https://athenea.autanabooks.com/index.php/revista/issue/feedAthenea Engineering sciences journal2024-11-20T23:52:31+00:00Franyelit Suárezeditorial@autanabooks.comOpen Journal Systems<p>The <strong>Athenea Journal</strong> is published in collaboration with Ecuador and Venezuela, highlighting the multicultural values of our lands and showcasing Latin America’s scientific contributions to the world, where science becomes a universal language without borders. It is a space where the brightest minds from our nations come together to contribute to global knowledge, showing that in science there are neither limits nor barriers—only the shared desire to advance together. Athenea is not just a journal but a bridge connecting hearts and talents, proving that when we work together, borders fade away, and the future fills with infinite possibilities.</p> <p><strong>Athenea </strong>is a scientific journal oriented to Engineering Sciences. It is published by AutanaBooks SAS, with the institutional support of the Universidad Experimental "Antonio José de Sucre" (UNEXPO), vice-rectorate Puerto Ordaz, Venezuela. Its main administrative office is located in Ecuador, and its editor is PhD Franyelit Suárez.<br>The journal Athenea focuses on Engineering Sciences and aims to publish academic and scientific material of high research level and quality, produced by scientists and researchers in Latin America and the world to disseminate the work of teaching and research.</p>https://athenea.autanabooks.com/index.php/revista/article/view/78Use of Maple in the teaching of physics in engineering2024-11-19T23:52:32+00:00Brexys Linares-Rodriguez blinares9307@utm.edu.ecYomber Montilla-Lopezymontillal@uteq.edu.ec<p>This paper presents a theoretical analysis of the use of new technologies in teaching physics in engineering careers. Special emphasis is made using Maple software, since it is an easy-to-use and free-access tool, which allows students to learn quickly and efficiently, besides providing potential graphic resources. The literature is reviewed and the main results and proposals for academic development that can favor physics teaching in engineering and technical careers are presented. The results reveal that technology in education is a significant alternative to creating spaces for group interaction and learning, which includes computational skills as a valuable resource for the new professional.</p> <p> </p>2024-10-26T03:23:06+00:00Copyright (c) 2024 Brexys Linares-Rodriguez , Yomber Montilla-Lopezhttps://athenea.autanabooks.com/index.php/revista/article/view/79Genesis, lithology and mineralogy iron ore deposits with high-grade metamorphism2024-11-20T23:52:31+00:00Ernesto Armando Nunez Avilaenunez@orinoco-iron.comJesus Ramon Lopez Herculesjlopez@unexpo.edu.veCesar Alfredo Bisier Marincalfredbis@gmail.comGenaro Jose Stabilito Casaresgenaros9500@gmail.com<p>This study presents a documentary investigation of the genesis of the San Isidro Ferrous Quadrilateral, located in the Bolivar State, Venezuela, with emphasis on Los Barrancos mine, describing the origin of the ferruginous quartzites and the formation by metamorphism of the iron-ore lithologies. The methodology for the evaluation of these ores was composed of a mineralogical characterization, a chemical analysis and a macroscopic inspection, to then classify them by their mineralogy and texture. The main results show that it was possible to define the genesis, lithology and mineralogy of this ferrous deposit.</p>2024-10-26T04:18:42+00:00Copyright (c) 2024 Ernesto Armando Nunez Avila, Jesus Ramon Lopez Hercules, Cesar Alfredo Bisier Marin, Genaro Jose Stabilito Casareshttps://athenea.autanabooks.com/index.php/revista/article/view/80Use of artificial intelligence in medical classification for hemiplegic patients2024-11-20T23:52:21+00:00Natalia P. Vazquez-Lebronvazquez_131431@students.pupr.eduJuan Valera-Marquezjvalera@pupr.eduRicardo Bravo-Perezrbravo@pupr.edu<p>This study explores a machine learning-based neural network system that uses MATLAB to classify hemiplegia, a disease that causes paralysis on one side of the body. An algorithm was developed to categorize patients into four established types of hemiplegia. Techniques such as Principal Component Analysis (PCA) and Self-Organizing Maps (SOMs) were used for dimensionality reduction and data clustering, while a Convolutional Neural Network (CNN) refined the classification. The algorithm identified distinct subgroups within the categories, indicating a more complex data structure. Despite promising results to aid clinical diagnosis, further exploration of these subcategories is needed.</p>2024-10-26T04:58:08+00:00Copyright (c) 2024 Natalia P. Vazquez-Lebron, Juan Valera-Marquez, Ricardo Bravo-Perez