Hybrid physics-machine learning models are increasingly being used in simulations of transport processes. Many complex multiphysics systems relevant to scientific and engineering applications include multiple spatiotemporal scales and comprise a mult...
Within the field of robotics, stiffness tuning technologies have potential for a variety of applications-perhaps most notably for robotic grasping. Many stiffness tuning grippers have been developed that can grasp fragile or irregularly shaped object...
This study examined whether an inertial measurement unit (IMU), in combination with machine learning, could accurately predict two indirect measures of bowling intensity through ball release speed (BRS) and perceived intensity zone (PIZ). One IMU was...
Neural networks : the official journal of the International Neural Network Society
Jan 7, 2021
Data sparsity is a common issue to train machine learning tools such as neural networks for engineering and scientific applications, where experiments and simulations are expensive. Recently physics-constrained neural networks (PCNNs) were developed ...
This study aims to analyze and model cathodic H recovery (r), coulombic efficiency (CE) with inputs of voltage, electrical conductivity (EC) and anode potential, and H production rate and total energy recovery with inputs of r and CE in a microbial e...
The estimation of human hand pose has become the basis for many vital applications where the user depends mainly on the hand pose as a system input. Virtual reality (VR) headset, shadow dexterous hand and in-air signature verification are a few examp...
Journal of chemical information and modeling
Mar 16, 2020
The use of machine learning in chemistry is on the rise for the prediction of chemical properties. The input feature representation or descriptor in these applications is an important factor that affects the accuracy as well as the extent of the expl...
Neural networks : the official journal of the International Neural Network Society
Nov 30, 2019
Humans perceive physical properties such as motion and elastic force by observing objects in visual scenes. Recent research has proven that computers are capable of inferring physical properties from camera images like humans. However, few studies pe...
Various methods based on hyperelastic assumptions have been developed to address the mathematical complexities of modeling motion and deformation of continuum manipulators. In this study, we propose a quasistatic approach for 3D modeling and real-tim...
Fixed-wing small, unmanned aerial vehicles usually fly in atmospheric boundary layers that are often under the influence of turbulent environments. Inspired by nature's flyers, an application of an energy-harvesting flight strategy for increasing the...