Výsledky vyhledávání - "Kim Dongchan"

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A Short-lived Rejuvenation during the Decades-long Changing-look Transition in the Nucleus of Mrk 1018

Autor: Lu, Kai-Xing, Li, Yan-Rong, Wu, Qingwen, Ho, Luis C., Zhang, Zhi-Xiang, Feng, Hai-Cheng, Li, Sha-Sha, Chen, Yong-Jie, Sun, Mouyuan, Shu, Xinwen, Guo, Wei-Jian, Cheng, Cheng, Wang, Jian-Guo, Kim, Dongchan, Wang, Jian-Min, Bai, Jin-Ming

Changing-look active galactic nuclei (CL-AGNs), characterized by emerging or disappearing of broad lines accompanied with extreme continuum flux variability, have drawn much attention for their potential of revealing physical processes underlying AGN

Externí odkaz: http://arxiv.org/abs/2411.18917

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CUE-M: Contextual Understanding and Enhanced Search with Multimodal Large Language Model

Autor: Go, Dongyoung, Whang, Taesun, Lee, Chanhee, Kim, Hwa-Yeon, Park, Sunghoon, Ji, Seunghwan, Kim, Jinho, Kim, Dongchan, Kim, Young-Bum

The integration of Retrieval-Augmented Generation (RAG) with Multimodal Large Language Models (MLLMs) has revolutionized information retrieval and expanded the practical applications of AI. However, current systems struggle in accurately interpreting

Externí odkaz: http://arxiv.org/abs/2411.12287

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A Panoramic Study of $K$-Factors for 111 Processes at the 14 TeV LHC

Autor: Kim, Dongjoo, Lee, Soojin, Jung, Hanseok, Kim, Dongchan, Kim, Jinheung, Song, Jeonghyeon

In this comprehensive study, we investigate $K$-factors ($K=\sigma_{\text{NLO}}/\sigma_{\text{LO}}\equiv 1+\delta K$) for a broad array of Standard Model processes at the 14 TeV LHC, which are pivotal for background assessments in Beyond the Standard

Externí odkaz: http://arxiv.org/abs/2402.16276

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Akademický článek

Experimental Study on the Chlorine-Induced Corrosion and Blister Formation of Steel Pipes Coated with Modified Polyethylene Powder.

Autor: Lee, Myung Kue¹ (AUTHOR) concrete@jj.ac.kr, Kim, Dongchan² (AUTHOR) kdc0357@seoultech.ac.kr, Kim, Min Ook² (AUTHOR) minookkim@seoultech.ac.kr

Publikováno v: Polymers (20734360). Sep2024, Vol. 16 Issue 17, p2415. 13p.

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Neural Motion Planning for Autonomous Parking

Autor: Kim, Dongchan, Huh, Kunsoo

This paper presents a hybrid motion planning strategy that combines a deep generative network with a conventional motion planning method. Existing planning methods such as A* and Hybrid A* are widely used in path planning tasks because of their abili

Externí odkaz: http://arxiv.org/abs/2111.06739

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Multi-Head Attention based Probabilistic Vehicle Trajectory Prediction

Autor: Kim, Hayoung, Kim, Dongchan, Kim, Gihoon, Cho, Jeongmin, Huh, Kunsoo

This paper presents online-capable deep learning model for probabilistic vehicle trajectory prediction. We propose a simple encoder-decoder architecture based on multi-head attention. The proposed model generates the distribution of the predicted tra

Externí odkaz: http://arxiv.org/abs/2004.03842

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