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[Abdul박사과정, Chemosphere, JCR11%] 물환경 데이타 결측치 보정 및 센서 검증 특화 기술 개발 (Missing data imputation-Deep variational residual autoencoders))
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  • 2021-10-21

Hi all,

 

I am pleased to inform you that Ph.D students, Abdul/Jorge's paper (w/ SangYun Kim) has been published for publication in Chemosphere (IF=7.08, JCR 11%). This is the 1st experience to be accepted in this journal @ emsel, famous journal in chemicals in the environment​ & Environmental Chemistry.

Please give your big hands to Abdul.

 

[274] Abdulrahman H. Ba-Alawi+ , Jorge Loy-Benitez+ , SangYun Kim, ChangKyoo Yoo*, Missing data imputation and sensor self-validation towards a sustainable operation of wastewater treatment plants via deep variational residual autoencoders, Chemosphere(ISSN: 0045-6535​, SCIE, JCR TOP 11%), 288(3), pp.132647 (2022.2) (Ack (3개): NRF: NRF중견2021R1A2C2007838 & & BKTproject(2020003160009) & CollaboR&D project(KOBI, Project No.S3105519)).

 

Deep learning deep variational residual autoencoders​ 알고리즘을 이용한 하수처리장 missing data 보정 및 센서검증 기술 개발

연구실 박사과정 Abdul/Jorge 통합과정학생 논문이 Chemosphere(ISSN: 0045-6535​, SCIE, JCR TOP 11%)저널에 게재 승인되었습니다 (공저자: 김상윤 석사과정 학생). 

연구 내용은 물환경에서 발생하는 missing data imputation(결측데이타 대체) 및 센서 데이타 보정관련 특화 방법론 기여로 특허 출원

Chemosphere저널은 환경화학(Environmental Chemistry​)분야 좋은 저널중 하나로 Chemosphere​ 저널에  연구실 논문으로 축하합니다.

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