Results 61 to 70 of about 10,677 (169)
Artificial intelligence–driven decoupling structure–activity relationship for lithium‐ion batteries
Artificial intelligence can efferently accelerate the high‐throughput screening of battery materials, the analysis of multiphase mechanisms, and the precise prediction of capacity and cycle life. This review systematically summarizes the applications of machine learning (ML) in decoupling the complex structure‐activity relationships of lithium‐ion ...
Tao Wang +6 more
wiley +1 more source
This research proposes a physics‐informed generative machine learning framework to design SHA800, a crack‐free γ′‐strengthened nickel‐based superalloy for laser powder bed fusion, achieving a 43% γ′ volume fraction and 587 HV0.2 hardness. ABSTRACT Fabricating γ′‐strengthened nickel‐based superalloys via laser powder bed fusion (LPBF) faces significant ...
Kai Guo +11 more
wiley +1 more source
ABSTRACT Purpose To develop a unified image reconstruction framework that bridges real‐time and gated cardiac MRI, including quantitative MRI. Methods We introduce generative multitasking, which learns subject‐ and dataset‐specific implicit neural temporal bases from sequence timings and an interpretable latent space for cardiac and respiratory motion.
Xinguo Fang, Anthony G. Christodoulou
wiley +1 more source
Efficient ECG classification based on the probabilistic Kullback-Leibler divergence
Diagnostic systems of cardiac arrhythmias face early and accurate detection challenges due to the overlap of electrocardiogram (ECG) patterns. Additionally, these systems must manage a huge number of features.
Dhiah Al-Shammary +5 more
doaj +1 more source
Functional traits allow ecologists to synthesise general rules of community assembly. In joint species distribution modelling, traits are increasingly used to explain species–environment relationships, with the intention of being able to generalise predictions to other species in other systems.
Hao Ran Lai +4 more
wiley +1 more source
On Weighted Kullback–Leibler Divergence for Doubly Truncated Random Variables
In this communication, we study doubly truncated weighted Kullback–Leibler divergence (KLD) between two nonnegative random variables. The proposed measure is a generalization of the dynamic weighted KLD introduced by Yasaei Sekeh et al. (2013).
Rajesh Moharana , Suchandan Kayal
doaj +1 more source
Positive perceptions of invasive species can hinder effective management, especially if management efforts that are rooted in scientific theories are misaligned with local ecological knowledge. We documented local ecological knowledge about land invasibility as predicted by invasion biology theories. Participants with greater local ecological knowledge
Laurel Mael Philpott, Orou G. Gaoue
wiley +1 more source
ABSTRACT Low‐cost sensors are increasingly being used, and also considered for usage in regulatory contexts like air quality monitoring. Proper sensor calibration and uncertainty evaluation is necessary in such cases. With the advance of mobile sensors, for example, installed on top of a car, new test and calibration paradigms are required, in ...
Gertjan Kok, Shahin Tabandeh
wiley +1 more source
ABSTRACT This paper proposes a Machine Learning (ML)‐enabled estimator‐controller design framework, in which a parameterized Model Predictive Controller (MPC) and a parameterized Moving Horizon Estimator (MHE) are jointly refined using Bayesian Optimization (BO).
Hossein Nejatbakhsh Esfahani +1 more
wiley +1 more source
Kullback-Leibler Divergence of Sleep-Wake Patterns Related with Depressive Severity in Patients with Epilepsy. [PDF]
Liu M +5 more
europepmc +1 more source

