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    ์ฒด์งˆ๋Ÿ‰์ง€์ˆ˜์™€ ํ—ˆ๋ฆฌ๋‘˜๋ ˆ๊ฐ€ ์‚ฌ๋ง๋ฅ ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ

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    ๋น„๋งŒ์˜ ์œ ๋ณ‘๋ฅ ์€ ์ „์„ธ๊ณ„์ ์œผ๋กœ ๋น ๋ฅด๊ฒŒ ์ฆ๊ฐ€ํ•˜๊ณ  ์žˆ์œผ๋ฉฐ, ํ˜„์žฌ ์ „ ์„ธ๊ณ„ ์„ฑ์ธ์ธ๊ตฌ์˜ 39%์— ๋‹ฌํ•˜๋Š” 19์–ต ๋ช…์ด ๊ณผ์ฒด์ค‘ ํ˜น์€ ๋น„๋งŒ์ธ๊ตฌ๋กœ ์•Œ๋ ค์ ธ ์žˆ๋‹ค. ๋น„๋งŒ์„ ์ธก์ •ํ•˜๋Š” ๋Œ€ํ‘œ์ ์ธ ๋ฐฉ๋ฒ•์€ ์ฒด์งˆ๋Ÿ‰์ง€์ˆ˜์ด๋ฉฐ, ์ด๋Š” ์‚ฌ๋ง๋ฅ ๊ณผ ์œ ์˜ํ•œ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ๊ฐ€์ง„๋‹ค๊ณ  ์•Œ๋ ค์ ธ ์žˆ๋‹ค. ๋น„๋งŒ์„ ์ธก์ •ํ•˜๋Š” ๋˜ ๋‹ค๋ฅธ ๋ฐฉ๋ฒ•์€ ๋ณต๋ถ€๋น„๋งŒ์˜ ์ •๋„๋ฅผ ๋‚˜ํƒ€๋‚ด๋Š” ํ—ˆ๋ฆฌ๋‘˜๋ ˆ๋กœ, ์ด ๋˜ํ•œ ์‚ฌ๋ง๋ฅ ๊ณผ ๋ฐ€์ ‘ํ•œ ๊ด€๋ จ์ด ์žˆ๋‹ค๊ณ  ์•Œ๋ ค์ ธ ์žˆ๋‹ค. ์ง€๊ธˆ๊นŒ์ง€ ์ฒด์งˆ๋Ÿ‰์ง€์ˆ˜์™€ ํ—ˆ๋ฆฌ๋‘˜๋ ˆ๊ฐ€ ๊ฐ๊ฐ ์‚ฌ๋ง๋ฅ ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์— ๋Œ€ํ•ด ๋ถ„์„ํ•œ ์—ฐ๊ตฌ๋Š” ๋งŽ์ด ์ฐพ์•„๋ณผ ์ˆ˜ ์žˆ์—ˆ์ง€๋งŒ, ์ฒด์งˆ๋Ÿ‰์ง€์ˆ˜์™€ ํ—ˆ๋ฆฌ๋‘˜๋ ˆ๋ฅผ ๊ฒฐํ•ฉํ•˜์—ฌ ์‚ฌ๋ง๋ฅ ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ํŒŒ์•…ํ•œ ์—ฐ๊ตฌ๋Š” ์ฐพ์•„๋ณด๊ธฐ ํž˜๋“ค์—ˆ๋‹ค. ๋”ฐ๋ผ์„œ ์ด ์—ฐ๊ตฌ์—์„œ๋Š” ์ฒด์งˆ๋Ÿ‰์ง€์ˆ˜์™€ ํ—ˆ๋ฆฌ๋‘˜๋ ˆ์— ๋”ฐ๋ผ ๋Œ€์ƒ์ž๋ฅผ ๊ตฌ๋ถ„ํ•˜์—ฌ ์ด๋“ค์˜ ์‚ฌ๋ง๋ฅ ์— ์–ด๋– ํ•œ ์˜ํ–ฅ์ด ์žˆ๋Š”์ง€ ์•Œ์•„๋ณด๊ณ ์ž ํ•˜์˜€๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ๊ตญ๋ฏผ๊ฑด๊ฐ•๋ณดํ—˜๊ณต๋‹จ ๊ฑด๊ฐ•๊ฒ€์ง„ ์ฝ”ํ˜ธํŠธDB ์ž๋ฃŒ๋ฅผ ํ™œ์šฉํ•˜์—ฌ 2009~2010๋…„ ๊ฑด๊ฐ•๊ฒ€์ง„ ์ฝ”ํ˜ธํŠธ์— ๋“ฑ๋ก๋œ ์ง‘๋‹จ์„ ๋Œ€์ƒ์œผ๋กœ ์‚ฌ๋ง์—ฌ๋ถ€ ๋ฐ ์‚ฌ๋ง์›์ธ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์‚ฌ๋ง์— ์˜ํ–ฅ์„ ๋ผ์น˜๋Š” ์งˆ๋ณ‘์„ ๊ณผ๊ฑฐ๋ ฅ์œผ๋กœ ๊ฐ€์ง€๊ณ  ์žˆ๋Š” ๋Œ€์ƒ์ž์™€ ๊ฒฐ์ธก๊ฐ’์„ ๊ฐ€์ง€๊ณ  ์žˆ๋Š” ๋Œ€์ƒ์ž๋ฅผ ์ œ์™ธํ•˜์˜€๋‹ค. ์‚ฌ๋ง์›์ธ์€ ๋ชจ๋“  ์›์ธ์œผ๋กœ ์ธํ•œ ์‚ฌ๋ง, ์•”์งˆํ™˜์œผ๋กœ ์ธํ•œ ์‚ฌ๋ง, ์‹ฌํ˜ˆ๊ด€๊ณ„์งˆํ™˜์œผ๋กœ ์ธํ•œ ์‚ฌ๋ง์œผ๋กœ ํŒŒ์•…ํ•˜์˜€์œผ๋ฉฐ, ์ฒด์งˆ๋Ÿ‰์ง€์ˆ˜์™€ ํ—ˆ๋ฆฌ๋‘˜๋ ˆ๊ฐ€ ์‚ฌ๋ง๋ฅ ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ์•Œ์•„๋ณด๊ธฐ ์œ„ํ•˜์—ฌ ์ฝ•์Šค๋น„๋ก€์œ„ํ—˜๋ชจ๋ธ์„ ์‚ฌ์šฉํ•˜์—ฌ ์ƒ์กด๋ถ„์„์„ ์‹ค์‹œํ•˜์˜€๋‹ค. ์ „์ฒด 139,252๋ช…์˜ ๋Œ€์ƒ์ž๊ฐ€ ๋ถ„์„์— ํฌํ•จ๋˜์—ˆ์œผ๋ฉฐ, ๋‚จ์„ฑ 82,830๋ช… ์ค‘ 2,179๋ช…(2.6%)์ด ๋ชจ๋“  ์›์ธ์œผ๋กœ ์ธํ•˜์—ฌ ์‚ฌ๋งํ•˜์˜€๊ณ , 1,018๋ช…(1.2%)์ด ์•”์งˆํ™˜์œผ๋กœ ์ธํ•˜์—ฌ ์‚ฌ๋งํ•˜์˜€์œผ๋ฉฐ, 295๋ช…(0.4%)์ด ์‹ฌํ˜ˆ๊ด€๊ณ„์งˆํ™˜์œผ๋กœ ์ธํ•˜์—ฌ ์‚ฌ๋งํ•˜์˜€๋‹ค. ์—ฌ์„ฑ์€ 56,422๋ช… ์ค‘ 694๋ช…(1.2%)์ด ๋ชจ๋“  ์›์ธ์œผ๋กœ ์ธํ•˜์—ฌ ์‚ฌ๋งํ•˜์˜€๊ณ , 307๋ช…(0.5%)์ด ์•”์งˆํ™˜์œผ๋กœ ์ธํ•˜์—ฌ ์‚ฌ๋งํ•˜์˜€์œผ๋ฉฐ, 122๋ช…(0.2%)์ด ์‹ฌํ˜ˆ๊ด€๊ณ„์งˆํ™˜์œผ๋กœ ์ธํ•˜์—ฌ ์‚ฌ๋งํ•˜์˜€๋‹ค. ๋‚จ์„ฑ๊ณผ ์—ฌ์„ฑ ๋ชจ๋‘์—์„œ ํ—ˆ๋ฆฌ๋‘˜๋ ˆ๊ฐ€ 5cm ์ฆ๊ฐ€ํ• ์ˆ˜๋ก ์ด ์‚ฌ๋ง๋ฅ ๊ณผ ์•”์งˆํ™˜์œผ๋กœ ์ธํ•œ ์‚ฌ๋ง๋ฅ ์ด ๊ฐ๊ฐ 10%์”ฉ ์ฆ๊ฐ€ํ•˜๋ฉฐ, ์‹ฌํ˜ˆ๊ด€๊ณ„์งˆํ™˜์œผ๋กœ ์ธํ•œ ์‚ฌ๋ง์˜ ๊ฒฝ์šฐ ๋‚จ์„ฑ์—์„œ 10%, ์—ฌ์„ฑ์—์„œ 5% ์ฆ๊ฐ€ํ•˜๋‚˜ ์œ ์˜ํ•˜์ง€๋Š” ์•Š์•˜๋‹ค. ๋ฐ˜๋ฉด ์ฒด์งˆ๋Ÿ‰์ง€์ˆ˜์˜ ๊ฒฝ์šฐ ๋‚จ์„ฑ์€ 1kg/mยฒ์ฆ๊ฐ€ํ•  ๋•Œ๋งˆ๋‹ค ์ด ์‚ฌ๋ง๋ฅ ์ด 10%, ์•”์งˆํ™˜์œผ๋กœ ์ธํ•œ ์‚ฌ๋ง๋ฅ ์ด 7% ๊ฐ์†Œํ•˜๋ฉฐ, ์—ฌ์„ฑ์˜ ๊ฒฝ์šฐ 1kg/mยฒ์ฆ๊ฐ€ํ•  ๋•Œ๋งˆ๋‹ค ์ด ์‚ฌ๋ง๋ฅ ์ด 8%, ์•”์งˆํ™˜์œผ๋กœ ์ธํ•œ ์‚ฌ๋ง์ด 7% ๊ฐ์†Œํ•˜์˜€๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ •์ƒ์ฒด์ค‘๊ตฐ์— ๋น„ํ•ด ์ €์ฒด์ค‘๊ตฐ์—์„œ ๋‚จ์„ฑ์˜ ์ด ์‚ฌ๋ง๋ฅ ์ด 1.51๋ฐฐ, ์—ฌ์„ฑ์˜ ์ด ์‚ฌ๋ง๋ฅ ์ด 1.7๋ฐฐ๋กœ ๋†’์•˜์œผ๋ฉฐ, ๋น„๋งŒ๊ตฐ์—์„œ๋Š” ๋‚จ์„ฑ๊ณผ ์—ฌ์„ฑ ๊ฐ๊ฐ 0.61๋ฐฐ์™€ 0.73๋ฐฐ๋กœ ์œ ์˜ํ•˜๊ฒŒ ๋‚ฎ์Œ์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋‚จ์„ฑ๊ณผ ์—ฌ์„ฑ ๋ชจ๋‘ ์ •์ƒ์ฒด์ค‘๊ตฐ๊ณผ ๊ณผ์ฒด์ค‘๊ตฐ์—์„œ ํ—ˆ๋ฆฌ๋‘˜๋ ˆ๊ฐ€ 5cm ์ฆ๊ฐ€ํ• ์ˆ˜๋ก ์ด ์‚ฌ๋ง๋ฅ ์ด ์ฆ๊ฐ€ํ•˜๋Š” ๊ฒฝํ–ฅ์„ ๋ณด์˜€์œผ๋ฉฐ, ์ •์ƒ์ฒด์ค‘๊ตฐ๊ณผ ๊ณผ์ฒด์ค‘๊ตฐ, ๋น„๋งŒ๊ตฐ ๋ชจ๋‘์—๊ฒŒ์„œ ํ—ˆ๋ฆฌ๋‘˜๋ ˆ๊ฐ€ ์ •์ƒ์— ๋น„ํ•ด ๋ณต๋ถ€๋น„๋งŒ์ด ๋ ์ˆ˜๋ก ์‚ฌ๋ง๋ฅ ์ด ์ฆ๊ฐ€ํ•˜๋Š” ๊ฒฝํ–ฅ์„ ๋ณผ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ด ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•˜์—ฌ ์ฒด์งˆ๋Ÿ‰์ง€์ˆ˜์™€ ํ—ˆ๋ฆฌ๋‘˜๋ ˆ๊ฐ€ ์‚ฌ๋ง์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์ฒด์งˆ๋Ÿ‰์ง€์ˆ˜์™€ ์‚ฌ๋ง์€ ์Œ์˜ ์ƒ๊ด€๊ด€๊ณ„, ํ—ˆ๋ฆฌ๋‘˜๋ ˆ์™€ ์‚ฌ๋ง์€ ์–‘์˜ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ์—ˆ์œผ๋ฉฐ, ๋‚จ์„ฑ๊ณผ ์—ฌ์„ฑ ๋ชจ๋‘ ์ €์ฒด์ค‘๊ตฐ์—์„œ ์‚ฌ๋ง๋ฅ ์ด ๊ฐ€์žฅ ๋†’์•˜์œผ๋ฉฐ, ๊ฐ™์€ ์ฒด์ค‘๊ตฐ์ด์—ฌ๋„ ํ—ˆ๋ฆฌ๋‘˜๋ ˆ๊ฐ€ ๋†’์„์ˆ˜๋ก ์‚ฌ๋ง๋ฅ ์ด ์ฆ๊ฐ€ํ•˜๋Š” ๊ฒƒ์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ฒด์งˆ๋Ÿ‰์ง€์ˆ˜๊ฐ€ ์ €์ฒด์ค‘๊ตฐ์ธ ๊ฒฝ์šฐ ์‚ฌ๋ง๋ฅ ์ด ๊ฐ€์žฅ ๋†’๊ธฐ ๋•Œ๋ฌธ์— ๋ฌด์กฐ๊ฑด ์ฒด์ค‘์„ ๋‚ฎ์ถ”๋Š” ๊ฒƒ ๋ณด๋‹ค๋Š” ์ ์ ˆํ•œ ์ฒด์ค‘์„ ์œ ์ง€ํ•˜๋Š” ๊ฒƒ์ด ์ค‘์š”ํ•˜๋ฉฐ, ๋ชจ๋“  ์ฒด์ค‘๊ตฐ์—์„œ ํ—ˆ๋ฆฌ๋‘˜๋ ˆ๋ฅผ ์กฐ์ ˆํ•˜๋Š” ๊ฒƒ์ด ํ•„์š”ํ•˜๋‹ค๋Š” ๊ฒƒ์„ ๋ณด์—ฌ์ค€๋‹ค๊ณ  ํ•  ์ˆ˜ ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ๊ฑด๊ฐ•๊ฒ€์ง„ ์‹œ ํ‚ค์™€ ๋ชธ๋ฌด๊ฒŒ๋งŒ ์ธก์ •ํ•˜์—ฌ ์ •์ƒ์ฒด์ค‘๊ตฐ๊ณผ ๊ณผ์ฒด์ค‘๊ตฐ์—๊ฒŒ ์ ์ ˆํ•œ ๊ฑด๊ฐ•์„ ์œ ์ง€ํ•˜๊ณ  ์žˆ๋‹ค๊ณ  ํ‰๊ฐ€ํ•˜๋Š” ๊ฒƒ์ด ์•„๋‹ˆ๋ผ, ํ—ˆ๋ฆฌ๋‘˜๋ ˆ๋„ ๊ฐ™์ด ์ธก์ •ํ•˜์—ฌ ๊ทธ๋“ค์˜ ๊ฑด๊ฐ•์ˆ˜์ค€์„ ํ‰๊ฐ€ํ•ด์•ผ ํ•˜๋Š” ๊ฒƒ์ด ํ•„์š”ํ•˜๋‹ค๋Š” ๊ฒƒ์„ ์•Œ ์ˆ˜ ์žˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ํ—ˆ๋ฆฌ๋‘˜๋ ˆ ์ธก์ •์€ ์„ฑ๋ณ„์ด๋‚˜ ๋‚˜์ด, ํก์—ฐ์—ฌ๋ถ€, ์†Œ๋“์ˆ˜์ค€, ์žฅ์• ์—ฌ๋ถ€์— ์ƒ๊ด€์—†์ด ์ด๋ฃจ์–ด์ ธ์•ผ ํ•  ๊ฒƒ์ด๋‹ค.open์„

    ๊ฐ•๊ฑด ํฌ์†Œ ๋ฒ ์ด์ฆˆ ๋ฌดํ•œ ์ธ์ž ๋ชจํ˜•

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ž์—ฐ๊ณผํ•™๋Œ€ํ•™ ํ†ต๊ณ„ํ•™๊ณผ, 2021. 2. ์ด์žฌ์šฉ.Most of previous works and applications of Bayesian factor model have assumed the normal likelihood regardless of its validity. We propose a Bayesian factor model for heavy-tailed high-dimensional data based on multivariate Student-t likelihood to obtain better covariance estimation. We use multiplicative gamma process shrinkage prior and factor number adaptation scheme proposed in Bhattacharya and Dunson [Biometrika (2011) 291-306]. Since a naive Gibbs sampler for the proposed model suffers from slow mixing, we propose a Markov Chain Monte Carlo algorithm where fast mixing of Hamiltonian Monte Carlo is exploited for some parameters in proposed model. Simulation results illustrate the gain in performance of covariance estimation for heavy-tailed high-dimensional data. We also provide a theoretical result that the posterior of the proposed model is weakly consistent under reasonable conditions. We conclude the paper with the application of proposed factor model on breast cancer metastasis prediction given DNA signature data of cancer cell.๋ฒ ์ด์ฆˆ ์ธ์ž ๋ชจํ˜•์— ๋Œ€ํ•œ ๋Œ€๋ถ€๋ถ„์˜ ์„ ํ–‰ ์—ฐ๊ตฌ๋Š” ์ž๋ฃŒ๊ฐ€ ๋”ฐ๋ฅด๋Š” ๋ถ„ํฌ๊ฐ€ ์ •๊ทœ๋ถ„ํฌ์ž„์„ ๊ฐ€์ •ํ•œ๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ๋‹ค๋ณ€์ˆ˜ t ๊ฐ€๋Šฅ๋„๋ฅผ ์‚ฌ์šฉํ•จ์œผ๋กœ์จ, ์ด์ƒ์น˜๊ฐ€ ์กด์žฌํ•˜๋Š” ๊ณ ์ฐจ์› ์ž๋ฃŒ์— ๋Œ€ํ•ด ๋” ๊ฐœ์„ ๋œ ๊ณต๋ถ„์‚ฐ ์ถ”์ • ์„ฑ๋Šฅ์„ ๊ฐ–๋Š” ๋ฒ ์ด์ฆˆ ์ธ์ž ๋ชจํ˜•์„ ์ œ์‹œํ•œ๋‹ค. ์ž ์žฌ์ธ์ž์˜ ์ˆ˜๋ฅผ ๊ฒฐ์ •ํ•˜๊ธฐ ์œ„ํ•ด์„œ ๋ณธ ๋ชจํ˜•์€, ๋ฌดํ•œํžˆ ๋งŽ์€ ์ž ์žฌ์ธ์ž์— ๋Œ€ํ•ด ์ˆ˜์ถ•์‚ฌ์ „๋ถ„ํฌ๋ฅผ ๋ถ€์—ฌํ•˜๊ณ  ์ด๋ฅผ ๋™์ ์œผ๋กœ ์ ˆ๋‹จํ•ด๋‚˜๊ฐ€๋Š” Bhattacharya์™€ Dunson [Biometrika (2011) 291-306]์˜ ๋ฐฉ๋ฒ•์„ ์ ์šฉํ–ˆ๋‹ค. ์ผ๋ฐ˜์ ์ธ ๊น์Šค ์ƒ˜ํ”Œ๋Ÿฌ๋Š” ๋Š๋ฆฐ ๋ฏน์‹ฑ์œผ๋กœ ์ธํ•ด ๋ณธ ์—ฐ๊ตฌ์—์„œ ์ œ์•ˆํ•œ ๋ชจํ˜•์˜ ์‚ฌํ›„๋ถ„ํฌ๋ฅผ ๊ณ„์‚ฐํ•˜๋Š” ๋ฐ ํ•œ๊ณ„๊ฐ€ ์žˆ๊ธฐ ๋•Œ๋ฌธ์—, ๋ณธ ์—ฐ๊ตฌ๋Š” ๋ชจํ˜• ๋‚ด ์ผ๋ถ€ ๋ชจ์ˆ˜์— ๋Œ€ํ•ด ํ•ด๋ฐ€ํ† ๋‹ˆ์•ˆ ๋ชฌํ…Œ ์นด๋ฅผ๋กœ ๋ฐฉ๋ฒ•์„ ์‚ฌ์šฉํ•œ ์‚ฌํ›„๋ถ„ํฌ ๊ณ„์‚ฐ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์‹œํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์ œ์•ˆ๋œ ๋ชจํ˜•์œผ๋กœ๋ถ€ํ„ฐ ์œ ๋„๋œ ์‚ฌํ›„๋ถ„ํฌ๊ฐ€ ํŠน์ • ์กฐ๊ฑด ํ•˜์—์„œ ์‚ฌํ›„์ผ์น˜์„ฑ์„ ๋งŒ์กฑํ•œ๋‹ค๋Š” ์ด๋ก ์  ์„ฑ์งˆ์„ ์ฆ๋ช…ํ•˜์˜€๋‹ค. ๋ชจ์˜์‹คํ—˜์„ ํ†ตํ•ด ๋ณธ ์—ฐ๊ตฌ์—์„œ ์ œ์•ˆ๋œ ๋ชจํ˜•์ด ์ด์ƒ์น˜๊ฐ€ ์กด์žฌํ•˜๋Š” ๊ณ ์ฐจ์› ์ž๋ฃŒ ํ•˜์—์„œ ๊ฐœ์„ ๋œ ๊ณต๋ถ„์‚ฐ ์ถ”์ • ์„ฑ๋Šฅ์„ ๋ณด์ธ๋‹ค๋Š” ๊ฒƒ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ๋‹ค. ๋˜ํ•œ ์•” ์กฐ์ง์˜ DNA ์‹œ๊ทธ๋‹ˆ์ฒ˜ ์ž๋ฃŒ์— ๋ณธ ์—ฐ๊ตฌ์—์„œ ์ œ์•ˆํ•œ ๊ณต๋ถ„์‚ฐ ์ถ”์ • ๋ชจํ˜•์„ ์ ์šฉํ•˜์—ฌ ์œ ๋ฐฉ์•” ์ „์ด ์—ฌ๋ถ€๋ฅผ ์˜ˆ์ธกํ•˜๋Š” ๋ถ„์„ ์‚ฌ๋ก€๋ฅผ ์†Œ๊ฐœํ•œ๋‹ค.Abstract Contents List of Tables List of Figures 1 Introduction 1 2 Factor Models 4 2.1 Settings 4 2.2 Bayesian Factor Models 5 2.2.1 Unidentifiability of Factor Loading 6 2.2.2 Unknown Latent Factor Dimension 7 3 Robust Sparse Bayesian Infinite Factor Models 9 3.1 Sparse Bayesian Infinite Factor Models 9 3.2 Robust Sparse Bayesian Infinite Factor Models 11 3.3 Inference 13 4 Theoretical Properties 16 5 Simulation Study 18 6 Real Data Analysis : T1T2 Node-Negative Breast Cancer Application 23 6.1 Background and Previous Researches 23 6.2 Model and Results 25 7 Discussion 27 8 Appendix 29 8.1 Proof of Theorem 1 29 8.2 Proof of Theorem 2 30 Abstract (In Korean) 39Maste

    Changes in the Business Cycle of the Korean Economy: Evidence and Explanations

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    With a relatively simple quantitative method, this study comprehensively analyzes the characteristics related to business cycles represented by macroeconomic variables of Korea since 1970. This empirical analysis deals with roughly following three topics:โ… . ์„œ ๋ก  โ…ก. ๊ตญ๋‚ด ๊ฒฝ๊ธฐ๋ณ€๋™์š”์ธ์˜ ์‹๋ณ„ ใ€€1. ๊ฒฝ๊ธฐ๋ณ€๋™์š”์ธ์˜ ์‹๋ณ„๊ณผ ๊ด€๋ จ๋œ ์Ÿ์  ใ€€2. ์„ ํ˜•์ถ”์„ธ์— ์˜ํ•œ ์ˆœํ™˜๋ณ€๋™์š”์ธ์˜ ์ถ”์ถœ ใ€€3. ์„ ํ˜•ํ•„ํ„ฐ๋ฅผ ์ด์šฉํ•œ ์ˆœํ™˜๋ณ€๋™์š”์ธ์˜ ์ถ”์ถœ โ…ข. ๊ฑฐ์‹œ๊ฒฝ์ œ๋ณ€์ˆ˜์˜ ๊ฒฝ๊ธฐ๋ณ€๋™์ƒ์˜ ์ผ๋ฐ˜์  ํŠน์ง• ใ€€1. ์ž๋ฃŒ ๋ฐ ๋ถ„์„๋ฐฉ๋ฒ• ใ€€2. ๊ตฌ์กฐ์  ๋ณ€

    A Study of Characteristics of Expectation in Inflation Dynamics

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    This paper attempts to demonstrate the critical role of expectation horizons in economic agents building their expectations for the future. It starts with the analysis of what constraints the economics-based assumption related to information efficiency coโ… . ์„œ ๋ก  โ…ก. ๊ธฐ๋Œ€๋ณ€์ˆ˜์˜ ๋ณด์ •๊ณผ์ • ใ€€1. ์ •๋ณดํšจ์œจ์„ฑ๊ณผ ๊ธฐ๋Œ€๋ณ€์ˆ˜์˜ ๋ณด์ • ใ€€2. ๊ธฐ๋Œ€๋ณ€์ˆ˜์˜ ์ž„์˜์  ๋ณด์ • โ…ข. ์ž„์˜์  ๋ณด์ •๊ณผ ๋ฌผ๊ฐ€๊ฒฐ์ •์‹ โ…ฃ. ์‹ค์ฆ๋ถ„์„ ใ€€1. ์šฐ๋ฆฌ๋‚˜๋ผ์˜ ์‚ฐ์ถœ ๋ฐ ์ธํ”Œ๋ ˆ์ด์…˜ ์ž๋ฃŒ์ƒ์˜ ํŠน์ง• ใ€€2. ์ธํ”Œ๋ ˆ์ด์…˜์— ๋Œ€ํ•œ ๊ตฌ์กฐ์  ์‹œ๊ณ„์—ด ๋ชจํ˜•์˜ ์ถ”

    Arbitrary-order symplectic time integrator for the acoustic wave equation using the pseudo-spectral method

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ํ˜‘๋™๊ณผ์ • ๊ณ„์‚ฐ๊ณผํ•™์ „๊ณต, 2017. 2. ์‹ ์ฐฝ์ˆ˜.A Hamiltonian system is symplectic. To simulate a Hamiltonian system, symplectic time integrators are generally appliedotherwise, the energy or the generalized energy is not conserved in the volume of interest. In this study, the symplectic nature of the acoustic wave system is proven. Then, a symplectic scheme that can be extended arbitrarily in temporal dimensions is suggested. The method is based on the Lax-Wendroff expansion of the time differentiation of acoustic wave variables, such as pressure and velocity, existing on the staggered time axis, i.e., one is on the integer grid, and the other is defined on the half integer of the time step. The series can be reduced to the pseudo-differential operator, which enables the application of other approximation techniques, such as the Jacobi-Anger expansion. By virtue of considering the property of the nature of the acoustic wave phenomena, the scheme is more stable and accurate than methods that do not consider symplecticity. Moreover, the phase error per time step can be kept sufficiently small to conduct simulation over long periods of time. According to the analysis of the scheme, the larger the time strides are, the more efficient the simulation is in terms of computing power when a sufficient number of multiplications of the map are accumulated. The effectiveness and accuracy are verified through simulation results using a homogeneous model in which the computed wavefield is equivalent to the analytic solution. The numerical results of the wavefield in the heterogeneous model also yield equivalent results irrespective of the time step lengths. The scheme can be applied to the source problemshowever, the time step is confined to describing the entire frequency component of the wavelet.1. Introduction 1 1.1. Background 1 1.2. Overview 8 1.3. Outline 10 2. Theory 11 2.1. Acoustic wave equation 11 2.2. Symplecticity and symplectic time integrator 18 2.2.1. Symplecticity of the transformation map 18 2.2.2. Symplectic time integrator 21 2.3. Arbitrary-order symplectic time integrator 26 3. Analysis 31 3.1. Stability analysis 32 3.2. Dispersion analysis 37 3.3. Phase analysis 45 3.4. Spectral accuracy and compromise 56 3.5. Source wavelet issue 67 4. Numerical Examples 70 4.1. Initial value problems 71 4.1.1. Homogeneous model 71 4.1.2. Synthetic heterogeneous model: Marmousi-2 72 4.2. Source problems 90 4.2.1. Homogeneous model 90 4.2.2. Synthetic heterogeneous model: Marmousi-2 91 4.3. Discussion on factors debasing the accuracy 107 5. Conclusions 112 References 115 Appendix A. Additional formulations 121 A1. Absorbing boundary conditions 121 A2. Analytic solution 126 Appendix B. Matlab codes 128 B1. Arbitrary-order symplectic time operator 128 B2. Analytic solution 131 ์ดˆ๋ก 133Docto

    Analysis on Koreaโ€™s Economic Volatility: Focusing on the Role of the Service Industry

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    This study discusses the phenomenon behind various forms of macroeconomic volatility faced by countries in terms of industrial structure through empirical analysis, and in the process attempts to validate the role of the service industry. The analysis shoโ… . ์„œ ๋ก  ใ€€โ…ก. ๊ฑฐ์‹œ๋ณ€๋™์„ฑ์˜ ๊ฒฝ์ œ์  ํ•จ์˜ ใ€€โ…ข. ๊ตญ๋‚ด ์‚ฐ์—…๊ตฌ์กฐ์™€๊ฒฝ๊ธฐ๋ณ€๋™์„ฑ ใ€€โ…ฃ. ๊ตญ์ œ๋น„๊ต๋ฅผ ํ†ตํ•œ ์‚ฐ์—…๊ตฌ์กฐ์™€ ๊ฒฝ๊ธฐ๋ณ€๋™์„ฑ์˜ ๊ด€๊ณ„ ใ€€โ…ค. ์ •์ฑ…์  ์‹œ์‚ฌ์  ๋ฐ ๊ฒฐ๋ก  ใ€€์ฐธ ๊ณ  ๋ฌธ ํ—Œ ใ€€[๋ถ€๋ก] ๋ณ€๋™์„ฑ ๋ถ„ํ•ด(Volatility Decomposition

    ๋ฏธ๊ตญ-ํŒŒํ‚ค์Šคํƒ„ ๊ตฐ์‚ฌ์ƒํ˜ธ์›์กฐ์ „๋žต๊ณผ ๋ฏธ๊ตญ ์„œ๋‚จ์•„์‹œ์•„ ๋ฐฉ์œ„์ „๋žต

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ •์น˜์™ธ๊ตํ•™๋ถ€(์™ธ๊ตํ•™์ „๊ณต), 2014. 2. ์ „์žฌ์„ฑ.๊ตญ ๋ฌธ ์ดˆ ๋ก ๋ณธ ์—ฐ๊ตฌ์˜ ๋ชฉ์ ์€ ๋ฏธ๊ตญ ํŒŒํ‚ค์Šคํƒ„ ๊ตฐ์‚ฌ์ƒํ˜ธ์›์กฐ์กฐ์•ฝ์˜ ์ฒด๊ฒฐ ์‹œ๊ธฐ์™€ ๋ฏธ์˜์•ˆ๋ณดํ˜‘๋ ฅ์˜ ๋ณ€ํ™” ์‚ฌ์ด์˜ ๊ด€๊ณ„๋ฅผ ๋ฐํžˆ๋Š” ๊ฒƒ์ด๋‹ค. 1954๋…„ 5์›” ํŒŒํ‚ค์Šคํƒ„์€ ๋ฏธ๊ตญ๊ณผ์˜ ์ƒํ˜ธ๋ฐฉ์œ„์›์กฐํ˜‘์ •์„ ์ฒด๊ฒฐํ–ˆ๋‹ค. ๊ทธ ํ•ด ํ•˜๋ฐ˜๊ธฐ์— ํŒŒํ‚ค์Šคํƒ„์€ ๋™๋‚จ์•„์‹œ์•„ ์กฐ์•ฝ๊ธฐ๊ตฌ์— ๊ฐ€์ž…ํ•˜๊ณ , ์ผ ๋…„ ํ›„ ๋ฐ”๊ทธ๋‹ค๋“œ ์กฐ์•ฝ์— ์ฐธ์—ฌํ•˜๋ฉฐ ๋ฏธ๊ตญ์˜ ์ค‘๋™๋ฐฉ์œ„ ๊ตฌ์ƒ์— ํ˜‘์กฐํ–ˆ๋‹ค. ์ด์™€ ๊ฐ™์€ ์ผ๋ จ์˜ ๋ณ€ํ™”๋Š” ๋ฏธ๊ตญ์˜ ์ค‘๋™์ •์ฑ… ๋ณ€ํ™”์™€ ๊นŠ์€ ๊ด€๋ จ์„ ๋งบ๊ณ  ์žˆ์—ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ๋ฏธ๊ตญ ํŒŒํ‚ค์Šคํƒ„ ๊ตฐ์‚ฌ๋™๋งน์ด ๋ฏธ๊ตญ์ด ๋ฏธ์˜ํ˜‘๋ ฅ์—์„œ ๋ฒ—์–ด๋‚˜ ๋…์ž์ ์ธ ์ค‘๋™์ •์ฑ…์„ ์ˆ˜๋ฆฝํ•˜์˜€๊ธฐ์— ์ฒด๊ฒฐ๋˜์—ˆ๋‹ค๊ณ  ์ฃผ์žฅํ•œ๋‹ค. ์ด์™€ ๊ฐ™์€ ์ฃผ์žฅ์€ ๊ธฐ์กด ์—ฐ๊ตฌ๋“ค์ด ์ œ์‹œํ•˜๋Š” ๋‘ ๊ฐ€์ง€ ๋ณ€์ˆ˜, ์ฆ‰ ์ธ๋„ ์™ธ๊ต์˜ ๊ฒฝ์ง์„ฑ๊ณผ ํŒŒํ‚ค์Šคํƒ„์˜ ์ง€์ •ํ•™์  ์ค‘์š”์„ฑ์ด ๋ฏธ๊ตญ ํŒŒํ‚ค์Šคํƒ„ ๋™๋งน์—์„œ ๊ฐ€์žฅ ์ค‘์š”ํ•จ์„ ๋ถ€์ •ํ•˜์ง€๋Š” ์•Š๋Š”๋‹ค. ๋Œ€์‹  ๋ณธ ์—ฐ๊ตฌ๋Š” 1954๋…„์ด๋ผ๋Š” ํŠน์ • ์‹œ์ ์— ๋‘ ๊ตญ๊ฐ€ ์‚ฌ์ด์— ๋™๋งน์ด ๋งบ์–ด์งˆ ์ˆ˜ ์žˆ์—ˆ๋˜ ์ด์œ ๋ฅผ ์ค‘๋™์ •์ฑ… ์ˆ˜๋ฆฝ ๊ณผ์ •์—์„œ ๋‚˜ํƒ€๋‚œ ๋ฏธ์˜์ •์ฑ…ํ˜‘๋ ฅ์˜ ์™€ํ•ด์—์„œ ์ฐพ๋Š”๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ๋ฏธ๊ตญ์˜ ์„œ๋‚จ์•„์‹œ์•„ ์ •์ฑ…์ด ํ˜•์„ฑ๋œ ๊ถค์ ์„ ์‹œ๊ธฐ ๊ตฌ๋ถ„์— ์ฃผ๋ชฉํ•˜๋ฉด์„œ ๋Œ์•„๋ณด์•˜๋‹ค. ์‚ฌํƒœ์˜ ์ถ”์ด๋Š” ํฌ๊ฒŒ ์„ธ ๋‹จ๊ณ„๋ฅผ ๊ฑฐ์นœ๋‹ค. ์šฐ์„  ์ œ 1๊ธฐ๋Š” 2์ฐจ ์„ธ๊ณ„๋Œ€์ „ ์ข…์ „ ์ด์ „๋ถ€ํ„ฐ ์ด์ง‘ํŠธ ์ฟ ๋ฐํƒ€ ์ด์ „๊นŒ์ง€๋กœ ๋ณผ ์ˆ˜ ์žˆ๋‹ค. ์ด ์‹œ๊ธฐ ๋ฏธ๊ตญ์˜ ์„œ๋‚จ์•„์‹œ์•„ ์ •์ฑ…์€ ๊ฐ„์ ‘ ๊ฐœ์ž…์˜ ํ˜•ํƒœ๋ฅผ ๋ ์—ˆ๋‹ค. ๊ทธ ์›์ธ์€ ์˜์ง€์˜ ๋ถ€์žฌ์—์„œ ์ฐพ์„ ์ˆ˜ ์žˆ๋‹ค. ์†Œ๋ จ๊ณผ์˜ ๋Œ€๊ฒฐ๊ตฌ๋„๊ฐ€ ๊ฐ€์‹œํ™”ํ•˜๋Š” ๊ณผ์ •์—์„œ๋„ ๋ฏธ๊ตญ์€ ๋ถˆํ•„์š”ํ•œ ํž˜์˜ ํ–‰์‚ฌ๋ฅผ ๊ฒฝ๊ณ„ํ–ˆ๋‹ค. ์—ฌ๊ธฐ์— ๋”ํ•ด ์„œ๋‚จ์•„์‹œ์•„๋Š” ๋ฏธ๊ตญ ๋Œ€์™ธ์ •์ฑ… ๊ฒฐ์ •๊ถŒ์ž๋“ค์—๊ฒŒ ๋งค์šฐ ์ƒ๊ฒฝํ•œ ์ง€์—ญ์ด์—ˆ๋‹ค. ์ด์™€ ๊ฐ™์€ ์ด์œ ๋กœ ์ด ์‹œ๊ธฐ ์ค‘๋™์ง€์—ญ์—์„œ ๋ฏธ๊ตญ์€ ์˜๊ตญ๊ณผ์˜ ํŒŒํŠธ๋„ˆ ์—ญํ• ์— ๋งŒ์กฑํ•˜๋ฉฐ ์˜๊ตญ ์ฃผ๋„์˜ ์ง€์—ญ ์•ˆ๋ณด์ฒด์ œ ๊ตฌ์„ฑ์— ๋™์˜ํ•˜๋Š” ๋ชจ์Šต์„ ๋ณด์˜€๋‹ค. ์ œ 2๊ธฐ๋Š” ์ด์ง‘ํŠธ ์ฟ ๋ฐํƒ€์—์„œ ๋ฏธ๊ตญ ํŒŒํ‚ค์Šคํƒ„ ๋™๋งน ์ฒด๊ฒฐ์— ์ด๋ฅด๋Š” ์‹œ๊ธฐ์ด๋‹ค. ์ด ์‹œ๊ธฐ ์˜๊ตญ ์ฃผ๋„์˜ ์ค‘๋™๋ฐฉ์œ„๊ตฌ์ƒ์€ ๊ตฌ์‹ฌ์  ์—ญํ• ์„ ํ•œ ์ด์ง‘ํŠธ์˜ ๋ณ€ํ™”๋กœ ์ธํ•˜์—ฌ ํ‘œ๋ฅ˜ํ•œ๋‹ค. ๋™ ์‹œ๊ธฐ ๋“ค์–ด์„  ์•„์ด์  ํ•˜์›Œ ํ–‰์ •๋ถ€๋Š” ํŠธ๋ฃจ๋จผ ํ–‰์ •๋ถ€ ๋ณด๋‹ค ์ ๊ทน์ ์œผ๋กœ ์†Œ๋ จ์˜ ์œ„ํ˜‘์— ์„ ์ œ์ ์œผ๋กœ ๋Œ€์ฒ˜ํ•˜๊ธฐ๋กœ ๊ฒฐ์ •ํ•˜์˜€๋‹ค. ๊ทธ๋ฆฌ๊ณ  ๊ทธ ๋ฐฉ์•ˆ์œผ๋กœ ๊ตญ๊ฐ€์˜ ์ƒ์กด๊ณผ ์ง€์—ญ ์•ˆ๋ณด์— ๋Œ€ํ•œ ์ฐธ์—ฌ๋ฅผ ๊ตํ™˜ํ•˜๋ฉฐ ์ผ๋ จ์˜ ์ง‘๋‹จ์•ˆ๋ณด์ฒด์ œ๋ฅผ ๋งŒ๋“ค๊ธฐ ์‹œ์ž‘ํ•œ๋‹ค. ๋ฏธ๊ตญ ํŒŒํ‚ค์Šคํƒ„ ๋™๋งน์˜ ๊ธฐ๋ณธ ๋…ผ๋ฆฌ ์—ญ์‹œ ๋ฐฉ์œ„์™€ ์ฐธ์—ฌ ๊ตํ™˜์˜ ์—ฐ์žฅ์„ ์ƒ์— ์žˆ์—ˆ๋‹ค. ์˜๊ตญ์˜ ์˜ํ–ฅ๋ ฅ ์•ฝํ™”๋ฅผ ๋ชฉ๋„ํ•˜๊ณ  ์ƒˆ๋กœ์šด ์ •๋ถ€๊ฐ€ ๋“ค์–ด์„  ๋ฏธ๊ตญ์€ ์ž๊ตญ ์ด์ต์— ๋ณด๋‹ค ๋ถ€ํ•ฉํ•˜๋Š” ์ƒˆ๋กœ์šด ์ง€์—ญ ์•ˆ๋ณด ์ฒด์ œ๋ฅผ ๊ตฌ์ถ•ํ•˜๋ ค ์‹œ๋„ํ•œ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ ์ œ 3๊ธฐ๋Š” ๋™๋งน ์ฒด๊ฒฐ ์ดํ›„๋ถ€ํ„ฐ ๋ฐ”๊ทธ๋‹ค๋“œ ์กฐ์•ฝ ์ฒด๊ฒฐ๊นŒ์ง€์˜ ์‹œ๊ธฐ์ด๋‹ค. ๋ฏธ๊ตญ ์ฃผ๋„์˜ ์„œ๋‚จ์•„์‹œ์•„ ์ง€์—ญ ์งˆ์„œ ๊ฐœํŽธ์€ ๋™๋‚จ์•„์‹œ์•„ ์กฐ์•ฝ๊ธฐ๊ตฌ์™€ ๋ฐ”๊ทธ๋‹ค๋“œ ์กฐ์•ฝ์œผ๋กœ ๋Œ€ํ‘œ๋˜๋Š” ์ƒˆ๋กœ์šด ์ง€์—ญ์•ˆ๋ณด๊ธฐ๊ตฌ๋“ค์˜ ์ฐฝ์„ค๋กœ ์—ฐ๊ฒฐ๋˜์—ˆ๋‹ค. ์ด์™€ ๊ฐ™์€ ๋ณ€ํ™”๋กœ ์ธํ•ด ๋ฏธ๊ตญ์€ ๋™๋งน ์ฒด์ œ๋ฅผ ๊ตฌ์ถ•ํ•œ ๋‹ค์–‘ํ•œ ์ง€์—ญ์—์„œ ์ง€์—ญ ๊ฐˆ๋“ฑ์— ๋Œ€ํ•œ ์ฑ…์ž„์„ ์งˆ ํ•„์š”์„ฑ์— ๋…ธ์ถœ๋˜์—ˆ๋‹ค. ๋˜ํ•œ ์ƒˆ๋กœ์šด ๊ฐœ์ž…์ „๋žต์€ ์ง€์—ญ ๊ตญ๊ฐ€๋“ค์˜ ๋ฐ˜๋ฐœ๊ณผ ์šฐ๋ ค๋ฅผ ๋‚ณ์•˜๋‹ค. ๋™๋งน์˜ ์ฒด๊ฒฐ์€ ๊ฐ€๊นŒ์ด๋Š” ์ธ๋„์™€ ์†Œ๋ จ์˜ ๋ฐ˜๋ฐœ์„ ๊ฐ€์ ธ์™”๋‹ค. ๋˜ํ•œ ๋™๋งน ์‹œ ๊ณ ๋ คํ•œ ์„œ๋กœ์˜ ์˜๋„ ์ฐจ์ด๋Š” ์žฅ๊ธฐ์ ์œผ๋กœ ๋™๋งน๊ตญ์ธ ํŒŒํ‚ค์Šคํƒ„์˜ ๋ฐ˜๋ฐœ๊นŒ์ง€ ๋ถˆ๋Ÿฌ์™”๋‹ค. ๋ฏธ๊ตญ ํŒŒํ‚ค์Šคํƒ„ ๋™๋งน์˜ ์‚ฌ๋ก€๋Š” ์ค‘๋™ ์ด์™ธ ์ง€์—ญ์˜ ์ง‘๋‹จ์•ˆ๋ณด์งˆ์„œ ์ˆ˜๋ฆฝ๊ณผ ๊ทธ ์‹คํŒจ ๊ณผ์ •์— ๋Œ€ํ•ด์„œ๋„ ์ถ”๊ฐ€์ ์ธ ์„ค๋ช…์„ ๊ฐ€๋Šฅ์ผ€ ํ•œ๋‹ค. ๊ทธ ๋Œ€ํ‘œ์ ์ธ ์‚ฌ๋ก€๋กœ๋Š” ๋™ ์‹œ๊ธฐ ์ด๋ฃจ์–ด์ง„ ๋™๋‚จ์•„์‹œ์•„ ์ง‘๋‹จ์•ˆ๋ณด์ฒด์ œ ๊ตฌ์ถ• ์‹œ๋„์™€ ์‹คํŒจ ๊ณผ์ •์„ ๋“ค ์ˆ˜ ์žˆ๋‹ค. ๋˜ํ•œ ๋ฏธ์˜ํ˜‘๋ ฅ์˜ ๊ฐ•ํ™”์™€ ์™€ํ•ด ๊ณผ์ •์€ ๋Œ€์™ธ์ •์ฑ… ๊ฒฐ์ •๊ถŒ์ž๋“ค์ด ์ƒํ™ฉ์˜ ๋ถˆํ™•์‹ค์„ฑ ์†์—์„œ ์ƒˆ๋กœ์šด ๋Œ€์•ˆ์„ ๋ชจ์ƒ‰ํ•˜๋Š” ๊ณผ์ •์„ ์ž˜ ๋ณด์—ฌ์ค€๋‹ค. ์ด ์ ์—์„œ ๋ณธ ์—ฐ๊ตฌ๋Š” ์ •์ฑ…์ด ๋นš์–ด์ง€๋Š” ๊ณผ์ •์„ ๋“ค์–ด ํ•œ ์ •์ฑ…์ด ์‹ค์ œ๋กœ ๊ณต๊ณ ํ™”๋˜๊ธฐ ์ „ ๋นš์–ด์ง„ ์‹œํ–‰์ฐฉ์˜ค๋ฅผ ๋ณด์—ฌ์ฃผ๋Š” ์˜์˜๋ฅผ ์ง€๋‹Œ๋‹ค.โ… . ์„œ๋ก ........................................................................1 1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ..................................................................1 2. ์„ ํ–‰ ์—ฐ๊ตฌ..................................................................3 3. ์—ฐ๊ตฌ ๊ฐ€์„ค..................................................................6 4. ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• ๋ฐ ์ž๋ฃŒ ์ด์šฉ...............................................10 โ…ก. ๋ฏธ๊ตญ-ํŒŒํ‚ค์Šคํƒ„ ์ƒํ˜ธ๋ฐฉ์œ„์›์กฐํ˜‘์ •์˜ ์„ฑ๋ฆฝ......................13 1. ๋ฏธ๊ตญ ํŒŒํ‚ค์Šคํƒ„ ๊ตฐ์‚ฌ๋™๋งน๊ณผ ์•„์ด์  ํ•˜์›Œ ์ •๋ถ€์˜ ๋“ฑ์žฅ..........14 2. ๋ฏธ๊ตญ ํŒŒํ‚ค์Šคํƒ„ ํ˜‘์ƒ์˜ ์ „๊ฐœ์™€ ๊ฒฐ๊ณผ................................18 3. ๋ฏธ๊ตญ ํŒŒํ‚ค์Šคํƒ„ ์ƒํ˜ธ๋ฐฉ์œ„์›์กฐํ˜‘์ •์˜ ์˜๋ฏธ........................22 4. ์†Œ๊ฒฐ........................................................................25 โ…ข. ๋ƒ‰์ „ ํ˜•์„ฑ๊ธฐ ๋ฏธ์˜ ์„œ๋‚จ์•„์‹œ์•„ ์ •์ฑ… ํ˜‘๋ ฅ (1948-1951).......26 1. ๋ƒ‰์ „ ํ˜•์„ฑ๊ธฐ ๋ฏธ๊ตญ ๋Œ€์™ธ์ •์ฑ…๊ณผ ์ค‘๋™์ •์ฑ…์˜ ํƒ„์ƒ...............27 2. ๋ฏธ๊ตญ ๋Œ€์™ธ์ •์ฑ…์˜ ์ „๊ฐœ์™€ ๋‚จ์•„์‹œ์•„, ๊ทธ๋ฆฌ๊ณ  ์นด์Šˆ๋ฏธ๋ฅด.........30 3. ๋ƒ‰์ „ ํ˜•์„ฑ๊ธฐ ๋Œ€์˜์ œ๊ตญ ํ•ด์ฒด์™€ ์ค‘๋™์ •์ฑ…..........................34 4. ๋Œ€์˜์ œ๊ตญ์˜ ํ•ด์ฒด์™€ ๋‚จ์•„์‹œ์•„ ์ •์ฑ… ๊ตฌ์ƒ..........................38 5. ์†Œ๊ฒฐ........................................................................44 โ…ฃ. ์ค‘๋™๋ฐฉ์œ„๊ธฐ๊ตฌ - ๊ตฌ์ƒ๊ณผ ํ•œ๊ณ„ (1951-1953)......................46 1. ๋ฏธ๊ตญ ๋Œ€์ „๋žต ์ „ํ™˜๊ณผ ์ค‘๋™๋ฐฉ์œ„๊ธฐ๊ตฌ ๊ตฌ์ƒ..........................46 2. ์ค‘๋™๋ฐฉ์œ„๊ธฐ๊ตฌ ๊ตฌ์ƒ์˜ ๋“ฑ์žฅ๊ณผ ๋ฏธ์˜ํ˜‘๋ ฅ์˜ ๊ตฌ์ฒดํ™”..............50 3. ์ค‘๋™๋ฐฉ์œ„๊ตฌ์ƒ์˜ ๋Œ€์•ˆํƒ์ƒ‰๊ณผ ๋ฏธ๊ตญ ํŒŒํ‚ค์Šคํƒ„ ์—ฐ๊ณ„ ๊ฐ•ํ™”.......55 4. ์˜๊ตญ ์ฃผ๋„ ์ค‘๋™๋ฐฉ์œ„๊ธฐ๊ตฌ ๊ตฌ์ƒ์˜ ์ „๊ฐœ์™€ ๊ทธ ๋…ผ๋ฆฌ...............59 5. ์˜๊ตญ์˜ ๋Œ€ ํŒŒํ‚ค์Šคํƒ„ ์ •์ฑ…๊ณผ ๊ทธ ๋ฐ˜ํ–ฅ...............................64 6. ์†Œ๊ฒฐ........................................................................70 โ…ค. ๋ฏธ๊ตญ-ํŒŒํ‚ค์Šคํƒ„ ๊ตฐ์‚ฌ๋™๋งน โ€“ ์ง‘๋‹จ์•ˆ๋ณด์™€ ์ •์ฑ…์ „ํ™˜(1953-1956)..........................................................................72 1. ๋ฏธ๊ตญ-ํŒŒํ‚ค์Šคํƒ„ ๋™๋งน๊ณผ ์•„์ด์  ํ•˜์›Œ ์ •๋ถ€์˜ ์ง€์—ญ์•ˆ๋ณด ๊ตฌ์ƒ...72 2. ๋ฏธ๊ตญ-ํŒŒํ‚ค์Šคํƒ„ ๋™๋งน์˜ ์„ฑ๋ฆฝ๊ณผ ์‹ ์ค‘๋™์ •์ฑ…์˜ ๋“ฑ์žฅ.............76 3. ์ค‘๋™๋ฐฉ์œ„๊ตฌ์ƒ์˜ ์ขŒ์ดˆ์™€ ๋ฏธ์˜๊ด€๊ณ„ ์•…ํ™”...........................80 4. ๋ฏธ๊ตญ-ํŒŒํ‚ค์Šคํƒ„ ๋™๋งน ์ดํ›„ - ๊ฐˆ๋“ฑ๊ตฌ์กฐ ๊ณต๊ณ ํ™”์™€ ์ง€์—ญ ๋ถˆ์•ˆ์ • ..................................................................................86 5. ์†Œ๊ฒฐ........................................................................92 โ…ฅ. ๊ฒฐ๋ก .......................................................................93 ์ฐธ๊ณ ๋ฌธํ—Œ......................................................................98 Abstract.....................................................................104 ํ‘œ ํ‘œ 1> ๋ฏธ๊ตญ์˜ ์˜๊ตญ-์ด์ง‘ํŠธ ํ˜‘์ƒ ์ค‘์žฌ์•ˆ..............................74 ํ‘œ 2> 1955๋…„ ์ด์Šคํƒ„๋ถˆ ํšŒ์˜์‹œ ํ•ฉ์˜๋œ ๋ฏธ๊ตญ์˜ ์ค‘๋™์ •์ฑ… ๋Œ€๊ฐ•...............................................................................77Maste

    Performance Enhancement Techniques for Sound Event Classification in Reverberant Environment

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์œตํ•ฉ๊ณผํ•™๊ธฐ์ˆ ๋Œ€ํ•™์› ์œตํ•ฉ๊ณผํ•™๋ถ€(๋””์ง€ํ„ธ์ •๋ณด์œตํ•ฉ์ „๊ณต),2019. 8. ์ด๊ต๊ตฌ.๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ž”ํ–ฅ ํ™˜๊ฒฝ์—์„œ์˜ ์‚ฌ์šด๋“œ ์ด๋ฒคํŠธ ๋ถ„๋ฅ˜์‹œ ์„ฑ๋Šฅ์„ ๊ฐœ์„ ํ•˜๋Š” ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ์‚ฌ์šด๋“œ ์ด๋ฒคํŠธ ๋ถ„๋ฅ˜๋Š” ๊ตํ†ต ์ƒํ™ฉ, ๋ฐฉ๋ฒ” ์ƒํ™ฉ ๊ฐ์ง€ ์‹œ์Šคํ…œ ๋“ฑ ๋‹ค์–‘ํ•œ ์‘์šฉ๋ถ„์•ผ์— ํ™œ๋ฐœํ•˜๊ฒŒ ์ ์šฉ๋˜๊ณ  ์žˆ๊ณ  ์‘์šฉ๋ถ„์•ผ์˜ ํŠน์„ฑ์ƒ ์‹ค์ œ ํ™˜๊ฒฝ์˜ ์žก์Œ๊ณผ ์ž”ํ–ฅ์— ๊ฐ•์ธํ•œ ์„ฑ๋Šฅ์„ ๊ฐ–๋Š” ๊ฒƒ์ด ์ค‘์š”ํ•œ ๋ฌธ์ œ์ด๋‹ค. ํ•˜์ง€๋งŒ ์ด๋Ÿฐ ์žก์Œ๊ณผ ์ž”ํ–ฅ ํ™˜๊ฒฝ์—์„œ์˜ ์‚ฌ์šด๋“œ ์ด๋ฒคํŠธ ๋ถ„๋ฅ˜ ์„ฑ๋Šฅ ์ €ํ•˜์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋Š” ์ €์กฐํ•˜๋ฉฐ ํŠนํžˆ ์ž”ํ–ฅ ํ™˜๊ฒฝ์—์„œ์˜ ์‚ฌ์šด๋“œ ์ด๋ฒคํŠธ ๋ถ„๋ฅ˜ ์—ฐ๊ตฌ๋Š” ์ „๋ฌดํ•œ ์‹ค์ •์ด๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ž”ํ–ฅ ํ™˜๊ฒฝ์—์„œ ์‚ฌ์šด๋“œ ์ด๋ฒคํŠธ ๋ถ„๋ฅ˜ ์„ฑ๋Šฅ์ด ์ €ํ•˜๋˜๋Š” ๊ฒƒ์„ ๊ด€์ฐฐํ•˜๊ณ  ์ด๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•œ ๊ฐœ์„  ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ๋จผ์ €, ์ž”ํ–ฅ ํ™˜๊ฒฝ์„ ๋ชจ๋ธ๋ง ํ•˜๊ธฐ ์œ„ํ•ด ์›๋ณธ ๋ฐ์ดํ„ฐ์…‹์„ ์ž”ํ–ฅ์ด ์กด์žฌํ•˜๋Š” ์‹ค์ œ ํ™˜๊ฒฝ์—์„œ ์žฌ๋…น์Œํ•œ ๋…น์Œ ํ…Œ์ŠคํŠธ์…‹๊ณผ ๊ณต๊ฐ„ ์ž„ํŽ„์Šค ์‘๋‹ต ๋ฐ์ดํ„ฐ์…‹์„ ์ด์šฉํ•˜์—ฌ ํ•ฉ์„ฑํ•œ ํ•ฉ์„ฑ ํ…Œ์ŠคํŠธ์…‹์„ ์ œ์ž‘ํ•˜์˜€๊ณ , ์ด๋ฅผ ์ด์šฉํ•˜์—ฌ ์ž”ํ–ฅ ํ™˜๊ฒฝ์—์„œ ์‚ฌ์šด๋“œ ์ด๋ฒคํŠธ ๋ถ„๋ฅ˜ ์„ฑ๋Šฅ์ด ์ €ํ•˜๋จ์„ ๊ด€์ฐฐํ•˜์˜€๋‹ค. ์„ฑ๋Šฅ ์ €ํ•˜์— ๋Œ€ํ•œ ๊ฐœ์„  ๊ธฐ๋ฒ•์œผ๋กœ ์ธ์œ„์ ์œผ๋กœ ์ œ์ž‘ํ•œ ๊ฐ€์ƒ ๊ณต๊ฐ„ ์ž„ํŽ„์Šค ์‘๋‹ต์„ ์ด์šฉํ•œ ๋ฐ์ดํ„ฐ ์ฆ๊ฐ€ ๋ฐฉ๋ฒ•๊ณผ ๊ณต๊ฐ„ ์ž„ํŽ„์Šค ์‘๋‹ต์„ ๋„คํŠธ์›Œํฌ์— ์ปจ๋””์…”๋‹ํ•˜๋Š” ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•˜์˜€๋‹ค. ์‹คํ—˜์„ ํ†ตํ•ด ์ œ์•ˆํ•œ ๋ฐ์ดํ„ฐ ์ฆ๊ฐ€ ๋ฐฉ๋ฒ•์ด ์ž”ํ–ฅ ํ™˜๊ฒฝ์—์„œ์˜ ์„ฑ๋Šฅ์„ ๊ฐœ์„ ํ•จ์„ ๊ฒ€์ฆํ•˜๋ฉฐ, ํŠนํžˆ ๋ฐ์ดํ„ฐ ์ฆ๊ฐ€ ๋ฐฉ๋ฒ•๊ณผ ์ปจ๋””์…”๋‹ ๊ธฐ๋ฒ•์„ ํ•จ๊ป˜ ์‚ฌ์šฉํ–ˆ์„ ๋•Œ ์ถ”๊ฐ€์ ์œผ๋กœ ์„ฑ๋Šฅ์ด ํ–ฅ์ƒ๋จ์„ ๋ณด์ธ๋‹ค. ๋˜ํ•œ ์ œ์•ˆํ•œ ์ปจ๋””์…”๋‹ ๊ธฐ๋ฒ•์ด ์ •ํ™•ํ•œ ๊ณต๊ฐ„ ์ž„ํŽ„์Šค ์‘๋‹ต ์˜ค๋””์˜ค๋ฅผ ๋ชจ๋ฅผ ๋•Œ๋ผ๋„ ๋Œ€๋žต์  ์ž”ํ–ฅ ์‹œ๊ฐ„ ์ •๋ณด๋ฅผ ํ†ตํ•ด ์„ฑ๋Šฅ์„ ํ–ฅ์ƒ์‹œํ‚ฌ ์ˆ˜ ์žˆ์Œ์„ ๋ณด์ธ๋‹ค.In this paper, we propose techniques to enhance performance of sound event classification in reverberant environment. Sound event classification is actively applied to various application fields such as anomaly detection system, and it is important to maintain robust performance in real-world environments. In real-world environments, noise and reverberation are the main factors that degrade the performance of sound event classification. However, the research on sound event classification in noisy and especially reverberant environments is poor. Therefore, in this paper, we observe the degradation phenomenon of sound event classification in reverberant environments and propose performance enhancement techniques for this phenomenon. To do this, we build a test set that models the reverberant environments and observe that sound event classification performance of the test set is degraded. In order to improve the performance, we propose a data augmentation method using an artificially synthesized room impulse response and a method of conditioning the room impulse response to the network. Experimental results show that the proposed data augmentation method improves performance in reverberant environments. It also demonstrates additional performance improvements when using with the proposed conditioning method together. Finally, we show that the proposed method improves the performance by using approximate reverberation time information even when accurate room impulse response audio is not known.์ œ1์žฅ ์„œ๋ก  6 1.1 ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ 6 1.2 ์—ฐ๊ตฌ ๋ชฉํ‘œ 9 ์ œ2์žฅ ๋ฐฐ๊ฒฝ ์ด๋ก  ๋ฐ ๊ด€๋ จ ์—ฐ๊ตฌ 10 2.1 ๋ฐฐ๊ฒฝ ์ด๋ก  10 2.1.1 ์‚ฌ์šด๋“œ ์ด๋ฒคํŠธ ๋ถ„๋ฅ˜ 10 2.1.2 ๋”ฅ๋Ÿฌ๋‹ ์—ฐ๊ตฌ 12 2.1.3 ์ž”ํ–ฅ ๋ฐ ๊ณต๊ฐ„ ์ž„ํŽ„์Šค ์‘๋‹ต 16 2.2 ๊ด€๋ จ ์—ฐ๊ตฌ 19 2.2.1 ์‚ฌ์šด๋“œ ์ด๋ฒคํŠธ ๋ถ„๋ฅ˜ ์—ฐ๊ตฌ 19 2.2.2 ์ œ์•ˆ ๊ธฐ๋ฒ• ๊ด€๋ จ ์—ฐ๊ตฌ 25 ์ œ3์žฅ ์ œ์•ˆ ๊ธฐ๋ฒ• 28 3.1 ๊ฐ€์ƒ ๊ณต๊ฐ„ ์ž„ํŽ„์Šค ์‘๋‹ต์„ ์ด์šฉํ•œ ๋ฐ์ดํ„ฐ ์ฆ๊ฐ€๋ฐฉ๋ฒ• 28 3.2 ๊ณต๊ฐ„ ์ž„ํŽ„์Šค ์‘๋‹ต ์ปจ๋””์…”๋‹ ๋„คํŠธ์›Œํฌ 31 ์ œ4์žฅ ์‹คํ—˜ 34 4.1 ์‹คํ—˜ ์ค€๋น„ 34 4.1.1 ๋ฐ์ดํ„ฐ์…‹ 34 4.1.2 ํ…Œ์ŠคํŠธ์…‹ ์ œ์ž‘ ๋ฐฉ๋ฒ• 35 4.1.3 ์‹คํ—˜ ์ƒ์„ธ ์„ค์ • 38 4.2 ์‹คํ—˜ ๊ฒฐ๊ณผ ๋ฐ ํ† ๋ก  42 4.2.1 ์ž”ํ–ฅ ํ™˜๊ฒฝ์—์„œ์˜ ์‚ฌ์šด๋“œ ์ด๋ฒคํŠธ ๋ถ„๋ฅ˜ ์„ฑ๋Šฅ ์ €ํ•˜ 42 4.2.2 ๋””์ปจ๋ณผ๋ฃจ์…˜ ์ ์šฉ ์‹œ ์„ฑ๋Šฅ ๋ฐ ํ•œ๊ณ„์  47 4.2.3 ๋ฐ์ดํ„ฐ ์ฆ๊ฐ€ ๋ฐฉ๋ฒ•์„ ์ด์šฉํ•œ ์„ฑ๋Šฅ ํ–ฅ์ƒ 49 4.2.4 ์ปจ๋””์…”๋‹ ๋„คํŠธ์›Œํฌ๋ฅผ ์ด์šฉํ•œ ์„ฑ๋Šฅ ํ–ฅ์ƒ 50 ์ œ5์žฅ ๊ฒฐ๋ก  58 5.1 ์—ฐ๊ตฌ ์˜์˜ 58 5.2 ํ•œ๊ณ„์  60 5.3 ํ–ฅํ›„ ์—ฐ๊ตฌ 61 ABSTRACT 68 ๊ฐ์‚ฌ์˜๊ธ€ 70Maste

    Chinas naval power buildup and security dilemma

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ •์น˜์™ธ๊ตํ•™๋ถ€, 2014. 8. ๋ฐฑ์ฐฝ์žฌ.์ค‘๊ตญ์˜ ๋ถ€์ƒ์ด ๊ตญ์ œ์ •์น˜ ์งˆ์„œ์— ์–ด๋–ค ์˜ํ–ฅ์„ ๋ฏธ์น ์ง€๋Š” ์„ธ๊ณ„์  ๊ด€์‹ฌ์‚ฌ์ด๋‹ค. ํ•œํŽธ์—์„  ์ค‘๊ตญ์ด ๋ฏธ๊ตญ๊ณผ ํŒจ๊ถŒ ๊ฒฝ์Ÿ์„ ๋ฒŒ์ด๋ฉด์„œ ๊ตฐ์‚ฌ์  ์ถฉ๋Œ์„ ๋ฒŒ์ผ ๊ฒƒ์ด๋ผ๊ณ  ์ฃผ์žฅํ•˜๋Š” ๋ฐ˜๋ฉด ๋‹ค๋ฅธ ํ•œํŽธ์—์„  ์ค‘๊ตญ์€ ๋ฏธ๊ตญ์ด ์ฃผ๋„ํ•˜๋Š” ๊ตญ์ œ์งˆ์„œ์— ํ‰ํ™”์ ์œผ๋กœ ํŽธ์ž…ํ•  ๊ฒƒ์ด๋ผ๋Š” ์ฃผ์žฅํ•œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ง€๊ธˆ๊นŒ์ง€ ๋Œ€๋ถ€๋ถ„ ์—ฐ๊ตฌ๋“ค์€ ์ค‘๊ตญ์˜ ๊ตฐ์‚ฌ์  ์ถฉ๋Œ ๊ฐ€๋Šฅ์„ฑ์„ ๋‹ค๋ฃจ๋ฉด์„œ๋„ ๊ทธ ๊ตฐ์‚ฌ๋ ฅ์˜ ์„ฑ๊ฒฉ์„ ๋ถ„์„ํ•˜์ง€ ์•Š์•˜๋‹ค๋Š” ๋ฐ ํ•œ๊ณ„๊ฐ€ ์žˆ๋‹ค. ์ค‘๊ตญ์˜ ๊ตฐ์‚ฌ์  ์œ„ํ˜‘์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋Š” ์ค‘๊ตญ์˜ ๊ตฐ์‚ฌ๋ ฅ์— ๋Œ€ํ•œ ์‹ค์ฆ์  ๋ถ„์„์„ ๋ฐ”ํƒ•์œผ๋กœ ์ด๋ค„์ ธ์•ผ ํ•œ๋‹ค. ์ด ๋…ผ๋ฌธ์€ ์ค‘๊ตญ์˜ ๊ตฐ์‚ฌ๋ ฅ, ๊ทธ ์ค‘์—์„œ๋„ ์ค‘๊ตญ ํ•ด๊ตฐ๋ ฅ ์ฆ๊ฐ•์˜ ์„ฑ๊ฒฉ์„ ๋ถ„์„ํ•œ๋‹ค. ํ•ด๊ตฐ๋ ฅ์€ ํŒจ๊ถŒ๊ตญ์ด ๋˜๋Š” ์ฃผ์š” ์ˆ˜๋‹จ์ด๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ๊ฐ•๋ ฅํ•œ ํ•ด๊ตฐ๋ ฅ์€ ๋ฐ”๋‹ค๋ผ๋Š” ์žฅ์• ๋ฅผ ๋„˜์–ด ์„ธ๊ณ„ ๊ณณ๊ณณ์— ๊ตฐ์‚ฌ๋ ฅ์„ ํˆฌ์‚ฌํ•  ์ˆ˜ ์žˆ๋Š” ์ „๋ ฅ์ด๋‹ค. ์œก๊ตฐ์€ ์ธ์ ‘ํ•œ ์ฃผ๋ณ€๊ตญ์— ์˜ํ–ฅ๋ ฅ์„ ๋ฐœํœ˜ํ•˜๋Š” ์ˆ˜๋‹จ์ธ ๋ฐ˜๋ฉด ํ•ด๊ตฐ์€ ๋ฐ”๋‹ค๋ผ๋Š” ์žฅ๋ฒฝ์„ ๋„˜์–ด ์„ธ๊ณ„ ๊ณณ๊ณณ์— ์˜ํ–ฅ๋ ฅ์„ ๋ฐœํœ˜ํ•  ์ˆ˜ ์žˆ๋Š” ์ „๋ ฅ์ด๋‹ค. ์ด ๋•Œ๋ฌธ์— ์ค‘๊ตญ์˜ ํ•ด๊ตฐ๋ ฅ ์ฆ๊ฐ•์€ ์ฃผ๋ณ€๊ตญ, ๋ฏธ๊ตญ๊ณผ์˜ ๊ตฐ์‚ฌ์  ๋งˆ์ฐฐ์„ ๋ถˆ๋Ÿฌ์˜ฌ ์ˆ˜ ์žˆ๋‹ค. ๋กœ๋ฒ„ํŠธ ์ €๋น„์Šค์˜ ๊ณต๊ฒฉ ๋ฐฉ์–ด ๊ท ํ˜• ์ด๋ก ์€ ์–ด๋–ค ๊ฒฝ์šฐ์— ๊ตฐ๋น„ ๊ฒฝ์Ÿ์ด ๊ฒฉํ™”๋ผ ๊ตฐ์‚ฌ์  ์ถฉ๋Œ๋กœ ์ด์–ด์ง€๋Š” ์•ˆ๋ณด ๋”œ๋ ˆ๋งˆ๊ฐ€ ์ดˆ๋ž˜๋˜๋Š”์ง€๋ฅผ ์„ค๋ช…ํ•œ๋‹ค. ์ €๋น„์Šค๋Š” ๊ตฐ์‚ฌ๋ ฅ ์ฆ๊ฐ•์˜ ์„ฑ๊ฒฉ๊ณผ ์˜๋„์— ๋”ฐ๋ผ ์•ˆ๋ณด๋”œ๋ ˆ๋งˆ๊ฐ€ ๋‹ค๋ฅด๊ฒŒ i ๋‚˜ํƒ€๋‚  ์ˆ˜ ์žˆ๋‹ค๊ณ  ๋ดค๋‹ค. ๊ทธ์˜ ์ด๋ก ์„ ๋ฐ”ํƒ•์œผ๋กœ ์ค‘๊ตญ์˜ ํ•ด๊ตฐ๋ ฅ ์ฆ๊ฐ•์ด ๊ตญ์ œ ์งˆ์„œ์— ๋ผ์น  ์˜ํ–ฅ์„ ๋ถ„์„ํ•  ์ˆ˜ ์žˆ๋‹ค. ๊ทธ๋Š” ๋ฌด๊ธฐ์ฒด๊ณ„์˜ ์„ฑ๊ฒฉ์ด ๊ณต๊ฒฉ์šฐ์œ„์ด๋ฉด์„œ ๊ณต๊ฒฉ ๋ฐฉ์–ด ์˜๋„๋ฅผ ๊ตฌ๋ถ„ํ•˜๊ธฐ ์–ด๋ ค์šธ ๋•Œ ์•ˆ๋ณด๋”œ๋ ˆ๋งˆ ๊ฐ€๋Šฅ์„ฑ์ด ๊ฐ€์žฅ ๋†’๋‹ค๊ณ  ํ–ˆ๋‹ค. ๋ฐ˜๋ฉด ๋ฌด๊ธฐ์ฒด๊ณ„๊ฐ€ ๋ฐฉ์–ด ์šฐ์œ„์ด๋ฉด์„œ ๊ณต๊ฒฉ ๋ฐฉ์–ด ์˜๋„๊ฐ€ ๊ตฌ๋ถ„๋  ๋•Œ ์•ˆ๋ณด๋”œ๋ ˆ๋งˆ ๊ฐ€๋Šฅ์„ฑ์ด ๊ฐ€์žฅ ๋‚ฎ๋‹ค๊ณ  ํ–ˆ๋‹ค. ์ค‘๊ตญ ํ•ด๊ตฐ์€ 1950๋…„๋Œ€๋ถ€ํ„ฐ 1970๋…„๋Œ€ ์ค‘๋ฐ˜๊นŒ์ง€ ๋ฐฉ์–ด์  ์˜๋„๊ฐ€ ๋ช…ํ™•ํ•˜๊ฒŒ ๋“œ๋Ÿฌ๋‚ฌ๋‹ค. ์ค‘๊ตญ์˜ ์œ„ํ˜‘์„ ๋ฏธ๊ตญ์œผ๋กœ ๋ณผ ๊ฒƒ์ธ์ง€, ์†Œ๋ จ์œผ๋กœ ๋ณผ ๊ฒƒ์ธ์ง€์— ๋Œ€ํ•œ ์ธ์‹์—๋Š” ๋ณ€ํ™”๊ฐ€ ์žˆ์—ˆ์ง€๋งŒ ํ•ด๊ตฐ ์ „๋žต์˜ ์ดˆ์ ์€ ์–ด๋””๊นŒ์ง€๋‚˜ ์—ฐ์•ˆ ๋ฐฉ์–ด์— ์žˆ์—ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ดํ›„ ์ค‘๊ตญ ํ•ด๊ตฐ ๋ฌด๊ธฐ์ฒด๊ณ„๊ฐ€ ๊ณต๊ฒฉ ์šฐ์œ„๋กœ ๋ฐ”๋€Œ๊ณ  ๊ทธ ์˜๋„๋Š” ๋ชจํ˜ธํ•ด์กŒ๋‹ค. ์ค‘๊ตญ์ด ํ™•๋ณดํ•˜๊ณ  ์žˆ๋Š” ํ•ญ๊ณต๋ชจํ•จ, ์ด์ง€์Šค ๊ตฌ์ถ•ํ•จ์€ ๊ณต๊ฒฉ ์šฐ์œ„ ์„ฑ๊ฒฉ์ด๋ฉฐ ์ค‘๊ตญ์€ ํ•ด๊ตฐ๋ ฅ ์ฆ๊ฐ•์˜ ์˜๋„๋ฅผ ๋ช…ํ™•ํ•˜๊ฒŒ ๋“œ๋Ÿฌ๋‚ด์ง€ ์•Š๊ณ  ์žˆ๋‹ค. ์ด๋Š” ์ €๋น„์Šค๊ฐ€ ์ œ์‹œํ•œ ์•ˆ๋ณด๋”œ๋ ˆ๋งˆ๊ฐ€ ์ด‰๋ฐœ๋˜๋Š” ๊ฐ€์žฅ ์œ„ํ—˜ํ•œ ๊ฒฝ์šฐ์— ํ•ด๋‹น๋œ๋‹ค. ๋ฏธ๊ตญ์€ ์ค‘๊ตญ์— ๊ตฐ์‚ฌ๋ ฅ ์ฆ๊ฐ•์˜ ์˜๋„๊ฐ€ ๋ชจํ˜ธํ•˜๋‹ค๊ณ  ์ง€์ ํ•˜๋ฉฐ ์ค‘๊ตญ์„ ๊ฒฌ์ œํ•˜๊ธฐ ์œ„ํ•ด ์•„์‹œ์•„, ํƒœํ‰์–‘ ์ง€์—ญ์— ํ•ด๊ตฐ ์ „๋ ฅ์„ ์ฆ๊ฐ•ํ•˜๊ณ  ์žˆ๋‹ค. ์ด๋ฅผ ๊ฒฌ์ œํ•˜๊ธฐ ์œ„ํ•ด ๋ฒ„๋ฝ ์˜ค๋ฐ”๋งˆ ๋ฏธ๊ตญ ๋Œ€ํ†ต๋ น์€ ์žฌ๊ท ํ˜• ์ „๋žต์„ ์ถ”์ง„ํ•˜๊ณ  ์žˆ๋‹ค. ๋ฏธ๊ตญ์€ 2020๋…„๊นŒ์ง€ ํ•ด๊ตฐ ํ•จ๋Œ€ 60%๋ฅผ ํƒœํ‰์–‘์œผ๋กœ ์ด๋™ ๋ฐฐ์น˜ํ•  ๊ณ„ํš์ด๋‹ค. ์ผ๋ณธ ์—ญ์‹œ ์ค‘๊ตญ ๊ตฐ์‚ฌ๋ ฅ ์ฆ๊ฐ•์„ ์ด์œ ๋กœ ํ•ด์ƒ์ž์œ„๋Œ€ ์ „๋ ฅ ํ™•๋Œ€๋ฅผ ๊พ€ํ•˜๋ฉฐ ์žˆ๋‹ค. ๋™๋ถ์•„์‹œ์•„์—์„œ ์•ˆ๋ณด ๋”œ๋ ˆ๋งˆ ์ƒํ™ฉ์ด ๊ฒฉํ™”๋˜๋ฉฐ ์ค‘๊ตญ, ๋ฏธ๊ตญ, ์ผ๋ณธ์ด ๊ตฐ๋น„ ๊ฒฝ์Ÿ์„ ๋ฒŒ์ด๋Š” ์ƒํ™ฉ์ด ๋นš์–ด์ง€๊ณ  ์žˆ๋Š” ๊ฒƒ์ด๋‹ค. ์ €๋น„์Šค์˜ ๊ณต๊ฒฉ ๋ฐฉ์–ด ๊ท ํ˜• ์ด๋ก ์ด ๋™๋ถ์•„์‹œ์•„ ๊ตญ์ œ ์ •์น˜ ์ƒํ™ฉ์—๋„ ๋งž์•„๋–จ์–ด์ง€๊ณ  ์žˆ๋Š” ๊ฒƒ์ด๋‹ค.How the rise of China would affect international politics arena is a matter of great concern for the globe. One argues China would fight US dominance in the western pacific region resulting in military conflict. Others say China would peacefully rise and fit into current world order conceived by the United States. Many of studies comtemplated China s possible military conflict but failed to analyze the nature of Chinas military development. Thus empirical assessment of Chinas military strength must precede to assess security risk posed by Beijings ever increasing military power. This article mainly focuses on development of China s naval forces. Naval power is central means to be a world hegemon. Army can be a useful source of power against neighboring states but it is naval force which enables hegemon s projection of power well beyond, overcoming oceans and seas. Therefore it might lead to Chinas confrontation over the waters with other countries, namely US. The offense-defense theory of Robert Jervis explains under what conditions intensity of the arms race rises whether it would lead to a military conflict caused by the security dilemma. Jervis pointed out that the nature and intentions of military build-up influence outcome of security dilemma. By applying his theory one may evaluate international outcome of Chinas naval power build-up. When offensive and defensive posture are not distinguishable but offense has an advantage the security dilemma is "very intense". Where offensive and defensive posture are distinguishable and defense has advantage the security dilemma has little intensity. China naval strategy heavily focused on the defensive until mid 1970s. US and Soviets view on the security risk of China may have fluctuated over the time. Still it was clear Chinas intent was for the defensive purposes. After 1970s China started to take more offensive position and Beijing s intentions became hard to interpret. China amassing aircraft carriers and aegis destroyers definitely shows offensive capabilities. Concerns were growing but China hasn t been showing indications whether newly acquired naval weapons were for the defense. By Jervis theory this could be labeled as very intense security dilemma situation. US points out China s intentions of expanding her military prowess are uncertain and tries to hold China in check by strengthening US naval forces in Asia and the Pacific Ocean. President Barack Obama has been implementing a new strategy named rebalance to Asia which aims to increases her presence through placing 60% of the US naval forces by 2020. Thus prompting arms race among the nations in North-east Asia which has been caused by the security dilemma. Jervis Offense- Defense Theory makes more sense given current North-east Asia s international dynamics and needs to be given more thoughts.์ œ 1 ์žฅ ์„œ ๋ก  1 ์ œ 1 ์ ˆ ๋ฌธ์ œ ์ œ๊ธฐ : ์ค‘๊ตญ์˜ ๋ถ€์ƒ์€ ํ‰ํ™”์ ์ผ ๊ฒƒ์ธ๊ฐ€? 1 ์ œ 2 ์ ˆ ๊ธฐ์กด ์—ฐ๊ตฌ์˜ ๊ฒ€ํ†  7 ์ œ 3 ์ ˆ ์—ฐ๊ตฌ์˜ ๊ตฌ์„ฑ 15 ์ œ 2 ์žฅ ์ด๋ก ๊ณผ ๋ฐฉ๋ฒ•๋ก  16 ์ œ 1 ์ ˆ ๊ณต๊ฒฉ ๋ฐฉ์–ด ๊ท ํ˜• ์ด๋ก  16 ์ œ 2 ์ ˆ ๊ณต๊ฒฉ๊ณผ ๋ฐฉ์–ด์˜ ๊ตฌ๋ถ„ 21 โ‘  ์ผ๋ฐ˜์  ๊ตฌ๋ถ„ 21 โ‘ก ์ œํ•ด๊ถŒ ๊ฐœ๋…์— ๋”ฐ๋ฅธ ๊ตฌ๋ถ„ 23 ์ œ 3 ์žฅ ๋ฌด๊ธฐ์ฒด๊ณ„ ๋ถ„์„ 26 ์ œ 1 ์ ˆ ์ค‘๊ตญ ํ•ด๊ตฐ ๋ฌด๊ธฐ์ฒด๊ณ„์˜ ๋ณ€ํ™” 26 ์ œ 2 ์ ˆ ๊ธฐ๋™ํ•จ๋Œ€๋กœ์˜ ๋ฐœ์ „ 34 โ‘  ๋ฏธ๊ตญ ํ•ด๊ตฐ ์›์ •๊ตฐ ๊ธฐ๋™๋ถ€๋Œ€ ๊ฐœ๋… 34 โ‘ก ์ค‘๊ตญ์˜ ๊ธฐ๋™ํ•จ๋Œ€ ์œก์„ฑ 3 ๋‹จ๊ณ„ ๊ณ„ํš 36 ์ œ 4 ์žฅ ํ•ด๊ตฐ ์ „๋žต ๋ถ„์„ 43 ์ œ 1 ์ ˆ ์—ฐ์•ˆ์—์„œ ๋Œ€์–‘์œผ๋กœ 43 โ‘  ๋งˆ์˜ค์ฉŒ๋‘ฅ์˜ ํ•ด์ƒ์ธ๋ฏผ์ „์Ÿ ๊ฐœ๋…(1949 ๋…„~1976 ๋…„) 43 โ‘ก ๋ฅ˜ํ™”์นญ ์ œ๋…์˜ ์ค‘๊ตญ ํ•ด๊ตฐ 3 ๋‹จ๊ณ„ ๊ฑด์„ค ๋ชฉํ‘œ 45 ์ œ 2 ์ ˆ ํ•ด์ƒ๊ตํ†ต๋กœ์—์„œ์˜ ์ œํ•ด๊ถŒ ํ™•๋ณด 49 ์ œ 3 ์ ˆ ์ค‘๊ตญ ๊ตญ๋ฐฉ๋ฐฑ์„œ์— ๋‚˜ํƒ€๋‚œ ํ•ด๊ตฐ ์ „๋žต 52 ์ œ 4 ์ ˆ ์†Œ๊ฒฐ 54 ์ œ 5 ์žฅ ์ฃผ๋ณ€๊ตญ์˜ ์ธ์‹๊ณผ ๋Œ€์‘ 57 ์ œ 1 ์ ˆ ๋ฏธ๊ตญ 57 ์ œ 2 ์ ˆ ์ผ๋ณธ 59 ์ œ 3 ์ ˆ ์†Œ๊ฒฐ 61 ์ œ 6 ์žฅ ๋งบ์Œ๋ง 62 ์ฐธ๊ณ  ๋ฌธํ—Œ 66Maste

    The Educational Interpretation of Mozi's Analects: Focused on the Conflict between Kongzi's School and Mozi's School

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    ์ด ๊ธ€์—์„œ๋Š” ์œ โ€ค๋ฌต์˜ ๋Œ€๋ฆฝ์„ ๊ทผ๋ณธ์ ์ธ ๋ถˆํ™”๋กœ ๊ทœ์ •ํ•˜๊ณ , ๋„์ „๊ณผ ์‘์ „์ด๋ผ๋Š” ์ธก๋ฉด์—์„œ ์„œ๋กœ์˜ ํ•ต์‹ฌ ๊ฐœ๋…์ธ ๊ฒธ์• ์„ค๊ณผ ์„ฑ์„ ์„ค์— ๋Œ€ํ•œ ๋ถ„์„์„ ์‹œ๋„ํ•˜์˜€๋‹ค. ์ด๋ฅผ ํ†ตํ•˜์—ฌ ๋ฌต๊ฐ€๊ฐ€ ์ •ํ™•ํžˆ ์–ด๋–ค ์ ์—์„œ ์œ ๊ฐ€์™€ ๋Œ€๋ฆฝํ•˜๊ณ  ์žˆ์œผ๋ฉฐ, ๊ทธ๊ฒƒ์ด ๊ต์œกํ•™์ ์œผ๋กœ ์–ด๋– ํ•œ ์ŠคํŽ™ํŠธ๋Ÿผ์„ ๋งŒ๋“ค์–ด๋‚ด๋Š”์ง€ ๋ฐํžˆ๊ณ ์ž ํ•˜์˜€๋‹ค. ๋ฌต์ž์˜ ๊ฒธ์• ์„ค์€ ์œ ๊ฐ€์  ๊ด€๊ณ„ ์งˆ์„œ์™€ ๊ทธ๊ฒƒ์˜ ๊ตฌ์ฒด์ ์ธ ๋ชจ์Šต์ธ ์˜ˆ์•…์— ๊ด€ํ•œ ์ „๋ฉด์ ์ธ ๋ถ€์ •์˜ ์ •์„œ๋ฅผ ๋‹ด๊ณ  ์žˆ๋‹ค. ๊ฒธ์• ๋Š” ํ”ํžˆ ๋‚ด๋‚จ์˜ ์ฐจ๋ณ„์ด ์—†๋Š” ๋ณดํŽธ์ ์ธ ์‚ฌ๋ž‘์œผ๋กœ ์ฝํžˆ๊ธฐ ์‰ฌ์šฐ๋‚˜, ๊ทธ๊ฒƒ์ด ๅˆฉ์˜ ์ƒํ˜ธ ๊ตํ™˜์„ ์ „์ œ๋กœ ํ•˜๋Š” ๊ฐœ๋…์ด๋ผ๊ณ  ๋ณด๋ฉด ์ƒ๊ฐ์€ ๋‹ฌ๋ผ์ง„๋‹ค. ๋งน์ž์— ์˜ํ•˜๋ฉด, ์ธ๊ฐ„์€ ๋งˆ์Œ ์•ˆ์— ์„ ์˜ ์‹ค๋งˆ๋ฆฌ(ๅ››็ซฏ)๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ๋Š” ๊นŒ๋‹ญ์— ์˜ˆ์•…์˜ ์‹ค์ฒœ ์ฃผ์ฒด๊ฐ€ ๋  ์ˆ˜ ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ผ์ƒ ์†์—์„œ ์˜ˆ์•…์˜ ํ•ฉ๋‹นํ•จ์„ ์–ป์–ด๋‚ด๊ธฐ ์œ„ํ•ด์„œ๋Š” ์น˜์—ดํ•œ ์ฃผ์ฒด์  ๋…ธ๋ ฅ์ด ์š”๊ตฌ๋œ๋‹ค. ๋งน์ž๋Š” ์„ฑ์„ ์„ค์˜ ๊ตฌ๋„๋ฅผ ํ†ตํ•˜์—ฌ ๋„๋•์„ฑ์˜ ์›์ฒœ์„ ๋งˆ์Œ์— ๋‘๋ฉด์„œ๋„ ๊ทธ ์•ˆ์— ์ฒœ์˜ ์กด์žฌ๋ฅผ ๋‚ด๋ ค์•‰ํ˜€(ๅขฎๅœจ) ์•ˆํŒŽ์˜ ๊ท ํ˜•์ถ”๋ฅผ ์œ ์ง€ํ•˜๋Š”๋ฐ ์„ฑ๊ณตํ•œ๋‹ค. ๋ฐ˜๋ฉด์— ๋ฌต์ž๋Š” ๋ณดํŽธ์ ์ธ ์‚ฌ๋ž‘์„ ์ง€์นญํ•˜๋Š” ๊ฒธ์• ๋ฅผ ์ฃผ์žฅํ•˜๋ฉด์„œ๋„ ๊ทธ ์›์ฒœ์„ ์ฒœ๊ณผ ๊ท€์‹ , ์ฒœ์ž ๋“ฑ ์™ธ์  ๊ถŒ์œ„์— ๋‘ ์œผ๋กœ์จ ๊ฒธ์• ์˜ ๊ฐ€์น˜๋ฅผ ๋„๋•์  ์ˆ˜์ค€์—์„œ ์ œ๋„์  ์ˆ˜์ค€์œผ๋กœ ๋Œ์–ด๋‚ด๋ฆฌ๋Š” ๊ฒฐ๊ณผ๋ฅผ ๊ฐ€์ ธ์™”๋‹ค. ๊ฒธ์• ์„ค์—์„œ์˜ ์ฃผ์ฒด์˜ ์‹ค์ข…์€ ์ด์šฉ๊ฐ€๋Šฅ์„ฑ์˜ ๊ทน๋Œ€ํ™”๋ผ๋Š” ๋ชฉํ‘œ ์•„๋ž˜ ๊ต์œก์„ ์ˆ˜๋‹จ์‹œํ•˜๋Š” ํ˜„๋Œ€๊ต์œก์˜ ๋…ผ๋ฆฌ์™€ ๋งž๋‹ฟ์•„ ์žˆ์œผ๋ฉฐ, ์„ฑ์„ ์„ค์€ ๊ทธ ๋Œ€์•ˆ์  ์‚ฌ์œ ์˜ ๊ธฐ๋ฐ˜์œผ๋กœ ์ž‘์šฉํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์ด๋‹ค. There are radical discrepancies between the doctrines of Kongzi and Mozi. In this study, we analyze the nature of jianai and xingshanshuo from the standpoint of 'challenge and response' in order to highlight the reasons why they are critical of one another. This study seeks to better understand the implications these doctrines as they apply to contemporary educationaltheory. Mozi's jianai is severely antagonistic toward confucian doctrines, especially that of the ritual ceremony. Semantically, jianai means 'all embracing love', but the concept essentially denotes the exchange of interests among people. Mozi argues that goodness always promises some benefit to all, but how do we know whether something is good or bad? He suggests that it is not related to the realm of human society; that it depends only on the will of Heaven,which is almighty. So it is not intrinsically related to the realm of human society. According to Mengzi, every human being has four good clues in his mind. He believes that every person has the potential to rise to the sphere of the sage, but that he should also attempt to attain an ideal disposition in everyday life. Whenever he reaches this ideal state, he has to 'transact' with other people to understand their horizons. This processes might be called self-cultivation. Essentially, Mengzi considered the human being to be an active moralagent. Though we rely on a certain definition of education, we cannot deny that education is actually an interactive process between teacher and student. If the two are in an ideal condition of teaching-learning, both teacher and student are able to learn from one another. Today, it is not easy to find this ideal situation in our educational system, because every school adheres * Lecturer, Korea National University of Education Abstract only to the goal of effective knowledge transmission and expanding utility of knowledge. Currently, as we begin the process of discarding the prevalent paradigm for a reconstructed new paradigm, we can find value in jianai and xingshanshuo regardless of whether that value is negative or positive. Overall, it is our duty to find a more suitable paradigm to integrate into our educational system and practices
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