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G.A. Rubio; Wilton Agila |
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Title |
Sustainable Energy: A Strategic View of Fuel Cells |
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Conference Article |
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2019 |
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8th International Conference on Renewable Energy Research and Applications (ICRERA 2019); Brasov, Rumania |
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239-243 |
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Based on the model of the proton exchange fuel cell in a strategic context,
this document develops the issue of energy as one of the pillars to achieve the
sustainability of our planet, considering the future scenarios up to the year 2060 of the
situation energy, hydrogen as a strategic vector and the contribution of the fuel cell in
solving the serious problems of environmental pollution and economic inequity that
humanity faces; for its application in the energy generation, telecommunications and
vehicle manufacturing industries. |
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gtsi @ user @ |
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110 |
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Author |
Carlos Monsalve; Alain April; Alain Abran |
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Title |
Requirements Elicitation Using BPM Notations: Focusing on the Strategic Level Representation |
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Conference Article |
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2011 |
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10th WSEAS international conference on Applied computer and applied computational science |
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235-241 |
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Business process modeling, levels of abstraction, requirements elicitation, case study, action research |
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Business process models (BPM) can be useful for requirements elicitation, among other uses. Since the active participation of all stakeholders is a key factor for successful requirements engineering, it is important that BPM be shared by all stakeholders. Unfortunately, organizations may end up with inconsistent BPM not covering all stakeholders’ needs and constraints. The use of multiple levels of abstraction (MLA), such as at the strategic, tactical and operational levels, is often used in various process-oriented initiatives to facilitate the consolidation of various stakeholders’ needs and constraints. This article surveys the use of MLA in recent BPM research publications and reports on a BPM action-research case study conducted in a Canadian organization, with the aim of exploring the usefulness of the strategic level. |
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CIDIS – Electrical and Computer Engineering Department Escuela Superior Politécnica del Litoral Km. 30.5 vía Perimetral |
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1100 rue Notre-Dame Ouest, Montréal, Québec H3C 1K3 CANADA |
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English |
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English |
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cidis @ cidis @ |
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16 |
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Author |
Carlos Monsalve; Alain April; Alain Abran |
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Title |
BPM and requirements elicitation at multiple levels of abstraction: A review |
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Conference Article |
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2011 |
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IADIS International Conference on Information Systems 2011 |
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237-242 |
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Business process modeling, levels of abstraction, requirements elicitation, requirements modeling, review |
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Business process models can be useful for requirements elicitation, among other things. Software development depends on the quality of the requirements elicitation activities, and so adequately modeling business processes (BPs) is critical. A key factor in achieving this is the active participation of all the stakeholders in the development of a shared vision of BPs.
Unfortunately, organizations often find themselves left with inconsistent BPs that do not cover all the stakeholders’ needs
and constraints. However, consolidation of the various stakeholder requirements may be facilitated through the use of multiple levels of abstraction (MLA). This article contributes to the research into MLA use in business process modeling (BPM) for software requirements by reviewing the theoretical foundations of MLA and their use in various BP-oriented approaches. |
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CIDIS-FIEC, Escuela Superior Politécnica del Litoral (ESPOL) Km. 30.5 vía Perimetral, |
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cidis @ cidis @ |
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15 |
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Author |
Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla |
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Title |
Image patch similarity through a meta-learning metric based approach |
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Conference Article |
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2019 |
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15th International Conference on Signal Image Technology & Internet based Systems (SITIS 2019); Sorrento, Italia |
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511-517 |
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Comparing images regions are one of the core methods used on computer vision for tasks like image classification, scene understanding, object detection and recognition. Hence, this paper proposes a novel approach to determine similarity of image regions (patches), in order to obtain the best representation of image patches. This problem has been studied by many researchers presenting different approaches, however, the ability to find the better criteria to measure the similarity on image regions are still a challenge. The present work tackles this problem using a few-shot metric based meta-learning framework able to compare image regions and determining a similarity measure to decide if there is similarity between the compared patches. Our model is training end-to-end from scratch. Experimental results
have shown that the proposed approach effectively estimates the similarity of the patches and, comparing it with the state of the art approaches, shows better results. |
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gtsi @ user @ |
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115 |
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