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Do Prompts Reshape Representations? An Empirical Study of Prompting Effects on Embeddings

๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ œ๋กœ์ƒท ๋ถ„๋ฅ˜๋ฅผ ์œ„ํ•œ ๋‹ค์–‘ํ•œ ํ”„๋กฌํ”„ํŠธ ํ…œํ”Œ๋ฆฟ์˜ ํšจ๊ณผ๋ฅผ ๊ฒฝํ—˜์ ์œผ๋กœ ์กฐ์‚ฌํ•œ๋‹ค. ์šฐ๋ฆฌ์˜ ์—ฐ๊ตฌ๋Š” ํ”„๋กฌํ”„ํŒ…์ด ์–ด๋–ป๊ฒŒ ํ‘œํ˜„์˜ ํ’ˆ์งˆ์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š”์ง€, ๊ทธ๋ฆฌ๊ณ  ์ด๋Ÿฌํ•œ ๋ณ€ํ™”๊ฐ€ ์ž‘์—…๊ณผ ๊ด€๋ จํ•˜์—ฌ ์–ด๋–ป๊ฒŒ ๋‚˜ํƒ€๋‚˜๋Š”์ง€๋ฅผ ํƒ๊ตฌํ•œ๋‹ค. ์šฐ๋ฆฌ๋Š” ํ”„๋กฌํ”„ํŠธ์™€ ํ‘œํ˜„ ์‚ฌ์ด์˜ ๋ณต์žกํ•œ ์ƒํ˜ธ์ž‘์šฉ์„ ๋ฐœ๊ฒฌํ–ˆ์œผ๋ฉฐ, ์ด๋Š” ๋‹จ์ˆœํžˆ ๋” ๊ด€๋ จ์„ฑ ์žˆ๋Š” ํ”„๋กฌํ”„ํŠธ๊ฐ€ ํ•ญ์ƒ ๋” ๋‚˜์€ ๊ฒฐ๊ณผ๋ฅผ ๊ฐ€์ ธ์˜จ๋‹ค๋Š” ๊ฐ€์ •์„ ๋’ค์—Ž๋Š”๋‹ค. ๋˜ํ•œ ์šฐ๋ฆฌ์˜ ๋ถ„์„์€ ์ด ์˜ˆ๊ธฐ์น˜ ์•Š์€ ํ–‰๋™์— ๊ธฐ์—ฌํ•˜๋Š” ์ž ์žฌ์  ์š”์ธ์„ ๋ฐํžŒ๋‹ค. ์ด๋Ÿฌํ•œ ํ†ต์ฐฐ๋ ฅ์€ ์‚ฌ์ „ ํ•™์Šต๋œ ์–ธ์–ด ๋ชจ๋ธ์˜ ๋™์ž‘์„ ์ดํ•ดํ•˜๊ณ  ๊ฐœ์„ ํ•˜๋Š” ๋ฐ ๋„์›€์ด ๋  ์ˆ˜ ์žˆ๋‹ค.

Driver Identification by Neural Network on Extracted Statistical   Features from Smartphone Data

Driver Identification by Neural Network on Extracted Statistical Features from Smartphone Data

๋ณธ ์—ฐ๊ตฌ๋Š” ์Šค๋งˆํŠธํฐ ์„ผ์„œ ๊ธฐ๋ฐ˜ ์šด์ „์ž ์‹๋ณ„ ์ด๋ผ๋Š” ์‹ค์šฉ์  ๋ฌธ์ œ์— ์ ‘๊ทผํ•˜๋ฉด์„œ, ๋ฐ์ดํ„ฐ ์ˆ˜์ง‘๋ถ€ํ„ฐ ๋ชจ๋ธ ํ‰๊ฐ€๊นŒ์ง€ ์ผ๊ด€๋œ ํŒŒ์ดํ”„๋ผ์ธ์„ ์ œ์‹œํ•œ๋‹ค๋Š” ์ ์—์„œ ์˜์˜๊ฐ€ ํฌ๋‹ค. 1. ๋ฐ์ดํ„ฐ ์ˆ˜์ง‘ ๋ฐ ์‹คํ—˜ ์„ค๊ณ„ ๊ฐ€์†๋„๊ณ„์™€ ์ž์ด๋กœ์Šค์ฝ”ํ”„๋Š” ๋Œ€๋ถ€๋ถ„์˜ ํ˜„๋Œ€ ์Šค๋งˆํŠธํฐ์— ๊ธฐ๋ณธ ํƒ‘์žฌ๋œ ์ €๋น„์šฉ ์„ผ์„œ์ด๋ฉฐ, ๋ณ„๋„์˜ ์™ธ๋ถ€ ์žฅ๋น„ ์—†์ด๋„ ์šด์ „ ํ–‰๋™์„ ์ •๋ฐ€ํžˆ ๊ธฐ๋กํ•  ์ˆ˜ ์žˆ๋‹ค. ๋…ผ๋ฌธ์€ ์ด๋Ÿฌํ•œ ์„ผ์„œ๋ฅผ ํ™œ์šฉํ•ด ์šด์ „ ์ค‘ ๋ฐœ์ƒํ•˜๋Š” ๋ฏธ์„ธํ•œ ์ง„๋™ยทํšŒ์ „ ํŒจํ„ด์„ ํฌ์ฐฉํ•œ๋‹ค๋Š” ์ ์—์„œ ๋น„์šฉ ํšจ์œจ์„ฑ์„ ๊ฐ•์กฐํ•œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๋ฐ์ดํ„ฐ ์ˆ˜์ง‘ ํ™˜๊ฒฝ(๋„๋กœ ์œ ํ˜•, ์ฐจ๋Ÿ‰ ์ข…๋ฅ˜, ์Šค๋งˆํŠธํฐ ์žฅ์ฐฉ ์œ„์น˜ ๋“ฑ)์— ๋Œ€ํ•œ ์ƒ์„ธ

Network HCI Data Computer Science Electrical Engineering and Systems Science
DRMS Co-design by F4MS

DRMS Co-design by F4MS

: ๋””์ง€ํ„ธ ๊ถŒ๋ฆฌ ๊ด€๋ฆฌ(DRM)๋Š” ๋””์ง€ํ„ธ ๊ฒฝ์ œ์—์„œ ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•˜๋ฉฐ, ๋‹ค์–‘ํ•œ ์žฅ์น˜์™€ ํ”Œ๋žซํผ์—์„œ ์‚ฌ์šฉ๋˜๋Š” ๋ชจ๋“  ๋””์ง€ํ„ธ ์ฝ˜ํ…์ธ ์— ๋Œ€ํ•œ ์š”๊ตฌ ์‚ฌํ•ญ์„ ์ถฉ์กฑํ•ด์•ผ ํ•ฉ๋‹ˆ๋‹ค. DRM ์‹œ์Šคํ…œ์€ ๋ณต์žกํ•˜๊ณ  ์œ ์—ฐํ•˜์ง€ ๋ชปํ•˜๋ฉฐ, ๋‹ค์–‘ํ•œ ๋ฏธ๋””์–ด์™€ ์‚ฌ์šฉ์ž ์š”๊ตฌ๋ฅผ ์ง€์›ํ•ด์•ผ ํ•˜๋Š” ์–ด๋ ค์›€์ด ์žˆ์Šต๋‹ˆ๋‹ค. ๊ธฐ์กด์˜ ์„ค๊ณ„ ๋„๊ตฌ๋“ค์€ ํ•˜๋“œ์›จ์–ด์™€ ์†Œํ”„ํŠธ์›จ์–ด ์„ค๊ณ„๋ฅผ ๋ถ„๋ฆฌํ•˜์—ฌ ์ ‘๊ทผํ•˜๊ธฐ ๋•Œ๋ฌธ์—, ์ด๋Ÿฌํ•œ ์‹œ์Šคํ…œ์˜ ์„ฑ๋Šฅ๊ณผ ํšจ์œจ์„ฑ์„ ์ €ํ•ดํ•ฉ๋‹ˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ด๋Ÿฌํ•œ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ์ฝ”๋””์ž์ธ ํ”„๋ ˆ์ž„์›Œํฌ๋ฅผ ์ œ์•ˆํ•ฉ๋‹ˆ๋‹ค. ์ฝ”๋””์ž์ธ์˜ ํ•ต์‹ฌ์€ ํ•˜๋“œ์›จ์–ด์™€ ์†Œํ”„ํŠธ์›จ์–ด ์„ค๊ณ„๋ฅผ ํ†ตํ•ฉํ•˜๊ณ  ์ƒํ˜ธ ์ž‘์šฉ์„ ํ†ต

Software Engineering Computer Science
Dynamic Advisor-Based Ensemble (dynABE): Case study in stock trend   prediction of critical metal companies

Dynamic Advisor-Based Ensemble (dynABE): Case study in stock trend prediction of critical metal companies

1. ์—ฐ๊ตฌ ๋™๊ธฐ์™€ ๊ธฐ์กด ํ•œ๊ณ„ ์ฃผ์‹ ๊ฐ€๊ฒฉ์€ ๋น„์„ ํ˜•์„ฑ, ๋น„์ •์ƒ์„ฑ, ๊ทธ๋ฆฌ๊ณ  ์™ธ๋ถ€ ์š”์ธ์— ์˜ํ•œ ๊ธ‰๊ฒฉํ•œ ๋ณ€๋™์„ ๋ณด์ด๋ฉฐ, ๋‹จ์ผ ๋ชจ๋ธ๋งŒ์œผ๋กœ๋Š” ์ด๋Ÿฌํ•œ ๋ณตํ•ฉ์„ฑ์„ ํฌ์ฐฉํ•˜๊ธฐ ์–ด๋ ต๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ๋Š” (โ‘  ์ผ๋ฐ˜ ์ง€ํ‘œ ๊ธฐ๋ฐ˜, โ‘ก ๊ฐ์„ฑ ๋ถ„์„ ๊ธฐ๋ฐ˜, โ‘ข ๊ธฐ์—… ๊ฐ„ ์ƒ๊ด€๊ด€๊ณ„ ๊ธฐ๋ฐ˜) ์„ธ ๊ฐ€์ง€ ์–‘์  ์ ‘๊ทผ๋ฒ•์œผ๋กœ ๋‚˜๋‰˜์ง€๋งŒ, ๊ฐ๊ฐ์ด ๊ฐ–๋Š” ์ •๋ณด ํŽธํ–ฅ๊ณผ ๋ชจ๋ธ ๊ณ ์ •์„ฑ ๋•Œ๋ฌธ์— ์‹ค์‹œ๊ฐ„ ์‹œ์žฅ ๋ณ€ํ™”์— ๋Œ€ํ•œ ์ ์‘๋ ฅ์ด ๋ถ€์กฑํ–ˆ๋‹ค. ํŠนํžˆ ๊ณ ์ฃผํŒŒ ๊ฑฐ๋ž˜์™€ ๊ฐ™์ด ์งง์€ ์‹œ๊ฐ„ ์•ˆ์— ๋ฐœ์ƒํ•˜๋Š” ํŒจํ„ด์„ ํฌ์ฐฉํ•˜๋ ค๋ฉด ๋„๋ฉ”์ธโ€‘ํŠนํ™” ์ •๋ณด์™€ ๋น ๋ฅธ ๋ชจ๋ธ ์—…๋ฐ์ดํŠธ๊ฐ€ ํ•„์ˆ˜์ ์ด๋‹ค. 2. dynABE์˜ ํ•ต์‹ฌ ์„ค๊ณ„ ๋„๋ฉ”์ธโ€‘ํŠนํ™”

Quantitative Finance Computational Engineering Statistics Machine Learning Computer Science
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
Dynamic Impact for Ant Colony Optimization algorithm

Dynamic Impact for Ant Colony Optimization algorithm

๋ณธ ์—ฐ๊ตฌ๋Š” ACO์˜ ํƒ์ƒ‰ ๋ฉ”์ปค๋‹ˆ์ฆ˜์— โ€˜๋™์  ์ž„ํŒฉํŠธ(Dynamic Impact)โ€™๋ผ๋Š” ์ƒˆ๋กœ์šด ๊ฐ•ํ™” ์š”์†Œ๋ฅผ ๋„์ž…ํ•จ์œผ๋กœ์จ, ๊ธฐ์กด ๋ฉ”ํƒ€ํœด๋ฆฌ์Šคํ‹ฑ์ด ์ง๋ฉดํ•˜๋˜ ๋น„์„ ํ˜• ์ž์›โ€‘์ ํ•ฉ๋„ ๊ด€๊ณ„๋ฅผ ํšจ๊ณผ์ ์œผ๋กœ ๋‹ค๋ฃจ๋Š” ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค. ๊ธฐ์กด ACO๋Š” ํŽ˜๋กœ๋ชฌ ์—…๋ฐ์ดํŠธ๊ฐ€ ํ˜„์žฌ ํ•ด์˜ ํ’ˆ์งˆ์— ๋น„๋ก€ํ•˜๋„๋ก ์„ค๊ณ„๋ผ ์žˆ์ง€๋งŒ, ํ•ด์˜ ๋ถ€๋ถ„ ๊ตฌ์กฐ ๊ฐ„ ์ƒํ˜ธ์ž‘์šฉ์„ ๊ณ ๋ คํ•˜์ง€ ๋ชปํ•œ๋‹ค๋Š” ํ•œ๊ณ„๊ฐ€ ์žˆ๋‹ค. Dynamic Impact๋Š” ๊ฐ ๊ฐœ๋ฏธ๊ฐ€ ์„ ํƒํ•œ ๊ฒฝ๋กœ์˜ ๋ถ€๋ถ„ ํ•ด ๊ฐ€ ์ „์ฒด ์ ํ•ฉ๋„์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ์ •๋Ÿ‰ํ™”ํ•˜๊ณ , ์ด๋ฅผ ํŽ˜๋กœ๋ชฌ ๊ฐ•ํ™”์— ๋ฐ˜์˜ํ•œ๋‹ค. ์ฆ‰, ํŠน์ • ์ž์› ์†Œ๋น„๊ฐ€ ์ „์ฒด ๋ชฉํ‘œ์— ๋ฏธ์น˜๋Š” โ€˜์ž„ํŒฉํŠธ

Computer Science Neural Computing
Early solar photographs by G. Roster (April 1893)

Early solar photographs by G. Roster (April 1893)

์กฐ๋ฅด์กฐ ๋กœ์Šคํ„ฐ(1843โ€‘1894)๋Š” 19์„ธ๊ธฐ ๋ง ์‚ฌ์ง„์ˆ ์„ ๊ณผํ•™ ์—ฐ๊ตฌ์— ์ ๊ทน ๋„์ž…ํ•œ ์ธ๋ฌผ๋กœ, ํŠนํžˆ ํ…”๋ ˆํฌํ† ๊ทธ๋ž˜ํ”ผ ๊ธฐ์ˆ ์„ ํ™œ์šฉํ•ด ๊ณ ๋ฐฐ์œจ ํƒœ์–‘ ๊ด€์ธก์„ ์‹œ๋„ํ–ˆ๋‹ค๋Š” ์ ์—์„œ ์˜๋ฏธ๊ฐ€ ํฌ๋‹ค. ๋กœ์Šคํ„ฐ๊ฐ€ ๋‚จ๊ธด ์„ธ ์žฅ์˜ ์‚ฌ์ง„์€ ๊ฐ๊ฐ 61๋ฐฐ, 68๋ฐฐ, 71๋ฐฐ๋ผ๋Š” ๋†’์€ ๋ฐฐ์œจ๋กœ ์ดฌ์˜๋˜์—ˆ์œผ๋ฉฐ, ์ด๋Š” ๋‹น์‹œ ์ผ๋ฐ˜์ ์ธ ์ผ๊ด‘ ์‚ฌ์ง„๋ณด๋‹ค ํ›จ์”ฌ ์ •๋ฐ€ํ•œ ํ•ด์ƒ๋„๋ฅผ ์ œ๊ณตํ•œ๋‹ค. ์‚ฌ์ง„์— ๋‚˜ํƒ€๋‚œ ํ‘์  ๊ตฐ์€ ํ˜„๋Œ€ GPR ๋ฐ์ดํ„ฐ์™€ ์ผ์น˜ํ•จ์„ ํ™•์ธํ–ˆ์œผ๋ฉฐ, ์ด๋Š” ๋กœ์Šคํ„ฐ์˜ ๊ด€์ธก์ด ๋‹จ์ˆœํ•œ ์‹œ๊ฐ์  ๊ธฐ๋ก์„ ๋„˜์–ด ๊ณผํ•™์  ์ •ํ™•์„ฑ์„ ๊ฐ–์ถ”์—ˆ์Œ์„ ๋ณด์—ฌ์ค€๋‹ค. ํ•˜์ง€๋งŒ ์‚ฌ์ง„ ์ž์ฒด์— ๋ช‡ ๊ฐ€์ง€ ํ•ด์„์ƒ์˜ ์ฃผ์˜์ ์ด ์žˆ

Physics
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Easy Acceleration with Distributed Arrays

์ด ๋…ผ๋ฌธ์—์„œ๋Š” ๋ถ„์‚ฐ ๋ฐฐ์—ด์ด ์–ด๋–ป๊ฒŒ ๊ณ ์ˆ˜์ค€ ํ”„๋กœ๊ทธ๋ž˜๋ฐ ์–ธ์–ด์™€ GPU ๊ฐ€์†๊ธฐ๋ฅผ ๋ณด์™„ํ•˜๋Š”์ง€, ๊ทธ๋ฆฌ๊ณ  ํ™•์žฅ ๊ฐ€๋Šฅํ•œ ์„ฑ๋Šฅ์„ ๋‹ฌ์„ฑํ•˜๊ธฐ ์œ„ํ•ด ๋ฐ์ดํ„ฐ ๊ตญ์†Œ์„ฑ์„ ํ™œ์šฉํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ํƒ๊ตฌํ•ฉ๋‹ˆ๋‹ค. ๋‹ค์–‘ํ•œ ํ•˜๋“œ์›จ์–ด ํ”Œ๋žซํผ์—์„œ ๋ถ„์‚ฐ ๋ฐฐ์—ด์˜ ์„ฑ๋Šฅ์„ ๋ถ„์„ํ•จ์œผ๋กœ์จ, ์ €์ž๋“ค์€ ์ˆ˜์ง์ , ์ˆ˜ํ‰์ , ์‹œ๊ฐ„์  ํ™•์žฅ์„ฑ์— ๋Œ€ํ•œ ํ†ต์ฐฐ๋ ฅ์„ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค. ํŠนํžˆ, CPU ์ฝ”์–ด, ๋…ธ๋“œ, GPU ๋…ธ๋“œ ๊ฐ„์˜ ๋ฉ”๋ชจ๋ฆฌ ๋Œ€์—ญํญ ํ–ฅ์ƒ์„ ๊ฐ•์กฐํ•˜๋ฉฐ, ์ด๋Š” ์• ํ”Œ๋ฆฌ์ผ€์ด์…˜ ๊ฐœ๋ฐœ์ž๋“ค์—๊ฒŒ ์ค‘์š”ํ•œ ์ •๋ณด๋ฅผ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค. ๋˜ํ•œ, MIT SuperCloud์˜ ๋Œ€๊ทœ๋ชจ ์ปดํ“จํŒ… ๋ฆฌ์†Œ์Šค๋ฅผ ํ™œ์šฉํ•˜์—ฌ ์‹ค์šฉ์ ์ธ ์„ฑ๋Šฅ ํ•œ๊ณ„๋ฅผ ํƒ๊ตฌํ•˜๊ณ 

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 Science Computer Vision
Editing Knowledge in Large Mathematical Corpora. A case study with   Semantic LaTeX (sTeX)

Editing Knowledge in Large Mathematical Corpora. A case study with Semantic LaTeX (sTeX)

๋ณธ ๋…ผ๋ฌธ์€ MKM ์ด๋ผ๋Š” ๋„“์€ ์—ฐ๊ตฌ ์˜์—ญ ์•ˆ์—์„œ โ€œ์ง€์‹ ํŽธ์ง‘โ€์ด๋ผ๋Š” ๊ตฌ์ฒด์ ์ธ ๋ฌธ์ œ์— ์ดˆ์ ์„ ๋งž์ถ˜๋‹ค. ์ €์ž๋Š” ๋จผ์ € ์ˆ˜ํ•™ ์ง€์‹์ด ๋ฐฉ๋Œ€ํ•œ ์–‘(์—ฐ๊ฐ„ ์•ฝ 3 ๋ฐฑ๋งŒ ํŽ˜์ด์ง€)์œผ๋กœ ์ƒ์‚ฐ๋œ๋‹ค๋Š” ํ˜„์‹ค์„ ์ œ์‹œํ•˜๊ณ , ์ธ๊ฐ„์ด ์ด๋ฅผ ๋ชจ๋‘ ์ฝ๊ณ  ์†Œํ™”ํ•˜๋Š” ๊ฒƒ์ด ๋ถˆ๊ฐ€๋Šฅํ•จ์„ ๊ฐ•์กฐํ•œ๋‹ค. ์ด๋•Œ๋ฌธ์— ์ปดํ“จํ„ฐ ๊ธฐ๋ฐ˜์˜ ๊ตฌ์กฐํ™”ยท๊ฒ€์ƒ‰ ๋„๊ตฌ๊ฐ€ ํ•„์ˆ˜์ ์ด๋ผ๋Š” ๋…ผ๋ฆฌ๋Š” ์„ค๋“๋ ฅ์ด ์žˆ๋‹ค. ํŠนํžˆ ๋‘ ๊ฐœ์˜ ๋…๋ฆฝ์ ์ธ ํ˜•์‹ํ™” ํ”„๋กœ์ ํŠธ(๊ตฌ์ฒด์ ์ธ ํ”„๋กœ์ ํŠธ ๋ช…์€ ๋…ผ๋ฌธ์— ๋ช…์‹œ๋˜์ง€ ์•Š์•˜์ง€๋งŒ, sTeX์™€ ๊ด€๋ จ๋œ ๊ธฐ์กด ์ž‘์—…์„ ์˜๋ฏธํ•จ)๋ฅผ ์‚ฌ๋ก€๋กœ ๋“ค์–ด, ์ ์ ˆํ•œ ๋„๊ตฌ๊ฐ€ ์ œ๊ณต๋  ๊ฒฝ์šฐ โ€œ์‹œ๊ฐ„โ€‘์†Œ๋ชจ์ ์ธ ์ž‘์—…โ€์ด ํฌ๊ฒŒ ๊ฐ

Computer Science Digital Libraries
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

System Quantitative Biology
Efficient Approximation of Optimal Control for Markov Games

Efficient Approximation of Optimal Control for Markov Games

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋ฌธ์ œ ์ •์˜ ์—ฐ์†์‹œ๊ฐ„ ๋งˆ์ฝ”ํ”„ ๊ฒฐ์ • ๊ณผ์ •(CTMDP)๊ณผ ์—ฐ์†์‹œ๊ฐ„ ๋งˆ์ฝ”ํ”„ ๊ฒŒ์ž„(CTMG)์€ ํ™•๋ฅ ์ ยท๋น„๊ฒฐ์ •์  ์‹œ์Šคํ…œ์„ ๋ชจ๋ธ๋งํ•˜๋Š” ๊ฐ•๋ ฅํ•œ ํ”„๋ ˆ์ž„์›Œํฌ์ด๋‹ค. ํŠนํžˆ ์‹œ๊ฐ„ ์ œํ•œ ๋„๋‹ฌ ๊ฐ€๋Šฅ์„ฑ(timeโ€‘bounded reachability) ๋ฌธ์ œ๋Š” โ€œ์ฃผ์–ด์ง„ ์‹œ๊ฐ„ T ์ด๋‚ด์— ๋ชฉํ‘œ ์ƒํƒœ G ์— ๋„๋‹ฌํ•  ํ™•๋ฅ ์„ ์ตœ๋Œ€(๋˜๋Š” ์ตœ์†Œ)ํ™”ํ•˜๋Š” ์Šค์ผ€์ค„๋Ÿฌ(๋˜๋Š” ์ „๋žต)๋ฅผ ์ฐพ๋Š” ๊ฒƒโ€์œผ๋กœ, ๋ชจ๋ธ ๊ฒ€์ฆ, ์„ฑ๋Šฅ ๋ถ„์„, ์•ˆ์ „์„ฑ ํ‰๊ฐ€ ๋“ฑ ๋‹ค์–‘ํ•œ ์‹ค์šฉ ๋ถ„์•ผ์—์„œ ํ•ต์‹ฌ์ ์ธ ๊ณผ์ œ๋กœ ์ธ์‹๋œ๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ๋Š” ์ฃผ๋กœ uniform ์Šค์ผ€์ค„๋Ÿฌ(์‹œ๊ฐ„์— ๋ฌด๊ด€ํ•œ)๋งŒ์„ ๋‹ค๋ฃจ์—ˆ์œผ๋‚˜, ์ตœ๊ทผ์—

Computer Science Systems and Control Game Theory Mathematics
Efficient Inventory Optimization of Multi Product, Multiple Suppliers   with Lead Time using PSO

Efficient Inventory Optimization of Multi Product, Multiple Suppliers with Lead Time using PSO

: ์ด ๋…ผ๋ฌธ์€ ๊ณต๊ธ‰๋ง ๊ด€๋ฆฌ์˜ ํ•ต์‹ฌ ์š”์†Œ์ธ ์žฌ๊ณ  ์ตœ์ ํ™”์— ๋Œ€ํ•œ ์‹ฌ์ธต์ ์ธ ๋ถ„์„์„ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค. ๋จผ์ €, ์ •๋ณด ํ˜๋ช…๊ณผ ๊ธ€๋กœ๋ฒŒํ™”๋กœ ์ธํ•ด ๊ณต๊ธ‰๋ง์˜ ๋ณต์žก์„ฑ์ด ์ฆ๊ฐ€ํ•˜๋ฉด์„œ ํšจ์œจ์ ์ธ ์žฌ๊ณ  ๊ด€๋ฆฌ๊ฐ€ ๋”์šฑ ์ค‘์š”ํ•ด์กŒ์Œ์„ ์ง€์ ํ•ฉ๋‹ˆ๋‹ค. ์žฌ๊ณ ๋Š” ๊ธฐ์—…์˜ ์ž๋ณธ ํˆฌ์ž์™€ ์ง์ ‘์ ์œผ๋กœ ์—ฐ๊ฒฐ๋˜์–ด ์žˆ์œผ๋ฉฐ, ์ ์ ˆํ•œ ์žฌ๊ณ  ์ˆ˜์ค€์„ ์œ ์ง€ํ•˜๋Š” ๊ฒƒ์€ ์‚ฌ์—…์˜ ์„ฑ๊ณต์— ๊ฒฐ์ •์ ์ธ ์˜ํ–ฅ์„ ๋ฏธ์นฉ๋‹ˆ๋‹ค. ์žฌ๊ณ  ๊ด€๋ฆฌ์—์„œ ๊ณ ๋ คํ•ด์•ผ ํ•  ์„ธ ๊ฐ€์ง€ ์ฃผ์š” ํ˜•ํƒœ๋Š” ๊ธฐ๋ณธ ์žฌ๊ณ , ๊ณ„์ ˆ์„ฑ ์žฌ๊ณ , ์•ˆ์ „ ์žฌ๊ณ ์ž…๋‹ˆ๋‹ค. ๊ธฐ๋ณธ ์žฌ๊ณ ๋Š” ์ˆ˜์š” ์˜ˆ์ธก์„ ๋งŒ์กฑ์‹œํ‚ค๊ธฐ ์œ„ํ•œ ํ•„์ˆ˜์ ์ธ ์žฌ๊ณ ์ด๋ฉฐ, ๊ณ„์ ˆ์„ฑ ์žฌ๊ณ ๋Š” ํŠน์ • ์‹œ๊ธฐ๋ณ„ ์ˆ˜์š” ์ฆ๊ฐ€์— ๋Œ€๋น„ํ•œ

Computer Science Neural Computing
Efficient reconfigurable regions management method for adaptive and   dynamic FPGA based systems

Efficient reconfigurable regions management method for adaptive and dynamic FPGA based systems

: ๋ณธ ๋…ผ๋ฌธ์€ FPGA ๊ธฐ๋ฐ˜ ์‹œ์Šคํ…œ์—์„œ ๋™์  ๋ถ€๋ถ„ ์žฌ๊ตฌ์„ฑ(DPR)์„ ์ ์šฉํ•˜์—ฌ ๋น„๋””์˜ค ๋ถ„์„ ์• ํ”Œ๋ฆฌ์ผ€์ด์…˜์˜ ํšจ์œจ์„ฑ์„ ๋†’์ด๋Š” ๋ฐฉ๋ฒ•์„ ์‹ฌ์ธต์ ์œผ๋กœ ๋ถ„์„ํ•ฉ๋‹ˆ๋‹ค. DPR ๊ธฐ์ˆ ์€ ์‹œ์Šคํ…œ์˜ ์œ ์—ฐ์„ฑ๊ณผ ์ ์‘์„ฑ์„ ๋†’์—ฌ์ฃผ๋Š” ํ•ต์‹ฌ ์š”์†Œ์ž…๋‹ˆ๋‹ค. ํŠนํžˆ, MPEG 7 CSD๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•œ ์ปท ๊ฐ์ง€ ์• ํ”Œ๋ฆฌ์ผ€์ด์…˜์€ ๊ฐ€๋ณ€ ๋ชจ๋“ˆ ํฌ๊ธฐ๋ฅผ ํ†ตํ•ด ๋‹ค์–‘ํ•œ ์‹œ๋‚˜๋ฆฌ์˜ค์— ๋Œ€์‘ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์ด๋Š” ํ•˜๋“œ์›จ์–ด ์ž‘์—…์ด ์‹œ์Šคํ…œ ์š”๊ตฌ ์‚ฌํ•ญ์— ๋”ฐ๋ผ ๋™์ ์œผ๋กœ ๋กœ๋“œ๋˜๊ณ  ์žฌ๋ฐฐ์น˜๋  ์ˆ˜ ์žˆ์Œ์„ ์˜๋ฏธํ•ฉ๋‹ˆ๋‹ค. DPR ๊ธฐ์ˆ ์˜ ์žฅ์ ์€ FPGA์˜ ์ผ๋ถ€๋ถ„์„ ์žฌ๊ตฌ์„ฑํ•˜๋ฉด์„œ๋„ ๋‚˜๋จธ์ง€ ์žฅ์น˜๊ฐ€ ์ค‘๋‹จ ์—†์ด ์ž‘๋™ํ•  ์ˆ˜ ์žˆ๋‹ค

Hardware Architecture Computer Science System
No Image

Efficient Vision-Language-Action Models for Embodied Manipulation: A Systematic Survey

VLA ๋ชจ๋ธ์€ ์ž์—ฐ์–ด ๋ช…๋ น๊ณผ ์‹œ๊ฐ ์ •๋ณด๋ฅผ ๋กœ๋ด‡์˜ ํ–‰๋™์œผ๋กœ ๋ณ€ํ™˜ํ•˜๋Š” ๋ฐ ์žˆ์–ด ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•ฉ๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ด๋Ÿฌํ•œ ์‹œ์Šคํ…œ์€ ์‹ค์‹œ๊ฐ„ ์„ฑ๋Šฅ์ด ์š”๊ตฌ๋˜๋Š” ๋ชจ๋ฐ”์ผ ์กฐ์ž‘๊ธฐ์™€ ๊ฐ™์€ ์—ฃ์ง€ ํ”Œ๋žซํผ์—์„œ ์ž‘๋™ํ•˜๊ธฐ ์œ„ํ•ด ํšจ์œจ์„ฑ๊ณผ ํ™•์žฅ์„ฑ์ด ํ•„์ˆ˜์ ์ž…๋‹ˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” VLA ๋ชจ๋ธ์˜ ํšจ์œจ์„ฑ์„ ํ–ฅ์ƒ์‹œํ‚ค๊ธฐ ์œ„ํ•œ ๋‹ค์–‘ํ•œ ์ ‘๊ทผ๋ฒ•์„ ๋ถ„์„ํ•ฉ๋‹ˆ๋‹ค. ๋จผ์ €, ๋ชจ๋ธ ์•„ํ‚คํ…์ฒ˜ ์ธก๋ฉด์—์„œ ๊ธฐ์กด VLA ๋ชจ๋ธ์˜ ๋ณต์žก๋„๋ฅผ ์ค„์ด๊ณ  ๊ฒฝ๋Ÿ‰ํ™”ํ•˜๋Š” ๋ฐฉ๋ฒ•์ด ์ œ์‹œ๋ฉ๋‹ˆ๋‹ค. ์ด๋Š” ๊ณ„์‚ฐ ๋น„์šฉ๊ณผ ๋ฉ”๋ชจ๋ฆฌ ์‚ฌ์šฉ๋Ÿ‰์„ ๊ฐ์†Œ์‹œ์ผœ ์‹ค์‹œ๊ฐ„ ์ถ”๋ก ์— ์ ํ•ฉํ•œ ๋ชจ๋ธ์„ ๊ฐœ๋ฐœํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ๋˜ํ•œ, ์ธ์‹ ๊ธฐ๋Šฅ ์ธก๋ฉด์—์„œ๋Š” ์‹œ๊ฐ์ 

System Model
Effort minimization in UI development by reusing existing DGML based UI   design for qualitative software development

Effort minimization in UI development by reusing existing DGML based UI design for qualitative software development

: ๋ณธ ๋…ผ๋ฌธ์€ ์†Œํ”„ํŠธ์›จ์–ด ๊ฐœ๋ฐœ ๋ถ„์•ผ์—์„œ ํšจ์œจ์„ฑ๊ณผ ์žฌ์‚ฌ์šฉ์„ฑ์— ๋Œ€ํ•œ ์ƒˆ๋กœ์šด ์ ‘๊ทผ ๋ฐฉ์‹์„ ์ œ์•ˆํ•ฉ๋‹ˆ๋‹ค. ์ผ๋ฐ˜์ ์œผ๋กœ UI ๋””์ž์ธ์€ ๋งŽ์€ ์‹œ๊ฐ„๊ณผ ๋…ธ๋ ฅ์ด ์†Œ์š”๋˜์ง€๋งŒ, ์žฌ์‚ฌ์šฉ์ด ๊ฑฐ์˜ ์ด๋ฃจ์–ด์ง€์ง€ ์•Š์Šต๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ์ €์ž๋“ค์€ UI ๋””์ž์ธ ๋ฌธ์„œ์˜ ์žฌ์‚ฌ์šฉ์„ฑ์„ ๊ฐ•์กฐํ•˜๋ฉฐ, ์ด๋ฅผ ํ†ตํ•ด ๊ฐœ๋ฐœ ๋‹จ๊ณ„์—์„œ๋„ ์žฌ์‚ฌ์šฉ์„ฑ์„ ๋‹ฌ์„ฑํ•  ์ˆ˜ ์žˆ๋‹ค๊ณ  ์ฃผ์žฅํ•ฉ๋‹ˆ๋‹ค. ๋…ผ๋ฌธ์—์„œ ์ œ์‹œํ•˜๋Š” ๋ฐฉ๋ฒ•๋ก ์€ ์ถ”๋ก ์„ ํ†ตํ•œ ๋””์ž์ธ ์žฌ์‚ฌ์šฉ์— ์ดˆ์ ์„ ๋งž์ถ”๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์ €์žฅ๋œ ๋””์ž์ธ ๋ฌธ์„œ์— ๋Œ€ํ•œ ๊ฒ€์ƒ‰๊ณผ ์ผ์น˜ ๊ณผ์ •์„ ํ†ตํ•ด ์ ํ•ฉํ•œ ๋””์ž์ธ ๋ชจ๋“ˆ์„ ์ฐพ๊ณ , ํ’ˆ์งˆ ๋งค๊ฐœ๋ณ€์ˆ˜๋ฅผ ๊ณ ๋ คํ•˜์—ฌ ์žฌ์‚ฌ์šฉ ์—ฌ๋ถ€๋ฅผ

Computer Science HCI
Electrons anomalous magnetic moment effects on electron-hydrogen   elastic collisions in the presence of a circularly polarized laser field

Electrons anomalous magnetic moment effects on electron-hydrogen elastic collisions in the presence of a circularly polarized laser field

: ์ „์ž ์ˆ˜์†Œ ํƒ„์„ฑ ์ถฉ๋Œ ๊ณผ์ •์€ ์ƒ๋Œ€๋ก ์  ํšจ๊ณผ์™€ ์ด์ƒ ์ž๊ธฐ ๋ชจ๋ฉ˜ํŠธ๋ผ๋Š” ๋‘ ๊ฐ€์ง€ ์ค‘์š”ํ•œ ์š”์†Œ๋ฅผ ๊ณ ๋ คํ•˜์—ฌ ๋ถ„์„๋˜์—ˆ์Šต๋‹ˆ๋‹ค. ๋จผ์ €, ๋””๋ž™ ๋ณผ์ฝ”ํ”„ ์ƒํƒœ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ์ด ๊ณผ์ •์„ ์„ค๋ช…ํ•จ์œผ๋กœ์จ ์ „์ž ๋“œ๋ ˆ์‹ฑ๊ณผ ๊ฐ™์€ ์ƒ๋Œ€๋ก ์  ํšจ๊ณผ๋ฅผ ๊ณ ๋ คํ•  ์ˆ˜ ์žˆ์—ˆ์Šต๋‹ˆ๋‹ค. ์ด๋Š” ์ „์ž์˜ ์›€์ง์ž„์ด ๋ ˆ์ด์ € ํ•„๋“œ์— ์˜ํ•ด ์˜ํ–ฅ์„ ๋ฐ›๋Š” ์ƒํ™ฉ์„ ๋ชจ๋ธ๋งํ•˜๋Š” ๋ฐ ๋„์›€์ด ๋ฉ๋‹ˆ๋‹ค. ๋˜ํ•œ, ์ด์ƒ ์ž๊ธฐ ๋ชจ๋ฉ˜ํŠธ์˜ ์˜ํ–ฅ์€ ์ „๊ธฐ์žฅ ๊ฐ•๋„์™€ ์ƒ๊ด€๊ด€๊ณ„๊ฐ€ ์žˆ๋‹ค๋Š” ๊ฒƒ์„ ๋ฐœ๊ฒฌํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด ์ด์ƒ ์ž๊ธฐ ๋ชจ๋ฉ˜ํŠธ๋Š” ์ „์ž ์ž๊ธฐ ๋ชจ๋ฉ˜ํŠธ ๊ฐ’์˜ ํŽธ์ฐจ์™€ ๊ด€๋ จ์ด ์žˆ์œผ๋ฉฐ, ์ด๋Š” QED ์ด๋ก ์—์„œ ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•ฉ๋‹ˆ๋‹ค. ์—ฐ๊ตฌ ๊ฒฐ๊ณผ

Physics
No Image

Endoscopic Depth Estimation Based on Deep Learning: A Survey

: ๋‚ด์‹œ๊ฒฝ ์‹ฌ๋„ ์ถ”์ •์— ๋Œ€ํ•œ ์ตœ์‹  ๋”ฅ ๋Ÿฌ๋‹ ๊ธฐ๋ฐ˜ ์ ‘๊ทผ๋ฒ•์„ ๋ถ„์„ํ•˜๊ณ , ์ด ๋ถ„์•ผ์˜ ๋ฐœ์ „๊ณผ ํ•œ๊ณ„๋ฅผ ์‚ดํŽด๋ด…๋‹ˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ ๋ฐ์ดํ„ฐ ํš๋“ ๊ณผ์ •๋ถ€ํ„ฐ ๋ฐฉ๋ฒ•๋ก ์  ์ธก๋ฉด, ๊ทธ๋ฆฌ๊ณ  ์‹ค์ œ ์ž„์ƒ ์ ์šฉ์— ์ด๋ฅด๊ธฐ๊นŒ์ง€ ํฌ๊ด„์ ์ธ ๊ฒ€ํ† ๋ฅผ ํ†ตํ•ด ํ•ด๋‹น ๊ธฐ์ˆ ์˜ ํ˜„์žฌ ์ƒํƒœ์™€ ๋ฏธ๋ž˜ ์ „๋ง์„ ์ œ์‹œํ•ฉ๋‹ˆ๋‹ค. ํŠนํžˆ, ๋‹ค์–‘ํ•œ ์‹ฌ๋„ ์ถ”์ • ๊ธฐ๋ฒ•๋“ค์„ ๋น„๊ตํ•˜๊ณ , ์ž„์ƒ ์‹œ๋‚˜๋ฆฌ์˜ค์—์„œ ์ง๋ฉดํ•˜๋Š” ๋„์ „ ๊ณผ์ œ์™€ ํ•ด๊ฒฐ์ฑ…์„ ๋…ผ์˜ํ•จ์œผ๋กœ์จ ์—ฐ๊ตฌ์ž๋“ค์—๊ฒŒ ์œ ์šฉํ•œ ํ†ต์ฐฐ๋ ฅ์„ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค.

Learning
Enhanced Optimization with Composite Objectives and Novelty Selection

Enhanced Optimization with Composite Objectives and Novelty Selection

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋ฌธ์ œ ์ •์˜ ๋‹ค๋ชฉ์  ์ง„ํ™” ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ Pareto front ๋ฅผ ํƒ์ƒ‰ํ•จ์œผ๋กœ์จ ์„œ๋กœ ๋‹ค๋ฅธ ๋ชฉํ‘œ ์‚ฌ์ด์˜ ์˜๋ฏธ ์žˆ๋Š” ํŠธ๋ ˆ์ด๋“œโ€‘์˜คํ”„๋ฅผ ์ œ๊ณตํ•œ๋‹ค. ํŠนํžˆ, ๋ณด์กฐ ๋ชฉํ‘œ(์˜ˆ: ๊ตฌ์กฐ, ๋น„์šฉ, ์ผ๊ด€์„ฑ)๋ฅผ ๋„์ž…ํ•˜๋ฉด ํƒ์ƒ‰ ์ง‘๋‹จ์ด ์ž์—ฐ์Šค๋Ÿฝ๊ฒŒ ๋‹ค์–‘ํ•œ โ€˜๋ฐœํŒโ€™๋“ค์„ ํ˜•์„ฑํ•˜๊ณ , ์ด๋Š” ๊ธฐ๋งŒ์ ์ธ ํ”ผํŠธ๋‹ˆ์Šค ์ง€ํ˜•์„ ํƒˆํ”ผํ•˜๋Š” ๋ฐ ํ•ต์‹ฌ์ ์ธ ์—ญํ• ์„ ํ•œ๋‹ค๋Š” ๊ธฐ์กด ์—ฐ๊ตฌ(Lehman & Miikkulainen, 2014; Meyerson & Miikkulainen, 2017)๋ฅผ ์ž˜ ์ •๋ฆฌํ•˜๊ณ  ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ €์ž๋Š” โ€œ๋ชจ๋“  ๋‹ค์–‘์„ฑ์ด ์œ ์šฉํ•œ ๊ฒƒ์€ ์•„๋‹ˆ๋‹คโ€๋ผ๋Š” ํ˜„์‹ค์ ์ธ ๊ด€

Computer Science Neural Computing
No Image

Enhanced Smart Contract Reputability Analysis using Multimodal Data Fusion on Ethereum

์Šค๋งˆํŠธ ๊ณ„์•ฝ์˜ ์‹ ๋ขฐ์„ฑ์„ ํ‰๊ฐ€ํ•˜๊ณ  ์‹ ๋ขฐํ•  ์ˆ˜ ์žˆ๋Š” ์ƒํƒœ๊ณ„๋ฅผ ๊ตฌ์ถ•ํ•˜๊ธฐ ์œ„ํ•œ ํ˜์‹ ์ ์ธ ์ ‘๊ทผ๋ฒ•์„ ์ œ์‹œํ•œ ๋ณธ ๋…ผ๋ฌธ์€ ๋‹ค์ค‘ ๋ชจ๋“œ ๋ฐ์ดํ„ฐ ์œตํ•ฉ ๊ธฐ๋ฒ•์— ์ดˆ์ ์„ ๋งž์ถ”๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ๊ธฐ์กด ๋ฐฉ๋ฒ•๋“ค์€ ์ฃผ๋กœ ์ฝ”๋“œ ๋ถ„์„์ด๋‚˜ ๊ฑฐ๋ž˜ ๋ฐ์ดํ„ฐ์— ์˜์กดํ•˜์—ฌ ์Šค๋งˆํŠธ ๊ณ„์•ฝ์˜ ์‹ ๋ขฐ๋„๋ฅผ ํŒ๋‹จํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ด๋Ÿฌํ•œ ๋‹จ์ผ ์†Œ์Šค ๊ธฐ๋ฐ˜์˜ ์ ‘๊ทผ๋ฒ•์€ ๋ณ€ํ™”ํ•˜๋Š” ํ™˜๊ฒฝ๊ณผ ๋ณต์žกํ•œ ๊ณ„์•ฝ ํ–‰๋™ ํŒจํ„ด์„ ํฌ์ฐฉํ•˜๋Š” ๋ฐ ํ•œ๊ณ„๊ฐ€ ์žˆ์—ˆ์Šต๋‹ˆ๋‹ค. ์ด์— ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” AI ๊ธฐ์ˆ ์„ ํ™œ์šฉํ•˜์—ฌ ์ฝ”๋“œ์™€ ๊ฑฐ๋ž˜ ๋ฐ์ดํ„ฐ๋ฅผ ํ†ตํ•ฉํ•˜๋Š” ๋‹ค์ค‘ ๋ชจ๋“œ ๋ฐ์ดํ„ฐ ์œตํ•ฉ ํ”„๋ ˆ์ž„์›Œํฌ๋ฅผ ์ œ์•ˆํ•ฉ๋‹ˆ๋‹ค. ํ•ต์‹ฌ์ ์ธ ๋ฐฉ๋ฒ•๋ก ์€ AI ๊ธฐ๋ฐ˜ ์ฝ”๋“œ ๋ถ„์„์— ์žˆ์Šต

Data Analysis
Enhancing Decision-Making in Windows PE Malware Classification During Dataset Shifts with Uncertainty Estimation

Enhancing Decision-Making in Windows PE Malware Classification During Dataset Shifts with Uncertainty Estimation

: ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” Windows PE ์•…์„ฑ์ฝ”๋“œ ๋ถ„๋ฅ˜๋ฅผ ์œ„ํ•œ ๊ธฐ์กด LightGBM(LGBM) ๊ธฐ๋ฐ˜ ํƒ์ง€๊ธฐ๋ฅผ ํ–ฅ์ƒ์‹œํ‚ค๋Š” ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•ฉ๋‹ˆ๋‹ค. ์ด๋ฅผ ์œ„ํ•ด Neural Networks(NN), PriorNet ๋ฐ Neural Network Ensembles๋ฅผ ํ†ตํ•ฉํ•˜์—ฌ ์„ธ ๊ฐ€์ง€ ๋ฒค์น˜๋งˆํฌ ๋ฐ์ดํ„ฐ์…‹์—์„œ ํ‰๊ฐ€ํ–ˆ์Šต๋‹ˆ๋‹ค. UCSB ๋ฐ์ดํ„ฐ์…‹์€ ์ฃผ๋กœ ํŒจํ‚น๋œ ์•…์„ฑ์ฝ”๋“œ๋กœ ๊ตฌ์„ฑ๋˜์–ด ์žˆ์–ด EMBER ๋ฐ BODMAS์— ๋น„ํ•ด ์ƒ๋‹นํ•œ ๋ถ„ํฌ ์ด๋™์„ ์œ ๋ฐœํ•˜๋ฉฐ, ์ด๋Š” ๋‚ด๊ตฌ์„ฑ ์ธก๋ฉด์—์„œ ๊นŒ๋‹ค๋กœ์šด ํ…Œ์ŠคํŠธ๋ฒ ๋“œ๊ฐ€ ๋ฉ๋‹ˆ๋‹ค. ์šฐ๋ฆฌ๋Š” ํ™•๋ฅ  ์ž„๊ณ„๊ฐ’ ์„ค์ •, PriorNet, ์•™์ƒ๋ธ” ๊ธฐ๋ฐ˜ ์ถ”

Data
Equivalence of the Random Oracle Model and the Ideal Cipher Model,   Revisited

Equivalence of the Random Oracle Model and the Ideal Cipher Model, Revisited

์ด ๋…ผ๋ฌธ์€ ์•”ํ˜ธํ•™์—์„œ ๊ฐ€์žฅ ๊ทผ๋ณธ์ ์ธ ๋‘ ์ด์ƒ ๋ชจ๋ธ, ์ฆ‰ ๋‚œ์ˆ˜ ์˜ค๋ผํด ๋ชจ๋ธ(ROM)๊ณผ ์ด์ƒ ์•”ํ˜ธ ๋ชจ๋ธ(idealโ€‘cipher model, ICM)์˜ ๊ด€๊ณ„๋ฅผ ์‹ฌ๋„ ์žˆ๊ฒŒ ํƒ๊ตฌํ•œ๋‹ค. ๋‘ ๋ชจ๋ธ์€ ๊ฐ๊ฐ ํ•ด์‹œ ํ•จ์ˆ˜์™€ ๋ธ”๋ก ์•”ํ˜ธ๋ฅผ ์ด์ƒํ™”ํ•œ ๊ฒƒ์œผ๋กœ, ์ˆ˜๋งŽ์€ ์‹ค์šฉ ํ”„๋กœํ† ์ฝœ์˜ ๋ณด์•ˆ ์ฆ๋ช…์— ์ „์ œ ์กฐ๊ฑด์œผ๋กœ ์‚ฌ์šฉ๋œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ โ€œ๊ตฌ๋ณ„ ๋ถˆ๊ฐ€๋Šฅ(indistinguishability)โ€๋งŒ์œผ๋กœ๋Š” ๋‘ ๋ชจ๋ธ์ด ์„œ๋กœ ์™„์ „ํžˆ ๋Œ€์ฒด ๊ฐ€๋Šฅํ•˜๋‹ค๊ณ  ๋งํ•˜๊ธฐ์— ๋ถ€์กฑํ•˜๋‹ค. ๊ณต๊ฒฉ์ž๋Š” ์–ธ์ œ๋“ ์ง€ ์›์‹œ ์˜ค๋ผํด์ด๋‚˜ ์ด์ƒ ์•”ํ˜ธ์— ์ง์ ‘ ์ ‘๊ทผํ•  ์ˆ˜ ์žˆ๊ธฐ ๋•Œ๋ฌธ์—, ์‹œ๋ฎฌ๋ ˆ์ดํ„ฐ๊ฐ€ ์ œ๊ณตํ•˜๋Š” ๊ฐ€์ƒ ์˜ค๋ผํด์ด

Cryptography and Security Mathematics Computational Complexity Model Computer Science Information Theory
Ergodic Control and Polyhedral approaches to PageRank Optimization

Ergodic Control and Polyhedral approaches to PageRank Optimization

์ด ๋…ผ๋ฌธ์€ PageRank ์ตœ์ ํ™”๋ผ๋Š” ์‹ค๋ฌด์ ยทํ•™๋ฌธ์  ๊ด€์‹ฌ์‚ฌ์— ๋Œ€ํ•ด ์—๋ฅด๊ณ ๋”• ์ œ์–ด ์ด๋ก  ๊ณผ ๋‹ค๋ฉด์ฒด ์ตœ์ ํ™” ๋ผ๋Š” ๋‘ ๊ฐ•๋ ฅํ•œ ์ˆ˜ํ•™์  ๋„๊ตฌ๋ฅผ ๊ฒฐํ•ฉํ•œ ์ ์ด ๊ฐ€์žฅ ํฐ ํ˜์‹ ์ด๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ๋“ค์€ ์ฃผ๋กœ ๋‹จ์ผ ํŽ˜์ด์ง€์— ๋Œ€ํ•œ ์ตœ์  ๋งํฌ ์‚ญ์ œยท์ถ”๊ฐ€ ์ „๋žต์„ ์ œ์‹œํ•˜๊ฑฐ๋‚˜, ์ „์—ญ์ ์ธ ์ œ์•ฝ ์—†์ด ๋ชจ๋“  ์™ธ๋ถ€ ๋งํฌ๋ฅผ ์ฐจ๋‹จํ•˜๋Š” โ€˜ํ‡ด๋ณด์  ์ „๋žตโ€™์„ ์ตœ์ ํ•ด๋กœ ๋„์ถœํ–ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์‹ค์ œ ์›น์‚ฌ์ดํŠธ ์šด์˜์ž๋Š” ์—ฌ๋Ÿฌ ํŽ˜์ด์ง€๋ฅผ ๋™์‹œ์— ๊ด€๋ฆฌํ•˜๋ฉด์„œ, ๊ฐ ํŽ˜์ด์ง€๋งˆ๋‹ค ํ•„์ˆ˜ยท์„ ํƒยท๊ธˆ์ง€ ๋งํฌ๊ฐ€ ์กด์žฌํ•˜๋Š” ๋ณตํ•ฉ์ ์ธ ์ œ์•ฝ์„ ๋งˆ์ฃผํ•œ๋‹ค. ์ €์ž๋“ค์€ ์ด๋Ÿฌํ•œ ํ˜„์‹ค์ ์ธ ์ƒํ™ฉ์„ ์ œ์•ฝ ๋งˆ์ฝ”ํ”„ ๊ฒฐ์ • ๊ณผ์ •(CMDP) ๋กœ

Computer Science Systems and Control Data Structures Mathematics
Error correcting code using tree-like multilayer perceptron

Error correcting code using tree-like multilayer perceptron

: ๋ณธ ๋…ผ๋ฌธ์€ ์˜ค๋ฅ˜ ์ˆ˜์ • ์ฝ”๋“œ ๋ถ„์•ผ์—์„œ ํŠธ๋ฆฌ ๊ตฌ์กฐ ํผ์…‰ํŠธ๋ก ์˜ ํ™œ์šฉ๊ณผ ๊ทธ ์„ฑ๋Šฅ์— ๋Œ€ํ•ด ์ง‘์ค‘์ ์œผ๋กœ ๋ถ„์„ํ•˜๊ณ  ์žˆ๋‹ค. ๋จผ์ €, ๋””์ง€ํ„ธ ๋ฐ์ดํ„ฐ ํ†ต์‹ ์—์„œ์˜ ์‹ ๋ขฐ์„ฑ ํ™•๋ณด์™€ ์ •๋ณด ์ด๋ก ์˜ ๋ฐœ์ „ ๊ณผ์ •์„ ์„œ์ˆ ํ•˜๋ฉฐ, ์˜ค๋ฅ˜ ์ˆ˜์ • ์ฝ”๋“œ์˜ ์ค‘์š”์„ฑ์„ ๊ฐ•์กฐํ•˜์˜€๋‹ค. ์ด์–ด์„œ ์„ ํ–‰ ์—ฐ๊ตฌ๋“ค์„ ์†Œ๊ฐœํ•˜๋ฉฐ, ํŠนํžˆ Hosaka et al.๊ณผ Shinzato et al.์˜ ์—ฐ๊ตฌ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ํŠธ๋ฆฌ ๊ตฌ์กฐ ํผ์…‰ํŠธ๋ก  ๋„คํŠธ์›Œํฌ๋ฅผ ์ œ์•ˆํ•˜์˜€๋‹ค. ํŠธ๋ฆฌ ๊ตฌ์กฐ ํผ์…‰ํŠธ๋ก ์€ ์ฝ”๋“œ์›Œ๋“œ ์ธ์ฝ”๋”ฉ์— ์žˆ์–ด ํšจ์œจ์ ์ธ ๋ฐฉ๋ฒ•์„ ์ œ๊ณตํ•˜๋ฉฐ, ๋‹จ์กฐ ๋ฐ ๋น„๋‹จ์กฐ ์œ ๋‹›์„ ํ™œ์šฉํ•˜์—ฌ ๋‹ค์–‘ํ•œ ๋ฐฉ์‹์˜ ์„ฑ๋Šฅ์„ ๋ถ„์„ํ•  ์ˆ˜ ์žˆ๋‹ค. ํ†ต๊ณ„ ์—ญ

Condensed Matter Computer Science Information Theory Mathematics
Etude et traitement automatique de langlais du XVIIe si`ecle :   outils morphosyntaxiques et dictionnaires

Etude et traitement automatique de langlais du XVIIe si`ecle : outils morphosyntaxiques et dictionnaires

: ์ด ๋…ผ๋ฌธ์€ 17์„ธ๊ธฐ ์˜์–ด์˜ ๋…ํŠนํ•œ ์–ธ์–ด์  ํŠน์ง•๊ณผ ๊ทธ ์‹œ๋Œ€ ๋ฌธํ—Œ์˜ ์ค‘์š”์„ฑ์„ ๊ฐ•์กฐํ•ฉ๋‹ˆ๋‹ค. 17์„ธ๊ธฐ ์˜์–ด๋Š” ์ฒ ์ž, ๊ตฌ๋ฌธ, ์–ดํœ˜ ์ธก๋ฉด์—์„œ ํ˜„๋Œ€ ์˜์–ด์™€ ๋งŽ์€ ์ฐจ์ด๊ฐ€ ์žˆ์œผ๋ฉฐ, ์ด๋Š” ์ผ๋ฐ˜ ๋…์ž๋“ค์—๊ฒŒ๋Š” ์ ‘๊ทผํ•˜๊ธฐ ์–ด๋ ค์šด ์žฅ๋ฒฝ์œผ๋กœ ์ž‘์šฉํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์—ฐ๊ตฌ์ž๋“ค์€ ์ด๋Ÿฌํ•œ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ณ , ์—ญ์‚ฌ์— ๋Œ€ํ•œ ์ดํ•ด๋ฅผ ๋•๊ธฐ ์œ„ํ•ด ์ž๋™ ๋ฒˆ์—ญ ๋„๊ตฌ๋ฅผ ๊ฐœ๋ฐœํ•˜๋Š” ๋ฐ ์ง‘์ค‘ํ–ˆ์Šต๋‹ˆ๋‹ค. ์—ฐ๊ตฌ ๋ถ„์•ผ์˜ ๋…ํŠนํ•œ ์ ์€ ์—ฌํ–‰๊ธฐ์™€ ์—ญ์‚ฌ์— ๋Œ€ํ•œ ์—ด์ •์ด ๊ฒฐํ•ฉ๋˜์–ด ์žˆ๋‹ค๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค. ํŠนํžˆ ํ”„๋ž‘์Šค์ธ๊ณผ ์˜๊ตญ์ธ ํ•™์ž๋“ค์˜ ๊ทธ๋ฆฌ์Šค ์•„๋‚˜ํ†จ๋ฆฌ์•„ ์—ฌํ–‰์„ ์žฌ์กฐ๋ช…ํ•จ์œผ๋กœ์จ, ์–ธ์–ด์  ๋ถ„์„๊ณผ ํ•จ๊ป˜ ์—ญ์‚ฌ์  ๋งฅ๋ฝ์„

Computer Science NLP
No Image

EVA: Expressive Virtual Avatars from Multi-view Videos

EVA์˜ ํ•ต์‹ฌ์€ ํ‘œํ˜„๋ ฅ ์žˆ๋Š” ํ…œํ”Œ๋ฆฟ ์ถ”์  ์•Œ๊ณ ๋ฆฌ์ฆ˜๊ณผ ๋ถ„๋ฆฌํ˜• 3D ๊ฐ€์šฐ์Šค ์™ธ๊ด€ ๋ชจ๋ธ์ž…๋‹ˆ๋‹ค. ์ด ๋‘ ๊ฐ€์ง€ ์š”์†Œ๋Š” ์•„๋ฐ”ํƒ€์— ๋Œ€ํ•œ ์™„์ „ํ•œ ์ œ์–ด์™€ ํ‘œํ˜„๋ ฅ์„ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค. ํ‘œํ˜„๋ ฅ ์žˆ๋Š” ํ…œํ”Œ๋ฆฟ ์ถ”์  ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ ๋‹ค์ค‘ ์‹œ์  ๋น„๋””์˜ค๋กœ๋ถ€ํ„ฐ ์‹ ์ฒด ์›€์ง์ž„, ์–ผ๊ตด ํ‘œ์ • ๋ฐ ๋น„๊ฐ•์ฒด ๋ณ€ํ˜•์„ ์ •ํ™•ํ•˜๊ฒŒ ๋ณต๊ตฌํ•˜๋Š” ๋ฐ ์žˆ์–ด ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•ฉ๋‹ˆ๋‹ค. ์ด๋Š” ๊ฑฐ์นœ ์ตœ์ ํ™”๋ถ€ํ„ฐ ์„ธ๋ถ€์ ์ธ ์ตœ์ ํ™”๊นŒ์ง€ ๋‹จ๊ณ„์ ์œผ๋กœ ์ง„ํ–‰๋˜๋Š” ์ตœ์ ํ™” ๊ณผ์ •์„ ํ†ตํ•ด ๋‹ฌ์„ฑ๋ฉ๋‹ˆ๋‹ค. ๋ถ„๋ฆฌํ˜• 3D ๊ฐ€์šฐ์Šค ์™ธ๊ด€ ๋ชจ๋ธ์€ ๋ชธ๊ณผ ์–ผ๊ตด์˜ ์™ธ๊ด€์„ ํšจ๊ณผ์ ์œผ๋กœ ๋ถ„๋ฆฌํ•ฉ๋‹ˆ๋‹ค. ์ด ์ ‘๊ทผ๋ฒ•์€ ๋‹จ์ผ ๊ฐ€์šฐ์Šค ์ถ”์ • ๋ฐฉ๋ฒ•๊ณผ๋Š” ๋‹ฌ๋ฆฌ, ๋‘ ๊ฐœ์˜ ๋…

Evaluation of angular dispersion for various propagation environments in   emerging 5G systems

Evaluation of angular dispersion for various propagation environments in emerging 5G systems

: 5G ์‹œ์Šคํ…œ์˜ ๋„์ž…๊ณผ ํ•จ๊ป˜, ํ†ต์‹  ๊ธฐ์ˆ ์€ ๋”์šฑ ๋ณต์žกํ•ด์ง€๊ณ  ๋‹ค์–‘ํ•œ ํ™˜๊ฒฝ์—์„œ ์ž‘๋™ํ•ด์•ผ ํ•ฉ๋‹ˆ๋‹ค. ๊ฐ๋„ ๋ถ„์‚ฐ ํ˜„์ƒ์€ ์ด๋Ÿฌํ•œ ์ƒˆ๋กœ์šด ์‹œ์Šคํ…œ์— ์ค‘์š”ํ•œ ์˜ํ–ฅ์„ ๋ฏธ์นฉ๋‹ˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ๊ฐ๋„ ๋ถ„์‚ฐ์„ ํ‰๊ฐ€ํ•˜๊ณ , ํŠนํžˆ 5G ์‹œ์Šคํ…œ์˜ ๊ด€์ ์—์„œ ๊ทธ ์ค‘์š”์„ฑ์„ ๊ฐ•์กฐํ•ฉ๋‹ˆ๋‹ค. ๊ฐ๋„ ๋ถ„์‚ฐ์€ ์ˆ˜์‹  ์‹ ํ˜ธ์— ๋‚˜ํƒ€๋‚˜๋Š” ๋‹ค์ค‘ ๊ฒฝ๋กœ ์ „ํŒŒ์˜ ํšจ๊ณผ์ž…๋‹ˆ๋‹ค. ์ด๋Š” ์‹œ๊ฐ„๊ณผ ๊ณต๊ฐ„ ์˜์—ญ์—์„œ ์‹ ํ˜ธ์˜ ์™œ๊ณก์„ ์ผ์œผํ‚ฌ ์ˆ˜ ์žˆ์œผ๋ฉฐ, ๋”ฐ๋ผ์„œ ํ†ต์‹  ์‹œ์Šคํ…œ์˜ ์„ฑ๋Šฅ์— ์ง์ ‘์ ์ธ ์˜ํ–ฅ์„ ๋ฏธ์นฉ๋‹ˆ๋‹ค. ํŠนํžˆ, 5G ์‹œ์Šคํ…œ์—์„œ๋Š” ๋น” ํ˜•์„ฑ ๊ธฐ์ˆ ๊ณผ ๋Œ€๊ทœ๋ชจ MIMO ์•ˆํ…Œ๋‚˜ ๋ฐฐ์—ด์„ ์‚ฌ์šฉํ•จ์œผ๋กœ์จ ๊ฐ๋„ ๋ถ„์‚ฐ ํ˜„์ƒ์ด ๋”

Mathematics System Computer Science Electrical Engineering and Systems Science Information Theory
Evidence for a compact jet dominating the broadband spectrum of the   black hole accretor XTE J1550-564

Evidence for a compact jet dominating the broadband spectrum of the black hole accretor XTE J1550-564

: ์ด ๋…ผ๋ฌธ์€ ๋ธ”๋ž™ํ™€ ๊ฐ•์ฐฉ ์‹œ์Šคํ…œ์˜ ๋ณต์žกํ•œ ์—ญํ•™์— ๋Œ€ํ•œ ํ†ต์ฐฐ๋ ฅ์„ ์ œ๊ณตํ•˜๋ฉฐ, ํŠนํžˆ ์ œํŠธ ์›๋ฐ˜ ์ƒํ˜ธ์ž‘์šฉ๊ณผ ๊ทธ ์˜ํ–ฅ์— ์ดˆ์ ์„ ๋งž์ถ”๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์ตœ๊ทผ ๋ช‡ ๋…„๊ฐ„ X์„  ์Œ์„ฑ๊ณ„์—์„œ ์ œํŠธ์˜ ๋ฐฉ์ถœ์„ ์‹๋ณ„ํ•˜๋ ค๋Š” ๋…ธ๋ ฅ์ด ์žˆ์—ˆ๊ณ , ์ด๋Ÿฌํ•œ ์ œํŠธ๋Š” ๊ฐ•์ฐฉ ์ค‘์ธ ๋ธ”๋ž™ํ™€ ๊ทผ์ฒ˜์—์„œ ์ƒ์„ฑ๋˜์–ด ์ด์ง„ ์‹œ์Šคํ…œ์œผ๋กœ๋ถ€ํ„ฐ ์—๋„ˆ์ง€๋ฅผ ์šด๋ฐ˜ํ•˜๋Š” ๊ฒƒ์œผ๋กœ ์•Œ๋ ค์ ธ ์žˆ์Šต๋‹ˆ๋‹ค. ์•ˆ์ •์ ์ด๊ณ  ์ง€์†์ ์ธ '์ฝคํŒฉํŠธ' ์ œํŠธ๋Š” ํ•˜๋“œ X์„  ์ƒํƒœ์—์„œ ๊ด€์ฐฐ๋˜๋ฉฐ, ์ด๋Š” ์ดˆ๋Œ€์งˆ๋Ÿ‰ ๋ธ”๋ž™ํ™€์ด ์žˆ๋Š” ํ™œ์„ฑ ์€ํ•˜ํ•ต(AGN)๊ณผ ์œ ์‚ฌํ•œ ํŠน์„ฑ์„ ๊ฐ€์ง์„ ์‹œ์‚ฌํ•ฉ๋‹ˆ๋‹ค. ์—ฐ๊ตฌ์ง„์€ XTE J1550 564 ์‹œ์Šคํ…œ์˜ 2000๋…„ ํญ๋ฐœ ๊ธฐ

Astrophysics
Evolutionary Games defined at the Network Mesoscale: The Public Goods   game

Evolutionary Games defined at the Network Mesoscale: The Public Goods game

๋ณธ ์—ฐ๊ตฌ๋Š” ์ง„ํ™” ๊ฒŒ์ž„ ์ด๋ก ๊ณผ ๋ณตํ•ฉ ๋„คํŠธ์›Œํฌ ๊ณผํ•™์„ ์œตํ•ฉํ•œ ํš๊ธฐ์ ์ธ ์ ‘๊ทผ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค. ๊ธฐ์กด์˜ 2์ธ ๊ฒŒ์ž„(์˜ˆ: ์ฃ„์ˆ˜์˜ ๋”œ๋ ˆ๋งˆ) ์ค‘์‹ฌ ์—ฐ๊ตฌ๋Š” ๋„คํŠธ์›Œํฌ ์ƒ์˜ ์Œ๋ณ„ ์ƒํ˜ธ์ž‘์šฉ๋งŒ์„ ๊ณ ๋ คํ–ˆ์œผ๋ฉฐ, ๋‹ค์ธ(mโ€‘์ธ) ๊ฒŒ์ž„์ธ ๊ณต๊ณต์žฌ ๊ฒŒ์ž„์€ ์ฐธ์—ฌ ์ง‘๋‹จ์˜ ๊ตฌ์„ฑ์ด ๊ฒฐ๊ณผ์— ๊ฒฐ์ •์ ์ธ ์˜ํ–ฅ์„ ๋ฏธ์นœ๋‹ค. ์ €์ž๋“ค์€ ์ด ์ ์„ ์ธ์‹ํ•˜๊ณ , ์‹ค์ œ ํ˜‘์—… ๋„คํŠธ์›Œํฌ์—์„œ ๊ด€์ฐฐ๋˜๋Š” โ€˜์‚ฌ๋žŒโ€‘ํ”„๋กœ์ ํŠธโ€™ ๊ด€๊ณ„๋ฅผ ์ด๋ถ„ ๊ทธ๋ž˜ํ”„ ํ˜•ํƒœ๋กœ ๋ชจ๋ธ๋งํ•˜์˜€๋‹ค. ์ด๋ถ„ ๊ทธ๋ž˜ํ”„๋Š” ๋‘ ์ข…๋ฅ˜์˜ ๋…ธ๋“œ(๊ฐœ์ธ๊ณผ ํ”„๋กœ์ ํŠธ)๋ฅผ ์—ฐ๊ฒฐํ•จ์œผ๋กœ์จ, ํ•œ ๊ฐœ์ธ์ด ๋™์‹œ์— ์—ฌ๋Ÿฌ ์ง‘๋‹จ์— ์ฐธ์—ฌํ•˜๊ฑฐ๋‚˜, ํ•˜๋‚˜์˜ ์ง‘๋‹จ์— ๋‹ค์ˆ˜์˜ ๊ฐœ์ธ์ด ์†ํ•˜๋Š” ๋ณตํ•ฉ

Physics Network Condensed Matter Social Networks Computer Science
No Image

EvoMem: Improving Multi-Agent Planning with Dual-Evolving Memory

์ด ๋…ผ๋ฌธ์€ ์ž์—ฐ์–ด ๊ณ„ํš์— ์žˆ์–ด ๊ธฐ์–ต์ด ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•œ๋‹ค๋Š” ๊ฐ€์„ค์„ ์„ธ์šฐ๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. EvoMem ํ”„๋ ˆ์ž„์›Œํฌ๋Š” ์ธ๊ฐ„๊ณผ ๊ฐ™์€ ๊ธฐ์–ต์„ ๋ชจ๋ฐฉํ•˜์—ฌ ์ œ์•ฝ ์‚ฌํ•ญ๊ณผ ํ”ผ๋“œ๋ฐฑ์„ ์ €์žฅํ•˜๊ณ  ์ถ”์ ํ•˜๋Š” ๋‘ ๊ฐ€์ง€ ๊ธฐ์–ต ๋ชจ๋“ˆ์„ ์ œ์•ˆํ•ฉ๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ์ ‘๊ทผ ๋ฐฉ์‹์€ ์—์ด์ „ํŠธ๋“ค์ด ๋ฐ˜๋ณต์ ์ธ ๋ฌธ์ œ ํ•ด๊ฒฐ ๊ณผ์ •์—์„œ ํšจ์œจ์ ์œผ๋กœ ์กฐ์ •ํ•  ์ˆ˜ ์žˆ๋„๋ก ๋•์Šต๋‹ˆ๋‹ค. ํŠนํžˆ, CMem์€ ์ž‘์—…์— ๋Œ€ํ•œ ์ดํ•ด๋ฅผ ํ–ฅ์ƒ์‹œํ‚ค๊ณ  QMem์€ ์†”๋ฃจ์…˜์˜ ์ •์ œ๋ฅผ ์œ„ํ•œ ํ”ผ๋“œ๋ฐฑ์„ ์ถ•์ ํ•จ์œผ๋กœ์จ ์—์ด์ „ํŠธ์˜ ์„ฑ๋Šฅ์„ ํ–ฅ์ƒ์‹œํ‚ต๋‹ˆ๋‹ค.

Exact prediction of S&P 500 returns

Exact prediction of S&P 500 returns

๋ณธ ๋…ผ๋ฌธ์€ ์ธ๊ตฌ ๊ตฌ์กฐ ๋ณ€ํ™”๊ฐ€ ์ฃผ์‹์‹œ์žฅ ์ˆ˜์ต๋ฅ ์„ ์˜ˆ์ธกํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ๊ฐ€์„ค์„ ์‹ค์ฆ์ ์œผ๋กœ ๊ฒ€์ฆํ•œ๋‹ค๋Š” ์ ์—์„œ ๋…์ฐฝ์ ์ด๋‹ค. ๋จผ์ € ๋ฐ์ดํ„ฐ ๊ตฌ์„ฑ ๋ฐฉ์‹์„ ์‚ดํŽด๋ณด๋ฉด, 1990โ€‘2003๋…„ ๊ตฌ๊ฐ„์˜ ์›”๊ฐ„ ์ธ๊ตฌ ์ถ”์ •์น˜๋ฅผ ์ด์šฉํ•˜๊ณ , 1990๋…„ ์ด์ „ ๊ตฌ๊ฐ„์€ 17์„ธ ์ธ๊ตฌ๋ฅผ 8๋…„ ์•ž๋‹น๊ฒจ 9์„ธ ์ธ๊ตฌ ๋ณ€๋™์„ ์ถ”์ •ํ•œ๋‹ค๋Š” โ€˜์‹œ๊ณ„์—ด ์ „์ง„โ€™ ๋ฐฉ๋ฒ•์„ ์ฑ„ํƒํ•˜์˜€๋‹ค. ์ด๋Š” ์‹ค์ œ 9์„ธ ์ธ๊ตฌ ์ž๋ฃŒ๊ฐ€ ๋ถ€์กฑํ•œ ์‹œ๊ธฐ์— ๋Œ€์ฒด ๋ณ€์ˆ˜๋ฅผ ๋งŒ๋“  ํ•ฉ๋ฆฌ์ ์ธ ์‹œ๋„์ด๋‚˜, ์ธ๊ตฌ ์„ฑ์žฅ ํŒจํ„ด์ด ์—ฐ๋ น๋ณ„๋กœ ๋™์ผํ•˜๊ฒŒ ์ „์ด๋œ๋‹ค๋Š” ์ „์ œ๊ฐ€ ๋‚ดํฌ๋˜์–ด ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ์ „์ง„๋œ ์ธ๊ตฌ ๋ณ€๋™์ด ์‹ค์ œ 9์„ธ ์ธ๊ตฌ์™€ ์–ผ๋งˆ๋‚˜ ์ผ์น˜ํ•˜๋Š”์ง€๋Š” ๋ณ„

Physics Quantitative Finance
Excerpt from the book World of Movable Objects

Excerpt from the book World of Movable Objects

์ด ์ฑ…์ด ์ œ์‹œํ•˜๋Š” ํ•ต์‹ฌ ์•„์ด๋””์–ด๋Š” โ€œ๊ฐ์ฒด์˜ ๋ฌผ๋ฆฌ์  ์ž์œ ๋„์™€ ์‚ฌ์šฉ์ž ์˜์‚ฌ๊ฒฐ์ •์˜ ์ฃผ๊ถŒ์„ ๋™์‹œ์— ํ™•๋Œ€ํ•œ๋‹คโ€ ๋Š” ์ ์ด๋‹ค. ์ „ํ†ต์ ์ธ GUI ํ”„๋ ˆ์ž„์›Œํฌ๋Š” ๊ฐœ๋ฐœ์ž๊ฐ€ UI ๋ ˆ์ด์•„์›ƒ๊ณผ ๋™์ž‘์„ ๋ฏธ๋ฆฌ ์ •์˜ํ•˜๊ณ , ์‚ฌ์šฉ์ž๋Š” ๊ทธ ํ‹€ ์•ˆ์—์„œ๋งŒ ์ž…๋ ฅ์„ ์ œ๊ณตํ•œ๋‹ค. ๋ฐ˜๋ฉด ์ €์ž๋Š” ๊ฐ์ฒด๋ฅผ ์ด๋™ยทํšŒ์ „ยทํฌ๊ธฐ ๋ณ€ํ™˜ ์ด๋ผ๋Š” ๊ธฐ๋ณธ ์—ฐ์‚ฐ์œผ๋กœ ์ถ”์ƒํ™”ํ•˜๊ณ , ์ด๋Ÿฌํ•œ ์—ฐ์‚ฐ์„ ์–ธ์ œ, ์–ด๋””์„œ, ์–ด๋–ค ์ˆœ์„œ๋กœ ์ ์šฉํ• ์ง€์— ๋Œ€ํ•œ ์„ ํƒ๊ถŒ์„ ์‚ฌ์šฉ์ž์—๊ฒŒ ์œ„์ž„ํ•œ๋‹ค. ์ด๋Š” ๋‘ ๊ฐ€์ง€ ์ค‘์š”ํ•œ ๋ณ€ํ™”๋ฅผ ์•ผ๊ธฐํ•œ๋‹ค. 1. ๋””์ž์ธโ€‘๊ตฌํ˜„ ๊ฒฝ๊ณ„์˜ ํ๋ฆผ ๊ฐœ๋ฐœ์ž๋Š” ๊ฐ์ฒด๊ฐ€ ์ œ๊ณตํ•ด์•ผ ํ•  ๋ณ€ํ™˜ ์ธํ„ฐํŽ˜์ด์Šค ๋งŒ ์ •์˜ํ•˜๋ฉด ๋œ๋‹ค. ๊ตฌ์ฒด

Computer Science HCI
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

Physics Astrophysics
Excited state calculations using phaseless auxiliary-field quantum Monte   Carlo: potential energy curves of low lying C2 singlet states

Excited state calculations using phaseless auxiliary-field quantum Monte Carlo: potential energy curves of low lying C2 singlet states

๋ณธ ๋…ผ๋ฌธ์€ ์ „์ž ๊ตฌ์กฐ ๊ณ„์‚ฐ ๋ถ„์•ผ์—์„œ ๊ฐ€์žฅ ์–ด๋ ค์šด ๋ฌธ์ œ ์ค‘ ํ•˜๋‚˜์ธ โ€˜๋“ค๋œฌ ์ƒํƒœ ์—๋„ˆ์ง€โ€™๋ฅผ ์œ„์ƒโ€‘๋ฌด์‹œ ๋ณด์กฐ์žฅ ์–‘์ž ๋ชฌํ…Œ์นด๋ฅผ๋กœ(AFQMC) ๋ฐฉ๋ฒ•์œผ๋กœ ํ•ด๊ฒฐํ•˜๋ ค๋Š” ์‹œ๋„๋ฅผ ์ƒ์„ธํžˆ ๋ณด๊ณ ํ•œ๋‹ค. ๊ธฐ์กด์˜ ๋‹ค์ฒด ์–‘์žํ™”ํ•™ ๋ฐฉ๋ฒ•์€ ๋ฐ”๋‹ฅ ์ƒํƒœ์—์„œ๋Š” CCSD(T)๋‚˜ FCI์™€ ๊ฐ™์€ ๊ณ ์ •๋ฐ€ ๋ฐฉ๋ฒ•์ด ๋„๋ฆฌ ์“ฐ์ด์ง€๋งŒ, ๋“ค๋œฌ ์ƒํƒœ์—์„œ๋Š” ๋‹ค์ค‘์ฐธ์กฐ ํŠน์„ฑ, ์ „์ž ์ƒ๊ด€์˜ ๋ณต์žก์„ฑ, ๊ทธ๋ฆฌ๊ณ  ๋ถ€ํ˜ธยท์œ„์ƒ ๋ฌธ์ œ ๋•Œ๋ฌธ์— ์ •ํ™•๋„๊ฐ€ ๊ธ‰๊ฒฉํžˆ ๋–จ์–ด์ง„๋‹ค. ํŠนํžˆ, ์ „ํ†ต์ ์ธ ํ™•์‚ฐ ๋ชฌํ…Œ์นด๋ฅผ๋กœ(DMC)๋Š” ๊ณ ์ • ๋…ธ๋“œ ๊ทผ์‚ฌ์— ํฌ๊ฒŒ ์˜์กดํ•ด ์‹œํ—˜ ํŒŒ๋™ํ•จ์ˆ˜์˜ ์งˆ์— ๋”ฐ๋ผ ๊ฒฐ๊ณผ๊ฐ€ ํฌ๊ฒŒ ๋ณ€๋™ํ•œ๋‹ค๋Š” ํ•œ๊ณ„๊ฐ€ ์žˆ๋‹ค. AF

Physics Condensed Matter
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Exemplar-Guided Planing: Enhanced LLM Agent for KGQA

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋ฌธ์ œ์  ์˜๋ฏธ ๊ฒฉ์ฐจ : ์ž์—ฐ์–ด ์งˆ์˜์™€ KG ํŠธ๋ฆฌํ”Œ ์‚ฌ์ด์˜ ํ‘œํ˜„ ์ฐจ์ด๋กœ LLM์ด ์ง์ ‘์ ์ธ ๊ณ„ํš์„ ์„ธ์šฐ๊ธฐ ์–ด๋ ค์›€. ํƒ์ƒ‰ ๋น„ํšจ์œจ : ๊ด€๊ณ„ ํƒ์ƒ‰ ๋‹จ๊ณ„์—์„œ ๋ถˆํ•„์š”ํ•œ ๊ฒฝ๋กœ๋ฅผ ๋งŽ์ด ํƒ์ƒ‰ํ•ด ์‹œ๊ฐ„ยท์ž์› ์†Œ๋ชจ๊ฐ€ ํผ. ํ•™์Šตโ€‘๋ถˆํ•„์š” ์ ‘๊ทผ์˜ ํ•œ๊ณ„ : ๊ธฐ์กด ๋ฐฉ๋ฒ•์€ ์‚ฌ์ „ ํ•™์Šต ์—†์ด LLM์— ์ „์ ์œผ๋กœ ์˜์กดํ•ด, ๊ธฐ์กด ๋ฐ์ดํ„ฐ์— ์กด์žฌํ•˜๋Š” ์„ฑ๊ณต์ ์ธ ์ถ”๋ก  ํŒจํ„ด์„ ์žฌํ™œ์šฉํ•˜์ง€ ๋ชปํ•จ. 2. ํ•ต์‹ฌ ์•„์ด๋””์–ด โ€“ Exemplarโ€‘Guided Planning (EGP) | ๊ตฌ์„ฑ ์š”์†Œ | ์—ญํ•  | ์ฃผ์š” ๊ธฐ์ˆ  | | | | | | Entity Templating |

Experiments with Different Indexing Techniques for Text Retrieval tasks   on Gujarati Language using Bag of Words Approach

Experiments with Different Indexing Techniques for Text Retrieval tasks on Gujarati Language using Bag of Words Approach

์ด ๋…ผ๋ฌธ์€ ์ธ๋„ ์„œ๋ถ€์—์„œ ์‚ฌ์šฉ๋˜๋Š” ๊ตฌ์ž๋ผํ‹ฐ์–ด๋ฅผ ๋Œ€์ƒ์œผ๋กœ, ์ „ํ†ต์ ์ธ Bagโ€‘ofโ€‘Words(BOW) ๋ชจ๋ธ์— ๋‹ค์–‘ํ•œ ์ธ๋ฑ์‹ฑ ์ „์ฒ˜๋ฆฌ ๊ธฐ๋ฒ•์„ ์ ์šฉํ–ˆ์„ ๋•Œ ๊ฒ€์ƒ‰ ์„ฑ๋Šฅ์ด ์–ด๋–ป๊ฒŒ ๋ณ€ํ•˜๋Š”์ง€๋ฅผ ์ฒด๊ณ„์ ์œผ๋กœ ๊ฒ€์ฆํ•œ๋‹ค๋Š” ์ ์—์„œ ์˜๋ฏธ๊ฐ€ ํฌ๋‹ค. ๊ตฌ์ž๋ผํ‹ฐ์–ด๋Š” ์–ด๋ฏธ ๋ณ€ํ™”์™€ ์ ‘์‚ฌ ํ™œ์šฉ์ด ํ™œ๋ฐœํ•œ ๊ต์ฐฉ์–ด์ด๋ฉฐ, ์˜์–ด์™€ ๊ฐ™์€ ๋ถ„์„์  ์–ธ์–ด์— ๋น„ํ•ด ํ˜•ํƒœ์†Œ ๋ถ„์„์ด ์–ด๋ ค์šด ํŠน์„ฑ์„ ๊ฐ€์ง„๋‹ค. ๋”ฐ๋ผ์„œ ๋‹จ์ˆœํžˆ ์›์‹œ ํ† ํฐ์„ ์ƒ‰์ธ์— ์‚ฌ์šฉํ•˜๋ฉด ๋™์ผ ์˜๋ฏธ๋ฅผ ๊ฐ€์ง„ ์„œ๋กœ ๋‹ค๋ฅธ ํ˜•ํƒœ์˜ ๋‹จ์–ด๊ฐ€ ๋ณ„๊ฐœ์˜ ์ธ๋ฑ์Šค๋กœ ์ฒ˜๋ฆฌ๋ผ ๊ฒ€์ƒ‰ ํšจ์œจ์ด ์ €ํ•˜๋  ์œ„ํ—˜์ด ์žˆ๋‹ค. ๋…ผ๋ฌธ์€ ์ด๋Ÿฌํ•œ ์–ธ์–ด์  ํŠน์„ฑ์„ ๊ณ ๋ คํ•ด ๋ถˆ์šฉ์–ด(st

Computer Science Information Retrieval Digital Libraries
Exploring Hadron Physics in Black Hole Formations: a New Promising   Target of Neutrino Astronomy

Exploring Hadron Physics in Black Hole Formations: a New Promising Target of Neutrino Astronomy

: ์ด ๋…ผ๋ฌธ์€ ์ฒœ์ฒด๋ฌผ๋ฆฌํ•™์—์„œ ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•˜๋Š” ๊ทน๋‹จ์ ์ธ ๋ฌผ๋ฆฌ ์กฐ๊ฑด ํ•˜์—์„œ์˜ ํ•ต์ž ๋ฌผ๋ฆฌํ•™์„ ํƒ๊ตฌํ•˜๋Š” ๋ฐ ์ดˆ์ ์„ ๋งž์ถ”๊ณ  ์žˆ๋‹ค. ํŠนํžˆ, ํ•ญ์„ฑ์˜ ์ผ์ƒ ๋ง๊ธฐ์— ์ผ์–ด๋‚˜๋Š” ์ค‘๋ ฅ ๋ถ•๊ดด์™€ ๊ทธ ๊ฒฐ๊ณผ๋กœ ๋ฐœ์ƒํ•˜๋Š” ๋ธ”๋ž™ํ™€ ํ˜•์„ฑ์— ๊ด€์‹ฌ์„ ๊ธฐ์šธ์ธ๋‹ค. ์ด๋Ÿฌํ•œ ์‚ฌ๊ฑด์€ ์•„์ง ๊ด€์ธก๋˜์ง€ ์•Š์•˜์ง€๋งŒ, ์ถ”์ •๋˜๋Š” ๋ธ”๋ž™ํ™€ ํ›„๋ณด๋“ค์ด ๋ฐœ๊ฒฌ๋˜๋ฉด์„œ ์—ฐ๊ตฌ์˜ ์ค‘์š”์„ฑ์ด ๋”์šฑ ๋ถ€๊ฐ๋˜๊ณ  ์žˆ๋‹ค. ์ด์ „ ์—ฐ๊ตฌ์—์„œ ์ œ์•ˆ๋œ '์‹คํŒจํ•œ ์ดˆ์‹ ์„ฑ' ๊ฐœ๋…์„ ๋ฐ”ํƒ•์œผ๋กœ, ์ด ๋…ผ๋ฌธ์—์„œ๋Š” ์ค‘์„ฑ๋ฏธ์†Œ ๋ฐฉ์ถœ ์ง€์† ์‹œ๊ฐ„์ด EOS(ํ•ต์ž ๋ฐฉ์ •์‹ ์ƒํƒœ)์˜ ๊ฐ•์„ฑ์— ๋ฏผ๊ฐํ•˜๋‹ค๋Š” ๊ฒƒ์„ ๋ณด์—ฌ์ค€๋‹ค. ์ด๋Š” ์‹คํŒจํ•œ ์ดˆ์‹ ์„ฑ์˜ ๊ด€์ธก์„ ํ†ตํ•ด ๋ฐ€๋„

NUCL-TH Astrophysics HEP-PH
No Image

Extreme Event Precursor Prediction in Turbulent Dynamical Systems via CNN-Augmented Recurrence Analysis

์ด ๋…ผ๋ฌธ์€ ๊ทนํ•œ ์‚ฌ๊ฑด์˜ ์„ ํ–‰ ์ง€ํ‘œ๋ฅผ ์˜ˆ์ธกํ•˜๋Š” ์ƒˆ๋กœ์šด ๋ฐฉ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ์ด๋Š” ์œ„์ƒ ๊ณต๊ฐ„ ์žฌ๊ตฌ์„ฑ๊ณผ ์žฌ๋ฐœ์ƒ ํ–‰๋ ฌ, ๊ทธ๋ฆฌ๊ณ  ํ•ฉ์„ฑ๊ณฑ ์‹ ๊ฒฝ๋ง์„ ํ†ตํ•ฉํ•˜์—ฌ ๋‚œ๋ฅ˜ ์‹œ์Šคํ…œ์—์„œ ๊ทนํ•œ ์‚ฌ๊ฑด์„ ๋ฏธ๋ฆฌ ๊ฐ์ง€ํ•  ์ˆ˜ ์žˆ๊ฒŒ ํ•œ๋‹ค. ํŠนํžˆ, ์ž„๊ณ„๊ฐ’์ด ์—†๋Š” ๋ถ„๋ฅ˜ ์ „๋žต์„ ํ†ตํ•ด ์ฃผ๊ด€์ ์ธ ๋งค๊ฐœ๋ณ€์ˆ˜ ํŠœ๋‹์˜ ํ•„์š”์„ฑ์„ ์—†์• ๊ณ , ์ ์€ ์–‘์˜ ๋ฐ์ดํ„ฐ๋กœ ํšจ์œจ์ ์ธ ํ›ˆ๋ จ์„ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•˜๋ฉฐ, ๋‹ค์–‘ํ•œ ์‹œ์Šคํ…œ์— ์ผ๋ฐ˜ํ™”ํ•  ์ˆ˜ ์žˆ๋Š” ๋Šฅ๋ ฅ์„ ๋ณด์—ฌ์ค€๋‹ค. ์ด๋Ÿฌํ•œ ์ ‘๊ทผ๋ฒ•์€ ๊ทนํ•œ ์‚ฌ๊ฑด์˜ ์˜ˆ์ธก๊ณผ ๊ด€๋ จ๋œ ๊ธฐ์กด ๋ฐฉ๋ฒ•๋“ค์˜ ํ•œ๊ณ„๋ฅผ ๊ทน๋ณตํ•˜๊ณ , ๋” ๋‚˜์€ ์„ฑ๋Šฅ๊ณผ ์‹ ๋ขฐ๋„๋ฅผ ์ œ๊ณตํ•œ๋‹ค.

System Analysis
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FairyGen: Storied Cartoon Video from a Single Child-Drawn Character

: FairyGen ์‹œ์Šคํ…œ์€ ์–ด๋ฆฐ์ด๋“ค์˜ ๊ทธ๋ฆผ์œผ๋กœ๋ถ€ํ„ฐ ์Šคํ† ๋ฆฌํ…”๋ง ์นดํˆฐ ์˜์ƒ์„ ์ƒ์„ฑํ•˜๋Š” ๋…ํŠนํ•œ ์ ‘๊ทผ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค. ์ด ์‹œ์Šคํ…œ์€ ์บ๋ฆญํ„ฐ ๋ชจ๋ธ๋ง๊ณผ ๋ฐฐ๊ฒฝ ์ƒ์„ฑ์„ ๋ถ„๋ฆฌํ•จ์œผ๋กœ์จ, ์บ๋ฆญํ„ฐ์˜ ๊ณ ์œ ํ•œ ์˜ˆ์ˆ ์  ์Šคํƒ€์ผ์„ ์œ ์ง€ํ•˜๋ฉด์„œ๋„ ์‹œ๊ฐ์ ์œผ๋กœ ๋งค๋ ฅ์ ์ธ ์žฅ๋ฉด์„ ๋งŒ๋“ค์–ด๋‚ธ๋‹ค. ๋˜ํ•œ ์‹œ๋„ค๋งˆํ‹ฑ ์ƒท ๋””์ž์ธ์„ ํ†ตํ•ด ์˜ํ™” ๊ฐ™์€ ํ’ˆ์งˆ์˜ ์˜์ƒ์„ ๊ตฌํ˜„ํ•œ๋‹ค. MLLM์„ ์‚ฌ์šฉํ•˜์—ฌ ์ƒ์„ฑ๋œ ์Šคํ† ๋ฆฌ๋ณด๋“œ๋Š” ๊ตฌ์กฐํ™”๋œ ์ด์•ผ๊ธฐ ํ๋ฆ„์„ ์ œ๊ณตํ•˜๋ฉฐ, ์ด๋Š” ์• ๋‹ˆ๋ฉ”์ด์…˜ ์ œ์ž‘ ๊ณผ์ •์—์„œ ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•œ๋‹ค. ์Šคํƒ€์ผ ์ „ํŒŒ ์–ด๋Œ‘ํ„ฐ๋Š” ์บ๋ฆญํ„ฐ์˜ ์Šคํƒ€์ผ์„ ํฌ์ฐฉํ•˜๊ณ  ์ด๋ฅผ ๋ฐฐ๊ฒฝ์— ์ ์šฉํ•˜์—ฌ ์‹œ๊ฐ์  ์ผ๊ด€์„ฑ์„ ์œ ์ง€ํ•˜๋Š”

Feedforward 3D Editing via Text-Steerable Image-to-3D

Feedforward 3D Editing via Text-Steerable Image-to-3D

: Steer3D๋Š” ์ด๋ฏธ ํ›ˆ๋ จ๋œ ์ด๋ฏธ์ง€ ํˆฌ 3D ์ƒ์„ฑ ๋ชจ๋ธ์— ํ…์ŠคํŠธ ๊ฐ€์ด๋“œ ๊ธฐ๋Šฅ์„ ์ถ”๊ฐ€ํ•˜์—ฌ, 3D ์ž์‚ฐ์„ ํŽธ์ง‘ํ•  ์ˆ˜ ์žˆ๊ฒŒ ํ•ฉ๋‹ˆ๋‹ค. ControlNet์˜ ์•„ํ‚คํ…์ฒ˜๋ฅผ ํ™œ์šฉํ•˜์—ฌ ์ด๋ฏธ์ง€ ํˆฌ 3D ์‚ฌ์ „ ํ•™์Šต์—์„œ ์–ป์€ ๋ชจ์–‘๊ณผ ๊ฐ์ฒด ์šฐ์„ ์ˆœ์œ„๋ฅผ ์ด์šฉํ•ฉ๋‹ˆ๋‹ค. ๋˜ํ•œ ์ž๋™ ๋ฐ์ดํ„ฐ ์—”์ง„์„ ๊ตฌ์ถ•ํ•˜์—ฌ ๋‹ค์–‘ํ•œ ๊ธฐํ•˜ํ•™์  ๋ฐ ์งˆ๊ฐ ํŽธ์ง‘ ์Œ์„ ์ƒ์„ฑํ•˜๊ณ , ๋‘ ๋‹จ๊ณ„ ํ›ˆ๋ จ ๋ ˆ์‹œํ”ผ๋ฅผ ํ†ตํ•ด ํ๋ฆ„ ์ผ์น˜ ํ›ˆ๋ จ๊ณผ ์ง์ ‘ ์„ ํ˜ธ๋„ ์ตœ์ ํ™”๋ฅผ ํ†ตํ•ฉํ•ฉ๋‹ˆ๋‹ค. Steer3D๋Š” ์–ธ์–ด ์ง€์‹œ๋ฅผ ์ž˜ ๋”ฐ๋ฅด๊ณ  ์›๋ž˜ 3D ์ž์‚ฐ๊ณผ์˜ ์ผ๊ด€์„ฑ์„ ์œ ์ง€ํ•˜๋ฉด์„œ๋„ ๋งค์šฐ ๋น ๋ฅธ ์†๋„๋ฅผ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค.

Fermi Gamma-ray Space Telescope: High-Energy Results from the First Year

Fermi Gamma-ray Space Telescope: High-Energy Results from the First Year

๋ณธ ๋ฆฌ๋ทฐ๋Š” Fermiโ€‘LAT์™€ GBM์ด 1๋…„๊ฐ„ ์ˆ˜ํ–‰ํ•œ ๊ด€์ธก ๊ฒฐ๊ณผ๋ฅผ ์ข…ํ•ฉ์ ์œผ๋กœ ํ‰๊ฐ€ํ•œ๋‹ค. ์ฒซ์งธ, LAT๋Š” ๊ธฐ์กด ฮณโ€‘ray ํƒ์‚ฌ์„ (EGRET ๋“ฑ)์— ๋น„ํ•ด ์œ ํšจ ๋ฉด์ ๊ณผ ์‹œ์•ผ๊ฐ€ ํฌ๊ฒŒ ํ™•๋Œ€๋˜์–ด, ํ•˜๋ฃจ ํ‰๊ท  2 ์ฒœ๊ฐœ์˜ ๊ด‘์ž๋ฅผ ์ˆ˜์ง‘ํ•  ์ˆ˜ ์žˆ๋‹ค. ์‹ค๋ฆฌ์ฝ˜ ์ŠคํŠธ๋ฆฝ ๊ฒ€์ถœ๊ธฐ๋ฅผ ์ด์šฉํ•œ ์ž…์ž ์ถ”์  ๊ธฐ์ˆ ์€ ๊ฐ๋„ ํ•ด์ƒ๋„๋ฅผ 0.1ยฐ ์ˆ˜์ค€์œผ๋กœ ํ–ฅ์ƒ์‹œ์ผฐ์œผ๋ฉฐ, ๋ฐฐ๊ฒฝ ์–ต์ œ ํšจ์œจ๋„ 10๋ฐฐ ์ด์ƒ ๊ฐœ์„ ๋˜์—ˆ๋‹ค. ์ด๋Ÿฌํ•œ ์„ฑ๋Šฅ ํ–ฅ์ƒ์€ ๋ฏธํ™•์ธ ๊ณ ์—๋„ˆ์ง€ ฮณโ€‘ray ์ฒœ์ฒด์˜ ์ •ํ™•ํ•œ ์œ„์น˜ ์ธก์ •๊ณผ ์ŠคํŽ™ํŠธ๋Ÿผ ๋ถ„์„์„ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•˜์—ฌ, EGRET ์นดํƒˆ๋กœ๊ทธ์— ๋‚จ์•„ ์žˆ๋˜ โ€˜๋ฏธํ™•์ธ ์†Œ์Šคโ€™๋“ค์„ ๋Œ€๋ถ€๋ถ„ ํ™•

Astrophysics HEP-EX
FIBER: A Multilingual Evaluation Resource for Factual Inference Bias

FIBER: A Multilingual Evaluation Resource for Factual Inference Bias

: ๋Œ€๊ทœ๋ชจ ์–ธ์–ด ๋ชจ๋ธ(LLM)์˜ ์‹ ๋ขฐ์„ฑ๊ณผ ํŽธํ–ฅ์— ๋Œ€ํ•œ ์šฐ๋ ค๊ฐ€ ์žˆ์Šต๋‹ˆ๋‹ค. ์‚ฌ์‹ค ์ง€์‹ ํƒ์ƒ‰์€ ์ด๋Ÿฌํ•œ ์ธก๋ฉด์„ ํ‰๊ฐ€ํ•˜๋Š” ์ฒด๊ณ„์ ์ธ ๋ฐฉ๋ฒ•์„ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค. FIBER๋Š” ๋‹จ์ผ ๋ฐ ๋‹ค์ค‘ ์—”ํ‹ฐํ‹ฐ ์„ค์ •์—์„œ ์‚ฌ์‹ค ์ง€์‹์„ ํ‰๊ฐ€ํ•˜๊ธฐ ์œ„ํ•œ ์ƒˆ๋กœ์šด ๋‹ค๊ตญ์–ด ๋ฐ์ดํ„ฐ ์„ธํŠธ์ž…๋‹ˆ๋‹ค. ์ด ๋ฐ์ดํ„ฐ ์„ธํŠธ๋Š” ์˜์–ด, ์ดํƒˆ๋ฆฌ์•„์–ด, ํ„ฐํ‚ค์–ด๋กœ ๋œ ๋ฌธ์žฅ ์™„์„ฑ, ์งˆ๋ฌธ ๋‹ต๋ณ€ ๋ฐ ๊ฐ์ฒด ์ˆ˜ ์˜ˆ์ธก ์ž‘์—…์„ ํฌํ•จํ•ฉ๋‹ˆ๋‹ค. ์šฐ๋ฆฌ๋Š” ํ”„๋กฌํ”„ํŠธ ์–ธ์–ด๊ฐ€ ์ถ”๋ก  ํŽธํ–ฅ์„ ์œ ๋„ํ•˜๋Š”์ง€, ๊ทธ๋ฆฌ๊ณ  LLM์ด ๋‹จ์ผ ์—”ํ‹ฐํ‹ฐ์™€ ๋‹ค์ค‘ ์—”ํ‹ฐํ‹ฐ ์งˆ๋ฌธ์— ์–ด๋–ป๊ฒŒ ์ˆ˜ํ–‰๋˜๋Š”์ง€๋ฅผ ์กฐ์‚ฌํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ฒฐ๊ณผ๋Š” ํ”„๋กฌํ”„ํŠธ์˜ ์–ธ์–ด๊ฐ€ ํŠนํžˆ ํ•ด๋‹น ์–ธ์–ด๋ฅผ ์‚ฌ์šฉํ•˜

Fine-tuning the Ant Colony System algorithm through Particle Swarm   Optimization

Fine-tuning the Ant Colony System algorithm through Particle Swarm Optimization

๋ณธ ๋…ผ๋ฌธ์€ ๋ฉ”ํƒ€ํœด๋ฆฌ์Šคํ‹ฑ ๋ถ„์•ผ์—์„œ โ€˜ํŒŒ๋ผ๋ฏธํ„ฐ ๋ฏธ์„ธ์กฐ์ •(Fineโ€‘Tuning)โ€™์ด๋ผ๋Š” ํ•ต์‹ฌ ๋ฌธ์ œ์— ์ ‘๊ทผํ•œ๋‹ค๋Š” ์ ์—์„œ ํ•™์ˆ ์ ยท์‹ค์šฉ์  ์˜์˜๊ฐ€ ํฌ๋‹ค. ACS๋Š” ๊ฐœ๋ฏธ์˜ ํŽ˜๋กœ๋ชฌ ๊ฒฝ๋กœ ํƒ์ƒ‰ ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•˜์—ฌ TSP์™€ ๊ฐ™์€ NPโ€‘Hard ๋ฌธ์ œ์— ๋Œ€ํ•ด ์ข‹์€ ๊ทผ์‚ฌํ•ด๋ฅผ ์ œ๊ณตํ•˜์ง€๋งŒ, ํƒ์ƒ‰ ๊ฐ•๋„์™€ ์ˆ˜๋ ด ์†๋„๋Š” qโ‚€, ฮฑ, ฯ, ฮฒ, ฯ† ๋“ฑ ๋‹ค์„ฏ ๊ฐœ์˜ ์‹ค์ˆ˜ยท์ •์ˆ˜ ํŒŒ๋ผ๋ฏธํ„ฐ์— ํฌ๊ฒŒ ์˜์กดํ•œ๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ์—์„œ๋Š” ๊ฒฝํ—˜์  ๊ทœ์น™์ด๋‚˜ ์ œํ•œ๋œ ์‹คํ—˜ ์„ค๊ณ„์— ์˜์กดํ•ด ํŒŒ๋ผ๋ฏธํ„ฐ๋ฅผ ์„ค์ •ํ–ˆ์œผ๋ฉฐ, ์ด๋Š” ์ƒˆ๋กœ์šด ์ธ์Šคํ„ด์Šค์— ์ ์šฉํ•  ๋•Œ ์„ฑ๋Šฅ ์ €ํ•˜ ์œ„ํ—˜์„ ๋‚ดํฌํ•œ๋‹ค. ์ด์— ์ €์ž๋“ค์€ ์ „์—ญ

Computer Science Neural Computing System Mathematics
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FineSkiing: A Fine-grained Benchmark for Skiing Action Quality Assessment

FineSkiing์€ ์Šคํ‚ค ๋™์ž‘์˜ ํ’ˆ์งˆ์„ ํ‰๊ฐ€ํ•˜๊ธฐ ์œ„ํ•œ ๋ฏธ์„ธ ์กฐ์ • ๋ฒค์น˜๋งˆํฌ๋กœ์„œ, ๊ธฐ์กด AQA ๋ฐ์ดํ„ฐ์…‹์˜ ํ•œ๊ณ„๋ฅผ ๊ทน๋ณตํ•˜๊ณ  ๋” ๋‚˜์€ ํ‰๊ฐ€๋ฅผ ์œ„ํ•ด ๊ณ ์•ˆ๋˜์—ˆ๋‹ค. ์ด ๋ฐ์ดํ„ฐ์…‹์€ ์Šคํ‚ค ๋™์ž‘์— ๋Œ€ํ•œ ์„ธ๋ถ€์ ์ธ ๋ถ€๋ถ„ ์ ์ˆ˜์™€ ๊ฐ์  ํ•ญ๋ชฉ์„ ์ œ๊ณตํ•˜์—ฌ ๋ณด๋‹ค ์ •๊ตํ•œ ํ‰๊ฐ€๋ฅผ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•œ๋‹ค. JudgeMind๋Š” ์ „๋ฌธ ์‹ฌํŒ์˜ ํŒ๋‹จ ๊ณผ์ •์„ ๋ชจ๋ฐฉํ•˜์—ฌ ์ •ํ™•์„ฑ๊ณผ ์‹ ๋ขฐ์„ฑ์„ ํ–ฅ์ƒ์‹œํ‚ค๋Š” ํ˜์‹ ์ ์ธ ๋ฐฉ๋ฒ•์ด๋‹ค. ๋น„๋””์˜ค๋ฅผ ์—ฌ๋Ÿฌ ๋‹จ๊ณ„๋กœ ๋‚˜๋ˆ„๊ณ  ๊ฐ ๋‹จ๊ณ„์— ์ ์ˆ˜๋ฅผ ๋งค๊ธฐ๋Š” ์ ‘๊ทผ ๋ฐฉ์‹์„ ํ†ตํ•ด ๋™์ž‘์˜ ๋‹ค์–‘ํ•œ ์ธก๋ฉด์„ ๊ณ ๋ คํ•  ์ˆ˜ ์žˆ๋‹ค. ๋˜ํ•œ, ์ œ์•ˆ๋œ ๋ชจ๋“ˆ์€ ํ•ต์‹ฌ ์˜์—ญ์— ๋Œ€ํ•œ ์ธ์‹์„ ๋†’์ด๊ณ  ์นด๋ฉ”๋ผ

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FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets

1. ์—ฐ๊ตฌ์˜ ์˜์˜์™€ ๊ธฐ์—ฌ | ๊ตฌ๋ถ„ | ๋‚ด์šฉ | ํ‰๊ฐ€ | | | | | | ๋ฐ์ดํ„ฐ | 19๊ฐœ ๋ฐ์ดํ„ฐ์…‹ ์ค‘ 4๊ฐœ๋Š” ๊ธฐ์กด์— ์—†๋˜ XBRL ๊ธฐ๋ฐ˜ ๋ฐ์ดํ„ฐ์…‹์œผ๋กœ, SEC 10โ€‘Kยท10โ€‘Q ๋“ฑ ์‹ค์ œ ๊ธฐ์—… ๋ณด๊ณ ์„œ๋ฅผ ํ™œ์šฉ | ๋†’์Œ โ€“ ๊ธˆ์œต ๋ถ„์•ผ ํŠน์ˆ˜ ๋ฐ์ดํ„ฐ ๋ถ€์กฑ ๋ฌธ์ œ๋ฅผ ํฌ๊ฒŒ ์™„ํ™” | | ๋ชจ๋ธ | 5๊ฐ€์ง€ ์ตœ์‹  LLM(์˜ˆ: Llamaโ€‘2โ€‘7B, Mistralโ€‘7B, Falconโ€‘7B ๋“ฑ)๊ณผ 5๊ฐ€์ง€ LoRA ๋ณ€ํ˜•(LoRA, AdaLoRA, IAยณ ๋“ฑ) ์กฐํ•ฉ | ๋‹ค์–‘์„ฑ ํ™•๋ณด โ€“ ๋ชจ๋ธยท๋ฐฉ๋ฒ• ๊ฐ„ ๋น„๊ต๊ฐ€ ๊ฐ€๋Šฅ | | ํ‰๊ฐ€ ์ง€ํ‘œ | ์ •ํ™•๋„ยทF1ยทBERTScore

Data
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FinTSB: A Comprehensive and Practical Benchmark for Financial Time Series Forecasting

: ๊ธˆ์œต ์‹œ๊ฐ„ ์‹œ๋ฆฌ์ฆˆ ์˜ˆ์ธก์€ ๋ณต์žกํ•œ ๋ถ„์•ผ๋กœ, ๋‹ค์–‘ํ•œ ๋„์ „ ๊ณผ์ œ์™€ ํ•œ๊ณ„์ ์„ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. FinTSB๋Š” ์ด๋Ÿฌํ•œ ๋ฌธ์ œ์ ๋“ค์„ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ์ œ์•ˆ๋œ ๋ฒค์น˜๋งˆํฌ์ด๋‹ค. ์ด ๋ฒค์น˜๋งˆํฌ๋Š” ์„ธ ๊ฐ€์ง€ ์ฃผ์š” ์ธก๋ฉด์—์„œ ๊ธฐ์กด ํ‰๊ฐ€ ๋ฐฉ๋ฒ•์˜ ํ•œ๊ณ„๋ฅผ ๊ทน๋ณตํ•˜๊ณ ์ž ํ•œ๋‹ค: ๋‹ค์–‘์„ฑ ๊ฒฉ์ฐจ, ํ‘œ์ค€ํ™” ๋ถ€์กฑ, ๊ทธ๋ฆฌ๊ณ  ์‹ค์ œ ์„ธ๊ณ„์™€์˜ ๋ถˆ์ผ์น˜. FinTSB๋Š” ๋‹ค์–‘ํ•œ ์ฃผ์‹ ์ด๋™ ํŒจํ„ด์„ ํฌ๊ด„์ ์œผ๋กœ ๋‹ค๋ฃจ๊ณ , ํ†ต์ผ๋œ ํ‰๊ฐ€ ํ”„๋กœํ† ์ฝœ์„ ์ œ๊ณตํ•˜๋ฉฐ, ์‹ค์ œ ๊ฑฐ๋ž˜ ์‹œ๋‚˜๋ฆฌ์˜ค๋ฅผ ๊ณ ๋ คํ•˜์—ฌ ์‹ค์šฉ์ ์ธ ์ ์šฉ ๊ฐ€๋Šฅ์„ฑ์„ ๋†’์ธ๋‹ค. ๋˜ํ•œ, ์‚ฌ์šฉ์ž ์นœํ™”์ ์ธ ํŒŒ์ดํ”„๋ผ์ธ์„ ํ†ตํ•ด ์—ฐ๊ตฌ์ž๋“ค์ด ์‰ฝ๊ฒŒ ์ ‘๊ทผํ•˜๊ณ  ์‹คํ—˜ํ•  ์ˆ˜ ์žˆ๋„๋ก ํ•œ

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FIXME: Towards End-to-End Benchmarking of LLM-Aided Design Verification

FIXME ํ”„๋ ˆ์ž„์›Œํฌ๋Š” ๊ธฐ๋Šฅ ๊ฒ€์ฆ์˜ ๋‹ค์–‘ํ•œ ์ธก๋ฉด์„ ํฌ๊ด„์ ์œผ๋กœ ๋‹ค๋ฃจ๊ธฐ ์œ„ํ•ด ์„ธ ๊ฐ€์ง€ ๋‚œ์ด๋„ ์ˆ˜์ค€๊ณผ ์—ฌ์„ฏ ๊ฐœ์˜ ํ•˜์œ„ ๋„๋ฉ”์ธ์„ ๋„์ž…ํ–ˆ๋‹ค. ์ด๋Š” ์„ค๊ณ„ ๋ผ์ดํ”„์‚ฌ์ดํด ์ „๋ฐ˜์— ๊ฑธ์ณ LLM์˜ ์„ฑ๋Šฅ์„ ํ‰๊ฐ€ํ•˜๊ณ , ๊ฐ ๋‹จ๊ณ„์—์„œ ์ง๋ฉดํ•˜๋Š” ๋„์ „ ๊ณผ์ œ๋ฅผ ์‹๋ณ„ํ•˜๊ธฐ ์œ„ํ•œ ๊ฒƒ์ด๋‹ค. ๋‚œ์ด๋„ ์ˆ˜์ค€์€ ์ดˆ๊ธ‰, ์ค‘๊ธ‰, ๊ณ ๊ธ‰์œผ๋กœ ๋‚˜๋‰˜๋ฉฐ, ๊ฐ๊ฐ ๊ธฐ๋ณธ์ ์ธ ๊ธฐ๋Šฅ ๊ฒ€์ฆ๋ถ€ํ„ฐ ๋ณต์žกํ•œ ์‹œ์Šคํ…œ ๋ ˆ๋ฒจ ๊ฒ€์ฆ๊นŒ์ง€๋ฅผ ๋‹ค๋ฃฌ๋‹ค. ํ•˜์œ„ ๋„๋ฉ”์ธ์—๋Š” ํ…Œ์ŠคํŠธ ์ผ€์ด์Šค ์ƒ์„ฑ, ๋ฒ„๊ทธ ๋””ํ…์…˜, ์ปค๋ฒ„๋ฆฌ์ง€ ๋ถ„์„, ๋ฆฌํฌํŒ… ๋ฐ ๋ฌธ์„œํ™”, ๋””๋ฒ„๊น…, ๊ทธ๋ฆฌ๊ณ  ์ตœ์ ํ™”๊ฐ€ ํฌํ•จ๋œ๋‹ค. ์ด๋Ÿฌํ•œ ๊ตฌ์กฐํ™”๋œ ์ ‘๊ทผ ๋ฐฉ์‹์€ LLM์˜ ์„ฑ๋Šฅ์„ ์„ธ

Flat Model Structures for Nonunital Algebras and Higher K-Theory

Flat Model Structures for Nonunital Algebras and Higher K-Theory

์ด ์—ฐ๊ตฌ๋Š” ๋น„๋‹จ์œ„ ๋Œ€์ˆ˜์— ๋Œ€ํ•œ Kโ€‘์ด๋ก ์„ ์ฒด๊ณ„์ ์œผ๋กœ ์ •๋ฆฝํ•˜๋ ค๋Š” ์žฅ๊ธฐ์ ์ธ ๋ชฉํ‘œ์— ์ค‘์š”ํ•œ ์ง„์ „์„ ์ œ๊ณตํ•œ๋‹ค. ์ „ํ†ต์ ์œผ๋กœ ๋น„๋‹จ์œ„ ํ™˜ A๋ฅผ ๋‹จ์œ„๊ฐ€ ์žˆ๋Š” ํ™˜ widetilde{A}์˜ ์–‘์ธก ์•„์ด๋””์–ผ๋กœ ์‚ฝ์ž…ํ•œ ๋’ค, widetilde{A}์— ๋Œ€ํ•œ ๊ธฐ์กด Kโ€‘์ด๋ก ์„ ์ด์šฉํ•ด A์˜ Kโ€‘์ด๋ก ์„ ์ •์˜ํ•˜๋Š” ๋ฐฉ๋ฒ•์ด ์“ฐ์—ฌ ์™”๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๋‹จ์œ„ ํ™•์žฅ์˜ ์„ ํƒ์ด ์œ ์ผํ•˜์ง€ ์•Š์œผ๋ฉฐ, ์„œ๋กœ ๋‹ค๋ฅธ ์„ ํƒ์€ ์„œ๋กœ ๋‹ค๋ฅธ ๋™ํ˜•๋ก ์ ยท๋™์ฐจ์  ์ •๋ณด๋ฅผ ์ดˆ๋ž˜ํ•œ๋‹ค๋Š” โ€˜์ ˆ์ œ ๋ฌธ์ œโ€™๊ฐ€ ์˜ค๋ž˜๋œ ๋‚œ๊ด€์œผ๋กœ ๋‚จ์•„ ์žˆ์—ˆ๋‹ค. Wodzicki๋Š” Hโ€‘๋‹จ์œ„ ์กฐ๊ฑด์ด ์ ˆ์ œ์„ฑ์„ ๋ณด์žฅํ•œ๋‹ค๋Š” ์ค‘์š”ํ•œ ๊ฒฐ๊ณผ๋ฅผ ์ œ์‹œํ–ˆ์ง€๋งŒ,

Model Mathematics
Flavor Transition Mechanisms of Propagating Astrophysical Neutrinos -A   Model Independent Parametrization

Flavor Transition Mechanisms of Propagating Astrophysical Neutrinos -A Model Independent Parametrization

: ์ฒœ์ฒด๋ฌผ๋ฆฌํ•™์  ์ค‘์„ฑ๋ฏธ์ž๋Š” ์šฐ์ฃผ์—์„œ ๋ฐœ์ƒํ•˜๋Š” ๋‹ค์–‘ํ•œ ํ˜„์ƒ๊ณผ ๋ฐ€์ ‘ํ•œ ๊ด€๋ จ์ด ์žˆ์Šต๋‹ˆ๋‹ค. ์ด ๋…ผ๋ฌธ์—์„œ๋Š” ์ค‘์„ฑ๋ฏธ์ž์˜ ๋ง› ์ „ํ™˜, ์ฆ‰ ์ค‘์„ฑ๋ฏธ์ž๊ฐ€ ์ด๋™ํ•˜๋ฉด์„œ ๋ง›(์ „์žํ˜•, ๋ฎค์˜จํ˜•, ํƒ€์šฐํ˜•)์ด ๋ณ€ํ•˜๋Š” ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ๋ถ„์„ํ•ฉ๋‹ˆ๋‹ค. ์ค‘์„ฑ๋ฏธ์ž ๋ง์›๊ฒฝ์˜ ๋ฐœ์ „์œผ๋กœ ์ธํ•ด ์ด๋Ÿฌํ•œ ๋ง› ์ „ํ™˜์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๊ฐ€ ํ™œ๋ฐœํ•ด์กŒ์Šต๋‹ˆ๋‹ค. ์ €์ž๋“ค์€ ๋ชจ๋ธ ๋…๋ฆฝ์ ์ธ ๋งค๊ฐœ๋ณ€์ˆ˜ํ™”๋ฅผ ํ†ตํ•ด ๋ง› ๋ณ€ํ™˜ ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ์„ค๋ช…ํ•˜๊ณ ์ž ํ•ฉ๋‹ˆ๋‹ค. ์ด๋Š” ๋‹ค์–‘ํ•œ ๋ง› ๋ณ€ํ™˜ ๋ชจ๋ธ์„ ํฌ๊ด„์ ์œผ๋กœ ๋‹ค๋ฃจ๊ณ , ๋ฏธ๋ž˜์˜ ์ค‘์„ฑ๋ฏธ์ž ๋ง์›๊ฒฝ์—์„œ ๊ด€์ธก ๊ฐ€๋Šฅํ•œ ๊ฒฐ๊ณผ๋ฅผ ์˜ˆ์ธกํ•˜๋Š” ๋ฐ ๋„์›€์ด ๋ฉ๋‹ˆ๋‹ค. ์ œ์•ˆ๋œ ๋งค๊ฐœ๋ณ€์ˆ˜ํ™”๋Š” ์†Œ์Šค์˜ ์ดˆ๊ธฐ ๋ง› ๋น„์œจ๊ณผ ์ง€๊ตฌ

Astrophysics HEP-PH Model
Fluorescence emission induced by extensive air showers in dependence on   atmospheric conditions

Fluorescence emission induced by extensive air showers in dependence on atmospheric conditions

: ๋ณธ ๋…ผ๋ฌธ์€ ์šฐ์ฃผ์„ ์˜ ์—๋„ˆ์ง€๋ฅผ ์ธก์ •ํ•˜๋Š” ๋ฐ ์žˆ์–ด ํ˜•๊ด‘ ๋น›์˜ ์ค‘์š”์„ฑ๊ณผ ๊ทธ ๋ฐฉ์ถœ์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๋‹ค์–‘ํ•œ ๋Œ€๊ธฐ ์กฐ๊ฑด์„ ์‹ฌ๋„ ์žˆ๊ฒŒ ๋ถ„์„ํ•ฉ๋‹ˆ๋‹ค. ํŠนํžˆ, ๊ณต๊ธฐ ์ƒค์›Œ์—์„œ ๋ฐœ์ƒํ•˜๋Š” ํ˜•๊ด‘ ๊ด‘์ž์˜ ์ˆ˜์™€ ๋Œ€๊ธฐ ์˜จ๋„, ๊ธฐ์••, ์Šต๋„์˜ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ์ง‘์ค‘์ ์œผ๋กœ ๋‹ค๋ฃน๋‹ˆ๋‹ค. ์šฐ์„ , ๋…ผ๋ฌธ์—์„œ๋Š” ํ˜•๊ด‘ ๊ด‘์ž์˜ ์ˆ˜๋ฅผ ๊ฒฐ์ •ํ•˜๋Š” Y(ฮป, P, T, e) ํ•จ์ˆ˜๋ฅผ ์ œ์•ˆํ•ฉ๋‹ˆ๋‹ค. ์ด ํ•จ์ˆ˜๋Š” ํŒŒ์žฅ, ๊ธฐ์••, ๊ธฐ์˜จ, ์ฆ๊ธฐ์••์— ๋”ฐ๋ผ ๋‹ฌ๋ผ์ง€๋Š” ํ˜•๊ด‘ ์ˆ˜์œจ์„ ๊ณ ๋ คํ•˜์—ฌ ๊ณต๊ธฐ ์ƒค์›Œ์—์„œ ๋ฐฉ์ถœ๋˜๋Š” ๋น›์˜ ์–‘์„ ๊ณ„์‚ฐํ•ฉ๋‹ˆ๋‹ค. ์ด๋Š” ๊ธฐ๋ณธ ์—๋„ˆ์ง€๋ฅผ ์žฌ๊ตฌ์„ฑํ•˜๋Š” ๋ฐ ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•ฉ๋‹ˆ๋‹ค. ๋‹ค์Œ์œผ๋กœ, ์งˆ์†Œ ๋ถ„์ž์˜

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