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Permanent URI for this collectionhttps://hdl.handle.net/11285/345284
Artículo científico o editorial en una publicación periódica académica sujeto a revisión de pares. Cumple con los índices internacionales o bases de datos de amplia cobertura, como el listado del Current Contents, ISI WEB of Knowledge (http://isiknowledge.com/) e índice de revistas mexicanas de CONACYT (www.conacyt.mx/dac/revistas). Éstos indizan y resumen los artículos de revistas seleccionadas, en todas las áreas del saber.
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- Scenarios for student-centered learning: RFiD Pocket Lab and IoT Platform as teaching tools(IEEEXplore, 2022-05-11) Crespo Saucedo, Raúl; López Caudana, Edgar Omar; Romo Medrano Mora, Katya Eugenia; Mantilla Caeiros, Alfredo Victor; https://ror.org/03ayjn504This paper contributes to the realization of learner-centered learning scenarios. It is developing an IoT learning platform for different educational levels. On the other hand, the use of “Pocket Labs” is proposed as an effective tool in the meaningful learning of emerging technologies. The fact that these tools can guide the student towards the realization of projects using a set of technologies that are on the rise generate as advantages: an increase in personnel familiar with the IoT, which has an economic impact on the industry, or that the learning is long term, as students develop and improve their understanding. Furthermore, the intention is to develop Information and Communication Tools (ICT) disciplinary competencies, which aligns with the spirit of the Tecnologico de Monterrey’s educational model. Both strategies are a relatively new teaching concept that supports students’ creativity and initiative, allowing them to wear and experiment with actual equipment at any time and place of their choice. Both experiences result in significant long-term learning in fundamental technologies for Education 4.0 and Industry 4.0. These include IoT, RFID (Radio Frequency Identification), NFC (Near Field Communications), Cloud Services, Etc.
- A basic permanent magnets array interaction project for teaching artificial intelligence as a complementary model(IEEEXplore, 2020-08-18) Varas Ibarra, Carlos; Sánchez Ochoa Ariza, Fernando; Luna Calderón, Luis Julio; Molina Gutiérrez, Arturo; López Caudana, Edgar Omar; https://ror.org/03ayjn504There are new algorithms such as artificial intelligence (AI) methodologies that have achieved accurate representation of experimental systems. On the other hand,undergraduate freshmen students must understand AImethodologies since the industry has developed several products based on those and some academic problems also can be solved using AI. If those students do not learn how to model real systems using AI, they will be losing the opportunity of applying this powerful tool for solving several real problems in their professional life. Since the AI model can be a representation for forecasting the performance of the real model, this model can help the design process and provide information during its operation. This paper proposes an engineering project to teach artificial intelligence algorithms using real systems that are non-linear. Since permanent magnets are used in several applications, they can be attractive for modeling those when they are interacting between them; hence, this paper shows the interaction among them when they are deployed as an electrical power source. Moreover, this source could be classified as a renewable energy source. The basic generation of electrical energy is based on changing the magnetic field. Although the operation principle is basic, the electrical source has a non-liner description that is extremely complex so AI could be applied to create a model that represents those non-linear relationships in a precise manner. The main goal of this work is to describe an undergraduate project that can be used for teaching how to model a real system using AI algorithms. The main characteristics and properties of the permanent magnets are studied for the comprehension of how magnets can be implemented. It is also examined the viability for the construction of an electric motor using only permanent magnets, based on the analysis of different designs and materials and finally an AI model is created.