Results 211 to 220 of about 1,432,311 (298)

Machine Learning–Based Optimization of Phthalate Extraction Conditions Using HS‐INME‐GC/MS Data

open access: yesJournal of Chemometrics, Volume 40, Issue 10, October 2026.
ABSTRACT Optimization of extraction conditions in GC/MS analysis remains challenging because experimental variables can interact in complex and nonlinear ways. In this study, a machine learning based chemometric workflow was applied to optimize headspace in‐needle microextraction GC/MS (HS‐INME‐GC/MS) conditions for four phthalates: dimethyl phthalate (
Hyeyoung Jung   +2 more
wiley   +1 more source

Optimization of bioactive compounds extraction from Rosa canina L. pseudofruit through the action of two hydrolytic enzyme preparations

open access: yesJournal of Chemical Technology &Biotechnology, Volume 101, Issue 10, Page 1954-1967, October 2026.
Abstract BACKROUND The pseudo‐fruit of Rosa canina L. is a rich source of bioactive compounds with antioxidant, anti‐inflammatory, anti‐cancer, anti‐diabetic, anti‐aging, and antimicrobial activities. The aim of the present study is the optimization of a green process based on the action of two hydrolytic enzyme preparations, namely Pectinex® Ultra ...
Zafeiria Lemoni   +6 more
wiley   +1 more source

Multi‐Objective Bayesian Co‐Optimization of Parameterized Moving Horizon Estimation and Model Predictive Control

open access: yesInternational Journal of Robust and Nonlinear Control, Volume 36, Issue 15, Page 7193-7213, October 2026.
ABSTRACT This paper proposes a Machine Learning (ML)‐enabled estimator‐controller design framework, in which a parameterized Model Predictive Controller (MPC) and a parameterized Moving Horizon Estimator (MHE) are jointly refined using Bayesian Optimization (BO).
Hossein Nejatbakhsh Esfahani   +1 more
wiley   +1 more source

Measuring Well-Being Over Time: The Adjusted Mazziotta–Pareto Index Versus Other Non-compensatory Indices

open access: yes, 2017
MAZZIOTTA, Matteo   +3 more
core   +1 more source

From SAM 1 to SAM 3: Benchmarking Zero‐Shot Cross‐Domain Medical Image Segmentation

open access: yesExpert Systems, Volume 43, Issue 10, October 2026.
ABSTRACT Segmentation models have demonstrated significant potential in medical image segmentation. However, there is currently a lack of systematic, cross‐generation comparative evaluations to assess whether the iterations from SAM1 to SAM 3 can effectively enhance the clinical applicability of zero‐shot segmentation. To address this issue, this paper
Shujun Lv   +5 more
wiley   +1 more source

Home - About - Disclaimer - Privacy