Results 91 to 100 of about 137,982 (257)
Unsupervised Decision Trees for Axis Unimodal Clustering
The use of decision trees for obtaining and representing clustering solutions is advantageous, due to their interpretability property. We propose a method called Decision Trees for Axis Unimodal Clustering (DTAUC), which constructs unsupervised binary ...
Paraskevi Chasani, Aristidis Likas
doaj +1 more source
We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang +2 more
wiley +1 more source
Hydrogen‐Assisted Fracture of Iron‐Based Fe–Ni–Al Alloys
Principal relations and fracture mechanisms of single‐phase and precipitate‐strengthened Fe–Ni–Al alloys subjected to prior electrochemical hydrogen charging are identified. The mechanisms of hydrogen effect on strength and microhardness are discussed, including hydrogen‐induced increase in microhardness and the role of hydrogen in fracture behavior ...
Nataliya Yadzhak +3 more
wiley +1 more source
Minimizing Size of Decision Trees for Multi-label Decision Tables [PDF]
Mohammad Azad, Mikhail Moshkov
doaj +1 more source
Classification of Diabetes Mellitus using Decision Trees
Diabetes Mellitus is a global health concern, with its prevalence and incidence rising sharply world-wide, including in Indonesia. Several factors contribute to the onset of diabetes mellitus, such as heredity, age, weight, and blood pressure.
Rinci Kembang Hapsari +3 more
doaj +1 more source
PASTA‐ELN: Simplifying Research Data Management for Experimental Materials Science
Research data management faces ongoing hurdles as many ELNs remain complex and restrictive. PASTA‐ELN offers an open‐source, cross‐platform solution that prioritizes simplicity, offline access, and user control. Its in tuitive folder structure, modular Python add‐ons, and open formats enable seamless documentation, FAIR data practices, and easy ...
S. Brinckmann, G. Winkens, R. Schwaiger
wiley +1 more source
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer +4 more
wiley +1 more source
A Practical Noise2Noise Denoising Pipeline for High‐Throughput Raman Spectroscopy
A lightweight and reproducible denoising pipeline for high‐throughput Raman spectroscopy is introduced, based on a 1D convolutional autoencoder trained with a Noise2Noise strategy. Using only repeated short‐exposure acquisitions, the method suppresses stochastic noise without reference spectra, enabling reliable spectral reconstruction while preserving
David Martin‐Calle +5 more
wiley +1 more source

