Results 51 to 60 of about 55,329 (202)
A Complete Framework for Acousto-Electric Tomography With Numerical Examples
IEEE Access, 2020 Acousto-electric tomography (AET) involves three steps to retrieve the distribution of conductivity in a domain of interest (DOI): measure the potential on the DOI boundary (usually with a limited number of electrodes set there), compute the power ...
Changyou Li +3 more
doaj +1 more source
Non-linear optimization of the material constants in Ogden's strain-energy function for incompressible isotropic elastic materials [PDF]
, 1981 The Levenberg—Marquardt non—linear least squares optimization algorithm is adapted to compute the material constants in Ogden' s strain—energy function for incompressible isotropic elastic materials. In previous papers, three terms have been included in
Ogden, R W, Twizell, E H
core
The geometry of nonlinear least squares with applications to sloppy models and optimization
, 2010 Parameter estimation by nonlinear least squares minimization is a common problem with an elegant geometric interpretation: the possible parameter values of a model induce a manifold in the space of data predictions.
A. Bakushinskii +29 more
core +1 more source
Advanced Science, EarlyView.Machine learning models predict in real time the onset of harmful microbubble collapse during microbubble‐enhanced focused ultrasound (MB‐FUS) and enable dynamic adjustment of sonication to prevent cavitation‐induced damage. This predictive control expands the safe operating window for bloodbrain barrier opening, enhancing nanoparticle delivery and ...
Hohyun Lee +17 more
wiley +1 more source
Confidence-aware Levenberg-Marquardt optimization for joint motion estimation and super-resolution
, 2016 Motion estimation across low-resolution frames and the reconstruction of high-resolution images are two coupled subproblems of multi-frame super-resolution.
Bercea, Cosmin +2 more
core +1 more source
Predicting Performance of Hall Effect Ion Source Using Machine Learning
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park +8 more
wiley +1 more source
Levenberg-Marquardt method for identifying Young's modulus of the elasticity imaging inverse problem
Electronic Research Archive, 2022 The present study focuses on reconstructing the Young's modulus for the elasticity imaging inverse problem. It is a very interesting and challenging problem encountered in tumor detection where the variation of the elastic properties of soft tissues ...
Talaat Abdelhamid +3 more
doaj +1 more source
Short-Term Dynamical Interactions Among Extrasolar Planets
, 2001 We show that short-term perturbations among massive planets in multiple planet systems can result in radial velocity variations of the central star which differ substantially from velocity variations derived assuming the planets are executing independent
Chambers, John E., Laughlin, Gregory
core +1 more source
A feasible and automatic free tool for T1 and ECV mapping [PDF]
, 2017 Purpose: Cardiac magnetic resonance (CMR) is a useful non-invasive tool for characterizing tissues and detecting myocardial fibrosis and edema. Estimation of extracellular volume fraction (ECV) using T1 sequences is emerging as an accurate biomarker in ...
Altabella, Luisa +8 more
core +1 more source
Advanced Intelligent Systems, EarlyView.This study introduces a data‐driven framework that combines deep reinforcement learning with classical path planning to achieve adaptive microrobot navigation. By training a surrogate neural network to emulate microrobot dynamics, the approach improves learning efficiency, reduces training time, and enables robust real‐time obstacle avoidance in ...
Amar Salehi +3 more
wiley +1 more source