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Author G.A. Rubio; Wilton Agila pdf  openurl
  Title (down) 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  
  Keywords  
  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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  Notes Approved no  
  Call Number gtsi @ user @ Serial 110  
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Author Nayeth I. Solorzano Alcivar, Robert Loor, Stalyn Gonzabay Yagual, & Boris X. Vintimilla pdf  openurl
  Title (down) 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  
  Keywords  
  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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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 131  
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Author Ángel Morera, Ángel Sánchez, A. Belén Moreno, Angel D. Sappa, & José F. Vélez pdf  isbn
openurl 
  Title (down) SSD vs. YOLO for Detection of Outdoor Urban Advertising Panels under Multiple Variabilities. Type Journal Article
  Year 2020 Publication Abbreviated Journal In Sensors  
  Volume Vol. 2020-August Issue 16 Pages pp. 1-23  
  Keywords object detection; urban outdoor panels; one-stage detectors; Single Shot MultiBox Detector (SSD); You Only Look Once (YOLO); detection metrics; object and scene imaging variabilities  
  Abstract This work compares Single Shot MultiBox Detector (SSD) and You Only Look Once (YOLO)

deep neural networks for the outdoor advertisement panel detection problem by handling multiple

and combined variabilities in the scenes. Publicity panel detection in images o ers important

advantages both in the real world as well as in the virtual one. For example, applications like Google

Street View can be used for Internet publicity and when detecting these ads panels in images, it could

be possible to replace the publicity appearing inside the panels by another from a funding company.

In our experiments, both SSD and YOLO detectors have produced acceptable results under variable

sizes of panels, illumination conditions, viewing perspectives, partial occlusion of panels, complex

background and multiple panels in scenes. Due to the diculty of finding annotated images for the

considered problem, we created our own dataset for conducting the experiments. The major strength

of the SSD model was the almost elimination of False Positive (FP) cases, situation that is preferable

when the publicity contained inside the panel is analyzed after detecting them. On the other side,

YOLO produced better panel localization results detecting a higher number of True Positive (TP)

panels with a higher accuracy. Finally, a comparison of the two analyzed object detection models

with di erent types of semantic segmentation networks and using the same evaluation metrics is

also included.
 
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  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 14248220 Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number cidis @ cidis @ Serial 133  
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Author Armin Mehri, Parichehr Behjati, Dario Carpio, and Angel D. Sappa pdf  openurl
  Title (down) SRFormer: Efficient Yet Powerful Transformer Network For Single Image Super Resolution Type Journal Article
  Year 2023 Publication IEEE access Abbreviated Journal  
  Volume Vol. 11 Issue Pages 121457 - 121469  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 21693536 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number cidis @ cidis @ Serial 227  
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Author Santos V.; Angel D. Sappa.; Oliveira M. & de la Escalera A. pdf  openurl
  Title (down) 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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  Corporate Author Thesis  
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  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
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  Notes Approved no  
  Call Number gtsi @ user @ Serial 119  
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Author Victor Santos; Angel D. Sappa; Miguel Oliveira pdf  openurl
  Title (down) Special Issue on Autonomous Driving an Driver Assistance Systems Type Journal Article
  Year 2017 Publication In Robotics and Autonomous Systems Journal Abbreviated Journal  
  Volume Vol. 91 Issue Pages pp. 208-209  
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  Abstract  
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  Corporate Author Thesis  
  Publisher Place of Publication Editor  
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  Series Volume Series Issue Edition  
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  Notes Approved no  
  Call Number gtsi @ user @ Serial 65  
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Author Luis Jacome-Galarza, Monica Villavicencio-Cabezas, Miguel Realpe-Robalino, Jose Benavides-Maldonado pdf  openurl
  Title (down) Software Engineering and Distributed Computing in image processing intelligent systems: a systematic literature review. Type Conference Article
  Year 2021 Publication 19th LACCEI International Multi-Conference for Engineering, Education, and Technology Abbreviated Journal  
  Volume Issue Pages  
  Keywords processing, software engineering, deep learning, intelligent vision systems, cloud computing.  
  Abstract Deep learning is experiencing an upward technology trend that is revolutionizing intelligent systems in several domains, such as image and speech recognition, machine translation, social network filtering, and the like. By reviewing a total of 80 studies reported from 2016 to 2020, the present article evaluates the application of software engineering to the field

of intelligent image processing systems, it also offers insights about aspects related to distributed computing for this type of systems. Results indicate that several topics of software engineering are mostly applied when academics are involved in developing projects associated to this kind of intelligent systems. The findings provide evidences that Apache Spark is the most

utilized distributed computing framework for image processing. In addition, Tensorflow is a popular framework used to build convolutional neural networks, which are the prevailing deep learning algorithms used in intelligent image processing systems.

Also, among big cloud providers, Amazon Web Services is the preferred computing platform across the industry sectors, followed by Google cloud.
 
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 154  
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Author Viñán-Ludeña M.S., De Campos L.M., Roberto Jacome Galarza, & Sinche Freire, J. url  openurl
  Title (down) Social media influence: a comprehensive review in general and in tourism domain Type Journal Article
  Year 2020 Publication Smart Innovation, Systems and Technologies. Abbreviated Journal  
  Volume 171, 2020 Issue Pages 25-35  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 190  
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Author Viñán-Ludeña, M.S., Roberto Jacome Galarza, Montoya, L.R., Leon, A.V., & Ramírez, C.C. url  openurl
  Title (down) Smart university: an architecture proposal for information management using open data for research projects. Type Journal Article
  Year 2020 Publication Advances in Intelligent Systems and Computing Abbreviated Journal  
  Volume 1137 AISC, 2020 Issue Pages 172-178  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 188  
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Author Miguel Realpe; Boris X. Vintimilla; Ljubo Vlacic pdf  url
openurl 
  Title (down) Sensor Fault Detection and Diagnosis for autonomous vehicles Type Conference Article
  Year 2015 Publication 2nd International Conference on Mechatronics, Automation and Manufacturing (ICMAM 2015), International Conference on, Singapur, 2015 Abbreviated Journal  
  Volume 30 Issue MATEC Web of Conferences Pages 1-6  
  Keywords  
  Abstract In recent years testing autonomous vehicles on public roads has become a reality. However, before having autonomous vehicles completely accepted on the roads, they have to demonstrate safe operation and reliable interaction with other traffic participants. Furthermore, in real situations and long term operation, there is always the possibility that diverse components may fail. This paper deals with possible sensor faults by defining a federated sensor data fusion architecture. The proposed architecture is designed to detect obstacles in an autonomous vehicle’s environment while detecting a faulty sensor using SVM models for fault detection and diagnosis. Experimental results using sensor information from the KITTI dataset confirm the feasibility of the proposed architecture to detect soft and hard faults from a particular sensor.  
  Address  
  Corporate Author Thesis  
  Publisher EDP Sciences Place of Publication Editor  
  Language English Summary Language English Original Title  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number cidis @ cidis @ Serial 42  
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