Explore how artificial intelligence and digital innovations are transforming sludge dewatering in wastewater systems, ...

By: Johan Potgieter - Cluster Industrial Software Lead at Schneider Electric Imagine walking into a factory where machines can think ahead, predict problems before it happens, and automatically make ...

The authors used a Bayesian modeling framework to fit behavior and serotonin neuron activity to reward history across multiple timescales. A key goal was to distinguish value coding from other ...

The human visual system provides us with a rich and meaningful percept of the world, transforming retinal signals into visuo-semantic representations. For a model of these representations, here we ...

Reliable fault diagnostics in gearboxes is of great importance to industries to improve production quality and reduce maintenance costs. In this paper, an improved evolving fuzzy (iEF) technique is ...

Advancements in nonlinear optics using 2D materials are transforming photonic devices, offering enhanced performance and ...

AI is transforming economic analysis, from natural language processing of central bank headlines to satellite imagery outperforming official statistics. This analysis is looking at how AI is enhancing ...

Causal Machine Learning (CML) unites ML techniques with CI in order to take advantage of both approaches’ strengths. CML ...

Abstract: The radial basis function neural network (RBFNN) is a learning model with better generalization ability, which attracts much attention in nonlinear system identification. Compared with the ...

Abstract: It is a common control issue that the input signal of the system is quantized in the controller-to-actuator channel via the communication network, but few results are available in ...

Department of Organic and Inorganic Chemistry, University of the Basque Country UPV/EHU, Barrio Sarriena, s/n, 48940 Leioa, Bizkaia, Spain ...