Results 111 to 120 of about 157,395 (292)
Scientific ReportsThe site selection of cold-chain logistics parks is an indispensable part of their planning and construction. This study aims to establish site selection model provide a scientific and sustainable for selecting and determining optimal cold chain ...
Lu Wang +3 more
doaj +1 more source
Advanced Engineering Materials, EarlyView.X‐ray computed tomography reveals how process‐induced defects evolve from green to sintered states in Fused Filament Fabrication (FFF)‐manufactured 17‐4PH stainless steel. Internal porosity, weakest cross‐sections, and fracture locations show strong correlation with tensile performance, demonstrating the potential of computed tomography (CT)‐based ...
György Ledniczky +3 more
wiley +1 more source
Bayesian input model selection for wrist control by a bionic hand
Current Directions in Biomedical EngineeringDynamic causal modelling is a promising tool to quantify hand movement neural control. It portrays the temporal path of signals across a network of distinct motor control areas in the brain.
Mohamed Abdul-Khaaliq, Aharonson Vered
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Machine Learning‐Assisted Inverse Design of Soft and Multifunctional Hybrid Liquid Metal Composites
Advanced Functional Materials, EarlyView.A machine learning framework is presented for inverse design of synthesizable multifunctional composites containing both liquid metal and solid inclusions. By integrating physics‐based modeling, data‐driven prediction, and Bayesian optimization, the approach enables intelligent design of experiments to identify optimal compositions and realize these ...
Lijun Zhou +5 more
wiley +1 more source
Bayesian Model Selection of Regular Vine Copulas
, 2018 Regular vine copulas are a flexible class of dependence models, but Bayesian methodology for model selection and inference is not yet fully developed.
Gruber, L. and Czado, D.
core +1 more source
BELMM: Bayesian model selection and random walk smoothing in time-series clustering. [PDF]
Bioinformatics, 2023 Sarala O, Pyhäjärvi T, Sillanpää MJ.
europepmc +1 more source
Bayesian model selection for group studies — Revisited
NeuroImage, 2014 In this paper, we revisit the problem of Bayesian model selection (BMS) at the group level. We originally addressed this issue in Stephan et al. (2009), where models are treated as random effects that could differ between subjects, with an unknown population distribution.
Rigoux, Lionel +3 more
openaire +3 more sources
Advanced Materials, EarlyView.Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu +3 more
wiley +1 more source
Bayesian Model Selection with Graph Structured Sparsity
J. Mach. Learn. Res., 2019 We propose a general algorithmic framework for Bayesian model selection. A spike-and-slab Laplacian prior is introduced to model the underlying structural assumption. Using the notion of effective resistance, we derive an EM-type algorithm with closed-form iterations to efficiently explore possible candidates for Bayesian model selection.
Youngseok Kim, Chao Gao
openaire +4 more sources
Advanced Materials, EarlyView.This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley +1 more source