Browsing by Autor "Francklin Rivas Echeverria"

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    ARQUITECTURA DE REFERENCIA PARA INTEGRACIÓN EN EMPRESAS DE PRODUCCIÓN INDUSTRIAL BASADA EN LA INTELIGENCIA ARTIFICIAL DISTRIBUIDA
    (2010) César Bravo Bravo; Jose Lisandro Aguilar Castro; Addison Ríos Bolívar; Joseph Aguilar Martin; Francklin Rivas Echeverria
    RESUMENEn este trabajo se propone una arquitectura de referencia para la integración de empresas de producción industrial basada en inteligencia artificial distribuida. Esta arquitectura aborda la complejidad de este tipo de empresas, proponiendo una alternativa para la interoperabilidad de sus componentes y la supervisión de las operaciones con una visibilidad global de los procesos de la empresa. La arquitectura propuesta consta de tres capas: una capa de integración, en donde se establecen los mecanismos de acceso a las fuentes de datos y aplicaciones de la empresa, un modelo de datos, en dónde se describen los objetos de negocio de la empresa, y una capa de gestión, en la cual, a través de sistemas multiagentes, se ejecutan y supervisan sus procesos de negocio.PALABRAS CLAVE: Arquitecturas de Empresas, Interoperabilidad de Sistemas, Holones, Sistemas Multiagentes. ABSTRACTThis contribution proposes a reference architecture for the integration of industrial production companies, based on distributed artificial intelligence. This architecture aims to deal with the complexity of this kind of companies proposing a way to allow the interoperability between their components, with a global visibility of the company business processes. The proposed architecture is composed by three layers: an integration layer, which establish the data sources and applications access mechanisms; a data meta-model, which describe the company business objects; and a management layer, where, through multi-agent systems, is developed the business process execution and supervision.KEYWORDS: Enterprises Architecture, Systems Interoperability, Holons, Multiagent Systems.
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    Translating UNESCO Artificial Intelligence Guidelines to Chemical Education and Its Intersection with Sustainable Development Goals
    (American Chemical Society, 2026) Yali Li; Laura Tolosa; Francklin Rivas Echeverria; Ronald Marquez
    As the utilization of artificial intelligence (AI) and generative AI (GenAI) is expanding in the educational field, it presents profound implications for STEM disciplines, particularly chemistry and chemical engineering. This Perspective explores the integration of AI in education, drawing from UNESCO guidelines and global recommendations from 2022 to 2025, underscoring the imperative of a human-centered pedagogical approach. The analysis highlights the transformative potential of AI in educational practices, focusing on enhanced personalized learning, teacher training, and academic management, all of which are seen as possibly contributing to advancing sustainable development goal 4 (SDG 4, quality education). It also discusses the risk of epistemic drift, where reliance on opaque algorithms may detach scientific inquiry from a causal understanding. We show examples of prompt engineering techniques for scientific illustration generation in the fields of chemistry and physical chemistry, and discuss its advantages, and limitations. Furthermore, the rapid development of AI technologies has outpaced the policy debates in most academic institutions, creating a significant policy gap in higher education. This is coupled with global disparity, where most academic institutions in high-income countries have implemented AI-driven tools by 2025, while access in low-income regions remains constrained. We argue that to harness the potential benefits of AI, the chemical education community must move beyond technical adoption to foster critical AI chemical literacy. This involves targeted investments in digital infrastructure and the development of assessments that prioritize human reasoning over algorithmic output. We conclude that the responsible integration of AI requires a shift from a content delivery model to a knowledge creation model guided by the high-level ethical frameworks proposed by UNESCO.