Results 101 to 110 of about 665,590 (295)
The Smoothness of kernel in Hardy spaces
, 2021 This paper provides a study of problems related to Hardy spaces left by G.\,Weiss in \cite{We}. First, We will prove that the Hardy spaces $H^p(\mathbb{R}^n)$ can be characterized by a fixed Lipschitz function.
openaire +2 more sources
Advanced Robotics Research, EarlyView.This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao +6 more
wiley +1 more source
Non Parametric Confidence Intervals for Receiver Operating Characteristic Curves [PDF]
We study methods for constructing confidence intervals, and confidence bands, for estimators of receiver operating characteristics. Particular emphasis is placed on the way in which smoothing should be implemented, when estimating either the ...
Rob J. Hyndman, Yanan Fan, Peter G. Hall
core
Autonomous Navigation of Pollen‐Inspired Magnetic Microrobots for Biomedical Applications
Advanced Robotics Research, EarlyView.A sunflower pollen‐inspired magnetic microrobot enables controlled rolling navigation in vessel‐like environments. Its open geometry reduces hydrodynamic drag, while vision‐based closed‐loop control, shortest‐path planning, and reinforcement learning support target‐reaching and maze navigation with microrobot‐scale accuracy, highlighting a route toward
Ali Anil Demircali +6 more
wiley +1 more source
Smoothing Estimation of Parameters in Censored Quantile Linear Regression Model
MathematicsIn this paper, we propose a smoothing estimation method for censored quantile regression models. The method associates the convolutional smoothing estimation with the loss function, which is quadratically derivable and globally convex by using a non ...
Mingquan Wang +5 more
doaj +1 more source
A Bayesian approach to parameter estimation for kernel density estimation via transformations [PDF]
In this paper, we present a Markov chain Monte Carlo (MCMC) simulation algorithm for estimating parameters in the kernel density estimation of bivariate insurance claim data via transformations.
David Pitt +3 more
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Neural Fields for Highly Accelerated 2D Cine Phase Contrast MRI
Advanced Science, EarlyView.ABSTRACT 2D cine phase contrast (CPC) MRI provides quantitative information on blood velocity and flow within the human vasculature. However, data acquisition is time‐consuming, motivating the reconstruction of the velocity field from undersampled measurements to reduce scan times. In this work, neural fields are proposed as a continuous spatiotemporal
Pablo Arratia +7 more
wiley +1 more source
Advanced Science, EarlyView.NeuroSuite provides a modular hardware‐software platform integrating Neuroweb and NeuroMaps to enable long‐term, in situ electrophysiological interrogation of air–liquid interface organoid slices while preserving tissue architecture. Its components can be used together or independently to capture real‐time activity, spatial network dynamics, and ...
Belquis Haider +14 more
wiley +1 more source
Empirical and Kernel Estimation of the ROC Curve
Acta Universitatis Lodziensis. Folia Oeconomica, 2015 The paper presents chosen methods for estimating the ROC (Receiver Operating Characteristic) curve, including parametric and nonparametric procedures.
Aleksandra Katarzyna Baszczyńska
doaj
ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
Advanced Science, EarlyView.The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray +3 more
wiley +1 more source