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Author | G.A. Rubio; Wilton Agila | ||||
Title | Sustainable Energy: A Strategic View of Fuel Cells | Type | Conference Article | ||
Year | 2019 | Publication | 8th International Conference on Renewable Energy Research and Applications (ICRERA 2019); Brasov, Rumania | Abbreviated Journal | |
Volume | Issue | Pages | 239-243 | ||
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Abstract | 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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Call Number | gtsi @ user @ | Serial | 110 | ||
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Author | G.A. Rubio; Wilton Agila | ||||
Title | Transients analysis in Proton Exchange Membrane Fuel Cells: A critical review | Type | Conference Article | ||
Year | 2019 | Publication | 8th International Conference on Renewable Energy Research and Applications (ICRERA 2019); Brasov, Rumania | Abbreviated Journal | |
Volume | Issue | Pages | 249-252 | ||
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Abstract | When a proton exchange fuel cell operates it produces in addition to electrical energy, heat and water as sub products, which impact on the performance of the cell. This paper analyzes the issue of transients and proposes a model that describes the dynamic operation of the fuel cell. The model considers the transients produced by electrochemical reactions, by flow water and by heat transfer. Two-phase flow transients result in increased the parasitic power losses and thermal transients may result in flooding or dryout of the GDL and membrane, understanding transient behavior is critical for reliable and predictable performance from the cell. |
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Call Number | gtsi @ user @ | Serial | 111 | ||
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Author | Raul A. Mira; Patricia L. Suarez; Rafael E. Rivadeneira; Angel D. Sappa | ||||
Title | PETRA: A Crowdsourcing-Based Platform for Rocks Data Collection and Characterization | Type | Conference Article | ||
Year | 2019 | Publication | IEEE ETCM 2019 Fourth Ecuador Technical Chapters Meeting; Guayaquil, Ecuador | Abbreviated Journal | |
Volume | Issue | Pages | 1-6 | ||
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Abstract | This paper presents details of a distributed platform intended for data acquisition, evaluation, storage and visualization, which is fully implemented under the crowdsourcing paradigm. The proposed platform is the result from collaboration between computer science and petrology researchers and it is intended for academic purposes. The platform is designed within a MTV (Model, Template and View) architecture and also designed for a collaborative data store and managing of rocks from multiple readers and writers, taking advantage of ubiquity of web applications, and neutrality of researchers from different communities to validate the data. The platform is being used and validated by students and academics from our university; in the near future it will be open to other users interested on this topic. |
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Call Number | gtsi @ user @ | Serial | 112 | ||
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Author | Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla | ||||
Title | Image patch similarity through a meta-learning metric based approach | Type | Conference Article | ||
Year | 2019 | Publication | 15th International Conference on Signal Image Technology & Internet based Systems (SITIS 2019); Sorrento, Italia | Abbreviated Journal | |
Volume | Issue | Pages | 511-517 | ||
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Abstract | 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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Call Number | gtsi @ user @ | Serial | 115 | ||
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Author | Miguel Realpe; Jonathan S. Paillacho Corredores; Joe Saverio & Allan Alarcon | ||||
Title | Open Source system for identification of corn leaf chlorophyll contents based on multispectral images | Type | Conference Article | ||
Year | 2019 | Publication | International Conference on Applied Technologies (ICAT 2019); Quito, Ecuador | Abbreviated Journal | |
Volume | Issue | Pages | 572-581 | ||
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Abstract | It is important for farmers to know the level of chlorophyll in plants since this depends on the treatment they should give to their crops. There are two common classic methods to get chlorophyll values: from laboratory analysis and electronic devices. Both methods obtain the chlorophyll level of one sample at a time, although they can be destructive. The objective of this research is to develop a system that allows obtaining the chlorophyll level of plants using images. Python programming language and different libraries of that language were used to develop the solution. It was decided to implement an image labeling module, a simple linear regression and a prediction module. The first module was used to create a database that links the values of the images with those of chlorophyll, which was then used to obtain linear regression in order to determine the relationship between these variables. Finally, the linear regression was used in the prediction system to obtain chlorophyll values from the images. The linear regression was trained with 92 images, obtaining a root-mean-square error of 7.27 SPAD units. While the testing was perform using 10 values getting a maximum error of 15.5%. It is concluded that the system is appropriate for chlorophyll contents identification of corn leaves in field tests. However, it can also be adapted for other measurement and crops. The system can be downloaded at github.com/JoeSvr95/NDVI-Checking [1]. |
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Call Number | gtsi @ user @ | Serial | 116 | ||
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Author | W. Agila; Gomer Rubio; L. Miranda; D. Sanaguano | ||||
Title | Open Control Architecture for the Characterization and Control of the PEM Fuel Cell | Type | Conference Article | ||
Year | 2019 | Publication | IEEE ETCM 2019 Fourth Ecuador Technical Chapters Meeting; Guayaquil, Ecuador | Abbreviated Journal | |
Volume | Issue | Pages | 1-5 | ||
Keywords | PEM fuel cell, Experimental System, Control Engineering. | ||||
Abstract | Proton exchange membrane (PEM) fuel cells, are an efficient and clean source of electrical energy. The analysis of its operation requires experimental work, which allows measuring, modeling and optimizing PEM fuel cells electrical behavior under different operating conditions. Therefore, having an experimentation platform that allows to easily carry out its study and control is essential. This research presents the design and development of an open instrumental system that allows measuring, controlling and determining the operating parameters of a PEM fuel cell. As results, the polarization curves, voltage-current, obtained by the system itself in different experimental conditions are shown. These curves are a very useful tool to evaluate the electrical behavior of the PEM battery. | ||||
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Call Number | gtsi @ user @ | Serial | 118 | ||
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Author | Santos V.; Angel D. Sappa.; Oliveira M. & de la Escalera A. | ||||
Title | Special Issue on Autonomous Driving and Driver Assistance Systems | Type | Journal Article | ||
Year | 2019 | Publication | In Robotics and Autonomous Systems | Abbreviated Journal | |
Volume | 121 | Issue | Pages | ||
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Call Number | gtsi @ user @ | Serial | 119 | ||
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Author | Suárez P. | ||||
Title | Processing and Representation of Multispectral Images Using Deep Learning Techniques | Type | Magazine Article | ||
Year | 2021 | Publication | In Electronic Letters on Computer Vision and Image Analysis | Abbreviated Journal | |
Volume | Vol. 19 | Issue | Issue 2 | Pages | pp. 5-8 |
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Corporate Author | Ph.D. Angel Sappa, Director & Ph.D. Boris Vintimilla, Codirector | Thesis | Master's thesis | ||
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Language | Español | Summary Language | Original Title | ||
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Notes | Approved | yes | |||
Call Number | cidis @ cidis @ | Serial | 122 | ||
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Author | Nayeth I. Solorzano Alcivar, Robert Loor, Stalyn Gonzabay Yagual, & Boris X. Vintimilla | ||||
Title | Statistical Representations of a Dashboard to Monitor Educational Videogames in Natural Language | Type | Conference Article | ||
Year | 2020 | Publication | ETLTC – ACM Chapter: International Conference on Educational Technology, Language and Technical Communication; Fukushima, Japan, 27-31 Enero 2020 | Abbreviated Journal | |
Volume | 77 | Issue | Pages | ||
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Abstract | This paper explains how Natural Language (NL) processing by computers, through smart programs as a way of Machine Learning (ML), can represent large sets of quantitative data as written statements. The study recognized the need to improve the implemented web platform using a dashboard in which we collected a set of extensive data to measure assessment factors of using children´s educational games. In this case, applying NL is a strategy to give assessments, build, and display more precise written statements to enhance the understanding of children´s gaming behavior. We propose the development of a new tool to assess the use of written explanations rather than a statistical representation of feedback information for the comprehension of parents and teachers with a lack of primary level knowledge in statistics. Applying fuzzy logic theory, we present verbatim explanations of children´s behavior playing educational videogames as NL interpretation instead of statistical representations. An educational series of digital game applications for mobile devices, identified as MIDI (Spanish acronym of “Interactive Didactic Multimedia for Children”) linked to a dashboard in the cloud, is evaluated using the dashboard metrics. MIDI games tested in local primary schools helps to evaluate the results of using the proposed tool. The guiding results allow analyzing the degrees of playability and usability factors obtained from the data produced when children play a MIDI game. The results obtained are presented in a comprehensive guiding evaluation report applying NL for parents and teachers. These guiding evaluations are useful to enhance children's learning understanding related to the school curricula applied to ludic digital games. |
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Call Number | cidis @ cidis @ | Serial | 131 | ||
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Author | Cristhian A. Aguilera, Cristhian Aguilera, Cristóbal A. Navarro, & Angel D. Sappa | ||||
Title | Fast CNN Stereo Depth Estimation through Embedded GPU Devices | Type | Journal Article | ||
Year | 2020 | Publication | Sensors 2020 | Abbreviated Journal | |
Volume | Vol. 2020-June | Issue | 11 | Pages | pp. 1-13 |
Keywords | stereo matching; deep learning; embedded GPU | ||||
Abstract | Current CNN-based stereo depth estimation models can barely run under real-time constraints on embedded graphic processing unit (GPU) devices. Moreover, state-of-the-art evaluations usually do not consider model optimization techniques, being that it is unknown what is the current potential on embedded GPU devices. In this work, we evaluate two state-of-the-art models on three different embedded GPU devices, with and without optimization methods, presenting performance results that illustrate the actual capabilities of embedded GPU devices for stereo depth estimation. More importantly, based on our evaluation, we propose the use of a U-Net like architecture for postprocessing the cost-volume, instead of a typical sequence of 3D convolutions, drastically augmenting the runtime speed of current models. In our experiments, we achieve real-time inference speed, in the range of 5–32 ms, for 1216 368 input stereo images on the Jetson TX2, Jetson Xavier, and Jetson Nano embedded devices. |
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Language | English | Summary Language | English | Original Title | |
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ISSN | 14248220 | ISBN | Medium | ||
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Notes | Approved | no | |||
Call Number | cidis @ cidis @ | Serial | 132 | ||
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