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연구자

1-9 out of 1499 results

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연구실

1-9 out of 942 results

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저널논문

1-3 out of 130610 results

Singular layer physics-informed neural network method for convection-dominated boundary layer problems in two dimensions JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, v.474, 2026-03

Keywords Singular perturbation Convection-dominated equations Characteristic points Scientific machine learning Boundary layer

Singular layer physics-informed neural network method for convection-dominated boundary layer problems in two dimensions
Gie, Gung-Min ; Hong, Youngjoon ; Jung, Chang-Yeol ; Lee, Dongseok

초록	This research explores neural network-based numerical approximation of two-dimensional convection-dominated singularly perturbed problems on square, circular, and elliptic domains. Singularly perturbed boundary value problems pose significant challenges due to sharp boundary layers in their solutions. Additionally, the characteristic points of these domains give rise to degenerate boundary layer problems. The stiffness of these problems, caused by sharp singular layers, can lead to substantial computational errors if not properly addressed. Conventional neural network-based approaches often fail to capture these sharp transitions accurately, highlighting a critical flaw in machine learning methods. To address these issues, we conduct a thorough boundary layer analysis to enhance our understanding of sharp transitions within the boundary layers, guiding the application of numerical methods. Specifically, we employ physics-informed neural networks (PINNs) to better handle these boundary layer problems. However, PINNs may struggle with rapidly varying singularly perturbed solutions in small domain regions, leading to inaccurate or unstable results. To overcome this limitation, we introduce a semi-analytic method that augments PINNs with singular layers or corrector functions. Our numerical experiments demonstrate significant improvements in both accuracy and stability, showcasing the effectiveness of our proposed approach.
서지사항	JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, v.474, 2026-03
ISSN	0377-0427
주제분야	Mathematics
저자 키워드	Singular perturbation Convection-dominated equations Characteristic points Scientific machine learning Boundary layer
DOI	10.1016/j.cam.2025.116918
자료유형	Article
기관	UNIST

Intestinal therapeutic agent delivery microrobot with magnetic targeting and pH-triggered degradation abilities Biomaterials, v.325, 2026-02

Keywords Magnetic targeting pH-triggering degradation Therapeutic agent delivery Microrobot Colorectal cancer

Intestinal therapeutic agent delivery microrobot with magnetic targeting and pH-triggered degradation abilities
Lee, Hyoryong ; Mun, Na Eun ; Yoon, Deockhee ; Choi, Yun-Jung ; Park, Jam-Eon ; Kim, Dong-Jae ; Yoo, Su Woong ; Park, Seung-Hwan ; Park, Sukho

초록	Oral drug delivery remains a clinically preferred route for colorectal cancer therapy due to its noninvasive nature and patient compliance. However, conventional formulations suffer from premature degradation in the gastric environment and poor site-specific targeting in the intestine, significantly reducing therapeutic efficacy. Here, we introduce an intestinal therapeutic agent delivery microrobot (ITAM) composed of a therapeutic agent (TA) encapsulated core, a magnetic nanoparticle (MNP) layer for precise magnetic guidance, and a protective layer to minimize the loss of functional materials. This layered structure enables gastric-resilient transit, magnetic localization to colorectal lesions, and colonic pH-triggered release of TAs. In vivo studies demonstrate that ITAM achieves superior lesion-specific targeting and therapeutic efficacy enhancement compared to conventional oral delivery. Furthermore, ITAM serves as a versatile platform for delivering various therapeutic substances, including drugs, cells, and beneficial microorganisms, broadening its potential applications in intestinal disease treatment and gut health modulation.
서지사항	Biomaterials, v.325, 2026-02
ISSN	0142-9612
주제분야	Engineering Materials Science
저자 키워드	Magnetic targeting pH-triggering degradation Therapeutic agent delivery Microrobot Colorectal cancer
DOI	10.1016/j.biomaterials.2025.123561
자료유형	Article
기관	DGIST

Human stem cell-based cell replacement therapy for Parkinson's disease: Enhancing the survival of postmitotic dopamine neuron grafts Neural Regeneration Research, v.21, no.2, pp.689 - 690, 2026-02

연구과제

1-3 out of 31436 results

자율주행을 위한 월드모델 : 3차원 의미론적 인지를 통한 미래 주행 영상의 시공간축 동질성 향상(이주민) 교육부, 이공분야기초연구사업, 윤성의, 2024-09 ~ 2024-11

(통합EZ)고친화도 메탄산화균의 생태생리학적 이해 증진 및 온실가스 배출저감 환경마이크로바이옴 기술 개발(2024년도) 과학기술정보통신부, 이공분야기초연구사업, 장진, 2024-05 ~ 2024-06

종양 발생 단계에서 동반되는 DNA 메틸레이션 변화 분석(2024년도) 과학기술정보통신부, KAIST기본사업1(정부), 주영석, 2024-05 ~ 2024-06

특허

1-3 out of 24162 results

무인 항공기 감지를 위한 주파수 변조 연속파 레이더 시스템 망 FREQUENCY MODULATED CONTINUOUS WAVE CHAIN RADAR SYSTEM FOR DETECTING UNMANNED AERIAL VEHICLE, Registration Number: 10-2015-0078711, Registration Date: 2027-05-26, 대한민국

II-VI 극소 나노클러스터 및 이의 제조방법 II-VI nanoclusters and method for preparing the same, Registration Number: 10-2840174, Registration Date: 2025-07-25, 대한민국

II-VI 극소 나노클러스터 및 이의 제조방법

요약정보	본 발명은 II-VI 극소 나노클러스터의 제조방법에 관한 것이다. 보다 상세하게는, 다작용기 유기리간드를 사용하여 다양한 용매에서 II-VI 극소 나노클러스터의 분산성을 향상시켜 추후 여러 전자 소자에 응용을 위한 용액공정을 가능하게 한다. 본 결과물은 2020년도 삼성전자미래기술육성센터의 재원으로 삼성전자미래기술육성센터의 지원을 받아 수행되었으며, 관련 과제정보는 아래와 같다. 연구과제명: 양자점의 생로병사 비밀규명을 통한 고효율・고안정성 양자점 소재・소자 개발 사업의 결과이다. "연구과제명: 양자점의 생로병사 비밀규명을 통한 고효율・고안정성 양자점 소재・소자 개발"	크게보기
타언어명	II-VI nanoclusters and method for preparing the same
출원번호	10-2023-0102571
출원일자	2023-08-07
등록번호	10-2840174
등록일자	2025-07-25
발명자	마현종, 양지웅
출원/등록국가	대한민국
기관	DGIST

고분자 고체 전해질 및 이를 포함하는 전고체 전지 Polymer solid electrolyte and all-solid state battery, Registration Number: 2840238, Registration Date: 2025-07-25, 대한민국

고분자 고체 전해질 및 이를 포함하는 전고체 전지

요약정보	본 발명은 이온전도성 고분자, 이미다졸륨을 포함하는 유기 이온성 플라스틱 결정(Organic Ionic Plastic Crystal) 및 리튬염을 포함하는, 고분자 고체 전해질에 관한 것으로, 일 양태에 따른 고분자 고체 전해질은 탁월한 이온전도도와 전기화학적 안정성을 동시에 구현할 수 있다.	크게보기
타언어명	Polymer solid electrolyte and all-solid state battery
출원번호	10-2023-0101434
출원일자	2023-08-03
등록번호	2840238
등록일자	2025-07-25
발명자	김은희, 김재현, 핫산 자말, 전인준
출원/등록국가	대한민국
기관	DGIST

학술활동

1-3 out of 88573 results

Development of chemical probes for capturing protein arginine kinases 6th Asian Chemical Biology Conference 2023, 대한민국, 2230-82-01 ~ 2023-08-23

Development of chemical probes for capturing protein arginine kinases
Lee, Shin Hyeon ; Kee, Jung-Min

초록	Protein kinases play a critical role in controlling numerous cellular regulation pathways and signal transduction.1 Protein arginine phosphorylation, one of the relatively acid-labile N- phosphorylations, has been identified in numerous prokaryotic and eukaryotic proteins.2 The only known protein Arg kinase is McsB in Gram-positive bacteria, which was characterized in 2009.3 McsB is a heat-stress responsive kinase and phosphorylates Arg residues in aggregated cytosolic proteins so that phosphoarginine (pArg) acts as a protein degradation tag recognized by the ClpC/ClpP protease system. Recently, bacterial-PROTAC was developed using pArg and ClpC- binding cyclic peptide to induce the degradation of the target protein.4 In contrast, no eukaryotic or mycobacterial protein Arg kinase has been identified despite the abundance of pArg sites in those organisms, hindering further studies of Arg phosphorylation. Herein, we report our progress in developing mechanism-based chemical probes to label and capture the elusive Arg kinase.
학술대회명	6th Asian Chemical Biology Conference 2023
개최국	대한민국
개최장소
개최일	2023-08-22
저자 키워드
DOI
기관	UNIST

Domain Knowledge-Informed Functional Outlier Detection for Line Quality Control Systems 한국경영과학회-대한산업공학회 2022 춘계공동학술대회, 대한민국, 2206-01 ~ 2206-04

Domain Knowledge-Informed Functional Outlier Detection for Line Quality Control Systems
Mun, Jonghwan ; Yoon, Kwonin ; Kim, Gyeongjun ; Yoo, Jitae ; Kim, Heesun ; Ryu, Nayi ; Kim, Sungil

초록
학술대회명	한국경영과학회-대한산업공학회 2022 춘계공동학술대회
개최국	대한민국
개최장소
개최일	2022-06-03
저자 키워드
DOI
기관	UNIST

광 네트워크를 통한 실시간 미디어 전송을 위한 멀티캐스트 라우팅 기법에 관한 연구 SWCC2008, 대한민국, ? ~ ?

연구장비

1-3 out of 3546 results