Over the past 50 years, the science of pediatric rheumatology has grown exponentially due to an expansion in the understanding of complex rheumatic conditions and a surge in novel targeted therapeutics. Physician‐scientists in the field of pediatric rheumatology have played major roles in these advancements that have improved the care of children ...
Ekemini A. Ogbu +2 more
wiley +1 more source
Knowledge-driven teaching-learning-based optimization algorithm for bi-objective flexible job-shop scheduling problem with tool allocation. [PDF]
Chen K, Yuan X, Tan W.
europepmc +1 more source
Neighborhood Socioeconomic Status and Short‐Term Functional Outcomes in Systemic Lupus Erythematosus
Objective Individuals with SLE can accumulate functional status (FS) impairment. We evaluated the association between neighborhood socioeconomic disadvantage, as measured by the area deprivation index (ADI), and FS in a national SLE sample. Methods Data were derived from RISE, a national electronic health record‐based registry.
Baljeet Rai +7 more
wiley +1 more source
A hybrid differential evolution algorithm for distributed assembly flexible job shop scheduling with batch delivery and inventory. [PDF]
Zhou S, Han S, Yang M, Du B.
europepmc +1 more source
A global-local neighborhood search algorithm and tabu search for flexible job shop scheduling problem. [PDF]
Escamilla Serna NJ +5 more
europepmc +1 more source
Objective We characterized emergency department (ED) gout visits and identified patient characteristics and health services patterns contributing to ED presentations. Methods We conducted a population‐based study of ED gout visits in Ontario, Canada between 2014 and 2023.
Timothy S.H. Kwok +7 more
wiley +1 more source
Offline reinforcement learning for learning to dispatch for job shop scheduling. [PDF]
Remmerden JV, Bukhsh Z, Zhang Y.
europepmc +1 more source
A Novel Approach to the Job Shop Scheduling Problem Based on the Deep Q-Network in a Cooperative Multi-Access Edge Computing Ecosystem. [PDF]
Moon J, Yang M, Jeong J.
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
A multi objective collaborative reinforcement learning algorithm for flexible job shop scheduling. [PDF]
Li J, Li S, He P, Li H.
europepmc +1 more source

