Examinando por Autor "Aguilar, J."

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    Autonomous recommender system architecture for virtual learning environments
    (Elsevier B.V., 2020-01-01) Monsalve-Pulido, J.; Aguilar, J.; Montoya, E.; Salazar, C.; Monsalve-Pulido, J.; Aguilar, J.; Montoya, E.; Salazar, C.; Universidad EAFIT. Departamento de Ingeniería de Sistemas; I+D+I en Tecnologías de la Información y las Comunicaciones
    This article proposes an architecture of an intelligent and autonomous recommendation system to be applied to any virtual learning environment, with the objective of efficiently recommending digital resources. The paper presents the architectural details of the intelligent and autonomous dimensions of the recommendation system. The paper describes a hybrid recommendation model that orchestrates and manages the available information and the specific recommendation needs, in order to determine the recommendation algorithms to be used. The hybrid model allows the integration of the approaches based on collaborative filter, content or knowledge. In the architecture, information is extracted from four sources: the context, the students, the course and the digital resources, identifying variables, such as individual learning styles, socioeconomic information, connection characteristics, location, etc. Tests were carried out for the creation of an academic course, in order to analyse the intelligent and autonomous capabilities of the architecture. © 2020 The Authors
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    Comparison and evaluation of different methods for the feature extraction from educational contents
    (MDPI Multidisciplinary Digital Publishing Institute, 2020-01-01) Aguilar, J.; Salazar, C.; Velasco, H.; Monsalve-Pulido, J.; Montoya, E.; Aguilar, J.; Salazar, C.; Velasco, H.; Monsalve-Pulido, J.; Montoya, E.; Universidad EAFIT. Departamento de Ingeniería de Sistemas; I+D+I en Tecnologías de la Información y las Comunicaciones
    This paper analyses the capabilities of different techniques to build a semantic representation of educational digital resources. Educational digital resources are modeled using the Learning Object Metadata (LOM) standard, and these semantic representations can be obtained from different LOM fields, like the title, description, among others, in order to extract the features/characteristics from the digital resources. The feature extraction methods used in this paper are the Best Matching 25 (BM25), the Latent Semantic Analysis (LSA), Doc2Vec, and the Latent Dirichlet allocation (LDA). The utilization of the features/descriptors generated by them are tested in three types of educational digital resources (scientific publications, learning objects, patents), a paraphrase corpus and two use cases: in an information retrieval context and in an educational recommendation system. For this analysis are used unsupervised metrics to determine the feature quality proposed by each one, which are two similarity functions and the entropy. In addition, the paper presents tests of the techniques for the classification of paraphrases. The experiments show that according to the type of content and metric, the performance of the feature extraction methods is very different; in some cases are better than the others, and in other cases is the inverse. © 2020 by the authors.
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    FAVO: Framework de gestión autónoma de organizaciones virtuales basado en la industria 4.0
    (Associacao Iberica de Sistemas e Tecnologias de Informacao, 2020-01-01) Lopez, C.-P.; Santorum, M.; Aguilar, J.; Lopez, C.-P.; Santorum, M.; Aguilar, J.; Universidad EAFIT. Departamento de Ingeniería de Sistemas; I+D+I en Tecnologías de la Información y las Comunicaciones
    In the information age, the digitalization is transforming traditional organizations, allowing them to improve their productivity, be more competitive and flexible. In addition, it gives them the opportunity to form strategic alliances, also called Virtual Organization (VO). Organizations have to face these challenges smartly, in order to collaborate effectively and achieve their goals. The existing literature shows that the different aspects of collaboration between VOs have been widely discussed and addressed, but no framework has been found that, based on the benefits of Industry 4.0, can be applied to the creation and management of VOs in a way autonomous. From this gap found in the literature, it is proposed to design a framework that guarantees the effectiveness of inter-organizational autonomous management, through the use of autonomous cycles of data analytics tasks and collaborative processes. © 2020, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved.
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    Industry 4.0: survey from a system integration perspective
    (TAYLOR & FRANCIS LTD, 2020-01-01) Sanchez, M.; Exposito, E.; Aguilar, J.; Sanchez, M.; Exposito, E.; Aguilar, J.; Universidad EAFIT. Departamento de Ingeniería de Sistemas; I+D+I en Tecnologías de la Información y las Comunicaciones
    In recent years, a revolution named Industry 4.0 has arisen. Industry 4.0 is presented as the integration of new advances in areas such as Cyber-Physical Systems, the Internet of Things and Everything (IoE), Cloud computing, the Internet of Services, Big Data Analysis, Smart Factories, Augmented Reality, among others. Industry 4.0 is not only a new industrial revolution, but also a crucial integration challenge that involves several actors from the IoE, which are people, data, services, and things. This paper proposes an approach to analyze the integration challenges in the context of Industry 4.0 using five integration levels, which are connection, communication, coordination, cooperation, and collaboration (5 C). In that sense, this paper presents a state of the art of recent studies in Industry 4.0 from an integration perspective, categorized according to the 5 C integration levels versus the four actors of IoE. Specifically, this paper considers several works intended to solve problems of autonomic integration in Industry 4.0 at the highest levels of the 5 C integration stack (coordination, cooperation, and collaboration). Also, this paper presents a case study from an integration perspective, which contemplates autonomy, self-organizing, among other aspects, in order to turn a traditional industry into a smart factory regarding the Industry 4.0 concept. © 2020, © 2020 Informa UK Limited, trading as Taylor & Francis Group.
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    Performance analysis of the ubiquitous and emergent properties of an autonomic reflective middleware for smart cities
    (Springer, 2020-01-01) Aguilar, J.; Jerez, M.; Mendonça, M.; Sánchez, M.; Aguilar, J.; Jerez, M.; Mendonça, M.; Sánchez, M.; Universidad EAFIT. Departamento de Ingeniería de Sistemas; I+D+I en Tecnologías de la Información y las Comunicaciones
    One of the biggest challenges in a Smart City is how to describe and dispose of the enormous and multiple sources of information, and how to share and merge it into a single infrastructure, in a timely and correct manner. A Smart City requires computational platforms, which allow the interconnection of multiple and embedded systems, such that the technology is integrated with people, and can respond to unpredictable situations. The integration of information and communications technology in these spaces, allows exploiting the wealth of information and knowledge generated in a Smart City, and improving its planning and services offered to its citizens. In this way, the people are immersed in these spaces, which are aware of their presence (context-sensitive) and adapt to their needs. The context analysis in a smart city allows making available services and information, to support ubiquitously the activities of the individuals. This study aims to analyze the emerging and ubiquitous capabilities of an Autonomic Reflective Middleware. The Middleware is based on intelligent agents that can be adapted to the existing dynamism in a city for, ubiquitously, responding to the requirements of citizens. It uses emerging ontologies that allow, not only the adaptation to the context of the moment and in real-time but also responds to unforeseen situations. © 2020, Springer-Verlag GmbH Austria, part of Springer Nature.
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    Specification of a Managing Agent of Emergent Serious Games for a Smart Classroom
    (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2020-01-01) Aguilar, J.; Altamiranda, J.; Diaz, F.; Aguilar, J.; Altamiranda, J.; Diaz, F.; Universidad EAFIT. Departamento de Ingeniería de Sistemas; I+D+I en Tecnologías de la Información y las Comunicaciones
    This article presents the specification of a Managing Agent of emergent serious games for a smart classroom. The Managing Agent of Emergent Serious Games is a manager of emergent serious games, which seeks to adapt emergent serious games to the subject that is developed in the smart classroom, with the aim of motivating the acquisition of knowledge and skills in students during their learning processes. The introduction of emergent serious games in a smart classroom allows incorporating a new type of teaching resource in the learning dynamic, which allows enriching with new strategies the learning process. © 2003-2012 IEEE.