Multi-objective optimization of dimensional accuracy and part weight in injection molding of a 3D curved shin guard plate. [PDF]
Hoang S, Pham VQ, Tran CC.
europepmc +1 more source
Machine Learning–Based Optimization of Phthalate Extraction Conditions Using HS‐INME‐GC/MS Data
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
Penalization method to convert Bayesian optimization methods into batch multi-objective Bayesian optimization methods. [PDF]
Holder A, DeBruin H, Sestito JM.
europepmc +1 more source
One Crisis to Solve Another? The Place of Care in a World of Automated Work
Journal of Social Philosophy, EarlyView.
Anca Gheaus
wiley +1 more source
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 gold rush optimization algorithm: Theoretical Extensions and applications in UAV path planning. [PDF]
Su K, Wang Y, Kong Y, Liu W.
europepmc +1 more source
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
Multi-Objective Optimization of Milling Process Parameters Using MOWOA and Comprehensive Performance Evaluation via AHP-TOPSIS. [PDF]
Cai F, Xia R.
europepmc +1 more source
From SAM 1 to SAM 3: Benchmarking Zero‐Shot Cross‐Domain Medical Image Segmentation
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

