Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. This study used machine learning models to investigate the potential of biosorbents ...

Abstract: Kernel extreme learning machine (KELM) not only inherits the high learning efficiency of the traditional extreme learning machine (ELM), but also mitigates the instability caused by random ...

Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, United States Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, ...

LCGC International interviewed Bob Pirok from the University of Amsterdam, Netherlands to discuss strategies for enhancing method robustness in 2D LC, practical approaches for tracking peaks across ...

No audio available for this content. High-precision GNSS applications, such as real-time displacement monitoring and vehicle navigation, rely heavily on resolving carrier-phase ambiguities. However, ...

20+ Machine Learning Methods in Groundbreaking Periodic Table From MIT, Google, Microsoft Your email has been sent A new “periodic table for machine learning” is reshaping how researchers explore AI, ...

Objective To develop and validate an interpretable machine learning (ML)-based frailty risk prediction model that combines real-time health data with validated scale assessments for enhanced ...

With the accelerating pace of urbanization, air pollution has emerged as a critical global challenge, where ozone (O 3) concentration dynamics have become a pivotal indicator of atmospheric quality ...

Reinforcement learning was tested as a means of improving liquid chromatography method development. KU Leuven and Vrije Universiteit Brussel researchers led efforts to improve deep reinforcement ...

1 School of Earth Science and Engineering, Xi’an Shiyou University, Xi’an, China. 2 Key Laboratory of Petroleum Geology and Reservoir, Xi’an Shiyou University, Xi’an, China. In the course of oil and ...