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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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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 131 | ||
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| Author | Patricia L. Suarez | ||||
| Title | Procesamiento y representación de imágenes multiespectrales usando técnicas de aprendizaje profundo (Ph.D. Angel Sappa, Director & Ph.D. Boris Vintimilla, Codirector.). Ph.D. thesis. | Type | Book Chapter | ||
| Year | 2020 | Publication | Ediciones FIEC-ESPOL. | Abbreviated Journal | |
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| Corporate Author | Ph.D. Angel Sappa, Director & Ph.D. Boris Vintimilla, Codirector. | Thesis | |||
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| Language | Español | Summary Language | Original Title | ||
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 144 | ||
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| Author | Charco, J.L., Sappa, A.D., Vintimilla, B.X., Velesaca, H.O. | ||||
| Title | Camera pose estimation in multi-view environments:from virtual scenarios to the real world | Type | Journal Article | ||
| Year | 2021 | Publication | In Image and Vision Computing Journal. (Article number 104182) | Abbreviated Journal | |
| Volume | Vol. 110 | Issue | Pages |
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| Keywords | Relative camera pose estimation, Domain adaptation, Siamese architecture, Synthetic data, Multi-view environments | ||||
| Abstract | This paper presents a domain adaptation strategy to efficiently train network architectures for estimating the relative camera pose in multi-view scenarios. The network architectures are fed by a pair of simultaneously acquired images, hence in order to improve the accuracy of the solutions, and due to the lack of large datasets with pairs of overlapped images, a domain adaptation strategy is proposed. The domain adaptation strategy consists on transferring the knowledge learned from synthetic images to real-world scenarios. For this, the networks are firstly trained using pairs of synthetic images, which are captured at the same time by a pair of cameras in a virtual environment; and then, the learned weights of the networks are transferred to the real-world case, where the networks are retrained with a few real images. Different virtual 3D scenarios are generated to evaluate the relationship between the accuracy on the result and the similarity between virtual and real scenarios—similarity on both geometry of the objects contained in the scene as well as relative pose between camera and objects in the scene. Experimental results and comparisons are provided showing that the accuracy of all the evaluated networks for estimating the camera pose improves when the proposed domain adaptation strategy is used, highlighting the importance on the similarity between virtual-real scenarios. |
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| Language | English | Summary Language | English | Original Title | |
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 147 | ||
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| Author | Jacome-Galarza L.-R | ||||
| Title | Crop yield prediction utilizing multimodal deep learning | Type | Conference Article | ||
| Year | 2021 | Publication | 16th Iberian Conference on Information Systems and Technologies, CISTI 2021, junio 23 – 26, 2021 | Abbreviated Journal | |
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| Keywords | Agricultura de precisión; sensores remotos; aprendizaje profundo multimodal; IoT; agentes inteligentes; computación aplicada. | ||||
| Abstract | La agricultura de precisión es una práctica vital para mejorar la producción de cosechas. El presente trabajo tiene como objetivo desarrollar un modelo multimodal de aprendizaje profundo que es capaz de producir un mapa de salud de cosechas. El modelo recibe como entradas imágenes multiespectrales y datos de sensores de campo (humedad, temperatura, estado del suelo, etc.) y crea un mapa de rendimiento de la cosecha. La utilización de datos multimodales tiene como finalidad extraer patrones ocultos del estado de salud de las cosechas y de esta manera obtener mejores resultados que los obtenidos mediante los índices de vegetación. |
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| Language | Español | Summary Language | Original Title | ||
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 150 | ||
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| Author | Rubio, G.A., Agila, W.E | ||||
| Title | A fuzzy model to manage water in polymer electrolyte membrane fuel cells | Type | Journal Article | ||
| Year | 2021 | Publication | In Processes Journal. (Article number 904) | Abbreviated Journal | |
| Volume | Vol. 9 | Issue | Issue 6 | Pages |
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| Keywords | PEM fuel cell, fuzzy, neural network, electrical response, flooding, drying. | ||||
| Abstract | In this paper, a fuzzy model is presented to determine in real-time the degree of dehydration or flooding of a proton exchange membrane of a fuel cell, to optimize its electrical response and consequently, its autonomous operation. By applying load, current and flux variations in the dry, normal, and flooded states of the membrane, it was determined that the temporal evolution of the fuel cell voltage is characterized by changes in slope and by its voltage oscillations. The results were validated using electrochemical impedance spectroscopy and show slope changes from 0.435 to 0.52 and oscillations from 3.6 mV to 5.2 mV in the dry state, and slope changes from 0.2 to 0.3 and oscillations from 1 mV to 2 mV in the flooded state. The use of fuzzy logic is a novelty and constitutes a step towards the progressive automation of the supervision, perception, and intelligent control of fuel cells, allowing them to reduce their risks and increase their economic benefits. | ||||
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 153 | ||
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| Author | Luis Jacome-Galarza, Monica Villavicencio-Cabezas, Miguel Realpe-Robalino, Jose Benavides-Maldonado | ||||
| Title | 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 | |
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| 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 | Rafael E. Rivadeneira, Angel Domingo Sappa, Vintimilla B. X. and Hammoud R. | ||||
| Title | A Novel Domain Transfer-Based Approach for Unsupervised Thermal Image Super- Resolution. | Type | Journal Article | ||
| Year | 2022 | Publication | Sensors | Abbreviated Journal | Sensors |
| Volume | Vol. 22 | Issue | Issue 6 | Pages |
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| Call Number | cidis @ cidis @ | Serial | 170 | ||
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| Author | Santos, V., Sappa, A.D., Oliveira, M. & de la Escalera, A. | ||||
| Title | Editorial: Special Issue on Autonomous Driving and Driver Assistance Systems – Some Main Trends | Type | Journal Article | ||
| Year | 2021 | Publication | In Journal: Robotics and Autonomous Systems. (Article number 103832) | Abbreviated Journal | |
| Volume | Vol. 144 | Issue | Pages |
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| Call Number | cidis @ cidis @ | Serial | 158 | ||
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| Author | Velesaca, H.O., Suárez, P. L., Mira, R., & Sappa, A.D. | ||||
| Title | Computer Vision based Food Grain Classification: a Comprehensive Survey | Type | Journal Article | ||
| Year | 2021 | Publication | In Computers and Electronics in Agriculture Journal. (Article number 106287) | Abbreviated Journal | |
| Volume | Vol. 187 | Issue | Pages |
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| Call Number | cidis @ cidis @ | Serial | 159 | ||
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| Author | Pereira J., Mora M. & W. Agila | ||||
| Title | Qualitative Model to Maximize Shrimp Growth at Low Cost | Type | Journal Article | ||
| Year | 2021 | Publication | 5th Ecuador Technical Chapters Meeting (ETCM 2021), Octubre 12 – 15 | Abbreviated Journal | |
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| Call Number | cidis @ cidis @ | Serial | 167 | ||
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