Machine learning and physics: A survey of integrated models
A Seyyedi, M Bohlouli, SN Oskoee - ACM Computing Surveys, 2023 - dl.acm.org
Predictive modeling of various systems around the world is extremely essential from the
physics and engineering perspectives. The recognition of different systems and the capacity …
physics and engineering perspectives. The recognition of different systems and the capacity …
Atomic-scale imaging of a 27-nuclear-spin cluster using a quantum sensor
Nuclear magnetic resonance (NMR) is a powerful method for determining the structure of
molecules and proteins. Whereas conventional NMR requires averaging over large …
molecules and proteins. Whereas conventional NMR requires averaging over large …
Ab Initio Simulations and Materials Chemistry in the Age of Big Data
GR Schleder, ACM Padilha… - Journal of chemical …, 2019 - ACS Publications
In this perspective, we discuss computational advances in the last decades, both in
algorithms as well as in technologies, that enabled the development, widespread use, and …
algorithms as well as in technologies, that enabled the development, widespread use, and …
Discussing the Spectra of Physics-Enhanced Machine Learning via a Survey on Structural Mechanics Applications
The intersection of physics and machine learning has given rise to a paradigm that we refer
to here as physics-enhanced machine learning (PEML), aiming to improve the capabilities …
to here as physics-enhanced machine learning (PEML), aiming to improve the capabilities …
[HTML][HTML] Roundness prediction in centreless grinding using physics-enhanced machine learning techniques
This work proposes a model for suggesting optimal process configuration in plunge
centreless grinding operations. Seven different approaches were implemented and …
centreless grinding operations. Seven different approaches were implemented and …
A semi-supervised physics-informed classifier for centerless grinding operations
M Leonesio, L Fagiano - 2022 IEEE Conference on Control …, 2022 - ieeexplore.ieee.org
Centerless grinding is a machining process characterized by highly nonlinear dynamics and
large model uncertainty, making it difficult to predict the quality of the worked parts on the …
large model uncertainty, making it difficult to predict the quality of the worked parts on the …
[HTML][HTML] Artificial intelligence enhanced two-dimensional nanoscale nuclear magnetic resonance spectroscopy
Two-dimensional nuclear magnetic resonance (NMR) is indispensable to molecule structure
determination. Nitrogen-vacancy center in diamond has been proposed and developed as …
determination. Nitrogen-vacancy center in diamond has been proposed and developed as …
Forecasting Smog Clouds With Deep Learning: A Proof-Of-Concept
V Oldenburg - 2024 - fse.studenttheses.ub.rug.nl
Air pollution and smog carry correlations to numerous pervasive health effects. Given the
risks, foreseeing toxic pollutant levels poses a vital challenge that, upon resolution, enacts a …
risks, foreseeing toxic pollutant levels poses a vital challenge that, upon resolution, enacts a …
Using visual technology to increase the productivity and quality of fruit classification in order to make retaining labour economically viable.
M van der Westhuizen - 2022 - scholar.sun.ac.za
Advancements in Industry 4.0 technologies are leading to the digitalisation and automation
of the agricultural sector. The risk of automation is that it could lead to the marginalisation of …
of the agricultural sector. The risk of automation is that it could lead to the marginalisation of …
[PDF][PDF] Science and Technology Journal, Vol. 7 Issue: 1 ISSN: 2321-3388
V Nirmala, A Rajagopal - mzu.edu.in
INTRODUCTION V. Nirmala1 and A. Rajagopal2* Science and Technology Journal, Vol. 7
Issue: 1 ISSN: 2321-3388 Page 1 INTRODUCTION new electricity, as per Prof Andrew Ng from …
Issue: 1 ISSN: 2321-3388 Page 1 INTRODUCTION new electricity, as per Prof Andrew Ng from …