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Open Graphs and Monoidal Theories

Open Graphs and Monoidal Theories

๋ณธ ๋…ผ๋ฌธ์€ ๊ทธ๋ž˜ํ”ฝ ์–ธ์–ด๋ฅผ ํ˜•์‹์ ์œผ๋กœ ๋‹ค๋ฃจ๋Š” ๋ฐ ์žˆ์–ด ๋‘ ๊ฐ€์ง€ ์ค‘์š”ํ•œ ๋ฌธ์ œ๋ฅผ ๋™์‹œ์— ํ•ด๊ฒฐํ•œ๋‹ค. ์ฒซ ๋ฒˆ์งธ๋Š” ๊ทธ๋ž˜ํ”„ ๊ตฌ์กฐ ์ž์ฒด๊ฐ€ ํƒ€์ž… ์‹œ์Šคํ…œ์„ ๋‚ดํฌํ•˜๋„๋ก ์„ค๊ณ„ ํ•˜๋Š” ๊ฒƒ์ด๊ณ , ๋‘ ๋ฒˆ์งธ๋Š” ๊ทธ ํƒ€์ž… ์‹œ์Šคํ…œ์ด ์žฌ์ž‘์„ฑ ๊ณผ์ •์—์„œ ๋ณด์กด ๋œ๋‹ค๋Š” ์ ์ด๋‹ค. ๊ธฐ์กด์˜ ๋ฌธ์ž์—ด ๋‹ค์ด์–ด๊ทธ๋žจ์€ ์‹œ๊ฐ์ ์œผ๋กœ ์ง๊ด€์ ์ด์ง€๋งŒ, ์ˆ˜ํ•™์  ๊ธฐ๋ฐ˜์ด ๋ถ€์กฑํ•ด ์ž๋™ํ™”๋œ ๋„๊ตฌ์— ์ ์šฉํ•˜๊ธฐ ์–ด๋ ค์› ๋‹ค. ์ €์ž๋“ค์€ ์˜คํ”ˆโ€‘๊ทธ๋ž˜ํ”„๋ผ๋Š” ๊ฐœ๋…์„ ๋„์ž…ํ•จ์œผ๋กœ์จ ๋ณ€(edge)์ด ๋ฐ˜๋“œ์‹œ ์ •์ ์— ์—ฐ๊ฒฐ๋  ํ•„์š”๊ฐ€ ์—†๋„๋ก ํ—ˆ์šฉํ•œ๋‹ค. ์ด๋Š” ์ž…๋ ฅยท์ถœ๋ ฅ ํฌํŠธ๋ฅผ ์ž์—ฐ์Šค๋Ÿฝ๊ฒŒ ๋ชจ๋ธ๋งํ•  ์ˆ˜ ์žˆ๊ฒŒ ํ•˜๋ฉฐ, ๋ณตํ•ฉ ์—ฐ์‚ฐ์„ ๊ตฌ์„ฑํ•  ๋•Œ โ€œ์™€

Computer Science Logic Mathematics
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Open Questions about Time and Self-reference in Living Systems

: ์ด ๋…ผ๋ฌธ์€ ์‚ด์•„์žˆ๋Š” ์‹œ์Šคํ…œ์˜ ๋ณธ์งˆ์ ์ธ ํŠน์„ฑ๊ณผ ๊ทธ๊ฒƒ์ด ๊ณผํ•™์  ์—ฐ๊ตฌ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์— ๋Œ€ํ•œ ์‹ฌ์ธต ๋ถ„์„์„ ์ œ๊ณตํ•œ๋‹ค. ์ž์—ฐ ์‹œ๊ฐ„๊ณผ ํ‘œํ˜„ ์‹œ๊ฐ„์˜ ๊ฐœ๋…์€ ๋ฌผ๋ฆฌ์  ๊ณผ์ •๊ณผ ์ƒ๋ช…์ฒด์˜ ๊ด€๊ณ„, ๊ทธ๋ฆฌ๊ณ  ์‹œ๊ฐ„์— ๋Œ€ํ•œ ์šฐ๋ฆฌ์˜ ์ดํ•ด๋ฅผ ์žฌ์ •์˜ํ•œ๋‹ค. ์ž๊ธฐ์ฐธ์กฐ์™€ ์ž๊ธฐ์ˆ˜์ •์€ ์ „ํ†ต์ ์ธ ํ˜•์‹์ฃผ์˜๋กœ๋Š” ์„ค๋ช…ํ•˜๊ธฐ ์–ด๋ ค์šด ๋ณต์žกํ•œ ํ˜„์ƒ์ด๋ฉฐ, ์ƒˆ๋กœ์šด ๋ชจ๋ธ๋ง ์ ‘๊ทผ๋ฒ•์ด ํ•„์š”ํ•˜๋‹ค. ์ €์ž๋“ค์€ ์ด๋Ÿฌํ•œ ํŠน์„ฑ์ด ์‚ด์•„์žˆ๋Š” ์‹œ์Šคํ…œ์˜ ์ฐฝ๋ฐœ์„ฑ๊ณผ ์ ์‘์„ฑ์— ํ•„์ˆ˜์ ์ž„์„ ๊ฐ•์กฐํ•˜๋ฉฐ, ๋‹ค์–‘ํ•œ ๊ณผํ•™ ๋ถ„์•ผ์—์„œ ์ด๋Ÿฌํ•œ ๊ฐœ๋…์„ ํ†ตํ•ฉํ•˜๋Š” ๊ฒƒ์ด ์ค‘์š”ํ•จ์„ ์‹œ์‚ฌํ•œ๋‹ค.

System
Optimal charging guidance strategies for electric vehicles by   considering dynamic charging requests in a time-varying road network

Optimal charging guidance strategies for electric vehicles by considering dynamic charging requests in a time-varying road network

: ์ „๊ธฐ์ฐจ(EV)๋Š” ํ™˜๊ฒฝ ๋ฐ ์—๋„ˆ์ง€ ๋ฌธ์ œ ํ•ด๊ฒฐ์— ์žˆ์–ด ์ค‘์š”ํ•œ ๋Œ€์•ˆ์œผ๋กœ ์ฃผ๋ชฉ๋ฐ›๊ณ  ์žˆ์ง€๋งŒ, ์ œํ•œ๋œ ์ฃผํ–‰ ๊ฑฐ๋ฆฌ์™€ ๋ถ€์กฑํ•œ ์ถฉ์ „ ์ธํ”„๋ผ๋Š” ์—ฌ์ „ํžˆ ํฐ ๋„์ „ ๊ณผ์ œ์ด๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ด๋Ÿฌํ•œ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ๋™์  ์ถฉ์ „ ์š”์ฒญ๊ณผ ์‹œ๊ฐ„ ๋ณ€ํ™” ๋„๋กœ๋ง์„ ๊ณ ๋ คํ•œ ์ตœ์ ์˜ ์ถฉ์ „ ๊ฐ€์ด๋“œ ์ „๋žต์„ ์ œ์•ˆํ•œ๋‹ค. ๋จผ์ €, EV ์šด์ „์ž์˜ ์—ฌํ–‰ ์ˆ˜์š”๋ฅผ ๊ณ ๋ คํ•œ ์ „๋žต์€ ์šด์ „์ž๋“ค์ด ๋ชฉ์ ์ง€๊นŒ์ง€ ๋„๋‹ฌํ•˜๋Š” ๋ฐ ํ•„์š”ํ•œ ๊ฒฝ๋กœ์™€ ์ถฉ์ „์†Œ ์„ ํƒ์„ ๋•๋Š”๋‹ค. ์ด๋Š” ์šด์ „์ž๋“ค์˜ ์ฃผํ–‰ ๊ฑฐ๋ฆฌ ๋ถˆ์•ˆ์„ ์ค„์ด๊ณ , ํšจ์œจ์ ์ธ ๊ฒฝ๋กœ ๊ณ„ํš์„ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•œ๋‹ค. ํŠนํžˆ, ์ตœ์ ํ™” ๊ธฐ์ค€์„ ์ฃผํ–‰ ๊ฑฐ๋ฆฌ์— ๋‘๋Š” ๊ฒƒ์€ EV์˜ ๋ฐฐํ„ฐ

Computer Science Systems and Control Network Electrical Engineering and Systems Science
Optimal Control Strategies in Delayed Sharing Information Structures

Optimal Control Strategies in Delayed Sharing Information Structures

: ๋ถ„์‚ฐ ์ œ์–ด ์‹œ์Šคํ…œ์˜ ์ตœ์  ์„ค๊ณ„๋Š” ์‹œ๊ฐ„์— ๋”ฐ๋ผ ์ฆ๊ฐ€ํ•˜๋Š” ๋ฐ์ดํ„ฐ๋ฅผ ์ฒ˜๋ฆฌํ•ด์•ผ ํ•˜๋Š” ์–ด๋ ค์›€์ด ์žˆ์Šต๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋ฐ์ดํ„ฐ ์ฆ๊ฐ€๋Š” ์ œ์–ด ๋ฒ•์น™์˜ ๋„๋ฉ”์ธ ํ™•์žฅ์„ ์•ผ๊ธฐํ•˜๋ฉฐ, ์ด๋Š” ์ตœ์  ์ „๋žต์„ ์ฐพ๊ณ  ๊ตฌํ˜„ํ•˜๋Š” ๋ฐ ํฐ ๋„์ „์ž…๋‹ˆ๋‹ค. ์ค‘์•™ ์ง‘์ค‘์‹ ํ™•๋ฅ  ์ œ์–ด๋Š” ์ด๋Ÿฌํ•œ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•œ ์ ‘๊ทผ๋ฒ•์œผ๋กœ, ์ •๋ณด ์ƒํƒœ์™€ ๊ตฌ์กฐ์  ๊ฒฐ๊ณผ๋ฅผ ํ†ตํ•ด ์‹œ๊ฐ„ ๋ถˆ๋ณ€ ๊ณต๊ฐ„์—์„œ ์ œ์–ด ๋ฒ•์น™์„ ๋‹ค๋ฃน๋‹ˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ง€์—ฐ ๊ณต์œ  ์ •๋ณด ๊ตฌ์กฐ๋ฅผ ๊ฐ€์ง„ ๋ถ„์‚ฐ ์ œ์–ด ์‹œ์Šคํ…œ์— ๋Œ€ํ•œ ๊ตฌ์กฐ์  ๋ถ„์„์„ ์ˆ˜ํ–‰ํ•ฉ๋‹ˆ๋‹ค. ์ด ๊ตฌ์กฐ๋Š” ๊ฐ ์ œ์–ด ์Šคํ…Œ์ด์…˜์ด ๊ณผ๊ฑฐ์˜ ๊ด€์ฐฐ๊ณผ ์ œ์–ด ๋™์ž‘์„ ์•Œ๊ณ  ์žˆ๋Š” ๊ฒƒ์œผ๋กœ, ๊ณ ์ „์ ์ธ ์™„์ „

Other CS Computer Science
Optimal excitation of two dimensional Holmboe instabilities

Optimal excitation of two dimensional Holmboe instabilities

: ์ธตํ™”๋œ ํ™˜๊ฒฝ์—์„œ ๋ฐœ์ƒํ•˜๋Š” Holmboe ๋ถˆ์•ˆ์ •์„ฑ์€ ์ธต๋ฅ˜์ธต์˜ ์•ˆ์ •์„ฑ์— ํฐ ์˜ํ–ฅ์„ ๋ฏธ์นฉ๋‹ˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ด๋Ÿฌํ•œ ๋ถˆ์•ˆ์ •์„ฑ์ด ์–ด๋–ป๊ฒŒ ๋ฐœ์ƒํ•˜๊ณ , ์–ด๋–ค ๋ฌผ๋ฆฌ์  ํŠน์„ฑ์„ ๊ฐ€์ง€๋Š”์ง€, ๊ทธ๋ฆฌ๊ณ  ๊ทธ ์˜ํ–ฅ์ด ์–ด๋– ํ•œ์ง€๋ฅผ ์ž์„ธํžˆ ๋ถ„์„ํ•ฉ๋‹ˆ๋‹ค. ๋จผ์ €, ์ธตํ™”๋œ ํ๋ฆ„์—์„œ์˜ ์ธต๋ฅ˜์ธต๊ณผ ๋‚œ๋ฅ˜์˜ ๋ฐœ๋‹ฌ์€ ๋ฆฌ์ฒ˜๋“œ์Šจ ์ˆ˜์— ์˜ํ•ด ๊ฒฐ์ •๋˜๋ฉฐ, ํŠนํžˆ ๋†’์€ ์ธตํ™”์œจ์—์„œ Holmboe ๋ถˆ์•ˆ์ •์„ฑ์ด ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•œ๋‹ค๋Š” ๊ฒƒ์„ ๋ฐํž™๋‹ˆ๋‹ค. Holmboe ๋ถˆ์•ˆ์ •์„ฑ์€ ์ผˆ๋นˆ ํ—ฌ๋ฆ„ํ™€์ธ (KH) ๋ถˆ์•ˆ์ •์„ฑ๊ณผ ๋‹ฌ๋ฆฌ ์ธตํ™”๊ฐ€ ์ง‘์ค‘๋œ ์ข์€ ์˜์—ญ์—์„œ๋„ ๋ฐœ์ƒํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์ด๋Š” KH ๋ชจ๋“œ๊ฐ€ ๋กœ์ปฌ ๋ฆฌ์ฒ˜๋“œ์Šจ ์ˆ˜๊ฐ€

Physics Astrophysics
Optimal Gradient Clock Synchronization in Dynamic Networks

Optimal Gradient Clock Synchronization in Dynamic Networks

: ๋ถ„์‚ฐ ์ปดํ“จํŒ… ์‹œ์Šคํ…œ์—์„œ๋Š” ์ฐธ์—ฌ์ž๋“ค ๊ฐ„์˜ ์กฐ์œจ์ด ํ•„์ˆ˜์ ์ด๋ฉฐ, ์ด๋ฅผ ์œ„ํ•ด ๊ณตํ†ต๋œ ์‹œ๊ฐ„ ๊ฐœ๋…์„ ์‚ฌ์šฉํ•˜๋Š” ๊ฒƒ์ด ์ผ๋ฐ˜์ ์ž…๋‹ˆ๋‹ค. ๊ฐ ๋…ธ๋“œ๋Š” ํ•˜๋“œ์›จ์–ด ํด๋Ÿญ์„ ๊ฐ€์ง€๊ณ  ์žˆ์ง€๋งŒ, ๊ทธ ์†๋„๊ฐ€ ๋ณ€ํ•˜๊ณ  ์„œ๋กœ ๋‹ค๋ฅธ ๋…ธ๋“œ ๊ฐ„์— ๋™๊ธฐํ™”๊ฐ€ ์ด๋ฃจ์–ด์ง€์ง€ ์•Š์„ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ํด๋Ÿญ ๋“œ๋ฆฌํ”„ํŠธ๋Š” ์ฃผ๊ธฐ์ ์ธ ํ†ต์‹ ์œผ๋กœ ํ•ด๊ฒฐํ•ด์•ผ ํ•˜์ง€๋งŒ, ์ง€์—ฐ๊ณผ ๋ถ€์ •ํ™•ํ•œ ์ถ”์ •์น˜๋ผ๋Š” ๋ฌธ์ œ๊ฐ€ ๋ฐœ์ƒํ•ฉ๋‹ˆ๋‹ค. ์ „ํ†ต์ ์œผ๋กœ ๋ถ„์‚ฐ ํด๋Ÿญ ๋™๊ธฐํ™” ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ ๊ธ€๋กœ๋ฒŒ ๊ธฐ์šธ๊ธฐ๋ฅผ ์ตœ์†Œํ™”ํ•˜๋Š” ๋ฐ ์ดˆ์ ์„ ๋งž์ถ”์—ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๊ฐ€๊นŒ์šด ๋…ธ๋“œ ๊ฐ„์˜ ๋™๊ธฐํ™”๊ฐ€ ๋” ์ค‘์š”ํ•  ์ˆ˜ ์žˆ๋Š” ์ƒํ™ฉ์ด ์กด์žฌํ•˜๋ฉฐ, ์ด๋Ÿฌํ•œ ๋ฌธ์ œ๋Š” ๊ธฐ์šธ๊ธฐ ํด๋Ÿญ

Computer Science Network Data Structures Distributed Computing
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Optimizing and benchmarking the computation of the permanent of general matrices

: ์˜๊ตฌ๊ฐ’ ๊ณ„์‚ฐ์€ ๋‹ค์–‘ํ•œ ๋ถ„์•ผ์—์„œ ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•˜๋ฉฐ, ํŠนํžˆ ์–‘์ž ์ปดํ“จํŒ…๊ณผ ๊ฐ™์€ ์‹ ํฅ ๊ธฐ์ˆ ์—์„œ๋Š” ๋”์šฑ ์ค‘์š”ํ•ด์ง€๊ณ  ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์ด๋Ÿฌํ•œ ์˜๊ตฌ๊ฐ’ ๊ณ„์‚ฐ์„ ํšจ์œจ์ ์œผ๋กœ ์ˆ˜ํ–‰ํ•˜๊ธฐ ์œ„ํ•œ ์†Œํ”„ํŠธ์›จ์–ด ํŒจํ‚ค์ง€๋ฅผ ๊ฐœ๋ฐœํ•˜๊ณ , ๊ทธ ์„ฑ๋Šฅ์„ ๋ถ„์„ํ•˜์˜€๋‹ค. ์„ธ ๊ฐ€์ง€ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ง€์›ํ•˜๋ฉฐ, ์ž…๋ ฅ ํ–‰๋ ฌ์˜ ํŠน์„ฑ์— ๋”ฐ๋ผ ์ตœ์ ์˜ ์•Œ๊ณ ๋ฆฌ์ฆ˜์œผ๋กœ ์ž๋™ ์ „ํ™˜ํ•˜๋Š” ๊ธฐ๋Šฅ์€ ํŠนํžˆ ์ฃผ๋ชฉํ•  ๋งŒํ•˜๋‹ค. ์ด๋Š” ๋‹ค์–‘ํ•œ ์œ ํ˜•์˜ ํ–‰๋ ฌ์— ๋Œ€ํ•œ ํšจ์œจ์ ์ธ ๊ณ„์‚ฐ ๋ฐฉ๋ฒ•์„ ์ œ๊ณตํ•จ์œผ๋กœ์จ, ์˜๊ตฌ๊ฐ’ ๊ณ„์‚ฐ ๋ถ„์•ผ์—์„œ ์ค‘์š”ํ•œ ๊ธฐ์—ฌ๋ฅผ ํ•˜์˜€๋‹ค๊ณ  ํ•  ์ˆ˜ ์žˆ๋‹ค. ๋˜ํ•œ, ์ง์‚ฌ๊ฐํ˜• ํ–‰๋ ฌ์— ๋Œ€ํ•œ ๊ธ€๋ฆฐ ์•Œ๊ณ ๋ฆฌ์ฆ˜์˜ ํ™•์žฅ์€ ๊ธฐ์กด ์—ฐ๊ตฌ

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Optimizing Freight Rail Electrification: A Framework for Charge Station Selection and Battery Charge/Swap Scheduling

๋ณธ ์—ฐ๊ตฌ๋Š” ๋ฐฐํ„ฐ๋ฆฌ ์ „๊ธฐ ํ™”๋ฌผ ์—ด์ฐจ์˜ ํšจ์œจ์ ์ธ ์šด์˜์„ ์œ„ํ•œ ํฌ๊ด„์ ์ธ ํ”„๋ ˆ์ž„์›Œํฌ๋ฅผ ์ œ๊ณตํ•œ๋‹ค. ์ถฉ์ „ ์ธํ”„๋ผ ์„ค๊ณ„์™€ ์ถฉ์ „ ์ผ์ • ์ˆ˜๋ฆฝ์€ ํƒ„์†Œ ๋ฐฐ์ถœ ์—†๋Š” ์šด์†ก ์‹œ์Šคํ…œ ๊ตฌ์ถ•์— ์žˆ์–ด ํ•ต์‹ฌ ์š”์†Œ์ด๋‹ค. ์ œ์‹œ๋œ ๋ชจ๋ธ์€ ๋‹ค์–‘ํ•œ ์ƒํ™ฉ๊ณผ ์š”๊ตฌ ์‚ฌํ•ญ์„ ๊ณ ๋ คํ•˜์—ฌ ์ตœ์ ์˜ ์†”๋ฃจ์…˜์„ ๋„์ถœํ•œ๋‹ค. ๋ฐฐํ„ฐ๋ฆฌ๋ฅผ ์ถฉ์ „ํ•˜๊ฑฐ๋‚˜ ๊ต์ฒดํ•  ์ˆ˜ ์žˆ๋Š” ์œ ์—ฐ์„ฑ์„ ์ œ๊ณตํ•จ์œผ๋กœ์จ, ์—ด์ฐจ๋Š” ๋” ํšจ์œจ์ ์ด๊ณ  ์ง€์† ๊ฐ€๋Šฅํ•œ ๋ฐฉ์‹์œผ๋กœ ์šด์˜๋  ์ˆ˜ ์žˆ๋‹ค. ๊ฐ ์—ด์ฐจ๊ฐ€ ์—ฌ๋Ÿฌ ๊ฐœ์˜ ๋ฐฐํ„ฐ๋ฆฌ๋ฅผ ์šด๋ฐ˜ํ•  ์ˆ˜ ์žˆ๋„๋ก ํ•จ์œผ๋กœ์จ, ์—ฐ๋ฃŒ ๊ณต๊ธ‰์˜ ์œ ์—ฐ์„ฑ์ด ํ–ฅ์ƒ๋˜๊ณ  ์—ด์ฐจ์˜ ๊ฐ€์šฉ์„ฑ๊ณผ ์‹ ๋ขฐ์„ฑ์ด ๋†’์•„์ง„๋‹ค. ์„ธ ๊ฐ€์ง€ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ๊ฐœ๋ฐœํ•˜์—ฌ ๋Œ€

Framework
Orbits of linear maps and regular languages

Orbits of linear maps and regular languages

์ด ์—ฐ๊ตฌ๋Š” ์„ ํ˜• ๋Œ€์ˆ˜์™€ ํ˜•์‹ ์–ธ์–ด ์ด๋ก ์„ ๊ต์ฐจ์‹œ์ผœ, ๊ธฐ์กด์— ๋ณ„๊ฐœ๋กœ ๋‹ค๋ฃจ์–ด์กŒ๋˜ ๋‘ ๋‚œ์ œ์— ์ƒˆ๋กœ์šด ๊ด€์ ์„ ์ œ๊ณตํ•œ๋‹ค. ์ฒซ ๋ฒˆ์งธ ๋ฌธ์ œ์ธ ์ฑ”๋ฒ„ ์น˜๊ธฐ ๋Š” ์„ ํ˜• ์‚ฌ์ƒ์˜ ๊ถค์ ์ด ๋‹ค๋ฉด์ฒด์™€ ๊ต์ฐจํ•˜๋Š”์ง€๋ฅผ ํŒ๋‹จํ•œ๋‹ค. ๊ถค์ ์€ ฮฆโฟ(x) ( nโˆˆโ„• ) ๋กœ ์ •์˜๋˜๋ฉฐ, ฮฆ์™€ x๊ฐ€ ์œ ๋ฆฌ ์ขŒํ‘œ๋กœ ์ฃผ์–ด์ง€๋ฏ€๋กœ ๊ถค์ ์˜ ๊ฐ ์›์†Œ๋„ ์œ ๋ฆฌ์ˆ˜์ด๋‹ค. ์ด๋•Œ ๋‹ค๋ฉด์ฒด๋Š” ์œ ํ•œ ๊ฐœ์˜ ์„ ํ˜• ๋ถ€๋“ฑ์‹์œผ๋กœ ๊ธฐ์ˆ ๋˜๋ฏ€๋กœ, ๋ฌธ์ œ๋Š” โ€œ๋ฌดํ•œํžˆ ์ƒ์„ฑ๋˜๋Š” ์œ ๋ฆฌ์  ์ง‘ํ•ฉ์ด ์œ ํ•œํ•œ ๋ฐ˜ํ‰๋ฉด(๋˜๋Š” ๊ณ ์ฐจ์› ์‹ค๋ฆฐ๋”)๊ณผ ๊ต์ฐจํ•˜๋Š”๊ฐ€?โ€๋ผ๋Š” ์งˆ๋ฌธ์œผ๋กœ ํ™˜์›๋œ๋‹ค. ์ด์™€ ๊ฐ™์€ ์งˆ๋ฌธ์€ ์„ ํ˜• ์žฌ๊ท€ ์ˆ˜์—ด(LRS) ์˜ ์˜์  ์กด์žฌ ๋ฌธ์ œ,

Computer Science Formal Languages Mathematics
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

Computer Science Network Networking
PACIFIC: a framework for generating benchmarks to check Precise Automatically Checked Instruction Following In Code

PACIFIC: a framework for generating benchmarks to check Precise Automatically Checked Instruction Following In Code

: PACIFIC์€ ์ž๋™์œผ๋กœ ๋ฒค์น˜๋งˆํฌ๋ฅผ ์ƒ์„ฑํ•˜๋Š” ํ”„๋ ˆ์ž„์›Œํฌ๋กœ, LLM์˜ ์ง€์นจ ์ค€์ˆ˜ ๋ฐ ์ฝ”๋“œ ๋“œ๋ผ์ด๋Ÿฐ ๋Šฅ๋ ฅ์„ ํ‰๊ฐ€ํ•ฉ๋‹ˆ๋‹ค. ์ด ํ”„๋ ˆ์ž„์›Œํฌ๋Š” ๋ช…ํ™•ํ•œ ์˜ˆ์ƒ ์ถœ๋ ฅ์„ ๊ฐ€์ง„ ๋ฒค์น˜๋งˆํฌ ๋ณ€ํ˜•์„ ์ƒ์„ฑํ•˜์—ฌ ๊ฐ„๋‹จํ•œ ์ถœ๋ ฅ ๋น„๊ต๋ฅผ ํ†ตํ•ด ํ‰๊ฐ€๋ฅผ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•ฉ๋‹ˆ๋‹ค. ๊ธฐ์กด ์ ‘๊ทผ ๋ฐฉ์‹๊ณผ ๋‹ฌ๋ฆฌ, PACIFIC์€ ๋„๊ตฌ ์‚ฌ์šฉ์ด๋‚˜ ์—์ด์ „ํŠธ์  ํ–‰๋™์— ์˜์กดํ•˜์ง€ ์•Š๊ณ  LLM์˜ ๊ณ ์œ ํ•œ ์ถ”๋ก  ๋Šฅ๋ ฅ์„ ํ‰๊ฐ€ํ•ฉ๋‹ˆ๋‹ค. ๋˜ํ•œ, ์ƒˆ๋กœ์šด ๋ฒค์น˜๋งˆํฌ ๋ณ€ํ˜•์„ ์‰ฝ๊ฒŒ ์ƒ์„ฑํ•˜์—ฌ ํ›ˆ๋ จ ๋ฐ์ดํ„ฐ ์˜ค์—ผ์„ ์™„ํ™”ํ•ฉ๋‹ˆ๋‹ค. ์šฐ๋ฆฌ๋Š” ๋‹ค์–‘ํ•œ ๋‚œ์ด๋„ ์ˆ˜์ค€์˜ ๋ฒค์น˜๋งˆํฌ๋ฅผ ์ƒ์„ฑํ•˜๊ณ  ์—ฌ๋Ÿฌ ์ตœ์ฒจ๋‹จ LLM์„ ํ‰๊ฐ€ํ•จ์œผ๋กœ์จ ํ”„๋ ˆ์ž„์›Œํฌ๋ฅผ

Framework
No Image

PALQA: A Novel Parameterized Position-Aware Lossy Quantum Autoencoder using LSB Control Qubit for Efficient Image Compression

์–‘์ž ์ปดํ“จํŒ…์˜ ๋ฐœ์ „๊ณผ ํ•จ๊ป˜, ์–‘์ž ์ด๋ฏธ์ง€ ์ฒ˜๋ฆฌ ๊ธฐ์ˆ ์€ ๊ณ ์ „์ ์ธ ์ปดํ“จํŒ…์„ ๋Šฅ๊ฐ€ํ•˜๋Š” ์ž ์žฌ๋ ฅ๊ณผ ๋‹ค์–‘ํ•œ ์‘์šฉ ๋ถ„์•ผ๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ํšจ์œจ์ ์ธ ์ด๋ฏธ์ง€ ์••์ถ•์„ ์œ„ํ•œ ์ƒˆ๋กœ์šด ์ ‘๊ทผ๋ฒ•์œผ๋กœ PALQA ํšŒ๋กœ๋ฅผ ์ œ์•ˆํ•œ๋‹ค. PALQA๋Š” ์ตœ์†Œ ์œ ์˜๋ฏธ ๋น„ํŠธ ์ œ์–ด ํ๋น—์„ ์‚ฌ์šฉํ•˜์—ฌ ์ด๋ฏธ์ง€๋ฅผ ์••์ถ•ํ•˜๋ฉฐ, ์ด๋Š” ํ‘œ์ค€ ํ‘œํ˜„ ์ ‘๊ทผ๋ฒ•์„ ์‚ฌ์šฉํ•จ์œผ๋กœ์จ ๊ธฐ์กด ์–‘์ž ์˜คํ† ์ธ์ฝ”๋”์˜ ํ•œ๊ณ„๋ฅผ ๊ทน๋ณตํ•œ๋‹ค. ๋˜ํ•œ, ์œ„์น˜ ์ธ์‹ ๊ธฐ์ˆ ์„ ํ†ตํ•ด ์ƒํƒœ ์—ฐ๊ฒฐ์—์„œ ๋” ๋‚˜์€ ์••์ถ• ๊ธฐํšŒ๋ฅผ ์ œ๊ณตํ•˜์—ฌ ์ด๋ฏธ์ง€ ํ’ˆ์งˆ์„ ํ–ฅ์ƒ์‹œํ‚จ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” PALQA ํšŒ๋กœ์˜ ์„ฑ๋Šฅ์„ JPEG ๋ฐ ๋‹ค๋ฅธ ์–‘์ž ํ‘œํ˜„ ๊ธฐ๋ฐ˜

No Image

PANER: A Paraphrase-Augmented Framework for Low-Resource Named Entity Recognition

์ €์ž์› Named Entity Recognition(NER)์€ ๋ ˆ์ด๋ธ” ํš๋“ ๋น„์šฉ์ด ๋†’๊ธฐ ๋•Œ๋ฌธ์— ์–ด๋ ค์›€์„ ๊ฒช์Šต๋‹ˆ๋‹ค. ์ด๋Š” ํŠนํžˆ ๋„๋ฉ”์ธ ํŠน์ • ์—”ํ‹ฐํ‹ฐ๋ฅผ ์‹๋ณ„ํ•ด์•ผ ํ•˜๋Š” ๊ฒฝ์šฐ์— ํ•ด๋‹น๋ฉ๋‹ˆ๋‹ค. ์ œ๋กœ์ƒท ๋ฐ ์ง€์นจ ํŠœ๋‹ ์ ‘๊ทผ ๋ฐฉ์‹์€ ์ด๋Ÿฌํ•œ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ์ œ์•ˆ๋˜์—ˆ์ง€๋งŒ, ์ œํ•œ๋œ ๋ฐ์ดํ„ฐ์™€ ์ปดํ“จํŒ… ํŒŒ์›Œ๋ฅผ ๊ฐ€์ง„ ๊ทธ๋ฃน์—๋Š” ์—ฌ์ „ํžˆ ๋„์ „ ๊ณผ์ œ๋กœ ๋‚จ์•„ ์žˆ์Šต๋‹ˆ๋‹ค. PANER๋Š” ์ด๋Ÿฌํ•œ ํ•œ๊ณ„๋ฅผ ๊ทน๋ณตํ•˜๊ธฐ ์œ„ํ•œ ๊ฐ€๋ฒผ์šด ์†Œ์ˆ˜์˜ NER ํ”„๋ ˆ์ž„์›Œํฌ์ž…๋‹ˆ๋‹ค. ์ด ํ”„๋ ˆ์ž„์›Œํฌ์˜ ํ•ต์‹ฌ ํ˜์‹ ์€ ๋‹ค์Œ๊ณผ ๊ฐ™์Šต๋‹ˆ๋‹ค: ์ฒซ์งธ, ์ด์ „ IT ์ ‘๊ทผ ๋ฐฉ์‹์—์„œ ์œ ๋ž˜๋œ ์›๋ฆฌ๋ฅผ ๊ฒฐํ•ฉํ•œ ์ƒˆ๋กœ์šด ์ง€์นจ ํŠœ๋‹

Framework
Parallel convolution processing using an integrated photonic tensor core

Parallel convolution processing using an integrated photonic tensor core

๋ณธ ๋…ผ๋ฌธ์€ ํ˜„์žฌ ๋ฐ์ดํ„ฐ ํญ์ฆ๊ณผ AI ์—ฐ์‚ฐ ์š”๊ตฌ ๊ธ‰์ฆ์ด๋ผ๋Š” ๋‘ ๊ฐ€์ง€ ์‚ฌํšŒยท๊ธฐ์ˆ ์  ์••๋ ฅ์— ๋Œ€์‘ํ•˜๊ธฐ ์œ„ํ•ด, ๊ด‘โ€‘์ธโ€‘๋ฉ”๋ชจ๋ฆฌ(Photonic Inโ€‘Memory) ๊ธฐ๋ฐ˜์˜ ํ…์„œ ์ฝ”์–ด ๋ผ๋Š” ์ƒˆ๋กœ์šด ํ•˜๋“œ์›จ์–ด ํŒจ๋Ÿฌ๋‹ค์ž„์„ ์ œ์‹œํ•œ๋‹ค๋Š” ์ ์—์„œ ์˜๋ฏธ๊ฐ€ ํฌ๋‹ค. ๊ธฐ์กด ์ „์ž์‹ ๊ฐ€์†๊ธฐ๋Š” ์ „๊ธฐ ์ธํ„ฐ์ปค๋„ฅํŠธ์˜ ์—๋„ˆ์ง€โ€‘๋Œ€โ€‘๋Œ€์—ญํญ ํŠธ๋ ˆ์ด๋“œ์˜คํ”„์— ์–ฝ๋งค์—ฌ ํ™•์žฅ์„ฑ์— ํ•œ๊ณ„๋ฅผ ๋ณด์ด์ง€๋งŒ, ํฌํ† ๋‹‰์Šค๋Š” ํŒŒ์žฅ๋ถ„ํ• ๋‹ค์ค‘ํ™”(WDM) ์™€ ๋‹ค์ฑ„๋„ ๊ด‘์›(๊ด‘์ฃผํŒŒ์ˆ˜ ์ฝค) ์„ ํ™œ์šฉํ•ด ๋ฌผ๋ฆฌ์  ํ•œ ๊ฐœ ์ฝ”์–ด ์•ˆ์—์„œ ์ˆ˜์ฒœ ๊ฐœ์˜ ํŒŒ์žฅ์„ ๋™์‹œ์— ์ฒ˜๋ฆฌํ•  ์ˆ˜ ์žˆ๋‹ค. ์ด๋Š” โ€˜์ฃผํŒŒ์ˆ˜ ๊ณต๊ฐ„โ€™์ด๋ผ๋Š” ์ถ”๊ฐ€ ์ฐจ์›์„ ๋„์ž…ํ•จ์œผ๋กœ์จ,

Physics Computer Science Emerging Technologies Condensed Matter
Parameter Calibration in Crowd Simulation Models using Approximate   Bayesian Computation

Parameter Calibration in Crowd Simulation Models using Approximate Bayesian Computation

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ํ•„์š”์„ฑ ๋ณดํ–‰์ž ๊ตฐ์ง‘ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์€ ๋„์‹œ ์„ค๊ณ„, ๋Œ€๊ทœ๋ชจ ํ–‰์‚ฌ ์•ˆ์ „, ๋น„์ƒ ๋Œ€ํ”ผ ๊ณ„ํš ๋“ฑ ๋‹ค์–‘ํ•œ ๋ถ„์•ผ์—์„œ ํ•„์ˆ˜์ ์ธ ์˜ˆ์ธก ์ˆ˜๋‹จ์ด๋‹ค. ์ด๋Ÿฌํ•œ ๋ชจ๋ธ์€ ๋ณดํ–‰์ž์˜ ์„ ํ˜ธ ์†๋„, ์ƒํ˜ธ์ž‘์šฉ ๊ฐ•๋„ ๋“ฑ ๋ฌผ๋ฆฌยท์‚ฌํšŒ์  ํŒŒ๋ผ๋ฏธํ„ฐ์— ์˜ํ•ด ๋™์ž‘์ด ๊ฒฐ์ •๋˜๋ฉฐ, ํŒŒ๋ผ๋ฏธํ„ฐ๊ฐ€ ํ˜„์‹ค๊ณผ ์–ผ๋งˆ๋‚˜ ์ผ์น˜ํ•˜๋А๋ƒ๊ฐ€ ๋ชจ๋ธ์˜ ์‹ ๋ขฐ์„ฑ์„ ์ขŒ์šฐํ•œ๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ์—์„œ๋Š” ๋ฏธ์‹œ์  ๊ถค์  ๋ฐ์ดํ„ฐ๋‚˜ ๊ฑฐ์‹œ์  ํ๋ฆ„ ํ†ต๊ณ„๋Ÿ‰์„ ์ด์šฉํ•ด ๋ชฉ์ ํ•จ์ˆ˜๋ฅผ ์ •์˜ํ•˜๊ณ , ์ตœ์ ํ™” ์•Œ๊ณ ๋ฆฌ์ฆ˜์œผ๋กœ ํŒŒ๋ผ๋ฏธํ„ฐ๋ฅผ ์ถ”์ •ํ•ด ์™”๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ด ์ ‘๊ทผ๋ฒ•์€ (i) ํŒŒ๋ผ๋ฏธํ„ฐ ์ถ”์ •๊ฐ’์— ๋Œ€ํ•œ ๋ถˆํ™•์‹ค์„ฑ ์ •๋ณด๋ฅผ ์ œ๊ณตํ•˜์ง€ ๋ชปํ•˜๊ณ , (ii) ๋ชจ

Applications Multiagent Systems Statistics Model Computer Science
Parts-of-Speech Tagger Errors Do Not Necessarily Degrade Accuracy in   Extracting Information from Biomedical Text

Parts-of-Speech Tagger Errors Do Not Necessarily Degrade Accuracy in Extracting Information from Biomedical Text

: PubMed์˜ ๋ฐฉ๋Œ€ํ•œ ๋…ผ๋ฌธ ์ˆ˜ ์ฆ๊ฐ€๋กœ ์ธํ•ด ์ƒ์‚ฐ์ ์ธ ๋ฌธํ—Œ ํ‰๊ฐ€๋ฅผ ์œ ์ง€ํ•˜๋Š” ๊ฒƒ์ด ์–ด๋ ค์›Œ์ง€๊ณ  ์žˆ๋‹ค. ์ •๋ณด ์ถ”์ถœ(IE)์€ ์ƒ๋ฌผํ•™์  ํ…์ŠคํŠธ ๋ถ„์„์— ์‚ฌ์šฉ๋˜๋ฉฐ, ์—”ํ‹ฐํ‹ฐ ์ƒํ˜ธ์ž‘์šฉ๊ณผ ๊ฐ™์€ ๋ช…์ œ๋ฅผ ๋„์ถœํ•œ๋‹ค. ๋‹ค์–‘ํ•œ IE ๋„๊ตฌ๋“ค์ด ๊ฐœ๋ฐœ๋˜์–ด ์™”์œผ๋ฉฐ, ๊ทธ์ค‘ Muscorian์€ ์ผ๋ฐ˜ POS ํƒœ๊ฑฐ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ์˜๋ฃŒ ๋ถ„์•ผ ํŠนํ™” ๋„๊ตฌ์™€ ์œ ์‚ฌํ•œ ์„ฑ๋Šฅ์„ ๋ณด์˜€๋‹ค. ์ด๋Š” ์˜ˆ์ƒ์น˜ ๋ชปํ•œ ๊ฒฐ๊ณผ๋กœ, ์ผ๋ฐ˜์ ์œผ๋กœ ํ’ˆ์‚ฌ ํƒœ๊น… ์˜ค๋ฅ˜๋Š” ์ „์ฒด ๊ณผ์ •์— ๋ถ€์ •์ ์ธ ์˜ํ–ฅ์„ ๋ฏธ์นœ๋‹ค๊ณ  ์•Œ๋ ค์ ธ ์žˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” MontyTagger์™€ MedPost์˜ ๋น„๊ต๋ฅผ ํ†ตํ•ด POS ํƒœ๊น… ์ •ํ™•๋„๊ฐ€ ์ •๋ณด ์ถ”

Computer Science Information Retrieval NLP
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PaTaRM: Bridging Pairwise and Pointwise Signals via Preference-Aware Task-Adaptive Reward Modeling

PaTaRM์€ ์ธ๊ฐ„ ํ”ผ๋“œ๋ฐฑ์— ๊ธฐ๋ฐ˜ํ•œ ๊ฐ•ํ™” ํ•™์Šต(RLHF)์˜ ํ•ต์‹ฌ์ธ ๋ณด์ƒ ๋ชจ๋ธ๋ง์„ ๊ฐœ์„ ํ•˜๊ธฐ ์œ„ํ•œ ์ ‘๊ทผ๋ฒ•์ž…๋‹ˆ๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ์ƒ์„ฑํ˜• ๋ณด์ƒ ๋ชจ๋ธ(GRMs)๊ณผ ์ „ํ†ต์ ์ธ ์Šค์นผ๋ผ RMs ์‚ฌ์ด์˜ trade off๋ฅผ ํ•ด๊ฒฐํ•˜๊ณ ์ž ํ•ฉ๋‹ˆ๋‹ค. ์Œ๊ฐ„ ๋ฐฉ๋ฒ•์€ ํ›ˆ๋ จ๊ณผ ์ถ”๋ก  ์‚ฌ์ด์˜ ๋ถˆ์ผ์น˜๋ผ๋Š” ๋ฌธ์ œ๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ์œผ๋ฉฐ, ์ ๊ฐ„ ๋ฐฉ๋ฒ•์€ ์ ˆ๋Œ€์  ์ฃผ์„์„ ์œ„ํ•œ ๋น„์šฉ์ด ๋งŽ์ด ๋“œ๋Š” ์ž‘์—…์ด ํ•„์š”ํ•ฉ๋‹ˆ๋‹ค. PaTaRM์€ ์ด๋Ÿฌํ•œ ๋‘ ๊ฐ€์ง€ ์ ‘๊ทผ๋ฒ•์˜ ์žฅ์ ์„ ๊ฒฐํ•ฉํ•˜์—ฌ ์ƒˆ๋กœ์šด ์„ ํ˜ธ๋„ ์ธ์‹ ๋ณด์ƒ(PAR) ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ์ œ์•ˆํ•ฉ๋‹ˆ๋‹ค. ์ด ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ํ†ตํ•ด ์Œ๊ฐ„ ๋ฐ์ดํ„ฐ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ์ ๊ฐ„ ํ›ˆ๋ จ์„ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•จ์œผ

Model
Perturbed Copula: Introducing the skew effect in the co-dependence

Perturbed Copula: Introducing the skew effect in the co-dependence

: ๊ต๋ž€๋œ ์ฝ”ํ”Œ๋ผ๋Š” ๊ธฐ์กด ๊ฐ€์šฐ์‹œ์•ˆ ์ฝ”ํ”Œ๋ผ์˜ ํ•œ๊ณ„๋ฅผ ๊ทน๋ณตํ•˜๊ธฐ ์œ„ํ•œ ํ˜์‹ ์ ์ธ ์ ‘๊ทผ๋ฒ•์ž…๋‹ˆ๋‹ค. ๊ฐ€์šฐ์‹œ์•ˆ ์ฝ”ํ”Œ๋ผ๋Š” ์‚ฐ์—…๊ณ„์—์„œ ๋„๋ฆฌ ์‚ฌ์šฉ๋˜์–ด ์™”์ง€๋งŒ, ๊ธฐ์ดˆ ์ž์‚ฐ์˜ ๋ถ„ํฌ๊ฐ€ ์™œ๊ณก๋˜๊ฑฐ๋‚˜ ๊ทน๋‹จ์ ์ธ ์‚ฌ๊ฑด์ด ๋ฐœ์ƒํ•  ์ˆ˜ ์žˆ๋Š” ์ƒํ™ฉ์—์„œ๋Š” ์ ํ•ฉํ•˜์ง€ ์•Š์„ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ํ•œ๊ณ„์ ์„ ๋ณด์™„ํ•˜๊ธฐ ์œ„ํ•ด ๊ต๋ž€๋œ ์ฝ”ํ”Œ๋ผ ๋ชจ๋ธ์ด ๋“ฑ์žฅํ•œ ๊ฒƒ์ž…๋‹ˆ๋‹ค. ๊ต๋ž€๋œ ๊ฐ€์šฐ์‹œ์•ˆ ์ฝ”ํ”Œ๋ผ๋Š” ๋‘ ๋ฌด์ž‘์œ„ ๋ณ€์ˆ˜์˜ ๊ณต์˜์กด์„ฑ์— ์™œ๊ณก์„ ๋„์ž…ํ•˜์—ฌ, ์ƒ๊ด€๊ด€๊ณ„ ๊ตฌ์กฐ๋ฅผ ๋”์šฑ ์ •ํ™•ํ•˜๊ฒŒ ๋ฐ˜์˜ํ•ฉ๋‹ˆ๋‹ค. ์ด ๋ชจ๋ธ์€ ๊ณตํ†ต์ ์ธ ํ™•๋ฅ  ๋ณ€๋™์„ฑ ์š”์ธ์ด ๋น ๋ฅด๊ฒŒ ํ‰๊ท ์œผ๋กœ ํšŒ๊ท€ํ•œ๋‹ค๋Š” ๊ฐ€์ • ํ•˜์— ๊ฐœ๋ฐœ๋˜์—ˆ์Šต๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๊ฐ€์ •์€ ๊ธฐ์ดˆ

Quantitative Finance
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Physically consistent and uncertainty-aware learning of spatiotemporal dynamics

์ด ๋…ผ๋ฌธ์—์„œ๋Š” ๋ฌผ๋ฆฌ์  ๋ฒ•์น™๊ณผ ๋ถˆํ™•์‹ค์„ฑ ์ธ์‹์„ ๊ณ ๋ คํ•˜์—ฌ ๊ณต๊ฐ„ ์‹œ๊ฐ„ ์—ญํ•™์˜ ์žฅ๊ธฐ ์˜ˆ์ธก ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•œ ์ƒˆ๋กœ์šด ๋ฐฉ๋ฒ•์„ ์ œ์•ˆํ•ฉ๋‹ˆ๋‹ค. PCNO๋Š” ๋ฌผ๋ฆฌ์  ์ œ์•ฝ์„ ๊ฐ•์ œํ•˜๋Š” ํ˜์‹ ์ ์ธ ๋ฐฉ๋ฒ•์œผ๋กœ์„œ, ๋Œ€๋ฆฌ ๋ชจ๋ธ์˜ ์ถœ๋ ฅ์„ ๋ฌผ๋ฆฌ ๋ฒ•์น™์„ ๋งŒ์กฑํ•˜๋Š” ํ•จ์ˆ˜ ๊ณต๊ฐ„์œผ๋กœ ํˆฌ์˜ํ•ฉ๋‹ˆ๋‹ค. ์ด๋Š” ๊ธฐ์กด ๋จธ์‹ ๋Ÿฌ๋‹ ๋ฐฉ๋ฒ•์ด ๊ฐ„๊ณผํ–ˆ๋˜ ๋ฌผ๋ฆฌ์  ์ผ๊ด€์„ฑ์„ ๋ณด์žฅํ•ฉ๋‹ˆ๋‹ค. ๋˜ํ•œ, ํ‘ธ๋ฆฌ์— ๊ณต๊ฐ„์—์„œ ํšจ์œจ์ ์œผ๋กœ ๊ณ„์‚ฐ๋˜๋Š” ๋ฌผ๋ฆฌ์ ์œผ๋กœ ์ผ๊ด€๋œ ํˆฌ์˜์ธต์€ ์งˆ๋Ÿ‰๊ณผ ์šด๋™๋Ÿ‰ ๋ณด์กด์„ ์œ ์ง€ํ•ฉ๋‹ˆ๋‹ค. DiffPCNO๋Š” PCNO์˜ ์˜ˆ์ธก์— ๊ธฐ๋ฐ˜ํ•˜์—ฌ ๋ถˆํ™•์‹ค์„ฑ์„ ์ •๋Ÿ‰ํ™”ํ•˜๊ณ  ์™„ํ™”ํ•˜๋Š” ๋ฐ ์ดˆ์ ์„ ๋งž์ถฅ๋‹ˆ๋‹ค. ํ™•์‚ฐ ๋ชจ๋ธ์„ ํ™œ์šฉํ•˜

Learning
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Physics-Aware Human-Object Rendering from Sparse Views via 3D Gaussian Splatting

HOGS๋Š” 3D ๊ฐ€์šฐ์‹œ์•ˆ ์Šคํ”Œ๋ž˜ํ„ฐ๋ง ๊ธฐ์ˆ ์„ ํ™œ์šฉํ•˜์—ฌ ํฌ์†Œํ•œ ๋ทฐ๋กœ๋ถ€ํ„ฐ ์ธ๊ฐ„๊ณผ ๋ฌผ์ฒด์˜ ์ƒํ˜ธ์ž‘์šฉ์„ ๋ Œ๋”๋งํ•˜๋Š” ํšจ์œจ์ ์ธ ๋ฐฉ๋ฒ•์„ ์ œ๊ณตํ•œ๋‹ค. ์ด ์ ‘๊ทผ๋ฒ•์€ ๋ฌผ๋ฆฌ์ ์œผ๋กœ ํƒ€๋‹นํ•œ ๊ฒฐ๊ณผ๋ฅผ ๋ณด์žฅํ•˜๊ธฐ ์œ„ํ•ด ์ž์„ธ ์ถ”์ • ๋ฐ ์ ‘์ด‰ ์˜์—ญ ์˜ˆ์ธก ๋ชจ๋“ˆ์„ ํ†ตํ•ฉํ•œ๋‹ค. ์‹คํ—˜ ๊ฒฐ๊ณผ, HOGS๋Š” ์‹œ๊ฐ์  ์ถฉ์‹ค๋„ ๋ฐ ๋ฌผ๋ฆฌ์  ์ •ํ™•์„ฑ ์ธก๋ฉด์—์„œ ๊ธฐ์กด ๋ฐฉ๋ฒ•๋ณด๋‹ค ์šฐ์ˆ˜ํ•œ ์„ฑ๋Šฅ์„ ๋ณด์ž„์„ ๋ณด์—ฌ์ค€๋‹ค. ๋˜ํ•œ ์† ์‚ฌ๋ฌผ ๊ทธ๋ฆฝ๊ณผ ๊ฐ™์€ ๋‹ค๋ฅธ ์ƒํ˜ธ์ž‘์šฉ ์ž‘์—…์œผ๋กœ์˜ ํ™•์žฅ ๊ฐ€๋Šฅ์„ฑ์„ ์ œ์‹œํ•จ์œผ๋กœ์จ, ์ด ํ”„๋ ˆ์ž„์›Œํฌ์˜ ์œ ์—ฐ์„ฑ๊ณผ ๋ฒ”์šฉ์„ฑ์„ ์ž…์ฆํ•œ๋‹ค.

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PhysWorld: From Real Videos to World Models of Deformable Objects via Physics-Aware Demonstration Synthesis

: PhysWorld ํ”„๋ ˆ์ž„์›Œํฌ๋Š” ์‹ค์ œ ์„ธ๊ณ„ ๋ฐ์ดํ„ฐ์˜ ๋ถ€์กฑ์ด๋ผ๋Š” ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ธฐ๋ฐ˜์˜ ์ ‘๊ทผ๋ฒ•์„ ์ทจํ•œ๋‹ค. ์ด๋Š” ๋ฌผ๋ฆฌ์ ์œผ๋กœ ์ผ๊ด€๋œ ๋””์ง€ํ„ธ ํŠธ์œˆ์„ ์ƒ์„ฑํ•˜๊ณ , ๋‹ค์–‘ํ•œ ์šด๋™ ํŒจํ„ด์„ ํ•ฉ์„ฑํ•˜์—ฌ ๋ฐ๋ชจ๋ฅผ ์ƒ์„ฑํ•˜๋Š” ๊ณผ์ •์„ ํฌํ•จํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ์ ‘๊ทผ๋ฒ•์€ ๊ฐ€์†Œ์„ฑ ๋ฌผ์ฒด๋“ค์˜ ์—ญํ•™์— ๋Œ€ํ•œ ์ดํ•ด๋ฅผ ํ–ฅ์ƒ์‹œํ‚ค๊ณ , ํšจ์œจ์ ์ธ ์„ธ๊ณ„ ๋ชจ๋ธ ํ•™์Šต์„ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•œ๋‹ค. ๋˜ํ•œ, PhysWorld๋Š” ์‹ค์ œ ์˜์ƒ์„ ์‚ฌ์šฉํ•˜์—ฌ ๋ฌผ๋ฆฌ์  ํŠน์„ฑ์„ ์กฐ์ •ํ•  ์ˆ˜ ์žˆ์œผ๋ฏ€๋กœ, ๋”์šฑ ์ •๊ตํ•˜๊ณ  ์ •ํ™•ํ•œ ์˜ˆ์ธก์ด ๊ฐ€๋Šฅํ•˜๋‹ค. ์ด ํ”„๋ ˆ์ž„์›Œํฌ์˜ ํ•ต์‹ฌ์€ ์‹œ๋ฎฌ๋ ˆ์ด์…˜๊ณผ ์‹ค์ œ ๋ฐ์ดํ„ฐ์˜ ๊ฒฐํ•ฉ์ด๋ฉฐ, ์ด๋ฅผ ํ†ตํ•ด ๋กœ

Model
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PICBench: Benchmarking LLMs for Photonic Integrated Circuits Design

: PICBench๋Š” ๊ด‘ํ•™ ์ง‘์  ํšŒ๋กœ ์„ค๊ณ„์— ๋Œ€ํ•œ LLM์˜ ์„ฑ๋Šฅ์„ ์ธก์ •ํ•˜๊ณ  ํ‰๊ฐ€ํ•˜๊ธฐ ์œ„ํ•œ ํฌ๊ด„์ ์ธ ํ”„๋ ˆ์ž„์›Œํฌ์ž…๋‹ˆ๋‹ค. ์ด ๋…ผ๋ฌธ์€ PIC ์„ค๊ณ„์˜ ์ž๋™ํ™”๋ฅผ ์œ„ํ•œ LLM์˜ ์ž ์žฌ๋ ฅ์„ ํƒ๊ตฌํ•˜๋ฉฐ, ํŠนํžˆ ๋ณต์žกํ•œ ์ฝ”๋“œ์™€ ๊ด€๋ จ๋œ ๊ณผ์ œ๋ฅผ ํ•ด๊ฒฐํ•ฉ๋‹ˆ๋‹ค. ์ˆ˜์‹ญ ๊ฐœ์˜ ๋‹ค์–‘ํ•œ PIC ์„ค๊ณ„ ๋ฌธ์ œ๊ฐ€ ํฌํ•จ๋œ ๋ฒค์น˜๋งˆํฌ๋Š” LLM์ด ์ง๋ฉดํ•˜๋Š” ๋„์ „๊ณผ ๊ธฐํšŒ๋ฅผ ๋ช…ํ™•ํ•˜๊ฒŒ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค. PICBench๋Š” ์ƒ์„ฑ๋œ PIC ์„ค๊ณ„์˜ ๊ตฌ๋ฌธ ๋ฐ ๊ธฐ๋Šฅ์„ ํ‰๊ฐ€ํ•˜๊ธฐ ์œ„ํ•ด ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ์ถœ๋ ฅ๊ณผ ์ „๋ฌธ๊ฐ€ ์†”๋ฃจ์…˜์„ ๋น„๊ตํ•˜๋Š” ์ž๋™ํ™” ํ”„๋กœ์„ธ์Šค๋ฅผ ์‚ฌ์šฉํ•ฉ๋‹ˆ๋‹ค. ์ด ์ ‘๊ทผ ๋ฐฉ์‹์€ LLM์˜ ์„ฑ๋Šฅ์„ ๊ฐ๊ด€์ ์œผ๋กœ ์ธก์ •ํ•˜๊ณ ,

Pinpointing Cosmic Ray Propagation With The AMS-02 Experiment

Pinpointing Cosmic Ray Propagation With The AMS-02 Experiment

๋งค๋ ฅ์ ์ธ ํ•œ๊ธ€ ์ œ๋ชฉ: [์šฐ์ฃผ์„  ์ „ํŒŒ๋ฅผ ๋ฐํžˆ๋‹ค: AMS 02 ์‹คํ—˜์˜ ์ž ์žฌ๋ ฅ] ์ดˆ๋ก ์ „์ฒด ๋ฒˆ์—ญ ๋ฐ ์ •๋ฆฌ: ์ด ๋…ผ๋ฌธ์€ ์•ŒํŒŒ ์ž๊ธฐ ๋ถ„๊ด‘๊ธฐ(AMS 02) ์‹คํ—˜์„ ํ†ตํ•ด ์šฐ์ฃผ์„ ์˜ ๊ธฐ์›๊ณผ ์ „ํŒŒ์— ๋Œ€ํ•œ ํ†ต์ฐฐ๋ ฅ์„ ์–ป๋Š” ๋ฐ ์ดˆ์ ์„ ๋งž์ถ”๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. AMS 02๋Š” ๊ตญ์ œ ์šฐ์ฃผ ์ •๊ฑฐ์žฅ์— ํƒ‘์žฌ๋  ์˜ˆ์ •์œผ๋กœ, ๊ธฐ๊ฐ€์ „์ž๋ณผํŠธ(GeV) ํ…Œ๋ผ์ „์ž๋ณผํŠธ(TeV) ๋ฒ”์œ„์˜ ์šฐ์ฃผ์„  ๊ตฌ์„ฑ๊ณผ ์ŠคํŽ™ํŠธ๋Ÿผ์„ ์ธก์ •ํ•  ์ˆ˜ ์žˆ๋Š” ๋›ฐ์–ด๋‚œ ๋Šฅ๋ ฅ์„ ๊ฐ–์ถ”๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์ด ๋…ผ๋ฌธ์—์„œ๋Š” AMS 02์˜ ์˜ˆ์ƒ ๋ฐ์ดํ„ฐ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ์šฐ๋ฆฌ ์€ํ•˜ ๋‚ด์—์„œ์˜ ์šฐ์ฃผ์„  ์ „ํŒŒ ๋ชจ๋ธ์„ ์ œํ•œํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ํƒ๊ตฌํ•ฉ๋‹ˆ๋‹ค. ์šฐ์ฃผ์„  ์ŠคํŽ™ํŠธ

Astrophysics
Planning Fallacy or Hiding Hand: Which Is the Better Explanation?

Planning Fallacy or Hiding Hand: Which Is the Better Explanation?

๋ณธ ๋…ผ๋ฌธ์€ ๋‘ ๊ฐ€์ง€ ์œ ๋ช…ํ•œ ํ–‰๋™๊ฒฝ์ œํ•™ยท๊ฒฝ์ œํ•™ ์ด๋ก ์„ ์ง์ ‘์ ์ธ ์‹ค์ฆ ๊ฒ€์ฆ์„ ํ†ตํ•ด ๋น„๊ตํ•จ์œผ๋กœ์จ, ํ•™์ˆ ์ ยท์ •์ฑ…์  ํ•จ์˜๋ฅผ ๋™์‹œ์— ๋„์ถœํ•œ๋‹ค๋Š” ์ ์—์„œ ์˜์˜๊ฐ€ ํฌ๋‹ค. ์ฒซ์งธ, ์ €์ž๋Š” โ€œ์ˆจ์€ ์†โ€์ด ์‹ค์ œ๋กœ ์กด์žฌํ•œ๋‹ค๋Š” ๋น„ํŒ๊ฐ€๋“ค์˜ ์ง€์ ์„ ์ธ์ •ํ•˜๊ณ , ์ด๋ฅผ ๊ฒ€์ฆํ•˜๊ธฐ ์œ„ํ•ด ๊ฐ€๋Šฅํ•œ ๊ฐ€์žฅ ๋ฐฉ๋Œ€ํ•œ ๋ฐ์ดํ„ฐ์…‹์„ ํ™œ์šฉํ•˜์˜€๋‹ค. 20 % ์ •๋„์˜ ํ”„๋กœ์ ํŠธ์—์„œ ๋น„์šฉ ์ดˆ๊ณผ๋ณด๋‹ค ์ด์ต ์ดˆ๊ณผ๊ฐ€ ๋” ํฌ๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๋‹ค๋Š” ๊ฒฐ๊ณผ๋Š” ํžˆ๋ฅด์Šˆ๋งŒ์ด ์ œ์‹œํ•œ โ€˜์˜ˆ์ƒ์น˜ ๋ชปํ•œ ์ด์ต์ด ๋น„์šฉ ์ดˆ๊ณผ๋ฅผ ์ƒ์‡„ํ•œ๋‹คโ€™๋Š” ๋ฉ”์ปค๋‹ˆ์ฆ˜์ด ํ˜„์‹ค์—์„œ๋„ ๋“œ๋ฌผ๊ฒŒ๋Š” ์ž‘๋™ํ•œ๋‹ค๋Š” ๊ฒƒ์„ ์‹œ์‚ฌํ•œ๋‹ค. ์ด๋Š” ํžˆ๋ฅด์Šˆ๋งŒ์˜ ์ด๋ก ์ด ์™„์ „ํžˆ ๋ฌด์‹œ๋  ์ˆ˜

Quantitative Finance
Point systems in Games for Health: A bibliometric scoping study

Point systems in Games for Health: A bibliometric scoping study

๋ณธ ์—ฐ๊ตฌ๋Š” ๊ฑด๊ฐ• ๊ฒŒ์ž„ ๋ถ„์•ผ์—์„œ ํฌ์ธํŠธยท์ ์ˆ˜ ์‹œ์Šคํ…œ์ด ์–ด๋–ป๊ฒŒ ๋…ผ์˜๋˜๊ณ  ์žˆ๋Š”์ง€๋ฅผ ์ตœ์ดˆ๋กœ ์ฒด๊ณ„์ ์œผ๋กœ ์กฐ๋ช…ํ•œ ์„œ์ง€๊ณ„๋Ÿ‰ ์Šค์ฝ”ํ•‘ ์—ฐ๊ตฌ๋ผ ํ•  ์ˆ˜ ์žˆ๋‹ค. ๋จผ์ € ๊ฒ€์ƒ‰ ์ „๋žต์ด ๋งค์šฐ ๊ตฌ์ฒด์ ์ด๋‹ค. โ€˜game โ€™, โ€˜healthโ€™, โ€˜point OR scoreโ€™, โ€˜system โ€™์ด๋ผ๋Š” ๋„ค ๊ฐ€์ง€ ํ•ต์‹ฌ ํ‚ค์›Œ๋“œ๋ฅผ ์กฐํ•ฉํ•จ์œผ๋กœ์จ ํฌ์ธํŠธ ๋ฉ”์ปค๋‹ˆ์ฆ˜์ด ํฌํ•จ๋œ ๊ฑด๊ฐ• ๊ฒŒ์ž„ ๋…ผ๋ฌธ์„ ์ตœ๋Œ€ํ•œ ํฌ๊ด„์ ์œผ๋กœ ํฌ์ฐฉํ•˜์˜€๋‹ค. ์˜์–ด ๋…ผ๋ฌธยท๋ฆฌ๋ทฐยทํ•™์ˆ ๋Œ€ํšŒ ๋…ผ๋ฌธ๋งŒ์„ ๋Œ€์ƒ์œผ๋กœ ํ•œ ์ ์€ ์—ฐ๊ตฌ ๋ฒ”์œ„์˜ ์ผ๊ด€์„ฑ์„ ํ™•๋ณดํ•˜๋ฉด์„œ๋„, ๋น„์˜์–ด๊ถŒ ์—ฐ๊ตฌ๊ฐ€ ๋ˆ„๋ฝ๋  ๊ฐ€๋Šฅ์„ฑ์„ ๋‚จ๊ธด๋‹ค. Scopus๋ฅผ ๋ฐ์ดํ„ฐ๋ฒ ์ด์Šค๋กœ ์„ ํƒํ•œ

Computer Science System Computers and Society Digital Libraries
Polarizabilities of Intermediate Sized Lithium Clusters From   Density-Functional Theory

Polarizabilities of Intermediate Sized Lithium Clusters From Density-Functional Theory

์ด ๋…ผ๋ฌธ์€ ๋ฆฌํŠฌ ๊ธˆ์† ํด๋Ÿฌ์Šคํ„ฐ๋ผ๋Š” ๋น„๊ต์  ๋‹จ์ˆœํ•œ ์•Œ์นผ๋ฆฌ ๊ธˆ์† ์‹œ์Šคํ…œ์„ ์ด์šฉํ•ด ์ „์ž ๋น„๊ตญ์†Œํ™”์™€ ๊ตญ์†Œํ™” ์‚ฌ์ด์˜ ์ „์ด ํ˜„์ƒ์„ ์ •๋Ÿ‰์ ์œผ๋กœ ํƒ๊ตฌํ•œ๋‹ค๋Š” ์ ์—์„œ ์˜๋ฏธ๊ฐ€ ํฌ๋‹ค. ์•Œ์นผ๋ฆฌ ๊ธˆ์† ์›์ž๋Š” ์™ธ๊ณฝ ์ „์ž๊ฐ€ ๋งค์šฐ ํผ์ ธ ์žˆ์–ด ์ž์œ  ์ „์ž ๊ฐ€์Šค ๋ชจ๋ธ์— ๊ทผ์ ‘ํ•œ๋‹ค๋Š” ์ „์ œ ํ•˜์—, ์ €์ž๋“ค์€ ์ด๋Ÿฌํ•œ ํŠน์„ฑ์„ DFT ๊ณ„์‚ฐ์— ์ง์ ‘ ์ ์šฉํ•จ์œผ๋กœ์จ ๊ธฐ์กด ์ž์œ  ์ „์ž ๊ฐ€์Šค ๊ธฐ๋ฐ˜ ๊ตํ™˜โ€‘์ƒ๊ด€ ๊ทผ์‚ฌ์˜ ํƒ€๋‹น์„ฑ์„ ๊ฒ€์ฆํ•œ๋‹ค. ํŠนํžˆ GGAโ€‘DFT์™€ ๋Œ€ํ˜• ๊ฐ€์šฐ์‹œ์•ˆ ๊ธฐ์ €ํ•จ์ˆ˜๋ฅผ ๊ฒฐํ•ฉํ•œ โ€˜NRLMOLโ€™ ๊ตฌํ˜„์€ ์ „์ž ๊ตฌ๋ฆ„์˜ ๋ฏธ์„ธํ•œ ๋น„๋Œ€์นญ์„ฑ์„ ํฌ์ฐฉํ•  ์ˆ˜ ์žˆ์–ด, ์ž‘์€ ํด๋Ÿฌ์Šคํ„ฐ(2 ~ 5์›์ž)๋ถ€ํ„ฐ

Condensed Matter Physics
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Policy Gradient-Based EMT-in-the-Loop Learning to Mitigate Sub-Synchronous Control Interactions

ํ•˜์œ„ ๋™๊ธฐ ์ œ์–ด ์ƒํ˜ธ ์ž‘์šฉ(SSCI)์€ ์ „๋ ฅ๋ง์—์„œ ์ค‘์š”ํ•œ ๋ฌธ์ œ์ด๋ฉฐ, ์ด๋Š” ์ œ์–ด ์ด๋“์˜ ์ž˜๋ชป๋œ ํŠœ๋‹๊ณผ ํŠน์ • ๊ทธ๋ฆฌ๋“œ ๊ตฌ์„ฑ์˜ ์กฐํ•ฉ์œผ๋กœ ์ธํ•ด ๋ฐœ์ƒํ•ฉ๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ SSCI๋Š” ์•ˆ์ •์„ฑ๊ณผ ์„ฑ๋Šฅ์— ์˜ํ–ฅ์„ ๋ฏธ์น  ์ˆ˜ ์žˆ๋Š” ์›์น˜ ์•Š๋Š” ์ง„๋™์„ ์œ ๋ฐœํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” SSCI๋ฅผ ์™„ํ™”ํ•˜๊ธฐ ์œ„ํ•ด ํ•™์Šต ๊ธฐ๋ฐ˜ ์ ‘๊ทผ ๋ฐฉ์‹์„ ์ œ์•ˆํ•ฉ๋‹ˆ๋‹ค. ์ด ๋ฐฉ๋ฒ•์€ EMT in the loop ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ํ”„๋ ˆ์ž„์›Œํฌ์™€ ๊ฐ•ํ™” ํ•™์Šต ๊ธฐ๋ฒ•์„ ๊ฒฐํ•ฉํ•˜์—ฌ ๊ทธ๋ฆฌ๋“œ ์กฐ๊ฑด์„ ๊ณ ๋ คํ•˜๊ณ  ์ œ์–ด ์ด๋“์„ ์ ์‘์ ์œผ๋กœ ํŠœ๋‹ํ•ฉ๋‹ˆ๋‹ค. ์ •์ฑ… ๊ธฐ์šธ๊ธฐ ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ SSCI๋ฅผ ์–ต์ œํ•˜๋Š” ์ตœ์ ์˜ ์ œ์–ด ์ด๋“์„ ์ฐพ๋Š” ๋ฐ

Learning
Post-Newtonian effects on Lagranges equilateral triangular solution for   the three-body problem

Post-Newtonian effects on Lagranges equilateral triangular solution for the three-body problem

๋ผ๊ทธ๋ž‘์ฃผ์˜ ์ •์‚ผ๊ฐํ˜• ํ•ด๋Š” ๊ณ ์ „ ์—ญํ•™์—์„œ ์งˆ๋Ÿ‰โ€‘์ค‘์‹ฌ์„ ๊ณตํ†ต์œผ๋กœ ํ•˜๋Š” ์„ธ ๋ฌผ์ฒด๊ฐ€ ์ผ์ •ํ•œ ๊ฐ์†๋„๋กœ ํšŒ์ „ํ•˜๋ฉด์„œ ์„œ๋กœ ์ •์‚ผ๊ฐํ˜•์„ ์ด๋ฃจ๋Š” ํŠน์ˆ˜ํ•œ ํ•ด์ด๋‹ค. ์ด ํ•ด๋Š” ๋‰ดํ„ด ์ค‘๋ ฅ ํ•˜์—์„œ๋Š” ์งˆ๋Ÿ‰ ๋น„์— ๊ด€๊ณ„์—†์ด ์กด์žฌํ•˜์ง€๋งŒ, ์ผ๋ฐ˜ ์ƒ๋Œ€์„ฑ ์ด๋ก ์˜ ํ›„์ฒœ ์ด๋ก (PN) ์ฐจ์ˆ˜์—์„œ๋Š” ์งˆ๋Ÿ‰ ๊ฐ„์˜ ๋น„๊ฐ€ ํ•ด์˜ ์กด์žฌ ์กฐ๊ฑด์— ์ง์ ‘์ ์ธ ์ œ์•ฝ์„ ๊ฐ€ํ•œ๋‹ค๋Š” ์ ์ด ๋ณธ ๋…ผ๋ฌธ์˜ ํ•ต์‹ฌ์ด๋‹ค. ๋จผ์ € ์ €์ž๋“ค์€ 1์ฐจ PN ๊ทผ์‚ฌ์‹(์ฆ‰, (v^{2}/c^{2})์™€ (GM/rc^{2}) ์ˆ˜์ค€์˜ ํ•ญ์„ ํฌํ•จ)์œผ๋กœ ์‚ผ์ฒด ์šด๋™ ๋ฐฉ์ •์‹์„ ์ „๊ฐœํ•˜๊ณ , ์ •์‚ผ๊ฐํ˜• ํ˜•ํƒœ๋ฅผ ์œ ์ง€ํ•˜๋„๋ก ํ•˜๋Š” ๋Œ€์นญ ์กฐ๊ฑด์„ ์ ์šฉํ•˜์˜€

MATH-PH Astrophysics General Relativity 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

Physics Computer Science Statistics Digital Libraries
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PPMStereo: Pick-and-Play Memory Construction for Consistent Dynamic Stereo Matching

PPMStereo๋Š” ๋™์  ์Šคํ…Œ๋ ˆ์˜ค ๋งค์นญ์„ ์œ„ํ•œ ํ˜์‹ ์ ์ธ ์ ‘๊ทผ ๋ฐฉ์‹์„ ์ œ์‹œํ•ฉ๋‹ˆ๋‹ค. ์ด ๋ฐฉ๋ฒ•์€ ๋ฉ”๋ชจ๋ฆฌ ๋ฒ„ํผ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ๊ณต๊ฐ„ ์‹œ๊ฐ„ ์ผ๊ด€์„ฑ์„ ๋ชจ๋ธ๋งํ•˜๋ฉด์„œ ๊ณ„์‚ฐ ํšจ์œจ์„ฑ์„ ์œ ์ง€ํ•˜๋Š” ๋ฐ ์ค‘์ ์„ ๋‘ก๋‹ˆ๋‹ค. ์ธ๊ฐ„๊ณผ ๊ฐ™์€ ๋‘ ๋‹จ๊ณ„ ์˜์‚ฌ ๊ฒฐ์ • ๊ณผ์ •์— ์˜๊ฐ์„ ๋ฐ›์•„, PPMStereo๋Š” ๊ฐ€์žฅ ๊ด€๋ จ ์žˆ๋Š” ํ”„๋ ˆ์ž„์„ ์„ ํƒํ•˜๊ณ  ๊ฐ€์ค‘์น˜๋ฅผ ๋ถ€์—ฌํ•˜์—ฌ ์‹œ๊ฐ„์  ์ผ๊ด€์„ฑ ์žˆ๋Š” ์ •๋ณด ์ง‘๊ณ„๋ฅผ ๋‹ฌ์„ฑํ•ฉ๋‹ˆ๋‹ค. ์ด ์ ‘๊ทผ ๋ฐฉ์‹์€ ์ปดํŒฉํŠธํ•œ ๋ฉ”๋ชจ๋ฆฌ ๋ฒ„ํผ๋ฅผ ์œ ์ง€ํ•˜๋ฉด์„œ๋„ ์ตœ์ฒจ๋‹จ ์„ฑ๋Šฅ์„ ์ œ๊ณตํ•œ๋‹ค๋Š” ์ ์—์„œ ๋…ํŠนํ•ฉ๋‹ˆ๋‹ค.

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Practical, Utilitarian Algorithm Configuration

๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” COUP์˜ ์‹ค์šฉ์ ์ธ ์ธก๋ฉด์„ ํ–ฅ์ƒ์‹œํ‚ค๊ธฐ ์œ„ํ•ด ๋ช‡ ๊ฐ€์ง€ ์ค‘์š”ํ•œ ๊ฐœ์„  ์‚ฌํ•ญ์„ ์ œ์•ˆํ•œ๋‹ค. ์ฒซ์งธ, ์šฐ๋ฆฌ๋Š” COUP๊ฐ€ ์œ ํ‹ธ๋ฆฌํ‹ฐ ํ•จ์ˆ˜์˜ ๊ตญ์†Œ ์ตœ๋Œ“๊ฐ’์— ์ˆ˜๋ ดํ•  ๊ฐ€๋Šฅ์„ฑ์„ ์ค„์ด๋Š” ์ƒˆ๋กœ์šด ์ดˆ๊ธฐํ™” ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค. ๋‘˜์งธ, ์šฐ๋ฆฌ๋Š” COUP์˜ ํƒ์ƒ‰ ๊ณต๊ฐ„์„ ๋” ํšจ์œจ์ ์œผ๋กœ ํƒ์ƒ‰ํ•˜๊ธฐ ์œ„ํ•œ ๊ฐœ์„ ๋œ ์ƒ˜ํ”Œ๋ง ์ „๋žต์„ ์†Œ๊ฐœํ•œ๋‹ค. ์…‹์งธ, ์šฐ๋ฆฌ๋Š” COUP์˜ ์„ฑ๋Šฅ์„ ํ–ฅ์ƒ์‹œํ‚ค๊ธฐ ์œ„ํ•ด ๋งค๊ฐœ๋ณ€์ˆ˜ ํŠœ๋‹ ์ ˆ์ฐจ๋ฅผ ์ œ์•ˆํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ๊ฐœ์„  ์‚ฌํ•ญ์€ ๋ชจ๋‘ ์ด๋ก ์  ๋ณด์žฅ์„ ์œ ์ง€ํ•˜๋ฉด์„œ COUP์˜ ์‹ค์šฉ์ ์ธ ์„ฑ๋Šฅ์„ ํฌ๊ฒŒ ํ–ฅ์ƒ์‹œํ‚จ๋‹ค. ๋˜ํ•œ, ์šฐ๋ฆฌ๋Š” ์•Œ๊ณ ๋ฆฌ์ฆ˜ ์„ ํƒ ๋ฌธ์ œ์— ๋Œ€ํ•œ ์†”๋ฃจ์…˜์ด ์œ ํ‹ธ๋ฆฌ

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Precise Gradient Discontinuities in Neural Fields for Subspace Physics

์ด ๋…ผ๋ฌธ์€ ์‹ ๊ฒฝ์žฅ์„ ์‚ฌ์šฉํ•˜์—ฌ ๋ฌผ๋ฆฌ์  ์‹œ์Šคํ…œ์—์„œ ๋‚˜ํƒ€๋‚˜๋Š” ๊ณต๊ฐ„ ๋„ํ•จ์ˆ˜์˜ ๋ถˆ์—ฐ์†์„ฑ์„ ์ •ํ™•ํ•˜๊ฒŒ ํ‘œํ˜„ํ•˜๊ธฐ ์œ„ํ•œ ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค. ๊ธฐ์กด์˜ ๊ฒฉ์ž ๊ธฐ๋ฐ˜ ๋ฐฉ๋ฒ•๊ณผ ๋‹ฌ๋ฆฌ, ์ œ์•ˆ๋œ ์ ‘๊ทผ๋ฒ•์€ ๋ชจ์–‘ ๊ฐ€์กฑ ์ „๋ฐ˜์— ๊ฑธ์ณ ์ผ๋ฐ˜ํ™”ํ•  ์ˆ˜ ์žˆ๋Š” ๋Šฅ๋ ฅ๊ณผ ํ•จ๊ป˜, ๋‹ค์–‘ํ•œ ๋ชจ์–‘์˜ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•œ๋‹ค. ์‹ ๊ฒฝ์žฅ์˜ ๋งค๋„๋Ÿฌ์›€์€ ๊ธฐ์šธ๊ธฐ ๋ถˆ์—ฐ์†์„ฑ์„ ํšจ๊ณผ์ ์œผ๋กœ ํ‘œํ˜„ํ•˜๋Š” ๋ฐ ์žฅ์• ๋ฌผ์ด ๋  ์ˆ˜ ์žˆ๋‹ค. ์ด ๋…ผ๋ฌธ์—์„œ๋Š” ์ž…๋ ฅ ์ขŒํ‘œ๋ฅผ ๋ณด๊ฐ•ํ•˜์—ฌ ์ด๋Ÿฌํ•œ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•œ๋‹ค. ์ด๋Š” ๋ฆฌํ”„ํŒ… ํ”„๋ ˆ์ž„์›Œํฌ์—์„œ ๋ถ€๋“œ๋Ÿฝ๊ฒŒ ์ œํ•œ๋œ ๊ฑฐ๋ฆฌ ํ•จ์ˆ˜๋ฅผ ์‚ฌ์šฉํ•จ์œผ๋กœ์จ ์ด๋ฃจ์–ด์ง„๋‹ค. ์ด๋ฅผ ํ†ตํ•ด ์ง„ํ™”ํ•˜๋Š” ์ธํ„ฐํŽ˜์ด์Šค์—์„œ์˜ ๊ธฐ์šธ๊ธฐ

Predicting Human Performance in Vertical Menu Selection Using Deep   Learning

Predicting Human Performance in Vertical Menu Selection Using Deep Learning

์ด ๋…ผ๋ฌธ์€ ์ธ๊ฐ„โ€‘์ปดํ“จํ„ฐ ์ƒํ˜ธ์ž‘์šฉ(HCI) ๋ถ„์•ผ์—์„œ ์˜ค๋ž˜๋œ ๊ณผ์ œ์ธ โ€œ์‚ฌ์šฉ์ž ์ˆ˜ํ–‰ ์‹œ๊ฐ„ ์˜ˆ์ธกโ€์„ ๋ฐ์ดํ„ฐโ€‘๋“œ๋ฆฌ๋ธ ๋ฐฉ์‹์œผ๋กœ ์ „ํ™˜ํ•œ ์ ์ด ๊ฐ€์žฅ ํฐ ํ˜์‹ ์ด๋‹ค. ๊ธฐ์กด์˜ Fittsโ€™ lawยทHickโ€™s law์™€ ๊ฐ™์€ ๋ถ„์„์  ๋ชจ๋ธ์€ ๊ฐ๊ฐ ์šด๋™ ์ œ์–ด์™€ ์˜์‚ฌ๊ฒฐ์ • ๊ณผ์ •์„ ์ˆ˜ํ•™์ ์œผ๋กœ ๋‹จ์ˆœํ™”ํ•˜์ง€๋งŒ, ์‹ค์ œ UI์—์„œ๋Š” ๋ฉ”๋‰ด ๊ธธ์ด, ์‹œ๊ฐ์  ๋ ˆ์ด์•„์›ƒ, ํ•ญ๋ชฉ ์˜๋ฏธ, ์‚ฌ์šฉ์ž์˜ ๊ธฐ์–ตยท๋ง๊ฐ ๋“ฑ ๋‹ค์ค‘ ์š”์ธ์ด ๋™์‹œ์— ์ž‘์šฉํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ๋ณตํ•ฉ์„ฑ์„ ๋ชจ๋ธ๋งํ•˜๋ ค๋ฉด ๋งค๋ฒˆ ์ƒˆ๋กœ์šด ๋ณ€์ˆ˜์™€ ํŒŒ๋ผ๋ฏธํ„ฐ๋ฅผ ์ถ”๊ฐ€ํ•ด์•ผ ํ•˜๋Š”๋ฐ, ์ด๋Š” ๋ชจ๋ธ ์„ค๊ณ„์™€ ๊ฒ€์ฆ์„ ๋ณต์žกํ•˜๊ฒŒ ๋งŒ๋“ ๋‹ค. ์ €์ž๋“ค์€ ์ด๋Ÿฌํ•œ ํ•œ๊ณ„๋ฅผ ๊ทน๋ณตํ•˜

Computer Science Learning HCI
Preserving Location Privacy in Mobile Edge Computing

Preserving Location Privacy in Mobile Edge Computing

๋ณธ ๋…ผ๋ฌธ์€ MEC ํ™˜๊ฒฝ์—์„œ ๋ฐœ์ƒํ•˜๋Š” ์ƒˆ๋กœ์šด ํ˜•ํƒœ์˜ ์œ„์น˜ ํ”„๋ผ์ด๋ฒ„์‹œ ์œ„ํ˜‘์„ ์ •ํ™•ํžˆ ์งš์–ด๋‚ธ๋‹ค. ๊ธฐ์กด LBSยทLS ์—ฐ๊ตฌ๋Š” โ€œ์œ„์น˜ ์ขŒํ‘œโ€๋ผ๋Š” ์ „์ œ ํ•˜์— ์ค‘์•™ ์„œ๋ฒ„๊ฐ€ ์‚ฌ์šฉ์ž์˜ ์œ„์น˜๋ฅผ ์•Œ์ง€ ๋ชปํ•˜๋„๋ก ํ•˜๋Š” ๋ฐฉ์‹์„ ์ฃผ๋กœ ํƒ๊ตฌํ–ˆ์ง€๋งŒ, MEC์—์„œ๋Š” ๋ฌด์„  ์‹ ํ˜ธ์˜ โ€˜์ง€๋ฌธ(fingerprint)โ€™ ์ž์ฒด๊ฐ€ ์œ„์น˜ ์ •๋ณด๋ฅผ ๋‚ดํฌํ•œ๋‹ค๋Š” ์ ์„ ๊ฐ•์กฐํ•œ๋‹ค. ์ฆ‰, ์ง€๋ฌธ์€ ๋ฌผ๋ฆฌ์  ์ขŒํ‘œ์™€ ๋™๋“ฑํ•œ ๋ฏผ๊ฐ ์ •๋ณด์ด๋ฉฐ, ์ด๋ฅผ ๋ณดํ˜ธํ•˜์ง€ ์•Š์œผ๋ฉด ๊ณต๊ฒฉ์ž๋Š” ์ง€๋ฌธ์„ ๋ถ„์„ํ•ด ์‚ฌ์šฉ์ž์˜ ์‹ค์ œ ์œ„์น˜๋ฅผ ์—ญ์ถ”์ •ํ•  ์ˆ˜ ์žˆ๋‹ค. ๋…ผ๋ฌธ์€ ๋‘ ๊ฐ€์ง€ ํ•ต์‹ฌ ์œ„ํ˜‘ ๋ชจ๋ธ์„ ์ œ์‹œํ•œ๋‹ค. ์ฒซ์งธ, ์ „ํ†ต์ ์ธ ์ค‘์•™์ง‘์ค‘ํ˜• ์œ„ํ˜‘ ๋ชจ

Computer Science Cryptography and Security
Preserving Privacy in Sequential Data Release against Background   Knowledge Attacks

Preserving Privacy in Sequential Data Release against Background Knowledge Attacks

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ํ•„์š”์„ฑ ํ˜„๋Œ€ ์‚ฌํšŒ์—์„œ๋Š” ๊ฐœ์ธ์˜ ํ–‰๋™ยท๊ฑฐ๋ž˜ ๊ธฐ๋ก์ด ๋””์ง€ํ„ธ ํ˜•ํƒœ๋กœ ์ง€์†์ ์œผ๋กœ ์ƒ์„ฑยท์ถ•์ ๋œ๋‹ค. ์ด๋Ÿฌํ•œ ๋ฐ์ดํ„ฐ๋Š” ์˜๋ฃŒ, ๊ธˆ์œต, ๊ตํ†ต ๋“ฑ ๋‹ค์–‘ํ•œ ๋ถ„์•ผ์—์„œ ๋ถ„์„ยท๊ณต์œ ๊ฐ€ ํ•„์ˆ˜์ ์ด์ง€๋งŒ, ๋™์‹œ์— ๊ฐœ์ธ ํ”„๋ผ์ด๋ฒ„์‹œ ์นจํ•ด ์œ„ํ—˜์„ ๋‚ดํฌํ•œ๋‹ค. ๊ธฐ์กด ํ”„๋ผ์ด๋ฒ„์‹œ ๋ณดํ˜ธ ์—ฐ๊ตฌ๋Š” ์ฃผ๋กœ(๊ฐ€) ๋‹จ์ผ ๋ฐ์ดํ„ฐ ๊ณต๊ฐœ ์‹œ์ ์— ๋Œ€ํ•œ ๋ฐฐ๊ฒฝ ์ง€์‹(์˜ˆ: ์ „์ฒด ์ธ๊ตฌ ํ†ต๊ณ„)๋งŒ์„ ๊ณ ๋ คํ•˜๊ฑฐ๋‚˜, (๋‚˜) ๋‹ค์ค‘ ๊ณต๊ฐœ์— ๋Œ€ํ•œ ์ผ๋ฐ˜์ ์ธ ์ต๋ช…ํ™” ๊ธฐ๋ฒ•(์˜ˆ: kโ€‘anonymity, lโ€‘diversity)๋งŒ์„ ์ œ์‹œํ–ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์‹ค์ œ ๊ณต๊ฒฉ์ž๋Š” ์—ฐ์†์ ์ธ ๊ณต๊ฐœ ๋ฅผ ๊ด€์ฐฐํ•˜๋ฉด์„œ ์‹œ๊ฐ„์— ๋”ฐ๋ผ ๋ณ€ํ•˜

Data Computer Science Databases
Pricing Financial Derivatives Subject to Counterparty Risk and Credit   Value Adjustment

Pricing Financial Derivatives Subject to Counterparty Risk and Credit Value Adjustment

: ์ด ๋…ผ๋ฌธ์€ ๊ธˆ์œต ํŒŒ์ƒ ์ƒํ’ˆ์˜ ๊ฐ€๊ฒฉ ์ฑ…์ •์—์„œ ์ƒ๋Œ€๋ฐฉ ์‹ ์šฉ ์œ„ํ—˜์˜ ์ค‘์š”์„ฑ์„ ๊ฐ•์กฐํ•˜๋ฉฐ, ๊ธฐ์กด ๋ฌธํ—Œ์˜ ์˜ค๋ฅ˜๋ฅผ ๋ฐ”๋กœ์žก๊ณ  CVA์— ๋Œ€ํ•œ ์‹ฌ์ธต์ ์ธ ์ดํ•ด๋ฅผ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค. ์‹ ์šฉ ์œ„ํ—˜์€ ๊ธˆ์œต ์‹œ์žฅ์—์„œ ์ค‘์š”ํ•œ ์š”์†Œ์ด๋ฉฐ, ํŠนํžˆ ๋””ํดํŠธ ๊ฐ€๋Šฅํ•œ ํŒŒ์ƒ ์ƒํ’ˆ์˜ ๊ฒฝ์šฐ ๊ทธ ์˜ํ–ฅ์ด ์ƒ๋‹นํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ๋”ฐ๋ผ์„œ ์ •ํ™•ํ•œ ๊ฐ€์น˜ ํ‰๊ฐ€์™€ CVA ๊ณ„์‚ฐ์€ ํ•„์ˆ˜์ ์ž…๋‹ˆ๋‹ค. ๋…ผ๋ฌธ์—์„œ ์ œ์‹œํ•œ ๋ชจ๋ธ์€ ๋‹ค์–‘ํ•œ ์‚ฌ๋ก€๋ฅผ ํฌ๊ด„ํ•˜๋ฉฐ, ์ผ๋ฐฉํ–ฅ ๋ฐ ์–‘๋ฐฉํ–ฅ ์‹ ์šฉ ์œ„ํ—˜์„ ๋ชจ๋‘ ๊ณ ๋ คํ•ฉ๋‹ˆ๋‹ค. ์ด๋Š” ๊ธˆ์œต ํŒŒ์ƒ ์ƒํ’ˆ์˜ ๋ณต์žก์„ฑ์„ ๋ฐ˜์˜ํ•˜๊ณ  ์‹ค์ œ ์‹œ์žฅ ์ƒํ™ฉ์— ๋Œ€ํ•œ ํ˜„์‹ค์ ์ธ ์ ‘๊ทผ๋ฒ•์„ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค. ํŠนํžˆ, ์•„๋ฉ”๋ฆฌ์นธ ์Šค

Quantitative Finance
Probabilistic verification and evaluation of Backoff procedure of the   WSN ECo-MAC protocol

Probabilistic verification and evaluation of Backoff procedure of the WSN ECo-MAC protocol

: ์ด ๋…ผ๋ฌธ์€ ๋ฌด์„  ์„ผ์„œ ๋„คํŠธ์›Œํฌ(WSN)์—์„œ ์‚ฌ์šฉ๋˜๋Š” ๋ฏธ๋””์–ด ์•ก์„ธ์Šค ์ œ์–ด ํ”„๋กœํ† ์ฝœ์ธ ECo MAC์— ๋Œ€ํ•œ ์‹ฌ์ธต์ ์ธ ๋ถ„์„์„ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค. ํŠนํžˆ, ECo MAC์˜ ๋ฐฑ์˜คํ”„ ์ ˆ์ฐจ์— ์ดˆ์ ์„ ๋งž์ถ”๊ณ  ์ด๋ฅผ ํ˜•์‹์ ์œผ๋กœ ๊ฒ€์ฆํ•˜๊ณ  ํ‰๊ฐ€ํ•˜๋Š” ๊ฒƒ์„ ๋ชฉํ‘œ๋กœ ํ•ฉ๋‹ˆ๋‹ค. WSN์€ ๋‹ค์–‘ํ•œ ์• ํ”Œ๋ฆฌ์ผ€์ด์…˜ ๋ถ„์•ผ์—์„œ ํ™œ์šฉ๋˜๋ฉฐ, ์ œํ•œ๋œ ์ž์›๊ณผ ํ™•๋ฅ ์  ํ–‰๋™์œผ๋กœ ์ธํ•ด ๋…ํŠนํ•œ ๋„์ „ ๊ณผ์ œ๋ฅผ ์ œ์‹œํ•ฉ๋‹ˆ๋‹ค. ์—ฐ๊ตฌ์ง„์€ ๋จผ์ € ECo MAC ํ”„๋กœํ† ์ฝœ๊ณผ ํ•จ๊ป˜ ์ œ์•ˆ๋œ ๋ฐฑ์˜คํ”„ ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ์†Œ๊ฐœํ•ฉ๋‹ˆ๋‹ค. ์ด ํ”„๋กœํ† ์ฝœ์€ ํ•˜์ด๋ธŒ๋ฆฌ๋“œ ์ ‘๊ทผ ๋ฐฉ์‹์„ ์ทจํ•˜์—ฌ ์„ธ ๊ฐ€์ง€ ์•ก์„ธ์Šค ๊ธฐ์ˆ ์„ ํ†ตํ•ฉํ•จ์œผ๋กœ์จ ํšจ์œจ์„ฑ์„ ํ–ฅ์ƒ์‹œ

Computer Science Networking
Process Ordering in a Process Calculus for Spatially-Explicit Ecological   Models

Process Ordering in a Process Calculus for Spatially-Explicit Ecological Models

์ด ์—ฐ๊ตฌ๋Š” ๊ฐœ์ฒด ๊ธฐ๋ฐ˜ ๋ชจ๋ธ๋ง์—์„œ ํ”ํžˆ ๊ฐ„๊ณผ๋˜๋Š” โ€œ์‹œ๊ฐ„ ๋‹จ์œ„ ๋‚ด ์‚ฌ๊ฑด ์ˆœ์„œโ€ ๋ฌธ์ œ๋ฅผ ํ˜•์‹์ ์œผ๋กœ ๋‹ค๋ฃจ๋Š” ์ ์—์„œ ์˜๋ฏธ๊ฐ€ ํฌ๋‹ค. ๊ธฐ์กด PALPS๋Š” ๊ฐœ์ฒด์˜ ์œ„์น˜ยท์ข… ์ •๋ณด๋ฅผ ํ”„๋กœ์„ธ์Šค์— ๋ถ€์ฐฉํ•˜๊ณ , ์ด๋™ยทํ†ต์‹ ยทํ™•๋ฅ ์  ์„ ํƒ์„ ํ†ตํ•ด ์ƒํƒœ ํ˜„์ƒ์„ ๊ธฐ์ˆ ํ–ˆ์ง€๋งŒ, ๋™์ผ ์‹œ๊ฐ„ ๋‹จ๊ณ„์—์„œ ๋ฐœ์ƒ ๊ฐ€๋Šฅํ•œ ์‚ฌ๊ฑด๋“ค์˜ ์ƒ๋Œ€์  ์ˆœ์„œ๋ฅผ ๋ช…์‹œ์ ์œผ๋กœ ์ œํ•œํ•˜์ง€ ์•Š์•˜๋‹ค. ์‹ค์ œ ์ƒํƒœํ•™ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์—์„œ๋Š” ์‚ฌ๋งยท๋ฒˆ์‹ยท์ด๋™ ๋“ฑ ์‚ฌ๊ฑด์˜ ์ˆœ์„œ๊ฐ€ ๊ฒฐ๊ณผ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์ด ํฌ๋ฏ€๋กœ, ์ •์ฑ…์ด๋ผ๋Š” ์™ธ๋ถ€ ๊ตฌ์กฐ๋ฅผ ๋„์ž…ํ•ด ๋ถ€๋ถ„ ์ˆœ์„œ๋ฅผ ์ •์˜ํ•จ์œผ๋กœ์จ ๋ชจ๋ธ๋Ÿฌ๊ฐ€ ์›ํ•˜๋Š” ๊ฐ€์ •์„ ์†์‰ฝ๊ฒŒ ์ ์šฉํ•  ์ˆ˜ ์žˆ๋‹ค. ์ •์ฑ…์„ ์ „์ด ๊ด€๊ณ„

Computer Science Logic Multiagent Systems Model
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ProofBridge: Auto-Formalization of Natural Language Proofs in Lean via Joint Embeddings

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ํ•„์š”์„ฑ NLโ†’FL ์ž๋™ ํ˜•์‹ํ™” ๋Š” ์ˆ˜ํ•™ ์ง€์‹์˜ ๋””์ง€ํ„ธํ™”์™€ ์ž๋™ ์ฆ๋ช… ์‹œ์Šคํ…œ์˜ ํ™•์žฅ์— ํ•ต์‹ฌ์ ์ธ ๊ธฐ์ˆ ์ด๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ๋Š” ์ •๋ฆฌ๋งŒ ํ˜น์€ ์ •๋ฆฌโ†’์ฆ๋ช… ํ๋ฆ„์— ์ง‘์ค‘ํ–ˆ์œผ๋ฉฐ, ์ •๋ฆฌ์™€ ์ฆ๋ช…์„ ๋™์‹œ์— ์ž๋™ํ™”ํ•˜๋Š” ํŒŒ์ดํ”„๋ผ์ธ์€ ๋ถ€์žฌํ–ˆ๋‹ค. ์ธ๊ฐ„์ด ์ง์ ‘ ๋ฒˆ์—ญํ•˜๋Š” ๋‹จ๊ณ„๋Š” ๋น„์šฉยท์‹œ๊ฐ„์ด ๋งŽ์ด ๋“ค๊ณ , ์˜ค๋ฅ˜ ์ „ํŒŒ ์œ„ํ—˜์ด ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ์™„์ „ ์ž๋™ํ™”๋Š” ์‹ค์šฉ์ ยทํ•™์ˆ ์  ๊ฐ€์น˜๊ฐ€ ํฌ๋‹ค. 2. ํ•ต์‹ฌ ์•„์ด๋””์–ด ๊ณต๋™ ์ž„๋ฒ ๋”ฉ ๊ณต๊ฐ„ : NL๊ณผ FL์„ ๋™์ผํ•œ ๋ฒกํ„ฐ ๊ณต๊ฐ„์— ๋งคํ•‘ํ•ด ์˜๋ฏธ์  ์œ ์‚ฌ์„ฑ์„ ์ง์ ‘ ๋น„๊ตํ•œ๋‹ค. ๋Œ€์กฐ ํ•™์Šต(contrastive learning) ์„ ํ™œ์šฉํ•ด

Properties of Pseudo-Primitive Words and their Applications

Properties of Pseudo-Primitive Words and their Applications

: ๋ณธ ๋…ผ๋ฌธ์€ ๊ฐ€์งœ ์›์‹œ์–ด์— ๋Œ€ํ•œ ์‹ฌ๋„ ์žˆ๋Š” ๋ถ„์„์„ ํ†ตํ•ด ์ž์œ ๊ตฐ ๋ฐ ์œ ํ•œํ•œ ๋‹จ์–ด์˜ ๋ฐ˜๊ตฐ์—์„œ ๋ฐœ์ƒํ•˜๋Š” Lyndon Schรผtzenberger ๋ฐฉ์ •์‹์˜ ์ผ๋ฐ˜ํ™”๋œ ํ˜•ํƒœ์ธ ํ™•์žฅ๋œ Lyndon Schรผtzenberger ๋ฐฉ์ •์‹์„ ๊ฐœ์„ ํ•˜๋Š” ๋ฐ ๊ธฐ์—ฌํ•ฉ๋‹ˆ๋‹ค. ๊ฐ€์งœ ์›์‹œ์–ด๋Š” ์›์‹œ์–ด ๊ฐœ๋…์˜ ํ™•์žฅ์œผ๋กœ, ํ•ญ๋“ฑํ•จ์ˆ˜ $theta$์— ๋Œ€ํ•œ ํŠน์„ฑ์„ ๊ณ ๋ คํ•˜์—ฌ ์ •์˜๋ฉ๋‹ˆ๋‹ค. ๋‹จ์–ด $u$๊ฐ€ $theta$ ์›์‹œ์–ด์ผ ๋•Œ, ์ด๋Š” ๋” ์งง์€ ๋‹จ์–ด $t$์™€ $theta(t)$์˜ ์—ฐ๊ฒฐ๋กœ ํ‘œํ˜„ํ•  ์ˆ˜ ์—†์Šต๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๊ฐ€์งœ ์›์‹œ์–ด์˜ ํŠน์„ฑ์€ ๋‹จ์–ด๋ฅผ ์กฐํ•ฉํ•˜๋Š” ๋ฐ ํ•„์ˆ˜์ ์ธ ๊ฐœ๋…๊ณผ ์—ฐ

Computer Science Computational Complexity
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Prudential Reliability of Large Language Models in Reinsurance: Governance, Assurance, and Capital Efficiency

: ๋ณธ ๋…ผ๋ฌธ์—์„œ ์ œ์•ˆํ•˜๋Š” ๊ฐ๋… ํ”„๋ ˆ์ž„์›Œํฌ๋Š” ์žฌ๋ณดํ—˜ ๋ถ„์•ผ์—์„œ LLM์˜ ์‹ ๋ขฐ์„ฑ์„ ํ‰๊ฐ€ํ•˜๊ธฐ ์œ„ํ•œ ํฌ๊ด„์ ์ธ ์ ‘๊ทผ ๋ฐฉ์‹์„ ์ œ๊ณตํ•œ๋‹ค. ๋‹ค์„ฏ ๊ฐ€์ง€ ๊ธฐ๋‘ฅ์œผ๋กœ ๊ตฌ์„ฑ๋œ ์•„ํ‚คํ…์ฒ˜๋Š” ๊ฑด์ „์„ฑ ๊ทœ์ œ ๊ธฐ๊ด€์˜ ์ง€์นจ์„ ์‹ค์šฉ์ ์ด๊ณ  ์ธก์ • ๊ฐ€๋Šฅํ•œ ์ œ์–ด ๋ฐฉ์‹์œผ๋กœ ๋ณ€ํ™˜ํ•˜์—ฌ LLM์ด ์žฌ๋ณดํ—˜ ํ™˜๊ฒฝ์— ์ ํ•ฉํ•œ์ง€ ํ‰๊ฐ€ํ•  ์ˆ˜ ์žˆ๊ฒŒ ํ•œ๋‹ค. RAIRAB ๋ฒค์น˜๋งˆํฌ๋ฅผ ํ†ตํ•ด ๊ฑฐ๋ฒ„๋„Œ์Šค ๋‚ด์žฌํ˜• LLM์˜ ์‹ ๋ขฐ์„ฑ๊ณผ ํˆฌ๋ช…์„ฑ์„ ํ‰๊ฐ€ํ•จ์œผ๋กœ์จ, ์ด ํ”„๋ ˆ์ž„์›Œํฌ๋Š” ๊ฑด์ „์„ฑ ๊ธฐ์ค€์— ๋ถ€ํ•ฉํ•˜๋Š” AI ์‹œ์Šคํ…œ์„ ์‹๋ณ„ํ•˜๊ณ  ์ด‰์ง„ํ•œ๋‹ค.

Model
Pushing BitTorrent Locality to the Limit

Pushing BitTorrent Locality to the Limit

์ด ์—ฐ๊ตฌ๋Š” P2P ์ฝ˜ํ…์ธ  ๋ฐฐํฌ๊ฐ€ ISP ๊ฐ„ ๋Œ€์—ญํญ์„ ๊ณผ๋„ํ•˜๊ฒŒ ์†Œ๋ชจํ•œ๋‹ค๋Š” ๊ธฐ์กด ๋ฌธ์ œ์ ์„ ๋ช…ํ™•ํžˆ ์งš์–ด๋‚ธ๋‹ค. ํŠนํžˆ BitTorrent ํ”„๋กœํ† ์ฝœ์ด ํ”ผ์–ด๋ฅผ ๋ฌด์ž‘์œ„๋กœ ์—ฐ๊ฒฐํ•˜๋„๋ก ์„ค๊ณ„๋ผ, ๋™์ผ ISP ๋‚ด์— ์กด์žฌํ•˜๋Š” ํ”ผ์–ด๋“ค์กฐ์ฐจ๋„ ์™ธ๋ถ€ ํ”ผ์–ด์™€ ๊ต๋ฅ˜ํ•˜๊ฒŒ ๋˜๋Š” ๊ตฌ์กฐ์  ๋น„ํšจ์œจ์„ ๊ฐ•์กฐํ•œ๋‹ค. ์ €์ž๋“ค์€ โ€œ์ง€์—ญ์„ฑ์„ ์–ผ๋งˆ๋‚˜ ๊ทน๋Œ€ํ™”ํ•  ์ˆ˜ ์žˆ๋Š”๊ฐ€โ€์™€ โ€œ์ „์ฒด ์ธํ„ฐ๋„ท ๊ทœ๋ชจ์—์„œ ์‹ค์ œ ์ ˆ๊ฐ ํšจ๊ณผ๋Š” ์–ด๋А ์ •๋„์ธ๊ฐ€โ€๋ผ๋Š” ๋‘ ํ•ต์‹ฌ ์งˆ๋ฌธ์— ์‹คํ—˜๊ณผ ์‹ค์ฆ์„ ๋™์‹œ์— ์ ์šฉํ•ด ๋‹ต์„ ์ œ์‹œํ•œ๋‹ค๋Š” ์ ์—์„œ ์—ฐ๊ตฌ ์„ค๊ณ„๊ฐ€ ๋›ฐ์–ด๋‚˜๋‹ค. ์ฒซ ๋ฒˆ์งธ ์‹คํ—˜์—์„œ๋Š” 10 000๋Œ€์˜ ํด๋ผ์ด์–ธํŠธ๋ฅผ ๋™์‹œ์— ์šด์˜ํ•ด ๋‹ค์–‘

Computer Science Networking
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QAOA-PCA: Enhancing Efficiency in the Quantum Approximate Optimization Algorithm via Principal Component Analysis

QAOA PCA๋Š” ์–‘์ž ์ปดํ“จํŒ… ๋ถ„์•ผ์—์„œ ์ค‘์š”ํ•œ ๊ธฐ์—ฌ๋ฅผ ํ•ฉ๋‹ˆ๋‹ค. ์ด ๊ธฐ๋ฒ•์€ QAOA ์•Œ๊ณ ๋ฆฌ์ฆ˜์˜ ํšจ์œจ์„ฑ์„ ํ–ฅ์ƒ์‹œํ‚ค๊ณ , ํŠนํžˆ ์ธต ์ˆ˜๊ฐ€ ์ฆ๊ฐ€ํ•จ์— ๋”ฐ๋ผ ๋ฐœ์ƒํ•˜๋Š” ๊ณ„์‚ฐ ๋ณต์žก๋„๋ฅผ ์ค„์ด๋Š” ๋ฐ ์ดˆ์ ์„ ๋งž์ถฅ๋‹ˆ๋‹ค. ์ฃผ์„ฑ๋ถ„ ๋ถ„์„์„ ํ™œ์šฉํ•˜์—ฌ ๋งค๊ฐœ๋ณ€์ˆ˜ ๊ณต๊ฐ„์„ ์ถ•์†Œํ•จ์œผ๋กœ์จ, ๋” ์ ์€ ๋ฐ˜๋ณต ํšŸ์ˆ˜๋กœ ์ตœ์ ํ™”๋ฅผ ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ๊ฒŒ ๋ฉ๋‹ˆ๋‹ค. ์ด๋Š” ์–‘์ž ์ปดํ“จํŒ…์—์„œ ์ค‘์š”ํ•œ ๋ฌธ์ œ์ธ ๊ณ ์ „์ ์ธ ์ตœ์ ํ™”๊ธฐ์˜ ์˜ค๋ฒ„ํ—ค๋“œ๋ฅผ ์ค„์ด๋Š” ๋ฐ ๋„์›€์ด ๋ฉ๋‹ˆ๋‹ค. ๋˜ํ•œ, QAOA PCA๋Š” ์ž‘์€ ๋ฌธ์ œ ์ธ์Šคํ„ด์Šค์˜ ๋งค๊ฐœ๋ณ€์ˆ˜๋กœ๋ถ€ํ„ฐ ์ฃผ์„ฑ๋ถ„์„ ์ถ”์ถœํ•˜๋Š” ๋…ํŠนํ•œ ์ ‘๊ทผ๋ฒ•์„ ์ทจํ•ฉ๋‹ˆ๋‹ค. ์ด ๋ฐฉ๋ฒ•์€ ๋” ํฐ ๋ฌธ์ œ์— ๋Œ€ํ•œ ํšจ์œจ

Analysis
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Quadratic Direct Forecast for Training Multi-Step Time-Series Forecast Models

์‹œ๊ฐ„ ์‹œ๋ฆฌ์ฆˆ ์˜ˆ์ธก์€ ๋ฏธ๋ž˜์˜ ์ถ”์„ธ๋ฅผ ํŒŒ์•…ํ•˜๊ณ , ์ด๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ์˜์‚ฌ ๊ฒฐ์ •์„ ๋‚ด๋ฆฌ๋Š” ๋ฐ ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๊ธฐ์กด ํ›ˆ๋ จ ๋ชฉํ‘œ๋Š” ๋ฏธ๋ž˜ ๋‹จ๊ณ„ ๊ฐ„์˜ ์ƒ๊ด€ ๊ด€๊ณ„๋ฅผ ๊ณ ๋ คํ•˜์ง€ ์•Š์•„ ํŽธํ–ฅ๋œ ๊ฒฐ๊ณผ๋ฅผ ์ดˆ๋ž˜ํ•  ์ˆ˜ ์žˆ๋‹ค. ์ œ์•ˆ๋œ QDF ๋ฐฉ๋ฒ•๋ก ์€ ์ด๋Ÿฌํ•œ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ๋ ˆ์ด๋ธ” ์ž์œจ ์ƒ๊ด€ ๊ด€๊ณ„ ํšจ๊ณผ๋ฅผ ๊ณ ๋ คํ•œ ๊ฐ€์ค‘ ํ–‰๋ ฌ์„ ๋„์ž…ํ•œ๋‹ค. ์ด๋Š” ๊ฐ ์˜ˆ์ธก ์ž‘์—…์— ์ ์ ˆํ•œ ๊ฐ€์ค‘์น˜๋ฅผ ํ• ๋‹นํ•˜์—ฌ, ๋ฏธ๋ž˜ ๋‹จ๊ณ„์— ๋Œ€ํ•œ ๋” ์ •ํ™•ํ•œ ์˜ˆ์ธก์„ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•œ๋‹ค. ๋˜ํ•œ, QDF๋Š” ๋‹ค์–‘ํ•œ ์˜ˆ์ธก ๋ชจ๋ธ์˜ ์„ฑ๋Šฅ ํ–ฅ์ƒ์„ ๋ณด์—ฌ์ฃผ๋ฉฐ, ์ตœ์ฒจ๋‹จ ๊ฒฐ๊ณผ๋ฅผ ๋‹ฌ์„ฑํ•จ์œผ๋กœ์จ ๊ทธ ์œ ์šฉ์„ฑ์„ ์ž…์ฆํ•˜์˜€๋‹ค.

Model
Qualitative modelling and analysis of regulations in multi-cellular   systems using Petri nets and topological collections

Qualitative modelling and analysis of regulations in multi-cellular systems using Petri nets and topological collections

์ด ์—ฐ๊ตฌ๋Š” ๋‹ค์„ธํฌ ์‹œ์Šคํ…œ์„ ์ •ํ˜•ํ™”๋œ ๋…ผ๋ฆฌ ๋„คํŠธ์›Œํฌ์™€ ๊ณต๊ฐ„ ์ •๋ณด๋ฅผ ๋™์‹œ์— ๋‹ค๋ฃฐ ์ˆ˜ ์žˆ๋Š” ํ†ตํ•ฉ ๋ชจ๋ธ๋ง ํ™˜๊ฒฝ์„ ์ œ๊ณตํ•œ๋‹ค๋Š” ์ ์—์„œ ํฐ ์˜์˜๋ฅผ ๊ฐ€์ง„๋‹ค. ๊ธฐ์กด์˜ Renรฉ Thomas ๋…ผ๋ฆฌ ๋ชจ๋ธ์€ ์„ธํฌ ๋‚ด๋ถ€์˜ ์กฐ์ ˆ ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ์ด์‚ฐ์  ์ƒํƒœ์™€ ์ „์ด ๊ทœ์น™์œผ๋กœ ํšจ๊ณผ์ ์œผ๋กœ ๊ธฐ์ˆ ํ–ˆ์ง€๋งŒ, ์„ธํฌ ๊ฐ„์˜ ๋ฌผ๋ฆฌ์ ยท์œ„์น˜์  ์ƒํ˜ธ์ž‘์šฉ์„ ๋ฐ˜์˜ํ•˜๊ธฐ์—๋Š” ํ•œ๊ณ„๊ฐ€ ์žˆ์—ˆ๋‹ค. ์ €์ž๋“ค์€ ์ด๋Ÿฌํ•œ ํ•œ๊ณ„๋ฅผ ๊ทน๋ณตํ•˜๊ธฐ ์œ„ํ•ด ๋‘ ๊ฐ€์ง€ ํ•ต์‹ฌ ๊ธฐ์ˆ ์„ ๋„์ž…ํ•˜์˜€๋‹ค. ์ฒซ ๋ฒˆ์งธ๋Š” ์ƒ‰์น ๋œ ํŽ˜ํŠธ๋ฆฌ๋ง์„ ์ด์šฉํ•ด ์กฐ์ ˆ ๊ทœ์น™์„ ์ „์ด ์‹œ์Šคํ…œ์œผ๋กœ ํ‘œํ˜„ํ•˜๊ณ , ๋‘ ๋ฒˆ์งธ๋Š” ์œ„์ƒํ•™์  ์ปฌ๋ ‰์…˜์„ ํ†ตํ•ด ๊ณต๊ฐ„ ๊ตฌ์„ฑ์„ ์ด์‚ฐ์ ์ธ ๊ตฌ์กฐ(

Analysis Computational Engineering System Model Computer Science
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Quality Assurance of LLM-generated Code: Addressing Non-Functional Quality Characteristics

์ด ๋…ผ๋ฌธ์€ LLM์ด ์ƒ์„ฑํ•œ ์ฝ”๋“œ์— ๋Œ€ํ•œ ํ’ˆ์งˆ ๋ณด์ฆ์˜ ์ค‘์š”์„ฑ์— ๋Œ€ํ•ด ์‹ฌ์ธต์ ์œผ๋กœ ๋ถ„์„ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ๊ธฐ๋Šฅ์  ์ •ํ™•์„ฑ ์™ธ์—๋„ ๋น„๊ธฐ๋Šฅ์  ํ’ˆ์งˆ ํŠน์„ฑ์„ ๊ณ ๋ คํ•˜๋Š” ๊ฒƒ์ด ์™œ ์ค‘์š”ํ•œ์ง€ ๊ฐ•์กฐํ•ฉ๋‹ˆ๋‹ค. ๋ณด์•ˆ, ์œ ์ง€๋ณด์ˆ˜์„ฑ ๋ฐ ์„ฑ๋Šฅ ํšจ์œจ์„ฑ๊ณผ ๊ฐ™์€ ์ธก๋ฉด์€ ์†Œํ”„ํŠธ์›จ์–ด ๊ฐœ๋ฐœ์—์„œ ํ•„์ˆ˜์ ์ธ ์š”์†Œ์ด๋ฉฐ, LLM์ด ์ƒ์„ฑํ•œ ์ฝ”๋“œ๊ฐ€ ์ด๋Ÿฌํ•œ ํ’ˆ์งˆ ๊ธฐ์ค€์„ ์ถฉ์กฑํ•ด์•ผ ํ•จ์„ ์ง€์ ํ•ฉ๋‹ˆ๋‹ค. ์ฒด๊ณ„์ ์ธ ๋ฌธํ—Œ๊ณ ์ฐฐ๊ณผ ์‚ฐ์—… ์›Œํฌ์ˆ์„ ํ†ตํ•ด ํ•™๊ณ„์™€ ์—…๊ณ„์˜ ๊ด€์‹ฌ๊ณผ ์šฐ์„ ์ˆœ์œ„๊ฐ€ ๋‹ค๋ฅด๋‹ค๋Š” ๊ฒƒ์„ ๋ฐœ๊ฒฌํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด๋Š” ๋ชจ๋ธ์˜ ์„ฑ๋Šฅ๊ณผ ์‹ค์ œ ์ ์šฉ ์‚ฌ์ด์˜ ๊ฐ„๊ทน์„ ๋“œ๋Ÿฌ๋ƒ…๋‹ˆ๋‹ค. ๋˜ํ•œ, ์ƒ์„ฑ๋œ ์ฝ”๋“œ๊ฐ€ ๊ธฐ์ˆ  ๋ถ€์ฑ„๋ฅผ ์ถ•์ ํ•  ์ˆ˜

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Quantifying Feature Importance for Online Content Moderation

์ด ๋…ผ๋ฌธ์—์„œ๋Š” ์˜จ๋ผ์ธ ์ฝ˜ํ…์ธ  ๊ด€๋ฆฌ์—์„œ ์‚ฌ์šฉ์ž์˜ ๋ฐ˜์‘์„ ์˜ˆ์ธกํ•˜๊ธฐ ์œ„ํ•œ ํŠน์ง• ์ค‘์š”๋„๋ฅผ ์ •๋Ÿ‰ํ™”ํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ–ˆ์Šต๋‹ˆ๋‹ค. ๋‹ค์–‘ํ•œ ์‚ฌ์šฉ์ž ํŠน์„ฑ์„ ๊ณ ๋ คํ•˜์—ฌ, Reddit์—์„œ ๋Œ€๊ทœ๋ชจ ๊ด€๋ฆฌ ๊ฐœ์ž… ํ›„์˜ ์‚ฌ์šฉ์ž ํ–‰๋™ ๋ณ€ํ™”๋ฅผ ์˜ˆ์ธกํ•˜๋Š” ๋ชจ๋ธ์„ ๊ฐœ๋ฐœํ–ˆ์Šต๋‹ˆ๋‹ค. ํƒ์š•์Šค๋Ÿฌ์šด ๊ธฐ๋Šฅ ์„ ํƒ ์ „๋žต์„ ์‚ฌ์šฉํ•˜์—ฌ, ๊ฐ€์žฅ ์˜ˆ์ธก๋ ฅ์ด ๋†’์€ ํŠน์ง•๋“ค์„ ์‹๋ณ„ํ•˜๊ณ  ๊ทธ ์ค‘์š”๋„๋ฅผ ์ถ”์ •ํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ์ ‘๊ทผ๋ฒ•์€ ์‚ฌ์šฉ์ž์˜ ํ™œ๋™, ๋…์„ฑ, ์ฐธ์—ฌ ๋‹ค์–‘์„ฑ์˜ ๋ณ€ํ™”์— ๋Œ€ํ•œ ํ†ต์ฐฐ๋ ฅ์„ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค. ๋˜ํ•œ, ์ €ํฌ๋Š” ํŠน์ • ์ž‘์—…์— ํŠนํ™”๋œ ํŠน์ง•๋“ค์ด ์กด์žฌํ•œ๋‹ค๋Š” ๊ฒƒ์„ ๋ฐœ๊ฒฌํ–ˆ์œผ๋ฉฐ, ์ด๋Š” ๊ด€๋ฆฌ ์ „๋žต ๊ฐœ๋ฐœ ์‹œ ๊ณ ๋ คํ•ด์•ผ ํ• 

Quantum Adiabatic Evolution for Global Optimization in Big Data

Quantum Adiabatic Evolution for Global Optimization in Big Data

๋ณธ ๋…ผ๋ฌธ์€ ๋น…๋ฐ์ดํ„ฐ ์ตœ์ ํ™” ๋ฌธ์ œ์— ๋ฌผ๋ฆฌํ•™โ€‘์ˆ˜ํ•™์  ํ”„๋ ˆ์ž„์›Œํฌ๋ฅผ ๋„์ž…ํ•œ๋‹ค๋Š” ์ ์—์„œ ํ˜์‹ ์ ์ด๋‹ค. ๋ฐ์ดํ„ฐ์˜ 4V(Volume, Velocity, Veracity, Complexity)๋ฅผ ๋ฌผ๋ฆฌ์  ์ž์œ ๋„์— ๋Œ€์‘์‹œ์ผœ ์–‘์ž ์œ„์ƒ์žฅ ์œผ๋กœ ํ•ด์„ํ•˜๋Š” ์‹œ๋„๋Š” ๊ธฐ์กด ํ†ต๊ณ„โ€‘ํ•™์Šต ๊ธฐ๋ฐ˜ ์ ‘๊ทผ๊ณผ๋Š” ์ „ํ˜€ ๋‹ค๋ฅธ ํŒจ๋Ÿฌ๋‹ค์ž„์„ ์ œ์‹œํ•œ๋‹ค. ํŠนํžˆ ์–‘์ž ์•„๋””์•„๋ฐ”ํ‹ฑ ์ง„ํ™”(Quantum Adiabatic Evolution) ๋ฅผ ์ด์šฉํ•ด ์ „์—ญ ์ตœ์ ํ™”๋ฅผ ์ˆ˜ํ–‰ํ•œ๋‹ค๋Š” ์•„์ด๋””์–ด๋Š”, ์–‘์ž ์ปดํ“จํŒ… ๋ถ„์•ผ์—์„œ ์•Œ๋ ค์ง„ โ€˜adiabatic quantum optimizationโ€™(AQO)๊ณผ ์œ ์‚ฌํ•˜์ง€๋งŒ,

Other CS Computer Science Data
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Quantum Circuit Design using a Progressive Widening Enhanced Monte Carlo Tree Search

: ์–‘์ž ์ปดํ“จํŒ… ๋ถ„์•ผ์—์„œ ํšจ์œจ์ ์ธ ์–‘์ž ํšŒ๋กœ ์„ค๊ณ„๋ฅผ ์œ„ํ•œ ์ƒˆ๋กœ์šด ์ ‘๊ทผ ๋ฐฉ์‹์€ ๋งค์šฐ ์ค‘์š”ํ•œ ์—ฐ๊ตฌ ์ฃผ์ œ์ด๋‹ค. ์ด ๋…ผ๋ฌธ์—์„œ๋Š” MCTS ๊ธฐ๋ฒ•์„ ํ™œ์šฉํ•˜์—ฌ ์–‘์ž ํšŒ๋กœ๋ฅผ ์„ค๊ณ„ํ•˜๋Š” ํ˜์‹ ์ ์ธ ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค. ํŠนํžˆ, ์ƒ˜ํ”Œ๋ง ๊ธฐ๋ฐ˜์˜ ์•ก์…˜ ๊ณต๊ฐ„๊ณผ ์ ์ง„์  ํ™•์žฅ ๊ธฐ์ˆ ์„ ํ†ตํ•ด ๊ธฐ์กด ๋ฐฉ๋ฒ•๋ณด๋‹ค ๋” ํšจ๊ณผ์ ์ด๊ณ  ํšจ์œจ์ ์ธ ํƒ์ƒ‰์ด ๊ฐ€๋Šฅํ•˜๋‹ค๋Š” ์ ์„ ๋ณด์—ฌ์ค€๋‹ค. ๋˜ํ•œ, ๋‹ค์–‘ํ•œ ์‘์šฉ ๋ถ„์•ผ์—์„œ ์•ˆ์ •์„ฑ๊ณผ ์„ฑ๋Šฅ์„ ์ž…์ฆํ•จ์œผ๋กœ์จ ์‹ค์šฉ์ ์ธ ์ธก๋ฉด์—์„œ๋„ ์ฃผ๋ชฉํ•  ๋งŒํ•˜๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ์–‘์ž ์•Œ๊ณ ๋ฆฌ์ฆ˜ ์„ค๊ณ„์— ์žˆ์–ด ์ค‘์š”ํ•œ ์ง„์ „์„ ๊ฐ€์ ธ์˜ฌ ์ˆ˜ ์žˆ์œผ๋ฉฐ, ํ–ฅํ›„ ์–‘์ž ์ปดํ“จํŒ…์˜ ๋ฐœ์ „์— ๊ธฐ์—ฌํ•  ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€๋œ๋‹ค

Quantum query complexity of minor-closed graph properties

Quantum query complexity of minor-closed graph properties

์ด ๋…ผ๋ฌธ์€ ๊ทธ๋ž˜ํ”„ ์ด๋ก ๊ณผ ์–‘์ž ์•Œ๊ณ ๋ฆฌ์ฆ˜ ์‚ฌ์ด์˜ ๊ต์ฐจ์ ์—์„œ ์ค‘์š”ํ•œ ํ†ต์ฐฐ์„ ์ œ๊ณตํ•œ๋‹ค. ๋งˆ์ด๋„ˆโ€‘ํ์‡„ ์„ฑ์งˆ์€ ๊ทธ๋ž˜ํ”„ ์ด๋ก ์—์„œ Robertsonโ€‘Seymour ์ •๋ฆฌ์™€ ๊นŠ์€ ์—ฐ๊ด€์ด ์žˆ์œผ๋ฉฐ, โ€œ๊ธˆ์ง€ ๋งˆ์ด๋„ˆ ์ง‘ํ•ฉโ€์ด๋ผ๋Š” ๊ฐ„๊ฒฐํ•œ ์ •์˜๋กœ ๋‹ค์–‘ํ•œ ๋ณตํ•ฉ ์„ฑ์งˆ์„ ํฌ๊ด„ํ•œ๋‹ค. ์ €์ž๋Š” ์ด๋Ÿฌํ•œ ์„ฑ์งˆ์„ ์–‘์ž ์งˆ์˜ ๋ณต์žก๋„ ๊ด€์ ์—์„œ ๋‘ ๊ฐ€์ง€ ํด๋ž˜์Šค๋กœ ๊ตฌ๋ถ„ํ•œ๋‹ค๋Š” ์ ์ด ํ•ต์‹ฌ์ด๋‹ค. ์ฒซ ๋ฒˆ์งธ ํด๋ž˜์Šค๋Š” ๊ธˆ์ง€ ๋งˆ์ด๋„ˆ๊ฐ€ ๋ฌดํ•œํžˆ ๋งŽ์€ ๊ฒฝ์šฐ์ด๋‹ค. ์—ฌ๊ธฐ์—๋Š” ํ‰๋ฉด์„ฑ, ํฌ๋ ˆ์ŠคํŠธ ์—ฌ๋ถ€, ํŠน์ • ๊ธธ์ด์˜ ๊ฒฝ๋กœ ๋ถ€์žฌ์™€ ๊ฐ™์€ ์ „ํ˜•์ ์ธ ์˜ˆ๊ฐ€ ํฌํ•จ๋œ๋‹ค. ์ €์ž๋Š” ๊ธˆ์ง€ ๋งˆ์ด๋„ˆ์™€ ๊ธˆ์ง€ ์„œ๋ธŒ๊ทธ๋ž˜ํ”„์˜ ๊ตฌ์กฐ์  ํŠน

Computer Science Quantum Physics Data Structures Computational Complexity

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