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A construction of noncontractible simply connected cell-like two   dimensional Peano continua

A construction of noncontractible simply connected cell-like two dimensional Peano continua

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋™๊ธฐ ์…€โ€‘๋ผ์ดํฌ ๋‹ค๋ฉด์ฒด์™€ ์ˆ˜์ถ•์„ฑ : ์ „ํ†ต์ ์œผ๋กœ ์…€โ€‘๋ผ์ดํฌ ๋‹ค๋ฉด์ฒด๋Š” ๋ชจ๋‘ ์ˆ˜์ถ• ๊ฐ€๋Šฅํ•˜๋‹ค๋Š” ์‚ฌ์‹ค์ด ์•Œ๋ ค์ ธ ์žˆ๋‹ค. Griffiths๋Š” 2์ฐจ์› ๋น„๋‹จ์ˆœ์—ฐ๊ฒฐ ์…€โ€‘๋ผ์ดํฌ ํ”ผ์•„๋…ธ ์—ฐ์†์ฒด๋ฅผ ๊ตฌ์„ฑํ•จ์œผ๋กœ์จ ์ด์™€ ๋ฐ˜๋Œ€๋˜๋Š” ์˜ˆ์‹œ๋ฅผ ์ œ์‹œํ–ˆ์œผ๋ฉฐ, ๊ทธ ์ผ๋ฐ˜ํ™”๊ฐ€ 3์ฐจ์› ๋น„์ˆ˜์ถ•์„ฑยท๋‹จ์ˆœ์—ฐ๊ฒฐ ์˜ˆ์‹œ๋กœ ์ด์–ด์กŒ๋‹ค. ํ•จ์ž์  ์ ‘๊ทผ : ๊ธฐ์กด ์˜ˆ์‹œ๋“ค์€ ๊ฐœ๋ณ„์ ์ธ ๊ตฌ์กฐ์— ์˜์กดํ–ˆ์ง€๋งŒ, ๋ณธ ๋…ผ๋ฌธ์€ ํ•จ์ž (SC) ๋ฅผ ํ†ตํ•ด ๋ฒ”์šฉ์ ์ธ ๋ณ€ํ™˜ ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ์ œ๊ณตํ•œ๋‹ค. ์ด๋Š” โ€œ์ž…๋ ฅ โ†’ ์ถœ๋ ฅโ€์ด ํ•จ์ˆ˜์  ์ด๋ฉฐ, ๋ณตํ•ฉ์ ์ธ ์œ„์ƒ๊ณต๊ฐ„์„ ์ฒด๊ณ„์ ์œผ๋กœ ๋‹ค๋ฃฐ ์ˆ˜ ์žˆ๊ฒŒ ํ•œ๋‹ค๋Š” ์ ์—์„œ ํฐ ์˜๋ฏธ๊ฐ€

Mathematics
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A Generalized Sampling Theorem for Frequency Localized Signals

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋™๊ธฐ ์‹œ๊ฐ„โ€‘์ฃผํŒŒ์ˆ˜ ๋กœ์ปฌ๋ผ์ด์ œ์ด์…˜ ์€ ์‹ ํ˜ธ๊ฐ€ ์‹œ๊ฐ„ยท์ฃผํŒŒ์ˆ˜ ์–‘์ชฝ์—์„œ ๊ธ‰๊ฒฉํžˆ ๊ฐ์†Œํ•˜๋Š” ํŠน์„ฑ์„ ์˜๋ฏธํ•œ๋‹ค(๋ฌธํ—Œ

Information Theory Mathematics Computer Science
A Handy Tool for History Keeping of Geant4 Tracks and its Application to   Studies of Fundamental Limits on PFA Performance

A Handy Tool for History Keeping of Geant4 Tracks and its Application to Studies of Fundamental Limits on PFA Performance

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉํ‘œ ์ œํŠธ ์—๋„ˆ์ง€ ๋ถ„ํ•ด๋Šฅ ์€ W/Z ๋ฐ ์ƒˆ๋กœ์šด ์ž…์ž(Higgs ๋“ฑ)์˜ ์งˆ๋Ÿ‰ ์ธก์ •์— ํ•ต์‹ฌ์ด๋ฉฐ, ๋ชฉํ‘œ๋Š” ์ž์—ฐํญ(โ‰ˆ2โ€“3 GeV) ์ˆ˜์ค€๊นŒ์ง€ ๋„๋‹ฌํ•˜๋Š” ๊ฒƒ์ด๋‹ค. Particle Flow Analysis (PFA) ๋Š” ํŠธ๋ž˜์ปค์—์„œ ์–ป์€ ์ „ํ•˜ ์ž…์ž ์ •๋ณด๋ฅผ ๊ทธ๋Œ€๋กœ ์‚ฌ์šฉํ•˜๊ณ , ์ค‘์„ฑ ์ž…์ž๋งŒ ์นผ๋ฆฌ๋ฏธํ„ฐ์— ์˜์กดํ•จ์œผ๋กœ์จ ์ตœ์ ์˜ ์—๋„ˆ์ง€ ํ•ฉ์„ฑ์„ ๋ชฉํ‘œ๋กœ ํ•œ๋‹ค. ๊ธฐ์กด PFA ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ ์•„์ง ๋ฏธ์„ฑ์ˆ™ํ•˜๊ณ , ํ•˜๋“œ์›จ์–ด(๊ณ ์ž…์ž๋ฐ€๋„ ์นผ๋ฆฌ๋ฏธํ„ฐ)์™€ ์†Œํ”„ํŠธ์›จ์–ด(ํด๋Ÿฌ์Šคํ„ฐ๋งยท๋งค์นญ) ๋‘ ์ถ• ๋ชจ๋‘์— ์˜์กดํ•œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์˜ ํ•ต์‹ฌ ๋ชฉํ‘œ๋Š” โ€˜์ด์ƒ์ ์ธโ€™ PFA (Cheated

Physics
A Six Degree-Of-Freedom Haptic Device Based On The Orthoglide And A   Hybrid Agile Eye

A Six Degree-Of-Freedom Haptic Device Based On The Orthoglide And A Hybrid Agile Eye

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ํ•„์š”์„ฑ VRยทAR ํ™˜๊ฒฝ์—์„œ ์ด‰๊ฐ ํ”ผ๋“œ๋ฐฑ ์€ ์‹œ๊ฐยท์ฒญ๊ฐ์— ๋น„ํ•ด ๊ตฌํ˜„ ๋‚œ์ด๋„๊ฐ€ ๋†’์œผ๋ฉฐ, ํ˜„์žฌ ์ƒ์šฉ ๋””๋ฐ”์ด์Šค(์˜ˆ: Phantom Desktop)๋Š” 3โ€‘DOF ํž˜ ํ”ผ๋“œ๋ฐฑ๋งŒ ์ œ๊ณตํ•œ๋‹ค. 6โ€‘DOF ์ด‰๊ฐ ๋””๋ฐ”์ด์Šค๋Š” ํž˜ + ํ† ํฌ ๋ฅผ ๋™์‹œ์— ์ „๋‹ฌํ•ด ๋ฌผ์ฒด ์กฐ์ž‘ยท์กฐ๋ฆฝ ์‹œ ์‹ค์ œ๊ฐ ํ–ฅ์ƒ์ด ๊ฐ€๋Šฅํ•˜์ง€๋งŒ, ๊ณ ๊ด€์„ฑยท๋ณต์žกํ•œ ๊ธฐ๊ตฌํ•™ ์ด ์‹ค์‹œ๊ฐ„ ์ œ์–ด๋ฅผ ๋ฐฉํ•ดํ•œ๋‹ค. ๋ณ‘๋ ฌ ๋ฉ”์ปค๋‹ˆ์ฆ˜์€ ๊ณ ๊ฐ•์„ฑยท์ €๊ด€์„ฑ ์„ ์ œ๊ณตํ•˜์ง€๋งŒ, ํšŒ์ „ ์ž์œ ๋„ ํ™•๋ณด์™€ ์ž‘์—…๊ณต๊ฐ„ ํ˜•ํƒœ(๋น„์ •๊ทœ) ๋ฌธ์ œ๊ฐ€ ์žˆ๋‹ค. 2. ์ฃผ์š” ๊ธฐ์—ฌ | ๊ตฌ๋ถ„ | ๋‚ด์šฉ | ์˜์˜ | | | | | | ๊ธฐ๊ตฌ ์„ค๊ณ„ | Ort

Robotics Computer Science
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An integrable discretization of the rational su(2) Gaudin model and related systems

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋™๊ธฐ ๊ฐ€์šฐ๋”˜ ๋ชจ๋ธ์€ 1970๋…„๋Œ€ ์ดˆ๋ฐ˜์— ์ œ์‹œ๋œ ์ดํ›„, ๊ณ ์ „ยท์–‘์ž ์Šคํ•€ ์ฒด์ธ์˜ ์žฅ๊ฑฐ๋ฆฌ ์ƒํ˜ธ์ž‘์šฉ์„ ๊ธฐ์ˆ ํ•˜๋Š” ๋Œ€ํ‘œ์ ์ธ ์ ๋ถ„ ๊ฐ€๋Šฅ ๋ชจ๋ธ๋กœ ์ž๋ฆฌ ์žก์•˜๋‹ค. ํŠนํžˆ su(2) ๋Œ€์ˆ˜์— ๊ธฐ๋ฐ˜ํ•œ ์œ ๋ฆฌํ˜• ๊ฐ€์šฐ๋”˜ ๋ชจ๋ธ์€ ๋ผ๊ทธ๋ž‘์ฃผ ํ† ํ”„, ํด๋ ˆ์‹œ ์‹œ์Šคํ…œ ๋“ฑ ๊ณ ์ „์—ญํ•™์˜ ์œ ๋ช…ํ•œ ์ ๋ถ„ ๊ฐ€๋Šฅ ์‹œ์Šคํ…œ๊ณผ ์ง์ ‘์ ์ธ ์—ฐ๊ด€์„ฑ์„ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. ์ตœ๊ทผ์—๋Š” ์–‘์ž์—ญํ•™, ์‘์ง‘๋ฌผ์งˆ ๋ฌผ๋ฆฌ, ๊ทธ๋ฆฌ๊ณ  ์ˆ˜ํ•™์  ๋ฌผ๋ฆฌ(์˜ˆ: Langlands ๋Œ€์‘, Seibergโ€‘Witten ์ด๋ก ) ๋“ฑ ๋‹ค์–‘ํ•œ ๋ถ„์•ผ์—์„œ ์žฌ์กฐ๋ช…๋˜๊ณ  ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ด๋Ÿฌํ•œ ๋ชจ๋ธ๋“ค์˜ ์‹œ๊ฐ„ ์ด์‚ฐํ™” โ€”์ฆ‰, ์—ฐ์† ํ๋ฆ„์„ ๋ณด์กด

Model System Nonlinear Sciences MATH-PH Mathematics
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Arrival Time Statistics in Global Disease Spread

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋ฌธ์ œ ์ •์˜ ๋ฉ”ํƒ€์ธ๊ตฌ ๋ชจ๋ธ ์€ ๊ฐ ๋„์‹œ๋ฅผ ํ•˜๋‚˜์˜ โ€œ๋…ธ๋“œโ€๋กœ, ๋„์‹œ ๋‚ด๋ถ€๋Š” ํ‰๊ท ์žฅ ๋ชจ๋ธ(SI, SIS, SIR ๋“ฑ)๋กœ, ๋„์‹œ ๊ฐ„ ์ „ํŒŒ๋Š” ์‚ฌ๋žŒ ์ด๋™(ํ•ญ๊ณต, ์ฒ ๋„ ๋“ฑ)์œผ๋กœ ๊ตฌํ˜„ํ•œ๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ๋Š” ์ „์—ผ๋ณ‘ ํ™•์‚ฐ์˜ ์ „๋ฐ˜์  ๊ทœ๋ชจ (์˜ˆ: ๊ฐ์—ผ์ž ์ˆ˜, ํŒŒ๋™ ์ „ํŒŒ ์†๋„)์—๋Š” ์ดˆ์ ์„ ๋งž์ท„์ง€๋งŒ, ํŠน์ • ๋„์‹œ์—์„œ ์ตœ์ดˆ ๊ฐ์—ผ์ž๊ฐ€ ๋„์ฐฉํ•˜๋Š” ์‹œ์ (Arrival Time) ์€ ๊ฑฐ์˜ ๋‹ค๋ฃจ์ง€ ์•Š์•˜๋‹ค. ๋„์ฐฉ ์‹œ๊ฐ์€ ๊ณต์ค‘๋ณด๊ฑด ๋Œ€์‘ (๋ฐฑ์‹ ยทํ•ญ์ƒ์ œ ๋ฐฐ๋ถ„, ๊ฒฉ๋ฆฌ ์ •์ฑ…)์—์„œ ํ•ต์‹ฌ์ ์ธ ์˜์‚ฌ๊ฒฐ์ • ๋ณ€์ˆ˜์ด๋ฏ€๋กœ, ์ด๋ฅผ ๋„คํŠธ์›Œํฌ ์ด๋ก ๊ณผ ๊ฒฐํ•ฉํ•ด ์˜ˆ์ธกํ•˜๋Š” ๊ฒƒ์ด ๋ณธ ๋…ผ๋ฌธ์˜ ํ•ต

Quantitative Biology
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Bayesian segmentation of hyperspectral images

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ํ•„์š”์„ฑ ์ดˆ๋ถ„๊ด‘ ์ด๋ฏธ์ง€ ๋Š” ์ˆ˜๋ฐฑ ๊ฐœ์— ๋‹ฌํ•˜๋Š” ์ŠคํŽ™ํŠธ๋Ÿผ ๋ฐด๋“œ๋ฅผ ์ œ๊ณตํ•ด ๋ฌผ์งˆ ๊ตฌ๋ถ„์— ๋›ฐ์–ด๋‚œ ์ •๋ณด๋ฅผ ๋‹ด๊ณ  ์žˆ์ง€๋งŒ, ๋ฐ์ดํ„ฐ ์–‘์ด ๋ฐฉ๋Œ€ํ•ด ์ „ํ†ต์ ์ธ ๋ถ„๋ฅ˜ยท์„ธ๋ถ„ํ™” ๊ธฐ๋ฒ•์œผ๋กœ๋Š” ์ถฉ๋ถ„ํ•œ ์„ฑ๋Šฅ์„ ๋‚ด๊ธฐ ์–ด๋ ต๋‹ค. ๊ธฐ์กด์˜ ๋‹ค์ค‘ยท๋‹ค์ŠคํŽ™ํŠธ๋Ÿผ ์ด๋ฏธ์ง€ ์„ธ๋ถ„ํ™” ๋ฐฉ๋ฒ•์€ ๋ฐด๋“œ ๊ฐ„ ๋…๋ฆฝ์„ฑ ์„ ์ „์ œ๋กœ ํ•˜์—ฌ, ์ดˆ๋ถ„๊ด‘ ๋ฐ์ดํ„ฐ์˜ ์ŠคํŽ™ํŠธ๋Ÿผ ์—ฐ์†์„ฑ ์„ ํ™œ์šฉํ•˜์ง€ ๋ชปํ•œ๋‹ค. 2. ํ•ต์‹ฌ ์•„์ด๋””์–ด | ์š”์†Œ | ๊ธฐ์กด ์ ‘๊ทผ | ๋ณธ ๋…ผ๋ฌธ์˜ ์ ‘๊ทผ | | | | | | ๋ ˆ์ด๋ธ” ๋ชจ๋ธ๋ง | ๋…๋ฆฝ์ ์ธ ๋ ˆ์ด๋ธ” ํ˜น์€ ๋‹จ์ˆœ ๊ณต๊ฐ„ ๋งˆ์ฝ”ํ”„ | ๊ณตํ†ต ๋ ˆ์ด๋ธ” z ๋ฅผ ๋ชจ๋“  ๋ฐด๋“œ์— ์ ์šฉ, ํฌ์ธ  MRF

Physics
Classification of interest rate curves using Self-Organising Maps

Classification of interest rate curves using Self-Organising Maps

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์  ๊ธˆ๋ฆฌ๊ณก์„ ์˜ ์ค‘์š”์„ฑ : ๊ธˆ๋ฆฌ๊ณก์„ ์€ ์ค‘์•™์€ํ–‰ ์ •์ฑ…, ์ฑ„๊ถŒ ๊ฐ€๊ฒฉ, ํŒŒ์ƒ์ƒํ’ˆ ๊ฐ€์น˜ ํ‰๊ฐ€ ๋“ฑ ๊ธˆ์œต ์ „๋ฐ˜์— ๊ฑธ์ณ ํ•ต์‹ฌ ์ž…๋ ฅ๊ฐ’์ด๋‹ค. ์ „ํ†ต์  ๋ชจ๋ธ ํ•œ๊ณ„ : Nelsonโ€‘Siegel ๋“ฑ ํŒŒ๋ผ๋ฉ”ํŠธ๋ฆญ ๋ชจ๋ธ์€ 3๊ฐœ์˜ ์š”์ธ(level, slope, curvature)์œผ๋กœ ์š”์•ฝํ•˜์ง€๋งŒ, ๋น„์„ ํ˜•ยท๋น„์ •์ƒ์  ๋ณ€๋™์„ ์ถฉ๋ถ„ํžˆ ํฌ์ฐฉํ•˜์ง€ ๋ชปํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ ๋ชฉํ‘œ : ๋น„์ง€๋„ ํ•™์Šต์ธ SOM์„ ์ด์šฉํ•ด ๊ธˆ๋ฆฌ๊ณก์„ ์„ ๊ณ ์ฐจ์› ๊ณต๊ฐ„์— ๊ทธ๋Œ€๋กœ ๋‘๊ณ , ๋ฐ์ดํ„ฐ ์ž์ฒด๊ฐ€ ๋“œ๋Ÿฌ๋‚ด๋Š” ๊ตฐ์ง‘ ๊ตฌ์กฐ๋ฅผ ํƒ์ƒ‰ํ•จ์œผ๋กœ์จ โ€œ์ „ํ˜•์ ์ธ ๊ธˆ๋ฆฌ๊ณก์„  ํ˜•ํƒœโ€๋ฅผ ๋ฐœ๊ฒฌํ•˜๊ณ , ์‹œ๊ฐ„์— ๋”ฐ๋ฅธ ๋ณ€๋™ ํŒจํ„ด์„ ํ•ด

Physics
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Cohomology theories for homotopy algebras and noncommutative geometry

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋™๊ธฐ โˆžโ€‘๋Œ€์ˆ˜์˜ ์ค‘์š”์„ฑ : $A infty$, $C infty$, $L infty$โ€‘๋Œ€์ˆ˜๋Š” ์ „ํ†ต์ ์ธ ์—ฐ์‚ฐ์ž ๋Œ€์ˆ˜๋ฅผ ๊ณ ์ฐจ ์—ฐ์‚ฐ์œผ๋กœ ํ™•์žฅํ•œ ๊ตฌ์กฐ๋กœ, Hโ€‘๊ณต๊ฐ„, ๋ฌธ์ž์—ด์žฅ ์ด๋ก , ์œ„์ƒ ฮฃโ€‘๋ชจ๋ธ ๋“ฑ ๋ฌผ๋ฆฌยท์ˆ˜ํ•™ ์ „๋ฐ˜์— ๊ฑธ์ณ ํ•ต์‹ฌ ์—ญํ• ์„ ํ•œ๋‹ค. ๊ธฐ์กด ์ ‘๊ทผ์˜ ํ•œ๊ณ„ : ์ „ํ†ต์ ์ธ ์ •์˜๋Š” ๋ณต์žกํ•œ ๊ณ ์ฐจ ๊ณฑ์…ˆ ์—ฐ์‚ฐ $m n$๋“ค์˜ ๊ด€๊ณ„์‹์— ์˜์กดํ•ด ๊ณ„์‚ฐ์ด ๋‚œํ•ดํ•˜๊ณ , ์ฝ”ํ˜ธ๋ชฐ๋กœ์ง€ ์ด๋ก ์„ ๋‹ค๋ฃฐ ๋•Œ๋Š” ๋ณต์žกํ•œ ์กฐํ•ฉ๋ก ์ด ํ•„์—ฐ์ ์œผ๋กœ ๋“ฑ์žฅํ•œ๋‹ค. ๋น„๊ฐ€ํ™˜ ๊ธฐํ•˜ํ•™๊ณผ์˜ ์—ฐ๊ฒฐ : Connesโ€‘Kontsevich์˜ ๋น„๊ฐ€ํ™˜ ๊ธฐํ•˜ํ•™์€ โ€œ๋น„๊ฐ€ํ™˜ ํ•จ์ˆ˜๋Œ€โ€๋ฅผ โ€˜๋น„๊ฐ€ํ™˜

Mathematics
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Communication under Strong Asynchronism

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋ฌธ์ œ ์„ค์ • ์ „ํ†ต์ ์ธ ์ •๋ณด์ด๋ก ์€ ์†ก์‹ ยท์ˆ˜์‹ ์ด ์™„๋ฒฝํžˆ ๋™๊ธฐํ™”๋œ ์ƒํ™ฉ์„ ์ „์ œ๋กœ ์ฑ„๋„ ์šฉ๋Ÿ‰์„ ์ •์˜ํ•œ๋‹ค. ์‹ค์ œ ๋ฌด์„ ยท์„ผ์„œ ๋„คํŠธ์›Œํฌ์—์„œ๋Š” ๋ฒ„์ŠคํŠธํ˜• ํŠธ๋ž˜ํ”ฝ์ด ์ผ๋ฐ˜์ ์ด๋ฉฐ, ์†ก์‹  ์‹œ์ ์ด ์ˆ˜์‹ ๊ธฐ์— ์•Œ๋ ค์ง€์ง€ ์•Š์€ ๋น„๋™๊ธฐ์„ฑ ์ด ํฐ ๋ฌธ์ œ๋กœ ๋– ์˜ค๋ฅธ๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ๋Š” ๋‹ค์ค‘์ ‘์†(MAC)์ด๋‚˜ ์‚ฝ์ž…ยท์‚ญ์ œ ์ฑ„๋„ ๋“ฑ์—์„œ ๋น„๋™๊ธฐ์„ฑ์„ ๋‹ค๋ฃจ์—ˆ์ง€๋งŒ, ์ ๋Œ€์  DMC ์—์„œ ๋น„๋™๊ธฐ์„ฑ์˜ ๊ทผ๋ณธ์ ์ธ ํ•œ๊ณ„์™€ ๊ฐ€๋Šฅํ•œ ์ „์†ก๋ฅ ์„ ์ฒด๊ณ„์ ์œผ๋กœ ๋ถ„์„ํ•œ ์—ฐ๊ตฌ๋Š” ๋“œ๋ฌผ๋‹ค. 2. ๋ชจ๋ธ๋ง์˜ ํ•ต์‹ฌ ์š”์†Œ ์ฑ„๋„ : ์ž…๋ ฅ ์•ŒํŒŒ๋ฒณ (mathcal{X}), ์ถœ๋ ฅ ์•ŒํŒŒ๋ฒณ (mathcal{Y}

Information Theory Mathematics Computer Science
Complexite des boreliens `a coupes denombrables

Complexite des boreliens `a coupes denombrables

| ๊ตฌ๋ถ„ | ๋‚ด์šฉ | | | | | ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ | Hurewicz ์ •๋ฆฌ๋Š” ๊ณ ์ „์ ์ธ Baire ๊ณ„์ธต์—์„œ (Pi^0 2) (G( delta))๊ฐ€ ์•„๋‹Œ ์ง‘ํ•ฉ์„ ๊ตฌ๋ถ„ํ•˜๋Š” ๋Œ€ํ‘œ์ ์ธ ๋„๊ตฌ์ด๋‹ค. Louveauโ€‘Saintโ€‘Raymond์ด ์ด๋ฅผ ์ „์ด ๊ณ„์ธต ์ „์ฒด๋กœ ํ™•์žฅํ–ˆ์œผ๋ฉฐ, ์ตœ๊ทผ์—๋Š” โ€œ์ž ์žฌ์ โ€(potential) ํด๋ž˜์Šค ๊ฐœ๋…์„ ๋„์ž…ํ•ด ํ† ํด๋กœ์ง€๋ฅผ ๋ฏธ์„ธํ•˜๊ฒŒ ๋ฐ”๊พธ์–ด๋„ ํŠน์ • ๋ณต์žก๋„์— ์†ํ•˜์ง€ ์•Š๋Š” ์ง‘ํ•ฉ์„ ์—ฐ๊ตฌํ•˜๊ณ  ์žˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ ์ด๋Ÿฌํ•œ ํ๋ฆ„์„ โ€œ๊ฐ€์‚ฐ ๋‹จ๋ฉดโ€์ด๋ผ๋Š” ์ถ”๊ฐ€ ์ œ์•ฝ ํ•˜์— ์ „์ด์‹œํ‚จ๋‹ค. | | ํ•ต์‹ฌ ์ •์˜ | pot((Gamma)) :

Mathematics
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Consistency of support vector machines for forecasting the evolution of an unknown ergodic dynamical system from observations with unknown noise

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋ฌธ์ œ ์ •์˜ Ergodic ๋™์—ญํ•™ ์‹œ์Šคํ…œ ((F^n) {nge0}) ์€ ์•Œ๋ ค์ง€์ง€ ์•Š์€ ๋งคํ•‘ (F:Mto M) (compact (Msubsetmathbb{R}^d)) ๋กœ ์ •์˜๋˜๊ณ , ๊ณ ์œ ํ•œ ergodic ์ธก๋„ (mu) ๋ฅผ ๊ฐ€์ง„๋‹ค. ๊ด€์ธก๊ฐ’์€ additive ์žก์Œ (varepsilon n) ๊ฐ€ ์„ž์ธ ํ˜•ํƒœ (X n F^n(x 0)+varepsilon n) ๋กœ ์ฃผ์–ด์ง€๋ฉฐ, ์žก์Œ ๊ณผ์ •์€ ์ •์ƒ(stationary) ์ด์ง€๋งŒ ๋ถ„ํฌ (nu) ์—ญ์‹œ ๋ฏธ์ง€์ด๋‹ค. ๋ชฉํ‘œ๋Š” ์œ ํ•œํ•œ ๊ด€์ธก ์‹œํ€€์Šค (T {X

System Mathematics Statistics
Constraint optimization and landscapes

Constraint optimization and landscapes

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋™๊ธฐ ์ œ์•ฝ ์ตœ์ ํ™” ๋Š” ๋ฌผ๋ฆฌํ•™(์œ ๋ฆฌ ์‹œ์Šคํ…œ)๊ณผ ์ปดํ“จํ„ฐ ๊ณผํ•™(๋…ผ๋ฆฌ์‹ ๋งŒ์กฑ, ๊ทธ๋ž˜ํ”„ ์ƒ‰์น ) ์‚ฌ์ด์˜ ๊ต์ฐจ์ ์— ์žˆ๋‹ค. ๊ธฐ์กด ๋ฌธํ—Œ์—์„œ๋Š” Random Close Packing (RCP) , optimal random packing , Jโ€‘point ๋“ฑ ์„œ๋กœ ๋‹ค๋ฅธ ์šฉ์–ด๊ฐ€ ํ˜ผ์šฉ๋ผ ํ˜ผ๋ž€์„ ์•ผ๊ธฐํ•œ๋‹ค. SATยทColoring ๋ถ„์•ผ์—์„œ๋Š” ๋™์ (ํด๋Ÿฌ์Šคํ„ฐ๋ง) ์ „์ด ฮฑ d ์ดํ›„ ๋ฌธ์ œ๊ฐ€ โ€˜hardโ€™ํ•ด์ง„๋‹ค๊ณ  ๋ฏฟ์—ˆ์ง€๋งŒ, ์‹ค์ œ๋กœ๋Š” ๋งค์šฐ ๋‹จ์ˆœํ•œ ์•Œ๊ณ ๋ฆฌ์ฆ˜๋„ ฮฑ d๋ฅผ ํ›จ์”ฌ ์ดˆ๊ณผํ•ด ํ•ด๋ฅผ ์ฐพ๋Š”๋‹ค. 2. ํ•ต์‹ฌ ์•„์ด๋””์–ด | ์š”์†Œ | ์„ค๋ช… | ๊ธฐ์กด ๊ฐœ๋…๊ณผ์˜ ์ฐจ์ด

Condensed Matter Computer Science Quantum Physics Nonlinear Sciences Computational Complexity
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Credit risk - A structural model with jumps and correlations

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋™๊ธฐ ๋ฌผ๋ฆฌํ•™โ€‘๊ธˆ์œต ๊ต์ฐจ์  : ์ตœ๊ทผ ๋ฌผ๋ฆฌํ•™์ž๋“ค์ด ๋ณต์žก๊ณ„ยทํ†ต๊ณ„๋ฌผ๋ฆฌํ•™ ๋„๊ตฌ๋ฅผ ๊ธˆ์œต์‹œ์žฅ์— ์ ์šฉํ•˜๋ฉด์„œ, ํŠนํžˆ โ€œfatโ€‘tailโ€ ํ˜„์ƒ์„ ์„ค๋ช…ํ•˜๋ ค๋Š” ์‹œ๋„๊ฐ€ ํ™œ๋ฐœํžˆ ์ง„ํ–‰๋˜๊ณ  ์žˆ๋‹ค. ์‹ ์šฉ์œ„ํ—˜์˜ ํŠน์ˆ˜์„ฑ : ์‹œ์žฅ์œ„ํ—˜๊ณผ ๋‹ฌ๋ฆฌ ์†์‹ค๋ถ„ํฌ๊ฐ€ ๊ฐ•ํ•˜๊ฒŒ ๋น„๋Œ€์นญ์ด๋ฉฐ, ๊ทน๋‹จ ์†์‹ค(ํ…Œ์ผ ์œ„ํ—˜)์ด ์‹ค์งˆ์ ์ธ ์ž๋ณธ ์†์‹ค์„ ์ดˆ๋ž˜ํ•œ๋‹ค. ๋”ฐ๋ผ์„œ ํ‰๊ท ยท๋ถ„์‚ฐ๋งŒ์œผ๋กœ๋Š” ์œ„ํ—˜์„ ์ถฉ๋ถ„ํžˆ ํ‰๊ฐ€ํ•  ์ˆ˜ ์—†์œผ๋ฉฐ, ๊ผฌ๋ฆฌ ์œ„ํ—˜์„ ์ •๋Ÿ‰ํ™”ํ•˜๋Š” ๋ชจ๋ธ์ด ํ•„์š”ํ•˜๋‹ค. 2. ๋ชจ๋ธ ์„ค๊ณ„ | ์š”์†Œ | ๋‚ด์šฉ | ๋ฌผ๋ฆฌํ•™์  ํ•ด์„ | | | | | | ๊ธฐ์ดˆ ํ”„๋กœ์„ธ์Šค | ๊ธฐ์—… ์ž์‚ฐ (A i(t)) ๋ฅผ

Quantitative Finance Condensed Matter Physics Model
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Critical Line in Random Threshold Networks with Inhomogeneous Thresholds

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋™๊ธฐ ๋ณต์žก๊ณ„ ๋„คํŠธ์›Œํฌ์™€ ๋™์—ญํ•™ : ์‹ ๊ฒฝ๋ง, ์œ ์ „์ž ์กฐ์ ˆ๋ง, ์ „๋ ฅ๋ง ๋“ฑ ๋‹ค์–‘ํ•œ ์‹ค์„ธ๊ณ„ ์‹œ์Šคํ…œ์€ ๋Œ€๊ทœ๋ชจ ์ƒํ˜ธ์ž‘์šฉ์„ ๊ฐ–๋Š”๋‹ค. Kauffman์˜ ๋žœ๋ค Boolean ๋„คํŠธ์›Œํฌ(RBN)๋Š” ์ด๋Ÿฌํ•œ ์‹œ์Šคํ…œ์„ ๋ชจ๋ธ๋งํ•˜๋Š” ๋Œ€ํ‘œ์  ํ”„๋ ˆ์ž„์›Œํฌ์˜€์ง€๋งŒ, ๊ณ„์‚ฐ ๋ณต์žก๋„์™€ ๋น„์„ ํ˜•์„ฑ ๋•Œ๋ฌธ์— ๋‹จ์ˆœํ™”๋œ ๋ชจ๋ธ์ด ํ•„์š”ํ–ˆ๋‹ค. RTN์˜ ์žฅ์  : RTN์€ ์ž…๋ ฅ ๊ฐ€์ค‘์น˜์™€ ์ž„๊ณ„๊ฐ’์„ ์ด์šฉํ•ด ์ด์ง„ ์ƒํƒœ๋ฅผ ๊ฒฐ์ •ํ•˜๋ฏ€๋กœ, RBN๋ณด๋‹ค ๊ณ„์‚ฐ๋Ÿ‰์ด ์ ๊ณ  ๋ถ„์„์ด ์šฉ์ดํ•˜๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๊ธฐ์กด ์—ฐ๊ตฌ๋Š” ์ฃผ๋กœ ๋™์งˆ ์ž„๊ณ„๊ฐ’ (๋ชจ๋“  ๋…ธ๋“œ๊ฐ€ ๊ฐ™์€ (h))์— ์ดˆ์ ์„ ๋งž์ถ”์—ˆ์œผ๋ฉฐ, ์ด์งˆ ์ž„๊ณ„๊ฐ’ ์ด

Condensed Matter Quantitative Biology Nonlinear Sciences Network
Design of moveable and resizable graphics

Design of moveable and resizable graphics

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋ฌธ์ œ ์ •์˜ ๋‘ ๋‹จ๊ณ„์˜ UI ํŒจ๋Ÿฌ๋‹ค์ž„ : ์œˆ๋„์šฐ ๋ ˆ๋ฒจ(์ƒ์œ„)์—์„œ๋Š” ์ด๋™ยทํฌ๊ธฐ์กฐ์ ˆ์ด ๊ธฐ๋ณธ์ด์ง€๋งŒ, ์• ํ”Œ๋ฆฌ์ผ€์ด์…˜ ๋‚ด๋ถ€(ํ•˜์œ„)์—์„œ๋Š” ์ปจํŠธ๋กค๊ณผ ๊ทธ๋ž˜ํ”ฝ ๊ฐ์ฒด๊ฐ€ ๊ณ ์ •๋ผ ์žˆ๋‹ค. ๊ธฐ์กด ํ•ด๊ฒฐ์ฑ…์˜ ํ•œ๊ณ„ : ํŒจ๋„์— ๊ทธ๋ฆผ์„ ๊ทธ๋ฆฌ๊ฑฐ๋‚˜ ๋น„ํŠธ๋งต ์Šค์ผ€์ผ๋ง์„ ์ด์šฉํ•˜๋Š” ๋ฐฉ๋ฒ•์€ ์‚ฌ๊ฐํ˜•์—๋งŒ ์ ์šฉ ๊ฐ€๋Šฅํ•˜๊ณ , ํ’ˆ์งˆ ์ €ํ•˜ยท๋ณต์žก๋„ ์ฆ๊ฐ€๋ผ๋Š” ๋ฌธ์ œ๋ฅผ ์•ˆ๊ณ  ์žˆ๋‹ค. ํ•ต์‹ฌ ๊ฐ€์„ค : โ€œ๊ทธ๋ž˜ํ”ฝ ๊ฐ์ฒด๋„ ์œˆ๋„์šฐ์™€ ๋™์ผํ•œ ์ด๋™ยทํฌ๊ธฐ์กฐ์ ˆ ๊ทœ์น™์„ ์ ์šฉํ•˜๋ฉด ์‚ฌ์šฉ์žโ€‘์ฃผ๋„ UI๊ฐ€ ์‹คํ˜„๋œ๋‹ค.โ€ 2. ์ œ์•ˆ๋œ ์„ค๊ณ„ ์›๋ฆฌ | ์š”์†Œ | ์„ค๋ช… | ์—ญํ•  | | | | | | GraphicalObj

HCI Graphics Computer Science
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Dispersionful analogue of the Whitham hierarchy

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋™๊ธฐ | ํ•ต์‹ฌ ํฌ์ธํŠธ | ๋‚ด์šฉ | | | | | Whitham ๊ณ„์ธต | Krichever๊ฐ€ ์ œ์‹œํ•œ ๋ณดํŽธ์  Whitham ๊ณ„์ธต์€ ๋ฆฌ๋งŒ ๊ณก๋ฉด์˜ ๋ชจ๋“ˆ๋ฆฌ ๊ณต๊ฐ„์„ ์ด์šฉํ•ด ๋ฌด๋ถ„์‚ฐ(dispersionless) ๋น„์„ ํ˜• ์ ๋ถ„๊ณ„(system)๋ฅผ ์ฒด๊ณ„ํ™”ํ•œ๋‹ค. ์˜โ€‘์ข… ๊ฒฝ์šฐ๊ฐ€ โ€œWhitham hierarchyโ€๋ผ ๋ถˆ๋ฆฌ๋ฉฐ KdV, Toda, AKNS ๋“ฑ ๋‹ค์–‘ํ•œ ๋ฌด๋ถ„์‚ฐ ์†”๋ฆฌํ†ค ๋ฐฉ์ •์‹์˜ ๊ทผ๋ณธ ๊ตฌ์กฐ๋ฅผ ์ œ๊ณตํ•œ๋‹ค. | | ๋ถ„์‚ฐ์„ฑ ์ด๋ก ์˜ ๋ถ€์žฌ | ๊ธฐ์กด Whitham ๊ณ„์ธต์„ โ€œ์–‘์žํ™”โ€ํ•ด ๋ถ„์‚ฐ์„ฑ์„ ๋„์ž…ํ•˜๋ ค๋ฉด ๊ณ ์ฐจ ์œ ํ•œ ๊ทน์ (finite pole) ๊ฐœ๋…

Mathematics MATH-PH Nonlinear Sciences
Distributed Decision Through Self-Synchronizing Sensor Networks in the   Presence of Propagation Delays and Asymmetric Channels

Distributed Decision Through Self-Synchronizing Sensor Networks in the Presence of Propagation Delays and Asymmetric Channels

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ์ฐจ๋ณ„์  ๊ธฐ์กด ํ•ฉ์˜/๋™๊ธฐํ™” ์—ฐ๊ตฌ : Olfatiโ€‘Saber & Murray, Tsitsiklis ๋“ฑ์€ ๋™์งˆ ์ง€์—ฐ ํ˜น์€ ์ฆ‰์‹œ ์ „๋‹ฌ ์„ ์ „์ œ๋กœ ํ‰๊ท ยท๊ฐ€์ค‘ ํ‰๊ท  ํ•ฉ์˜๋ฅผ ๋ถ„์„ํ•˜์˜€๋‹ค. ๋น„๋Œ€์นญยท๋น„๋™์งˆ ์ง€์—ฐ์„ ๋‹ค๋ฃฌ ์—ฐ๊ตฌ๋Š” ์ œํ•œ์ ์ด๋ฉฐ, ๋Œ€๋ถ€๋ถ„ ์ˆ˜๋ ด ์กฐ๊ฑด ๋งŒ ์ œ์‹œํ•˜๊ณ  ์ตœ์ข… ํ•ฉ์˜๊ฐ’์ด ์ธก์ •๊ฐ’๊ณผ ๋ฌด๊ด€ํ•œ ๋ฐ”์ด์–ด์Šค ๋ฅผ ํฌํ•จํ•œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์˜ ํ˜์‹  : ๊ทธ๋ž˜ํ”„ ๋ชจ๋ธ๋ง : ๊ฐ€์ค‘์น˜๊ฐ€ ์ฑ„๋„ ๊ฐ์‡ ยท์ „์†ก ์ „๋ ฅ์— ์ง์ ‘ ์—ฐ๊ด€๋œ ๊ฐ€์ค‘์น˜ ๋ฐฉํ–ฅ ๊ทธ๋ž˜ํ”„ ๋ฅผ ์‚ฌ์šฉํ•ด ๋ฌผ๋ฆฌ์  ๋ฌด์„  ์ฑ„๋„์„ ์ •ํ™•ํžˆ ๋ฐ˜์˜. ์ „ํŒŒ ์ง€์—ฐ ํฌํ•จ : ๊ฐ ๋งํฌ๋งˆ๋‹ค ๊ฑฐ๋ฆฌยท์‹œ๊ฐ„ ์˜คํ”„์…‹ ์— ๊ธฐ๋ฐ˜ํ•œ ๋น„๋™์งˆ

Network Multiagent Systems Distributed Computing Computer Science
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Diversity-Multiplexing Tradeoff of Asynchronous Cooperative Diversity in Wireless Networks

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋™๊ธฐ ๋ฆด๋ ˆ์ด ๋™๊ธฐํ™”์˜ ์–ด๋ ค์›€ : ๊ธฐ์กด ํ˜‘๋™ ๋‹ค์ด๋ฒ„์‹œํ‹ฐ ์—ฐ๊ตฌ๋Š” ๋ฆด๋ ˆ์ด ๊ฐ„ ์™„๋ฒฝํ•œ ์‹ฌ๋ณผ ์ˆ˜์ค€ ๋™๊ธฐํ™”๋ฅผ ์ „์ œํ•œ๋‹ค. ์‹ค์ œ ์ธํ”„๋ผ๊ฐ€ ์—†๋Š” adโ€‘hocยท์„ผ์„œ ๋„คํŠธ์›Œํฌ์—์„œ๋Š” ์ด ๊ฐ€์ •์ด ํ˜„์‹ค์ ์œผ๋กœ ๋ถˆ๊ฐ€๋Šฅํ•˜๋‹ค. DM ํŠธ๋ ˆ์ด๋“œ์˜คํ”„ : Zhengโ€‘Tse ํ”„๋ ˆ์ž„์›Œํฌ๋ฅผ ๋ฆด๋ ˆ์ด ์ฑ„๋„์— ์ ์šฉํ•ด ๋‹ค์ด๋ฒ„์‹œํ‹ฐ์™€ ์ŠคํŽ™ํŠธ๋Ÿผ ํšจ์œจ ์‚ฌ์ด์˜ ๊ทผ๋ณธ์ ์ธ ๊ด€๊ณ„๋ฅผ ์ •๋Ÿ‰ํ™”ํ•œ๋‹ค. ์ด๋Š” ์‹œ์Šคํ…œ ์„ค๊ณ„ ์‹œ โ€œ์–ผ๋งˆ๋‚˜ ๋งŽ์€ ๋‹ค์ด๋ฒ„์‹œํ‹ฐ๋ฅผ ํฌ๊ธฐํ•˜๊ณ  ๋ฉ€ํ‹ฐํ”Œ๋ ‰์‹ฑ์„ ์–ป์„ ๊ฒƒ์ธ๊ฐ€โ€๋ฅผ ๋ช…ํ™•ํžˆ ํŒ๋‹จํ•˜๊ฒŒ ํ•ด์ค€๋‹ค. 2. ์ œ์•ˆ๋œ ๋น„๋™๊ธฐ ์Šคํ‚ด | ์Šคํ‚ด | ํ•ต์‹ฌ ์•„์ด๋””์–ด | ์ฃผ์š” ๊ฐ€์ • | ๊ธฐ๋Œ€

Network Information Theory Mathematics Computer Science
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e-Science initiatives in Venezuela

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉํ‘œ eโ€‘Science ์ •์˜ : John Taylor(2000)๊ฐ€ ์ œ์‹œํ•œ ๊ฐœ๋…์œผ๋กœ, ์ „ ์„ธ๊ณ„ ๊ณผํ•™์ž๋“ค์ด ์„œ๋น„์Šค ์ง€ํ–ฅํ˜• ์ปดํ“จํŒ…ยท๋ฐ์ดํ„ฐ ์ธํ”„๋ผ๋ฅผ ํ†ตํ•ด ํ˜‘์—…ํ•˜๋Š” ํ™˜๊ฒฝ์„ ์˜๋ฏธํ•œ๋‹ค. ๋ฒ ๋„ค์ˆ˜์—˜๋ผ ์ƒํ™ฉ : CeCalCULA์™€ IVIC์€ ๊ตญ๊ฐ€ ์ฐจ์›์˜ ๊ณ ์„ฑ๋Šฅ ์ปดํ“จํŒ…(HPC)ยท๊ทธ๋ฆฌ๋“œ ์ธํ”„๋ผ๋ฅผ ๊ตฌ์ถ•ํ•˜๊ณ , ์ด๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ์ง€์—ญยท๊ตญ์ œ ํ˜‘์—…์„ ์ด‰์ง„ํ•˜๊ณ ์ž ํ•จ. ํ•ต์‹ฌ ๋ชฉํ‘œ : ๊ธฐ์กด ๋ ˆ๊ฑฐ์‹œ ๊ณผํ•™ ์• ํ”Œ๋ฆฌ์ผ€์ด์…˜(Fortran ๊ธฐ๋ฐ˜)์„ ์›น/๊ทธ๋ฆฌ๋“œ ํฌํ„ธ ํ˜•ํƒœ๋กœ ์ „ํ™˜ํ•˜์—ฌ, ์‚ฌ์šฉ์ž๊ฐ€ ๋ณต์žกํ•œ ๋ช…๋ น์ค„ยทํŒŒ์ผ ์กฐ์ž‘ ์—†์ด๋„ ๊ณ ์„ฑ๋Šฅ ๊ณ„์‚ฐ์„ ์ˆ˜ํ–‰ํ•˜๋„๋ก ํ•˜๋Š” ๊ฒƒ. 2.

Computational Engineering Distributed Computing Computer Science
ell-adic class field theory for regular local rings

ell-adic class field theory for regular local rings

1. ๋ฌธ์ œ ์„ค์ • ๋ฐ ๋ฐฐ๊ฒฝ ์ •๊ทœ ๊ตญ์†Œํ™˜ (A) ๋ฅผ ๋Œ€์ƒ์œผ๋กœ ํ•œ ๊ณ ์ฐจ์› ํด๋ž˜์Šค ํ•„๋“œ ์ด๋ก ์€ ๊ธฐ์กด์— ์ฐจ์› 1 (์ฆ‰, ์ง€์—ญ์ฒด)์—์„œ๋งŒ ์™„์ „ํžˆ ์ •๋ฆฝ๋ผ ์žˆ์—ˆ๋‹ค. Matsumi(2014)์˜ ๊ฒฐ๊ณผ๋Š” ์ฐจ์› (n) ์— ๋Œ€ํ•œ โ€˜(p)โ€‘adicโ€™ ๋ฒ„์ „์„ ์ œ์‹œํ–ˆ์ง€๋งŒ, (ellneq p) ์ธ ๊ฒฝ์šฐ๋Š” ๋‚จ์•„ ์žˆ์—ˆ๋‹ค. ์ €์ž๋Š” (ell)โ€‘adic ์ƒํ™ฉ์„ ๋‹ค๋ฃจ๋ฉด์„œ, Galois ๊ธฐํ˜ธ ์‚ฌ์ƒ์˜ ์ „์‚ฌ์„ฑ ์ด๋ผ๋Š” ๊ฐ€์ •์„ ๋„์ž…ํ•œ๋‹ค. ์ด๋Š” Blochโ€“Kato ์˜ˆ์ธก(์ „์‚ฌ์„ฑ)๊ณผ ๋™๋“ฑํ•˜๋ฉฐ, ํ˜„์žฌ๊นŒ์ง€๋Š” ์ฐจ์› 2 ์ดํ•˜์™€ ํŠน์ • ํŠน์ˆ˜ ๊ฒฝ์šฐ์—๋งŒ ๊ฒ€์ฆ๋œ ๊ฐ€์ •์ด๋‹ค. 2. ํ•ต

Mathematics
GCP: Gossip-based Code Propagation for Large-scale Mobile Wireless   Sensor Networks

GCP: Gossip-based Code Propagation for Large-scale Mobile Wireless Sensor Networks

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ํ•„์š”์„ฑ ๋ชจ๋ฐ”์ผ WSN ์€ ๋„คํŠธ์›Œํฌ ํ† ํด๋กœ์ง€๊ฐ€ ์ง€์†์ ์œผ๋กœ ๋ณ€ํ•˜๊ณ , ๋…ธ๋“œ๊ฐ€ ์ž์‹ ์˜ ์œ„์น˜๋ฅผ ์•Œ ์ˆ˜ ์—†๋Š” ๊ฒฝ์šฐ๊ฐ€ ๋งŽ๋‹ค. ๊ธฐ์กด์˜ ๊ณ ์ •ํ˜• WSN์šฉ ์—…๋ฐ์ดํŠธ ๊ธฐ๋ฒ•(์˜ˆ: ์ค‘์•™ ์„œ๋ฒ„ ๊ธฐ๋ฐ˜, ์ „์ฒด ํ”Œ๋Ÿฌ๋”ฉ)์€ ์—๋„ˆ์ง€ ๋‚ญ๋น„์™€ ๋ถ€ํ•˜ ์ง‘์ค‘์„ ์ดˆ๋ž˜ํ•œ๋‹ค. P2PยทEpidemic(๊ฐ€์‹ญ) ๋ชจ๋ธ ์€ ๋ฌด์„  ๋งค์ฒด์˜ ๋ฉ€ํ‹ฐ์บ์ŠคํŠธ ํŠน์„ฑ์„ ํ™œ์šฉํ•ด ์ œํ•œ๋œ ๋กœ์ปฌ ๋ทฐ๋งŒ์œผ๋กœ๋„ ์ „์ฒด ๋„คํŠธ์›Œํฌ์— ์ •๋ณด๋ฅผ ๋น ๋ฅด๊ฒŒ ํ™•์‚ฐ์‹œํ‚ฌ ์ˆ˜ ์žˆ๋‹ค. ์ด๋Š” ๋Œ€๊ทœ๋ชจ, ๋™์ ์ธ ์„ผ์„œ ๋„คํŠธ์›Œํฌ์— ์ ํ•ฉํ•œ ์„ค๊ณ„ ํŒจ๋Ÿฌ๋‹ค์ž„์ด๋‹ค. 2. GCP ์„ค๊ณ„ ํ•ต์‹ฌ | ๋ฉ”์ปค๋‹ˆ์ฆ˜ | ๋™์ž‘ ๋ฐฉ์‹ | ๊ธฐ๋Œ€ ํšจ๊ณผ | | |

Networking Network Computer Science
Geo-neutrinos and Earths interior

Geo-neutrinos and Earths interior

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋™๊ธฐ ์ง€๊ตฌ ๋‚ด๋ถ€ ํƒ์‚ฌ์˜ ํ•œ๊ณ„ : ํ˜„์žฌ ์ธ๋ฅ˜๊ฐ€ ์ง์ ‘ ์ ‘๊ทผํ•  ์ˆ˜ ์žˆ๋Š” ๊นŠ์ด๋Š” 12 km์— ๋ถˆ๊ณผํ•˜๋ฉฐ, ์ด๋Š” ์ง€๊ตฌ ๋ฐ˜๊ฒฝ(โ‰ˆ 6370 km)์˜ 0.2 %์— ํ•ด๋‹นํ•œ๋‹ค. ์ง€์ง„ํ•™์ด ์ œ๊ณตํ•˜๋Š” ๋ฐ€๋„ ๋ชจ๋ธ์€ ์กฐ์„ฑ ์ •๋ณด๋ฅผ ์ œ๊ณตํ•˜์ง€ ๋ชปํ•œ๋‹ค. ์ง€์˜คโ€‘์ค‘์„ฑ์ž์˜ ๋…ํŠน์„ฑ : U, Th, Kโดโฐ ๋ถ•๊ดด์—์„œ ๋ฐœ์ƒํ•˜๋Š” ๋ฐ˜์ค‘์„ฑ์ž๋Š” ๊ฑฐ์˜ ๋ฌดํก์ˆ˜ยท๋ฌด์‚ฐ๋ž€์œผ๋กœ ์ง€๊ตฌ ๋‚ด๋ถ€๋ฅผ ํ†ต๊ณผํ•ด ๋ฐ”๋กœ ๊ฒ€์ถœ๊ธฐ์— ๋„๋‹ฌํ•œ๋‹ค. ๋”ฐ๋ผ์„œ ์ „ ์ง€๊ตฌ์  โ€œ๊ด‘ํ•™โ€ ์—ญํ• ์„ ์ˆ˜ํ–‰ํ•œ๋‹ค๋Š” ์ ์—์„œ ๊ธฐ์กด ์ง€๊ตฌ ๋ฌผ๋ฆฌยทํ™”ํ•™์  ๋ฐฉ๋ฒ•์„ ๋ณด์™„ํ•œ๋‹ค. 2. ํ•ต์‹ฌ ๊ณผํ•™ ๋ชฉํ‘œ | ๋ชฉํ‘œ | ๊ธฐ๋Œ€ ํšจ๊ณผ | | | | | ๋ฐฉ

Astrophysics NUCL-TH NUCL-EX Physics HEP-PH
Interplay of polarization geometry and rotational dynamics in high   harmonic generation from coherently rotating linear molecule

Interplay of polarization geometry and rotational dynamics in high harmonic generation from coherently rotating linear molecule

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์  ๊ณ ์กฐํŒŒ ๋ฐœ์ƒ(HHG)์€ ๊ฐ•๋ ฌ ๋ ˆ์ด์ €์™€ ์›์žยท๋ถ„์ž ์‚ฌ์ด์—์„œ n๊ฐœ์˜ ๊ด‘์ž๋ฅผ ํ•˜๋‚˜์˜ ๊ณ ์—๋„ˆ์ง€ ๊ด‘์ž(โ„ฮฉ nโ„ฯ‰)๋กœ โ€œ์œตํ•ฉโ€์‹œํ‚ค๋Š” ๋น„์„ ํ˜• ๊ณผ์ •์ด๋‹ค. ์ „์ž๋Š” ์‹ค์ œ ์ƒํƒœ ๋ณ€ํ™”๋ฅผ ๊ฒช์ง€ ์•Š์œผ๋ฉฐ, ๋‹จ์ง€ ์ด‰๋งค ์—ญํ• ์„ ํ•œ๋‹ค. ๋ถ„์ž ํšŒ์ „์ด ๋ ˆ์ด์ €์™€ ์ƒํ˜ธ์ž‘์šฉํ•˜๋ฉด์„œ ์‹œ๊ฐ„์— ๋”ฐ๋ผ ์ •๋ ฌยท๋น„์ •๋ ฌ์ด ๋ฐ˜๋ณต๋˜๋Š” โ€˜๋ฆฌ๋ฐ”์ด๋ฒŒ(revival)โ€™ ํ˜„์ƒ์ด ๋‚˜ํƒ€๋‚˜๋ฉฐ, ์ด๋Š” HHG ์‹ ํ˜ธ์— ์ง์ ‘์ ์ธ ์˜ํ–ฅ์„ ๋ฏธ์นœ๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ๋Š” ์ฃผ๋กœ ํšŒ์ „ ๋™์—ญํ•™(์‹œ๊ฐ„ ์ง€์—ฐ) ํ˜น์€ ํŽธ๊ด‘ ๊ฐ๋„ ์ค‘ ํ•˜๋‚˜๋งŒ์„ ๋ณ€ํ™”์‹œ์ผœ HHG๋ฅผ ์กฐ์‚ฌํ–ˆ์ง€๋งŒ, ๋‘ ๋ณ€์ˆ˜๋ฅผ ๋™์‹œ์— ์กฐ์ ˆํ–ˆ์„ ๋•Œ ๋‚˜ํƒ€๋‚˜๋Š” ๋ณต

Physics
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L.V.Kantorovich and Linear Programming

1. ์นธํ† ๋กœ๋น„์น˜์˜ ์ดˆ๊ธฐ ์—ฐ๊ตฌ์™€ ์„ ํ˜•๊ณ„ํš๋ฒ•์˜ ํƒ„์ƒ 1939๋…„ ์ €์„œ์™€ โ€œํ•ด๊ฒฐ ์Šน์ˆ˜โ€ ๊ฐœ๋…์€ ์˜ค๋Š˜๋‚  ์ด์ค‘ ๋ฌธ์ œ(Dual Problem)์™€ ๋ผ๊ทธ๋ž‘์ฃผ ์Šน์ˆ˜๋ฒ•์˜ ๊ฒฝ์ œ์  ํ•ด์„์„ ์ตœ์ดˆ๋กœ ์ œ์‹œํ•˜์˜€๋‹ค. ์ด๋Š” โ€œ๊ฐ๊ด€์ ์œผ๋กœ ๊ฒฐ์ •๋œ ๊ฐ€์น˜(objectively determined valuations)โ€๋ผ๋Š” ์šฉ์–ด๋กœ ๊ฐ€๊ฒฉ ๊ฐœ๋…์„ ์ˆ˜ํ•™์ ์œผ๋กœ ์ •๋ฆฝํ•œ ์ ์—์„œ ํ˜์‹ ์ ์ด๋‹ค. ์ด๋ก ์  ๊ธฐ๋ฐ˜์€ ํ•จ์ˆ˜ํ•ด์„ํ•™(ํŠนํžˆ M.G. Krein์˜ ํ•™ํŒŒ)๊ณผ ์—ฐ๊ณ„๋˜์–ด, Lโ€‘๋ชจ๋ฉ˜ํŠธ ๋ฌธ์ œ์™€ ๊ฐ™์€ ๊ณ ์ „์  ๋ฌธ์ œ์— ์ตœ์ ํ™” ๊ธฐ๋ฒ•์„ ๋„์ž…ํ•˜์˜€๋‹ค. 2. ์†Œ๋ จ ์ฒด์ œ์™€ ์ด๋…์  ์ €ํ•ญ 1940โ€‘50๋…„๋Œ€๋Š” โ€˜๋ช…๋ นโ€‘ํ–‰์ •

Mathematics
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Learning Probabilistic Models of Word Sense Disambiguation

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉํ‘œ ๋ฌธ์ œ ์ •์˜ : ๋‹ค์˜์–ด์˜ ์˜ฌ๋ฐ”๋ฅธ ์˜๋ฏธ๋ฅผ ๋ฌธ๋งฅ์— ๋”ฐ๋ผ ์„ ํƒํ•˜๋Š” WSD๋Š” ๊ธฐ๊ณ„ ๋ฒˆ์—ญ, ์ •๋ณด ๊ฒ€์ƒ‰, ๋ฌธ์„œ ๋ถ„๋ฅ˜ ๋“ฑ ๋‹ค์–‘ํ•œ NLP ์‘์šฉ์—์„œ ํ•ต์‹ฌ ๊ณผ์ œ์ด๋‹ค. ์ „ํ†ต์  ํ•œ๊ณ„ : ์ธ๊ฐ„์€ ๋ฐฉ๋Œ€ํ•œ ์„ธ๊ณ„ ์ง€์‹๊ณผ ์–ธ์–ด ์ง๊ด€์„ ํ™œ์šฉํ•˜์ง€๋งŒ, ์ด๋ฅผ ์ปดํ“จํ„ฐ๊ฐ€ ์™„์ „ํ•˜๊ฒŒ ๋ชจ๋ธ๋งํ•˜๊ธฐ๋Š” ์–ด๋ ค์›Œ โ€˜์ฝ”ํผ์Šค ๊ธฐ๋ฐ˜โ€™ ์ ‘๊ทผ์ด ํ•„์š”ํ•˜๋‹ค. ๋ณธ ๋…ผ๋ฌธ์˜ ๊ธฐ์—ฌ : (1) ์ง€๋„ํ•™์Šต์—์„œ ์ƒˆ๋กœ์šด ๋ชจ๋ธ ํƒ์ƒ‰ ์ „๋žต๊ณผ ํ‰๊ฐ€ ๊ธฐ์ค€์„ ๋„์ž…, (2) ๋น„์ง€๋„ํ•™์Šต์—์„œ EMยทGibbs๋ฅผ ์ด์šฉํ•œ ์ž ์žฌ ์˜๋ฏธ ์ถ”์ • ๋ฐฉ๋ฒ•์„ ์ œ์‹œ, (3) ๋‚˜์ด๋ธŒ ๋ฒ ์ด์ฆˆ ๋ชจ๋ธ์˜ ์„ฑ๊ณต ์›์ธ์„ ์ด๋ก ์ ์œผ๋กœ ๋ถ„์„ํ•œ๋‹ค

Artificial Intelligence Model Computer Science NLP Learning
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Leibniz seminorms for 'Matrix algebras converge to the sphere'

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋™๊ธฐ ๋ฌผ๋ฆฌํ•™์  ๋™๊ธฐ : ๊ณ ์—๋„ˆ์ง€ ๋ฌผ๋ฆฌยท์ŠคํŠธ๋ง ์ด๋ก ์—์„œ๋Š” โ€œ๋งคํŠธ๋ฆญ์Šค ๋ชจ๋ธ์ด ๊ตฌ๋ฉด(๋˜๋Š” ๋‹ค๋ฅธ ๊ณต๊ฐ„)์œผ๋กœ ์ˆ˜๋ ดํ•œ๋‹คโ€๋Š” ์„œ์ˆ ์ด ์ž์ฃผ ๋“ฑ์žฅํ•œ๋‹ค. ํŠนํžˆ ๋‹จ๊ทน์ž(๋ชจ๋…ธํด) ๋ฒˆ๋“ค ์ด ๋งคํŠธ๋ฆญ์Šค ๋Œ€์ˆ˜ ์œ„์˜ ๋น„๊ฐ€ํ™˜ ๋ฒˆ๋“ค์— ๋Œ€์‘ํ•œ๋‹ค๋Š” ์ฃผ์žฅ์— ์ˆ˜ํ•™์  ๊ทผ๊ฑฐ๊ฐ€ ํ•„์š”ํ–ˆ๋‹ค. ์ˆ˜ํ•™์  ์ „์ œ : ์ €์ž๋Š” ์ด์ „ ๋…ผ๋ฌธ(

HEP-TH Mathematics
Linear-programming Decoding of Non-binary Linear Codes

Linear-programming Decoding of Non-binary Linear Codes

| ๊ตฌ๋ถ„ | ๋‚ด์šฉ | | | | | ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ํ•„์š”์„ฑ | ๊ณ ์† ๋ฐ์ดํ„ฐ ์ „์†ก์—์„œ๋Š” ๋Œ€์—ญํญ ํšจ์œจ์„ ๋†’์ด๊ธฐ ์œ„ํ•ด ๊ณ ์ฐจ ๋ณ€์กฐ์™€ ๋น„์ด์ง„ ์ฝ”๋”ฉ์ด ํ•„์ˆ˜์ ์ด๋‹ค. ๊ธฐ์กด LDPCโ€‘BP( beliefโ€‘propagation) ๋””์ฝ”๋”ฉ์€ ๋น„์ด์ง„ ๊ฒฝ์šฐ ๋ถ„์„์ด ๋ณต์žกํ•˜๊ณ , ML ๋””์ฝ”๋”ฉ์€ ๊ณ„์‚ฐ๋Ÿ‰์ด ๊ธ‰๊ฒฉํžˆ ์ฆ๊ฐ€ํ•œ๋‹ค. LP ๋””์ฝ”๋”ฉ์€ ์ด ๋‘ ๊ทน๋‹จ ์‚ฌ์ด์˜ ์ ˆ์ถฉ์ ์œผ๋กœ, ์ด๋ก ์  ๋ณด์ฆ(MLโ€‘certificate)๊ณผ ๋‹คํ•ญ์‹ ๋ณต์žก๋„๋ฅผ ์ œ๊ณตํ•œ๋‹ค. | | ์ฃผ์š” ๊ธฐ์—ฌ | 1. ๋น„์ด์ง„ LP ๋””์ฝ”๋”ฉ ํ”„๋ ˆ์ž„์›Œํฌ โ€“ ๋น„์ด์ง„ ์‹ฌ๋ณผ์„ 0/1 ๋ฒกํ„ฐ(๊ธธ์ด qโ€‘1)๋กœ ๋งคํ•‘ํ•˜๊ณ , ์ด๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ์ œ์•ฝ

Information Theory Mathematics Computer Science
Mosaic Pruning: A Hierarchical Framework for Generalizable Pruning of Mixture-of-Experts Models

Mosaic Pruning: A Hierarchical Framework for Generalizable Pruning of Mixture-of-Experts Models

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋ฌธ์ œ ์ •์˜ SMoE์˜ ์žฅ์  : ํ† ํฐ๋‹น ํ™œ์„ฑํ™”๋˜๋Š” ํŒŒ๋ผ๋ฏธํ„ฐ ์ˆ˜๋ฅผ ํฌ๊ฒŒ ์ค„์—ฌ ๋Œ€๊ทœ๋ชจ ๋ชจ๋ธ์˜ ์ถ”๋ก  ํšจ์œจ์„ฑ์„ ๋†’์ธ๋‹ค. ํ•ต์‹ฌ ๋ณ‘๋ชฉ : ๋ชจ๋“  ์ „๋ฌธ๊ฐ€๋ฅผ ๋ฉ”๋ชจ๋ฆฌ์— ์ƒ์ฃผ์‹œ์ผœ์•ผ ํ•˜๋ฏ€๋กœ GPU ๋ฉ”๋ชจ๋ฆฌ ์š”๊ตฌ๋Ÿ‰์ด ์ˆ˜์‹ญ GB์— ๋‹ฌํ•œ๋‹ค(์˜ˆ: Mixtralโ€‘8x7B > 80 GB). ์ „๋ฌธ๊ฐ€ ์ค‘๋ณต : ํ•™์Šต ๊ณผ์ •์—์„œ ์ผ๋ถ€ ์ „๋ฌธ๊ฐ€๊ฐ€ ์„œ๋กœ ์œ ์‚ฌํ•œ ๊ธฐ๋Šฅ์„ ์ˆ˜ํ–‰ํ•˜๊ฑฐ๋‚˜ ๊ฑฐ์˜ ์‚ฌ์šฉ๋˜์ง€ ์•Š์•„ ์••์ถ• ๊ฐ€๋Šฅ์„ฑ์ด ์กด์žฌํ•œ๋‹ค. ๊ธฐ์กด ํ”„๋ฃจ๋‹ ํ•œ๊ณ„ : Enumeration Pruning ๋“ฑ์€ ์ผ๋ฐ˜ ์ฝ”ํผ์Šค(C4, WikiText) ๊ธฐ๋ฐ˜ ์†์‹ค ์ตœ์†Œํ™”์— ์ดˆ์ ์„ ๋งž์ถ”์–ด, ์ „๋ฌธ

Framework Model
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Multi-physics Extension of OpenFMO Framework

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ํ•„์š”์„ฑ ๋ฉ€ํ‹ฐํ”ผ์ง์Šค ์‹œ๋ฎฌ๋ ˆ์ด์…˜์˜ ๊ธ‰์ฆ : ํ˜„๋Œ€ ๊ณผํ•™ยท๊ณตํ•™ ๋ฌธ์ œ๋Š” ์—ฌ๋Ÿฌ ๋ฌผ๋ฆฌยทํ™”ํ•™ ์ด๋ก ์„ ๊ฒฐํ•ฉํ•ด์•ผ ํ•˜๋Š” ๊ฒฝ์šฐ๊ฐ€ ๋Š˜์–ด๋‚˜๊ณ  ์žˆ๋‹ค(์˜ˆ: QM/MM, QM/MD, FMOโ€‘RISM). ์ปดํ“จํŒ… ํ™˜๊ฒฝ์˜ ๊ธ‰๋ณ€ : ๊ทธ๋ฆฌ๋“œยทํด๋ผ์šฐ๋“œยทํŽซ๋ผ์Šค์ผ€ ์Šˆํผ์ปดํ“จํ„ฐ ๋“ฑ ๋‹ค์–‘ํ•œ ์ด๊ธฐ์ข… ์ž์›์ด ๋“ฑ์žฅํ•˜๋ฉด์„œ, ์†Œํ”„ํŠธ์›จ์–ด๋Š” ์ด์‹์„ฑยทํ™•์žฅ์„ฑ ์„ ๋ฐ˜๋“œ์‹œ ํ™•๋ณดํ•ด์•ผ ํ•œ๋‹ค. 2. ๊ธฐ์กด ์—ฐ๊ตฌ์™€ ์ฐจ๋ณ„์  | ๊ตฌ๋ถ„ | ๊ธฐ์กด FMO ๊ตฌํ˜„ | ๋ณธ ๋…ผ๋ฌธ์˜ ํŠน์ง• | | | | | | ๊ตฌํ˜„ ๋ฐฉ์‹ | GAMESS ๊ธฐ๋ฐ˜ โ€œLooselyโ€‘coupled FMOโ€ (NAREGI ํ”„๋กœ์ ํŠธ) |

Physics Distributed Computing Framework Computer Science
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Mutual information in random Boolean models of regulatory networks

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋™๊ธฐ ์ƒ๋ฌผํ•™์  ๋งฅ๋ฝ : ์„ธํฌ ๋‚ด ์œ ์ „์ž ์กฐ์ ˆ๋ง์€ ์ˆ˜์ฒœ ๊ฐœ์˜ ์œ ์ „์ž๊ฐ€ ๋ณต์žกํ•˜๊ฒŒ ์–ฝํžŒ ๋„คํŠธ์›Œํฌ์ด๋ฉฐ, ์ด๋“ค์˜ ๋™์‹œ์ ยทํ˜‘์กฐ์  ํ™œ๋™์„ ์ •๋Ÿ‰ํ™”ํ•˜๋Š” ๊ฒƒ์ด ํ•ต์‹ฌ ๊ณผ์ œ์ด๋‹ค. ์ •๋ณด ์ด๋ก ์  ์ ‘๊ทผ : ๋‘ ๋…ธ๋“œ์˜ ์‹œ๊ฐ„ ์‹œ๊ณ„์—ด ๊ฐ„ ์ƒํ˜ธ ์ •๋ณด๋Š” ํ•œ ๋…ธ๋“œ์˜ ์ƒํƒœ๊ฐ€ ๋‹ค๋ฅธ ๋…ธ๋“œ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ์ธก์ •ํ•œ๋‹ค. ๋„คํŠธ์›Œํฌ ์ „์ฒด์— ๋Œ€ํ•œ ํ‰๊ท  โŸจIโŸฉ๋Š” โ€œ์ „์—ญ ํ˜‘์กฐ์„ฑโ€์„ ๋‚˜ํƒ€๋‚ด๋Š” ์ž์—ฐ์Šค๋Ÿฌ์šด ์ฒ™๋„๋‹ค. ์ž„๊ณ„์„ฑ ๊ฐ€์„ค : ๊ธฐ์กด ์—ฐ๊ตฌ(์˜ˆ: Kauffman, Aldana ๋“ฑ)๋Š” ์œ ์ „์ž ๋„คํŠธ์›Œํฌ๊ฐ€ ์ž„๊ณ„(critical) ์ƒํƒœ์— ์žˆ์„ ๊ฒฝ์šฐ, ์•ˆ์ •์„ฑ๊ณผ ์œ ์—ฐ์„ฑ ์‚ฌ์ด์˜ ์ตœ์  ๊ท 

Quantitative Biology Network Model
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Nonlinear option pricing models for illiquid markets: scaling properties and explicit solutions

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ํ•„์š”์„ฑ ์ „ํ†ต์ ์ธ Blackโ€‘Scholes ๋ชจ๋ธ์€ ์™„์ „ ์œ ๋™์„ฑ ๊ณผ ๋ฌด๋งˆ์ฐฐ ์„ ์ „์ œ๋กœ ํ•˜์ง€๋งŒ, ์‹ค์ œ ์‹œ์žฅ์—์„œ๋Š” ๋Œ€๊ทœ๋ชจ ํ—ค์ง€ ๊ฑฐ๋ž˜๊ฐ€ ๊ฐ€๊ฒฉ์— ์˜ํ–ฅ์„ ๋ฏธ์ณ ์‹œ์žฅ ์ถฉ๊ฒฉ(market impact) ์ด ๋ฐœ์ƒํ•œ๋‹ค. ์ตœ๊ทผ ๊ธˆ์œต๊ณตํ•™์—์„œ๋Š” ๊ฑฐ๋ž˜๋น„์šฉ, SDEโ€‘๊ธฐ๋ฐ˜ ๋ชจ๋ธ, ๊ท ํ˜•(Reactionโ€‘function) ๋ชจ๋ธ ๋“ฑ ์„ธ ๊ฐ€์ง€ ์ ‘๊ทผ๋ฒ•์ด ์ œ์‹œ๋˜์—ˆ์œผ๋ฉฐ, ์ด๋“ค ๋ชจ๋‘ ํŒŒ์ƒ์ƒํ’ˆ ๊ฐ€๊ฒฉ์„ ๋น„์„ ํ˜• PDE ๋กœ ๊ธฐ์ˆ ํ•œ๋‹ค๋Š” ๊ณตํ†ต์ ์„ ๊ฐ€์ง„๋‹ค. ๋น„์„ ํ˜• PDE๋Š” ํ•ด์„์  ํ•ด๊ฐ€ ๋“œ๋ฌผ์–ด ์ˆ˜์น˜ํ•ด์„ ์— ์˜์กดํ•˜๋Š” ๊ฒฝ์šฐ๊ฐ€ ๋งŽ๋‹ค. ๋”ฐ๋ผ์„œ ๋ช…์‹œ์  ํ•ด ๋ฅผ ํ™•๋ณดํ•˜๋Š” ๊ฒƒ์€ ๋ชจ๋ธ ๊ฒ€

Quantitative Finance Mathematics Model
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On elliptic differential operators with shifts: II. The cohomological index formula

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋™๊ธฐ ์‹œํ”„ํŠธ๊ฐ€ ์žˆ๋Š” (pseudo)๋ฏธ๋ถ„ ์—ฐ์‚ฐ์ž๋Š” ์ „ํ†ต์ ์ธ ๊ตญ์†Œ ์—ฐ์‚ฐ์ž์™€ ๋‹ฌ๋ฆฌ ๋น„๊ตญ์†Œ(coefficient) ๊ตฌ์กฐ ๋ฅผ ๊ฐ–๋Š”๋‹ค. ์ด๋Š” ๊ตฐ ฮ“๊ฐ€ ๋งค๋‹ˆํด๋“œ M์— ์ž‘์šฉํ•˜๋ฉด์„œ ์ •์˜๋˜๋Š” โ€˜์‹œํ”„ํŠธ ์—ฐ์‚ฐ์žโ€™

Mathematics
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On the Minimum Number of Transmissions in Single-Hop Wireless Coding Networks

1. ๋ฌธ์ œ ์ •์˜์™€ ๋ชจ๋ธ๋ง ์‹œ์Šคํ…œ : ๋‹จ์ผ ์„œ๋ฒ„ (s)์™€ (m)๊ฐœ์˜ ํด๋ผ์ด์–ธํŠธ (C {c 1,dots,c m})๊ฐ€ 1โ€‘hop ๋ธŒ๋กœ๋“œ์บ์ŠคํŠธ ์ฑ„๋„์„ ๊ณต์œ ํ•œ๋‹ค. ํŒจํ‚ท ์ง‘ํ•ฉ : (P {p 1,dots,p n}). ๊ฐ ํด๋ผ์ด์–ธํŠธ (c i)๋Š” Wants ์ง‘ํ•ฉ (W(c i)subseteq P) (ํ•„์š”ํ•œ ํŒจํ‚ท) Has ์ง‘ํ•ฉ (H(c i)subseteq P) (์ด๋ฏธ ๋ณด์œ ํ•œ ํŒจํ‚ท) ์ „์†ก : ์„œ๋ฒ„๋Š” ์›๋ณธ ํŒจํ‚ท ํ˜น์€ ์„ ํ˜• ๊ฒฐํ•ฉ (x sum {j 1}^{n} g {j} p j) (๊ณ„์ˆ˜ (g jin GF(q)

Computer Science Networking Information Theory Network Mathematics
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On the p-adic Beilinson conjecture for number fields

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋™๊ธฐ ๋ฒ ์ผ๋ฆฐ์Šจ ์ถ”์ธก ์€ ๋ชจ๋“  ๋Œ€์ˆ˜์  ๋‹ค์–‘์ฒด (X/mathbf{Q})์— ๋Œ€ํ•ด, Deligne cohomology ์™€ motivic cohomology ์‚ฌ์ด์˜ ๋ ˆ๊ทค๋ ˆ์ดํ„ฐ ์‚ฌ์ƒ์ด ํŠน์ˆ˜๊ฐ’ (L(H^{i 1}(X),n))์™€ ์ง์ ‘ ์—ฐ๊ฒฐ๋œ๋‹ค๊ณ  ์˜ˆ์ธกํ•œ๋‹ค. ํ˜„์žฌ๊นŒ์ง€ ์™„์ „ํ•œ ๊ฒ€์ฆ์€ ์ˆ˜์ฒด (์ฆ‰, (X operatorname{Spec}k))์— ํ•œ์ •๋˜๋ฉฐ, ์ด๋Š” Borel ์ •๋ฆฌ์™€ Beilinsonโ€‘Regulator๊ฐ€ ๊ฒฐํ•ฉ๋œ ๊ฒฐ๊ณผ์ด๋‹ค. 1980๋…„๋Œ€ ์ดํ›„ pโ€‘adic ๋ฒ ์ผ๋ฆฐ์Šจ ํ˜•ํƒœ์˜ ์ถ”์ธก์ด ์ œ๊ธฐ๋˜์—ˆ์œผ๋‚˜, syntomic coh

Mathematics
On the relation of Voevodskys algebraic cobordism to Quillens K-theory

On the relation of Voevodskys algebraic cobordism to Quillens K-theory

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋™๊ธฐ ๋Œ€์ˆ˜์  ์ฝ”๋ณผ๋“œ (mathrm{MGL}) ์€ Voevodsky๊ฐ€ motivic stable homotopy theory ์•ˆ์—์„œ ์ •์˜ํ•œ ( mathbf{P}^1) ์ŠคํŽ™ํŠธ๋Ÿผ ์ด๋ฉฐ, ๋ณต์†Œ ์ฝ”๋ณผ๋“œ (MU) ์˜ ๋Œ€์ˆ˜์  ๋ฒ„์ „์ด๋‹ค. Quillen Kโ€‘์ด๋ก  ์€ ๋Œ€์ˆ˜๊ธฐํ•˜ํ•™์—์„œ ๊ฐ€์žฅ ๊ธฐ๋ณธ์ ์ธ ๋ถˆ๋ณ€๋Ÿ‰ ์ค‘ ํ•˜๋‚˜์ด๋ฉฐ, Thomasonโ€‘Trobaugh Kโ€‘์ด๋ก ์€ ๊ทธ ํ™•์žฅํŒ์œผ๋กœ, ์Šคํ‚ค๋งˆ ์ „๋ฐ˜์— ๊ฑธ์นœ Kโ€‘์ด๋ก ์„ ์ œ๊ณตํ•œ๋‹ค. ๋‘ ์ด๋ก  ์‚ฌ์ด์˜ ๊ด€๊ณ„๋Š” โ€œ์ฝ”๋ณผ๋“œ โ†’ Kโ€‘์ด๋ก โ€ ์ด๋ผ๋Š” ๊ณ ์ „์ ์ธ ์œ„์ƒํ•™์  ์ „ํ†ต์„ ๋Œ€์ˆ˜์  ์ƒํ™ฉ์œผ๋กœ ์˜ฎ๊ธฐ๋Š”

Mathematics
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Poyntings theorem for planes waves at an interface: a scattering matrix approach

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉํ‘œ ์Šค์บํ„ฐ๋ง ๋งคํŠธ๋ฆญ์Šค(S) ๋Š” ์–‘์ž์—ญํ•™ยท์ „์ž๊ธฐํ•™์—์„œ ๋‹ค์ค‘ ์‚ฐ๋ž€ ํ˜„์ƒ์„ ๊ฐ„๊ฒฐํžˆ ๊ธฐ์ˆ ํ•˜๋Š” ํ•ต์‹ฌ ๋„๊ตฌ์ด๋ฉฐ, ์ „์†ก ๋งคํŠธ๋ฆญ์Šค์™€๋Š” ๋™๋“ฑํ•˜์ง€๋งŒ ์ž…ยท์ถœ๋ ฅ ํŒŒ๋™ ์ง„ํญ์„ ์ง์ ‘ ์—ฐ๊ฒฐํ•œ๋‹ค. ๊ธฐ์กด ์ „์ž๊ธฐํ•™์—์„œ๋Š” ์ „์†ก ๋งคํŠธ๋ฆญ์Šค๊ฐ€ ์ฃผ๋กœ ์‚ฌ์šฉ๋˜์—ˆ์œผ๋‚˜, S ๋ฅผ ์—๋„ˆ์ง€ ๋ณด์กด(ํฌ์ธํŒ… ์ •๋ฆฌ)๊ณผ ์—ฐ๊ฒฐํ•จ์œผ๋กœ์จ ๋ฌผ๋ฆฌ์  ์˜๋ฏธ๋ฅผ ๋ช…ํ™•ํžˆ ํ•˜๊ณ , ์†์‹ค(ํก์ˆ˜) ์กด์žฌ ์‹œ์—๋„ ์ผ๊ด€๋œ ํ”„๋ ˆ์ž„์›Œํฌ๋ฅผ ์ œ๊ณตํ•˜๊ณ ์ž ํ•œ๋‹ค. 2. ์ด๋ก ์  ์ „๊ฐœ | ๋‹จ๊ณ„ | ํ•ต์‹ฌ ๋‚ด์šฉ | ์ˆ˜์‹ยทํ•ต์‹ฌ ์•„์ด๋””์–ด | | | | | | (i) ํฌ์ธํŒ… ์ •๋ฆฌ | ์‹œ๊ฐ„ ํ‰๊ท  ํ˜•ํƒœ๋กœ ์ „์ž๊ธฐ ์—๋„ˆ์ง€ ํ๋ฆ„๊ณผ ์ „๋ ฅ

Physics
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Programming Telepathy: Implementing Quantum Non-Locality Games

| ๊ตฌ๋ถ„ | ๋‚ด์šฉ | ํ‰๊ฐ€ยท์˜์˜ | | | | | | ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ | ์–‘์ž ๋น„๊ตญ์†Œ์„ฑ ๊ฒŒ์ž„์€ ์–‘์ž ํ†ต์‹  ๋ณต์žก๋„ ์—ฐ๊ตฌ์—์„œ ๊ณ ์ „ยท์–‘์ž ๊ฒฝ๊ณ„์˜ ์ง๊ด€์  ์‚ฌ๋ก€๋กœ ๋„๋ฆฌ ํ™œ์šฉ๋œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๊ธฐ์กด ์—ฐ๊ตฌ๋Š” ์ฃผ๋กœ ๋ฌผ๋ฆฌโ€‘์ˆ˜ํ•™์  ์ฆ๋ช…์— ๋จธ๋ฌผ๋Ÿฌ, ์†Œํ”„ํŠธ์›จ์–ด ๊ณตํ•™์  ๊ด€์ (๋ช…์„ธยท์ •ํ˜• ๊ฒ€์ฆ)๊ณผ๋Š” ๊ฒฉ๋ฆฌ๋ผ ์žˆ์—ˆ๋‹ค. | ์–‘์ž ์ •๋ณด์™€ ํ˜•์‹ ๋ฐฉ๋ฒ•๋ก ์„ ์—ฐ๊ฒฐํ•˜๋ ค๋Š” ์‹œ๋„๋Š” ๋งค์šฐ ํ˜์‹ ์ ์ด๋ฉฐ, ์–‘์ž ์•Œ๊ณ ๋ฆฌ์ฆ˜ยทํ”„๋กœํ† ์ฝœ์˜ ์‹ ๋ขฐ์„ฑ ํ™•๋ณด์— ํ•„์ˆ˜์ ์ธ ๊ธฐ๋ฐ˜์„ ์ œ๊ณตํ•œ๋‹ค. | | ํ•ต์‹ฌ ๋ฐฉ๋ฒ•๋ก  | ์–‘์ž ์„œ์ˆ ํ˜• ํ”„๋กœ๊ทธ๋ž˜๋ฐ (QPP) : ๊ธฐ์กด ์„œ์ˆ ํ˜• ํ”„๋กœ๊ทธ๋ž˜๋ฐ(predictive programming)

Programming Languages Computer Science Quantum Physics
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Quantum Signatures of Solar System Dynamics

1. ์—ฐ๊ตฌ ๋™๊ธฐ์™€ ๋ฐฐ๊ฒฝ ์—ญ์‚ฌ์  ์—ฐ๊ฒฐ ๊ณ ๋ฆฌ : ์ €์ž๋Š” 1920โ€‘๋Œ€ โ€œ๊ตฌ ์–‘์ž์—ญํ•™โ€์ด ์›์ž ์ŠคํŽ™ํŠธ๋Ÿผ์„ ์„ค๋ช…ํ•˜๋ฉด์„œ ๋งˆ์ฃผํ•œ ๊ณต๋ช…(Resonance)ยทํ‡ดํ™”(Accidental Degeneracy) ๋ฌธ์ œ๋ฅผ ์ฒœ์ฒด์—ญํ•™์— ๊ทธ๋Œ€๋กœ ์ ์šฉํ•œ๋‹ค๋Š” ๋…ํŠนํ•œ ๊ด€์ ์„ ์ œ์‹œํ•œ๋‹ค. ์ด๋Š” Bohrโ€‘Sommerfeld ์–‘์žํ™”๊ฐ€ ํ–‰์„ฑ ๊ถค๋„์—๋„ ์ ์šฉ๋  ์ˆ˜ ์žˆ๋‹ค๋Š” ๊ฐ€์„ค์„ ์ „์ œ๋กœ ํ•œ๋‹ค. Heisenberg์˜ ํ˜์‹  : Heisenberg๊ฐ€ ๋งคํŠธ๋ฆญ์Šค ์—ญํ•™์„ ์ฐฝ์‹œํ•œ ๋ฐฐ๊ฒฝ์„ โ€œ๊ณต๋ช… ์กฐ๊ฑด์„ ๋งŒ์กฑ์‹œํ‚ค๋Š” ๊ณ ์ „์  ์ฃผ๊ธฐ ๊ถค๋„โ€์˜ ์กด์žฌ์™€ ์—ฐ๊ฒฐ์‹œ์ผœ, ์–‘์žํ™” ๊ทœ์น™์„ ํ–‰์„ฑ๊ณ„์— ๊ทธ๋Œ€๋กœ ์˜ฎ๊ธธ ์ˆ˜ ์žˆ์Œ์„

System Physics
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Schwingers Magnetic Model of Matter: Can It Help Us With Grand Unification?

1. ์—ฐ๊ตฌ ๋™๊ธฐ์™€ ๋ชฉํ‘œ ๋Œ€ํ†ต์ผ์˜ ์‹คํ—˜์  ๊ฒ€์ฆ ์š”๊ตฌ : ์ €์ž๋Š” โ€œ์ƒˆ๋กœ์šด ์ด๋ก ์ด ์‹คํ—˜์ ์œผ๋กœ ๊ฒ€์ฆ๋  ๋•Œ๊นŒ์ง€๋Š” ์˜๋ฏธ๊ฐ€ ์—†๋‹คโ€๋Š” ์ž…์žฅ์„ ๊ฐ•์กฐํ•˜๋ฉฐ, ๊ธฐ์กด ์ดˆ๋ˆ ์ด๋ก  ๋“ฑ ๊ณ ์ฐจ์›ยท๊ณ ์—๋„ˆ์ง€ ๋ชจ๋ธ์ด ํ˜„์žฌ ์‹คํ—˜๊ณผ ๊ดด๋ฆฌ๋ผ ์žˆ์Œ์„ ๋น„ํŒํ•œ๋‹ค. ์†”๋ฆฌํ†ค ๊ธฐ๋ฐ˜ ์œ ํ•œ ์ด๋ก  : ์ „์ž์™€ ๊ฐ™์€ ์ ์ „ํ•˜ ๋ชจ๋ธ์ด ์ดˆ๊ธฐ์— ๋ฌดํ•œ ์ž๊ธฐ์—๋„ˆ์ง€๋ฅผ ์ดˆ๋ž˜ํ•˜๋Š” ๋ฌธ์ œ๋ฅผ ํ”ผํ•˜๊ธฐ ์œ„ํ•ด, ์ž…์ž๋ฅผ ์œ ํ•œํ•œ ๋ฐ˜๊ฒฝ์„ ๊ฐ€์ง„ ์†”๋ฆฌํ†ค ์œผ๋กœ ๋ชจ๋ธ๋งํ•˜๊ณ ์ž ํ•œ๋‹ค. ์ด๋Š” ์ „ํ†ต์ ์ธ ์ •๊ทœํ™”ยท์žฌ๊ทœ๊ฒฉํ™” ์ ˆ์ฐจ๋ฅผ ํšŒํ”ผํ•˜๋Š” ๋ฐฉํ–ฅ์ด๋‹ค. 2. ํ•ต์‹ฌ ์ œ์•ˆ โ€“ ์Šˆ์œ™๊ฑฐ์˜ MMM ์žฌ๊ฒ€ํ†  | ์š”์†Œ | ๊ธฐ์กด QCD์™€์˜ ์ฐจ์ด์  | ๋…ผ๋ฌธ์—์„œ ์ œ

Physics Model
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Selection simultanee dindex et de vues materialisees

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ํ•„์š”์„ฑ ๋ฐ์ดํ„ฐ ์›จ์–ดํ•˜์šฐ์Šค ํŠน์„ฑ : ์Šคํƒ€ ์Šคํ‚ค๋งˆยท์Šค๋…ธ์šฐํ”Œ๋ ˆ์ดํฌ ์Šคํ‚ค๋งˆ์—์„œ ๋‹ค์ˆ˜์˜ ์กฐ์ธ๊ณผ ์ง‘๊ณ„๊ฐ€ ๋นˆ๋ฒˆํžˆ ๋ฐœ์ƒ, ์ด๋Š” I/O ๋น„์šฉ์„ ๊ธ‰์ฆ์‹œํ‚จ๋‹ค. ์ธ๋ฑ์Šค vs ๋ฌผ๋ฆฌํ™”๋œ ๋ทฐ : ์ธ๋ฑ์Šค๋Š” ์„ ํƒ๋„(Selectivity)๊ฐ€ ๋†’์€ ์ปฌ๋Ÿผ์— ์œ ๋ฆฌํ•˜๊ณ , ์กฐ์ธ ๋น„์šฉ์„ ๊ฐ์†Œ์‹œํ‚จ๋‹ค. ๋ฌผ๋ฆฌํ™”๋œ ๋ทฐ๋Š” ์ง‘๊ณ„ยท์กฐ์ธ ๊ฒฐ๊ณผ๋ฅผ ๋ฏธ๋ฆฌ ์ €์žฅํ•ด, ๋Œ€๊ทœ๋ชจ ์Šค์บ”์„ ํšŒํ”ผํ•œ๋‹ค. ๊ณตํ†ต ์ œ์•ฝ : ๋‘ ๊ตฌ์กฐ ๋ชจ๋‘ ์ €์žฅ ๊ณต๊ฐ„ ๊ณผ ๊ฐฑ์‹  ๋น„์šฉ ์„ ๊ณต์œ ํ•œ๋‹ค. ๋”ฐ๋ผ์„œ ๋™์‹œ์— ๊ณ ๋ คํ•˜์ง€ ์•Š์œผ๋ฉด ๋น„ํšจ์œจ์ ์ธ ์ž์› ์‚ฌ์šฉ์ด ๋ฐœ์ƒํ•œ๋‹ค. 2. ์ฃผ์š” ๊ธฐ์—ฌ | ๋ฒˆํ˜ธ | ๋‚ด์šฉ | ์˜์˜ | | | |

Databases Computer Science
Splay Trees, Davenport-Schinzel Sequences, and the Deque Conjecture

Splay Trees, Davenport-Schinzel Sequences, and the Deque Conjecture

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋™๊ธฐ ์Šคํ”Œ๋ ˆ์ด ํŠธ๋ฆฌ๋Š” ์ž๊ธฐ์กฐ์ •(selfโ€‘adjusting) ์ด์ง„ ํƒ์ƒ‰ ํŠธ๋ฆฌ๋กœ, ์‚ฝ์ž…ยท์‚ญ์ œยท๊ฒ€์ƒ‰ ์—ฐ์‚ฐ ์‹œ๋งˆ๋‹ค ์ ‘๊ทผ๋œ ๋…ธ๋“œ๋ฅผ ๋ฃจํŠธ๋กœ ๋Œ์–ด์˜ฌ๋ฆฌ๋Š” splay ์—ฐ์‚ฐ์„ ์ˆ˜ํ–‰ํ•œ๋‹ค. ๋™์  ์ตœ์ ์„ฑ(Dynamic Optimality) ์ถ”์ธก : ์–ด๋–ค ์˜จ๋ผ์ธ ์ด์ง„ ํƒ์ƒ‰ ํŠธ๋ฆฌ๋ผ๋„ ์‚ฌ์ „์— ์ „์ฒด ์ ‘๊ทผ ์ˆœ์„œ๋ฅผ ์•Œ๋ฉด ์ตœ์ ์˜ ๋น„์šฉ์— ์ƒ์ˆ˜๋ฐฐ ์ด๋‚ด๋กœ ์ ‘๊ทผํ•  ์ˆ˜ ์žˆ์–ด์•ผ ํ•œ๋‹ค๋Š” ๊ฐ•๋ ฅํ•œ ๊ฐ€์„ค. ํ˜„์žฌ๊นŒ์ง€๋Š” subโ€‘logarithmic ๊ฒฝ์Ÿ๋น„์œจ์„ ๋ณด์žฅํ•˜๋Š” ๊ฒฐ๊ณผ์กฐ์ฐจ ์กด์žฌํ•˜์ง€ ์•Š์œผ๋ฉฐ, ์ฃผ์š” ๋ฏธํ•ด๊ฒฐ ๋ฌธ์ œ๋Š” Deque , Traversal , Split ์ถ”์ธก์ด๋‹ค.

Data Structures Computer Science
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Stable stochastic dynamics in yeast cell cycle

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ์˜์˜ ๋…ธ์ด์ฆˆ์™€ ์ƒ๋ช… ํ˜„์ƒ : ์„ธํฌ ๋‚ด ํ™”ํ•™ ๋ฐ˜์‘์€ ๋ถ„์ž ์ˆ˜๊ฐ€ ์ ์–ด ๋‚ด์žฌ์ ( intrinsic) ๋…ธ์ด์ฆˆ๊ฐ€ ํฌ๊ฒŒ ์ž‘์šฉํ•œ๋‹ค. ํšจ๋ชจ์™€ ๊ฐ™์€ ๋‹จ์„ธํฌ ์ƒ๋ฌผ์—์„œ๋Š” ๊ฐ™์€ ์œ ์ „์ž๋ฅผ ๊ฐ€์ง„ ๊ฐœ์ฒด ๊ฐ„์—๋„ ๋ฐœํ˜„ ์ˆ˜์ค€์ด ํฌ๊ฒŒ ๋‹ฌ๋ผ์ง„๋‹ค(1โ€‘3). ๊ธฐ์กด ๋ชจ๋ธ์˜ ํ•œ๊ณ„ : Tyson ๋“ฑ์€ ๋ฏธ๋ถ„๋ฐฉ์ •์‹ ๊ธฐ๋ฐ˜์˜ ๊ฒฐ์ •๋ก ์  ๋ชจ๋ธ์„, Li ๋“ฑ์€ Boolean ๋„คํŠธ์›Œํฌ๋ฅผ ์ œ์‹œํ–ˆ์ง€๋งŒ, ๋‘ ์ ‘๊ทผ ๋ชจ๋‘ ๋…ธ์ด์ฆˆ ๋ฐœ์ƒ ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ์™ธ๋ถ€ ์ž…๋ ฅ์œผ๋กœ๋งŒ ์ทจ๊ธ‰ํ–ˆ๋‹ค. ๋”ฐ๋ผ์„œ โ€œ๋…ธ์ด์ฆˆ๊ฐ€ ์‹ค์ œ๋กœ ์–ด๋–ป๊ฒŒ ์ƒ์„ฑ๋˜๊ณ , ์–ด๋–ป๊ฒŒ ์–ต์ œ๋˜๋Š”๊ฐ€?โ€์— ๋Œ€ํ•œ ๋‹ต์ด ๋ถ€์กฑํ–ˆ๋‹ค. 2. ๋ชจ๋ธ ์„ค๊ณ„ | ์š”์†Œ

Quantitative Biology
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Structural plasticity of single chromatin fibers revealed by torsional manipulation

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์  ํฌ๋กœ๋งˆํ‹ด์˜ ๋ฌผ๋ฆฌ์  ํŠน์„ฑ ์€ ์ „์‚ฌยท๋ณต์ œยท์ˆ˜์„  ๋“ฑ ํ•ต ๋‚ด ํ•ต์‹ฌ ๊ณผ์ •์— ์ง์ ‘์ ์ธ ์˜ํ–ฅ์„ ๋ฏธ์น˜์ง€๋งŒ, ๊ธฐ์กด ์—ฐ๊ตฌ๋Š” ์ฃผ๋กœ ์ธ์žฅ(ํž˜) ์กฐ๊ฑด์— ํ•œ์ •๋ผ ์žˆ์—ˆ๋‹ค. ํ† ์…˜(๋น„ํ‹€๋ฆผ) ์ŠคํŠธ๋ ˆ์Šค ๋Š” DNA ๋ณต์ œยท์ „์‚ฌ ๊ณผ์ •์—์„œ ๋ฐœ์ƒํ•˜๋Š” ์ž์—ฐ์Šค๋Ÿฌ์šด ๋ฌผ๋ฆฌ์  ํž˜์ด๋ฉฐ, ํฌ๋กœ๋งˆํ‹ด์ด ์ด๋ฅผ ์–ด๋–ป๊ฒŒ ํก์ˆ˜ยท์กฐ์ ˆํ•˜๋Š”์ง€๋Š” ์•„์ง ๋ช…ํ™•ํžˆ ๋ฐํ˜€์ง€์ง€ ์•Š์•˜๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ๋‹จ์ผ ํฌ๋กœ๋งˆํ‹ด ์„ฌ์œ  ์— ํ† ์…˜์„ ๊ฐ€ํ•จ์œผ๋กœ์จ, ๋‰ดํด๋ ˆ์˜ค์†œ์ด ์ž…ยท์ถœ๊ตฌ DNA ๊ต์ฐจ ์ƒํƒœ๋ฅผ ์ „ํ™˜ํ•˜๋ฉฐ ๊ตฌ์กฐ์  ๊ฐ€์†Œ์„ฑ์„ ๋ฐœํœ˜ํ•œ๋‹ค๋Š” ์ƒˆ๋กœ์šด ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ์ œ์‹œํ•œ๋‹ค. 2. ์‹คํ—˜ ์„ค๊ณ„ ๋ฐ ๋ฐฉ๋ฒ• | ๋‹จ๊ณ„ | ๋‚ด์šฉ |

Quantitative Biology Physics
Sylvesters Minorant Criterion, Lagrange-Beltrami Identity, and   Nonnegative Definiteness

Sylvesters Minorant Criterion, Lagrange-Beltrami Identity, and Nonnegative Definiteness

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋™๊ธฐ ์–‘์ •๋ถ€ํ˜ธ์™€ ๋น„์Œ์–‘์„ฑ ์ •๋ถ€ํ˜ธ ๋Š” ๋‹ค๋ณ€์ˆ˜ ๋ฏธ๋ถ„ํ•™ยท์ตœ์ ํ™”ยท๋ณผ๋ก์„ฑ ์ด๋ก ์—์„œ ํ•ต์‹ฌ์ ์ธ ์—ญํ• ์„ ํ•œ๋‹ค. ๊ธฐ์กด ๊ต๊ณผ์„œ์—์„œ๋Š” Sylvesterโ€™s Criterion (์„ ํ–‰ ์ฃผ์†Œํ–‰๋ ฌ์‹์ด ๋ชจ๋‘ ์–‘์ˆ˜ โ‡” ์–‘์ •๋ถ€ํ˜ธ)๋งŒ์„ ๊ฐ•์กฐํ•˜๊ณ , ๋น„์Œ์–‘์„ฑ ์ •๋ถ€ํ˜ธ์— ๋Œ€ํ•œ ๋ช…์‹œ์  ํŒ์ • ๊ธฐ์ค€์€ ๊ฑฐ์˜ ๋‹ค๋ฃจ์ง€ ์•Š๋Š”๋‹ค. ์ผ๋ถ€ ๋ฌธํ—Œ์—์„œ๋Š” โ€œ์„ ํ–‰ ์ฃผ์†Œํ–‰๋ ฌ์‹์ด ๋น„์Œ์–‘์ด๋ฉด ๋น„์Œ์–‘์„ฑ ์ •๋ถ€ํ˜ธโ€๋ผ๊ณ  ์ž˜๋ชป ๊ธฐ์ˆ ํ•˜๊ณ  ์žˆ์–ด, ์ •ํ™•ํ•œ ์ •๋ฆฌ๊ฐ€ ํ•„์š”ํ•˜๋‹ค. 2. ์ฃผ์š” ๊ฒฐ๊ณผ 1. ์–‘์ •๋ถ€ํ˜ธ ํŒ์ • ๊ธฐ์กด Sylvesterโ€™s Criterion๋ฅผ 2ยท3 ์ฐจ์›์— ๋Œ€ํ•ด ์™„์ „ ์ž๋ช… ์ฆ๋ช… ์„ ์ œ๊ณต

Mathematics
Symbolic-computation study of integrable properties for the   (2+1)-dimensional Gardner equation with the two-singular-manifold method

Symbolic-computation study of integrable properties for the (2+1)-dimensional Gardner equation with the two-singular-manifold method

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ์˜์˜ Painlevรฉ ๋ถ„์„ โ†’ ํŠน์ด ๋งค๋‹ˆํด๋“œ ๋ฐฉ๋ฒ• : ์ „ํ†ต์ ์ธ SMM์€ ํ•˜๋‚˜์˜ ์ „๊ฐœ ๊ฐ€์ง€๋งŒ์„ ์ด์šฉํ•ด ๋ผํฌ์Šค ์Œยท๋ฐ”์ด๋ž™ํ„ฐ ๋ณ€ํ™˜ ๋“ฑ์„ ์–ป๋Š”๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๊ฐ€๋“œ๋„ˆ ๋ฐฉ์ •์‹๊ณผ ๊ฐ™์ด ๋‘ ๊ฐœ์˜ ์ „๊ฐœ ๊ฐ€์ง€(ฮต ยฑ1)๋ฅผ ๊ฐ–๋Š” ๊ฒฝ์šฐ, ๋‹จ์ผ SMM์œผ๋กœ๋Š” ์ถฉ๋ถ„ํ•œ ์ •๋ณด๋ฅผ ์ถ”์ถœํ•˜๊ธฐ ์–ด๋ ต๋‹ค. ๋‘โ€‘ํŠน์ดโ€‘๋งค๋‹ˆํด๋“œ ๋ฐฉ๋ฒ• : ๋‘ ๊ฐœ์˜ ๋…๋ฆฝ์ ์ธ ํŠน์ด ๋งค๋‹ˆํด๋“œ ฯ†, ฯ•๋ฅผ ๋™์‹œ์— ๋„์ž…ํ•ด ํŠธ๋ ์ผ€์ด์…˜ ์„ ์ˆ˜ํ–‰ํ•จ์œผ๋กœ์จ, ๋‘ ์ „๊ฐœ ๊ฐ€์ง€๋ฅผ ๋ชจ๋‘ ํ™œ์šฉํ•œ๋‹ค. ์ด๋Š” ๊ธฐ์กด ์—ฐ๊ตฌ(์˜ˆ: mKdV, SG, ์ˆ˜์ • KP)์—์„œ ์„ฑ๊ณต์ ์œผ๋กœ ์ ์šฉ๋œ ๋ฐ” ์žˆ๋‹ค. 2. ์ฃผ์š” ๊ฒฐ๊ณผ | ํ•ญ๋ชฉ

Nonlinear Sciences
No Image

The Fermat-Torricelli problem in normed planes and spaces

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ์˜์˜ ํŽ˜๋ฅด๋งˆโ€‘ํ† ๋ฆฌ์ฒผ๋ฆฌ ๋ฌธ์ œ ๋Š” ์œ ํด๋ฆฌ๋“œ ๊ฑฐ๋ฆฌ์—์„œ โ€œ๋ชจ๋“  ์ ์— ๋Œ€ํ•œ ๊ฑฐ๋ฆฌ ํ•ฉ์„ ์ตœ์†Œํ™”ํ•˜๋Š” ์ โ€์„ ์ฐพ๋Š” ๊ณ ์ „ ์ตœ์ ํ™” ๋ฌธ์ œ์ด๋ฉฐ, ์‹œ์„ค ๋ฐฐ์น˜ยท๋„คํŠธ์›Œํฌ ์„ค๊ณ„ ๋“ฑ ์‹ค์šฉ ๋ถ„์•ผ์—์„œ ํ•ต์‹ฌ์ ์ธ ์—ญํ• ์„ ํ•œ๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ๋Š” ์ฃผ๋กœ ์œ ํด๋ฆฌ๋“œ ํ˜น์€ ํŠน์ • ๋…ธ๋ฆ„(์˜ˆ: $L^1$, $L^infty$) ์— ํ•œ์ •๋ผ ์žˆ์—ˆ์œผ๋ฉฐ, ์ผ๋ฐ˜์ ์ธ Minkowski ๊ณต๊ฐ„์— ๋Œ€ํ•œ ์ฒด๊ณ„์ ์ธ ์ •๋ฆฌ๋Š” ๋ถ€์กฑํ–ˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ โ€œ๋…ธ๋ฆ„์ด ๋ฐ”๋€Œ์–ด๋„ ์œ ์ง€๋˜๋Š” ๊ธฐํ•˜ํ•™์  ๊ตฌ์กฐโ€ ์— ์ดˆ์ ์„ ๋งž์ถ”์–ด, FT locus ๋ฅผ ์ฝ˜ ๊ต์ฐจ ์™€ $d$โ€‘์„ธ๊ทธ๋จผํŠธ ๋ผ๋Š” ๋ณดํŽธ์  ๋„๊ตฌ๋กœ ์„ค๋ช…ํ•œ๋‹ค๋Š” ์ ์—์„œ

Mathematics
The Moravian crossroads. Mathematics and mathematicians in Brno between   German traditions and Czech hopes

The Moravian crossroads. Mathematics and mathematicians in Brno between German traditions and Czech hopes

1. ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ๊ณผ ์˜์˜ ๋‹ค๋ฌธํ™” ์ง€์—ญ์œผ๋กœ์„œ์˜ ๋ชจ๋ผ๋น„์•„ ๋ธŒ๋ฅด๋…ธ๋Š” ๋…์ผ์–ด ์‚ฌ์šฉ ์ธ๊ตฌ์™€ ์ฒด์ฝ”์–ด ์‚ฌ์šฉ ์ธ๊ตฌ๊ฐ€ ์•ฝ 30โ€‘40 %์”ฉ์„ ์ฐจ์ง€ํ•œ ๋ณตํ•ฉ ๋ฏผ์กฑ ๊ตฌ์„ฑ์„ ๊ฐ€์ง€๊ณ  ์žˆ์—ˆ๋‹ค. 1910๋…„ ์ธ๊ตฌ์กฐ์‚ฌ์™€ 1919๋…„ ์ •์น˜์  ์ƒํ™ฉ์— ๋”ฐ๋ฅธ ์ธ์‹ ์ฐจ์ด๋Š” โ€˜๋…์ผ์ธโ€™ยทโ€˜์ฒด์ฝ”์ธโ€™ ์ •์ฒด์„ฑ์ด ๊ณ ์ •๋˜์ง€ ์•Š์•˜์Œ์„ ๋ณด์—ฌ์ค€๋‹ค. ์—ญ์‚ฌโ€‘์ˆ˜ํ•™ํ•™(Historiography of Mathematics)๊ณผ ๋ฏผ์กฑ์ฃผ์˜ ์ €์ž๋Š” ์ˆ˜ํ•™์‚ฌ์˜ ์ง€์—ญ์  ์ „๊ฐœ๋ฅผ ์ •์น˜ยท์‚ฌํšŒ์  ๋งฅ๋ฝ๊ณผ ๋ถ„๋ฆฌํ•  ์ˆ˜ ์—†๋‹ค๊ณ  ์ฃผ์žฅํ•œ๋‹ค. ์ด๋Š” ์ˆ˜ํ•™์ด โ€˜์–ธ์–ดยท๋ฌธํ™”์  ์žฅ๋ฒฝโ€™์— ์˜ํ•ด ์–ด๋–ป๊ฒŒ ์ œํ•œยท์ด‰์ง„๋˜์—ˆ๋Š”์ง€๋ฅผ ๋ณด์—ฌ์ฃผ๋Š” ์ค‘์š”ํ•œ ์‚ฌ๋ก€๋‹ค.

Mathematics
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The Virtual Manufacturing concept: Scope, Socio-Economic Aspects and Future Trends

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ํ•„์š”์„ฑ ์ œ์กฐ ๋ณต์žก๋„ยท์‹œ์žฅ ๋ณ€๋™์„ฑ ์ฆ๊ฐ€ : ์ œํ’ˆ์€ ์ ์  ๋ณต์žกํ•ด์ง€๊ณ , ์†Œ๋Ÿ‰ยท๋‹คํ’ˆ์ข… ์ƒ์‚ฐ์ด ์ผ๋ฐ˜ํ™”๋˜๋ฉด์„œ ์œ ์—ฐยท๋ฏผ์ฒฉํ•œ ์ƒ์‚ฐ ์ฒด๊ณ„๊ฐ€ ์š”๊ตฌ๋œ๋‹ค. ์ง€๋ฆฌ์ ยท์กฐ์ง์  ๋ถ„์‚ฐ : ๊ธ€๋กœ๋ฒŒ ๊ณต๊ธ‰๋ง๊ณผ ์ง€์‹ยท์ •๋ณด ํ๋ฆ„์ด ๋ณต์žกํ•ด์ง์— ๋”ฐ๋ผ, ์‹ค์ œ ๊ณต์ •์„ ์‚ฌ์ „์— ๊ฒ€์ฆํ•  ์ˆ˜ ์žˆ๋Š” ๊ฐ€์ƒ ํ™˜๊ฒฝ์ด ํ•„์ˆ˜์ ์ด๋‹ค. 2. ๊ฐ€์ƒ ์ œ์กฐ(VM)์˜ ์ •์˜์™€ ๋ฒ”์œ„ | ์ •์˜ | ํ•ต์‹ฌ ์š”์†Œ | | | | | ํ†ตํ•ฉยทํ•ฉ์„ฑ ์ œ์กฐ ํ™˜๊ฒฝ (University of Maryland) | Environment (๋„๊ตฌยท๋ชจ๋ธยท๋ฐฉ๋ฒ•ยท์กฐ์ง ์›์น™) โ†’ Exercising (์‹œ๋ฎฌ๋ ˆ์ด์…˜ ์‹คํ–‰) โ†’

Robotics Computer Science

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