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Ítem Adaptive LAMDA applied to identify and regulate a process with variable dead time(Institute of Electrical and Electronics Engineers Inc., 2020-01-01) Morales L.; Pozo D.; Aguilar J.; Rosales A.; Universidad EAFIT. Departamento de Ingeniería de Sistemas; I+D+I en Tecnologías de la Información y las ComunicacionesIn this paper, an adaptive intelligent controller based on the fuzzy algorithm called LAMDA (Learning Algorithm for Multivariable Data Analysis) is presented in order to identify and regulate a process with variable dead time. The original algorithm has been used for supervised and unsupervised learning, whose main field of application is the identification of functional states of the systems. In this work a modification of LAMDA has been implemented which is capable of online learning using hybrid techniques. The proposal consists of two stages: training stage to learn about the unknown plant in order to establish initial parameters to the controller, and a second phase, called application, in which the control strategy is updated using online learning. The proposed method is tested in the control objective of regulation of a process with variable dead time, to analyze the viability of its utilization in these types of systems in which their dynamics are variable and unknown. © 2020 IEEE.Ítem Colombia's cyberinfrastructure for biodiversity: Building data infrastructure in emerging countries to foster socioeconomic growth(Wiley Open Access, 2019-12-22) De Vega, Jose J.; Davey, Robert P.; Duitama, Jorge; Escobar, Dairo; Cristancho, Marco A.; Etherington, Graham J.; Minotto, Alice; Pineda J.D.; Correa Alvarez J; Camargo, Anyela V.; Haerty, Wilfried; Mallarino, Juan P.; Barreto, Emiliano; Fuentes, Narcis; Di, Federica; Universidad EAFIT. Departamento de Ciencias; Biodiversidad, Evolución y ConservaciónScience and innovation are not a luxury but a prerequisite for social and economic development (Annan, 2003).Ítem An Entropy-Based Graph Construction Method for Representing and Clustering Biological Data(SPRINGER, 2019-10-01) Ariza-Jiménez L.; Pinel N.; Villa L.F.; Quintero O.L.; Universidad EAFIT. Departamento de Ciencias; Biodiversidad, Evolución y ConservaciónUnsupervised learning methods are commonly used to perform the non-trivial task of uncovering structure in biological data. However, conventional approaches rely on methods that make assumptions about data distribution and reduce the dimensionality of the input data. Here we propose the incorporation of entropy related measures into the process of constructing graph-based representations for biological datasets in order to uncover their inner structure. Experimental results demonstrated the potential of the proposed entropy-based graph data representation to cope with biological applications related to unsupervised learning problems, such as metagenomic binning and neuronal spike sorting, in which it is necessary to organize data into unknown and meaningful groups. © 2020, Springer Nature Switzerland AG.Ítem Geoportal for the management of natural threat and risk(IEEE, 2014-01-01) Castro Benavides, Lina Maria; Vila Ortega, Jose Joaquin; Rivera Valencia, Diana Marcela; Acosta Correa, Beatriz Susana; Universidad EAFIT. Departamento de Ingeniería de Sistemas; I+D+I en Tecnologías de la Información y las ComunicacionesThe Natural Threat and Risk Geoportal of Quindío is a technological platform that allows the publication of geographic information by official sources and scientists, search information, download maps and data by users, exchange and download of geographic information about natural hazard in the region. This project was conceived by the international initiative of the Latin American Community of Spatial Data Infrastructure - LatinIDE and also includes trends such as Web 2.0 philosophy or 'web of people'. © 2014 IEEE.Ítem IMP: a pipeline for reproducible reference-independent integrated metagenomic and metatranscriptomic analyses(BioMed Central Ltd., 2016-12-16) Narayanasamy, S.; Jarosz, Y.; Muller, E.E.L.; Heintz-Buschart, A.; Herold, M.; Kaysen, A.; Laczny, C.C.; Pinel, N.; May, P.; Wilmes, P.; Universidad EAFIT. Departamento de Ciencias; Biodiversidad, Evolución y ConservaciónExisting workflows for the analysis of multi-omic microbiome datasets are lab-specific and often result in sub-optimal data usage. Here we present IMP, a reproducible and modular pipeline for the integrated and reference-independent analysis of coupled metagenomic and metatranscriptomic data. IMP incorporates robust read preprocessing, iterative co-assembly, analyses of microbial community structure and function, automated binning, as well as genomic signature-based visualizations. The IMP-based data integration strategy enhances data usage, output volume, and output quality as demonstrated using relevant use-cases. Finally, IMP is encapsulated within a user-friendly implementation using Python and Docker. IMP is available at http://r3lab.uni.lu/web/imp/ (MIT license).Ítem Improving the business processes management from the knowledge management(Association for Computing Machinery, 2016-01-01) Marta S. Tabares; Giraldo, Liliana; Aguilar, Luis; Universidad EAFIT. Departamento de Ingeniería de Sistemas; I+D+I en Tecnologías de la Información y las ComunicacionesThis paper proposes a model that integrates the knowledge management to the business processes management in order to improve the process performance. The proposal defines the knowledge management flow as an element that interacts with part workflows and provides rules and actions in the BPMN elements in order to improve the BPM. To achieve the aim, first, a survey was made in forty Colombian' companies in order to identify the state of the practice about business process management, knowledge management and their use through the workflows; then, different elements were identified and characterized in order to achieve the integration model proposed. This was experimented in forty business workflows of the companies analyzed. A use case shows how the interactions among model elements are, and how these can improve the process performance. This experience allowed to measuring the effect that the integration had in the business process management by means of a new metric that involve the knowledge management in the workflow. Finally, it was possible conclude that the knowledge management must be part to the BPM impacting directly the workflow, in order to improve the result offered to the organizational actors and customers.Ítem An innovation model in curriculum design for teaching engineering at universidad EAFIT(Institute of Electrical and Electronics Engineers Inc., 2015-01-01) Zea, C.M.; Rodriguez, A.; Bueno, N.A.; Universidad EAFIT. Departamento de Ingeniería de Sistemas; I+D+I en Tecnologías de la Información y las ComunicacionesConstant changes in technology pose continuous challenges for higher education institutions that are training the engineers of the future. These changes are making it necessary to adapt the curriculum in order to develop the skills needed by the XXI century engineer. Moreover, instead of thinking in a large curriculum reform at a specific moment, it is necessary to define curriculum management processes that include change as a natural component of the process. In addition to these global trends, each institution has a particular context and thus, the analysis in each institution has unique characteristics, a common methodological approach, and a reference model that can be built as long as it is flexible enough to include that context. This paper describes a model developed for curriculum management inside the School of Engineering at Universidad EAFIT - Colombia. This model includes the institutional context and is based on a process approach defined by the Business Process Management (BPM) methodology. The model uses the Burlton Hexagon as a theoretical framework to identify organizational structure, strategies, policies, infrastructure, technology tools and human capital. It is also a mechanism for specifying curricular macro processes including the global and institutional context. The proposed model is based on three pillars: (a) scientific research in education, which promotes the use of the scientific method as a strategy to ensure an approach to problems based on evidence which allows the construction of educational innovation projects, (b) education engineering focused on engineering education, which transforms the learning by developing basic, professional, and transversal skills as well as those specific for an engineer of the XXI century, and (c) interactive educational communities, both face to face and virtual, as spaces for knowledge management that support collaborative working and experience-sharing, managed by its members working together promoting initiatives to develop educational innovation projects focused on specific topics, that answer questions related to teaching and learning needs. The formulation and development of educational innovation projects are the responses to different needs identified on specific courses that are transformed into research questions. These projects aim to renew the curriculum so that it dynamically evolves based on classroom experiences. Thus, the curriculum renewal is based on critical thinking about the problems found in engineering education. The use of the scientific method and the collaborative approach enables drawing solid conclusions based on the experimental results. The model proposes the formulation and development of innovative educational projects in which scientific research applied in education aims to transform teaching, academic and administrative practices. As consequence, curricular innovations that integrate learning objects and educational, methodological and assessment strategies, are developed by an interactive learning community composed by teachers. Finally, the results obtained by applying the model in some courses in the School of Engineering of Universidad EAFIT are presented. These results include reducing the drop-out rate of students, redefining admission and graduation profiles, and micro-curricular redesign based on competences using projects, among others. © 2014 IEEE.Ítem Pensamientos poco artificiales(Universidad EAFIT, 2024-08-23) Querubín, Valeria; Universidad EAFITÍtem Poster: Collaborative data exploration using two navigation strategies(IEEE COMPUTER SOC, 2009-01-01) Gomez, Omar; Trefftz, Helmuth; Boulanger, Pierre; Bischof, Walter F.; Universidad EAFIT. Departamento de Ingeniería de Sistemas; I+D+I en Tecnologías de la Información y las ComunicacionesVirtual collaborative systems are vital tools for accessing and sharing scientific data visualizations. This paper shows how two different modes of collaboration can affect user performance in a specific exploration task. Experiments with groups of users that are working in pairs showed that the lack of mobility can affect the ability to achieve specific exploration goals in a virtual environment. Our analysis reveals that the task was completed more efficiently when users were allowed to move freely and independently instead of working with limited mobility. In these systems, users adapted their own abilities and minimized theeffect of mobility restrictions. ©2009 IEEE.Ítem Towards an improved ASUM-DM process methodology for cross-disciplinary multi-organization big data & analytics projects(Springer Verlag, 2018-01-01) Angée, S.; Lozano-Argel, S.I.; Montoya-Munera, E.N.; Ospina-Arango, J.-D.; Tabares-Betancur, M.S.; Universidad EAFIT. Departamento de Ingeniería de Sistemas; I+D+I en Tecnologías de la Información y las ComunicacionesThe development of big data & analytics projects with the participation of several corporate divisions and research groups within and among organizations is a non-trivial problem and requires well-defined roles and processes. Since there is no accepted standard for the implementation of big data & analytics projects, project managers have to either adapt an existing data mining process methodology or create a new one. This work presents a use case for a big data & analytics project for the banking sector. The authors found out that an adaptation of ASUM-DM, a refined CRISP-DM, with the addition of big data analysis, application prototyping, and prototype evaluation, plus a strong project management work with an emphasis in communications proved the best solution to develop a cross-disciplinary, multi-organization, geographically-distributed big data & analytics project. © 2018, Springer Nature Switzerland AG.