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On the variational noncommutative Poisson geometry

: ์ด ๋…ผ๋ฌธ์€ ๊ณ ์ฐจ์› ๊ณต๊ฐ„์—์„œ ๋น„์ปค๋ฎค๋‹ˆํ‹ฐ ๋ณ€๋ถ„ ํฌ์Šจ ๊ธฐํ•˜ํ•™์„ ํƒ๊ตฌํ•˜๊ณ , ํŠนํžˆ ๋น„์ปค๋„ ์„ฑ์งˆ์„ ๊ฐ€์ง„ ํ•ด๋ฐ€ํ„ด ์—ฐ์‚ฐ์ž๊ฐ€ ๋ฌผ๋ฆฌ์  ์‹œ์Šคํ…œ์˜ ์ง„ํ™”๋ฅผ ์–ด๋–ป๊ฒŒ ์„ค๋ช…ํ•˜๋Š”์ง€์— ์ดˆ์ ์„ ๋งž์ถ”๊ณ  ์žˆ๋‹ค. ์ด๋ฅผ ํ†ตํ•ด ์ƒˆ๋กœ์šด ์ˆ˜ํ•™์  ๋„๊ตฌ์™€ ์ด๋ก ์ด ๋ฌผ๋ฆฌํ•™์—์„œ์˜ ์‘์šฉ ๊ฐ€๋Šฅ์„ฑ์— ๋Œ€ํ•ด ๊นŠ๊ฒŒ ๋ถ„์„ํ•˜๊ณ  ์žˆ๋‹ค. ๋น„์ปค๋ฎค๋‹ˆํ‹ฐ ์ œํŠธ ๊ณต๊ฐ„ ๋…ผ๋ฌธ์€ n์ฐจ์› ์œ ํ–ฅ R ๋‹ค์ค‘๋ณ€ ๊ณก๋ฉด ์œ„์—์„œ ์ •์˜๋˜๋Š” ๋ฌดํ•œ ์ œํŠธ ๊ณต๊ฐ„์„ ํƒ๊ตฌํ•œ๋‹ค. ์ด ๊ณต๊ฐ„์€ Noether ๋น„์ปค๋ฎค๋‹ˆํ‹ฐ ์„ ํ˜• ํ–‰๋ ฌ ์—ฐ์‚ฐ์ž๋ฅผ ํฌํ•จํ•˜๋ฉฐ, ์ด๋ฅผ ํ†ตํ•ด ๋ฌผ๋ฆฌ์  ์‹œ์Šคํ…œ์˜ ๋ณ€๋ถ„ ๊ตฌ์กฐ๋ฅผ ์ดํ•ดํ•  ์ˆ˜ ์žˆ๋‹ค. ํŠนํžˆ, A์˜ ๊ณต์—ญ Aโ€ ๋Š” pโ‚๊ณผ A(pโ‚‚)

HEP-TH Mathematics MATH-PH Nonlinear Sciences
A generalized Young inequality and some new results on fractal space

A generalized Young inequality and some new results on fractal space

: ๋ณธ ์—ฐ๊ตฌ๋Š” ๊ณ ์ „์ ์ธ ์˜ ๋ถˆํ‰๋“ฑ์„ ๋ถ„์ˆ˜ ์ง‘ํ•ฉ์—์„œ ์ผ๋ฐ˜ํ™”ํ•˜๋Š” ๋ฐ ์ดˆ์ ์„ ๋งž์ถ”๊ณ  ์žˆ๋‹ค. ์ด๋Š” ์–‘(Yang) ๋ถ„์ˆ˜ ์ง‘ํ•ฉ๊ณผ ๊ทธ ๊ธฐํ•˜ํ•™์  ํ‘œํ˜„์„ ํ†ตํ•ด ์ด๋ฃจ์–ด์ง„๋‹ค. ์ด๋Ÿฌํ•œ ์ ‘๊ทผ๋ฒ•์€ ์‹ค์ˆ˜ ๋ฒˆ์„ ๋ถ„์ˆ˜ ์ฐจ์›์œผ๋กœ ํ•ด์„ํ•จ์œผ๋กœ์จ, ๊ณ ์ „์ ์ธ ๋ถˆํ‰๋“ฑ์˜ ์ƒˆ๋กœ์šด ๊ด€์ ๊ณผ ํ™•์žฅ์„ฑ์„ ์ œ๊ณตํ•œ๋‹ค. 1. ์–‘(Yang) ๋ถ„์ˆ˜ ์ง‘ํ•ฉ ์ด๋ก  ์–‘(Yang) ๋ถ„์ˆ˜ ์ง‘ํ•ฉ ์ด๋ก ์€ ๊ธฐ์กด์˜ ์‹ค์ˆ˜ ์ง‘ํ•ฉ์—์„œ ๋ฒ—์–ด๋‚˜, ๋ถ„์ˆ˜ ์ฐจ์›์„ ๊ฐ–๋Š” ์ง‘ํ•ฉ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ•œ๋‹ค. ํŠนํžˆ, ์–‘(Yang) ๊ธฐํ•˜ํ•™์  ํ‘œํ˜„์—์„œ๋Š” ์‹ค์ˆ˜ ๋ฒˆ์ด ๋ถ„์ˆ˜ ์ฐจ์›์˜ ์ ์œผ๋กœ ํ•ด์„๋œ๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด, 1ฮฑ + 2ฮฑ 3ฮฑ์™€ ๊ฐ™์€ ๊ด€๊ณ„๊ฐ€

Mathematics
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Guaranteed successful strategies for a square achievement game on an n by n grid

์ด ๋…ผ๋ฌธ์€ ์ •์‚ฌ๊ฐํ˜• ๋‹ฌ์„ฑ ๊ฒŒ์ž„์—์„œ ์ตœ์ ์˜ ํ”Œ๋ ˆ์ด ์ „๋žต์— ๋Œ€ํ•œ ์‹ฌ๋„ ์žˆ๋Š” ๋ถ„์„์„ ์ œ๊ณตํ•œ๋‹ค. ์ด ๊ฒŒ์ž„์€ n x n ๊ทธ๋ฆฌ๋“œ ์œ„์—์„œ ๋‘ ํ”Œ๋ ˆ์ด์–ด๊ฐ€ 'O'์™€ 'X'๋ฅผ ๋ฒˆ๊ฐˆ์•„ ๋ฐฐ์น˜ํ•˜๋ฉฐ, ์ฒซ ๋ฒˆ์งธ ํ”Œ๋ ˆ์ด์–ด๋Š” ์ˆ˜ํ‰ ๋ฐ ์ˆ˜์ง ๋ณ€์˜ ๋ชจ์„œ๋ฆฌ์— 4๊ฐœ์˜ ์…€์„ ์ ์œ ํ•˜์—ฌ ์Šน๋ฆฌ๋ฅผ ๋‹ฌ์„ฑํ•ด์•ผ ํ•œ๋‹ค. ๋…ผ๋ฌธ์€ SQRGAME2๋ผ๋Š” ์ปดํ“จํ„ฐ ํ”„๋กœ๊ทธ๋žจ์„ ์‚ฌ์šฉํ•ด n์ด 3, 4, 5์ผ ๋•Œ ๊ฐ ํ”Œ๋ ˆ์ด์–ด๊ฐ€ ์ตœ์ ์˜ ์ „๋žต์œผ๋กœ ๊ฒŒ์ž„์—์„œ ์–ด๋–ป๊ฒŒ ์ด๊ธธ ์ˆ˜ ์žˆ๋Š”์ง€ ๋ถ„์„ํ•œ๋‹ค. ๊ฒŒ์ž„์˜ ๊ทœ์น™๊ณผ ์ง„ํ–‰ ๋ฐฉ์‹์— ๋Œ€ํ•œ ์ž์„ธํ•œ ์„ค๋ช…์€ ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. G๋Š” 0๋ถ€ํ„ฐ (์ ์–ด๋„) n 1๊นŒ์ง€์˜ ์ •์ˆ˜ ์ธ๋ฑ์Šค ๋ฒ”์œ„๋ฅผ ๊ฐ€

Mathematics Computer Science Discrete Mathematics
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Filtrations of Formal Languages by Arithmetic Progressions

๋ณธ ๋…ผ๋ฌธ์€ Berstel ์™ธ ์—ฐ๊ตฌ์ž๋“ค์ด ์ œ์‹œํ•œ ํ•„ํ„ฐ๋ง ๊ฐœ๋…์„ ์žฌ๊ฒ€ํ† ํ•˜๊ณ , ํŠนํžˆ ์‚ฐ์ˆ ์ง„ํ–‰๋ ฌ์„ ์ด์šฉํ•œ ํ•„ํ„ฐ๋ง ๋ฐฉ๋ฒ•์— ์ดˆ์ ์„ ๋งž์ถ”์–ด ์ •๊ทœ ์–ธ์–ด์™€ ๋ฌธ๋ฒ•์  ์ž์œ  ์–ธ์–ด์˜ ํŠน์„ฑ์„ ๋ถ„์„ํ•œ๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ์ฃผ๋กœ ๋ฌดํ•œ ํ•„ํ„ฐ ์ง‘ํ•ฉ S {s1, s2, ...} ์— ๋Œ€ํ•ด ์ฃผ์–ด์ง„ ์–ธ์–ด L ์˜ ๋ชจ๋“  ํ•„ํ„ฐ๋ง๋œ ์–ธ์–ด { L

Formal Languages Computer Science
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Three limits to the physical world

: ์ด ๋…ผ๋ฌธ์€ ๋ฌผ๋ฆฌ ์„ธ๊ณ„์—์„œ ์ค‘์š”ํ•œ ์„ธ ๊ฐ€์ง€ ํ•œ๊ณ„๋ฅผ ๋‹ค๋ฃจ๊ณ  ์žˆ์œผ๋ฉฐ, ๊ฐ๊ฐ์˜ ํ•œ๊ณ„๋Š” ์šฐ์ฃผ ์ƒ์ˆ˜์™€ ๊ด€๋ จ๋œ ์•„์ธ์Šˆํƒ€์ธ ํ•œ๊ณ„, ํ—ค์ด์ŠคํŒ…์Šค ํ•œ๊ณ„, ๊ทธ๋ฆฌ๊ณ  ์Šˆ๋ฐ”๋ฅด์ธ ์‹ค๋“œ ๋ฐ˜์ง€๋ฆ„์— ๋Œ€ํ•œ ํ•œ๊ณ„๋กœ ๊ตฌ์„ฑ๋ฉ๋‹ˆ๋‹ค. ์ด๋“ค ํ•œ๊ณ„๋Š” ๋ฌผ๋ฆฌ ์„ธ๊ณ„์—์„œ ์งˆ๋Ÿ‰๊ณผ ์—๋„ˆ์ง€ ๋ฐ€๋„์˜ ๊ทนํ•œ์„ ์ •์˜ํ•˜๋ฉฐ, ์ด๋ฅผ ํ†ตํ•ด ์šฐ์ฃผ์˜ ๊ตฌ์กฐ์™€ ์„ฑ์งˆ์„ ์ดํ•ดํ•˜๋Š” ๋ฐ ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•ฉ๋‹ˆ๋‹ค. ์šฐ์„ , ์•„์ธ์Šˆํƒ€์ธ ํ•œ๊ณ„๋Š” ์šฐ์ฃผ ์ƒ์ˆ˜ ฮ›๋ฅผ ํ†ตํ•ด ์„ค๋ช…๋˜๋ฉฐ, ์ด๋Š” ํ˜„์žฌ ์šฐ์ฃผ์˜ ์•”ํ‘ ์—๋„ˆ์ง€ ์ง€๋ฐฐ ์ƒํƒœ์— ๋Œ€ํ•œ ํ•ด์„๊ณผ ์—ฐ๊ฒฐ๋ฉ๋‹ˆ๋‹ค. ์ด ๋…ผ๋ฌธ์—์„œ ์ œ์‹œ๋œ ฯฮ› ~ 10^ 120์€ ์šฐ์ฃผ์˜ ํ˜„์žฌ ๋ฐ€๋„์™€ ๋™์ผํ•˜๋ฉฐ, ์ด๋ฅผ ํ†ตํ•ด

Physics Astrophysics
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Exact solutions of equations for the Burgers hierarchy

: ์ด ๋…ผ๋ฌธ์€ ๋น„์„ ํ˜• ์ง„ํ™” ๋ฐฉ์ •์‹์ธ ๋ฒ„๊ฑฐ์Šค ๊ณ„์ธต์— ๋Œ€ํ•œ ์ •ํ™•ํ•œ ํ•ด์™€ ๊ทธ ํ•ด๋ฒ•์„ ์ฐพ๋Š” ๋ฐ ์‚ฌ์šฉ๋˜๋Š” ์ผ๋ฐ˜ํ™”๋œ ์ฝœ ํ˜ธํ”„ ๋ณ€ํ™˜์— ๋Œ€ํ•ด ๊นŠ๊ฒŒ ๋ถ„์„ํ•˜๊ณ  ์žˆ๋‹ค. ๋ฒ„๊ฑฐ์Šค ๊ณ„์ธต์€ n์˜ ๊ฐ’์— ๋”ฐ๋ผ ๋‹ค์–‘ํ•œ ํ˜•ํƒœ์˜ ๋น„์„ ํ˜• ๋ฐฉ์ •์‹์œผ๋กœ ๊ตฌ์„ฑ๋˜๋ฉฐ, ํŠนํžˆ n 1์ผ ๋•Œ ๋ฒ„๊ฑฐ์Šค ๋ฐฉ์ •์‹, n 2์ผ ๋•Œ ์ƒค๋ฅด๋งˆ ํƒ€์†Œ ์˜ฌ๋ฒ„(STO) ๋ฐฉ์ •์‹ ๋“ฑ์ด ํฌํ•จ๋œ๋‹ค. ๋…ผ๋ฌธ์—์„œ๋Š” ์ฝœ ํ˜ธํ”„ ๋ณ€ํ™˜์„ ์ผ๋ฐ˜ํ™”ํ•˜์—ฌ ์ด๋Ÿฌํ•œ ๋ฐฉ์ •์‹๋“ค์˜ ์ •ํ™•ํ•œ ํ•ด๋ฅผ ์ฐพ๋Š” ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค. ์ด ๋ณ€ํ™˜์€ ๋น„์„ ํ˜• ๋ฐฉ์ •์‹์„ ์„ ํ˜•ํ™”ํ•˜๋Š” ๋ฐ ์‚ฌ์šฉ๋˜๋ฉฐ, ์ด๋ฅผ ํ†ตํ•ด ๋‹ค์–‘ํ•œ ์œ ํ˜•์˜ ํ•ด๋ฅผ ๊ตฌ์„ฑํ•  ์ˆ˜ ์žˆ๋‹ค. ํŠนํžˆ, ์—ฌํ–‰ ํŒŒ๋™์„ ์‚ฌ์šฉํ•˜์ง€

Nonlinear Sciences
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Reply to 'Comment' by A. V. Tsiganov

: ๋ณธ ๋…ผ๋ฌธ์€ A. V. Tsiganov์˜ 'Comment'์— ๋Œ€ํ•œ ๋ฐ˜๋ก ์„ ์ œ์‹œํ•˜๋ฉด์„œ ๊ณ ๋ ˆ์•„ํ”„ ๋ฌธ์ œ์—์„œ ์‚ฌ์šฉ๋˜๋Š” ๋ถ„๋ฆฌ ๋ณ€์ˆ˜์™€ ๊ทธ ์„ฑ์งˆ์— ๋Œ€ํ•ด ์‹ฌ๋„ ์žˆ๊ฒŒ ๊ฒ€ํ† ํ•œ๋‹ค. ํŠนํžˆ, ๋…ผ๋ฌธ์—์„œ๋Š” Tsiganov๊ฐ€ ์ฃผ์žฅํ•œ uโ‚, uโ‚‚ ๋ณ€์ˆ˜๊ฐ€ ์ดˆ๊ธฐ ํฌ์•„์†ก ๋ธŒ๋ž˜ํ‚ท์— ๋Œ€ํ•ด ๋น„๊ณต์œ ์ ์ด๊ธฐ ๋•Œ๋ฌธ์— ๋ถ„๋ฆฌ ๋ณ€์ˆ˜๊ฐ€ ์•„๋‹ˆ๋ผ๋Š” ์ฃผ์žฅ์„ ๋ฐ˜๋ฐ•ํ•˜๊ณ  ์žˆ๋‹ค. 1. ๋ณ€์ˆ˜ uโ‚, uโ‚‚์˜ ๋น„๊ณต์œ ์„ฑ๊ณผ ๋ถ„๋ฆฌ ๋ณ€์ˆ˜ Tsiganov๋Š”

Nonlinear Sciences
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A Theorem of Probability

์ด ๋…ผ๋ฌธ์€ ํ™•๋ฅ ๋ก ์—์„œ ํ•ต์‹ฌ์ ์ธ ๊ฐœ๋…์ธ ๊ธฐ๋Œ€๊ฐ’๊ณผ ๋ฌด์ž‘๋ž˜ ๋ณ€์ˆ˜ ์‹œํ€€์Šค์— ๋Œ€ํ•ด ๊นŠ๊ฒŒ ๋‹ค๋ฃน๋‹ˆ๋‹ค. ์ฃผ์š” ๋‚ด์šฉ์€ ๋‹ค์Œ๊ณผ ๊ฐ™์Šต๋‹ˆ๋‹ค: 1. ํ™•๋ฅ  ๊ณต๊ฐ„ ๋ฐ ๋ฌด์ž‘์œ„ ๋ณ€์ˆ˜์˜ ์ •์˜ : ๋…ผ๋ฌธ์€ ๋จผ์ € ํ™•๋ฅ  ๊ณต๊ฐ„ (ฮฉ, F, P) ๋ฅผ ์ •์˜ํ•ฉ๋‹ˆ๋‹ค. ์—ฌ๊ธฐ์„œ ฮฉ๋Š” ๋ชจ๋“  ๊ฐ€๋Šฅํ•œ ๊ฒฐ๊ณผ๋“ค์˜ ์ง‘ํ•ฉ, F๋Š” ์ด๋“ค ๊ฒฐ๊ณผ์— ๋Œ€ํ•œ ์‹œ๊ทธ๋งˆ ๋Œ€์ˆ˜(sigma algebra), ๊ทธ๋ฆฌ๊ณ  P๋Š” ํ™•๋ฅ  ์ธก๋„(probability measure)์ž…๋‹ˆ๋‹ค. ๋ฌด์ž‘์œ„ ๋ณ€์ˆ˜ Xโ‚™์€ ๊ฐ ฯ‰ โˆˆ ฮฉ ์— ๋Œ€ํ•ด ๊ฐ’์„ ๊ฐ€์ง€๋ฉฐ, ์ด ๊ฐ’๋“ค์€ ๋น„์Œ(non negative)์ด๋ผ๋Š” ํŠน์„ฑ์„ ๊ฐ€์ง‘๋‹ˆ๋‹ค. 2. ๊ธฐ๋Œ€๊ฐ’์˜ ์ •์˜ :

Mathematics
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Errors in Improved Polynomial Algorithm For 3 Sat Proposed By Narendra Chaudhari

๋ณธ ๋…ผ๋ฌธ์€ ๋‚˜๋ฅด์—”๋“œ๋ผ ์ฐจ์šฐ๋‹ค๋ฆฌ๊ฐ€ ๊ฐœ๋ฐœํ•˜๊ณ  ๊ฐœ์„ ํ•œ 3 SAT ๋ฌธ์ œ ํ•ด๊ฒฐ ์•Œ๊ณ ๋ฆฌ์ฆ˜์˜ ํ•œ๊ณ„๋ฅผ ํƒ์ƒ‰ํ•œ๋‹ค. 3 SAT ๋ฌธ์ œ๋Š” ์ปดํ“จํ„ฐ ๊ณผํ•™์—์„œ ์ค‘์š”ํ•œ NP ์™„์ „ ๋ฌธ์ œ๋กœ, ์ด๋ฅผ ๋‹คํ•ญ ์‹œ๊ฐ„ ๋‚ด์— ํ•ด๊ฒฐํ•˜๋Š” ๊ฒƒ์€ P NP ๋ฌธ์ œ์™€ ๋ฐ€์ ‘ํ•˜๊ฒŒ ์—ฐ๊ด€๋˜์–ด ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ, ์ด ๋ฌธ์ œ์— ๋Œ€ํ•œ ํšจ์œจ์ ์ธ ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด ์ œ์‹œ๋  ๊ฒฝ์šฐ ๊ทธ ์ค‘์š”์„ฑ์€ ์ด๋ฃจ ๋งํ•  ์ˆ˜ ์—†๋‹ค. ๋…ผ๋ฌธ์—์„œ๋Š” ์ฐจ์šฐ๋‹ค๋ฆฌ์˜ ๊ฐœ์„ ๋œ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ๋‘ ๊ฐ€์ง€ ์‚ฌ๋ก€๋ฅผ ํ†ตํ•ด ๋ถ„์„ํ•œ๋‹ค. ์ด ์‚ฌ๋ก€๋“ค์€ ๋ชจ๋‘ 9๊ฐœ์˜ ๋ณ€์ˆ˜(a1๋ถ€ํ„ฐ a9๊นŒ์ง€)๋กœ ๊ตฌ์„ฑ๋˜๋ฉฐ, ๊ฐ๊ฐ์˜ ์‚ฌ๋ก€๋Š” ํŠน์ • ์กฐํ•ฉ ์ •๊ทœ ํ˜•์‹(CNF)์˜ ์ ˆ๋“ค๋กœ ํ‘œํ˜„๋œ๋‹ค. ์ด๋Ÿฌํ•œ CN

Computer Science Computational Complexity
Cicada: a Heavy but Agile Flyer

Cicada: a Heavy but Agile Flyer

์ด ๋…ผ๋ฌธ์€ ๋งค๋ฏธ์˜ ๋น„ํ–‰ ๋ฉ”์ปค๋‹ˆ์ฆ˜์— ๋Œ€ํ•œ ๊นŠ์ด ์žˆ๋Š” ๋ถ„์„์„ ์ œ๊ณตํ•˜๋ฉฐ, ํŠนํžˆ ๊ทธ๋“ค์˜ ๋ฌด๊ฑฐ์šด ์ฒด์ค‘์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ๋†’์€ ์–‘๋ ฅ์„ ๋ฐœ์ƒ์‹œํ‚ค๋Š” ๋Šฅ๋ ฅ์— ์ดˆ์ ์„ ๋งž์ถ”๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ๊ณค์ถฉ ๋น„ํ–‰์˜ ๋ณต์žก์„ฑ์„ ์ดํ•ดํ•˜๋Š” ๋ฐ ์ค‘์š”ํ•œ ๋‹จ๊ณ„๋ฅผ ์ œ๊ณตํ•˜๊ณ  ์žˆ์œผ๋ฉฐ, ์ด๋Ÿฌํ•œ ์ง€์‹์€ ๋งˆ์ดํฌ๋กœ ์—์–ด ๋น„ํžˆํด(MAV) ์„ค๊ณ„์—์„œ ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. 1. ๋งค๋ฏธ์˜ ํŠน์„ฑ ๋ถ„์„ ๋งค๋ฏธ๋Š” ๋‹ค๋ฅธ ๊ณค์ถฉ๋“ค์— ๋น„ํ•ด ์ƒ๋Œ€์ ์œผ๋กœ ๋ฌด๊ฑฐ์šด ์ฒด์ค‘์„ ๊ฐ€์ง€๊ณ  ์žˆ์ง€๋งŒ, ๋†’์€ ์–‘๋ ฅ์„ ๋ฐœ์ƒ์‹œ์ผœ ๋‚  ์ˆ˜ ์žˆ๋Š” ๋Šฅ๋ ฅ์ด ์žˆ์Šต๋‹ˆ๋‹ค. ์ด ์—ฐ๊ตฌ์—์„œ๋Š” ์ด๋Ÿฌํ•œ ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ์ดํ•ดํ•˜๊ธฐ ์œ„ํ•ด ๊ณ ์† ํฌ๊ทธ๋ผ๋ฉ”ํŠธ๋ฆฌ ์‹œ์Šคํ…œ

Physics
Inclusion of Unambiguous RE#s is NP-Hard

Inclusion of Unambiguous RE#s is NP-Hard

: ๋ณธ ๋…ผ๋ฌธ์€ ์ •๊ทœํ‘œํ˜„์‹(REs)์˜ ํฌํ•จ์„ฑ ๋ฌธ์ œ์— ๋Œ€ํ•œ ์ค‘์š”ํ•œ ์ด๋ก ์  ๊ฒฐ๊ณผ๋ฅผ ์ œ์‹œํ•˜๋ฉฐ, ํŠนํžˆ ๋ช…ํ™•ํ•œ REs์˜ ๊ฒฝ์šฐ์—๋„ NP ๋‚œ์ œ์ž„์„ ์ฆ๋ช…ํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ๊ฒฐ๊ณผ๋Š” XML ์Šคํ‚ค๋งˆ ์ฝ˜ํ…์ธ  ๋ชจ๋ธ์—์„œ ์š”๊ตฌ๋˜๋Š” ๋ช…ํ™•์„ฑ์„ ๋งŒ์กฑํ•˜๋”๋ผ๋„ ๊ณ„์‚ฐ์ ์œผ๋กœ ํ•ด๊ฒฐํ•˜๊ธฐ ์–ด๋ ค์šด ๋ฌธ์ œ๋ผ๋Š” ๊ฒƒ์„ ์‹œ์‚ฌํ•œ๋‹ค. 1. ์„œ๋ก  ์„œ๋ก ์—์„œ๋Š” ์ด์ „ ์—ฐ๊ตฌ

Computational Complexity Computer Science
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Jacobians and Hessians of Mean Value Coordinates for Closed Triangular Meshes

์ด ๋…ผ๋ฌธ์€ ํ์‡„ ์‚ผ๊ฐ๋ง์— ๋Œ€ํ•œ ํ‰๊ท ๊ฐ’ ์ขŒํ‘œ๋ฅผ ๋‹ค๋ฃจ๋Š” ๋ฐ ์ค‘์ ์„ ๋‘๊ณ  ์žˆ์œผ๋ฉฐ, ์ด๋ฅผ ํ†ตํ•ด 3์ฐจ์› ๊ณต๊ฐ„ ๋‚ด์—์„œ ๋ฉ”์‰ฌ ๋ณ€ํ˜• ๋ฐ ๋ณด๊ฐ„ ๊ณผ์ •์„ ๋ถ„์„ํ•ฉ๋‹ˆ๋‹ค. ์ฃผ์š” ๋‚ด์šฉ๊ณผ ๋ถ„์„์€ ๋‹ค์Œ๊ณผ ๊ฐ™์Šต๋‹ˆ๋‹ค. 1. ํ‰๊ท ๊ฐ’ ์ขŒํ‘œ์˜ ์ •์˜์™€ ๊ณ„์‚ฐ ๋…ผ๋ฌธ์—์„œ๋Š” ํ์‡„ ์‚ผ๊ฐ๋ง M์˜ ๊ผญ์ง“์  p i๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ 3์ฐจ์› ๊ณต๊ฐ„ ๋‚ด ์  ฮท๋ฅผ ํ‘œํ˜„ํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•ฉ๋‹ˆ๋‹ค. ์ด๋Š” w i๋ผ๋Š” ๊ฐ€์ค‘์น˜๋ฅผ ํ†ตํ•ด ์ด๋ฃจ์–ด์ง€๋ฉฐ, ์ด ๊ฐ€์ค‘์น˜๋“ค์€ ฮป i๋ฅผ ํ†ตํ•ด ์ •์˜๋ฉ๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๊ฐ€์ค‘์น˜๋“ค์„ ์ด์šฉํ•ด ํ‰๊ท ๊ฐ’ ์ขŒํ‘œ๋ฅผ ๊ณ„์‚ฐํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. 2. ํ•จ์ˆ˜ ๋ณด๊ฐ„๊ณผ ์„ ํ˜• ์ •๋ฐ€๋„ ํ‰๊ท ๊ฐ’ ์ขŒํ‘œ๋Š” ์‚ผ๊ฐ๋ง ๋‚ด์—์„œ ๊ฐ ๊ผญ์ง“์ 

Computer Science Graphics
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Markov-Binary Visibility Graph: a new method for analyzing Complex Systems

์ฃ„์†กํ•ฉ๋‹ˆ๋‹ค, ํ•˜์ง€๋งŒ ์ œ๊ณต๋œ ํ…์ŠคํŠธ ์กฐ๊ฐ์—๋Š” ์‹ค์ œ ๋‚ด์šฉ์ด ํฌํ•จ๋˜์–ด ์žˆ์ง€ ์•Š์•„์„œ ๋…ผ๋ฌธ์˜ ์ดˆ๋ก์ด๋‚˜ ์‹ฌ๋„ ๋ถ„์„์„ ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์—†์Šต๋‹ˆ๋‹ค. ๋…ผ๋ฌธ์˜ ๋ณธ๋ฌธ ๋˜๋Š” ์ค‘์š”ํ•œ ๋ถ€๋ถ„์„ ํฌํ•จํ•˜๋Š” ์ถ”๊ฐ€ ์ •๋ณด๊ฐ€ ํ•„์š”ํ•ฉ๋‹ˆ๋‹ค. ๋งŒ์•ฝ ๋…ผ๋ฌธ์˜ ํŠน์ • ์„น์…˜์ด๋‚˜ ์š”์•ฝ, ๊ทธ๋ž˜ํ”„, ํ‘œ ๋“ฑ์„ ์ œ๊ณตํ•ด ์ฃผ์‹ค ๊ฒฝ์šฐ, ๊ทธ์— ๋”ฐ๋ฅธ ๋ถ„์„๊ณผ ๋ฒˆ์—ญ์„ ๋„์™€๋“œ๋ฆด ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

Physics Nonlinear Sciences System
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Structure of lexicographic Groebner bases in three variables of ideals of dimension zero

: ์„œ๋ก  ๋ฐ ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋…ผ๋ฌธ์€ ๋‹ค๋ณ€์ˆ˜ ๋‹คํ•ญ์‹ ๋ฐ˜ํ™˜์˜ ์ œ๋กœ ์ฐจ์› ์ด์ƒ์ ๊ณผ ๊ทธ๋กœ๋ธŒ๋„ˆ ๊ธฐ์ €์— ์ดˆ์ ์„ ๋งž์ถ”๊ณ  ์žˆ๋‹ค. ํŠนํžˆ, 3๊ฐœ ๋ณ€์ˆ˜ x , y , z ๋ฅผ ์‚ฌ์šฉํ•˜๋Š” ๋‹คํ•ญ์‹ ๋ฐ˜ํ™˜ R

Symbolic Computation Computer Science
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Returns in futures markets and $nu=3$ t-distribution

๋ณธ ๋…ผ๋ฌธ์€ ๊ณ ์ฃผํŒŒ๋กœ ์ƒ˜ํ”Œ๋ง๋œ ๊ธˆ์œต ์‹œ๊ฐ„ ์‹œ๋ฆฌ์ฆˆ์˜ ๋กœ๊ทธ ๋ฐ˜ํ™˜ ํ™•๋ฅ  ๋ถ„ํฌ๋ฅผ ๋ถ„์„ํ•˜๊ณ , ์ด๋ฅผ ํ†ตํ•ด t ๋ถ„ํฌ๊ฐ€ ์‹ค์ œ ๋ฐ์ดํ„ฐ์™€ ์–ผ๋งˆ๋‚˜ ์ž˜ ์ผ์น˜ํ•˜๋Š”์ง€ ๊ฒ€์ฆํ•ฉ๋‹ˆ๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ์–‘์  ๊ธˆ์œต์—์„œ ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•˜๋Š” ๋กœ๊ทธ ๋ฐ˜ํ™˜ ๋ถ„ํฌ์— ๋Œ€ํ•œ ๊นŠ์ด ์žˆ๋Š” ์ดํ•ด๋ฅผ ์ œ๊ณตํ•˜๋ฉฐ, ํŠนํžˆ ฮฝ โ‰ˆ 3์ธ t ๋ถ„ํฌ์˜ ์ค‘์š”์„ฑ์„ ๊ฐ•์กฐํ•ฉ๋‹ˆ๋‹ค. 1. ๊ธˆ์œต ์‹œ๊ฐ„ ์‹œ๋ฆฌ์ฆˆ์™€ ๋กœ๊ทธ ๋ฐ˜ํ™˜ ๊ธˆ์œต ์‹œ๊ฐ„ ์‹œ๋ฆฌ์ฆˆ๋Š” ๊ฐ€๊ฒฉ ๋ณ€๋™์„ ๋‚˜ํƒ€๋‚ด๋ฉฐ, ์ด ๋ณ€๋™์€ ๋กœ๊ทธ ๋ฐ˜ํ™˜ x(t) log

Quantitative Finance
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Next-to-next-to-leading order post-Newtonian spin(1)-spin(2) Hamiltonian for self-gravitating binaries

: ๋ณธ ๋…ผ๋ฌธ์€ ๊ณ ์† ์ž์ „ํ•˜๋Š” ๋ฐ€๋„ ๋†’์€ ๋ฌผ์ฒด ๊ฐ„์˜ ์ƒํ˜ธ์ž‘์šฉ์— ๋Œ€ํ•œ ํฌ์ŠคํŠธ๋‰ดํ„ด(PN) ์Šคํ•€(1) ์Šคํ•€(2) ํ•ด๋ฐ€ํ† ๋‹ˆ์•ˆ์„ ์œ ๋„ํ•˜๊ณ  ๋ถ„์„ํ•ฉ๋‹ˆ๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ์ผ๋ฐ˜ ์ƒ๋Œ€์„ฑ ์ด๋ก ์—์„œ ๋‘ ๋ฌผ์ฒด๊ฐ€ ๊ณ ์†์œผ๋กœ ํšŒ์ „ํ•  ๋•Œ์˜ ๋™์—ญํ•™์  ํ–‰๋™์„ ์ดํ•ดํ•˜๋Š” ๋ฐ ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•ฉ๋‹ˆ๋‹ค. 1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์  ๋ณธ ๋…ผ๋ฌธ์€ ๊ธฐ์กด์˜ ์Šคํ•€ ์ƒํ˜ธ์ž‘์šฉ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋ฅผ ํ™•์žฅํ•˜๊ณ , ํŠนํžˆ 4PN ์ˆœ์„œ๊นŒ์ง€ ๊ณ„์‚ฐ๋œ ํ•ด๋ฐ€ํ† ๋‹ˆ์•ˆ์„ ์ œ์‹œํ•ฉ๋‹ˆ๋‹ค. ์ด๋Š” ๋‘ ๋ฌผ์ฒด๊ฐ€ ๊ณ ์†์œผ๋กœ ํšŒ์ „ํ•˜๋Š” ๊ฒฝ์šฐ์— ์ ์šฉ๋˜๋ฉฐ, ์ผ๋ฐ˜ ์ƒ๋Œ€์„ฑ ์ด๋ก ์—์„œ์˜ ๊ทผ์‚ฌ์น˜์ธ ํฌ์ŠคํŠธ๋‰ดํ„ด(PN) ์ ‘๊ทผ๋ฒ•์„ ์‚ฌ์šฉํ•˜์—ฌ ์œ ๋„๋ฉ๋‹ˆ๋‹ค. 2. ์—ฐ๊ตฌ ๋ฐฉ

HEP-TH General Relativity Astrophysics
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A radial version of the Central Limit Theorem

์ด ๋…ผ๋ฌธ์˜ ํ•ต์‹ฌ ์•„์ด๋””์–ด๋Š” ์›๋ž˜์˜ ์ค‘์‹ฌ๊ทนํ•œ์ •๋ฆฌ(Central Limit Theorem, CLT)๋ฅผ ๋ฐฉ์‚ฌํ˜• ๋ฒ„์ „์œผ๋กœ ํ™•์žฅํ•˜๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค. ์ด ํ™•์žฅ์„ ํ†ตํ•ด ๋น„๋“ฑ๋ฐฉ์„ฑ ๊ฐ€์šฐ์Šค ํ•จ์ˆ˜๋ฅผ ๊ทผ์‚ฌํ•  ์ˆ˜ ์žˆ๋Š” ์ƒˆ๋กœ์šด ๋ฐฉ๋ฒ•๋ก ์„ ์ œ์‹œํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. 1. ๋ฐฉ์‚ฌํ˜• CLT์™€ ๋น„๋“ฑ๋ฐฉ์„ฑ ๊ฐ€์šฐ์Šค ํ•จ์ˆ˜์˜ ๊ทผ์‚ฌ ๋…ผ๋ฌธ์€ ๊ฐ ๋ฐฉ์‚ฌ ๋ฐฉํ–ฅ์— ๋”ฐ๋ผ ๋ฐ•์Šค ํ•จ์ˆ˜ ํญ์„ ์กฐ์ ˆํ•จ์œผ๋กœ์จ ๋น„๋“ฑ๋ฐฉ์„ฑ ๊ฐ€์šฐ์Šค ํ•จ์ˆ˜๋ฅผ ๊ทผ์‚ฌํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ์•„์ด๋””์–ด๋ฅผ ์ œ์‹œํ•ฉ๋‹ˆ๋‹ค. ์ด๋Š” ํŠนํžˆ 4๋ฐฉํ–ฅ ๋ฐ•์Šค ์Šคํ”Œ๋ผ์ธ์ด๋ผ๋Š” ํŠน๋ณ„ํ•œ ๊ฒฝ์šฐ์—์„œ ํšจ๊ณผ์ ์ž…๋‹ˆ๋‹ค. ๊ณต๋ถ„์‚ฐ์„ ์ œ์–ดํ•˜๊ธฐ ์œ„ํ•ด ๋‹จ์ˆœํžˆ ๋ฐ•์Šค ๋ถ„ํฌ ํญ์„ ์กฐ์ ˆํ•˜๋Š” ๊ฐ„๋‹จํ•œ ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด

Information Theory Mathematics Computer Science Computer Vision
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Definition and Existence of the Eigenderivative

: ๋ณธ ๋…ผ๋ฌธ์€ ๊ณ ์œ ๊ฐ’๊ณผ ๊ณ ์œ ๋ฒกํ„ฐ์˜ ๋ณ€ํ™”์œจ์„ ์ •๋Ÿ‰ํ™”ํ•˜๊ธฐ ์œ„ํ•œ '๊ณ ์œ ๋„๋ฏธ์•ˆ'์ด๋ผ๋Š” ๊ฐœ๋…์„ ์†Œ๊ฐœํ•˜๊ณ , ์ด์— ๋Œ€ํ•œ ์กด์žฌ์„ฑ ์ฆ๋ช…์„ ์ˆ˜ํ–‰ํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ์—ฐ๊ตฌ๋Š” ์„ ํ˜• ๋Œ€์ˆ˜ํ•™ ๋ฐ ํ•จ์ˆ˜ ํ•ด์„ํ•™ ๋ถ„์•ผ์—์„œ ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•˜๋Š” ์—ฐ์‚ฐ์ž์˜ ๊ทผ์‚ฌ์™€ ๊ด€๋ จ๋œ ๋ฌธ์ œ๋ฅผ ๋‹ค๋ฃจ๋ฉฐ, ํŠนํžˆ ์—ฐ์†์ ์ธ ๋ณ€ํ™”๋ฅผ ๊ฒฝํ—˜ํ•˜๋Š” ์‹œ์Šคํ…œ์˜ ๋™์  ํŠน์„ฑ์„ ์ดํ•ดํ•˜๋Š”๋ฐ ์žˆ์–ด ํ•ต์‹ฌ์ ์ธ ๋„๊ตฌ๊ฐ€ ๋  ์ˆ˜ ์žˆ๋‹ค. ๋…ผ๋ฌธ์€ ๋จผ์ € ์‹ค์ˆ˜ ๋˜๋Š” ๋ณต์†Œ์ˆ˜ ๋ฐ”๋‚˜ํ ๊ณต๊ฐ„ X์—์„œ ์‹œ์ž‘ํ•œ๋‹ค. ์ด ๊ณต๊ฐ„์€ ๋‹จ์ˆœ ํ•จ์ˆ˜๋“ค์˜ ์ง๊ต ์ง‘ํ•ฉ์œผ๋กœ ๊ตฌ์„ฑ๋œ ๋ฒกํ„ฐ ๊ณต๊ฐ„์˜ ์™„์„ฑ์ฒด๋กœ, ์ด๋Ÿฌํ•œ ์„ค์ •์€ ๊ณ ์œ ๊ฐ’๊ณผ ๊ณ ์œ ๋ฒกํ„ฐ์— ๋Œ€ํ•œ ๋ถ„์„์„ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•œ๋‹ค. ํŠน

Mathematics
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Extrapolation of Urn Models via Poissonization: Accurate Measurements of the Microbial Unknown

๋ณธ ๋…ผ๋ฌธ์€ ๋ฏธ์ƒ๋ฌผ ๊ณต๋™์ฒด ๋‚ด์˜ ๋‹ค์–‘์„ฑ์„ ์ธก์ •ํ•˜๋Š” ๊ธฐ์กด ๋ฐฉ๋ฒ•๋ก ์˜ ํ•œ๊ณ„๋ฅผ ๊ทน๋ณตํ•˜๊ณ ์ž, ์ƒ˜ํ”Œ๋ง๋˜์ง€ ์•Š์€ ํด๋ž˜์Šค์˜ ๋น„์œจ์„ ์˜ˆ์ธกํ•˜๋Š” ์ƒˆ๋กœ์šด ์ ‘๊ทผ ๋ฐฉ์‹์„ ์ œ์•ˆํ•œ๋‹ค. ์ด๋Š” ๋ฏธ์ƒ๋ฌผ ์—ฐ๊ตฌ์—์„œ ์ค‘์š”ํ•œ ๋ฌธ์ œ ์ค‘ ํ•˜๋‚˜์ธ '๋ฏธ์ง€์˜ ์–‘'์— ๋Œ€ํ•œ ์ •ํ™•ํ•œ ์ธก์ •์„ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•œ๋‹ค. ๋…ผ๋ฌธ์€ ์šฐ๋ฅธ ๋ชจ๋ธ๊ณผ ํฌ์ƒํ™” ๋…ผ์ฆ์„ ํ™œ์šฉํ•˜์—ฌ, ์•„์ง ๋ฐœ๊ฒฌ๋˜์ง€ ์•Š์€ ์ข…์˜ ์กด์žฌ๋ฅผ ๊ฐ€์ •ํ•˜๊ณ  ์ด๋ฅผ ์˜ˆ์ธกํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค. ์ด๋Š” ์ƒ˜ํ”Œ๋ง๋œ ๋ฐ์ดํ„ฐ์—์„œ ๋ฏธ์ง€์˜ ์–‘์„ ์ถ”๋ก ํ•˜๋Š”๋ฐ ์žˆ์–ด ์ค‘์š”ํ•œ ๋ฐœ์ „์ด๋‹ค. ํŠนํžˆ, ๊ณ ์ •๋œ ์ƒ˜ํ”Œ ํฌ๊ธฐ์—์„œ๋„ ์›๋ณธ ์ƒ˜ํ”Œ์˜ ํ•˜์œ„ ์ง‘ํ•ฉ์— ๋Œ€ํ•ด ๋งค์šฐ ์ •ํ™•ํ•œ ์˜ˆ์ธก ๊ฒฐ๊ณผ๋ฅผ ์ œ๊ณตํ•จ์œผ๋กœ์จ

Quantitative Biology Statistics Mathematics Model
Total coloring of pseudo-outerplanar graphs

Total coloring of pseudo-outerplanar graphs

: 1. ์ด ์ƒ‰์น  ๋ฌธ์ œ์™€ ๊ทธ ์ค‘์š”์„ฑ ์ด ์ƒ‰์น  ๋ฌธ์ œ๋Š” ๊ทธ๋ž˜ํ”„ ์ด๋ก ์—์„œ ์ค‘์š”ํ•œ ์œ„์น˜๋ฅผ ์ฐจ์ง€ํ•˜๋ฉฐ, ๊ฐ ์ •์ ๊ณผ ๊ฐ„์„ ์— ๊ณ ์œ ํ•œ ์ƒ‰์ƒ์„ ํ• ๋‹นํ•˜๋Š” ๋ฐฉ์‹์œผ๋กœ ๊ทธ๋ž˜ํ”„์˜ ๊ตฌ์กฐ์  ํŠน์„ฑ์„ ์ดํ•ดํ•˜๊ณ  ๋ถ„์„ํ•ฉ๋‹ˆ๋‹ค. ํŠนํžˆ, ์ด ์ƒ‰์น  ์ถ”์ธก์€ ๊ทธ๋ž˜ํ”„์˜ ์ตœ๋Œ€ ์ฐจ์ˆ˜ ฮ”(G)์™€ ๊ด€๋ จ๋œ ์ค‘์š”ํ•œ ๋ฌธ์ œ๋กœ, ์ด ์ถ”์ธก์ด ์ฆ๋ช…๋˜๋ฉด ๋งŽ์€ ๊ทธ๋ž˜ํ”„ ํด๋ž˜์Šค์— ๋Œ€ํ•œ ์ด ์ƒ‰์ƒ ์ˆ˜๋ฅผ ๊ฒฐ์ •ํ•˜๋Š” ๋ฐ ๋„์›€์ด ๋ฉ๋‹ˆ๋‹ค. 2. ์œ„์ƒ์  ์™ธํŒ ๊ทธ๋ž˜ํ”„์˜ ์ •์˜ ๋ฐ ํŠน์„ฑ ์œ„์ƒ์  ์™ธํŒ ๊ทธ๋ž˜ํ”„๋Š” ๊ฐ ๋ธ”๋ก์ด ๊ณ ์ •๋œ ์› ์œ„์—์„œ ์ •์ ๋“ค์„ ๋ฐฐ์น˜ํ•˜๊ณ , ๊ฐ„์„ ๋“ค์ด ์›์˜ ๋””์Šคํฌ ๋‚ด๋ถ€์—์„œ ์„œ๋กœ ๊ต์ฐจํ•˜์ง€ ์•Š๋„๋ก ๋ฐฐ์น˜๋  ์ˆ˜ ์žˆ๋Š” ๊ทธ๋ž˜

Mathematics Computer Science Discrete Mathematics
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Representing a profinite group as the homeomorphism group of a continuum

: ์ด ๋…ผ๋ฌธ์€ ํ”„๋กœํ•€ํŠธ ๊ตฐ(profinite group)์˜ ํ‘œํ˜„์— ์ƒˆ๋กœ์šด ์ ‘๊ทผ ๋ฐฉ์‹์„ ์ œ์‹œํ•˜๊ณ  ์žˆ๋‹ค. ํŠนํžˆ, ์ด ์—ฐ๊ตฌ๋Š” ๊ทธ๋ž˜ํ”„ ์ด๋ก ์„ ํ™œ์šฉํ•˜์—ฌ ํ”„๋กœํ•€ํŠธ ๊ตฐ์„ ์—ฐ์†์ ์ธ ์—ฐ๊ฒฐ๋œ ๋ฉ”ํŠธ๋ฆญ ๊ณต๊ฐ„์˜ ํ™ˆ์˜ค๋ชจ๋ฅดํ”ผ์ฆ˜ ๊ทธ๋ฃน(homeomorphism group)์œผ๋กœ ํ‘œํ˜„ํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ํƒ๊ตฌํ•œ๋‹ค. 1. ๊ธฐ์กด ์—ฐ๊ตฌ์™€์˜ ์ฐจ๋ณ„ํ™” ๊ธฐ์กด ์—ฐ๊ตฌ์—์„œ๋Š” ์ฃผ๋กœ ํ”„๋กœํ•€ํŠธ ๊ตฐ์ด ์ปดํŒฉํŠธํ•œ ์—ฐ๊ฒฐ๋œ ๋ฉ”ํŠธ๋ฆญ ๊ณต๊ฐ„์˜ ํ™ˆ์˜ค๋ชจ๋ฅดํ”ผ์ฆ˜ ๊ทธ๋ฃน๊ณผ ๋™ํ˜•์ด๋ผ๋Š” ์‚ฌ์‹ค์„ ์ฆ๋ช…ํ•˜์˜€๋‹ค(

Mathematics
Reversibility in Massive Concurrent Systems

Reversibility in Massive Concurrent Systems

: ๋ณธ ๋…ผ๋ฌธ์€ ๋Œ€๊ทœ๋ชจ ๋ณ‘๋ ฌ ์‹œ์Šคํ…œ์—์„œ ์—ญ์ „ ๊ฐ€๋Šฅ์„ฑ์˜ ๊ฐœ๋…๊ณผ ๊ทธ ์ ์šฉ ๋ฒ”์œ„๋ฅผ ํƒ๊ตฌํ•˜๊ณ  ์žˆ๋‹ค. ์—ญ์ „ ๊ฐ€๋Šฅ์„ฑ์€ ์ž…๋ ฅ ๋ฐ์ดํ„ฐ๊ฐ€ ์ˆœ์ฐจ์ ์œผ๋กœ ์ฒ˜๋ฆฌ๋˜๋ฉด์„œ, ์ฒซ ๋ฒˆ์งธ ์ž…๋ ฅ์ด ๋‘ ๋ฒˆ์งธ ์ž…๋ ฅ ์—†์ด๋„ ๋ฐฉ์ถœ๋˜์–ด ๋‹ค๋ฅธ ์—ฐ์‚ฐ์ž์— ์˜ํ•ด ์‚ฌ์šฉ๋  ์ˆ˜ ์žˆ๋Š” ๋Šฅ๋ ฅ์„ ์˜๋ฏธํ•œ๋‹ค. ์ด๋Š” ๋ณ‘๋ ฌ ์‹œ์Šคํ…œ์—์„œ ํšจ์œจ์ ์ธ ๋ฐ์ดํ„ฐ ์ฒ˜๋ฆฌ์™€ ํ”„๋กœ์„ธ์‹ฑ์„ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•˜๋Š” ์ค‘์š”ํ•œ ํŠน์„ฑ์ด๋‹ค. ๋…ผ๋ฌธ์€ ์—ญ์ „ ๊ฐ€๋Šฅ์„ฑ์˜ ๊ตฌ์กฐ๋ฅผ ๋ถ„์„ํ•˜๋ฉด์„œ, ํŠนํžˆ ์ผ๊ด€์„ฑ ์ œ์•ฝ ์กฐ๊ฑด ํ•˜์—์„œ ๋‹ค์ค‘์„ฑ์ด ์ œ๊ฑฐ๋œ ์—ญ์ „ ๊ฐ€๋Šฅํ•œ ๊ตฌ์กฐ์— ์ดˆ์ ์„ ๋งž์ถ”๊ณ  ์žˆ๋‹ค. ์ด๋Š” ๋ณ‘๋ ฌ ์‹œ์Šคํ…œ ๋‚ด์—์„œ ๋ฐ์ดํ„ฐ ์ฒ˜๋ฆฌ ๊ณผ์ •์ด ์ผ๊ด€์„ฑ์„ ์œ ์ง€ํ•˜๋„๋ก ํ•˜๋Š” ์ค‘์š”ํ•œ

Formal Languages Distributed Computing Computer Science System
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Greedy Set Cover Estimations

๋ณธ ๋…ผ๋ฌธ์€ ์ง‘ํ•ฉ ๋ฎ๊ธฐ ๋ฌธ์ œ(Set Cover Problem)์— ๋Œ€ํ•œ ์ƒˆ๋กœ์šด ์ ‘๊ทผ ๋ฐฉ์‹์„ ์ œ์•ˆํ•˜๋ฉฐ, ํŠนํžˆ ์ด์ง„ ํƒ์ƒ‰ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ด์šฉํ•œ ๊ทผ์‚ฌ ์•Œ๊ณ ๋ฆฌ์ฆ˜์˜ ๊ฐœ์„ ์ ์„ ๋‹ค๋ฃฌ๋‹ค. ์ง‘ํ•ฉ ๋ฎ๊ธฐ ๋ฌธ์ œ๋Š” NP ์™„์ „ ๋ฌธ์ œ๋กœ ์•Œ๋ ค์ ธ ์žˆ์–ด ์ •ํ™•ํ•œ ํ•ด๊ฒฐ์ฑ…์„ ์ฐพ๋Š” ๊ฒƒ์ด ๋งค์šฐ ์–ด๋ ต๋‹ค๋Š” ์ ์—์„œ ์ค‘์š”ํ•˜๋‹ค. ๋”ฐ๋ผ์„œ, ๋ณธ ๋…ผ๋ฌธ์€ ์ด ๋ฌธ์ œ๋ฅผ ํšจ๊ณผ์ ์œผ๋กœ ๊ทผ์‚ฌํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•จ์œผ๋กœ์จ ์‹ค์šฉ์ ์ธ ํ•ด๊ฒฐ์ฑ…์„ ์ œ๊ณตํ•œ๋‹ค. ๊ธฐ์กด ์ ‘๊ทผ ๋ฐฉ์‹์˜ ํ•œ๊ณ„ ๊ธฐ์กด์˜ ์ ‘๊ทผ ๋ฐฉ์‹์—์„œ๋Š” ๊ฐ ์—ด์— ์ตœ์†Œ m๊ฐœ์˜ 1์ด ์žˆ๋Š” (0,1) ํ–‰๋ ฌ๋กœ ์ง‘ํ•ฉ ๋ฎ๊ธฐ ๋ฌธ์ œ๋ฅผ ํ‘œํ˜„ํ•˜๊ณ , ์ด์ง„ ํƒ์ƒ‰์„ ํ†ตํ•ด ๊ฐ€์žฅ ๋งŽ์€ 1์„ ํฌํ•จํ•˜

Computer Science Discrete Mathematics
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The M/M/Infinity Service System with Ranked Servers in Heavy Traffic

: ๋ณธ ๋…ผ๋ฌธ์€ ๋ฌดํ•œ ์„œ๋ฒ„ ์‹œ์Šคํ…œ์—์„œ ๊ณ ๊ฐ ์ฒ˜๋ฆฌ ๊ณผ์ •์„ ์ˆ˜ํ•™์ ์œผ๋กœ ํƒ๊ตฌํ•˜๋ฉฐ, ํŠนํžˆ Newell์ด ์ œ๊ธฐํ•œ ๊ท ํ˜• ์ƒํƒœ์—์„œ ์ƒˆ๋กœ์šด ๊ณ ๊ฐ์„ ์ฒ˜๋ฆฌํ•˜๋Š” ์„œ๋ฒ„์˜ ์ธ๋ฑ์Šค ๋ถ„ํฌ์— ๋Œ€ํ•œ ๋ฌธ์ œ๋ฅผ ๋‹ค๋ฃฌ๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ๊ธฐ์กด์˜ ๊ทผ์‚ฌ์‹๋“ค์— ๋Œ€ํ•œ ์—„๋ฐ€ํ•œ ์ฆ๋ช…๊ณผ ๋” ๋†’์€ ์ฐจ์ˆ˜์˜ ๋ถ„ํฌ๋ฅผ ํ™•๋ฆฝํ•˜๋Š”๋ฐ ์ดˆ์ ์„ ๋งž์ถ˜๋‹ค. ๋…ผ๋ฌธ์—์„œ ์ฃผ์š” ๊ด€์‹ฌ์‚ฌ๋Š” ๊ณ ๊ฐ์ด ๋„์ฐฉํ•  ๋•Œ ๊ฐ€์žฅ ๋‚ฎ์€ ์ธ๋ฑ์Šค๋ฅผ ๊ฐ€์ง„ ๋น„์–ด์žˆ๋Š” ์„œ๋ฒ„์— ํ• ๋‹น๋˜๋Š” ๊ณผ์ •์ด๋‹ค. ์ด๋Š” M/M/โˆž ์„œ๋น„์Šค ์‹œ์Šคํ…œ์ด๋ผ๊ณ  ์•Œ๋ ค์ ธ ์žˆ์œผ๋ฉฐ, ฮป โ†’ โˆž์˜ ํ•œ๊ณ„ ์ƒํ™ฉ์—์„œ ๊ด‘๋ฒ”์œ„ํ•˜๊ฒŒ ์—ฐ๊ตฌ๋˜์—ˆ๋‹ค. Newell์€ L์ด '

Performance Mathematics Computer Science System
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A Novel Attack against Android Phones

๋ณธ ๋…ผ๋ฌธ์€ ์•ˆ๋“œ๋กœ์ด๋“œ ์Šค๋งˆํŠธํฐ์˜ ๋ณด์•ˆ ์ทจ์•ฝ์ ์„ ์ง‘์ค‘์ ์œผ๋กœ ๋ถ„์„ํ•˜๊ณ , ์ด๋ฅผ ์•…์šฉํ•  ์ˆ˜ ์žˆ๋Š” ์ƒˆ๋กœ์šด ๊ณต๊ฒฉ ๊ธฐ๋ฒ•์„ ์ œ์‹œํ•ฉ๋‹ˆ๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” 2011๋…„ 1๋ถ„๊ธฐ์— ๊ฐ€์žฅ ๋งŽ์ด ํŒ๋งค๋œ ์šด์˜์ฒด์ œ์ธ ์•ˆ๋“œ๋กœ์ด๋“œ๋ฅผ ๋Œ€์ƒ์œผ๋กœ ํ•˜๋ฉฐ, ํŠนํžˆ ์Šค๋งˆํŠธํฐ ์‚ฌ์šฉ์ž๋“ค์ด ์ง๋ฉดํ•˜๊ฒŒ ๋  ์ž ์žฌ์ ์ธ ์œ„ํ˜‘์— ๋Œ€ํ•ด ๊ฒฝ๊ฐ์‹ฌ์„ ๋ถˆ๋Ÿฌ์ผ์œผํ‚ค๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์ทจ์•ฝ์ ์˜ ์‹ฌ๊ฐ์„ฑ ๋ณธ ๋…ผ๋ฌธ์—์„œ ์ œ์‹œ๋œ ๊ณต๊ฒฉ ๊ธฐ๋ฒ•์€ ๋งค์šฐ ์น˜๋ช…์ ์ž…๋‹ˆ๋‹ค. ์ด๋Š” ๋‹จ์ˆœํžˆ ์•…์„ฑ ์• ํ”Œ๋ฆฌ์ผ€์ด์…˜์„ ์„ค์น˜ํ•˜๋Š” ๋ฐ ๊ทธ์น˜์ง€ ์•Š๊ณ , ์‚ฌ์šฉ์ž์˜ ์ธ์‹ ์—†์ด ์ด๋ฃจ์–ด์ง‘๋‹ˆ๋‹ค. ์ฆ‰, ์‚ฌ์šฉ์ž๊ฐ€ ์–ด๋– ํ•œ ๊ถŒํ•œ๋„ ๋ถ€์—ฌํ•˜์ง€ ์•Š์•„๋„ ์•…์„ฑ ์• ํ”Œ๋ฆฌ์ผ€์ด์…˜์ด ์ž๋™์œผ๋กœ ์„ค

Computer Science Cryptography and Security
No Image

The Degree Sequence of Random Apollonian Networks

๋ณธ ๋…ผ๋ฌธ์€ ๋žœ๋ค ์•„ํด๋กœ๋‹ˆ ๋„คํŠธ์›Œํฌ(RANs)์˜ ์ •๋„ ๋ถ„ํฌ์— ๋Œ€ํ•œ ๊นŠ์ด ์žˆ๋Š” ๋ถ„์„์„ ์ œ๊ณตํ•˜๋ฉฐ, ์ด๋Š” ๊ทธ๋ž˜ํ”„ ์ด๋ก ์—์„œ ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•˜๋Š” ๋ชจ๋ธ ์ค‘ ํ•˜๋‚˜์ด๋‹ค. RANs๋Š” ํ‰๋ฉด ๊ทธ๋ž˜ํ”„๋กœ์„œ, ๊ฐ ๋‹จ๊ณ„์—์„œ ๋ฌด์ž‘์œ„๋กœ ์‚ผ๊ฐํ˜•์„ ์„ ํƒํ•˜๊ณ  ๊ทธ ๋‚ด๋ถ€์— ์ƒˆ๋กœ์šด ์ •์ ์„ ์ถ”๊ฐ€ํ•˜์—ฌ ๋„คํŠธ์›Œํฌ๋ฅผ ํ™•์žฅํ•œ๋‹ค. 1. ์„œ๋ก  ์„œ๋ก ์—์„œ๋Š” ๋ณธ ๋…ผ๋ฌธ์˜ ์ฃผ์š” ๋ชฉํ‘œ์™€ ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ์ด ์„ค๋ช…๋œ๋‹ค. RANs๋Š”

Physics Network Mathematics Social Networks Computer Science
No Image

The cradle of pyramids in satellite images

๋ณธ ๋…ผ๋ฌธ์€ ์œ„์„ฑ ์ด๋ฏธ์ง€์™€ ์›๊ฒฉ ๊ฐ์ง€ ๊ธฐ๋ฒ•์ด ์–ด๋–ป๊ฒŒ ์ด์ง‘ํŠธ ๊ณ ๋Œ€ ์œ ์  ๋ฐœ๊ตด์— ํ™œ์šฉ๋  ์ˆ˜ ์žˆ๋Š”์ง€๋ฅผ ํƒ๊ตฌํ•˜๊ณ  ์žˆ๋‹ค. ์ €์ž๋Š” ๊ตฌ๊ธ€ ๋งต์Šค์˜ ์ด๋ฏธ์ง€ ์ฒ˜๋ฆฌ ๊ธฐ๋Šฅ๊ณผ SIR C/X SAR ๋ ˆ์ด๋” ์‹œ์Šคํ…œ์„ ๋น„๊ต ๋ถ„์„ํ•จ์œผ๋กœ์จ, ์›๊ฒฉ ๊ฐ์ง€ ๊ธฐ๋ฒ•์˜ ํšจ๊ณผ์„ฑ์„ ์ž…์ฆํ•˜๋ ค๊ณ  ๋…ธ๋ ฅํ•œ๋‹ค. 1. ์›๊ฒฉ ๊ฐ์ง€ ๊ธฐ๋ฒ•์˜ ์ค‘์š”์„ฑ ๋…ผ๋ฌธ์€ ๊ณ ๊ณ ํ•™์—์„œ ์›๊ฒฉ ๊ฐ์ง€ ๊ธฐ๋ฒ•์ด ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•œ๋‹ค๋Š” ์ ์„ ๊ฐ•์กฐํ•˜๊ณ  ์žˆ๋‹ค. ํŠนํžˆ, SIR C/X SAR ๋ ˆ์ด๋” ์‹œ์Šคํ…œ๊ณผ ๊ตฌ๊ธ€ ๋งต์Šค์˜ ์ด๋ฏธ์ง€๋ฅผ ๋น„๊ต ๋ถ„์„ํ•จ์œผ๋กœ์จ, ์ด๋Ÿฌํ•œ ๊ธฐ์ˆ ๋“ค์ด ์ด์ง‘ํŠธ ๊ณ ๋Œ€ ์œ ์  ๋ฐœ๊ตด์— ์–ด๋–ป๊ฒŒ ํ™œ์šฉ๋  ์ˆ˜ ์žˆ๋Š”์ง€ ์„ค๋ช…ํ•œ๋‹ค. 2. ๊ตฌ๊ธ€

Physics
Constraining dark matter signal from a combined analysis of Milky Way   satellites using the Fermi-LAT

Constraining dark matter signal from a combined analysis of Milky Way satellites using the Fermi-LAT

๋ณธ ๋…ผ๋ฌธ์€ ํŽ˜๋ฅด๋ฏธ LAT๋ฅผ ์ด์šฉํ•˜์—ฌ ์—ฌ๋Ÿฌ ๋‚œ์†Œ ๊ตฌํ˜• ์€ํ•˜(dSph)์—์„œ ์•”ํ‘ ๋ฌผ์งˆ(DM) ์‹ ํ˜ธ๋ฅผ ํƒ์‚ฌํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ๊ฐœ๋ณ„ dSph์— ๋Œ€ํ•œ ๋ถ„์„ ๊ฒฐ๊ณผ๋ฅผ ๊ฒฐํ•ฉํ•จ์œผ๋กœ์จ, ์•”ํ‘ ๋ฌผ์งˆ ์‹ ํ˜ธ์˜ ๊ฐ๋„๋ฅผ ํ–ฅ์ƒ์‹œํ‚ค๊ณ ์ž ํ•ฉ๋‹ˆ๋‹ค. ์„œ๋ก  ํŽ˜๋ฅด๋ฏธ LAT๋Š” 20MeV์—์„œ 300GeV ์ด์ƒ์˜ ์—๋„ˆ์ง€๋ฅผ ์ธก์ •ํ•  ์ˆ˜ ์žˆ๋Š” ๋Šฅ๋ ฅ์„ ๊ฐ€์ง€๊ณ  ์žˆ์–ด, ์•”ํ‘ ๋ฌผ์งˆ ํƒ์‚ฌ์— ์ ํ•ฉํ•œ ๋„๊ตฌ์ž…๋‹ˆ๋‹ค. ํŠนํžˆ, ์•ฝํ•˜๊ฒŒ ์ƒํ˜ธ์ž‘์šฉํ•˜๋Š” ๋ฌด๊ฑฐ์šด ์ž…์ž(WIMP)๋ฅผ ๋Œ€์ƒ์œผ๋กœ ํ•ฉ๋‹ˆ๋‹ค. ๋ถ„์„ ๋ฐฉ๋ฒ• ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์—ฌ๋Ÿ ๊ฐœ์˜ dSph์— ๋Œ€ํ•œ ๊ฒฐํ•ฉ ๊ฐ€๋Šฅ๋„ ๋ถ„์„์„ ์ˆ˜ํ–‰ํ•˜์˜€์Šต๋‹ˆ๋‹ค. ์ด

Analysis HEP-PH Astrophysics
Weighted Radial Variation for Node Feature Classification

Weighted Radial Variation for Node Feature Classification

๋ณธ ๋…ผ๋ฌธ์€ ๋ณต์žกํ•œ ๋„คํŠธ์›Œํฌ์—์„œ ๋…ธ๋“œ ํŠน์„ฑ ๋ถ„๋ฅ˜์˜ ์ƒˆ๋กœ์šด ์ ‘๊ทผ๋ฒ•์ธ ๊ฐ€์ค‘ ๋ฐฉ์‚ฌ ๋ณ€์ด(WRV) ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. WRV๋Š” ๊ฐ ๋…ธ๋“œ์— ๋Œ€ํ•œ ๋ฒกํ„ฐ ํ๋ฆ„ ๊ตฌ์„ฑ์— ๊ธฐ๋ฐ˜ํ•˜์—ฌ, ์นด๋ฅด๋””๋‚˜๋ฆฌํ‹ฐ(๋…ธ๋“œ ๊ฐ„ ์—ฐ๊ฒฐ ์ˆ˜), ๋ฐฉํ–ฅ, ๊ธธ์ด, ๊ทธ๋ฆฌ๊ณ  ํ๋ฆ„ ํฌ๊ธฐ์˜ ์ธก๋ฉด์—์„œ ๋™๊ธฐํ™”๋œ ๊ฐ ์—”ํ‹ฐํ‹ฐ์˜ ๋ฒกํ„ฐ๋ฅผ ์‚ฌ์šฉํ•ฉ๋‹ˆ๋‹ค. ์ด๋Š” ๋ณต์žกํ•œ ๋„คํŠธ์›Œํฌ ๋ถ„์„์—์„œ ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•˜๋Š”๋ฐ, ํŠนํžˆ ๋น„์ธ์ ‘ ๊ณต๊ฐ„์— ์—ฐ๊ฒฐ๋˜๋Š” ์ธ๊ฐ„๊ณผ ์ •๋ณด ํ๋ฆ„์˜ ๋ณต์žกํ•œ ์—ญํ•™์„ ์ดํ•ดํ•˜๋Š” ๋ฐ ์œ ์šฉํ•ฉ๋‹ˆ๋‹ค. WRV ๊ณผ์ •์€ ๋ณ„ ๋ชจ์–‘ ์—”ํ‹ฐํ‹ฐ์˜ ๊ฐœ๋ณ„ ํ๋ฆ„ ๋ฒกํ„ฐ๋ฅผ 0 360ยฐ ์ŠคํŽ™ํŠธ๋Ÿผ์— ํŽผ์ณ ๋…ํŠนํ•œ ์‹ ํ˜ธ๋ฅผ ํ˜•์„ฑํ•˜๋ฉฐ, ์ด

Computer Science Computer Vision Physics
Interaction of neutralino dark matter with cosmic rays and PAMELA/ATIC   data

Interaction of neutralino dark matter with cosmic rays and PAMELA/ATIC data

: 1. ์„œ๋ก  ๋ถ„์„ ์•”ํ‘๋ฌผ์งˆ์€ ์ฃผ๋กœ ์ค‘๋ ฅ์— ์˜ํ•ด๋งŒ ๋“œ๋Ÿฌ๋‚˜๋Š” ๊ฒƒ์œผ๋กœ ์•Œ๋ ค์ ธ ์žˆ์ง€๋งŒ, ๋น›๋‚˜๋Š” ์ค‘์„ฑ๋ฏธ์ž ์•”ํ‘๋ฌผ์งˆ์˜ ๊ฒฝ์šฐ, ๊ฐ€๋ฒผ์šด ์ค‘์„ฑ๋ฏธ์ž(mโ‚™ โ‰ค 10โปยณ GeV)๋กœ ๊ตฌ์„ฑ๋  ๋•Œ์—๋Š” ์•ฝํ•œ ์ƒํ˜ธ์ž‘์šฉ์—๋„ ์ฐธ์—ฌํ•  ์ˆ˜ ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์šฐ์ฃผ์„  ์–‘์„ฑ์ž์™€ ์ค‘์„ฑ๋ฏธ์ž ์•”ํ‘๋ฌผ์งˆ ๊ฐ„์˜ ์ถฉ๋Œ์„ ๋ถ„์„ํ•œ๋‹ค. ์ด ๊ณผ์ •์€ ์ฐจ๊ธฐ(chargino) ์ƒ์„ฑ๊ณผ ๋ ˆํ”„ํ†ค ๋ถ•๊ดด๋ฅผ ๋™๋ฐ˜ํ•˜๋ฉฐ, ์ตœ์ข…์ ์œผ๋กœ ์ „์ž ๋ฐ˜์ค‘์„ฑ๋ฏธ์ž ์Œ์ด ์ƒ์„ฑ๋œ๋‹ค. 2. ๊ณผ์ • ๋ถ„์„ ๋…ผ๋ฌธ์—์„œ๋Š” ์—๋„ˆ์ง€ ๋ฐ ์šด๋™๋Ÿ‰ ๋ณด์กด ๋ฒ•์น™์„ ์‚ฌ์šฉํ•˜์—ฌ ์ค‘์„ฑ๋ฏธ์ž์™€ ์ฐจ๊ธฐ์˜ ์—๋„ˆ์ง€๋ฅผ ๊ณ„์‚ฐํ•œ๋‹ค. ์ด๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™์€ ๋ฐฉ์ •์‹์œผ๋กœ ํ‘œํ˜„๋œ๋‹ค: ์ค‘

Astrophysics Data
A Novel Template-Based Learning Model

A Novel Template-Based Learning Model

: ๋ณธ ๋…ผ๋ฌธ์€ ํ…œํ”Œ๋ฆฟ ๊ธฐ๋ฐ˜ ํ•™์Šต ๋ชจ๋ธ์„ ํ†ตํ•ด ์ƒˆ๋กœ์šด ๊ด€์ฐฐ ๋ฐ์ดํ„ฐ๋ฅผ ์ดํ•ดํ•˜๋Š” ๋ฐฉ๋ฒ•์— ๋Œ€ํ•ด ์„ค๋ช…ํ•˜๊ณ  ์žˆ๋‹ค. ์ด ๋ชจ๋ธ์€ ์ฃผ๋กœ ๊ด€์ฐฐ ๋ฐ์ดํ„ฐ ๊ฐ„์˜ ์œ ์‚ฌ์„ฑ ํƒ์ƒ‰๊ณผ ๋น„๊ต๋ฅผ ํ†ตํ•ด ์ƒˆ๋กœ์šด ๊ฐœ๋…์„ ํ•™์Šตํ•˜๊ณ  ์ถ”์ƒํ™”ํ•˜๋Š”๋ฐ ์ดˆ์ ์„ ๋งž์ถ”๊ณ  ์žˆ๋‹ค. 1. ํ…œํ”Œ๋ฆฟ ๊ธฐ๋ฐ˜ ํ•™์Šต ๋ชจ๋ธ์˜ ๊ตฌ์„ฑ ์š”์†Œ ๊ธฐํ•˜ํ•™์  ๋ฌ˜์‚ฌ : ์ด ๋ชจ๋ธ์€ ๊ด€์ฐฐ ๋ฐ์ดํ„ฐ๋ฅผ ๊ธฐํ•˜ํ•™์ ์œผ๋กœ ๋ฌ˜์‚ฌํ•˜๋Š” ๋ฐฉ์‹์„ ์‚ฌ์šฉํ•œ๋‹ค. ์ด๋ฅผ ํ†ตํ•ด ๊ฐ์ฒด์˜ ๊ฒฝ๊ณ„์™€ ํ˜•ํƒœ๋ฅผ ์ •ํ™•ํ•˜๊ฒŒ ํŒŒ์•…ํ•  ์ˆ˜ ์žˆ๋‹ค. ์ธ๊ฐ„ ์‹œ๊ฐ ์‹ ๊ฒฝ ์‹œ์Šคํ…œ์— ์˜๊ฐ ๋ฐ›์€ ์„ค๋ช…์ž : ์ธ๊ฐ„์˜ ์‹œ๊ฐ ์ธ์ง€ ๊ณผ์ •์—์„œ ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•˜๋Š” ์š”์†Œ๋“ค์„ ๋ชจ๋ธ๋งํ•˜์—ฌ, ๋” ์ •๊ตํ•œ ๋ฐ์ดํ„ฐ

Model Machine Learning Computer Science Learning
Jancars formal system for deciding bisimulation of first-order grammars   and its non-soundness

Jancars formal system for deciding bisimulation of first-order grammars and its non-soundness

: 1. ์ฒซ ๋ฒˆ์งธ ์ˆœ์„œ ๋ฌธ๋ฒ•๊ณผ ํ–‰๋™ ์•ŒํŒŒ๋ฒณ์˜ ์ •์˜ ๋…ผ๋ฌธ์€ ์ฒซ ๋ฒˆ์งธ ์ˆœ์„œ ๋ฌธ๋ฒ•์— ๋Œ€ํ•œ ๋น„์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด Jancar์˜ ํ˜•์‹ ์‹œ์Šคํ…œ์„ ๊ฒ€ํ† ํ•œ๋‹ค. ์ด ๊ณผ์ •์—์„œ ํ–‰๋™ ์•ŒํŒŒ๋ฒณ A์™€ ์ค‘๊ฐ„ ๋ผ๋ฒจ ์•ŒํŒŒ๋ฒณ T, ๊ทธ๋ฆฌ๊ณ  ๋งต LAB A: T โ†’ A๋ฅผ ์ •์˜ํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ์ •์˜๋Š” ์ฒซ ๋ฒˆ์งธ ์ˆœ์„œ ๋ฌธ๋ฒ• G (N, A, R)์„ ๊ตฌ์„ฑํ•˜๋Š” ๋ฐ ํ•„์š”ํ•œ ๊ธฐ๋ณธ ์š”์†Œ๋ฅผ ์ œ๊ณตํ•˜๋ฉฐ, ์—ฌ๊ธฐ์„œ N์€ ๋น„ํ„ฐ๋ฏธ๋„ ์ง‘ํ•ฉ, A๋Š” ํ–‰๋™ ์•ŒํŒŒ๋ฒณ, ๊ทธ๋ฆฌ๊ณ  R์€ ๊ทœ์น™ ์ง‘ํ•ฉ์ด๋‹ค. 2. Jancar ํ˜•์‹ ์‹œ์Šคํ…œ์˜ ๊ฐœ์š” Jancar์˜ ํ˜•์‹ ์‹œ์Šคํ…œ์€

Computer Science Formal Languages Logic System
Casting Robotic End-effectors To Reach Faraway Moving Objects

Casting Robotic End-effectors To Reach Faraway Moving Objects

๋ณธ ๋…ผ๋ฌธ์€ ๋กœ๋ด‡ ์—”๋“œ ์ดํŽ™ํ„ฐ๊ฐ€ ๋ฉ€๋ฆฌ ๋–จ์–ด์ง„ ์›€์ง์ด๋Š” ๋ฌผ์ฒด๋ฅผ ์žก๋Š” ๋ฌธ์ œ์— ๋Œ€ํ•œ ํ˜์‹ ์ ์ธ ์ ‘๊ทผ๋ฒ•์„ ์ œ์‹œํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ๊ธฐ์กด์˜ ์บ์ŠคํŒ… ์กฐ์ž‘์ด ๊ณ ์ •๋œ ๋ฌผ์ฒด๋ฅผ ๋Œ€์ƒ์œผ๋กœ ํ•œ ๊ฒƒ๊ณผ ๋‹ฌ๋ฆฌ, ๋ณธ ๋…ผ๋ฌธ์€ 3์ฐจ์› ๊ณต๊ฐ„์—์„œ ์›€์ง์ด๋Š” ํƒ€๊ฒŸ์„ ์žก๋Š” ๋ฐ ์ดˆ์ ์„ ๋งž์ถ”๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. 1. ์บ์ŠคํŒ… ์กฐ์ž‘์˜ ์›๋ฆฌ์™€ ์ ์šฉ ์บ์ŠคํŒ… ์กฐ์ž‘์€ ๊ฐ€๋ฒผ์šด ์ผ€์ด๋ธ”์„ ํ†ตํ•ด ์—ฐ๊ฒฐ๋œ ์—”๋“œ ์ดํŽ™ํ„ฐ๋ฅผ ๋˜์ ธ ๋ฉ€๋ฆฌ ๋–จ์–ด์ง„ ์œ„์น˜์— ๋ฐฐ์น˜ํ•˜๋Š” ๊ธฐ์ˆ ์ž…๋‹ˆ๋‹ค. ์ด๋Š” ๋กœ๋ด‡์ด ์ง์ ‘ ์ ‘๊ทผํ•˜๊ธฐ ์–ด๋ ค์šด ๊ฑฐ๋ฆฌ๋ฅผ ๊ทน๋ณตํ•  ์ˆ˜ ์žˆ๋Š” ๋ฐฉ๋ฒ•์œผ๋กœ, ํŠนํžˆ ์›๊ฒฉ ์ƒ˜ํ”Œ ํš๋“ ๋ฐ ๋ฐ˜ํ™˜, ๊ตฌ์กฐ ๋“ฑ ๋‹ค์–‘ํ•œ ์‘์šฉ ๋ถ„์•ผ์—์„œ ํ™œ์šฉ ๊ฐ€๋Šฅํ•ฉ๋‹ˆ๋‹ค.

Computer Science Robotics
Distributed Collision-free Protocol for AGVs in Industrial Environments

Distributed Collision-free Protocol for AGVs in Industrial Environments

: ๋ณธ ๋…ผ๋ฌธ์€ ์‚ฐ์—… ํ™˜๊ฒฝ์—์„œ ์ž์œจ ์ด๋™ ์ฐจ๋Ÿ‰(AGVs) ๊ทธ๋ฃน์˜ ์•ˆ์ „ํ•˜๊ณ  ํšจ์œจ์ ์ธ ๊ด€๋ฆฌ๋ฅผ ์œ„ํ•œ ๋ถ„์‚ฐ ์ถฉ๋Œ ๋ฐฉ์ง€ ํ”„๋กœํ† ์ฝœ์„ ์ œ์•ˆํ•œ๋‹ค. ์ด๋Š” ๋™์  ํ™˜๊ฒฝ์—์„œ AGVs๊ฐ€ ๋ฏธ๋ฆฌ ์ •์˜๋œ ๊ฒฝ๋กœ๋ฅผ ๋”ฐ๋ผ ์ด๋™ํ•˜๋ฉด์„œ ๋ฐœ์ƒํ•  ์ˆ˜ ์žˆ๋Š” ๋‹ค์–‘ํ•œ ๋ฌธ์ œ๋“ค์„ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ๊ณ ์•ˆ๋˜์—ˆ๋‹ค. 1. ๋ถ„์‚ฐ ์กฐ์ • ์•Œ๊ณ ๋ฆฌ์ฆ˜ ์ œ์•ˆ๋œ ๋ถ„์‚ฐ ์กฐ์ • ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ ๊ณต์œ  ์ž์› ํ”„๋กœํ† ์ฝœ๊ณผ ์žฌ๊ณ„ํš ์ „๋žต์„ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•œ๋‹ค. ์ด๋Š” AGVs๊ฐ€ ๋™์ผํ•œ ๊ฒฝ๋กœ๋ฅผ ๋”ฐ๋ผ ์ด๋™ํ•˜๊ฑฐ๋‚˜ ๊ต์ฐจํ•˜๋Š” ๊ฒฝ์šฐ์— ๋ฐœ์ƒํ•  ์ˆ˜ ์žˆ๋Š” ์ถฉ๋Œ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•œ ๊ฒƒ์ด๋‹ค. ๋˜ํ•œ, ๊ต์ฐฉ ์ƒํƒœ(์‹œ์Šคํ…œ์ด ์ •์ง€๋œ ์ƒํƒœ)์™€ ์‚ด๋ก(๋ชฉ์ ์ง€ ๋„๋‹ฌ

Robotics Computer Science
Distributed Consensus on Set-valued Information

Distributed Consensus on Set-valued Information

: ๋ณธ ๋…ผ๋ฌธ์€ ๋ถ„์‚ฐ ์—์ด์ „ํŠธ ์‹œ์Šคํ…œ์—์„œ ์ •๋ณด์˜ ์ˆ˜๋ ด์„ ์—ฐ๊ตฌํ•˜๋Š” ๋ฐ ์ดˆ์ ์„ ๋งž์ถ”๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ํŠนํžˆ, ์ด ์—ฐ๊ตฌ๋Š” ๊ธฐ์กด์— ์‹ค์ˆ˜๋กœ ํ‘œํ˜„๋˜๋˜ ์ •๋ณด๋ฅผ ์ง‘ํ•ฉ์œผ๋กœ ํ‘œํ˜„ํ•จ์œผ๋กœ์จ ์ƒˆ๋กœ์šด ๊ด€์ ๊ณผ ์ ‘๊ทผ ๋ฐฉ์‹์„ ์ œ์‹œํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ์ ‘๊ทผ์€ ๋ถ„์‚ฐ ์‹œ์Šคํ…œ ๋‚ด์—์„œ ์—์ด์ „ํŠธ๋“ค์ด ์–ด๋–ป๊ฒŒ ์ƒํ˜ธ ์ž‘์šฉํ•˜๋ฉฐ ์ •๋ณด๋ฅผ ๊ณต์œ ํ•˜๊ณ  ์ˆ˜๋ ดํ•˜๋Š”์ง€๋ฅผ ๋ณด๋‹ค ์ •๊ตํ•˜๊ฒŒ ์ดํ•ดํ•  ์ˆ˜ ์žˆ๊ฒŒ ํ•ฉ๋‹ˆ๋‹ค. ๋…ผ๋ฌธ์—์„œ๋Š” ์ง‘ํ•ฉ์˜ ๋™์—ญํ•™์„ ๋ถ€์šธ ๋งต ํด๋ž˜์Šค๋กœ ํ‘œํ˜„ํ•ฉ๋‹ˆ๋‹ค. ์ด๋Š” ์—ฐํ•ฉ, ๊ต์ง‘ํ•ฉ, ๊ทธ๋ฆฌ๊ณ  ๋ณด์™„์ด๋ผ๋Š” ์„ธ ๊ฐ€์ง€ ๊ธฐ๋ณธ์ ์ธ ์ง‘ํ•ฉ ์—ฐ์‚ฐ๋งŒ์œผ๋กœ ๊ตฌ์„ฑ๋ฉ๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ์ œํ•œ๋œ ์ง‘ํ•ฉ ์—ฐ์‚ฐ์€ ๋ณต์žก์„ฑ์„ ์ค„์ด๋ฉด์„œ๋„ ํ•ต์‹ฌ

Robotics Computer Science
Distributed Intrusion Detection for the Security of Societies of Robots

Distributed Intrusion Detection for the Security of Societies of Robots

๋ณธ ๋…ผ๋ฌธ์€ ์ž์œจ ๋กœ๋ด‡ ์ง‘๋‹จ ๋‚ด์—์„œ ์ž ์žฌ์  ์นจ์ž…์ž๋ฅผ ๊ฐ์ง€ํ•˜๋Š” ๋ฌธ์ œ๋ฅผ ๋‹ค๋ฃจ๋ฉฐ, ์ด๋Š” ๋ถ„์‚ฐ ํ™˜๊ฒฝ์—์„œ์˜ ๋ณด์•ˆ ๋ฌธ์ œ ํ•ด๊ฒฐ์„ ์œ„ํ•œ ์ค‘์š”ํ•œ ์—ฐ๊ตฌ์ž…๋‹ˆ๋‹ค. ์ฃผ์š” ๋‚ด์šฉ๊ณผ ๊ทธ ์ค‘์š”์„ฑ์„ ๋‹ค์Œ๊ณผ ๊ฐ™์ด ๋ถ„์„ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. 1. ์นจ์ž…์ž ์ •์˜์™€ ๊ฐ์ง€ ๋ฐฉ๋ฒ• ๋…ผ๋ฌธ์€ ์นจ์ž…์ž๋ฅผ ์ž์œจ์ ์œผ๋กœ ํ–‰๋™ํ•˜์ง€ ์•Š๋Š” ๋กœ๋ด‡์œผ๋กœ ์ •์˜ํ•˜๋ฉฐ, ์ด๋Š” ๊ณ ์žฅ์ด๋‚˜ ์•…์˜์ ์ธ ์žฌํ”„๋กœ๊ทธ๋ž˜๋ฐ ๋“ฑ ๋‹ค์–‘ํ•œ ์›์ธ์— ์˜ํ•ด ๋ฐœ์ƒํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ๊ฐœ๋ณ„ ๋กœ๋ด‡์ด ์ž์‹ ์˜ ์ƒํƒœ์™€ ์ธ์ ‘ํ•œ ์ด์›ƒ๊ณผ์˜ ํ†ต์‹ ์„ ํ†ตํ•ด ์ •๋ณด๋ฅผ ์ˆ˜์ง‘ํ•˜๊ณ  ์ด๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ์นจ์ž…์ž๋ฅผ ๊ฐ์ง€ํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์ œ์•ˆํ•ฉ๋‹ˆ๋‹ค. 2. ๋ถ„์‚ฐ ํ™˜๊ฒฝ

Detection Robotics Computer Science
Logical Consensus for Distributed and Robust Intrusion Detection

Logical Consensus for Distributed and Robust Intrusion Detection

๋ณธ ๋…ผ๋ฌธ์€ ๋„คํŠธ์›Œํฌ ๋‚ด์—์„œ ์—์ด์ „ํŠธ๋“ค์ด ์ง€์—ญ์ ์œผ๋กœ ์ˆ˜์ง‘ํ•œ ์ •๋ณด๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ์ „๋ฐ˜์ ์ธ ์œ„ํ˜‘์— ๋Œ€ํ•œ ํ•ฉ์˜๋ฅผ ๋„์ถœํ•˜๋Š” ์ƒˆ๋กœ์šด ๋ฐฉ๋ฒ•์„ ์ œ์•ˆํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์ด๋Š” ํŠนํžˆ ๋ถ„์‚ฐ ํ™˜๊ฒฝ์—์„œ ๊ฐ ๋…ธ๋“œ๊ฐ€ ๋…๋ฆฝ์ ์œผ๋กœ ํŒ๋‹จํ•  ์ˆ˜ ์žˆ๋Š” ๋Šฅ๋ ฅ์„ ๊ฐ•ํ™”ํ•จ์œผ๋กœ์จ, ๋„คํŠธ์›Œํฌ ์ „์ฒด์˜ ์•ˆ์ •์„ฑ๊ณผ ๋ณด์•ˆ์„ฑ์„ ํ–ฅ์ƒ์‹œํ‚ค๋Š”๋ฐ ์ค‘์ ์„ ๋‘๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ๋…ผ๋ฌธ์€ ๋…ผ๋ฆฌ์  ํ•ฉ์˜ ๋ฌธ์ œ๋ฅผ ์ •์˜ํ•˜๊ณ , ์ด๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•œ ๊ธฐ์กด ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋“ค์„ ๊ฒ€ํ† ํ•ฉ๋‹ˆ๋‹ค. ํŠนํžˆ ์„ธํฌ ์ž๋™์ฒด์™€ ์œ ํ•œ ์ƒํƒœ ์ดํ„ฐ๋ ˆ์ด์…˜ ๋งต์˜ ์ˆ˜๋ ด์„ฑ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋Š” ์—์ด์ „ํŠธ๋“ค์ด ์ง€์—ญ์ ์œผ๋กœ ์ˆ˜์ง‘ํ•œ ์ •๋ณด๋ฅผ ์ „๋ฐ˜์ ์ธ ํ•ฉ์˜๋กœ ์—ฐ๊ฒฐํ•˜๋Š” ๋ฐ ์ค‘์š”ํ•œ ์—ญํ• ์„

Detection Robotics Computer Science
A Thomason-like Quillen equivalence between quasi-categories and   relative categories

A Thomason-like Quillen equivalence between quasi-categories and relative categories

: ๋ณธ ๋…ผ๋ฌธ์€ ๊ณ ๊ธ‰ ์ˆ˜ํ•™์  ๊ฐœ๋…์„ ๋ฐ”ํƒ•์œผ๋กœ ์‹œํ”Œ๋ฆฌ์–ผ ์ง‘ํ•ฉ(quasi categories)๊ณผ ์ƒ๋Œ€ ๋ฒ”์ฃผ(relative categories) ๊ฐ„์˜ ๊ด€๊ณ„๋ฅผ ํƒ๊ตฌํ•˜๊ณ  ์žˆ๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ํŠนํžˆ ์กฐ์•Œ ๋™ํ˜•์„ฑ(Quillen equivalence)์ด๋ผ๋Š” ์ค‘์š”ํ•œ ๋„๊ตฌ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ๋‘ ๋ฒ”์ฃผ์˜ ๊ตฌ์กฐ์™€ ๊ทธ ์‚ฌ์ด์˜ ๊ด€๊ณ„๋ฅผ ๋ถ„์„ํ•œ๋‹ค. 1. ์กฐ์•Œ ๋™ํ˜•์„ฑ๊ณผ ํ†ฐ์Šจ ๋™ํ˜•์„ฑ ์กฐ์•Œ ๋™ํ˜•์„ฑ์€ ๋‘ ๋ชจ๋ธ ๋ฒ”์ฃผ(model categories) ๊ฐ„์— ์กด์žฌํ•˜๋Š” ํŠน์ • ์ข…๋ฅ˜์˜ ๋™์น˜๊ด€๊ณ„์ด๋‹ค. ์ด๋Š” ๋‘ ๋ฒ”์ฃผ์˜ ๊ตฌ์กฐ์™€ ๊ทธ ์‚ฌ์ด์˜ ๊ด€๊ณ„๋ฅผ ์ดํ•ดํ•˜๋Š”๋ฐ ์ค‘์š”ํ•œ ๋„๊ตฌ๋กœ ์‚ฌ์šฉ๋œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์กฐ

Mathematics
Personalized Event-Based Surveillance and Alerting Support for the   Assessment of Risk

Personalized Event-Based Surveillance and Alerting Support for the Assessment of Risk

์ด ๋…ผ๋ฌธ์€ ๊ณต๊ณต ๋ณด๊ฑด ๋ถ„์•ผ์—์„œ ์ค‘์š”ํ•œ ๋ฌธ์ œ์ธ ๊ณผ๋ถ€ํ•˜๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•œ ์ด๋ฒคํŠธ ๊ธฐ๋ฐ˜ ๊ฐ์‹œ ์‹œ์Šคํ…œ์˜ ๊ฐœ์„  ๋ฐฉ์•ˆ์„ ์ œ์‹œํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ํŠนํžˆ, ์ „์—ผ๋ณ‘ ๋ชจ๋‹ˆํ„ฐ๋ง๊ณผ ๊ด€๋ จ๋œ ์ •๋ณด๊ฐ€ ๊ธ‰์ฆํ•จ์— ๋”ฐ๋ผ ์ด๋ฅผ ํšจ๊ณผ์ ์œผ๋กœ ๊ด€๋ฆฌํ•˜๋Š” ๊ฒƒ์ด ์ ์  ๋” ์ค‘์š”ํ•ด์ง€๊ณ  ์žˆ๋Š” ์ƒํ™ฉ์—์„œ, ๊ณต๋ฌด์›๋“ค์ด ํ•„์š”ํ•œ ์ •๋ณด๋ฅผ ๋น ๋ฅด๊ณ  ์ •ํ™•ํ•˜๊ฒŒ ํŒŒ์•…ํ•  ์ˆ˜ ์žˆ๋„๋ก ๋•๋Š” ๋ฐฉ๋ฒ•์„ ์ œ์•ˆํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ๋…ผ๋ฌธ์€ ๋‘ ๊ฐ€์ง€ ์ฃผ์š” ๊ธฐ๋ฒ•์„ ์†Œ๊ฐœํ•ฉ๋‹ˆ๋‹ค. ์ฒซ ๋ฒˆ์งธ๋กœ, ์‚ฌ์šฉ์ž์˜ ์„ ํ˜ธ๋„์— ๋”ฐ๋ผ ์‹ ํ˜ธ๋ฅผ ํ•„ํ„ฐ๋งํ•˜๋Š” ๋ฐฉ๋ฒ•์ž…๋‹ˆ๋‹ค. ์ด๋Š” ๊ณต๋ฌด์›๋“ค์ด ํ•„์š”ํ•˜์ง€ ์•Š์€ ์ •๋ณด๋‚˜ ๋…ธ์ด์ฆˆ๋กœ๋ถ€ํ„ฐ ํ•ด๋ฐฉ๋˜์–ด ์ค‘์š”ํ•œ ๊ฒฝ๋ณด์™€ ๋ณด๊ณ ์„œ์— ์ง‘์ค‘ํ•  ์ˆ˜

Computers and Society Computer Science

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