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Lumpability Abstractions of Rule-based Systems

Lumpability Abstractions of Rule-based Systems

๋ณธ ์—ฐ๊ตฌ๋Š” ๊ทœ์น™ ๊ธฐ๋ฐ˜(ruleโ€‘based) ํ˜น์€ ์—์ด์ „ํŠธ ๊ธฐ๋ฐ˜(agentโ€‘based) ๋ชจ๋ธ๋ง์ด ์ „ํ†ต์ ์ธ ํ™”ํ•™ ๋™์—ญํ•™์˜ ํ•œ๊ณ„๋ฅผ ์–ด๋–ป๊ฒŒ ๊ทน๋ณตํ•  ์ˆ˜ ์žˆ๋Š”์ง€๋ฅผ ์ฒด๊ณ„์ ์œผ๋กœ ํƒ๊ตฌํ•œ๋‹ค. ๋จผ์ €, ์ƒ์ฒด๋ถ„์ž ๋ฐ˜์‘ ์‹œ์Šคํ…œ์—์„œ ๋ฐœ์ƒํ•˜๋Š” ์กฐํ•ฉ์  ํญ๋ฐœ(combinatorial explosion)์„ ์ง€์ ํ•˜๊ณ , ์ด๋ฅผ ์™„์ „ํ•˜๊ฒŒ ์—ด๊ฑฐํ•˜๋Š” ๊ฒƒ์ด ์‹คํ—˜์ ์œผ๋กœ๋„ ์ด๋ก ์ ์œผ๋กœ๋„ ๋ถˆ๊ฐ€๋Šฅํ•จ์„ ๊ฐ•์กฐํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ์ƒํ™ฉ์—์„œ โ€œ๊ทœ์น™โ€์€ ํŠน์ • ๋งฅ๋ฝ์—๋งŒ ์˜์กดํ•˜๋Š” ์ œํ•œ๋œ ์‚ฌ๊ฑด์„ ๊ธฐ์ˆ ํ•จ์œผ๋กœ์จ, ์™„์ „ํžˆ ์ •์˜๋˜์ง€ ์•Š์€ ๋ถ„์ž ์ข…์— ๋Œ€ํ•ด์„œ๋„ ์ ์šฉ ๊ฐ€๋Šฅํ•˜๊ฒŒ ๋งŒ๋“ ๋‹ค. ๋…ผ๋ฌธ์€ ๊ธฐ์กด์˜ ํ”„๋ž˜๊ทธ๋จผํŠธ(fragm

Computer Science Computational Engineering System
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Machine Learning and Public Health: Identifying and Mitigating Algorithmic Bias through a Systematic Review

๊ธฐ๊ณ„ ํ•™์Šต์€ ๊ณต๊ณต ๋ณด๊ฑด ๋ถ„์•ผ์—์„œ ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•  ์ˆ˜ ์žˆ์ง€๋งŒ, ํŽธํ–ฅ๋œ ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด ๊ธฐ์กด ๋ถˆํ‰๋“ฑ์„ ์•…ํ™”์‹œํ‚ฌ ์œ„ํ—˜๋„ ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ฒด๊ณ„์ ์ธ ๋ฌธํ—Œ ๊ณ ์ฐฐ์„ ํ†ตํ•ด ๋„ค๋œ๋ž€๋“œ์˜ ๊ณต๊ณต ๋ณด๊ฑด ๊ธฐ๊ณ„ ํ•™์Šต ์—ฐ๊ตฌ์—์„œ ์•Œ๊ณ ๋ฆฌ์ฆ˜ ํŽธํ–ฅ์— ๋Œ€ํ•œ ๋…ผ์˜์™€ ๋ณด๊ณ ๊ฐ€ ์–ด๋–ป๊ฒŒ ์ด๋ฃจ์–ด์ง€๊ณ  ์žˆ๋Š”์ง€ ๋ถ„์„ํ•˜์˜€๋‹ค. ๊ทธ ๊ฒฐ๊ณผ, ๋ฐ์ดํ„ฐ ์ƒ˜ํ”Œ๋ง๊ณผ ๋ˆ„๋ฝ ๋ฐ์ดํ„ฐ ๊ด€ํ–‰์€ ์ž˜ ๋ฌธ์„œํ™”๋˜์–ด ์žˆ์ง€๋งŒ, ๊ณต์ •์„ฑ ํ‹€, ํ•˜์œ„ ๊ทธ๋ฃน ๋ถ„์„ ๋ฐ ์ž ์žฌ์  ํ”ผํ•ด์— ๋Œ€ํ•œ ๋…ผ์˜๋Š” ๋ถ€์กฑํ•œ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ด๋Ÿฌํ•œ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ACAR ํ”„๋ ˆ์ž„์›Œํฌ๋ฅผ ์ œ์•ˆํ•œ๋‹ค. ์ด ํ”„๋ ˆ์ž„์›Œํฌ๋Š” ๊ธฐ๊ณ„ ํ•™์Šต ๋ผ์ดํ”„์‚ฌ

System Learning
Magneto-elastic torsional oscillations of magnetars

Magneto-elastic torsional oscillations of magnetars

๋ณธ ์—ฐ๊ตฌ๋Š” ๋งˆ๊ทธ๋„คํ„ฐ ๋‚ด๋ถ€์—์„œ ๋ฐœ์ƒํ•˜๋Š” ๋ณตํ•ฉ์ ์ธ ์ง„๋™ ํ˜„์ƒ์„ ์ตœ์ดˆ๋กœ ์ „์ ์œผ๋กœ ์ผ๋ฐ˜ ์ƒ๋Œ€๋ก ์  ํ‹€ ์•ˆ์—์„œ ๋ชจ์‚ฌํ•œ ์ ์—์„œ ํฐ ์˜๋ฏธ๋ฅผ ๊ฐ€์ง„๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ๋“ค์€ (1) ์ˆœ์ˆ˜ํ•œ ๊ป์งˆ ์ „๋‹จ ๋ชจ๋“œ๋งŒ์„ ๊ณ ๋ คํ•˜๊ฑฐ๋‚˜, (2) ๊ป์งˆ ์—†์ด ์ˆœ์ˆ˜ ์•Œ๋ ˆ๋ธ ํŒŒ๋™๋งŒ์„ ๋‹ค๋ฃจ๋Š” ๋‘ ๊ฐˆ๋ž˜์˜ ์ ‘๊ทผ๋ฒ•์— ๋จธ๋ฌผ๋ €๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์‹ค์ œ SGR(softโ€‘gamma repeater)์—์„œ ๊ด€์ธก๋˜๋Š” QPO๋Š” (10^{15}) G ์ˆ˜์ค€์˜ ์ดˆ๊ฐ•๋ ฅ ์ž๊ธฐ์žฅ์ด ์กด์žฌํ•จ์„ ๊ฐ์•ˆํ•  ๋•Œ, ๊ป์งˆ๊ณผ ์ฝ”์–ด๊ฐ€ ๋™์‹œ์— ์ฐธ์—ฌํ•˜๋Š” ์ž๊ธฐโ€‘ํƒ„์„ฑ ๊ฒฐํ•ฉ ๋ชจ๋“œ๊ฐ€ ํ•„์ˆ˜์ ์ด๋‹ค. ๋ฐฉ๋ฒ•๋ก  ์ €์ž๋“ค์€ 2์ฐจ์› ์ผ๋ฐ˜ ์ƒ๋Œ€๋ก ์  ์ด์ƒ์ ์ธ MH

Astrophysics General Relativity
Management of quality requirements in agile and rapid software   development: A systematic mapping study

Management of quality requirements in agile and rapid software development: A systematic mapping study

์†Œํ”„ํŠธ์›จ์–ด ํ’ˆ์งˆ๊ณผ ์š”๊ตฌ ์‚ฌํ•ญ ๊ด€๋ฆฌ ์†Œํ”„ํŠธ์›จ์–ด ์‹œ์Šคํ…œ์˜ ํ’ˆ์งˆ์€ ๊ธฐ์ˆ  ํ˜์‹  ์‹œ๋Œ€์— ํ•„์ˆ˜์ ์ธ ์š”์†Œ๋กœ ์ž๋ฆฌ ์žก์•˜๋‹ค. ๊ธฐ์—…๋“ค์€ IT ์˜ˆ์‚ฐ ์ค‘ ์ƒ๋‹น ๋ถ€๋ถ„์„ ์†Œํ”„ํŠธ์›จ์–ด ํ’ˆ์งˆ ๋ณด์ฆ ๋ฐ ํ…Œ์ŠคํŠธ์— ํ• ๋‹นํ•˜๊ณ  ์žˆ์œผ๋ฉฐ, ์ด๋Š” ํ–ฅํ›„ ๋”์šฑ ์ฆ๊ฐ€ํ•  ๊ฒƒ์œผ๋กœ ์˜ˆ์ธก๋œ๋‹ค. ์ด๋Ÿฌํ•œ ์ถ”์„ธ๋Š” ๊ณ ํ’ˆ์งˆ์˜ ์†Œํ”„ํŠธ์›จ์–ด ์‹œ์Šคํ…œ์— ๋Œ€ํ•œ ์ˆ˜์š”๋ฅผ ๋ฐ˜์˜ํ•œ๋‹ค. ํ’ˆ์งˆ ์š”๊ตฌ ์‚ฌํ•ญ(QR)์€ ์†Œํ”„ํŠธ์›จ์–ด์˜ ์›ํ•˜๋Š” ํ’ˆ์งˆ์„ ์ •์˜ํ•˜๋ฉฐ, ์œ ์ง€๋ณด์ˆ˜์„ฑ, ์‹ ๋ขฐ์„ฑ, ๊ฐ€์šฉ์„ฑ, ์‚ฌ์šฉ์„ฑ, ๋ฌด๊ฒฐ์„ฑ๊ณผ ๊ฐ™์€ ํŠน์„ฑ์„ ํฌํ•จํ•œ๋‹ค. QR์€ ๊ธฐ๋Šฅ์  ์š”๊ตฌ ์‚ฌํ•ญ๊ณผ ์œ ์‚ฌํ•˜์ง€๋งŒ, ๊ทธ ์˜๋ฏธ์™€ ํ‘œํ˜„ ๋ฐฉ๋ฒ•์—์„œ ๋…ํŠนํ•œ ์ธก๋ฉด์„ ๊ฐ€์ง„๋‹ค. ๋”ฐ๋ผ์„œ QR

Software Engineering Computer Science System
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Mapped Exponent and Asymptotic Critical Exponent of Words

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋ฌธ์ œ ์ •์˜ ๋ฐ˜๋ณต์„ฑ(์žฌํ˜„์„ฑ) ์€ ์กฐํ•ฉ๋ก ์  ๋‹จ์–ด ์ด๋ก ์—์„œ ํ•ต์‹ฌ์ ์ธ ๊ฐœ๋…์ด๋ฉฐ, ํŠนํžˆ ์ง€์ˆ˜(exponent) ์™€ ์ž„๊ณ„ ์ง€์ˆ˜(critical exponent) ๋Š” ๋‹จ์–ด๊ฐ€ ์–ผ๋งˆ๋‚˜ โ€œ๋ฐ˜๋ณตโ€๋˜๋Š”์ง€๋ฅผ ์ •๋Ÿ‰ํ™”ํ•œ๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ๋Š” ์ฃผ๋กœ ๋™ํ˜• ์‚ฌ์ƒ(automorphisms) ํ˜น์€ ๋™ํ˜• ์‚ฌ์ƒ๊ตฐ ์— ์˜ํ•œ ์ง€์ˆ˜ ๋ณด์กด์„ฑ์„ ๋‹ค๋ฃจ์—ˆ์œผ๋‚˜, ์ „๋‹จ์‚ฌ(injective) ์‚ฌ์ƒ ์ด ๋ฐ˜๋ณต์„ฑ์„ ์–ด๋–ป๊ฒŒ ๋ณ€ํ˜•์‹œํ‚ค๋Š”์ง€๋Š” ์ถฉ๋ถ„ํžˆ ํƒ๊ตฌ๋˜์ง€ ์•Š์•˜๋‹ค. ์ด ๋…ผ๋ฌธ์€ โ€œ์ „๋‹จ์‚ฌ ์‚ฌ์ƒ์ด ๋‹จ์–ด์˜ ๋ฐ˜๋ณต์„ฑ์„ ์–ผ๋งˆ๋‚˜ ์ฆํญ์‹œํ‚ฌ ์ˆ˜ ์žˆ๋Š”๊ฐ€?โ€๋ผ๋Š” ์งˆ๋ฌธ์„ ๋‘ ๊ฐ€์ง€ ๊ด€์ (์œ ํ•œยท๋ฌดํ•œ)์—์„œ ์ฒด๊ณ„์ 

Mathematical link of evolving aging and complexity

Mathematical link of evolving aging and complexity

๋ณธ ๋…ผ๋ฌธ์€ ๋…ธํ™” ํ˜„์ƒ์„ โ€˜๋ณต์žก์„ฑ์˜ ์ ์ง„์  ๊ฐ์†Œโ€™๋ผ๋Š” ๊ฐœ๋…์  ํ‹€์— ๋†“๊ณ , ์ด๋ฅผ ์ •๋Ÿ‰ํ™”ํ•  ์ˆ˜ ์žˆ๋Š” ์ƒˆ๋กœ์šด ์ˆ˜ํ•™์  ๋ชจ๋ธ์„ ์ œ์‹œํ•œ๋‹ค๋Š” ์ ์—์„œ ํ•™์ œ๊ฐ„ ์—ฐ๊ตฌ์˜ ์ข‹์€ ์‚ฌ๋ก€๋ผ ํ•  ์ˆ˜ ์žˆ๋‹ค. ๊ธฐ์กด์˜ Gompertz ๋ฒ•์น™์ด๋‚˜ Weibull, Heligmanโ€‘Pollard ๋“ฑ์€ ๊ณ ๋ น์ธต์—์„œ ๊ด€์ธก๋˜๋Š” ์‚ฌ๋ง๋ฅ  ํŽธ์ฐจ๋ฅผ ์ถฉ๋ถ„ํžˆ ์„ค๋ช…ํ•˜์ง€ ๋ชปํ•œ๋‹ค๋Š” ํ•œ๊ณ„๊ฐ€ ์žˆ์—ˆ์œผ๋ฉฐ, ์ด๋Š” ๋ณต์žก๊ณ„ ์ด๋ก ๊ณผ์˜ ์—ฐ๊ฒฐ ๊ณ ๋ฆฌ๊ฐ€ ๋ถ€์กฑํ–ˆ๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ์ €์ž๋“ค์€ ๋ฌผ๋ฆฌํ•™์—์„œ ๋„๋ฆฌ ์‚ฌ์šฉ๋˜๋Š” ํ™•์žฅ ์ง€์ˆ˜ ํ•จ์ˆ˜(KWW ํ•จ์ˆ˜) ๋ฅผ ์ƒ์กด ๊ณก์„ ์— ์ ์šฉํ•จ์œผ๋กœ์จ, โ€˜์‹œ๊ฐ„(์—ฐ๋ น)โ€™์„ ๋ฌด์ฐจ์› ๋ณ€์ˆ˜ (u x/alpha

Physics Quantitative Biology
Matrix Completion from Noisy Entries

Matrix Completion from Noisy Entries

๋ณธ ๋…ผ๋ฌธ์€ ํ–‰๋ ฌ ์™„์„ฑ ๋ฌธ์ œ๋ฅผ ๋‘ ๊ฐ€์ง€ ๊ด€์ ์—์„œ ์ฒด๊ณ„์ ์œผ๋กœ ์กฐ๋ช…ํ•œ๋‹ค. ์ฒซ ๋ฒˆ์งธ๋Š” ์ƒ˜ํ”Œ ๋ณต์žก๋„ ์™€ ๋ณต์› ์ •ํ™•๋„ ์‚ฌ์ด์˜ ๊ทผ๋ณธ์ ์ธ ํ•œ๊ณ„๋ฅผ ๊ทœ๋ช…ํ•˜๋Š” ๊ฒƒ์ด๋ฉฐ, ๋‘ ๋ฒˆ์งธ๋Š” ์‹ค์ œ ๋ฐ์ดํ„ฐ์— ์กด์žฌํ•˜๋Š” ์žก์Œ๊ณผ ๊ทผ์‚ฌ ๋žญํฌ ๊ตฌ์กฐ์— ๋Œ€ํ•œ ๊ฐ•์ธ์„ฑ ์„ ํ™•๋ณดํ•˜๋Š” ๊ฒƒ์ด๋‹ค. 1. ๋ฐฐ๊ฒฝ ๋ฐ ๊ธฐ์กด ์—ฐ๊ตฌ ํ–‰๋ ฌ (M) ์˜ ๊ฐ€์žฅ ํฐ ํŠน์ด๊ฐ’๊ณผ ํŠน์ด๋ฒกํ„ฐ๋Š” ๋ฐ์ดํ„ฐ์˜ ํ•ต์‹ฌ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ๋‚˜ํƒ€๋‚ด๋ฉฐ, ์ด๋ฅผ ์ด์šฉํ•œ ์ŠคํŽ™ํŠธ๋Ÿผ ๊ธฐ๋ฒ•์€ ๋จธ์‹ ๋Ÿฌ๋‹ยทํ†ต๊ณ„ยท์‹ ํ˜ธ์ฒ˜๋ฆฌ ์ „๋ฐ˜์— ๊ฑธ์ณ ๊ธฐ๋ณธ ๋„๊ตฌ๋กœ ์ž๋ฆฌ ์žก์•˜๋‹ค. CandรจsยทRecht(2008)์™€ CandรจsยทTao(2009)๋Š” ๋ณผ๋ก ์™„ํ™”(convex re

Computer Science Statistics Machine Learning
Maxwells Demon and its Fallacies Demystified

Maxwells Demon and its Fallacies Demystified

: ๋งฅ์Šค์›ฐ์˜ ์•…๋งˆ๋Š” ์ œ์ž„์Šค ํด๋Ÿฌํฌ ๋งฅ์Šค์›ฐ์ด ์ œ์•ˆํ•œ ๊ฐœ๋…์œผ๋กœ, ๊ฐ€์Šค์˜ ๊ท ํ˜• ์ƒํƒœ์—์„œ ์—ด ๋ถ„์ž๋ฅผ ์„ ํƒ์ ์œผ๋กœ ๋ถ„๋ฅ˜ํ•˜์—ฌ ์—ด์—ญํ•™ ์ œ2๋ฒ•์น™์„ ์œ„๋ฐ˜ํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ์•„์ด๋””์–ด๋ฅผ ์ œ์‹œํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด ์•…๋งˆ๋Š” ๊ณผํ•™์  ์‚ฌ๊ณ ์™€ ์ฐฝ์˜์„ฑ์„ ์ž๊ทนํ•˜๋Š” ํฅ๋ฏธ๋กœ์šด ์ฃผ์ œ์ด์ง€๋งŒ, ๋™์‹œ์— ๋งŽ์€ ์˜คํ•ด์™€ ๋ชจ์ˆœ๋œ ์ฃผ์žฅ์ด ์กด์žฌํ•ฉ๋‹ˆ๋‹ค. ๋งฅ์Šค์›ฐ๊ณผ ๊ทธ์˜ ์ถ”์ข…์ž๋“ค์€ ์•…๋งˆ์˜ ์ž‘๋™์— ์ง‘์ค‘ํ•˜์—ฌ ๋ถ„์ž ๋‹จ์œ„์˜ ๊ฒŒ์ดํŠธ๋ฅผ ํ†ต๊ณผ์‹œํ‚ค๋Š” ๊ณผ์ •์— ์ฃผ๋ชฉํ–ˆ์Šต๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ๊ทธ๋“ค์€ ๋ฌด์งˆ์„œํ•œ ๋ถ„์ž๋“ค์˜ ๋™์‹œ ๊ฐ„์„ญ์„ ๊ฐ„๊ณผํ–ˆ์œผ๋ฉฐ, ์ด๋Š” ์—ด์—ญํ•™ ์ œ2๋ฒ•์น™์˜ ํ•ต์‹ฌ์ ์ธ ์š”์†Œ์ž…๋‹ˆ๋‹ค. ๋ฐ˜๋ฉด, ์•…๋งˆ๋ฅผ ํ‡ด์น˜ํ•˜๋ ค๋Š” ์‚ฌ๋žŒ๋“ค์€ ์ธก์ •, ์ •๋ณด ์ €

Physics Condensed Matter
No Image

Mean-Variance Optimization and Algorithm for Finite-Horizon Markov Decision Processes

: ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ํ‰๊ท ๊ณผ ๋ถ„์‚ฐ์„ ๊ฒฐํ•ฉํ•œ ์ง€ํ‘œ๋ฅผ ์ตœ๋Œ€ํ™”ํ•˜๋Š” ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด, ๊ฐ€์งœ ํ‰๊ท ๊ณผ ๊ฐ€์งœ ๋ถ„์‚ฐ ๊ฐœ๋…์„ ๋„์ž…ํ•˜์—ฌ MDP๋ฅผ ๋ฐ”์ด๋ ˆ๋ฒจ ๊ตฌ์กฐ๋กœ ๋ณ€ํ™˜ํ•ฉ๋‹ˆ๋‹ค. ์ด ์ ‘๊ทผ ๋ฐฉ์‹์€ ์—ญ์‚ฌ ์˜์กดํ˜• ๊ฒฐ์ •๋ก ์  ์ •์ฑ…์˜ ์ตœ์ ์„ฑ๊ณผ ๋‚ด๋ถ€์˜ MDP ์ตœ์ ๊ฐ’์ด ๊ฐ€์งœ ํ‰๊ท ์— ๋Œ€ํ•ด ์กฐ๊ฐ๋ณ„ ์ด์ฐจ ํ•จ์ˆ˜์˜ ์˜ค๋ชฉ์„ฑ์ด๋ผ๋Š” ํŠน์„ฑ์„ ํ™œ์šฉํ•ฉ๋‹ˆ๋‹ค. ๋˜ํ•œ, ๋ฐ˜๋ณต ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์•ˆํ•˜์—ฌ ํšจ์œจ์ ์œผ๋กœ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๋ฉฐ, ์ˆ˜๋ ด์„ฑ๊ณผ ์ „์—ญ ์ตœ์ ์— ๋„๋‹ฌํ•˜๋Š” ์กฐ๊ฑด์„ ์ œ์‹œํ•ฉ๋‹ˆ๋‹ค. ๋‹ค๊ธฐ๊ฐ„ ํฌํŠธํด๋ฆฌ์˜ค ์„ ํƒ ๋ฌธ์ œ์™€ ๊ฐ™์€ ์‹ค์ œ ์‚ฌ๋ก€๋ฅผ ํ†ตํ•ด ๋ณธ ์—ฐ๊ตฌ์˜ ์ ์šฉ ๊ฐ€๋Šฅ์„ฑ์„ ์ž…์ฆํ•˜๊ณ , ๊ธˆ์œต ๊ณตํ•™์—์„œ ๊ณ ์ „์ ์ธ ๊ฒฐ๊ณผ์™€ ์ผ

Measure and integral with purely ordinal scales

Measure and integral with purely ordinal scales

์ด ๋…ผ๋ฌธ์€ โ€œ์ˆ˜์น˜๊ฐ€ ์•„๋‹ˆ๋ผ ์ˆœ์„œ๋งŒ์œผ๋กœ ์ธก์ •ยทํ†ตํ•ฉ์„ ํ•  ์ˆ˜ ์žˆ๋Š”๊ฐ€?โ€๋ผ๋Š” ๊ทผ๋ณธ์ ์ธ ์งˆ๋ฌธ์— ๋Œ€ํ•œ ์ฒด๊ณ„์ ์ธ ๋‹ต์„ ์ œ์‹œํ•œ๋‹ค๋Š” ์ ์—์„œ ํ•™์ˆ ์  ์˜์˜๊ฐ€ ํฌ๋‹ค. ์ „ํ†ต์ ์ธ ์ธก์ • ์ด๋ก ์€ ์‹ค์ˆ˜์ฒด๊ณ„ (mathbb{R}) ์˜ ๋Œ€์ˆ˜ ๊ตฌ์กฐ์™€ ์ˆœ์„œ ๊ตฌ์กฐ๋ฅผ ๋™์‹œ์— ํ™œ์šฉํ•œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์‹ค์ œ ์˜์‚ฌ๊ฒฐ์ • ์ƒํ™ฉโ€”ํŠนํžˆ ์ธ๊ฐ„์˜ ์œ„ํ—˜ยท๋ถˆํ™•์‹ค์„ฑ ์ธ์ง€โ€”์—์„œ๋Š” ์ˆœ์„œ ์ •๋ณด๋งŒ์ด ์˜๋ฏธ๋ฅผ ๊ฐ–๋Š” ๊ฒฝ์šฐ๊ฐ€ ๋นˆ๋ฒˆํ•˜๋‹ค. ์ €์ž๋“ค์€ ์ด๋Ÿฌํ•œ ์ƒํ™ฉ์„ ๋ฐ˜์˜ํ•˜๊ธฐ ์œ„ํ•ด ์™„์ „ ์„ ํ˜• ๊ฒฉ์ž (M) ๋ฅผ ๊ธฐ๋ณธ ์ฒ™๋„๋กœ ์ฑ„ํƒํ•˜๊ณ , ํŠน๋ณ„ํžˆ ๋ฐ˜์‚ฌ ๊ฒฉ์ž (R) ๋ฅผ ๋„์ž…ํ•จ์œผ๋กœ์จ โ€˜์ฐธ์กฐ์  (O)โ€™(๋ณดํ†ต ํ˜„์ƒ ์œ ์ง€)

Computer Science Discrete Mathematics Mathematics
Measurement of the evolution of technology: A new perspective

Measurement of the evolution of technology: A new perspective

๋ณธ ๋…ผ๋ฌธ์€ ๊ธฐ์ˆ  ์ง„ํ™”๋ฅผ ์ธก์ •ํ•˜๊ธฐ ์œ„ํ•œ ์ƒˆ๋กœ์šด ์ด๋ก ์ ยท์‹ค์ฆ์  ํ‹€์„ ์ œ์‹œํ•œ๋‹ค๋Š” ์ ์—์„œ ํ•™์ˆ ์  ์˜์˜๊ฐ€ ํฌ๋‹ค. ์ฒซ ๋ฒˆ์งธ๋กœ, ์ €์ž๋Š” โ€˜๊ธฐ์ˆ  ๊ธฐ์ƒโ€™์ด๋ผ๋Š” ๊ฐœ๋…์„ ๋„์ž…ํ•ด ๊ธฐ์ˆ  ๊ฐ„ ์ƒํ˜ธ์ž‘์šฉ์„ ์ƒ๋ฌผํ•™์  ๊ธฐ์ƒ ๊ด€๊ณ„์— ๋น„์œ ํ•œ๋‹ค. ์ด๋Š” ๊ธฐ์กด์˜ ๊ธฐ์ˆ  ํ˜์‹  ์—ฐ๊ตฌ๊ฐ€ ์ฃผ๋กœ ๊ธฐ์ˆ  ์ž์ฒด์˜ ์„ฑ๋Šฅ ํ–ฅ์ƒ์ด๋‚˜ ์‹œ์žฅ ์ˆ˜์šฉ์— ์ดˆ์ ์„ ๋งž์ถ”๋˜ ๊ฒƒ๊ณผ ๋‹ฌ๋ฆฌ, ๊ธฐ์ˆ ์ด ๋‹ค๋ฅธ ๊ธฐ์ˆ ์— ์˜์กดํ•˜๊ฑฐ๋‚˜ ์˜ํ–ฅ์„ ๋ฐ›๋Š” ๊ตฌ์กฐ์  ๊ด€๊ณ„๋ฅผ ๊ฐ•์กฐํ•œ๋‹ค๋Š” ์ ์—์„œ ์ฐจ๋ณ„ํ™”๋œ๋‹ค. ํŠนํžˆ, ํ˜ธ์ŠคํŠธโ€‘ํŒŒ๋ผ์‚ฌ์ดํŠธ ๊ด€๊ณ„๋ฅผ ์ •๋Ÿ‰ํ™”ํ•˜๊ธฐ ์œ„ํ•ด โ€˜์ง„ํ™” ์„ฑ์žฅ ๊ณ„์ˆ˜(evolutionary growth coefficient)โ€™๋ผ๋Š” ์ง€ํ‘œ๋ฅผ

Quantitative Finance
menoci: Lightweight Extensible Web Portal enabling FAIR Data Management   for Biomedical Research Projects

menoci: Lightweight Extensible Web Portal enabling FAIR Data Management for Biomedical Research Projects

menoci ๋…ผ๋ฌธ์€ ํ˜„์žฌ ์ƒ๋ฌผ์˜ํ•™ ์—ฐ๊ตฌ ํ˜„์žฅ์—์„œ ๊ฐ€์žฅ ์‹œ๊ธ‰ํžˆ ์š”๊ตฌ๋˜๋Š” ๋ฐ์ดํ„ฐ ๊ด€๋ฆฌ ๋ฌธ์ œ๋ฅผ ์ฒด๊ณ„์ ์œผ๋กœ ์ง„๋‹จํ•˜๊ณ , ์‹ค์šฉ์ ์ธ ํ•ด๊ฒฐ์ฑ…์„ ์ œ์‹œํ•œ๋‹ค๋Š” ์ ์—์„œ ํ•™์ˆ ์ ยท์‹ค๋ฌด์  ๊ฐ€์น˜๋ฅผ ๋™์‹œ์— ์ง€๋‹Œ๋‹ค. ์ฒซ์งธ, ์š”๊ตฌ์‚ฌํ•ญ ์ •์˜ ๋‹จ๊ณ„๊ฐ€ ๋‘๋“œ๋Ÿฌ์ง„๋‹ค. ์ €์ž๋“ค์€ ๋…์ผ์—ฐ๊ตฌ์žฌ๋‹จ(DFG)์˜ โ€˜Good Scientific Practiceโ€™ ์ง€์นจ, FAIR ์›์น™, ๊ทธ๋ฆฌ๊ณ  ์ž๊ธˆ ์ง€์› ๊ธฐ๊ด€ยทํ•™์ˆ ์ง€ยท๋Œ€ํ•™ยทํ•ต์‹ฌ ์‹œ์„ค ๋“ฑ ๋‹ค์ค‘ ์ดํ•ด๊ด€๊ณ„์ž์˜ ์š”๊ตฌ๋ฅผ ์ข…ํ•ฉํ•ด โ€˜๊ธฐ๋Šฅ์  ์š”๊ตฌ(๋ฐ์ดํ„ฐ ์ˆ˜์ง‘ยท๋ฉ”ํƒ€๋ฐ์ดํ„ฐ ์ฃผ์„ยท์‹๋ณ„์ž ๋ถ€์—ฌยท๋ณด์กด)โ€™์™€ โ€˜ํ’ˆ์งˆ์  ์š”๊ตฌ(์‚ฌ์šฉ์„ฑยท๋ณด์•ˆยท์ง€์† ๊ฐ€๋Šฅ์„ฑยท์žฌ์‚ฌ์šฉ์„ฑ)โ€™๋ฅผ ๋ช…ํ™•ํžˆ

Data Computer Science Databases Digital Libraries
Mobile Based Secure Digital Wallet for Peer to Peer Payment System

Mobile Based Secure Digital Wallet for Peer to Peer Payment System

๋ณธ ๋…ผ๋ฌธ์€ ์ „ํ†ต์ ์ธ ์€ํ–‰ยทATM ๊ธฐ๋ฐ˜ ๊ฒฐ์ œ ์ธํ”„๋ผ๊ฐ€ ๋„คํŠธ์›Œํฌ ์žฅ์•  ์‹œ ์„œ๋น„์Šค ๋งˆ๋น„๋ฅผ ์ดˆ๋ž˜ํ•œ๋‹ค๋Š” ๋ฌธ์ œ์ ์„ ์ถœ๋ฐœ์ ์œผ๋กœ ์‚ผ์•„, ๋ชจ๋ฐ”์ผ ๊ธฐ๊ธฐ ๊ธฐ๋ฐ˜ ๋””์ง€ํ„ธ ์ง€๊ฐ‘ ์ด๋ผ๋Š” ์ƒˆ๋กœ์šด ํŒจ๋Ÿฌ๋‹ค์ž„์„ ์ œ์‹œํ•œ๋‹ค. ์ฃผ์š” ๊ธฐ์—ฌ๋Š” ์„ธ ๊ฐ€์ง€ ์ถ•์œผ๋กœ ์ •๋ฆฌํ•  ์ˆ˜ ์žˆ๋‹ค. 1. ๋ณด์•ˆ ์ธ์‹(Securityโ€‘aware) ์„ค๊ณ„ ๋””์ง€ํ„ธ ์ง€๊ฐ‘์€ ํด๋ผ์ด์–ธํŠธโ€‘์‚ฌ์ด๋“œ ์•”ํ˜ธํ™” ๋ฅผ ๊ธฐ๋ณธ์œผ๋กœ ํ•œ๋‹ค. ๊ฐœ์ธ ์‹๋ณ„ ์ •๋ณด(PII)์™€ ๊ฑฐ๋ž˜ ๋ฐ์ดํ„ฐ๋Š” ์ „์†ก ์ „ AESโ€‘256 ๋“ฑ ๊ฐ•๋ ฅํ•œ ๋Œ€์นญํ‚ค ์•”ํ˜ธํ™”์™€ RSA ๊ธฐ๋ฐ˜ ๊ณต๊ฐœํ‚ค ์„œ๋ช…์„ ํ†ตํ•ด ๋ฌด๊ฒฐ์„ฑ๊ณผ ๊ธฐ๋ฐ€์„ฑ์„ ํ™•๋ณดํ•œ๋‹ค. โ€˜Thin Walletโ€™๊ณผ ๋‹ฌ๋ฆฌ ์„œ๋ฒ„์— ๋ฏผ

Computer Science Computational Engineering System
Mobile Cloud Computing in Healthcare Using Dynamic Cloudlets for   Energy-Aware Consumption

Mobile Cloud Computing in Healthcare Using Dynamic Cloudlets for Energy-Aware Consumption

: ์˜๋ฃŒ ๋ถ„์•ผ์—์„œ MCC๋Š” ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•˜๊ณ  ์žˆ์ง€๋งŒ, ์—๋„ˆ์ง€ ์†Œ๋น„์™€ ๊ด€๋ จ๋œ ๋ฌธ์ œ๋Š” ํ•ด๊ฒฐํ•ด์•ผ ํ•  ๊ณผ์ œ์ž…๋‹ˆ๋‹ค. DEMCCM์€ ์ด๋Ÿฌํ•œ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ๋…ํŠนํ•œ ์ ‘๊ทผ๋ฒ•์„ ์ œ์‹œํ•ฉ๋‹ˆ๋‹ค. ๋™์  ํด๋ผ์šฐ๋“œ๋ฆฟ์„ ํ™œ์šฉํ•˜์—ฌ ๋„คํŠธ์›Œํฌ ํ™˜๊ฒฝ์˜ ๋ณ€ํ™”์— ์ ์‘ํ•˜๊ณ , ์ตœ์ ์˜ ํด๋ผ์šฐ๋“œ ์„œ๋ฒ„๋ฅผ ์„ ํƒํ•จ์œผ๋กœ์จ HCP ์žฅ์น˜์˜ ์—๋„ˆ์ง€ ํšจ์œจ์„ฑ์„ ํ–ฅ์ƒ์‹œํ‚ต๋‹ˆ๋‹ค. ์ด ๋ชจ๋ธ์˜ ํ•ต์‹ฌ์€ ๋™์  ํ”„๋กœ๊ทธ๋ž˜๋ฐ์„ ํ†ตํ•ด ์—๋„ˆ์ง€ ์†Œ๋น„๋ฅผ ์ตœ์†Œํ™”ํ•˜๋ฉด์„œ๋„ ์„œ๋น„์Šค ์„ฑ๋Šฅ์„ ์œ ์ง€ํ•˜๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค. ์ด๋Š” ๋ชจ๋ฐ”์ผ ์žฅ์น˜์™€ ํด๋ผ์šฐ๋“œ ์„œ๋ฒ„ ๊ฐ„์˜ ํ†ต์‹ ์—์„œ ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•ฉ๋‹ˆ๋‹ค. ํŠนํžˆ, ๋ถˆ์•ˆ์ •ํ•œ ๋ฌด์„  ๋„คํŠธ์›Œํฌ ํ™˜๊ฒฝ์—์„œ๋„

Computer Science Distributed Computing
ModelChain: Decentralized Privacy-Preserving Healthcare Predictive   Modeling Framework on Private Blockchain Networks

ModelChain: Decentralized Privacy-Preserving Healthcare Predictive Modeling Framework on Private Blockchain Networks

: ๊ธฐ๊ด€ ๊ฐ„ ์˜๋ฃŒ ์˜ˆ์ธก ๋ชจ๋ธ๋ง์€ ๋‹ค์–‘ํ•œ ์ด์ ์„ ๊ฐ€์ ธ๋‹ค์ค€๋‹ค. ๊ณผํ•™์  ๊ทผ๊ฑฐ๋ฅผ ์ƒ์„ฑํ•˜๊ณ  ๋น„๊ต ํšจ๊ณผ ์—ฐ๊ตฌ์— ๊ธฐ์—ฌํ•˜๋ฉฐ, ์ƒ๋ฌผ์˜ํ•™ ๋ฐœ๊ฒฌ์„ ๊ฐ€์†ํ™”ํ•˜๊ณ  ํ™˜์ž ์น˜๋ฃŒ๋ฅผ ๊ฐœ์„ ํ•  ์ˆ˜ ์žˆ๋‹ค. ํŠนํžˆ, ๊ธฐ๊ด€ ๊ฐ„ ๋ฐ์ดํ„ฐ ๊ณต์œ ๋Š” ํŠน์ • ๊ฒฐ๊ณผ๋ฅผ ์˜ˆ์ธกํ•˜๋Š” ๋ฐ ๋„์›€์ด ๋˜๋ฉฐ, ์ด๋Š” ๊ฐ ๊ธฐ๊ด€์˜ ๊ธฐ๋ก๋งŒ์œผ๋กœ๋Š” ๋ถ€์กฑํ•œ ์ •๋ณด๋ฅผ ๋ณด์™„ํ•ด ์ค€๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๊ธฐ์กด ๋ฐฉ๋ฒ•๋“ค์€ ์ค‘์•™ ์ง‘์ค‘์‹ ์•„ํ‚คํ…์ฒ˜์— ๊ธฐ๋ฐ˜์„ ๋‘๊ณ  ์žˆ์–ด ์—ฌ๋Ÿฌ ๊ฐ€์ง€ ์œ„ํ—˜๊ณผ ์ทจ์•ฝ์ ์„ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. ๋จผ์ €, ๊ธฐ๊ด€ ์ •์ฑ…์˜ ๋ฌธ์ œ๋กœ ์ธํ•ด ๋‹จ์ผ ์ค‘์•™ ์„œ๋ฒ„์— ๊ถŒํ•œ์„ ์–‘๋„ํ•˜๊ธฐ๋ฅผ ๊บผ๋ คํ•  ์ˆ˜ ์žˆ๋‹ค. ๋˜ํ•œ, ๋‹จ์ผ ์žฅ์• ์ (Single Point of Fa

Network Cryptography and Security Framework Computers and Society Model Computer Science
Modeling the high-energy radiation in gamma-ray binaries

Modeling the high-energy radiation in gamma-ray binaries

๋ณธ ๋…ผ๋ฌธ์€ ๊ฐ๋งˆ์„  ์ด์ค‘์„ฑ๊ณ„์—์„œ ๊ด€์ธก๋˜๋Š” ๋ณต์žกํ•œ ๊ณ ์—๋„ˆ์ง€ ๋ฐฉ์ถœ ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ๋ฌผ๋ฆฌ์ ์œผ๋กœ ์ผ๊ด€๋œ ํ•˜๋‚˜์˜ ํ”„๋ ˆ์ž„์›Œํฌ ์•ˆ์— ํ†ตํ•ฉํ•˜๋ ค๋Š” ์‹œ๋„์ด๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ๋“ค์€ ์ฃผ๋กœ โ€˜์ถฉ๋Œ๋œ(shocked)โ€™ ํŽ„์Šคํ’ ์˜์—ญ์—์„œ ์ „์žโ€‘์–‘์ „์ž ์Œ์ด ๋™๊ธฐํ™”์™€ ์—ญ์ปดํ”„ํ„ด ๊ณผ์ •์„ ํ†ตํ•ด ๋ณต์‚ฌ๋ฅผ ๋งŒ๋“ ๋‹ค๊ณ  ๊ฐ€์ •ํ–ˆ์ง€๋งŒ, ์ €์ž๋Š” โ€˜๋น„์ถฉ๋Œ๋œ(unshocked)โ€™ ํŽ„์Šคํ’์—์„œ๋„ ์—ญ์ปดํ”„ํ„ด๋งŒ์œผ๋กœ ์ถฉ๋ถ„ํžˆ ๊ณ ์—๋„ˆ์ง€ ๊ฐ๋งˆ์„ ์„ ์ƒ์‚ฐํ•  ์ˆ˜ ์žˆ์Œ์„ ๊ฐ•์กฐํ•œ๋‹ค. ์ด๋Š” ํŽ„์Šคํ’์ด ๋ณ„ํ’์— ์˜ํ•ด ์••์ถ•๋˜๊ธฐ ์ „๊นŒ์ง€ ์ž๊ธฐ์žฅ์ด ํ๋ฆ„์— ๊ณ ์ •(frozenโ€‘in)๋˜์–ด ์žˆ์–ด ๋™๊ธฐํ™” ๋ณต์‚ฌ๊ฐ€ ์–ต์ œ๋˜๊ณ , ์ „์ž๋“ค์ด ๋ณ„๋น›์„ ์ง์ ‘ ์—…์Šค

Astrophysics Model
Modeling the structure and evolution of discussion cascades

Modeling the structure and evolution of discussion cascades

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ํ•„์š”์„ฑ ์ธํ„ฐ๋„ท ์ƒ์—์„œ ์ธ๊ฐ„์ด ์˜๊ฒฌ์„ ๊ตํ™˜ํ•˜๋Š” ๊ณผ์ •์€ ๋Œ€๋ถ€๋ถ„ ํŠธ๋ฆฌ ํ˜•ํƒœ์˜ โ€˜ํ™œ๋™ ์บ์Šค์ผ€์ด๋“œโ€™๋กœ ๋‚˜ํƒ€๋‚œ๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ๋Š” ๋ธ”๋กœ๊ทธ ํฌ์ŠคํŠธ, ํŠธ์œ„ํ„ฐ ๋ฆฌํŠธ์œ—, ์ฒด์ธ ๋ ˆํ„ฐ ๋“ฑ ๋น„๊ต์  ๋‹จ์ˆœํ•œ ์ •๋ณด ์ „๋‹ฌ ๋ฉ”์ปค๋‹ˆ์ฆ˜์— ์ดˆ์ ์„ ๋งž์ถ”์—ˆ์œผ๋ฉฐ, ๋ณต์žกํ•œ ์˜๊ฒฌ ๊ตํ™˜์„ ํฌํ•จํ•˜๋Š” ์žฅ๊ธฐ ํ† ๋ก ์— ๋Œ€ํ•œ ๋ชจ๋ธ๋ง์€ ๊ฑฐ์˜ ์ด๋ฃจ์–ด์ง€์ง€ ์•Š์•˜๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ ์ด๋Ÿฌํ•œ ๊ณต๋ฐฑ์„ ๋ฉ”์šฐ๊ธฐ ์œ„ํ•ด, ๊ณ ๋„์˜ ์ƒํ˜ธ์ž‘์šฉ์„ ํŠน์ง•์œผ๋กœ ํ•˜๋Š” ํ† ๋ก  ์บ์Šค์ผ€์ด๋“œ๋ฅผ ๋Œ€์ƒ์œผ๋กœ ํ•˜์—ฌ ๊ตฌ์กฐยท์ง„ํ™” ์–‘์ƒ์„ ์ •๋Ÿ‰ํ™”ํ•œ๋‹ค๋Š” ์ ์—์„œ ํ•™๋ฌธ์ ยท์‹ค์šฉ์  ์˜์˜๊ฐ€ ํฌ๋‹ค. 2. ๋ฐ์ดํ„ฐ์…‹์˜ ์ด์งˆ์„ฑ Slashdot : ๊ธฐ์ˆ ยท

Physics Computer Science Social Networks Model
Modelling dynamic programming problems by generalized d-graphs

Modelling dynamic programming problems by generalized d-graphs

์ด ๋…ผ๋ฌธ์€ ๋™์  ๊ณ„ํš๋ฒ•์„ ๊ทธ๋ž˜ํ”„ ์ด๋ก ๊ณผ ์—ฐ๊ฒฐ์ง“๋Š” ๊ธฐ์กด ์—ฐ๊ตฌ ํ๋ฆ„์„ ํ™•์žฅํ•œ๋‹ค๋Š” ์ ์—์„œ ํ•™์ˆ ์  ์˜์˜๊ฐ€ ํฌ๋‹ค. ์ „ํ†ต์ ์œผ๋กœ DP๋Š” ์ตœ์ ์„ฑ ์›๋ฆฌ๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•œ ์žฌ๊ท€์‹(ํ•จ์ˆ˜ ๋ฐฉ์ •์‹)์„ ํ•˜ํ–ฅ์‹์œผ๋กœ ๊ตฌํ˜„ํ•˜๋Š” ์ ˆ์ฐจ๋กœ ์ดํ•ด๋˜์–ด ์™”์œผ๋ฉฐ, ์ด๋ฅผ ๋ฌด์‚ฌ์ดํด ๊ตฌ์กฐ์˜ ๊ทธ๋ž˜ํ”„(์˜ˆ: DPโ€‘tree, dโ€‘graph, ํŽ˜ํŠธ๋ฆฌ ๋„ท)๋กœ ๋ณ€ํ™˜ํ•˜๋Š” ์‹œ๋„๊ฐ€ ๋‹ค์ˆ˜ ์ œ์‹œ๋˜์—ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ด๋Ÿฌํ•œ ์ ‘๊ทผ์€ โ€œ์ˆœํ™˜ ํ•จ์ˆ˜ ๋ฐฉ์ •์‹โ€์„ ํฌํ•จํ•˜๋Š” ๋ฌธ์ œ๋ฅผ ๋ฐฐ์ œํ•œ๋‹ค๋Š” ํ•œ๊ณ„๊ฐ€ ์žˆ๋‹ค. ์‹ค์ œ๋กœ ์ตœ๋‹จ ๊ฒฝ๋กœ ๋ฌธ์ œ์—์„œ ๋ฒจ๋งŒโ€‘ํฌ๋“œ ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด ์ž‘๋™ํ•˜๋Š” ๊ทธ๋ž˜ํ”„๋Š” ์Œ์˜ ๊ฐ€์ค‘ ์‚ฌ์ดํด์ด ์กด์žฌํ•  ๊ฒฝ์šฐ์—๋„ ์ผ์ • ์กฐ๊ฑด ํ•˜์—

Computer Science Data Structures Model
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ModSkill: Physical Character Skill Modularization

ModSkill์€ ๋ณต์žกํ•œ ์ „์ฒด ๋ชธ์ฒด ๊ธฐ์ˆ ์„ ๋…๋ฆฝ์ ์ธ ์‹ ์ฒด ๋ถ€์œ„๋ฅผ ์œ„ํ•œ ๋ชจ๋“ˆํ˜• ๊ธฐ์ˆ ๋กœ ๋ถ„๋ฆฌํ•จ์œผ๋กœ์จ, ์ธ๊ฐ„ ๋™์ž‘์˜ ๋‹ค์–‘์„ฑ๊ณผ ์—ญ๋™์„ฑ์„ ํšจ๊ณผ์ ์œผ๋กœ ๋‹ค๋ฃจ๋Š” ๋ฐ ๋„์›€์„ ์ค€๋‹ค. ์ด ํ”„๋ ˆ์ž„์›Œํฌ๋Š” ์ •์ฑ… ๊ด€์ฐฐ์„ ์ฒ˜๋ฆฌํ•˜์—ฌ ๊ฐ ์‹ ์ฒด ๋ถ€์œ„์— ๋Œ€ํ•œ ์ €์ˆ˜์ค€ ์ปจํŠธ๋กค๋Ÿฌ๋ฅผ ์•ˆ๋‚ดํ•˜๋Š” ์Šคํ‚ฌ ์ž„๋ฒ ๋”ฉ์„ ์ƒ์„ฑํ•œ๋‹ค. ๋˜ํ•œ, Active Skill Learning ์ ‘๊ทผ๋ฒ•์€ ๋„์ „์ ์ธ ์ถ”์  ์‹œ๋‚˜๋ฆฌ์˜ค์—์„œ ์ •์ฑ… ํ•™์Šต์„ ํ–ฅ์ƒํ•˜๊ธฐ ์œ„ํ•ด ํฐ ๋™์ž‘ ์ƒ์„ฑ ๋ชจ๋ธ์„ ํ™œ์šฉํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ๋ชจ๋“ˆํ™” ๋ฐ ์ ์‘์  ์ƒ˜ํ”Œ๋ง ๊ธฐ๋ฒ•์„ ํ†ตํ•ด ModSkill์€ ๊ธฐ์กด ๋ฐฉ๋ฒ•๋ณด๋‹ค ์ •ํ™•ํ•œ ์ „์ฒด ๋ชธ์ฒด ๋™์ž‘ ์ถ”์ ์„ ๋‹ฌ์„ฑํ•˜๊ณ , ๋‹ค

Modular Construction of Fixed Point Combinators and Clocked Boehm Trees

Modular Construction of Fixed Point Combinators and Clocked Boehm Trees

: ๊ณ ์ •์  ์ฝค๋น„๋„ค์ดํ„ฐ๋Š” ๋žŒ๋‹ค ๊ณ„์‚ฐ๋ฒ•๊ณผ ๋…ผ๋ฆฌ์˜ ํ•ต์‹ฌ์ ์ธ ๊ฐœ๋…์œผ๋กœ, ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ด๋Ÿฌํ•œ ๊ณ ์ „์ ์ธ ๊ฐœ๋…์˜ ๊ตฌ์กฐ์™€ ํŠน์„ฑ์„ ์‹ฌ๋„ ์žˆ๊ฒŒ ๋ถ„์„ํ•ฉ๋‹ˆ๋‹ค. ์—ฐ๊ตฌ์ž๋“ค์€ fpc์˜ ๋ชจ๋“ˆ์‹ ๊ตฌ์„ฑ์— ์ดˆ์ ์„ ๋งž์ถ”๊ณ , ๋‹ค์–‘ํ•œ ์ƒ์„ฑ ๋„์‹์„ ๊ฐœ๋ฐœํ•˜์—ฌ ์ƒˆ๋กœ์šด fpc๋ฅผ ๋งŒ๋“ค์–ด๋ƒ…๋‹ˆ๋‹ค. ํŠนํžˆ, Scott์˜ ๋ฐฉ์ •์‹์ธ BY BY S๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ์ƒˆ๋กœ์šด fpc ์‹œํ€€์Šค๋ฅผ ์ƒ์„ฑํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•ฉ๋‹ˆ๋‹ค. ์ด๋Š” Y๊ฐ€ fpc์ผ ๋•Œ, Y P1 ... Pn๋„ fpc๋ผ๋Š” ์‚ฌ์‹ค์„ ์ด์šฉํ•˜๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋ชจ๋“ˆ์‹ ๊ตฌ์„ฑ์„ ํ†ตํ•ด ๋งŽ์€ ์ƒˆ๋กœ์šด ๊ณ ์ •์  ์ฝค๋น„๋„ค์ดํ„ฐ๋ฅผ ๋งŒ๋“ค์–ด๋‚ผ ์ˆ˜ ์žˆ์ง€๋งŒ, ๊ทธ ์‹ ๊ทœ์„ฑ์„ ์ฆ๋ช…

Computer Science Logic
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Moral Susceptibility and Robustness under Persona Role-Play in Large Language Models

๋ณธ ์—ฐ๊ตฌ๋Š” ์–ธ์–ด ๋ชจ๋ธ์˜ ๋„๋•์  ์ธก๋ฉด์— ์ดˆ์ ์„ ๋งž์ถ”๊ณ , ํŠนํžˆ ์ธ๋ฌผ ์—ญํ• ๊ทน์ด ์ด๋“ค์˜ ๋„๋•์  ํŒ๋‹จ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ์กฐ์‚ฌํ•˜์˜€๋‹ค. MFQ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ, ์šฐ๋ฆฌ๋Š” ๋ชจ๋ธ๋“ค์ด ๋‹ค์–‘ํ•œ ์ธ๋ฌผ์„ ์—ฐ๊ธฐํ•  ๋•Œ ๋‚˜ํƒ€๋‚˜๋Š” ๋„๋•์  ์ทจ์•ฝ์„ฑ๊ณผ ๋กœ๋ธŒ์ŠคํŠธ๋‹ˆ์Šค๋ฅผ ์ •๋Ÿ‰ํ™”ํ•˜๋Š” ์ƒˆ๋กœ์šด ๋ฐฉ๋ฒ•์„ ์ œ์•ˆํ–ˆ๋‹ค. ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋Š” ๋ชจ๋ธ์˜ ์ข…๋ฅ˜์™€ ํฌ๊ธฐ๊ฐ€ ์ด๋Ÿฌํ•œ ์†์„ฑ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ๋ณด์—ฌ์ฃผ๋ฉฐ, ํŠนํžˆ Claude ๊ณ„์—ด์ด ๊ฐ€์žฅ ๋†’์€ ๋กœ๋ธŒ์ŠคํŠธ๋‹ˆ์Šค๋ฅผ ๋ณด์˜€๋‹ค๋Š” ์ ์€ ์ฃผ๋ชฉํ•  ๋งŒํ•˜๋‹ค. ๋˜ํ•œ, ์ทจ์•ฝ์„ฑ๊ณผ ๋กœ๋ธŒ์ŠคํŠธ๋‹ˆ์Šค ๊ฐ„์˜ ์ƒ๊ด€๊ด€๊ณ„๋Š” ์–ธ์–ด ๋ชจ๋ธ์˜ ๋„๋•์  ํ–‰๋™์— ๋Œ€ํ•œ ์ƒˆ๋กœ์šด ํ†ต์ฐฐ๋ ฅ์„ ์ œ๊ณตํ•œ๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ์–ธ์–ด ๋ชจ๋ธ์˜

Model
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Morphisms and BWT-run Sensitivity

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋™๊ธฐ BWTโ€‘๋Ÿฐ ์€ ์ตœ๊ทผ ์••์ถ• ์ธ๋ฑ์Šค(ํŠนํžˆ FMโ€‘index)์˜ ๊ณต๊ฐ„ ํšจ์œจ์„ฑ์„ ์˜ˆ์ธกํ•˜๋Š” ์ง€ํ‘œ๋กœ ํ™œ์šฉ๋œ๋‹ค. ๋Ÿฐ ์ˆ˜๊ฐ€ ์ž‘์„์ˆ˜๋ก RLEโ€‘์••์ถ•์ด ํšจ๊ณผ์ ์ด๋ฉฐ, ์ด๋Š” ๋ฐ˜๋ณต ๋ฌธ์ž์—ด ์ฒ˜๋ฆฌ์— ํฐ ์ด์ ์„ ์ œ๊ณตํ•œ๋‹ค. ์ฃผ์ž…ํ˜• ๋ชจํ•‘ ์€ ๊ฐ ์•ŒํŒŒ๋ฒณ ๊ธฐํ˜ธ๋ฅผ ์„œ๋กœ ๊ฒน์น˜์ง€ ์•Š๋Š” ๋ฌธ์ž์—ด๋กœ ์น˜ํ™˜ํ•˜๋Š” ๋ณ€ํ™˜์œผ๋กœ, ๋ฌธ์ž์—ด ์ด๋ก ยท์ฝ”๋“œ ์ด๋ก ์—์„œ ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ด๋Ÿฌํ•œ ์น˜ํ™˜์ด BWTโ€‘๋Ÿฐ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์€ ์•„์ง ์ฒด๊ณ„์ ์œผ๋กœ ๊ทœ๋ช…๋˜์ง€ ์•Š์•˜๋‹ค. 2. ์ฃผ์š” ๊ธฐ์—ฌ | ๋ฒˆํ˜ธ | ๋‚ด์šฉ | ์˜์˜ | | | | | | โ‘  | ์ด์ง„ ์•ŒํŒŒ๋ฒณ์—์„œ BWTโ€‘๋Ÿฐ ๋ฏผ๊ฐ๋„์™€ ์›์‹œ

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Motion In-Betweening for Densely Interacting Characters

๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ๋ฐ€์ ‘ํ•˜๊ฒŒ ์ƒํ˜ธ์ž‘์šฉํ•˜๋Š” ์บ๋ฆญํ„ฐ๋“ค์˜ ๋ชจ์…˜ ํ•ฉ์„ฑ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ์ƒˆ๋กœ์šด ์ ‘๊ทผ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค. ๊ธฐ์กด ๋ฐฉ๋ฒ•๋“ค์€ ์ฃผ๋กœ ๋‹จ์ผ ์บ๋ฆญํ„ฐ์˜ ์›€์ง์ž„์— ์ดˆ์ ์„ ๋งž์ถ”์—ˆ๊ธฐ ๋•Œ๋ฌธ์—, ์—ฌ๋Ÿฌ ์บ๋ฆญํ„ฐ๊ฐ€ ํ•จ๊ป˜ ์›€์ง์ด๋Š” ๊ฒฝ์šฐ ์ž์—ฐ์Šค๋Ÿฌ์šด ์ƒํ˜ธ์ž‘์šฉ์„ ์œ ์ง€ํ•˜๋Š” ๊ฒƒ์ด ๋„์ „ ๊ณผ์ œ๋กœ ๋‚จ์•„์žˆ๋‹ค. ์šฐ๋ฆฌ๋Š” ํฌ๋กœ์Šค ์ŠคํŽ˜์ด์Šค ์ธ ๋น„ํŠธ์œˆ๋‹์ด๋ผ๋Š” ๋ฐฉ๋ฒ•์„ ํ†ตํ•ด ๊ฐ ์บ๋ฆญํ„ฐ์˜ ๋‹ค๋ฅธ ์กฐ๊ฑด๋ถ€ ํ‘œํ˜„ ๊ณต๊ฐ„์—์„œ ์ƒํ˜ธ์ž‘์šฉ์„ ๋ชจ๋ธ๋งํ•จ์œผ๋กœ์จ ์ด ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ณ ์ž ํ•œ๋‹ค. ๋˜ํ•œ, ์žฅ๊ธฐ๊ฐ„์˜ ์ƒํ˜ธ์ž‘์šฉ๊ณผ ๋ชจ์…˜ ํ’ˆ์งˆ์„ ์œ ์ง€ํ•˜๊ธฐ ์œ„ํ•ด ์ ๋Œ€์  ํ•™์Šต๊ณผ ์ž ์žฌ ๊ณต๊ฐ„ ์ •์ œ ๊ธฐ๋ฒ•์„ ํ™œ์šฉํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ์ ‘๊ทผ๋ฒ•์€ ์ž์—ฐ์Šค

Multi Product Inventory Optimization using Uniform Crossover Genetic   Algorithm

Multi Product Inventory Optimization using Uniform Crossover Genetic Algorithm

: ๊ณต๊ธ‰๋ง ๊ด€๋ฆฌ๋Š” ๊ธฐ์—…์˜ ์„ฑ๊ณต์— ์žˆ์–ด ํ•ต์‹ฌ์ ์ธ ์š”์†Œ์ด๋ฉฐ, ๊ทธ ์ค‘์—์„œ๋„ ์žฌ๊ณ  ๊ด€๋ฆฌ๋Š” ๋งค์šฐ ์ค‘์š”ํ•œ ๋ถ„์•ผ์ž…๋‹ˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ ์žฌ๊ณ  ๊ด€๋ฆฌ์™€ ๊ด€๋ จ๋œ ๋‹ค์–‘ํ•œ ์ธก๋ฉด์„ ์‹ฌ๋„ ์žˆ๊ฒŒ ๋ถ„์„ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ๋จผ์ €, ๊ณต๊ธ‰๋ง ๊ด€๋ฆฌ์—์„œ ์žฌ๊ณ ์˜ ์ค‘์š”์„ฑ๊ณผ ๋น„์šฉ ์ ˆ๊ฐ ํšจ๊ณผ๋ฅผ ๊ฐ•์กฐํ•ฉ๋‹ˆ๋‹ค. ์žฌ๊ณ ๋Š” ๊ณต๊ธ‰๋ง ๋‚ด ์ œํ’ˆ์˜ ํ๋ฆ„์„ ์œ ์ง€ํ•˜๋Š” ๋ฐ ํ•„์ˆ˜์ ์ด์ง€๋งŒ, ๊ณผ๋„ํ•œ ์žฌ๊ณ ๋Š” ๋ถˆํ•„์š”ํ•œ ๋น„์šฉ์„ ๋ฐœ์ƒ์‹œํ‚ต๋‹ˆ๋‹ค. ๋”ฐ๋ผ์„œ ํšจ์œจ์ ์ธ ์žฌ๊ณ  ๊ด€๋ฆฌ๋Š” ๊ธฐ์—…์˜ ์ˆ˜์ต์„ฑ์„ ํ–ฅ์ƒ์‹œํ‚ค๋Š” ๋ฐ ์ง์ ‘์ ์ธ ์˜ํ–ฅ์„ ๋ฏธ์นฉ๋‹ˆ๋‹ค. ๋˜ํ•œ, ๋ณธ ๋…ผ๋ฌธ์€ ์žฌ๊ณ  ๊ด€๋ฆฌ ๋ฌธ์ œ์˜ ๋ณต์žก์„ฑ๊ณผ ๋‹ค์–‘ํ•œ ์š”์†Œ๋ฅผ ์„ค๋ช…ํ•ฉ๋‹ˆ๋‹ค. ์ˆ˜์š” ํŒจํ„ด, ํ’ˆ๋ชฉ ๊ณต๊ธ‰,

Computer Science Neural Computing
Multi-Instrument X-ray Observations of Thermonuclear Bursts with Short   Recurrence Times

Multi-Instrument X-ray Observations of Thermonuclear Bursts with Short Recurrence Times

: Type I X ์„  ํญ๋ฐœ์€ ์ค‘์„ฑ์ž๋ณ„์˜ ์™ธํ”ผ์—์„œ ์ผ์–ด๋‚˜๋Š” ์—ดํ•ต ๋ฐ˜์‘์œผ๋กœ ์ธํ•ด ๋ฐœ์ƒํ•œ๋‹ค. ์ด ๋ฌผ์งˆ์€ ๋™๋ฐ˜์„ฑ์œผ๋กœ๋ถ€ํ„ฐ ๋กœ์Šˆ ๋กœ๋ธŒ ๋„˜์นจ์„ ํ†ตํ•ด ์ถ•์ ๋˜๋ฉฐ, ์ผ๋ฐ˜์ ์œผ๋กœ ์ˆ˜์†Œ ๋ฐ ํ—ฌ๋ฅจ์ด ์ฃผ๋œ ์—ฐ๋ฃŒ์ด๋‹ค. ํ˜„์žฌ์˜ 1์ฐจ์› ๋ชจ๋ธ์€ ์ด๋Ÿฌํ•œ ํญ๋ฐœ์˜ ๋‹ค์–‘ํ•œ ํŠน์„ฑ์„ ์„ค๋ช…ํ•  ์ˆ˜ ์žˆ์ง€๋งŒ, ์งง์€ ์žฌ๋ฐœ ์‹œ๊ฐ„์„ ๊ฐ€์ง„ ํญ๋ฐœ์€ ๊ธฐ์กด ๋ชจ๋ธ๊ณผ ์ƒ์ถฉํ•˜๋Š” ํ˜„์ƒ์œผ๋กœ ์—ฌ๊ฒจ์ ธ ์™”๋‹ค. ์งง์€ ์žฌ๋ฐœ ์‹œ๊ฐ„์„ ๊ฐ€์ง„ ํญ๋ฐœ์€ ์ค‘์„ฑ์ž๋ณ„ ํ‘œ๋ฉด์˜ ํŠน์ • ์˜์—ญ์— ๊ตญํ•œ๋œ ๋ฌผ์งˆ ์ถ•์ ์ด๋‚˜ ์ˆ˜์†Œ/ํ—ฌ๋ฅจ์˜ ๋ถ€๋ถ„์ ์ธ ์—ฐ์†Œ๊ฐ€ ์›์ธ์ผ ์ˆ˜ ์žˆ๋‹ค. ๋˜ํ•œ, ์ค‘์„ฑ์ž๋ณ„์˜ ๋น ๋ฅธ ํšŒ์ „ ์ฃผํŒŒ์ˆ˜๋Š” ํญ๋ฐœ ์‚ฌ์ด์˜ ์งง์€ ์‹œ๊ฐ„ ๋™์•ˆ ํ˜ผํ•ฉ์„

Astrophysics
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Multiscale modelling of thermally stressed superelastic polyimide

์ด ๋…ผ๋ฌธ์—์„œ๋Š” ์—ฐ์†์ฒด ์Šค์ผ€์ผ๊ณผ ์›์ž ์Šค์ผ€์ผ์„ ์—ฐ๊ฒฐํ•˜์—ฌ, ์—ด ์‘๋ ฅ ํ•˜์˜ ์žฌ๋ฃŒ์˜ ๊ฑฐ๋™์„ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ํ•˜๊ณ  ๋ถ„์„ํ•˜์˜€๋‹ค. SPH ๋ชจ๋ธ๊ณผ MD ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ๊ฒฐํ•ฉํ•จ์œผ๋กœ์จ, ์—ด ํŒฝ์ฐฝ๊ณผ ๊ฐ™์€ ํ˜„์ƒ์„ ํฌ์ฐฉํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋˜ํ•œ, ์•Œ๋ฃจ๋ฏธ๋Š„ ํŒ์— ๋Œ€ํ•œ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ํ†ตํ•ด ์Šˆํผ์—˜๋ผ์Šคํ‹ฑ ํด๋ฆฌ์ด๋ฏธ๋“œ์˜ ์šฐ์ˆ˜ํ•œ ์ ˆ์—ฐ ๋Šฅ๋ ฅ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์ด๋Š” ์žฌ๋ฃŒ์˜ ๋‹ค์ค‘ ์Šค์ผ€์ผ ๊ฑฐ๋™์„ ์ดํ•ดํ•˜๊ณ , ์—ด์—ญํ•™์  ํŠน์„ฑ์„ ๋ถ„์„ํ•˜๋Š” ๋ฐ ์žˆ์–ด ์ค‘์š”ํ•œ ๊ธฐ์—ฌ๋ฅผ ํ•œ๋‹ค.

Model
Mutual Clustering Coefficient-based Suspicious-link Detection approach   for Online Social Networks

Mutual Clustering Coefficient-based Suspicious-link Detection approach for Online Social Networks

๋ณธ ๋…ผ๋ฌธ์€ ๊ฐ€์งœ ํ”„๋กœํ•„์ด OSN์— ์นจํˆฌํ•˜๋Š” ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ โ€˜๊ณตํ†ต ์นœ๊ตฌโ€™ ํ˜„์ƒ์— ์ดˆ์ ์„ ๋งž์ถ”์–ด ๋ถ„์„ํ•œ๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ์—์„œ๋Š” ๋‘ ์‚ฌ์šฉ์ž๊ฐ€ ๋‹ค์ˆ˜์˜ ๊ณตํ†ต ์นœ๊ตฌ๋ฅผ ๊ฐ€์งˆ ๊ฒฝ์šฐ, ์˜คํ”„๋ผ์ธ์—์„œ ์ด๋ฏธ ์•Œ๊ณ  ์žˆ๊ฑฐ๋‚˜ ์œ ์‚ฌํ•œ ๊ด€์‹ฌ์‚ฌ๋ฅผ ๊ณต์œ ํ•  ๊ฐ€๋Šฅ์„ฑ์ด ๋†’์•„ ์นœ๊ตฌ ์š”์ฒญ์ด ์ˆ˜๋ฝ๋œ๋‹ค๊ณ  ๋ณด๊ณ ํ•˜์˜€๋‹ค. ๊ฐ€์งœ ์‚ฌ์šฉ์ž๋Š” ์ด๋Ÿฌํ•œ ์‹ฌ๋ฆฌ๋ฅผ ์ด์šฉํ•ด ํŠน์ • ์ปค๋ฎค๋‹ˆํ‹ฐ(๊ทธ๋ฃนยทํŽ˜์ด์ง€) ๋‚ด์—์„œ ๋‹ค์ˆ˜์˜ ์‹ค์ œ ์‚ฌ์šฉ์ž๋ฅผ ์—ฐ๊ฒฐ๋ง์— ๋Œ์–ด๋“ค์ธ๋‹ค. ์ด๋•Œ ๊ฐ€์งœ ํ”„๋กœํ•„๊ณผ ์‹ค์ œ ์‚ฌ์šฉ์ž ์‚ฌ์ด์—๋Š” ํ”„๋กœํ•„ ์œ ์‚ฌ์„ฑ ์ด ๊ฑฐ์˜ ์กด์žฌํ•˜์ง€ ์•Š์Œ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ , ๋‹ค์ˆ˜์˜ ๊ณตํ†ต ์ด์›ƒ ์ด ์กด์žฌํ•˜๋ฉด ์‹ ๋ขฐ๋„๊ฐ€ ์ „ํŒŒ๋˜์–ด ์ถ”๊ฐ€์ ์ธ ์นœ๊ตฌ ์š”

Computer Science Social Networks Network Detection
NbO2-based memristive neurons for burst-based perceptron

NbO2-based memristive neurons for burst-based perceptron

๋ณธ ์—ฐ๊ตฌ๋Š” ๋‰ด๋กœ๋ชจํ”ฝ ํ•˜๋“œ์›จ์–ด ์„ค๊ณ„์—์„œ ๊ฐ€์žฅ ํ•ต์‹ฌ์ ์ธ ์š”์†Œ์ธ โ€˜์ธ๊ณต ๋‰ด๋Ÿฐโ€™์˜ ๋™์  ํŠน์„ฑ์„ ๋ฉค๋ฆฌ์Šคํ„ฐ ์†Œ์ž๋ฅผ ํ†ตํ•ด ๊ตฌํ˜„ํ•˜๊ณ , ์ด๋ฅผ ์‹ค์ œ ์‹ ๊ฒฝ๋ง ๊ตฌ์กฐ์— ์ ์šฉํ•œ ์ตœ์ดˆ ์ˆ˜์ค€์˜ ์‹คํ—˜์  ์ฆ๋ช…์„ ์ œ๊ณตํ•œ๋‹ค๋Š” ์ ์—์„œ ํ•™๋ฌธ์ ยท์‚ฐ์—…์  ์˜๋ฏธ๊ฐ€ ํฌ๋‹ค. 1. NbOโ‚‚ ๋ฉค๋ฆฌ์Šคํ„ฐ์˜ ๋ฌผ๋ฆฌ์  ํŠน์„ฑ NbOโ‚‚๋Š” ์ ˆ์—ฐโ€‘๊ธˆ์† ์ „์ด(IMT)๋ฅผ ๋ณด์ด๋Š” ์ „์ด๊ธˆ์†์‚ฐํ™”๋ฌผ๋กœ, ์ „์••์ด ์ž„๊ณ„๊ฐ’์„ ์ดˆ๊ณผํ•˜๋ฉด ๊ธ‰๊ฒฉํžˆ ์ €ํ•ญ์ด ๊ฐ์†Œํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ๋น„์„ ํ˜• ์ „๋„ ํŠน์„ฑ์€ โ€˜allโ€‘orโ€‘nothingโ€™ ์ŠคํŒŒ์ดํฌ ๋ฐœ์ƒ ๋ฉ”์ปค๋‹ˆ์ฆ˜๊ณผ ์ž์—ฐ์Šค๋Ÿฝ๊ฒŒ ์—ฐ๊ฒฐ๋œ๋‹ค. ๋…ผ๋ฌธ์—์„œ๋Š” ์ž„๊ณ„ ์ „์••์—์„œ์˜ ์ €ํ•ญ(R th)๊ณผ ์œ ์ง€ ์ „์••์—์„œ

Computer Science Electrical Engineering and Systems Science Emerging Technologies
Nemotron 3 Nano: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning

Nemotron 3 Nano: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning

: ๋„ค๋ชจํŠธ๋ก  3 ๋‚˜๋…ธ๋Š” ์—์ด์ „ํ‹ฑ ์ถ”๋ก ์„ ์œ„ํ•œ ํšจ์œจ์ ์ธ ๋ฏน์Šค์ณ ์˜ค๋ธŒ ์—‘์Šคํผ์ธ  ํ•˜์ด๋ธŒ๋ฆฌ๋“œ ๋ง˜๋ฐ” ํŠธ๋žœ์Šคํฌ๋จธ ๋ชจ๋ธ์ž…๋‹ˆ๋‹ค. ์ด ๋ชจ๋ธ์€ Mamba 2์™€ Grouped Query Attention์„ ๊ฒฐํ•ฉํ•˜์—ฌ ์—์ด์ „ํ‹ฑ, ์ถ”๋ก  ๋ฐ ์ฑ„ํŒ… ๋Šฅ๋ ฅ์„ ๊ฐ–์ถ˜ ์–ธ์–ด ๋ชจ๋ธ์„ ๋งŒ๋“ญ๋‹ˆ๋‹ค. ๋˜ํ•œ ๋งค๊ฐœ๋ณ€์ˆ˜๋ฅผ ํฌ์†Œํ•˜๊ฒŒ ํ™•์žฅํ•˜๊ณ  ์ •ํ™•๋„ ์ถ”๋ก  ์ฒ˜๋ฆฌ๋Ÿ‰ ๊ฒฝ๊ณ„๋ฅผ ๊ฐœ์„ ํ•˜๊ธฐ ์œ„ํ•ด ๋ฏน์Šค์ณ ์˜ค๋ธŒ ์—‘์Šคํผ์ธ  ๋ ˆ์ด์–ด๋ฅผ ์‚ฌ์šฉํ•ฉ๋‹ˆ๋‹ค. ์ด ๋ชจ๋ธ์€ 316์–ต ๊ฐœ์˜ ์ด ๋งค๊ฐœ๋ณ€์ˆ˜ ์ค‘ ์ „๋ฐฉ ์ „๋‹ฌ๋‹น 32์–ต ๊ฐœ(์ž„๋ฒ ๋”ฉ ํฌํ•จ ์‹œ 36์–ต ๊ฐœ)๋งŒ ํ™œ์„ฑํ™”ํ•˜์—ฌ ํšจ์œจ์„ฑ์„ ๋†’์˜€์Šต๋‹ˆ๋‹ค. ๋„ค๋ชจํŠธ๋ก  3 ๋‚˜๋…ธ๋Š” ๋‹ค์–‘ํ•œ ๋ฒค์น˜๋งˆํฌ์—

Model
Network Science approach to Modelling Emergence and Topological   Robustness of Supply Networks: A Review and Perspective

Network Science approach to Modelling Emergence and Topological Robustness of Supply Networks: A Review and Perspective

๋ณธ ๋ฆฌ๋ทฐ๋Š” ๊ณต๊ธ‰๋ง ๋„คํŠธ์›Œํฌ(SCN)๋ฅผ ๋ณตํ•ฉ ์ ์‘ ์‹œ์Šคํ…œ์œผ๋กœ ๊ทœ์ •ํ•˜๊ณ , ๋„คํŠธ์›Œํฌ ๊ณผํ•™์ด ์ œ๊ณตํ•˜๋Š” ๋„๊ตฌ๋“ค์„ ํ†ตํ•ด SCN์˜ ๊ตฌ์กฐ์ ยท๋™์  ํŠน์„ฑ์„ ์ฒด๊ณ„์ ์œผ๋กœ ํƒ๊ตฌํ•œ๋‹ค๋Š” ์ ์—์„œ ํ•™๋ฌธ์ ยท์‹ค๋ฌด์  ์˜์˜๊ฐ€ ํฌ๋‹ค. ์ฒซ ๋ฒˆ์งธ๋กœ, ์ €์ž๋Š” ์ง€๋‚œ 10๋…„๊ฐ„ ๋ฐœํ‘œ๋œ ์ฃผ์š” ๋…ผ๋ฌธ๋“ค์„ ๋Œ€์ƒ์œผ๋กœ ์‚ฌ์šฉ๋œ ๋ชจ๋ธ๋ง ๊ธฐ๋ฒ•์„ ๋ถ„๋ฅ˜ํ•œ๋‹ค. ์—ฌ๊ธฐ์—๋Š” ๋ฌด์ž‘์œ„ ๊ทธ๋ž˜ํ”„, ์Šค์ผ€์ผํ”„๋ฆฌ ๋ชจ๋ธ, ๊ณ„์ธต์  ๋ชจ๋“ˆ๋Ÿฌ ๊ตฌ์กฐ, ๊ทธ๋ฆฌ๊ณ  ์ตœ๊ทผ ๊ฐ ๋…ธ๋“œ์˜ โ€˜์ ํ•ฉ๋„โ€™๋ฅผ ๋ฐ˜์˜ํ•œ ์ƒ์„ฑ ๋ชจ๋ธ ๋“ฑ์ด ํฌํ•จ๋œ๋‹ค. ๊ฐ ๋ฐฉ๋ฒ•๋ก ์€ ๋„คํŠธ์›Œํฌ์˜ ์„ฑ์žฅ ๋ฉ”์ปค๋‹ˆ์ฆ˜(์˜ˆ: ์„ ํ˜ธ์  ์—ฐ๊ฒฐ, ์ง€์—ญ์  ์ œ์•ฝ, ๋น„์šฉ ์ตœ์†Œํ™”)๊ณผ ์œ„์ƒ์  ๊ฒฐ๊ณผ(์˜ˆ: ์ฐจ์ˆ˜

Physics Applications Network Statistics Social Networks Model Computer Science
Network-wide Statistical Modeling and Prediction of Computer Traffic

Network-wide Statistical Modeling and Prediction of Computer Traffic

: ์ด ๋…ผ๋ฌธ์€ ์ปดํ“จํ„ฐ ๋„คํŠธ์›Œํฌ์˜ ํŠธ๋ž˜ํ”ฝ ์˜ˆ์ธก๊ณผ ๊ด€๋ จํ•˜์—ฌ ๊ธฐ์กด ๋ฐฉ๋ฒ•์˜ ํ•œ๊ณ„๋ฅผ ๊ทน๋ณตํ•˜๊ณ  ์ƒˆ๋กœ์šด ์ ‘๊ทผ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค๋Š” ์ ์—์„œ ๋งค์šฐ ํฅ๋ฏธ๋กญ์Šต๋‹ˆ๋‹ค. ์ €์ž๋“ค์€ ๋„คํŠธ์›Œํฌ ์ „๋ฐ˜์— ๊ฑธ์นœ ํŠธ๋ž˜ํ”ฝ ๋ชจ๋ธ์„ ๊ฐœ๋ฐœํ•˜๊ธฐ ์œ„ํ•ด ๋ฌผ๋ฆฌ์ ์œผ๋กœ ํ•ด์„ ๊ฐ€๋Šฅํ•œ ํ™•๋ฅ  ๋ชจ๋ธ์„ ์ œ์•ˆํ•ฉ๋‹ˆ๋‹ค. ์ด๋Š” ์ง์ ‘ ์ธก์ •์ด ์–ด๋ ค์šด ๋งํฌ์˜ ํŠธ๋ž˜ํ”ฝ ๋ณ€๋™์„ ๊ฐ„์ ‘์ ์œผ๋กœ ์˜ˆ์ธกํ•  ์ˆ˜ ์žˆ๊ฒŒ ํ•ฉ๋‹ˆ๋‹ค. ํ”Œ๋กœ์šฐ ๋ ˆ๋ฒจ ๋ฐ์ดํ„ฐ๋Š” ์ •ํ™•ํ•œ ์ •๋ณด๋ฅผ ์ œ๊ณตํ•˜์ง€๋งŒ ์–ป๊ณ  ์ฒ˜๋ฆฌํ•˜๋Š” ๋ฐ ๋น„์šฉ์ด ๋งŽ์ด ๋“ญ๋‹ˆ๋‹ค. ๋ฐ˜๋ฉด, ๋งํฌ ๋ ˆ๋ฒจ ๋ฐ์ดํ„ฐ๋Š” ์‰ฝ๊ฒŒ ์–ป์„ ์ˆ˜ ์žˆ์ง€๋งŒ ํ”Œ๋กœ์šฐ์— ๋Œ€ํ•œ ์ •๋ณด๊ฐ€ ๋ถ€์กฑํ•ฉ๋‹ˆ๋‹ค. ์ด ๋…ผ๋ฌธ์—์„œ๋Š” ์ด๋Ÿฌํ•œ ๋‘ ๊ฐ€์ง€ ๋ฐ์ดํ„ฐ ์œ ํ˜•

Applications Network Mathematics Statistics Model
Neutrino oscillation and expected event rate of supernova neutrinos in   adiabatic explosion model

Neutrino oscillation and expected event rate of supernova neutrinos in adiabatic explosion model

: ๋ณธ ๋…ผ๋ฌธ์€ ์ค‘์„ฑ๋ฏธ์ž ๋ฌผ๋ฆฌํ•™ ๋ฐ ์ดˆ์‹ ์„ฑ ๋ฌผ๋ฆฌํ•™ ๋ถ„์•ผ์—์„œ ์ค‘์š”ํ•œ ์—ฐ๊ตฌ๋ฅผ ์ˆ˜ํ–‰ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ํŠนํžˆ ๋‹จ์—ด ํญ๋ฐœ ๋ชจ๋ธ์„ ์‚ฌ์šฉํ•˜์—ฌ ์ค‘์‹ฌ ๋ถ•๊ดด ์ดˆ์‹ ์„ฑ์˜ ์ค‘์„ฑ๋ฏธ์ž ์ง„๋™๊ณผ ์ด๋ฒคํŠธ์œจ์„ ๋ถ„์„ํ•จ์œผ๋กœ์จ, ๊ธฐ์กด ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„๋ฅผ ๋„˜์–ด์„œ๋Š” ์ƒˆ๋กœ์šด ํ†ต์ฐฐ๋ ฅ์„ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค. ๋จผ์ €, ์—ญ๊ณ„์ธต๊ณผ ์ •์ƒ๊ณ„์ธต์˜ ์ค‘์„ฑ๋ฏธ์ž ์ด๋ฒคํŠธ์œจ์ด ฮธโ‚โ‚ƒ์— ๋”ฐ๋ผ ๋‹ฌ๋ผ์ง„๋‹ค๋Š” ์ ์„ ๋ฐœ๊ฒฌํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด๋Š” ์ค‘์„ฑ๋ฏธ์ž ๋ฌผ๋ฆฌํ•™์—์„œ ์ค‘์š”ํ•œ ํ˜ผํ•ฉ ๊ฐ๋„์ธ ฮธโ‚โ‚ƒ์˜ ์˜ํ–ฅ์„ ๋ช…ํ™•ํ•˜๊ฒŒ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค. ๋˜ํ•œ ์ถฉ๊ฒฉํŒŒ์˜ ์˜ํ–ฅ์€ sinยฒ 2ฮธโ‚โ‚ƒ๊ฐ€ ํŠน์ • ๊ฐ’์„ ์ดˆ๊ณผํ•  ๋•Œ ๋‚˜ํƒ€๋‚œ๋‹ค๋Š” ๊ฒƒ์„ ํ™•์ธํ–ˆ์œผ๋ฉฐ, ์ด๋Š” ์ถฉ๊ฒฉํŒŒ ์ „ํŒŒ ๋ฉ”์ปค๋‹ˆ์ฆ˜์— ๋Œ€

Astrophysics Model
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Newton to Einstein: Axiom-Based Discovery via Game Design

๊ณผํ•™์  ๋ฐœ๊ฒฌ์€ ๊ท€๋‚ฉ์  ํŒจํ„ด ์ธ์‹์—์„œ ๊ณต๋ฆฌ ๊ธฐ๋ฐ˜ ์ถ”๋ก ์œผ๋กœ ์ „ํ™˜ํ•ด์•ผ ํ•œ๋‹ค. ์ด๋Š” ๊ธฐ๊ณ„ ํ•™์Šต์ด ์ƒˆ๋กœ์šด ์ง€์‹์„ ํƒ๊ตฌํ•˜๊ณ  ์ดํ•ดํ•˜๋Š” ๋ฐ ์žˆ์–ด ๋” ํšจ๊ณผ์ ์ด๊ณ  ์ฐฝ์˜์ ์ธ ์ ‘๊ทผ๋ฒ•์„ ์ทจํ•  ์ˆ˜ ์žˆ์Œ์„ ์˜๋ฏธํ•œ๋‹ค. ์šฐ๋ฆฌ๋Š” ๊ฒŒ์ž„ ๋””์ž์ธ์„ ํ†ตํ•ด ์ด๋Ÿฌํ•œ ์•„์ด๋””์–ด๋ฅผ ๊ตฌํ˜„ํ•œ๋‹ค. ์—์ด์ „ํŠธ๋“ค์€ ํ™˜๊ฒฝ ๋‚ด์—์„œ ์ž‘๋™ํ•˜๋ฉฐ, ์ด ํ™˜๊ฒฝ์€ ๊ณต๋ฆฌ์— ์˜ํ•ด ์ง€๋ฐฐ๋œ๋‹ค. ์—์ด์ „ํŠธ๋Š” ์˜ˆ์™ธ์ ์ธ ๊ด€์ฐฐ์ด๋‚˜ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ๊ณต๋ฆฌ๋ฅผ ์ˆ˜์ •ํ•˜๊ณ  ์ ์‘์‹œํ‚จ๋‹ค. ์ด๋Ÿฌํ•œ ์ ‘๊ทผ๋ฒ•์€ ๊ธฐ๊ณ„ ํ•™์Šต ์‹œ์Šคํ…œ์ด ๊ธฐ์กด ์ด๋ก ์˜ ํ•œ๊ณ„๋ฅผ ๋›ฐ์–ด๋„˜๊ณ  ์ƒˆ๋กœ์šด ๋ฐœ๊ฒฌ์„ ํ•  ์ˆ˜ ์žˆ๋„๋ก ํ•œ๋‹ค.

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Not All Instances Are Equally Valuable: Towards Influence-Weighted Dataset Distillation

: ๊ธฐ์กด ๋ฐ์ดํ„ฐ์…‹ ์ฆ๋ฅ˜ ๋ฐฉ๋ฒ•์€ ๋ชจ๋“  ์‹ค์ œ ์ธ์Šคํ„ด์Šค๊ฐ€ ๋™๋“ฑํ•œ ๊ฐ€์น˜๋ฅผ ๊ฐ€์ง„๋‹ค๊ณ  ๊ฐ€์ •ํ•˜์ง€๋งŒ, ์ด๋Š” ์‹ค์„ธ๊ณ„ ๋ฐ์ดํ„ฐ์…‹์˜ ๋ณต์žก์„ฑ์„ ๊ฐ„๊ณผํ•˜๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค. IWD๋Š” ์˜ํ–ฅ๋ ฅ ํ•จ์ˆ˜๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ๊ฐ ์ธ์Šคํ„ด์Šค์˜ ๊ธฐ์—ฌ๋„๋ฅผ ํ‰๊ฐ€ํ•˜๊ณ , ์ด๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ๊ฐ€์ค‘์น˜๋ฅผ ํ• ๋‹นํ•ฉ๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ์ ‘๊ทผ๋ฒ•์€ ์œ ์ตํ•œ ๋ฐ์ดํ„ฐ๋ฅผ ๊ฐ•์กฐํ•˜๊ณ  ํ•ด๋กœ์šด ๋ฐ์ดํ„ฐ๋ฅผ ์ค„์ž„์œผ๋กœ์จ ์ฆ๋ฅ˜๋œ ๋ฐ์ดํ„ฐ์…‹์˜ ํ’ˆ์งˆ์„ ํ–ฅ์ƒ์‹œํ‚ต๋‹ˆ๋‹ค. ๋˜ํ•œ, IWD์˜ ๋ชจ๋“ˆ์‹ ์„ค๊ณ„๋Š” ๋‹ค์–‘ํ•œ ์ฆ๋ฅ˜ ํ”„๋ ˆ์ž„์›Œํฌ์— ์‰ฝ๊ฒŒ ์ ์šฉ๋  ์ˆ˜ ์žˆ์–ด, ๋ฒ”์šฉ์„ฑ๊ณผ ํ™œ์šฉ์„ฑ์„ ๋†’์ž…๋‹ˆ๋‹ค.

Data
Numerical Accuracy Comparison of Two Boundary Conditions Commonly used   to Approximate Shear Stress Distributions in Tissue Engineering Scaffolds   Cultured under Flow Perfusion

Numerical Accuracy Comparison of Two Boundary Conditions Commonly used to Approximate Shear Stress Distributions in Tissue Engineering Scaffolds Cultured under Flow Perfusion

๋ณธ ๋…ผ๋ฌธ์€ ์กฐ์ง๊ณตํ•™ ์Šค์บํด๋“œ ์„ค๊ณ„ ๋‹จ๊ณ„์—์„œ ํ•„์ˆ˜์ ์ธ ์ „๋‹จ ์‘๋ ฅ ์˜ˆ์ธก์˜ ์‹ ๋ขฐ์„ฑ์„ ํ™•๋ณดํ•˜๊ธฐ ์œ„ํ•ด, ๋Œ€ํ‘œ ๋ถ€ํ”ผ ์š”์†Œ(RVE) ์ ‘๊ทผ๋ฒ•์— ์ ์šฉ๋˜๋Š” ๊ฒฝ๊ณ„์กฐ๊ฑด์˜ ์ •ํ™•์„ฑ์„ ์ฒด๊ณ„์ ์œผ๋กœ ๊ฒ€์ฆํ•œ ์ ์—์„œ ํ•™์ˆ ์ ยท์‹ค์šฉ์  ์˜์˜๊ฐ€ ํฌ๋‹ค. ์ฒซ์งธ, ์ €์ž๋“ค์€ ์‹ค์ œ ์Šค์บํด๋“œ์˜ ๋ฏธ์„ธ๊ตฌ์กฐ๋ฅผ ๋งˆ์ดํฌ๋กœโ€‘CT๋กœ ๊ณ ํ•ด์ƒ๋„ ๋ณต์›ํ•œ ๋’ค, ๋ผํ‹ฐ์Šคโ€‘๋ณผ์ธ ๋งŒ ๋ฐฉ๋ฒ•(LBM)์ด๋ผ๋Š” ์ž…์ž ๊ธฐ๋ฐ˜ CFD ๊ธฐ๋ฒ•์„ ์‚ฌ์šฉํ•ด ์ „๋‹จ ์‘๋ ฅ์„ ์ง์ ‘ ๊ณ„์‚ฐํ•˜์˜€๋‹ค. LBM์€ ๋ณต์žกํ•œ ๋‹ค๊ณต์„ฑ ๋งค์ฒด์—์„œ์˜ ํ๋ฆ„์„ ํšจ์œจ์ ์œผ๋กœ ํ•ด์„ํ•  ์ˆ˜ ์žˆ๋Š” ์žฅ์ ์ด ์žˆ์–ด, ์ „ํ†ต์ ์ธ ์œ ํ•œ์š”์†Œ๋ฒ•(FEM)์ด๋‚˜ ์œ ํ•œ์ฒด์ ๋ฒ•(FVM)๋ณด๋‹ค ๋ฏธ์„ธ๊ตฌ์กฐ์˜

Quantitative Biology
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Ocean-E2E: Hybrid Physics-Based and Data-Driven Global Forecasting of Extreme Marine Heatwaves with End-to-End Neural Assimilation

Ocean E2E ํ”„๋ ˆ์ž„์›Œํฌ๋Š” MHW ์˜ˆ์ธก์„ ์œ„ํ•ด ๋ฌผ๋ฆฌ ๊ธฐ๋ฐ˜ ๋ชจ๋ธ๋ง๊ณผ ๋ฐ์ดํ„ฐ ์ฃผ๋„ํ˜• ์ ‘๊ทผ๋ฒ•์„ ๊ฒฐํ•ฉํ•œ ํ˜์‹ ์ ์ธ ๋ฐฉ๋ฒ•๋ก ์„ ์ œ์‹œํ•œ๋‹ค. ํ•ด์–‘ ์ค‘๊ทœ๋ชจ ์ด๋™๊ณผ ๋Œ€๊ธฐ ํ•ด์–‘ ์ƒํ˜ธ์ž‘์šฉ์˜ ํšจ๊ณผ๋ฅผ ๋ช…์‹œ์ ์œผ๋กœ ๊ณ ๋ คํ•จ์œผ๋กœ์จ, ๊ธฐ์กด ์ˆ˜์น˜ ๋ชจ๋ธ์˜ ํ•œ๊ณ„๋ฅผ ๊ทน๋ณตํ•˜๊ณ  ๋ณด๋‹ค ์ •ํ™•ํ•œ ์˜ˆ์ธก์„ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•œ๋‹ค. ๋˜ํ•œ, ์—”๋“œํˆฌ์—”๋“œ ๋ฐ์ดํ„ฐ ๋™ํ™” ๊ธฐ๋ฒ•์„ ํ†ตํ•ด ๋‹ค์–‘ํ•œ ์‹œ๊ฐ„ ์ฒ™๋„์—์„œ MHW์˜ ๋ฐœ์ƒ๊ณผ ๋ฐœ๋‹ฌ ๊ณผ์ •์„ ํฌ์ฐฉํ•  ์ˆ˜ ์žˆ๋‹ค. ์ด ํ”„๋ ˆ์ž„์›Œํฌ๋Š” ํ•ด์–‘ ์ƒํƒœ๊ณ„์˜ ๊ฑด๊ฐ•๊ณผ ๊ธฐํ›„ ๋ณ€ํ™”์— ๋Œ€ํ•œ ์ดํ•ด๋ฅผ ๋†’์ด๋Š” ๋ฐ ๊ธฐ์—ฌํ•˜๋ฉฐ, ํ–ฅํ›„ ๊ธฐํ›„ ๋ชจ๋ธ๋ง ๋ฐ ์˜ˆ๋ณด ๋ถ„์•ผ์—์„œ ์ค‘์š”ํ•œ ๋„๊ตฌ๊ฐ€ ๋  ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€๋œ๋‹ค.

Data
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ODE-GS: Latent ODEs for Dynamic Scene Extrapolation with 3D Gaussian Splatting

ODE GS๋Š” 3D ๊ฐ€์šฐ์‹œ์•ˆ ์Šคํ”Œ๋ž˜ํŒ…๊ณผ ์ž ์žฌ ์‹ ๊ฒฝ ์ƒ๋ฏธ๋ถ„ ๋ฐฉ์ •์‹(ODE)๋ฅผ ํ†ตํ•ฉํ•˜์—ฌ ๋™์  ์žฅ๋ฉด์˜ ๋ฏธ๋ž˜ ์™ธ์‚ฝ์„ ์œ„ํ•œ ํ˜์‹ ์ ์ธ ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•ฉ๋‹ˆ๋‹ค. ์ด ์ ‘๊ทผ๋ฒ•์€ ์‹œ๊ฐ„์— ๋”ฐ๋ผ ๋ณ€ํ™”ํ•˜๋Š” ์žฅ๋ฉด์„ ๋ชจ๋ธ๋งํ•˜๊ณ , ํŠนํžˆ ๊ณ ์ •๋œ ์‹œ๊ฐ„ ์ฐฝ ๋‚ด์—์„œ์˜ ๋ณด๊ฐ„์ด ์•„๋‹Œ ๋ฏธ๋ž˜์˜ ์˜ˆ์ธก์„ ๋ชฉํ‘œ๋กœ ํ•ฉ๋‹ˆ๋‹ค. ODE GS๋Š” ๊ฐ€์šฐ์‹œ์•ˆ ๋งค๊ฐœ๋ณ€์ˆ˜ ๊ถค๋„๋ฅผ ์—ฐ์†์ ์ธ ์ž ์žฌ ์—ญํ•™์œผ๋กœ ๋‹ค๋ฃจ๋ฉฐ, ์ด๋ฅผ ํ†ตํ•ด ํƒ€์ž„ ์Šคํƒฌํ”„ ์˜์กด์„ฑ์„ ์ œ๊ฑฐํ•˜๊ณ  ๋” ๋‚˜์€ ์ผ๋ฐ˜ํ™” ๋Šฅ๋ ฅ์„ ์–ป์Šต๋‹ˆ๋‹ค. ์ด ๋ฐฉ๋ฒ•์€ ๋จผ์ € ๊ด€์ฐฐ๋œ ์‹œ๊ฐ„ ์ฐฝ ๋‚ด์—์„œ ์ •ํ™•ํ•œ ๊ฐ€์šฐ์‹œ์•ˆ ๊ถค๋„๋ฅผ ์ƒ์„ฑํ•˜๋Š” ๋ณด๊ฐ„ ๋ชจ๋ธ์„ ํ•™์Šตํ•ฉ๋‹ˆ๋‹ค. ๊ทธ ํ›„, ๊ณผ๊ฑฐ์˜ ๊ถค๋„๋ฅผ

On analytic properties of entropy rate

On analytic properties of entropy rate

๋ณธ ๋…ผ๋ฌธ์€ ์—”ํŠธ๋กœํ”ผ์œจ์ด๋ผ๋Š” ์ •๋ณดโ€‘์ด๋ก  ํ•ต์‹ฌ๋Ÿ‰์˜ ํ•ด์„์  ๊ตฌ์กฐ๋ฅผ ์ „๋ณ€๋™(totalโ€‘variation, TV) ์œ„์ƒ์ด๋ผ๋Š” ์ž์—ฐ์Šค๋Ÿฌ์šด ์ธก์ • ๊ณต๊ฐ„ ์œ„์—์„œ ํƒ๊ตฌํ•œ๋‹ค๋Š” ์ ์—์„œ ์ด๋ก ์ ยท์‹ค์šฉ์  ์˜๋ฏธ๊ฐ€ ํฌ๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ๋Š” ์ฃผ๋กœ ํŠน์ • ๋ชจ๋ธ(์˜ˆ: ๋งˆ๋ฅด์ฝ”ํ”„ ์ฒด์ธ, ์ผ๋ถ€ ์€๋‹‰ ๋งˆ๋ฅด์ฝ”ํ”„ ๋ชจ๋ธ)์—์„œ ๋‹ซํžŒ ํ˜•ํƒœ์˜ ์—”ํŠธ๋กœํ”ผ์‹์ด ์กด์žฌํ•œ๋‹ค๋Š” ์‚ฌ์‹ค์— ์˜์กดํ–ˆ์œผ๋ฉฐ, ์ผ๋ฐ˜์ ์ธ ์ด์‚ฐ ํ™•๋ฅ ์›์— ๋Œ€ํ•ด์„œ๋Š” ๊ฑฐ์˜ ์•Œ๋ ค์ง„ ๋ฐ”๊ฐ€ ์—†์—ˆ๋‹ค. ์ €์ž๋“ค์€ โ€œ์—”ํŠธ๋กœํ”ผ์œจ์€ ๋‹ซํžŒ ์‹์ด ์—†๋”๋ผ๋„ ์œ„์ƒ์  ์—ฐ์†์„ฑโ€์ด๋ผ๋Š” ์ƒˆ๋กœ์šด ๊ด€์ ์„ ์ œ์‹œํ•จ์œผ๋กœ์จ, ๋ชจ๋ธโ€‘๋น„ํŠน์ •์ ์ธ ๋ณดํŽธ์  ๊ฒฐ๊ณผ๋ฅผ ์–ป๋Š”๋‹ค. ํ•ต์‹ฌ ๊ธฐ๋ฒ• 1. ์ „

Computer Science Information Theory Mathematics
On Constructive Connectives and Systems

On Constructive Connectives and Systems

์ด ๋…ผ๋ฌธ์€ ํ˜„๋Œ€ ๋…ผ๋ฆฌํ•™์—์„œ โ€˜๊ตฌ์„ฑ์ โ€™์ด๋ผ๋Š” ๊ฐœ๋…์„ ๋ณด๋‹ค ์—„๋ฐ€ํžˆ ๊ทœ์ •ํ•˜๊ณ , ๊ทธ ๊ทœ์ •์ด ์˜๋ฏธ๋ก ๊ณผ ์ฆ๋ช… ์ด๋ก  ์‚ฌ์ด์˜ ๋‹ค๋ฆฌ๋ฅผ ๋†“๋Š” ์—ญํ• ์„ ํ•œ๋‹ค๋Š” ์ ์—์„œ ํ•™์ˆ ์  ์˜์˜๊ฐ€ ํฌ๋‹ค. ๋จผ์ € ์ €์ž๋Š” ์ •๊ทœ(regular) ๋‹จ์ผ ๊ฒฐ๋ก  ์‹œํ€€์Šค ์ฒด๊ณ„ ๋ผ๋Š” ํ‹€์„ ์„ค์ •ํ•œ๋‹ค. ์—ฌ๊ธฐ์„œ โ€˜์ •๊ทœโ€™๋Š” ์ ˆ๋‹จ(cut) ๊ทœ์น™์„ ์ œ์™ธํ•œ ๋ชจ๋“  ๊ทœ์น™์ด ๋ถ€๋ถ„์‹(property) ์„ฑ์งˆ ์„ ๋งŒ์กฑํ•œ๋‹ค๋Š” ์˜๋ฏธ์ด๋ฉฐ, ์ด๋Š” ์ „ํ†ต์ ์ธ โ€˜์ ˆ๋‹จ ์ œ๊ฑฐ ๊ฐ€๋Šฅ์„ฑโ€™๊ณผ ์ง์ ‘ ์—ฐ๊ฒฐ๋œ๋‹ค. ์‹œํ€€์Šค์˜ ํ›„์†์ด ๋น„์–ด ์žˆ์„ ์ˆ˜ ์žˆ๋‹ค๋Š” ํ—ˆ์šฉ์€ ๊ธฐ์กด์˜ ๋‹ค์ค‘ ๊ฒฐ๋ก  ์ฒด๊ณ„์™€ ์ฐจ๋ณ„ํ™”๋˜๋Š” ์ ์œผ๋กœ, ๋‹จ์ผ ๊ฒฐ๋ก  ์ฒด๊ณ„๊ฐ€ ๊ฐ–๋Š” ๊ตฌ์กฐ์  ๋‹จ์ˆœ

Computer Science System Logic
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On Finding Similar Items in a Stream of Transactions

๋ณธ ๋…ผ๋ฌธ์€ ์ŠคํŠธ๋ฆฌ๋ฐ ๋ฐ์ดํ„ฐ ๋งˆ์ด๋‹ ๋ถ„์•ผ์—์„œ โ€œ๋นˆ๋„ ํฅ๋ฏธโ€๋ผ๋Š” ์ „ํ†ต์  ๊ฐ€์ •์„ ๊นจ๊ณ , ์‹ค์ œ ๋น„์ฆˆ๋‹ˆ์Šค ํ˜„์žฅ์—์„œ ๋” ์˜๋ฏธ ์žˆ๋Š” ์œ ์‚ฌ๋„ ๊ธฐ๋ฐ˜ ์•„์ดํ…œ ์Œ ํƒ์ƒ‰ ๋ฌธ์ œ์— ์ฒซ ๋ฐœ์„ ๋””๋Ž ๋‹ค. ์ €์ž๋“ค์€ ๋จผ์ € ๊ณต๊ฐ„ ํ•˜ํ•œ ์„ ์ˆ˜ํ•™์ ์œผ๋กœ ์ฆ๋ช…ํ•จ์œผ๋กœ์จ, ๊ธฐ์กด ๋นˆ๋ฒˆ ํ•ญ๋ชฉ ์ง‘ํ•ฉ ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด ์ŠคํŠธ๋ฆผ ํ™˜๊ฒฝ์—์„œ ๊ทผ๋ณธ์ ์ธ ๋ฉ”๋ชจ๋ฆฌ ํ•œ๊ณ„์— ๋ด‰์ฐฉํ•œ๋‹ค๋Š” ์ ์„ ๋ช…ํ™•ํžˆ ์ œ์‹œํ•œ๋‹ค. ํ•˜ํ•œ์‹

Computer Science Data Structures Databases
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On generating functions and automata associated to reflections in Coxeter systems

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋™๊ธฐ 1997๋…„ Stembridge๊ฐ€ ์ œ๊ธฐํ•œ โ€œ๋ฐ˜์‚ฌ์˜ ํฌ์ธ์นด๋ ˆ ๊ธ‰์ˆ˜๊ฐ€ ์œ ๋ฆฌํ•จ์ˆ˜์ธ๊ฐ€?โ€๋ผ๋Š” ์งˆ๋ฌธ์€ ๋ฌดํ•œ ์ฝ”์‹œํ„ฐ ๊ตฐ์—์„œ ๋ถ€๋ถ„์ง‘ํ•ฉ์˜ ์„ฑ์žฅ๋ฅ ์„ ์ดํ•ดํ•˜๋Š” ํ•ต์‹ฌ ๋ฌธ์ œ์ด๋‹ค. ๊ธฐ์กด ํ•ด๋‹ต์€ de Man(1999)์ด Brinkโ€‘Howlett ์ž๋™๊ธฐ๋ฅผ ์ด์šฉํ•ด ์–ป์—ˆ์ง€๋งŒ, ์ƒํƒœ ์ˆ˜๊ฐ€ ๊ธ‰๊ฒฉํžˆ ๋Š˜์–ด๋‚˜ ์‹ค์šฉ์„ฑ์ด ๋–จ์–ด์กŒ๋‹ค. ๋˜ํ•œ ํšŒ๋ฌธ ๊ฐ์†Œ์–ด ์–ธ์–ด๊ฐ€ ์ •๊ทœ์ธ์ง€ ์—ฌ๋ถ€๋Š” ์ž๋™ํ™” ์ด๋ก ์—์„œ โ€œ์ •๊ทœ ์–ธ์–ด โ†’ ํšŒ๋ฌธ ์ œํ•œ โ†’ ์ปจํ…์ŠคํŠธ ์ž์œ โ€๋ผ๋Š” ์ผ๋ฐ˜์ ์ธ ๋น„์ •๊ทœ์„ฑ ๊ฒฐ๊ณผ์™€ ์ถฉ๋Œํ•  ๊ฐ€๋Šฅ์„ฑ์ด ์žˆ์–ด ํฅ๋ฏธ๋กœ์šด ์งˆ๋ฌธ์ด๋‹ค. 2. ํ•ต์‹ฌ ๊ฐœ๋… โ€“ ๋ฐ˜์‚ฌโ€‘ํ”„๋ฆฌํ”ฝ์Šค ๋ฐ˜์‚ฌ (t)

System Mathematics
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On saturated triangulation-free convex geometric graphs

1. ๋ฌธ์ œ ์„ค์ •์˜ ์ƒˆ๋กœ์›€ ๊ธฐ์กด ์—ฐ๊ตฌ๋Š” โ€œ๊ฐ€๋Šฅํ•œ ๊ฐ€์žฅ ๋งŽ์€ ๊ฐ„์„ โ€์„ ์ฐพ๋Š” extremal ๋ฌธ์ œ์— ์ง‘์ค‘ํ–ˆ์ง€๋งŒ, ๋ณธ ๋…ผ๋ฌธ์€ โ€œํฌํ™”โ€๋ผ๋Š” ๊ฐœ๋…์„ ๋„์ž…ํ•ด ๊ทน์†Œยท๊ทน๋Œ€ ์‚ฌ์ด์˜ ๊ตฌ์กฐ ๋ฅผ ํƒ๊ตฌํ•œ๋‹ค. ์ด๋Š” ๊ทธ๋ž˜ํ”„ ์ด๋ก ์—์„œ โ€œsaturationโ€์ด ๋…๋ฆฝ ์ง‘ํ•ฉ, ๋งค์นญ, ํด๋ฆฌํฌ ๋“ฑ์— ์ ์šฉ๋œ ์ „ํ†ต์ ์ธ ์ ‘๊ทผ๊ณผ ์œ ์‚ฌํ•˜์ง€๋งŒ, ๊ธฐํ•˜ํ•™์  ์ œ์•ฝ(๋ณผ๋ก ๋‹ค๊ฐํ˜•์˜ ๋Œ€๊ฐ์„ )๊ณผ triangulationโ€‘free ์กฐ๊ฑด์ด ๊ฒฐํ•ฉ๋œ ๋…ํŠนํ•œ ์‚ฌ๋ก€๋‹ค. 2. ๊ตฌ์„ฑ ๋ฐฉ๋ฒ• ๋ฐ ์ฆ๋ช… ๊ธฐ๋ฒ• O(n log n) ํฌํ™” ๊ทธ๋ž˜ํ”„ : ์ €์ž๋“ค์€ ์žฌ๊ท€์  ๋ถ„ํ•  ๊ณผ ๋กœ๊ทธโ€‘๊นŠ์ด ํŠธ๋ฆฌ ๊ตฌ์กฐ๋ฅผ ์ด์šฉํ•ด, ๊ฐ ๋‹จ๊ณ„์—์„œ

On the algebraic cobordism spectra MSL and MSp

On the algebraic cobordism spectra MSL and MSp

์ด ์—ฐ๊ตฌ๋Š” Voevodsky๊ฐ€ ๋„์ž…ํ•œ ๋Œ€์ˆ˜์  ์ฝ”๋ณด๋ฅด๋””์ฆ˜ ์ŠคํŽ™ํŠธ๋Ÿผ (MGL)์„ ๊ธฐ๋ฐ˜์œผ๋กœ, ํŠน์ˆ˜์„ ํ˜•๊ตฐ (SL)๊ณผ ์‹ฌํ”Œ๋ ‰ํ‹ฑ๊ตฐ (Sp)์— ๋Œ€์‘ํ•˜๋Š” ๋‘ ์ƒˆ๋กœ์šด ์ŠคํŽ™ํŠธ๋Ÿผ (MSL)๊ณผ (MSp)์„ ์ฒด๊ณ„์ ์œผ๋กœ ๊ตฌ์ถ•ํ•œ๋‹ค๋Š” ์ ์—์„œ ์˜๋ฏธ๊ฐ€ ํฌ๋‹ค. ๋จผ์ € ์ €์ž๋“ค์€ (BSL {n})์™€ (MSL {n})์— ๋Œ€ํ•œ (GL {n}) ์ž‘์šฉ์„ ๊ณ ๋ คํ•˜๋ฉด์„œ, ๋ถ€๋ถ„๋‹ค๋ฐœ์˜ ์ง์ ‘ํ•ฉ์— ์˜ํ•ด ์œ ๋„๋˜๋Š” ๋ชจ๋…ธ์ด๋“œ ๊ตฌ์กฐ์™€์˜ ํ˜ธํ™˜์„ฑ์„ ํ™•๋ณดํ•œ๋‹ค. ์—ฌ๊ธฐ์„œ ํ•ต์‹ฌ์€ (GL {n}) ์ž‘์šฉ์ด ๊ณ ์ •์ ์„ ๊ฐ–์ง€ ์•Š์Œ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ , (Sigma {n}subset Sp

Mathematics
On the approximation ability of evolutionary optimization with   application to minimum set cover

On the approximation ability of evolutionary optimization with application to minimum set cover

๋ณธ ๋…ผ๋ฌธ์€ ์ง„ํ™” ์•Œ๊ณ ๋ฆฌ์ฆ˜(EA)์˜ ๊ทผ์‚ฌ ๋Šฅ๋ ฅ ์ด๋ผ๋Š” ๋น„๊ต์  ๋ฏธ๊ฐœ์ฒ™ ์˜์—ญ์„ ์ฒด๊ณ„์ ์œผ๋กœ ํƒ๊ตฌํ•œ๋‹ค๋Š” ์ ์—์„œ ํ•™์ˆ ์  ์˜์˜๊ฐ€ ํฌ๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ๋“ค์€ ์ฃผ๋กœ EA๊ฐ€ ์ตœ์  ํ•ด์— ๋„๋‹ฌํ•˜๋Š” ๋ฐ ํ•„์š”ํ•œ ์‹œ๊ฐ„ ๋ณต์žก๋„์— ์ดˆ์ ์„ ๋งž์ถ”์—ˆ์œผ๋ฉฐ, ์‹ค์ œ ์‘์šฉ์—์„œ๋Š” โ€œ์ถฉ๋ถ„ํžˆ ์ข‹์€โ€ ํ•ด๋ฅผ ๋น ๋ฅด๊ฒŒ ์–ป๋Š” ๊ฒƒ์ด ๋” ์ค‘์š”ํ•จ์„ ๊ฐ„๊ณผํ–ˆ๋‹ค. ์ €์ž๋“ค์€ ์ด๋ฅผ ๋ณด์™„ํ•˜๊ธฐ ์œ„ํ•ด ๊ฒฉ๋ฆฌ๋œ ์ง‘๋‹จ์„ ๊ฐ–๋Š” ๋‹จ์ˆœ ์ง„ํ™” ์•Œ๊ณ ๋ฆฌ์ฆ˜(SEIP) ๋ผ๋Š” ์ƒˆ๋กœ์šด ํ”„๋ ˆ์ž„์›Œํฌ๋ฅผ ๋„์ž…ํ•œ๋‹ค. SEIP์€ ๊ฒฉ๋ฆฌ ํ•จ์ˆ˜(isolation function) ๋ฅผ ํ†ตํ•ด ํ•ด๋“ค ๊ฐ„์˜ ๊ฒฝ์Ÿ์„ ์กฐ์ ˆํ•จ์œผ๋กœ์จ, ๋™์ผํ•œ ์•Œ๊ณ ๋ฆฌ์ฆ˜ ๊ตฌ์กฐ ์•ˆ์—์„œ ๋‹จ

Computer Science Neural Computing
On the Connectivity and Multihop Delay of Ad Hoc Cognitive Radio   Networks

On the Connectivity and Multihop Delay of Ad Hoc Cognitive Radio Networks

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋ฌธ์ œ ์ •์˜ ์ธ์ง€ ๋ผ๋””์˜ค ๋„คํŠธ์›Œํฌ๋Š” 1์ฐจ ์‚ฌ์šฉ์ž์˜ ์ŠคํŽ™ํŠธ๋Ÿผ์„ ๋™์ ์œผ๋กœ ๊ณต์œ ํ•จ์œผ๋กœ์จ ์ŠคํŽ™ํŠธ๋Ÿผ ํšจ์œจ์„ ๋†’์ด์ง€๋งŒ, 2์ฐจ ์‚ฌ์šฉ์ž๋Š” 1์ฐจ ํŠธ๋ž˜ํ”ฝ์˜ ์‹œ๊ณต๊ฐ„์  ๋ณ€๋™์— ๋”ฐ๋ผ ๋งํฌ๊ฐ€ ๋Š๊ธฐ๊ฑฐ๋‚˜ ์žฌ์ƒ์„ฑ๋˜๋Š” ๋™์  ํ† ํด๋กœ์ง€ ๋ฅผ ๊ฐ–๋Š”๋‹ค. ๊ธฐ์กด์˜ ๋™์งˆ( homogeneous) adโ€‘hoc ๋„คํŠธ์›Œํฌ ์ด๋ก ์€ ์ด๋Ÿฌํ•œ ๋™์  ์ŠคํŽ™ํŠธ๋Ÿผ ์ œ์•ฝ์„ ๋ฐ˜์˜ํ•˜์ง€ ๋ชปํ•œ๋‹ค. ๋”ฐ๋ผ์„œ ์ €์ž๋“ค์€ โ€œ์—ฐ๊ฒฐ์„ฑโ€์„ ๋‹จ์ˆœํžˆ ๊ทธ๋ž˜ํ”„๊ฐ€ ํ•˜๋‚˜์˜ ๋ฌดํ•œ ์—ฐ๊ฒฐ ์„ฑ๋ถ„์„ ๊ฐ–๋Š”์ง€ ์—ฌ๋ถ€๊ฐ€ ์•„๋‹ˆ๋ผ, ๋‘ ์ž„์˜์˜ 2์ฐจ ์‚ฌ์šฉ์ž ์‚ฌ์ด์— ์œ ํ•œํ•œ ์ตœ์†Œ ๋‹ค์ค‘ ํ™‰ ์ง€์—ฐ(MMD)์ด ์กด์žฌํ•˜๋Š”๊ฐ€ ๋กœ ์ •์˜ํ•จ์œผ๋กœ์จ, ์ง€์—ฐ

Computer Science Network Networking
On the origin of variable gamma-ray emission from the Crab Nebula

On the origin of variable gamma-ray emission from the Crab Nebula

๋ณธ ๋…ผ๋ฌธ์€ ํฌ๋ž˜๋ธŒ ์„ฑ์šด์—์„œ ๊ด€์ธก๋˜๋Š” ๊ธ‰๊ฒฉํ•œ ๊ฐ๋งˆ์„  ํ”Œ๋ ˆ์–ด์˜ ๋ฌผ๋ฆฌ์  ๊ทผ์›์„ โ€˜๋‚ด๋ถ€ ๋งค๋“ญโ€™์ด๋ผ๋Š” ๋ฏธ์„ธ ๊ตฌ์กฐ์™€ ์—ฐ๊ฒฐ์ง“๋Š” ์ƒˆ๋กœ์šด ํ•ด์„์„ ์ œ์‹œํ•œ๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ์—์„œ๋Š” ํŽ„์„œ ํ’์ด ํ˜•์„ฑํ•˜๋Š” ์ข…๋‹จ ์ถฉ๊ฒฉ๋ฉด์—์„œ์˜ ํ™•์‚ฐ ์ถฉ๊ฒฉ ๊ฐ€์†, 2์ฐจ ํŽ˜๋ฅด๋ฏธ ๊ฐ€์†, ํ˜น์€ ์ž๊ธฐ ์žฌ๊ฒฐํ•ฉ ๋“ฑ ์—ฌ๋Ÿฌ ๊ฐ€์† ๋ฉ”์ปค๋‹ˆ์ฆ˜์ด ์ œ์•ˆ๋˜์—ˆ์ง€๋งŒ, ์‹ค์ œ ๊ฐ€์† ์œ„์น˜๋ฅผ ์ง์ ‘ ํ™•์ธํ•˜๊ธฐ๋Š” ์–ด๋ ค์› ๋‹ค. ์ €์ž๋“ค์€ ์ตœ์‹  3์ฐจ์› ์ƒ๋Œ€๋ก ์  MHD ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ์ด์šฉํ•ด ์ถฉ๊ฒฉ๋ฉด์ด ๋น„์ •๋ฐฉํ–ฅ(Oblique) ํ˜•ํƒœ๋ฅผ ๋ ๋ฉฐ, ์ด๋กœ ์ธํ•ด ๋ฐฉ์ถœ์ด ๊ด€์ธก์ž ๋ฐฉํ–ฅ์œผ๋กœ ๊ฐ•ํ•˜๊ฒŒ ํŽธํ–ฅ๋˜๋Š” ๋„ํ”Œ๋Ÿฌ ๋น„๋ฐ ํšจ๊ณผ๊ฐ€ ๋ฐœ์ƒํ•œ๋‹ค๋Š” ์ ์„ ์ •๋Ÿ‰์ ์œผ๋กœ ์ž…

Physics Astrophysics
On Three Alternative Characterizations of Combined Traces

On Three Alternative Characterizations of Combined Traces

๋ณธ ์—ฐ๊ตฌ๋Š” โ€˜๊ฒฐํ•ฉ ์ถ”์ (comtrace)โ€™์ด๋ผ๋Š” ๋น„๊ต์  ์ƒˆ๋กญ๊ณ  ์•„์ง ์ถฉ๋ถ„ํžˆ ์ •๋ฆฝ๋˜์ง€ ์•Š์€ ๊ฐœ๋…์„ ์„ธ ๊ฐ€์ง€ ์„œ๋กœ ๋‹ค๋ฅธ ์ˆ˜ํ•™์  ๊ตฌ์กฐ์™€ ๋™๋“ฑํ•˜๊ฒŒ ์—ฐ๊ฒฐํ•จ์œผ๋กœ์จ, ๋™์‹œ์„ฑ ์ด๋ก  ์ „๋ฐ˜์— ๊ฑธ์นœ ํ†ตํ•ฉ์  ์ดํ•ด๋ฅผ ์‹œ๋„ํ•œ๋‹ค. ์ฒซ ๋ฒˆ์งธ๋กœ, comtrace ๋ชซ๊ตฐ ์€ ๋‹จ๊ณ„ ์„œ์—ด์„ ๋ฌธ์ž์—ด์ฒ˜๋Ÿผ ๋‹ค๋ฃจ๋ฉด์„œ ๋™์‹œ์„ฑยท์ง๋ ฌํ™” ๊ด€๊ณ„์— ์˜ํ•ด ์ •์˜๋œ ๋™์น˜ ๊ด€๊ณ„๋ฅผ ๋ชซ์œผ๋กœ ์ทจํ•˜๋Š” ๋Œ€์ˆ˜์  ๊ตฌ์กฐ์ด๋‹ค. ์ด ์ ‘๊ทผ๋ฒ•์€ ๊ธฐ์กด Mazurkiewicz ์ถ”์  ์ด๋ก ์—์„œ ์‚ฌ์šฉ๋˜๋Š” โ€˜๋™๋“ฑ๋ฅ˜โ€™๋ฅผ ๊ทธ๋Œ€๋กœ ์ฐจ์šฉํ•˜์ง€๋งŒ, ๋‹จ๊ณ„๋ผ๋Š” ๋” ํฐ ์›์ž ๋‹จ์œ„๋ฅผ ํ—ˆ์šฉํ•จ์œผ๋กœ์จ ๋™์‹œ ์‹คํ–‰์„ ์ž์—ฐ์Šค๋Ÿฝ๊ฒŒ ํฌ์ฐฉํ•œ๋‹ค. ๋‘ ๋ฒˆ์งธ๋กœ,

Computer Science Formal Languages Distributed Computing
No Image

One-factorizations of complete multipartite graphs with distance constraints

| ๊ตฌ๋ถ„ | ๋‚ด์šฉ | | | | | ์—ฐ๊ตฌ ๋™๊ธฐ | ์„ค๊ณ„ ์ด๋ก ๊ณผ ์ฝ”๋”ฉ ์ด๋ก  ์‚ฌ์ด์˜ ๊ต์ฐจ์ ์—์„œ, ํŠนํžˆ ์ƒ์ˆ˜ ๊ฐ€์ค‘์น˜ ์ฝ”๋“œ ์™€ ๊ทธ๋ž˜ํ”„ ์ผ์ธ์žํ™” ๋ฅผ ์—ฐ๊ฒฐํ•จ์œผ๋กœ์จ ์ƒˆ๋กœ์šด ์ตœ์  ์ฝ”๋“œ ๊ตฌ์กฐ๋ฅผ ์ฐพ๊ณ ์ž ํ•จ. ๊ฑฐ๋ฆฌ 3์€ (๊ฐ€์ค‘์น˜ 2, ์•ŒํŒŒ๋ฒณ ํฌ๊ธฐ (q g+1)) ์ฝ”๋“œ์—์„œ ๊ฐ€์žฅ ํฅ๋ฏธ๋กœ์šด ๋น„ํŠธโ€‘์ „์†ก ํšจ์œจ์„ ์ œ๊ณตํ•œ๋‹ค. | | ํ•ต์‹ฌ ์ •์˜ | ARโ€‘graph : ํ‰ํ–‰(edgeโ€‘parallel) ์—†์ด ์ตœ๋Œ€ํ•œ ๋งŽ์€ 1โ€‘์ •๊ทœ(๋˜๋Š” ๊ฑฐ์˜ 1โ€‘์ •๊ทœ) ์„œ๋ธŒ๊ทธ๋ž˜ํ”„. <br> ODAR(n,g) : (nle g)์ผ ๋•Œ ๊ฑฐ๋ฆฌ 3 ์„œ๋ธŒ๊ทธ๋ž˜ํ”„๋ฅผ (g^{2})๊ฐœ๋กœ ๋ถ„ํ•ดํ•˜

Mathematics
Online Expectation-Maximisation

Online Expectation-Maximisation

๋ณธ ์žฅ์€ ์˜จ๋ผ์ธ EM ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ด๋ก ์ ยท์‹ค์šฉ์  ๊ด€์ ์—์„œ ์ฒด๊ณ„์ ์œผ๋กœ ์ •๋ฆฌํ•œ๋‹ค. ๋จผ์ € โ€œonlineโ€์ด๋ผ๋Š” ํ˜•์šฉ์‚ฌ์˜ ์˜๋ฏธ๋ฅผ ๋ช…ํ™•ํžˆ ๊ตฌ๋ถ„ํ•œ๋‹ค. ๋จธ์‹ ๋Ÿฌ๋‹ ๋ถ„์•ผ์—์„œ ํ”ํžˆ ์“ฐ์ด๋Š” ์˜จ๋ผ์ธ ํ•™์Šต์€ ๊ด€์ธก์น˜๋ฅผ ์ˆœ์ฐจ์ ์œผ๋กœ ๋„์ž…ํ•˜๋ฉด์„œ ์ผ๋ฐ˜ํ™” ์˜ค์ฐจ๋ฅผ ๋ถ„์„ํ•˜๋Š” ๋ฐฉ๋ฒ•๋ก ์„ ๊ฐ€๋ฆฌํ‚ค์ง€๋งŒ, ์—ฌ๊ธฐ์„œ๋Š” ๋ฐ์ดํ„ฐ ์ €์žฅ ์—†์ด ์‹ค์‹œ๊ฐ„์œผ๋กœ ํŒŒ๋ผ๋ฏธํ„ฐ๋ฅผ ๊ฐฑ์‹ ํ•˜๋Š” ์ „ํ†ต์ ์ธ ํ†ต๊ณ„ ์ถ”์ • ๋ฐฉ์‹์„ ๋งํ•œ๋‹ค. ์ด๋Š” ์‹ ํ˜ธ ์ฒ˜๋ฆฌยท์ œ์–ด ๋ถ„์•ผ์—์„œ โ€œadaptiveโ€ ํ˜น์€ โ€œrecursiveโ€ ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด๋ผ ๋ถˆ๋ฆฌ๋Š” ์ ‘๊ทผ๊ณผ ๋™์ผ์„ ์ƒ์— ์žˆ๋‹ค. ์ €์ž๋Š” โ€œrecursiveโ€๋ผ๋Š” ์šฉ์–ด๊ฐ€ ์ปดํ“จํ„ฐ ๊ณผํ•™์—์„œ ๊ด‘๋ฒ”์œ„ํ•˜๊ฒŒ

Statistics

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