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Author (down) Wilton Agila; Gomer Rubio; Francisco Vidal; B. Lima
Title Real time Qualitative Model for estimate Water content in PEM Fuel Cell Type Conference Article
Year 2019 Publication 8th International Conference on Renewable Energy Research and Applications (ICRERA 2019); Brasov, Rumania Abbreviated Journal
Volume Issue Pages 455-459
Keywords
Abstract To maintain optimum performance of the electrical

response of a fuel cell, a real time identification of the

malfunction situations is required. Critical fuel cell states depend,

among others, on the variable demand of electric load and are

directly related to the membrane hydration level. The real time

perception of relevant states in the PEM fuel cell states space, is

still a challenge for the PEM fuel cell control systems. Current

work presents the design and implementation of a methodology

based upon fuzzy decision techniques that allows real time

characterization of the dehydration and flooding states of a PEM

fuel cell. Real time state estimation is accomplished through a

perturbation-perception process on the PEM fuel cell and further

on voltage oscillation analysis. The real time implementation of

the perturbation-perception algorithm to detect PEM fuel cell

critical states is a novelty and a step forwards the control of the

PEM fuel cell to reach and maintain optimal performance.
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Notes Approved no
Call Number gtsi @ user @ Serial 109
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Author (down) 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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Notes Approved no
Call Number gtsi @ user @ Serial 118
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Author (down) Stalin Francis Quinde
Title Un nuevo modelo BM3D-RNCA para mejorar la estimación de la imagen libre de ruido producida por el método BM3D. (Ph.D. Angel Sappa, Director.). M.Sc. thesis Type Book Chapter
Year 2019 Publication Ediciones FIEC-ESPOL Abbreviated Journal
Volume Issue Pages
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Corporate Author Ph.D. Angel Sappa, Director. Thesis Master's thesis
Publisher Place of Publication Editor
Language Español Summary Language Original Title
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Notes Approved no
Call Number gtsi @ user @ Serial 117
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Author (down) Shendry Rosero Vásquez
Title Reconocimiento facial: técnicas tradicionales y técnicas de aprendizaje profundo, un análisis. (Ph.D. Angel Sappa, Director & Ph.D. Boris Vintimilla, Codirector.). M.Sc. thesis Type Book Chapter
Year 2019 Publication Ediciones FIEC-ESPOL Abbreviated Journal
Volume Issue Pages
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Address
Corporate Author Ph.D. Angel Sappa, Director de tesis & Ph.D. Boris Vintimilla, Codirector Thesis Master's thesis
Publisher Place of Publication Editor
Language Español Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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Area Expedition Conference
Notes Approved yes
Call Number gtsi @ user @ Serial 114
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Author (down) Sebastián Fuenzalida; Keyla Toapanta; Jonathan S. Paillacho Corredores; Dennys Paillacho
Title Forward and Inverse Kinematics of a Humanoid Robot Head for Social Human Robot-Interaction Type Conference Article
Year 2019 Publication IEEE ETCM 2019 Fourth Ecuador Technical Chapters Meeting; Guayaquil, Ecuador Abbreviated Journal
Volume Issue Pages
Keywords
Abstract This paper presents an analysis of forward and inverse kinematics for a humanoid robotic head. The robotic head is used for the study of social human-robot interaction, such as a support tool to maintain the attention of patients with Autism Spectrum Disorder. The design of a parallel robot that emulates human head movements through a closed structure is presented. The position and orientation in this space is controlled by three servomotors. For this, the solutions made for the kinematic problem are encompassed by a geometric analysis of a mobile base. This article describes a non-systematic method,

called the geometric method, and compares some of the most popular existing methods considering reliability and computational cost. The geometric method avoids the use of changing reference systems, and instead uses geometric

relationships to directly obtain the position based on joint variables; and the other way around. Therefore, it converges in a few iterations and has a low computational cost.
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Notes Approved no
Call Number gtsi @ user @ Serial 113
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Author (down) 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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Notes Approved no
Call Number gtsi @ user @ Serial 119
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Author (down) Roberto Jacome Galarza; Miguel-Andrés Realpe-Robalino; Chamba-Eras LuisAntonio; Viñán-Ludeña MarlonSantiago and Sinche-Freire Javier-Francisco
Title Computer vision for image understanding. A comprehensive review Type Conference Article
Year 2019 Publication International Conference on Advances in Emerging Trends and Technologies (ICAETT 2019); Quito, Ecuador Abbreviated Journal
Volume Issue Pages 248-259
Keywords
Abstract Computer Vision has its own Turing test: Can a machine describe the contents of an image or a video in the way a human being would do? In this paper, the progress of Deep Learning for image recognition is analyzed in order to know the answer to this question. In recent years, Deep Learning has increased considerably the precision rate of many tasks related to computer vision. Many datasets of labeled images are now available online, which leads to pre-trained models for many computer vision applications. In this work, we gather information of the latest techniques to perform image understanding and description. As a conclusion we obtained that the combination of Natural Language Processing (using Recurrent Neural Networks and Long Short-Term Memory) plus Image Understanding (using Convolutional Neural Networks) could bring new types of powerful and useful applications in which the computer will be able to answer questions about the content of images and videos. In order to build datasets of labeled images, we need a lot of work and most of the datasets are built using crowd work. These new applications have the potential to increase the human machine interaction to new levels of usability and user’s satisfaction.
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Notes Approved no
Call Number gtsi @ user @ Serial 97
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Author (down) 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
Keywords
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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Notes Approved no
Call Number gtsi @ user @ Serial 112
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Author (down) Rafael E. Rivadeneira; Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla.
Title Thermal Image SuperResolution through Deep Convolutional Neural Network. Type Conference Article
Year 2019 Publication 16th International Conference on Image Analysis and Recognition (ICIAR 2019); Waterloo, Canadá Abbreviated Journal
Volume Issue Pages 417-426
Keywords
Abstract Due to the lack of thermal image datasets, a new dataset has been acquired for proposed a superesolution approach using a Deep Convolution Neural Network schema. In order to achieve this image enhancement process a new thermal images dataset is used. Di?erent experiments have been carried out, ?rstly, the proposed architecture has been trained using only images of the visible spectrum, and later it has been trained with images of the thermal spectrum, the results showed that with the network trained with thermal images, better results are obtained in the process of enhancing the images, maintaining the image details and perspective. The thermal dataset is available at http://www.cidis.espol.edu.ec/es/dataset
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Notes Approved no
Call Number gtsi @ user @ Serial 103
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Author (down) Patricia L. Suarez; Angel D. Sappa; Boris X. Vintimilla; Riad I. Hammoud
Title Image Vegetation Index through a Cycle Generative Adversarial Network Type Conference Article
Year 2019 Publication Conference on Computer Vision and Pattern Recognition Workshops (CVPR 2019); Long Beach, California, United States Abbreviated Journal
Volume Issue Pages 1014-1021
Keywords
Abstract This paper proposes a novel approach to estimate the

Normalized Difference Vegetation Index (NDVI) just from

an RGB image. The NDVI values are obtained by using

images from the visible spectral band together with a synthetic near infrared image obtained by a cycled GAN. The

cycled GAN network is able to obtain a NIR image from

a given gray scale image. It is trained by using unpaired

set of gray scale and NIR images by using a U-net architecture and a multiple loss function (gray scale images are

obtained from the provided RGB images). Then, the NIR

image estimated with the proposed cycle generative adversarial network is used to compute the NDVI index. Experimental results are provided showing the validity of the proposed approach. Additionally, comparisons with previous

approaches are also provided.
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Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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Notes Approved no
Call Number gtsi @ user @ Serial 106
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