Results 141 to 150 of about 57,451 (216)
Using Learning Analytics to Evaluate the Clinical Education Podcast Format. [PDF]
Horta L, Ho D, Lau KHV.
europepmc +1 more source
Facial cosmetic therapy use amongst patients with systemic sclerosis: an Australian cohort study
Objective Systemic sclerosis (SSc) is associated with numerous facial manifestations for which patients may engage in cosmetic therapies. It is unclear how patients with SSc use these therapies. This study sought to characterise patient engagement and experiences with cosmetic therapies for SSc‐related and non‐SSc‐related facial changes.
Zachary Warren +11 more
wiley +1 more source
Integrating and retrieving learning analytics data from heterogeneous platforms using ontology alignment: Graph-based approach. [PDF]
Musa MH +6 more
europepmc +1 more source
Biomedical research involving United States Veterans continues to advance healthcare beyond the Veterans Health Administration. This is particularly true in rheumatoid arthritis (RA), where Veteran‐centric research has uncovered novel insights into pathogenesis, risk factors, and disease manifestations, informing clinical care and research across both ...
Austin M. Wheeler +20 more
wiley +1 more source
A review of learning analytics opportunities and challenges for K-12 education. [PDF]
Paolucci C +5 more
europepmc +1 more source
Learning Analytics for Tracking Student Progress in LMS
QAZDAR A +5 more
europepmc +1 more source
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
Learning analytics for enhanced professional capital development: a systematic review. [PDF]
de La Hoz-Ruiz J +3 more
europepmc +1 more source
dynoGP: Deep Gaussian Processes for Dynamic System Identification
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +2 more
wiley +1 more source
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 +8 more
wiley +1 more source

