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Author |
Nayeth I. Solorzano Alcivar, Robert Loor, Stalyn Gonzabay Yagual, & Boris X. Vintimilla |
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Title |
Statistical Representations of a Dashboard to Monitor Educational Videogames in Natural Language |
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Conference Article |
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Year |
2020 |
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ETLTC – ACM Chapter: International Conference on Educational Technology, Language and Technical Communication; Fukushima, Japan, 27-31 Enero 2020 |
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77 |
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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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no |
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cidis @ cidis @ |
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131 |
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Author |
Miguel Realpe; Boris X. Vintimilla; Ljubo Vlacic |
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Title |
Sensor Fault Detection and Diagnosis for autonomous vehicles |
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Conference Article |
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Year |
2015 |
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2nd International Conference on Mechatronics, Automation and Manufacturing (ICMAM 2015), International Conference on, Singapur, 2015 |
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30 |
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MATEC Web of Conferences |
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1-6 |
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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. |
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EDP Sciences |
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English |
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English |
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cidis @ cidis @ |
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42 |
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Author |
Ma. Paz Velarde; Erika Perugachi; Dennis G. Romero; Ángel D. Sappa; Boris X. Vintimilla |
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Title |
Análisis del movimiento de las extremidades superiores aplicado a la rehabilitación física de una persona usando técnicas de visión artificial. |
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Journal Article |
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2015 |
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Revista Tecnológica ESPOL-RTE |
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Vol. 28 |
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pp. 1-7 |
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Rehabilitation; RGB-D Sensor; Computer Vision; Upper limb |
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Comúnmente durante la rehabilitación física, el diagnóstico dado por el especialista se basa en observaciones cualitativas que sugieren, en algunos casos, conclusiones subjetivas. El presente trabajo propone un enfoque cuantitativo, orientado a servir de ayuda a fisioterapeutas, a través de una herramienta interactiva y de bajo costo que permite medir los movimientos de miembros superiores. Estos movimientos son capturados por un sensor RGB-D y procesados mediante la metodología propuesta, dando como resultado una eficiente representación de movimientos, permitiendo la evaluación cuantitativa de movimientos de los miembros superiores. |
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ESPOL |
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English |
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cidis @ cidis @ |
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39 |
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Author |
Angel D. Sappa; Juan A. Carvajal; Cristhian A. Aguilera; Miguel Oliveira; Dennis G. Romero; Boris X. Vintimilla |
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Title |
Wavelet-Based Visible and Infrared Image Fusion: A Comparative Study |
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Journal Article |
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Year |
2016 |
Publication |
Sensors Journal |
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Vol. 16 |
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pp. 1-15 |
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Keywords |
image fusion; fusion evaluation metrics; visible and infrared imaging; discrete wavelet transform |
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This paper evaluates different wavelet-based cross-spectral image fusion strategies adopted to merge visible and infrared images. The objective is to find the best setup independently of the evaluation metric used to measure the performance. Quantitative performance results are obtained with state of the art approaches together with adaptations proposed in the current work. The options evaluated in the current work result from the combination of different setups in the wavelet image decomposition stage together with different fusion strategies for the final merging stage that generates the resulting representation. Most of the approaches evaluate results according to the application for which they are intended for. Sometimes a human observer is selected to judge the quality of the obtained results. In the current work, quantitative values are considered in order to find correlations between setups and performance of obtained results; these correlations can be used to define a criteria for selecting the best fusion strategy for a given pair of cross-spectral images. The whole procedure is evaluated with a large set of correctly registered visible and infrared image pairs, including both Near InfraRed (NIR) and LongWave InfraRed (LWIR). |
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cidis @ cidis @ |
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47 |
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