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An introduction to L{e}vy processes with applications in finance

An introduction to L{e}vy processes with applications in finance

์ด ๊ฐ•์˜๋…ธํŠธ๋Š” ๋ ˆ๋น„ ๊ณผ์ •์„ ์ฒ˜์Œ ์ ‘ํ•˜๋Š” ๋…์ž๋ฅผ ๋Œ€์ƒ์œผ๋กœ ํ•˜๋ฉด์„œ๋„, ๊ธˆ์œต ๋ถ„์•ผ์—์„œ์˜ ์‹ค์šฉ์  ํ™œ์šฉ๊นŒ์ง€ ์•„์šฐ๋ฅด๋Š” ๊ท ํ˜• ์žกํžŒ ๊ตฌ์„ฑ์„ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. ์ฒซ ๋ฒˆ์งธ ํŒŒํŠธ์—์„œ ๋ ˆ๋น„ ์ ํ”„โ€‘ํ™•์‚ฐ ๊ณผ์ •์„ โ€˜์žฅ๋‚œ๊ฐโ€™ ์˜ˆ์‹œ๋กœ ์‚ผ์•„, ๋ณต์žกํ•œ ๋ ˆ๋น„ ๊ณผ์ •์˜ ํ•ต์‹ฌ ๊ตฌ์กฐ๋ฅผ ๋‹จ์ˆœํ™”ํ•œ๋‹ค๋Š” ์ ‘๊ทผ์€ ํ•™์Šต ํšจ์œจ์„ ํฌ๊ฒŒ ๋†’์ธ๋‹ค. ๋ฌดํ•œ ๊ฐ€๋ถ„์„ฑ์—์„œ ๋ ˆ๋น„โ€‘ํ‚จ์น˜ํ‚ค ๊ณต์‹๊นŒ์ง€ ํ๋ฆ„์„ ์ž์—ฐ์Šค๋Ÿฝ๊ฒŒ ์—ฐ๊ฒฐํ•จ์œผ๋กœ์จ, ๋…์ž๋Š” ํ™•๋ฅ ๋ถ„ํฌ์™€ ํ™•๋ฅ ๊ณผ์ • ์‚ฌ์ด์˜ ๊นŠ์€ ์—ฐ๊ด€์„ฑ์„ ์ง๊ด€์ ์œผ๋กœ ํŒŒ์•…ํ•  ์ˆ˜ ์žˆ๋‹ค. ํŠนํžˆ ๋ ˆ๋น„โ€‘์ดํ†  ๋ถ„ํ•ด์™€ ๋ ˆ๋น„ ์ธก๋„์˜ ์—ญํ• ์„ ์ƒ์„ธํžˆ ์„ค๋ช…ํ•˜๋ฉด์„œ, ๊ฒฝ๋กœ ํŠน์„ฑ(์ ํ”„ ๋นˆ๋„, ํฌ๊ธฐ)๊ณผ ๋ชจ๋ฉ˜ํŠธ ๊ตฌ์กฐ

Mathematics Quantitative Finance
Bus Trajectory-Based Street-Centric Routing for Message Delivery in   Urban Vehicular Ad hoc Networks

Bus Trajectory-Based Street-Centric Routing for Message Delivery in Urban Vehicular Ad hoc Networks

๋ณธ ์—ฐ๊ตฌ๋Š” VANET ํ™˜๊ฒฝ์—์„œ ๊ธฐ์กด ๋…ธ๋“œโ€‘์ค‘์‹ฌ ๋ผ์šฐํŒ…์ด ๊ฐ–๋Š” ํ•œ๊ณ„๋ฅผ ๋ช…ํ™•ํžˆ ์งš์–ด๋‚ธ ๋’ค, ๊ฑฐ๋ฆฌโ€‘์ค‘์‹ฌ ์ด๋ผ๋Š” ์ƒˆ๋กœ์šด ํŒจ๋Ÿฌ๋‹ค์ž„์„ ์ œ์‹œํ•œ๋‹ค๋Š” ์ ์—์„œ ํ•™์ˆ ์ ยท์‹ค์šฉ์  ์˜์˜๊ฐ€ ํฌ๋‹ค. ์ฒซ์งธ, ๋ฒ„์Šค๋ผ๋Š” ๊ธฐ์กด ๊ตํ†ต ์ธํ”„๋ผ๋ฅผ ๊ณ ์ • ๊ถค์  ์ด๋ผ๋Š” ํ™•์‹คํ•œ ๊ณต๊ฐ„์  ํŠน์„ฑ์œผ๋กœ ๋ชจ๋ธ๋งํ•œ๋‹ค๋Š” ์ ‘๊ทผ์€, ์ฐจ๋Ÿ‰๋“ค์˜ ๋ถˆ๊ทœ์น™ํ•˜๊ณ  ์˜ˆ์ธก ๋ถˆ๊ฐ€๋Šฅํ•œ ์›€์ง์ž„์œผ๋กœ ์ธํ•œ ํ† ํด๋กœ์ง€ ๋ณ€๋™์„ฑ์„ ํฌ๊ฒŒ ์™„ํ™”ํ•œ๋‹ค. ๋ฒ„์Šค๋Š” ์ผ์ •ํ•œ ์‹œ๊ฐ„ ๊ฐ„๊ฒฉ์œผ๋กœ ๋™์ผํ•œ ๋…ธ์„ ์„ ์ˆœํšŒํ•˜๋ฏ€๋กœ, ํŠน์ • ๋„๋กœ ๊ตฌ๊ฐ„์—์„œ ๋ฒ„์Šค๊ฐ€ ๋“ฑ์žฅํ•  ํ™•๋ฅ ์„ ์‚ฌ์ „์— ๊ณ„์‚ฐํ•  ์ˆ˜ ์žˆ๋‹ค. ๋…ผ๋ฌธ์€ ์ด๋ฅผ ๊ฑฐ๋ฆฌ ์ผ๊ด€์„ฑ ํ™•๋ฅ (PSC) ๋กœ ์ •์˜ํ•˜๊ณ , ๋„๋กœโ€‘๋ ˆ๋ฒจ

Cryptography and Security Computer Science Networking Network Electrical Engineering and Systems Science
Cause Clue Clauses: Error Localization using Maximum Satisfiability

Cause Clue Clauses: Error Localization using Maximum Satisfiability

์ด ๋…ผ๋ฌธ์€ ๋””๋ฒ„๊น… ๊ณผ์ •์—์„œ โ€œ์‹คํŒจ ํŠธ๋ ˆ์ด์Šค โ†’ ์›์ธ ์ฝ”๋“œโ€๋ผ๋Š” ์ „ํ†ต์ ์ธ ์ธ๊ณผ ๊ด€๊ณ„๋ฅผ ํ˜•์‹์ ์œผ๋กœ ๋ชจ๋ธ๋งํ•œ ์ ์ด ๊ฐ€์žฅ ํฐ ํ˜์‹ ์ด๋‹ค. ๊ธฐ์กด์˜ ๋™์  ๋ถ„์„ ๊ธฐ๋ฒ•์€ ํ”ํžˆ ์‹คํ–‰ ๊ฒฝ๋กœ๋ฅผ ๊ทธ๋Œ€๋กœ ๋”ฐ๋ผ๊ฐ€๋ฉฐ ํžˆํŠธ ์นด์šดํŠธ๋‚˜ ์Šฌ๋ผ์ด์Šค๋ฅผ ์ด์šฉํ•ด ํ›„๋ณด ์˜์—ญ์„ ์ขํžˆ์ง€๋งŒ, ์‹ค์ œ๋กœ ์–ด๋А ๋ฌธ์žฅ์„ ์ˆ˜์ •ํ•ด์•ผ ํŠธ๋ ˆ์ด์Šค ์ž์ฒด๊ฐ€ ๋ถˆ๊ฐ€๋Šฅํ•ด์ง€๋Š”์ง€๋ฅผ ์ •๋Ÿ‰์ ์œผ๋กœ ํŒ๋‹จํ•˜๊ธฐ๋Š” ์–ด๋ ค์› ๋‹ค. ์ €์ž๋“ค์€ ์ด๋ฅผ MAXโ€‘SAT ๋ผ๋Š” ์ตœ์ ํ™” ๋ฌธ์ œ์— ๋งคํ•‘ํ•จ์œผ๋กœ์จ, โ€œ๊ฐ€๋Šฅํ•œ ํ•œ ๋งŽ์€ ์‹คํ–‰ ์กฐ๊ฑด์„ ์œ ์ง€ํ•˜๋ฉด์„œ(soft ์ ˆ) ๋ฐ˜๋“œ์‹œ ๋งŒ์กฑํ•ด์•ผ ํ•˜๋Š” ์ œ์•ฝ( hard ์ ˆ)โ€์„ ๋™์‹œ์— ๊ณ ๋ คํ•œ๋‹ค. ๊ตฌํ˜„์ƒ์˜ ํ•ต์‹ฌ์€ ์‹ฌ

Programming Languages Computer Science Software Engineering
Core Collapse Supernovae using CHIMERA: Gravitational Radiation from   Non-Rotating Progenitors

Core Collapse Supernovae using CHIMERA: Gravitational Radiation from Non-Rotating Progenitors

๋ณธ ๋…ผ๋ฌธ์€ CHIMERA ์ฝ”๋“œ๊ฐ€ ์ œ๊ณตํ•˜๋Š” ๊ณ ํ•ด์ƒ๋„ ๋‹ค๋ฌผ๋ฆฌ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ํ™œ์šฉํ•ด, ๋น„ํšŒ์ „ ์ „๊ตฌ์ฒด๊ฐ€ ํ•ต ๋ถ•๊ดด ํ›„ ๋ฐฉ์ถœํ•˜๋Š” ์ค‘๋ ฅํŒŒ์˜ ์‹œ๊ฐ„ยท์ฃผํŒŒ์ˆ˜ ํŠน์„ฑ์„ ์ฒด๊ณ„์ ์œผ๋กœ ๊ทœ๋ช…ํ•œ ์ ์—์„œ ํฐ ์˜๋ฏธ๋ฅผ ๊ฐ€์ง„๋‹ค. ์ฒซ ๋ฒˆ์งธ๋กœ, ๋„ค ๋‹จ๊ณ„๋กœ ๊ตฌ๋ถ„๋œ ํŒŒํ˜• ๊ตฌ์กฐ๋Š” CCSN ๋‚ด๋ถ€์—์„œ ์ผ์–ด๋‚˜๋Š” ๋ฌผ๋ฆฌ์  ๊ณผ์ •๋“ค์„ ์ง์ ‘์ ์œผ๋กœ โ€˜์ฒญ๊ฐํ™”โ€™ํ•œ๋‹ค๋Š” ์ ์—์„œ ํ˜์‹ ์ ์ด๋‹ค. ์ฆ‰์‹œ ๋ฐœ์ƒ ๋‹จ๊ณ„๋Š” PNS ๋‚ด๋ถ€์˜ ๊ณ ์ฃผํŒŒ ์ง„๋™๊ณผ ์ถฉ๊ฒฉํŒŒ ์ „ํŒŒ์— ์˜ํ•œ ์ €์ฃผํŒŒ ๋ณ€์กฐ๊ฐ€ ๋™์‹œ์— ๋‚˜ํƒ€๋‚˜๋Š” ๋ณตํ•ฉ ์‹ ํ˜ธ๋กœ, ์ด์ „ ์—ฐ๊ตฌ๊ฐ€ PNS ๋Œ€๋ฅ˜๋งŒ์„ ์›์ธ์œผ๋กœ ์ œ์‹œํ–ˆ๋˜ ํ•ด์„์„ ํ™•์žฅํ•œ๋‹ค. ์ด๋Š” ํ•ต ๋ฐ˜๋™ ์งํ›„ ๋ฌผ์งˆ์ด ๊ธ‰๊ฒฉํžˆ ์žฌ๋ฐฐ์—ด

Astrophysics
DNA Probabilities in People v. Prince: When are racial and ethnic   statistics relevant?

DNA Probabilities in People v. Prince: When are racial and ethnic statistics relevant?

๋ณธ ๋…ผ๋ฌธ์€ DNA ์ฆ๊ฑฐ์˜ ํ†ต๊ณ„์  ํ•ด์„์ด ๋ฒ•์ •์—์„œ ์–ด๋–ป๊ฒŒ ์˜ค์šฉ๋  ์ˆ˜ ์žˆ๋Š”์ง€๋ฅผ ์‹ฌ๋„ ์žˆ๊ฒŒ ํƒ๊ตฌํ•œ๋‹ค. ๋จผ์ € ์ €์ž๋Š” DNA ์ผ์น˜์˜ ์„ค๋“๋ ฅ์„ ํ‰๊ฐ€ํ•  ๋•Œ โ€˜๊ฐ€๋Šฅ๋„ ๋น„(likelihood ratio)โ€™๊ฐ€ ๊ฐ€์žฅ ์ ์ ˆํ•œ ์ง€ํ‘œ์ž„์„ ๊ฐ•์กฐํ•œ๋‹ค. ๊ฐ€๋Šฅ๋„ ๋น„๋Š” โ€œํ”ผ๊ณ ์™€ ์ผ์น˜ํ•˜๋Š” DNA๊ฐ€ ์‹ค์ œ ๋ฒ”์ธ์˜ DNA์ผ ํ™•๋ฅ โ€๊ณผ โ€œ๋ฌด๊ด€ํ•œ ์ œ3์ž๊ฐ€ ์šฐ์—ฐํžˆ ๋™์ผ ํ”„๋กœํŒŒ์ผ์„ ๊ฐ€์งˆ ํ™•๋ฅ โ€์„ ๋น„๊ตํ•จ์œผ๋กœ์จ, ๋‹จ์ˆœํžˆ ์ ˆ๋Œ€ ํ™•๋ฅ ์„ ์ œ์‹œํ•˜๋Š” ๊ฒƒ๋ณด๋‹ค ๋ฐฐ์‹ฌ์›์—๊ฒŒ ์ง๊ด€์ ์ธ ํŒ๋‹จ ๊ทผ๊ฑฐ๋ฅผ ์ œ๊ณตํ•œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ํ˜„์žฌ ๋ฏธ๊ตญ ๋ฒ•์›์—์„œ ํ”ํžˆ ์‚ฌ์šฉ๋˜๋Š” โ€˜์ธ์ข…ยท๋ฏผ์กฑ๋ณ„ ๋ฌด์ž‘์œ„ ์ผ์น˜ ํ™•๋ฅ โ€™์€ ์‹ค์ œ ์‚ฌ๊ฑด๊ณผ ๋ฌด๊ด€ํ•œ

Statistics Applications
Edge Preserving Image Denoising in Reproducing Kernel Hilbert Spaces

Edge Preserving Image Denoising in Reproducing Kernel Hilbert Spaces

๋ณธ ์—ฐ๊ตฌ๋Š” ์ด๋ฏธ์ง€ ๋””๋…ธ์ด์ง• ๋ถ„์•ผ์—์„œ ์˜ค๋ž˜๋œ ๊ณผ์ œ์ธ โ€œ์—์ง€ ๋ณด์กดโ€ ๋ฌธ์ œ๋ฅผ ์ปค๋„ ๋ฐฉ๋ฒ•๋ก ์ด๋ผ๋Š” ํ˜„๋Œ€์  ๋„๊ตฌ๋กœ ์ ‘๊ทผํ•œ๋‹ค๋Š” ์ ์—์„œ ์˜๋ฏธ๊ฐ€ ํฌ๋‹ค. ๊ธฐ์กด์˜ ์›จ์ด๋ธŒ๋ฆฟ ๊ธฐ๋ฐ˜ ๊ธฐ๋ฒ•์€ ๋‹ค์ค‘ ํ•ด์ƒ๋„ ๋ถ„์„์„ ํ†ตํ•ด ์žก์Œ์„ ์–ต์ œํ•˜์ง€๋งŒ, ๊ณ ์ฃผํŒŒ ์„ฑ๋ถ„(์ฆ‰, ์—์ง€)์„ ๋™์‹œ์— ์–ต์ œํ•˜๋Š” ๋ถ€์ž‘์šฉ์ด ์žˆ๋‹ค. ์ €์ž๋Š” RKHS๋ผ๋Š” ๋ฌดํ•œ ์ฐจ์›์˜ ํ•จ์ˆ˜ ๊ณต๊ฐ„์„ ์ด์šฉํ•ด ๋น„์„ ํ˜• ๋ณ€ํ™˜์„ ์ž์—ฐ์Šค๋Ÿฝ๊ฒŒ ์ˆ˜ํ–‰ํ•˜๋ฉด์„œ๋„, Representer ์ •๋ฆฌ๋ฅผ ํ†ตํ•ด ์ตœ์ ํ™” ํ•ด๋ฅผ ์œ ํ•œ ๊ฐœ์˜ ์ปค๋„ ํ•จ์ˆ˜๋“ค์˜ ์„ ํ˜• ๊ฒฐํ•ฉ ํ˜•ํƒœ๋กœ ์ถ•์†Œํ•œ๋‹ค. ์ด๋Š” ๊ณ„์‚ฐ ๋ณต์žก๋„๋ฅผ ํฌ๊ฒŒ ๋‚ฎ์ถ”๋ฉด์„œ๋„ ์ด๋ก ์  ์ตœ์ ์„ฑ์„ ์œ ์ง€ํ•  ์ˆ˜ ์žˆ๋Š” ๊ฐ•์ ์ด๋‹ค.

Computer Vision Computer Science
Excitation of acoustic waves by vortices in the quiet Sun

Excitation of acoustic waves by vortices in the quiet Sun

๋ณธ ๋…ผ๋ฌธ์€ ํƒœ์–‘ ํ‘œ๋ฉด ๊ทผ์ฒ˜์—์„œ ๊ด€์ธก๋˜๋Š” 5๋ถ„ ์ง„๋™(ํƒœ์–‘์˜ pโ€‘๋ชจ๋“œ)์˜ ๋ฏธ์„ธ ๋ฐœ์ƒ ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ๊ตฌ์ฒด์ ์œผ๋กœ ๋ฐํžˆ๋ ค๋Š” ์‹œ๋„๋กœ, ๊ธฐ์กด์˜ โ€˜์ „๋‹จโ€‘์••๋ ฅ ๋ณ€๋™โ€™ ์ค‘์‹ฌ ์ด๋ก ์„ ๋ณด์™„ํ•œ๋‹ค. ์ €์ž๋“ค์€ ์ตœ์‹  3์ฐจ์› ๋ณต์‚ฌโ€‘MHD ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ์ฝ”๋“œ โ€œSolarBoxโ€(A. Wray ๊ฐœ๋ฐœ)๋ฅผ ํ™œ์šฉํ•ด, ์‹ค์ œ ๊ด€์ธก๊ณผ ์ผ์น˜ํ•˜๋„๋ก ๊ณ ํ•ด์ƒ๋„(์ˆ˜๋ฐฑ ํ‚ฌ๋กœ๋ฏธํ„ฐ ์ˆ˜์ค€) ๊ฒฉ์ž๋ฅผ ์ ์šฉํ•˜์˜€๋‹ค. ํŠนํžˆ, ๋Œ€๊ทœ๋ชจ ์™€๋ฅ˜(Largeโ€‘Eddy) ๋ชจ๋ธ๋ง์„ ๋„์ž…ํ•จ์œผ๋กœ์จ, ์†Œ์šฉ๋Œ์ด ํŠœ๋ธŒ๊ฐ€ ํ˜•์„ฑยท์†Œ๋ฉธํ•˜๋Š” ์„œ๋ธŒ๊ทธ๋ฆฌ๋“œ ํ˜„์ƒ์„ ๋ฌผ๋ฆฌ์ ์œผ๋กœ ์žฌํ˜„ํ–ˆ๋‹ค๋Š” ์ ์ด ์ฃผ๋ชฉํ•  ๋งŒํ•˜๋‹ค. ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ฒฐ๊ณผ๋Š” ๋‘ ๊ฐ€์ง€ ํ•ต์‹ฌ์ ์ธ

Astrophysics Physics
Geographic constraints on social network groups

Geographic constraints on social network groups

๋ณธ ๋…ผ๋ฌธ์€ ๋ชจ๋ฐ”์ผ ํ†ต์‹  ๊ธฐ๋ก์ด๋ผ๋Š” ์‹ค์‹œ๊ฐ„ยท๋Œ€๊ทœ๋ชจ ์œ„์น˜ ๋ฐ์ดํ„ฐ๋ฅผ ํ™œ์šฉํ•ด ์‚ฌํšŒ ๋„คํŠธ์›Œํฌ ๋‚ด ์ปค๋ฎค๋‹ˆํ‹ฐ์˜ ์ง€๋ฆฌ์  ํŠน์„ฑ์„ ์ตœ์ดˆ๋กœ ์ •๋Ÿ‰์ ์œผ๋กœ ํƒ๊ตฌํ•œ ์ ์—์„œ ํ•™๋ฌธ์  ์˜์˜๊ฐ€ ํฌ๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ๋“ค์€ ์ฃผ๋กœ ์„ค๋ฌธยท๋ธ”๋กœ๊ทธ ํ”„๋กœํ•„ ๋“ฑ ์ž๋ฐœ์  ๋ณด๊ณ ์— ์˜์กดํ–ˆ์œผ๋ฉฐ, ๊ฑฐ๋ฆฌ์™€ ์นœ๋ฐ€๋„ ์‚ฌ์ด์˜ ๊ฐ์†Œ ๊ด€๊ณ„๋ฅผ ์ œ์‹œํ–ˆ์ง€๋งŒ, ์‹ค์ œ ํ†ต์‹  ์œ„์น˜์™€ ๋„คํŠธ์›Œํฌ ์œ„์ƒ์ด ๋™์‹œ์— ๊ณ ๋ ค๋œ ๋ถ„์„์€ ๋“œ๋ฌผ์—ˆ๋‹ค. ์ €์ž๋“ค์€ โ€˜๊ฐ€์žฅ ๋งŽ์ด ์ด์šฉํ•œ ๊ธฐ์ง€๊ตญโ€™์„ ๊ฐœ์ธ์˜ ์ฃผ์š” ๊ฑฐ์ฃผยทํ™œ๋™์ง€์ ์œผ๋กœ ๊ฐ€์ •ํ•จ์œผ๋กœ์จ, ๊ฐœ์ธ๋ณ„ ์ง€๋ฆฌ์  ์ค‘์‹ฌ์„ ํ•ฉ๋ฆฌ์ ์œผ๋กœ ์ถ”์ •ํ•˜์˜€๋‹ค. ์ด๋Š” ํ†ต์‹  ๊ธฐ๋ก์ด ์ผ์ƒ ์ƒํ™œ ์ „๋ฐ˜์— ๊ฑธ์ณ ์ง€์†์ ์œผ๋กœ ๋ฐœ์ƒํ•œ๋‹ค

Condensed Matter Computer Science Social Networks Physics Network
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

Machine Learning Statistics Computer Science
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,

Distributed Computing Computer Science Formal Languages
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
p-Norm Flow Optimization in a Network

p-Norm Flow Optimization in a Network

๋ณธ ์—ฐ๊ตฌ๋Š” ๋„คํŠธ์›Œํฌ ํ๋ฆ„ ์ตœ์ ํ™” ๋ฌธ์ œ๋ฅผ ์„ ํ˜• ๋ณด์กด ์ œ์•ฝ์‹๊ณผ ๋น„์„ ํ˜• ๋น„์šฉ ํ•จ์ˆ˜์˜ ๊ฒฐํ•ฉ ํ˜•ํƒœ๋กœ ์ •ํ˜•ํ™”ํ•œ ์ ์—์„œ ์ด๋ก ์  ์˜์˜๊ฐ€ ํฌ๋‹ค. ํŠนํžˆ, ๋ชจ๋“  ํŠธ๋ž˜ํ”ฝ์ด ๋‹จ์ผ ๋ชฉ์ ์ง€๋กœ ์ง‘์ค‘๋œ singleโ€‘commodity ๋ชจ๋ธ์„ ์ฑ„ํƒํ•จ์œผ๋กœ์จ ์ตœ์†Œ ์ปท์…‹ ์ด๋ก ๊ณผ ์ง์ ‘ ์—ฐ๊ฒฐ์‹œ์ผฐ๋‹ค. ์ตœ์†Œ ์ปท์…‹์€ ๋„คํŠธ์›Œํฌ ์ „์ฒด ์ฒ˜๋ฆฌ๋Ÿ‰์˜ ์ƒํ•œ์„ ๊ฒฐ์ •ํ•˜๋Š” ํ•ต์‹ฌ ๊ฐœ๋…์ด๋ฉฐ, ๋…ผ๋ฌธ์€ ์ด ์ƒํ•œ์„ ์‹ค์ œ ๋ผ์šฐํŒ… ์ •์ฑ…์— ๋ฐ˜์˜ํ•˜๋ ค๋Š” ์‹œ๋„๋ฅผ ๋ณด์ธ๋‹ค. ํ–‰๋ ฌ (C) ์˜ ๊ตฌ์„ฑ์€ ๊ฐ ๊ฐ„์„ ์— ๋ถ€์—ฌ๋œ ๋ฐฉํ–ฅ์— ๋”ฐ๋ผ ( 1,0,+1) ๋กœ ํ‘œ์‹œ๋˜๋ฉฐ, ์ด๋Š” ์ „ํ†ต์ ์ธ ํ๋ฆ„ ๋ณด์กด ๋ฐฉ์ •์‹๊ณผ ๋™์ผํ•˜์ง€๋งŒ, ์ธ๋ฑ์Šค

Networking Network Computer Science
Risk Factors Associated with Mortality in Game of Thrones: A   Longitudinal Cohort Study

Risk Factors Associated with Mortality in Game of Thrones: A Longitudinal Cohort Study

๋ณธ ์—ฐ๊ตฌ๋Š” ๊ฐ€์ƒ์˜ ํ…”๋ ˆ๋น„์ „ ๋“œ๋ผ๋งˆ๋ฅผ ์—ญํ•™์  ๊ด€์ ์—์„œ ๋ถ„์„ํ•œ ๋…ํŠนํ•œ ์‹œ๋„์ด๋‹ค. ์ฝ”ํ˜ธํŠธ ์ •์˜๋Š” โ€œ์ฒซ ํšŒ ๋ฐฉ์˜ ์ดํ›„ ํ™”๋ฉด ์‹œ๊ฐ„ 5๋ถ„ ์ด์ƒโ€์ด๋ผ๋Š” ๊ฐ๊ด€์  ๊ธฐ์ค€์„ ๋‘์–ด, ์ฃผ์š” ๋“ฑ์žฅ์ธ๋ฌผ์„ ํฌ๊ด„ํ•˜๋ ค๋Š” ์˜๋„๊ฐ€ ์—ฟ๋ณด์ธ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ด ๊ธฐ์ค€์€ ํ™”๋ฉด ์‹œ๊ฐ„์— ๋”ฐ๋ผ ์ธ๋ฌผ ์„ ํƒ์ด ํŽธํ–ฅ๋  ๊ฐ€๋Šฅ์„ฑ์„ ๋‚ดํฌํ•œ๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด, ์ดˆ๊ธฐ ์‹œ์ฆŒ์— ์งง๊ฒŒ ๋“ฑ์žฅํ–ˆ์ง€๋งŒ ํ›„๋ฐ˜์— ์ค‘์š”ํ•œ ์—ญํ• ์„ ๋งก์€ ์ธ๋ฌผ์€ ์ œ์™ธ๋  ์ˆ˜ ์žˆ๋‹ค. ๋˜ํ•œ โ€œ5๋ถ„ ์ด์ƒโ€์ด๋ผ๋Š” ์ ˆ๋Œ€๊ฐ’์€ ์‹œ์ฆŒ๋งˆ๋‹ค ์—ํ”ผ์†Œ๋“œ ๊ธธ์ด์™€ ํŽธ์ง‘ ๋ฐฉ์‹์ด ๋‹ค๋ฅด๋ฏ€๋กœ, ์‹ค์ œ โ€˜๋…ธ์ถœโ€™ ์ •๋„๋ฅผ ์ •ํ™•ํžˆ ๋ฐ˜์˜ํ•˜์ง€ ๋ชปํ•œ๋‹ค๋Š” ํ•œ๊ณ„๊ฐ€ ์žˆ๋‹ค. ์—ฐ๊ตฌ๋Š” ์ „์ฒด 132๋ช…

Statistics
Robustness of Probabilistic Models to Low-Quality Data: A Multi-Perspective Analysis

Robustness of Probabilistic Models to Low-Quality Data: A Multi-Perspective Analysis

๋ณธ ๋…ผ๋ฌธ์€ ์ €ํ’ˆ์งˆ ๋ฐ์ดํ„ฐ๊ฐ€ ๋‹ค์–‘ํ•œ ๋ชจ๋ธ์˜ ๊ฒฌ๊ณ ์„ฑ์— ๋ฏธ์น˜๋Š” ์ฐจ๋ณ„์ ์ธ ์˜ํ–ฅ์„ ์ฒด๊ณ„์ ์œผ๋กœ ์กฐ์‚ฌํ•˜๊ณ  ๋ถ„์„ํ•œ ์—ฐ๊ตฌ์ด๋‹ค. ํŠนํžˆ, ์ž๋™ํšŒ๊ท€ ์–ธ์–ด ๋ชจ๋ธ๊ณผ ํด๋ž˜์Šค ์กฐ๊ฑด ํ™•์‚ฐ ๋ชจ๋ธ, ๊ทธ๋ฆฌ๊ณ  ๋ถ„๋ฅ˜๊ธฐ ๊ฐ„์˜ ์„ฑ๋Šฅ ์ฐจ์ด๋ฅผ ๊ฐ•์กฐํ•œ๋‹ค. GPT 2์™€ ๊ฐ™์€ ์ž๋™ํšŒ๊ท€ ์–ธ์–ด ๋ชจ๋ธ์€ ํ† ํฐ ์˜ค์—ผ๋ฅ ์ด 50%์— ๋‹ฌํ•˜๋”๋ผ๋„ ๊ฒฌ๊ณ ์„ฑ์„ ์œ ์ง€ํ•˜๋ฉฐ, ์ด๋Š” ํ•ด๋‹น ๋ชจ๋ธ๋“ค์ด ์ €ํ’ˆ์งˆ ๋ฐ์ดํ„ฐ์—์„œ๋„ ๋›ฐ์–ด๋‚œ ์„ฑ๋Šฅ์„ ๋ฐœํœ˜ํ•  ์ˆ˜ ์žˆ๋Š” ๊ฐ•๊ฑด์„ฑ์˜ ํ•œ ์˜ˆ์‹œ๋ฅผ ๋ณด์—ฌ์ค€๋‹ค. ๋ฐ˜๋ฉด, ํด๋ž˜์Šค ์กฐ๊ฑด ํ™•์‚ฐ ๋ชจ๋ธ์€ ๊ฐ™์€ ์ •๋„์˜ ์˜ค์—ผ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ์žฌ์•™์ ์ธ ์„ฑ๋Šฅ ์ €ํ•˜๋ฅผ ๊ฒฝํ—˜ํ•œ๋‹ค. ์ด๋Š” ์ด๋ฏธ์ง€ ๋ ˆ์ด๋ธ” ์ผ๊ด€์„ฑ์ด ๊ธฐ์ค€์น˜ ๋Œ€๋น„

Model Data Analysis
Role of line-of-sight cosmic ray interactions in forming the spectra of   distant blazars in TeV gamma rays and high-energy neutrinos

Role of line-of-sight cosmic ray interactions in forming the spectra of distant blazars in TeV gamma rays and high-energy neutrinos

์ด ๋…ผ๋ฌธ์€ ์›๊ฑฐ๋ฆฌ ๋ธ”๋ ˆ์ด์ €์—์„œ ๊ด€์ธก๋˜๋Š” TeV ๊ฐ๋งˆ์„  ์ŠคํŽ™ํŠธ๋Ÿผ์ด ์ „ํ†ต์ ์ธ โ€œ1์ฐจ ๊ฐ๋งˆ์„  + EBL ํก์ˆ˜โ€ ์‹œ๋‚˜๋ฆฌ์˜ค๋งŒ์œผ๋กœ๋Š” ์„ค๋ช…๋˜์ง€ ์•Š๋Š”๋‹ค๋Š” ๋ฌธ์ œ์ ์„ ์ถœ๋ฐœ์ ์œผ๋กœ ์‚ผ๋Š”๋‹ค. ๊ธฐ์กด ๋ชจ๋ธ์€ ๊ฐ๋งˆ์„ ์ด ์€ํ•˜๊ฐ„ ๊ณต๊ฐ„์„ ํ†ต๊ณผํ•˜๋ฉด์„œ EBL์™€์˜ ์Œ์ƒ์„ฑ์— ์˜ํ•ด ๊ธ‰๊ฒฉํžˆ ๊ฐ์‡ ๋˜๋ฉฐ, ํŠนํžˆ 1 TeV ๊ทผ์ฒ˜์—์„œ ๋šœ๋ ทํ•œ ์ปท์˜คํ”„๊ฐ€ ๋‚˜ํƒ€๋‚˜์•ผ ํ•œ๋‹ค๊ณ  ์˜ˆ์ธกํ•œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์‹ค์ œ ๊ด€์ธก๋œ ์ŠคํŽ™ํŠธ๋Ÿผ์€ ์ด๋Ÿฌํ•œ ์ปท์˜คํ”„๊ฐ€ ๊ฑฐ์˜ ๋ณด์ด์ง€ ์•Š์œผ๋ฉฐ, ์ด๋Š” ๋‘ ๊ฐ€์ง€ ํ•ด์„(EBL๊ฐ€ ๋งค์šฐ ๋‚ฎ๋‹ค, ํ˜น์€ ์†Œ์Šค๊ฐ€ ๋น„์ •์ƒ์ ์œผ๋กœ ๊ฐ•๊ฒฝํ•œ ๋‚ด์žฌ ์ŠคํŽ™ํŠธ๋Ÿผ์„ ๊ฐ€์ง„๋‹ค)์œผ๋กœ๋งŒ ์„ค๋ช…ํ•˜๋ ค ํ•˜๋ฉด ๋ฌผ๋ฆฌ์ ์œผ๋กœ ๋น„ํ˜„์‹ค์ ์ธ ๊ฐ€์ •

Astrophysics HEP-PH
Semantic Distance Measurement based on Multi-Kernel Gaussian Processes

Semantic Distance Measurement based on Multi-Kernel Gaussian Processes

์ด ๋…ผ๋ฌธ์€ ์˜๋ฏธ ๊ฑฐ๋ฆฌ ์ธก์ •์„ ์œ„ํ•œ ์ƒˆ๋กœ์šด ์ ‘๊ทผ๋ฒ•์„ ์ œ์‹œํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ๊ธฐ์กด์˜ ๊ณ ์ •์ ์ธ ์˜๋ฏธ ๊ฑฐ๋ฆฌ ์ธก์ • ๋ฐฉ๋ฒ•๋“ค์ด ํŠน์ • ๋ฐ์ดํ„ฐ ๋ถ„ํฌ๋‚˜ ์ž‘์—… ์š”๊ตฌ์‚ฌํ•ญ์— ์ ์‘ํ•˜๊ธฐ ์–ด๋ ต๋‹ค๋Š” ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด, ๋‹ค์ค‘ ์ปค๋„ ๊ฐ€์šฐ์‹œ์•ˆ ํ”„๋กœ์„ธ์Šค(MK GP)๋ฅผ ํ™œ์šฉํ•œ ์ƒˆ๋กœ์šด ๋ฐฉ๋ฒ•๋ก ์„ ์ œ์•ˆํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์ด ์ ‘๊ทผ๋ฒ•์€ ํ…์ŠคํŠธ์™€ ์—ฐ๊ด€๋œ ์ž ์žฌ์  ์˜๋ฏธ ํ•จ์ˆ˜๋ฅผ ๊ฐ€์šฐ์‹œ์•ˆ ํ”„๋กœ์„ธ์Šค๋กœ ๋ชจ๋ธ๋งํ•˜๋ฉฐ, ์ด๋ฅผ ํ†ตํ•ด ๋ฐ์ดํ„ฐ๋กœ๋ถ€ํ„ฐ ์ž๋™์œผ๋กœ ํ•™์Šต๋˜๋Š” ์ปค๋„ ํŒŒ๋ผ๋ฏธํ„ฐ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ๋” ์œ ์—ฐํ•œ ์ธก์ •์„ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•ฉ๋‹ˆ๋‹ค. ํŠนํžˆ, Matรฉrn ์ปค๋„๊ณผ ๋‹คํ•ญ์‹ ์š”์†Œ๋ฅผ ๊ฒฐํ•ฉํ•œ ๋ณตํ•ฉ ์ปค๋„์„ ์‚ฌ์šฉํ•จ์œผ๋กœ์จ ๋‹ค์–‘ํ•œ

Sentiment Analysis of Code-Mixed Languages leveraging Resource Rich   Languages

Sentiment Analysis of Code-Mixed Languages leveraging Resource Rich Languages

๋ณธ ์—ฐ๊ตฌ๋Š” ์ฝ”๋“œโ€‘๋ฏน์Šค ํ…์ŠคํŠธ ๊ฐ์„ฑ ๋ถ„์„์ด๋ผ๋Š” ์•„์ง ์ถฉ๋ถ„ํžˆ ํƒ๊ตฌ๋˜์ง€ ์•Š์€ ๋ถ„์•ผ์— ๋Œ€์กฐ ํ•™์Šต์ด๋ผ๋Š” ์ตœ์‹  ๊ธฐ๋ฒ•์„ ์ ์šฉํ•จ์œผ๋กœ์จ ๋‘ ๊ฐ€์ง€ ์ฃผ์š” ํ˜์‹ ์„ ์ œ์‹œํ•œ๋‹ค. ์ฒซ์งธ, ํŒŒ๋ผ๋ฏธํ„ฐ ๊ณต์œ  ์Œ๋‘ฅ์ด Biโ€‘LSTM ์„ ์ด์šฉํ•ด ๋‘ ๋ฌธ์žฅ์„ ๋™์‹œ์— ์ธ์ฝ”๋”ฉํ•˜๊ณ , ์ด๋“ค์˜ ์ถœ๋ ฅ ๋ฒกํ„ฐ ๊ฐ„ ์œ ์‚ฌ๋„๋ฅผ ์—๋„ˆ์ง€ ๊ธฐ๋ฐ˜ ์†์‹ค ํ•จ์ˆ˜๋กœ ์ตœ์†Œํ™”ํ•œ๋‹ค๋Š” ์„ค๊ณ„๋Š”, ๋™์ผ ๊ฐ์„ฑ์„ ๊ฐ€์ง„ ๋ฌธ์žฅ์€ ๊ฐ์„ฑ ๊ณต๊ฐ„์—์„œ ๊ฐ€๊น๊ฒŒ, ๋‹ค๋ฅธ ๊ฐ์„ฑ์„ ๊ฐ€์ง„ ๋ฌธ์žฅ์€ ๋ฉ€๋ฆฌ ๋ฐฐ์น˜๋˜๋„๋ก ๊ฐ•์ œํ•œ๋‹ค. ์ด๋Š” ๊ธฐ์กด์˜ ๋‹จ์ผ ๋„คํŠธ์›Œํฌ ๊ธฐ๋ฐ˜ ๋ถ„๋ฅ˜๊ธฐ์™€ ๋‹ฌ๋ฆฌ ๊ฐ์„ฑ ๊ฐ„ ์ƒ๋Œ€์  ๊ฑฐ๋ฆฌ ๋ฅผ ๋ช…์‹œ์ ์œผ๋กœ ํ•™์Šตํ•˜๊ฒŒ ํ•˜์—ฌ, ๋ผ๋ฒจ์ด ์ œํ•œ์ ์ธ ์ƒํ™ฉ์—์„œ๋„

NLP Computer Science Analysis
The communication complexity of non-signaling distributions

The communication complexity of non-signaling distributions

๋ณธ ๋…ผ๋ฌธ์€ ํ†ต์‹  ๋ณต์žก๋„ ์ด๋ก ๊ณผ ์–‘์ž ์ •๋ณด ์ด๋ก  ์‚ฌ์ด์˜ ๊ต์ฐจ์ ์„ ์ฒด๊ณ„์ ์œผ๋กœ ํƒ๊ตฌํ•œ๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ๋Š” ์ฃผ๋กœ ํŠน์ • ๋ฌธ์ œ(์˜ˆ: XOR ๊ฒŒ์ž„, ๋ถˆ๋ฆฌ์–ธ ํ•จ์ˆ˜) ํ˜น์€ ํŠน์ • ๋ชจ๋ธ(์˜ˆ: ํ•œ ๋ฒˆ์˜ ๋ผ์šด๋“œ, ๊ณต์œ  ์–ฝํž˜)์—์„œ ๊ฐœ๋ณ„์ ์ธ ํ•˜ํ•œ์„ ์ œ์‹œํ•ด ์™”์œผ๋ฉฐ, ๊ฐ๊ฐ์˜ ๊ธฐ๋ฒ•์ด ์„œ๋กœ ๋‹ค๋ฅธ ์ˆ˜ํ•™์  ๋„๊ตฌ(์˜ˆ: Fourier ๋ถ„์„, ์ •๋ณด ์ด๋ก ์  ๋ถˆ๊ท ํ˜•)์™€ ์—ฐ๊ฒฐ๋ผ ์žˆ์—ˆ๋‹ค. ์ €์ž๋“ค์€ ์ด๋Ÿฌํ•œ ํŒŒํŽธํ™”๋œ ๊ฒฐ๊ณผ๋“ค์„ ํ•˜๋‚˜์˜ ํ†ตํ•ฉ ํ”„๋ ˆ์ž„์›Œํฌ ์•ˆ์œผ๋กœ ๋Œ์–ด๋“ค์ธ๋‹ค. ํ•ต์‹ฌ์€ โ€œaffine ์กฐํ•ฉโ€์ด๋ผ๋Š” ๊ฐœ๋…์ด๋‹ค. ์ €์ž๋“ค์€ ๋ณต์žก๋„๊ฐ€ ๋‚ฎ์€ ๊ธฐ๋ณธ ๋ถ„ํฌ๋“ค์˜ ์„ ํ˜•(์ •ํ™•ํžˆ๋Š” affine) ๊ฒฐํ•ฉ์„ ํ†ตํ•ด

Computer Science Quantum Physics Computational Complexity
VIGIL: A Reflective Runtime for Self-Healing Agents

VIGIL: A Reflective Runtime for Self-Healing Agents

V.I.G.I.L์€ ๊ธฐ์กด ์—์ด์ „ํŠธํ˜• LLM ์‹œ์Šคํ…œ์ด ์•ˆ๊ณ  ์žˆ๋Š” ๊ทผ๋ณธ์ ์ธ ์•ฝ์ ์„ ์ฒด๊ณ„์ ์œผ๋กœ ๋ณด์™„ํ•œ๋‹ค๋Š” ์ ์—์„œ ํ•™์ˆ ์ ยท์‹ค์šฉ์  ์˜๋ฏธ๊ฐ€ ํฌ๋‹ค. ์ฒซ์งธ, ๋Œ€๋ถ€๋ถ„์˜ ํ˜„์žฌ ์—์ด์ „ํŠธ๋Š” โ€œLLMโ€‘driven scriptโ€ ์ˆ˜์ค€์— ๋จธ๋ฌผ๋Ÿฌ, ํ”„๋กฌํ”„ํŠธ์™€ ๋„๊ตฌ ํ˜ธ์ถœ์„ ์ผ๊ด€์„ฑ ์—†์ด ์กฐํ•ฉํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ๊ตฌ์กฐ๋Š” ๋Ÿฐํƒ€์ž„ ์˜ค๋ฅ˜๊ฐ€ ๋ฐœ์ƒํ–ˆ์„ ๋•Œ ์›์ธ ์ถ”์ ์ด ๊ฑฐ์˜ ๋ถˆ๊ฐ€๋Šฅํ•˜๊ณ , ์ธ๊ฐ„ ๊ฐœ์ž… ์—†์ด๋Š” ์ž์ฒด ๋ณต๊ตฌ๊ฐ€ ์ด๋ฃจ์–ด์ง€์ง€ ์•Š๋Š”๋‹ค. VIGIL์€ ํ˜•์ œ ์—์ด์ „ํŠธ์˜ ๋ชจ๋“  ํ–‰๋™์„ ๋กœ๊ทธ ํ˜•ํƒœ๋กœ ๊ธฐ๋กํ•˜๊ณ , ์ด๋ฅผ ๊ฐ์ •ํ™”(emotional representation)ํ•œ๋‹ค๋Š” ๋…ํŠนํ•œ ์ ‘๊ทผ์„ ์ฑ„ํƒํ•œ

Breather continuation from infinity in nonlinear oscillator chains

Breather continuation from infinity in nonlinear oscillator chains

์ด ๋…ผ๋ฌธ์€ ๋น„์„ ํ˜• ๊ฒฉ์ž ์‹œ์Šคํ…œ์—์„œ โ€˜๋ธŒ๋ฆฌํ„ฐ(breather)โ€™๋ผ ๋ถˆ๋ฆฌ๋Š” ๊ตญ์†Œํ™”๋œ ์‹œ๊ฐ„์ฃผ๊ธฐ ํ•ด์˜ ์กด์žฌ์™€ ์—ฐ์†์„ฑ์„ ๋‹ค๋ฃจ๋Š” ์ด๋ก  ๋ฌผ๋ฆฌํ•™ยท์ˆ˜ํ•™ ๋ถ„์•ผ์˜ ์ค‘์š”ํ•œ ์ง„์ „์„ ์ œ์‹œํ•œ๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ์—์„œ๋Š” ์ฃผ๋กœ ๊ฒฐํ•ฉ์ด ์™„์ „ํžˆ ์ฐจ๋‹จ๋œ (gamma 0) ์ƒํƒœ์—์„œ ๊ฐœ๋ณ„ ์ง„๋™์ž์˜ ๊ณ ๋ฆฝ๋œ ์ฃผ๊ธฐํ•ด๋ฅผ ์ฐพ์•„, ์ด๋ฅผ ์ž‘์€ ๊ฒฐํ•ฉ (gamma>0)์œผ๋กœ ์—ฐ์†์‹œํ‚ค๋Š” โ€˜๋ฐ˜์—ฐ์†๊ทนํ•œ(antiโ€‘continuum)โ€™ ๊ธฐ๋ฒ•์„ ์‚ฌ์šฉํ•ด ์™”๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ด ๋ฐฉ๋ฒ•์€ ํฌํ…์…œ์ด ๊ฐ–๋Š” ์ „์—ญ์ ์ธ ๊ตฌ์กฐ, ํŠนํžˆ ๋ฌดํ•œ๋Œ€๋กœ ๋ป—์€ ์šฐ๋ฌผ์ด๋‚˜ ์žฅ๋ฒฝ ์œ„์—์„œ์˜ ์ง„๋™์„ ์ถฉ๋ถ„ํžˆ ํฌ์ฐฉํ•˜์ง€ ๋ชปํ•œ๋‹ค๋Š” ํ•œ๊ณ„๊ฐ€ ์žˆ๋‹ค.

Nonlinear Sciences Mathematics
Transport in networks with multiple sources and sinks

Transport in networks with multiple sources and sinks

์ด ๋…ผ๋ฌธ์€ ๋ณต์ˆ˜์˜ ์ถœ๋ฐœ์ ๊ณผ ๋„์ฐฉ์ ์ด ๋™์‹œ์— ํ™œ์„ฑํ™”๋˜๋Š” ์ƒํ™ฉ์„ ๋„คํŠธ์›Œํฌ ์ „์†ก ์ด๋ก ์— ์ •์‹์œผ๋กœ ๋„์ž…ํ•จ์œผ๋กœ์จ, ๊ธฐ์กด ์—ฐ๊ตฌ๊ฐ€ ์ฃผ๋กœ ๋‹ค๋ฃจ๋˜ ๋‹จ์ผ ์Œ ์ „์†ก ๋ชจ๋ธ์„ ํ™•์žฅํ•œ๋‹ค๋Š” ์ ์—์„œ ํ•™๋ฌธ์  ์˜์˜๊ฐ€ ํฌ๋‹ค. ์ €์ž๋“ค์€ ๋จผ์ € ์ „๋ฅ˜์™€ ํ๋ฆ„์ด๋ผ๋Š” ๋‘ ๊ฐ€์ง€ ์ „ํ˜•์ ์ธ ์ „์†ก ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ๊ตฌ๋ถ„ํ•œ๋‹ค. ์ „๋ฅ˜๋Š” ๊ฐ ๋งํฌ๊ฐ€ ๋‹จ์œ„ ์ €ํ•ญ์„ ๊ฐ–๋Š” ์ „๊ธฐ ํšŒ๋กœ ๋ชจ๋ธ์— ๊ธฐ๋ฐ˜ํ•ด ๊ฒฝ๋กœ ๊ธธ์ด์— ๋น„๋ก€ํ•œ ์†์‹ค์„ ํฌํ•จํ•˜๊ณ , ํ๋ฆ„์€ ๋ชจ๋“  ๋งํฌ๊ฐ€ ๋‹จ์œ„ ์šฉ๋Ÿ‰์„ ๊ฐ–๋Š” ์ตœ๋Œ€ ํ๋ฆ„(maxโ€‘flow) ๋ฌธ์ œ์™€ ๋™๋“ฑํ•˜๊ฒŒ ์ •์˜ํ•œ๋‹ค. ์ด ๋‘ ๋ชจ๋ธ์„ ๋™์ผํ•œ ๋„คํŠธ์›Œํฌ ๊ตฌ์กฐ์— ์ ์šฉํ•จ์œผ๋กœ์จ, โ€œ๋ณ‘๋ชฉ ํ˜„์ƒโ€์ด๋ผ๋Š” ๊ณตํ†ต๋œ

Network Computer Science Condensed Matter Discrete Mathematics
GDP growth rate and population

GDP growth rate and population

์ด ๋…ผ๋ฌธ์€ โ€œGDP ์„ฑ์žฅ ๊ฒฝ์ œ์  ์ถ”์„ธ + ์ธ๊ตฌ ์—ฐ๋ นํ•ญโ€์ด๋ผ๋Š” ๊ฐ„๊ฒฐํ•œ ์ˆ˜์‹์œผ๋กœ ๊ฑฐ์‹œ๊ฒฝ์ œ ์„ฑ์žฅ ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ์žฌ๊ตฌ์„ฑํ•œ๋‹ค๋Š” ์ ์—์„œ ํ˜์‹ ์ ์ด๋‹ค. ๊ธฐ์กด ์„ฑ์žฅ ์ด๋ก ์€ ๊ธฐ์ˆ ์ง„๋ณด, ์ž๋ณธ์ถ•์ , ์ธ์ ์ž๋ณธ ๋“ฑ ๋‹ค์ˆ˜์˜ ์š”์ธ์„ ๋ณตํ•ฉ์ ์œผ๋กœ ๊ณ ๋ คํ•˜์ง€๋งŒ, ์ €์ž๋Š” ์‹ค์งˆ 1์ธ๋‹น GDP ๋ณ€๋™์„ ์˜ค์ง ๋‘ ๋ณ€์ˆ˜โ€”(T {cr})์™€ 9์„ธ ์ธ๊ตฌ ๋ณ€ํ™”์œจโ€”๋กœ ์ถ•์†Œํ•œ๋‹ค. ์ฒซ ๋ฒˆ์งธ ํ•ญ์ธ (T {cr}^{ 1})๋Š” ํ‰๊ท  ์†Œ๋“ ์„ฑ์žฅ ๊ธฐ๊ฐ„์˜ ์—ญ์ˆ˜๋กœ, ์ด๋Š” ๊ฐœ์ธ์ด ๊ฒฝ๋ ฅ ์ดˆ๊ธฐ์— ๊ธ‰๊ฒฉํžˆ ์†Œ๋“์„ ๋Š˜๋ฆฌ๋‹ค๊ฐ€ ์ ์ฐจ ์„ฑ์žฅ ์†๋„๊ฐ€ ์™„๋งŒํ•ด์ง€๋Š” ํ˜„์ƒ์„ ์ˆ˜ํ•™์ ์œผ๋กœ ํฌ์ฐฉํ•œ๋‹ค. (T {cr})๊ฐ€ ์‹ค์งˆ 1

Physics Quantitative Finance
Arxiv 2512.23731

Arxiv 2512.23731

๋ณธ ๋…ผ๋ฌธ์€ ์ง€๊ตฌ ๋‚ด๋ถ€์˜ ํƒ„์„ฑ ์ง„๋™์ด ๋Œ€๊ธฐ์™€ ์ง์ ‘์ ์ธ ํ”ผ๋“œ๋ฐฑ ๋ฃจํ”„๋ฅผ ํ˜•์„ฑํ•œ๋‹ค๋Š” ํš๊ธฐ์ ์ธ ๊ฐ€์„ค์„ ์ œ์‹œํ•œ๋‹ค. ๊ธฐ์กด ๊ธฐํ›„ ๋ชจ๋ธ์€ ํƒœ์–‘ ๋ณต์‚ฌ, ํ•ด์–‘โ€‘๋Œ€๊ธฐ ์ƒํ˜ธ์ž‘์šฉ, ์˜จ์‹ค๊ฐ€์Šค ๋†๋„ ๋“ฑ์„ ์ค‘์‹ฌ์œผ๋กœ ์ „๊ฐœ๋ผ ์™”์œผ๋ฉฐ, ์ง€๊ตฌ ๋‚ด๋ถ€ ์—ญํ•™์€ ๋ณดํ†ต ์žฅ๊ธฐ ์ง€์งˆํ•™์  ์‹œ๊ฐ„์ฒ™๋„(์ˆ˜๋ฐฑ๋งŒ ๋…„)์—์„œ๋งŒ ๊ณ ๋ ค๋˜์—ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ €์ž๋“ค์€ 2024โ€‘2025๋…„ ์‚ฌ์ด์— ๊ด€์ธก๋œ ๊ทน๋‹จ์ ์ธ ํ‰๊ท  ํ•ด์ˆ˜๋ฉด ๊ธฐ์••(์ตœ์ € 921 hPa, ์ตœ๊ณ  1 060 hPa)๊ณผ ์—ฐ์†์ ์ธ ๋Œ€๊ทœ๋ชจ ์ง€์ง„์„ ๋™์‹œ์— ๋ถ„์„ํ•จ์œผ๋กœ์จ, ๋‹จ๊ธฐ(์ˆ˜์ผโ€‘์ˆ˜์ฃผ) ๊ทœ๋ชจ์—์„œ๋„ ๋‚ด๋ถ€ ์ง„๋™์ด ๋Œ€๊ธฐ์•• ๋ณ€๋™์„ ์œ ๋ฐœํ•  ์ˆ˜ ์žˆ์Œ์„ ์‹ค์ฆํ•œ๋‹ค. ํ•ต์‹ฌ

Arxiv 2512.23731

Arxiv 2512.23731

๋ณธ ๋…ผ๋ฌธ์€ ์ง€๊ตฌ ๋‚ด๋ถ€์˜ ํƒ„์„ฑ ์ง„๋™์ด ๋Œ€๊ธฐ์™€ ์ง์ ‘์ ์ธ ํ”ผ๋“œ๋ฐฑ ๋ฃจํ”„๋ฅผ ํ˜•์„ฑํ•œ๋‹ค๋Š” ํš๊ธฐ์ ์ธ ๊ฐ€์„ค์„ ์ œ์‹œํ•œ๋‹ค. ๊ธฐ์กด ๊ธฐํ›„ ๋ชจ๋ธ์€ ํƒœ์–‘ ๋ณต์‚ฌ, ํ•ด์–‘โ€‘๋Œ€๊ธฐ ์ƒํ˜ธ์ž‘์šฉ, ์˜จ์‹ค๊ฐ€์Šค ๋†๋„ ๋“ฑ์„ ์ค‘์‹ฌ์œผ๋กœ ์ „๊ฐœ๋ผ ์™”์œผ๋ฉฐ, ์ง€๊ตฌ ๋‚ด๋ถ€ ์—ญํ•™์€ ๋ณดํ†ต ์žฅ๊ธฐ ์ง€์งˆํ•™์  ์‹œ๊ฐ„์ฒ™๋„(์ˆ˜๋ฐฑ๋งŒ ๋…„)์—์„œ๋งŒ ๊ณ ๋ ค๋˜์—ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ €์ž๋“ค์€ 2024โ€‘2025๋…„ ์‚ฌ์ด์— ๊ด€์ธก๋œ ๊ทน๋‹จ์ ์ธ ํ‰๊ท  ํ•ด์ˆ˜๋ฉด ๊ธฐ์••(์ตœ์ € 921 hPa, ์ตœ๊ณ  1 060 hPa)๊ณผ ์—ฐ์†์ ์ธ ๋Œ€๊ทœ๋ชจ ์ง€์ง„์„ ๋™์‹œ์— ๋ถ„์„ํ•จ์œผ๋กœ์จ, ๋‹จ๊ธฐ(์ˆ˜์ผโ€‘์ˆ˜์ฃผ) ๊ทœ๋ชจ์—์„œ๋„ ๋‚ด๋ถ€ ์ง„๋™์ด ๋Œ€๊ธฐ์•• ๋ณ€๋™์„ ์œ ๋ฐœํ•  ์ˆ˜ ์žˆ์Œ์„ ์‹ค์ฆํ•œ๋‹ค. ํ•ต์‹ฌ

Scientific Realism and Classical Physics

Scientific Realism and Classical Physics

๋ณธ ๋…ผ๋ฌธ์€ ๊ณผํ•™ ์‹ค์žฌ์ฃผ์˜๋ผ๋Š” ์ฒ ํ•™์  ์ž…์žฅ์„ ์‹œ๊ฐ„์ถ•์— ๋”ฐ๋ผ ๊ตฌ์ฒด์ ์ธ ์กด์žฌ๋ก ์  ๊ตฌ์„ฑ์š”์†Œ์™€ ์—ฐ๊ฒฐ์‹œํ‚ด์œผ๋กœ์จ, ๊ณ ์ „ ๋ฌผ๋ฆฌํ•™์˜ ์—ญ์‚ฌ๋ฅผ โ€˜์‹ค์ฒด์˜ ์ง„ํ™”โ€™๋ผ๋Š” ๊ด€์ ์—์„œ ์žฌ์กฐ๋ช…ํ•œ๋‹ค๋Š” ์ ์—์„œ ํ•™์ˆ ์  ์˜์˜๊ฐ€ ํฌ๋‹ค. ์ฒซ ๋ฒˆ์งธ ๋‹จ๊ณ„๋Š” ๋‰ดํ„ด์ด ์ œ์‹œํ•œ ๋„ค ๊ฐ€์ง€ ๊ธฐ๋ณธ ์‹ค์ฒด์ด๋‹ค. ๋‰ดํ„ด์€ ๋ฌผ์งˆ์„ โ€˜์ ˆ๋Œ€์ ์œผ๋กœ ๋‹จ๋‹จํ•˜๊ณ  ํŒŒ๊ดด๋˜์ง€ ์•Š๋Š” ์ž…์žโ€™๋กœ ๊ฐ€์ •ํ•˜๊ณ , ์ด ์ž…์ž๋“ค์ด ๋ณ€ํ•˜์ง€ ์•Š๋Š” 3์ฐจ์› ๊ณต๊ฐ„๊ณผ ์ ˆ๋Œ€์ ์ธ ์‹œ๊ฐ„์ด๋ผ๋Š” ๋ฐฐ๊ฒฝ ์œ„์—์„œ ํž˜์— ์˜ํ•ด ์›€์ง์ธ๋‹ค๊ณ  ๋ณด์•˜๋‹ค. ์—ฌ๊ธฐ์„œ โ€˜์ ˆ๋Œ€ ๊ณต๊ฐ„ยท์‹œ๊ฐ„โ€™์€ ๊ด€์ธก์ž์™€ ๋ฌด๊ด€ํ•˜๊ฒŒ ์กด์žฌํ•˜๋Š” ๋…๋ฆฝ์  ์‹ค์žฌ์ด๋ฉฐ, ์ด๋Š” ์‹ค์žฌ์ฃผ์˜๊ฐ€ ์š”๊ตฌํ•˜๋Š” โ€˜๊ด€์ธก ๊ฐ€๋Šฅํ•œ ์„ธ๊ณ„

Physics Quantum Physics
Constraints on the Cosmic-Ray Density Gradient beyond the Solar Circle   from Fermi gamma-ray Observations of the Third Galactic Quadrant

Constraints on the Cosmic-Ray Density Gradient beyond the Solar Circle from Fermi gamma-ray Observations of the Third Galactic Quadrant

๋ณธ ์—ฐ๊ตฌ๋Š” Fermi LAT์˜ ๋›ฐ์–ด๋‚œ ๊ฐ๋„์™€ ๊ฐ๋„ ํ•ด์ƒ๋„๋ฅผ ํ™œ์šฉํ•ด ์ œ3 ์€ํ•˜ ์‚ฌ๋ถ„๋ฉด์˜ ํ™•์‚ฐ ฮณโ€‘์„ ์„ ์ •๋ฐ€ํ•˜๊ฒŒ ๋ถ„๋ฆฌยท๋ชจ๋ธ๋งํ•จ์œผ๋กœ์จ, ์€ํ•˜ ์™ธ๊ณฝ(ํƒœ์–‘๊ณ„์—์„œ 8 kpc ์ด์ƒ)์—์„œ์˜ ์šฐ์ฃผ์„ (CR) ๋ฐ€๋„์™€ ์ŠคํŽ™ํŠธ๋Ÿผ์„ ์ง์ ‘ ์ถ”์ •ํ–ˆ๋‹ค๋Š” ์ ์—์„œ ์˜๋ฏธ๊ฐ€ ํฌ๋‹ค. ๊ธฐ์กด COSโ€‘BยทEGRET ์‹œ์ ˆ์—๋Š” ๊ด€์ธก ์žฅ๋น„์˜ ์ œํ•œ์œผ๋กœ ์€ํ•˜ ์ค‘์‹ฌ์—์„œ ๋ฉ€๋ฆฌ ๋–จ์–ด์ง„ ์˜์—ญ์˜ CR ๋ถ„ํฌ๋ฅผ ์ •ํ™•ํžˆ ํŒŒ์•…ํ•˜๊ธฐ ์–ด๋ ค์› ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ด๋ฒˆ ๋ถ„์„์—์„œ๋Š” ion{H}{I}์™€ CO(๋ถ„์ž์ˆ˜์†Œ) ํŠธ๋ ˆ์ด์„œ ๊ฐ๊ฐ์— ๋Œ€ํ•œ ์ปฌ๋Ÿผ ๋งต์„ ์ตœ์‹  Leiden/Argentine/Bonn ์„œ๋ฒ ์ด์™€ CO ์ „์ด์„  ๋ฐ

Astrophysics
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. ์ „

Information Theory Computer Science Mathematics
Power-law Distributions in Information Science - Making the Case for   Logarithmic Binning

Power-law Distributions in Information Science - Making the Case for Logarithmic Binning

ํŒŒ์›Œโ€‘๋Ÿฌํ”„ ๋ถ„ํฌ๋Š” โ€œํฐ ๊ฐ’์ด ๋“œ๋ฌผ๊ฒŒ ๋‚˜ํƒ€๋‚œ๋‹คโ€๋Š” ์ง๊ด€์ ์ธ ํŠน์„ฑ์„ ๊ฐ–๊ณ  ์žˆ์–ด, ์ €์ž ์ƒ์‚ฐ์„ฑ, ๋…ผ๋ฌธ ์ธ์šฉ ํšŸ์ˆ˜, ํ•™์ˆ  ๋ฌธํ—Œ ์‚ฐํฌ, ํ˜‘์—… ํƒœ๊น… ํ–‰๋™ ๋“ฑ ๋‹ค์–‘ํ•œ ์ •๋ณด๊ณผํ•™ ํ˜„์ƒ์„ ์„ค๋ช…ํ•˜๋Š” ๋ฐ ๋„๋ฆฌ ํ™œ์šฉ๋œ๋‹ค(Nelson 2005 ๋“ฑ). ๊ทธ๋Ÿฌ๋‚˜ ์‹ค์ œ ๋ฐ์ดํ„ฐ๋ฅผ ๋ถ„์„ํ•  ๋•Œ๋Š” ํ‘œ๋ณธ ํฌ๊ธฐ๊ฐ€ ์ œํ•œ์ ์ด๊ณ , ํŠนํžˆ ๊ผฌ๋ฆฌ ์˜์—ญ์—์„œ ๊ด€์ธก๊ฐ’์ด ๊ทนํžˆ ์ ์–ด ํ†ต๊ณ„์  ์žก์Œ์ด ํฌ๊ฒŒ ์ž‘์šฉํ•œ๋‹ค. ์ „ํ†ต์ ์œผ๋กœ ์—ฐ๊ตฌ์ž๋“ค์€ ์›์‹œ ๋นˆ๋„ํ‘œ๋ฅผ ๊ทธ๋Œ€๋กœ ํ”Œ๋กฏํ•˜๊ฑฐ๋‚˜, ๋ˆ„์  ๋ถ„ํฌ๋ฅผ ์ด์šฉํ•ด ํŒŒ์›Œโ€‘๋Ÿฌํ”„ ์—ฌ๋ถ€๋ฅผ ํŒ๋‹จํ•œ๋‹ค. ๋ˆ„์  ๋ฐฉ์‹์€ ์‹œ๊ฐ์ ์œผ๋กœ ๋งค๋„๋Ÿฝ๊ฒŒ ๋ณด์ด์ง€๋งŒ, ์ž‘์€ ํ‘œ๋ณธ์ด ๋ˆ„์ ๋˜๋ฉด์„œ ์›๋ž˜์˜ ๋ณ€๋™์„ฑ

Digital Libraries Statistics Computer Science Physics
A study of spectral and timing properties of Cyg X-1 based on a large   sample of pointed RXTE observations

A study of spectral and timing properties of Cyg X-1 based on a large sample of pointed RXTE observations

์ด ๋…ผ๋ฌธ์€ ์‚ฌ์ด๊ทธ Xโ€‘1์ด๋ผ๋Š” ๊ณ ํ’ˆ์งˆ ๋ธ”๋ž™ํ™€ Xโ€‘์„  ์ด์ค‘์„ฑ๊ณ„์˜ ๋ณต์žกํ•œ ๋ณ€๋™์„ฑ์„ ์ดํ•ดํ•˜๊ธฐ ์œ„ํ•ด โ€˜๋Œ€๊ทœ๋ชจ ํ‘œ๋ณธ + ๋ฌผ๋ฆฌ ๋ชจ๋ธโ€™์ด๋ผ๋Š” ๋‘ ์ถ•์„ ๋™์‹œ์— ํ™œ์šฉํ•œ ์ ์ด ๊ฐ€์žฅ ํฐ ๊ฐ•์ ์ด๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ๋“ค์€ ์ฃผ๋กœ (1) ์†Œ์ˆ˜์˜ ๋Œ€ํ‘œ ๊ด€์ธก์„ ์ •๋ฐ€ํ•˜๊ฒŒ ๋ถ„์„ํ•˜๊ฑฐ๋‚˜, (2) ์ˆ˜๋ฐฑ ๊ฐœ์˜ ๊ด€์ธก์„ ์ƒ‰โ€‘์ƒ‰๋„์™€ ๊ฐ™์€ ๋น„์ •๋Ÿ‰์  ์ง€ํ‘œ๋กœ๋งŒ ๋ถ„๋ฅ˜ํ•˜๋Š” ๋‘ ๊ฐ€์ง€ ์ ‘๊ทผ๋ฒ• ์ค‘ ํ•˜๋‚˜์— ๋จธ๋ฌผ๋ €๋‹ค. ์ €์ž๋“ค์€ ์ด ๋‘ ๋ฐฉ๋ฒ•์„ ๊ฒฐํ•ฉํ•ด, ์ „์ฒด 700์—ฌ ํšŒ์˜ ๊ด€์ธก ์ค‘ ์ƒ‰โ€‘์ƒ‰๋„ ์ƒ์—์„œ ์—ฐ์†์ ์ธ ์„ ํ˜• ๊ตฌ์กฐ๋ฅผ ๋ฐœ๊ฒฌํ•˜๊ณ  ์ด๋ฅผ โ€˜์ŠคํŽ™ํŠธ๋Ÿผ ์ƒํƒœ ํŒŒ๋ผ๋ฏธํ„ฐโ€™๋ผ๋Š” ์ •๋Ÿ‰์  ์ถ•์œผ๋กœ ์ „ํ™˜ํ•˜์˜€๋‹ค. ์ด๋Š” ์ŠคํŽ™ํŠธ๋Ÿผ ์ „

Astrophysics
Relating timed and register automata

Relating timed and register automata

์ด ๋…ผ๋ฌธ์€ ์‹œ๊ฐ„ ์ž๋™์ž์™€ ๋ ˆ์ง€์Šคํ„ฐ ์ž๋™์ž๋ผ๋Š” ๋‘ ์ „ํ†ต์ ์ธ ๋ชจ๋ธ ์‚ฌ์ด์— ์กด์žฌํ•˜๋Š” ๊นŠ์€ ๊ตฌ์กฐ์  ์œ ์‚ฌ์„ฑ์„ ์ฒด๊ณ„์ ์œผ๋กœ ๋ฐํ˜€๋‚ธ๋‹ค. ๋จผ์ € ์ €์ž๋“ค์€ ๊ฐ ๋ชจ๋ธ์ด โ€œ์ €์žฅ ์žฅ์น˜โ€๋ผ๋Š” ๊ณตํ†ต๋œ ํ™•์žฅ ์š”์†Œ๋ฅผ ๊ฐ–๋Š”๋‹ค๋Š” ์ ์„ ๊ฐ•์กฐํ•œ๋‹ค. ์‹œ๊ฐ„ ์ž๋™์ž๋Š” ๋ฆฌ์…‹ ์‹œ์ ๋ถ€ํ„ฐ ํ๋ฅธ ์‹œ๊ฐ„์„ ์ธก์ •ํ•˜๋Š” ์‹œ๊ณ„๋ฅผ, ๋ ˆ์ง€์Šคํ„ฐ ์ž๋™์ž๋Š” ๋ฐ์ดํ„ฐ๋ฅผ ์ €์žฅํ•˜๊ณ  ์ดํ›„ ๋น„๊ต์— ํ™œ์šฉํ•˜๋Š” ๋ ˆ์ง€์Šคํ„ฐ๋ฅผ ์ œ๊ณตํ•œ๋‹ค. ๊ฒ‰๋ณด๊ธฐ ์ฐจ์ด๋Š” ํฌ์ง€๋งŒ, ๋‘ ๋ชจ๋ธ์ด ํ•ด๊ฒฐํ•ด์•ผ ํ•˜๋Š” ํ•ต์‹ฌ ๊ฒฐ์ • ๋ฌธ์ œโ€”๊ณต์ง‘ํ•ฉ์„ฑ, ์ „์—ญ์„ฑ, ํฌํ•จ์„ฑโ€”๋Š” ๋™์ผํ•œ ๋ณต์žก๋„ ๊ตฌ๋„๋ฅผ ๊ณต์œ ํ•œ๋‹ค๋Š” ์ ์ด ๊ธฐ์กด ์—ฐ๊ตฌ๋“ค(์˜ˆ: PSPACEโ€‘complete, ๋น„์›์‹œ ์žฌ

Logic Computer Science Formal Languages
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
Effects of forest fire severity on terrestrial carbon emission and   ecosystem production in the Himalayan region, India

Effects of forest fire severity on terrestrial carbon emission and ecosystem production in the Himalayan region, India

๋ณธ ๋…ผ๋ฌธ์€ ํžˆ๋ง๋ผ์•ผ ๋‚จ๋ถ€, ํŠนํžˆ ์ธ๋„ ์šฐํƒ€๋ผ์นธ๋“œ ์ง€์—ญ์˜ ์‚ฐ๋ถˆ์ด ํƒ„์†Œ ์ˆœํ™˜๊ณผ ์ƒํƒœ๊ณ„ ์ƒ์‚ฐ์„ฑ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ๋‹ค๊ฐ์ ์ธ ์›๊ฒฉ ํƒ์‚ฌ ์ง€ํ‘œ์™€ ๊ด‘ํ•ฉ์„ฑ ๋ชจ๋ธ์„ ๊ฒฐํ•ฉํ•ด ์ •๋Ÿ‰ํ™”ํ•œ ์ ์—์„œ ํ•™์ˆ ์ ยท์‹ค์šฉ์  ์˜์˜๊ฐ€ ํฌ๋‹ค. ์ฒซ์งธ, ํ™”์žฌ ์ „ํ›„์˜ LST(์ง€ํ‘œ๋ฉด ์˜จ๋„) ๋ถ„์„์„ ํ†ตํ•ด ์ „์—ญ์ ์ธ ํ•ซ์ŠคํŒŸ์„ ์ž๋™ ๊ฒ€์ถœํ•œ ๋ฐฉ๋ฒ•์€ ๊ธฐ์กด์— ํ˜„์žฅ ์กฐ์‚ฌ์— ์˜์กดํ•˜๋˜ ์ ‘๊ทผ๋ฒ•๋ณด๋‹ค ์‹œ๊ฐ„ยท์ธ๋ ฅ ๋น„์šฉ์„ ํฌ๊ฒŒ ์ ˆ๊ฐํ•œ๋‹ค. MODIS์˜ 1 km ํ•ด์ƒ๋„๋Š” ๊ด‘๋ฒ”์œ„ ์ง€์—ญ์„ ์ปค๋ฒ„ํ•˜๋ฉด์„œ๋„ ์—ฐ๋„๋ณ„ ๋น„๊ต๊ฐ€ ๊ฐ€๋Šฅํ•ด, ํ™”์žฌ ๊ฐ•๋„์™€ ๊ณต๊ฐ„ ๋ถ„ํฌ๋ฅผ ์ •๋ฐ€ํ•˜๊ฒŒ ํŒŒ์•…ํ•  ์ˆ˜ ์žˆ๋‹ค. ๋‘˜์งธ, NBR, BAI, NMDI, SAV

Quantitative Biology System
The Measurement of the Hubble Constant H_0 in the Solar System

The Measurement of the Hubble Constant H_0 in the Solar System

์ด ์—ฐ๊ตฌ๋Š” ์ „ํ†ต์ ์ธ ์ฒœ๋ฌธํ•™์  ๊ฑฐ๋ฆฌ ์‚ฌ๋‹ค๋ฆฌ์™€๋Š” ์ „ํ˜€ ๋‹ค๋ฅธ ์ ‘๊ทผ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค๋Š” ์ ์—์„œ ํ˜์‹ ์ ์ด๋‹ค. ํ—ˆ๋ธ” ์ƒ์ˆ˜๋Š” ๋ณดํ†ต ์ˆ˜์‹ญ ๋ฉ”๊ฐ€ํŒŒ์„น ์ด์ƒ ๊ฑฐ๋ฆฌ์˜ ์€ํ•˜๋‚˜ ์ดˆ์‹ ์„ฑ, ํ˜น์€ ์ค‘๋ ฅํŒŒ ํ‘œ์ค€์‹ ํ˜ธ๋ฅผ ์ด์šฉํ•ด ์ถ”์ •ํ•œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ €์ž๋“ค์€ โ€œ๊ทน๋‹จ์ ์œผ๋กœ ์งง์€ ๊ฑฐ๋ฆฌโ€์ธ ํƒœ์–‘๊ณ„ ๊ทœ๋ชจ(์ˆ˜์ฒœ AU ์ดํ•˜)์—์„œ ๋น›์˜ ํŒŒ์žฅ์ด ์šฐ์ฃผ ํŒฝ์ฐฝ์— ์˜ํ•ด ๋ฏธ์„ธํ•˜๊ฒŒ ๋Š˜์–ด๋‚˜๋Š” ํ˜„์ƒ์„ ์ง์ ‘ ์ธก์ •ํ•œ๋‹ค๋Š” ์ „์ œ์— ๊ธฐ๋ฐ˜ํ•œ๋‹ค. ํ•ต์‹ฌ ์•„์ด๋””์–ด๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. FLRW ๋ฉ”ํŠธ๋ฆญ์— ์˜ํ•ด ์ •์˜๋˜๋Š” ์Šค์ผ€์ผ ํŒฉํ„ฐ (a(t))๊ฐ€ ์‹œ๊ฐ„์— ๋”ฐ๋ผ ๋ณ€ํ•˜๋ฉด, ์ „์ž๊ธฐ ํŒŒ๋™์˜ ์ฃผํŒŒ์ˆ˜๋Š” ( Delta f/f t,H {

Astrophysics System Physics
History-sensitive versus future-sensitive approaches to security in   distributed systems

History-sensitive versus future-sensitive approaches to security in distributed systems

(800์ž ์ด์ƒ) ๋ณธ ๋…ผ๋ฌธ์€ ๋ถ„์‚ฐ ์‹œ์Šคํ…œ ๋ณด์•ˆ์— ์žˆ์–ด ์‹œ๊ฐ„์  ๊ด€์  ์„ ๋‘ ์ถ•์œผ๋กœ ๊ตฌ๋ถ„ํ•œ๋‹ค๋Š” ์ ์—์„œ ์ด๋ก ์ ยท์‹ค์šฉ์  ์˜์˜๋ฅผ ๋™์‹œ์— ์ง€๋‹Œ๋‹ค. ๊ธฐ์กด์˜ ๋ฏธ๋ž˜โ€‘๊ฐ์ง€ ์ ‘๊ทผ๋ฒ•์€ ์ •์  ๋ถ„์„์„ ํ†ตํ•ด ํ”„๋กœ๊ทธ๋žจ์ด ์•ž์œผ๋กœ ์ˆ˜ํ–‰ํ•  ํ–‰๋™์„ ์˜ˆ์ธกํ•˜๊ณ , ๊ทธ ์˜ˆ์ธก ๊ฒฐ๊ณผ์— ๋”ฐ๋ผ ์ ‘๊ทผ์„ ํ—ˆ์šฉํ•˜๊ฑฐ๋‚˜ ์ฐจ๋‹จํ•œ๋‹ค. ์ด ๋ฐฉ์‹์€ ์ •๋ณด ํ๋ฆ„ ์ œ์–ด ์— ๊ฐ•์ ์„ ๋ณด์ด๋ฉฐ, ํŠนํžˆ ์ˆœ์ฐจ์  ํ”„๋กœ๊ทธ๋žจ์ด๋‚˜ ์ œํ•œ๋œ ๋™์‹œ์„ฑ์„ ๊ฐ–๋Š” ์‹œ์Šคํ…œ์—์„œ ํšจ๊ณผ์ ์ด๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๋ถ„์‚ฐ ํ™˜๊ฒฝ์€ ๋‹ค์ค‘ ์œ„์น˜ ๊ฐ„ ๋™์‹œ ์ƒํ˜ธ์ž‘์šฉ ๊ณผ ๋น„๋™๊ธฐ์  ๋ฉ”์‹œ์ง• ์ด ๋นˆ๋ฒˆํžˆ ์ผ์–ด๋‚˜๋ฏ€๋กœ, ๋‹จ์ผ ํ”„๋กœ์„ธ์Šค์˜ ๋ฏธ๋ž˜ ํ–‰๋™๋งŒ์„ ๊ณ ๋ คํ•˜๋Š” ๊ฒƒ์œผ๋กœ๋Š” ์ „์ฒด ์‹œ

System Computer Science Cryptography and Security Distributed Computing Programming Languages
Long-term X-ray Variability Study of IC342 from XMM-Newton Observations

Long-term X-ray Variability Study of IC342 from XMM-Newton Observations

๋ณธ ๋…ผ๋ฌธ์€ IC 342๋ผ๋Š” ๊ทผ๊ฑฐ๋ฆฌ ๋‚˜์„ ์€ํ•˜๋ฅผ ๋Œ€์ƒ์œผ๋กœ, XMMโ€‘Newton์˜ EPICโ€‘PN ๋ฐ MOS ์นด๋ฉ”๋ผ๋ฅผ ์ด์šฉํ•ด 4๋…„(2001โ€“2005) ๋™์•ˆ ๋„ค ์ฐจ๋ก€์— ๊ฑธ์นœ ๊ด€์ธก ๋ฐ์ดํ„ฐ๋ฅผ ์ •๋ฐ€ํ•˜๊ฒŒ ๋ถ„์„ํ•จ์œผ๋กœ์จ, ์€ํ•˜ ๋‚ด Xโ€‘์„  ์ ์›์ฒœ๋“ค์˜ ์žฅ๊ธฐ ๋ณ€๋™ ํŠน์„ฑ์„ ์ตœ์ดˆ๋กœ ์ „๋ฉด์ ์œผ๋กœ ์ œ์‹œํ•œ ์ ์—์„œ ํฐ ์˜๋ฏธ๋ฅผ ๊ฐ€์ง„๋‹ค. ์ฒซ์งธ, ๊ฒ€์ถœ๋œ 61๊ฐœ์˜ Xโ€‘์„  ์›์ฒœ ์ค‘ 39๊ฐœ๊ฐ€ ์žฅ๊ธฐ ๋ณ€๋™์„ ๋ณด์˜€๋‹ค๋Š” ๊ฒฐ๊ณผ๋Š” IC 342๊ฐ€ ๋‹จ์ˆœํžˆ ๋ช‡ ๊ฐœ์˜ ์ดˆ๊ด‘๋„ Xโ€‘์„  ์›์ฒœ(ULX)์œผ๋กœ๋งŒ ์ง€๋ฐฐ๋˜๋Š” ๊ฒƒ์ด ์•„๋‹ˆ๋ผ, ๋‹ค์ˆ˜์˜ ๋ณ€๋™์„ฑ ๋†’์€ ์ €๊ด‘๋„ ์›์ฒœ๋“ค( (L {mathrm{X}} sim

Astrophysics
Reasoning About Knowledge of Unawareness Revisited

Reasoning About Knowledge of Unawareness Revisited

๋ณธ ์—ฐ๊ตฌ๋Š” ์ธ์‹(logic of awareness) ๋ถ„์•ผ์—์„œ ์˜ค๋žซ๋™์•ˆ ๋‚จ์•„ ์žˆ๋˜ ๋‘ ๊ฐ€์ง€ ํ•ต์‹ฌ ๋ฌธ์ œ๋ฅผ ๋™์‹œ์— ํ•ด๊ฒฐํ•œ๋‹ค. ์ฒซ ๋ฒˆ์งธ๋Š” โ€œ๋ฌด์ธ์‹์— ๋Œ€ํ•œ ์ธ์‹(knowledge of unawareness)โ€์„ ์ •ํ˜•ํ™”ํ•˜๋Š” ๊ฒƒ์ด์—ˆ๊ณ , ๋‘ ๋ฒˆ์งธ๋Š” ์—์ด์ „ํŠธ๊ฐ€ ๋ชจ๋“  ๊ณต์‹์— ๋Œ€ํ•ด ์ž์‹ ์ด ์ธ์‹ํ•˜๊ณ  ์žˆ๋Š”์ง€ ์—ฌ๋ถ€๋ฅผ ํ™•์‹ ํ•˜์ง€ ๋ชปํ•˜๋Š” ์ƒํ™ฉ์„ ๋ชจ๋ธ๋งํ•˜๋Š” ๊ฒƒ์ด์—ˆ๋‹ค. ๊ธฐ์กด์˜ FH ๋ชจ๋ธ์€ ๊ฐ ์„ธ๊ณ„๋งˆ๋‹ค ๋™์ผํ•œ ์–ธ์–ด๋ฅผ ๊ฐ€์ •ํ•˜๊ณ , ์ธ์‹ ์—ฐ์‚ฐ์ž๋ฅผ ํ†ตํ•ด ์—์ด์ „ํŠธ๊ฐ€ ์–ด๋–ค ๊ณต์‹์„ โ€˜๋ช…์‹œ์ ์œผ๋กœโ€™ ์•ˆ๋Š”์ง€๋ฅผ ์ •์˜ํ•œ๋‹ค. ์ด ๊ตฌ์กฐ๋Š” ์›์‹œ ๋ช…์ œ์— ๋Œ€ํ•œ ์–‘ํ™”๋ฅผ ๋„์ž…ํ•ด โ€œ์–ด๋–ค ์‚ฌ์‹ค์„ ๋ชจ๋ฅธ๋‹คโ€

Logic Game Theory Artificial Intelligence Computer Science
Cohomology of real Grassmann manifold and KP flow

Cohomology of real Grassmann manifold and KP flow

๋ณธ ๋…ผ๋ฌธ์€ KP ๋ฐฉ์ •์‹์ด๋ผ๋Š” 2โ€‘์ฐจ์› ๋น„์„ ํ˜• ํŒŒ๋™ ๋ฐฉ์ •์‹์˜ ํŠน์ˆ˜ ํ•ด๊ฐ€ ์‹ค๊ทธ๋ผ์Šค๋งŒ ๋‹ค์–‘์ฒด ( operatorname{Gr}(k,n) ) ์™€ ์ง์ ‘์ ์ธ ์œ„์ƒํ•™์  ์ •๋ณด๋ฅผ ์–ด๋–ป๊ฒŒ ์—ฐ๊ฒฐํ•˜๋Š”์ง€๋ฅผ ์ฒด๊ณ„์ ์œผ๋กœ ๋ฐํžŒ๋‹ค. ํ•ต์‹ฌ ์•„์ด๋””์–ด๋Š” ( tau )โ€‘ํ•จ์ˆ˜(ํƒ€์šฐ ํ•จ์ˆ˜)๋ฅผ ์™€๋ฅด์‹œ์•ˆ ํ–‰๋ ฌ์‹ ํ˜•ํƒœ๋กœ ์ •์˜ํ•˜๊ณ , ์ด๋ฅผ ( f {i}(x,y,t) sum {j 1}^{n}a {ij}E {j}(x,y,t) ) ์™€ ๊ฐ™์€ ์œ ํ•œ ํ‘ธ๋ฆฌ์— ๊ธ‰์ˆ˜๋กœ ์ œํ•œํ•จ์œผ๋กœ์จ, ๊ณ„์ˆ˜ ํ–‰๋ ฌ ( Ainmathbb{R}^{ktimes n} ) ๊ฐ€ ์‹ค๊ทธ๋ผ์Šค๋งŒ ๋‹ค์–‘์ฒด์˜ ํ•œ ์ 

MATH-PH Nonlinear Sciences Mathematics
Cosmic ray propagation time scales: lessons from radioactive nuclei and   positron data

Cosmic ray propagation time scales: lessons from radioactive nuclei and positron data

๋ณธ ๋…ผ๋ฌธ์€ ์ „ํ†ต์ ์ธ โ€˜๋ฆฌํ‚ค ๋ฐ•์Šคโ€™๋‚˜ ํ™•์‚ฐ ๋ชจ๋ธ์— ์˜์กดํ•˜์ง€ ์•Š๊ณ , ๊ด€์ธก๋œ ๋ฐฉ์‚ฌ์„ฑ ํ•ต ๋น„์œจ๊ณผ ์–‘์ „์ž ์ŠคํŽ™ํŠธ๋Ÿผ์„ ์ง์ ‘ ๋น„๊ตํ•จ์œผ๋กœ์จ ์€ํ•˜ ๋‚ด ์šฐ์ฃผ์„ ์˜ ํ‰๊ท  ์ฒด๋ฅ˜ ์‹œ๊ฐ„์„ ๋ชจ๋ธโ€‘๋…๋ฆฝ์ ์œผ๋กœ ์ถ”์ •ํ•œ๋‹ค๋Š” ์ ์—์„œ ์˜๋ฏธ๊ฐ€ ํฌ๋‹ค. ์ €์ž๋“ค์€ ๊ณ ์—๋„ˆ์ง€ ์˜์—ญ(๊ฐ•์„ฑ โ‰ณ 10 GV)์—์„œ ์—๋„ˆ์ง€ ์†์‹คยทํš๋“์„ ๋ฌด์‹œํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ์ „์ œ ํ•˜์—, CR grammage (X {rm esc})์™€ ์ƒ์‚ฐ๋Ÿ‰ (Q i) ์‚ฌ์ด์˜ ๊ฒฝํ—˜์  ๊ด€๊ณ„ (J i X {rm esc} Q i / m {rm ISM}) ๋ฅผ ํ™œ์šฉํ•œ๋‹ค. ์ด ์‹์€ ๋ชจ๋“  ํ—ˆ์šฉ ๊ฐ€๋Šฅํ•œ ์ „ํŒŒ ๋ชจ๋ธ์ด ๋งŒ์กฑํ•ด์•ผ ํ•˜๋Š”

Astrophysics Data HEP-PH
Dynamic Characteristics of the Low-Temperature Decomposition of the C20   Fullerene

Dynamic Characteristics of the Low-Temperature Decomposition of the C20 Fullerene

๋ณธ ๋…ผ๋ฌธ์€ ์ €์˜จ์—์„œ์˜ ํด๋Ÿฌ์Šคํ„ฐ ๋ถ„ํ•ด๋ผ๋Š” ์ „ํ˜•์ ์ธ โ€˜ํฌ๊ท€ ์‚ฌ๊ฑด(rare event)โ€™ ๋ฌธ์ œ์— ๋Œ€ํ•œ ๊ณ„์‚ฐ์  ์ ‘๊ทผ๋ฒ•์„ ์ƒˆ๋กญ๊ฒŒ ์ œ์‹œํ•œ๋‹ค๋Š” ์ ์—์„œ ๊ณผํ•™ยท๊ณตํ•™ ๋ถ„์•ผ์— ์ค‘์š”ํ•œ ์˜๋ฏธ๋ฅผ ๊ฐ€์ง„๋‹ค. ์ „ํ†ต์ ์ธ ๋ถ„์ž๋™์—ญํ•™์€ ์›์žยท๋ถ„์ž์˜ ์›€์ง์ž„์„ ๋ฏธ์‹œ์ ์ธ ์‹œ๊ฐ„ ๋‹จ๊ณ„(ํŽจํ† ์ดˆ ์ˆ˜์ค€)๋กœ ์ง์ ‘ ์ ๋ถ„ํ•จ์œผ๋กœ์จ ์ˆ˜์‹ญ ๋‚˜๋…ธ์ดˆ ์ •๋„์˜ ์‹œ๋ฎฌ๋ ˆ์ด์…˜๋งŒ์ด ํ˜„์‹ค์ ์œผ๋กœ ๊ฐ€๋Šฅํ•˜๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ Cโ‚‚โ‚€ ํ’€๋Ÿฌ๋ Œ๊ณผ ๊ฐ™์ด ์ˆ˜์ดˆยท์ˆ˜๋ถ„ยท์ˆ˜์‹œ๊ฐ„์— ์ด๋ฅด๋Š” ๊ฑฐ์‹œ์  ์ˆ˜๋ช…์„ ๊ฐ–๋Š” ์‹œ์Šคํ…œ์„ ์ง์ ‘ MD๋กœ ๋‹ค๋ฃจ๋ฉด ๊ณ„์‚ฐ ๋น„์šฉ์ด ์ฒœ๋ฌธํ•™์ ์œผ๋กœ ์ฆ๊ฐ€ํ•œ๋‹ค. ์ €์ž๋“ค์€ ์ด๋Ÿฌํ•œ ์‹œ๊ฐ„โ€‘์Šค์ผ€์ผ ๊ฒฉ์ฐจ๋ฅผ ๋ฉ”์šฐ๊ธฐ ์œ„ํ•ด โ€˜MDโ€‘MC ํ˜ผํ•ฉ

Condensed Matter Physics
Diffuse Hard X-ray Emission in Starburst Galaxies as Synchrotron from   Very High Energy Electrons

Diffuse Hard X-ray Emission in Starburst Galaxies as Synchrotron from Very High Energy Electrons

์ด ์—ฐ๊ตฌ๋Š” ๋ณ„ํญ๋ฐœ ์€ํ•˜์—์„œ ๊ด€์ธก๋˜๋Š” ํ™•์‚ฐ ๊ฒฝ์งˆ Xโ€‘์„ ์ด ์ „ํ†ต์ ์ธ ์—ด๋ณต์‚ฌยทHMXBยท์—ญ์ปดํ”„ํ„ด ๋ชจ๋ธ๋งŒ์œผ๋กœ๋Š” ์ถฉ๋ถ„ํžˆ ์„ค๋ช…๋˜์ง€ ์•Š๋Š”๋‹ค๋Š” ์ ์— ์ฃผ๋ชฉํ•œ๋‹ค. ์ €์ž๋“ค์€ 10โ€“100 TeV ์ „์ž์— ์˜ํ•œ ๋™๊ธฐ๋ณต์‚ฌ๊ฐ€ Xโ€‘์„  ๋ฐด๋“œ์— ๊ธฐ์—ฌํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ์ƒˆ๋กœ์šด ๊ฐ€๋Šฅ์„ฑ์„ ์ œ์‹œํ•œ๋‹ค. ์ด๋ฅผ ์œ„ํ•ด 1์ฐจ ์ „์ž, ํŒŒ์ด์˜จ 2์ฐจ ์ „์žยท์–‘์ „์ž, ๊ทธ๋ฆฌ๊ณ  ๊ฐ๋งˆโ€‘๊ด‘์ž ์Œ์ƒ์„ฑ ์ „์žยท์–‘์ „์ž์˜ ์„ธ ๊ฐ€์ง€ ์ƒ์‚ฐ ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ๋ชจ๋‘ ํฌํ•จํ•œ ์ข…ํ•ฉ์ ์ธ ์šฐ์ฃผ์„  ์ „์ด ๋ชจ๋ธ์„ ๊ตฌ์ถ•ํ•˜์˜€๋‹ค. ๋ชจ๋ธ์€ ์ „๋ ฅ๋ฒ• ํ˜•ํƒœ์˜ ์ฃผ์ž… ์ŠคํŽ™ํŠธ๋Ÿผ์„ ๊ฐ€์ •ํ•˜๊ณ , ์€ํ•˜๋ณ„ ์ž๊ธฐ์žฅ ๊ฐ•๋„์™€ ๊ฐ€์Šค ๋ฐ€๋„, FIR ๋ณต์‚ฌ์žฅ ๊ฐ•๋„๋ฅผ ์‹ค์ œ ๊ด€์ธก๊ฐ’

Astrophysics
The Sample Complexity of Dictionary Learning

The Sample Complexity of Dictionary Learning

๋ณธ ๋…ผ๋ฌธ์€ ๋”•์…”๋„ˆ๋ฆฌ ํ•™์Šต(dictionary learning) ๋ฌธ์ œ๋ฅผ ์ƒ˜ํ”Œ ๋ณต์žก๋„(sample complexity) ๊ด€์ ์—์„œ ์ฒด๊ณ„์ ์œผ๋กœ ๋ถ„์„ํ•œ๋‹ค๋Š” ์ ์—์„œ ์˜๋ฏธ๊ฐ€ ํฌ๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ๋“ค์€ ์ฃผ๋กœ ์•Œ๊ณ ๋ฆฌ์ฆ˜์  ์ˆ˜๋ ด ์†๋„๋‚˜ ์žฌ๊ตฌ์„ฑ ์˜ค์ฐจ์— ์ดˆ์ ์„ ๋งž์ถ”์—ˆ์ง€๋งŒ, ์—ฌ๊ธฐ์„œ๋Š” ์ผ๋ฐ˜ํ™”(generalization) โ€”์ฆ‰, ํ•™์Šต์— ์‚ฌ์šฉ๋œ ์œ ํ•œ ์ƒ˜ํ”Œ ์ง‘ํ•ฉ์œผ๋กœ๋ถ€ํ„ฐ ์–ป์€ ์‚ฌ์ „์ด ์ƒˆ๋กœ์šด, ๋ณด์ง€ ๋ชปํ•œ ์‹ ํ˜ธ์— ๋Œ€ํ•ด ์–ด๋А ์ •๋„์˜ ์˜ค๋ฅ˜๋ฅผ ๋ณด์ผ์ง€๋ฅผ ์ด๋ก ์ ์œผ๋กœ ์ •๋Ÿ‰ํ™”ํ•œ๋‹ค. 1. ๋ฌธ์ œ ์„ค์ •๊ณผ ํ•ต์‹ฌ ๊ฐ€์ • ์‹ ํ˜ธ ๊ณต๊ฐ„ (X mathbb{R}^{n}) ์—์„œ ์‹ ํ˜ธ (x)๋Š” ์‚ฌ์ „

Learning Statistics Computer Science Machine Learning
Using Humanoid Robot to Instruct and Evaluate Performance of a Physical   Task

Using Humanoid Robot to Instruct and Evaluate Performance of a Physical Task

๋ณธ ๋…ผ๋ฌธ์€ ์‚ฌํšŒ์  ์ง€์› ๋กœ๋ด‡(Socially Assistive Robots) ๋ถ„์•ผ์—์„œ โ€˜์ง€์‹œยท๊ด€์ฐฐยทํ”ผ๋“œ๋ฐฑโ€™ ์‚ผ์œ„์ผ์ฒด ๊ตฌ์กฐ๋ฅผ ์‹ค์ œ ๋ฌผ๋ฆฌ ๊ณผ์ œ์— ์ ์šฉํ•œ ์ตœ์ดˆ ์‚ฌ๋ก€ ์ค‘ ํ•˜๋‚˜๋กœ ํ‰๊ฐ€ํ•  ์ˆ˜ ์žˆ๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ๋“ค์€ ์ฃผ๋กœ ๋กœ๋ด‡์ด ๊ต์œกยท์žฌํ™œยท๋™๊ธฐ ๋ถ€์—ฌ ์—ญํ• ์„ ์ˆ˜ํ–‰ํ•˜๋Š” ๋ฐ ์ดˆ์ ์„ ๋งž์ถ”์—ˆ์œผ๋ฉฐ, ์‚ฌ์šฉ์ž์˜ ์ˆ˜ํ–‰ ๋Šฅ๋ ฅ์„ ์ •๋Ÿ‰์ ์œผ๋กœ ์ธก์ •ํ•˜๋Š” ๋ฐฉ๋ฒ•๋ก ์€ ์ƒ๋Œ€์ ์œผ๋กœ ๋ถ€์กฑํ–ˆ๋‹ค. ์ด ์ ์—์„œ ์ €์ž๋“ค์€ Boxโ€‘andโ€‘Blocks Test๋ผ๋Š” ํ‘œ์ค€ํ™”๋œ ์‹ ๊ฒฝ์‹ฌ๋ฆฌ ๊ฒ€์‚ฌ ๋„๊ตฌ๋ฅผ ๋ณ€ํ˜•ํ•จ์œผ๋กœ์จ, ๋กœ๋ด‡์ด ์ธ๊ฐ„ ๊ต์‚ฌ์™€ ๋™์ผํ•œ ์—ญํ• ์„ ์ˆ˜ํ–‰ํ•˜๋ฉด์„œ๋„ ์ž๋™ํ™”๋œ ๋ฐ์ดํ„ฐ ์ˆ˜์ง‘์ด ๊ฐ€๋Šฅํ•˜๋„๋ก ์„ค๊ณ„ํ•˜

HCI Computer Science
Sensitivity analysis of a computational model of the   IKK-NF-{kappa}B-I{kappa}B{alpha}-A20 signal transduction network

Sensitivity analysis of a computational model of the IKK-NF-{kappa}B-I{kappa}B{alpha}-A20 signal transduction network

๋ณธ ๋…ผ๋ฌธ์€ NFโ€‘ฮบB ์‹ ํ˜ธ ์ „๋‹ฌ ๋„คํŠธ์›Œํฌ์˜ ๋ณตํ•ฉ์„ฑ์„ ์ •๋Ÿ‰์ ์œผ๋กœ ํ•ด์„ํ•˜๊ธฐ ์œ„ํ•ด โ€˜๋ฏผ๊ฐ๋„ ๋ถ„์„โ€™์ด๋ผ๋Š” ์‹œ์Šคํ…œ ์ƒ๋ฌผํ•™์  ์ ‘๊ทผ๋ฒ•์„ ์ฒด๊ณ„์ ์œผ๋กœ ์ ์šฉํ•œ ์ ์ด ๊ฐ€์žฅ ํฐ ๊ฐ•์ ์ด๋‹ค. ๋จผ์ € ๋ชจ๋ธ ์„ ํƒ์— ์žˆ์–ด Lipniacki ๋“ฑ(2010, 2011)์ด ์ œ์‹œํ•œ IKKโ€‘NFโ€‘ฮบBโ€‘IฮบBฮฑโ€‘A20 ๋„คํŠธ์›Œํฌ๋ฅผ ์ฑ„ํƒํ–ˆ๋Š”๋ฐ, ์ด๋Š” ๊ธฐ์กด Hoffmann ๋ชจ๋ธ์— ๋น„ํ•ด ๋‘ ๊ฐœ์˜ ์Œ์„ฑ ํ”ผ๋“œ๋ฐฑ( IฮบBฮฑ, A20 )์„ ๋ช…์‹œ์ ์œผ๋กœ ํฌํ•จํ•จ์œผ๋กœ์จ ์‹ค์ œ ์„ธํฌ ๋‚ด ์‹ ํ˜ธ ์–ต์ œ ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ๋ณด๋‹ค ํ˜„์‹ค์ ์œผ๋กœ ์žฌํ˜„ํ•œ๋‹ค๋Š” ์žฅ์ ์ด ์žˆ๋‹ค. ์„ธ ๊ฐ€์ง€ ์ƒ˜ํ”Œ๋ง ๋ฐฉ๋ฒ•์€ ๊ฐ๊ฐ ์žฅ๋‹จ์ ์ด ๋šœ๋ ทํ•˜๋‹ค. ๋‹จ์ผ

Quantitative Biology Model Network Analysis
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
A Massive Progenitor of the Luminous Type IIn Supernova 2010jl

A Massive Progenitor of the Luminous Type IIn Supernova 2010jl

๋ณธ ๋…ผ๋ฌธ์€ SN 2010jl์ด๋ผ๋Š” ๊ทน๋„๋กœ ๋ฐ์€ Type IIn ์ดˆ์‹ ์„ฑ์˜ ์ „๊ตฌ์ฒด๋ฅผ ์ง์ ‘ ํƒ์ƒ‰ํ•œ ์ตœ์ดˆ์˜ ์‚ฌ๋ก€ ์ค‘ ํ•˜๋‚˜๋กœ, ๊ทธ ๊ณผํ•™์  ์˜๋ฏธ๊ฐ€ ๋งค์šฐ ํฌ๋‹ค. ๋จผ์ € ์ €์ž๋“ค์€ ํญ๋ฐœ ์ „ HST ๋ณด๊ด€ ์ด๋ฏธ์ง€์™€ ํญ๋ฐœ ์งํ›„ ์ง€์ƒ๋ง์›๊ฒฝ ์ด๋ฏธ์ง€์˜ ์ •๋ฐ€ํ•œ ์ขŒํ‘œ ์ •ํ•ฉ์„ ํ†ตํ•ด ์ดˆ์‹ ์„ฑ ์œ„์น˜์™€ 1ฯƒ ์ด๋‚ด์— ์ผ์น˜ํ•˜๋Š” ํ‘ธ๋ฅธ ์ ์›์„ ํ™•์ธํ•˜์˜€๋‹ค. ์ด ์ ์›์˜ ์ ˆ๋Œ€ ๋“ฑ๊ธ‰(โˆ’12 mag)์€ ์ผ๋ฐ˜์ ์ธ ๊ฐœ๋ณ„ ์ฒญ์ƒ‰ํ•ญ์„ฑ๋ณด๋‹ค ์ˆ˜์‹ญ ๋ฐฐ ๋ฐ์œผ๋ฉฐ, ๋”ฐ๋ผ์„œ ๋‹จ์ผ ๋ณ„๋ณด๋‹ค๋Š” ์ง‘๋‹จ์ ์ธ ๊ด‘์›์ผ ๊ฐ€๋Šฅ์„ฑ์ด ๋†’๋‹ค. ์ €์ž๋“ค์€ ๋„ค ๊ฐ€์ง€ ์‹œ๋‚˜๋ฆฌ์˜ค๋ฅผ ์ œ์‹œํ–ˆ๋Š”๋ฐ, ํŠนํžˆ โ€˜๋‚˜์ด < 6 Myr์ธ ๊ฑฐ๋Œ€ํ•œ ์ฒญ์ƒ‰์„ฑ๋‹จโ€™๊ณผ

Astrophysics
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

General Relativity Astrophysics
Regularized Risk Minimization by Nesterovs Accelerated Gradient   Methods: Algorithmic Extensions and Empirical Studies

Regularized Risk Minimization by Nesterovs Accelerated Gradient Methods: Algorithmic Extensions and Empirical Studies

๋ณธ ๋…ผ๋ฌธ์€ Nesterov ๊ฐ€์† ๊ฒฝ์‚ฌ๋ฒ•(AGM)์„ ์ •๊ทœํ™” ์œ„ํ—˜ ์ตœ์†Œํ™”(RRM) ๋ฌธ์ œ์— ์ ์šฉํ•˜๊ธฐ ์œ„ํ•œ ์ด๋ก ์ ยท์‹คํ—˜์  ํ† ๋Œ€๋ฅผ ์ƒˆ๋กญ๊ฒŒ ๊ตฌ์ถ•ํ•œ๋‹ค๋Š” ์ ์—์„œ ์˜๋ฏธ๊ฐ€ ํฌ๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ์—์„œ๋Š” AGM์ด ์ผ๋ฐ˜์ ์ธ ๋ณผ๋ก ์ตœ์ ํ™”์—์„œ๋Š” (O(1/sqrt{varepsilon})) ์˜ ๋ณต์žก๋„๋กœ ๋›ฐ์–ด๋‚œ ์ˆ˜๋ ด ์†๋„๋ฅผ ๋ณด์˜€์ง€๋งŒ, SVM๊ณผ ๊ฐ™์€ ์ตœ๋Œ€โ€‘๋งˆ์ง„ ๋ชจ๋ธ์—์„œ๋Š” ๊ตฌ์กฐ์  ์ œ์•ฝ(์˜ˆ: ์ง€์› ๋ฒกํ„ฐ๊ฐ€ ๋Œ€๋ถ€๋ถ„ ๊ฒฝ๊ณ„์— ์œ„์น˜) ๋•Œ๋ฌธ์— ํšจ์œจ์„ฑ์ด ์ €ํ•˜๋˜๋Š” ๊ฒƒ์ด ์‹ค์ฆ๋˜์—ˆ๋‹ค. ์ €์ž๋“ค์€ ์ด๋Ÿฌํ•œ ํ•œ๊ณ„๋ฅผ ๊ทน๋ณตํ•˜๊ธฐ ์œ„ํ•ด ๋‘ ๊ฐ€์ง€ ํ•ต์‹ฌ ์ „๋žต์„ ์ œ์‹œํ•œ๋‹ค. ์ฒซ ๋ฒˆ์งธ๋Š” ๊ฒฝํ—˜ ์œ„ํ—˜ (R {

Computer Science Machine Learning
Search for gamma-ray emission from magnetars with the Fermi Large Area   Telescope

Search for gamma-ray emission from magnetars with the Fermi Large Area Telescope

๋ณธ ์—ฐ๊ตฌ๋Š” Fermiโ€‘LAT์ด ์ œ๊ณตํ•˜๋Š” ๋†’์€ ๊ฐ๋„์™€ ๋„“์€ ์‹œ์•ผ๋ฅผ ํ™œ์šฉํ•ด ๋งˆ๊ทธ๋„คํ„ฐ๋ผ๋Š” ํŠน์ˆ˜ํ•œ ๊ณ ์ž๊ธฐ์žฅ ์ค‘์„ฑ์ž๋ณ„ ์ง‘๋‹จ์˜ GeV ฮณโ€‘์„  ๋ฐฉ์ถœ ๊ฐ€๋Šฅ์„ฑ์„ ์ตœ์ดˆ๋กœ ์ฒด๊ณ„์ ์œผ๋กœ ๊ฒ€์ฆํ•˜์˜€๋‹ค. ๋ฐ์ดํ„ฐ๋Š” โ€œPass 6 Diffuseโ€ ์ด๋ฒคํŠธ ํด๋ž˜์Šค๋ฅผ ์‚ฌ์šฉํ•ด ๋ฐฐ๊ฒฝ์„ ์ตœ๋Œ€ํ•œ ์–ต์ œํ–ˆ์œผ๋ฉฐ, 20 MeVโ€“300 GeV ๊ตฌ๊ฐ„ ์ „์ฒด๋ฅผ ๋ถ„์„ํ•˜์˜€๋‹ค. ์†Œ์Šค๋ณ„๋กœ ์ˆ˜ํ–‰ํ•œ ์ตœ๋Œ€์šฐ๋„(โ€œTSโ€) ๊ฒ€์ •์—์„œ๋Š” ๋ชจ๋“  ๋Œ€์ƒ์— ๋Œ€ํ•ด TS < 25(ํ†ต๊ณ„์  ์œ ์˜๋ฏธ์„ฑ ๊ธฐ์ค€)๋กœ, ์‹ค์ œ ์‹ ํ˜ธ๊ฐ€ ์กด์žฌํ•˜์ง€ ์•Š์Œ์„ ํ™•์ธํ–ˆ๋‹ค. ์ƒํ•œ์„  ์ถ”์ •์€ ๊ฐ ๋งˆ๊ทธ๋„คํ„ฐ์˜ ์œ„์น˜์™€ ๊ฑฐ๋ฆฌ, ๊ทธ๋ฆฌ๊ณ  ์•Œ๋ ค์ง„ Xโ€‘rayยท์†Œํ”„ํŠธ

Astrophysics
Timed Parity Games: Complexity and Robustness

Timed Parity Games: Complexity and Robustness

๋ณธ ๋…ผ๋ฌธ์€ ์‹ค์‹œ๊ฐ„ ์‹œ์Šคํ…œ ์„ค๊ณ„ยท๊ฒ€์ฆ ๋ถ„์•ผ์—์„œ ํ•ต์‹ฌ์ ์ธ ๋‘ ๋ฌธ์ œ, ๋ณต์žก๋„ ๊ฐ์†Œ ์™€ ์ „๋žต์˜ ๊ฐ•์ธ์„ฑ ์„ ๋™์‹œ์— ๋‹ค๋ฃจ๊ณ  ์žˆ๋‹ค. ๋จผ์ €, ํƒ€์ž„๋“œ ์˜คํ† ๋งˆํ†ค ์œ„์—์„œ ๋™์‹œ์ ์œผ๋กœ ํ–‰๋™๊ณผ ์ง€์—ฐ์„ ์ œ์•ˆํ•˜๋Š” ๊ฒŒ์ž„์€ ๋ณธ์งˆ์ ์œผ๋กœ ๋ฌดํ•œ ์ƒํƒœยท๋ฌดํ•œ ์‹œ๊ฐ„ ๊ณต๊ฐ„์„ ๊ฐ–๋Š”๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ์—์„œ๋Š” ์ด๋Ÿฌํ•œ ๊ฒŒ์ž„์„ ์ง์ ‘ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ๋ณต์žก๋„๊ฐ€ EXPTIME ์ˆ˜์ค€์— ์ด๋ฅด๋Š” ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด ์ œ์‹œ๋˜์—ˆ์œผ๋ฉฐ, ์‹ค์ œ ์ ์šฉ์— ํ•œ๊ณ„๊ฐ€ ์žˆ์—ˆ๋‹ค. ์ €์ž๋“ค์€ ์‹œ๊ณ„ ์˜์—ญ(clock regions) ๊ฐœ๋…์„ ํ™œ์šฉํ•ด ๋ฌดํ•œ ์ƒํƒœ ๊ณต๊ฐ„์„ ์œ ํ•œํ•œ ์˜์—ญ ๊ทธ๋ž˜ํ”„๋กœ ์ถ”์ƒํ™”ํ•œ๋‹ค๋Š” ์ ์—์„œ ๊ธฐ์กด ์ ‘๊ทผ๋ฒ•๊ณผ ์ฐจ๋ณ„ํ™”๋œ๋‹ค. ์ค‘์š”ํ•œ ์ 

Logic Computer Science

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