78 research outputs found

    ์Šคํฌ๋ฆฝํŠธ ๊ธฐ๋ฐ˜์˜ ๋ฒ”์šฉ 3์ฐจ์› ์ธ์ฒด ์ธก์ • ์‹œ์Šคํ…œ ๊ฐœ๋ฐœ

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ƒํ™œ๊ณผํ•™๋Œ€ํ•™ ์˜๋ฅ˜ํ•™๊ณผ, 2018. 8. ๊น€์„ฑ๋ฏผ.๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ธ์ฒด ์Šค์บ๋„ˆ ์ข…๋ฅ˜์™€ ๊ด€๊ณ„์—†์ด 3์ฐจ์› ์ธ์ฒด ์Šค์บ” ๋ฐ์ดํ„ฐ๋กœ๋ถ€ํ„ฐ ๋žœ๋“œ๋งˆํฌ๋ฅผ ๊ฒ€์ƒ‰ํ•˜๊ณ  ๊ฐ์ข… ์น˜์ˆ˜๋ฅผ ์ธก์ •ํ•˜๋Š”๋ฐ ํ•„์š”ํ•œ 3์ฐจ์› ์ธ์ฒด ์ธก์ • ์‹œ์Šคํ…œ์„ ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ์—ฌ๋Ÿฌ ์ธ์ฒด ์Šค์บ๋„ˆ์—์„œ ์ƒ์„ฑ๋œ ๋‹ค์–‘ํ•œ ํ˜•์‹์˜ 3์ฐจ์› ํ˜•์ƒ ๋ฐ์ดํ„ฐ๋ฅผ ์ž…์ถœ๋ ฅ์— ํ•„์š”ํ•œ ์ค‘๋ฆฝ์  ๋ฐ์ดํ„ฐ ๊ตฌ์กฐ๋กœ ์„ค๊ณ„ํ•˜๊ณ , ์„ค๊ณ„ํ•œ ๋ฐ์ดํ„ฐ ๊ตฌ์กฐ๋กœ ๋ณ€ํ™˜ํ•  ์ˆ˜ ์žˆ๋Š” ๋ฐ์ดํ„ฐ ๋ณ€ํ™˜ ์†Œํ”„ํŠธ์›จ์–ด๋ฅผ ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. ๋˜ํ•œ, ์ธก์ •ํ•ด์•ผ ํ•  ๋žœ๋“œ๋งˆํฌ๋‚˜ ์น˜์ˆ˜๋ฅผ ์†Œํ”„ํŠธ์›จ์–ด์— ๋ฏธ๋ฆฌ ์ •์˜ํ•ด ๋‘์ง€ ์•Š๊ณ  ์‹œ์Šคํ…œ์—์„œ ๊ฐœ๋ฐœ๋œ ์Šคํฌ๋ฆฝํŠธ ์–ธ์–ด๋กœ ์‚ฌ์šฉ์ž๊ฐ€ ์ธก์ •ํ•˜๊ธฐ ์›ํ•˜๋Š” ๋žœ๋“œ๋งˆํฌ๋‚˜ ์น˜์ˆ˜๋ฅผ ์ง์ ‘ ์ •์˜ํ•  ์ˆ˜ ์žˆ๊ฒŒ ์†Œํ”„ํŠธ์›จ์–ด ๊ฐœ๋ฐœํ•˜์—ฌ ํ”„๋กœ๊ทธ๋ž˜๋ฐ์— ๋Œ€ํ•œ ์ง€์‹์ด ์—†๋Š” ์‚ฌ์šฉ์ž๋ผ๋„ ์ธ์ฒด ์Šค์บ” ๋ฐ์ดํ„ฐ์˜ ํŠน์„ฑ์— ๋”ฐ๋ผ ์ž์œ ๋กญ๊ฒŒ ์ธ์ฒด ์ธก์ •์„ ์‹คํ–‰ํ•  ์ˆ˜ ์žˆ๋„๋ก ํ•˜์˜€๋‹ค. ์ด๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์ƒ…์ ์ด๋‚˜ ๊ฒจ๋“œ๋ž‘์  ๊ฐ™์ด ์ธ์ฒด ์ธก์ •์— ์ค‘์š”ํ•˜์ง€๋งŒ ์ •์˜ํ•˜๊ธฐ ๊นŒ๋‹ค๋กœ์šด ๋žœ๋“œ๋งˆํฌ๋ฅผ ์ž๋™์œผ๋กœ ์ฐพ๋Š” ํ•จ์ˆ˜๋„ ์ถ”๊ฐ€ํ•˜์˜€์œผ๋ฉฐ, ์ง์ ‘ ๋งŒ์ง€๊ฑฐ๋‚˜ ๋ผˆ์„ ํ†ตํ•ด ๊ฒ€์ƒ‰ํ•  ์ˆ˜ ์žˆ๋Š” ๋žœ๋“œ๋งˆํฌ๋ฅผ ์ธก์ •ํ•˜๊ธฐ ์œ„ํ•ด ์ธ๊ณต์‹ ๊ฒฝ๋ง์„ ํ™œ์šฉํ•˜์—ฌ ์ž๋™์œผ๋กœ ๋žœ๋“œ๋งˆํฌ๋ฅผ ๊ฒ€์ƒ‰ํ•˜๋Š” ๊ธฐ๋Šฅ๋„ ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. ๋์œผ๋กœ, ์ธก์ • ๊ฒฐ๊ณผ๋ฅผ ๋‹ค์–‘ํ•œ ๋ฐฉ๋ฒ•์œผ๋กœ ์‹œ๊ฐํ™”ํ•˜์—ฌ ๋ฐ์ดํ„ฐ ๋ถ„์„ ์ž‘์—…์ด ์šฉ์ดํ•˜๋„๋ก ๊ฐœ๋ฐœํ•˜์˜€์œผ๋ฉฐ, ์ด์™€ ๊ฐ™์€ ๋ชจ๋“  ์ž‘์—…์ด ํŽธ๋ฆฌํ•˜๋„๋ก ํ†ตํ•ฉ ๊ฐœ๋ฐœ ํ™˜๊ฒฝ์œผ๋กœ 3์ฐจ์› ์ธ์ฒด ์ธก์ • ์‹œ์Šคํ…œ์„ ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. ์ฃผ์š”์–ด : 3์ฐจ์› ์ธ์ฒด ์Šค์บ” ๋ฐ์ดํ„ฐ, ์ธ์ฒด ์ธก์ •, ๋ฒ”์šฉ ์†Œํ”„ํŠธ์›จ์–ด, ์Šคํฌ๋ฆฝํŠธ ๊ธฐ๋ฐ˜ ์ธก์ •, ๋žœ๋“œ๋งˆํฌ ๊ฒ€์ƒ‰, ํ†ตํ•ฉ ๊ฐœ๋ฐœ ํ™˜๊ฒฝ์ œ 1 ์žฅ ์„œ ๋ก  1 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ์˜ ํ•„์š”์„ฑ 1 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ์˜ ๋ชฉ์  4 ์ œ 2 ์žฅ ์„ ํ–‰ ์—ฐ๊ตฌ 5 ์ œ 1 ์ ˆ ์ž๋™ ๋žœ๋“œ๋งˆํฌ ์ธก์ • 5 ์ œ 2 ์ ˆ ์ž๋™ ์ธ์ฒด ์ธก์ • ์ƒ์šฉ ์†Œํ”„ํŠธ์›จ์–ด 8 ์ œ 3 ์žฅ ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• 10 ์ œ 1 ์ ˆ ์ธ์ฒด ๋ชจ๋ธ ๋ฐ์ดํ„ฐ ์„ค๊ณ„ 10 ์ œ 2 ์ ˆ ์ธ์ฒด ์ธก์ • ์†Œํ”„ํŠธ์›จ์–ด ์„ค๊ณ„ 12 ์ œ 4 ์žฅ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ ๋ฐ ๊ณ ์ฐฐ 14 ์ œ 1 ์ ˆ ๋ฐ์ดํ„ฐ ๋ณ€ํ™˜ ์†Œํ”„ํŠธ์›จ์–ด 14 ์ œ 2 ์ ˆ ํ†ตํ•ฉ ๊ฐœ๋ฐœ ํ™˜๊ฒฝ 15 ์ œ 3 ์ ˆ ์Šคํฌ๋ฆฝํŠธ ์‹œ์Šคํ…œ๊ณผ ๋ช…๋ น์–ด ์ •์˜ 17 1. ๊ธฐ๋ณธ ๋ช…๋ น์–ด 19 2. ๊ธฐํ•˜ํ•™ ๊ด€๋ จ ๋ช…๋ น์–ด 20 3. ์ธก์ • ๊ด€๋ จ ๋ช…๋ น์–ด 27 4. ํŠน์ˆ˜ ๋ช…๋ น์–ด 34 ์ œ 4 ์ ˆ ์Šคํฌ๋ฆฝํŠธ ์ž‘์„ฑ 42 1. ์ธ์ฒด ์˜์—ญ ๋ถ„ํ•  42 2. ์˜์—ญ ๋ถ„ํ•  ํ™œ์šฉ 45 ์ œ 5 ์ ˆ ๊ธฐ๊ณ„ ํ•™์Šต์„ ํ™œ์šฉํ•œ ๋žœ๋“œ๋งˆํฌ ๊ฒ€์ƒ‰ 48 ์ œ 5 ์žฅ ๊ฒฐ๋ก  ๋ฐ ์ œ์–ธ 51 ์ฐธ๊ณ ๋ฌธํ—Œ 53 Abstract 56 ๋ถ€ ๋ก 58Maste

    CMOS ํ™•์žฅ์„ ์œ„ํ•œ InGaAs MISFET์˜ ๊ฒŒ์ดํŠธ ์ ˆ์—ฐ๋ง‰๊ณผ ํ‘œ๋ฉด์ฒ˜๋ฆฌ์— ๊ด€ํ•œ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ „๊ธฐยท์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2015. 2. ์„œ๊ด‘์„.๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” Recessed planar type InGaAs MISFET ๊ตฌ์กฐ์—์„œ ๊ฐ€์žฅ ์ค‘์š”ํ•œ ๊ฒŒ์ดํŠธ ์ ˆ์—ฐ๋ง‰๊ณผ ๊ณ„๋ฉดํŠน์„ฑ์— ๊ด€ํ•œ ์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ํฐ ๋“œ๋ ˆ์ธ ์ „๋ฅ˜์™€ ํŠธ๋žœ์Šค์ปจ๋•ํ„ด์Šค, ๋‚ฎ์€ ๋ˆ„์„ค ์ „๋ฅ˜๊ฐ’์„ ๊ฐ–๋Š” InGaAs MISFET์— ์ ํ•ฉํ•œ ์ ˆ์—ฐ๋ง‰์˜ ํŠน์„ฑ์„ ์–ป๊ธฐ ์œ„ํ•ด, ์—ฌ๋Ÿฌ ๊ฐ€์ง€ ์ ˆ์—ฐ๋ง‰ ๋ฌผ์งˆ ํ›„๋ณด๊ตฐ ์ค‘์—์„œ ์‚ฐ์†Œ๊ธฐ๊ฐ€ ์—†๋Š” ๋ง‰์ธ PEALD SiNx ๋ง‰์„ ์„ ํƒํ•˜์˜€๋‹ค. ์ „๋ฐ˜์ ์œผ๋กœ InGaAs MISFET ๊ตฌ์กฐ์˜ ๊ฒŒ์ดํŠธ ์Šคํƒ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ํ‘œ๋ฉด์˜ Dit๊ฐ’๊ณผ ์ปคํŒจ์‹œํ„ด์Šค ํ™•์‚ฐํ˜„์ƒ์„ ์ค„์ด๊ณ  ์—ด์  ์•ˆ์ •์„ฑ์„ ์œ ์ง€ํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ๋ชจ์ƒ‰ํ•˜์˜€๋‹ค. ICP-CVD ์‹œ์Šคํ…œ์„ ์ด์šฉํ•˜์—ฌ SiNx ๋ฐ•๋ง‰์˜ ์ฆ์ฐฉ ๊ณต์ •์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ•˜์˜€๊ณ  ์ด๋ฅผ ํ†ตํ•ด ์—ด์  ์•ˆ์ •์„ฑ์„ ๊ฐ–๊ณ  ๋‚ฎ์€ ์ฃผํŒŒ์ˆ˜์—์„œ ์ปคํŒจ์‹œํ„ด์Šค ํ™•์‚ฐํ˜„์ƒ์ด ์ž‘์€ ์†Œ์ž๋ฅผ ์ œ์ž‘ ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ฑ”๋ฒ„ ์ฒ™ ์ฆ์ฐฉ ์˜จ๋„๋ฅผ ๋ณ€ํ™”์‹œ์ผœ๊ฐ€๋ฉฐ ์ฃผํŒŒ์ˆ˜์— ๋”ฐ๋ฅธ ์ปคํŒจ์‹œํ„ด์Šค ํ™•์‚ฐํ˜„์ƒ์„ ๊ฐœ์„ ํ•˜๋Š” ๋ฐฉ์•ˆ์„ ์ฐพ์•˜๋‹ค. ๋˜ํ•œ ํ‘œ๋ฉด์˜ ์ž์—ฐ์‚ฐํ™”๋ง‰ ์ฒ˜๋ฆฌ๋ฅผ ์œ„ํ•ด ๋””์ง€ํ„ธ ์—์น˜, ์•”๋ชจ๋‹ˆ์•„ ์—ผ๊ธฐ์„ฑ ์šฉ์•ก ์ฒ˜๋ฆฌ๋ฅผ ํ†ตํ•ด์„œ ๊ฐœ์„ ๋œ ๋ˆ„์„ค ์ „๋ฅ˜ ํŠน์„ฑ์„ ์–ป์—ˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ํ‘œ๋ฉด์˜ ๋ฐ๋ฏธ์ง€ ๊ฐ์†Œ๋ฅผ ์œ„ํ•ด N2 ํ”Œ๋ผ์ฆˆ๋งˆ ํŒŒ์›Œ๋ฅผ ๋‚ฎ์ถ”์–ด ๋ˆ„์„ค ์ „๋ฅ˜๋ฅผ ๋”์šฑ ๊ฐ์†Œ์‹œํ‚ฌ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ถ”๊ฐ€์ ์œผ๋กœ ๋ฉ”ํƒˆ ์ฆ์ฐฉ ์ดํ›„ ์—ด์ฒ˜๋ฆฌ๋ฅผ ํ†ตํ•ด ๋ฌธํ„ฑ์ „์••์„ ์–‘์ชฝ์œผ๋กœ ์ด๋™์‹œํ‚ค๊ณ  ํžˆ์Šคํ…Œ๋ฆฌ์‹œ์Šค, ์ฃผํŒŒ์ˆ˜์— ๋”ฐ๋ฅธ ์ปคํŒจ์‹œํ„ด์Šค ํ™•์‚ฐํ˜„์ƒ์„ ๊ฐœ์„ ํ•˜์˜€์œผ๋ฉฐ ํŠธ๋žœ์Šค์ปจ๋•ํ„ด์Šค์™€ ๋“œ๋ ˆ์ธ ์ „๋ฅ˜๋ฅผ ์ฆ๊ฐ€์‹œ์ผฐ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ ์ˆ˜์†Œ ๋ถ„์œ„๊ธฐ์˜ ์—ด์ฒ˜๋ฆฌ๋ฅผ ํ†ตํ•ด ๊ธฐ์กด์˜ ์งˆ์†Œ ๋ถ„์œ„๊ธฐ์˜ ์—ด์ฒ˜๋ฆฌ ๋ณด๋‹ค ๋ˆ„์„ค์ „๋ฅ˜๋ฅผ ๋”์šฑ ๊ฐ์†Œ์‹œํ‚ฌ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์œ„์— ์—ด๊ฑฐํ•œ ๋ฐฉ๋ฒ•๋“ค์„ ์ข…ํ•ฉํ•˜์—ฌ ๊ฒŒ์ดํŠธ ๊ธธ์ด๊ฐ€ ์งง์€ ์†Œ์ž(~100nm)๋ฅผ ์ œ์ž‘ํ•˜์—ฌ ๊ฐœ์„ ๋œ ํŠน์„ฑ์„ ์–ป์—ˆ๋‹ค. ์ถ”๊ฐ€์ ์œผ๋กœ high-k ๋ฌผ์งˆ์„ ๊ฒŒ์ดํŠธ ์ ˆ์—ฐ๋ง‰์œผ๋กœ ์‚ฌ์šฉํ•˜๊ธฐ ์œ„ํ•ด SiNx/Al2O3 ์ด์ค‘๋ง‰์— ๋Œ€ํ•œ ์—ฐ๊ตฌ ๋ฐ ์†Œ์ž ์ œ์ž‘์„ ํ†ตํ•ด ๋ฌธํ„ฑ์ „์•• ์ดํ•˜์—์„œ์˜ ๊ธฐ์šธ๊ธฐ ๊ฐ’์„ ๊ฐœ์„ ์‹œํ‚ค๋Š” ์—ฐ๊ตฌ๋„ ์ง„ํ–‰ ํ•˜์˜€๋‹ค.Contents Chapter 1. Introduction 1.1 Overview of InGaAs MISFETs 1.2 Gate stack engineering for InGaAs Chapter 2. Preparation for InGaAs MISFETs 2.1 Mesa isolation and gate recess 2.2 Ohmic contact for InGaAs MISFETs 2.3 Epitaxial layer structure of InGaAs MISFETs Chapter 3. Gate stack engineering for InGaAs MISFETs 3.1 Digital etch 3.2 Surface treatment 3.3 Dielectric interface โ€“ Deposition temperature 3.4 Dielectric interface โ€“ Thickness 3.5 Dielectric interface โ€“ Plasma power 3.6 Annealing โ€“ Post metallization annealing 3.7 Dual dielectric โ€“ SiNx/Al2O3 Chapter 4. Fabrication of planar type InGaAs MISFETs 4.1 Process of recessed 2ใŽ› gate MISFET 4.2 Measurements and results 4.3 TEM images of fabricated devices Chapter 5. Conclusions 5.1 Summary and conclusions ReferencesMaste

    Process Simulation for the Digital Twin System in Apparel Assembly Line

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ์ƒํ™œ๊ณผํ•™๋Œ€ํ•™ ์˜๋ฅ˜ํ•™๊ณผ, 2023. 2. ๊น€์„ฑ๋ฏผ.The implementation of smart factories has emerged as a key goal for the Fourth Industrial Revolution. In this study, as a first step to implementing smart factories in apparel manufacturing, an apparel assembly line simulator that can be utilized in a digital twin system was developed for generating automatically a virtual assembly line and simulating a real assembly line. The mixed task assignment technique was applied to the modular production concept to solve the apparel assembly line balancing problem. Specifically, an algorithm was implemented to generate workstations by first classifying tasks into modules through an analysis of the manufacturing process and assigning grouped tasks in the single taskโ€“multiple workers and multiple tasksโ€“single worker assignment methods. Then, worker assignment was sequentially performed considering the skill level of the worker. The total production time required by 41 workers to produce 100 men's shirts was 85.7% lower than that reported previously. Even when only 31.7% of the workers were assigned to the apparel assembly line, the total production time reduced by 67.3%. The reason for this drastic reduction in the total production time was that in this study, line balancing was performed by sequentially implementing task and worker assignment, unlike previous studies that limited the apparel assembly line balancing problem to worker assignment and did not consider task assignment. Given that the effect of line balancing by task assignment is considerably greater than that based on worker assignment, the apparel assembly line balancing problem in the design stage must not be limited to worker assignment, and task assignment must be simultaneously considered. Next, the apparel assembly line simulator was developed for generating automatically a virtual assembly line by the mixed work assignment technique and performing simulation using the generated assembly line. A case study was conducted with the process analysis data of the technical jacket obtained from the apparel manufacturing factory to evaluate the developed simulator. As a result of the automatic generation and modification test, the apparel assembly line was generated with line balancing performed at 97.4% of all workstations. The applicability of the simulator developed in various scenarios was examined, and the results also highlighted that the developed simulator could be used for order selection, production planning, and apparel assembly line planning and operation. The developed apparel assembly line simulator automatically replaced the time-consuming handwork such as layout design or assembly line modeling in existing commercial simulation software, so it is expected to have the advantage to respond quickly or to make continuous modifications. The module-based mixed task assignment technique in this study is effective in solving the line balancing problem, and the developed apparel assembly line simulator is convenient by automatically generating a virtual apparel assembly line but also it can be used to simulate the actual apparel assembly line. In addition, the automatically generated apparel assembly line can be used as a virtual counterpart of the digital twin, and it is expected that a complete digital twin system of the apparel assembly line can be implemented through additional research for monitoring the actual apparel assembly line.4์ฐจ ์‚ฐ์—… ํ˜๋ช…์— ๋Œ€๋น„ํ•˜๊ธฐ ์œ„ํ•œ ์Šค๋งˆํŠธ ๊ณต์žฅ(smart factory)์˜ ๊ตฌํ˜„์€ ์ œ์กฐ ์‚ฐ์—…์˜ ์ตœ๋Œ€ ๊ด€์‹ฌ์‚ฌ ์ค‘ ํ•˜๋‚˜์ด๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์˜๋ฅ˜ ์ œ์กฐ ์‚ฐ์—…์—์„œ์˜ ์Šค๋งˆํŠธ ๊ณต์žฅ์„ ๊ตฌํ˜„ํ•˜๊ธฐ ์œ„ํ•œ ์ฒซ๊ฑธ์Œ์œผ๋กœ ๋””์ง€ํ„ธ ํŠธ์œˆ(digital twin) ์‹œ์Šคํ…œ์—์„œ ํ™œ์šฉ๋  ์ˆ˜ ์žˆ๋Š” ๊ฐ€์ƒ์˜ ์˜๋ฅ˜ ๋ด‰์ œ ๋ผ์ธ์„ ์ž๋™์œผ๋กœ ์ƒ์„ฑํ•˜๊ณ , ์‹ค์ œ ์˜๋ฅ˜ ๋ด‰์ œ ๋ผ์ธ์„ ๋ชจ์‚ฌํ•  ์ˆ˜ ์žˆ๋Š” ์˜๋ฅ˜ ๋ด‰์ œ ๋ผ์ธ ์‹œ๋ฎฌ๋ ˆ์ดํ„ฐ๋ฅผ ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. ๋จผ์ €, ์˜๋ฅ˜ ๋ด‰์ œ ๋ผ์ธ์˜ ์ตœ์ ํ™”๋ฅผ ์œ„ํ•œ ๋ผ์ธ ๋ฐธ๋Ÿฐ์‹ฑ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ๋ชจ๋“ˆํ™” ๊ฐœ๋…์„ ์ ์šฉํ•œ ํ˜ผํ•ฉ ์ž‘์—… ํ• ๋‹น ๊ธฐ๋ฒ•์„ ์ œ์‹œํ•˜์˜€๋‹ค. ์ƒ์‚ฐํ•˜๋ ค๋Š” ์˜๋ฅ˜์˜ ๊ณต์ •์„ ๋ถ„์„ํ•˜์—ฌ ๊ฐ ์ž‘์—…์„ ๋ชจ๋“ˆ๋กœ ๋ถ„๋ฅ˜ํ•˜๊ณ , ๋‹จ์ผ ์ž‘์—…-๋ณต์ˆ˜ ์ž‘์—…์ž ํ• ๋‹น ๋ฐฉ์‹๊ณผ ๋‹ค์ค‘ ์ž‘์—…-๋‹จ์ˆ˜ ์ž‘์—…์ž ํ• ๋‹น ๋ฐฉ์‹์œผ๋กœ ๊ทธ๋ฃนํ™”๋œ ์ž‘์—…์„ ๋ฐฐ๋ถ„ํ•˜์—ฌ ์›Œํฌ์Šคํ…Œ์ด์…˜์„ ์ƒ์„ฑํ•˜๋Š” ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ๊ตฌํ˜„ํ•˜์˜€๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ž‘์—…์ž์˜ ์ž‘์—… ์ˆ™๋ จ๋„๋ฅผ ๊ณ ๋ คํ•œ ์ž‘์—…์ž ๋ฐฐ์น˜์— ๋”ฐ๋ฅธ ๋ผ์ธ ๋ฐธ๋Ÿฐ์‹ฑ์„ ์ถ”๊ฐ€๋กœ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ๋ผ์ธ ๋ฐธ๋Ÿฐ์‹ฑ ๊ฒฐ๊ณผ๋ฅผ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•ด ๋‚จ์ž ์…”์ธ  100๋ฒŒ์„ ์ƒ์‚ฐํ•˜๋Š” ์‹คํ—˜์—์„œ ์„ ํ–‰ ์—ฐ๊ตฌ์˜ 31.7% ์ž‘์—… ์ธ์›๋งŒ์œผ๋กœ ์ด์ƒ์‚ฐ์‹œ๊ฐ„์ด 67.3%๋งŒํผ ๋‹จ์ถ•๋˜์—ˆ์œผ๋ฉฐ, ์ž‘์—…์ž ์ˆ˜๊ฐ€ ๋™์ผํ•œ ๊ฒฝ์šฐ์—๋Š” ์ด์ƒ์‚ฐ์‹œ๊ฐ„์ด 85.7%๋งŒํผ ๋‹จ์ถ•๋˜์—ˆ๋‹ค. ์ด์ƒ์‚ฐ์‹œ๊ฐ„์ด ํš๊ธฐ์ ์œผ๋กœ ๋‹จ์ถ•๋œ ์ด์œ ๋Š” ์„ค๊ณ„ ๋‹จ๊ณ„์˜ ์˜๋ฅ˜ ๋ด‰์ œ ๋ผ์ธ ๋ฐธ๋Ÿฐ์‹ฑ ๋ฌธ์ œ๋ฅผ ์ž‘์—…์ž ๋ฐฐ์น˜ ๋ฌธ์ œ๋กœ ํ•œ์ •ํ•œ ์„ ํ–‰ ์—ฐ๊ตฌ์™€ ๋‹ฌ๋ฆฌ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ž‘์—… ๋ฐฐ๋ถ„์— ๋”ฐ๋ฅธ ๋ผ์ธ ๋ฐธ๋Ÿฐ์‹ฑ๊ณผ ์ž‘์—…์ž ๋ฐฐ์น˜์— ๋”ฐ๋ฅธ ๋ผ์ธ ๋ฐธ๋Ÿฐ์‹ฑ์„ ๋ชจ๋‘ ์ˆ˜ํ–‰ํ–ˆ๊ธฐ ๋•Œ๋ฌธ์ด๋ฉฐ, ์‹คํ—˜ ๊ฒฐ๊ณผ๋ฅผ ๊ณ ๋ คํ•  ๋•Œ ์„ค๊ณ„ ๋‹จ๊ณ„์˜ ์˜๋ฅ˜ ๋ด‰์ œ ๋ผ์ธ ๋ฐธ๋Ÿฐ์‹ฑ ๋ฌธ์ œ์—์„œ ์ž‘์—… ๋ฐฐ๋ถ„์€ ๋ฐ˜๋“œ์‹œ ๊ณ ๋ ค๋˜์–ด์•ผ ํ•œ๋‹ค. ๋‹ค์Œ์œผ๋กœ, ํ˜ผํ•ฉ ์ž‘์—… ํ• ๋‹น ๊ธฐ๋ฒ•์œผ๋กœ ๋ผ์ธ ๋ฐธ๋Ÿฐ์‹ฑ์ด ์ˆ˜ํ–‰๋œ ์˜๋ฅ˜ ๋ด‰์ œ ๋ผ์ธ์ด ์ž๋™์œผ๋กœ ์ƒ์„ฑ๋˜๊ณ , ์ƒ์„ฑ๋œ ์˜๋ฅ˜ ๋ด‰์ œ ๋ผ์ธ์„ ํ™œ์šฉํ•˜์—ฌ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ๋Š” ๋ด‰์ œ ๋ผ์ธ ์‹œ๋ฎฌ๋ ˆ์ดํ„ฐ๋ฅผ ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. ๊ฐœ๋ฐœ๋œ ์‹œ๋ฎฌ๋ ˆ์ดํ„ฐ๋ฅผ ๊ฒ€์ฆํ•˜๊ธฐ ์œ„ํ•ด ์˜๋ฅ˜ ์ œ์กฐ ๊ณต์žฅ์œผ๋กœ๋ถ€ํ„ฐ ์–ป์€ ํ…Œํฌ๋‹ˆ์ปฌ ์ž์ผ“์˜ ๊ณต์ • ๋ถ„์„ ๋ฐ์ดํ„ฐ๋ฅผ ๊ฐ€์ง€๊ณ  ์‚ฌ๋ก€ ์—ฐ๊ตฌ๋ฅผ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ์˜๋ฅ˜ ๋ด‰์ œ ๋ผ์ธ์˜ ์ž๋™ ์ƒ์„ฑ ๋ฐ ์ˆ˜์ • ๊ธฐ๋Šฅ ํ…Œ์ŠคํŠธ ๊ฒฐ๊ณผ, ์•ฝ 97.4%์˜ ์›Œํฌ์Šคํ…Œ์ด์…˜์—์„œ ์ž‘์—…์ด ์ •์ƒ์ ์œผ๋กœ ๋ฐฐ๋ถ„๋œ ์˜๋ฅ˜ ๋ด‰์ œ ๋ผ์ธ์ด ์ƒ์„ฑ๋˜์—ˆ๋‹ค. ๋˜ํ•œ ๋‹ค์–‘ํ•œ ์‹œ๋‚˜๋ฆฌ์˜ค๋กœ ๊ฐœ๋ฐœ๋œ ์‹œ๋ฎฌ๋ ˆ์ดํ„ฐ์˜ ํ™œ์šฉ ๊ฐ€๋Šฅ์„ฑ์„ ๊ฒ€ํ† ํ–ˆ์œผ๋ฉฐ, ๊ฐœ๋ฐœ๋œ ์‹œ๋ฎฌ๋ ˆ์ดํ„ฐ๊ฐ€ ์ฃผ๋ฌธ ์„ ์ •, ์ƒ์‚ฐ ๊ณ„ํš, ์˜๋ฅ˜ ๋ด‰์ œ ๋ผ์ธ ๊ณ„ํš ๋ฐ ์šด์˜์— ํ™œ์šฉ๋  ์ˆ˜ ์žˆ์Œ์ด ํ™•์ธ๋˜์—ˆ๋‹ค. ๊ฐœ๋ฐœ๋œ ์˜๋ฅ˜ ๋ด‰์ œ ๋ผ์ธ ์ „์šฉ ์‹œ๋ฎฌ๋ ˆ์ดํ„ฐ๋Š” ๊ธฐ์กด์˜ ์ƒ์šฉ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ์†Œํ”„ํŠธ์›จ์–ด์—์„œ์˜ ๋ ˆ์ด์•„์›ƒ ์ž‘์„ฑ์ด๋‚˜ ์˜๋ฅ˜ ๋ด‰์ œ ๋ผ์ธ์˜ ๋ชจ๋ธ๋ง๊ณผ ๊ฐ™์€ ์‹œ๊ฐ„์ด ์˜ค๋ž˜ ๊ฑธ๋ฆฌ๋Š” ์ˆ˜์ž‘์—…์„ ์ž๋™์œผ๋กœ ๋Œ€์ฒดํ•˜์˜€๊ธฐ ๋•Œ๋ฌธ์— ๋น ๋ฅธ ๋Œ€์‘์ด๋‚˜ ์ง€์†์ ์ธ ์ˆ˜์ •์ด ์šฉ์ดํ•˜๋‹ค๋Š” ์ ์—์„œ ์ด์ ์ด ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€๋œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ ์ œ์‹œํ•œ ๋ชจ๋“ˆ ๊ธฐ๋ฐ˜์˜ ํ˜ผํ•ฉ ์ž‘์—… ํ• ๋‹น ๊ธฐ๋ฒ•์€ ๋ผ์ธ ๋ฐธ๋Ÿฐ์‹ฑ ๋ฌธ์ œ ํ•ด๊ฒฐ์— ํšจ๊ณผ์ ์ด๋ฉฐ, ๊ฐœ๋ฐœ๋œ ๋ด‰์ œ ๋ผ์ธ ์‹œ๋ฎฌ๋ ˆ์ดํ„ฐ๋Š” ์ž๋™์œผ๋กœ ๊ฐ€์ƒ์˜ ์˜๋ฅ˜ ๋ด‰์ œ ๋ผ์ธ์„ ์ƒ์„ฑํ•˜์—ฌ ํŽธ๋ฆฌํ•  ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ธฐ๋Šฅ์„ ํ†ตํ•ด ์‹ค์ œ ์˜๋ฅ˜ ๋ด‰์ œ ๋ผ์ธ์˜ ์ตœ์  ์šด์˜์— ํ™œ์šฉ๋  ์ˆ˜ ์žˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ž๋™์œผ๋กœ ์ƒ์„ฑ๋˜๋Š” ์˜๋ฅ˜ ๋ด‰์ œ ๋ผ์ธ์€ ๋””์ง€ํ„ธ ํŠธ์œˆ์˜ ๊ฐ€์ƒ ๋Œ€์‘๋ฌผ๋กœ ํ™œ์šฉ๋  ์ˆ˜ ์žˆ์œผ๋ฉฐ, ์‹ค์ œ ์˜๋ฅ˜ ๋ด‰์ œ ๋ผ์ธ์˜ ๋ชจ๋‹ˆํ„ฐ๋ง์„ ์œ„ํ•œ ์ถ”๊ฐ€์ ์ธ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ์˜๋ฅ˜ ๋ด‰์ œ ๋ผ์ธ์˜ ์™„์ „ํ•œ ๋””์ง€ํ„ธ ํŠธ์œˆ ์‹œ์Šคํ…œ์„ ๊ตฌํ˜„ํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์ด๋ผ ๊ธฐ๋Œ€ํ•œ๋‹ค.์ œ 1 ์žฅ ์„œ๋ก  1 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ์˜ ํ•„์š”์„ฑ 1 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ์˜ ๋ชฉ์  6 ์ œ 2 ์žฅ ์ด๋ก ์  ๋ฐฐ๊ฒฝ 7 ์ œ 1 ์ ˆ ์˜๋ฅ˜ ๋ด‰์ œ ๋ผ์ธ ๋ฐธ๋Ÿฐ์‹ฑ 7 1. ์˜๋ฅ˜ ๋ด‰์ œ ๋ผ์ธ์˜ ์ดํ•ด 7 2. ์˜๋ฅ˜ ๋ด‰์ œ ๋ผ์ธ ๋ฐธ๋Ÿฐ์‹ฑ์˜ ์ดํ•ด 12 ์ œ 2 ์ ˆ ๋””์ง€ํ„ธ ํŠธ์œˆ์„ ์œ„ํ•œ ์˜๋ฅ˜ ๋ด‰์ œ ๋ผ์ธ ์‹œ๋ฎฌ๋ ˆ์ดํ„ฐ 18 1. ๋””์ง€ํ„ธ ํŠธ์œˆ์˜ ์ดํ•ด 18 2. ์˜๋ฅ˜ ๋ด‰์ œ ๋ผ์ธ์˜ ๋””์ง€ํ„ธ ํŠธ์œˆ 19 3. ์ƒ์šฉ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ์†Œํ”„ํŠธ์›จ์–ด 23 ์ œ 3 ์žฅ ์—ฐ๊ตฌ๋ฐฉ๋ฒ• 26 ์ œ 1 ์ ˆ ๋ชจ๋“ˆ ๊ธฐ๋ฐ˜ ํ˜ผํ•ฉ ์ž‘์—… ํ• ๋‹น ๊ธฐ๋ฒ• 27 1. ๊ณต์ • ๋ถ„์„ 29 2. ๋ชจ๋“ˆ ๋ถ„๋ฅ˜ 32 3. ์ž‘์—…์ž ์ˆ˜์™€ ์ƒ์‚ฐ๋Ÿ‰ ์„ค์ • 34 4. ๋ชจ๋“ˆ๋ณ„ ์›Œํฌ์Šคํ…Œ์ด์…˜ ์ˆ˜ ์‚ฐ์ • 36 5. ๋ชจ๋“ˆ๋ณ„ ์›Œํฌ์Šคํ…Œ์ด์…˜ ์ƒ์„ฑ 38 6. ์ž‘์—…์ž ๋ฐฐ์น˜ 41 ์ œ 2 ์ ˆ ์˜๋ฅ˜ ๋ด‰์ œ ๋ผ์ธ ์‹œ๋ฎฌ๋ ˆ์ดํ„ฐ 45 1. ์˜๋ฅ˜ ๋ด‰์ œ ๋ผ์ธ ์‹œ๋ฎฌ๋ ˆ์ดํ„ฐ ๊ฐœ๋ฐœ 45 2. ์‚ฌ๋ก€ ์—ฐ๊ตฌ 50 ์ œ 4 ์žฅ ๊ฒฐ๊ณผ ๋ฐ ๊ณ ์ฐฐ 57 ์ œ 1 ์ ˆ ๋ชจ๋“ˆ ๊ธฐ๋ฐ˜ ํ˜ผํ•ฉ ์ž‘์—… ํ• ๋‹น ๊ธฐ๋ฒ• 57 1. ์›Œํฌ์Šคํ…Œ์ด์…˜ ์ƒ์„ฑ ๋ฐ ์ž‘์—… ๋ฐฐ๋ถ„ 57 2. ์ž‘์—…์ž ๋ฐฐ์น˜ 59 3. ์ž‘์—…์ž ๋ฐฐ์น˜ ์ „ํ›„ ๋ถ„์„ 61 4. ๋‹จ๊ณ„๋ณ„ ๋ผ์ธ ๋ฐธ๋Ÿฐ์‹ฑ์˜ ํšจ๊ณผ 66 ์ œ 2 ์ ˆ ์˜๋ฅ˜ ๋ด‰์ œ ๋ผ์ธ ์‹œ๋ฎฌ๋ ˆ์ดํ„ฐ 70 1. ์˜๋ฅ˜ ๋ด‰์ œ ๋ผ์ธ ์‹œ๋ฎฌ๋ ˆ์ดํ„ฐ ๊ฐœ์š” 70 2. ์˜๋ฅ˜ ๋ด‰์ œ ๋ผ์ธ ์ž๋™ ์ƒ์„ฑ 72 3. ์ž๋™ ์ƒ์„ฑ๋œ ์˜๋ฅ˜ ๋ด‰์ œ ๋ผ์ธ ๊ฒ€ํ†  74 4. ์‹œ๋‚˜๋ฆฌ์˜ค๋ฅผ ํ†ตํ•œ ์‚ฌ๋ก€ ์—ฐ๊ตฌ 80 ์ œ 5 ์žฅ ๊ฒฐ๋ก  86 ์ œ 1 ์ ˆ ์š”์•ฝ ๋ฐ ์—ฐ๊ตฌ์˜ ์˜์˜ 86 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„ ๋ฐ ์ œ์–ธ 89 ์ฐธ๊ณ ๋ฌธํ—Œ 91 Abstract 98 ๋ถ€๋ก 101๋ฐ•

    ้ฆฌ้Ÿ“์˜ ๆ”ฟๅ‹ข่ฎŠๅ‹•๊ณผ 3์„ธ๊ธฐ ็™พๆฟŸ์˜ ๅˆถ้œธ

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์‚ฌ๋ฒ”๋Œ€ํ•™ ์‚ฌํšŒ๊ต์œก๊ณผ, 2018. 2. ์„œ์˜์‹.๋ณธ ๋…ผ๋ฌธ์€ ์šฐ๋ฆฌ ์ธก ์ž๋ฃŒ์™€ ์ค‘๊ตญ ์ธก ์ž๋ฃŒ๋ฅผ ์ƒํ˜ธ ่ฃœๅฎŒ็š„์œผ๋กœ ์šด์šฉํ•˜์—ฌ ็™พๆฟŸ๊ฐ€ ้ฆฌ้Ÿ“์„ ๋Œ€ํ‘œํ•˜๋Š” ไฝ็ฝฎ์— ์ด๋ฅด๋Š” ๊ณผ์ •์„ ๅฏฆ่ญ‰็š„์œผ๋กœ ็ณพๆ˜Žํ•œ ๊ฒƒ์ด๋‹ค. ๋ฐฑ์ œ์˜ ์„ฑ๋ฆฝ๊ณผ ๋ฐœ์ „ ๊ณผ์ •์„ ้Ÿ“ๅœ‹ ๅคไปฃๅฒ์˜ ์ „์ฒด์  ํ๋ฆ„์œผ๋กœ ็œบๆœ›ํ•˜๋Š” ์œ„์—์„œ ๅคๆœ้ฎฎ ์‚ฌํšŒ์˜ ็นผ่ตท็š„ ๋ฐœ์ „ ํ˜•ํƒœ์˜ ์ผ๋ถ€๋กœ ํŒŒ์•…ํ•˜๋Š” ๋ฐ ไธป็œผ้ปž์„ ๋‘์—ˆ๋‹ค. ไธ‰้Ÿ“์œผ๋กœ ๊ตฌ์„ฑ๋˜์—ˆ์œผ๋ฉฐ ่พฐ็Ž‹์ด ็›ก็Ž‹ไธ‰้Ÿ“ไน‹ๅœฐํ•˜๋Š” ์ง„๊ตญ์€ ๋ฌธํ—Œ์ƒ ์ ์–ด๋„ ์„œ๊ธฐ์ „ 2์„ธ๊ธฐ ํ›„๋ฐ˜๋ถ€ํ„ฐ ๊ทธ ์กด์žฌ๊ฐ€ ํ™•์ธ๋œ๋‹ค. ์ง„๊ตญ์€ ๆผข๊ณผ ไบคๆถ‰ํ•˜๋Š” ํ•œํŽธ ่ก›ๆปฟๆœ้ฎฎ์œผ๋กœ๋ถ€ํ„ฐ ไบกๅ‘ฝํ•œ ๋Œ€๊ทœ๋ชจ ๆต็งปๆฐ‘ ์ง‘๋‹จ์„ ์ˆ˜์šฉํ•˜๊ณ  ๋ณดํ˜ธํ•˜๋Š” ๋“ฑ ๊ทธ ์„ธ๋ ฅ์ด ์œ„๋งŒ์กฐ์„ ๊ณผ ๆฏ”่‚ฉ๋  ์ •๋„์˜€๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ง„๊ตญ์€ ์„œ๊ธฐ์ „ 1์„ธ๊ธฐ ์ค‘์—ฝ์— ์ ‘์–ด๋“ค์–ด ๊ทธ ์ฒด์ œ๊ฐ€ ํฌ๊ฒŒ ๅ‹•ๆ–ํ•˜๊ธฐ ์‹œ์ž‘ํ•˜์˜€๋‹ค. ่พฐ้Ÿ“ ่ซธๅœ‹์ด ๋…์ž์ ์œผ๋กœ ๅฑ…่ฅฟๅนฒ์„ ๅ…ฑ็ซ‹ํ•จ์œผ๋กœ์จ ๆ–ฐ็พ…๋ฅผ ํ˜•์„ฑํ•˜์—ฌ ์ง„๊ตญ์—์„œ ์ดํƒˆํ•œ ์ผ์„ ๊ณ„๊ธฐ๋กœ ์‚ผํ•œ์€ ๊ฐ๊ธฐ ๅˆ†็ซ‹ํ•˜๋Š” ํ๋ฆ„์— ๋†“์˜€๊ณ , ์•„์šธ๋Ÿฌ ์‚ผํ•œ์˜ ็Ž‹์ธ ็›ฎๆ”ฏๅœ‹ ์ง„์™•์˜ ์˜๋„๋ ฅ๋„ ํฌ๊ฒŒ ์•ฝํ™”ํ•˜์˜€๋‹ค. ์ด๋Ÿฌํ•œ ๆ”ฟๅ‹ข์˜ ่ฎŠๅ‹• ์†์—์„œ ๋งˆํ•œ์˜ ๅฐๅœ‹๋“ค์€ ์ง„ํ•œ์˜ ๋ถ„๋ฆฝ์— ไพฟไน˜ํ•˜์—ฌ ์ƒˆ๋กœ์šด ์งˆ์„œ๋ฅผ ๋ชจ์ƒ‰ํ•˜๋ฉฐ ๊ฐ์ง€์—์„œ ๅคงๅฐ์˜ ํ†ตํ•ฉ์„ธ๋ ฅ์„ ํ˜•์„ฑํ•˜๊ธฐ ์‹œ์ž‘ํ•˜์˜€๋Š”๋ฐ, ๊ทธ ํ•˜๋‚˜๊ฐ€ ๋ฐฑ์ œ์˜€๋‹ค. ๋ฐฑ์ œ๋Š” ๊ณ ๊ตฌ๋ ค ๊ณ„ํ†ต์˜ ไบกๅ‘ฝ ์ง‘๋‹จ์ด ๊ฑด์„คํ•œ ๅๆฟŸ๋ฅผ ์ค‘์‹ฌ์œผ๋กœ ํ•œ๊ฐ• ์œ ์—ญ์˜ ่ซธๅœ‹์ด ๊ฒฐํ•ฉํ•˜๋Š” ๋ฐฉ์‹์œผ๋กœ ์„ฑ๋ฆฝ๋˜์—ˆ๋‹ค. ๋งˆํ•œ์˜ ไธ€ๅ“ก์œผ๋กœ ์„ฑ๋ฆฝํ•œ ๋ฐฑ์ œ๋Š” ์ข๊ฒŒ๋Š” ๋งˆํ•œ ์‚ฌํšŒ, ๋„“๊ฒŒ๋Š” ่พฐๅœ‹ ์‚ฌํšŒ๋ฅผ ๆฏ่ƒŽ๋กœ ํ•˜์—ฌ ๊ฑฐ๊ธฐ์„œ ์–ป์€ ๊ฒฝํ—˜๊ณผ ๋ฌธํ™”๋Šฅ๋ ฅ์„ ็นผๆ‰ฟํ•˜๋ฉฐ ๋ฐœ์ „ํ•˜์˜€๋‹ค. ์ง„๊ตญ์€ ์‚ผํ•œ ่ซธๅœ‹์ด ๋ชจ์—ฌ ่พฐ็Ž‹์„ ๊ณต๋ฆฝํ•˜๊ณ  ๊ทธ ์ง„์™•์— ่ซธๅœ‹์ด ๆ‰€ๅฑฌํ•˜๋Š” ๋ฐฉ์‹์œผ๋กœ ์šด์˜๋˜์—ˆ๋Š”๋ฐ ๋ฐฑ์ œ๊ฐ€ ์„ฑ๋ฆฝยท์šด์˜๋˜๋Š” ์›๋ฆฌ๋„ ๊ธฐ๋ณธ์ ์œผ๋กœ ์ด์™€ ๋‹ค๋ฅด์ง€ ์•Š์•˜๋‹ค. ํ•œ๊ฐ•์œ ์—ญ์˜ ๋งˆํ•œ ่ซธๅœ‹์ด ๋ชจ์—ฌ์„œ ๅ…ฑ็ซ‹ํ•œ ๋ฐฑ์ œ์˜ ็Ž‹์€ ๅ‰ๆ”ฏ๋ผ ์นญํ•ด์กŒ๋‹ค. ์ด๋Š” ็ฎ•ๅญๆœ้ฎฎ์˜ ็ฎ•ๅญ, ๊ณ ๊ตฌ๋ ค์˜ ็š†ๆฌก, ๊ทธ๋ฆฌ๊ณ  ์ง„ํ•œ์˜ ๅฑ…่ฅฟๅนฒ๊ณผ ๋Œ€์‘ํ•˜๋Š” ๋งˆํ•œ์˜ ็Ž‹่™Ÿ์˜€๋‹ค. 3์„ธ๊ธฐ ์ค‘์—ฝ, ๋งˆํ•œ์€ ๋ณต์ˆ˜์˜ ๅ‰ๆ”ฏ ์„ธ๋ ฅ๋“ค์ด ๋…๋ฆฝ์ ์œผ๋กœ ็ซ็ซ‹ํ•˜๋Š” ํ˜•๊ตญ์„ ์ด๋ฃจ๊ณ  ์žˆ์—ˆ๋‹ค. ์ „ํ†ต์˜ ๋ชฉ์ง€๊ตญ ์ˆ˜์žฅ์ด ๋ช…๋ชฉ์ƒ์œผ๋กœ๋Š” ่พฐ็Ž‹์œผ๋กœ ๊ธฐ๋Šฅํ•˜๊ณ  ์žˆ์—ˆ์ง€๋งŒ, ๊ธฐ์‹ค ์ง„์™• ์„ธ๋ ฅ์€ ๊ณผ๊ฑฐ์˜ ์œ„์ƒ์„ ๊ฑฐ์˜ ์ƒ์‹คํ•˜๊ณ  ๅ‰ๆ”ฏ ์„ธ๋ ฅ์˜ ํ•˜๋‚˜๋กœ ์กด์žฌํ•˜๋‹ค์‹œํ”ผ ํ•˜๋Š” ์ฒ˜์ง€์— ์žˆ์—ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋งˆํ•œ์˜ ํ˜•์„ธ๋Š”, ์ด์›ƒํ•œ ์‹ ๋ผ๋กœ๋ถ€ํ„ฐ ์ ์ฆํ•˜๋Š” ๊ตฐ์‚ฌ์  ์••๋ฐ• ๋ฐ ๆ›น้ญ์˜ ์นจ๋žต์ „์Ÿ์„ ๊ณ„๊ธฐ๋กœ ๋ณ€ํ™”ํ•˜๊ธฐ ์‹œ์ž‘ํ•˜์˜€๋‹ค. ๅฐ้ญ ์ „ํˆฌ์˜ ๊ฒฐ๊ณผ ้Ÿ“้‚ฃๅฅš ๋ฐ ่‡ฃ?ๆฒฝๅœ‹ ๅ‰ๆ”ฏ ์„ธ๋ ฅ ๋“ฑ ๋‹ค์ˆ˜์˜ ๋งˆํ•œ ์†Œ๊ตญ์ด ์ค‘๊ตญ ์„ธ๋ ฅ์—๊ฒŒ ํ•ญ๋ณตํ•˜๊ธฐ์— ์ด๋ฅด๋ €๋‹ค. ์ด๋Š” ๋งˆํ•œ ์‚ฌํšŒ ์ „์ฒด์— ์ถฉ๊ฒฉ์„ ๋˜์กŒ๊ณ  ์œ„๊ธฐ์˜์‹์„ ์‹ฌ์–ด์คฌ๋‹ค. ๊ฐ์ง€์—์„œ ๋ณ‘๋ฆฝํ•˜๋˜ ๅ‰ๆ”ฏ ์„ธ๋ ฅ๋“ค์€ ์ด ์‚ฌ๊ฑด์„ ๊ณ„๊ธฐ๋กœ ็ตๆŸ์„ ๊ฐ•ํ™”ํ•˜๊ณ  ์™ธ๋ถ€ ์„ธ๋ ฅ์˜ ์นจ๋žต์— ๊ณต๋™์œผ๋กœ ๋Œ€์‘ํ•˜๊ณ  ๊ต์„ญํ•ด์•ผ ํ•  ํ•„์š”์„ฑ์„ ๅˆ‡ๆ„Ÿํ•˜๊ฒŒ ๋˜์—ˆ๋‹ค. ์ด๋“ค์€ ๊ณผ๊ฑฐ์— ๋งˆํ•œ ่ซธๅœ‹ ์ „์ฒด๊ฐ€ ้ฆฌ้Ÿ“็Ž‹์„ ์ค‘์‹ฌ์œผ๋กœ ํ†ตํ•ฉ๋˜์–ด ์žˆ์—ˆ๊ณ , ํ•œ๋•Œ๋Š” ์‚ผํ•œ ์ค‘ ์ตœ๋Œ€ ์„ธ๋ ฅ์œผ๋กœ์„œ ์ง„์™•์„ ๋‚ด๋˜ ์—ญ์‚ฌ์  ๊ธฐ์–ต๊ณผ ๊ฒฝํ—˜์„ ๋˜์‚ด๋ ค ๋‹น๋Œ€์˜ ๊ธ‰๋ณ€ํ•˜๋Š” ์ •์„ธ์— ๋Œ€์‘ํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ๊ณง ๋งˆํ•œ์˜ ๅ‰ๆ”ฏ ์„ธ๋ ฅ๋“ค์€ ์„œ๋กœ ๋ชจ์—ฌ ๊ทธ๋“ค ๊ฐ€์šด๋ฐ ์ตœ๋Œ€์˜ ๅ‰ๆ”ฏ ์„ธ๋ ฅ์„ ๋˜ ํ•œ ๋ฒˆ ๅ…ฑ็ซ‹ํ•˜์—ฌ ?ๅ‰ๆ”ฏ๋กœ ์‚ผ๊ณ , ๊ทธ๋“ค์ด ?ๅ‰ๆ”ฏ์— ๆ‰€ๅฑฌํ•˜๋Š” ๋ฐฉ์‹์œผ๋กœ ๋งˆํ•œ์˜ ๆ”ฟๆฒป้ซ”ๅˆถ๋ฅผ ์žฌํŽธ์„ฑํ•˜๊ธฐ ์‹œ์ž‘ํ•˜์˜€๋‹ค. ์ด ํ†ตํ•ฉ์„ธ๋ ฅ์˜ ๊ตฌ์‹ฌ์ฒด๋Š” ๋ฐฑ์ œ์˜€๊ณ , ๋ฐฑ์ œ์˜ ๅค?็Ž‹์ด ?ๅ‰ๆ”ฏ๋กœ ๊ณต๋ฆฝ๋˜์—ˆ๋‹ค. ์ด๋•Œ๋ถ€ํ„ฐ ็™พๆฟŸๆœฌ็ด€๋Š” ํ•œ๊ฐ•์œ ์—ญ์˜ ๅ‰ๆ”ฏ ์„ธ๋ ฅ์˜ ์—ญ์‚ฌ๊ฐ€ ์•„๋‹Œ ๋งˆํ•œ ?ๅ‰ๆ”ฏ์˜ ์—ญ์‚ฌ๋กœ ์ „ํ™˜๋˜์—ˆ๊ณ , ์ด์— ๊ณ ์ด์™•์€ ์ค‘๊ตญ ์ธก์— ์˜ํ•ด ๋ฐฑ์ œ์˜ ๅง‹็ฅ–๋กœ ์ธ์‹๋˜๊ธฐ๋„ ํ•˜์˜€๋‹ค. ๋ฐฑ์ œ ๊ณ ์ด์™•์€ ๋งˆํ•œ ์ „์ฒด๋ฅผ ๋Œ€ํ‘œํ•˜๋Š” ์„ธ๋ ฅ์œผ๋กœ์„œ ์•ˆ์œผ๋กœ๋Š” ์—ฌํƒ€์˜ ๅ‰ๆ”ฏ ์„ธ๋ ฅ๋“ค์„ ํ†ตํ•ฉํ•˜๊ณ  ํ†ต์น˜ ๊ตฌ์กฐ๋ฅผ ์ •๋น„ํ•˜๋Š” ๋“ฑ ๊ตญ๊ฐ€์ฒด์ œ๋ฅผ ไธ€ๆ–ฐํ•˜์˜€๊ณ , ๋ฐ–์œผ๋กœ๋Š” ๊ณ ๊ตฌ๋ คยท์‹ ๋ผ ๋ฐ ์ค‘๊ตญ ์„ธ๋ ฅ๊ณผ ๊ต์„ญํ•˜๊ณ  ๋•Œ๋กœ๋Š” ๋Œ€๊ฒฐํ•˜๋ฉฐ ๋งˆํ•œ์„ ๏ฆดๅฐŽํ•ด ๋‚˜๊ฐ”๋‹ค.ๅœ‹ๆ–‡ๆŠ„้Œ„ 1. ๅบ่จ€ 1 2. ็›ฎๆ”ฏๅœ‹ ไธญๅฟƒ ่พฐๅœ‹้ซ”ๅˆถ์˜ ๆง‹้€ ์™€ ๅฑๆฉŸ 6 3. ๅ‰ๆ”ฏ์˜ ็ซ็ซ‹๊ณผ ้ฆฌ้Ÿ“ ๆ”ฟๅ‹ข์˜ ่ฎŠๅ‹• 23 4. ็™พๆฟŸ์˜ ๅˆถ?์™€ ่พฐๅœ‹้ซ”ๅˆถ์˜ ็ต‚็„‰ 45 5. ็ต่ชž 61 ๅƒ่€ƒๆ–‡็ป 65 ่‹ฑๆ–‡ๆŠ„้Œ„(Abstract) 73Maste

    Deletion of TRPC3 in mice reduces store-operated Ca2+ influx and the severity of acute pancreatitis

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    BACKGROUND & AIMS: Receptor-stimulated Ca(2+) influx is a critical component of the Ca(2+) signal and mediates all cellular functions regulated by Ca(2+). However, excessive Ca(2+) influx is highly toxic, resulting in cell death, which is the nodal point in all forms of pancreatitis. Ca(2+) influx is mediated by store-operated channels (SOCs). the identity and function of the native SOCs in most cells is unknown. METHODS: Here, we determined the role of deletion of Trpc3 in mice on Ca(2+) signaling, exocytosis, intracellular trypsin activation, and pancreatitis. RESULTS: Deletion of TRPC3 reduced the receptor-stimulated and SOC-mediated Ca(2+) influx by about 50%, indicating that TRPC3 functions as an SOC in vivo. the reduced Ca(2+) influx in TRPC3(-/-) acini resulted in reduced frequency of the physiologic Ca(2+) oscillations and of the pathologic sustained increase in cytosolic Ca(2+) levels caused by supramaximal stimulation and by the toxins bile acids and palmitoleic acid ethyl ester. Consequently, deletion of TRPC3 shifted the dose response for receptor-stimulated exocytosis and prevented the pathologic inhibition of digestive enzyme secretion at supramaximal agonist concentrations. Accordingly, deletion of TRPC3 markedly reduced intracellular trypsin activation and excessive actin depolymerization in vitro and the severity of pancreatitis in vivo. CONCLUSIONS: These findings establish the native TRPC3 as an SOC in vivo and a role for TRPC3-mediated Ca(2+) influx in the pathogenesis of acute pancreatitis and suggest that TRPC3 should be considered a target for prevention of pancreatic damage in acute pancreatitis.ope

    RANKL-mediated reactive oxygen species pathway that induces long lasting Ca2+ oscillations essential for osteoclastogenesis

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    RANKL (receptor activator of NF-kappaB ligand) induces osteoclastogenesis by activating multiple signaling pathways in osteoclast precursor cells, chief among which is induction of long lasting oscillations in the intracellular concentration of Ca(2+) ([Ca(2+)](i)). The [Ca(2+)](i) oscillations activate calcineurin, which activates the transcription factor NFATc1. The pathway by which RANKL induces [Ca(2+)](i) oscillations and osteoclastogenesis is poorly understood. Here we report the discovery of a novel pathway induced by RANKL to cause a long lasting increase in reactive oxygen species (ROS) and [Ca(2+)](i) oscillations that is essential for differentiation of bone marrow-derived monocytes into osteoclasts. The pathway includes RANKL-mediated stimulation of Rac1 to generate ROS, which stimulate phospholipase Cgamma1 to evoke [Ca(2+)](i) oscillations by stimulating Ca(2+) release from the inositol 1,4,5-trisphosphate pool and STIM1-regulated Ca(2+) influx. Induction and activation of the pathway is observed only after 24-h stimulation with RANKL and lasts for at least 3 days. The physiological role of the pathway is demonstrated in mice with deletion of the Peroxiredoxin II gene and results in a mark increase is ROS and, consequently, a decrease in bone density. Moreover, bone marrow-derived monocytes in PrxII(-/-) primary culture show increased ROS and spontaneous [Ca(2+)](i) oscillations. These findings identify the primary RANKL-stimulated pathway to trigger the late stages of osteoclastogenesis and regulate bone resorptionope

    Prognostic Markers and Long-Term Outcomes After Aortic Valve Replacement in Patients With Chronic Aortic Regurgitation

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    Background The objectives of the present study were (1) to evaluate the echocardiographic prognostic factors associated with improved left ventricular (LV) systolic function after aortic valve replacement, and (2) to compare the long-term outcomes after aortic valve replacement in chronic aortic regurgitation (AR) patients with or without LV dysfunction. Methods and Results A total of 280 patients who underwent aortic valve replacement because of chronic aortic regurgitation were studied. Patients with reduced LV systolic function (LV ejection fraction [LVEF] <50%; group reduced LVEF [rEF]; N=80) were compared with those with preserved LV systolic function (LVEF โ‰ฅ50%; group preserved LVEF; N=200). Postoperative clinical outcomes, overall survival, and freedom from cardiac death were compared. Postoperative echocardiographic examinations were reviewed, and changes in echocardiographic parameters were analyzed. The parameters related to LVEF improvement or normalization were evaluated, and risk factors affecting long-term survival were identified. Follow-up was complete in 100% of patients, with a median follow-up of 104.8 months. Overall and cardiac mortality-free survival rates at postoperative 10 years were 80.1% and 92.9% and 87.3% and 97.2% in groups rEF and preserved LVEF, respectively (P=0.036 and P=0.058, respectively). LVEF tended to decrease in the early postoperative period but improved thereafter in both groups. Preoperative early diastolic transmitral flow velocity/mitral annular tissue velocity ratio was a parameter of postoperative improvement or normalization of LVEF in all patients (area under the curve, 0.719; P=0.003) and in group rEF patients (area under the curve, 0.726; P=0.011) with a cutoff value of 12.73. Preoperative early diastolic transmitral flow velocity/mitral annular tissue velocity ratio also was the parameter of overall survival in all patients (hazard ratio [HR], 1.08; P=0.001) and in group rEF patients (HR, 1.08; P=0.005). Conclusions Long-term outcomes and survival after aortic valve replacement were related to preoperative LV function in patients with chronic aortic regurgitation. Preoperative early diastolic transmitral flow velocity/mitral annular tissue velocity ratio was correlated with the postoperative improvement or normalization of LVEF and long-term survival, especially in group rEF patients.ope

    An apparatus to control centrifugal valves

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    ๋ณธ ๋ฐœ๋ช…์€, ์ฑ”๋ฒ„ ๋ฐ ์ฑ”๋ฒ„์™€ ์—ฐ๊ฒฐ๋˜๋Š” ์ฑ„๋„์„ ๊ตฌ๋น„ํ•˜๋Š” ๋ชธ์ฒด ๋ฐ ์ฑ„๋„์„ ๊ฐœํํ•˜๋Š” ๋ฐธ๋ธŒ๋ฅผ ๊ตฌ๋น„ํ•˜๋Š” ๋ชธ์ฒด๋ถ€์™€, ๋ชธ์ฒด ์ƒ์— ๊ฒฐํ•ฉ๋˜๊ณ , ๋ฐธ๋ธŒ์— ๋Œ€์‘๋˜๋Š” ์œ„์น˜์— ๋ฐฐ์น˜๋˜๋Š” ๊ฐ€์—ด ๋ถ€์žฌ๋ฅผ ๊ตฌ๋น„ํ•˜๋Š” ๊ฐ€์—ด๋ถ€์™€, ๋ชธ์ฒด๋ถ€ ๋ฐ ๊ฐ€์—ด๋ถ€๋ฅผ ํ•จ๊ป˜ ํšŒ์ „์‹œํ‚ค๋Š” ํšŒ์ „ ๊ตฌ๋™๋ถ€๋ฅผ ํฌํ•จํ•˜๊ณ , ๋ฐธ๋ธŒ๋Š” ๋ชธ์ฒด๋ถ€ ๋ฐ ๊ฐ€์—ด๋ถ€๊ฐ€ ํ•จ๊ป˜ ํšŒ์ „ํ•˜๋Š” ๋™์•ˆ ๊ฐ€์—ด ๋ถ€์žฌ์— ์˜ํ•ด ์ฑ„๋„์„ ๊ฐœํํ•˜๋„๋ก ํ˜•์„ฑ๋˜๋Š” ์›์‹ฌ ๋ฐธ๋ธŒ ์ œ์–ด ์žฅ์น˜๋ฅผ ์ œ๊ณตํ•œ๋‹ค. ์ด๋ฅผ ํ†ตํ•ด, ์›์‹ฌ ๋ฐธ๋ธŒ ์ œ์–ด ์žฅ์น˜์˜ ๋ฐธ๋ธŒ๋ฅผ ์ •๋ฐ€ํ•˜๊ฒŒ ์ œ์–ดํ•  ์ˆ˜ ์žˆ๋‹ค

    ๊ณต๊ฐ„์˜ ๊ฐ€์‹œ์„ฑ์— ๊ธฐ๋ฐ˜ํ•œ ERAM ๋ชจ๋ธ : ์ดˆ๋Œ€ํ˜• ๋ณตํ•ฉ๊ณต๊ฐ„์˜ ๊ณต๊ฐ„์ด์šฉํ–‰ํƒœ ์˜ˆ์ธก์„ ์ค‘์‹ฌ์œผ๋กœ

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๊ฑด์ถ•ํ•™๊ณผ,2006.Maste
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