Results 151 to 160 of about 79,858 (307)
A Machine Learning Model for Interpretable PECVD Deposition Rate Prediction
This study develops six machine learning models (k‐nearest neighbors, support vector regression, decision tree, random forest, CatBoost, and backpropagation neural network) to predict SiNx deposition rates in plasma‐enhanced chemical vapor deposition using hybrid production and simulation data.
Yuxuan Zhai +8 more
wiley +1 more source
Dataset of GenAI preferences and digital citizenship multidimensional among Indonesian students. [PDF]
Prasetiyo WH +6 more
europepmc +1 more source
We propose a residual‐based adversarial‐gradient moving sample (RAMS) method for scientific machine learning that treats samples as trainable variables and updates them to maximize the physics residual, thereby effectively concentrating samples in inadequately learned regions.
Weihang Ouyang +4 more
wiley +1 more source
Smart Bioinspired Material‐Based Actuators: Current Challenges and Prospects
This work gathers, in a review style, an extensive and comprehensive literature overview on the development of autonomous actuators based on synthetic materials, bringing together valuable knowledge from several studies. Furthermore, the article identifies the fundamental principles of actuation mechanisms and defines key parameters to address the size
Alejandro Palacios +4 more
wiley +1 more source
Translational framework for implementation evaluation and research: a critical approach to patient-centred equity design. [PDF]
May CR +16 more
europepmc +1 more source
The World Turned on its Head: Coloniality, Civility and the Decolonial Imperative [PDF]
Hernández, Roberto D
core +1 more source
The polymerase chain reaction (PCR).Perturbation Theory and Machine Learning framework integrates perturbation theory and machine learning to classify genetic sequences, distinguishing ancient DNA from modern controls and predicting tree health from soil metagenomic data.
Jose L. Rodriguez +19 more
wiley +1 more source
A study on the moral autonomy of adolescents-an empirical analysis based on the third time national moral survey. [PDF]
Chen Y, Wang J.
europepmc +1 more source

