http://erevistas.uacj.mx/ojs/index.php/culcyt/issue/feedCultura Científica y Tecnológica2025-11-28T00:00:00-07:00Dr. Manuel Antonio Ramos Murilloculcyt@uacj.mxOpen Journal Systems<p>Revista de investigación en ingeniería e innovación tecnológica, con revisión por pares doble ciega. Publica artículos de investigación, artículos de revisión, notas técnicas y trabajos galardonados, en la modalidad de publicación continua. Acceso abierto.</p> <p>Latindex • Dialnet • Repositorio UACJ</p>http://erevistas.uacj.mx/ojs/index.php/culcyt/article/view/7177Optimality Criteria Optimization of Truss Structures Under Multiple Frequency Constraints by the Linear Approximation Resizing Rule2025-10-10T20:23:00-06:00José Alfredo Ramírez Monaresjose.ramirez@uacj.mxElva Lilia Jardón Reynosoelva.reynoso@uacj.mxQuirino Estrada Barbosaquirino.estrada@uacj.mx<p>The optimization of structures requires an efficient method to minimize weight, while satisfying multiple types of constraints. This approach generalizes the optimality criteria for the specific type of constraints in the frequency. Equations of motion for truss structures are considered to obtain the derivatives of the constraints required by the optimality criterion. Exponential and linear resizing optimization rules for the design variables are described. In the first, the optimized areas are compared with the analytical solution for a continuous rod. As a second example the optimized frequencies, weights and areas obtained by the linear resizing rule are compared to reference values. Both examples demonstrate the validity and effectiveness of the optimality criteria approach for the frequency constraints in truss structures.</p>2025-11-28T00:00:00-07:00Derechos de autor 2025 José Alfredo Ramírez Monares, Elva Lilia Jardón Reynoso, Quirino Estrada Barbosahttp://erevistas.uacj.mx/ojs/index.php/culcyt/article/view/6916ChaCha20 Encryption Algorithm Security Enhancement through Artificial Intelligence-Based Random Noisy Injection: A Case Study2025-11-10T12:38:26-07:00Edgar Rangel Lugoerangel_lugo@hotmail.comKevin Uriel Rangel Ríos kgvppro@gmail.comLeonel González Vidalesleonel.gv@cdaltamirano.tecnm.mxCarlos Alberto Bernal Beltrán carlosalberto.bb@cdaltamirano.tecnm.mxCinthya Maybeth Rangel Ríosmaybethrangelrios@gmail.comRosa Isabel Reynoso Andrésrosaisabel.ra@cdaltamirano.tecnm.mxCésar del Ángel Rodríguez Torrescesardelangel.rt@cdaltamirano.tecnm.mxLucero de Jesús Ascencio Antúnezlucerodejesus.aa@cdaltamirano.tecnm.mx<p>The problem of digital data theft is receiving growing attention in organizations because it may produce significant financial losses. This issue can be handled using dynamic encryption methodologies. There exists safety encryption alternatives such as AES (Advanced Encryption Standard) and RSA (Rivest-Shamir-Adleman). However, it is known that these algorithms have been threatened by quantum computing advent. Thereby, the aim of this research is to suggest novel dynamic encryption alternatives using artificial intelligence (AI), based on a noisy injection scheme on ciphertext, as it has the potential to mislead cybercriminals. Several aspects related to this subject were studied. Despite that quantum computing was not used, other measures have been proposed. The designed methodology was focused over the updating of ChaCha20 strategy combined with random Caesar II methodology. This fusion of techniques, referred to as random noisy ChaCha20, is suggested for increasing ciphertext security. Our novel proposal was compared with other random noisy alternatives such as random noisy DES, random noisy 3DES, random noisy AES-256, and random noisy Blowfish. The obtained results were dynamic ciphertext outputs. These schemes are limited to the ASCII table values. In conclusion, the suggested alternatives presented here may be difficult for cybercriminals to decrypt.</p>2025-12-31T00:00:00-07:00Derechos de autor 2026 Edgar Rangel Lugo , Kevin Uriel Rangel Ríos , Leonel González Vidales, Carlos Alberto Bernal Beltrán , Rosa Isabel Reynoso Andrés, César Del Ángel Rodríguez Torres, Lucero De Jesús Ascencio Antúnez Ascencio Antúnez