Results 251 to 260 of about 235,639 (329)
Automatic recognition of multiparty human interactions using dynamic Bayesian networks
Alfred Dielmann
openalex +1 more source
Climate Stress Testing on European SME Securitised Loans Under Climate Mitigation Scenarios
ABSTRACT Assessing the future impact of climate risks on the probability of default (PD) of small and medium enterprises (SMEs) is challenging due to limited disclosure, policy uncertainty and exposure to physical risks. This paper addresses this gap by integrating macroeconomic variables from the Network for Greening the Financial System (NGFS ...
Luca Zanin, Raffaella Calabrese
wiley +1 more source
Consumer Adoption of Internet of Things
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
Bayesian inference captures metabolite-bacteria interactions in a microbial community. [PDF]
Jansma J, Landi P, Hui C.
europepmc +1 more source
Machine Learning Paradigm for Advanced Battery Electrolyte Development
Electrolyte materials determine ion transport kinetics within the bulk and interphases, ultimately influencing the performance of battery systems. As data‐driven paradigms increasingly reshape materials discovery, this review provides an application‐oriented exploration of the intersection between machine learning and electrolyte science. By evaluating
Chang Su +4 more
wiley +1 more source
Using Dynamic Causal Bayesian Networks to Assess the Role of Patient-Centered Care and Individual-Level Barriers on Viral Suppression Changes Among a Cohort of People with HIV. [PDF]
Trepka MJ +9 more
europepmc +1 more source
Integrated Aspen HYSYS–machine learning framework for predicting product yields and quality variables. Abstract Crude oil refining is a complex process requiring precise modelling to optimize yield, quality, and efficiency. This study integrates Aspen HYSYS® simulations with machine learning techniques to develop predictive models for key refinery ...
Aldimiro Paixão Domingos +3 more
wiley +1 more source
Bayesian neural network-based policy effect prediction for green transformation of power business environment. [PDF]
Shen Y +5 more
europepmc +1 more source

