Conference submissions

Mathematical modelling for mesoscopic computational analysis of droplets using Morse and Coulombian potentials

Erick Sanchez-Gaitan¹ , Francisco Delgado²

¹ITESM, Sciences, Mexico
²ITESM, Sciences, Mexico

Abstract

Acknowledgements:

Keywords: Physical models;Computer simulation;Emulsions;Droplets modeling;Two-phase systems

Creating novel mathematical models for bacterial growth assisted by artificial intelligence

Estela Delgado-Ceballos¹ , Agustin Sanchez-Vazquez² , Francisco Delgado³

¹ITESM, Sciences, Mexico
²ITESM, Mechanical engineering, Mexico
³ITESM, Sciences, Mexico

Abstract

Acknowledgements:

Keywords: Mathematical modelling;Biotechnology;Bacterial growth;Artificial intelligence;Computer simulation;Education innovation;Higher Education

GeoGebra and ChatGPT in the Learning of a Specific Line Equation Among Pedagogy Students in Antofagasta, Chile

Jorge Olivares Funes¹ , Pablo Martin² , Flor Campos³ , Alexandra Burgos⁴

¹Universidad de Antofagasta, Mathematics, Chile
²Universidad de Antofagasta, Physic, Chile
³Universidad de Antofagasta, , Chile
⁴Universidad de Antofagasta, mathematics, Chile

Abstract

Keywords: ChatGpt;GeoGebra;Qualitative;Learning;Case study

Perceptions of mathematics teachers from the Antofagasta region of Chile regarding artificial intelligence

Jorge Olivares Funes¹ , Pablo Martin² , Carlos Portillo³ , Melissa Sanchez Tapullima⁴

¹Universidad de Antofagasta, Mathematics, Chile
²Universidad de Antofagasta, Physic, Chile
³Universidad de Antofagasta, , Chile
⁴Universidad de Antofagasta, Mathematics, Chile

Abstract

Keywords: Artificial Intelligence;Qualitative;Perceptions;Learning;Teachers

Double Stochastic Quantization:Non perturbative approach for Stochastic Quantization

Jaykov Foukzon¹

¹Israel Institution of Technology, Haifa, Israel, Center for Mathematical Sciences, Israel

Abstract

Keywords: Langevin equation;quantum field theory;Stochastic Quantization

Enhancement of classical force field predictions of hydrogen bonding in water, methanol and their crossed dimers using machine learning

Emil OBEID¹

¹American University of the Middle East , Chemistry, Kuwait

Abstract

Acknowledgements:

Keywords: Machine-learning (ML) algorithms;machine-learning force fields (MLFFs) energies;hydrogen bonds strength;water methanol dimers;Hydrogen life-span

Laser Boring Elastic Modulus Treatment for Dull and Blunt Surfaces Hub and Shaft Assembly of Press-Fit Parts

Solomon Ubani¹

¹I-Form, Department of Mechanical and Manufacturing Engineering, United Kingdom

Abstract

Keywords: Laser boring;Press-fit;Hubs;Dull;Surface;Blunt;Machine tool

Scientific supporters

Developed by I-DAS
Terms and conditions

secretariat@icmsquare.net
(+30)6944 371 526

Cookies used on this website!

This website uses cookies necessary to access the author's secure area. The website cannot function properly without these cookies. Cookies used for Preferences, Statistics and Marketing ARE NOT USED.