and protector humans, but also hides changes and pluralities of natures. Therefore, others such as Latour and Morton have recommended that the concept of nature be abandoned (Morton, 2007; Latour, 2017). However, no one has the right to discard concepts used in reality, and the practice of conservation of nature is already weaving its own meaning in our world. Denying "nature conservation" is an easy criticism of reality, and it can have the effect of blinding one's eyes to the dangers and damages that deconstructions cause. This study avoids such easy criticism. Instead, remembering the story of Haraway (1997) that our lives already exist in the contradiction of the entanglement of fiction and reality, this study explores what world the nature conservation collectivities are in and with whom it is worlding the world in detail. To this end, I conducted field work for 13 months at a non-profit environmental organization and a government-funded research institute, both of whih actively act against and research on marine debris, and wrote an ethnography based on this work. Ethnography was used as a research methodology that deeply intervenes in a world that a researcher is concerned with, without taking a particular side in advance. In this study, the world built with marine debris is explored in four major streams. First, it looks at a process of capture and revelation of marine debris in Korea. Marine debris has emerged as a global problem since it began to be distinguished from other objects, such as marine waste or just litter. At this point, vision, the process of capturing things, depends on the situated body. Marine debris is visualized through institutions, animals and scientific instruments, tangible things, images, and numbers. In this study, the transformation process of marine debris by various forms is called translation. In particular, microplastics have overturned the proposition that marine debris is an easily visible object and has connected a new way of understanding objects. The existence of microplastics, which is difficult to see with the naked eye, has allowed marine debris to enter into the scientific field, and has also changed the way of conservation practices against marine debris. Marine debris through translation has taken on more meaning than marine debris itself. Translated marine debris cannot be free from fiction, but at the same time, it can have richer meanings because of that. In addition, marine debris is not only translated but also mediates other beings, in particular allowing the marine debris observer to see a specific world. Marine debris, as a hyperobject, transcends a particular space-time, tying local seas as one homogeneous ocean, connecting the past and the future. It helps build a world which is spatially homogeneous but temporally disconnected. Here, it is the ocean currents that play a decisive role in making the earth a 'global space' of marine debris. The ocean current causes a circulation of artifacts that humans do not intend. In particular, thanks to the current in East Asia, humans in Japan, Korea, and China have formed a "social" relation through "gifts (Mauss, 1925)," or marine debris . Moreover, the difference of temporality among objects such as Earth, human beings and plastic amplifies the sense of transcorporeality in terms of risk (Alaimo, 2010). The human connected to marine debris faces the hybridity of a world, leading to the declaration of the Plasticocene. A "war" against marine debris is justified because the Plasticocene is a sign of risk of hybridity for conservationists. The war on marine debris is another name for global marine conservation, which emphasizes obedience to science. Science becomes the basis and strategy of practices, and 'experts' who have acquired scientific knowledge have become the representatives of the marine debris problem. In addition, experts are regarded as transparent beings which present facts, and science is also regarded as the only form of knowledge that reveals nature as it is. Because right and wrong are divided by whether they obey or disobey the science, they have virtually no need to fight anyone if they believe in science. Thus, this war becomes a form of education in which no one is criticized, but rather only asked for cooperation and partnership. Despite the limitations of this contradictory war, the possibility of weaving a new world was within it. This is because, in the practices of scientific inquiry activities to get to know and understand the enemy, the hyperobject, marine debris is split and becomes other beings, that is, parts of whole debris, through being classified. Classification is not only a basic practice of knowing, but also a political action that makes different positions and stands against a counterpart, because it makes different narratives showing different small things depending on the ways of classification. When parts of marine debris, for example, Styrofoam buoys, fishing gear, food wrappers and so on, become a matter of concern, human being become split in multiple and various beings associated with them. Accordingly, the politics of things is not a competition between non-human versus human, but a politics between the associations of {nonhuman beings-human beings} which repeats compromises, antagonisms, splits, and reunions. In this way, science could be understood as a tool for realizing politics without the only one answer, rather than being praised or denied by itself. The dynamic possibilities of a world can easily be defined as praise to infinite multiplicity and contingency. But the structural constraints of beings never allow us to let go of our responsibilities. This study says that the relationship between marine debris and humans is on the horizon of infinite possibilities, but at the same time it never denies that the damage caused by marine debris is serious and that we must do something about it. The problem posed here is rather about the attitude of establishing a relationship. Arrogance is inherent in the attitude of the "Human" towards others who might appear in ways we do not know. Humankind makes the world homogeneous with its ambition to control the world. But when we split the narrative from the arrogance, we come across parts that are greater than the whole, and we recover modesty from the parts. Then the Human becomes small and various human beings. In the repeated process of building alliances and splits with small non-humans, small humans learn to endure the complexity and contingency of a world, and in the newly emerging meanings, they can find an earthly ethics rather than a heavenly one. Only then does one world have the potential to become another world. This study was written with an aspiration for the modesty which is produced by seeing the possibilities of other worlds while being so entrenched in reality.์ œ 1 ์žฅ ์„œ๋ก  1 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ๊ณผ ๋ชฉ์  1 1. ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ์˜ ๋ถ€์ƒ 1 2. ํ™˜๊ฒฝ์‚ฌํšŒํ•™์˜ ์—ฐ๊ตฌ๋Œ€์ƒ์œผ๋กœ์„œ ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ 4 3. ์—ฐ๊ตฌ ์งˆ๋ฌธ 9 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ ๋ฐฉ๋ฒ•๋ก  11 1. ๋ฏผ์กฑ์ง€ ๋ฐฉ๋ฒ•๋ก  11 2. ์—ฐ๊ตฌ ํ˜„์žฅ 15 3. ์—ฐ๊ตฌ์ž์˜ ์œ„์น˜ 21 ์ œ 3 ์ ˆ ๋…ผ๋ฌธ ๊ตฌ์„ฑ 23 ์ œ 2 ์žฅ ์ด๋ก ์  ๋…ผ์˜์™€ ์„ ํ–‰์—ฐ๊ตฌ 25 ์ œ 1 ์ ˆ ์ž์—ฐ์— ๋Œ€ํ•œ ๊ด€์ ๊ณผ ์„ธ๊ณ„์ง“๊ธฐ 25 1. ์‹ค์žฌ๋ก ๊ณผ ๊ตฌ์„ฑ์ฃผ์˜์˜ ํ•œ๊ณ„: ํ–‰์œ„์ž-์—ฐ๊ฒฐ๋ง ์ด๋ก ๊ณผ ์ž์—ฐ๋ฌธํ™” 25 2. ์„ธ๊ณ„์ง“๊ธฐ์™€ ๊ณต๋™์ƒ์‚ฐ 34 ์ œ 2 ์ ˆ ์ฃผ์ฒด-๊ฐ์ฒด ๊ด€๊ณ„ ๋„ˆ๋จธ์˜ ์กด์žฌ๋ก ๊ณผ ์ดˆ๊ณผ๊ฐ์ฒด 41 1. ์กด์žฌ์˜ ์œ„๊ณ„์—์„œ ์กด์žฌ์˜ ๋ฏผ์ฃผ์ฃผ์˜๋กœ 41 2. ๋‹ค๋ฅธ ๊ฐ์ฒด๋ฅผ ๋Œ์–ด๋“ค์ด๋Š” ๊ฐ์ฒด: ์ดˆ๊ณผ๊ฐ์ฒด 48 ์ œ 3 ์ ˆ ์ธ๋ฅ˜์„ธ์™€ ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ 53 ์ œ 3 ์žฅ ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ์™€์˜ ๋งˆ์ฃผ์นจ 61 ์ œ 1 ์ ˆ ๋ˆˆ์— ๋ณด์ด๋Š” ์˜ค์—ผ 61 1. ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ์˜ ๊ตฌ์„ฑ 61 2. ๋ณผ์ˆ˜๋ก ๋” ์ž˜ ๋ณด์ด๋Š” ์‚ฌ๋ฌผ 66 ์ œ 2 ์ ˆ ๋งจ๋ˆˆ, ํ˜„๋ฏธ๊ฒฝ, ๋ถ„๊ด‘๊ธฐ: ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ์— ๋Œ€ํ•œ ์‹œ๊ฐ์˜ ์ด๋™๊ณผ ๋ฏธ์„ธํ”Œ๋ผ์Šคํ‹ฑ์˜ ๋“ฑ์žฅ 74 ์ œ 3 ์ ˆ ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ ๋ชฉ๊ฒฉ์ž๊ฐ€ ๋œ ๋น„์ธ๊ฐ„ ์ƒ๋ฌผ 84 1. ํ”ผํ•ด์ž, ๋งค๊ฐœ์ž, ์นจ์ž…์ž, ๊ฑฐ์ฃผ์ž 85 2. ๋ชฉ๊ฒฉ์ž์™€ ๊ด€๊ณ„ ๋งบ๊ธฐ: ํ•ด์–‘์˜ ๋Œ€ํ‘œ์ž์™€ ๊ณผํ•™ 93 ์ œ 4 ์ ˆ ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ๋ฅผ ๋“œ๋Ÿฌ๋‚ด๊ธฐ 99 1. ๋ฌผ๊ฑด, ์ด๋ฏธ์ง€, ์ˆซ์ž๋กœ ๋“œ๋Ÿฌ๋‚ด๊ธฐ 99 2. ๋“œ๋Ÿฌ๋‚ด๊ธฐ์˜ ๊ณผ์ž‰ 104 ์ œ 5 ์ ˆ ์†Œ๊ฒฐ: ๋งค๊ฐœ๋˜์–ด ํฌ์ฐฉ๋˜๋Š” ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ 113 ์ œ 4 ์žฅ ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ๋ฅผ ํ†ตํ•ด ๋งˆ์ฃผํ•œ ์„ธ๊ณ„ 114 ์ œ 1 ์ ˆ ์ง€๊ตฌ๋ฅผ ํ•˜๋‚˜๋กœ ์ž‡๋Š” ๋ฐ”๋‹ค: ํ•ด์–‘์˜ ๊ณต๊ฐ„์„ฑ 114 1. ๋Œ์•„๋‹ค๋‹ˆ๋ฉด์„œ ์—ฐ๊ฒฐ๋˜๋Š” ์ดˆ๊ณผ๊ฐ์ฒด 114 2. ์ง€์—ญ๋ฏผ์˜ ๋ฐ”๋‹ค, ์„ธ๊ณ„์‹œ๋ฏผ์˜ ๋ฐ”๋‹ค 122 ์ œ 2 ์ ˆ ์ง€๊ตฌ, ์ธ๊ฐ„, ํ”Œ๋ผ์Šคํ‹ฑ์˜ ์—ฐ๊ฒฐ๊ณผ ๋‹จ์ ˆ: ์กด์žฌ๋“ค์˜ ์‹œ๊ฐ„์ฐจ 131 1. ์ง€๊ตฌ, ์ธ๋ฅ˜, ํ”Œ๋ผ์Šคํ‹ฑ์˜ ์‹œ๊ฐ„์ฐจ 131 2. ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ์˜ ํšก๋‹จ-์‹ ์ฒด์ ์ธ ์œ„ํ—˜: ์ „์ฒด์™€ ๋ถ€๋ถ„๊ณผ ๊ทธ ๋ถ€๋ถ„์˜ ์—ฐ์‡„ 134 ์ œ 3 ์ ˆ ํ”Œ๋ผ์Šคํ‹ฑ์„ธ ํ˜น์€ ํ”Œ๋ผ์Šคํ‹ฑ ์‹œ๋Œ€ 139 1. ํ”Œ๋ผ์Šคํ‹ฑ์ด๊ฑฐ๋‚˜, ํ”Œ๋ผ์Šคํ‹ฑ์ด ์•„๋‹ˆ๊ฑฐ๋‚˜ 139 2. ํ”Œ๋ผ์Šคํ‹ฑ์„ธ์— ์˜ค์‹  ๊ฒƒ์„ ํ™˜์˜ํ•ฉ๋‹ˆ๋‹ค 143 ์ œ 4 ์ ˆ ์†Œ๊ฒฐ: ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ์™€ ํ•จ๊ป˜ ์„ธ๊ณ„์ง“๊ธฐ 148 ์ œ 5 ์žฅ ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ์— ๋Œ€ํ•ญํ•˜๋Š” ๋ฌผ์งˆ-๋‹ด๋ก ์  ์‹ค์ฒœ 149 ์ œ 1 ์ ˆ ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ๋ผ๋Š” ์ , ๊ทธ์™€ ๋งž์„  โ€œ์ „์Ÿโ€ 149 ์ œ 2 ์ ˆ ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ์— ๋งž์„œ๋Š” ๊ณผํ•™ 159 1. ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ ๋ฌธ์ œ ํ•ด๊ฒฐ์— ๊ธฐ์—ฌํ•˜๋Š” ์‹œ๋ฏผ๊ณผํ•™ 159 2. ์ „๋ฌธ๊ณผํ•™์„ ํ†ตํ•œ ํ•ด์–‘๋ณด์ „ 175 ์ œ 3 ์ ˆ ๊ณผํ•™ํ™”๋œ ํ•ด์–‘๋ณด์ „์˜ ๋Œ€ํ‘œ์ž 183 1. ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ ์ „๋ฌธ๊ฐ€ ๋˜๊ธฐ: ๋‹จ์ ˆ๊ณผ ์—ฐ๊ฒฐ 184 2. ์—ฐ๊ตฌ์†Œ ํ˜น์€ ์‹œ๋ฏผ๋‹จ์ฒด 194 ์ œ 4 ์ ˆ ์‹ธ์šธ ํ•„์š” ์—†๋Š” ์ „์Ÿ: ๋ชจ๋‘๊ฐ€ ํ˜‘๋ ฅํ•˜๋Š” ์ง€๊ตฌ์  ํ•ด์–‘๋ณด์ „ 201 1. ํŒŒํŠธ๋„ˆ์‹ญ 201 2. ๋น„ํŒ์˜ ์†Œ์ง„ 213 ์ œ 5 ์ ˆ ์†Œ๊ฒฐ: ๋ณด์ „์„ ์œ„ํ•œ ์ „์Ÿ์˜ ๋ชจ์ˆœ 217 ์ œ 6 ์žฅ ์ชผ๊ฐœ์ง€๋Š” ์ดˆ๊ณผ๊ฐ์ฒด์™€ ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ ์ •์น˜ 219 ์ œ 1 ์ ˆ ํŒจ๋ฐฐ๊ฐ€ ์˜ˆ๊ฒฌ๋œ ์ „์Ÿ 220 1. ์˜ˆ๊ฒฌ๋œ ํŒจ๋ฐฐ: ํ•ด๊ฒฐ์ง€์ƒ์ฃผ์˜์˜ ๋ง‰๋‹ค๋ฅธ ๊ธธ 220 2. ์˜ˆ๊ฒฌ๋œ ํŒจ๋ฐฐ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ : ๋น„๊ทผ๋Œ€๋„, ๊ทผ๋Œ€๋„ ์•„๋‹Œ ์œ„์น˜ 225 ์ œ 2 ์ ˆ ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ ๋ถ„๋ฅ˜ํ•˜๊ธฐ 231 1. ๊ณผ์†Œํ•œ ์ „์ฒด: ํ•ด์–‘ํ”Œ๋ผ์Šคํ‹ฑ 231 2. ๋ถˆ์ถฉ๋ถ„ํ•œ ๋ถ„๋ฅ˜: ๋‹ค๋ฅธ ๋ฐฉ์‹์˜ ๊ฐ€๋Šฅ์„ฑ 237 ์ œ 3 ์ ˆ ์ชผ๊ฐœ์ง€๋Š” ๋ถ€๋ถ„๋“ค ๋”ฐ๋ผ๊ฐ€๊ธฐ: ํ•œ๊ตญ๊ณผ ์ง€๊ตฌ์™€ ์ธ๋„๋„ค์‹œ์•„ ์“ฐ๋ ˆ๊ธฐ 244 ์ œ 4 ์ ˆ ์ „์Ÿ์˜ ์ตœ์ „์„ ์—์„œ ์ชผ๊ฐœ์ง€๋Š” ์ธ๊ฐ„๊ณผ ์‚ฌ๋ฌผ 249 ์ œ 5 ์ ˆ ์†Œ๊ฒฐ: ์‚ถ์˜ ๋™๋ฐ˜์ž๋กœ์„œ์˜ ์  255 ์ œ 7 ์žฅ ๊ฒฐ๋ก  257 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ ์š”์•ฝ: ํ•ด์–‘์“ฐ๋ ˆ๊ธฐ์™€ ํ•จ๊ป˜ํ•˜๋Š” ์„ธ๊ณ„์ง“๊ธฐ 257 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ์˜ ํ•จ์˜์™€ ์‹œ์‚ฌ์  259 ์ฐธ๊ณ ๋ฌธํ—Œ 266 Abstract 29

    ๊ฐ„ ์กฐ์˜์ˆ ์„ ์œ„ํ•œ ํ˜ˆ๊ด€ ๋ชจ๋ธ ๊ธฐ๋ฐ˜์˜ ๊ตญ๋ถ€ ์ ์‘ 2D-3D ์ •ํ•ฉ ์•Œ๊ณ ๋ฆฌ์ฆ˜ ๊ธฐ๋ฒ• ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ „๊ธฐยท์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2017. 2. ์‹ ์˜๊ธธ.Two-dimensionalโ€“three-dimensional (2Dโ€“3D) registration between intra-operative 2D digital subtraction angiography (DSA) and pre-operative 3D computed tomography angiography (CTA) can be used for roadmapping purposes. However, through the projection of 3D vessels, incorrect intersections and overlaps between vessels are produced because of the complex vascular structure, which make it difficult to obtain the correct solution of 2Dโ€“3D registration. To overcome these problems, we propose a registration method that selects a suitable part of a 3D vascular structure for a given DSA image and finds the optimized solution to the partial 3D structure. The proposed algorithm can reduce the registration errors because it restricts the range of the 3D vascular structure for the registration by using only the relevant 3D vessels with the given DSA. To search for the appropriate 3D partial structure, we first construct a tree model of the 3D vascular structure and divide it into several subtrees in accordance with the connectivity. Then, the best matched subtree with the given DSA image is selected using the results from the coarse registration between each subtree and the vessels in the DSA image. Finally, a fine registration is conducted to minimize the difference between the selected subtree and the vessels of the DSA image. In experimental results obtained using 10 clinical datasets, the average distance errors in the case of the proposed method were 2.34 ยฑ 1.94 mm. The proposed algorithm converges faster and produces more correct results than the conventional method in evaluations on patient datasets.Chapter 1 Introduction 1 1.1 Background 1 1.2 Problem statement 6 1.3 Main contributions 8 1.4 Contents organization 10 Chapter 2 Related Works 12 2.1 Overview 12 2.1.1 Definitions 14 2.1.2 Intensity-based and feature-based registration 17 2.2 Neurovascular applications 19 2.3 Liver applications 22 2.4 Cardiac applications 27 2.4.1 Rigid registration 27 2.4.2 Non-rigid registration 31 Chapter 3 3D Vascular Structure Model 33 3.1 Vessel segmentation 34 3.1.1 Overview 34 3.1.2 Vesselness filter 36 3.1.3 Vessel segmentation 39 3.2 Skeleton extraction 40 3.2.1 Overview 40 3.2.2 Skeleton extraction based on fast marching method 41 3.3 Graph construction 45 3.4 Generation of subtree structures from 3D tree model 46 Chapter 4 Locally Adaptive Registration 52 4.1 2D centerline extraction 53 4.1.1 Extraction from a single DSA image 54 4.1.2 Extraction from angiographic image sequence 55 4.2 Coarse registration for the detection of the best matched subtree 58 4.3 Fine registration with selected 3D subtree 61 Chapter 5 Experimental Results 63 5.1 Materials 63 5.2 Phantom study 65 5.3 Performance evaluation 69 5.3.1 Evaluation for a single DSA image 69 5.3.2 Evaluation for angiographic image sequence 75 5.4 Comparison with other methods 77 5.5 Parameter study 87 Chapter 6 Conclusion 90 Bibliography 92 ์ดˆ๋ก 109Docto

    A study on Machine Learning for Prediction of the Shipbuilding Lead Time

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    In recent years, big data technology, which is one of the biggest issues in IT field, has been applied in various fields as data has increased exponentially compared to the past, however, in the shipbuilding and offshore industries, the use of big data related technology is relatively rare compared to other manufacturing industries such as automobile and electronics industries. But, shipbuilding and offshore industry is one-piece manufacturing industry, and statistics-based analysis such as the Big Data methodology can be very effective because vast amounts of data are generated throughout the entire life cycle and are highly variable in the manufacturing environment. As a result, the big data-based machine learning research is progressing slowly in the shipbuilding industry. However, this is limited to the design field that manages the fixed variables and it is difficult to apply it in terms of production management such as lead time which is the basis of construction activity. In particular, the standard data such as production lead time is highly variable due to various process variables so, it is necessary to study changing from causation viewpoint to correlation to solve it. Therefore, in this paper, I has constructed a prediction model applying machine learning and deep learning algorithm to improve the standard data for the time factor of production lead time. In order to predict the variable lead time considering the various properties of the product in comparison with the standard lead time, I collect data from several shipyards and apply various machine learning and deep learning algorithms to predict the production lead time according to the process. Respectively. To analyze the data, open source such as R and Python language was used and a lead time prediction model based on the algorithm was created. Various evaluation indices were used to evaluate the prediction model generated by the analysis algorithm. In addition, I compared the results of machine learning and deep learning algorithms with those of previous studies, and the decision support for the establishment of standard information according to various process variables is made possible. | ์ตœ๊ทผ IT ๋ถ„์•ผ์—์„œ ๊ฐ€์žฅ ํฐ ํ™”๋‘์ธ ๋น…๋ฐ์ดํ„ฐ ๊ธฐ์ˆ ์€ ๊ณผ๊ฑฐ์— ๋น„ํ•ด ๋ฐ์ดํ„ฐ๊ฐ€ ๊ธฐํ•˜๊ธ‰์ˆ˜์ ์œผ๋กœ ์ฆ๊ฐ€ํ•จ์— ๋”ฐ๋ผ ๋‹ค์–‘ํ•œ ๋ถ„์•ผ์—์„œ ์ ์šฉ๋˜๊ณ  ์žˆ์ง€๋งŒ ์ž๋™์ฐจ, ์ „์ž ์—…์ข… ๋“ฑ์˜ ๋‹ค๋ฅธ ์ œ์กฐ์—…์— ๋น„ํ•ด ์กฐ์„  ๋ฐ ํ•ด์–‘์‚ฐ์—…์—์„œ๋Š” ๋น…๋ฐ์ดํ„ฐ ๊ด€๋ จ ๊ธฐ์ˆ ์˜ ํ™œ์šฉ์‚ฌ๋ก€๊ฐ€ ์ƒ๋Œ€์ ์œผ๋กœ ๋“œ๋ฌธ ์‹ค์ •์ด๋‹ค. ํ•˜์ง€๋งŒ ์กฐ์„  ๋ฐ ํ•ด์–‘์‚ฐ์—…์€ ์ผํ’ˆ ์ œ์กฐ ์‚ฐ์—…์œผ๋กœ ์˜์—…, ์„ค๊ณ„, ๊ฑด์กฐ, ์œ ์ง€ ๋ณด์ˆ˜ ๋“ฑ ์ „์ฒด ์ˆ˜๋ช… ์ฃผ๊ธฐ์—์„œ ๋ฐฉ๋Œ€ํ•œ ๋ฐ์ดํ„ฐ๊ฐ€ ์ƒ์„ฑ๋˜๊ณ , ์ œ์กฐ ํ™˜๊ฒฝ์— ๋”ฐ๋ผ ๋ณ€๋™์„ฑ์ด ํฌ๊ธฐ ๋•Œ๋ฌธ์— ๋น…๋ฐ์ดํ„ฐ ๋ฐฉ๋ฒ•๋ก ๊ณผ ๊ฐ™์€ ํ†ต๊ณ„ ๊ธฐ๋ฐ˜ ๋ถ„์„์ด ํฐ ํšจ๊ณผ๋ฅผ ๋ฐœํœ˜ํ•  ์ˆ˜ ์žˆ๋‹ค. ์ด๋กœ ์ธํ•ด ๋น…๋ฐ์ดํ„ฐ ๊ธฐ๋ฐ˜์˜ ๊ธฐ๊ณ„ํ•™์Šต ์—ฐ๊ตฌ๋Š” ์กฐ์„ ์—…์—์„œ๋„ ์„œ์„œํžˆ ์ง„ํ–‰๋˜๊ณ  ์žˆ์œผ๋‚˜ ์ด๋Š” ๊ณ ์ •๋ณ€์ˆ˜๋ฅผ ๊ด€๋ฆฌํ•˜๋Š” ์„ค๊ณ„ ๋ถ„์•ผ์— ํ•œ์ •๋˜์–ด ์žˆ์œผ๋ฉฐ ๊ฑด์กฐ ํ™œ๋™์˜ ๊ทผ๊ฐ„์ด ๋˜๋Š” ๊ธฐ์ค€ ์ •๋ณด, ์ฆ‰ ์›๋‹จ์œ„๋‚˜ ์‹œ์ˆ˜, ๋ฆฌ๋“œํƒ€์ž„ ๋“ฑ์˜ ์ƒ์‚ฐ๊ด€๋ฆฌ ๊ด€์ ์—์„œ๋Š” ์ ์šฉ์— ์–ด๋ ค์›€์„ ๊ฒช๊ณ  ์žˆ๋‹ค. ํŠนํžˆ ์ƒ์‚ฐ ๋ฆฌ๋“œํƒ€์ž„์ด๋ผ๋Š” ๊ธฐ์ค€์ •๋ณด๋Š” ๋‹ค์–‘ํ•œ ๊ณต์ •๋ณ€์ˆ˜๋กœ ์ธํ•œ ๋ณ€๋™์„ฑ์ด ํฌ๊ธฐ ๋•Œ๋ฌธ์— ์ด๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด์„œ ํ˜„์‹ค์ ์œผ๋กœ ํ•œ๊ณ„๊ฐ€ ์žˆ๋Š” ์˜์—ญ์— ๋Œ€ํ•ด Causation์—์„œ Correlation ๊ด€์ ์— ๋”ฐ๋ฅธ ์—ฐ๊ตฌ๊ฐ€ ํ•„์š”ํ•˜๋‹ค๊ณ  ๋ณธ๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ƒ์‚ฐ ๋ฆฌ๋“œํƒ€์ž„์ด๋ผ๋Š” ์‹œ๊ฐ„์š”์†Œ์— ๋Œ€ํ•œ ๊ธฐ์ค€์ •๋ณด ์ฒด๊ณ„ ๊ฐœ์„ ์„ ์œ„ํ•ด ๊ธฐ๊ณ„ํ•™์Šต ๋ฐ ๋”ฅ๋Ÿฌ๋‹ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ ์šฉํ•œ ์˜ˆ์ธก๋ชจ๋ธ์„ ๊ตฌ์ถ•ํ•˜์˜€๋‹ค. ๊ธฐ์กด์— ๊ด€๋ฆฌ๋˜๋Š” ์กฐ์„ ์†Œ์˜ ํ‘œ์ค€ ๋ฆฌ๋“œํƒ€์ž„์— ๋Œ€๋น„ํ•˜์—ฌ ์ œํ’ˆ์˜ ๋‹ค์–‘ํ•œ ์†์„ฑ์„ ๊ณ ๋ คํ•œ ๋ณ€๋™ ๋ฆฌ๋“œํƒ€์ž„์„ ์˜ˆ์ธกํ•˜๊ธฐ ์œ„ํ•ด ์—ฌ๋Ÿฌ ์กฐ์„ ์†Œ์˜ ๋ฐ์ดํ„ฐ๋ฅผ ์ˆ˜์ง‘ํ•˜์˜€๊ณ  ๊ณต์ •์— ๋”ฐ๋ฅธ ์ƒ์‚ฐ ๋ฆฌ๋“œํƒ€์ž„์„ ์˜ˆ์ธกํ•˜๊ธฐ ์œ„ํ•œ ๋‹ค์–‘ํ•œ ๊ธฐ๊ณ„ํ•™์Šต ๋ฐ ๋”ฅ๋Ÿฌ๋‹ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ ์šฉํ•˜์˜€๋‹ค. ๋ฐ์ดํ„ฐ๋ฅผ ๋ถ„์„ํ•˜๊ธฐ ์œ„ํ•ด์„œ R๊ณผ Python ์–ธ์–ด ๋“ฑ์˜ ์˜คํ”ˆ์†Œ์Šค๋ฅผ ํ™œ์šฉํ•˜์˜€์œผ๋ฉฐ ์•Œ๊ณ ๋ฆฌ์ฆ˜์— ๋”ฐ๋ฅธ ๋ฆฌ๋“œํƒ€์ž„ ์˜ˆ์ธก๋ชจ๋ธ์„ ์ƒ์„ฑํ•˜์˜€๋‹ค. ๋ถ„์„ ์•Œ๊ณ ๋ฆฌ์ฆ˜์— ๋”ฐ๋ผ ์ƒ์„ฑ๋œ ์˜ˆ์ธก๋ชจ๋ธ์˜ ํ‰๊ฐ€๋ฅผ ์œ„ํ•ด ์—ฌ๋Ÿฌ ๊ฐ€์ง€ ํ‰๊ฐ€์ง€ํ‘œ๋ฅผ ํ™œ์šฉํ•˜์˜€๋‹ค. ๋˜ํ•œ, ๊ธฐ์กด์—ฐ๊ตฌ ๊ฒฐ๊ณผ์— ๋น„ํ•ด ๊ธฐ๊ณ„ํ•™์Šต๊ณผ ๋”ฅ๋Ÿฌ๋‹ ์•Œ๊ณ ๋ฆฌ์ฆ˜์— ๋”ฐ๋ฅธ ์œ ์˜๋ฏธํ•œ ๊ฒฐ๊ณผ๋ฅผ ๋น„๊ตํ•˜์—ฌ ์กฐ์„ ์†Œ์—์„œ์˜ ํ™œ์šฉ์„ฑ์„ ๊ฒ€ํ† ํ•ด๋ณด๊ณ  ๋‹ค์–‘ํ•œ ๊ณต์ •๋ณ€์ˆ˜์— ๋”ฐ๋ฅธ ๊ธฐ์ค€์ •๋ณด ์ˆ˜๋ฆฝ์— ๋Œ€ํ•œ ์˜์‚ฌ๊ฒฐ์ • ์ง€์›์„ ๊ฐ€๋Šฅํ•˜๋„๋ก ํ•˜์˜€๋‹ค.1. ์„œ ๋ก  1 1.1 ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ 1 1.1.1 ์กฐ์„ ์†Œ์˜ ์ƒ์‚ฐ๊ด€๋ฆฌ 3 1.1.2 ๋น…๋ฐ์ดํ„ฐ ๋ฐฉ๋ฒ•๋ก  4 1.2 ๊ด€๋ จ ์—ฐ๊ตฌ ๋™ํ–ฅ 7 1.2.1 ์ œ์กฐ์—… ๋น…๋ฐ์ดํ„ฐ ์—ฐ๊ตฌ ์‚ฌ๋ก€ 7 1.2.2 ์กฐ์„ ์—… ๋น…๋ฐ์ดํ„ฐ ์—ฐ๊ตฌ ์‚ฌ๋ก€ 8 2. ๋ถ„์„ ์•Œ๊ณ ๋ฆฌ์ฆ˜ ๋ฐ ์ ์šฉ๋ฐฉ์•ˆ 10 2.1 ๊ธฐ๊ณ„ํ•™์Šต ์•Œ๊ณ ๋ฆฌ์ฆ˜ 10 2.1.1 ํšŒ๊ท€๋ถ„์„ 13 2.1.2 ์ธ๊ณต์‹ ๊ฒฝ๋ง 13 2.1.3 ์˜์‚ฌ๊ฒฐ์ •๋‚˜๋ฌด 14 2.2 ๋”ฅ๋Ÿฌ๋‹ ์•Œ๊ณ ๋ฆฌ์ฆ˜ 16 2.2.1 Multi-Layer Perceptron (MLP) 18 2.2.2 Recurrent Neural Network (RNN) 19 2.2.3 ๋”ฅ๋Ÿฌ๋‹ ๋ผ์ด๋ธŒ๋Ÿฌ๋ฆฌ 20 2.3 ๋ฐ์ดํ„ฐ ๋ถ„์„๊ณผ์ • 23 2.3.1 ๋ฐ์ดํ„ฐ ์ˆ˜์ง‘ 25 2.3.2 ๋ฐ์ดํ„ฐ ์ฒ˜๋ฆฌ 25 2.3.3 ๋ชจ๋ธ ๊ตฌ์ถ• 30 2.3.4 ๋ฐ์ดํ„ฐ ํ‰๊ฐ€ 30 3. ์˜ˆ์ธก๋ชจ๋ธ ๊ตฌ์ถ•์„ ์œ„ํ•œ ์กฐ์„ ์†Œ ๋ฐ์ดํ„ฐ ๋ถ„์„ 32 3.1 ๋ธ”๋ก ์ ˆ๋‹จ๊ณต์ • ์ค‘์ผ์ • ๊ณ„ํš ๋ฐ์ดํ„ฐ ๋ถ„์„ 34 3.2 ๋ธ”๋ก ํƒ‘์žฌ๊ณต์ • ์‹ค์  ๋ฐ์ดํ„ฐ ๋ถ„์„ 39 3.3 ํ•ด์–‘ํ”Œ๋žœํŠธ ๋ฐฐ๊ด€์žฌ ๊ณต๊ธ‰๋ง ๋ฐ์ดํ„ฐ ๋ถ„์„ 47 4. ์˜ˆ์ธก๋ชจ๋ธ ๊ฒฐ๊ณผ ๋ถ„์„ 56 4.1 ๊ธฐ๊ณ„ํ•™์Šต ๋ชจ๋ธ๋ง ๊ฒฐ๊ณผ๋ถ„์„ 56 4.2 ๋”ฅ๋Ÿฌ๋‹ ๋ชจ๋ธ๋ง ๊ฒฐ๊ณผ๋ถ„์„ 62 4.3 ์•Œ๊ณ ๋ฆฌ์ฆ˜์— ๋”ฐ๋ฅธ ๊ฒฐ๊ณผ๋ถ„์„ 68 5. ๊ฒฐ๋ก  73 5.1 ์—ฐ๊ตฌ ๊ฒฐ๋ก  73 5.2 ํ–ฅํ›„ ๊ณผ์ œ 74 ์ฐธ๊ณ ๋ฌธํ—Œ 75 ๋ถ€๋ก A 77Maste

    Effect of Expanding Benefit Coverage for Cancer Patients on Equity

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋ณด๊ฑด๋Œ€ํ•™์› : ๋ณด๊ฑดํ•™๊ณผ, 2014. 8. ๊ถŒ์ˆœ๋งŒ.๋ณธ ์—ฐ๊ตฌ์˜ ๋ชฉ์ ์€ ์•” ํ™˜์ž์˜ ๋ณธ์ธ์ผ๋ถ€๋ถ€๋‹ด์„ ๊ฒฝ๊ฐํ•ด์ฃผ๋Š” ๋ณธ์ธ๋ถ€๋‹ด ์‚ฐ์ •ํŠน๋ก€์ œ๊ฐ€ ์˜๋ฃŒ๋น„๋ถ€๋‹ด ๋ฐ ์˜๋ฃŒ์ด์šฉ์— ๋ฏธ์นœ ์˜ํ–ฅ์„ ์‚ดํŽด๋ณด๊ณ , ๋น„๊ธ‰์—ฌ๊ฐ€ ํฌํ•จ๋œ ์‹ค์งˆ์ ์ธ ์ง€์ถœ๋‹จ์œ„์ธ ๊ฐ€๊ตฌ ๋‹จ์œ„์˜ ์˜๋ฃŒ๋น„๋ถ€๋‹ด์— ๋ฏธ์นœ ์˜ํ–ฅ์„ ํ‰๊ฐ€ํ•˜๋Š” ๊ฒƒ์ด๋‹ค. ๋˜ํ•œ ํ˜•ํ‰์„ฑ ์ธก๋ฉด์—์„œ ํ‰๊ฐ€ํ•  ํ•„์š”์„ฑ์— ๋”ฐ๋ผ, ๊ทธ ์˜ํ–ฅ์˜ ์†Œ๋“๊ณ„์ธต๋ณ„ ์ฐจ์ด๋ฅผ ์‚ดํŽด๋ณด์•˜๋‹ค. 2009๋…„ 12์›”๋ถ€ํ„ฐ ์‹œํ–‰๋œ ์•”ํ™˜์ž ์ž…์›, ์™ธ๋ž˜ ๋ณธ์ธ๋ถ€๋‹ด๋ฅ  ์ธํ•˜(10%โ†’5%)(๋ณด๊ฑด๋ณต์ง€๋ถ€ ๊ณ ์‹œ ์ œ2009-208ํ˜ธ)๋ฅผ ๋Œ€์ƒ์œผ๋กœ, ํ•œ๊ตญ์˜๋ฃŒํŒจ๋„ 2009๋…„๊ณผ 2010๋…„ ์ž๋ฃŒ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ, ์ •์ฑ… ์ „ํ›„์˜ ์•” ํ™˜์ž์™€ ๊ฐ„์งˆํ™˜ ํ™˜์ž๋ฅผ ๊ฐ๊ฐ ์ถ”์ถœํ•˜์—ฌ ๋ฐ์ดํ„ฐ๋ฅผ ๊ฒฐํ•ฉํ•˜๊ณ , ๊ฐ€๊ตฌ์› ๋‹จ์œ„, ๊ฐ€๊ตฌ ๋‹จ์œ„๋กœ ์ด์ค‘์ฐจ์ด๋ถ„์„(DID)๊ณผ ์‚ผ์ค‘์ฐจ์ด๋ถ„์„(DDD)์„ ์‹ค์‹œํ•˜์˜€๋‹ค. ๋ถ„์„ ๊ฒฐ๊ณผ์— ๋”ฐ๋ฅด๋ฉด, ์ •์ฑ…์ด ์™ธ๋ž˜์™€ ์ž…์›์„ ํฌํ•จํ•œ ์˜๋ฃŒ์ด์šฉ ๋ฐ ๊ฐ€๊ตฌ๋‹จ์œ„์˜ ๊ณผ๋ถ€๋‹ด์˜๋ฃŒ๋น„ ์ง€์ถœ์— ๋ฏธ์นœ ์˜ํ–ฅ์ด ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•˜์ง€ ์•Š์•˜๋‹ค. ๋ณธ ์—ฐ๊ตฌ์˜ ๊ฒฐ๊ณผ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ, ๋ณธ์ธ๋ถ€๋‹ด๋ฅ  ์ธํ•˜ ์ •์ฑ…(10%โ†’5%)์ด ๋น„๊ธ‰์—ฌ ๋ถ€๋ถ„์ด ํฌํ•จ๋œ ์•” ํ™˜์ž์˜ ์‹ค์งˆ์ ์ธ ๋ณธ์ธ๋ถ€๋‹ด ์˜๋ฃŒ๋น„์— ๋Œ€ํ•œ ์˜ํ–ฅ์ด ๋ฏธ๋ฏธํ•œ ๊ฒƒ์„ ํ™•์ธํ•˜์˜€์œผ๋ฉฐ, ํŠนํžˆ ์ €์†Œ๋“์ธต์˜ ๊ณผ๋ถ€๋‹ด์˜๋ฃŒ๋น„์— ๋Œ€ํ•œ ์žฌ์ •์ ์ธ ๋ณดํ˜ธ๋ฅผ ์ œ๊ณตํ•˜๋Š” ์ถ”๊ฐ€์  ์ •์ฑ…์ด ํ•„์š”ํ•จ์„ ์ œ์–ธํ•œ๋‹ค.์ œ 1 ์žฅ ์„œ ๋ก  ์ œ 1 ์ ˆ ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ ๋ฐ ํ•„์š”์„ฑ 1. ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ 2. ์—ฐ๊ตฌ์˜ ํ•„์š”์„ฑ ์ œ 2 ์ ˆ ์—ฐ๊ตฌ์˜ ๋ชฉ์  ์ œ 2 ์žฅ ์ด๋ก ์  ๋ฐฐ๊ฒฝ ๋ฐ ์„ ํ–‰์—ฐ๊ตฌ ์ œ 1 ์ ˆ ์ด๋ก ์  ๋ฐฐ๊ฒฝ 1. ๋ณด์žฅ์„ฑ ๊ฐ•ํ™” ์ •์ฑ… 2. ์ด์ค‘์ฐจ์ด ๋ถ„์„๋ฐฉ๋ฒ• ์ œ 2 ์ ˆ ์„ ํ–‰์—ฐ๊ตฌ ๊ณ ์ฐฐ 1. ์„ ํ–‰์—ฐ๊ตฌ ๊ณ ์ฐฐ 2. ์„ ํ–‰์—ฐ๊ตฌ ๊ณ ์ฐฐ ๊ฒฐ๊ณผ ์ œ 3 ์žฅ ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• ์ œ 1 ์ ˆ ์ž๋ฃŒ์› ์ œ 2 ์ ˆ ๋ถ„์„๋Œ€์ƒ ์ œ 3 ์ ˆ ๋ถ„์„๋ฐฉ๋ฒ• 1. ํ†ต๊ณ„์  ๋ฐฉ๋ฒ• 2. ๋ณ€์ˆ˜ ์„ค์ • 3. ์—ฐ๊ตฌ๋ชจํ˜• ์ œ 4 ์žฅ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ ์ œ 1 ์ ˆ ๋ถ„์„ โ… -์ •์ฑ…์˜ ์˜๋ฃŒ์ด์šฉ ์˜ํ–ฅ ํ‰๊ฐ€ 1. ์ผ๋ฐ˜์  ํŠน์„ฑ 2. ์˜๋ฃŒ์ด์šฉ์— ๋ฏธ์นœ ์˜ํ–ฅ๊ณผ ์†Œ๋“๊ณ„์ธต๋ณ„ ์˜ํ–ฅ ์ฐจ์ด ์ œ 2 ์ ˆ ๋ถ„์„ โ…ก-์ •์ฑ…์˜ ๊ณผ๋ถ€๋‹ด์˜๋ฃŒ๋น„ ์˜ํ–ฅ ํ‰๊ฐ€ 1. ์ผ๋ฐ˜์  ํŠน์„ฑ 2. ๊ณผ๋ถ€๋‹ด์˜๋ฃŒ๋น„ ๋ฐœ์ƒ์— ๋ฏธ์นœ ์˜ํ–ฅ๊ณผ ์†Œ๋“๊ณ„์ธต๋ณ„ ์˜ํ–ฅ ์ฐจ์ด ์ œ 5 ์žฅ ๊ณ  ์ฐฐ ์ œ 1 ์ ˆ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ์— ๋Œ€ํ•œ ๊ณ ์ฐฐ ์ œ 2 ์ ˆ ์—ฐ๊ตฌ์˜ ์ œํ•œ์  ์ œ 6 ์žฅ ๊ฒฐ ๋ก  ์ฐธ ๊ณ  ๋ฌธ ํ—Œ ๋ถ€ ๋ก AbstractMaste

    Ventilation and Filtration Control Strategy considering Indoor and Outdoor Particle Environmental Conditions of Apartment Building

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ๊ฑด์ถ•ํ•™๊ณผ, 2018. 2. ์—ฌ๋ช…์„.์‹ค๋‚ด ๊ณต๊ธฐ์งˆ ๋ฌธ์ œ๊ฐ€ ๋Œ€๋‘ ๋˜๋ฉด์„œ ์‹ ์ถ• ๊ณต๋™์ฃผํƒ์— ํ™˜๊ธฐ์žฅ์น˜ ์„ค๋น„๊ฐ€ ์˜๋ฌดํ™”๋˜๊ณ , ์ตœ๊ทผ ๋ฏธ์„ธ๋จผ์ง€ ๋ฌธ์ œ๊ฐ€ ๊ธ‰๋ถ€์ƒํ•˜๋ฉด์„œ ์‹ค๋‚ด ๊ณต๊ธฐ์ฒญ์ •๊ธฐ์˜ ๋ณด๊ธ‰๋ฅ ์ด ํ™•๋Œ€๋˜๊ณ  ์žˆ๋‹ค. ์‹œ์Šคํ…œ์˜ ๋ณด๊ธ‰์€ ๋ณดํŽธํ™”๋˜๊ณ  ์žˆ์œผ๋‚˜ ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€์™€ ์ „๋ฐ˜์ ์ธ ์‹ค๋‚ด ๊ณต๊ธฐ์งˆ์„ ๊ด€๋ฆฌํ•˜๊ธฐ ์œ„ํ•ด ๋‘ ์‹œ์Šคํ…œ์„ ํšจ์œจ์ ์œผ๋กœ ์šด์˜ํ•  ์ˆ˜ ์žˆ๋Š” ์ œ์–ด๋ฐฉ์•ˆ์€ ์•„์ง๊นŒ์ง€ ๋ฏธ๋น„ํ•˜๋‹ค. ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€ ๊ด€๋ฆฌ๋ฅผ ์œ„ํ•œ ํ™˜๊ธฐ๋Š” ์‹ค์™ธ ๋ฏธ์„ธ๋จผ์ง€ ๋†๋„์™€ ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€ ๋ฐœ์ƒ ์ •๋„์— ๋”ฐ๋ผ ์œ ๋ฆฌํ•˜๊ธฐ๋„ ํ•˜๊ณ , ๋ถˆ๋ฆฌ ํ•  ์ˆ˜๋„ ์žˆ๋‹ค. ํ™˜๊ธฐ๊ฐ€ ์œ ๋ฆฌํ•œ ๊ฒฝ์šฐ์—๋Š” ๋ชฉํ‘œ๋†๋„๋ฅผ ๋งŒ์กฑ์‹œํ‚ค๊ธฐ ์œ„ํ•ด ํ•„์š”ํ•œ ํ™˜๊ธฐ๋Ÿ‰๊ณผ ํ•จ๊ป˜ ์ถ”๊ฐ€์ ์ธ ๊ณต๊ธฐ์ฒญ์ •๊ธฐ์˜ ์šด์ „์ด ํ•„์š”ํ•œ์ง€ ํŒ๋‹จํ•˜์—ฌ ์ œ์–ด๋Ÿ‰์„ ๊ฒฐ์ •ํ•˜๊ณ , ํ™˜๊ธฐ๊ฐ€ ๋ถˆ๋ฆฌํ•œ ๊ฒฝ์šฐ์—๋Š” ๊ธฐํƒ€ ์‹ค๋‚ด์—์„œ ๋ฐœ์ƒํ•˜๋Š” ์˜ค์—ผ๋ฌผ์งˆ์„ ๊ณ ๋ คํ•œ ์ตœ์†Œ ํ™˜๊ธฐ๋Ÿ‰ ํ™•๋ณด ๋ฐ ๋ฏธ์„ธ๋จผ์ง€ ์ œ์–ด๋ฅผ ์œ„ํ•œ ๊ณต๊ธฐ์ฒญ์ •๊ธฐ์˜ ์šด์ „์ด ํ•„์š”ํ•˜๋‹ค. ๋”ฐ๋ผ์„œ, ๊ณ„์†์ ์œผ๋กœ ๋ณ€ํ™”ํ•˜๋Š” ๋ฏธ์„ธ๋จผ์ง€ ํ™˜๊ฒฝ์กฐ๊ฑด์—์„œ ํ™˜๊ธฐ๊ฐ€ ์œ ๋ฆฌํ•œ ํ™˜๊ฒฝ๊ณผ ๋ถˆ๋ฆฌํ•œ ํ™˜๊ฒฝ์„ ํŒ๋‹จํ•˜์—ฌ Ventilation๊ณผ Filtration์˜ ์ œ์–ด ๋ชจ๋“œ์™€ ์ œ์–ด๋Ÿ‰์„ ๊ฒฐ์ •ํ•  ์ˆ˜ ์žˆ๋Š” ์ œ์–ด ์ „๋žต์ด ํ•„์š”ํ•˜๋‹ค. ์ด๋ฅผ ์œ„ํ•˜์—ฌ ์‹ค๋‚ด์™ธ ๋ฏธ์„ธ๋จผ์ง€ ํ™˜๊ฒฝ์กฐ๊ฑด์„ ํŒ๋‹จํ•  ์ˆ˜ ์žˆ๋„๋ก ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€ ๋†๋„ํ•ด์„๋ชจ๋ธ๊ณผ ์ด๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•œ ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€ ๋ฐœ์ƒ ์˜ˆ์ธก ๋ชจ๋ธ์„ ๊ตฌ์ถ•ํ•˜์˜€๋‹ค. ๊ตฌ์ถ•๋œ ๋ชจ๋ธ๋กœ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ํ†ตํ•ด ํ™˜๊ฒฝ์กฐ๊ฑด๊ณผ ์ œ์–ด๊ด€๋ จ ์˜ํ–ฅ์ธ์ž์˜ ๋ณ€ํ™”์— ๋”ฐ๋ฅธ ์‹ค๋‚ด๋†๋„ ํŠน์„ฑ์„ ๋ถ„์„ํ•˜๊ณ , ์ด๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ํ™˜๊ฒฝ์กฐ๊ฑด์— ๋”ฐ๋ผ ๋ชฉํ‘œ๋†๋„๋ฅผ ๋งŒ์กฑ์‹œํ‚ค๊ธฐ ์œ„ํ•œ ์ œ์–ด๋ชจ๋“œ์™€ ์ œ์–ด๋Ÿ‰์„ ๊ฒฐ์ •ํ•  ์ˆ˜ ์žˆ๋Š” Control limit ์ปค๋ธŒ (CL ์ปค๋ธŒ)๋ฅผ ๋„์ถœํ•˜์˜€๋‹ค. CL ์ปค๋ธŒ๋ฅผ ํ™œ์šฉํ•˜์—ฌ ๋ฏธ์„ธ๋จผ์ง€์˜ ์‹ค๋‚ด ๋ชฉํ‘œ ๋†๋„๋ฅผ ๋งŒ์กฑ์‹œํ‚ค๊ณ  ์ „๋ฐ˜์ ์ธ ์‹ค๋‚ด ๊ณต๊ธฐ์งˆ๊ณผ ์—๋„ˆ์ง€๋ฅผ ๊ณ ๋ คํ•œ Ventilation๊ณผ Filtration ์ œ์–ด ์ „๋žต์„ ์ œ์‹œํ•˜๊ณ , ์ œ์–ด์˜ ์ ์šฉ ํšจ๊ณผ๋ฅผ ํ‰๊ฐ€ํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ์˜ ๊ฒฐ๊ณผ๋ฅผ ์š”์•ฝํ•˜๋ฉด ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. (1) ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€ ๋†๋„๋Š” ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์—ฌ๋Ÿฌ ํ™˜๊ฒฝ์กฐ๊ฑด ์ธ์ž ์ค‘ ํŠนํžˆ, ์‹ค์™ธ ๋ฏธ์„ธ๋จผ์ง€ ๋†๋„์™€ ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€ ๋ฐœ์ƒ์œจ์˜ ์˜ํ–ฅ์„ ํฌ๊ฒŒ ๋ฐ›๋Š”๋‹ค. ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€ ๋†๋„ ๊ฐœ์„ ์„ ์œ„ํ•ด Ventilation ์ œ์–ด๋ฅผ ์ ์šฉํ•˜๋Š” ๊ฒฝ์šฐ, ํ™˜๊ธฐํ’๋Ÿ‰์ด ์ž‘์„ ๋•Œ๋Š” ์™ธ๊ธฐ ๋„์ž…๋Ÿ‰์ด ์ž‘์•„ ํ•„ํ„ฐํšจ์œจ์˜ ์˜ํ–ฅ์ด ํฌ์ง€ ์•Š๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ํ™˜๊ธฐํ’๋Ÿ‰์ด ํด ๋•Œ ์ €ํšจ์œจ ํ•„ํ„ฐ์˜ ์ ์šฉ์€ ์‹ค์™ธ ๋ฏธ์„ธ๋จผ์ง€ ๋†๋„๊ฐ€ ๋†’์•„์ง์— ๋”ฐ๋ผ ์‹ค๋‚ด ๋†๋„๋ฅผ ๊ธ‰๊ฒฉํžˆ ์ฆ๊ฐ€์‹œํ‚ฌ ์ˆ˜ ์žˆ๊ธฐ ๋•Œ๋ฌธ์— ์ค‘ํšจ์œจ ๋“ฑ๊ธ‰ ์ด์ƒ์˜ ํ•„ํ„ฐ ์ ์šฉ์ด ์š”๊ตฌ๋œ๋‹ค. Filtration ์ œ์–ด์˜ ๊ฒฝ์šฐ, ํ•„ํ„ฐํšจ์œจ์ด ํด์ˆ˜๋ก ํ’๋Ÿ‰ ์ฆ๊ฐ€์— ๋”ฐ๋ฅธ ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€ ๋†๋„ ๊ฐœ์„  ํšจ๊ณผ๊ฐ€ ๋” ์ปค์ง€๋ฏ€๋กœ ๊ณ ํšจ์œจ ํ•„ํ„ฐ ์ ์šฉ์ด ์œ ๋ฆฌํ•˜๋‹ค. (2) ๊ณ„์†ํ•ด์„œ ๋ณ€ํ™”ํ•˜๋Š” ์‹ค์™ธ ๋ฏธ์„ธ๋จผ์ง€ ๋†๋„๋ฅผ ์ธก์ •ํ•˜๊ณ , ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€ ๋ฐœ์ƒ์œจ์„ ์˜ˆ์ธกํ•˜์—ฌ Ventilation๊ณผ Filtration ์ œ์–ด ๋ชจ๋“œ์™€ ์ œ์–ด๋Ÿ‰์„ ๊ฒฐ์ •ํ•  ์ˆ˜ ์žˆ๋Š” ์ œ์–ด ์ „๋žต์„ ์ œ์‹œํ•˜์˜€๋‹ค. ์ด๋ฅผ ์ ์šฉํ•˜๋ฉด, ์‹ค์™ธ ๋ฏธ์„ธ๋จผ์ง€ ๋†๋„๊ฐ€ ๋†’๊ณ , ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€ ๋ฐœ์ƒ์œจ๋„ ๋†’์€ ํ™˜๊ฒฝ์กฐ๊ฑด์—์„œ ๊ธฐ์กด ์ œ์–ด์™€ ๋น„๊ตํ•˜์—ฌ ์œ ์‚ฌํ•œ ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€ ๋†๋„๋ฅผ ์œ ์ง€ํ•˜๊ณ  ๋น„์Šทํ•œ ํŒฌ๋™๋ ฅ์„ ์‚ฌ์šฉํ•˜๋ฉด์„œ ์‹ค๋‚ด ๋ฐœ์ƒ ์˜ค์—ผ๋ฌผ์งˆ ๊ด€๋ฆฌ์—๋Š” ์œ ๋ฆฌํ•˜์˜€๋‹ค. ์‹ค์™ธ ๋ฏธ์„ธ๋จผ์ง€ ๋†๋„๊ฐ€ ๋†’๊ณ , ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€ ๋ฐœ์ƒ์œจ์ด ๋‚ฎ์„ ๋•Œ๋Š” ์ƒ๋Œ€์ ์ธ ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€ ๋†๋„๋Š” ๋†’์•˜์œผ๋‚˜ ๋ฏธ์„ธ๋จผ์ง€ ์‹ค๋‚ด ๋ชฉํ‘œ๋†๋„ ์ดํ•˜ ์œ ์ง€๋Š” ๊ฐ€๋Šฅํ•˜์˜€๊ณ , ์‹ค๋‚ด ๋ฐœ์ƒ ์˜ค์—ผ๋ฌผ์งˆ ๊ด€๋ฆฌ์— ์œ ๋ฆฌํ•˜๋ฉฐ ํŒฌ๋™๋ ฅ์„ ์ ๊ฒŒ ์‚ฌ์šฉํ•˜์˜€๋‹ค. ์‹ค์™ธ ๋ฏธ์„ธ๋จผ์ง€ ๋†๋„๋Š” ๋‚ฎ๊ณ , ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€ ๋ฐœ์ƒ์œจ์€ ๋†’์€ ํ™˜๊ฒฝ์กฐ๊ฑด์—์„œ๋Š” ํŒฌ๋™๋ ฅ์€ ์ƒ๋Œ€์ ์œผ๋กœ ๋งŽ์ด ์‚ฌ์šฉํ•˜์ง€๋งŒ ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€ ๋†๋„ ๊ฒฝ๊ฐ์— ์œ ๋ฆฌํ•˜์˜€๋‹ค. ์‹ค์™ธ ๋ฏธ์„ธ๋จผ์ง€ ๋†๋„๋„ ๋‚ฎ๊ณ , ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€ ๋ฐœ์ƒ์œจ๋„ ๋‚ฎ์„ ๋•Œ๋Š” ์ƒ๋Œ€์ ์œผ๋กœ ์ ์€ ํŒฌ๋™๋ ฅ์„ ์‚ฌ์šฉํ•˜๋ฉด์„œ ์œ ์‚ฌํ•œ ์ˆ˜์ค€์œผ๋กœ ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€ ๋†๋„ ๋ฐ ์‹ค๋‚ด ๋ฐœ์ƒ ์˜ค์—ผ๋ฌผ์งˆ ๊ด€๋ฆฌ๋ฅผ ํ•  ์ˆ˜ ์žˆ๋‹ค.์ œ 1 ์žฅ ์„œ ๋ก  1 1.1 ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์  1 1.2 ์—ฐ๊ตฌ์˜ ๋ฒ”์œ„ ๋ฐ ๋ฐฉ๋ฒ• 5 ์ œ 2 ์žฅ ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€ ์ œ์–ด๋ฅผ ์œ„ํ•œ ์˜ˆ๋น„์  ๊ณ ์ฐฐ 10 2.1 ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€ ๋†๋„ ํ˜•์„ฑ ๊ฐœ์š” 11 2.1.1 ๋ฏธ์„ธ๋จผ์ง€์˜ ํŠน์„ฑ 11 2.1.2 ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€์˜ ๋†๋„ ํ˜•์„ฑ ๋ฉ”์ปค๋‹ˆ์ฆ˜ 16 2.1.3 ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€ ๋†๋„ ํ˜•์„ฑ ์˜ํ–ฅ์ธ์ž 19 2.2 ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€ ํ‰๊ฐ€๋ฐฉ๋ฒ• 29 2.2.1 ์ธก์ •์— ์˜ํ•œ ํ‰๊ฐ€ 29 2.2.2 ๋ชจ๋ธ๋ง์— ์˜ํ•œ ํ‰๊ฐ€ 30 2.3 Ventilation๊ณผ Filtration ์ œ์–ด ๊ด€๋ จ ๊ธฐ์กด ์—ฐ๊ตฌ 38 2.3.1 Prescribed ventilation๊ณผ filtration ์ œ์–ด์—ฐ๊ตฌ 38 2.3.2 ํ™˜๊ฒฝ ๋Œ€์‘ํ˜• ventilation๊ณผ filtration ์ œ์–ด์—ฐ๊ตฌ 40 2.4 ์†Œ ๊ฒฐ 45 ์ œ 3 ์žฅ ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€ ๋†๋„ ๋ฐ ๋ฐœ์ƒ ์˜ˆ์ธก ํ•ด์„๋ชจ๋ธ 47 3.1 ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€ ๋†๋„ ๋ฐ ๋ฐœ์ƒ ์˜ˆ์ธก ํ•ด์„์ด๋ก  48 3.1.1 ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€ ๋†๋„ ํ•ด์„์ด๋ก  48 3.1.2 ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€ ๋ฐœ์ƒ ์˜ˆ์ธก ํ•ด์„์ด๋ก  55 3.2 ์˜ํ–ฅ์ธ์ž ๋„์ถœ ๋ฐ ํ•ด์„๋ชจ๋ธ ๊ตฌ์ถ• 57 3.3 ํ˜„์žฅ์‹คํ—˜์„ ํ†ตํ•œ ํ•ด์„๋ชจ๋ธ ๊ฒ€์ฆ 59 3.3.1 ํ•ด์„๋ชจ๋ธ์˜ ๊ณ„์ˆ˜ ์ถ”์ • 61 3.3.2 ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€ ๋†๋„ ํ•ด์„๋ถ€์˜ ๊ฒ€์ฆ 68 3.3.3 ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€ ๋ฐœ์ƒ ์˜ˆ์ธก ํ•ด์„๋ถ€์˜ ๊ฒ€์ฆ 74 3.4 ์†Œ ๊ฒฐ 76 ์ œ 4 ์žฅ ์ฃผ์š” ์˜ํ–ฅ์ธ์ž ๋ณ€ํ™”์— ๋”ฐ๋ฅธ ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€ ๋†๋„ํŠน์„ฑ 77 4.1 ์ฃผ์š” ์˜ํ–ฅ์ธ์ž ์„ ์ • ๋ฐ ํ‰๊ฐ€๋ฒ”์œ„ ๊ฒฐ์ • 78 4.1.1 ์ฃผ์š” ์˜ํ–ฅ์ธ์ž์˜ ์„ ์ • 78 4.1.2 ์ฃผ์š” ์˜ํ–ฅ์ธ์ž์˜ ํ‰๊ฐ€๋ฒ”์œ„ 83 4.2 ์ฃผ์š” ์˜ํ–ฅ์ธ์ž ๋ณ€ํ™”์— ๋”ฐ๋ฅธ ์‹ค๋‚ด ๋†๋„ํŠน์„ฑ 86 4.2.1 ํ™˜๊ฒฝ์กฐ๊ฑด ์˜ํ–ฅ์ธ์ž์˜ ๋ณ€ํ™”์— ๋”ฐ๋ฅธ ํŠน์„ฑ 86 4.2.2 Ventilation ์ œ์–ด๊ด€๋ จ ์˜ํ–ฅ์ธ์ž์˜ ๋ณ€ํ™”์— ๋”ฐ๋ฅธ ํŠน์„ฑ 89 4.2.3 Filtration ์ œ์–ด๊ด€๋ จ ์˜ํ–ฅ์ธ์ž์˜ ๋ณ€ํ™”์— ๋”ฐ๋ฅธ ํŠน์„ฑ 96 4.3 ์†Œ ๊ฒฐ 100 ์ œ 5 ์žฅ Ventilation๊ณผ Filtration์— ์˜ํ•œ ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€ ์ œ์–ด ์ „๋žต 103 5.1 ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€ ์ œ์–ด ๊ฐœ๋… 104 5.1.1 ํ™˜๊ฒฝ์กฐ๊ฑด์— ๋”ฐ๋ฅธ ์‹ค๋‚ด ๋ฏธ์„ธ๋จผ์ง€ ์ œ์–ด ๊ฐœ๋… 106 5.1.2 Control limit (CL) ์ปค๋ธŒ๋ฅผ ํ™œ์šฉํ•œ ์ œ์–ด ๊ฐœ๋… 110 5.2 Ventilation๊ณผ Filtration ์ œ์–ด๋ชจ๋“œ์™€ ์ œ์–ด๋Ÿ‰ ๊ฒฐ์ •๋ฐฉ๋ฒ• 121 5.2.1 ํ™˜๊ฒฝ์กฐ๊ฑด ํŒŒ์•… (Step 1 & 2) 122 5.2.2 ํ™˜๊ฒฝ์กฐ๊ฑด ๋ณ„ ์ œ์–ด๋ชจ๋“œ์™€ ์ œ์–ด๋Ÿ‰ ๊ฒฐ์ •๋ฐฉ๋ฒ• (Step 3) 126 5.3 Ventilation๊ณผ Filtration ์ œ์–ด ์•Œ๊ณ ๋ฆฌ์ฆ˜ ๋„์ถœ ๋ฐ ์ ์šฉ 132 5.3.1 Ventilation๊ณผ Filtration ์ œ์–ด ์•Œ๊ณ ๋ฆฌ์ฆ˜ ๋„์ถœ 132 5.3.2 Ventilation๊ณผ Filtration ์ œ์–ด์˜ ์ ์šฉ 136 5.4 ์†Œ ๊ฒฐ 143 ์ œ 6 ์žฅ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ํ†ตํ•œ ์ œ์–ด ์ „๋žต ์ ์šฉํšจ๊ณผ ํ‰๊ฐ€ 145 6.1 ํ‰๊ฐ€ ๊ฐœ์š” 146 6.1.1 ํ‰๊ฐ€ ์š”์†Œ 146 6.1.2 ํ‰๊ฐ€ ๋ชจ๋ธ 149 6.2 ํ‰๊ฐ€ ์ผ€์ด์Šค 154 6.2.1 ํ™˜๊ฒฝ์กฐ๊ฑด ์ผ€์ด์Šค 154 6.2.2 ์‹œ์Šคํ…œ ๋ฐ ์ œ์–ด ์ผ€์ด์Šค 156 6.3 ํ‰๊ฐ€ ๊ฒฐ๊ณผ 160 6.3.1 ํ™˜๊ฒฝ์กฐ๊ฑด E1์— ๋Œ€ํ•œ ์‹œ์Šคํ…œ ๋ฐ ์ œ์–ด ์ผ€์ด์Šค ๋น„๊ต 160 6.3.2 ํ™˜๊ฒฝ์กฐ๊ฑด E2์— ๋Œ€ํ•œ ์‹œ์Šคํ…œ ๋ฐ ์ œ์–ด ์ผ€์ด์Šค ๋น„๊ต 163 6.3.3 ํ™˜๊ฒฝ์กฐ๊ฑด E3์— ๋Œ€ํ•œ ์‹œ์Šคํ…œ ๋ฐ ์ œ์–ด ์ผ€์ด์Šค ๋น„๊ต 166 6.4 ์†Œ ๊ฒฐ 169 ์ œ 7 ์žฅ ๊ฒฐ ๋ก  173 ์ฐธ ๊ณ  ๋ฌธ ํ—Œ 181Docto

    ๋‚จํƒœํ‰์–‘๋„์„œ๊ตญ์˜ ๊ธฐํ›„๋ณ€ํ™” ์ ์‘ ์žฌ์ •์— ๋Œ€ํ•œ ์ ‘๊ทผ์„ฑ ์—ฐ๊ตฌ: ํ”ผ์ง€ ์‚ฌ๋ก€๋ฅผ ์ค‘์‹ฌ์œผ๋กœ

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ํ™˜๊ฒฝ๊ณ„ํšํ•™๊ณผ, 2017. 2. ์œค์ˆœ์ง„.Accessing Climate Finance in the Pacific Island Countries: A Case Study of the Fiji Islands Jihyea Kim Department of Environmental Planning Graduate School of Environmental Studies Seoul National University The Paris Agreement made at the 21st session of the Conference of Parties (COP) of the United Nations Framework Convention on Climate Change (UNFCCC) was the first-ever universal, legally binding global climate deal that set the stage for a new era of enhanced climate finance for developing countries. Reaffirming the commitment of developed countries to mobilize 100 billion USD a year by 2020, the agreement stressed the equal importance of adaptation finance alongside mitigation finance and called for UNFCCC climate funds to balance their allocation and distribution of climate finance. Within this framework, climate adaptation finance was emphasized as an important source of finance for the Pacific Island Countries (PICs) โ€“ islands that bear little responsibility for climate change but are extremely vulnerable to the impacts of climate change. Funding has been made available for the regionhowever, access to these funds has not been an easy task for the PICs and the gap between the inflow of funds and the actual needed amount is increasing. This study uses the case study of Fiji to understand the system of climate adaptation finance in the PICs, the challenges that hinder them from accessing the needed amounts of finance, and the opportunities that lie ahead. The study is a qualitative exploratory study in that it seeks to determine the nature of the research issue on which little or no previous research has been done. Literature reviews, site visits and interviews are used as a means of exploring the research objectives and collecting initial information and data needed to answer the research questions. The results of this study are divided into two parts. First, the three key elements of the climate finance system are financial flow, actor groups and modes of access. The current climate adaptation finance system in Fiji is consists of two types of flow- bilateral and multilateralfour main actor groups- donors, finance institutions, implementing entities, and recipient governmentand two modes of access- direct and indirect. Differing combinations of these three elements create diverse structures of climate adaptation finance. Second, the three main challenges of accessing climate adaptation finance are: national capacity constraints that limit accesscomplex, long and different processes for accessand the potential adverse effects of direct access accreditation on national systems. The three main opportunities for future access are: increased attention to national institutional strengthening and capacity buildingstreamlined processes for accreditation and project approval for PICsand regional information sharing and networking. The findings of this exploratory case study of Fiji serve as a broad reflection of the reality of accessing climate adaptation finance in the PICs and provide a basis for future research on climate adaptation finance in the Pacific region. Keywords: Climate Change Adaptation, Adaptation Finance, Accessing Adaptation Finance, Fiji, Pacific Island Countries Student Number: 2014-24025I. Introduction 1 1. Research Background 1 2. Research Purpose, Scope and Objectives 4 II. Literature Review and Theoretical Framework 6 1. Climate Adaptation Finance 6 2. Accessing Climate Adaptation Finance 18 III. Case Introduction: The Fiji Islands 26 1. Geographic, Political and Socio-Economic Background 26 2. Climate Change Impacts and Urgent Needs in Fiji 30 3. Climate Change Awareness of Pacific Communities 35 IV. Research Methodology 38 1. Research Methodology and Design 38 2. Research Reliability and Validity 46 V. Accessing Climate Adaptation Finance in Fiji 48 1. Architecture of Climate Adaptation Finance 48 2. Accreditation and Project Approval 58 3. Status of Access for Fiji and the PICs 67 VI. Challenges and Opportunities in Accessing Climate Adaptation Finance in Fiji 70 1. Challenges in Accessing Adaptation Finance 70 2. Opportunities in Accessing Adaptation Finance 90 3. Summary of Findings and the Way Forward 97 VII. Conclusion 101 1. Research Summary 101 2. Implications of Research and Future Research 102 References 105 Appendix A 115 Appendix B 116 Abstract Korean 120Maste

    ๊ณ ์šฉ๋Ÿ‰ pitavastatin์ด ๊ฒฝ๋™๋งฅ ํƒ„์„ฑ์— ์ฃผ๋Š” ์˜ํ–ฅ์„ ๋ฐ˜์  ์ถ”์  ์˜์ƒ์„ ์ด์šฉํ•˜์—ฌ ๋ถ„์„ํ•œ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ž„์ƒ์˜๊ณผํ•™๊ณผ, 2017. 2. ๊น€์šฉ์ง„.Background: Two-dimensional speckle-tracking strain imaging has been introduced for the precise assessment of arterial mechanics. The objective of this study was to evaluate the short-term effects of pitavastatin on carotid artery elasticity measured by speckle tracking methods. Methods: This study included 30 statin-naรฏve patients (age, 61.6 ยฑ 7.6 years26.7% male) with hypercholesterolemia. Circumferential carotid artery strain (CAS) was measured using speckle-tracking imaging before and after 3 months of high-dose pitavastatin treatment (4 mg daily). Results: After 3 months, circumferential CAS was significantly increased compared to baseline (from 2.73 ยฑ 1.17% to 3.27 ยฑ 1.53%, p = 0.029). Among conventional carotid elasticity metrics, strain measured by B-mode improved significantly after statin therapy. No significant change in carotid intima-media thickness was observed after pitavastatin treatment (from 0.73 ยฑ 0.18 to 0.71 ยฑ 0.16 mm, p = 0.913). Conclusions: Short-term treatment with high-dose pitavastatin improved carotid artery elasticity measured by speckle-tracking methods. These speckle-tracking imaging-based measurements may allow the early noninvasive assessment of favorable effects of medical intervention in patients with hypercholesterolemia.Introduction 1 Methods 3 Results 7 Discussion 15 Conclusion 19 References 20 ๊ตญ๋ฌธ์ดˆ๋ก 24Maste

    ์ง์žฅ ์‹ ๊ฒฝ๋‚ด๋ถ„๋น„์ข…์–‘์˜ ๋‚ด์‹œ๊ฒฝ์  ์ ๋ง‰์ ˆ์ œ์ˆ ์˜ ์น˜๋ฃŒ ์„ฑ์ 

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ž„์ƒ์˜๊ณผํ•™๊ณผ, 2017. 2. ๊น€์šฉ์ง„.Introduction: The incidence of rectal neuroendocrine tumors (NETs) is rapidly increasing because of the frequent use of endoscopic screening for colorectal cancers. However, the clinical outcomes of endoscopic resection for rectal NETs are still unclear. The aim of this study was to assess the histologically complete resection (H-CR) rate and recurrence after the endoscopic resection for rectal NETs. Methods: A retrospective analysis was performed in the patients who underwent endoscopic mucosal resection (EMR) of rectal NETs between January 2002 and March 2015 at Seoul National University Hospital. Primary outcomes were H-CR and recurrence rates after the endoscopic resection. H-CR was defined as free of tumor invasion in the lateral and deep margins of resected specimens. Results: Among 277 patients, 243 (88%) were treated with conventional EMR, 23 (8%) with EMR using a dual-channel endoscope, and 11 (4%) with EMR after precutting. The median tumor size was 4.96 (range, 1-22) mm in diameter and 264 (95%) of the lesions were confined to mucosa and submucosal layer. The en-bloc resection rate was 99% and all patients achieved endoscopically complete resection. The H-CR rates were 75%, 74% and 73% for conventional EMR, EMR using a dual-channel endoscope and EMR after precutting, respectively. Multivariate analysis showed that H-CR was associated with tumor size regardless of endoscopic treatment modalities (p=0.001). Of the 277 patients, 183 patients (66%) underwent at least one endoscopic follow-up. Four out of the 183 patients (2%) with endoscopic follow-up had tumor recurrence with a median of 45 months (range 2-98). There was 1 case of disease-related death occurred 167 months after the endoscopic treatment because of bone marrow failure as a result of tumor metastasis. Conclusions: Although the en-bloc resection rate was 99% in rectal NETs, H-CR rates were 72-74% for various EMR procedures. H-CR may be associated with tumor size regardless of endoscopic treatment modalities.Introduction 1 Material and Methods 3 Results 7 Discussion 16 References 23 Abstract in Korean 27Maste

    "์ผ์ƒ์˜ ๊ธฐ์ ๋“ค": ๋ฒ„์ง€๋‹ˆ์•„ ์šธํ”„์˜ ใ€Ž๋“ฑ๋Œ€๋กœใ€์— ๋“œ๋Ÿฌ๋‚œ ์ˆœ๊ฐ„์˜ ๋ฏธํ•™

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์˜์–ด์˜๋ฌธํ•™๊ณผ, 2016. 2. ์†์˜์ฃผ.๋ณธ ๋…ผ๋ฌธ์€ ๋ฒ„์ง€๋‹ˆ์•„ ์šธํ”„๊ฐ€ ๊ทธ๋…€์˜ ์—ฌ๋Ÿฌ ์—์„ธ์ด ์†์—์„œ ์ง„์‹คํ•œ ์‚ถ์€ ๋ฌด์—‡์ธ๊ฐ€์— ๋Œ€ํ•ด ๋Š์ž„์—†์ด ๊ณ ๋ฏผํ•œ ์ž‘๊ฐ€๋ผ๋Š” ์ ์— ์ฐฉ์•ˆํ•˜์—ฌ ์šธํ”„๊ฐ€ ใ€Ž๋“ฑ๋Œ€๋กœใ€์—์„œ ๊ทธ๋ ค๋‚ธ ์ง„์‹คํ•œ ์‚ถ์€ ๋ฌด์—‡์ธ์ง€ ํƒ๊ตฌํ•œ๋‹ค. ๊ตฌ์ฒด์ ์œผ๋กœ ๋ณธ ๋…ผ๋ฌธ์€ ใ€Ž๋“ฑ๋Œ€๋กœใ€์—์„œ ์˜ฌ๋ฐ”๋ฅธ ์ธ์‹์˜ ๋ฐฉ์‹์ด ๊ณง ์˜จ์ „ํ•œ ์‚ถ์„ ์‚ฌ๋Š” ๊ฒƒ์œผ๋กœ ์ด์–ด์ง„๋‹ค๋Š” ๊ฒƒ์„ ๋ฐํžŒ๋‹ค. ๊ณง ใ€Ž๋“ฑ๋Œ€๋กœใ€์—์„œ ์กด์žฌ๋ก ๊ณผ ์ธ์‹๋ก ์€ ๋ถˆ๊ฐ€๋ถ„์˜ ๊ด€๊ณ„์— ์žˆ๋‹ค๋Š” ๊ฒƒ์„ ๋ฐํžˆ๋Š” ๊ฒƒ์ด๋‹ค. 1์žฅ์—์„œ๋Š” ์ธ๋ฌผ๋“ค์˜ ์ž์œ ๋กœ์šด ์ธ์‹์„ ๊ฐ€๋กœ๋ง‰๋Š” ๊ฐ€๋ถ€์žฅ์ œ์˜ ๊ทœ๋ฒ”๋“ค์— ๋Œ€ํ•ด ์‚ดํŽด๋ณธ๋‹ค. ๊ฐ€๋ถ€์žฅ์ œ์˜ ๊ทœ๋ฒ”๋“ค์€ ๊ฐœ์ธ์—๊ฒŒ ์—ญํ• ๊ณผ ์ž„๋ฌด๋ฅผ ๋ถ€์—ฌํ•จ์œผ๋กœ์จ ๊ฐœ์ธ์„ ์ •์˜ํ•œ๋‹ค. ๊ฐ€๋ถ€์žฅ์ œ๊ฐ€ ๋ถ€๊ณผํ•œ ์ธ์‹์˜ ํ‹€ ์†์—์„œ ๊ฐœ์ธ์˜ ์ž๊ธฐ ์ž์‹ ๊ณผ ๋‚จ, ๊ทธ๋ฆฌ๊ณ  ์„ธ์ƒ ์ „๋ฐ˜์— ๋Œ€ํ•œ ์ดํ•ด๋Š” ์ œํ•œ๋˜๊ณ  ์™œ๊ณก๋œ๋‹ค. ์„ฑ์—ญํ• ์„ ๋น„๋กฏํ•œ ๋‹ค์–‘ํ•œ ์—ญํ• ๋“ค๋กœ ์ธํ•ด ๊ทธ ์—ญํ• ์— ๋งž๋„๋ก ์ž์‹ ์˜ ๋‚ด์  ์ž์•„๋ฅผ ์–ต์••ํ•˜๊ฑฐ๋‚˜, ํƒ€์ธ๊ณผ์˜ ๊ด€๊ณ„๋ฅผ ์œ ์—ฐํ•˜์ง€ ๋ชปํ•œ ๋ฐฉ์‹์œผ๋กœ ๋งบ๋Š” ๊ฒƒ์ด ๋ฌธ์ œ๊ฐ€ ๋œ๋‹ค. 1์žฅ์—์„œ๋Š” ๊ฐ€๋ถ€์žฅ์ œ๊ฐ€ ๋ถ€์—ฌํ•˜๋Š” ๋‹จ์„ ์ ์ธ ์‹œ์„ ์ด ์˜จ์ „ํ•œ ์‚ถ์„ ๋ฐฉํ•ดํ•˜๋Š” ์š”์†Œ๋กœ์„œ ๋‹ค๋ฃจ์–ด์ง„๋‹ค. 2์žฅ์—์„œ๋Š” ใ€Ž๋“ฑ๋Œ€๋กœใ€์—์„œ ํ˜„์‹ค์ด ์–ด๋–ป๊ฒŒ ๊ตฌํ˜„๋˜๊ณ  ์žˆ๋Š” ์ง€๋ฅผ ๋‹ค๋ฃจ๋ฉด์„œ ๊ฐœ์ธ์ด ํ˜„์‹ค์„ ์ธ์‹ํ•˜๋Š” ํƒœ๋„๊ฐ€ ์‚ถ์—์„œ์˜ ๊ฒฝํ—˜๊ณผ ๋ฐ€์ ‘ํ•œ ๊ด€๊ณ„๊ฐ€ ์žˆ์Œ์„ ๋ฐํžŒ๋‹ค. ์œ ๋™์ ์ด์–ด์„œ ์‰ฝ๊ฒŒ ์ดํ•ดํ•˜๊ฑฐ๋‚˜ ํ™˜์›ํ•˜๊ธฐ๊ฐ€ ๋ถˆ๊ฐ€๋Šฅํ•œ ํ˜„์‹ค ์•ž์—์„œ ์ธ๋ฌผ์€ ๋ถˆ์•ˆ๊ฐ์„ ๋Š๋ผ๊ณ  ๊ทธ ๊ฒฐ๊ณผ ํ˜„์‹ค์˜ ์œ ๋™์„ฑ์„ ์ธ์ •ํ•˜์ง€ ์•Š๋Š” ์–ต์••์ ์ธ ์„ธ๊ณ„๊ด€์œผ๋กœ ๋ถˆ์•ˆ๊ฐ์„ ํ•ด์†Œํ•˜๋ ค ํ•˜๊ฑฐ๋‚˜ ๋ฐ˜๋Œ€๋กœ ํ˜„์‹ค ์•ž์—์„œ์˜ ์‹ค๋ง๊ณผ ์ขŒ์ ˆ, ๋ถ„๋…ธ ๋“ฑ์œผ๋กœ ์ธํ•ด ํ—ˆ๋ฌด์ฃผ์˜๋‚˜ ๋น„๊ด€์ฃผ์˜์— ๋น ์ง€๋Š” ๋ชจ์Šต์„ ๋ณด์—ฌ์ค€๋‹ค. 2์žฅ์—์„œ๋Š” ์ด๋Ÿฌํ•œ ํ˜„์‹ค๊ณผ ๊ฐœ์ธ ๊ฐ„์˜ ๊ฐˆ๋“ฑ ์–‘์ƒ์„ ๋‹ค๋ฃจ๋ฉฐ ํ˜„์‹ค์„ ์–ต์••ํ•˜๊ฑฐ๋‚˜ ํ˜„์‹ค์— ์œ„์ถ•๋˜๋Š” ํƒœ๋„๊ฐ€ ๋ชจ๋‘ ์ž์œ ๋กญ๊ณ  ํ’์š”๋กœ์šด ๊ฒฝํ—˜์„ ์ œํ•œํ•œ๋‹ค๋Š” ์ธก๋ฉด์—์„œ ๋ฌธ์ œ๊ฐ€ ๋จ์„ ๋ฐํžŒ๋‹ค. 3์žฅ์—์„œ๋Š” ใ€Ž๋“ฑ๋Œ€๋กœใ€๊ฐ€ ํ˜„์‹ค์„ ์–ต์••ํ•˜์ง€๋„, ํ˜„์‹ค์— ์–ต๋ˆŒ๋ฆฌ์ง€๋„ ์•Š๋Š” ์ ˆ๋ฌ˜ํ•œ ๊ท ํ˜•์˜ ์ง€์ ์„ ์ฐพ๊ณ  ์žˆ์œผ๋ฉฐ, ๊ทธ ๊ท ํ˜•์€ ์ˆœ๊ฐ„์„ ์‚ฌ๋Š” ๊ฒƒ์„ ํ†ตํ•ด์„œ ๋„๋‹ฌ๋  ์ˆ˜ ์žˆ๋‹ค๋Š” ๊ฒƒ์„ ๋ฐํžŒ๋‹ค. ใ€Ž๋“ฑ๋Œ€๋กœใ€์—์„œ๋Š” ์ˆœ๊ฐ„์„ ์‚ฌ๋Š” ๊ฒƒ์„ ํ†ตํ•ด ์ธ์‹ ์ƒ์˜ ๋ฌธ์ œ์— ๊ทผ๊ฑฐํ•œ ์‚ถ์˜ ์ œํ•œ์„ ๋šซ๊ณ  ์ƒ์ƒํ•œ ๊ฒฝํ—˜์„ ํ•  ์ˆ˜ ์žˆ์Œ์ด ๋“œ๋Ÿฌ๋‚œ๋‹ค. ํ˜„์‹ค๊ณผ ๊ฐœ์ธ ๊ฐ„์˜ ๊ฐˆ๋“ฑ์€ ์ƒ๋‹น๋ถ€๋ถ„ ํ˜„์‹ค์˜ ์œ ๋™์„ฑ์„ ์ธ์ •ํ•˜์ง€ ์•Š๋Š” ๋‹จ์„ ์ ์ธ ์‹œ๊ฐ์— ๊ธฐ์ธํ•˜๊ธฐ ๋•Œ๋ฌธ์—, ์ผ์ƒ ์†์˜ ์ˆœ๊ฐ„์„ ์‚ด๋ฉฐ ํ˜„์‹ค์˜ ์œ ๋™์„ฑ์„ ์„ฌ์„ธํ•˜๊ฒŒ ์ธ์‹ํ•จ์œผ๋กœ์จ ๊ฐœ์ธ์€ ๋ณด๋‹ค ์ž์œ ๋กญ๊ณ  ํ’์š”๋กœ์šด ๊ฒฝํ—˜์„ ํ•  ์ˆ˜ ์žˆ๊ฒŒ ๋œ๋‹ค.1. ์„œ๋ก  1 ๋ณธ๋ก 1. ๊ฐ€๋ถ€์žฅ์ œ์™€ ์ธ์‹์˜ ์™œ๊ณก 26 ๋ณธ๋ก 2. ํ˜„์‹ค ์ธ์‹๊ณผ ์‚ถ์— ๋Œ€ํ•œ ํƒœ๋„ 45 ๋ณธ๋ก 3. ์œ„๋Œ€ํ•œ ๊ณ„์‹œ์—์„œ ์ผ์ƒ์˜ ๊ธฐ์ ๋“ค๋กœ 65 5. ๊ฒฐ๋ก  82 ์ธ์šฉ๋ฌธํ—Œ 84 Abstract 89Maste
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