Results 151 to 160 of about 828 (253)
Residual-aided CSI-free end-to-end learning for multiuser MIMO. [PDF]
Affum EA, Futa O, Oppong MA, Biney DO.
europepmc +1 more source
Abstract figure legend The ultrarapid delayed rectifier potassium current (IKur) has long been considered an atrial‐specific current with no functional role in the ventricles, despite evidence of its expression in ventricular myocytes. In the present study we challenged this prevailing concept and investigated the potential role of IKur in ventricular ...
Alaa Amin E. Abdelmagid +17 more
wiley +1 more source
FedCARE: Fuzzy-Supervised Federated Inference with Confidence Gating for Resilient IIoT Sensor Networks. [PDF]
Mostafa B +3 more
europepmc +1 more source
Mukti Acharya, Tarkeshwar Singh
openaire +1 more source
Stable Cuts, NAC‐Colourings and Flexible Realisations of Graphs
ABSTRACT A (2‐dimensional) realisation of a graph G is a pair ( G , p ), where p maps the vertices of G to R 2. A realisation is flexible if it can be continuously deformed while keeping the edge lengths fixed, and rigid otherwise. We say that G is rigid if every generic realisation of G is rigid; otherwise, G is flexible. In this paper, we investigate
Katie Clinch +5 more
wiley +1 more source
Graph-theoretic active learning for the closed-loop discovery of stochastic heterogeneous composites. [PDF]
Qiu L, Zhang S, Yang Y, Wang M.
europepmc +1 more source
A Min–Max Relation on Dicuts and Dijoins in Weighted Chordal Digraphs
ABSTRACT In a digraph, a dicut is a cut where all the arcs cross in one direction. A dijoin is a subset of arcs that intersects every dicut. Edmonds and Giles conjectured that in a weighted digraph, the minimum weight of a dicut is equal to the maximum size of a packing of dijoins. This has been disproved. However, the unweighted version conjectured by
Gérard Cornuéjols, Siyue Liu, R. Ravi
wiley +1 more source
Safe causal-graph primal-dual multi-agent scheduling for energy- and latency-constrained edge-assisted cognitive radio networks. [PDF]
Kannan T +3 more
europepmc +1 more source
Accelerating Sustainable Epoxy Resin Development Through Bayesian Optimization and Inverse Design
Development of a machine learning framework for the optimization of the Tg of partially bio‐based epoxy resin formulations in a 13‐component design space using Bayesian optimization, active learning, random design, and inverse design. The results show that the BO effectively navigates high‐dimensional formulation spaces, and the final ML model could ...
Natalie Wunder +3 more
wiley +1 more source
Characterization of healthy vs. diabetic (73:67$$ 73:67 $$) random forest classification group and its Bayesian network learned through NOTEARS structure algorithm on multi‐modal data. Shown computed SHapley Additive exPlanation (SHAP) values for various features.
Ina Hanninger +8 more
wiley +1 more source

