Results 191 to 200 of about 2,687,568 (346)

Het korset van de normaliteit

open access: yesHandelingen, 2020
Trees Versteegen
doaj  

LATE-BLOOMING TREES [PDF]

open access: green, 1894
T. S. Stevens
openalex   +1 more source

Anisotropic Surface Microrollers for Endovascular Navigation: A Computational Analysis with a Case Study in Hepatic Perfusion

open access: yesAdvanced Theory and Simulations, EarlyView.
Computational fluid dynamics analyses assess the upstream locomotion performance of anisotropic microrollers with varying height‐to‐width ratios. Observing their successful upstream locomotion in veins, their performance in hepatic circulation is investigated for treating primary liver cancer.
Burak Arslan   +8 more
wiley   +1 more source

SyMO: A Hybrid Approach for Multi‐Objective Optimization of Crystal Growth Processes

open access: yesAdvanced Theory and Simulations, EarlyView.
The hybrid SyMO (Symbolic regression Multi‐objective Optimization) framework combines Computational Fluid Dynamics (CFD), machine learning, and mathematical optimization techniques to investigate the effects of various process parameters, furnace geometries, and radiation shield material properties on key crystal quality metrics in Czochralski silicon (
Milena Petkovic, Natasha Dropka
wiley   +1 more source

Stones placed in pine-trees by birds [PDF]

open access: green, 1884
Charles Russell Orcutt
openalex   +1 more source

Accurate and Efficient Behavioral Modeling of GaN HEMTs Using An Optimized Light Gradient Boosting Machine

open access: yesAdvanced Theory and Simulations, EarlyView.
Machine Learning (ML) and optimization have permeated almost every aspect of engineering applications. Recent years have seen great traction toward ML‐based GaN HEMT modelling. However, ML‐based GaN HEMT models are mostly developed using variants of Artificial Neural Network (ANN).
Saddam Husain   +2 more
wiley   +1 more source

Bioelectrical synchronization of <i>Picea abies</i> during a solar eclipse. [PDF]

open access: yesR Soc Open Sci
Chiolerio A   +6 more
europepmc   +1 more source

Predicting Fiber Length Characteristics of Recycled Cotton and Cellulose Fiber Blends Using Machine Learning Models

open access: yesAdvanced Theory and Simulations, EarlyView.
This study explores machine learning‐driven prediction of fiber length characteristics in sustainable yarn blends made from recycled cotton and Lyocell. By analyzing empirical data through models like Random Forest and Gradient Boosting, and interpreting results with SHAP, key fiber length features from the Staple Diagram and Fibrogram are identified ...
Tuser Tirtha Biswas   +2 more
wiley   +1 more source

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