Results 51 to 60 of about 1,153,224 (274)
Investigation of a physical model-based machine-learning force field for BaZrO3 perovskite
Journal of Aeronautical Materials, 2023 Interatomic potential is a key component of large-scale atomic simulation of materials. For scientific problems in complex environments such as high temperature，high pressure and irradiation，the interactions between atoms are often very complex.
ZHAO Liang, NIU Hongwei, JING Yuhang
doaj +1 more source
The effect of multi‐leaf collimator leaf width on VMAT treatment plan quality
Journal of Applied Clinical Medical Physics, EarlyView.Abstract Background The advent of volumetric modulated arc therapy (VMAT) in radiotherapy has made it one of the most commonly used techniques in clinical practice. VMAT is the delivery of intensity modulated radiation therapy (IMRT) while the gantry is in motion, and existing literature has shown it has decreased treatment delivery times and the ...
Gregory Sadharanu Peiris +3 more
wiley +1 more source
Journal of Marine Science and Engineering, 2023 Many achievements toward unmanned surface vehicles have been made using artificial intelligence theory to assist the decisions of the navigator. In particular, there has been rapid development in autonomous collision avoidance techniques that employ the ...
Zhe Sun, Yunsheng Fan, Guofeng Wang
doaj +1 more source
CLADAG 2021 BOOK OF ABSTRACTS AND SHORT PAPERS [PDF]
, 2021 The book collects the short papers presented at the 13th Scientific Meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society (SIS). The meeting has been organized by the Department of Statistics, Computer Science and Applications of the University of Florence, under the auspices of the Italian Statistical ...
Leonardo Egidi +3 more
openaire +48 more sources
Comprehensive clinical evaluation of novel 4DCT‐based lung function imaging methods
Journal of Applied Clinical Medical Physics, EarlyView.Abstract Purpose Methods have been developed that apply image processing to 4DCTs to generate 4DCT‐ventilation/perfusion lung imaging. Traditional methods for 4DCT‐ventilation rely on Hounsfield‐Unit (HU) density‐change methods and suffer from poor numerical robustness while not providing 4DCT‐perfusion data.
Ehsan Golkar +6 more
wiley +1 more source
Dynamical stability and chaos in artificial neural network trajectories along training
Frontiers in Complex SystemsThe process of training an artificial neural network involves iteratively adapting its parameters so as to minimize the error of the network’s prediction, when confronted with a learning task.
Kaloyan Danovski +2 more
doaj +1 more source
Learning Stabilization Control from Observations by Learning Lyapunov-like Proxy Models [PDF]
arXiv, 2023 The deployment of Reinforcement Learning to robotics applications faces the difficulty of reward engineering. Therefore, approaches have focused on creating reward functions by Learning from Observations (LfO) which is the task of learning policies from expert trajectories that only contain state sequences.
arxiv
Home‐Based Tele‐tDCS in Amyotrophic Lateral Sclerosis: Feasibility, Safety, and Preliminary Efficacy
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease with limited treatment options. Transcranial direct current stimulation (tDCS) shows promise as a neuromodulatory intervention in various neurological disorders, but its application in ALS, particularly in a remote, home‐based format, remains underexplored.
Sangeetha Madhavan +6 more
wiley +1 more source
Learning Deep Energy Shaping Policies for Stability-Guaranteed Manipulation [PDF]
arXiv, 2021 Deep reinforcement learning (DRL) has been successfully used to solve various robotic manipulation tasks. However, most of the existing works do not address the issue of control stability. This is in sharp contrast to the control theory community where the well-established norm is to prove stability whenever a control law is synthesized.
arxiv
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Sleep spindles are an electrophysiological fingerprint of the sleeping human brain. They can be described in terms of duration, frequency, amplitude, and density, and vary widely according to age and sex. Spindles play a role in sleep and wake functions and are altered in several neurological and psychiatric disorders.
Julien Coelho +8 more
wiley +1 more source