Results 211 to 220 of about 7,662,414 (297)
From Uncertainty to Risk: How Firms Respond in Circular Economy Transitions
Business Strategy and the Environment, EarlyView.ABSTRACT The transition to a circular economy exposes firms to multiple sources of uncertainty, yet existing research largely treats these challenges as barriers rather than drivers of firm behavior. This paper develops a conceptual understanding of how uncertainty is translated into risk and how this shapes firm responses in circular economy contexts.
Hiva Rastegar, Gabriel Eweje
wiley +1 more source
Risk Assessment and Mapping of Hand, Foot, and Mouth Disease at the County Level in Mainland China Using Spatiotemporal Zero-Inflated Bayesian Hierarchical Models. [PDF]
Int J Environ Res Public Health, 2018 Song C +5 more
europepmc +1 more source
Consumer Adoption of Internet of Things
Journal of Consumer Behaviour, Volume 24, Issue 2, Page 673-693, March 2025.ABSTRACT The Internet of Things (IoT), a pivotal technology in enhancing user connectivity, faces a paradox: its widespread potential yet limited consumer adoption. This study addresses this dichotomy by synthesizing a large‐scale meta‐analytic structural equation modeling (MASEM) and hierarchical linear meta‐analysis (HiLMA) of 2736 effect sizes from ...
Wagner Junior Ladeira +6 more
wiley +1 more source
Detecting disease-associated genomic outcomes using constrained mixture of Bayesian hierarchical models for paired data. [PDF]
PLoS One, 2017 Li Y +6 more
europepmc +1 more source
Carbon Energy, EarlyView.Incorporating AI to optimize solution, process, and environment enables efficient prediction of structural properties and performance, allowing tailoring of GDL, CL, and PEM fabrication to guide PEMFC toward 9.0 kW L‒1 by 2040. ABSTRACT The performance and commercial viability of proton exchange membrane fuel cells (PEMFCs) are constrained by key ...
Shangfeng Jiang +11 more
wiley +1 more source
Laminar Burning Velocity of Ammonia‐Hydrogen Mixtures Predicted by Machine Learning
Chemie Ingenieur Technik, EarlyView.Ammonia–hydrogen blends aid defossilization, but slow combustion kinetics require complex modeling. Although chemical kinetic modeling is computationally expensive, machine learning surrogates offer fast predictions. This study trained GPR, DT, and ANN models on 1445 experimental points.
Georg Klepp +2 more
wiley +1 more source
The Canadian Journal of Chemical Engineering, EarlyView.This study shows that integrating multiple machine learning models with optimization and decision‐making improves chemical process design, and that a consensus‐based strategy across models provides more robust and reliable operating recommendations than any single model, especially under limited or noisy data conditions.
Farough Agin +2 more
wiley +1 more source
Hierarchical Bayesian Modelling of Visual Attention
Proceedings of the 9th International Conference on Computer Vision Theory and Applications, 2014 openaire +2 more sources
The Canadian Journal of Chemical Engineering, EarlyView.Abstract Engineering graduate students confuse the scientific method and problem solving when presenting their pre‐doctoral exams and theses: Science discourse adopts question and hypotheses to assert and establish a study's rationale, while it is problem and objectives in engineering design.
Gregory S. Patience +4 more
wiley +1 more source
Weighting Bayesian information in human judgment under uncertainty: a hierarchical theory of cognitive biases. [PDF]
Front PsycholKopp B.
europepmc +1 more source