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Privacy in Federated Learning with Spiking Neural Networks

Privacy in Federated Learning with Spiking Neural Networks

์ŠคํŒŒ์ดํ‚น ์‹ ๊ฒฝ๋ง(SNN)์ด ์ตœ๊ทผ ์—ฃ์ง€ ๋””๋ฐ”์ด์Šค์™€ ์ €์ „๋ ฅ AI ์†”๋ฃจ์…˜์—์„œ ๊ฐ๊ด‘๋ฐ›๋Š” ์ด์œ ๋Š”, ๋‰ด๋Ÿฐ์ด ์ŠคํŒŒ์ดํฌ(์ด์‚ฐ์ ์ธ ์ „๊ธฐ ํŽ„์Šค) ํ˜•ํƒœ๋กœ ์ •๋ณด๋ฅผ ์ „๋‹ฌํ•จ์œผ๋กœ์จ ์—ฐ์‚ฐ๋Ÿ‰๊ณผ ์—๋„ˆ์ง€ ์†Œ๋น„๋ฅผ ์ตœ์†Œํ™”ํ•  ์ˆ˜ ์žˆ๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ์ด๋Ÿฌํ•œ ๊ตฌ์กฐ์  ํŠน์„ฑ์€ ๊ธฐ์กด์˜ ์—ฐ์†์ ์ธ ํ™œ์„ฑ๊ฐ’์„ ์‚ฌ์šฉํ•˜๋Š” ์ธ๊ณต์‹ ๊ฒฝ๋ง(ANN)๊ณผ ๊ทผ๋ณธ์ ์œผ๋กœ ๋‹ค๋ฅด๋ฉฐ, ํŠนํžˆ ํ•™์Šต ๊ณผ์ •์—์„œ๋„ ์ฐจ๋ณ„์ ์„ ๋งŒ๋“ ๋‹ค. ANN์€ ์—ญ์ „ํŒŒ๋ฅผ ํ†ตํ•ด ์ •ํ™•ํ•œ ๋ฏธ๋ถ„๊ฐ’์„ ๊ณ„์‚ฐํ•ด ๊ฐ€์ค‘์น˜๋ฅผ ์—…๋ฐ์ดํŠธํ•˜์ง€๋งŒ, SNN์€ ์ŠคํŒŒ์ดํฌ ๋ฐœ์ƒ ์ž์ฒด๊ฐ€ ๋น„๋ฏธ๋ถ„ ๊ฐ€๋Šฅํ•˜๊ธฐ ๋•Œ๋ฌธ์— ๋Œ€๋ฆฌ ๊ทธ๋ž˜๋””์–ธํŠธ(surrogate gradient)๋ผ๋Š” ๊ทผ์‚ฌ ๋ฐฉ๋ฒ•์„ ๋„

Network Learning
Can Vibe Coding Beat Graduate CS Students? An LLM vs. Human Coding Tournament on Market-driven Strategic Planning

Can Vibe Coding Beat Graduate CS Students? An LLM vs. Human Coding Tournament on Market-driven Strategic Planning

์ด ๋…ผ๋ฌธ์€ ํ˜„์žฌ LLM ๊ธฐ๋ฐ˜ ์ฝ”๋“œ ์ƒ์„ฑ ์—ฐ๊ตฌ๊ฐ€ ์ง๋ฉดํ•œ ๊ทผ๋ณธ์ ์ธ ํ‰๊ฐ€ ๋ฌธ์ œ๋ฅผ ์งš์–ด๋‚ธ๋‹ค. ๋Œ€๋ถ€๋ถ„์˜ ๊ธฐ์กด ๋ฒค์น˜๋งˆํฌ๋Š” ๋‹จ์ˆœํžˆ ์ฝ”๋“œ๊ฐ€ ๋ฌธ๋ฒ•์ ์œผ๋กœ ์˜ฌ๋ฐ”๋ฅธ์ง€, ํ˜น์€ ์‚ฌ์ „ ์ •์˜๋œ ํ…Œ์ŠคํŠธ ์ผ€์ด์Šค๋ฅผ ํ†ต๊ณผํ•˜๋Š”์ง€๋งŒ์„ ํ™•์ธํ•œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์‹ค์ œ ์‚ฐ์—… ํ˜„์žฅ์—์„œ๋Š” ์ฝ”๋“œ๊ฐ€ ๋ณต์žกํ•œ ์˜์‚ฌ๊ฒฐ์ • ํ๋ฆ„, ์ตœ์ ํ™” ์•Œ๊ณ ๋ฆฌ์ฆ˜, ๊ทธ๋ฆฌ๊ณ  ๋‹ค์ค‘ ์—์ด์ „ํŠธ ๊ฐ„์˜ ์ „๋žต์  ์ƒํ˜ธ์ž‘์šฉ์„ ํšจ๊ณผ์ ์œผ๋กœ ๊ตฌํ˜„ํ•ด์•ผ ํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ์š”๊ตฌ๋ฅผ ๋ฐ˜์˜ํ•˜๊ธฐ ์œ„ํ•ด ์—ฐ๊ตฌ์ง„์€ Auctionโ€‘Pickupโ€‘Delivery Problem(APDP)์ด๋ผ๋Š” ๋ณตํ•ฉ ๋ฌผ๋ฅ˜ ๋ฌธ์ œ๋ฅผ ์„ ํƒํ–ˆ๋‹ค. APDP๋Š” ์ž…์ฐฐ ๋‹จ๊ณ„์—์„œ ๋ถˆํ™•์‹คํ•œ ๊ฒฝ์Ÿ ์ƒํ™ฉ

Leveraging LLMs for reward function design in reinforcement learning control tasks

Leveraging LLMs for reward function design in reinforcement learning control tasks

๋ณธ ๋…ผ๋ฌธ์ด ์ œ์‹œํ•˜๋Š” LEARNโ€‘Opt ํ”„๋ ˆ์ž„์›Œํฌ๋Š” ๊ฐ•ํ™”ํ•™์Šต์—์„œ ๋ณด์ƒ ํ•จ์ˆ˜๋ฅผ ์„ค๊ณ„ํ•˜๋Š” ์ „ํ†ต์ ์ธ ์›Œํฌํ”Œ๋กœ์šฐ๋ฅผ ๊ทผ๋ณธ์ ์œผ๋กœ ์žฌ๊ตฌ์„ฑํ•œ๋‹ค๋Š” ์ ์—์„œ ํ•™์ˆ ์ ยท์‹ค์šฉ์  ์˜์˜๊ฐ€ ํฌ๋‹ค. ๊ธฐ์กด ๋ฐฉ๋ฒ•๋“ค์€ ๋ณดํ†ต ๋‘ ๋‹จ๊ณ„, ์ฆ‰(1) ์ธ๊ฐ„์ด ์ •์˜ํ•œ ๋ฉ”ํŠธ๋ฆญ์„ ๊ธฐ๋ฐ˜์œผ๋กœ ํ›„๋ณด ๋ณด์ƒ ํ•จ์ˆ˜๋ฅผ ์ƒ์„ฑํ•˜๊ณ , (2) ์ธ๊ฐ„ ํ˜น์€ ์ „๋ฌธ๊ฐ€ ํ”ผ๋“œ๋ฐฑ์„ ํ†ตํ•ด ํ›„๋ณด๋ฅผ ์ •์ œํ•˜๋Š” ๊ณผ์ •์„ ๊ฑฐ์นœ๋‹ค. ์ด๋Ÿฌํ•œ ์ ‘๊ทผ์€ ์ธ๊ฐ„ ์ „๋ฌธ๊ฐ€์˜ ๊ฐ€์šฉ์„ฑ์— ํฌ๊ฒŒ ์˜์กดํ•˜๋ฉฐ, ํŠนํžˆ ๋ณต์žกํ•œ ๋„๋ฉ”์ธ์—์„œ๋Š” ๋ฉ”ํŠธ๋ฆญ ์„ค๊ณ„ ์ž์ฒด๊ฐ€ ์–ด๋ ค์šด ๋ฌธ์ œ๋‹ค. LEARNโ€‘Opt๋Š” LLM์„ ํ™œ์šฉํ•ด ์‹œ์Šคํ…œ ์„ค๋ช…๊ณผ ๊ณผ์ œ ๋ชฉํ‘œ๋งŒ์„ ์ž…๋ ฅ์œผ๋กœ ๋ฐ›์•„, ์ž๋™์œผ

Learning
Re-Key-Free, Risky-Free: Adaptable Model Usage Control

Re-Key-Free, Risky-Free: Adaptable Model Usage Control

ADALOC์ด ์ œ์‹œํ•˜๋Š” ํ•ต์‹ฌ ์•„์ด๋””์–ด๋Š” โ€œํ‚ค ์˜์—ญ(Access Key Region)โ€์„ ๋ชจ๋ธ ํŒŒ๋ผ๋ฏธํ„ฐ์˜ ์ผ๋ถ€๋กœ ๊ณ ์ •ํ•˜๊ณ , ์ดํ›„ ๋ฐœ์ƒํ•˜๋Š” ๋ชจ๋“  ํŒŒ์ธํŠœ๋‹ยท์ „์ดํ•™์Šตยท๋„๋ฉ”์ธ ์ ์‘ ๋“ฑ์„ ์ด ์˜์—ญ์—๋งŒ ์ œํ•œํ•œ๋‹ค๋Š” ์ ์ด๋‹ค. ๊ธฐ์กด์˜ ํ‚ค ๊ธฐ๋ฐ˜ ๋ณดํ˜ธ ๋ฐฉ์‹์€ ์ „์ฒด ํŒŒ๋ผ๋ฏธํ„ฐ์— ์•”ํ˜ธํ™”๋œ ๋งˆ์Šคํฌ๋ฅผ ์ ์šฉํ•˜๊ฑฐ๋‚˜, ํŠน์ • ๋ ˆ์ด์–ด์— ๋น„๋ฐ€๊ฐ’์„ ์‚ฝ์ž…ํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ๋ฐฉ๋ฒ•์€ ๋ชจ๋ธ์ด ์—…๋ฐ์ดํŠธ๋  ๋•Œ ๋งˆ์Šคํฌ๊ฐ€ ์†์ƒ๋˜๊ฑฐ๋‚˜, ์ƒˆ๋กœ์šด ํŒŒ๋ผ๋ฏธํ„ฐ๊ฐ€ ํ‚ค์™€ ๋…๋ฆฝ์ ์œผ๋กœ ๋ณ€ํ˜•๋ผ ๋ณดํ˜ธ๊ฐ€ ๋ฌดํšจํ™”๋˜๋Š” ๋ฌธ์ œ๊ฐ€ ์žˆ๋‹ค. ADALOC์€ ์ฒ˜์Œ ํ‚ค๋ฅผ ์„ ์ •ํ•  ๋•Œ, ๋ชจ๋ธ์˜ ์†์‹ค ๊ณก๋ฉด๊ณผ ํŒŒ๋ผ๋ฏธํ„ฐ ๋ฏผ๊ฐ๋„๋ฅผ ๋ถ„์„ํ•ด โ€œ์—…๋ฐ

Model
Understanding Accelerator Compilers via Performance Profiling

Understanding Accelerator Compilers via Performance Profiling

๋ณธ ๋…ผ๋ฌธ์€ ๊ฐ€์†๊ธฐ ์„ค๊ณ„ ์–ธ์–ด(ADL) ์ปดํŒŒ์ผ๋Ÿฌ๊ฐ€ ๊ฐ–๋Š” ๋ณธ์งˆ์ ์ธ ๋ณต์žก์„ฑ๊ณผ ์˜ˆ์ธก ๋ถˆ๊ฐ€๋Šฅ์„ฑ์„ ์ง€์ ํ•˜๊ณ , ์ด๋ฅผ ๋ณด์™„ํ•˜๊ธฐ ์œ„ํ•œ ํ”„๋กœํŒŒ์ผ๋ง ๋„๊ตฌ์˜ ํ•„์š”์„ฑ์„ ์„ค๋“๋ ฅ ์žˆ๊ฒŒ ์ œ์‹œํ•œ๋‹ค. ADL์€ ํ•˜๋“œ์›จ์–ด ์„ค๊ณ„์™€ ์†Œํ”„ํŠธ์›จ์–ด ๊ฐœ๋ฐœ ์‚ฌ์ด์˜ ์ค‘๊ฐ„ ๋‹จ๊ณ„์— ์œ„์น˜ํ•ด, ๋†’์€ ์ƒ์‚ฐ์„ฑ๊ณผ ์„ฑ๋Šฅ์„ ๋™์‹œ์— ์ถ”๊ตฌํ•œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๊ณ ์ˆ˜์ค€ ์–ธ์–ด์˜ ์ถ”์ƒํ™”์™€ ์‚ฌ์ดํดโ€‘์ •๋ฐ€ ํ•˜๋“œ์›จ์–ด ๊ตฌํ˜„ ์‚ฌ์ด์˜ ๋ณ€ํ™˜ ๊ณผ์ •์€ ๋‹ค์ค‘ ๋‹จ๊ณ„ ์ตœ์ ํ™”์™€ ๋ณต์žกํ•œ ์Šค์ผ€์ค„๋ง์„ ์š”๊ตฌํ•œ๋‹ค. ํŠนํžˆ, ๋ฐ์ดํ„ฐ ๊ฒฝ๋กœ ์ตœ์ ํ™”์™€ ์ œ์–ด ํ๋ฆ„ ๋ณ€ํ™˜์€ ์„œ๋กœ ์ƒ์ถฉ๋˜๋Š” ๋ชฉํ‘œ๋ฅผ ๊ฐ€์งˆ ์ˆ˜ ์žˆ์–ด, ์ปดํŒŒ์ผ๋Ÿฌ๋Š” ํœด๋ฆฌ์Šคํ‹ฑ ๊ธฐ๋ฐ˜ ์˜์‚ฌ๊ฒฐ์ •์„ ๋ฐ˜๋ณตํ•œ๋‹ค. ์ด๋Ÿฌ

VADE: Variance-Aware Dynamic Sampling via Online Sample-Level Difficulty Estimation for Multimodal RL

VADE: Variance-Aware Dynamic Sampling via Online Sample-Level Difficulty Estimation for Multimodal RL

GRPO์™€ GSPO์™€ ๊ฐ™์€ ๊ทธ๋ฃน ๊ธฐ๋ฐ˜ ์ •์ฑ… ์ตœ์ ํ™” ๊ธฐ๋ฒ•์€ ๋‹ค์ค‘๋ชจ๋‹ฌ ๋ชจ๋ธ์ด ๋ณต์žกํ•œ ์ž…๋ ฅโ€‘์ถœ๋ ฅ ๊ด€๊ณ„๋ฅผ ํ•™์Šตํ•˜๋„๋ก ์„ค๊ณ„๋˜์—ˆ์œผ๋ฉฐ, ๊ทธ๋ฃน๋ณ„ ๋กค์•„์›ƒ์„ ํ†ตํ•ด ๋‹ค์–‘ํ•œ ์ƒํ™ฉ์— ๋Œ€ํ•œ ํ–‰๋™์„ ๋™์‹œ์— ํ‰๊ฐ€ํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ์ ‘๊ทผ๋ฒ•์˜ ํ•ต์‹ฌ ์žฅ์ ์€ โ€œ์ƒ๋Œ€ ์ด์ (relative advantage)โ€์„ ์ด์šฉํ•ด ๋™์ผํ•œ ๋ณด์ƒ์„ ๋ฐ›์€ ์ƒ˜ํ”Œ๋“ค ์‚ฌ์ด์—์„œ๋„ ๋ฏธ์„ธํ•œ ์ฐจ์ด๋ฅผ ํฌ์ฐฉํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ์ ์ด๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์‹ค์ œ ํ•™์Šต ๊ณผ์ •์—์„œ ํŠน์ • ๊ทธ๋ฃน ๋‚ด ๋ชจ๋“  ์‘๋‹ต์ด ๋™์ผํ•œ ๋ณด์ƒ์„ ๋ฐ›๋Š” ๊ฒฝ์šฐ, ์ด์  ์ถ”์ •๊ฐ’์ด 0์— ์ˆ˜๋ ดํ•˜๊ฒŒ ๋˜๊ณ , ๊ฒฐ๊ณผ์ ์œผ๋กœ ์ •์ฑ… ์—…๋ฐ์ดํŠธ์— ํ•„์š”ํ•œ ๊ทธ๋ž˜๋””์–ธํŠธ๊ฐ€ ์‚ฌ๋ผ์ง€๋Š” โ€˜๊ทธ๋ผ๋””์–ธ

Evaluating perturbation robustness of generative systems that use COBOL code inputs

Evaluating perturbation robustness of generative systems that use COBOL code inputs

๋ณธ ๋…ผ๋ฌธ์ด ๋‹ค๋ฃจ๋Š” ํ•ต์‹ฌ ๋ฌธ์ œ๋Š” โ€œLLM ๊ธฐ๋ฐ˜ ์‹œ์Šคํ…œ์ด ์ž…๋ ฅ ์ฝ”๋“œ์˜ ์‚ฌ์†Œํ•œ ๋ณ€ํ˜•์— ์–ผ๋งˆ๋‚˜ ์ทจ์•ฝํ•œ๊ฐ€โ€๋ผ๋Š” ์งˆ๋ฌธ์ด๋‹ค. ํŠนํžˆ COBOL์ด๋ผ๋Š” ๋ ˆ๊ฑฐ์‹œ ์–ธ์–ด๋Š” ๊ธˆ์œตยท๋ณดํ—˜ยท์ •๋ถ€ ๋“ฑ ํ•ต์‹ฌ ์‚ฐ์—…์—์„œ ์•„์ง๋„ ๋Œ€๊ทœ๋ชจ ์šด์˜ ์‹œ์Šคํ…œ์„ ์ง€ํƒฑํ•˜๊ณ  ์žˆ์œผ๋ฉฐ, ๊ทธ ์ฝ”๋“œ๋ฒ ์ด์Šค๋Š” ๋Œ€๋ถ€๋ถ„ ํ์‡„ํ˜•์ด๋ฉฐ LLM ํ›ˆ๋ จ ๋ฐ์ดํ„ฐ์— ํฌํ•จ๋˜์ง€ ์•Š๋Š”๋‹ค. ๋”ฐ๋ผ์„œ ๊ธฐ์กด์˜ LLM ํ‰๊ฐ€ ๋ฐฉ๋ฒ•์„ ๊ทธ๋Œ€๋กœ ์ ์šฉํ•˜๊ธฐ ์–ด๋ ต๋‹ค. ์ €์ž๋“ค์€ ์ด๋Ÿฌํ•œ ์ƒํ™ฉ์„ ์ธ์‹ํ•˜๊ณ , COBOL ์ฝ”๋“œ๋ฅผ ๋Œ€์ƒ์œผ๋กœ ํ•˜๋Š” ์ „์šฉ ๊ฒฌ๊ณ ์„ฑ ํ‰๊ฐ€ ํ”„๋ ˆ์ž„์›Œํฌ๋ฅผ ์„ค๊ณ„ํ•˜์˜€๋‹ค. ์ฒซ ๋ฒˆ์งธ ๊ธฐ์—ฌ๋Š” โ€œCOBOL ํŒŒ๋ผ๊ทธ๋ž˜ํ”„ ๋ฐ ์ „์ฒด ํ”„๋กœ๊ทธ๋žจ ์ˆ˜์ค€์˜ ๋ณ€

System
GNSS Jammer Direction Finding in Dynamic Scenarios Using an Inertial-based Multi-Antenna System

GNSS Jammer Direction Finding in Dynamic Scenarios Using an Inertial-based Multi-Antenna System

๋ณธ ๋…ผ๋ฌธ์€ GNSS ์žฌ๋ฐ ์‹ ํ˜ธ ํƒ์ง€ยท์œ„์น˜์ถ”์ • ๋ถ„์•ผ์—์„œ ๋‘ ๊ฐ€์ง€ ํ˜์‹ ์ ์ธ ์š”์†Œ๋ฅผ ๊ฒฐํ•ฉํ•œ๋‹ค. ์ฒซ์งธ, ์ €๋น„์šฉยท๋ฒ”์šฉ์ ์ธ SDR ํ”Œ๋žซํผ์ธ Ettus USRP X440๊ณผ 2 ร— 2 ํŒจ์น˜ ์•ˆํ…Œ๋‚˜ ๋ฐฐ์—ด์„ ํ™œ์šฉํ•ด ์‹ค์‹œ๊ฐ„ I/Q ๋ฐ์ดํ„ฐ๋ฅผ ํ™•๋ณดํ•œ๋‹ค๋Š” ์ ์€ ์‹คํ—˜ ์žฌํ˜„์„ฑ๊ณผ ํ™•์žฅ์„ฑ์„ ํฌ๊ฒŒ ๋†’์ธ๋‹ค. ์ „ํ†ต์ ์ธ ๋‹จ์ผ ์•ˆํ…Œ๋‚˜ ๊ธฐ๋ฐ˜ AoA ์ถ”์ •์€ ์•ˆํ…Œ๋‚˜ ๊ฐ„ ์œ„์ƒ ์ฐจ์ด๋ฅผ ์ด์šฉํ•˜์ง€๋งŒ, ๋ฐฐ์—ด์ด 2 ร— 2์— ๋ถˆ๊ณผํ•ด ๊ฐ๋„ ํ•ด์ƒ๋„๊ฐ€ ์ œํ•œ์ ์ด๋‹ค. ์ด๋ฅผ ๋ณด์™„ํ•˜๊ธฐ ์œ„ํ•ด ์ €์ž๋“ค์€ ํ”Œ๋žซํผ์˜ ์ด๋™์„ ์ด์šฉํ•œ ํ•ฉ์„ฑ ๊ฐœ๊ตฌ(Synthetic Aperture) ๋ฐฉ์‹์„ ๋„์ž…ํ•œ๋‹ค. ์ด๋™ ๊ฒฝ๋กœ์™€ ์†๋„

System
Shape-Adapting Gated Experts: Dynamic Expert Routing for Colonoscopic Lesion Segmentation

Shape-Adapting Gated Experts: Dynamic Expert Routing for Colonoscopic Lesion Segmentation

๋ณธ ๋…ผ๋ฌธ์€ ์ „ํ†ต์ ์ธ CNNโ€‘Transformer ํ˜ผํ•ฉ ๊ตฌ์กฐ๊ฐ€ ๊ณ ์ •๋œ ์—ฐ์‚ฐ ๊ทธ๋ž˜ํ”„์™€ ์ •์ ์ธ ๋ผ์šฐํŒ… ์ „๋žต์— ์˜์กดํ•จ์œผ๋กœ์จ ๋ฐœ์ƒํ•˜๋Š” ๋‘ ๊ฐ€์ง€ ๊ทผ๋ณธ์ ์ธ ํ•œ๊ณ„๋ฅผ ์ง€์ ํ•œ๋‹ค. ์ฒซ ๋ฒˆ์งธ๋Š” ์ž…๋ ฅ ์ด๋ฏธ์ง€์˜ ๊ทœ๋ชจยทํ˜•ํƒœ๊ฐ€ ํฌ๊ฒŒ ๋ณ€๋™ํ•˜๋Š” ์ „๋ณ‘ ์Šฌ๋ผ์ด๋“œ(WSI)์™€ ๊ฐ™์€ ์ดˆ๊ณ ํ•ด์ƒ๋„ ์˜๋ฃŒ ์˜์ƒ์—์„œ ๋ถˆํ•„์š”ํ•œ ์—ฐ์‚ฐ์ด ๊ณผ๋‹คํ•˜๊ฒŒ ๋ฐœ์ƒํ•œ๋‹ค๋Š” ์ ์ด๋‹ค. ๋‘ ๋ฒˆ์งธ๋Š” ๊ณ ์ • ๋ผ์šฐํŒ…์ด ๋‹ค์–‘ํ•œ ์„ธํฌ ํ˜•ํƒœ์™€ ์กฐ์ง ๊ตฌ์กฐ์— ๋Œ€ํ•œ ์ ์‘์„ฑ์„ ์ €ํ•ดํ•œ๋‹ค๋Š” ์ ์ด๋‹ค. ์ด๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ์ œ์•ˆ๋œ Shapeโ€‘Adapting Gated Experts(SAGE)๋Š” โ€˜์ „๋ฌธ๊ฐ€(Expert)โ€™๋ผ๋Š” ๊ฐœ๋…์„ ๋„์ž…ํ•ด

Wireless Power Transfer and Intent-Driven Network Optimization in AAVs-assisted IoT for 6G Sustainable Connectivity

Wireless Power Transfer and Intent-Driven Network Optimization in AAVs-assisted IoT for 6G Sustainable Connectivity

๋ณธ ์—ฐ๊ตฌ๋Š” 6G ์‹œ๋Œ€์— ๊ธ‰์ฆํ•˜๋Š” ์ดˆ์—ฐ๊ฒฐ IoT ํ™˜๊ฒฝ๊ณผ ์ž์œจํ•ญ๊ณต๊ธฐ(AAV)์˜ ํ˜‘์—…์„ ์œ„ํ•œ ํ•ต์‹ฌ ๊ธฐ์ˆ ์  ๊ณผ์ œ๋ฅผ ์ฒด๊ณ„์ ์œผ๋กœ ํ•ด๊ฒฐํ•˜๊ณ ์ž ํ•œ๋‹ค. ์ฒซ ๋ฒˆ์งธ ๊ณผ์ œ๋Š” ์‚ฌ์šฉ์ž ์˜๋„๋ฅผ ์ •ํ™•ํžˆ ํŒŒ์•…ํ•˜๋Š” ๊ฒƒ์ด๋‹ค. ๊ธฐ์กด์˜ ์˜๋„ ์ถ”๋ก  ๋ชจ๋ธ์€ ์ฃผ๋กœ ํ…์ŠคํŠธ ๊ธฐ๋ฐ˜์˜ ๋ช…์‹œ์  ํ‘œํ˜„์— ์˜์กดํ•˜๋Š”๋ฐ, ์‹ค์ œ ํ˜„์žฅ์—์„œ๋Š” ์Œ์„ฑ, ์„ผ์„œ ๋ฐ์ดํ„ฐ, ๋น„์ •ํ˜• ์‹ ํ˜ธ ๋“ฑ ๋‹ค์–‘ํ•œ ํ˜•ํƒœ์˜ ๋ชจํ˜ธํ•˜๊ณ  ๋ถˆ์™„์ „ํ•œ ์ž…๋ ฅ์ด ์กด์žฌํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ์ƒํ™ฉ์—์„œ ์•”์‹œ์  ์˜๋„ ๋ชจ๋ธ๋ง์„ ๋„์ž…ํ•จ์œผ๋กœ์จ, ์ž…๋ ฅ์˜ ๋ถˆํ™•์‹ค์„ฑ์„ ํ™•๋ฅ ์  ํ‘œํ˜„์œผ๋กœ ์ „ํ™˜ํ•˜๊ณ , ํ•˜์ดํผ์ฐจ์›(Hyperdimensional) ๊ณต๊ฐ„์— ๋งคํ•‘ํ•จ์œผ๋กœ์จ ๊ณ ์ฐจ์› ํŠน์„ฑ

Network
QuickLAP: Quick Language-Action Preference Learning for Autonomous Driving Agents

QuickLAP: Quick Language-Action Preference Learning for Autonomous Driving Agents

๋ณธ ๋…ผ๋ฌธ์€ ์ธ๊ฐ„โ€‘๋กœ๋ด‡ ์ƒํ˜ธ์ž‘์šฉ(HRI) ๋ถ„์•ผ์—์„œ ์žฅ๊ธฐ์ ์œผ๋กœ ์ค‘์š”ํ•œ ๋ฌธ์ œ์ธ โ€˜๋‹ค์ค‘๋ชจ๋‹ฌ ํ”ผ๋“œ๋ฐฑ์„ ํ†ตํ•œ ๋ณด์ƒ ํ•™์Šตโ€™์— ๋Œ€ํ•ด ์‹ค์šฉ์ ์ธ ํ•ด๊ฒฐ์ฑ…์„ ์ œ์‹œํ•œ๋‹ค. ๊ธฐ์กด ์—ฐ๊ตฌ๋“ค์€ ๋ฌผ๋ฆฌ์  ๊ต์ •(์˜ˆ: ์‹œ์—ฐ, ๋ฌผ๋ฆฌ์  ๋Œ์–ด๋‹น๊น€)์ด๋‚˜ ์–ธ์–ด์  ์ง€์‹œ(์˜ˆ: ๋ช…๋ น๋ฌธ, ์„ค๋ช…) ์ค‘ ํ•˜๋‚˜์— ์ดˆ์ ์„ ๋งž์ถ”์—ˆ์œผ๋ฉฐ, ๋‘ ๋ชจ๋‹ฌ๋ฆฌํ‹ฐ๋ฅผ ๊ฒฐํ•ฉํ•˜๋ ค๋Š” ์‹œ๋„๋Š” ๋Œ€๋ถ€๋ถ„ ๊ทœ์น™ ๊ธฐ๋ฐ˜์ด๊ฑฐ๋‚˜ ์‚ฌํ›„ ํ†ตํ•ฉ ๋ฐฉ์‹์— ๋จธ๋ฌผ๋ €๋‹ค. ์ด๋Ÿฌํ•œ ์ ‘๊ทผ์€ (1) ๋ฌผ๋ฆฌ์  ๊ต์ •์ด ์˜๋„ ํ•ด์„์— ๋ถˆํ™•์‹ค์„ฑ์„ ๋‚ดํฌํ•˜๊ณ , (2) ์–ธ์–ด๊ฐ€ ๊ตฌ์ฒด์ ์ธ ํ–‰๋™ ๋งคํ•‘์„ ์ œ๊ณตํ•˜์ง€ ๋ชปํ•œ๋‹ค๋Š” ๊ทผ๋ณธ์ ์ธ ํ•œ๊ณ„๋ฅผ ๊ทน๋ณตํ•˜์ง€ ๋ชปํ•œ๋‹ค. QuickLAP์€ ์ด๋Ÿฌํ•œ

Learning
Polarity-Aware Probing for Quantifying Latent Alignment in Language Models

Polarity-Aware Probing for Quantifying Latent Alignment in Language Models

๋ณธ ๋…ผ๋ฌธ์€ ์ตœ๊ทผ ๊ธ‰๋ถ€์ƒํ•˜๊ณ  ์žˆ๋Š” ๋น„์ง€๋„ํ˜• ํƒ์ง€ ๊ธฐ๋ฒ•์ธ Contrastโ€‘Consistent Search(CCS)์˜ ์ •๋ ฌ ํ‰๊ฐ€ ๊ฐ€๋Šฅ์„ฑ์„ ์‹ฌ๋„ ์žˆ๊ฒŒ ํƒ๊ตฌํ•œ๋‹ค. ๊ธฐ์กด CCS๋Š” ๋ชจ๋ธ์ด ํŠน์ • ์ž…๋ ฅ์— ๋Œ€ํ•ด ์ผ๊ด€๋œ ๋‚ด๋ถ€ ํ‘œํ˜„์„ ์ƒ์„ฑํ•˜๋Š”์ง€๋ฅผ ํ™•์ธํ•จ์œผ๋กœ์จ, ํ† ํฐ ์ˆ˜์ค€์˜ ์ถœ๋ ฅ ์—†์ด๋„ ๋ชจ๋ธ์ด ์–ด๋–ค โ€˜์‹ ๋…โ€™์„ ๊ฐ€์ง€๊ณ  ์žˆ๋Š”์ง€๋ฅผ ์ถ”๋ก ํ•œ๋‹ค๋Š” ์žฅ์ ์ด ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ด๋Ÿฌํ•œ ์ ‘๊ทผ์ด ์‹ค์ œ๋กœ ๋ชจ๋ธ์ด ํ•ด๋กœ์šด ๋‚ด์šฉ๊ณผ ์•ˆ์ „ํ•œ ๋‚ด์šฉ์„ ์–ด๋–ป๊ฒŒ ๊ตฌ๋ถ„ํ•˜๊ณ , ๊ทธ ๊ตฌ๋ถ„์ด ์ •๋ ฌ(Alignment)๊ณผ ์–ผ๋งˆ๋‚˜ ์—ฐ๊ด€๋˜๋Š”์ง€๋Š” ์•„์ง ๋ช…ํ™•ํžˆ ๊ทœ๋ช…๋˜์ง€ ์•Š์•˜๋‹ค. ์—ฐ๊ตฌ์ง„์€ ๋จผ์ € CCS๊ฐ€ ํ•ด๋กœ์šด ์ง„์ˆ ๊ณผ

Model
Pre-cache: A Microarchitectural Solution to prevent Meltdown and Spectre

Pre-cache: A Microarchitectural Solution to prevent Meltdown and Spectre

๋ฉœํŠธ๋‹ค์šด๊ณผ ์ŠคํŽ™ํ„ฐ๋Š” ํ˜„๋Œ€ CPU๊ฐ€ ์ฑ„ํƒํ•œ ์‚ฌ์ „ ์‹คํ–‰(outโ€‘ofโ€‘order) ๋ฐ ์ถ”์ธก ์‹คํ–‰(speculative execution) ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ์•…์šฉํ•œ๋‹ค. ์ด ๋ฉ”์ปค๋‹ˆ์ฆ˜์€ ํ”„๋กœ๊ทธ๋žจ ํ๋ฆ„์„ ์˜ˆ์ธกํ•ด ๋ฏธ๋ฆฌ ๋ช…๋ น์„ ์‹คํ–‰ํ•˜๊ณ , ๊ฒฐ๊ณผ๋ฅผ ๋ ˆ์ง€์Šคํ„ฐ์™€ ์บ์‹œ ๊ฐ™์€ ๋งˆ์ดํฌ๋กœ์•„ํ‚คํ…์ฒ˜ ๊ตฌ์กฐ์— ์ €์žฅํ•œ๋‹ค. ์ •์ƒ์ ์ธ ์‹คํ–‰์ด ๋๋‚˜๋ฉด ์ž˜๋ชป๋œ ์ถ”์ธก์— ์˜ํ•ด ์ƒ์„ฑ๋œ ๊ฒฐ๊ณผ๋Š” ํ๊ธฐ๋˜์ง€๋งŒ, ๊ทธ ๊ณผ์ •์—์„œ ์บ์‹œ ๋ผ์ธ์— ๋‚จ์€ ํ”์ ์€ ์‚ฌ๋ผ์ง€์ง€ ์•Š๋Š”๋‹ค. ๊ณต๊ฒฉ์ž๋Š” ์ด๋Ÿฌํ•œ ์บ์‹œ ์ž”์—ฌ๋ฌผ์„ ํƒ€์ด๋ฐ ์ธก์ •์„ ํ†ตํ•ด ์ฝ์–ด ๋น„๋ฐ€ ๋ฐ์ดํ„ฐ๋ฅผ ๋ณต์›ํ•œ๋‹ค. ๊ธฐ์กด ์†Œํ”„ํŠธ์›จ์–ด ํŒจ์น˜๋Š” ํŠน์ • ๋ช…๋ น์–ด ์‹œํ€€์Šค์— ๋ฉ”๋ชจ๋ฆฌ ์žฅ

Series Prediction based on Algebraic Approximants

Series Prediction based on Algebraic Approximants

์ด ๋…ผ๋ฌธ์€ ๋ณต์žกํ•œ ํ•จ์ˆ˜์˜ ์‹œํ€€์Šค ์˜ˆ์ธก์„ ์œ„ํ•œ ์ƒˆ๋กœ์šด ์ ‘๊ทผ๋ฒ•์„ ์ œ์‹œํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ํŠนํžˆ, ์ด ์—ฐ๊ตฌ๋Š” ๋Œ€์ˆ˜์  ๊ทผ์‚ฌ์™€ ํ—ˆ๋ฏธํŠธ ํŒŒ๋ฐ ๋‹คํ•ญ์‹(HPP)์— ์ค‘์ ์„ ๋‘๊ณ  ์žˆ์œผ๋ฉฐ, ์ด๋ฅผ ํ†ตํ•ด ๋ณต์žกํ•œ ์‹œํ€€์Šค๋ฅผ ํšจ๊ณผ์ ์œผ๋กœ ์˜ˆ์ธกํ•  ์ˆ˜ ์žˆ๋Š” ๋ฐฉ๋ฒ•๋ก ์„ ๊ฐœ๋ฐœํ•˜์˜€์Šต๋‹ˆ๋‹ค. 1. ๋Œ€์ˆ˜์  ๊ทผ์‚ฌ์˜ ๊ฐœ๋… ๋…ผ๋ฌธ์€ ๋Œ€์ˆ˜์  ๊ทผ์‚ฌ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ๋ณต์žกํ•œ ํ•จ์ˆ˜์˜ ์ง€์ˆ˜ ๊ธ‰์ˆ˜๋ฅผ ๊ทผ์‚ฌํ•˜๋Š” ๋ฐฉ๋ฒ•์— ๋Œ€ํ•ด ์„ค๋ช…ํ•ฉ๋‹ˆ๋‹ค. ์ด๋Š” ํ—ˆ๋ฏธํŠธ ํŒŒ๋ฐ ๋‹คํ•ญ์‹(HPP)์„ ์ด์šฉํ•ด ์ˆ˜ํ–‰๋˜๋ฉฐ, HPP๋Š” ์ฃผ์–ด์ง„ ํ•จ์ˆ˜ f ๊ฐ€ ์ง€์ˆ˜ ๊ธ‰์ˆ˜ ํ˜•ํƒœ๋กœ ํ‘œํ˜„๋  ๋•Œ, ์ด๋ฅผ ๊ทผ์‚ฌํ•˜๋Š” ๋‹คํ•ญ์‹ ์ง‘ํ•ฉ์ž…๋‹ˆ๋‹ค. 2. ํ—ˆ๋ฏธํŠธ ํŒŒ๋ฐ ๋‹คํ•ญ์‹์˜ ๊ตฌ์„ฑ

Mathematics Physics
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, ํ•˜

Software Engineering System Data Computer Science Astrophysics
Orbit Mode observation Technique Developed for VERITAS

Orbit Mode observation Technique Developed for VERITAS

: VERITAS ๋ง์›๊ฒฝ์€ ๋งค์šฐ ์—๋„ˆ์ง€๊ฐ€ ๋†’์€ ๊ฐ๋งˆ์„ ์„ ํƒ์ง€ํ•˜๋Š” ๋ฐ ์‚ฌ์šฉ๋˜๋Š” ์ฒด๋ Œ์ฝ”ํ”„ ๋ง์›๊ฒฝ์œผ๋กœ, ๋ฏธ๊ตญ ์• ๋ฆฌ์กฐ๋‚˜์ฃผ์— ์œ„์น˜ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์ด ๋ง์›๊ฒฝ์€ 100 GeV์—์„œ 30 TeV ์‚ฌ์ด์˜ ์—๋„ˆ์ง€๋ฅผ ๊ฐ€์ง„ ๊ฐ๋งˆ์„ ์„ ํƒ์ง€ํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ, ๊ทธ ์ •ํ™•๋„์™€ ๋ถ„ํ•ด๋Šฅ์€ ๋งค์šฐ ๋†’์Šต๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๊ณ ์„ฑ๋Šฅ ๋•๋ถ„์— VERITAS๋Š” ์šฐ์ฃผ์—์„œ ๋ฐœ์ƒํ•˜๋Š” ๋‹ค์–‘ํ•œ ํ˜„์ƒ์„ ์—ฐ๊ตฌํ•˜๋Š”๋ฐ ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์ด ๋…ผ๋ฌธ์—์„œ๋Š” ์ด ๋ง์›๊ฒฝ์˜ ์ƒˆ๋กœ์šด ๊ด€์ธก ๋ชจ๋“œ์ธ '๊ถค๋„' ๋ชจ๋“œ๋ฅผ ์†Œ๊ฐœํ•˜๊ณ , ๊ทธ ํšจ๊ณผ์™€ ์ ์šฉ ๊ฐ€๋Šฅ์„ฑ์— ๋Œ€ํ•ด ์„ค๋ช…ํ•ฉ๋‹ˆ๋‹ค. ๊ธฐ์กด์˜ ์ง„๋™ ๋ชจ๋“œ์—์„œ๋Š” ๋ง์›๊ฒฝ์˜ ์ค‘์‹ฌ์ด ๊ณ ์ •

Astrophysics
Another elementary proof of $: sum_{n ge 1}{1/{n^2}} = pi^2/6,$ and   a recurrence formula for $,zeta{(2k)}$

Another elementary proof of $: sum_{n ge 1}{1/{n^2}} = pi^2/6,$ and a recurrence formula for $,zeta{(2k)}$

: ๋ณธ ๋…ผ๋ฌธ์€ ๋ฆฌ๋งŒ ์ œํƒ€ ํ•จ์ˆ˜ ฮถ(s)์˜ ํŠน๋ณ„ํ•œ ๊ฒฝ์šฐ์ธ ฮถ(2k)์— ๋Œ€ํ•œ ์ƒˆ๋กœ์šด ์ ‘๊ทผ ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•˜๋ฉฐ, ํŠนํžˆ ฮถ(2) ฯ€ยฒ/6์ด๋ผ๋Š” ์ค‘์š”ํ•œ ๊ฒฐ๊ณผ๋ฅผ ๊ฐ„๋‹จํ•˜๊ฒŒ ์ฆ๋ช…ํ•˜๊ณ  ์žฌ๊ท€ ๊ณต์‹์„ ๋„์ถœํ•ฉ๋‹ˆ๋‹ค. ์ด ๋…ผ๋ฌธ์€ Dancs์™€ He (2006)์˜ ์—ฐ๊ตฌ์—์„œ ์‹œ์ž‘ํ•˜์—ฌ, sin(nฯ€) ๋Œ€์‹  cos(nฯ€)๋ฅผ ์‚ฌ์šฉํ•œ ๊ธ‰์ˆ˜ ์ „๊ฐœ ๋ฐฉ๋ฒ•์„ ํ†ตํ•ด ฮถ(2k)์— ๋Œ€ํ•œ ์ƒˆ๋กœ์šด ์ฆ๋ช…๊ณผ ์žฌ๊ท€ ๊ณต์‹์„ ์ œ์‹œํ•ฉ๋‹ˆ๋‹ค. 1. ์‹ฌํ”Œํ•œ ์ฆ๋ช…๊ณผ ์žฌ๊ท€ ๊ณต์‹ ๋…ผ๋ฌธ์€ ๋จผ์ € s 1์ผ ๋•Œ ํ•ด๋ฐ€ํ„ด ๊ธ‰์ˆ˜๊ฐ€ ๋ฐœ์‚ฐํ•จ์„ ์–ธ๊ธ‰ํ•˜๊ณ , ์ œ๊ณฑ ะ‘ะตั€ะฝัƒะปะปะธ ์ˆ˜ Bk๋ฅผ z/e^z 1์˜ ํƒ€์ผ๋Ÿฌ ๊ธ‰์ˆ˜ ์ „๊ฐœ์—์„œ z

Mathematics
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Class-based Rough Approximation with Dominance Principle

์ด ๋…ผ๋ฌธ์€ ๋‹ค์ค‘ ๊ธฐ์ค€ ์˜์‚ฌ๊ฒฐ์ • ๋ถ„์„(MCDA)๊ณผ ์ง€๋ฐฐ ๊ธฐ๋ฐ˜ ๊ฑฐ์นœ ์ง‘ํ•ฉ ์ ‘๊ทผ๋ฒ•(DRSA)์„ ์ค‘์‹ฌ์œผ๋กœ, ๊ณ ์ „์ ์ธ ๊ฑฐ์นœ ์ง‘ํ•ฉ ์ ‘๊ทผ๋ฒ•(CRSA)์˜ ํ•œ๊ณ„์™€ DRSA์˜ ์žฅ์ ์„ ํƒ๊ตฌํ•œ๋‹ค. MCDA๋Š” ๋‹ค์–‘ํ•œ ๊ธฐ์ค€์— ๋”ฐ๋ผ ํ‰๊ฐ€๋œ ๊ฐ์ฒด๋“ค ์ค‘์—์„œ ์ตœ์ ์˜ ๊ฒฐ์ •์„ ๋‚ด๋ฆฌ๋Š” ๋ฐ ์‚ฌ์šฉ๋˜๋ฉฐ, ์ด ๋…ผ๋ฌธ์€ ์ด๋ฅผ ์œ„ํ•œ ํšจ๊ณผ์ ์ธ ์ˆ˜ํ•™์  ๋„๊ตฌ๋กœ์„œ CRSA์™€ DRSA๋ฅผ ๋น„๊ตํ•˜๊ณ  ๋ถ„์„ํ•œ๋‹ค. CRSA๋Š” ๋ถˆ๋ถ„๋ช…์„ฑ ๊ด€๊ณ„๋ฅผ ํ†ตํ•ด ์ง€์‹ ๊ฑฐ์น ๊ธฐ๋ฅผ ๊ตฌ์ถ•ํ•˜๋Š” ๋ฐ˜๋ฉด, DRSA๋Š” ์˜์‚ฌ๊ฒฐ์ • ํ‘œ์—์„œ์˜ ์ง€๋ฐฐ ๊ด€๊ณ„์— ์ดˆ์ ์„ ๋งž์ถ˜๋‹ค. ์ด ๋…ผ๋ฌธ์€ ํŠนํžˆ ์„ ํ˜ธ๋„ ์ˆœ์„œ ๋ฐ์ดํ„ฐ ์ฒ˜๋ฆฌ์— ํ•œ๊ณ„๊ฐ€ ์žˆ๋Š” CRSA์™€

Computational Complexity Computer Science Artificial Intelligence
Two temperature accretion flows around rotating black holes and   determining the kerr parameter of sources

Two temperature accretion flows around rotating black holes and determining the kerr parameter of sources

์ด ๋…ผ๋ฌธ์€ ํšŒ์ „ํ•˜๋Š” ๋ธ”๋ž™ํ™€ ์ฃผ๋ณ€์—์„œ ๋ฐœ์ƒํ•˜๋Š” ๋‘ ์˜จ๋„ ์ถ•์  ํ๋ฆ„์„ ์—ฐ๊ตฌํ•˜๊ณ , ์ด๋ฅผ ํ†ตํ•ด ๋‹ค์–‘ํ•œ ์ฒœ์ฒด ํ˜„์ƒ์„ ์„ค๋ช…ํ•˜๋ ค๋Š” ๋ชฉํ‘œ๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. ํŠนํžˆ, Cyg X 1๊ณผ ๊ฐ™์€ ์ €์˜จ ๊ณ ์ฒด ์ƒํƒœ๋ฅผ ๊ฐ€์ง„ ์ฒœ์ฒด์˜ ํŠน์„ฑ์„ ๋‹จ์ˆœํ•œ ์ผ€ํ”Œ๋Ÿฌ์  ์ถ•์  ์›๋ฐ˜ ๋ชจ๋ธ๋กœ๋Š” ์„ค๋ช…ํ•˜๊ธฐ ์–ด๋ ต๋‹ค๋Š” ์ ์„ ๊ฐ•์กฐํ•˜๋ฉฐ, ์ด๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ๋‘ ์˜จ๋„ ํ๋ฆ„ ๋ชจ๋ธ์„ ์ œ์‹œํ•œ๋‹ค. 1. ๊ธฐ์กด ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„์™€ ์ƒˆ๋กœ์šด ์ ‘๊ทผ ๋ฐฉ์‹ ๊ธฐ์กด ์—ฐ๊ตฌ์—์„œ๋Š” Cyg X 1๊ณผ ๊ฐ™์€ ์ฒœ์ฒด์˜ ์ €์˜จ ๊ณ ์ฒด ์ƒํƒœ๋ฅผ ๋‹จ์ˆœํ•œ ์ผ€ํ”Œ๋Ÿฌ์  ์ถ•์  ์›๋ฐ˜ ๋ชจ๋ธ๋กœ๋Š” ์„ค๋ช…ํ•˜๊ธฐ ์–ด๋ ค์› ๋‹ค. ์ด๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด Eardley, Lightma

General Relativity Astrophysics
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Field amplification, vortex formation, and electron acceleration in a plasma protoshock: effect of asymmetric density profile

: ๋ณธ ๋…ผ๋ฌธ์€ ์ดˆ๊ณ ์—๋„ˆ์ง€ ๋ฐฉ์‚ฌ์„  ์‚ฌ๊ฑด ์ค‘ ๊ฐ€์žฅ ๊ฐ•๋ ฅํ•œ ๊ฒƒ์œผ๋กœ ์•Œ๋ ค์ง„ GRB์˜ ์ฆ‰๊ฐ์ ์ธ ๋ฐฉ์ถœ ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ์ดํ•ดํ•˜๊ธฐ ์œ„ํ•œ ์ค‘์š”ํ•œ ๋‹จ๊ณ„๋ฅผ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค. ํŠนํžˆ, ์ด ์—ฐ๊ตฌ๋Š” ํ”Œ๋ผ์ฆˆ๋งˆ ์ถฉ๊ฒฉ์—์„œ ์ž๊ธฐ์žฅ ์ฆํญ๊ณผ ์ „์ž ๊ฐ€์†์— ๋Œ€ํ•œ ์‹ฌ๋„ ์žˆ๋Š” ๋ถ„์„์„ ์ˆ˜ํ–‰ํ•˜์˜€์Šต๋‹ˆ๋‹ค. 1. ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ์„ค์ • ๋ฐ ์ดˆ๊ธฐ ์กฐ๊ฑด ๋…ผ๋ฌธ์€ ๋‘ ๊ฐœ์˜ ํ”Œ๋ผ์ฆˆ๋งˆ ๊ตฌ๋ฆ„์ด x 0์—์„œ ์ถฉ๋Œํ•˜๋Š” ์ƒํ™ฉ์„ ๋ชจ๋ธ๋งํ•ฉ๋‹ˆ๋‹ค. ์ด ์ค‘ ํ•˜๋‚˜๋Š” ๋ฐ€๋„๊ฐ€ ๋†’๊ณ  ๋‹ค๋ฅธ ํ•˜๋‚˜๋Š” ํฌ๋ฐ•ํ•œ ๊ตฌ๋ฆ„์œผ๋กœ, ๊ฐ๊ฐ์˜ ์ดˆ๊ธฐ ์ „์ž ๋ฐ ์ด์˜จ ์ˆ˜๋ฐ€๋„๋Š” n1๊ณผ n2 n1/10์ž…๋‹ˆ๋‹ค. ๋‘ ๊ตฌ๋ฆ„์€ ์„œ๋กœ ๋ฐ˜๋Œ€ ๋ฐฉํ–ฅ์œผ๋กœ x ์ถ•์— ๋Œ€ํ•ด ์ผ์ •ํ•œ ์†๋„๋กœ

Astrophysics
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Fluctuations of the depth of maximum in extensive air showers and cross-section of p-air inelastic interaction for energy range 10^15-10^17 eV

: ์ด ๋…ผ๋ฌธ์€ ์•ผ์ฟ ์ธ ํฌ ๋ฐฐ์—ด์„ ์ด์šฉํ•œ ์ดˆ๊ณ ์—๋„ˆ์ง€ ์šฐ์ฃผ์„ (UHECR)์˜ ๊ด€์ธก๊ณผ ๋ถ„์„์— ์ค‘์ ์„ ๋‘๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์—ฐ๊ตฌํŒ€์€ ๊ด‘ํ•™์ , ๋ฌด์˜จ์  ๋ฐ ์ฒด๋ Œ์ฝ”ํ”„ ์„ฑ๋ถ„๋“ค์„ ์ธก์ •ํ•˜์—ฌ ๊ด‘๋ฒ”์œ„ํ•œ ๊ณต๊ธฐ ์ƒค์›Œ(EAS)๋ฅผ ์—ฐ๊ตฌํ•˜์˜€์œผ๋ฉฐ, ์ด๋ฅผ ํ†ตํ•ด ์ถฉ์ „ ์ž…์ž์™€ ๋ฌด์˜จ ์ž…์ž์˜ ๋ถ„ํฌ๋ฅผ 1 GeV ์ด์ƒ์œผ๋กœ ๊ด€์ฐฐํ•˜๊ณ , ์ฒด๋ Œ์ฝ”ํ”„ ๋น›์˜ ์ธก๋ฉด์„ ํ†ตํ•ด ๊ณต๊ธฐ ์ƒค์›Œ์˜ ์ˆ˜์ง ๋ฐœ๋‹ฌ์„ ์žฌ๊ตฌ์„ฑํ•˜์˜€์Šต๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ์ธก์ •์€ ์ฒด๋ Œ์ฝ”ํ”„ ๋น›์˜ ๋Œ€๊ธฐ ๋ถ„ํฌ ์กฐ๊ฑด์— ์•ฝํ•˜๊ฒŒ ์˜์กดํ•˜์ง€๋งŒ, ์ƒค์›Œ ๊ธฐํ•˜ํ•™ ์žฌ๊ตฌ์„ฑ์—๋Š” ์ •ํ™•๋„๊ฐ€ ํฌ๊ฒŒ ์˜ํ–ฅ์„ ๋ฏธ์นฉ๋‹ˆ๋‹ค. ๋…ผ๋ฌธ์—์„œ ์ค‘์š”ํ•œ ํฌ์ธํŠธ ์ค‘ ํ•˜๋‚˜๋Š” xโ‚™ ์ตœ๋Œ€ ๋ฐ์ดํ„ฐ๋ฅผ ํ™œ์šฉํ•œ ํƒ„์„ฑ

HEP-EX Astrophysics
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Jets and outflows in Radio Galaxies: implications for AGN feedback

: ๋ณธ ์—ฐ๊ตฌ๋Š” ๊ณ ํ•ด์ƒ๋„ X์„  ๋ถ„๊ด‘ํ•™์„ ์‚ฌ์šฉํ•˜์—ฌ ๋ผ๋””์˜ค ๋ฐ์€(RL) ํ™œ๋™์€ํ•˜(AGN)์˜ ํ•ต ์ฃผ๋ณ€ ํ™˜๊ฒฝ์„ ํƒ๊ตฌํ•˜๋Š” ์ค‘์š”ํ•œ ๋ฐœ์ „์„ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค. ํŠนํžˆ, ์ด ์—ฐ๊ตฌ์—์„œ๋Š” 3C 382์™€ 3C 390.3์ด๋ผ๋Š” ๋‘ ๊ฐœ์˜ ๊ด‘์„  ์† ๋ผ๋””์˜ค ์€ํ•˜(BLRG)์—์„œ ๋”ฐ๋œปํ•œ ํก์ˆ˜์ž(WA)๋ฅผ ๋ฐœ๊ฒฌํ•˜๊ณ  ๊ทธ ํŠน์„ฑ์„ ๋ถ„์„ํ•˜์˜€์Šต๋‹ˆ๋‹ค. X์„  ๋ถ„๊ด‘ํ•™ ๊ธฐ์ˆ ์˜ ๋ฐœ์ „ ๊ณ ํ•ด์ƒ๋„ X์„  ๋ถ„๊ด‘ํ•™์€ AGN ์ฃผ๋ณ€ ํ™˜๊ฒฝ์„ ํƒ๊ตฌํ•˜๋Š” ๋ฐ ์ค‘์š”ํ•œ ๋„๊ตฌ๋กœ ํ™œ์šฉ๋˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์ด ์—ฐ๊ตฌ์—์„œ๋Š” XMM Newton/๋ฐ˜์‚ฌ ๊ฒฉ์ž ๋ถ„๊ด‘๊ณ„(RGS) ๋ฐ์ดํ„ฐ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ๋‘ ๊ฐœ์˜ BLRG์—์„œ WA ํŠน์„ฑ์„ ๋ถ„์„ํ•˜์˜€์Šต๋‹ˆ

Astrophysics
High-energy spectrum and zenith-angle distribution of atmospheric   neutrinos

High-energy spectrum and zenith-angle distribution of atmospheric neutrinos

: ๋ณธ ๋…ผ๋ฌธ์€ ๊ณ ์—๋„ˆ์ง€ ๋Œ€๊ธฐ ์ค‘์„ฑ๋ฏธ์ž(AN)์˜ ์—๋„ˆ์ง€ ์ŠคํŽ™ํŠธ๋Ÿผ๊ณผ ์ฒœ์ •๊ฐ ๋ถ„ํฌ๋ฅผ ๊ณ„์‚ฐํ•˜๊ณ  ๋‹ค์–‘ํ•œ ๋ชจ๋ธ์„ ํ†ตํ•ด ๊ทธ ๊ฒฐ๊ณผ๋ฅผ ๋ถ„์„ํ•œ๋‹ค. AN์€ ์šฐ์ฃผ์„  ํ•ต์ด ์ง€๊ตฌ ์ƒ์ธต๋Œ€๊ธฐ์™€ ์ถฉ๋Œํ•˜๋ฉด์„œ ์ƒ์„ฑ๋˜๋Š” ์ค‘์„ฑ๋ฏธ์ž๊ฐ€ ๋ถ•๊ดดํ•˜๋Š” ๊ณผ์ •์—์„œ ๋ฐœ์ƒํ•˜๋ฉฐ, ์ด๋Š” ์ €์—๋„ˆ์ง€์—์„œ๋Š” ์ค‘์„ฑ๋ฏธ์ž ์ง„๋™ ์—ฐ๊ตฌ์— ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•˜๋ฉฐ ๊ณ ์—๋„ˆ์ง€์—์„œ๋Š” ์ฒœ๋ฌธํ•™์  ์ค‘์„ฑ๋ฏธ์ž ์‹คํ—˜์˜ ๋ฐฐ๊ฒฝ ์žก์Œ์œผ๋กœ ์ž‘์šฉํ•œ๋‹ค. ๋…ผ๋ฌธ์€ QGSJET II 03, SIBYLL 2.1 ๋ฐ Kimel & Mokhov(KM) ๋ชจ๋ธ์„ ์‚ฌ์šฉํ•˜์—ฌ AN ํ๋ฆ„์„ ๊ณ„์‚ฐํ•˜๊ณ , ์ด ๊ฒฐ๊ณผ๋ฅผ Frejus, AMANDA II ๋ฐ IceCube

HEP-PH HEP-EX Astrophysics
On the properties of the RHESSI intermediate-duration gamma-ray bursts

On the properties of the RHESSI intermediate-duration gamma-ray bursts

: ๋ณธ ๋…ผ๋ฌธ์€ ์ค‘๊ฐ„ ์ง€์† ์‹œ๊ฐ„ ๊ฐ๋งˆ์„  ํญ๋ฐœ(GRB)์˜ ํŠน์„ฑ์„ ๋ถ„์„ํ•˜๊ณ , ์ด๋ฅผ ์งง์€ GRB์™€ ๊ธด GRB ๊ทธ๋ฃน๊ณผ ๋น„๊ตํ•˜์—ฌ ๊ทธ ์ฐจ์ด๋ฅผ ํŒŒ์•…ํ•˜๋Š” ๋ฐ ์ดˆ์ ์„ ๋งž์ถ”๊ณ  ์žˆ๋‹ค. ์—ฐ๊ตฌ๋Š” RHESSI ์œ„์„ฑ์—์„œ ์ˆ˜์ง‘๋œ ๋ฐ์ดํ„ฐ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ์ง„ํ–‰๋˜์—ˆ์œผ๋ฉฐ, 2002๋…„๋ถ€ํ„ฐ 2008๋…„๊นŒ์ง€์˜ ๊ธฐ๊ฐ„ ๋™์•ˆ ๊ด€์ธก๋œ ๊ฐ๋งˆ์„  ํญ๋ฐœ์„ ๋ถ„์„ํ•˜์˜€๋‹ค. ๋ฐฉ๋ฒ•๋ก  ์ค‘๊ฐ„ ์ง€์† ์‹œ๊ฐ„ GRB ๊ทธ๋ฃน ์‹๋ณ„: ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ตœ๋Œ€ ์šฐ๋„ ๋น„์œจ ํ…Œ์ŠคํŠธ์™€ ์ด๋ถ„ ๋ถ„ํฌ ์ ํ•ฉ์„ ํ†ตํ•ด ์ค‘๊ฐ„ ์ง€์† ์‹œ๊ฐ„ GRB ๊ทธ๋ฃน์„ ์‹๋ณ„ํ–ˆ๋‹ค. ์ŠคํŽ™ํŠธ๋Ÿผ ์ง€์—ฐ, ํ”ผํฌ ์นด์šดํŠธ์œจ, ์ ์ƒ‰ํŽธ์ด, ์ดˆ์‹ ์„ฑ ๊ด€์ธก ๋ฐ ํ˜ธ์ŠคํŠธ ์€ํ•˜ ๋ณ„ ํ˜•์„ฑ๋ฅ ์—

Astrophysics
No Image

Properties of Magnetized Quark-Hybrid Stars

๋ณธ ๋…ผ๋ฌธ์€ ์ž๊ธฐ์žฅ ๋ณ„์ธ ๋งค๊ทธ๋„คํƒ€๋ฅด์™€ ์ฟผํฌ ํ•˜์ด๋ธŒ๋ฆฌ๋“œ ๋ณ„(QHS)์˜ ๊ตฌ์กฐ ๋ฐ ํŠน์„ฑ์— ๋Œ€ํ•ด ์‹ฌ๋„ ์žˆ๊ฒŒ ๋ถ„์„ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ํŠนํžˆ, QHS๋Š” SQM ํ•ต์„ ์ค‘์‹ฌ์œผ๋กœ ํ•˜์ „ ๋ฌผ์งˆ ๊ป์งˆ๋กœ ๊ตฌ์„ฑ๋œ ๋ณ„๋กœ ๋ชจ๋ธ๋ง๋ฉ๋‹ˆ๋‹ค. ์ด ๋…ผ๋ฌธ์€ ์ด๋Ÿฌํ•œ ๋ณ„๋“ค์˜ ์งˆ๋Ÿ‰ ๋ฐ˜์ง€๋ฆ„(M R) ๊ด€๊ณ„์™€ ํšŒ์ „ ์ฃผ๊ธฐ, ๊ทธ๋ฆฌ๊ณ  ์ค‘๋ ฅ ํ‘œ๋ฉด ์ ์ƒ‰ ํŽธํ–ฅ ๋“ฑ์„ ๋ถ„์„ํ•˜์—ฌ QHS์™€ ์ „ํ†ต์ ์ธ ์ค‘์„ฑ์ž๋ณ„(NS) ์‚ฌ์ด์˜ ์ฐจ์ด๋ฅผ ๋ฐํžˆ๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. 1. QHS์˜ ๋ชจ๋ธ๋ง ๋ฐ ํŠน์„ฑ QHS๋Š” SQM ํ•ต์„ ์ค‘์‹ฌ์œผ๋กœ ํ•˜์ „ ๋ฌผ์งˆ ๊ป์งˆ๋กœ ๊ตฌ์„ฑ๋œ ๋ณ„์ž…๋‹ˆ๋‹ค. ์ด ๋…ผ๋ฌธ์—์„œ๋Š” MIT ๊ฐ€๋ฐฉ ๋ชจ๋ธ๊ณผ ์‘์ถ•๋œ ํ•˜์ „ ๋ฌผ์งˆ์— ๋Œ€ํ•œ ๋ฐฉ์ •์‹

HEP-PH Astrophysics
Damage spreading in the sandpile model of SOC

Damage spreading in the sandpile model of SOC

๋ณธ ๋…ผ๋ฌธ์€ ๋ชจ๋ž˜๋”๋ฏธ ๋ชจ๋ธ์—์„œ ์ž‘์€ ๊ต๋ž€์ด ์–ด๋–ป๊ฒŒ ํ™•์‚ฐ๋˜๋Š”์ง€๋ฅผ ์—ฐ๊ตฌํ•˜๋Š” ๊ฒƒ์œผ๋กœ, ์ด๋Š” ์ž์œจ ์‹œ์Šคํ…œ์˜ ๋™์  ํ–‰๋™์— ๋Œ€ํ•œ ์ค‘์š”ํ•œ ์ดํ•ด๋ฅผ ์ œ๊ณตํ•œ๋‹ค. ํŠนํžˆ, ์ด ์—ฐ๊ตฌ๋Š” ์†์ƒ(damage)์˜ ํ™•์‚ฐ์„ ํ†ตํ•ด SOC ์ƒํƒœ์—์„œ์˜ ์—ญ๋™์„ฑ์„ ํƒ๊ตฌํ•˜๋ฉฐ, ์ด๋ฅผ ํ†ตํ•ด ๋ชจ๋ž˜๋”๋ฏธ ๋ชจ๋ธ์ด ์–ด๋–ป๊ฒŒ ์ž๊ธฐ ์กฐ์งํ™”๋˜๊ณ  ๋น„ํŒ์ ์ธ ์ƒํƒœ๋ฅผ ์œ ์ง€ํ•˜๋Š”์ง€์— ๋Œ€ํ•œ ๊นŠ์€ ํ†ต์ฐฐ๋ ฅ์„ ์ œ๊ณตํ•œ๋‹ค. 1. ๋ชจ๋ธ ๋ฐ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๋ชจ๋ž˜๋”๋ฏธ ๋ชจ๋ธ์€ ๊ฒฉ์ž ์ž๋™์ž ๋ชจ๋ธ๋กœ, ๊ฐ ์‚ฌ์ดํŠธ๋Š” ์ •์ˆ˜ ๊ฐ’์„ ๊ฐ€์งˆ ์ˆ˜ ์žˆ๋Š” ๋ณ€์ˆ˜ z(i, j)๋ฅผ ๊ฐ–๋Š”๋‹ค. ์ด ๊ฐ’์€ ๋ชจ๋ž˜ ์ž…์ž๊ฐ€ ์ถ”๊ฐ€๋  ๋•Œ๋งˆ๋‹ค ์ฆ๊ฐ€ํ•˜๊ณ , ํŠน์ • ์ž„๊ณ„๊ฐ’ zm์—

Condensed Matter Nonlinear Sciences Model
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
New Principles of Coordination in Large-scale Micro- and   Molecular-Robotic Groups

New Principles of Coordination in Large-scale Micro- and Molecular-Robotic Groups

๋งค๋ ฅ์ ์ธ ํ•œ๊ธ€ ์ œ๋ชฉ: ๋Œ€๊ทœ๋ชจ ๋ฏธ์„ธ ๋ฐ ๋ถ„์ž ๋กœ๋ด‡ ์ง‘๋‹จ ์กฐ์ •์˜ ์ƒˆ๋กœ์šด ์›์น™ ์ดˆ๋ก ์ „์ฒด ๋ฒˆ์—ญ ๋ฐ ์ •๋ฆฌ: ์ด ๋…ผ๋ฌธ์€ '์ž์Šค๋ฏผ(Jasmine)' ๋กœ๋ด‡์„ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•œ ๊ตฐ์ง‘ ์—ฐ๊ตฌ์—์„œ ์œ ๋ž˜ํ•œ ๋™๊ธฐ ๋ถ€์—ฌ ์‹คํ—˜์— ๋Œ€ํ•ด ๋‹ค๋ฃน๋‹ˆ๋‹ค. ์ด ํ”Œ๋žซํผ์„ ํ†ตํ•ด ๋‹ค์–‘ํ•œ ์ƒ๋ฌผ ์˜๊ฐ ์ ‘๊ทผ ๋ฐฉ์‹์„ ํ…Œ์ŠคํŠธํ•˜๊ณ , ์ œํ•œ๋œ ๊ฐ์ง€ ๋ฐ ํ†ต์‹  ๋Šฅ๋ ฅ์„ ๋ฐ”ํƒ•์œผ๋กœ ํ†ต์ œ ๊ฐ€๋Šฅ ๋ฐœ์ƒ์  ์ง‘๋‹จ ํ–‰๋™์„ ๊ฐœ๋ฐœํ•ฉ๋‹ˆ๋‹ค. ๋กœ๋ด‡์˜ ํฌ๊ธฐ๋Š” 26 x 26 x 20mm(์ตœ์‹  ๋ฒ„์ „์€ 30 x 30 x 20mm)์ด๋ฉฐ, ์‹คํ—˜์—์„œ ์‚ฌ์šฉ๋œ ๋กœ๋ด‡ ์ˆ˜๋Š” 50~130๋Œ€์ž…๋‹ˆ๋‹ค. ์‹คํ—˜์˜ ๋ชฉ์ ์€ ๋กœ๋ด‡ ์ง‘๋‹จ ๋‚ด ์ •๋ณด ์ „๋‹ฌ์— ๊ด€ํ•œ

Robotics Computer Science
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Recovery of a Sparse Integer Solution to an Underdetermined System of Linear Equations

๋ณธ ๋…ผ๋ฌธ์€ ์Šค๋งˆํŠธ ๊ทธ๋ฆฌ๋“œ์—์„œ ๋ฐœ์ƒํ•˜๋Š” ์ด์ง„ ํ•ด ๋ณต์› ๋ฌธ์ œ๋ฅผ ๋‹ค๋ฃจ๋ฉฐ, ํŠนํžˆ m < n ์ธ ๊ฒฝ์šฐ ๋ฌดํ•œํ•œ ์‹ค์ˆ˜ ํ•ด์™€ ์—ฌ๋Ÿฌ ์ด์ง„ ํ•ด๊ฐ€ ์กด์žฌํ•  ์ˆ˜ ์žˆ๋Š” ์ƒํ™ฉ์„ ๊ณ ๋ คํ•ฉ๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋ฌธ์ œ๋Š” NP ํ•˜๋“œ๋กœ ์•Œ๋ ค์ ธ ์žˆ์œผ๋ฉฐ, ์ด๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด Mangasarian ๋“ฑ์ด ์ œ์•ˆํ•œ ๋ฐฉ๋ฒ•๋ก ์„ ๊ธฐ๋ฐ˜์œผ๋กœ ์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. 1. ๋ฌธ์ œ์˜ ๋ฐฐ๊ฒฝ๊ณผ ์ค‘์š”์„ฑ ๋…ผ๋ฌธ์€ ์Šค๋งˆํŠธ ๊ทธ๋ฆฌ๋“œ์—์„œ ๋ฐœ์ƒํ•˜๋Š” ์ด์ง„ ํ•ด ๋ณต์› ๋ฌธ์ œ์— ๋Œ€ํ•ด ๋‹ค๋ฃน๋‹ˆ๋‹ค. ๊ฐ ๊ณ ๊ฐ ๊ฐ€๊ตฌ๋Š” ์ €์ „์•• ๋ณ€์••๊ธฐ์˜ ์„ธ ๊ฐ€์ง€ ์ „์œ„ ์ค‘ ํ•˜๋‚˜์— ์—ฐ๊ฒฐ๋˜์–ด ์žˆ์œผ๋ฉฐ, ์ด๋ฅผ ์ถ”์ถœํ•˜๊ธฐ ์œ„ํ•ด A ํ–‰๋ ฌ์„ ์‚ฌ์šฉํ•ฉ๋‹ˆ๋‹ค. ์—ฌ๊ธฐ์„œ A ์˜ ์—ด

Information Theory Machine Learning Computer Science System Discrete Mathematics 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
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
Turbulent viscosity variability in self-propelled body wake model

Turbulent viscosity variability in self-propelled body wake model

: ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ž๊ฐ€ ์ถ”์ง„์ฒด์˜ ๋‚œ๋ฅ˜ ํ›„๋ฅ˜์—์„œ ์ผ์ •ํ•œ ๋‚œ๋ฅ˜ ์ ๋„ ๊ฐ€์ •์„ ํ๊ธฐํ•˜๊ณ , ์ขŒํ‘œ์— ๋”ฐ๋ฅธ ๋ณ€๋™์„ ๊ณ ๋ คํ•˜๋Š” ์ƒˆ๋กœ์šด ์ ‘๊ทผ ๋ฐฉ์‹์„ ์ œ์‹œํ•œ๋‹ค. ์ด๋Š” ์‹ค์ œ ํ๋ฆ„ ํ˜„์ƒ๊ณผ ๋” ์ž˜ ๋ถ€ํ•ฉํ•˜๋ฉฐ, ๊ธฐ์กด ๋ชจ๋ธ์˜ ํ•œ๊ณ„๋ฅผ ๊ทน๋ณตํ•˜๋ ค๋Š” ์‹œ๋„์ด๋‹ค. 1. ๋‚œ๋ฅ˜ ํ›„๋ฅ˜์˜ ์ค‘์š”์„ฑ ๋‚œ๋ฅ˜ ํ›„๋ฅ˜์˜ ์—ฐ๊ตฌ๋Š” ๊ณผํ•™์  ์ดํ•ด๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์‹ค์šฉ์ ์ธ ์ธก๋ฉด์—์„œ๋„ ๋งค์šฐ ์ค‘์š”ํ•˜๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด, ๊ณตํ•ญ ์šด์˜์—์„œ๋Š” ๋‚œ๋ฅ˜ ํ›„๋ฅ˜๊ฐ€ ๋น„ํ–‰๊ธฐ์˜ ์ด์ฐฉ๋ฅ™์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋ฉฐ, ํ•ด์–‘ ํ‘œ์ธต์—์„œ์˜ ํ˜ผํ•ฉ ๊ณผ์ •์€ ์„ ๋ฐ•์˜ ์šดํ•ญ๊ณผ ์ง์ ‘์ ์œผ๋กœ ์—ฐ๊ด€๋˜์–ด ์žˆ๋‹ค. ํŠนํžˆ, ์„ ๋ฐ•์˜ ๋‚œ๋ฅ˜ ํ›„๋ฅ˜๋Š” ๋ ˆ์ด๋” ๊ด€์ธก ํ•ด์„์—์„œ ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•˜

Physics Model
Upper Limit on the Diffuse $nu_mu$ Flux with the ANTARES Telescope

Upper Limit on the Diffuse $nu_mu$ Flux with the ANTARES Telescope

๋ณธ ๋…ผ๋ฌธ์€ ANTARES ์ค‘์„ฑ์ž ๋ง์›๊ฒฝ์„ ์ด์šฉํ•˜์—ฌ ๋งค์šฐ ๋†’์€ ์—๋„ˆ์ง€์˜ ์šฐ์ฃผ ๋ฌด์˜จ์ค‘์„ฑ์ž์˜ ์กด์žฌ๋ฅผ ํƒ์ƒ‰ํ•˜๊ณ , ๊ทธ ํ™•์‚ฐ ํ๋ฆ„ ์ƒํ•œ์„ ์„ ์ œ์‹œํ•œ๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” 2007๋…„ 12์›”๋ถ€ํ„ฐ 2009๋…„ 12์›”๊นŒ์ง€ ์ˆ˜์ง‘๋œ ๋ฐ์ดํ„ฐ๋ฅผ ๋ถ„์„ํ•˜์—ฌ ์ˆ˜ํ–‰๋˜์—ˆ์œผ๋ฉฐ, ANTARES ๋ง์›๊ฒฝ์€ ์ง€์ค‘ํ•ด์— ์„ค์น˜๋œ 885๊ฐœ์˜ ๊ด‘๋ฉ€ํ‹ฐํ”Œ๋ผ์ด์–ด ํŠœ๋ธŒ(PMT)๋กœ ๊ตฌ์„ฑ๋˜์–ด ์žˆ๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ์šฐ์ฃผ ๋ฌด์˜จ์ค‘์„ฑ์ž์˜ ์ŠคํŽ™ํŠธ๋Ÿผ์ด ๋Œ€๊ธฐ ๋ฌด์˜จ์ค‘์„ฑ์ž๋ณด๋‹ค ๋” ๋†’์€ ์—๋„ˆ์ง€๋ฅผ ๊ฐ€์งˆ ๊ฒƒ์œผ๋กœ ์˜ˆ์ƒ๋จ์— ๋”ฐ๋ผ, ํŠน์ • ๋ฐฉํ–ฅ์— ๋Œ€ํ•œ ๊ฐ€์ • ์—†์ด ๊ณ ์—๋„ˆ์ง€ ์‚ฌ๊ฑด์˜ ์ดˆ๊ณผ ์—ฌ๋ถ€๋ฅผ ๋ถ„์„ํ•œ๋‹ค. ๋ฐฐ๊ฒฝ ๋ฐ ๋ฐฉ๋ฒ•๋ก  ANTARES ๋ง์›

Astrophysics
Notes on Electronic Lexicography

Notes on Electronic Lexicography

๋ณธ ๋…ผ๋ฌธ์€ ์ „์ž ์‚ฌ์ „์˜ ๋ณธ์งˆ๊ณผ ๊ทธ ์ค‘์š”์„ฑ์„ ๋‹ค๊ฐ๋„๋กœ ๋ถ„์„ํ•˜๋ฉฐ, ๋””์ง€ํ„ธ ์‹œ๋Œ€์—์„œ ์–ธ์–ด ์ž๋ฃŒ ํ‘œํ˜„ ๋ฐฉ์‹์— ๋Œ€ํ•œ ์ƒˆ๋กœ์šด ๊ด€์ ์„ ์ œ์‹œํ•œ๋‹ค. ์ฃผ์š” ๋‚ด์šฉ์„ ์„ธ ๊ฐ€์ง€ ํฐ ๋ฒ”์ฃผ๋กœ ๋‚˜๋ˆ„์–ด ์‚ดํŽด๋ณด๋ฉด ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. 1. ์ „์ž ์‚ฌ์ „์˜ ๋ณธ์งˆ๊ณผ ์˜๋ฏธ ์žฌํ•ด์„ ์ „์ž ์‚ฌ์ „์€ ๋‹จ์ˆœํžˆ ์ข…์ด ์‚ฌ์ „์˜ ๋””์ง€ํ„ธ ๋ณ€ํ˜•์ฒด๊ฐ€ ์•„๋‹ˆ๋ผ, ์ƒˆ๋กœ์šด ์˜๋ฏธ์™€ ๊ธฐ๋Šฅ์„ ์ง€๋‹Œ ๋…ํŠนํ•œ ์–ธ์–ด ์ž๋ฃŒ๋กœ ์ •์˜๋œ๋‹ค. ์ด๋Š” '์ข…์ด ์ „์ž' ์ด๋ถ„๋ฒ•์—์„œ ๋ฒ—์–ด๋‚˜ ํ…์ŠคํŠธ์™€ ๋งค์ฒด๋ฅผ ๋ถ„๋ฆฌํ•˜์ง€ ์•Š๋Š” ๋ณธ์งˆ์ ์ธ ๊ด€์ ์„ ์ œ์‹œํ•œ๋‹ค. ์ „์ž ์‚ฌ์ „์€ ๋””์ง€ํ„ธ ํ™˜๊ฒฝ์—์„œ ์˜๋ฏธ ์ƒ์„ฑ ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ํ†ตํ•ด ์„ธ๋ถ„ํ™”๋œ ์˜๋ฏธ๋ฅผ ์ œ๊ณตํ•˜๋ฉฐ, ์ด๋ฅผ ํ†ตํ•ด ๋…

NLP Computer Science
No Image

A Non-Mainstream Viewpoint on Apparent Superluminal Phenomena in AGN Jet

: ๋ฐฐ๊ฒฝ๊ณผ ๋ฌธ์ œ์˜ ์ค‘์š”์„ฑ AGN ์ œํŠธ์—์„œ ๊ด€์ฐฐ๋˜๋Š” ์ดˆ๊ด‘์† ํ˜„์ƒ์€ ์ƒ๋Œ€๋ก ์  ๋น” ๋ชจ๋ธ๋กœ ์„ค๋ช…๋˜์–ด ์™”๋‹ค. ์ด ๋ชจ๋ธ์€ ๋น›์˜ ์†๋„ c ์— ๋Œ€ํ•œ ๊ด€์ธก๋œ ์ „๋‹จ ์†๋„๋ฅผ ๊ณ„์‚ฐํ•˜๋Š” ๋ฐ ์‚ฌ์šฉ๋˜๋ฉฐ, ์ด๋ฅผ ํ†ตํ•ด AGN ์ œํŠธ ๋‚ด์—์„œ ๋ฌผ์งˆ์ด ๋น›๋ณด๋‹ค ๋” ๋น ๋ฅด๊ฒŒ ์›€์ง์ด๋Š” ๊ฒƒ์ฒ˜๋Ÿผ ๋ณด์ผ ์ˆ˜ ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ด๋Ÿฌํ•œ ํ˜„์ƒ์€ ์ƒ๋Œ€๋ก ์  ํšจ๊ณผ์™€ ๊ด€๋ จ๋˜์–ด ์žˆ์œผ๋ฉฐ, ์‹ค์ œ ์†๋„๋Š” ๋น›์˜ ์†๋„ c ๋ฅผ ์ดˆ๊ณผํ•˜์ง€ ์•Š๋Š”๋‹ค. ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• ๋ฐ ๊ฒฐ๊ณผ ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ „ํ†ต์ ์ธ ๋ชจ๋ธ์„ ํ™•์žฅํ•˜์—ฌ ์ฃผ๋ณ€ ๋งค์งˆ ๋‚ด์—์„œ ๋น›์˜ ์ง‘๋‹จ ์†๋„๊ฐ€ 1์ด ์•„๋‹Œ ๊ฒฝ์šฐ๋ฅผ ๊ณ ๋ คํ•œ๋‹ค. ์ด๋Š” ์ฃผ๋ณ€ ๋งค์งˆ์˜ ํŠน์„ฑ์— ๋”ฐ๋ผ ๋น›์˜ ์†๋„๊ฐ€ ๋ณ€

Astrophysics
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
Electrostatic accelerometer with bias rejection for deep space   gravitation tests

Electrostatic accelerometer with bias rejection for deep space gravitation tests

์ด ๋…ผ๋ฌธ์€ ์šฐ์ฃผ ์ค‘๋ ฅ ์‹คํ—˜์„ ์œ„ํ•œ ๊ณ ๋„๋กœ ์ •๊ตํ•œ ์ „๊ธฐ ๊ฐ€์†๋„๊ณ„์ธ ๋ฏธํฌ๋กœ์Šคํƒ€๋ฅด(MicroSTAR)์™€ ๋ฐ”์ด์–ด์Šค ์žฌ๊ฑฐ์ ˆ ์‹œ์Šคํ…œ์— ๋Œ€ํ•œ ์‹ฌ์ธต ๋ถ„์„์„ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ์šฐ์ฃผ์—์„œ์˜ ๋น„์ค‘๋ ฅ ํ™˜๊ฒฝ์—์„œ ๋ฐœ์ƒํ•˜๋Š” ๊ทนํžˆ ๋ฏธ์„ธํ•œ ๊ฐ€์†๋„๋ฅผ ์ธก์ •ํ•˜๊ธฐ ์œ„ํ•œ ์ƒˆ๋กœ์šด ์ ‘๊ทผ ๋ฐฉ์‹์„ ์ œ์‹œํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. 1. ๋ฏธํฌ๋กœ์Šคํƒ€๋ฅด(MicroSTAR)์™€ ๋ฐ”์ด์–ด์Šค ์žฌ๊ฑฐ์ ˆ ์‹œ์Šคํ…œ ๋ฏธํฌ๋กœ์Šคํƒ€๋ฅด : ์ด๋Š” ์ „ํ•˜ ๊ฐ€์†๋„๊ณ„๋กœ, Onera์—์„œ ๊ฐœ๋ฐœ๋œ ์˜จ๋ผ ๊ธฐ์ˆ ์„ ํ™œ์šฉํ•˜์—ฌ ์œ„์„ฑ์˜ ๋น„์ค‘๋ ฅ ํ™˜๊ฒฝ์—์„œ ๋ฐœ์ƒํ•˜๋Š” ๊ทนํžˆ ๋ฏธ์„ธํ•œ ๊ฐ€์†๋„๋ฅผ ์ธก์ •ํ•ฉ๋‹ˆ๋‹ค. ์ธก์ • ๋…ธ์ด์ฆˆ๋Š” 1.8 ร— 10^ 4 mยทs^ 2 ๋ฒ”

General Relativity Physics
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More Mouldy Data: Another mycoplasma gene jumps the silicon barrier into the human genome

: ์ด ๋…ผ๋ฌธ์€ ์ƒ๋ช…์ •๋ณดํ•™ ๋ถ„์•ผ์—์„œ ์ค‘์š”ํ•œ ์ด์Šˆ ์ค‘ ํ•˜๋‚˜์ธ ๋ฐ์ดํ„ฐ๋ฒ ์ด์Šค ์˜ค์—ผ์— ๋Œ€ํ•ด ๊นŠ๊ฒŒ ๋‹ค๋ฃน๋‹ˆ๋‹ค. ํŠนํžˆ, ์ธ๊ฐ„ ์œ ์ „์ฒด ์„œ์—ด ๋ฐ์ดํ„ฐ์˜ ์ •ํ™•์„ฑ๊ณผ ์‹ ๋ขฐ์„ฑ์ด ์ค‘์š”ํ•จ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ , ์ด๋Ÿฌํ•œ ๋ฐ์ดํ„ฐ๊ฐ€ ๊ณฐํŒก์ด DNA๋กœ ์˜ค์—ผ๋˜์–ด ์žˆ๋‹ค๋Š” ์‚ฌ์‹ค์„ ๋ฐœ๊ฒฌํ•œ ์—ฐ๊ตฌ์ง„์€ ์ด ๋ฌธ์ œ๋ฅผ ์‹ฌ๊ฐํ•˜๊ฒŒ ๋ฐ›์•„๋“ค์ž…๋‹ˆ๋‹ค. 1. ๋ฐ์ดํ„ฐ๋ฒ ์ด์Šค ์˜ค์—ผ์˜ ๋ฐฐ๊ฒฝ ์ธ๊ฐ„ ์œ ์ „์ฒด ์„œ์—ด์ด ์ฒ˜์Œ ์ถœํŒ๋˜์—ˆ์„ ๋•Œ๋ถ€ํ„ฐ, ๋ฐ์ดํ„ฐ ์ •ํ™” ๋ฌธ์ œ๊ฐ€ ๋…ผ์˜๋˜์—ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ด๋Ÿฌํ•œ ๋…ผ์˜๋Š” ์ฃผ๋กœ ๊ธฐ์ˆ ์  ์ธก๋ฉด์— ์ดˆ์ ์„ ๋งž์ถ”์—ˆ์œผ๋ฉฐ, ์‹ค์ œ ๋ฐ์ดํ„ฐ ์˜ค์—ผ ๋ฌธ์ œ๋ฅผ ์™„์ „ํžˆ ํ•ด๊ฒฐํ•˜์ง€ ๋ชปํ–ˆ์Šต๋‹ˆ๋‹ค. ์ตœ๊ทผ ์—ฐ๊ตฌ์—์„œ๋Š” ์ธ๊ฐ„ ์œ ์ „์ฒด ์„œ์—ด์ด

Quantitative Biology Data
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A Useful Property of the Finite Nonabelian Groups

: ์ด ๋…ผ๋ฌธ์€ ์œ ํ•œ ๋น„์•„๋ฒจ ๊ตฐ์˜ ๊ตฌ์กฐ์— ๋Œ€ํ•ด ๊นŠ๊ฒŒ ํƒ๊ตฌํ•˜๋ฉฐ, ํŠนํžˆ ๊ทธ ์ค‘์‹ฌ๊ณผ ์ตœ๋Œ€ ์•„๋ฒจ ๋ถ€๋ถ„๊ตฐ ์‚ฌ์ด์˜ ๊ด€๊ณ„๋ฅผ ๋ถ„์„ํ•œ๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ๊ตฐ๋ก ์—์„œ ์ค‘์š”ํ•œ ๊ฐœ๋…์ธ Z ์˜์กด์„ฑ์„ ํ†ตํ•ด ์ด๋Ÿฌํ•œ ๊ตฐ๋“ค์˜ ํŠน์„ฑ์„ ์ดํ•ดํ•˜๋Š”๋ฐ ์ค‘์ ์„ ๋‘”๋‹ค. 1. ์ •์˜์™€ ๊ธฐ๋ณธ ๊ฐœ๋… ๋…ผ๋ฌธ์€ ์œ ํ•œ ๋น„์•„๋ฒจ ๊ตฐ G์— ๋Œ€ํ•ด ์ค‘์‹ฌ Z์™€ ์ตœ๋Œ€ ์•„๋ฒจ ๋ถ€๋ถ„๊ตฐ H i (i 1,2,...,r)๋ฅผ ์ •์˜ํ•œ๋‹ค. ์—ฌ๊ธฐ์„œ ๊ฐ H i๋Š” ์„œ๋กœ ๋‹ค๋ฅธ ์ตœ๋Œ€ ์•„๋ฒจ ๋ถ€๋ถ„๊ตฐ์ด๋ฉฐ, ๋ชจ๋“  i, j์— ๋Œ€ํ•ด i j์ผ ๋•Œ๋งŒ H i H j๊ฐ€ ์„ฑ๋ฆฝํ•œ๋‹ค. ๋˜ํ•œ G๊ฐ€ Z ์˜์กด์ ์ด๋ผ๋Š” ๊ฐœ๋…์„ ๋„์ž…ํ•˜๋Š”๋ฐ, ์ด๋Š” ๋‘ ๋ถ€๋ถ„๊ตฐ H i์™€

Mathematics
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
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™€

Computational Geometry Computer Science Data Structures
Searching for radio relics and halos. Their role in the formation and   acceleration of extragalactic cosmic rays

Searching for radio relics and halos. Their role in the formation and acceleration of extragalactic cosmic rays

: ๋ณธ ๋…ผ๋ฌธ์€ ์€ํ•˜๋‹จ ๋‚ด์—์„œ ๋ฐœ์ƒํ•˜๋Š” ๋น„์—ด์  ๋ผ๋””์˜ค ๋ฐฉ์ถœ ํ˜„์ƒ์ธ ํ• ๋กœ(halo), ์œ ๋ฌผ(relic), ๊ทธ๋ฆฌ๊ณ  ๋ฏธํ• ๋กœ(minihalo)์˜ ์—ญํ• ์„ ํƒ์ƒ‰ํ•˜๊ณ , ์ด๋“ค ํ˜„์ƒ์ด ์€ํ•˜๊ฐ„ ์šฐ์ฃผ์„  ๊ฐ€์† ๋ฐ ํ˜•์„ฑ์— ์–ด๋–ค ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š”์ง€ ๋ถ„์„ํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ๋ผ๋””์˜ค ๋ฐฉ์ถœ์€ ์ƒ๋Œ€๋ก ์  ์ „์ž๋“ค์˜ ์žฌ๊ฐ€์† ๋˜๋Š” ์ธํŠธ๋ผํด๋Ÿฌ์Šคํ„ฐ ๋งค์งˆ(ICM)๊ณผ์˜ ์–‘์„ฑ์ž ์–‘์„ฑ์ฒด ์ถฉ๋Œ์„ ํ†ตํ•ด ํ˜•์„ฑ๋œ ๊ฒƒ์œผ๋กœ ์—ฌ๊ฒจ์ง„๋‹ค. ์•„์šฐ๊ฑฐ ํ˜‘์—…๋‹จ์€ ์ดˆ๊ณ ์—๋„ˆ์ง€ ์šฐ์ฃผ์„ (UHECR)๊ณผ ์€ํ•˜๋‹จ ์ค‘์‹ฌ์˜ ๊ฐ•๋ ฅํ•œ ๋ผ๋””์˜ค ์€ํ•˜(AGN)์™€์˜ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ๋ฐœ๊ฒฌํ–ˆ์œผ๋ฉฐ, ์ด๋Ÿฌํ•œ AGN์˜ ๊ฐ€์† ๋ฉ”์ปค๋‹ˆ์ฆ˜์€ ๋‚ด๋ถ€ ์ œํŠธ ๋ฐ ๋ผ๋””์˜ค

HEP-PH Astrophysics
On drug transport after intravenous administration

On drug transport after intravenous administration

๋ณธ ๋…ผ๋ฌธ์€ ์•ฝ๋ฌผ ๋‹จ๋ฐฑ์งˆ ๊ฒฐํ•ฉ์˜ ์—ญ๋™์„ฑ๊ณผ ์ด๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•œ ์ˆ˜ํ•™์  ๋ชจ๋ธ๋ง ์ ‘๊ทผ๋ฒ•์— ๋Œ€ํ•ด ์‹ฌ๋„ ์žˆ๊ฒŒ ๋‹ค๋ฃฌ๋‹ค. ์ฃผ์š” ๋‚ด์šฉ์€ ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค: 1. ์•ฝ๋ฌผ ๋‹จ๋ฐฑ์งˆ ๊ฒฐํ•ฉ์˜ ์ •์˜์™€ ์—ญํ•  : ์•ฝ๋ฌผ ๋‹จ๋ฐฑ์งˆ ๊ฒฐํ•ฉ์€ ๋‹จ๋ฐฑ์งˆ๊ณผ ์•ฝ๋ฌผ ๋ถ„์ž ๊ฐ„์˜ ์ผ์‹œ์ ์ธ ๊ฒฐํ•ฉ์œผ๋กœ, ์ด๋Š” ์งˆ๋Ÿ‰ ์ž‘์šฉ ๋ฒ•์น™์— ๋”ฐ๋ผ ๋ฐ€๋ฆฌ์ดˆ ๋‹จ์œ„๋กœ ์ง„ํ–‰๋œ๋‹ค. ์‹คํ—˜์‹ค ํ™˜๊ฒฝ์—์„œ ๋น„๊ฒฐํ•ฉ๋œ ์•ฝ๋ฌผ ๋ถ„์ž๋Š” ์ž์œ  ์•ฝ๋ฌผ ํ˜ˆ์ค‘ ๋†๋„์™€ ์ด ํ˜ˆ์ค‘ ์•ฝ๋ฌผ ๋†๋„์˜ ๋น„์œจ์„ ํ†ตํ•ด ๊ณ„์‚ฐ๋˜๋ฉฐ, ์ด๋Š” ์ƒˆ๋กœ์šด ์•ฝ๋ฌผ ์„ค๊ณ„ ์‹œ ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•œ๋‹ค. 2. ์ž์œ  ์•ฝ๋ฌผ ๊ฐ€์„ค์— ๋Œ€ํ•œ ์˜๋ฌธ ์ œ๊ธฐ : ์Šค๋ฏธ์Šค ์—ฐ๊ตฌํŒ€์€ '์ž์œ  ์•ฝ๋ฌผ ๊ฐ€์„ค'์— ๋Œ€ํ•ด ์˜๋ฌธ์„

Quantitative Biology
Reproductive and non-reproductive solutions of the matrix equation AXB=C

Reproductive and non-reproductive solutions of the matrix equation AXB=C

Catchy Title KO: ์žฌ์ƒ์„ฑ๊ณผ ๋น„์žฌ์ƒ์„ฑ ํ•ด๋ฅผ ํ†ตํ•œ ํ–‰๋ ฌ ๋ฐฉ์ •์‹ AXB C์˜ ํ•ด๊ฒฐ Abstract KO: ๋ณธ ๋…ผ๋ฌธ์€ S. B. Preลกiฤ‡๊ฐ€ ๋„์ž…ํ•œ ์žฌ์ƒ์‹ ๋ฐฉ์ •์‹์˜ ๊ฐœ๋…์„ ๋ฐ”ํƒ•์œผ๋กœ, ํ–‰๋ ฌ ๋ฐฉ์ •์‹ AXB C์— ๋Œ€ํ•œ ํ•ด๋ฅผ ๋ถ„์„ํ•œ๋‹ค. ํŠนํžˆ, ์ด ๋…ผ๋ฌธ์—์„œ๋Š” ์žฌ์ƒ์„ฑ์  ํ•ด์™€ ๋น„์žฌ์ƒ์„ฑ์  ํ•ด์˜ ๊ตฌ๋ถ„๊ณผ ๊ทธ ํ•ด์˜ ์ผ๋ฐ˜์ ์ธ ํ˜•ํƒœ๋ฅผ ๋‹ค๋ฃฌ๋‹ค. R. Penrose์˜ ์ •๋ฆฌ์— ๋”ฐ๋ผ, ์ผ๊ด€๋œ ํ–‰๋ ฌ ๋ฐฉ์ •์‹ AXB C์˜ ์ผ๋ฐ˜ ํ•ด๋Š” ํŠน์ • ์กฐ๊ฑด ํ•˜์—์„œ {1} ์—ญํ–‰๋ ฌ์„ ์‚ฌ์šฉํ•˜์—ฌ ํ‘œํ˜„๋  ์ˆ˜ ์žˆ๋‹ค. ๋˜ํ•œ, Preลกiฤ‡์˜ ๊ฒฐ๊ณผ์™€ Haveriฤ‡์˜ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ์žฌ์ƒ์„ฑ์  ํ•ด

Mathematics
Electroluminescence in photovoltaic cell

Electroluminescence in photovoltaic cell

: ๋ณธ ๋…ผ๋ฌธ์€ ๋ฐœ๊ด‘ ํƒœ์–‘์ „์ง€(Electroluminescence, EL) ํ˜„์ƒ์„ ์ดฌ์˜ํ•˜๋Š” ๊ธฐ์ˆ ์„ ์ƒ์„ธํžˆ ์„ค๋ช…ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์ด๋Š” ๊ณผํ•™์ž๋“ค์ด ํƒœ์–‘์ „์ง€์˜ ์„ฑ๋Šฅ๊ณผ ์ƒํƒœ๋ฅผ ์‹œ๊ฐ์ ์œผ๋กœ ๋ถ„์„ํ•  ์ˆ˜ ์žˆ๋Š” ์ค‘์š”ํ•œ ๋„๊ตฌ์ž…๋‹ˆ๋‹ค. 1. EL ํ˜„์ƒ ๋ฐ ์นด๋ฉ”๋ผ ๊ฐ๋„ ๋ฌธ์ œ ํƒœ์–‘์ „์ง€๋Š” ์ž‘๋™ ์ค‘์— ์†Œ๋Ÿ‰์˜ ๋ฐฉ์‚ฌ์„ ์„ ๋ฐฉ์ถœํ•ฉ๋‹ˆ๋‹ค. ์ด ๋ฐฉ์‚ฌ์„ ์€ ์ฃผ๋กœ ์ ์™ธ์„  ์˜์—ญ์— ์œ„์น˜ํ•˜๋ฉฐ, ์ƒ์šฉ ๋””์ง€ํ„ธ ์นด๋ฉ”๋ผ๋Š” ์ด๋Ÿฌํ•œ ๋น›์„ ํšจ๊ณผ์ ์œผ๋กœ ํฌ์ฐฉํ•˜๊ธฐ ์–ด๋ ต์Šต๋‹ˆ๋‹ค. ๋Œ€๋ถ€๋ถ„์˜ CCD ์„ผ์„œ๋Š” ๊ทผ์ ์™ธ์„ (1000nm๊นŒ์ง€)์— ๋ฏผ๊ฐํ•˜์ง€๋งŒ, IR ํ•„ํ„ฐ๋ฅผ ํ†ตํ•ด IR ๋น›์œผ๋กœ ์ธํ•œ ํ๋ฆผ ํ˜„์ƒ์„ ๋ณด์™„ํ•ฉ๋‹ˆ๋‹ค. ์ด๋กœ

Physics
Hydrogen Geysers: Explanation for Observed Evidence of Geologically   Recent Volatile-Related Activity on Mercurys Surface

Hydrogen Geysers: Explanation for Observed Evidence of Geologically Recent Volatile-Related Activity on Mercurys Surface

: ์ด ๋…ผ๋ฌธ์€ ์ˆ˜์„ฑ์˜ ์ง€ํ˜• ํ˜•์„ฑ์— ๋Œ€ํ•œ ์ƒˆ๋กœ์šด ์ด๋ก ์„ ์ œ์‹œํ•˜๊ณ  ์žˆ์œผ๋ฉฐ, ๊ทธ ์ค‘์‹ฌ์—๋Š” ํœ˜๋ฐœ์„ฑ ํ™œ๋™๊ณผ ์ฒ ์˜ ์—ญํ• ์ด ์žˆ์Šต๋‹ˆ๋‹ค. ์ €์ž๋Š” ๊ธฐ์กด ๋ชจ๋ธ๋“ค๊ณผ๋Š” ๋‹ค๋ฅธ ๊ด€์ ์„ ํ†ตํ•ด ์ˆ˜์„ฑ์˜ ํ•ต์— ์—„์ฒญ๋‚œ ์–‘์˜ ์ˆ˜์†Œ๊ฐ€ ํฌํ•จ๋˜์–ด ์žˆ๋‹ค๋Š” ๊ฐ€์„ค์„ ๋‚ด์„ธ์šฐ๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. 1. ํœ˜๋ฐœ์„ฑ ํ™œ๋™์˜ ์ค‘์š”์„ฑ ์ˆ˜์„ฑ ํ‘œ๋ฉด์—์„œ ๋ฐœ๊ฒฌ๋œ '๋น„์ •์ƒ์ ์ธ ์ง€ํ˜•'์€ ํœ˜๋ฐœ์„ฑ ํ™œ๋™์œผ๋กœ ์ธํ•ด ํ˜•์„ฑ๋˜์—ˆ๋‹ค๋Š” ์ฃผ์žฅ์ด ์ œ๊ธฐ๋˜์—ˆ์Šต๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ์ง€ํ˜•์€ ์ˆ˜์„ฑ์˜ ๊ณ ์œ ํ•œ ํŠน์ง• ์ค‘ ํ•˜๋‚˜๋กœ, ๊ทธ ์›์ธ์„ ๊ทœ๋ช…ํ•˜๋Š” ๊ฒƒ์€ ํ–‰์„ฑ ๊ณผํ•™์— ์ค‘์š”ํ•œ ์˜๋ฏธ๋ฅผ ๊ฐ–์Šต๋‹ˆ๋‹ค. 2. ์ˆ˜์„ฑ ํ•ต ๋‚ด๋ถ€์˜ ํœ˜๋ฐœ์„ฑ ์š”์†Œ ์ €์ž๋Š” ์ดˆ๊ธฐ ํƒœ์–‘๊ณ„์—์„œ ๋ฐœ์ƒํ•œ

Physics
LSM is not generated by binary functions

LSM is not generated by binary functions

์ด ๋…ผ๋ฌธ์€ ๋กœ๊ทธ ์Šˆํผ๋ชจ๋“ˆ๋Ÿฌ(LSM) ํ•จ์ˆ˜ ์ง‘ํ•ฉ์˜ ๋ชจ๋“  ํ•จ์ˆ˜๊ฐ€ IMP๋กœ ์ •์˜๋  ์ˆ˜ ์žˆ๋Š”์ง€ ์—ฌ๋ถ€๋ฅผ ํƒ๊ตฌํ•˜๋ฉฐ, ์ด๋ฅผ ๋ถ€์ •์ ์œผ๋กœ ๊ฒฐ๋ก ์ง“๋Š”๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ํŠนํžˆ T2 ๊ตฌ์„ฑ ๊ฐ€๋Šฅ์„ฑ๊ณผ ๊ด€๋ จ๋œ ์ตœ์†Œํ•œ์˜ ์—ฐ์‚ฐ์„ ์‚ฌ์šฉํ•˜์—ฌ ์ด์ง„ LSM ํ•จ์ˆ˜๋ฅผ ํฌํ•จํ•˜๋Š” ์ง‘ํ•ฉ C๋ฅผ ๊ตฌ์„ฑํ•˜๊ณ , ์ด๋ฅผ PPS ฯ‰ ์ •์˜ ๊ฐ€๋Šฅ์„ฑ๊ณผ ์—ฐ๊ฒฐํ•œ๋‹ค. ๋…ผ๋ฌธ์€ ๋‹ค์Œ๊ณผ ๊ฐ™์€ ํ•ต์‹ฌ ๊ฐœ๋…๋“ค์„ ๋‹ค๋ฃฌ๋‹ค: 1. LSM ํ•จ์ˆ˜ ์ •์˜ : F(x โˆจ y)F(x โˆง y) โ‰ฅ F(x)F(y) (๋ชจ๋“  x, y โˆˆ {0, 1}^k์— ๋Œ€ํ•ด)๋ฅผ ๋งŒ์กฑํ•˜๋Š” ํ•จ์ˆ˜๋“ค๋กœ ๊ตฌ์„ฑ๋œ๋‹ค. 2. T2 ๊ตฌ์„ฑ ๊ฐ€๋Šฅ์„ฑ๊ณผ ์ตœ์†Œ ์—ฐ์‚ฐ : ์ด์ง„ LS

Computational Complexity Computer Science
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Monochromatic Progressions in Random Colorings

: 1. ๋ฐ˜๋”์™€๋ฅด๋ด ์ •๋ฆฌ์™€ W(k) ๋ฐ˜๋”์™€๋ฅด๋ด ์ •๋ฆฌ๋Š” ๋žจ์ง€ ์ด๋ก ์—์„œ ์ค‘์š”ํ•œ ์œ„์น˜๋ฅผ ์ฐจ์ง€ํ•˜๋ฉฐ, ๋ชจ๋“  ์–‘์˜ ์ •์ˆ˜ k์— ๋Œ€ํ•ด W(k)๋ผ๋Š” ์ƒํ•œ์„ ์„ ์ œ์‹œํ•ฉ๋‹ˆ๋‹ค. ์ด๋Š” {1, 2, ..., W(k)}์˜ 2์ƒ‰ ๋ถ„๋ฅ˜์—์„œ kํ•ญ ์•„๋ ˆํŠธ๋ฆญ ์ง„ํ–‰์ด ๋ฐ˜๋“œ์‹œ ๋ชจ๋…ธํฌ๋กฌ์œผ๋กœ ๋‚˜ํƒ€๋‚œ๋‹ค๋Š” ๊ฒƒ์„ ์˜๋ฏธํ•ฉ๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ W(k)์˜ ์ •ํ™•ํ•œ ๊ฐ’์€ k๊ฐ€ ์ž‘์„ ๋•Œ๋งŒ ์•Œ๋ ค์ ธ ์žˆ์œผ๋ฉฐ, k๊ฐ€ ์ปค์งˆ์ˆ˜๋ก ์ด ๊ฐ’์„ ๊ตฌํ•˜๋Š” ๊ฒƒ์ด ๋งค์šฐ ์–ด๋ ค์›Œ์ง‘๋‹ˆ๋‹ค. 2. ํ™•๋ฅ ์  ์ ‘๊ทผ: N+(k)์™€ N (k) N+(k)๋Š” {1, 2, ..., N+(k)}์˜ 2์ƒ‰ ๋ถ„๋ฅ˜์—์„œ kํ•ญ ์•„๋ ˆํŠธ๋ฆญ ์ง„ํ–‰์ด ํฌํ•จ๋  ํ™•๋ฅ ์ด

Computer Science Mathematics Discrete Mathematics
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Quantum Cost Efficient Reversible BCD Adder for Nanotechnology Based Systems

๋ณธ ๋…ผ๋ฌธ์€ ์—ญ์ „ํŒŒ ๋…ผ๋ฆฌ ํšŒ๋กœ์˜ ์ค‘์š”์„ฑ๊ณผ ๊ทธ ์ ์šฉ ๋ฒ”์œ„์— ๋Œ€ํ•ด ์ƒ์„ธํžˆ ์„ค๋ช…ํ•˜๋ฉฐ, ํŠนํžˆ BCD ๋ง์…ˆ๊ธฐ์˜ ์–‘์ž ๋น„์šฉ ํšจ์œจ์ ์ธ ์„ค๊ณ„๋ฅผ ์ œ์‹œํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ์—ญ์ „ํŒŒ ๊ฒŒ์ดํŠธ์˜ ํŠน์„ฑ์„ ์ดํ•ดํ•˜๋Š” ๋ฐ ์ค‘์ ์„ ๋‘๊ณ  ์žˆ์œผ๋ฉฐ, ์ด๋ฅผ ํ†ตํ•ด ์ €์ „๋ ฅ ํšŒ๋กœ ์„ค๊ณ„์™€ ๋‚˜๋…ธ๊ธฐ์ˆ  ๋ถ„์•ผ์—์„œ ์ค‘์š”ํ•œ ๋ฐœ์ „์„ ์ด๋ฃจ์—ˆ์Šต๋‹ˆ๋‹ค. 1. ์—ญ์ „ํŒŒ ๋…ผ๋ฆฌ์˜ ์ค‘์š”์„ฑ ์—ญ์ „ํŒŒ ๋…ผ๋ฆฌ๋Š” ์ •๋ณด ์†์‹ค ์—†์ด ์ž‘๋™ํ•˜๊ธฐ ๋•Œ๋ฌธ์— ์—ด ๋ฐœ์ƒ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์ด๋Š” ํŠนํžˆ ์ €์ „๋ ฅ ์†Œ๋ชจ ํšŒ๋กœ ์„ค๊ณ„์— ์žˆ์–ด ๋งค์šฐ ์ค‘์š”ํ•œ ํŠน์ง•์ž…๋‹ˆ๋‹ค. ์—ญ์ „ํŒŒ ๊ฒŒ์ดํŠธ๋Š” ์ž…๋ ฅ๊ณผ ์ถœ๋ ฅ ๊ฐ„ 1๋Œ€1 ๋งคํ•‘์„ ๊ตฌํ˜„ํ•˜๋ฉฐ, ์ด๋ฅผ ํ†ตํ•ด

System Computer Science Hardware Architecture
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Improved Astable Multivibrator

: ๋ณธ ๋…ผ๋ฌธ์€ ์•„์Šคํ…Œ๋ธ” ํšŒ๋กœ์˜ ์ถœ๋ ฅ ํŒŒํ˜• ๊ฐœ์„ ์„ ๋ชฉํ‘œ๋กœ ํ•˜๋ฉฐ, ์ด๋ฅผ ์œ„ํ•ด ๊ธฐ์กด ์„ค๊ณ„์—์„œ ๋ฐœ์ƒํ•˜๋Š” ๋ฌธ์ œ์ ์„ ๋ถ„์„ํ•˜๊ณ  ์ƒˆ๋กœ์šด ์†”๋ฃจ์…˜์„ ์ œ์‹œํ•œ๋‹ค. ์ „ํ†ต์ ์ธ ๋‘ ํŠธ๋žœ์ง€์Šคํ„ฐ ์•„์Šคํ…Œ๋ธ” ํšŒ๋กœ๋Š” ์ฝ˜๋ด์„œ๊ฐ€ ์ง€๋‚˜์น˜๊ฒŒ ๋น ๋ฅด๊ฒŒ ์ถฉ์ „๋˜์ง€ ์•Š๋„๋ก ํ•˜๋Š” ์‹œ๊ฐ„ ์ƒ์ˆ˜(R C ์ƒ์ˆ˜) ๋•Œ๋ฌธ์— ์ถœ๋ ฅ ํŒŒํ˜•์ด ๋А๋ฆฌ๊ฒŒ ์ƒ์Šนํ•˜๋Š” ๋ฌธ์ œ๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด R C ์ƒ์ˆ˜ ๊ฐ’์„ ๋‚ฎ์ถ”๋ฉด ์ „๋ ฅ ์†Œ๋ชจ๊ฐ€ ์ฆ๊ฐ€ํ•˜๋ฏ€๋กœ, ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ด ๊ฐ’์„ ๋ณ€๊ฒฝํ•˜์ง€ ์•Š๊ณ ๋„ ํŒŒํ˜•์„ ๊ฐœ์„ ํ•  ์ˆ˜ ์žˆ๋Š” ์ƒˆ๋กœ์šด ํšŒ๋กœ ์„ค๊ณ„๋ฅผ ์ œ์•ˆํ•œ๋‹ค. ์ƒˆ๋กœ์šด ํšŒ๋กœ ์„ค๊ณ„๋Š” ์ฝ˜๋ด์„œ์˜ ์ถฉ์ „ ๊ฒฝ๋กœ๋ฅผ ๋ณ€๊ฒฝํ•˜์—ฌ ์ปฌ๋ ‰ํ„ฐ

Physics

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