International journal of engineering and computer science

Machine learning and its use in the automatic extraction of metadata from academic articles

Rashid Turgunbaev — 2024-03-28

This article provides detailed information on machine learning processes, learning methods, supervised learning, unsupervised learning, semi-supervised learning, reinforcement learning, and the use of machine learning algorithms in the automatic extraction of metadata. Classification and regressive types of supervised learning, including decision trees, decision rules, Naive Bayes classifiers, Bayesian trust networks, nearest neighbor classifiers, linear discriminant functions, logistic regression, support vector machines, artificial neural networks, clustering and dimensionality reduction methods of unsupervised learning, semi-supervised learning, and reinforcement learning methods are also discussed.

LED lights and their impact on energy savings in a residential environment

Valentín Bladimir Palacios-Intriago — 2024-08-16

LED lights play an essential role in saving energy in homes, the objective of the research was to study their lifespan and efficiency compared to traditional lighting. The result was that energy efficiency and reduced consumption up to its durability, has positive economic benefits, in addition its environmental impact is lower, it has been proven to be a comprehensive and sustainable choice for domestic lighting.

The use of PhET to enhance the learning of mechanical energy in high school students of the Fiscomisional Educational Unit “Cinco de Mayo”

José Alvaro Mecias-Valencia — 2024-11-06

The use of the PhET simulation has proven to be an effective tool to improve the learning of mechanical energy in third-year high school students of the Fiscomisional Educational Unit "Cinco de Mayo". This research aimed to apply said simulator to facilitate the understanding of key concepts such as energy conservation, types of energy and energy transformation. Theoretical methods were used to collect information and empirical methods to evaluate its effectiveness, such as survey, interview and observation sheet. The results obtained showed that the use of the PhET simulation promoted a better understanding of mechanical energy concepts, allowing students to interactively visualize complex phenomena that would otherwise be difficult to illustrate with traditional methods. Furthermore, it was found that this digital tool made the teaching-learning process more attractive and dynamic, significantly improving the participation and motivation of students in the classroom.