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Sang-Soo Baek

Showing results (1-10 of 29) with videos related to

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Chemosphere|February 12, 2024
Profiling emerging micropollutants in urban stormwater runoff using suspect and non-target screening via high-resolution mass spectrometryDaeho Kang, Daeun Yun, Kyung Hwa Cho, et al.
Environmental Science & Technology|May 9, 2025
Assessing Event-Driven Dynamics of Pesticides and Transformation Products in an Agricultural Stream Using Comprehensive Target, Suspect, and Nontarget AnalysisDaeho Kang, Daeun Yun, Kyung Hwa Cho, et al.
Water Research|March 19, 2023
Characterization of micropollutants in urban stormwater using high-resolution monitoring and machine learningDaeun Yun, Daeho Kang, Kyung Hwa Cho, et al.
Environmental Science and Ecotechnology|December 20, 2024
Graph neural networks and transfer entropy enhance forecasting of mesozooplankton community dynamicsMinhyuk Jeung, Min-Chul Jang, Kyoungsoon Shin, et al.
The Science of the Total Environment|October 16, 2021
Analysis of micropollutants in a marine outfall using network analysis and decision treeSang-Soo Baek, Daeun Yun, JongCheol Pyo, et al.
Journal of Hazardous Materials|November 13, 2024
CNT functionalized GdCoBi ternary metal oxide nanocomposite for electrochemical detection of perfluorooctanoic acid and energy storage applicationsFouzia Mashkoor, Mohd Shoeb, Mohammed Naved Khan, et al.
Journal of Hazardous Materials|September 2, 2016
Watershed-scale modeling on the fate and transport of polycyclic aromatic hydrocarbons (PAHs)Mayzonee Ligaray, Sang Soo Baek, Hye-Ok Kwon, et al.
Water Research|November 4, 2020
Replacing the internal standard to estimate micropollutants using deep and machine learningSang-Soo Baek, Younghun Choi, Junho Jeon, et al.
Water Research|August 13, 2021
Cyanobacteria cell prediction using interpretable deep learning model with observed, numerical, and sensing data assemblageJongCheol Pyo, Kyung Hwa Cho, Kyunghyun Kim, et al.
Water Research|May 6, 2022
Hierarchical deep learning model to simulate phytoplankton at phylum/class and genus levels and zooplankton at the genus levelSang-Soo Baek, Eun-Young Jung, JongCheol Pyo, et al.
Pageof 3

Showing results (1-10 of 29) with videos related to

Sort By:
Pageof 3
Chemosphere|February 12, 2024
Profiling emerging micropollutants in urban stormwater runoff using suspect and non-target screening via high-resolution mass spectrometryDaeho Kang, Daeun Yun, Kyung Hwa Cho, et al.
Environmental Science & Technology|May 9, 2025
Assessing Event-Driven Dynamics of Pesticides and Transformation Products in an Agricultural Stream Using Comprehensive Target, Suspect, and Nontarget AnalysisDaeho Kang, Daeun Yun, Kyung Hwa Cho, et al.
Water Research|March 19, 2023
Characterization of micropollutants in urban stormwater using high-resolution monitoring and machine learningDaeun Yun, Daeho Kang, Kyung Hwa Cho, et al.
Environmental Science and Ecotechnology|December 20, 2024
Graph neural networks and transfer entropy enhance forecasting of mesozooplankton community dynamicsMinhyuk Jeung, Min-Chul Jang, Kyoungsoon Shin, et al.
The Science of the Total Environment|October 16, 2021
Analysis of micropollutants in a marine outfall using network analysis and decision treeSang-Soo Baek, Daeun Yun, JongCheol Pyo, et al.
Journal of Hazardous Materials|November 13, 2024
CNT functionalized GdCoBi ternary metal oxide nanocomposite for electrochemical detection of perfluorooctanoic acid and energy storage applicationsFouzia Mashkoor, Mohd Shoeb, Mohammed Naved Khan, et al.
Journal of Hazardous Materials|September 2, 2016
Watershed-scale modeling on the fate and transport of polycyclic aromatic hydrocarbons (PAHs)Mayzonee Ligaray, Sang Soo Baek, Hye-Ok Kwon, et al.
Water Research|November 4, 2020
Replacing the internal standard to estimate micropollutants using deep and machine learningSang-Soo Baek, Younghun Choi, Junho Jeon, et al.
Water Research|August 13, 2021
Cyanobacteria cell prediction using interpretable deep learning model with observed, numerical, and sensing data assemblageJongCheol Pyo, Kyung Hwa Cho, Kyunghyun Kim, et al.
Water Research|May 6, 2022
Hierarchical deep learning model to simulate phytoplankton at phylum/class and genus levels and zooplankton at the genus levelSang-Soo Baek, Eun-Young Jung, JongCheol Pyo, et al.
Pageof 3