Results 51 to 60 of about 88,242 (260)
Additive Gaussian Process Regression for Predictive Design of High‐Performance, Printable Silicones
Advanced Engineering Materials, EarlyView.A chemistry‐aware design framework for tuning printable polydimethylsiloxane (PDMS) for vat photopolymerization (VPP) is developed using additive Gaussian process (GP) modeling. Polymer network mechanics informs variable groupings, feasible formulation constraints, and interaction variables.
Roxana Carbonell +3 more
wiley +1 more source
Variational learning for Gaussian mixture models [PDF]
IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), 2006 This paper proposes a joint maximum likelihood and Bayesian methodology for estimating Gaussian mixture models. In Bayesian inference, the distributions of parameters are modeled, characterized by hyperparameters. In the case of Gaussian mixtures, the distributions of parameters are considered as Gaussian for the mean, Wishart for the covariance, and ...
Nikolaos Nasios, Adrian G. Bors
openaire +2 more sources
Multimodal Data‐Driven Microstructure Characterization
Advanced Engineering Materials, EarlyView.A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang +4 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.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
Fine-Grained Image Classification With Gaussian Mixture Layer
IEEE Access, 2018 Fine-grained image classification aims at recognizing different subordinates in one basic-level category, for example, distinguishing species of birds. Compared with basic-level classification, it has both low inter-class and high intra-class variances ...
Jingyun Liang +3 more
doaj +1 more source
Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying
Advanced Engineering Materials, EarlyView.An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara +8 more
wiley +1 more source
IEEE Access, 2020 Customized production, quality variation of raw materials and other factors make industrial processes work in multiple operating modes. In general, complex industrial processes have strong nonlinearity under each operating mode. In this paper, a Gaussian
Peng Tang +4 more
doaj +1 more source
Underground target detection algorithm based on improved Gaussian mixture model
Gong-kuang zidonghua, 2021 The monitoring video images of underground coal mine have problems such as poor quality, noisy and being susceptible to sudden changes in illumination.
ZHANG Xiaoyan, GUO Haitao
doaj +1 more source
Gaussian mixture models for model improvement
CoRR19 pages, 10 figures, submitted for ...
Paolo Villani +3 more
openaire +2 more sources
In Situ Micromechanical Study of Bimodal γ′–γ″ Precipitate Assemblies in Ni–Cr–Al–Nb Superalloy
Advanced Engineering Materials, EarlyView.A Ni–Cr–Al–Nb superalloy with a bimodal γ′–γ″ precipitate distribution is developed. Composite precipitate assemblies form through heterogeneous nucleation, effectively impeding dislocation motion. Micropillar compression reveals high strength at room and elevated temperatures, governed by precipitate shearing, with coupled faulting mechanisms ...
Ujjval Bansal +4 more
wiley +1 more source