KOINEU Logo
Can the same generation of astronomers see both the short gamma-ray   bursts and their supernovae precursors?

Can the same generation of astronomers see both the short gamma-ray bursts and their supernovae precursors?

์ด ๋…ผ๋ฌธ์€ ์ฒœ๋ฌธํ•™ ๋ถ„์•ผ์—์„œ ์ค‘์š”ํ•œ ๋ฌธ์ œ๋ฅผ ๋‹ค๋ฃจ๊ณ  ์žˆ๋‹ค. ๋‹จ๊ธฐ ๊ฐ๋งˆ์„  ํ‰๋ฐœ(GRB)๊ณผ ๊ทธ ์ „์กฐ๋ฌผ์ธ ์ดˆ์‹ ์„ฑ(SN) ์‚ฌ์ด์˜ ๊ด€๊ณ„์— ๋Œ€ํ•œ ์ดํ•ด๋Š” ์šฐ์ฃผ์˜ ๊ทน๋‹จ์ ์ธ ๋ฌผ๋ฆฌ ํ˜„์ƒ์„ ์—ฐ๊ตฌํ•˜๋Š” ๋ฐ ์žˆ์–ด ํ•ต์‹ฌ์ ์ด๋‹ค. 1. ๋‹จ๊ธฐ GRB์™€ SN์˜ ์—ฐ๊ด€์„ฑ ๋…ผ๋ฌธ์€ ๋‹จ๊ธฐ GRB๊ฐ€ ์ค‘์„ฑ์ž๋ณ„์ด๋‚˜ ๋ธ”๋ž™ํ™€์˜ ์ดํ•ฉ์œผ๋กœ ๋ฐœ์ƒํ•œ๋‹ค๋Š” ๊ธฐ์กด ๊ฐ€์„ค์„ ๋ฐ”ํƒ•์œผ๋กœ ํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ์ดํ•ฉ ๊ณผ์ •์—์„œ ์ž์„ํ™”๋œ ์ค‘์„ฑ์ž๋ณ„์ด ์ถฉ๋Œํ•˜๋ฉด, ์ดˆ๊ฐ•๋ ฅ ์ž๊ธฐ์žฅ๊ณผ ์ œํŠธ ๊ตฌ์กฐ๊ฐ€ ํ˜•์„ฑ๋˜์–ด ๋‹จ๊ธฐ GRB๋ฅผ ์ƒ์„ฑํ•œ๋‹ค. ์ด๋Š” ์ˆ˜์น˜ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ฒฐ๊ณผ๋กœ ๋’ท๋ฐ›์นจ๋œ๋‹ค. 2. SN ํญ๋ฐœ ํ›„ ๋‹จ๊ธฐ GRB ๋ฐœ์ƒ ๊ฐ€๋Šฅ์„ฑ ๋…ผ๋ฌธ์€ SN ํญ

Astrophysics
Convergence of Outputs When Two Large Language Models Interact in a Multi-Agentic Setup

Convergence of Outputs When Two Large Language Models Interact in a Multi-Agentic Setup

: ๋ณธ ์—ฐ๊ตฌ๋Š” ๋Œ€ํ˜• ์–ธ์–ด ๋ชจ๋ธ(Large Language Model, LLM)์ด ์„œ๋กœ ์ƒํ˜ธ์ž‘์šฉํ•˜๋Š” ๋‹ค์ค‘ ์—์ด์ „ํŠธ ์„ค์ •์—์„œ์˜ ์ˆ˜๋ ด ํ˜„์ƒ์„ ํƒ๊ตฌํ•˜์˜€์Šต๋‹ˆ๋‹ค. ์ด ์—ฐ๊ตฌ์—์„œ๋Š” ๋ฏธ์ŠคํŠธ๋ž„ ๋„ค๋ชจ ๋ฒ ์ด์Šค 2407๊ณผ ๋ผ๋งˆ 2 13B HF ๋‘ ๋ชจ๋ธ์„ ์‚ฌ์šฉํ•˜์—ฌ ์‹คํ—˜์„ ์ˆ˜ํ–‰ํ•˜์˜€์œผ๋ฉฐ, ๊ฐ ๋ชจ๋ธ์€ ๋…๋ฆฝ์ ์œผ๋กœ ํ›ˆ๋ จ๋œ ๊ณ ์œ ํ•œ ๊ฐ€์ค‘์น˜์™€ ํ† ํฐ๋ผ์ด์ €๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์‹คํ—˜์—์„œ๋Š” ์ดˆ๊ธฐ ์งง์€ ๋ฌธ์žฅ์œผ๋กœ ์‹œ์ž‘ํ•˜๋Š” ๋Œ€ํ™”์—์„œ ๋‘ ๋ชจ๋ธ์ด ์ƒ๋Œ€๋ฐฉ์˜ ์ถœ๋ ฅ์— ์‘๋‹ตํ•˜๋ฉฐ 25ํšŒ ๋ฐ˜๋ณต๋˜๋Š” ๊ณผ์ •์„ ๊ด€์ฐฐํ•˜์˜€์Šต๋‹ˆ๋‹ค. ์ˆ˜๋ ด ํ˜„์ƒ์˜ ํŠน์ง• ์ˆ˜๋ ด ํ˜„์ƒ์€ ๋Œ€ํ™”๊ฐ€ ์ง„ํ–‰๋จ์— ๋”ฐ๋ผ ์ผ๊ด€์„ฑ ์žˆ๋Š” ํŒจํ„ด์ด ๋‚˜ํƒ€๋‚˜

Model
Cryptolysis v.0.0.1 - A Framework for Automated Cryptanalysis of   Classical Ciphers

Cryptolysis v.0.0.1 - A Framework for Automated Cryptanalysis of Classical Ciphers

๋ณธ ๋…ผ๋ฌธ์€ ๊ณ ์ „ ์•”ํ˜ธ ํ•ด๋…์„ ์ž๋™ํ™”ํ•˜๊ธฐ ์œ„ํ•ด ๊ฐœ๋ฐœ๋œ ํ”„๋ ˆ์ž„์›Œํฌ 'ํฌ๋ฆฝํ†จ๋ฆฌ์‹œ์Šค'์˜ ์„ค๊ณ„์™€ ๊ตฌํ˜„ ๋ฐฉ๋ฒ•์„ ์ƒ์„ธํžˆ ๋‹ค๋ฃจ๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์ด ํ”„๋กœ์ ํŠธ๋Š” ์ž๋ฐ” ์–ธ์–ด๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•˜๋ฉฐ, ๋ฉ”๋ชจ๋ฆฌ ๊ด€๋ฆฌ์™€ ์ปฌ๋ ‰์…˜ ๊ด€๋ฆฌ์˜ ์šฉ์ด์„ฑ ๋•๋ถ„์— ํšจ์œจ์ ์ธ ๊ฐœ๋ฐœ ํ™˜๊ฒฝ์„ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค. ์‹œ์Šคํ…œ ์•„ํ‚คํ…์ฒ˜ ํฌ๋ฆฝํ†จ๋ฆฌ์‹œ์Šค์˜ ์‹œ์Šคํ…œ ์•„ํ‚คํ…์ฒ˜๋Š” ์•”ํ˜ธ ์ƒ์„ฑ ๋ฐ ํ…Œ์ŠคํŠธ๋ฅผ ์œ„ํ•œ ๋‚ด๋ถ€ ๋„๊ตฌ์™€ ๊ณต๊ฒฉ ๋ชจ๋“ˆ๋กœ ๊ตฌ์„ฑ๋˜์–ด ์žˆ์Šต๋‹ˆ๋‹ค. ๊ฐ ๊ตฌ์„ฑ ์š”์†Œ ๊ฐ„ ์ƒํ˜ธ ์ž‘์šฉ์€ ์ž์„ธํžˆ ์„ค๋ช…๋˜์–ด ์žˆ์œผ๋ฉฐ, ์ด๋ฅผ ํ†ตํ•ด ํ”„๋ ˆ์ž„์›Œํฌ์˜ ์ „์ฒด์ ์ธ ๊ตฌ์กฐ๋ฅผ ์ดํ•ดํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ํŒจํ‚ค์ง€ ๊ตฌ์กฐ : ์ž๋ฐ” ํŒจํ‚ค์ง€ ๊ตฌ์กฐ๋Š” ์• ํ”Œ๋ฆฌ์ผ€์ด์…˜์˜ ๋ชจ๋“ˆ

Cryptography and Security Analysis Framework Software Engineering Computer Science
Geometric Data Science

Geometric Data Science

: ์ด ์ฑ…์€ '๋ฐ์ดํ„ฐ๊ฐ€ ์žˆ๋Š” ๊ณณ์— ๊ธฐํ•˜ํ•™์ด ์žˆ๋‹ค'๋ผ๋Š” ์ฃผ์ œ๋กœ, ์‹ค์ œ ๋ฐ์ดํ„ฐ์™€ ๊ทธ ํ‘œํ˜„์„ ๊ธฐํ•˜ํ•™์ ์œผ๋กœ ๋ถ„์„ํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค. ์ด๋Š” ๋‹จ์ˆœํžˆ ๋ฐ์ดํ„ฐ๋ฅผ ์ˆซ์ž๋‚˜ ์ด๋ฏธ์ง€๋กœ๋งŒ ๋ณด๋Š” ๊ฒƒ์ด ์•„๋‹ˆ๋ผ, ๋ฐ์ดํ„ฐ์˜ ๊ธฐํ•˜ํ•™์  ๊ตฌ์กฐ๋ฅผ ์ดํ•ดํ•˜๊ณ  ์ด๋ฅผ ํ†ตํ•ด ๋” ๊นŠ์€ ํ†ต์ฐฐ๋ ฅ์„ ์–ป์œผ๋ ค๋Š” ์‹œ๋„์ด๋‹ค. 1. ๋ฐ์ดํ„ฐ์™€ ๊ทธ ํ‘œํ˜„ ๋ฐ์ดํ„ฐ์˜ ๋ชจํ˜ธ์„ฑ : ์‹ค์ œ ๊ฐ์ฒด์™€ ๋””์ง€ํ„ธ ํ‘œํ˜„ ๊ฐ„์—๋Š” ํฐ ์ฐจ์ด๊ฐ€ ์žˆ๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด, ์ž๋™์ฐจ๋Š” ํ”ฝ์…€ ๊ธฐ๋ฐ˜ ์ด๋ฏธ์ง€๋กœ ํ‘œํ˜„๋˜์ง€๋งŒ, ์ด๋Š” ๋ฌผ๋ฆฌ์  ๊ฐ์ฒด์™€๋Š” ๋งค์šฐ ๋‹ค๋ฅด๋‹ค. ๋˜ํ•œ, ๊ฐ™์€ ๊ฐ์ฒด๋ผ๋„ ๋‹ค์–‘ํ•œ ํ‘œํ˜„์„ ๊ฐ€์งˆ ์ˆ˜ ์žˆ์–ด ๋ชจํ˜ธ์„ฑ์ด ๋ฐœ์ƒํ•œ๋‹ค. ๊ธฐํ•˜ํ•™์  ์ ‘๊ทผ :

Data
Jancars formal system for deciding bisimulation of first-order grammars   and its non-soundness

Jancars formal system for deciding bisimulation of first-order grammars and its non-soundness

: 1. ์ฒซ ๋ฒˆ์งธ ์ˆœ์„œ ๋ฌธ๋ฒ•๊ณผ ํ–‰๋™ ์•ŒํŒŒ๋ฒณ์˜ ์ •์˜ ๋…ผ๋ฌธ์€ ์ฒซ ๋ฒˆ์งธ ์ˆœ์„œ ๋ฌธ๋ฒ•์— ๋Œ€ํ•œ ๋น„์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด Jancar์˜ ํ˜•์‹ ์‹œ์Šคํ…œ์„ ๊ฒ€ํ† ํ•œ๋‹ค. ์ด ๊ณผ์ •์—์„œ ํ–‰๋™ ์•ŒํŒŒ๋ฒณ A์™€ ์ค‘๊ฐ„ ๋ผ๋ฒจ ์•ŒํŒŒ๋ฒณ T, ๊ทธ๋ฆฌ๊ณ  ๋งต LAB A: T โ†’ A๋ฅผ ์ •์˜ํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ์ •์˜๋Š” ์ฒซ ๋ฒˆ์งธ ์ˆœ์„œ ๋ฌธ๋ฒ• G (N, A, R)์„ ๊ตฌ์„ฑํ•˜๋Š” ๋ฐ ํ•„์š”ํ•œ ๊ธฐ๋ณธ ์š”์†Œ๋ฅผ ์ œ๊ณตํ•˜๋ฉฐ, ์—ฌ๊ธฐ์„œ N์€ ๋น„ํ„ฐ๋ฏธ๋„ ์ง‘ํ•ฉ, A๋Š” ํ–‰๋™ ์•ŒํŒŒ๋ฒณ, ๊ทธ๋ฆฌ๊ณ  R์€ ๊ทœ์น™ ์ง‘ํ•ฉ์ด๋‹ค. 2. Jancar ํ˜•์‹ ์‹œ์Šคํ…œ์˜ ๊ฐœ์š” Jancar์˜ ํ˜•์‹ ์‹œ์Šคํ…œ์€

Computer Science System Logic Formal Languages
No Image

Mapping the gender attrition gap in academic psychology

๋ณธ ์—ฐ๊ตฌ๋Š” ๋Œ€๊ทœ๋ชจ ๋ฐ์ดํ„ฐ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ์—ฌ์„ฑ๋“ค์ด ํ•™๊ณ„๋ฅผ ๋– ๋‚˜๋Š” ์ด์œ ์™€ ์‹œ๊ธฐ๋ฅผ ๋ถ„์„ํ–ˆ๋‹ค. ๊ทธ ๊ฒฐ๊ณผ, ์ดˆ์ฐฝ๊ธฐ ๊ฒฝ๋ ฅ์—์„œ ํ•™์ˆ ์  ์„ฑ๊ณผ๊ฐ€ ์ค‘์š”ํ•˜๋ฉฐ, ํŠนํžˆ ์ œ1์ €์ž ๋…ผ๋ฌธ์€ ์—ฌ์„ฑ๋“ค์˜ ์ž”๋ฅ˜์— ๊ฒฐ์ •์ ์ธ ์š”์ธ์ž„์„ ๋ฐํ˜”๋‹ค. ๋˜ํ•œ, ํ˜‘์—… ๋„คํŠธ์›Œํฌ๋‚˜ ๊ธฐ๊ด€ ํ™˜๊ฒฝ๋ณด๋‹ค๋„ ํ•™์ˆ ์  ์„ฑ๊ณผ๊ฐ€ ๋” ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•œ๋‹ค๋Š” ๊ฒƒ์„ ๋ฐœ๊ฒฌํ–ˆ๋‹ค. ์ด๋Š” ํ•™๊ณ„์—์„œ ์—ฌ์„ฑ๋“ค์ด ์ง๋ฉดํ•˜๋Š” ์žฅ๋ฒฝ์ด ๋ฌด์—‡์ธ์ง€ ์ดํ•ดํ•˜๊ณ , ์ด๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•œ ์กฐ๊ธฐ ๊ฐœ์ž…์˜ ํ•„์š”์„ฑ์„ ๊ฐ•์กฐํ•œ๋‹ค.

Massive particle production from accelerated sources in high magnetic   fields

Massive particle production from accelerated sources in high magnetic fields

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์  ๋ณธ ๋…ผ๋ฌธ์€ ๊ณ ๊ฐ•๋„ ์ž๊ธฐ์žฅ ๋‚ด์—์„œ ๊ฐ€์†๋œ ์–‘์„ฑ์ž๊ฐ€ ์ค‘์„ฑ ํ”ผ์˜จ์„ ๋ฐฉ์ถœํ•˜๋Š” ๊ณผ์ •์— ๋Œ€ํ•œ ๋ฐ˜๊ณ ์ „์  ๊ทผ์‚ฌ ๋ฐฉ๋ฒ•์„ ์‚ฌ์šฉํ•œ ๋ถ„์„์„ ์ˆ˜ํ–‰ํ•œ๋‹ค. ์ด๋Š” ์ž…์ž ๋ฌผ๋ฆฌํ•™์˜ ์ค‘์š”ํ•œ ๋ถ€๋ถ„์œผ๋กœ, ํŠนํžˆ ๊ฐ•๋ ฅํ•œ ์ž๊ธฐ์žฅ์ด ์กด์žฌํ•˜๋Š” ์ฒœ์ฒด๋ฌผ๋ฆฌํ•™์  ํ™˜๊ฒฝ์—์„œ ๋ฐœ์ƒํ•  ์ˆ˜ ์žˆ๋Š” ํ˜„์ƒ์„ ์ดํ•ดํ•˜๋Š”๋ฐ ์ค‘์š”ํ•˜๋‹ค. 2. ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• ๋ฐ˜๊ณ ์ „์  ๊ทผ์‚ฌ : ์›๋ณธ ์ž…์ž๋Š” ๊ณ ์ „ ์ „๋ฅ˜์™€ ์ง€์ •๋œ ๊ถค์ ์„ ๊ฐ€์ง„ ์ž…์ž๋กœ ๋ฌ˜์‚ฌ๋˜๋ฉฐ, ๋ฐฉ์ถœ๋˜๋Š” ์ž…์ž๋“ค์€ ์™„์ „ํžˆ ์–‘์žํ™”๋œ ํ•„๋“œ๋กœ ๊ฐ„์ฃผ๋œ๋‹ค. ์ž…์ž ์ƒ์„ฑ ์กฐ๊ฑด : ์ž๊ธฐ์žฅ ๋‚ด์—์„œ ์›€์ง์ด๋Š” ๊ฒฝ์šฐ, ๋ฐ˜๊ณ ์ „์  ๊ทผ์‚ฌ์˜ ์œ ํšจ์„ฑ์€ ํŠน์ • ์กฐ๊ฑด์ด ์ถฉ์กฑ๋  ๋•Œ ๋ณด

Astrophysics
NystagmusNet: Explainable Deep Learning for Photosensitivity Risk Prediction

NystagmusNet: Explainable Deep Learning for Photosensitivity Risk Prediction

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ํ•„์š”์„ฑ ๋ˆˆ์ง„ํƒ• + ๊ด‘๋ฏผ๊ฐ์„ฑ ์€ ๋ฐ๊ธฐ ๋ณ€ํ™”์— ๋”ฐ๋ผ ๋ˆˆ์˜ ์ง„๋™์ด ํฌ๊ฒŒ ์ฆ๊ฐ€ํ•ด ์‹œ์•ผ ์œ ์ง€ยท๊ท ํ˜• ์žก๊ธฐ์— ์–ด๋ ค์›€์„ ์ดˆ๋ž˜ํ•œ๋‹ค. ํ˜„์žฌ ์น˜๋ฃŒ๋ฒ•(์ƒ‰์•ˆ๊ฒฝ, ์•ฝ๋ฌผ)์€ ๋ฐ˜์‘ํ˜• ์ด๋ฉฐ, ์‚ฌ์ „ ์œ„ํ—˜ ์˜ˆ์ธกยท๊ฐœ์ธํ™”๊ฐ€ ๋ถ€์กฑํ•˜๋‹ค. ๋”ฅ๋Ÿฌ๋‹์ด ์•ˆ๊ตฌ ์›€์ง์ž„ ์ถ”์ ยท์‹œ๊ฐ ํ™˜๊ฒฝ ๋ถ„์„์— ์„ฑ๊ณตํ•œ ์‚ฌ๋ก€๊ฐ€ ๋Š˜์–ด๋‚˜๋ฉด์„œ, ์˜ˆ์ธก ๊ธฐ๋ฐ˜ ๋ณด์กฐ๊ธฐ์ˆ  ์— ๋Œ€ํ•œ ๊ธฐ๋Œ€๊ฐ€ ๋†’์•„์กŒ๋‹ค. 2. ์ฃผ์š” ๊ธฐ์—ฌ (Contributions) | ๋ฒˆํ˜ธ | ๋‚ด์šฉ | ์˜์˜ | | | | | | 1 | ์ด์ค‘โ€‘branch CNN ์„ค๊ณ„ โ€“ ๋ฐ๊ธฐ ์ด๋ฏธ์ง€์™€ ๋ˆˆ ์›€์ง์ž„ ๋ณ€๋™์„ฑ์„ ๋ณ„๋„ ์ฒ˜๋ฆฌ ํ›„ ์œตํ•ฉ | ๋ฉ€ํ‹ฐ๋ชจ๋‹ฌ ํŠน

Learning
On the Non-Termination of Rupperts Algorithm

On the Non-Termination of Rupperts Algorithm

๋ฃจํผํŠธ ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ ์‚ผ๊ฐํ™” ๊ณผ์ •์—์„œ ๊ฐ๋„์— ๋Œ€ํ•œ ์—„๊ฒฉํ•œ ์ œํ•œ์„ ์„ค์ •ํ•จ์œผ๋กœ์จ, ํ‰๋ฉด ๊ทธ๋ž˜ํ”„๋ฅผ ์•ˆ์ •์ ์ธ ๊ตฌ์กฐ๋กœ ๋ณ€ํ™˜ํ•˜๋Š” ๋ฐ ์ค‘์ ์„ ๋‘๊ณ  ์žˆ๋‹ค. ์ด ์•Œ๊ณ ๋ฆฌ์ฆ˜์˜ ํ•ต์‹ฌ์€ ๋ชจ๋“  ์‚ผ๊ฐํ˜•์ด ์ตœ์†Œ ๊ฐ๋„ ฮฑ๋ณด๋‹ค ์ž‘๊ฑฐ๋‚˜ ๊ฐ™์€ ๊ฐ๋„๋ฅผ ๊ฐ€์ง€๋„๋ก ํ•˜๋Š” ๊ฒƒ์ด๋‹ค. ์ดˆ๊ธฐ ์—ฐ๊ตฌ์—์„œ๋Š” 20.7ยฐ๊ฐ€ ์ด ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด ์ข…๋ฃŒ๋˜๋Š” ๊ฐ€์žฅ ์ž‘์€ ฮฑ ๊ฐ’์œผ๋กœ ์ œ์‹œ๋˜์—ˆ์œผ๋‚˜, ํ›„์† ์‹คํ—˜์„ ํ†ตํ•ด ์ด๋Š” ๋งค์šฐ ๋ณด์ˆ˜์ ์ธ ์ถ”์ •์ด๋ผ๋Š” ๊ฒƒ์ด ๋ฐํ˜€์กŒ๋‹ค. ํŒŒ๋ธŒ ์˜ˆ์ œ์˜ ๋ถ„์„: ์Šคํ‹ฐ๋ธ ํŒŒ๋ธŒ๋Š” ๋ฃจํผํŠธ ์•Œ๊ณ ๋ฆฌ์ฆ˜์—์„œ ๋น„์ข…๊ฒฐ์„ฑ์ด ๋ฐœ์ƒํ•˜๋Š” ๊ฒฝ์šฐ๋ฅผ ๋ณด์—ฌ์ฃผ๋Š” ์˜ˆ์ œ๋ฅผ ์ œ์‹œํ–ˆ๋‹ค. ์ด ์˜ˆ์ œ์—์„œ๋Š” ๋‘ ๊ฐœ์˜ ์ธ์ ‘ํ•œ ์„ธ๊ทธ๋จผํŠธ๊ฐ€ 3

Computer Science Computational Geometry
Origin of the bright prompt optical emission in the naked eye burst

Origin of the bright prompt optical emission in the naked eye burst

์„œ๋ก  ๋ถ„์„ GRB 080319B๋Š” ๊ฐ๋งˆ์„ ๊ณผ ๊ด‘ํ•™ ์˜์—ญ ๋ชจ๋‘์—์„œ ๊ณ ํ•ด์ƒ๋„๋กœ ๊ด€์ธก๋œ ํฌ๊ท€ํ•œ ์‚ฌ๊ฑด์œผ๋กœ, ์ด ์‚ฌ๊ฑด์˜ ์‹œ๊ฐ ๋“ฑ๊ธ‰์€ V 5.3์œผ๋กœ ๋งจ๋ˆˆ์œผ๋กœ ๊ด€์ธก์ด ๊ฐ€๋Šฅํ•˜๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๊ทธ ๊ฑฐ๋ฆฌ๋Š” ์šฐ์ฃผ๋ก ์  ๊ฑฐ๋ฆฌ์ธ z 0.937๋กœ ๋งค์šฐ ๋ฉ€๋‹ค. ์ด๋Ÿฌํ•œ ๋ฐ์€ ๊ด‘ํ•™ ์‹ ํ˜ธ๋ฅผ ์„ค๋ช…ํ•˜๊ธฐ ์œ„ํ•ด Synchro Self Compton (SSC) ๋ฉ”์ปค๋‹ˆ์ฆ˜๊ณผ ๋‘ ๊ฐ€์ง€ ๋‹ค๋ฅธ ์ „์ž ์ง‘๋‹จ์—์„œ ๋ฐœ์ƒํ•˜๋Š” ๊ฐ๋งˆ์„  ๋ฐฉ์ถœ์ด ์ œ์•ˆ๋˜์—ˆ์ง€๋งŒ, ์ด๋“ค ์‹œ๋‚˜๋ฆฌ์˜ค๋Š” ์—๋„ˆ์ง€ ์œ„๊ธฐ์™€ ์ž๊ธฐ ํก์ˆ˜ ์ฃผํŒŒ์ˆ˜๊ฐ€ ๊ด‘ํ•™ ์˜์—ญ์— ๋„๋‹ฌํ•˜๋Š” ๋ฌธ์ œ ๋“ฑ ์—ฌ๋Ÿฌ ์–ด๋ ค์›€์„ ๊ฒช๊ณ  ์žˆ๋‹ค. ๋†’์€ ๋ณ€๋™์„ฑ์„ ๊ฐ€์ง„ ์ƒ๋Œ€๋ก ์  ํ๋ฆ„์˜ ๊ด‘ํ•™

Astrophysics
Possible explanations of the Maunder minimum from a flux transport   dynamo model

Possible explanations of the Maunder minimum from a flux transport dynamo model

: ์„œ๋ก  ๋ถ„์„ ์„œ๋ก ์—์„œ ์ €์ž๋“ค์€ ํƒœ์–‘ ํ™œ๋™ ์ฃผ๊ธฐ ์ค‘ ๊ฐ€์žฅ ์ค‘์š”ํ•œ ํŠน์ง• ์ค‘ ํ•˜๋‚˜์ธ ๋งˆ์šด๋” ์ตœ์†Œ๊ธฐ์— ๋Œ€ํ•ด ์„ค๋ช…ํ•œ๋‹ค. ์ด ๊ธฐ๊ฐ„ ๋™์•ˆ ํƒœ์–‘ ํ‘์  ์ˆ˜๊ฐ€ ํ˜„์ €ํžˆ ๊ฐ์†Œํ–ˆ์œผ๋ฉฐ, ์ด๋Ÿฌํ•œ ์‚ฌ์‹ค์€ ์—ฌ๋Ÿฌ ์—ฐ๊ตฌ์—์„œ ํ™•์ธ๋˜์—ˆ๋‹ค(Ribes & Nesme Ribes, 1993; Hoyt & Schatten, 1996). ํŠนํžˆ, ์–‘ ๊ทน๋ฐ˜๊ตฌ ๋ชจ๋‘์—์„œ ํƒœ์–‘ ํ‘์  ์ˆ˜๊ฐ€ ๊ฑฐ์˜ ์ œ๋กœ์— ๊ฐ€๊นŒ์›Œ์กŒ์œผ๋ฉฐ ๋‚จ๋ฐ˜๊ตฌ์—์„œ๋Š” ๋งˆ์ง€๋ง‰ ๋‹จ๊ณ„์—์„œ ๋ช‡ ๊ฐœ์˜ ํ‘์ ์ด ๋‚˜ํƒ€๋‚ฌ๋‹ค(Ribes & Nesme Ribes, 1993). ์ฝ”์Šค๋ชจ์ œ๋‹‰ ๋™์œ„ ์›์†Œ ๋ฐ์ดํ„ฐ(Beer et al., 1998; Miyah

Astrophysics Model
Proportional integral derivative booster for neural networks-based time-series prediction: Case of water demand prediction

Proportional integral derivative booster for neural networks-based time-series prediction: Case of water demand prediction

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ํ•„์š”์„ฑ ๋‹ค๋‹จ๊ณ„ ์˜ˆ์ธก์˜ ํ•ต์‹ฌ ๊ณผ์ œ : ๋ฐ˜๋ณต(iterative) ์ „๋žต์„ ์‚ฌ์šฉํ•  ๊ฒฝ์šฐ, ์ด์ „ ๋‹จ๊ณ„์˜ ์˜ˆ์ธก๊ฐ’์ด ๋‹ค์Œ ๋‹จ๊ณ„ ์ž…๋ ฅ์— ์‚ฌ์šฉ๋ผ ์˜ค์ฐจ ๋ˆ„์  ๋ฌธ์ œ๊ฐ€ ๋ฐœ์ƒํ•œ๋‹ค. ๊ธฐ์กด ํ•ด๊ฒฐ์ฑ…์€ ๋ชจ๋ธ์„ ๋‹ค์ค‘์œผ๋กœ ๊ตฌ์„ฑํ•˜๊ฑฐ๋‚˜ ๋ณต์žกํ•œ ์‚ฌ์ „โ€‘ํ›„์ฒ˜๋ฆฌ ๊ธฐ๋ฒ•์„ ๋„์ž…ํ•ด ๋ณต์žก๋„๊ฐ€ ๊ธ‰์ฆํ•œ๋‹ค. PID ์ œ์–ด์˜ ์žฅ์  : ํŒŒ๋ผ๋ฏธํ„ฐ๊ฐ€ 3๊ฐœ(Kp, Ki, Kd)๋ฟ์ด๋ฉฐ, ์‹ค์‹œ๊ฐ„ ์ œ์–ด์— ๊ฒ€์ฆ๋œ ์•ˆ์ •์„ฑ์„ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. ์ด๋ฅผ ์˜ˆ์ธก ์˜ค๋ฅ˜ ๋ณด์ •์— ์ ์šฉํ•˜๋ฉด ๋ณต์žก๋„ ์ฆ๊ฐ€ ์—†์ด ์„ฑ๋Šฅ์„ ๋Œ์–ด์˜ฌ๋ฆด ์ˆ˜ ์žˆ๋‹ค. 2. ์ œ์•ˆ ๋ฐฉ๋ฒ•(PID ๋ถ€์Šคํ„ฐ)์˜ ํ•ต์‹ฌ ์•„์ด๋””์–ด | ๋‹จ๊ณ„ | ๋‚ด์šฉ | | |

Network
Rigidity analysis of HIV-1 protease

Rigidity analysis of HIV-1 protease

๋ณธ ๋…ผ๋ฌธ์€ HIV 1 ํ”„๋กœํ…Œ์•„์ œ์˜ ๊ตฌ์กฐ ๊ฐ•๋„๋ฅผ ๋ถ„์„ํ•˜๋Š” ๋ฐ ์ดˆ์ ์„ ๋งž์ถ”๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. HIV 1 ํ”„๋กœํ…Œ์•„์ œ๋Š” AIDS ๋ฐ”์ด๋Ÿฌ์Šค์˜ ๋ณต์ œ ๊ณผ์ •์—์„œ ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•˜๋Š” ํšจ์†Œ๋กœ, ์ด ํšจ์†Œ์˜ ๊ตฌ์กฐ์™€ ๊ธฐ๋Šฅ์— ๋Œ€ํ•œ ์ดํ•ด๋Š” ํ•ญ๋ฐ”์ด๋Ÿฌ์Šค ์น˜๋ฃŒ๋ฒ• ๊ฐœ๋ฐœ์— ์žˆ์–ด ํ•ต์‹ฌ์ ์ธ ์š”์†Œ์ž…๋‹ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” FIRST(Flexible and Rigid Clusters) ์†Œํ”„ํŠธ์›จ์–ด๋ฅผ ํ™œ์šฉํ•˜์—ฌ HIV 1 ํ”„๋กœํ…Œ์•„์ œ์˜ ๊ฐ•๋„ ๋ถ„์„์„ ์ˆ˜ํ–‰ํ–ˆ์Šต๋‹ˆ๋‹ค. FIRST ์†Œํ”„ํŠธ์›จ์–ด๋Š” ํŽ˜๋ธ” ๊ฒŒ์ž„ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•˜๋ฉฐ, ๋‹จ๋ฐฑ์งˆ ๋‚ด์—์„œ ๊ฒฐํ•ฉ์— ์˜ํ•œ ์ œ์•ฝ ์กฐ๊ฑด๊ณผ ์›์ž ์ž์œ ๋„๋ฅผ ๋งค์นญ์‹œ์ผœ ๊ฐ•๊ณ ํ•œ

Quantitative Biology Analysis
ROOT13: Spotting Hypernyms, Co-Hyponyms and Randoms

ROOT13: Spotting Hypernyms, Co-Hyponyms and Randoms

ROOT13์€ ์ž์—ฐ์–ด ์ฒ˜๋ฆฌ(NLP) ๋ถ„์•ผ์—์„œ ํ•˜์ดํผ๋‹ˆ๋ฆ„, ๊ณตํžˆํฌ๋ช… ๋ฐ ๋ฌด์ž‘์œ„ ๋‹จ์–ด๋ฅผ ๊ตฌ๋ณ„ํ•˜๋Š” ์ค‘์š”ํ•œ ๋ฌธ์ œ์— ๋Œ€ํ•œ ํ•ด๊ฒฐ์ฑ…์„ ์ œ์‹œํ•œ๋‹ค. ์ด ๋…ผ๋ฌธ์˜ ํ•ต์‹ฌ์€ ๋žœ๋ค ํฌ๋ ˆ์ŠคํŠธ ์•Œ๊ณ ๋ฆฌ์ฆ˜๊ณผ 13๊ฐœ์˜ ๋น„๊ฐ๋… ์ฝ”ํผ์Šค ๊ธฐ๋ฐ˜ ํŠน์ง•์„ ์‚ฌ์šฉํ•˜์—ฌ ์ด๋Ÿฌํ•œ ๋‹จ์–ด ๊ด€๊ณ„๋ฅผ ์ •ํ™•ํ•˜๊ฒŒ ๋ถ„๋ฅ˜ํ•˜๋Š” ์‹œ์Šคํ…œ์„ ๊ฐœ๋ฐœํ•œ ๊ฒƒ์ด๋‹ค. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ์ค‘์š”์„ฑ ์ž์—ฐ์–ด ์ฒ˜๋ฆฌ์—์„œ ํ•˜์ดํผ๋‹ˆ๋ฆ„, ๊ณตํžˆํฌ๋ช… ๊ทธ๋ฆฌ๊ณ  ๋ฌด์ž‘์œ„ ๋‹จ์–ด์˜ ๊ตฌ๋ณ„์€ ํ•ต์‹ฌ์ ์ธ ๊ณผ์ œ์ด๋‹ค. ์ด๋Š” ์‚ฌ์ „ ์ž‘์„ฑ, ๋ฌธ์žฅ ์žฌ๊ตฌ์„ฑ, ํ…์ŠคํŠธ ํ•จ์˜ ๋ถ„์„ ๋“ฑ ๋‹ค์–‘ํ•œ ์‘์šฉ ๋ถ„์•ผ์— ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•œ๋‹ค. ํŠนํžˆ, ํ•˜์ดํผ๋‹ˆ๋ฆ„๊ณผ ๊ณตํžˆํฌ๋ช…์€ ์˜๋ฏธ์  ๊ด€๊ณ„๋ฅผ ์ดํ•ดํ•˜๋Š”

Computer Science NLP
SGR 0418+5729: a low-magnetic-field magnetar

SGR 0418+5729: a low-magnetic-field magnetar

SGR 0418+5729๋Š” 2009๋…„์— ๋ฐœ๊ฒฌ๋œ ๋งˆ๊ทธ๋„คํƒ€๋ฅด๋กœ, ์ด ๋ณ„์€ ๋งค์šฐ ๋‚ฎ์€ ํ‘œ๋ฉด ์Œ๊ทน์ž ์ž๊ธฐ์žฅ ๊ฐ•๋„๋ฅผ ๊ฐ€์ง„ ๊ฒƒ์œผ๋กœ ์•Œ๋ ค์ ธ ์žˆ๋‹ค. ์ด ๋…ผ๋ฌธ์—์„œ๋Š” SGR 0418+5729์˜ ํšŒ์ „ ์†๋„ ๊ฐ์†Œ์œจ๊ณผ ํŠน์„ฑ ์—ฐ๋ น์„ ๋ถ„์„ํ•˜์—ฌ ๊ทธ ํ‘œ๋ฉด ์Œ๊ทน์ž ์ž๊ธฐ์žฅ์„ ์ถ”์ •ํ•˜๊ณ , ์ด๋ฅผ ํ†ตํ•ด ๋งˆ๊ทธ๋„คํƒ€๋ฅด ๋ชจ๋ธ์— ๋Œ€ํ•œ ์ƒˆ๋กœ์šด ์ดํ•ด๋ฅผ ์ œ์‹œํ•œ๋‹ค. 1. SGR 0418+5729์˜ ํŠน์ง• SGR 0418+5729๋Š” 2009๋…„ 6์›” 5์ผ ํŽ˜๋ฅด๋ฏธ ๊ฐ๋งˆ์„  ํญ๋ฐœ ๋ชจ๋‹ˆํ„ฐ์— ์˜ํ•ด ๋‘ ๊ฐœ์˜ ๋งˆ๊ทธ๋„คํƒ€์™€ ์œ ์‚ฌํ•œ ๊ธ‰๋ฐœ๊ด‘์„ ๊ด€์ธกํ•˜๋ฉด์„œ ๋ฐœ๊ฒฌ๋˜์—ˆ๋‹ค. ์ดํ›„ X ์„  ์œ„์„ฑ ๊ด€์ธก์„ ํ†ตํ•ด SGR 0418+

Astrophysics
Status of GDL - GNU Data Language

Status of GDL - GNU Data Language

: GDL์€ ์ฒœ๋ฌธํ•™ ๋ถ„์•ผ์—์„œ IDL์˜ ๋ฌด๋ฃŒ ๋Œ€์ฒด ์†Œํ”„ํŠธ์›จ์–ด๋กœ ๋„๋ฆฌ ์‚ฌ์šฉ๋˜๊ณ  ์žˆ์œผ๋ฉฐ, ๋‹ค์–‘ํ•œ ๋ฐ์ดํ„ฐ ๋ถ„์„๊ณผ ์‹œ๊ฐํ™” ์ž‘์—…์— ํ™œ์šฉ๋ฉ๋‹ˆ๋‹ค. GDL์˜ ์ฃผ์š” ํŠน์ง• ์ค‘ ํ•˜๋‚˜๋Š” IDL๊ณผ์˜ ์™„๋ฒฝํ•œ ๋ฌธ๋ฒ• ํ˜ธํ™˜์„ฑ์œผ๋กœ, ๊ธฐ์กด IDL ์ฝ”๋“œ๋ฅผ ์‰ฝ๊ฒŒ GDL์—์„œ ์‹คํ–‰ํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ์ ์ž…๋‹ˆ๋‹ค. ์ด๋กœ ์ธํ•ด ์ฒœ๋ฌธํ•™์ž๋“ค์€ ๋น„์šฉ ๋ถ€๋‹ด ์—†์ด ๊ณ ๊ธ‰ ๋ฐ์ดํ„ฐ ๋ถ„์„ ๋ฐ ์‹œ๊ฐํ™” ์ž‘์—…์„ ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. GDL์€ ๋‹ค์–‘ํ•œ ํ”Œ๋žซํผ์—์„œ ์‹คํ–‰ ๊ฐ€๋Šฅํ•˜๋ฉฐ, Linux, BSD, Mac OSX, OpenSolaris ๋“ฑ ์ฃผ์š” ์šด์˜ ์ฒด์ œ๋ฅผ ์ง€์›ํ•ฉ๋‹ˆ๋‹ค. ๋˜ํ•œ, ์—ฌ๋Ÿฌ ์šด์˜ ์ฒด์ œ์— ๋Œ€ํ•œ ์‚ฌ์ „ ์ปดํŒŒ์ผ

Data Computer Science Astrophysics Computational Engineering
The Stochastic Universe: Professor A.M. Mathais 75th Birthday

The Stochastic Universe: Professor A.M. Mathais 75th Birthday

A.M. ๋งˆํƒ€์ด ๊ต์ˆ˜๋Š” 1970๋…„๋Œ€๋ถ€ํ„ฐ ํ™•๋ฅ  ๋ฐ ํ†ต๊ณ„๋ฅผ ํ™œ์šฉํ•œ ๋ฌผ๋ฆฌํ•™ ์—ฐ๊ตฌ ํ”„๋กœ๊ทธ๋žจ์„ ์‹œ์ž‘ํ•˜์—ฌ, ์ •๋ณด ์ด๋ก ๊ณผ ์—”ํŠธ๋กœํ”ผ ํ•จ์ˆ˜, ์ •๊ทœ ๋ถ„ํฌ, ๊ทธ๋ฆฌ๊ณ  ์ผ๋ฐ˜ํ™”๋œ ํ•˜์ดํผ์ง€์ˆ˜ ํ•จ์ˆ˜ ๋“ฑ์„ ๋‹ค๋ฃฌ ์„ธ ๊ถŒ์˜ ๋‹จํ–‰๋ณธ์„ ์ถœํŒํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ์˜ ์—ฐ๊ตฌ๋Š” ์ˆ˜ํ•™๊ณผ ๋ฌผ๋ฆฌํ•™ ๊ฐ„์˜ ๊นŠ์€ ์—ฐ๊ด€์„ฑ์„ ๊ฐ•์กฐํ•˜๋ฉฐ, ํŠนํžˆ ํ†ต๊ณ„๋ฌผ๋ฆฌํ•™์—์„œ ์•„์ง ํ˜•์‹์  ๊ณต๋ฆฌ๊ณ„๊ฐ€ ๊ฐœ๋ฐœ๋˜์ง€ ๋ชปํ•œ ๋ถ€๋ถ„์— ์ฃผ๋ชฉํ•ฉ๋‹ˆ๋‹ค. ์ˆ˜ํ•™๊ณผ ๋ฌผ๋ฆฌํ•™์˜ ์ƒํ˜ธ์ž‘์šฉ์€ ์˜ค๋žœ ์—ญ์‚ฌ๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด, ์ผ๋ฐ˜ ์ƒ๋Œ€์„ฑ์ด๋ก ์€ ๋ฆฌ๋งŒ ๊ธฐํ•˜ํ•™์„ ๋ฐ”ํƒ•์œผ๋กœ ํ•˜๋ฉฐ, ์–‘์ž์—ญํ•™์€ ํ•จ์ˆ˜ ๋ถ„์„์— ํฌ๊ฒŒ ์˜์กดํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์•„์ธ์Šˆํƒ€์ธ์€ 1915๋…„์—

Physics
Thucy: An LLM-based Multi-Agent System for Claim Verification across Relational Databases

Thucy: An LLM-based Multi-Agent System for Claim Verification across Relational Databases

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ํ•„์š”์„ฑ ์ฃผ์žฅ ๊ฒ€์ฆ์˜ ๋ฐ์ดํ„ฐ ๊ฒฉ์ฐจ : ๊ธฐ์กด ์—ฐ๊ตฌ๋Š” ์ˆ˜๋ฐฑ ํ–‰ ์ˆ˜์ค€์˜ ๋‹จ์ผ ํ…Œ์ด๋ธ”์— ๊ตญํ•œ๋ผ, ์‹ค์ œ ๊ณต๊ณต ๋ฐ์ดํ„ฐ๋ฒ ์ด์Šค(์ˆ˜์‹ญยท์ˆ˜๋ฐฑ ํ…Œ์ด๋ธ”, ์ˆ˜๋ฐฑ๋งŒ ํ–‰)์™€์˜ ์—ฐ๋™์ด ์–ด๋ ค์› ๋‹ค. ํˆฌ๋ช…์„ฑ ์š”๊ตฌ : ๊ฒ€์ฆ ๊ฒฐ๊ณผ์— ๋Œ€ํ•œ โ€œ๋ธ”๋ž™๋ฐ•์Šคโ€์‹ ์„ค๋ช…์ด ์•„๋‹ˆ๋ผ, ์ „๋ฌธ๊ฐ€๊ฐ€ ์ง์ ‘ ๊ฒ€์ฆ ๊ณผ์ •์„ ์žฌํ˜„ยท์ˆ˜์ •ํ•  ์ˆ˜ ์žˆ๋Š” SQL ์ฆ๊ฑฐ ์ œ๊ณต์ด ํ•„์ˆ˜์ ์ด๋‹ค. 2. ํ•ต์‹ฌ ๊ธฐ์—ฌ | ๊ตฌ๋ถ„ | ๊ธฐ์กด ์‹œ์Šคํ…œ | Thucy์˜ ์ฐจ๋ณ„์  | | | | | | ๋ฐ์ดํ„ฐ ๋ฒ”์œ„ | ๋‹จ์ผ ํ…Œ์ด๋ธ”, ์ž‘์€ ๊ทœ๋ชจ | ๋‹ค์ค‘ DBยท๋‹ค์ค‘ ํ…Œ์ด๋ธ” (ํฌ๋กœ์Šคโ€‘DB/ํฌ๋กœ์Šคโ€‘Table) | | ์Šคํ‚ค๋งˆ ์˜์กด์„ฑ

Data System
When AI Bends Metal: AI-Assisted Optimization of Design Parameters in Sheet Metal Forming

When AI Bends Metal: AI-Assisted Optimization of Design Parameters in Sheet Metal Forming

: ๋ณธ ๋…ผ๋ฌธ์€ AI์™€ ๊ณ ์„ฑ๋Šฅ ์ปดํ“จํŒ…(HPC)์„ ํ™œ์šฉํ•˜์—ฌ ์‹œํŠธ ๊ธˆ์† ํ˜•์„ฑ ๊ณผ์ •์—์„œ ์„ค๊ณ„ ๋งค๊ฐœ๋ณ€์ˆ˜ ์ตœ์ ํ™”๋ฅผ ์ž๋™ํ™”ํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•˜๊ณ  ์žˆ๋‹ค. ์ด๋Š” ์ „ํ†ต์ ์ธ ์ˆ˜์ž‘์—… ๋ฐฉ์‹์— ๋น„ํ•ด ์‹œ๊ฐ„๊ณผ ๋น„์šฉ์„ ํฌ๊ฒŒ ์ ˆ๊ฐํ•  ์ˆ˜ ์žˆ๋Š” ํ˜์‹ ์ ์ธ ์ ‘๊ทผ๋ฒ•์ด๋‹ค. 1. AI ์ง€์› ์›Œํฌํ”Œ๋กœ์šฐ์˜ ๊ตฌ์„ฑ ์š”์†Œ ๋…ผ๋ฌธ์—์„œ ์ œ์•ˆ๋œ AI ์ง€์› ์›Œํฌํ”Œ๋กœ์šฐ๋Š” ๋‘ ๊ฐ€์ง€ ์ฃผ์š” ๊ตฌ์„ฑ ์š”์†Œ๋ฅผ ํฌํ•จํ•œ๋‹ค: ์ „๋ฌธ๊ฐ€ ์ฐธ์—ฌ ๊ฐ์†Œ : ๋ฒ ์ด์ฆˆ ์ตœ์ ํ™”๋ฅผ ํ†ตํ•ด ์ „๋ฌธ๊ฐ€์˜ ๊ฐœ์ž…์„ ์ค„์ด๊ณ , ์ดˆ๊ธฐ ์„ค๊ณ„ ์ถ”์ •๊ณผ ์ตœ์ ํ™” ๋ฃจํ”„์—์„œ ์ž๋™ํ™”๋ฅผ ๋„์ž…ํ•œ๋‹ค. ํšจ์œจ์ ์ธ ์„ค๊ณ„ ๋งค๊ฐœ๋ณ€์ˆ˜ ํƒ์ƒ‰ : ๊ฐ€์šฐ์Šค ํ”„๋กœ์„ธ์Šค ์ž ์žฌ ๋ณ€์ˆ˜ ๋ชจ๋ธ(GPL

Satisfiability Modulo Theory Meets Inductive Logic Programming

Satisfiability Modulo Theory Meets Inductive Logic Programming

1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋™๊ธฐ ILP์˜ ๊ฐ•์  : ๊ด€๊ณ„ํ˜• ๋ฐ์ดํ„ฐ์—์„œ 1์ฐจ ๋…ผ๋ฆฌ ๊ทœ์น™์„ ํ•™์Šตํ•จ์œผ๋กœ์จ ๋†’์€ ํ•ด์„ ๊ฐ€๋Šฅ์„ฑ๊ณผ ๊ฐ•๋ ฅํ•œ ์ผ๋ฐ˜ํ™” ๋Šฅ๋ ฅ์„ ์ œ๊ณตํ•œ๋‹ค. ILP์˜ ํ•œ๊ณ„ : ์ˆ˜์น˜ ์ œ์•ฝ(์ž„๊ณ„๊ฐ’, ์„ ํ˜•/๋น„์„ ํ˜• ๊ด€๊ณ„ ๋“ฑ)์„ ์ง์ ‘ ์œ ๋„ํ•˜์ง€ ๋ชปํ•œ๋‹ค. ๊ธฐ์กด ๋ฐฉ๋ฒ•์€ 1) ์ด์‚ฐํ™” (threshold discretisation) โ†’ ์ •๋ณด ์†์‹ค, 2) ์ˆ˜๋™ ์„ค๊ณ„ ์ˆ ์–ด โ†’ ๋„๋ฉ”์ธ ์˜์กด์„ฑ, 3) bottomโ€‘clause ๊ธฐ๋ฐ˜ โ†’ ๋‹จ์ผ ์˜ˆ์ œ์—๋งŒ ์˜์กด, ๋‹ค์ค‘ ์˜ˆ์ œ ๊ฐ„์˜ ์ „์—ญ ์ˆ˜์น˜ ํŒจํ„ด์„ ํฌ์ฐฉ ๋ชปํ•จ. 2. ์ œ์•ˆ ๋ฐฉ๋ฒ•๋ก  | ๋‹จ๊ณ„ | ๋‹ด๋‹น ์‹œ์Šคํ…œ | ์ฃผ์š” ์—ญํ•  | | | |

Catching UX Flaws in Code: Leveraging LLMs to Identify Usability Flaws at the Development Stage

Catching UX Flaws in Code: Leveraging LLMs to Identify Usability Flaws at the Development Stage

: ์ด ๋…ผ๋ฌธ์€ ๋Œ€๊ทœ๋ชจ ์–ธ์–ด ๋ชจ๋ธ(LLM)์ธ GPT 4o๋ฅผ ํ™œ์šฉํ•˜์—ฌ ์›น ์• ํ”Œ๋ฆฌ์ผ€์ด์…˜์˜ ์‚ฌ์šฉ์„ฑ ๊ฒฐํ•จ์„ ์ดˆ๊ธฐ ๊ฐœ๋ฐœ ๋‹จ๊ณ„์—์„œ ์ž๋™์œผ๋กœ ์‹๋ณ„ํ•˜๋Š” ๋ฐฉ๋ฒ•๋ก ์„ ์ œ์‹œํ•œ๋‹ค. ์ „ํ†ต์ ์ธ ์‚ฌ์šฉ์„ฑ ํ‰๊ฐ€๋Š” ์‹œ๊ฐ„๊ณผ ์ž์› ์†Œ๋ชจ๊ฐ€ ํฌ๊ณ  ์ฃผ๊ด€์ ์ผ ์ˆ˜ ์žˆ์–ด, ํŠนํžˆ ์†Œ๊ทœ๋ชจ ํŒ€์ด๋‚˜ ์ดˆ๊ธฐ ํ”„๋กœ์ ํŠธ์—์„œ๋Š” ์ด๋Ÿฌํ•œ ์ ‘๊ทผ ๋ฐฉ์‹์ด ํ•œ๊ณ„๋ฅผ ๊ฐ€์งˆ ์ˆ˜ ์žˆ๋‹ค. ์ด์— ๋”ฐ๋ผ LLM์˜ ๋ฐœ์ „์€ ์‚ฌ์šฉ์„ฑ ๋ฌธ์ œ๋ฅผ ์ž๋™ํ™”๋œ ๋ฐฉ์‹์œผ๋กœ ์‹๋ณ„ํ•  ์ˆ˜ ์žˆ๋Š” ์ƒˆ๋กœ์šด ๊ฐ€๋Šฅ์„ฑ์„ ์ œ์‹œํ•œ๋‹ค. 1. ์—ฐ๊ตฌ ๋ฐฉ๋ฒ•๋ก  ๋…ผ๋ฌธ์€ Jakob Nielsen์˜ 10๊ฐ€์ง€ ์‚ฌ์šฉ์„ฑ ์ง๊ด€ ์ง€์นจ์„ ๊ธฐ๋ฐ˜์œผ๋กœ GPT 4o ๋ชจ๋ธ์ด ์›น์‚ฌ์ดํŠธ ์†Œ์Šค ์ฝ”๋“œ๋ฅผ

Diffusion of Confidential Information on Networks

Diffusion of Confidential Information on Networks

: ๋ณธ ๋…ผ๋ฌธ์€ ๋””์ง€ํ„ธ ์„ธ์ƒ์—์„œ ๊ฐœ์ธ์ •๋ณด์™€ ๋น„๋ฐ€์ •๋ณด๊ฐ€ ์–ด๋–ป๊ฒŒ ํผ์ ธ๋‚˜๊ฐ€๋Š”์ง€๋ฅผ ์ˆ˜ํ•™์ ์œผ๋กœ ๋ชจ๋ธ๋งํ•˜๊ณ  ๋ถ„์„ํ•˜๋Š” ๋ฐ ์ดˆ์ ์„ ๋งž์ถ”๊ณ  ์žˆ๋‹ค. ์ด๋Š” ์ •๋ณด ๊ธฐ์ˆ ์˜ ๋ฐœ์ „์œผ๋กœ ์ธํ•ด ์–ธ์ œ ์–ด๋””์„œ๋“  ์ •๋ณด๋ฅผ ๊ณต์œ ํ•  ์ˆ˜ ์žˆ๊ฒŒ ๋˜๋ฉด์„œ, ๋ฏผ๊ฐํ•œ ์ฝ˜ํ…์ธ ์˜ ๋ณด์•ˆ ์œ ์ง€๊ฐ€ ๋”์šฑ ์ค‘์š”ํ•˜๊ฒŒ ๋œ ์ƒํ™ฉ์„ ๋ฐ˜์˜ํ•œ๋‹ค. ๋„คํŠธ์›Œํฌ ๊ตฌ์กฐ์™€ ๊ฐœ์ธ์ •๋ณด ํ™•์‚ฐ ๋ณธ ๋…ผ๋ฌธ์€ ๋„คํŠธ์›Œํฌ ์ด๋ก ์„ ๊ธฐ๋ฐ˜์œผ๋กœ ๋‹ค์–‘ํ•œ ์œ ํ˜•์˜ ๋„คํŠธ์›Œํฌ์—์„œ ์ •๋ณด์˜ ํ™•์‚ฐ ํŒจํ„ด์„ ๋ถ„์„ํ•˜๊ณ  ์žˆ๋‹ค. ๋„คํŠธ์›Œํฌ๋Š” ์ (๋…ธ๋“œ)๊ณผ ์„ (์—ฃ์ง€)์œผ๋กœ ๊ตฌ์„ฑ๋˜๋ฉฐ, ๋…ธ๋“œ์™€ ์—ฃ์ง€์˜ ์—ฐ๊ฒฐ ๋ฐฉ์‹์— ๋”ฐ๋ผ ์—ฌ๋Ÿฌ ๊ฐ€์ง€ ํ˜•ํƒœ๋กœ ๊ตฌ๋ถ„๋œ๋‹ค. 1. ์™„์ „ํ•œ ๋„คํŠธ์›Œํฌ : ๋ชจ

Physics Computer Science Social Networks Network
Efficient Kernel Mapping and Comprehensive System Evaluation of LLM Acceleration on a CGLA

Efficient Kernel Mapping and Comprehensive System Evaluation of LLM Acceleration on a CGLA

๋ณธ ๋…ผ๋ฌธ์€ ๋Œ€๊ทœ๋ชจ ์–ธ์–ด ๋ชจ๋ธ(LLM)์˜ ์ถ”๋ก  ๊ฐ€์†ํ™”์— ๋Œ€ํ•œ ์ข…ํ•ฉ์ ์ธ ํ‰๊ฐ€๋ฅผ ์ œ์‹œํ•˜๋ฉฐ, ํŠนํžˆ ์žฌ๊ตฌ์„ฑ ๊ฐ€๋Šฅํ•œ ์„ ํ˜• ๋ฐฐ์—ด(CGLA) ๊ธฐ๋ฐ˜ ์•„ํ‚คํ…์ฒ˜์ธ IMAX๋ฅผ ์‚ฌ์šฉํ•œ ์„ฑ๋Šฅ ๋ถ„์„์„ ์ค‘์ ์œผ๋กœ ๋‹ค๋ฃน๋‹ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” LLM์ด ์š”๊ตฌํ•˜๋Š” ๋†’์€ ๊ณ„์‚ฐ ์ž์›๊ณผ ์—๋„ˆ์ง€ ์†Œ๋น„ ๋ฌธ์ œ์— ๋Œ€์‘ํ•˜๊ธฐ ์œ„ํ•ด, CGLA๊ฐ€ ์ œ๊ณตํ•˜๋Š” ํšจ์œจ์„ฑ๊ณผ ์œ ์—ฐ์„ฑ์„ ๊ฐ•์กฐํ•ฉ๋‹ˆ๋‹ค. 1. LLM ์ถ”๋ก  ๊ฐ€์†ํ™”์˜ ํ•„์š”์„ฑ LLM์€ ํ…์ŠคํŠธ ์ฒ˜๋ฆฌ, ์ž์—ฐ์–ด ์ฒ˜๋ฆฌ, ์ฝ”๋“œ ์ƒ์„ฑ ๋“ฑ ๋‹ค์–‘ํ•œ ๋ถ„์•ผ์—์„œ ํ™œ์šฉ๋˜๋ฉฐ, ์ด์— ๋”ฐ๋ฅธ ๋†’์€ ๊ณ„์‚ฐ ์ž์› ์š”๊ตฌ์™€ ์—๋„ˆ์ง€ ์†Œ๋น„๋Š” ๋ฐ์ดํ„ฐ ์„ผํ„ฐ์˜ ์šด์˜ ๋น„์šฉ๊ณผ ํ™˜๊ฒฝ ๋ฌธ์ œ๋ฅผ ์•ผ๊ธฐํ•ฉ๋‹ˆ๋‹ค.

System
๋ฉ”ํƒ€์„œํ”ผ์Šค ๊ธฐ๋ฐ˜ ๋‚˜๋…ธํฌํ†ค๋‹‰์Šค ๊ธฐ์ดˆ ๋ชจ๋ธ MOCLIP์˜ ๊ณ ์† ๋ฌด์ œํ•œ ์„ค๊ณ„์™€ ๊ด‘ํ•™ ์ €์žฅ ํ˜์‹ 

๋ฉ”ํƒ€์„œํ”ผ์Šค ๊ธฐ๋ฐ˜ ๋‚˜๋…ธํฌํ†ค๋‹‰์Šค ๊ธฐ์ดˆ ๋ชจ๋ธ MOCLIP์˜ ๊ณ ์† ๋ฌด์ œํ•œ ์„ค๊ณ„์™€ ๊ด‘ํ•™ ์ €์žฅ ํ˜์‹ 

: ๋‚˜๋…ธ๊ด‘ํ•™ ๋ถ„์•ผ์—์„œ ๋”ฅ ๋Ÿฌ๋‹์˜ ๋„์ž…์€ ๋ฉ”ํƒ€ ํ‘œ๋ฉด, ๊ด‘ํ•™ ๊ฒฐ์ •, ํ”Œ๋ผ์Šค๋ชจ๋‹‰์Šค ๋“ฑ ๋‹ค์–‘ํ•œ ์˜์—ญ์—์„œ ํ˜์‹ ์„ ๊ฐ€์ ธ์™”์Šต๋‹ˆ๋‹ค. ํŠนํžˆ, ์ธ๊ณต ์ผ๋ฐ˜ ์ง€๋Šฅ(AGI) ๊ฐœ๋…์˜ ํ†ตํ•ฉ์€ ๋ฐ์ดํ„ฐ ์ค‘์‹ฌ ๊ณผํ•™ ๋ฐ ๋ฌผ๋ฆฌ์  ์„ค๊ณ„ ๊ฐ„์˜ ๊ฒฉ์ฐจ๋ฅผ ํ•ด์†Œํ•˜๊ณ  ์ ์‘ํ˜• ๊ด‘ํ•™ ์†”๋ฃจ์…˜์„ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ AGI ๋ฐœ์ „์˜ ํ•ต์‹ฌ์—๋Š” ๊ธฐ์ดˆ ๋ชจ๋ธ(FM)์ด ์žˆ์œผ๋ฉฐ, ์ด๋Š” ๋‹ค์–‘ํ•œ ๊ณผํ•™ ๋ถ„์•ผ์—์„œ ํ˜์‹ ์„ ์ด๋Œ๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ๋‚˜๋…ธ๊ด‘ํ•™์— FM์„ ์ ์šฉํ•˜๋Š” ๋ฐ ์žˆ์–ด ๊ฐ€์žฅ ํฐ ๋„์ „ ๊ณผ์ œ๋Š” ํ›ˆ๋ จ ๋ฐ์ดํ„ฐ์˜ ๋ถ€์กฑ์ž…๋‹ˆ๋‹ค. ๋‚˜๋…ธ๊ตฌ์กฐ๋ฌผ์˜ ์ž์œ ๋„(DOFs)๊ฐ€ ์ฆ๊ฐ€ํ•จ์— ๋”ฐ๋ผ ํ•„์š”ํ•œ ๋ฐ์ดํ„ฐ ์„ธํŠธ ํฌ๊ธฐ ๋˜ํ•œ ๊ธฐํ•˜๊ธ‰์ˆ˜์ ์œผ

No Image

$p$-ary sequences with six-valued cross-correlation function: a new decimation of Niho type

์ด ๋…ผ๋ฌธ์€ ํ™€์ˆ˜ ์†Œ์ˆ˜ $p$์™€ $n 2m$์— ๋Œ€ํ•ด ์ƒˆ๋กœ์šด ๋‹ˆํ˜ธ ์œ ํ˜•์˜ ๋ถ„ํ• ์„ ์ œ์‹œํ•˜๊ณ , ์ด๋ฅผ ํ†ตํ•ด ์–ป์–ด์ง„ ๊ต์ฐจ์ƒ๊ด€ ํ•จ์ˆ˜๊ฐ€ ์ตœ๋Œ€ 6๊ฐœ ๊ฐ’์œผ๋กœ ์ œํ•œ๋˜๋Š” ๊ฒƒ์„ ๋ณด์—ฌ์ค€๋‹ค. ์ด๋Š” ์ผ๋ฐ˜ํ™”๋œ ๋‹ˆํ˜ธ ์ •๋ฆฌ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ์ฆ๋ช…๋˜๋ฉฐ, ํŠนํžˆ $p$ ์ง„์ˆ˜ $m$ ์‹œํ€€์Šค์™€ ๊ทธ ๋ถ„ํ•  ์‹œํ€€์Šค ๊ฐ„์˜ ๊ต์ฐจ์ƒ๊ด€์ด ๋งค์šฐ ์ œํ•œ์ ์ด๋ผ๋Š” ์‚ฌ์‹ค์„ ๊ฐ•์กฐํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ๊ฒฐ๊ณผ๋Š” ํ†ต์‹  ์‹œ์Šคํ…œ์—์„œ ์˜ค๋ฅ˜ ๊ฒ€์ถœ ๋ฐ ์ˆ˜์ •์— ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•˜๋Š”๋ฐ, ์ด๋Š” ๊ต์ฐจ์ƒ๊ด€ ๊ฐ’์ด ์ ์„์ˆ˜๋ก ์‹ ํ˜ธ ๊ฐ„ ๊ฐ„์„ญ์ด ์ค„์–ด๋“ค๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ๋˜ํ•œ, ๋…ผ๋ฌธ์€ ๊ต์ฐจ์ƒ๊ด€์˜ ํฌ๊ธฐ๊ฐ€ $4sqrt{p^{n}} 1$๋ณด๋‹ค ์ž‘๊ฑฐ๋‚˜ ๊ฐ™์Œ์„ ๋ณด

Computer Science Discrete Mathematics Information Theory Mathematics
$sigma$-homogeneity of Borel sets

$sigma$-homogeneity of Borel sets

๋ณธ ๋…ผ๋ฌธ์€ ๋ณด๋  ์ง‘ํ•ฉ์˜ ๋™์งˆ์„ฑ์— ๋Œ€ํ•œ ๊นŠ์ด ์žˆ๋Š” ์ดํ•ด๋ฅผ ์ œ๊ณตํ•˜๋ฉฐ, ํŠนํžˆ ์นธํ† ์–ด ์ง‘ํ•ฉ C ๋‚ด์—์„œ ๋ณด๋  ์ง‘ํ•ฉ์˜ ๊ตฌ์กฐ์™€ ๊ทธ ์„ฑ์งˆ์„ ํƒ๊ตฌํ•œ๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” h ๋™์งˆ ๊ณต๊ฐ„์ด๋ผ๋Š” ๊ฐœ๋…์„ ์ค‘์‹ฌ์œผ๋กœ ์ง„ํ–‰๋˜๋ฉฐ, ์ด๋ฅผ ํ†ตํ•ด ๋ณด๋  ์ง‘ํ•ฉ์˜ ๋™์งˆ์„ฑ์„ ๋ถ„์„ํ•˜๊ณ  ์žˆ๋‹ค. 1. ๊ธฐ๋ณธ ๊ฐœ๋… ๋ฐ ์ •์˜ ๋…ผ๋ฌธ์—์„œ๋Š” ๋จผ์ € ๋ช‡ ๊ฐ€์ง€ ์ค‘์š”ํ•œ ์šฉ์–ด๋ฅผ ์ •์˜ํ•œ๋‹ค: ์นธํ† ์–ด ์ง‘ํ•ฉ (C) : ์ด์‚ฐ์  ์ˆ˜์™€ ํ•ฉ๋ฆฌ์  ์ˆ˜๋ฅผ ๊ฐ๊ฐ P, Q๋กœ ํ‘œ๊ธฐํ•˜๋ฉฐ, ์‹ค์ˆ˜ R์€ P์™€ Q์˜ ํ•ฉ์ง‘ํ•ฉ์œผ๋กœ ํ‘œํ˜„๋œ๋‹ค. h ๋™์งˆ ๊ณต๊ฐ„ : 0์ฐจ์› ํ† ํด๋กœ์ง€ ๊ณต๊ฐ„ X๊ฐ€ ๋ชจ๋“  ๋น„๊ณตํ—ˆ ํด๋กœํ”„ ์—ด๋ถ„ U์— ๋Œ€ํ•ด U์™€ X๊ฐ€ ํ™ˆ๋ชจ๋ฅดํ”ฝ(h

Mathematics
5,000,000 Delays -- Some Statistics

5,000,000 Delays -- Some Statistics

: ๋ณธ ๋…ผ๋ฌธ์€ VLBI ์ง€์—ฐ ์‹œ๊ฐ„ ๋ฐ์ดํ„ฐ๋ฅผ ํ†ตํ•ด ์ฒœ๋ฌธํ•™์˜ ์žฅ๊ธฐ์  ๋ฐœ์ „์„ ๋ถ„์„ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. 5,000,000๊ฐœ ์ด์ƒ์˜ VLBI ์ง€์—ฐ ์‹œ๊ฐ„์ด ์ˆ˜์ง‘๋œ ๊ฒƒ์€ ์ฒœ๋ฌธํ•™ ๋ถ„์•ผ์—์„œ ์ค‘์š”ํ•œ ์ด์ •ํ‘œ๋กœ, ์ด๋ฅผ ํ†ตํ•ด ๋‹ค์–‘ํ•œ ํ†ต๊ณ„์™€ ํŒจํ„ด์„ ํŒŒ์•…ํ•  ์ˆ˜ ์žˆ๊ฒŒ ๋˜์—ˆ์Šต๋‹ˆ๋‹ค. ๊ด€์ธก ์„ธ์…˜๊ณผ ์—ญ๋Ÿ‰ ๋ถ„์„ ๊ด€์ธก ์„ธ์…˜์€ 24์‹œ๊ฐ„ ์„ธ์…˜์ด ๊ฐ€์žฅ ๋งŽ์ด ์ด๋ฃจ์–ด์กŒ์œผ๋ฉฐ, ์ด๋Š” ์—ฐ๊ตฌ์˜ ์ค‘์š”์„ฑ์„ ๋ฐ˜์˜ํ•ฉ๋‹ˆ๋‹ค. ํŠนํžˆ, 18์‹œ๊ฐ„ ์ด์ƒ ์ง€์†๋œ ์„ธ์…˜ ์ˆ˜๊ฐ€ ์ „์ฒด ์„ธ์…˜ ์ค‘ ์ƒ๋‹น ๋ถ€๋ถ„์„ ์ฐจ์ง€ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ์žฅ๊ธฐ ๊ด€์ธก์€ ๋ฐ์ดํ„ฐ์˜ ์ •ํ™•์„ฑ๊ณผ ์‹ ๋ขฐ์„ฑ์„ ๋†’์ด๋Š” ๋ฐ ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•ฉ๋‹ˆ๋‹ค. ์—ญ๋Ÿ‰ ๋ถ„์„์—์„œ

Physics
A 1-dimensional Peano continuum which is not an IFS attractor

A 1-dimensional Peano continuum which is not an IFS attractor

: ๋ณธ ๋…ผ๋ฌธ์€ ๋ณต์žกํ•œ ์œ„์ƒ ๊ณต๊ฐ„ ์ด๋ก ๊ณผ ๊ด€๋ จ๋œ ์ค‘์š”ํ•œ ๋ฌธ์ œ๋ฅผ ๋‹ค๋ฃจ๊ณ  ์žˆ๋‹ค. ํŠนํžˆ, ๋ฌดํ•œ ์ฐจ์›์˜ ํ‰๋ฉด Peano ์—ฐ์†์ฒด๊ฐ€ IFS attractor์™€ ๋™ํ˜•์ด ๋  ์ˆ˜ ์žˆ๋Š”์ง€์— ๋Œ€ํ•œ ์งˆ๋ฌธ์„ ์ œ๊ธฐํ•˜๊ณ  ์ด๋ฅผ ๋ถ€์ •์ ์œผ๋กœ ํ•ด๊ฒฐํ•œ๋‹ค. IFS attractor๋Š” ๋ฐ˜๋ณต ํ•จ์ˆ˜ ์‹œ์Šคํ…œ(Iterated Function System)์„ ํ†ตํ•ด ์ƒ์„ฑ๋˜๋Š” ์ง‘ํ•ฉ์œผ๋กœ, ์••์ถ•๋œ ๋ฉ”ํŠธ๋ฆญ ๊ณต๊ฐ„์—์„œ ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•œ๋‹ค. ์ด ๋…ผ๋ฌธ์—์„œ๋Š” IFS attractor์˜ ์œ„์ƒํ•™์  ์„ฑ์งˆ์— ๋Œ€ํ•ด ๊นŠ์ด ์žˆ๊ฒŒ ๋ถ„์„ํ•œ๋‹ค. ํŠนํžˆ, ์—ฐ๊ฒฐ๋œ IFS attractor๋Š” ๊ตญ์†Œ์ ์œผ๋กœ ์—ฐ๊ฒฐ๋˜์–ด ์žˆ๊ณ , ์†์„ฑ

Mathematics
A Brief Review of SIAM Review

A Brief Review of SIAM Review

๋ณธ ๋…ผ๋ฌธ์€ SIAM ๋ฆฌ๋ทฐ ์ €๋„์˜ ๋ณ€ํ™”์™€ ๊ทธ ์˜ํ–ฅ๋ ฅ์„ ๋ถ„์„ํ•˜๊ณ , ํ–ฅํ›„ ๊ฐœ์„  ๋ฐฉ์•ˆ์„ ์ œ์‹œํ•œ๋‹ค. 1999๋…„ ์žฌ์กฐ์ง ์ดํ›„, SIAM ๋ฆฌ๋ทฐ ๋Š” ์—ฌ๋Ÿฌ ์„น์…˜์œผ๋กœ ๊ตฌ๋ถ„๋˜๋ฉฐ, ์ด๋กœ ์ธํ•ด ์ €๋„์˜ ๊ตฌ์„ฑ์ด ํฌ๊ฒŒ ๋ฐ”๋€Œ์—ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ด๋Ÿฌํ•œ ๋ณ€ํ™”๊ฐ€ ์ €๋„์˜ ์˜ํ–ฅ๋ ฅ์„ ํ–ฅ์ƒ์‹œํ‚ค์ง€ ๋ชปํ•œ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. 1. SIAM ๋ฆฌ๋ทฐ์˜ ๊ฐœ์š”์™€ ๋ณ€ํ™” SIAM ๋ฆฌ๋ทฐ๋Š” SIAM์—์„œ ๋ฐœํ–‰ํ•˜๋Š” 12๊ฐœ ์ด์ƒ์˜ ํ•™์ˆ  ์ €๋„ ์ค‘ ํ•˜๋‚˜๋กœ, ๋ชจ๋“  ํšŒ์›์—๊ฒŒ ๋ฐฐํฌ๋˜๋Š” ์„ ๋„์ ์ธ ์ €๋„์ด๋‹ค. 1999๋…„์— ์ด๋ฃจ์–ด์ง„ ์ฃผ์š” ๋ณ€๊ฒฝ ์‚ฌํ•ญ์€ ์ €๋„์˜ ํ”„๋กœํ•„์„ ๋†’์ด๊ธฐ ์œ„ํ•œ ๊ฒƒ์ด์—ˆ๋‹ค. ์ด ๋ณ€ํ™”๋Š” ์ปฌ๋Ÿฌ ์ธ์‡„ ๋„์ž…๊ณผ ํ•จ๊ป˜

Mathematics
A Class of Special Solutions for the Ultradiscrete Painleve II   Equation

A Class of Special Solutions for the Ultradiscrete Painleve II Equation

: ๋ณธ ๋…ผ๋ฌธ์€ ํŒŒ์ธ๋ ˆ๋ธŒ II ๋ฐฉ์ •์‹์˜ ์ดˆ๊ณ ๊ธ‰ ์ด์‚ฐํ™”๋œ ํ˜•ํƒœ๋ฅผ ์—ฐ๊ตฌํ•˜๊ณ , ์ด๋ฅผ ํ†ตํ•ด ์–ป์–ด์ง€๋Š” ํŠน๋ณ„ํ•œ ํ•ด์— ๋Œ€ํ•ด ์‹ฌ๋„ ์žˆ๊ฒŒ ๋ถ„์„ํ•œ๋‹ค. ํŠนํžˆ, q ์ฐจ๋ถ„ ์œ ์‚ฌํ˜• ์—์–ด๋ฆฌ ๋ฐฉ์ •์‹์„ ๊ธฐ๋ฐ˜์œผ๋กœ udPII (์ดˆ๊ณ ๊ธ‰ ์ด์‚ฐํ™” ํŒŒ์ธ๋ ˆ๋ธŒ II) ๋ฐฉ์ •์‹์˜ ํŠน์ˆ˜ํ•ด๋ฅผ ๊ตฌ์ถ•ํ•˜๊ณ  ๊ทธ ์„ฑ์งˆ์„ ํƒ๊ตฌํ•œ๋‹ค. ์ดˆ๊ณผ ์ด์‚ฐํ™”์™€ p ์ดˆ๊ณผ ์ด์‚ฐํ™” ์ดˆ๊ณผ ์ด์‚ฐํ™”๋Š” ์ฃผ์–ด์ง„ ์ฐจ๋ถ„ ๋ฐฉ์ •์‹์„ ์…€ ์˜คํ† ๋งˆํ†ค์œผ๋กœ ๋ณ€ํ™˜ํ•˜๋Š” ๊ณผ์ •์ด๋‹ค. ์ด ๊ณผ์ •์—์„œ ์ข…์† ๋ณ€์ˆ˜ x<sub>n</sub> ์€ ์ด์‚ฐ ๊ฐ’์„ ๊ฐ€์ง€๊ฒŒ ๋˜๋ฉฐ, ์ด๋ฅผ ํ†ตํ•ด ์›๋ž˜์˜ ๋ฏธ๋ถ„ ๋ฐฉ์ •์‹์ด ์กฐ๊ฐ ์„ ํ˜• ๋ฐฉ์ •์‹์œผ๋กœ ๊ทผ์‚ฌ๋œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ '์Œ์˜ ๋ฌธ์ œ'๋กœ

Nonlinear Sciences Mathematics
A conjecture on independent sets and graph covers

A conjecture on independent sets and graph covers

๋ณธ ๋…ผ๋ฌธ์€ ๊ทธ๋ž˜ํ”„ ์ด๋ก ์˜ ํ•ต์‹ฌ ๊ฐœ๋…์ธ ๋…๋ฆฝ ์ง‘ํ•ฉ๊ณผ ์ปค๋ฒ„๋ฅผ ๋‹ค๋ฃจ๋ฉฐ, ํŠนํžˆ M ์ปค๋ฒ„์™€ ๋ฒ ํ…Œ ๊ทผ์‚ฌ(Bethe approximation) ์‚ฌ์ด์˜ ๊ด€๊ณ„๋ฅผ ํƒ๊ตฌํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ์—ฐ๊ตฌ๋Š” ํ†ต๊ณ„ ๋ฌผ๋ฆฌํ•™์—์„œ ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•˜๋Š” ๋ถ„ํ•  ํ•จ์ˆ˜(partition function)์™€ ์ž์œ  ์—๋„ˆ์ง€(free energy)์— ๋Œ€ํ•œ ์ดํ•ด๋ฅผ ํ™•์žฅํ•˜๋Š” ๋ฐ ๊ธฐ์—ฌํ•œ๋‹ค. 1. ๋‹ค๋ณ€์ˆ˜ ๋…๋ฆฝ ์ง‘ํ•ฉ ๋‹คํ•ญ์‹๊ณผ M ์ปค๋ฒ„ ๋…ผ๋ฌธ์€ ๊ทธ๋ž˜ํ”„ G์˜ ๋‹ค๋ณ€์ˆ˜ ๋…๋ฆฝ ์ง‘ํ•ฉ ๋‹คํ•ญ์‹์„ ์ •์˜ํ•˜๊ณ , ์ด๋ฅผ ํ†ตํ•ด ๋…๋ฆฝ ์ง‘ํ•ฉ์˜ ํฌ๊ธฐ์— ๋”ฐ๋ฅธ ๊ฐ€์ค‘์น˜๋ฅผ ํ‘œํ˜„ํ•œ๋‹ค. ์ด ๋‹คํ•ญ์‹์€ G์˜ ๋ชจ๋“  ๋…๋ฆฝ ์ง‘ํ•ฉ I์— ๋Œ€ํ•ด x^{|I|

Computer Science Discrete Mathematics Mathematics
A deterministic algorithm for fitting a step function to a weighted   point-set

A deterministic algorithm for fitting a step function to a weighted point-set

: ๋ณธ ๋…ผ๋ฌธ์€ k๋‹จ๊ณ„ ํ•จ์ˆ˜๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ๊ฐ€์ค‘๋œ ์  ์ง‘ํ•ฉ์„ ๊ทผ์‚ฌํ•˜๋Š” ๋ฌธ์ œ์— ๋Œ€ํ•œ ์ƒˆ๋กœ์šด ์ ‘๊ทผ ๋ฐฉ์‹์„ ์ œ์•ˆํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์ด ๋ฌธ์ œ๋Š” ๋ฐ์ดํ„ฐ๋ฒ ์ด์Šค ์‘์šฉ ํ”„๋กœ๊ทธ๋žจ์—์„œ ํšจ์œจ์ ์ธ ๋ฐ์ดํ„ฐ ์ €์žฅ ๋ฐ ์ฟผ๋ฆฌ ์ฒ˜๋ฆฌ ์†๋„ ํ–ฅ์ƒ์„ ์œ„ํ•ด ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•ฉ๋‹ˆ๋‹ค. 1. k๋‹จ๊ณ„ ํ•จ์ˆ˜์™€ ์ค‘๋Ÿ‰์ ์˜ ์ •์˜ k๋‹จ๊ณ„ ํ•จ์ˆ˜๋Š” ์‹ค์ˆ˜ ์‹œํ€€์Šค๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ๊ฐ ๊ตฌ๊ฐ„์— ์ƒ์ˆ˜ ๊ฐ’์„ ๊ฐ€์ง€๋Š” ํ•จ์ˆ˜์ž…๋‹ˆ๋‹ค. ์ค‘๋Ÿ‰์ ์€ (x, y, w)๋กœ ํ‘œํ˜„๋˜๋ฉฐ, ์—ฌ๊ธฐ์„œ x์™€ y๋Š” ์ ์˜ ์ขŒํ‘œ์ด๊ณ , w๋Š” ํ•ด๋‹น ์ ์˜ ๋ฌด๊ฒŒ๋ฅผ ๋‚˜ํƒ€๋ƒ…๋‹ˆ๋‹ค. 2. ๊ทผ์‚ฌ ๋ฌธ์ œ ์ฃผ์–ด์ง„ ๊ฐ€์ค‘๋œ ์  ์ง‘ํ•ฉ P์— ๋Œ€ํ•ด k๋‹จ๊ณ„ ํ•จ์ˆ˜ f๋ฅผ ์ฐพ์•„์„œ P์™€

Computer Science Computational Geometry Data Structures
A Formal Approach for Agent Based Large Concurrent Intelligent Systems

A Formal Approach for Agent Based Large Concurrent Intelligent Systems

: ๋ณธ ๋…ผ๋ฌธ์€ ์—์ด์ „ํŠธ ๊ธฐ๋ฐ˜ ๋ชจ๋ธ๋ง์„ ํ†ตํ•œ ๋ณต์žก ์ง€๋Šฅํ˜• ์‹œ์Šคํ…œ ์„ค๊ณ„์— ์ดˆ์ ์„ ๋งž์ถ”๊ณ  ์žˆ์œผ๋ฉฐ, ์ด๋Š” ํ˜„์žฌ์˜ ํ”„๋กœ์ ํŠธ ๊ด€๋ฆฌ์™€ ์‹œ์Šคํ…œ ๊ฐœ๋ฐœ์—์„œ ์ง๋ฉดํ•˜๋Š” ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•œ ์ƒˆ๋กœ์šด ์ ‘๊ทผ๋ฒ•์œผ๋กœ ์ œ์‹œ๋œ๋‹ค. ํŠนํžˆ, ์—์ด์ „ํŠธ ๊ธฐ๋ฐ˜ ๋ชจ๋ธ๋ง์€ ๋ณต์žกํ•œ ์‹œ์Šคํ…œ์„ ํšจ๊ณผ์ ์œผ๋กœ ์„ค๊ณ„ํ•˜๊ณ  ๊ตฌํ˜„ํ•  ์ˆ˜ ์žˆ๋Š” ๋ฐฉ๋ฒ•๋ก  ์ค‘ ํ•˜๋‚˜๋กœ ์ฃผ๋ชฉ๋ฐ›๊ณ  ์žˆ๋‹ค. 1. ์—์ด์ „ํŠธ์˜ ์ž์œจ์„ฑ๊ณผ ๋ฐ˜์‘์„ฑ ๋…ผ๋ฌธ์—์„œ๋Š” ์—์ด์ „ํŠธ์˜ ํ•ต์‹ฌ ํŠน์ง•์œผ๋กœ ์ž์œจ์„ฑ๊ณผ ๋ฐ˜์‘์„ฑ์„ ๊ฐ•์กฐํ•œ๋‹ค. ์ž์œจ์„ฑ์€ ์—์ด์ „ํŠธ๊ฐ€ ์Šค์Šค๋กœ ์ž‘๋™ํ•˜๊ณ , ์‹œ์Šคํ…œ ๋ชฉํ‘œ๋ฅผ ๋‹ฌ์„ฑํ•˜๊ธฐ ์œ„ํ•ด ๋‚ด๋ถ€ ํ•˜์œ„ ๋ชฉํ‘œ๋ฅผ ์„ค์ •ํ•˜๊ณ  ์ด๋ฅผ ์ˆ˜ํ–‰ํ•˜๋Š” ๋Šฅ๋ ฅ์„ ์˜๋ฏธํ•œ๋‹ค. ์ด

Software Engineering Computer Science System
A Frequent Closed Itemsets Lattice-based Approach for Mining Minimal   Non-Redundant Association Rules

A Frequent Closed Itemsets Lattice-based Approach for Mining Minimal Non-Redundant Association Rules

: ๋ณธ ๋…ผ๋ฌธ์€ ํ˜‘์—… ๊ทœ์น™ ์ถ”์ถœ ๊ณผ์ •์—์„œ ์ค‘์š”ํ•œ ๋‘ ๋‹จ๊ณ„, ์ฆ‰ ๋นˆ๋„ ํ•ญ๋ชฉ ์ง‘ํ•ฉ(Frequent Itemsets)์˜ ๋ฐœ๊ฒฌ๊ณผ ์ด๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ํ•œ ํ˜‘์—… ๊ทœ์น™ ์ƒ์„ฑ์— ์ดˆ์ ์„ ๋งž์ถ”๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ํŠนํžˆ, ์ด ์—ฐ๊ตฌ๋Š” ์ตœ์†Œ ๋น„์ค‘๋ณต ์—ฐ๊ด€ ๊ทœ์น™(MNAR) ์ถ”์ถœ์„ ์œ„ํ•œ ์ƒˆ๋กœ์šด ์ ‘๊ทผ๋ฒ•์„ ์ œ์•ˆํ•˜๋ฉฐ, ๊ธฐ์กด ๋ฐฉ๋ฒ•๋“ค๊ณผ ๋น„๊ต ๋ถ„์„์„ ํ†ตํ•ด ๊ทธ ํšจ์œจ์„ฑ์„ ์ž…์ฆํ•˜๊ณ ์ž ํ•ฉ๋‹ˆ๋‹ค. 1. ํ˜‘์—… ๊ทœ์น™ ์ถ”์ถœ์˜ ๊ธฐ๋ณธ ๊ฐœ๋…๊ณผ ์•Œ๊ณ ๋ฆฌ์ฆ˜ ํ˜‘์—… ๊ทœ์น™ ์ถ”์ถœ์€ ํฌ๊ฒŒ ๋‘ ๋‹จ๊ณ„๋กœ ๋‚˜๋ˆŒ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค: ๋นˆ๋„ ํ•ญ๋ชฉ ์ง‘ํ•ฉ(FI) ๋˜๋Š” ๋นˆ๋„ ๋‹ซํžŒ ํ•ญ๋ชฉ ์ง‘ํ•ฉ(FCI)์„ ์ฐพ๋Š” ๊ณผ์ •๊ณผ ์ด๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ํ˜‘์—… ๊ทœ์น™์„ ์ƒ

Computer Science Databases
A generalized Young inequality and some new results on fractal space

A generalized Young inequality and some new results on fractal space

: ๋ณธ ์—ฐ๊ตฌ๋Š” ๊ณ ์ „์ ์ธ ์˜ ๋ถˆํ‰๋“ฑ์„ ๋ถ„์ˆ˜ ์ง‘ํ•ฉ์—์„œ ์ผ๋ฐ˜ํ™”ํ•˜๋Š” ๋ฐ ์ดˆ์ ์„ ๋งž์ถ”๊ณ  ์žˆ๋‹ค. ์ด๋Š” ์–‘(Yang) ๋ถ„์ˆ˜ ์ง‘ํ•ฉ๊ณผ ๊ทธ ๊ธฐํ•˜ํ•™์  ํ‘œํ˜„์„ ํ†ตํ•ด ์ด๋ฃจ์–ด์ง„๋‹ค. ์ด๋Ÿฌํ•œ ์ ‘๊ทผ๋ฒ•์€ ์‹ค์ˆ˜ ๋ฒˆ์„ ๋ถ„์ˆ˜ ์ฐจ์›์œผ๋กœ ํ•ด์„ํ•จ์œผ๋กœ์จ, ๊ณ ์ „์ ์ธ ๋ถˆํ‰๋“ฑ์˜ ์ƒˆ๋กœ์šด ๊ด€์ ๊ณผ ํ™•์žฅ์„ฑ์„ ์ œ๊ณตํ•œ๋‹ค. 1. ์–‘(Yang) ๋ถ„์ˆ˜ ์ง‘ํ•ฉ ์ด๋ก  ์–‘(Yang) ๋ถ„์ˆ˜ ์ง‘ํ•ฉ ์ด๋ก ์€ ๊ธฐ์กด์˜ ์‹ค์ˆ˜ ์ง‘ํ•ฉ์—์„œ ๋ฒ—์–ด๋‚˜, ๋ถ„์ˆ˜ ์ฐจ์›์„ ๊ฐ–๋Š” ์ง‘ํ•ฉ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ•œ๋‹ค. ํŠนํžˆ, ์–‘(Yang) ๊ธฐํ•˜ํ•™์  ํ‘œํ˜„์—์„œ๋Š” ์‹ค์ˆ˜ ๋ฒˆ์ด ๋ถ„์ˆ˜ ์ฐจ์›์˜ ์ ์œผ๋กœ ํ•ด์„๋œ๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด, 1ฮฑ + 2ฮฑ 3ฮฑ์™€ ๊ฐ™์€ ๊ด€๊ณ„๊ฐ€

Mathematics
A Majorization Order on Monomials and Termination of a Successive   Difference Substitution Algorithm

A Majorization Order on Monomials and Termination of a Successive Difference Substitution Algorithm

๋ณธ ๋…ผ๋ฌธ์€ ์„ฑ๊ณต์ ์ธ ์ฐจ๋ถ„ ๋Œ€์ฒด ์•Œ๊ณ ๋ฆฌ์ฆ˜(KSDS)์˜ ์ข…๊ฒฐ์„ฑ์— ๋Œ€ํ•œ ์‹ฌ๋„ ์žˆ๋Š” ์—ฐ๊ตฌ๋ฅผ ์ œ๊ณตํ•˜๋ฉฐ, ํŠนํžˆ ์ฃผ์š”ํ™” ์ˆœ์„œ๋ฅผ ์ด์šฉํ•˜์—ฌ ์ด ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด ์–ธ์ œ ์ข…๋ฃŒ๋˜๋Š”์ง€ ๋ถ„์„ํ•œ๋‹ค. KSDS๋Š” ๋‹คํ•ญ์‹ ํ•จ์ˆ˜์—์„œ ํŠน์ • ์กฐ๊ฑด์„ ๋งŒ์กฑํ•˜๋Š” ๊ฒฝ์šฐ ์–‘์ ์œผ๋กœ ์ข…๋ฃŒ๋˜๋ฉฐ, ์ด๋Ÿฌํ•œ ์กฐ๊ฑด์€ ์ฃผ๋กœ ๋‹จํ•ญ์‹์˜ ๊ณ„์ˆ˜์™€ ๊ทธ๋“ค์˜ ๊ด€๊ณ„์— ๊ธฐ๋ฐ˜ํ•œ๋‹ค. 1. KSDS์˜ ์ •์˜ ๋ฐ ๋ฐฐ๊ฒฝ KSDS๋Š” ์ž…๋ ฅ ํ•จ์ˆ˜ f๋ฅผ ๋‹คํ•ญ์‹ ํ˜•ํƒœ๋กœ ํ‘œํ˜„ํ•˜๊ณ , ์ด ๋‹คํ•ญ์‹์—์„œ ํŠน์ •ํ•œ ๋Œ€์ฒด ๊ทœ์น™์„ ์ ์šฉํ•˜์—ฌ ์ƒˆ๋กœ์šด ๋‹คํ•ญ์‹์„ ์ƒ์„ฑํ•˜๋Š” ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด๋‹ค. ๋…ผ๋ฌธ์—์„œ๋Š” ๋‹จํ•ญ์‹์ด ์–‘์ˆ˜ ๋˜๋Š” ์Œ์ˆ˜ ๊ณ„์ˆ˜๋ฅผ ๊ฐ€์งˆ ๋•Œ์˜ ํŠน์„ฑ์„ ์ •์˜ํ•œ๋‹ค. ํŠน

Computer Science Symbolic Computation Mathematics
A method to develop mission critical data processing systems for   satellite based instruments. The spinning mode case

A method to develop mission critical data processing systems for satellite based instruments. The spinning mode case

๋ณธ ๋…ผ๋ฌธ์€ ํ˜„๋Œ€ ์œ„์„ฑ ์‹คํ—˜์˜ ๋ณต์žก์„ฑ์„ ๊ณ ๋ คํ•œ ๋ฐ์ดํ„ฐ ์ฒ˜๋ฆฌ ์‹œ์Šคํ…œ ๊ฐœ๋ฐœ ๋ฐฉ๋ฒ•๋ก ์— ์ดˆ์ ์„ ๋งž์ถ”๊ณ  ์žˆ๋‹ค. ํŠนํžˆ, ํšŒ์ „ ๋ชจ๋“œ์—์„œ์˜ ๋ฐ์ดํ„ฐ ์ฒ˜๋ฆฌ๋ฅผ ์œ„ํ•œ SPIPI ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์•ˆํ•˜๊ณ , ์ด๋ฅผ ํ†ตํ•ด ์œ„์„ฑ ๊ธฐ๋ฐ˜ ์‹คํ—˜์—์„œ ๋ฐœ์ƒํ•˜๋Š” ๋‹ค์–‘ํ•œ ์ž์› ๊ด€๋ จ ์ œ์•ฝ ์กฐ๊ฑด์„ ํ•ด๊ฒฐํ•˜๋ ค๋Š” ์˜๋„๊ฐ€ ๋ช…ํ™•ํžˆ ๋“œ๋Ÿฌ๋‚œ๋‹ค. 1. ์‹œ์Šคํ…œ ๊ฐœ์š” ๋ฐ ๋ฌธ์ œ ์ธ์‹ ํ˜„๋Œ€ ์œ„์„ฑ ์‹คํ—˜์€ ๋น„ํ–‰ ๋ฐ ์ง€์ƒ ์„ธ๊ทธ๋จผํŠธ๋กœ ๊ตฌ์„ฑ๋œ ๋ณต์žกํ•œ ์‹ค์‹œ๊ฐ„ ์‹œ์Šคํ…œ์œผ๋กœ, ํฌ๊ธฐ, ๋ฌด๊ฒŒ, ์ „๋ ฅ ์†Œ๋น„, ์‹ค์‹œ๊ฐ„ ์‘๋‹ต ์š”๊ตฌ์‚ฌํ•ญ, ๊ณ ์žฅ ๋‚ด์„ฑ ๋“ฑ์˜ ์ž์› ๊ด€๋ จ ์ œ์•ฝ ์กฐ๊ฑด์„ ๊ฐ€์ง„๋‹ค. ์ด๋Ÿฌํ•œ ์‹œ์Šคํ…œ์€ ๋†’์€ ์ˆ˜์ค€์˜ ๋ณด์ฆ์ด ํ•„์š”ํ•˜๋ฉฐ, ํ•˜

Astrophysics System Software Engineering Computer Science Data
No Image

A New Limit on Planck Scale Lorentz Violation from Gamma-ray Burst Polarization

์ด ๋…ผ๋ฌธ์€ ์šฐ์ฃผํ•™์  ์š”์ธ์„ ๊ณ ๋ คํ•œ ๋กœ๋ Œ์ธ  ๋ถˆ๋ณ€์„ฑ ์œ„๋ฐ˜(LIV)์˜ ์ฒซ ๋ฒˆ์งธ ์ฐจ์ˆ˜ $E/M {rm Planck}$์— ๋Œ€ํ•œ ์ œ์•ฝ์„ ๊ฒ€ํ† ํ•˜๊ณ , ์ด๋ฅผ ํ†ตํ•ด ๊ด‘์ž์— ๋Œ€ํ•œ LIV๋ฅผ ๋ถ„์„ํ•œ๋‹ค. ํŠนํžˆ, ๊ฐ๋งˆ์„  ํญ๋ฐœ GRB041219a์—์„œ ๊ด€์ฐฐ๋œ ์†Œ๊ทน์„ฑ ๊ฐ๋งˆ์„  ๋ฐฉ์ถœ์˜ ๊ทนํ™”๋ฅผ ์ด์šฉํ•˜์—ฌ ์ง„๊ณต ์ด์ค‘๊ตด์ ˆ์ด ์—†๋Š” ๊ฒƒ์„ ํ™•์ธํ•จ์œผ๋กœ์จ, ๋กœ๋ Œ์ธ  ์œ„๋ฐ˜์„ ๊ฒ€์ฆํ•˜๋Š” ์ƒˆ๋กœ์šด ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ์ตœ๊ทผ ๊ฐœ์„ ๋œ ํญ๋ฐœ์˜ ์ ์ƒ‰ํŽธ์ด ์ถ”์ • ๋ฐฉ๋ฒ•์„ ์‚ฌ์šฉํ•˜์—ฌ QED์— ๋Œ€ํ•œ ํšจ๊ณผ์  ๊ตญ์†Œ ์–‘์ž์žฅ ์ด๋ก (QFT)์˜ ๋ผ๊ทธ๋ž‘์ง€์•ˆ์— ๋Œ€ํ•œ ์ฐจ์› 5 ๋กœ๋ Œ์ธ  ์œ„๋ฐ˜ ์ˆ˜์ •์— ๋Œ€ํ•œ ์ œ์•ฝ์„ ์œ ๋„ํ•œ๋‹ค.

Astrophysics HEP-PH General Relativity
A Non-Equilibrium Ionization Model of the Local and Loop I Bubbles -   Tracing the Ovi Distribution

A Non-Equilibrium Ionization Model of the Local and Loop I Bubbles - Tracing the Ovi Distribution

: ๋ณธ ๋…ผ๋ฌธ์€ ํ˜„์ง€ ๊ฑฐํ’ˆ(Local Bubble)๊ณผ Loop I ๊ฑฐํ’ˆ์˜ ๋น„ํ‰ํ˜• ์ด์˜จํ™” ๊ตฌ์กฐ์— ๋Œ€ํ•œ ์‹ฌ์ธต์ ์ธ ๋ถ„์„์„ ์ œ๊ณตํ•˜๋ฉฐ, ํŠนํžˆ OVI(Oxygen VI) ํก์ˆ˜ ๊ธฐ์กฐ ๋ฐ€๋„์™€ ๊ด€๋ จ๋œ ๊ด€์ธก ๋ฐ์ดํ„ฐ๋ฅผ ์žฌํ˜„ํ•˜๋Š” ๋ฐ ์ดˆ์ ์„ ๋งž์ถ”๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์—ฐ๊ตฌ๋Š” ๊ณ ํ•ด์ƒ๋„ 3์ฐจ์› ์œ ์ฒด์—ญํ•™ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ํ†ตํ•ด ์ด์˜จํ™” ๊ตฌ์กฐ์˜ ์ง„ํ™”๋ฅผ ์ถ”์ ํ•˜๊ณ , ์ด๋ฅผ ์‹ค์ œ ๊ด€์ธก ๊ฒฐ๊ณผ์™€ ๋น„๊ตํ•˜์—ฌ LB ๋ฐ Loop I ๊ฑฐํ’ˆ์˜ ๋ฌผ๋ฆฌ์  ํŠน์„ฑ์„ ์ดํ•ดํ•˜๋Š”๋ฐ ์ค‘์ ์„ ๋‘์—ˆ์Šต๋‹ˆ๋‹ค. ์„œ๋ก : ํ˜„์ง€ ๊ฑฐํ’ˆ์€ ํƒœ์–‘๊ณ„ ์ฃผ๋ณ€์— ์œ„์น˜ํ•œ X์„  ๋ฐฉ์ถœ ์ง€์—ญ์œผ๋กœ, ๊ทธ ํฌ๊ธฐ์™€ ์„ฑ์งˆ์ด ์—ฌ์ „ํžˆ ์™„๋ฒฝํ•˜๊ฒŒ ์ดํ•ด๋˜์ง€ ์•Š์€ ์ƒํƒœ

Astrophysics Model
A non-standard Lax formulation of the Harry Dym hierarchy and its   supersymmetric extension

A non-standard Lax formulation of the Harry Dym hierarchy and its supersymmetric extension

์ด ๋…ผ๋ฌธ์€ ๊ณ ์ „ ํ†ตํ•ฉ ๊ฐ€๋Šฅํ•œ ์‹œ์Šคํ…œ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ•˜๋ฉด์„œ ํŠนํžˆ Korteweg de Vries (KdV) ๋ฐฉ์ •์‹๊ณผ Harry Dym (HD) ๋ฐฉ์ •์‹์„ ์ค‘์‹ฌ์œผ๋กœ ์ƒˆ๋กœ์šด N 2 ์ดˆ๋Œ€์นญ HD ๋ฐฉ์ •์‹์„ ๋ฐœ๊ฒฌํ•˜๊ณ ์ž ํ•ฉ๋‹ˆ๋‹ค. ์ด๋“ค ๋ฐฉ์ •์‹์€ ์ˆ˜์‹ญ ๋…„ ๋™์•ˆ ๋‹ค์–‘ํ•œ ํ™•์žฅ์ด ์ด๋ฃจ์–ด์ ธ ์™”์œผ๋ฉฐ, ํŠนํžˆ ์ˆ˜ํผ ๋Œ€์นญ ํ™•์žฅ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๊ฐ€ ํ™œ๋ฐœํ–ˆ์Šต๋‹ˆ๋‹ค. 1. ๊ณ ์ „ ํ†ตํ•ฉ ๊ฐ€๋Šฅํ•œ ์‹œ์Šคํ…œ๊ณผ ์ˆ˜ํผ ๋Œ€์นญํ™” ๊ณ ์ „ ํ†ตํ•ฉ ๊ฐ€๋Šฅํ•œ ์‹œ์Šคํ…œ์€ ์†”๋ฆฌํ†ค ๋ฐฉ์ •์‹์œผ๋กœ ์•Œ๋ ค์ ธ ์žˆ์œผ๋ฉฐ, ์ด๋“ค ๋ฐฉ์ •์‹์€ ๋‹ค์–‘ํ•œ ํ™•์žฅ์ด ๊ฐ€๋Šฅํ•ฉ๋‹ˆ๋‹ค. ํŠนํžˆ ์ˆ˜ํผ ๋Œ€์นญ ํ™•์žฅ์„ ํ†ตํ•ด ์ƒˆ๋กœ์šด ๋ณด์† ํ•„๋“œ๊ฐ€ ๋„์ž…๋˜๊ฑฐ๋‚˜ ๊ธฐ

Nonlinear Sciences
A note on the generalized min-sum set cover problem

A note on the generalized min-sum set cover problem

๋งค๋ ฅ์ ์ธ ํ•œ๊ธ€ ์ œ๋ชฉ: ์ผ๋ฐ˜ํ™”๋œ ์ตœ์†Œ ํ•ฉ ์ง‘ํ•ฉ ์ปค๋ฒ„ ๋ฌธ์ œ์— ๋Œ€ํ•œ ๊ฐœ์„ ๋œ ์•Œ๊ณ ๋ฆฌ์ฆ˜ ์ดˆ๋ก ์ „์ฒด ๋ฒˆ์—ญ ๋ฐ ์ •๋ฆฌ: ์ด ๋…ผ๋ฌธ์—์„œ๋Š” ์ผ๋ฐ˜ํ™”๋œ ์ตœ์†Œ ํ•ฉ ์ง‘ํ•ฉ ์ปค๋ฒ„ ๋ฌธ์ œ๋ฅผ ๋‹ค๋ฃจ๋ฉฐ, ์ด ๋ฌธ์ œ๋Š” Feige, Lovรกsz, Tetali์™€ Hassin, Levin์ด ๊ฐ๊ฐ ์†Œ๊ฐœํ•œ ์ตœ์†Œ ํ•ฉ ์ง‘ํ•ฉ ์ปค๋ฒ„ ๋ฌธ์ œ์™€ ์ตœ์†Œ ์ง€์—ฐ ์ง‘ํ•ฉ ์ปค๋ฒ„ ๋ฌธ์ œ์˜ ์ผ๋ฐ˜ํ™”์ž…๋‹ˆ๋‹ค. Azar, Gamzu, Yin์€ O(log r) ๊ทผ์‚ฌ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์‹œํ–ˆ์œผ๋ฉฐ, Bansal, Gupta, Krishnaswamy๋Š” ์ด๋ฅผ ๊ฐœ์„ ํ•˜์—ฌ 485.1์˜ ์„ฑ๋Šฅ ๋ณด์žฅ์„ ๋‹ฌ์„ฑํ–ˆ์Šต๋‹ˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” Skutella

Computer Science Data Structures
A Note on the Grothendieck Group of an Additive Category

A Note on the Grothendieck Group of an Additive Category

๋งค๋ ฅ์ ์ธ ํ•œ๊ธ€ ์ œ๋ชฉ: ๊ฐ€์‚ฐ ๋ฒ”์ฃผ์™€ ๊ทธ๋กœํ…๋””ํฌ ๊ทธ๋ฃน์˜ ๋™ํ˜•์„ฑ ์ดˆ๋ก ์ „์ฒด ๋ฒˆ์—ญ ๋ฐ ์ •๋ฆฌ: ๋ณธ ๋…ผ๋ฌธ์€ ๊ฐ€์‚ฐ ๋ฒ”์ฃผ์˜ ์Šคํ”Œ๋ฆฟ ๊ทธ๋กœํ…๋””ํฌ ๊ทธ๋ฃน๊ณผ ํ•ด๋‹น ๋ฒ”์ฃผ์˜ ์œ ํ•œ ๋ณต์žก์ฒด์˜ ํ˜ธ๋ชจํ† ํ”ผ ๋ฒ”์ฃผ์—์„œ์˜ ์‚ผ๊ฐํ™”๋œ ๊ทธ๋กœํ…๋””ํฌ ๊ทธ๋ฃน์ด ๋™ํ˜•์ธ์ง€์— ๋Œ€ํ•œ ์งˆ๋ฌธ์„ ๋‹ค๋ฃฌ๋‹ค. ํŠนํžˆ, ๊ฐ€์‚ฐ ๋ฒ”์ฃผ A์™€ ๊ทธ์˜ ์œ ํ•œ ๋ณต์žก์ฒด์˜ ํ˜ธ๋ชจํ† ํ”ผ ๋ฒ”์ฃผ Kb(A)๋ฅผ ๊ณ ๋ คํ•  ๋•Œ, A์˜ ์Šคํ”Œ๋ฆฟ ๊ทธ๋กœํ…๋””ํฌ ๊ทธ๋ฃน KโŠ•(A)๊ฐ€ Kb(A)์˜ ์‚ผ๊ฐํ™”๋œ ๊ทธ๋กœํ…๋””ํฌ ๊ทธ๋ฃน Kโ–ณ(Kb(A))์™€ ๋™ํ˜•์ธ ๊ฒƒ์„ ์ฆ๋ช…ํ•œ๋‹ค. ์ด๋Š” ํ˜ธ๋ชจํ† ํ”ผ ๋ฒ”์ฃผ์—์„œ์˜ ์—์šธ๋Ÿฌ ํŠน์„ฑ์ด ์›๋ž˜ ๊ตฌ์กฐ๋ฅผ ๋ณต์›ํ•˜๋Š” ๋ฐ ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•œ๋‹ค๋Š” ์ ์—์„œ

Mathematics
A Note on the Group-theoretic Approach to Fast Matrix Multiplication

A Note on the Group-theoretic Approach to Fast Matrix Multiplication

: ์ด ๋…ผ๋ฌธ์€ ํ–‰๋ ฌ ๊ณฑ์…ˆ ์•Œ๊ณ ๋ฆฌ์ฆ˜์˜ ๋ณต์žก๋„๋ฅผ ์ค„์ด๋Š” ๋ฐ ์žˆ์–ด ๊ทธ๋ฃน ์ด๋ก ์  ์ ‘๊ทผ ๋ฐฉ์‹์˜ ์ค‘์š”์„ฑ์— ๋Œ€ํ•ด ํƒ๊ตฌํ•˜๊ณ  ์žˆ๋‹ค. ์ „ํ†ต์ ์ธ ํ–‰๋ ฌ ๊ณฑ์…ˆ ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ O(nยณ) ์‹œ๊ฐ„ ๋ณต์žก๋„๋ฅผ ๊ฐ€์ง„๋‹ค. ๊ทธ๋Ÿฌ๋‚˜, ๋ณด๋‹ค ํšจ์œจ์ ์ธ ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด ์กด์žฌํ•˜๋ฉฐ, ๊ฐ€์žฅ ๋น ๋ฅธ ์•Œ๋ ค์ง„ ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ Don Coppersmith์™€ Shmuel Winograd์— ์˜ํ•ด ์ œ์‹œ๋œ O(nยฒ.376) ์‹œ๊ฐ„ ๋ณต์žก๋„์˜ ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด๋‹ค. ๋…ผ๋ฌธ์—์„œ๋Š” ํ–‰๋ ฌ ๊ณฑ์…ˆ ์•Œ๊ณ ๋ฆฌ์ฆ˜์˜ ์„ฑ๋Šฅ์„ ํ–ฅ์ƒ์‹œํ‚ค๋Š” ๋ฐ ์žˆ์–ด ๊ทธ๋ฃน ์ด๋ก ์  ์ ‘๊ทผ ๋ฐฉ์‹์˜ ์ค‘์š”์„ฑ์„ ๊ฐ•์กฐํ•œ๋‹ค. ํŠนํžˆ, 2003๋…„์— ์ฝ”ํ—จ(Cohn)๊ณผ ์šฐ๋งŒ์Šค(Umans)์ด

Computer Science Symbolic Computation Mathematics
A note on triangle-free graphs

A note on triangle-free graphs

: ๋ณธ ๋…ผ๋ฌธ์€ ์‚ผ๊ฐ ๋ฌด๋ณ€ ๊ทธ๋ž˜ํ”„์˜ ์ด๋ก ์  ํƒ๊ตฌ๋ฅผ ์ค‘์‹ฌ์œผ๋กœ ์ง„ํ–‰๋˜๋ฉฐ, ํŠนํžˆ ์ด๋Ÿฌํ•œ ๊ทธ๋ž˜ํ”„๊ฐ€ ๊ฐ–๋Š” ํŠน์„ฑ๊ณผ ๊ทธ์— ๋”ฐ๋ฅธ ์—ฌ๋Ÿฌ ์กฐ๊ฑด๋“ค์„ ๋ถ„์„ํ•˜๊ณ  ์žˆ๋‹ค. ์‚ผ๊ฐ ๋ฌด๋ณ€ ๊ทธ๋ž˜ํ”„๋ž€ ๊ฐ„๋‹จํžˆ ๋งํ•ด ์‚ผ๊ฐํ˜•์„ ํฌํ•จํ•˜์ง€ ์•Š๋Š” ๊ทธ๋ž˜ํ”„๋ฅผ ์˜๋ฏธํ•˜๋ฉฐ, ์ด๋Š” ๊ทธ๋ž˜ํ”„ ์ด๋ก ์—์„œ ์ค‘์š”ํ•œ ์—ฐ๊ตฌ ๋Œ€์ƒ ์ค‘ ํ•˜๋‚˜์ด๋‹ค. ๋…ผ๋ฌธ์˜ ์ดˆ๋ฐ˜๋ถ€์—์„œ๋Š” ๊ธฐ๋ณธ์ ์ธ ์šฉ์–ด์™€ ์ •์˜๊ฐ€ ์ œ์‹œ๋œ๋‹ค. ํŠนํžˆ, ์ •์ ๊ณผ ๊ฐ„์„ ์˜ ์ง‘ํ•ฉ, ์ฐจ์ˆ˜, ์ง€๋ฆ„ ๋“ฑ์˜ ๊ฐœ๋…์ด ์†Œ๊ฐœ๋˜๋ฉฐ, ์ด๋Ÿฌํ•œ ๊ธฐ์ดˆ์ ์ธ ์ •์˜๋“ค์€ ์ดํ›„ ๋…ผ์˜์— ์žˆ์–ด ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•œ๋‹ค. ๋˜ํ•œ, Cn๊ณผ Km,n์ด๋ผ๋Š” ํŠน๋ณ„ํ•œ ํ˜•ํƒœ์˜ ๊ทธ๋ž˜ํ”„๋“ค์ด ์–ธ๊ธ‰๋˜๋Š”๋ฐ, ์ด๋Š” ์‚ผ๊ฐ ๋ฌด๋ณ€

Computer Science Discrete Mathematics
A Novel Adaptive Routing through Fitness Function Estimation Technique   with Multiple QoS Parameters Compliance

A Novel Adaptive Routing through Fitness Function Estimation Technique with Multiple QoS Parameters Compliance

๋ณธ ๋…ผ๋ฌธ์€ ๋„คํŠธ์›Œํฌ ๋ผ์šฐํŒ… ๊ธฐ์ˆ  ์ค‘ ํ•˜๋‚˜์ธ ๊ฑฐ๋ฆฌ ๋ฒกํ„ฐ(DV) ํ”„๋กœํ† ์ฝœ์„ ๊ฐœ์„ ํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ํŠนํžˆ, ๋‹ค์ค‘ QoS ๋งค๊ฐœ๋ณ€์ˆ˜๋ฅผ ์ค€์ˆ˜ํ•˜๋ฉด์„œ๋„ ํšจ์œจ์ ์ธ ๊ฒฝ๋กœ ์„ ํƒ์ด ๊ฐ€๋Šฅํ•œ ์ƒˆ๋กœ์šด ์ ์‘ํ˜• ๋ผ์šฐํŒ… ๊ธฐ๋ฒ•์— ์ดˆ์ ์„ ๋งž์ถ”๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. 1. ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์  ๋ผ์šฐํŒ…์€ ๋„คํŠธ์›Œํฌ์—์„œ ๋ฐ์ดํ„ฐ ํŒจํ‚ท์„ ์›ํ•˜๋Š” ๋ชฉ์ ์ง€๊นŒ์ง€ ์ „์†กํ•˜๊ธฐ ์œ„ํ•œ ํ•ต์‹ฌ ๊ธฐ์ˆ ์ž…๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜, ๊ธฐ์กด์˜ DV ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ ๋ผ์šฐํŒ… ๋ฃจํ”„์™€ count to infinity ๋ฌธ์ œ ๋“ฑ์˜ ํ•œ๊ณ„๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋ฌธ์ œ์ ์„ ํ•ด๊ฒฐํ•˜๊ณ ์ž ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ŠคํŒฌ๋‹ ํŠธ๋ฆฌ ์ ‘๊ทผ ๋ฐฉ์‹์„ ํ™œ์šฉํ•œ ์ƒˆ๋กœ์šด

Computer Science Networking
A Novel comprehensive method for real time Video Motion Detection   Surveillance

A Novel comprehensive method for real time Video Motion Detection Surveillance

๋ณธ ๋…ผ๋ฌธ์€ ์ €๋ ดํ•˜๊ณ  ํšจ์œจ์ ์ธ ์‹ค์‹œ๊ฐ„ ๋น„๋””์˜ค ๋ชจ์…˜ ๊ฐ์ง€ ๋ณด์•ˆ ์‹œ์Šคํ…œ(VMDss)์˜ ์„ค๊ณ„์™€ ๊ตฌํ˜„์„ ๋‹ค๋ฃจ๊ณ  ์žˆ๋‹ค. ์ด ์‹œ์Šคํ…œ์€ ์‚ฌ์šฉ์ž ์นœํ™”์ ์ด๊ณ  ์›๊ฒฉ ์ œ์–ด๊ฐ€ ๊ฐ€๋Šฅํ•˜๋ฉฐ, ๋ฏธ๋ฆฌ ์ •์˜๋œ ์ƒ‰์ƒ ๊ฐ์ฒด ์ถ”์  ๊ธฐ๋Šฅ์„ ํฌํ•จํ•˜๊ณ  ์žˆ์–ด ๋‹ค์–‘ํ•œ ํ™˜๊ฒฝ์—์„œ ์œ ์šฉํ•˜๊ฒŒ ํ™œ์šฉ๋  ์ˆ˜ ์žˆ๋‹ค. 1. ์‹œ์Šคํ…œ ๊ตฌ์„ฑ ์ „์†ก ์„น์…˜ : ์ปดํ“จํ„ฐ, RS232 ์ธํ„ฐํŽ˜์ด์Šค, ๋งˆ์ดํฌ๋กœ์ปจํŠธ๋กค๋Ÿฌ, RF ์†ก์‹ ๊ธฐ, RF ๋น„๋””์˜ค ์ˆ˜์‹ ๊ธฐ๋กœ ๊ตฌ์„ฑ๋˜์–ด ์žˆ์œผ๋ฉฐ, ์ด๋“ค ์š”์†Œ๋Š” ์‹œ๊ฐ ์ •๋ณด๋ฅผ ์ˆ˜์ง‘ํ•˜๊ณ  ์ œ์–ด ์‹ ํ˜ธ๋ฅผ ์ „์†กํ•˜๋Š” ์—ญํ• ์„ ์ˆ˜ํ–‰ํ•œ๋‹ค. ์ˆ˜์‹  ์„น์…˜ : ๋ชจ๋ฐ”์ผ ํ”Œ๋žซํผ, RF ์ˆ˜์‹ ๊ธฐ, ๋งˆ์ดํฌ๋กœ์ปจํŠธ๋กค๋Ÿฌ, RF ์นด๋ฉ”

Computer Science Computer Vision Detection
A point of order 8

A point of order 8

๋ณธ ๋…ผ๋ฌธ์€ ๋ณต์†Œํ‰๋ฉด ์ƒ์˜ ์ด์‚ฐ์  ๊ณก์„ , ํŠนํžˆ ํƒ€์›๊ณก์„ ์—์„œ 8์ฐจ ์ฃผ๊ธฐ์ ์„ ํ‘œํ˜„ํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค. ์ด๋Š” ์ˆ˜ํ•™์ ์œผ๋กœ ๋งค์šฐ ์ค‘์š”ํ•œ ๊ฐœ๋…์œผ๋กœ, ํŠนํžˆ ํƒ€์›๊ณก์„ ์ด ๊ฐ–๋Š” ๋Œ€์ˆ˜์  ๊ตฌ์กฐ์™€ ๊ธฐํ•˜ํ•™์  ์„ฑ์งˆ์— ๋Œ€ํ•œ ์ดํ•ด๋ฅผ ๊นŠ๊ฒŒ ํ•œ๋‹ค. ํƒ€์›๊ณก์„ ์€ ๋ณต์†Œํ‰๋ฉด์—์„œ ๋‹ค์Œ๊ณผ ๊ฐ™์€ ๋ฐฉ์ •์‹์œผ๋กœ ์ •์˜๋œ๋‹ค:

Mathematics
A possible use of the Khas protractor

A possible use of the Khas protractor

: ๋ณธ ๋…ผ๋ฌธ์€ ๊ณ ๋Œ€ ์ด์ง‘ํŠธ ๊ฑด์ถ•๊ฐ€ ์นด์˜ ๋ฌด๋ค์—์„œ ๋ฐœ๊ฒฌ๋œ ๋ฌผ์ฒด๋ฅผ ์ž(protractor)๋กœ ๊ฐ„์ฃผํ•˜๊ณ , ์ด๋ฅผ ํ†ตํ•ด ๊ฒฝ์‚ฌ๋ฉด ๊ฐ๋„๋ฅผ ์ธก์ •ํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ๊ฐ€์„ค์€ ๊ณ ๋Œ€ ์ด์ง‘ํŠธ ์„๊ณต ๊ธฐ์ˆ ๊ณผ ๊ฑด์ถ•์— ๋Œ€ํ•œ ์ดํ•ด๋ฅผ ๋„“ํžˆ๋Š” ๋ฐ ์ค‘์š”ํ•œ ์˜๋ฏธ๊ฐ€ ์žˆ๋‹ค. 1. ์นด์˜ ๋ฌด๋ค์—์„œ ๋ฐœ๊ฒฌ๋œ ๋ฌผ์ฒด ์นด์™€ ๊ทธ์˜ ์•„๋‚ด ๋ฉ”๋ฆฌํŠธ์˜ ๋ฌด๋ค์€ 18์™•์กฐ ์‹œ๋Œ€์˜ ์™„๋ฒฝํ•˜๊ฒŒ ๋ณด์กด๋œ ๋ฌด๋ค์œผ๋กœ, ์ด๊ณณ์—์„œ๋Š” ๊ฑด์ถ•๊ฐ€ ์นด๊ฐ€ ์ผ์ƒ์ ์œผ๋กœ ์‚ฌ์šฉํ•˜๋˜ ์—ฌ๋Ÿฌ ๋„๊ตฌ๋“ค์ด ๋ฐœ๊ฒฌ๋˜์—ˆ๋‹ค. ํŠนํžˆ ๋ชฉ์žฌ๋กœ ๋งŒ๋“ค์–ด์ง„ ์ ‘์ด์‹ ๊ด€์ ˆ์„ ๊ฐ€์ง„ ์ž(cubit)์™€ ๊ธ€์“ฐ๊ธฐ ๋„๊ตฌ ๋“ฑ์ด ํฌํ•จ๋˜์–ด ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋ฌผํ’ˆ๋“ค์€ ์นด์˜ ์ง

Physics Mathematics

< Category Statistics (Total: 2544) >

Electrical Engineering and Systems Science
100
General
525
General Relativity
21
HEP-EX
17
HEP-LAT
3
HEP-PH
37
HEP-TH
19
MATH-PH
36
NUCL-EX
2
NUCL-TH
4
Quantum Physics
35

Start searching

Enter keywords to search articles

โ†‘โ†“
โ†ต
ESC
โŒ˜K Shortcut