Results 201 to 210 of about 346,211 (298)

The impact of digital education on household allocation of risky financial assets in China. [PDF]

Sci Rep
Huang R, Shuai Q, Zhang Y, Chen Y, Zhang Q.   +4 more
europepmc   +1 more source

Deep Learning Approaches for Classifying Crack States With Overload and Predicting Fatigue Parameters in a Titanium Alloy

Advanced Intelligent Systems, EarlyView.
This study proposes a deep learning approach to evaluate the fatigue crack behavior in metals under overload conditions. Using digital image correlation to capture the strain near crack tips, convolutional neural networks classify crack states as normal, overload, or recovery, and accurately predict fatigue parameters.
Seon Du Choi, Suman Timilsina, Youn Woo Shin, Yong Nam Kwon, Kee‐Sun Sohn, Ji Sik Kim   +5 more
wiley   +1 more source

Stranded assets in European agriculture during food system transformations. [PDF]

Nat Food
Kortleve AJ, Mogollón JM, Harwatt H, Bruckner M, Liu B, Behrens P.   +5 more
europepmc   +1 more source

Deep Reinforcement Learning Approaches for Sensor Data Collection by a Swarm of UAVs

Advanced Intelligent Systems, EarlyView.
This article presents four decentralized reinforcement learning algorithms for autonomous data harvesting and investigates how collaboration improves collection efficiency. It also presents strategies to minimize training times by improving model flexibility, enabling algorithms to operate with varying number of agents and sensors.
Thiago de Souza Lamenza, Bruno José Olivieri de Souza, Markus Endler   +2 more
wiley   +1 more source

How does carbon pricing leverage emission reductions in the power sector? Evidence from China's national carbon market. [PDF]

Carbon Balance Manag
Song Y, Li Y, Peng K.
europepmc   +1 more source

Bayesian Optimisation for the Experimental Sciences: A Practical Guide to Data‐Efficient Optimisation of Laboratory Workflows

Advanced Intelligent Systems, EarlyView.
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He, Martin Singull, T. Jesper Jacobsson   +2 more
wiley   +1 more source

Efficiency analysis of listed pharmaceutical companies in China: A method combining three-stage DEA with undesirable output, PCA, and tobit regression. [PDF]

PLoS One
Sun J, Rosli AB, Daud A.
europepmc   +1 more source

Human‐Machine Mutual Trust Based Shared Control Framework for Intelligent Vehicles

Advanced Intelligent Systems, EarlyView.
This work introduces a bidirectional‐trust‐driven shared control framework for human‐machine co‐driving. The method models human‐to‐machine trust from intention discrepancies and Bayesian skill assessment, and machine‐to‐human trust from integrated ability evaluation.
Zhishuai Yin, Qian Li, Zhiwei Li, Xukai Zhai, Jinhui Gao   +4 more
wiley   +1 more source

Capitalising (on) industrial epidemics: examining the influence of the 'Big Three' asset managers on corporate governance in key health-harming commodity industries. [PDF]

Global Health
Wood B, Slater S, Friel S, Schram A, Frank N, Sacks G.   +5 more
europepmc   +1 more source

A Flexible and Energy‐Efficient Compute‐in‐Memory Accelerator for Kolmogorov–Arnold Networks

Advanced Intelligent Systems, EarlyView.
This article presents KA‐CIM, a compute‐in‐memory accelerator for Kolmogorov–Arnold Networks (KANs). It enables flexible and efficient computation of arbitrary nonlinear functions through cross‐layer co‐optimization from algorithm to device. KA‐CIM surpasses CPU, ASIC, VMM‐CIM, and prior KAN accelerators by 1–3 orders of magnitude in energy‐delay ...
Chirag Sudarshan, Oliver Artner, Paul‐Philipp Manea, Sebastian Siegel, Susanne Hoffmann‐Eifert, Regina Dittmann, John Paul Strachan   +6 more
wiley   +1 more source