84 research outputs found

    ์ž์ด๋‹ˆ์น˜(ๅœจๆ—ฅ) ๋ฏผ์กฑ๊ต์œก์˜ ํ˜•ํƒœ: ๋™๊ฒฝํ•œ๊ตญํ•™๊ต์™€ ๋„๊พœ์กฐ์„ ์ค‘๊ณ ๊ธ‰ํ•™๊ต ์‚ฌ๋ก€๋ฅผ ์ค‘์‹ฌ์œผ๋กœ

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ตญ์ œ๋Œ€ํ•™์› ๊ตญ์ œํ•™๊ณผ(๊ตญ์ œ์ง€์—ญํ•™์ „๊ณต), 2021. 2. Erik Mobrand.After the imperial Japans colonial rule of Korea ended in 1945, Korean residents in Japan โ€“ zainichi (ๅœจๆ—ฅ) โ€“ set up a temporary Korean Language Institute with purpose of preparing zainichi in going back to their homeland. However, Koreas politically unstable situation on top of Japans systematic cap on belongings the zainichi could possess left them with no choice but to stay. Now, zainichi is situated in a unique position in the discourse of Korean diaspora as they continue to live in a nation that was once a perpetrator to their ancestors and homeland. This uniqueness created systematic obstacles for zainichis ethnic education to take place within Japan. Accordingly, zainichis ethnic education faces constant institutional challenges up until now. This research aims to examine how the zainichi ethnic education is manifested within contemporary Japanese society. Furthermore, newly emerged social and ethnic values for new generations of zainichi will be diagnosed. In doing so, main findings of the research will provide guidance for zainichi community in formulating an appropriate policy for future direction of zainichi ethnic education.1945 ๋…„ ์ผ์ œ ์‹๋ฏผํ†ต์น˜๋กœ๋ถ€ํ„ฐ ์กฐ์„ ์˜ ๊ด‘๋ณต ํ›„, ๋‹น์‹œ ์ž์ด๋‹ˆ์น˜(ๅœจๆ—ฅ)๋“ค์€ ๊ณ ๊ตญ์—์„œ์˜ ์ƒํ™œ์„ ์œ„ํ•˜์—ฌ ์ผ๋ณธ์— ์ž„์‹œ๊ตญ์–ด๊ฐ•์Šต์†Œ๋ฅผ ์„ค๋ฆฝํ•œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜, ๋‹น์‹œ ํ•œ๋ฐ˜๋„์˜ ์ •์น˜์ ์œผ๋กœ ๋ถˆ์•ˆ์ •ํ•œ ์ƒํ™ฉ๊ณผ ์ผ๋ณธ์ •๋ถ€์˜ ์˜๋„์ ์ธ ์žฌ์‚ฐ ๋ฐ˜์ถœ๊ธˆ์ง€ ์กฐ์น˜์— ๋”ฐ๋ผ, ๊ท€๊ตญ์— ๋Œ€ํ•œ ๊ฟˆ์€ ์ขŒ์ ˆ๋˜๊ณ  ๋Œ€๋ถ€๋ถ„์˜ ์ž์ด๋‹ˆ์น˜๋“ค์€ ์ผ๋ณธ์— ๊ฑฐ๋ฅ˜ํ•˜๊ธฐ๋ฅผ ์„ ํƒํ•œ๋‹ค. ํ˜„์žฌ๊นŒ์ง€๋„ ์ž์ด๋‹ˆ์น˜๋Š” ๊ทธ๋“ค์˜ ์‹๋ฏผ์ง€๋ฐฐ์— ๋Œ€ํ•œ ๊ฐ€ํ•ด์ž์˜€๋˜ ๋‚˜๋ผ์—์„œ ์‚ด์•„๊ฐ€๊ณ  ์žˆ๊ณ , ์ด๋Ÿฌํ•œ ํŠน์ด์„ฑ์€ ๋””์•„์Šคํฌ๋ผ ๋‹ด๋ก ์—์„œ๋„ ํŠน๋ณ„ํžˆ ๋ถ€๊ฐ๋˜๋Š” ๋ถ€๋ถ„์ด๋‹ค. ํ˜„์žฌ๊นŒ์ง€๋„ ์ž์ด๋‹ˆ์น˜์˜ ๋ฏผ์กฑ๊ต์œก์€ ์ดˆ์ฐฝ๊ธฐ๋ถ€ํ„ฐ ์ง€์†์ ์ธ ์ œ๋„์  ์ฐจ๋ณ„๋กœ ๋งŽ์€ ์–ด๋ ค์›€์„ ๊ฒช๊ณ  ์žˆ๋‹ค. ์ž์ด๋‹ˆ์น˜์˜ ๋ฏผ์กฑ๊ต์œก์€ ๋ฏผ์กฑ ์ •์ฒด์„ฑ ํ˜•์„ฑ์— ์žˆ์–ด ํฐ ์—ญํ• ์„ ํ•˜๊ณ  ์žˆ๋‹ค๋Š” ์ ์—์„œ ์—ฐ๊ตฌ์˜ ์ค‘์š”์„ฑ์ด ์žˆ๋‹ค๊ณ  ํ‰๊ฐ€๋œ๋‹ค. ์•„์ง๋„ ์ž์ด๋‹ˆ์น˜๋“ค์˜ ๋ฏผ์กฑ๊ต์œก์ด ์ผ๋ณธ ์ •๋ถ€ ๋ฐ ์‚ฌํšŒ์˜ ์ œ๋„์  ๋ฐ•ํ•ด๋ฅผ ๋ฐ›๊ณ ์žˆ๋‹ค. ๋ฏธ๋ž˜์‚ฌํšŒ์—์„œ๋„ ์ผ๋ณธ ์‚ฌํšŒ์—์„œ ์ •์ƒ์ ์ธ ์‚ฌํšŒ์ƒํ™œ์„ ์˜์œ„ํ•  ์ˆ˜ ์žˆ๋„๋ก ์ž์ด๋‹ˆ์น˜๋“ค์˜ ์ •์ฒด์„ฑ์„ ์œ ์ง€ํ•˜๋ฉด์„œ, ์ผ๋ณธ์˜ ์ œ๋„์  ๋ฐ ์‚ฌํšŒ์ ์ธ ์ฐจ๋ณ„์„ ์ œ๊ฑฐํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ๋ฏผ์กฑ๊ต์œก์˜ ๋ฐฉํ–ฅ์„ฑ ๋ฐ ์ง€์†๊ฐ€๋Šฅ์„ฑ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๊ฐ€ ๋ฐ˜๋“œ์‹œ ์ด๋ฃจ์–ด์ ธ์•ผ ํ•œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ ํ˜„์žฌ์˜ ์ผ๋ณธ ์‚ฌํšŒ์—์„œ ์ž์ด๋‹ˆ์น˜์˜ ๋ฏผ์กฑ๊ต์œก์ด ์–ด๋–ค ํ˜•ํƒœ๋กœ ๋ฐœ์ƒํ•˜๋Š”์ง€ ํŒŒ์•…ํ•˜๋Š” ๋ฐ์— ๊ทธ ๋ชฉ์ ์ด ์žˆ๋‹ค. ๋‚˜์•„๊ฐ€, ์ƒˆ๋กœ์šด ์„ธ๋Œ€์˜ ์ž์ด๋‹ˆ์น˜์—๊ฒŒ ์ค‘์š”ํ•œ ์‚ฌํšŒ์  ๋ฐ ๋ฏผ์กฑ์  ๊ฐ€์น˜๋ฅผ ์‚ดํŽด๋ณด๋Š” ๊ฒƒ๋„ ๊ณ ์ฐฐํ•ด ๋ณด์•˜๋‹ค. ์—ฐ๊ตฌ๊ฒฐ๊ณผ์— ๋”ฐ๋ฅธ ์ž์ด๋‹ˆ์น˜์˜ ๋ฏผ์กฑ๊ต์œก์— ๋Œ€ํ•œ ๋ฐฉํ–ฅ์„ฑ ๋ฐ ์ง€์†๊ฐ€๋Šฅ์„ฑ์˜ ์ œ์‹œ๋ฅผ ํ†ตํ•˜์—ฌ ์ž์ด๋‹ˆ์น˜์™€ ๊ด€๋ จ๋œ ์กฐ๊ตญ์˜ ์ง€์› ๋ฐ ์ผ๋ณธ์˜ ์ •์ฑ… ์‹œํ–‰์˜ ๊ธ์ •์ ์ธ ๋ฐœ์ „์— ๊ธฐ์—ฌํ•˜๋Š”๋ฐ ์—ฐ๊ตฌ์˜ ์˜๋ฏธ๊ฐ€ ์žˆ๋‹ค.I. Introduction 1 1. Brief History of Zainichi Ethnic Education 2 2. Structural Make-up of Zainichi Society 24 2-1. Group of Republic of Korea Residents in Japan โ€“ Mindan 26 2-2. General Association of Korean Residents in Japan โ€“ Chongryun 28 3. Literature Review 31 4. Limitation of Previous Research and Research Question 34 II. Theoretical Framework and Research Methodology 36 1. Ethnic Education Methods and Influencing Factors 36 1-1. External Influencing Factors for Mindan-Affiliated Ethnic Schools 36 1-2. Internal Influencing Factors for Mindan-Affiliated Ethnic Schools 38 1-3. External Influencing Factors for Chongryun-Affiliated Ethnic Schools 40 1-4. Internal Influencing Factors for Chongryun-Affiliated Ethnic Schools 42 2. Research Methodology 47 2-1. Textbook Education and Extracurricular Activity Analysis Methodology 47 2-2. Interview Methodology 49 III. Comparative Analysis of Ethnic Education Methods 53 1. Mindan-Affiliated Ethnic Schools 56 1-1. Textbook Education Analysis 56 1-2. Extracurricular Activity Analysis 66 2. Chongryun-Affiliated Ethnic Schools 85 2-1. Textbook Education Analysis 85 2-2. Extracurricular Activity Analysis 112 IV. Interview Analysis 116 1. Mindan-Affiliated Respondents 117 1-1. Ahn 117 2. Chongryun-Affiliated Respondents 122 2-1. Park 122 2-2. Kim 128 V. Main Findings 130 VI. Conclusion 136 VII. Bibliography 140 VIII. Appendix 145 IX. Interview Transcripts 146 X. ๊ตญ๋ฌธ์ดˆ๋ก 165 XI. Acknowledgement 167Maste

    ๋Œ€๊ธฐ์•• ํ”Œ๋ผ์ฆˆ๋งˆ์™€ ๋‚œ๋ฐฑ์„ ํ™œ์šฉํ•œ ์–‘ํŒŒ ๋ถ„๋ง ๋‚ด ์ฒœ์—ฐ ์•„์งˆ์‚ฐ ์ฆ์ง„๋ฐฉ์•ˆ ๋ฐ ์œก์ œํ’ˆ์—์˜ ์ ์šฉ

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๋†์—…์ƒ๋ช…๊ณผํ•™๋Œ€ํ•™ ๋†์ƒ๋ช…๊ณตํ•™๋ถ€, 2020. 8. ์กฐ์ฒ ํ›ˆ.The efficacy of egg white addition during atmospheric pressure plasma (APP) treatment on onions to replace synthetic sodium nitrite in the processed sausage was evaluated. Onions were treated with APP alone (PO) or in the presence of 30% egg whites (w/w, POE). While PO also showed an increase in nitrite content, the addition of egg white resulted in an approximately four-fold increase in nitrite content in POE compared to PO. After freeze-drying and processing into the powder form, the nitrite content of both PO and POE was concentrated well without loss. To test the practical application of this technique, four different materials of no nitrite (None), sodium nitrite (SN), PO powder, and POE powder were added to sausages then evaluated on a consumer scale. POE sausages retained a similar nitrite content, emulsion stability, and visual redness to the sausages added with sodium nitrite. Also, POE sausages achieved improved textural properties and onion like-odor, and significantly reduced warmed-over flavor. From these results, we concluded that onion powder enriched with nitrite by APP can effectively replace synthetic sodium nitrite in processed sausages without compromising their flavor.๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์•„์งˆ์‚ฐ ๋ฐ ์งˆ์‚ฐ์„ ๊ฑฐ์˜ ํ•จ์œ ํ•˜์ง€ ์•Š์€ ์–‘ํŒŒ๋ฅผ ๋‚œ๋ฐฑ๊ณผ ํ•จ๊ป˜ ๋Œ€๊ธฐ์•• ํ”Œ๋ผ์ฆˆ๋งˆ ์ฒ˜๋ฆฌํ•ด ์ฒœ์—ฐ ์•„์งˆ์‚ฐ ์†Œ์žฌ๋กœ ๊ฐ€๊ณตํ•˜๊ณ , ์ด๋ฅผ ์‹ค์ œ ์œก๊ฐ€๊ณตํ’ˆ ์ œ์กฐ์— ์ ์šฉํ•˜์—ฌ ํ•ด๋‹น ์†Œ์žฌ์˜ ์•„์งˆ์‚ฐ์—ผ ๋Œ€์ฒด ๊ฐ€๋Šฅ์„ฑ์„ ํ™•์ธํ•˜๊ณ ์ž ํ•œ๋‹ค. ์‹คํ—˜์€ ๋‹ค์Œ๊ณผ ๊ฐ™์ด ์„ธ ๋‹จ๊ณ„๋กœ ๋‚˜๋ˆ„์–ด ์ง„ํ–‰๋˜์—ˆ๋‹ค. (1) ์ƒ์–‘ํŒŒ๋ฅผ ํ”Œ๋ผ์ฆˆ๋งˆ ์ฒ˜๋ฆฌํ•˜์—ฌ ์ฒœ์—ฐ ์•„์งˆ์‚ฐ ์†Œ์žฌ๋ฅผ ์ƒ์‚ฐํ•˜๋Š” ๊ณผ์ •์—์„œ pH ์™„์ถฉํšจ๊ณผ๊ฐ€ ์žˆ๋Š” ๋‚œ๋ฐฑ์˜ ์ฒจ๊ฐ€๋ฅผ ํ†ตํ•œ ์•„์งˆ์‚ฐ ์ƒ์„ฑํšจ์œจ์˜ ์ฆ์ง„ ์—ฌ๋ถ€๋ฅผ ํ™•์ธํ•˜์˜€๊ณ , (2) ์ƒ์‚ฐํ•œ ์•„์งˆ์‚ฐ ์†Œ์žฌ์˜ ์ €์žฅ์„ฑ ๋ฐ ์‚ฐ์—…์  ํ™œ์šฉ ๊ฐ€๋Šฅ์„ฑ์„ ํ™•๋ณดํ•˜๊ธฐ ์œ„ํ•ด ๋ถ„๋ง ํ˜•ํƒœ๋กœ ๊ฐ€๊ณตํ•œ ํ›„ ๊ทธ ํŠน์„ฑ์„ ์กฐ์‚ฌํ•˜์˜€์œผ๋ฉฐ, (3) ์ตœ์ข…์ ์œผ๋กœ, ์ด๋ฅผ ์‹ค์ œ ์œก๊ฐ€๊ณตํ’ˆ ์—ผ์ง€์— ์ ์šฉํ•˜์—ฌ ๊ฐ€๊ณต๋œ ๋ถ„๋ง์˜ ์•„์งˆ์‚ฐ์—ผ ๋Œ€์ฒด ๊ฐ€๋Šฅ์„ฑ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์‹คํ—˜ 1์˜ ๊ฒฐ๊ณผ, ์ค‘๋Ÿ‰ ๋Œ€๋น„ 30% ์ˆ˜์ค€์˜ ๋‚œ๋ฐฑ์„ ์ฒจ๊ฐ€ํ•œ ์–‘ํŒŒ์—์„œ ํ”Œ๋ผ์ฆˆ๋งˆ ์ฒ˜๋ฆฌ์— ์˜ํ•œ pH ์ €ํ•˜๊ฐ€ ํšจ๊ณผ์ ์œผ๋กœ ์ง€์—ฐ๋จ์— ๋”ฐ๋ผ ์ด ํ”Œ๋ผ์ฆˆ๋งˆ ์ฒ˜๋ฆฌ์‹œ๊ฐ„์ด ์ฆ๊ฐ€๋˜์—ˆ๊ณ , ์ธก์ •๋œ ์ž”๋ฅ˜ ์•„์งˆ์‚ฐ ํ•จ๋Ÿ‰ ๋˜ํ•œ ์–‘ํŒŒ๋งŒ ๋‹จ๋…์œผ๋กœ ํ”Œ๋ผ์ฆˆ๋งˆ ์ฒ˜๋ฆฌํ•œ ๊ฒƒ์— ๋น„ํ•ด 4๋ฐฐ ์ด์ƒ ๋†’์•„์ ธ ๋‚œ๋ฐฑ์˜ ์ฒจ๊ฐ€๊ฐ€ ํ”Œ๋ผ์ฆˆ๋งˆ์˜ ์•„์งˆ์‚ฐ ์ƒ์„ฑํšจ์œจ์„ ํ–ฅ์ƒํ•  ์ˆ˜ ์žˆ์Œ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์‹คํ—˜ 2์—์„œ๋Š” ์‚ฐ์—…์  ํ™œ์šฉ์„ฑ ์ฆ์ง„์„ ์œ„ํ•ด ์ƒ์‚ฐ๋œ ์•„์งˆ์‚ฐ ๋†์ถ• ์–‘ํŒŒ ์†Œ์žฌ๋ฅผ ๋™๊ฒฐ๊ฑด์กฐ ํ›„ ๋ถ„์‡„ํ•˜์—ฌ ๋ถ„๋ง ์ƒ์œผ๋กœ ๊ฐ€๊ณตํ•˜์˜€์œผ๋ฉฐ, ์ด ๊ณผ์ •์—์„œ ์•„์งˆ์‚ฐ์€ ์†Œ์‹ค๋˜์ง€ ์•Š๊ณ  ๋ถ„๋ง ๋‚ด์— ๋†’์€ ํ•จ๋Ÿ‰์œผ๋กœ ์ž”์กดํ•˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋˜ํ•œ, ํ”Œ๋ผ์ฆˆ๋งˆ ์ฒ˜๋ฆฌํ•œ ์–‘ํŒŒ ๋ถ„๋ง์€ ๋‚œ๋ฐฑ ์ฒจ๊ฐ€ ์—ฌ๋ถ€์™€ ์ƒ๊ด€์—†์ด ๋ณต๊ท€ ๋Œ์—ฐ๋ณ€์ด ์œ ๋ฐœ์„ฑ์„ ๋‚˜ํƒ€๋‚ด์ง€ ์•Š์•˜์œผ๋ฉฐ, ๋‚œ๋ฐฑ ํ•จ์œ  ์–‘ํŒŒ ๋ถ„๋ง์˜ ์กฐ๋‹จ๋ฐฑ ๋ฐ ์กฐํšŒ๋ถ„ ํ•จ๋Ÿ‰์€ ์ƒ์–‘ํŒŒ ๋ถ„๋ง ๋˜๋Š” ํ”Œ๋ผ์ฆˆ๋งˆ ๋‹จ๋…์ฒ˜๋ฆฌํ•œ ์–‘ํŒŒ ๋ถ„๋ง๋ณด๋‹ค ์œ ์˜ํ•˜๊ฒŒ ๋†’์€ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์‹คํ—˜ 3์—์„œ๋Š” ์ฒจ๊ฐ€ํ•œ ์†Œ์žฌ์˜ ์ข…๋ฅ˜๋ฅผ ๋‹ฌ๋ฆฌํ•˜์—ฌ ์œ ํ™”ํ˜• ์†Œ์‹œ์ง€๋ฅผ ์ œ์กฐํ•œ ํ›„ ๊ฐ๊ฐ์˜ ํ’ˆ์งˆ์„ ํ‰๊ฐ€ํ•˜์˜€๊ณ , ์•„๋ฌด๊ฒƒ๋„ ์ฒจ๊ฐ€ํ•˜์ง€ ์•Š์€ ์†Œ์‹œ์ง€, ์•„์งˆ์‚ฐ์—ผ ์ฒจ๊ฐ€ ์†Œ์‹œ์ง€, ๋‹จ๋…์œผ๋กœ ํ”Œ๋ผ์ฆˆ๋งˆ ์ฒ˜๋ฆฌํ•œ ์–‘ํŒŒ ๋ถ„๋ง ๋ฐ ๋‚œ๋ฐฑ๊ณผ ํ•จ๊ป˜ ํ”Œ๋ผ์ฆˆ๋งˆ ์ฒ˜๋ฆฌํ•œ ์–‘ํŒŒ ๋ถ„๋ง ์ฒจ๊ฐ€ ์†Œ์‹œ์ง€์˜ ๋„ค ๊ทธ๋ฃน์œผ๋กœ ๋‚˜๋ˆ„์–ด ์ง„ํ–‰ํ•˜์˜€๋‹ค. ์‹คํ—˜ ๊ฒฐ๊ณผ, ๋‚œ๋ฐฑ ํ•จ์œ  ์–‘ํŒŒ ๋ถ„๋ง ์ฒจ๊ฐ€ ์†Œ์‹œ์ง€๋Š” ์ž”๋ฅ˜ ์•„์งˆ์‚ฐ ํ•จ๋Ÿ‰, ์ ์ƒ‰๋„ ํ•ญ๋ชฉ์—์„œ ์•„์งˆ์‚ฐ์—ผ ์ฒจ๊ฐ€ ์†Œ์‹œ์ง€์™€ ์œ ์‚ฌํ•œ ์ˆ˜์ค€์„ ๋‚˜ํƒ€๋ƒˆ์œผ๋ฉฐ, ์œ ํ™” ์•ˆ์ •์„ฑ ๋ฐ ์กฐ์ง๊ฐ ํŠน์„ฑ์€ ๋‹ค๋ฅธ ์†Œ์‹œ์ง€๋“ค์— ๋น„ํ•ด ์œ ์˜ํ•˜๊ฒŒ ๊ฐœ์„ ๋˜์—ˆ๋‹ค. ์™ธ๊ด€ ๋ฐ ํ›„๊ฐ ํ‰๊ฐ€ ๊ฒฐ๊ณผ, ๋‚œ๋ฐฑ ํ•จ์œ  ์–‘ํŒŒ ๋ถ„๋ง์„ ์ฒจ๊ฐ€ํ•œ ์†Œ์‹œ์ง€๋Š” ์™ธ๊ด€์ƒ์˜ ์ ์ƒ‰๋„ ํ•ญ๋ชฉ์—์„œ ์•„์งˆ์‚ฐ์—ผ ์ฒจ๊ฐ€ ์†Œ์‹œ์ง€์™€ ๋น„์Šทํ•œ ์ ์ˆ˜๋ฅผ ๊ธฐ๋กํ•˜์˜€์œผ๋ฉฐ ์œ ์˜์ ์ธ ์ฐจ์ด๋Š” ์—†์—ˆ๋‹ค. ๋˜ํ•œ, ๋‚œ๋ฐฑ ํ•จ์œ  ์–‘ํŒŒ ๋ถ„๋ง์„ ์ฒจ๊ฐ€ํ•œ ์†Œ์‹œ์ง€๋Š” ์†Œ๋น„์ž์—๊ฒŒ ๋ถ€์ •์ ์œผ๋กœ ์ธ์‹๋  ์ˆ˜ ์žˆ๋Š” ๊ฐ€์—ด ์‚ฐํŒจ์ทจ ํ•ญ๋ชฉ์—์„œ ๊ฐ€์žฅ ๋‚ฎ์€ ์ ์ˆ˜๋ฅผ, ์–‘ํŒŒ ํ–ฅ ํ•ญ๋ชฉ์—์„œ๋Š” ์œ ์˜ํ•˜๊ฒŒ ๋†’์€ ์ ์ˆ˜๋ฅผ ํš๋“ํ•œ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๊ฒฐ๋ก ์ ์œผ๋กœ, ๋‚œ๋ฐฑ๊ณผ ํ•จ๊ป˜ ํ”Œ๋ผ์ฆˆ๋งˆ ์ฒ˜๋ฆฌํ•œ ์–‘ํŒŒ ๋ถ„๋ง์€ ์œ ํ™”ํ˜• ์†Œ์‹œ์ง€์—์„œ ์•„์งˆ์‚ฐ์—ผ์„ ์ฒจ๊ฐ€ํ•˜๋Š” ๊ฒƒ๊ณผ ์œ ์‚ฌํ•œ ํšจ๊ณผ๋ฅผ ๋ณด์ผ ๋ฟ ์•„๋‹ˆ๋ผ, ์†Œ์‹œ์ง€์˜ ์œ ํ™” ์•ˆ์ •์„ฑ ๋ฐ ํ’๋ฏธ๋ฅผ ํ–ฅ์ƒํ•  ์ˆ˜ ์žˆ์–ด ์‚ฐ์—…์—์„œ ๊ณ ํ’ˆ์งˆ์˜ ์œก๊ฐ€๊ณตํ’ˆ ์ œ์กฐ๋ฅผ ์œ„ํ•œ ์ฒœ์—ฐ ์•„์งˆ์‚ฐ ๋†์ถ• ์†Œ์žฌ๋กœ์จ ํ™œ์šฉ๋  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ์‚ฌ๋ฃŒ๋œ๋‹ค.Chapter I. Literature review 1 1.1. Sodium nitrite 1 1.1.1. History 1 1.1.2. Functions 2 1.1.2.1. Colorant 2 1.1.2.2. Flavor enhancer 2 1.1.2.3. Antimicrobial effect 3 1.1.2.4. Antioxidant effect 4 1.1.3. Application for meat products 4 1.1.3.1. Meat curing 4 1.1.3.2. Consumer concerns and demands 5 1.1.4. Natural nitrite sources 6 1.2. APP and foods 7 1.2.1. Definition of APP 7 1.2.2. Application of APP in the food industry 8 1.2.2.1. Microbial inactivation 8 1.2.2.2. Enhancement of the activity of bioactive substances 9 1.2.3. Nitrite generation using APP 10 1.3. APP for meat curing 11 1.3.1. Direct APP treatment on meat 11 1.3.2. Use of APP-treated materials 12 1.3.3. Limitation of APP 13 Chapter II. Enriching onion powder with natural nitrite for meat curing using atmospheric pressure plasma and egg whites 14 2.1. Introduction 14 2.2. Materials and methods 17 2.2.1. Experiment 1: Effect of APP treatment on fresh onions in the presence of egg whites 17 2.2.1.1. Sample preparation 17 2.2.1.2. pH 20 2.2.1.3. Residual nitrite content 20 2.2.2. Experiment 2: Characteristics of APP-treated onion powder 21 2.2.2.1. Sample preparation 21 2.2.2.2. Residual nitrite content 23 2.2.2.3. Proximate composition 23 2.2.2.4. Instrumental color 23 2.2.2.5. Mutagenicity 24 2.2.3. Experiment 3: Application of APP-treated onion powder as a natural nitrite source to sausages 25 2.2.3.1. Sausages manufacture 25 2.2.3.2. pH 27 2.2.3.3. Residual nitrite content 27 2.2.3.4. Instrumental color 27 2.2.3.5. Emulsion stability 27 2.2.3.6. Texture profile analysis 28 2.2.3.7. Visual and olfactory properties 28 2.2.4. Statistical analysis 29 2.3. Results and discussion 30 2.3.1. Experiment 1: Effect of APP treatment on fresh onions in the presence of egg whites 30 2.3.1.1. pH and hydrogen ion concentration 30 2.3.1.2. Residual nitrite content 33 2.3.2. Experiment 2: Characteristics of APP-treated onion powder 35 2.3.2.1. Residual nitrite content 35 2.3.2.2. Proximate composition 37 2.3.2.3. Instrumental color 39 2.3.2.4. Mutagenicity 42 2.3.3. Experiment 3: Application of APP-treated onion powder to sausage processing 44 2.3.3.1. pH 44 2.3.3.2. Residual nitrite content 46 2.3.3.3. Instrumental color 48 2.3.3.4. Emulsion stability 51 2.3.3.5. Texture profile analysis 53 2.3.3.6. Visual and olfactory properties 56 2.4. Conclusion 59 References 60 Summary in Korean 74Maste

    ๋Œ€ํ•œ๋ฏผ๊ตญ์˜ ์ฝ”๋กœ๋‚˜-19 ํŒฌ๋ฐ๋ฏน ํ•˜์—์„œ Cycle Threshold Values์˜ ์—ญํ•™์  ํ™œ์šฉ

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๋ณด๊ฑด๋Œ€ํ•™์› ๋ณด๊ฑดํ•™๊ณผ(๋ณด๊ฑดํ•™์ „๊ณต), 2023. 2. ํ™ฉ์Šน์‹.Backgrounds Cycle Threshold values [Ct values] are the measured values, the determinants of positivity in a COVID-19 diagnosis. Studies on the usefulness of Ct values for forecasting the number of COVID-19 newly confirmed are being actively conducted worldwide because of their features that are inversely proportional to the virus load, and their association with infectious/infectious power (et al., 2021; Rodrรญguez et al., 2021). On the other side, Ct values have been used only in the diagnostic field in Korea. Forecasting the number of newly confirmed cases and strategies for responding to health and infectious diseases has relied on the time-varying reproduction number [Rt] from the beginning of the COVID-19 outbreak. Rt indicates how many additional confirmed cases one confirmed patient has created. However, Rt has some limitations. It is challenging to reduce Rt estimation to less than a week (Lin et al., 2022), and its definition and calculation formula require identifying the infection route (Yoo, 2021; Jung, 2020). To improve the forecasting model of COVID-19 newly confirmed in Korea, this study conducted the forecasting with Ct values to supplement the limitations of Rt. As a result of a systematic literature review, there were some differences between the results of static estimation and dynamic estimation. The research objectives are as follows. First, Rt and Ct values were compared through the Ct values time series distribution by COVID-19 pandemic periods and visually verified whether Ct values could forecast the actual new confirmation. Next, time series analysis-based forecasting of the COVID-19 confirmation pattern using the Ct values by COVID-19 pandemic periods was conducted to determine the time difference of several days when predictive power is the highest. This study conducted forecasting by using both static and dynamic estimation methods for comparison of each result. Methods The study period included 489,133 specimens collected for SARS CoV-2 diagnostic testing about two years from February 7, 2020, to December 31, 2021. Following domestic RT-PCR protocol, this study used Ct values RdRp as representative Ct values. Based on the Korea Disease Control and Prevention Agency [KDCA] publication, the periods of the COVID-19 pandemic in Korea were classified into four periods. This study presented the descriptive statistics table and graph for each variable of the diagnostic test results to understand the overall diagnostic test results of the samples included in the analysis. For visual verification before forecasting, the distribution pattern of the Ct values by the COVID-19 pandemic periods at the population group level is expressed as a time series graph along with the Rt and the number of new confirmed cases, respectively. After verifying the limitations of Rt and the utility of Ct values (a forecasting index for new confirmation) through the two distribution graphs, a statistical analysis was conducted to confirm the actual predictive power of Ct values. To ascertain the time difference when Ct values show the highest predictive power to newly confirmed cases, this study conducted both static and dynamic estimation methods with time lags. As a static method, a simple linear regression model was used, and as a dynamic method, the Distributed Lag Model [DLM] was used. An alpha of 0.05 was used for all tests, and all graphs and statistical analyses were performed with STATA (version 17). Results As a result of the descriptive statistics, most of the diagnostic tests were conducted at examination institutions, and more than half of the confirmed patients were in their 20s to 50s. More than half of the diagnostic kit products used were Seegene, the same gene amplification equipment was used in almost all tests, and more than half of the samples used were throat swabs (NPS/OPS). Ct values E, RdRp, and N all showed similar distribution forms, and values were mainly distributed between 10-20. In the two Ct values distribution pattern graphs, it was visually ascertained that the change in Rt did not sufficiently explain the period when the number of new confirmed cases increased rapidly compared to Ct values. Also, it was ascertained that the Ct values were first affected before the change in the quarantine policy affects the number of confirmed cases. Through these two time-series distribution graphs, it was assumed that it is possible to forecast the occurrence of confirmed patients according to the distribution of Ct values. Static estimation (simple linear regression model) and dynamic estimation (DLM) were used to perform forecasting of the actual occurrence of new confirmed cases using Ct values. First, as a result of the simple linear regression model, the forecasting was the best in the lag of 5-14 days. For forecasting through the simple linear regression model, the time difference with the highest predictive power differed by COVID-19 pandemic periods (11 days of the total period, 9 days of the first period, 5 days of the second period, 14 days of the third period, and 10 days of the fourth period). However, the results were likely to be false regression because it does not assume the normality of the time series. Also, the number of newly confirmed cases is difficult to forecast simply as a result of simultaneous static estimation, it was necessary to eliminate the effects of temporal fluctuations and make forecasts through dynamic estimation. After removing the effect of time fluctuations through DLM, both the third and fourth periods, which have no autocorrelation of the error term, were the best forecasted until the three-day time difference. As a result of the forecast through Rt in the same analysis method, it was best always forecasted at the 8-day time difference. And this study compared the forecast of the number of newly confirmed cases through Ct values and Rt by specifying the time of Omicron spread. However, the analysis period was short for 30 days and it was hard to get significant results because the dominant species period of Omicron was from February 2022. Conclusions This study confirmed the epidemiological utility of forecasting the newly confirmed cases by Ct values, which was rarely used in Korea. A COVID 19 forecast study was conducted using the domestic Ct values distribution at the population group level, including the time when the mutated virus appeared. It is the first domestic study to perform forecasts through Ct values using both static and dynamic models, and it revealed that Ct values can be used as a short-term (3 days) COVID-19 forecast indicator. Based on the results of this study, if various follow-up studies are conducted by combining clinical and policy indicators, the epidemiological utility of Ct values as well as predicting the number of new confirmed cases will be further expanded to contribute to establishing health policies.1. INTRODUCTION 1 1.1 Study Background 1 1.2 Systematic review 2 1.3 Study objective 8 2. METHODS 9 2.1 Study design 9 2.2 Data source 10 2.3 Sample size 11 2.4 Statistical analysis 13 3. RESULTS 16 3.1 Descriptive statistics for diagnostic test results 16 3.2 Distribution patterns of Ct values in Korea 20 3.3 Forecasting the number of newly confirmed cases based on the Ct values 27 3.3.1. Static model: Simple Linear regression model 27 3.3.2. Dynamic model: Finite Distributed Lag Model (FDL Model) 34 4. DISCUSSION 44 4.1 Summary of results 44 4.2 Comparison with previous studies 45 4.3 Strengths and Limitations 46 4.4 Public health implications 47 5. CONCLUSION 48 REFERENCES 49 APPENDIX 53 ABSTRACT 82์„

    Design of Ion Beam Etcher appllying Magnetized Inductively Coupled Plasma and a Study on etch characteristics of MTJ layer materials

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› ๊ณต๊ณผ๋Œ€ํ•™ ์ „๊ธฐยท์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2017. 8. ํ™์šฉํƒ.์ตœ๊ทผ์— ์ „์ž ์‚ฐ์—…์ด ๋ฐœ๋‹ฌํ•จ์— ๋”ฐ๋ผ ์ „์ž ๊ธฐ๊ธฐ๋“ค ๋ง‰๋Œ€ํ•œ ์ •๋ณด๋ฅผ ์ฒ˜๋ฆฌํ•  ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์ €์žฅํ•˜๋Š” ๊ธฐ๋Šฅ์ด ์š”๊ตฌ๋˜๊ณ  ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ์ถ”์„ธ์— ๋”ฐ๋ผ์„œ ์•ž์œผ๋กœ ์‚ฌ์šฉ๋  ๋ฉ”๋ชจ๋ฆฌ๋Š” ๋น ๋ฅธ ์Šคํ”ผ๋“œ์™€ ๋Œ€์šฉ๋Ÿ‰, ๋‚ฎ์€ ํŒŒ์›Œ ์†Œ๋น„์™€ ๋น„ํœ˜๋ฐœ์„ฑ์˜ ํŠน์ง•์ด ํ•„์ˆ˜์ ์œผ๋กœ ์š”๊ตฌ๋œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ํ˜„์žฌ ๊ฐ€์žฅ ๋„๋ฆฌ ์‚ฌ์šฉ๋˜๊ณ  ์žˆ๋Š” DRAM ๊ณผ flash ๋ฉ”๋ชจ๋ฆฌ๋Š” ํ•œ๊ณ„์„ฑ์„ ๊ฐ€์ง€๊ณ  ์žˆ์œผ๋ฏ€๋กœ ์ด๋ฅผ ๋Œ€์ฒดํ•  ์ƒˆ๋กœ์šด ๋ฉ”๋ชจ๋ฆฌ ์†Œ์ž์ธ PRAM, MRAM, ReRAM ๋“ฑ์˜ ์—ฐ๊ตฌ๊ฐ€ ์ง€์†๋˜๊ณ  ์žˆ๋‹ค. ์ƒˆ๋กญ๊ฒŒ ๊ฐœ๋ฐœ์ค‘์ธ ๋‹ค์–‘ํ•œ ๋ฉ”๋ชจ๋ฆฌ ์†Œ์ž์ค‘์—์„œ๋„ ํŠนํžˆ STT-MRAM ์€ high density, high speed, low power consumption, non-volatile ๋“ฑ์˜ ๋‹ค์–‘ํ•œ ์žฅ์ ์„ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. ๊ทธ๋ž˜์„œ, STT-MRAM ์€ ์ปดํ“จํ„ฐ ๊ตฌ์กฐ์˜ ๋ฉ”๋ชจ๋ฆฌ hierarchy ๊ตฌ์กฐ๋ฅผ ๋ฐ”๊ฟ€ ์ˆ˜ ์žˆ๋Š” ์ž ์žฌ์ ์ธ ๊ฐ€๋Šฅ์„ฑ์„ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค๊ณ  ๋ณผ ์ˆ˜ ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ์ด์œ ๋กœ ๊ถ๊ทน์˜ ๋ฉ”๋ชจ๋ฆฌ๋ผ๊ณ  ๋ถˆ๋ฆฌ๊ณ  ์žˆ๋Š” STT-MRAM ์˜ ๊ฐœ๋ฐœ์„ ์œ„ํ•ด MTJ layer ๋ฌผ์งˆ๋“ค์˜ ์ตœ์ ํ™”์— ๋Œ€ํ•œ ์—ฐ๊ตฌ, ์ „๊ธฐ์  ํŠน์„ฑ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ, MTJ layer ์‹๊ฐ ๊ณต์ •์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋“ฑ์ด ์ง„ํ–‰๋˜๊ณ  ์žˆ๋‹ค. STT-MRAM ์— ๋Œ€ํ•œ ๋‹ค์–‘ํ•œ ์—ฐ๊ตฌ ์ค‘์—์„œ๋„ ๋ณธ ๋…ผ๋ฌธ์€ ์‹๊ฐ ๊ณต์ •์— ์ดˆ์ ์„ ๋งž์ถฐ ์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ•˜์˜€๋‹ค. STT-MRAM ์—์„œ read/writhe ์˜ ํ•ต์‹ฌ์—ญํ• ์„ ํ•˜๋Š” ๊ฒƒ์€ MTJ layer ๋กœ์จ CoFeB, W, Ru, Ta, FePt, TiN ๋“ฑ์˜ ๋‹ค์–‘ํ•œ ๊ธˆ์†๋ฌผ์งˆ๋“ค๋กœ ๊ตฌ์„ฑ์ด ๋˜์–ด์žˆ๋‹ค. ์ผ๋ฐ˜์ ์€ RIE type ์‹๊ฐ ์žฅ๋น„์—์„œ๋Š” ์‹๊ฐํ›„์— ์ƒ๊ธฐ๋Š” byproducts ๋“ค์ด ์ธก๋ฉด์— ๋ถ™๊ฒŒ ๋œ๋‹ค. ์ด์ฒ˜๋Ÿผ ์‹๊ฐ๋œ ๋ฌผ์งˆ๋“ค์ด ํŒจํ„ด์˜ sidewall ์— redeposition ๋˜๋Š” ํ˜„์ƒ์œผ๋กœ ์ธํ•ด ์†Œ์ž๋Š” ๋™์ž‘ํ•˜์ง€ ์•Š๊ฒŒ ๋˜๋ฉฐ ์ด๋ฅผ ํ•ด๊ฒฐํ•˜๋Š” ๊ฒƒ์ด ๊ฐ€์žฅ ํฐ ์ด์Šˆ์ด๋‹ค. ์ด๋ฅผ ํ•ด๊ฒฐํ•˜๊ณ ์ž ๊ธฐ์กด์˜ RIE type ์‹๊ฐ ์žฅ์น˜๊ฐ€ ์•„๋‹Œ, ion beam etcher (IBE) ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ํŒจํ„ด ์‹๊ฐ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๊ฐ€ ์ง€์†๋˜๊ณ  ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ IBE ๋Š” ๋‚ฎ์€ ์‹๊ฐ๋ฅ ๋กœ ์ธํ•ด ํŒจํ„ด ์‹๊ฐ์— ์˜ค๋žœ์‹œ๊ฐ„์ด ๊ฑธ๋ฆฌ๊ณ  ์ด์˜จ์—๋„ˆ์ง€์™€ ์‹๊ฐ๋ฅ ์„ ๋…๋ฆฝ์ ์œผ๋กœ ์ œ์–ดํ•  ์ˆ˜ ์—†์œผ๋ฉฐ ์‹๊ฐ ๊ท ์ผ๋„ ๋˜ํ•œ ์ข‹์ง€ ์•Š์•„ ์–‘์‚ฐํ™”์— ์–ด๋ ค์›€์„ ๊ฒช๊ณ  ์žˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ๊ธฐ์กด์˜ IBE ์—์„œ์˜ ๋‹จ์ ์„ ํ•ด๊ฒฐํ•˜๊ณ ์ž ๋‹ค์–‘ํ•œ ์—ฐ๊ตฌ๋“ค์ด ์ง„ํ–‰๋˜์—ˆ๋‹ค. ์šฐ์„ , ๋‚ฎ์€ etch rate ์˜ ๋ฌธ์ œ์ ๊ณผ ์ด์˜จ์—๋„ˆ์ง€์™€ ion flux ๋ฅผ ๋…๋ฆฝ์ ์œผ๋กœ ์ œ์–ดํ•˜๊ธฐ ์œ„ํ•ด, ์žํ™” ์œ ๋„ ๊ฒฐํ•ฉ ํ”Œ๋ผ์ฆˆ๋งˆ ์†Œ์Šค๋ฅผ ์ด์šฉํ•˜์—ฌ ์ƒˆ๋กญ๊ฒŒ ์ด์˜จ ๋น” ์‹๊ฐ ์žฅ์น˜๋ฅผ ์„ค๊ณ„ํ•˜์˜€๋‹ค. ์žํ™” ์œ ๋„ ๊ฒฐํ•ฉ ํ”Œ๋ผ์ฆˆ๋งˆ๋Š” ํŠน์ • ์กฐ๊ฑด์„ ๋งŒ์กฑํ•  ๋•Œ R-wave ๊ฐ€ ์ „ํŒŒ๋˜๋ฉฐ ์ด๋กœ ์ธํ•ด ๊ณ ๋ฐ€๋„ ํ”Œ๋ผ์ฆˆ๋งˆ๋ฅผ ํ˜•์„ฑํ•  ์ˆ˜ ์žˆ๋Š” ํŠน์ง•์„ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. ์ด์— ๋Œ€ํ•œ ์„ค๊ณ„๋ฅผ ์œ„ํ•ด์„œ๋Š” ์ „์ž์„์˜ ์œ„์น˜์™€ ์ž๊ธฐ์žฅ์˜ ๊ตฌ๋ฐฐ ๋ฐ ํฌ๊ธฐ๊ฐ€ ์ค‘์š”ํ•œ๋ฐ ์ƒ์šฉ ์†Œํ”„ํŠธ์›จ์–ด์ธ FEMM ์„ ์ด์šฉํ•˜์˜€๋‹ค. MICP-IBE ์˜ ์„ค๊ณ„๋ฅผ ํ•œ ํ›„์— ์ž๊ธฐ์žฅ, ์†Œ์ŠคํŒŒ์›Œ, ๊ทธ๋ฆฌ๋“œ ์ „์•• ๋“ฑ์˜ ๊ฐ€๋ณ€์— ๋”ฐ๋ผ ํ”Œ๋ผ์ฆˆ๋งˆ์˜ ๋ฐฉ์ „ํŠน์„ฑ ๋ฐ ์ด์˜จ ๋น”์˜ ํŠน์„ฑ์— ๋Œ€ํ•˜์—ฌ ์‚ดํŽด๋ณด์•˜๋‹ค. ์ž๊ธฐ์žฅ์˜ ๊ฐ€๋ณ€์— ๋”ฐ๋ผ ํ”Œ๋ผ์ฆˆ๋งˆ ๋ฐ€๋„๋Š” ์ฆ๊ฐ€ํ•˜๋Š” ๊ฒƒ์œผ๋กœ ์ธก์ •๋˜๋‚˜, R-wave ๋กœ ์ธํ•œ ๋ฐฉ์ „ mechanism ์œผ๋กœ ์ธํ•˜์—ฌ ํŠน์ˆ˜ํ•œ ์กฐ๊ฑด์—์„œ maximum ์˜ ํ”Œ๋ผ์ฆˆ๋งˆ ๋ฐ€๋„๋ฅผ ๊ฐ€์ง€๋Š” ๊ฒƒ์„ ํ™•์ธ ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ํ”Œ๋ผ์ฆˆ๋งˆ ๋ฐ€๋„์™€ ์ „์ž์˜จ๋„์˜ ์ฆ๊ฐ€์— ๋”ฐ๋ผ ion flux ๋˜ํ•œ ์ฆ๊ฐ€ํ•˜๋Š” ๊ฒƒ์„ ํ™•์ธ ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์†Œ์ŠคํŒŒ์›Œ๊ฐ€ ์ฆ๊ฐ€ํ• ๋•Œ๋Š” ํ”Œ๋ผ์ฆˆ๋งˆ ๋ฐ€๋„๊ฐ€ ์ง€์†์ ์œผ๋กœ ์ฆ๊ฐ€ํ•˜์ง€๋งŒ, ion flux ๋Š” ํŠน์ • ์†Œ์ŠคํŒŒ์›Œ์—์„œ maximum ๊ฐ’์„ ๊ฐ€์ง€๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์ด๋Š” ํ”Œ๋ผ์ฆˆ๋งˆ ๋ฐ€๋„์™€ ์Šคํฌ๋ฆฐ ๊ทธ๋ฆฌ๋“œ์—์„œ ํ˜•์„ฑ๋˜๋Š” sheath ๋ชจ์–‘๊ณผ์˜ ๊ด€๊ณ„์— ๋”ฐ๋ฅธ ๊ฒƒ์œผ๋กœ์จ ์ ์ ˆํ•˜๊ฒŒ sheath ๊ฐ€ ํ˜•์„ฑ๋˜์–ด์•ผ๋งŒ beam focus ๊ฐ€ ์›ํ™œํ•˜๊ฒŒ ๋˜๋Š” ๊ฒƒ์ž„์„ ํ™•์ธํ•˜์˜€๋‹ค. Screen grid ์™€ Acceleration grid ์˜ ์ ˆ๋Œ€์ ์ธ ์ „์•• ์ฐจ์ด์— ์˜ํ•ด์„œ๋„ sheath ๋‘๊ป˜์™€ ๋ชจ์–‘์ด ๊ฒฐ์ •๋˜๊ธฐ ๋•Œ๋ฌธ์— ์ธ๊ฐ€๋˜๋Š” ๊ทธ๋ฆฌ๋“œ ์ „์••์—ญ์‹œ๋„ ๋งค์šฐ ์ค‘์š”ํ•˜๋‹ค. ๋‹ค์‹œ ๋งํ•˜๋ฉด, ๊ทธ๋ฆฌ๋“œ ์ „์••์˜ ํฌ๊ธฐ๋Š” ์ตœ์ ์˜ ion beam ์˜ ํšจ์œจ์„ ๊ทน๋Œ€ํ™” ์‹œํ‚ค๊ธฐ ์œ„ํ•ด ๋งค์šฐ ์ค‘์š”ํ•œ ์š”์†Œ์ด๋ฉฐ, screen grid ์™€ acceleration grid ๋Š” ion energy ์™€ ion flux ๋ฅผ ๊ฐ๊ฐ ์ œ์–ดํ•˜๊ฒŒ ๋œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ƒˆ๋กœ์šด MICP-IBE ์˜ ์„ค๊ณ„๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ๊ท ์ผ๋„ ํŠน์„ฑ ๊ฐœ์„ ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋„ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ์šฐ์„ , ์ž๊ธฐ์žฅ์˜ ๊ตฌ๋ฐฐ๋ฅผ ๋‹ค์–‘ํ™” ์‹œํ‚ค๊ธฐ ์œ„ํ•˜์—ฌ ์ „์ž์„์„ ์ถ”๊ฐ€์ ์œผ๋กœ ์…‹์—…์„ ํ•˜์˜€๋‹ค. ํ”Œ๋ผ์ฆˆ๋งˆ ๋ฐ€๋„, ion flux, etch rate ์˜ non-uniformity value ๋ฅผ ๋‹ค์–‘ํ•œ ์ž๊ธฐ์žฅ ๊ตฌ๋ฐฐ ์กฐ๊ฑด์—์„œ ๋ชจ๋‘ ์ธก์ •ํ•˜์˜€๋‹ค. ํ”Œ๋ผ์ฆˆ๋งˆ ๋‚ด์—์„œ flute instability ํ˜„์ƒ์ด ์–ต์ œ๋˜๋Š” ํŠน์„ฑ์ด ๋งŒ์กฑ๋˜์–ด์•ผ๋งŒ ๊ท ์ผ๋„ ํŠน์„ฑ์ด ํ–ฅ์ƒ๋˜๋Š” ๊ฒƒ์œผ๋กœ ํ™•์ธ๋˜์–ด์กŒ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜, ์ž๊ธฐ์žฅ์˜ ๊ตฌ๋ฐฐ๋ฅผ flute instability ๋ฅผ ์–ต์ œํ•˜๋Š” ์กฐ๊ฑด์œผ๋กœ์จ ๊ท ์ผ๋„๋ฅผ ๊ฐœ์„ ํ•˜๋Š” ๊ฒƒ์—๋Š” ํ•œ๊ณ„์ ์„ ๋ณด์ด๊ณ  ์žˆ์—ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๊ด€์ ์—์„œ ์ถ”๊ฐ€์ ์œผ๋กœ ๊ท ์ผ๋„ ํŠน์„ฑ์„ ๊ฐœ์„ ์„ ํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ๊ทธ๋ฆฌ๋“œ์˜ ๋ฐ˜๊ฒฝ๋ฐฉํ–ฅ์ด ์ฆ๊ฐ€ํ•จ์— ๋”ฐ๋ผ ๊ทธ๋ฆฌ๋“œ ๊ตฌ๋ฉ์˜ ๋ฐ€๋„๊ฐ€ ์ฆ๊ฐ€ํ•˜๋Š” ํ˜•ํƒœ์˜ ์ƒˆ๋กœ์šด ๊ทธ๋ฆฌ๋“œ๋ฅผ ์ƒˆ๋กญ๊ฒŒ ์„ค๊ณ„ํ•˜์˜€๋‹ค. ๊ทธ๋ฆฌ๋“œ ๊ตฌ๋ฉ์˜ ๋ฐ€๋„๊ฐ€ ๊ท ์ผํ•œ Conventional grid ์™€ ๋ฐ˜๊ฒฝ๋ฐฉํ–ฅ์— ๋”ฐ๋ผ ๊ตฌ๋ฉ์˜ ๋ฐ€๋„๊ฐ€ ๋‹ค๋ฅธ proposed grid ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ion flux ์™€ etch rate ๊ท ์ผ๋„ ํŠน์„ฑ์— ๋Œ€ํ•œ ์‹คํ—˜์ด ์ง„ํ–‰๋˜์—ˆ๋‹ค. CoFeB ๋ฌผ์งˆ์˜ non-uniformity values ๋ฅผ ์ธก์ •ํ•˜์˜€์„ ๊ฒฝ์šฐ, proposed grid ๋ฅผ ์‚ฌ์šฉํ•  ๊ฒฝ์šฐ๊ฐ€ (11.65%) conventional grid ๋ฅผ ์‚ฌ์šฉํ•  ๊ฒฝ์šฐ (17.50%) ๋ณด๋‹ค ๋” ๋‚ฎ์€ ๊ฒƒ์„ ํ™•์ธ ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ํ•œ ํŽธ, MTJ layer ๋ฅผ ๊ตฌ์„ฑํ•˜๋Š” ๋‹ค์–‘ํ•œ ๋ฌผ์งˆ๋“ค์˜ ์‹๊ฐ ํŠน์„ฑ๋„ ์‚ดํŽด๋ณด์•˜๋‹ค. CoFeB, Ta, TiN, W, SiO2 ๋“ฑ์˜ ๋ฌผ์งˆ๋“ค์„ line and space ํŒจํ„ด์„ ๊ฐ€์ง€๋Š” ์ƒ˜ํ”Œ๋กœ ์ง์ ‘ ๋งŒ๋“ค์—ˆ์œผ๋ฉฐ ๊ฐ ๋ฌผ์งˆ๋“ค์„ ๊ธฐ์กด์˜ RIE type etcher ์™€ ์ƒˆ๋กญ๊ฒŒ ์„ค๊ณ„ํ•œ MICP-IBE ์—์„œ ์‹๊ฐ ์‹คํ—˜์„ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ๊ธฐ์กด์˜ RIE type etcher ์—์„œ๋Š” MICP ์‹๊ฐ ์žฅ์น˜์™€ ICP ์˜ ์‹๊ฐ ์žฅ์น˜์—์„œ์˜ ์‹๊ฐ ํŠน์„ฑ์ด ๋น„๊ต๋˜์—ˆ๋‹ค. ํŠนํžˆ, facet ๊ฐ๋„ ์ฐจ์ด๊ฐ€ ์ƒ์ดํ•˜๊ฒŒ ์ธก์ •๋˜์—ˆ๋Š”๋ฐ ๊ฐ๋„ ํŠน์„ฑ์„ ๋ถ„์„ํ•ด ๋ณธ ๊ฒฐ๊ณผ, MICP ์‹๊ฐ ์žฅ์น˜๊ฐ€ ํŒจํ„ด ์ธก๋ฉด์— ์žฌ์ฆ์ฐฉ๋˜๋Š” ๋ฌผ์งˆ๋“ค์„ ๊ฐ์†Œ์‹œํ‚ค๋Š” ๊ฒƒ์— ์œ ๋ฆฌํ•˜๋‹ค๋Š” ๊ฒƒ์„ ํ™•์ธ ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜, ์™„๋ฒฝํ•˜๊ฒŒ ์ œ๊ฑฐํ•˜๋Š” ๊ฒƒ์€ ๋ถˆ๊ฐ€๋Šฅํ•˜์˜€๊ณ  ์ด์— ๋Œ€ํ•œ ํŠน์„ฑ์„ ์‚ดํŽด๋ณด๊ณ ์ž ์•ž์„œ ์„ค๊ณ„๋œ MICP-IBE ๋ฅผ ์ด์šฉํ•˜์—ฌ ์‹๊ฐ ์‹คํ—˜์„ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ๊ธฐ๋ณธ์ ์œผ๋กœ ์ด์˜จ์—๋„ˆ์ง€ ๊ฐ€๋ณ€์— ๋”ฐ๋ฅธ ์‹๊ฐํŠน์„ฑ์„ ์‚ดํŽด๋ณด์•˜๊ณ  ์ธก๋ฉด์— ์žฌ์ฆ์ฐฉ๋˜๋Š” ๋ฌผ์งˆ๋“ค์„ ์ œ๊ฑฐํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ๊ธฐํŒ์˜ tilt angle ๋ณ€ํ™”์— ๋”ฐ๋ฅธ ์‹๊ฐ ํŠน์„ฑ ๋˜ํ•œ ์‚ดํŽด๋ณด์•˜๋‹ค. ๊ธฐํŒ์˜ tilt ๋ณ€ํ™”์— ๋”ฐ๋ผ etch rate ๋„ ๋ณ€ํ•˜์˜€์œผ๋ฉฐ maximum ๊ฐ’์„ ๊ฐ€์ง€๋Š” ๊ฒƒ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๊ณ  ์ธก๋ฉด์— ์žฌ์ฆ์ฐฉ๋œ ๋ฌผ์งˆ์ด ์ œ๊ฑฐ๋˜๋Š” ํ˜„์ƒ ๋˜ํ•œ ํ™•์ธ ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค.์ œ 1 ์žฅ ์„œ ๋ก  1 1.1 ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์  1 1.2 ๋…ผ๋ฌธ์˜ ๊ตฌ์„ฑ 5 ์ œ 2 ์žฅ ํ”Œ๋ผ์ฆˆ๋งˆ ์‹๊ฐ ์žฅ์น˜ ๋ฐ ์ด์˜จ ๋น” ์‹๊ฐ ์žฅ์น˜ 7 2.1 ๋ฐ˜๋„์ฒด ๋ถ„์•ผ์˜ ํ”Œ๋ผ์ฆˆ๋งˆ ์‹๊ฐ ์‘์šฉ 7 2.2 ๋‹ค์–‘ํ•œ ํ”Œ๋ผ์ฆˆ๋งˆ ์†Œ์Šค๋ฅผ ์ด์šฉํ•œ ํ”Œ๋ผ์ฆˆ๋งˆ ์‹๊ฐ ์žฅ์น˜ 9 2.2.1 ํ”Œ๋ผ์ฆˆ๋งˆ ์‹๊ฐ ์žฅ์น˜์˜ ์ข…๋ฅ˜ 9 2.2.2 ์šฉ๋Ÿ‰ ๊ฒฐํ•ฉ ํ”Œ๋ผ์ฆˆ๋งˆ (CCP) ์žฅ์น˜์˜ ์›๋ฆฌ 16 2.2.3 ์œ ๋„ ๊ฒฐํ•ฉ ํ”Œ๋ผ์ฆˆ๋งˆ (ICP) ์žฅ์น˜์˜ ์›๋ฆฌ 20 2.2.4 ์žํ™” ์œ ๋„ ๊ฒฐํ•ฉ ํ”Œ๋ผ์ฆˆ๋งˆ (M-ICP) ์žฅ์น˜์˜ ์›๋ฆฌ 25 2.3 ๋‹ค์–‘ํ•œ ํ”Œ๋ผ์ฆˆ๋งˆ ์†Œ์Šค๋ฅผ ์ด์šฉํ•œ ์ด์˜จ ๋น” ์‹๊ฐ ์žฅ์น˜ 30 2.3.1 ์ด์˜จ ๋น” ์‹๊ฐ ์žฅ์น˜ ๊ตฌ์กฐ์™€ ํŠน์ง• 30 2.3.2 ๋‹ค์–‘ํ•œ ํ”Œ๋ผ์ฆˆ๋งˆ ์†Œ์Šค์˜ ์ด์˜จ ๋น” ์‹๊ฐ ์žฅ์น˜ ์ข…๋ฅ˜ 34 2.3.3 ์ด์˜จ ๋น” ์‹๊ฐ ์žฅ์น˜๋ฅผ ์ด์šฉํ•œ ์„ ํ–‰ ์—ฐ๊ตฌ 37 ์ œ 3 ์žฅ M-ICP ์ด์˜จ ๋น” ์‹๊ฐ ์žฅ์น˜ ์„ค๊ณ„ ๋ฐ ๋ฐฉ์ „ ํŠน์„ฑ 41 3.1 M-ICP ์ด์˜จ ๋น” ์‹๊ฐ ์žฅ์น˜ ๊ตฌ์„ฑ ๋ฐ ์ „์ž์„ ์„ค๊ณ„ 43 3.1.1 FEMM ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ์ด์šฉํ•œ ์ „์ž์„ ๋ชจ๋ธ๋ง 43 3.1.2 M-ICP ์ด์˜จ ๋น” ์‹๊ฐ ์žฅ์น˜์˜ ๊ตฌ์„ฑ 46 3.2 ์ž๊ธฐ์žฅ ์ตœ์ ํ™” ์„ค๊ณ„ 49 3.2.1 ์ž๊ธฐ์žฅ ์ตœ์ ํ™”์™€ ๊ด€๋ จ๋œ ์ด๋ก  ๋ฐ ์„ ํ–‰ ์—ฐ๊ตฌ 49 3.2.2 ์ „๋ฅ˜ ์ธ๊ฐ€ ์กฐ๊ฑด์— ๋”ฐ๋ฅธ ์ž๊ธฐ์žฅ์˜ ๊ณต๊ฐ„ ๋ถ„ํฌ ๋ณ€ํ™” 53 3.3 ์ž๊ธฐ์žฅ ๊ฐ€๋ณ€์— ๋”ฐ๋ฅธ ๋ฐฉ์ „ ๋ฐ ion beam flux ํŠน์„ฑ 60 3.3.1 Langmuir probe๋ฅผ ์ด์šฉํ•œ ํ”Œ๋ผ์ฆˆ๋งˆ ์ง„๋‹จ 60 3.3.2 Ion energy analyzer๋ฅผ ์ด์šฉํ•œ ion beam flux ์ธก์ • 63 3.3.3 ์ž๊ธฐ์žฅ ์„ธ๊ธฐ์— ๋”ฐ๋ฅธ ๋ฐฉ์ „ ํŠน์„ฑ 69 3.3.4 ์ž๊ธฐ์žฅ ์„ธ๊ธฐ์— ๋”ฐ๋ฅธ ion beam flux ํŠน์„ฑ 74 3.4 RF power ๊ฐ€๋ณ€์— ๋”ฐ๋ฅธ ๋ฐฉ์ „ ๋ฐ ion beam fluxํŠน์„ฑ 79 3.4.1 RF power ๊ฐ€๋ณ€์— ๋”ฐ๋ฅธ ๋ฐฉ์ „ ํŠน์„ฑ 79 3.4.2 RF power ๊ฐ€๋ณ€์— ๋”ฐ๋ฅธ ion beam flux ํŠน์„ฑ 82 3.5 IBE ๊ทธ๋ฆฌ๋“œ์˜ sheath ํ˜•์„ฑ๊ณผ ion beam flux์˜ ์ƒ๊ด€๊ด€๊ณ„ 87 3.5.1 ๊ทธ๋ฆฌ๋“œ์˜ ์‰ฌ์Šค ํ˜•์„ฑ ์›๋ฆฌ ๋ฐ ์ด๋ก  87 3.5.2 Screen grid ์ „์••์— ๋”ฐ๋ฅธ ion beam flux ํŠน์„ฑ 90 3.5.3 Accelerator grid ์ „์••์— ๋”ฐ๋ฅธ ion beam flux ํŠน์„ฑ 93 3.6 ์š”์•ฝ ๋ฐ ํ–ฅํ›„ ๊ณผ์ œ 96 ์ œ 4 ์žฅ M-ICP ์ด์˜จ ๋น” ์‹๊ฐ ์žฅ์น˜์˜ ๊ท ์ผ๋„ ํŠน์„ฑ 98 4.1 ์ž๊ธฐ์žฅ ๊ตฌ๋ฐฐ์™€ ๊ท ์ผ๋„์˜ ์ƒ๊ด€๊ด€๊ณ„์— ๊ด€ํ•œ ์„ ํ–‰ ์—ฐ๊ตฌ 99 4.2 ์ „์ž์„ ์ „๋ฅ˜ ์ธ๊ฐ€ ์กฐ๊ฑด์— ๋”ฐ๋ฅธ ์ž๊ธฐ์žฅ์˜ ๊ณต๊ฐ„ ๋ถ„ํฌ 101 4.3 ์ž๊ธฐ์žฅ ๊ตฌ๋ฐฐ์— ๋”ฐ๋ฅธ ๊ท ์ผ๋„ ํŠน์„ฑ 105 4.3.1 ํ”Œ๋ผ์ฆˆ๋งˆ ๋ฐ€๋„ ๋ฐ ์ „์ž์˜จ๋„ ๊ท ์ผ๋„ ํŠน์„ฑ 105 4.3.2 Ion beam flux ์˜ ๊ท ์ผ๋„ ํŠน์„ฑ 110 4.3.3 ์‹๊ฐ ๊ท ์ผ๋„ ํŠน์„ฑ 116 4.4 ๊ทธ๋ฆฌ๋“œ ๊ตฌ๋ฉ์˜ ๋ฐ€๋„ ๋ถ„ํฌ์— ๋”ฐ๋ฅธ ๊ท ์ผ๋„ ํŠน์„ฑ 121 4.4.1 ๊ทธ๋ฆฌ๋“œ ๊ตฌ๋ฉ์˜ ๋ฐ€๋„ ๋ถ„ํฌ์˜ ์„ค๊ณ„ 121 4.4.2 Ion beam flux ์˜ ๊ท ์ผ๋„ ํŠน์„ฑ 125 4.4.3 ์‹๊ฐ ๊ท ์ผ๋„ ํŠน์„ฑ 139 4.5 ์š”์•ฝ ๋ฐ ํ–ฅํ›„ ๊ณผ์ œ 133 ์ œ 5 ์žฅ MTJ layer ๊ตฌ์„ฑ ๋ฌผ์งˆ๋“ค์˜ ์‹๊ฐ ํŠน์„ฑ 135 5.1 ์ฐจ์„ธ๋Œ€ ๋‰ด ๋ฉ”๋ชจ๋ฆฌ ๊ฐœ๋ฐœ ํ˜„ํ™ฉ ๋ฐ ์ข…๋ฅ˜ 136 5.2 STT-MRAM์˜ ๊ตฌ์กฐ ๋ฐ ๋™์ž‘ ์›๋ฆฌ 139 5.3 MTJ layer ์‹๊ฐ ์„ ํ–‰์—ฐ๊ตฌ 143 5.4 Sputter yield ์‹œ๋ฎฌ๋ ˆ์ด์…˜ 147 5.5 ์‹๊ฐ ์‹คํ—˜์— ์‚ฌ์šฉ๋œ line pattern ์ƒ˜ํ”Œ ์ œ์ž‘ 153 5.6 ICP ๋ฐ M-ICP ํ”Œ๋ผ์ฆˆ๋งˆ ์‹๊ฐ ์žฅ์น˜์˜ ์‹๊ฐ ํŠน์„ฑ 155 5.6.1 Facet ํ˜•์„ฑ๊ณผ redeposition ์˜ ๊ด€๊ณ„ 155 5.6.2 ICP ํ”Œ๋ผ์ฆˆ๋งˆ ์‹๊ฐ ์žฅ์น˜์˜ facet ๋ฐ ์‹๊ฐ ํŠน์„ฑ 159 5.6.3 M-ICP ํ”Œ๋ผ์ฆˆ๋งˆ ์‹๊ฐ ์žฅ์น˜์˜ facet ๋ฐ ์‹๊ฐ ํŠน์„ฑ 168 5.6.4 MTJ layer ๊ตฌ์„ฑ๋ฌผ์งˆ๋“ค์˜ ์‹๊ฐ ํŠน์„ฑ ๋น„๊ต 178 5.6.5 RIE type ์‹๊ฐ ์žฅ์น˜์˜ ํ•œ๊ณ„์„ฑ 180 5.7 M-ICP ์ด์˜จ ๋น” ์‹๊ฐ ์žฅ์น˜์˜ ์‹๊ฐ ํŠน์„ฑ. 182 5.7.1 ์ด์˜จ ์—๋„ˆ์ง€์— ๋ณ€ํ™”์— ๋”ฐ๋ฅธ ์‹๊ฐ ํŠน์„ฑ 182 5.7.2 ๊ธฐํŒ tilt ๊ฐ๋„ ๋ณ€ํ™”์— ๋”ฐ๋ฅธ ์‹๊ฐ ํŠน์„ฑ 188 5.8 ์š”์•ฝ ๋ฐ ํ–ฅํ›„ ๊ณผ์ œ 192 ์ œ 6 ์žฅ ๊ฒฐ๋ก  195 ์ฐธ๊ณ  ๋ฌธํ—Œ 200 ABSTRACT 208Docto

    Speech Enhancement Using Noise-Robust Speech Representation Model

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ์œตํ•ฉ๊ณผํ•™๊ธฐ์ˆ ๋Œ€ํ•™์› ์ง€๋Šฅ์ •๋ณด์œตํ•ฉํ•™๊ณผ, 2022. 8. ์ด๊ต๊ตฌ.๊ธฐ์กด์˜ ๋”ฅ ๋Ÿฌ๋‹ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ํ™œ์šฉํ•œ ์‹œ๊ฐ„ ์˜์—ญ์—์„œ์˜ ์Œ์„ฑ ํ–ฅ์ƒ์€ ๋ฐœํ™” ๋ฐ์ดํ„ฐ๋ฅผ ํŠน์ง•์œผ๋กœ ์ธ์ฝ”๋”ฉ ํ•œ ํ›„, ์ด๋ฅผ ์žก์Œ์ด ์ œ๊ฑฐ๋œ ๋ฐœํ™” ๋ฐ์ดํ„ฐ๋กœ ๋””์ฝ”๋”ฉ ํ•˜๋Š” ์˜คํ†  ์ธ์ฝ”๋” ๋ชจ๋ธ์„ ๋ณดํŽธ์ ์œผ๋กœ ์ฑ„ํƒํ–ˆ๋‹ค. ์ตœ๊ทผ ๋‹ค์–‘ํ•œ ๋ถ„์•ผ์—์„œ ์ž๊ธฐ ์ง€๋„ ํ•™์Šต์„ ํ†ตํ•œ ์‚ฌ์ „ ํ›ˆ๋ จ ๋ชจ๋ธ์ด ์‚ฌ์šฉ๋˜๊ณ  ์žˆ๋‹ค. ์Œ์„ฑ๊ณผ ๊ด€๋ จํ•œ ์‚ฌ์ „ ํ›ˆ๋ จ ๋ชจ๋ธ๋“ค์€ ์ž๋™ ์Œ์„ฑ ์ธ์‹์ด๋‚˜ ๊ฐ์ • ๋ถ„๋ฅ˜ ๋“ฑ ๋‹ค์–‘ํ•œ ์ž‘์—…์„ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ์‚ฌ์šฉ๋˜๊ณ  ์žˆ๋‹ค. ์‚ฌ์ „ ํ›ˆ๋ จ ๋ชจ๋ธ์„ ์‚ฌ์šฉํ•˜์—ฌ ์ž‘์—…์„ ํ•ด๊ฒฐํ•œ ์—ฐ๊ตฌ๋“ค์€ ๊ธฐ์กด ์—ฐ๊ตฌ๋“ค๋ณด๋‹ค ๋†’์€ ์„ฑ๋Šฅ์„ ๋ฐœํœ˜ํ•˜๊ณ  ์žˆ์œผ๋‚˜, ์Œ์„ฑ ํ–ฅ์ƒ ์ž‘์—…์—์„œ๋Š” ์‚ฌ์ „ ํ›ˆ๋ จ ๋ชจ๋ธ์ด ํ™œ์šฉ๋˜๊ณ  ์žˆ๋Š” ์‚ฌ๋ก€๊ฐ€ ์ ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์‹œ๊ฐ„ ์˜์—ญ์—์„œ์˜ ์Œ์„ฑ ํ–ฅ์ƒ ๋ชจ๋ธ๋กœ์จ ๋ณดํŽธ์ ์œผ๋กœ ์ฑ„ํƒ๋˜๋Š” ์˜คํ†  ์ธ์ฝ”๋”์™€ ๊ฐ™์ด ๋™์ผํ•œ ๊ตฌ์กฐ์˜ ์ธ์ฝ”๋”/๋””์ฝ”๋”๋ฅผ ์ฑ„ํƒํ•˜๋Š” ๋Œ€์‹ , ์‚ฌ์ „ ํ›ˆ๋ จ๋œ ์ž๊ธฐ ์ง€๋„ ๋ฐœํ™” ํ‘œ์ƒ ๋ชจ๋ธ๊ณผ ์Œ์„ฑ ํ•ฉ์„ฑ๊ธฐ๋ฅผ ํ™œ์šฉํ•œ ์ƒˆ๋กœ์šด ๊ตฌ์กฐ์˜ ์Œ์„ฑ ํ–ฅ์ƒ ๋ชจ๋ธ์„ ์ œ์•ˆํ•œ๋‹ค. ์ œ์•ˆ๋œ ๋ชจ๋ธ์€ ์‚ฌ์ „ ํ›ˆ๋ จ๋œ ์ž๊ธฐ ์ง€๋„ ๋ฐœํ™” ํ‘œ์ƒ ๋ชจ๋ธ์„ ๋ฏธ์„ธ์กฐ์ •ํ•˜์—ฌ ์žก์Œ ํŠน์ง•์ด ์ œ๊ฑฐ๋œ, ํ–ฅ์ƒ๋œ ๋ฐœํ™” ํ‘œ์ƒ์„ ์ถ”์ถœํ•˜๊ณ , ์ด๋ฅผ ์Œ์„ฑ ํ•ฉ์„ฑ๊ธฐ๋ฅผ ํ†ตํ•ด ํ–ฅ์ƒ๋œ ๋ฐœํ™” ๋ฐ์ดํ„ฐ๋กœ ํ•ฉ์„ฑํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ์‚ฌ์ „ ํ›ˆ๋ จ๋œ ์ž๊ธฐ ์ง€๋„ ๋ฐœํ™” ํ‘œ์ƒ ๋ชจ๋ธ์—์„œ ์ถœ๋ ฅ๋˜๋Š” ๊นจ๋—ํ•œ ๋ฐœํ™” ํ‘œ์ƒ์ด ์Œ์„ฑ ํ•ฉ์„ฑ๊ธฐ๋ฅผ ํ™œ์šฉํ•˜์—ฌ ์Œ์„ฑ์„ ์žฌํ•ฉ์„ฑํ•  ์ˆ˜ ์žˆ์Œ์„ ๋ณด์ธ๋‹ค. ๋˜ํ•œ, ์žก์Œ์ด ์„ž์ธ ๋ฐœํ™” ํ‘œ์ƒ์—์„œ ์žก์Œ ํŠน์ง•์„ ์ œ๊ฑฐํ•˜์—ฌ ๊นจ๋—ํ•œ ๋ฐœํ™”๋ฅผ ํ•ฉ์„ฑํ•  ์ˆ˜ ์žˆ๋„๋ก, ํ–ฅ์ƒ๋œ ๋ฐœํ™” ํ‘œ์ƒ์„ ์ถœ๋ ฅํ•  ์ˆ˜ ์žˆ๋Š” target ๋ชจ๋ธ์„ ํ›ˆ๋ จํ•˜๊ธฐ ์œ„ํ•ด ์–‘์งˆ์˜ ๋ฐœํ™” ํ‘œ์ƒ์„ ์ถœ๋ ฅํ•˜๋Š” ์‚ฌ์ „ ํ›ˆ๋ จ ๋ชจ๋ธ์„ teacher ๋ชจ๋ธ๋กœ ์‚ฌ์šฉํ•œ๋‹ค. target ๋ชจ๋ธ์—์„œ ์ถœ๋ ฅ๋˜๋Š” ํ–ฅ์ƒ๋œ ๋ฐœํ™” ํ‘œ์ƒ์ด teacher ๋ชจ๋ธ์—์„œ ์ถœ๋ ฅ๋˜๋Š” ๊นจ๋—ํ•œ ๋ฐœํ™” ํ‘œ์ƒ์ด ๋  ์ˆ˜ ์žˆ๋„๋ก ํ›ˆ๋ จํ•˜๋Š” ๋ฐฉ๋ฒ•๋“ค์— ๋Œ€ํ•ด ๋…ผํ•œ๋‹ค. ์ œ์•ˆ๋œ ๋ฐฉ๋ฒ•์„ ํ†ตํ•ด ํ•™์Šต๋œ ์Œ์„ฑ ํ–ฅ์ƒ ๋ชจ๋ธ์˜ ์„ฑ๋Šฅ์„ ๋ณด์ด๊ณ , ๋ชจ๋ธ์˜ ํ•œ๊ณ„์ ๊ณผ ์ด๋ฅผ ๊ทน๋ณตํ•˜๊ธฐ ์œ„ํ•ด ํ•„์š”ํ•œ ํ–ฅํ›„ ์—ฐ๊ตฌ์— ๊ด€ํ•˜์—ฌ ๋…ผํ•œ๋‹ค.Speech enhancement models in the time domain have adopted an autoencoder-based model architecture, which encodes noisy speech into features and decodes it into clean speech. Recently, pre-trained self-supervised speech representation models have been used in various fields. Pre-trained models in the audio domain are used for various tasks such as automatic speech recognition and emotion classification. Studies that solve tasks using a pre-trained model perform better than previous studies, but there are fewer cases where a pre-trained model was used for speech enhancement. In this study, instead of using an autoencoder, which is commonly adopted as a speech enhancement model in the time domain, we propose a novel speech synthesizer-based speech enhancement model using self-supervised speech representations. The proposed model fine-tunes the pre-trained self-supervised speech representation model to extract the enhanced speech representation, with the noise feature removed, and synthesize it to enhanced speech data via a speech synthesizer. Through this work, we show that a clean speech representation from a pre-trained self-supervised speech representation model can be re-synthesized via a speech synthesizer. In addition, a pre-trained model which extracts high-quality speech representation is used as a teacher model to train a target model, which extracts noise-robust representation. We discuss the ways to train the target model so that the enhanced speech representations extracted by the target model become the clean speech representation extracted by the teacher model. We demonstrate the performance of the proposed speech enhancement model and discuss the limitation of the proposed model and further works.์ œ 1 ์žฅ ์„œ ๋ก  6 1.1 ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ 6 1.2 ์—ฐ๊ตฌ ๋ชฉํ‘œ 8 ์ œ 2 ์žฅ ๋ฐฐ๊ฒฝ ์ด๋ก  ๋ฐ ๊ด€๋ จ ์—ฐ๊ตฌ 10 2.1 ๋ฐฐ๊ฒฝ ์ด๋ก  10 2.1.1 ์Œ์„ฑ ํ–ฅ์ƒ 10 2.1.2 ์ž๊ธฐ ์ง€๋„ ๋ฐœํ™” ํ‘œ์ƒ ๋ชจ๋ธ 12 2.1.3 ์Œ์„ฑ ํ•ฉ์„ฑ 12 2.1.4 ์Œ์„ฑ ํ–ฅ์ƒ ํ‰๊ฐ€ ์ง€ํ‘œ 13 2.2 ๊ด€๋ จ ์—ฐ๊ตฌ 15 2.2.1 ์Œ์„ฑ ํ–ฅ์ƒ ์—ฐ๊ตฌ 15 2.2.2 Wav2Vec 2.0 18 2.2.3 HiFi-GAN 20 ์ œ 3 ์žฅ ์ œ์•ˆ ๊ธฐ๋ฒ• 22 3.1 ์‚ฌ์ „ ํ›ˆ๋ จ๋œ ์ž๊ธฐ ์ง€๋„ ๋ฐœํ™” ํ‘œ์ƒ ๋ชจ๋ธ๊ณผ ์Œ์„ฑ ํ•ฉ์„ฑ๊ธฐ๋ฅผ ํ™œ์šฉํ•œ ์Œ์„ฑ ์žฌํ•ฉ์„ฑ 22 3.2 ์žก์Œ์— ๊ฐ•๊ฑดํ•œ ๋ฐœํ™” ํ‘œ์ƒ ๋ชจ๋ธ๊ณผ ์Œ์„ฑ ํ•ฉ์„ฑ๊ธฐ๋ฅผ ํ™œ์šฉํ•œ ์Œ์„ฑ ํ–ฅ์ƒ 24 3.2.1 Supervised contrastive learning์„ ํ™œ์šฉํ•œ ์žก์Œ/๋ฐœํ™” ํŠน์ง• ๋ถ„๋ฆฌ 24 3.2.2 Teacher ๋ชจ๋ธ๊ณผ target ๋ชจ๋ธ ๊ฐ„์˜ ๊ฑฐ๋ฆฌ ์ตœ์†Œํ™” 27 ์ œ 4 ์žฅ ์‹ค ํ—˜ 29 4.1 ์‹คํ—˜ ์ค€๋น„ 29 4.1.1 ๋ฐ์ดํ„ฐ์…‹ 29 4.1.2 ์‹คํ—˜์— ์‚ฌ์šฉ๋œ ์†์‹ค ํ•จ์ˆ˜ ๋ฐ ํ•™์Šต ํ™˜๊ฒฝ ์„ค์ • 31 4.1.3 ๋น„๊ต ๋Œ€์ƒ ๋ชจ๋ธ ์„ค์ • ๋ฐ ์„ฑ๋Šฅ ์ธก์ • 37 4.2 ์‹คํ—˜ ๊ฒฐ๊ณผ ๋ฐ ํ† ๋ก  37 4.2.1 ์Œ์„ฑ ์žฌํ•ฉ์„ฑ๊ธฐ ์‹คํ—˜ 38 4.2.2 ์Œ์„ฑ ํ–ฅ์ƒ ์‹คํ—˜ 43 ์ œ 5 ์žฅ ๊ฒฐ ๋ก  51 5.1 ์—ฐ๊ตฌ ์˜์˜ 51 5.2 ํ•œ๊ณ„์  52 5.3 ํ–ฅํ›„ ์—ฐ๊ตฌ 53 ABSTRACT 59์„

    K๋Œ€ํ•™๊ต๋ฅผ ์ค‘์‹ฌ์œผ๋กœ

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์‚ฌ๋ฒ”๋Œ€ํ•™ ๊ต์œกํ•™๊ณผ(๊ต์œกํ•™์ „๊ณต),2019. 8. ๋ฐฑ์ˆœ๊ทผ.OECD (2003) defined core competencies as abilities to achieve successful life throughout their lifetime for entire people in the world' and emphasized the enhancement of core competencies through education. Since then, many nations have emphasized the development and application of competency-based curricula in both primary and secondary education as well as in higher education. It is very important to diagnose and evaluate students' growth and development in order to understand the effects of newly implemented competency-based curriculum. Each institute of higher education has its own core competencies to reveal the founding philosophies. So researches are requited to develop proper assessment tools for each institute and to assess students competencies with the tools. Therefore, new core competency diagnostic tools for collegiate students suitable for the university are newly developed, Research is needed to confirm changes in core competencies. The purpose of this study is to develop and to validate a diagnostic tool for the core competencies of K university students(KCCA, K university Core Competency Assessment) in Gyeonggi province, and to analyze their competency levels. The research questions are following. 1. Is the newly developed diagnostic tool for core competencies valid? 2. What are the core competency levels of K university students. To address the questions, a 5 point Likert scale assessment tool for collegiate core competencies was developed with following procedures: a comprehensive literature review, two time expert review and a pilot test(78 students). The tool consisted of five sub-core competencies such as 'Boundless', 'Able, Reliable, Understanding and Networking. 2,151 students were participated in early September core competency assessment, and the result of the assessment was analyzed for construct validation and reliability. To analyze discriminant validity, 113 students were participated in early October Korea Collegiate Essential Skills Assessment (K-CESA), which is most commonly used for collegiate competency evalucation and developed by Korea Ministry of Education (MOE) and Korea Research Institute for Vocational Education and Training (KRIVET). Findings of the study is following; First of all, the newly developed collegiate core competency assessment tool (60 questions) is valid. 7 professors and 2 administrators reviewed the questions twice, and the average of review results was 4.33 over 5 and the range were between 3.78~4.78. Confirmative factor analysis was examined successfully since the model fit was acceptable and 20 sub factors and 10 secondary factors were suitable(TLI 0.912~962, CFI 0.935~0.971, RMSEA 0.052~0,068). To analyze discriminant validity, correlation analysis between KCCA and K-CESA was examined, and the discriminant validity was good since the correlation was statistically not significant. The entire tool reliability (Cronbach ฮฑ) was 0.956 and of sub competency reliabilities were between 0.816~0.882. Secondly, the K university student core competency was 3.80 over 5 and sub core competencies were 3.67~4.00. According to the fields of study (Humanity, Social Science, Natural Science, Applied Science and Art and physical education), the art and physical education majors had higher level of competencies in Able than the natural science majors, and the humanity majors had higher level of competencies in Understanding than the natural science majors. The competency level in Boundless and Reliable were different by student year. Male students had higher level of entire competencies than female students. K university students were grouped in 3 by latent profile analysis: excellent, average, poor. The distribution was different by field of study and sex. It is necessary to note the generalization of the results is limited since the assessment tool was developed in a self-report scale and small number of students participated in test-retest. To find out the effect of a university education in more comprehensive and stable manners, various types of assessment are supposed to be applied and stronger inducement should be used for more students participation.OECD(2003)๋Š” ํ•ต์‹ฌ์—ญ๋Ÿ‰์„ ๋ชจ๋“  ์‚ฌ๋žŒ์ด ์ „์ƒ์• ๋ฅผ ํ†ตํ•ด ์„ฑ๊ณต์ ์ธ ์‚ถ์„ ์˜์œ„ํ•˜๋Š”๋ฐ ํ•ต์‹ฌ์ด ๋˜๋Š” ์—ญ๋Ÿ‰์ด๋ผ ์ •์˜ํ•˜๊ณ , ๊ต์œก์„ ํ†ตํ•œ ํ•ต์‹ฌ์—ญ๋Ÿ‰์˜ ์ฆ์ง„์„ ๊ฐ•์กฐํ•˜์˜€๋‹ค. ์ดํ›„ ๊ฐ๊ตญ์€ ์ดˆ์ค‘๋“ฑ๊ต์œก์—์„œ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ๊ณ ๋“ฑ๊ต์œก์—์„œ๋„ ์—ญ๋Ÿ‰๊ธฐ๋ฐ˜ ๊ต์œก๊ณผ์ •์˜ ๊ฐœ๋ฐœ๊ณผ ์ ์šฉ์„ ์ค‘์‹œํ•˜๊ณ  ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋งฅ๋ฝ์—์„œ ์ƒˆ๋กญ๊ฒŒ ์‹œํ–‰๋˜๊ณ  ์žˆ๋Š” ์—ญ๋Ÿ‰๊ธฐ๋ฐ˜ ๊ต์œก๊ณผ์ •์˜ ํšจ๊ณผ๋ฅผ ํŒŒ์•…ํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ํ•™์ƒ์˜ ํ•ต์‹ฌ์—ญ๋Ÿ‰์„ ์ง„๋‹จํ•˜๊ณ  ํ‰๊ฐ€ํ•˜๋Š” ๊ฒƒ์ด ๋งค์šฐ ์ค‘์š”ํ•˜๋‹ค. ํŠนํžˆ ๊ณ ๋“ฑ๊ต์œก์„ ๋‹ด๋‹นํ•˜๋Š” ๋Œ€ํ•™๋“ค์€ ๊ฑดํ•™์ด๋…์ด๋‚˜ ์ถ”๊ตฌํ•˜๋Š” ์ธ์žฌ์ƒ์ด ๋‹ค๋ฅด๊ณ , ์ด๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ์ฆ์ง„ํ•˜๊ณ ์ž ํ•˜๋Š” ํ•ต์‹ฌ์—ญ๋Ÿ‰๋„ ์„œ๋กœ ๋‹ค๋ฅธ ์ƒํ™ฉ์ด๋ฏ€๋กœ ํ•ด๋‹น ๋Œ€ํ•™์— ์ ํ•ฉํ•œ ๋Œ€ํ•™์ƒ์šฉ ํ•ต์‹ฌ์—ญ๋Ÿ‰ ์ง„๋‹จ๋„๊ตฌ๋ฅผ ์ƒˆ๋กญ๊ฒŒ ๊ฐœ๋ฐœํ•˜๊ณ  ๊ทธ ์ง„๋‹จ๋„๊ตฌ๋ฅผ ํ™œ์šฉํ•˜์—ฌ ๋Œ€ํ•™์ƒ ํ•ต์‹ฌ์—ญ๋Ÿ‰์˜ ์ˆ˜์ค€ ๋“ฑ์„ ํŒŒ์•…ํ•˜๊ธฐ ์œ„ํ•œ ์—ฐ๊ตฌ๊ฐ€ ํ•„์š”ํ•œ ์‹ค์ •์ด๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ๊ฒฝ๊ธฐ๋„ ์†Œ์žฌ K๋Œ€ํ•™๊ต ํ•™์ƒ๋“ค์˜ ํ•ต์‹ฌ์—ญ๋Ÿ‰ ์ˆ˜์ค€์„ ํŒŒ์•…ํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์ง„๋‹จ๋„๊ตฌ๋ฅผ ๊ฐœ๋ฐœํ•œ ํ›„ ํƒ€๋‹นํ™”ํ•˜๊ณ , ๊ทธ ์ง„๋‹จ๋„๊ตฌ๋ฅผ ์ด์šฉํ•˜์—ฌ ์ธก์ •ํ•œ ํ•ต์‹ฌ์—ญ๋Ÿ‰์˜ ์ˆ˜์ค€์„ ๋ถ„์„ํ•˜๊ธฐ ์œ„ํ•œ ๊ฒƒ์ด๋ฉฐ, ์ฃผ์š” ์—ฐ๊ตฌ ๋ฌธ์ œ๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ์ฒซ์งธ, K๋Œ€ํ•™๊ต ํ•™์ƒ์šฉ ํ•ต์‹ฌ์—ญ๋Ÿ‰ ์ง„๋‹จ๋„๊ตฌ๋Š” ์–‘ํ˜ธํ•œ๊ฐ€? ๋‘˜์งธ, K๋Œ€ํ•™๊ต ํ•™์ƒ๋“ค์˜ ํ•ต์‹ฌ์—ญ๋Ÿ‰ ์ˆ˜์ค€์€ ์–ด๋– ํ•œ๊ฐ€? K๋Œ€ํ•™๊ต ํ•™์ƒ์šฉ ํ•ต์‹ฌ์—ญ๋Ÿ‰ ์ง„๋‹จ๋„๊ตฌ๋ฅผ ๊ฐœ๋ฐœํ•˜๊ธฐ ์œ„ํ•˜์—ฌ, ๊ด€๋ จ ์„ ํ–‰์—ฐ๊ตฌ๋“ค์„ ์ข…ํ•ฉ์ ์œผ๋กœ ๋ถ„์„ํ•˜๊ณ , 2์ฐจ์— ๊ฑธ์นœ ์ „๋ฌธ๊ฐ€ํ˜‘์˜ํšŒ์™€ ์˜ˆ๋น„๊ฒ€์‚ฌ(์ด 78๋ช…) ๋“ฑ์„ ๊ฑฐ์ณ 5์  ๋ฆฌ์ปคํŠธ(Likert)ํ˜• ์ฒ™๋„๋ฅผ ํ™œ์šฉํ•˜์˜€๋‹ค. ํ•ด๋‹น ์ง„๋‹จ๋„๊ตฌ๋Š” 5๊ฐœ์˜ ํ•ต์‹ฌ์—ญ๋Ÿ‰('์ฐฝ์˜์œตํ•ฉ์—ญ๋Ÿ‰', ์ „๋ฌธ์—ญ๋Ÿ‰, ์‹œ๋ฏผ์˜์‹, ์†Œํ†ต์—ญ๋Ÿ‰, ํ˜‘์—…์—ญ๋Ÿ‰)์œผ๋กœ ๊ตฌ์„ฑ๋˜์—ˆ๋‹ค. ์ƒˆ๋กญ๊ฒŒ ๊ฐœ๋ฐœํ•œ K๋Œ€ํ•™๊ต ํ•™์ƒ์šฉ ํ•ต์‹ฌ์—ญ๋Ÿ‰ ์ง„๋‹จ๋„๊ตฌ์˜ ์–‘ํ˜ธ๋„๋ฅผ ๊ฒ€์ฆํ•˜๊ธฐ ์œ„ํ•˜์—ฌ, 9์›”์ดˆ์— ํ•™๋ถ€์ƒ ์ „์ฒด๋ฅผ ๋Œ€์ƒ์œผ๋กœ ๋ณธ๊ฒ€์‚ฌ๋ฅผ ์‹ค์‹œํ•˜์—ฌ(์ด 2,151๋ช…), ๊ตฌ์ธํƒ€๋‹น๋„์™€ ์‹ ๋ขฐ๋„ ๋“ฑ์„ ๋ถ„์„ํ•˜์˜€๋‹ค. ๋˜ํ•œ ํ•ด๋‹น ์ง„๋‹จ๋„๊ตฌ์˜ ๋ณ€๋ณ„ํƒ€๋‹น๋„๋ฅผ ๋ถ„์„ํ•˜๊ธฐ ์œ„ํ•˜์—ฌ, ๊ต์œก๋ถ€์™€ ํ•œ๊ตญ์ง์—…๋Šฅ๋ ฅ๊ฐœ๋ฐœ์›์—์„œ ๊ฐœ๋ฐœํ•˜์—ฌ ์‹ค์‹œํ•˜๋ฉฐ ์ผ๋ฐ˜์ ์œผ๋กœ ๋งŽ์ด ์‚ฌ์šฉํ•˜๊ณ  ์žˆ๋Š” ๋Œ€ํ•™์ƒํ•ต์‹ฌ์—ญ๋Ÿ‰์ง„๋‹จ(K-CESA)์„ 10์›”์ดˆ์— ์‹ค์‹œํ•˜์˜€๋‹ค (์ด 133๋ช…). ์ฃผ์š” ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋ฅผ ์š”์•ฝํ•˜๋ฉด ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ์ฒซ์งธ, ๊ฐœ๋ฐœํ•œ K๋Œ€ํ•™๊ต ํ•™์ƒ์šฉ ํ•ต์‹ฌ์—ญ๋Ÿ‰ ์ง„๋‹จ๋„๊ตฌ(์ด 60๋ฌธํ•ญ์œผ๋กœ ๊ตฌ์„ฑ)๋Š” K๋Œ€ํ•™๊ต ํ•™์ƒ์˜ ํ•ต์‹ฌ์—ญ๋Ÿ‰์„ ์ธก์ •ํ•˜๊ธฐ์— ์–‘ํ˜ธํ•œ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๊ต์ˆ˜ 7์ธ๊ณผ ์—…๋ฌด๋‹ด๋‹น์ž 2์ธ์œผ๋กœ ๊ตฌ์„ฑ๋œ ์ „๋ฌธ๊ฐ€ํ˜‘์˜ํšŒ๋ฅผ ํ†ตํ•ด ๋ฌธํ•ญ์˜ ๋‚ด์šฉํƒ€๋‹น๋„๋ฅผ ๊ฒ€ํ† ํ•œ ๊ฒฐ๊ณผ ์ตœ์ข…๋ฌธํ•ญ์˜ ๋‚ด์šฉํƒ€๋‹น๋„๋Š” 5์  ๋งŒ์ ์— ํ‰๊ท ์ด 4.33์ ์ด๋ฉฐ ๊ทธ ๋ฒ”์œ„๋Š” 3.78~4.78๋กœ ๋‚˜ํƒ€๋‚˜ ์–‘ํ˜ธํ•˜์˜€๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ง„๋‹จ๋„๊ตฌ์˜ ๊ตฌ์ธํƒ€๋‹น๋„๋ฅผ ๊ฒ€ํ† ํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ๊ฐ ํ•ต์‹ฌ์—ญ๋Ÿ‰๋ณ„๋กœ ํ™•์ธ์  ์š”์ธ๋ถ„์„์„ ์‹ค์‹œํ•œ ๊ฒฐ๊ณผ, ๋ชจํ˜•์˜ ์ ํ•ฉ๋„ ์ค‘ TLI๋Š” 0.912~962, CFI๋Š” 0.935~0.971, RMSEA๋Š” 0.052~0,068์˜ ๋ฒ”์œ„๋กœ ๋‚˜ํƒ€๋‚˜ ๋ชจ๋‘ ์–‘ํ˜ธํ•˜์˜€๋‹ค. K-CESA์˜ 6๊ฐ€์ง€ ํ•ต์‹ฌ์—ญ๋Ÿ‰๊ณผ์˜ ๋ณ€๋ณ„ํƒ€๋‹น๋„๋ฅผ ๊ฒ€ํ† ํ•˜๊ธฐ ์œ„ํ•˜์—ฌ K-CESA๋ฅผ ํ™œ์šฉํ•œ ์ง„๋‹จ์ž๋ฃŒ์™€ ์ƒ๊ด€๋ถ„์„์„ ์‹ค์‹œํ•œ ๊ฒฐ๊ณผ ์ „์ฒด ์ด์ ์˜ ์ƒ๊ด€์€ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•˜์ง€ ์•Š์•˜์œผ๋ฉฐ, ๊ฐœ๋ณ„ ํ•ต์‹ฌ์—ญ๋Ÿ‰๋“ค ๊ฐ„์˜ ์ƒ๊ด€๋„ โ€“0.016~0.357๋กœ ๋Œ€์ฒด๋กœ ๋‚ฎ์•„ ๋ณ€๋ณ„ํƒ€๋‹น๋„๊ฐ€ ์–‘ํ˜ธํ•œ ์ˆ˜์ค€์ด์—ˆ๋‹ค. ์•„์šธ๋Ÿฌ ํ•ด๋‹น ์ง„๋‹จ๋„๊ตฌ์˜ ์‹ ๋ขฐ๋„(Cronbach ฮฑ)๋Š” 0.956์œผ๋กœ ๋†’๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๊ณ , 5๊ฐ€์ง€ ํ•ต์‹ฌ์—ญ๋Ÿ‰๋ณ„ ์‹ ๋ขฐ๋„์˜ ๋ฒ”์œ„๋„ 0.816~0.882๋กœ ๋†’๊ฒŒ ๋‚˜ํƒ€๋‚˜ ์–‘ํ˜ธํ•˜์˜€๋‹ค. ๋‘˜์งธ, K๋Œ€ํ•™๊ต ํ•™์ƒ์˜ ์ „์ฒด ํ•ต์‹ฌ์—ญ๋Ÿ‰์€ 5์  ๋งŒ์ ์— 3.80์ ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๊ณ , 5๊ฐ€์ง€ ํ•ต์‹ฌ์—ญ๋Ÿ‰๋ณ„ ๋ฒ”์œ„๋Š” 3.67~4.00์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ „๊ณต๋ณ„ 5๊ฐœ์˜ ํ•™๋ฌธ๋ถ„์•ผ(์ธ๋ฌธํ•™, ์‚ฌํšŒ๊ณผํ•™, ์ž์—ฐ๊ณผํ•™, ์‘์šฉ๊ณผํ•™, ์˜ˆ์ˆ ๏ฝฅ์ฒด์œก) ์— ๋”ฐ๋ผ ๋ถ„์„ํ•œ ๊ฒฐ๊ณผ ์ „์ฒด ํ•ต์‹ฌ์—ญ๋Ÿ‰์€ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•œ ์ฐจ์ด๊ฐ€ ๋‚˜ํƒ€๋‚˜์ง€ ์•Š์•˜์œผ๋‚˜, ์ „๋ฌธ์—ญ๋Ÿ‰์— ์žˆ์–ด ์˜ˆ์ˆ ๏ฝฅ์ฒด์œก ์ „๊ณต ํ•™์ƒ๋“ค์˜ ํ•ต์‹ฌ์—ญ๋Ÿ‰์ด ์ž์—ฐ๊ณผํ•™ ์ „๊ณต ํ•™์ƒ์˜ ํ•ต์‹ฌ์—ญ๋Ÿ‰๋ณด๋‹ค ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•˜๊ฒŒ ๋†’์•˜๊ณ , ์†Œํ†ต์—ญ๋Ÿ‰์— ์žˆ์–ด ์ธ๋ฌธํ•™ ์ „๊ณต ํ•™์ƒ๋“ค์˜ ํ•ต์‹ฌ์—ญ๋Ÿ‰์ด ์ž์—ฐ๊ณผํ•™ ์ „๊ณต ํ•™์ƒ์˜ ํ•ต์‹ฌ์—ญ๋Ÿ‰๋ณด๋‹ค ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•˜๊ฒŒ ๋†’์•˜๋‹ค. 4๊ฐœ ํ•™๋…„๋ณ„ ์ „์ฒด ํ•ต์‹ฌ์—ญ๋Ÿ‰ ์ˆ˜์ค€์€ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•œ ์ฐจ์ด๊ฐ€ ๋‚˜ํƒ€๋‚˜์ง€ ์•Š์•˜์œผ๋‚˜, ํ•ต์‹ฌ์—ญ๋Ÿ‰๋ณ„๋กœ ๋ถ„์„ํ•  ๊ฒฝ์šฐ ์ฐฝ์˜์œตํ•ฉ์—ญ๋Ÿ‰๊ณผ ์‹œ๋ฏผ์˜์‹์—์„œ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•œ ์ฐจ์ด๊ฐ€ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์„ฑ๋ณ„์— ๋”ฐ๋ผ ๋ถ„์„ํ•œ ๊ฒฐ๊ณผ ์ „์ฒด ํ•ต์‹ฌ์—ญ๋Ÿ‰์€ ๋‚จํ•™์ƒ์ด ์—ฌํ•™์ƒ๋ณด๋‹ค ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•˜๊ฒŒ ๋†’์•˜๊ณ (t=8.49, p<0.001), ํ•ต์‹ฌ์—ญ๋Ÿ‰๋ณ„๋กœ ๋ถ„์„ํ•  ๊ฒฝ์šฐ '์ฐฝ์˜์œตํ•ฉ์—ญ๋Ÿ‰'๊ณผ ์ „๋ฌธ์—ญ๋Ÿ‰, ํ˜‘์—…์—ญ๋Ÿ‰์— ์žˆ์–ด ๋‚จํ•™์ƒ์ด ์—ฌํ•™์ƒ๋ณด๋‹ค ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•˜๊ฒŒ ๋†’๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์•„์šธ๋Ÿฌ ์ „์ฒด ํ•ต์‹ฌ์—ญ๋Ÿ‰์— ๋Œ€ํ•œ ์ž ์žฌํ”„๋กœํŒŒ์ผ๋ถ„์„์„ ์‹ค์‹œํ•œ ๊ฒฐ๊ณผ ์šฐ์ˆ˜, ๋ณดํ†ต, ๋ฏธํก์˜ 3๊ฐœ ์ง‘๋‹จ์œผ๋กœ ๋ถ„๋ฅ˜๋˜์—ˆ๊ณ , ํ•™๋ฌธ๋ถ„์•ผ๋ณ„ ๋ฐ ์„ฑ๋ณ„์— ๋”ฐ๋ฅธ ์ง‘๋‹จ๋ณ„ ๋ถ„ํฌ์—๋Š” ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•œ ์ฐจ์ด๊ฐ€ ๋‚˜ํƒ€๋‚ฌ๊ณ , ํ•™๋…„์— ๋”ฐ๋ฅธ ์ง‘๋‹จ๋ณ„ ๋ถ„ํฌ ์ฐจ์ด๋Š” ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•˜์ง€ ์•Š์•˜๋‹ค. ์ด ์—ฐ๊ตฌ์—์„œ ๊ฐœ๋ฐœํ•œ K๋Œ€ํ•™๊ต ํ•™์ƒ์šฉ ํ•ต์‹ฌ์—ญ๋Ÿ‰ ์ง„๋‹จ๋„๊ตฌ๋Š” ์–‘ํ˜ธํ•œ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ์œผ๋‚˜ ๊ฐœ๋ฐœํ•œ ์ง„๋‹จ๋„๊ตฌ๊ฐ€ ์ž๊ธฐ๋ณด๊ณ ์‹ ์ฒ™๋„์ด๊ณ  ๊ฒ€์‚ฌ์— ์‘ํ•œ ํ•™์ƒ ์ˆ˜๊ฐ€ ๋‹ค์†Œ ์ œํ•œ์ ์ด์—ˆ๋‹ค๋Š” ์  ๋“ฑ์—์„œ ๊ฒฐ๊ณผ์˜ ํ•ด์„๊ณผ ์ผ๋ฐ˜ํ™”์— ์œ ์˜ํ•  ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ํ–ฅํ›„ ๋Œ€ํ•™์ƒ๋“ค์˜ ํ•ต์‹ฌ์—ญ๋Ÿ‰์„ ์ง„๋‹จํ•จ์— ์žˆ์–ด์„œ ๊ด€์ฐฐํ˜•์ด๋‚˜ ์ˆ˜ํ–‰ํ˜• ์ฒ™๋„๋ฅผ ํ™œ์šฉํ•˜๋Š” ๋“ฑ ์ง„๋‹จ๋ฐฉ์‹์„ ๋‹ค์–‘ํ™”ํ•˜๊ณ , ํ•ต์‹ฌ์—ญ๋Ÿ‰๊ณผ ๊ทธ ์ง„๋‹จ์˜ ์ค‘์š”์„ฑ ๋“ฑ์— ๋Œ€ํ•œ ํ™๋ณด๋ฅผ ๊ฐ•ํ™”ํ•˜๊ฑฐ๋‚˜ ์ฐธ์—ฌ์— ๋”ฐ๋ฅธ ์ธ์„ผํ‹ฐ๋ธŒ๋ฅผ ์ œ๊ณตํ•˜๋Š” ๋“ฑ ๋” ๋งŽ์€ ํ•™์ƒ๋“ค์ด ์‘๋‹ตํ•  ์ˆ˜ ์žˆ๋„๋ก ๋…ธ๋ ฅํ•œ๋‹ค๋ฉด, ํ•ด๋‹น ๋Œ€ํ•™์˜ ์—ญ๋Ÿ‰๊ธฐ๋ฐ˜ ๊ต์œก์˜ ํšจ๊ณผ๋ฅผ ๋ณด๋‹ค ์ข…ํ•ฉ์ ์ด๊ณ  ์ฒด๊ณ„์ ์œผ๋กœ ํŒŒ์•…ํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์ด๋‹ค.โ… . ์„œ๋ก  1 1. ์—ฐ๊ตฌ์˜ ํ•„์š”์„ฑ ๋ฐ ๋ชฉ์  1 2. ์—ฐ๊ตฌ ๋ฌธ์ œ 4 โ…ก. ์ด๋ก ์  ๋ฐฐ๊ฒฝ 5 1. ๋Œ€ํ•™์ƒ์˜ ํ•ต์‹ฌ์—ญ๋Ÿ‰ 5 ๊ฐ€. ํ•ต์‹ฌ์—ญ๋Ÿ‰ 5 ๋‚˜. ๋Œ€ํ•™์ƒ์˜ ํ•ต์‹ฌ์—ญ๋Ÿ‰ 18 ๋‹ค. K๋Œ€ํ•™๊ต์˜ ํ•ต์‹ฌ์—ญ๋Ÿ‰ 20 2. ๋Œ€ํ•™์ƒ ํ•ต์‹ฌ์—ญ๋Ÿ‰ ์ง„๋‹จ๋„๊ตฌ 24 ๊ฐ€. ๊ตญ๋‚ด ์ฃผ์š” ๋Œ€ํ•™๊ต์˜ ํ•ต์‹ฌ์—ญ๋Ÿ‰๊ณผ ์ง„๋‹จ๋„๊ตฌ 24 ๋‚˜. ์ƒ์• ์—ญ๋Ÿ‰ ๊ด€์ ์—์„œ ๋Œ€ํ•™์ƒ ๋Œ€์ƒ ํ•ต์‹ฌ์—ญ๋Ÿ‰ ์ง„๋‹จ๋„๊ตฌ 29 โ…ข. ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• ๋ฐ ์ ˆ์ฐจ 33 1. ์—ฐ๊ตฌ ๋Œ€์ƒ 33 ๊ฐ€. ์ธก์ •๋„๊ตฌ ๊ฐœ๋ฐœ์„ ์œ„ํ•œ ์˜ˆ๋น„๊ฒ€์‚ฌ ๋Œ€์ƒ 33 ๋‚˜. ํ•ต์‹ฌ์—ญ๋Ÿ‰ ์ง„๋‹จ์„ ์œ„ํ•œ ๋ณธ๊ฒ€์‚ฌ ๋Œ€์ƒ 34 ๋‹ค. ๋ณ€๋ณ„ํƒ€๋‹น๋„ ๊ฒ€์ฆ์„ ์œ„ํ•œ K-CESA ๋Œ€์ƒ 35 2. ์—ฐ๊ตฌ์ ˆ์ฐจ 36 3. ์ž๋ฃŒ ๋ถ„์„ ๋ฐฉ๋ฒ• 39 โ…ฃ. ๋Œ€ํ•™์ƒ์šฉ ํ•ต์‹ฌ์—ญ๋Ÿ‰ ์ง„๋‹จ๋„๊ตฌ ๊ฐœ๋ฐœ ๋ฐ ํƒ€๋‹นํ™” 41 1. K๋Œ€ํ•™๊ต ํ•™์ƒ์šฉ ํ•ต์‹ฌ์—ญ๋Ÿ‰ ์ง„๋‹จ๋„๊ตฌ ๊ฐœ๋ฐœ 41 ๊ฐ€. ์ด๋ก ์  ํƒ์ƒ‰์„ ํ†ตํ•œ ํ•˜์œ„์˜์—ญ ์„ค์ • ๋ฐ ์ดˆ๊ธฐ๋ฌธํ•ญ ๊ฐœ๋ฐœ 43 ๋‚˜. ์ „๋ฌธ๊ฐ€ํ˜‘์˜ํšŒ๋ฅผ ํ†ตํ•œ ๋‚ด์šฉํƒ€๋‹น์„ฑ ๊ฒ€ํ†  ๋ฐ ์˜ˆ๋น„๋ฌธํ•ญ ์„ ์ • 51 ๋‹ค. ์˜ˆ๋น„๊ฒ€์‚ฌ ๊ฒฐ๊ณผ ๋ถ„์„์„ ํ†ตํ•œ ๋ณธ๊ฒ€์‚ฌ ๋ฌธํ•ญ ์„ ์ • 63 2. ๋Œ€ํ•™์ƒ ํ•ต์‹ฌ์—ญ๋Ÿ‰ ์ง„๋‹จ๋„๊ตฌ ํƒ€๋‹นํ™” 76 ๊ฐ€. ๋‚ด์šฉํƒ€๋‹น๋„ 76 ๋‚˜. ๊ตฌ์ธํƒ€๋‹น๋„ 78 ๋‹ค. ๋ณ€๋ณ„ํƒ€๋‹น๋„ ๊ฒ€์ฆ 91 ๋ผ. ์‹ ๋ขฐ๋„ 96 โ…ค. ๋Œ€ํ•™์ƒ ํ•ต์‹ฌ์—ญ๋Ÿ‰ ์ˆ˜์ค€ 97 1. K๋Œ€ํ•™๊ต ํ•ต์‹ฌ์—ญ๋Ÿ‰์˜ ์ „๋ฐ˜์  ์ˆ˜์ค€ 97 ๊ฐ€. ๊ธฐ์ˆ ํ†ต๊ณ„ ๋ถ„์„ 97 ๋‚˜. ํ•ต์‹ฌ์—ญ๋Ÿ‰ ๊ฐ„์˜ ์ƒ๊ด€๋ถ„์„ 99 2. ์‘๋‹ต์ž ํŠน์„ฑ๋ณ„ ํ•ต์‹ฌ์—ญ๋Ÿ‰ ์ˆ˜์ค€์˜ ์ฐจ์ด 100 ๊ฐ€. ํ•™๋ฌธ๋ถ„์•ผ๋ณ„ ํ•ต์‹ฌ์—ญ๋Ÿ‰ ์ˆ˜์ค€ ์ฐจ์ด ๊ฒ€์ฆ 100 ๋‚˜. ํ•™๋…„๋ณ„ ํ•ต์‹ฌ์—ญ๋Ÿ‰ ์ˆ˜์ค€ ์ฐจ์ด ๊ฒ€์ฆ 105 ๋‹ค. ์„ฑ๋ณ„ ํ•ต์‹ฌ์—ญ๋Ÿ‰ ์ˆ˜์ค€ ์ฐจ์ด ๊ฒ€์ฆ 107 3. K๋Œ€ํ•™๊ต ํ•™์ƒ์˜ ํ•ต์‹ฌ์—ญ๋Ÿ‰ ์ˆ˜์ค€ ์ž ์žฌํ”„๋กœํŒŒ์ผ ๋ถ„์„ 109 ๊ฐ€. ์ž ์žฌ์ง‘๋‹จ์˜ ์ˆ˜ 109 ๋‚˜. ์ž ์žฌ์ง‘๋‹จ์˜ ํŠน์„ฑ 112 ๋‹ค. ์‘๋‹ต์ž ํŠน์„ฑ์— ๋”ฐ๋ฅธ ์ž ์žฌ์ง‘๋‹จ์˜ ๋ถ„ํฌ 114 โ…ฅ. ์š”์•ฝ ๋ฐ ๋…ผ์˜ 117 1. ์š”์•ฝ 117 2. ๋…ผ์˜ ๋ฐ ์ œ์–ธ 119 ์ฐธ ๊ณ  ๋ฌธ ํ—Œ 123 [๋ถ€๋ก 1] K๋Œ€ํ•™๊ต ํ•™์ƒ์šฉ ํ•ต์‹ฌ์—ญ๋Ÿ‰ ์ง„๋‹จ๋„๊ตฌ(์ตœ์ข…) 143 [๋ถ€๋ก 2] Mplus๋ฅผ ์ด์šฉํ•œ LPA์˜ ๋ช…๋ น๋ฌธ ์˜ˆ์‹œ 148 [๋ถ€๋ก 3] 2017ํ•™๋…„๋„ ACE+ ์„ ์ • ๋Œ€ํ•™๊ต์˜ ํ•ต์‹ฌ์—ญ๋Ÿ‰ 149 Abstract 161Docto

    ์ฒญ์†Œ๋…„์˜ ์„ธ๊ณ„์‹œ๋ฏผ์„ฑ ๋ฐœ๋‹ฌ๊ณผ์ • ์—ฐ๊ตฌ : ๋Œ€ํ•œ๋ฏผ๊ตญ ์—ฌ์„ฑ๊ฐ€์กฑ๋ถ€ ์ฒญ์†Œ๋…„ ๊ตญ์ œ๊ต๋ฅ˜ํ™œ๋™์˜ ์‚ฌ๋ก€

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› ์‚ฌ๋ฒ”๋Œ€ํ•™ ํ˜‘๋™๊ณผ์ • ๊ธ€๋กœ๋ฒŒ๊ต์œกํ˜‘๋ ฅ์ „๊ณต, 2017. 8. ๊น€ํ˜•๋ ฌ.This study aims to look into the experiences of the youth participating in the International Youth Exchange program in Korea and to analyze how it contributes to their Global Citizenship improvement. To be specific, it first examines what the youth experience in the International Youth Exchange program, looks into what procedures these experiences take in order to formulate their Global Citizenship, and finds out how each of their specific experiences matches with the conceptual elements of Global Citizenship and what this correlation implies. Data were collected from 189 report papers written by the youth participants of Intergovernmental Youth Exchange program performed by The Ministry of Gender Equality and Family in the Republic of Korea from the year of 2008 to 2016, including the contents of daily journals, testimonials, and personal reports, etc. Based on their experience in the context of the youths' participation, it is possible to present a new perspective different from the one of existing researches and reports which has viewed only from the aspects of policy itself or the viewpoint of the planners and operators of the International Youth Exchange programs. In addition, it is possible to present a different insight from existing researches that quantitatively have looked into the effects of the youth's Global Citizenship improvement by participation in International Exchange activitiesthis study uses qualitative research methodology not only to demonstrate the effects of the youth's Global Citizenship improvement but also to explain in depth how the developmental process of their Global Citizenship formation turns out. As a result of the analysis, there has been a pattern of the youths Global Citizenship development which consists of 6 phases: 1) The youth have a world-friendly attitude of expectation and excitement during preparation for their dispatch to a foreign country. 2) They encounter the fundamental and important facts about the host country so that they are able to build an understanding of its history, culture, and the life of the native people during the early phase of their visit. 3) They realize their national and transnational identities and self-reflect on those. 4) They find the local youth important as their peers. 5) They experience the local peoples life and are engaged in their civil activities. 6) They reflect on themselves and try to take action as global citizens in the latter period of this program. In the experience of approaching foreigners in a strange land, the youth reflect upon their identity, find their new self through the process of 'otherization' and objectification, and design their own dreams and futures more specifically as global citizens. Most of these future plans include their commitment to take concrete action to improve themselves to communicate more effectively with people in the world, to understand them more deeply, and to contribute to the global civil society as global citizens.Chapter I. Introduction 1 1.1. Background & Statement of the Problem 1 1.2. Purpose of the Study & Research Questions 3 1.3. Significance of the Study 3 Chapter II. Literature Review 6 2.1. Global Citizenship 6 2.1.1. Background of Global Citizenship 6 2.1.1.1. Development of Global Citizenship 6 2.1.1.2. Similar Concept of Global Citizenship 11 2.1.2. What is Global Citizenship 17 2.1.2.1. Definition 17 2.1.2.2. Elements of Global Citizenship 20 2.2. International Youth Exchange and Global Citizenship 25 2.2.1. The concept of International Youth Exchange 25 2.2.2. The Preceding Research about Global Citizenship in International Youth Exchange Programs 30 2.3. International Youth Exchange in Korea 38 2.3.1. Operation of International Youth Exchange 39 2.3.2. The Intergovernmental Youth Exchange program in Korea 42 Chapter III. Methodology 49 3.1. Research Design 49 3.1.1. Qualitative Methodology 50 3.1.2. Data Collection 51 3.1.3. Data Analysis 52 3.2. Limitation 53 Chapter IV. Finding 54 4.1. During Preparation: Expectation and Excitement 54 4.2. Encountering the Fundamental and Important Facts 57 4.3. Realizing their Identity and Self-reflecting on it 61 4.4. Finding the Peers Important 70 4.5. Experience and Engagement 75 4.6. During the Latter Period: Taking Action 82 Chapter V. Discussion 89 5.1. The Pattern of Developing Global Citizenship 89 5.2. Intercultural Communication 92 Chapter VI. Conclusion 99 6.1. Conclusion 99 6.2. Implications 100 Bibliography 105 ๊ตญ๋ฌธ์ดˆ๋ก 108Maste

    1928~1936๋…„ ๊ฐ€์ฐฝ ์ข…๋ชฉ์„ ์ค‘์‹ฌ์œผ๋กœ

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์Œ์•…๋Œ€ํ•™ ์Œ์•…๊ณผ, 2021. 2. ๊น€์šฐ์ง„.๋ณธ ์—ฐ๊ตฌ๋Š” ์œ ์„ฑ๊ธฐ์Œ๋ฐ˜๊ณผ ๊ฒฝ์„ฑ์ค‘์•™๋ฐฉ์†ก์„ ํ†ตํ•ด ํ™œ๋™ํ–ˆ๋˜ ํ•œ์„ฑ๊ถŒ๋ฒˆ๊ณผ ์กฐ์„ ๊ถŒ๋ฒˆ ์†Œ์† ์—ฌ์„ฑ ์Œ์•…์ธ๋“ค์˜ ๊ฐ€์ฐฝ ์ข…๋ชฉ์„ ํ†ตํ•ด ๊ทธ ์Œ์•… ํ™œ๋™ ์–‘์ƒ์„ ์‚ดํŽด๋ณด๊ณ , ๋‘ ๊ถŒ๋ฒˆ์ด 1928๋…„์—์„œ 1936๋…„์— ๊ฑธ์ณ ํ˜•์„ฑํ•˜์˜€๋˜ ์Œ์•…์  ์„ฑํ–ฅ์„ ๊ตฌ๋ช…(็ฉถๆ˜Ž)ํ•œ ๊ฒƒ์ด๋‹ค. ํ•œ์„ฑ๊ถŒ๋ฒˆ์€ ์ •๊ฐ€๋ฅ˜ ์•…๊ณก ์ค‘์—์„œ๋Š” ์‹œ์กฐ ๊ฐ€์ฐฝ์ด ์ฃผ๋ฅผ ์ด๋ฃจ๊ณ , ์‚ฌ๋‹นํŒจ ์†Œ๋ฆฌ๋ฅผ ์ด์–ด๋ฐ›์€ ๊ฒฝ์„œ๋„ ์žก๊ฐ€๋ฅผ ์ฃผ๋กœ ๊ฐ€์ฐฝํ•˜์˜€๋‹ค. ์‹ค์ œ ์•…๊ณก์˜ ๊ฐ€์ฐฝ์— ์žˆ์–ด, ์ •๊ฐ€๋ฅ˜ ์•…๊ณก์€ ์†์†Œ๋ฆฌ์˜ ์‚ฌ์šฉ์ด ์ œํ•œ์ ์ด๋ฉฐ ๋น„๊ต์  ํญ์ด ๋„“์€ ์„œ๋„์†Œ๋ฆฌ ์š”์„ฑ์„ ์‚ฌ์šฉํ•˜์˜€๋‹ค. ์ž”๊ฐ€๋ฝ์˜ ์ถœํ˜„์ด ์ ์—ˆ๊ณ  ์Œ์˜ ์ง€์†์— ์žˆ์–ด ์งง์€ ๋ฐ•์œผ๋กœ ๋Š์–ด๋‚ด๋“ฏ์ด ํ‘œํ˜„ํ•˜๋Š” ๊ฒฝํ–ฅ์„ ๋ณด์—ฌ ์”ฉ์”ฉํ•˜๊ณ  ๊ฑฐ์นœ ์Œ์ƒ‰์œผ๋กœ ํ‘œํ˜„๋˜์—ˆ๋‹ค. ์žก๊ฐ€๋ฅ˜ ์•…๊ณก์˜ ๊ฐ€์ฐฝ์€ ํ†ต์†์ ์ธ ์‚ฌ์„ค์„ ์‚ฌ์šฉํ•˜๊ณ  ๋‹ค์–‘ํ•œ ์ถœํ˜„์Œ๊ณผ ์ ˆ ๋งˆ๋‹ค ํ›„๋ ด์˜ ์„ ์œจ์ด ๋ณ€ํ™”ํ•œ ๊ฒƒ์„ ํ†ตํ•ด ์žก๊ฐ€๋ฅ˜ ์•…๊ณก์˜ ์œ ์—ฐํ•œ ๊ฐ€์ฐฝ์ด ๊ฐ€๋Šฅํ•  ์ˆ˜ ์žˆ์„ ๋งŒํผ ๋Šฅ์ˆ™ํ•œ ์—ญ๋Ÿ‰์„ ๊ฐ–์ถ”๊ณ  ์žˆ๋˜ ๊ฒƒ์œผ๋กœ ๋ณด์ธ๋‹ค. ์กฐ์„ ๊ถŒ๋ฒˆ์€ ์ •๊ฐ€๋ฅ˜ ์•…๊ณก ์ค‘์—์„œ๋Š” ๊ฐ€๊ณก ๊ฐ€์ฐฝ์ด ์ฃผ๋ฅผ ์ด๋ฃจ๊ณ , ๋šœ๋ ทํ•œ ์ง€์—ญ์  ์‹œ๊น€์ƒˆ๊ฐ€ ๋“œ๋Ÿฌ๋‚˜๋Š” ์žก๊ฐ€๋ฅ˜ ์•…๊ณก์„ ์ฃผ๋กœ ๊ฐ€์ฐฝํ•˜์˜€๋‹ค. ์‹ค์ œ ๊ฐ€์ฐฝ์„ ํ†ตํ•˜์—ฌ ๋‚˜ํƒ€๋‚œ ์กฐ์„ ๊ถŒ๋ฒˆ ์ •๊ฐ€๋ฅ˜ ์•…๊ณก์€ ์†์†Œ๋ฆฌ์˜ ์‚ฌ์šฉ์ด ๋นˆ๋ฒˆํ•˜๊ณ  ์ž์œ ๋กœ์› ์œผ๋ฉฐ ํญ์ด ์ข์€ ์ •๊ฐ€ ์š”์„ฑ์„ ์ฃผ๋กœ ์‚ฌ์šฉํ•˜์˜€๋‹ค. ๊ธด ํ˜ธํก์œผ๋กœ ํ•˜๋‚˜์˜ ์Œ์„ ์ง€์†ํ•˜๋ฉฐ ์ธ์ ‘ํ•œ ์Œ์„ ํ†ตํ•œ ๋‹ค์–‘ํ•œ ์ž”๊ฐ€๋ฝ์ด ์ถœํ˜„ํ•˜์—ฌ ๋น„๊ต์  ์œ ๋ คํ•˜๊ณ  ์„ฌ์„ธํ•˜๊ฒŒ ํ‘œํ˜„๋˜์—ˆ๋‹ค. ์žก๊ฐ€๋ฅ˜ ์•…๊ณก์€ ํ•œ์‹œ์˜ ์–ด๊ตฌ๋ฅผ ์ฐจ์šฉํ•œ ์‚ฌ์„ค์„ ์‚ฌ์šฉํ•˜๊ณ , ์ œํ•œ์ ์ธ ์Œ์˜ ์ถœํ˜„๊ณผ ๋ฐ•์ž ๋‹จ์œ„๋กœ ์งง๊ฒŒ ๊ตฌ๋ถ„๋˜๋Š” ๋ฐ•์˜ ๋ช…ํ™•์„ฑ์œผ๋กœ ์ธํ•ด ๋‹จ์กฐ๋กญ๊ณ  ๊ฐ„๊ฒฐํ•˜๊ฒŒ ํ‘œํ˜„๋˜์—ˆ๋‹ค. ๋˜ํ•œ, ํ•œ์„ฑ๊ถŒ๋ฒˆ์—์„œ๋Š” ๋‚˜ํƒ€๋‚˜์ง€ ์•Š๋Š” ์…ˆ์—ฌ๋ฆผ๊ณผ ๋‹ค์ด๋‚ด๋ฏน์ด ์ •๊ฐ€์™€ ์žก๊ฐ€๋ฅ˜ ์Œ์•…์— ๋ชจ๋‘ ๋‚˜ํƒ€๋‚œ ์ ์„ ํ†ตํ•ด ์Œ์ƒ‰๊ณผ ์Œํ–ฅ์„ ํ†ตํ•œ ์Œ์•…์  ๋ณ€ํ™”๋ฅผ ์ถ”๊ตฌํ–ˆ์œผ๋ฉฐ, ์ด์™€ ๊ฐ™์€ ์Œ์•…์  ํ‘œํ˜„์— ๋†’์€ ๊ธฐ๋Ÿ‰์„ ๊ฐ–์ถ”๊ณ  ์žˆ๋˜ ๊ฒƒ์œผ๋กœ ๋ณด์ธ๋‹ค. ์ด๋ฅผ ํ†ตํ•ด ๋งค์ฒด์˜ ๋ฐœ๋‹ฌ๋กœ ์ธํ•ด ์Œ์•… ์œ ํ†ต ๊ณผ์ •์ด ๋ณ€ํ™”ํ–ˆ๋˜ 1928๋…„๋ถ€ํ„ฐ 1936๋…„์—๋Š” ๊ด€๊ธฐ ์ถœ์‹ ์œผ๋กœ์„œ ๊ถ์ค‘ ๊ฐ€๋ฌด ๋Šฅํ•˜์—ฌ ์ •ํ†ต ๊ถ์ค‘ ๋ฌธํ™”๋ฅผ ๊ณ„์Šนํ–ˆ์„ ๊ฒƒ์œผ๋กœ ์•Œ๋ ค์ง„ ํ•œ์„ฑ๊ถŒ๋ฒˆ๊ณผ ์‚ผํŒจ์™€ ํ–ฅ๊ธฐ๋ฅผ ์ค‘์‹ฌ์œผ๋กœ ํ˜•์„ฑ๋˜์–ด ์‹œ์ • ๋ฌธํ™”์— ๋Šฅํ•˜์˜€์„ ๊ฒƒ์œผ๋กœ ์•Œ๋ ค์ง„ ์กฐ์„ ๊ถŒ๋ฒˆ์— ๊ด€ํ•œ ๊ธฐ์กด์˜ ์„ ํ–‰์—ฐ๊ตฌ ๊ฒฐ๊ณผ์™€๋Š” ์ƒ์ดํ•œ ์Œ์•…์  ์„ฑํ–ฅ์„ ๊ฐ–์ถ”๊ณ  ์žˆ์—ˆ์Œ์„ ์•Œ ์ˆ˜ ์žˆ๋‹ค.This study will examine the music activities of the two groups based on the songs of Hanseong-Gwonbeon and J oseon-Gwonbeon, who performed on Phonographic Record and Gyeongseong Broadcasting Station(JODK). This aims to reveal the musical tendencies that two Gwonbeons formed between 1928 and 1936. First of all, Hanseong-Gwonbeon mainly sang the Sijo among J eongGa genreโ€™s music, and sang the traditional J apga of Seoul and its surroundings, which inherited the sound of Sadang-pae(a traditional singing group that was active in the 19th century). - 156 - In the actual song, J eongGa genre music was expressed in a bolder and thicker style than a delicate musical expression. J apga genre music used popular lyrics and more diverse notes than J oseon-Gwonbeon. This shows that the Hanseong had higher skills in popular and fashionable music. Next, J oseon-Gwonbeon mainly sang the song, which was Gagok mainly of the J eongGa genreโ€™s music, and mainly sang the J apga genre music, which clearly revealed the local expression. In the actual song, J eong Ga genre music was highly professional with delicate musical expressions. Chinese characters were also used in J apga genre music, or singing methods such as J eong Ga genreโ€™s music. Therefore, J oseon-Gwonbeon was better at expressing traditional pungryu-bang vocal music. This study revealed that from 1928 to 1936, these two groups had a different musical tendency from the previously known Hanseong-Gwonbeon and J oseon-GwonbeonI. ์„œ ๋ก  1 1. ์—ฐ๊ตฌ๋ชฉ์  ๋ฐ ํ•„์š”์„ฑ 1 2. ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  4 3. ์—ฐ๊ตฌ ๋ฒ”์œ„ ๋ฐ ๋ฐฉ๋ฒ• 7 II. ๋งค์ฒด์— ๋”ฐ๋ฅธ ๊ถŒ๋ฒˆ ๋ณ„ ์Œ์•… ํ™œ๋™ ์–‘์ƒ 13 1. ์œ ์„ฑ๊ธฐ์Œ๋ฐ˜ 13 1) ํ•œ์„ฑ, ์กฐ์„ ๊ถŒ๋ฒˆ์˜ ์ •๊ฐ€๋ฅ˜ ์•…๊ณก ์ถœ๋ฐ˜ ํ˜„ํ™ฉ 13 2) ํ•œ์„ฑ, ์กฐ์„ ๊ถŒ๋ฒˆ์˜ ์žก๊ฐ€๋ฅ˜ ์•…๊ณก ์ถœ๋ฐ˜ ํ˜„ํ™ฉ 25 2. ๊ฒฝ์„ฑ์ค‘์•™๋ฐฉ์†ก๊ตญ 46 1) ํ•œ์„ฑ, ์กฐ์„ ๊ถŒ๋ฒˆ์˜ ์ •๊ฐ€๋ฅ˜ ์•…๊ณก ๋ฐฉ์†ก ํ™œ๋™ 47 2) ํ•œ์„ฑ, ์กฐ์„ ๊ถŒ๋ฒˆ์˜ ์žก๊ฐ€๋ฅ˜ ์•…๊ณก ๋ฐฉ์†ก ํ™œ๋™ 58 3. ์†Œ๊ฒฐ๋ก  78 III. ๊ถŒ๋ฒˆ ๋ณ„ ์Œ์•…์žฅ๋ฅด์˜ ์„ฑ๊ฒฉ 81 1. ์ •๊ฐ€๋ฅ˜ ์•…๊ณก 81 1) ํ•œ์„ฑ, ์กฐ์„ ๊ถŒ๋ฒˆ์˜ &lt;๊ถŒ์ฃผ๊ฐ€&gt; ์—ฐํ–‰ ์–‘์ƒ 82 2) ํ•œ์„ฑ, ์กฐ์„ ๊ถŒ๋ฒˆ์˜ &lt;๊ถŒ์ฃผ๊ฐ€&gt; ๋น„๊ต 86 2. ์žก๊ฐ€๋ฅ˜ ์•…๊ณก 110 1) ํ•œ์„ฑ, ์กฐ์„ ๊ถŒ๋ฒˆ์˜ &lt;๊ฐœ์„ฑ๋‚œ๋ด‰๊ฐ€&gt; ์—ฐํ–‰ ์–‘์ƒ 110 2) ํ•œ์„ฑ, ์กฐ์„ ๊ถŒ๋ฒˆ์˜ &lt;๊ฐœ์„ฑ๋‚œ๋ด‰๊ฐ€&gt; ๋น„๊ต 113 3. ์†Œ๊ฒฐ๋ก  138 IV. ํ•œ์„ฑ๊ถŒ๋ฒˆ๊ณผ ์กฐ์„ ๊ถŒ๋ฒˆ์˜ ์Œ์•…์  ์„ฑํ–ฅ 143 V. ๊ฒฐ๋ก  147 ์ฐธ๊ณ ๋ฌธํ—Œ 151Maste

    ์™ธ๋กœ์›€์ด ์‚ฌํšŒ์  ์ž๊ธฐํšจ๋Šฅ๊ฐ์„ ํ†ตํ•ด ์‚ฌํšŒ๋ถˆ์•ˆ์— ๋ฏธ์น˜๋Š” ๊ฐ„์ ‘ํšจ๊ณผ

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์‚ฌํšŒ๊ณผํ•™๋Œ€ํ•™ ์‹ฌ๋ฆฌํ•™๊ณผ, 2018. 2. ๊ถŒ์„๋งŒ.Because of the changes in contemporary society, loneliness has become an increasingly important social issue that affects both mental and physical health. Although loneliness appears to have a particularly strong connection to social anxiety, the pathway from loneliness to social anxiety is poorly understood. Thus, this study aimed to not only investigate a pathway between loneliness and social anxiety but also examine how social self-efficacy mediates their relationship. Although a direct relationship between loneliness and social self-efficacy has not been examined in detail, the close relationship between the two variables has been indicated in several studies. Moreover, since the impact social self-efficacy has on social anxiety is evident from previous studies, social self-efficacy is expected to play a role in mediating the pathway between loneliness and social anxiety. In Study 1, the indirect effect of loneliness on social anxiety was examined by using self-report. Independent impacts loneliness has on subtypes of social anxiety were tested through various scales (SPS-6/ SIAS-6, SAQ). Data analysis showed that, while loneliness showed significant indirect effects to all subtype of social anxiety, social interaction anxiety, compared to other facets of social anxiety, was more strongly associated with loneliness. In Study 2, an experimental study was designed to examine the causal effects of loneliness on social anxiety. Although existing studies have indicated the impact of loneliness on social anxiety, the relationship between loneliness and social anxiety is still vague. In accordance with previous studies, this study used loneliness manipulation in a controlled environment to examine the causal role of loneliness in social anxiety. Mediation variable was social self-efficacy as it was in Study 1. The result showed that reduced loneliness predicts higher social self-efficacy, which in turn lowers social anxiety. However, increased loneliness affected neither social self-efficacy nor social anxiety. In bootstrapping analysis, the indirect effect of loneliness on social anxiety was significant at 95% confidence level. This study contributes to the understanding of the indirect role loneliness has on social anxiety and specifies the pathway using survey and experimental approach. Implications and limitations are also discussed along with suggestions for future studies.Introduction 1 Social Isolation and Loneliness 3 Loneliness and Mental Disorders 4 Loneliness and Social Anxiety Disorder 6 Purpose of the Present Study 12 Study 1 15 Method 17 Results 21 Discussion 27 Study 2 29 Method 31 Results 38 Discussion 45 General Discussion 49 References 53 Appendix 67 Abstract in Korean 81Maste

    Anti-prostate cancer effect of GV1001, a novel GnRHR ligand

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์•ฝํ•™๋Œ€ํ•™ ์•ฝํ•™๊ณผ, 2019. 2. ๊ฐ•๊ฑด์šฑ.GV1001, a 16-amino acid fragment of the human telomerase reverse transcriptase catalytic subunit (hTERT), has been developed as an injectable formulation of cancer vaccine. Here, we revealed for the first time that GV1001 is a novel ligand for gonadotropin-releasing hormone receptor (GnRHR). Binding of GV1001 to GnRHR stimulated the Gฮฑs-coupled cAMP signaling pathway and antagonized Gฮฑq-coupled Ca2+ release by leuprolide acetate (LA), a GnRHR agonist. We then tested whether GV1001 has an inhibitory effect on tumor growth of LNCaP cells, androgen receptorโ€“positive human prostate cancer (PCa) cells. GV1001 significantly inhibited tumor growth and induced apoptosis in LNCaP-implanted xenografts. Interestingly, mRNA expression of matrix metalloproteinase2 and matrix metalloproteinase9 was suppressed by GV1001, but not by LA. Moreover, GV1001 inhitbited the proliferaion and migration of PCa cells and induced GnRHR-dependent apoptosis. Inhibition of androgen receptor (AR) activity or androgen deficiency is known to cause resistance of prostate cancer to anti-androgen agents. GV1001 treatment increased both cAMP/PKA-dependent AR phosphorylation and androgen-response element (ARE)-mediated transcriptional activity in LNCaP cells. The enhanced AR activation by GV1001 suppressed the cell migration ability of LNCaP cells. Although AR activity is generally considered as a major mediator of PCa growth, interaction of AR with specific coregulators can determine the fate of PCa progression such as metastasis and chemoresistance. Among diverse AR coregulators, Gene Expression Ominibus (GEO) analyses showed that YAP1 was identified as a key gene for metastasis of prostate cancer. cAMP/PKA-dependent Ser-127 phosphorylation and the subsequent ubiquitination of YAP1 were enhanced by GV1001 in LNCaP cells. Moreover, GV1001-induced YAP1 degradation inhibited its binding to AR and consequently suppressed the expression of downstream target genes of YAP1. Inhibitory effect of cell migration by GV1001 was completely reversed by overexpression of YAP5SA, constitutive active form of YAP1. Spleen-liver metastasis mouse model confirmed that liver metastasis of PCa cells implanted in spleen was significantly inhibited by GV1001 injection. Taken together, our data reveal that GV1001 is a novel ligand of GnRHR and shows anti-cancer efficacy in PCa.ํ•ญ์•” ๋ฐฑ์‹ ์ธ GV1001์€ ์ธ๊ฐ„ ํ…”๋กœ๋จธ๋ผ์•„์ œ ์—ญ์ „์‚ฌํšจ์†Œ ์ด‰๋งค ์†Œ๋‹จ์œ„(hTERT)์˜ ์ผ๋ถ€ 16๊ฐœ ์•„๋ฏธ๋…ธ์‚ฐ์œผ๋กœ ๊ตฌ์„ฑ๋œ ํŽฉํƒ€์ด๋“œ๋กœ ์ธ์ฒด ๋ฉด์—ญ๊ณ„ ์ค‘ ์•”์„ธํฌ ์„ ํƒ์ ์ธ T์„ธํฌ ๊ธฐ๋Šฅ์„ ๊ฐ•ํ™”์‹œํ‚ค๋Š” cancer vaccine์ด๋‹ค. ์ตœ๊ทผ ๋‹ค์–‘ํ•œ ์•”์ข…์— ๋Œ€ํ•ด GV1001์ด ํ•ญ์•” ํšจ๋Šฅ์„ ๊ฐ–๋Š”๋‹ค๋Š” ์—ฐ๊ตฌ์™€ ์ž„์ƒ ๊ฒฐ๊ณผ๊ฐ€ ๋ณด๊ณ ๋˜์–ด ์žˆ์ง€๋งŒ, ์•„์ง๊นŒ์ง€ ํ•ญ์•”์ œ๋กœ์จ ๊ทธ ๊ธฐ๋Šฅ๊ณผ ๊ธฐ์ „์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋Š” ๋ถ€์กฑํ•˜๋‹ค. ์ „๋ฆฝ์„ ์•”์€ ๋‚จ์„ฑ์—์„œ ๊ฐ€์žฅ ๋งŽ์ด ๋ฐœ๋ณ‘ํ•˜๋Š” ์•”์ข…์ด๋ฉฐ, ์•”์— ์˜ํ•œ ์‚ฌ๋ง์˜ ์ฃผ๋œ ์›์ธ์ด๋‹ค. ์ „๋ฆฝ์„ ์•” ์น˜๋ฃŒ ์š”๋ฒ•์œผ๋กœ๋Š” ํ˜ธ๋ฅด๋ชฌ ์š”๋ฒ•, ์ „๋ฆฝ์„ ์ ์ œ์ˆ , ๋ฐฉ์‚ฌ์„  ์น˜๋ฃŒ ๋ฐ ํ•ญ์•”ํ™”ํ•™์š”๋ฒ•์ด ์‚ฌ์šฉ๋˜๋Š”๋ฐ ํŠนํžˆ ํ˜ธ๋ฅด๋ชฌ ์š”๋ฒ•์ด ๋‹จ๋… ํ˜น์€ ๋ณ‘์šฉ์œผ๋กœ ๋‹ค๋ฅธ ์น˜๋ฃŒ ์š”๋ฒ•๊ณผ ํ•จ๊ป˜ ์‚ฌ์šฉ๋œ๋‹ค. ์ „๋ฆฝ์„ ์•”์˜ ์น˜๋ฃŒ๊ฐ€ ์–ด๋ ค์šด ์ด์œ ๋Š” ํ•ญ์•”์ œ ์ €ํ•ญ์„ฑ ์ „๋ฆฝ์„ ์•”์œผ๋กœ ์‰ฝ๊ฒŒ ์•…์„ฑํ™”๋˜๊ธฐ ๋•Œ๋ฌธ์ธ๋ฐ, ์•…์„ฑํ™”๊ฐ€ ์ผ์–ด๋‚˜๋ฉด ๋นˆ๋ฒˆํ•œ ์žฌ๋ฐœ๊ณผ ๋น ๋ฅธ ์ „์ด๋กœ ์ธํ•˜์—ฌ ์‚ฌ๋ง๋ฅ ์ด ํฌ๊ฒŒ ๋†’์•„์ง„๋‹ค. ํ˜„์žฌ๊นŒ์ง€ ์ด๋Ÿฌํ•œ ์ „์ด์„ฑ ์ „๋ฆฝ์„ ์•”์— ๋Œ€ํ•œ ์ง„๋‹จ ๋งˆ์ปค์™€ ์น˜๋ฃŒ ์ „๋žต์ด ๋ถ€์กฑํ•œ ์‹ค์ •์ด๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” GV1001์„ GnRH ์ˆ˜์šฉ์ฒด์— ์ž‘์šฉํ•˜๋Š” ์ƒˆ๋กœ์šด ๋ฆฌ๊ฐ„๋“œ๋กœ ์ œ์‹œํ•˜๊ณ , ์•…์„ฑ ์ „๋ฆฝ์„ ์•”์— ์ ์šฉ ๊ฐ€๋Šฅํ•œ ์ƒˆ๋กœ์šด ์น˜๋ฃŒ ์•ฝ์ œ๋กœ ๊ทœ๋ช…ํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ์ฒซ ๋ฒˆ์งธ, GV1001์„ ์ตœ์ดˆ๋กœ GnRH ์ˆ˜์šฉ์ฒด ๋ฆฌ๊ฐ„๋“œ๋กœ์„œ ์ œ์‹œํ•˜๊ณ  ๊ทธ ๊ธฐ๋Šฅ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ๋‘ ๋ฒˆ์งธ, ์ „๋ฆฝ์„ ์•”์˜ ์•…์„ฑํ™” ํ˜•ํƒœ์ธ ์•”์„ธํฌ ์ „์ด์— ๋Œ€ํ•œ GV1001์˜ ๊ธฐ๋Šฅ๊ณผ ๊ธฐ์ „ ํƒ๊ตฌ๋ฅผ ํ†ตํ•œ ์ „๋ฆฝ์„ ์•” ์น˜๋ฃŒ ์š”๋ฒ• ๋ฐœ๊ตด์„ ์—ฐ๊ตฌ ๋ชฉํ‘œ๋กœ ์„ค์ •ํ•˜์˜€๋‹ค. GV1001์˜ ๊ตฌ์กฐ ๋ถ„์„ ๊ฒฐ๊ณผ, ํŽฉํƒ€์ด๋“œ ์„œ์—ด ์ผ๋ถ€๊ฐ€ GnRH ์œ ์‚ฌ์ฒด๋“ค๊ณผ ์ค‘์ฒฉ๋˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์ด ์„œ์—ด์€ GnRH ์œ ์‚ฌ์ฒด๊ฐ€ ์ˆ˜์šฉ์ฒด์™€ ๊ฒฐํ•ฉํ•˜๋Š” ๋ฐ์— ํ•ต์‹ฌ์ ์ธ ์—ญํ• ์„ ๋‹ด๋‹นํ•˜๊ณ  ์žˆ์„ ๊ฒƒ์œผ๋กœ ์˜ˆ์ธก๋˜์–ด GV1001์ด GnRH ์ˆ˜์šฉ์ฒด์™€ ๊ฒฐํ•ฉํ•˜๋Š”์ง€ ํ™•์ธํ•˜์˜€๊ณ , ๊ฒฐ๊ณผ์ ์œผ๋กœ GnRH ์ˆ˜์šฉ์ฒด์™€ ๊ฒฐํ•ฉํ•˜์—ฌ ํ•˜์œ„ ์‹ ํ˜ธ ์ „๋‹ฌ์„ ๋งค๊ฐœํ•˜๊ณ  ์žˆ์Œ์„ ๊ด€์ฐฐํ•˜์˜€๋‹ค. ๋˜ํ•œ, ๋Œ€ํ‘œ์ ์ธ GnRH ์œ ์‚ฌ์ฒด์ธ leuprolide acetate(LA)์™€ ๋น„๊ตํ•˜์˜€์„ ๋•Œ, LA ์ฒ˜์น˜์— ์˜ํ•˜์—ฌ GnRH ์ˆ˜์šฉ์ฒด ์ฃผ์š” ํ•˜์œ„ ์ „๋‹ฌ ์‹ ํ˜ธ์ธ Gฮฑq-์นผ์Š˜ ๋ถ„๋น„๊ฐ€ ์ฆ๊ฐ€ํ•œ ๋ฐ˜๋ฉด GV1001 ์ฒ˜์น˜์— ์˜ํ•˜์—ฌ ๋ถ€์ฐจ์ ์ธ ํ•˜์œ„ ์ „๋‹ฌ ์‹ ํ˜ธ์ธ Gฮฑs-cAMP ์‹ ํ˜ธ๊ฐ€ ํ™œ์„ฑํ™” ๋˜๋Š” ๊ฒƒ์„ ๊ด€์ฐฐํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. LA์™€ GV1001๋Š” ๋˜ํ•œ ๊ฒฝ์Ÿ์ ์œผ๋กœ ์ƒํ˜ธ ์‹ ํ˜ธ ์ „๋‹ฌ์„ ์–ต์ œํ•˜์˜€์œผ๋ฉฐ, ์ด๋Ÿฌํ•œ ์‹ ํ˜ธ ์ „๋‹ฌ์€ GnRH ์ˆ˜์šฉ์ฒด์— ์˜์กด์ ์œผ๋กœ ๊ด€์ฐฐ๋˜์—ˆ๋‹ค. GV1001์˜ GnRH ์ˆ˜์šฉ์ฒด ๋งค๊ฐœ ์ „๋ฆฝ์„ ์•” ์–ต์ œ ํšจ๊ณผ๋ฅผ ํ‰๊ฐ€ํ•˜๊ธฐ ์œ„ํ•ด ๋™๋ฌผ ์‹คํ—˜๊ณผ ์„ธํฌ ์‹คํ—˜์„ ์ง„ํ–‰ํ•˜์˜€๋‹ค. GV1001์„ ๋ฐ˜๋ณตํ•˜์—ฌ ํˆฌ์—ฌํ–ˆ์„ ๋•Œ, ๋ˆ„๋“œ ๋งˆ์šฐ์Šค์˜ ํ˜ˆ์ค‘ ํ…Œ์Šคํ† ์Šคํ…Œ๋ก  ์ˆ˜์น˜๊ฐ€ ํ˜„์ €ํžˆ ๊ฐ์†Œํ•˜์˜€์œผ๋ฉฐ, ์ •์•ก ์†Œํฌ ๋ฌด๊ฒŒ๊ฐ€ ์œ ์˜ํ•˜๊ฒŒ ๊ฐ์†Œํ•˜์˜€๋‹ค. ๋˜ํ•œ, GV1001 ์ฒ˜์น˜์— ์˜ํ•ด ์ „๋ฆฝ์„ ์•” ์ด์ข… ์ด์‹ ๋ˆ„๋“œ ๋งˆ์šฐ์Šค ๋ชจ๋ธ์—์„œ LNCaP ์„ธํฌ์ฃผ ์ข…์–‘์˜ ๋ถ€ํ”ผ๊ฐ€ ๊ฐ์†Œํ•˜์˜€์œผ๋ฉฐ ์ข…์–‘ ๋‚ด ์„ธํฌ์ž๊ฐ€์‚ฌ๋ฉธ ๋งˆ์ปค์˜ ์œ ๋„์™€ ์„ธํฌ์ฆ์‹ ๋งˆ์ปค์˜ ์–ต์ œ๊ฐ€ ๊ด€์ฐฐ๋˜์—ˆ๋‹ค. ์•”์„ธํฌ ์ „์ด ์œ ๋„ ์ธ์ž์ธ MMP2, MMP9์˜ ์ข…์–‘ ๋‚ด mRNA ๋ฐœํ˜„ ์ˆ˜์ค€์„ ํ‰๊ฐ€ํ•œ ๊ฒฐ๊ณผ GV1001 ์ฒ˜์น˜์— ์˜ํ•ด MMP2, MMP9์˜ mRNA ๋ฐœํ˜„ ์ˆ˜์ค€์ด ์–ต์ œ๋˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์„ธํฌ ์‹คํ—˜์—์„œ GV1001 ์ฒ˜์น˜์— ์˜ํ•ด LNCaP๊ณผ PC-3 ์„ธํฌ์ฃผ ์ฆ์‹์ด ๊ฐ์†Œ๋˜์—ˆ์œผ๋ฉฐ, Transwell-์„ธํฌ ์ด๋™๋Šฅ ํ‰๊ฐ€ ๊ฒฐ๊ณผ์—์„œ๋„ LNCaP๊ณผ PC-3-์„ธํฌ์ฃผ ์ด๋™๋Šฅ์ด ๊ฐ์†Œํ•˜์˜€๋‹ค. ๋˜ํ•œ, LNCaP๊ณผ PC-3 ์„ธํฌ์ฃผ ๋‚ด์˜ ์„ธํฌ์ž๊ฐ€์‚ฌ๋ฉธ ์œ ๋„ ํšจ๊ณผ๊ฐ€ ๊ด€์ฐฐ๋˜์—ˆ๋‹ค. GV1001์˜ ์„ธํฌ์ž๊ฐ€์‚ฌ๋ฉธ ์œ ๋„ ํšจ๊ณผ๋Š” GnRH ์ˆ˜์šฉ์ฒด์— ์˜์กด์ ์œผ๋กœ ๊ด€์ฐฐ๋˜์—ˆ๋‹ค. ์ด๋Ÿฌํ•œ GV1001์˜ ์•”์„ธํฌ ๋ฐœํ˜„-GnRH ์ˆ˜์šฉ์ฒด์— ๋Œ€ํ•œ ์ง์ ‘์ ์ธ ์•”์„ธํฌ ์–ต์ œ ํšจ๊ณผ๊ฐ€ ์ƒ์ฒด ๋‚ด์—์„œ ๊ด€์ฐฐ๋˜๋Š”์ง€ ํ‰๊ฐ€ํ•˜๊ธฐ ์œ„ํ•ด CRISPR/Cas9 ์œ ์ „์ž ํŽธ์ง‘ ์‹œ์Šคํ…œ์„ ๋„์ž…ํ•œ LNCaP ์ „๋ฆฝ์„ ์•” ์„ธํฌ์ฃผ๋ฅผ ๊ตฌ์ถ•ํ•˜์—ฌ ์ด์ข… ์ด์‹ ๋ˆ„๋“œ ๋งˆ์šฐ์Šค ๋ชจ๋ธ์„ ๊ตฌ์ถ•ํ•˜์˜€๋‹ค. ๊ทธ ๊ฒฐ๊ณผ, GV1001 ์ฒ˜์น˜์—๋„ GnRH ์ˆ˜์šฉ์ฒด ํŽธ์ง‘ LNCaP ์„ธํฌ์ฃผ ์ข…์–‘์˜ ๋ถ€ํ”ผ๊ฐ€ ์œ ์˜ํ•˜๊ฒŒ ๊ฐ์†Œํ•˜์ง€ ์•Š์•˜๋‹ค. ์ด๋Ÿฌํ•œ ๊ฒฐ๊ณผ๋Š” GV1001์˜ ์ „๋ฆฝ์„  ์ข…์–‘ ์–ต์ œ ํšจ๊ณผ๊ฐ€ ๋‡Œํ•˜์ˆ˜์ฒด ํ˜ธ๋ฅด๋ชฌ ๋ถ„๋น„ ์„ธํฌ ๋ฐ ์•”์„ธํฌ ์ž์ฒด์— ๋ฐœํ˜„๋œ GnRH ์ˆ˜์šฉ์ฒด ๋ชจ๋‘๋ฅผ ๊ฒฝ์œ ํ•˜์—ฌ ๋‚˜ํƒ€๋‚˜๋Š” ํšจ๊ณผ์ž„์„ ์‹œ์‚ฌํ•œ๋‹ค. ์ „๋ฆฝ์„ ์•” ์ด์ข… ์ด์‹ ๋ˆ„๋“œ ๋งˆ์šฐ์Šค ๋ชจ๋ธ์—์„œ GV1001์€ ์ข…์–‘ ๋‚ด MMP2, MMP9์˜ mRNA ๋ฐœํ˜„ ์ˆ˜์ค€์„ ์–ต์ œํ•˜์˜€์œผ๋ฉฐ, LNCaP, PC-3 ์„ธํฌ์ฃผ์˜ ์ด๋™๋Šฅ์„ ๊ฐ์†Œ์‹œํ‚จ ๋ฐ” ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ์„ธํฌ ์ด๋™๋Šฅ ๋ฐ ์ „์ด์— ๋ฏธ์น˜๋Š” GV1001์˜ ์˜ํ–ฅ์— ๋Œ€ํ•ด ํƒ๊ตฌํ•˜๊ธฐ ์œ„ํ•ด ์„ธํฌ ํ‘œํ˜„ํ˜• ๋ณ€ํ™”๋ฅผ ๊ด€์ฐฐํ•˜์˜€๋‹ค. GV1001์˜ ์ฒ˜์น˜๋Š” LNCaP ์„ธํฌ์˜ ์ƒํ”ผ๊ฐ„์—ฝ์ „ํ™˜(epithelial-mesenchymal transition, EMT)์„ ์–ต์ œํ•˜์˜€๋‹ค. ๋˜ํ•œ, ultra-low attachment surface plate ์—์„œ ๋ฐฐ์–‘๋œ LNCaP ์„ธํฌ์˜ ๊ตฌ ํ˜•์„ฑ๋Šฅ์ด GV1001 ์ฒ˜์น˜์— ์˜ํ•ด ์–ต์ œ๋˜๋Š” ๊ฒƒ์„ ๊ด€์ฐฐํ•˜์˜€๋‹ค. ์ „๋ฆฝ์„ ์•” ์„ธํฌ์˜ ์„ธํฌ ํ‘œํ˜„ํ˜• ๋ฐ ์ด๋™๋Šฅ์— ๋ฏธ์น˜๋Š” GV1001์˜ ์˜ํ–ฅ์ด ๊ฒฐ๊ณผ์ ์œผ๋กœ ์ƒ์ฒด ๋‚ด์—์„œ ๋‹ค๋ฅธ ์žฅ๊ธฐ๋กœ์˜ ์ „์ด๋ฅผ ์–ต์ œํ•  ์ˆ˜ ์žˆ๋Š”์ง€ ๋น„์žฅ-๊ฐ„ ์ „์ด ๋งˆ์šฐ์Šค ๋ณ‘๋ฆฌ ๋ชจ๋ธ(spleen-liver metastasis)์„ ํ†ตํ•ด ํ‰๊ฐ€ํ•˜์˜€๋‹ค. ๋น„์žฅ์— LNCaP ์„ธํฌ๋ฅผ ์ฃผ์ž…ํ•œ ํ›„ GV1001์„ ์ฒ˜์น˜ํ•˜์˜€์„ ๋•Œ, ๊ฐ„ ์ „์ด ๋ฐœ์ƒ ๋นˆ๋„์™€ ์ข…์–‘ ๋ฉด์ ์ด ๋ชจ๋‘ ๊ฐ์†Œ๋˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์•ˆ๋“œ๋กœ๊ฒ ๊ฒฐํ•์ด๋‚˜ AR ํ™œ์„ฑ ์ €ํ•ด๋Š” ์ „๋ฆฝ์„ ์•”์˜ ํ•ญ-์•ˆ๋“œ๋กœ๊ฒ ์•ฝ์ œ์— ๋Œ€ํ•œ ์ €ํ•ญ์„ฑ์˜ ์›์ธ์ด ๋˜๊ณ  ๋‹ค์–‘ํ•œ ๋ฐœ์•”์›์„ฑ ์‹ ํ˜ธ์ „๋‹ฌ์„ ์ด‰์ง„ํ•˜๋Š” ๊ฒƒ์œผ๋กœ ์•Œ๋ ค์ ธ์žˆ๋‹ค. GV1001์˜ ์ „๋ฆฝ์„ ์•” ์–ต์ œ, ํŠนํžˆ ์ด๋™๋Šฅ์˜ ์–ต์ œ์— AR ํ™œ์„ฑ์ด ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š”์ง€ ํ‰๊ฐ€ํ•˜์˜€๊ณ , AR์˜ Gฮฑs-cAMP ์‹ ํ˜ธ ์˜์กด์  ํ™œ์„ฑํ™”๊ฐ€ ๊ด€์ฐฐ๋˜์—ˆ๋‹ค. GV1001์˜ ์ฒ˜์น˜์— ์˜ํ•ด LNCaP-์„ธํฌ์ฃผ ๋‚ด AR์˜ ์ธ์‚ฐํ™”์™€ androgen-response element(ARE) ๋งค๊ฐœ ์ „์‚ฌํ™œ์„ฑ์ด ์ฆ๊ฐ€ํ•˜๋Š” ๊ฒƒ์„ western blot assay์™€ luciferase assay๋ฅผ ํ†ตํ•ด ๊ด€์ฐฐํ•˜์˜€๋‹ค. ์ด๋Ÿฌํ•œ AR ํ™œ์„ฑํ™” ๋ฐ AR ๋ฐœํ˜„ ์ฆ๊ฐ€๋Š” LNCaP ์„ธํฌ์ฃผ์˜ ์„ธํฌ ์ด๋™๋Šฅ์„ ์–ต์ œํ–ˆ๋‹ค. AR ํ™œ์„ฑ์€ ์ผ๋ฐ˜์ ์œผ๋กœ ์ „๋ฆฝ์„ ์•”์˜ ์ฆ์‹์„ ๋งค๊ฐœํ•˜๋Š” ์ฃผ์š” ์ธ์ž๋กœ ์•Œ๋ ค์ ธ ์žˆ์œผ๋‚˜, ์ „์ด ์–ต์ œ๋ฅผ ์œ ๋„ํ•˜๋Š” ๊ธฐ์ „์„ ํƒ๊ตฌํ•˜๊ธฐ ์œ„ํ•ด AR๊ณผ ๊ฒฐํ•ฉํ•˜๋Š” ๋ณด์กฐํ™œ์„ฑ์ž์˜ ์—ญํ• ์„ ๊ทœ๋ช…ํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. AR ๊ฒฐํ•ฉ ๋ณด์กฐํ™œ์„ฑ์ž์™€ GnRH ์ˆ˜์šฉ์ฒด ํ•˜์œ„ ์ „๋‹ฌ ์‹ ํ˜ธ ์ค‘ Gฮฑs-cAMP ์‹ ํ˜ธ ํŠน์ด์  ํ™œ์„ฑํ™”์˜ ์—ฐ๊ด€์„ฑ์„ ํ‰๊ฐ€ํ•˜๊ธฐ ์œ„ํ•ด ์ „๋ฆฝ์„ ์•” ํ™˜์ž์˜ ์ „์ด์™€ ๊ด€๋ จ๋œ ์œ ์ „์ž ๋ฐœํ˜„์„ ๋ถ„์„ํ•˜์˜€๊ณ  ํ•ต์‹ฌ ์œ ์ „์ž๋กœ YAP1์„ ๋„์ถœํ•˜์˜€๋‹ค. ์„ธํฌ ์‹คํ—˜์„ ํ†ตํ•ด GV1001 ์ฒ˜์น˜์— ์˜ํ•œ YAP1์˜ ์ธ์‚ฐํ™”, ์„ธํฌ์งˆ ๋‚ด ์ถ•์  ๋ฐ ์œ ๋น„ํ€ดํ‹ดํ™”-๋‹จ๋ฐฑ๋ถ„ํ•ดํšจ์†Œ ํ™œ์„ฑํ™”๋ฅผ ๊ด€์ฐฐํ•˜์˜€๋‹ค. YAP1์˜ ๋ถ„ํ•ด์— ๋”ฐ๋ผ AR๊ณผ์˜ ๊ฒฐํ•ฉ์ด ์ €ํ•ด๋˜๊ณ  YAP1 ์˜์กด์  ํƒ€๊ฒŸ ์œ ์ „์ž์˜ ๋ฐœํ˜„์ด ์–ต์ œ๋˜์—ˆ๋‹ค. ๋˜ํ•œ, YAP1 ํƒ€๊ฒŸ ์œ ์ „์ž์˜ ํ”„๋กœ๋ชจํ„ฐ ๋ถ€์œ„์— ๋Œ€ํ•œ AR์˜ ๊ฒฐํ•ฉ๋Šฅ ์—ญ์‹œ ์–ต์ œ๋˜๋Š” ๊ฒƒ์ด ๊ด€์ฐฐ๋˜์—ˆ๋‹ค. ์ด๋Ÿฌํ•œ YAP1์˜ ํ™œ์„ฑ ์–ต์ œ ํšจ๊ณผ๋Š” GV1001์˜ Gฮฑs-cAMP ์‹ ํ˜ธ ์˜์กด์ ์œผ๋กœ ๊ด€์ฐฐ๋˜์—ˆ๋‹ค. ์„ธํฌ ์ „์ด ์‹คํ—˜์„ ํ†ตํ•ด GV1001์˜ Gฮฑs-cAMP ์‹ ํ˜ธ ์˜์กด์  YAP1 ํ™œ์„ฑ ์–ต์ œ๊ฐ€ ์„ธํฌ ์ „์ด๋ฅผ ์–ต์ œํ•˜๊ณ  ์žˆ์Œ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์ „๋ฆฝ์„ ์•” ์„ธํฌ์˜ ์„ฑ์žฅ๊ณผ ์ „์ด์— ๋ฏธ์น˜๋Š” YAP1์˜ ์—ญํ• ์„ ํ‰๊ฐ€ํ•˜๊ธฐ ์œ„ํ•ด CRISPR/Cas9 ์œ ์ „์ž ํŽธ์ง‘ ์‹œ์Šคํ…œ์„ ๋„์ž…ํ•œ YAP1 ํŽธ์ง‘ LNCaP ์„ธํฌ์ฃผ๋ฅผ ๊ตฌ์ถ•ํ•˜์˜€๋‹ค. YAP1 ํŽธ์ง‘ LNCaP ์„ธํฌ์ฃผ๋Š” ์„ธํฌ์˜ ์ด๋™๋Šฅ์ด ๋Œ€์กฐ๊ตฐ LNCaP ์„ธํฌ์ฃผ์— ๋น„ํ•˜์—ฌ ํ˜„์ €ํ•˜๊ฒŒ ์–ต์ œ๋˜์–ด ์žˆ์—ˆ์œผ๋ฉฐ, ๋ˆ„๋“œ ๋งˆ์šฐ์Šค ๋ชจ๋ธ์—์„œ ์ข…์–‘์˜ ์„ฑ์žฅ์ด ๋Œ€์กฐ๊ตฐ LNCaP ์„ธํฌ์ฃผ ์ข…์–‘์— ๋น„ํ•˜์—ฌ ์œ ์˜ํ•˜๊ฒŒ ๋Š๋ฆฐ ๊ฒƒ์„ ๊ด€์ฐฐํ•˜์˜€๋‹ค. ๋˜ํ•œ, YAP1 ํŽธ์ง‘ LNCaP ์„ธํฌ์ฃผ์—์„œ GV1001์— ์˜ํ•œ ์„ธํฌ ์ด๋™๋Šฅ ์–ต์ œ ํšจ๊ณผ๋Š” ๊ด€์ฐฐ๋˜์ง€ ์•Š์•˜๋‹ค. ํ™œ์„ฑํ™”๋œ YAP1์€ ํ•ต ๋‚ด์— ์กด์žฌํ•˜์—ฌ ๋‹ค์–‘ํ•œ ๋ฐœ์•”์›์„ฑ ์œ ์ „์ž๋“ค์˜ ์ „์‚ฌ๋ฅผ ์ด‰์ง„ํ•˜๋Š” ์ „์‚ฌ ์ธ์ž๋กœ ์ž‘์šฉํ•œ๋‹ค. ํ™œ์„ฑํ™” YAP1์˜ ๋ฐœํ˜„์„ ์ด‰์ง„(constitutive active)ํ•˜๋Š” ํ˜•ํƒœ์ธ YAP5SA๋ฅผ ๊ณผ๋ฐœํ˜„์‹œํ‚จ ํ›„ YAP1์˜ ๊ณผํ™œ์„ฑ์ด ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ํ‰๊ฐ€ํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. YAP1 ํŽธ์ง‘ LNCaP ์„ธํฌ์ฃผ์™€ ๋ฐ˜๋Œ€๋กœ YAP5SA ๋ฐœํ˜„ LNCaP ์„ธํฌ์ฃผ๋Š” ๋Œ€์กฐ๊ตฐ LNCaP ์„ธํฌ์ฃผ์— ๋น„ํ•˜์—ฌ ์„ธํฌ์˜ ์ด๋™๋Šฅ์ด ํ˜„์ €ํ•˜๊ฒŒ ์ฆ๊ฐ€๋˜์–ด ์žˆ์—ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜, YAP1 ํŽธ์ง‘ LNCaP ์„ธํฌ์ฃผ์™€ ๋งˆ์ฐฌ๊ฐ€์ง€๋กœ, GV1001์— ์˜ํ•œ ์„ธํฌ ์ด๋™๋Šฅ ์–ต์ œ ํšจ๊ณผ๋Š” YAP5SA ๋ฐœํ˜„ LNCaP ์„ธํฌ์ฃผ์—์„œ๋„ ๊ด€์ฐฐ๋˜์ง€ ์•Š์•˜๋‹ค. ์ข…ํ•ฉํ•˜์—ฌ ๋ณผ ๋•Œ, ๋ณธ ์—ฐ๊ตฌ์—์„œ ๊ทœ๋ช…ํ•œ GV1001์˜ GnRH ์ˆ˜์šฉ์ฒด ๋ฆฌ๊ฐ„๋“œ๋กœ์จ์˜ ์—ญํ• ์€ Gฮฑs-cAMP ์‹ ํ˜ธ์˜ ์„ ํƒ์  ํ™œ์„ฑํ™”์ด๋ฉฐ Gฮฑs-cAMP ์‹ ํ˜ธ ์ „๋‹ฌ์„ ํ†ตํ•ด YAP1์˜ ํ™œ์„ฑ ์–ต์ œ์™€ AR์˜ ํ™œ์„ฑํ™”๊ฐ€ ์œ ๋„๋˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. AR-YAP1 ๊ฒฐํ•ฉ์€ AR ํ™œ์„ฑํ™”์— ๋”ฐ๋ฅธ ์ „์ด ์ด‰์ง„์˜ ์ฃผ์š”ํ•œ ์ธ์ž์ด๊ณ , ์ด๋ฅผ ์ €ํ•ดํ–ˆ์„ ๋•Œ ์ „์ด ์–ต์ œ ํšจ๊ณผ๊ฐ€ ๊ด€์ฐฐ๋œ๋‹ค. ๋”ฐ๋ผ์„œ ์ „๋ฆฝ์„ ์•”์˜ ์•…์„ฑํ™”๋ฅผ ์ œ์–ดํ•˜๋Š” ์ƒˆ๋กœ์šด ํƒ€๊ฒŸ์œผ๋กœ YAP1์„ ์ œ์‹œํ•˜๋ฉฐ, ์ด๋ฅผ ํ™œ์šฉํ•˜๋ฉด ๊ธฐ์กด ํ˜ธ๋ฅด๋ชฌ ์น˜๋ฃŒ์ œ์˜ ์ €ํ•ญ์„ฑ ๋งค๊ฐœ ๊ธฐ์ „์„ ์ดํ•ดํ•˜๊ณ  ์ „๋ฆฝ์„ ์•”์˜ ์ƒˆ๋กœ์šด ์น˜๋ฃŒ ๋ฐฉ์•ˆ์„ ๋„์ถœํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€๋œ๋‹ค.๋ชฉ ์ฐจ ๊ตญ๋ฌธ์š”์•ฝ i ๋ชฉ์ฐจ vii List of figures ix List of abbreviations x I. ์„œ๋ก  1 II. ์—ฐ๊ตฌ์žฌ๋ฃŒ ๋ฐ ๋ฐฉ๋ฒ• 9 ์‹œ์•ฝ ๋ฐ ์žฌ๋ฃŒ 9 ์„ธํฌ ๋ฐฐ์–‘ 9 ๋ฆฌ๊ฐ„๋“œ-์ˆ˜์šฉ์ฒด ๊ฒฐํ•ฉ๋Šฅ ํ‰๊ฐ€ 10 ์ŠคํŠธ๋ ™ํƒ€์•„๋น„๋”˜-๋น„์˜คํ‹ด ๊ฒฐํ•ฉ๋Šฅ ํ‰๊ฐ€ (Streptavidin-Biotin binding assay) 10 FITC-ํ‘œ์ง€ GV1001์„ ์ด์šฉํ•œ ์„ธํฌ ๋‚ด ์œ„์น˜ ํ‰๊ฐ€ 11 ์„ธํฌ ๋‚ด ์นผ์Š˜ ์ •๋Ÿ‰ 11 ๋ฆฌํฌํ„ฐ ์œ ์ „์ž ๋ถ„์„ (Reporter gene assay) 12 ๋ฉด์—ญํ™”ํ•™์  ๋ถ„์„ (Immunoblot analysis) 12 cDNA์˜ Realtime RT-PCR 13 ํ˜•์งˆ๋„์ž… (Transfection) 14 ์„ธํฌ ์ฆ์‹ ๋ถ„์„๋ฒ• 15 ์—ผ์ƒ‰์งˆ๋ฉด์—ญ์นจ์ „๋ฒ• (Chromatin immunoprecipitation assays) 16 ์ฒด์™ธ ์„ธํฌ์˜ ์ด๋™์„ฑ ๋ถ„์„๋ฒ• 16 ๋ฉด์—ญ์นจ๊ฐ•๋ฒ• (Immunoprecipitation) 17 Caspase-3/7 ํ™œ์„ฑ ํ‰๊ฐ€ 17 ์•” ์„ฑ์žฅ ๋งˆ์šฐ์Šค ๋ณ‘๋ฆฌ ๋ชจ๋ธ (Xenograft nude mouse model) 18 TUNEL ๋ถ„์„๋ฒ• (Terminal deoxynucleotidyl transferase dUTP nick end labeling assay) 18 ๋ฉด์—ญ์กฐ์งํ™”ํ•™์—ผ์ƒ‰ (Immunohistochemistry) 19 ๋งˆ์šฐ์Šค ํ˜ˆ์ค‘ ํ…Œ์Šคํ† ์Šคํ…Œ๋ก  ์ •๋Ÿ‰ 19 ๋น„์žฅ-๊ฐ„ ์ „์ด ๋งˆ์šฐ์Šค ๋ณ‘๋ฆฌ ๋ชจ๋ธ 19 ํ†ต๊ณ„๋ถ„์„ 20 III. ์—ฐ๊ตฌ๊ฒฐ๊ณผ 21 1) GV1001์˜ ์ „๋ฆฝ์„ ์•” ์–ต์ œ ํšจ๊ณผ ๋ฐ ํƒ€๊ฒŸ ๊ทœ๋ช… 21 1. GV1001๊ณผ GnRH ๊ตฌ์กฐ ์œ ์‚ฌ์ฒด๋“ค์˜ ํŽฉํƒ€์ด๋“œ ๊ตฌ์กฐ ๋ถ„์„ 21 2. GV1001์— ์˜ํ•œ GnRH ์ˆ˜์šฉ์ฒด ํ•˜์œ„ ์‹ ํ˜ธ ์ „๋‹ฌ ํ‰๊ฐ€ 26 3. GV1001์— ์˜ํ•œ ์ „๋ฆฝ์„  ์ข…์–‘ ์–ต์ œ ํšจ๊ณผ 30 4. GV1001์˜ ์ „๋ฆฝ์„ ์•” ์„ธํฌ ์ฆ์‹๊ณผ ์ด๋™๋Šฅ ์–ต์ œ ํšจ๊ณผ 35 5. GV1001์— ์˜ํ•œ ์„ธํฌ์ž๊ฐ€์‚ฌ๋ฉธ ์œ ๋„ ํšจ๊ณผ 39 2) ์ „๋ฆฝ์„ ์•” ์•…์„ฑํ™”์— ๋”ฐ๋ฅธ ์ „์ด ๊ธฐ์ „ ๋ฐ ์น˜๋ฃŒ์  ํƒ€๊ฒŸ ์ œ์‹œ 44 1. ์ „๋ฆฝ์„ ์•” ์„ธํฌ์˜ ์ƒํ”ผ๊ฐ„์—ฝ์ „ํ™˜(EMT) ๋ฐ ์ „์ด ์–ต์ œ ํšจ๊ณผ 44 2. ์ „๋ฆฝ์„ ์•” ์„ธํฌ์—์„œ AR์˜ ์„ธํฌ ์ด๋™๋Šฅ ์กฐ์ ˆ 49 3. ์ „๋ฆฝ์„ ์•” ์„ธํฌ์—์„œ GV1001์˜ AR ํ™œ์„ฑ ์กฐ์ ˆ 51 4. GV1001์˜ AR ํ™œ์„ฑํ™” ์‹ ํ˜ธ ์กฐ์ ˆ 54 5. ์ „๋ฆฝ์„ ์•”์—์„œ AR ๋ณด์กฐ์กฐ์ ˆ์ž YAP1์˜ ํ™œ์„ฑ 58 6. YAP1 ํ™œ์„ฑํ™” ์กฐ์ ˆ์— ์˜ํ•œ ์„ธํฌ ์ด๋™๋Šฅ ์กฐ์ ˆ ํšจ๊ณผ 63 IV. ๊ณ ์ฐฐ 68 V. ์ฐธ๊ณ ๋ฌธํ—Œ 76 VI. Abstract 88 VII. Curriculum Vitae 91 VIII. ๊ฐ์‚ฌ์˜ ๊ธ€ 94 List of figures Figure 1. Binding of GV1001 to GnRHR 22 Figure 2. Docking studies of GV1001 to GnRHR 24 Figure 3. Selective activation of Gฮฑs-cAMP pathway by GV1001 28 Figure 4. In vivo anti-cancer effect of GV1001 32 Figure 5. Effects of GV1001 on cell proliferation and migration in PCa cells 36 Figure 6. GnRHR-dependent apoptosis induction by GV1001 41 Figure 7. Effects of GV1001 on PCa-tumor metastasis 46 Figure 8. Regulation of AR in PCa migration model in vitro 50 Figure 9. Activation of AR by GV1001 in PCa cells 52 Figure 10. Gฮฑs-cAMP pathway-dependent activation of AR by GV1001 56 Figure 11. Inactivation of YAP1 and AR-coregulator switch by GV1001 60 Figure 12. Effects of YAP1 regulation on PCa in vitro migration and in vivo progression 65Docto
    • โ€ฆ
    corecore