Results 251 to 260 of about 207,453 (329)

Climate Stress Testing on European SME Securitised Loans Under Climate Mitigation Scenarios

Business Strategy and the Environment, EarlyView.
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

Two-Tier heuristic search for ransomware-as-a-service based cyberattack défense analysis using explainable Bayesian deep learning model. [PDF]

Sci Rep
Almuflih AS.
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, Weng Marc Lim, Fernando de Oliveira Santini, Tareq Rasul, Bernardo Frantz, Jean Carlos de Oliveira Rosa, Mohd Azhar   +6 more
wiley   +1 more source

"A novel adaptive gesture recognition framework for bionic hands using Stacked Autoencoder (SAE), Adaptive Bayesian Feature Selection (ABFS), MODWT, and Hybrid sEMG-MMG Sensor Modality". [PDF]

MethodsX
Yadav AP, Patil SR.
europepmc   +1 more source

Scenario Deduction of Oil Spill from Tankersin a Ship-Ship Collision Based on the KnowledgeElement and Dynamic Bayesian Network [PDF]

Min Zeng, Yaoyao Wei, Kang-xin Yu, Hai-nan Huang, Tian Xie   +4 more
openalex   +1 more source

Machine Learning Paradigm for Advanced Battery Electrolyte Development

Carbon Energy, EarlyView.
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, Mengfan Pei, Keyu Chen, Xigao Jian, Fangyuan Hu   +4 more
wiley   +1 more source

Neural mechanisms of flexible perceptual inference. [PDF]

PLoS Comput Biol
Schwarcz J, Bauer J, Rajabi H, Marmur G, Reiner R, Lottem E, Kadmon J.   +6 more
europepmc   +1 more source

Enterprise Compliance Risk Identification and Economic Management Optimization Based on Dynamic Bayesian Network

Zhuhan Sun
openalex   +1 more source

Data‐driven simulation of crude distillation using Aspen HYSYS and comparative machine learning models

The Canadian Journal of Chemical Engineering, EarlyView.
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, Heleno Bispo, Thiago Vaz da Costa, Sérgio Mauro da Silva Neiro   +3 more
wiley   +1 more source

Modelling variability in functional brain networks using embeddings. [PDF]

Imaging Neurosci (Camb)
Huang R, Gohil C, Woolrich M.
europepmc   +1 more source