Results 181 to 190 of about 15,708 (271)
Distributed Urban Platooning towards High Flexibility, Adaptability, and Stability. [PDF]
Jeong S, Baek Y, Son SH.
europepmc +1 more source
Cognitive Behavioral Therapy for Youth with Childhood‐Onset Lupus: A Randomized Clinical Trial
Objective Our objective was to determine the feasibility and acceptability of the Treatment and Education Approach for Childhood‐onset Lupus (TEACH), a six‐session cognitive behavioral intervention addressing depressive, fatigue, and pain symptoms, delivered remotely to individual youth with lupus by a trained interventionist.
Natoshia R. Cunningham +29 more
wiley +1 more source
A Novel Spider Monkey Optimization for Reliable Data Dissemination in VANETs Based on Machine Learning. [PDF]
Gupta D, Rathi R.
europepmc +1 more source
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 +16 more
wiley +1 more source
Adaptive Localization-Free Secure Routing Protocol for Underwater Sensor Networks. [PDF]
Alharbi A, Ibrahim S.
europepmc +1 more source
Objective We assessed the effectiveness of PrismRA to improve clinical outcomes among patients with rheumatoid arthritis (RA) initiating treatment with a biologic or targeted synthetic disease‐modifying antirheumatic drug (b/tsDMARD). Methods PrismRA incorporated 19 gene expression features and four clinical features to assess a patient's likelihood of
Fenglong Xie +3 more
wiley +1 more source
Scalable Forward-Forward Algorithm
We propose a scalable Forward-Forward (FF) algorithm that eliminates the need for backpropagation by training each layer separately. Unlike backpropagation, FF avoids backward gradients and can be more modular and memory efficient, making it appealing for large networks.
openaire +2 more sources
A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems
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 +2 more
wiley +1 more source
Bio-Inspired Algorithms for Efficient Clustering and Routing in Flying Ad Hoc Networks. [PDF]
Agrawal J, Arafat MY.
europepmc +1 more source

