Results 151 to 160 of about 23,411 (246)

Compressive Strength-Based Classification of Eco-Friendly Concretes Using Machine Learning Models. [PDF]

Materials (Basel)
Alcala-Gonzalez D, Mateo LF, Quijano MÁ, Más-López MI, García-Del-Toro EM.   +4 more
europepmc   +1 more source

Evaluation of a novel EHR sidecar application to display RA clinical outcomes during clinic visits: results of a stepped‐wedge cluster randomized pragmatic trial

Arthritis Care &Research, Accepted Article.
Objective We developed a novel EHR sidecar application to visualize key rheumatoid arthritis (RA) outcomes, including disease activity, physical function, and pain, via a patient‐facing graphical interface designed for use during outpatient visits (“RA PRO dashboard”).
Gabriela Schmajuk, Jing Li, Cathy Nasrallah, Cherish Wilson, Alicia Hamblin, Christine Hariz, Cammie Young, Stephen Shiboski, Emma Kersey, Mary Nakamura, Judith F. Ashouri, Mehrdad Matloubian, Andrew J. Gross, Jennifer Barton, Beth Berrean, Jonathan Prugh, Jinoos Yazdany   +16 more
wiley   +1 more source

Interplay between ground deformation and seismicity during the 2005-2025 unrest at Campi Flegrei. [PDF]

Sci Rep
Godano C, Convertito V, Tramelli A, Petrillo G.   +3 more
europepmc   +1 more source

A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems

International Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.
A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam, Anthony Siming Chen, Guido Herrmann   +2 more
wiley   +1 more source

BioSet2Vec: extraction of k-mer dictionaries from multiple sets of biological sequences via big data technologies. [PDF]

BMC Bioinformatics
Galluzzo Y, Giancarlo R, Rombo SE, Utro F.   +3 more
europepmc   +1 more source

Hopfield Neural Networks for Online Constrained Parameter Estimation With Time‐Varying Dynamics and Disturbances

International Journal of Adaptive Control and Signal Processing, EarlyView.
This paper proposes two projector‐based Hopfield neural network (HNN) estimators for online, constrained parameter estimation under time‐varying data, additive disturbances, and slowly drifting physical parameters. The first is a constraint‐aware HNN that enforces linear equalities and inequalities (via slack neurons) and continuously tracks the ...
Miguel Pedro Silva
wiley   +1 more source

Deformable registration and generative modelling of aortic anatomies by auto-decoders and neural ODEs. [PDF]

NPJ Biol Phys Mech
Tenderini R, Pegolotti L, Kong F, Pagani S, Regazzoni F, Marsden AL, Deparis S.   +6 more
europepmc   +1 more source

An Adaptive Human Pilot Model With Reaction Time Delay for Enhanced Adaptive Control in Piloted Systems

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces an adaptive human pilot model that captures pilot time‐delay effects in adaptive control systems. The model enables the prediction of pilot–controller interactions, facilitating safer integration and improved design of adaptive controllers for piloted applications.
Abdullah Habboush, Yildiray Yildiz
wiley   +1 more source

A machine learning approach to predict positive coronary artery calcium scores in individuals with diabetes: a cross-sectional analysis of ELSA-Brasil baseline data. [PDF]

Braz J Med Biol Res
Amorim JL, Bensenor IM, Alencar AP, Pereira AC, Goulart AC, Lotufo PA, Santos IS.   +6 more
europepmc   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source