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| Author | Cristina L. Abad; Yi Lu; Roy H. Campbell | ||||
| Title | DARE: Adaptive Data Replication for Efficient Cluster Scheduling | Type | Conference Article | ||
| Year | 2011 | Publication | IEEE International Conference on Cluster Computing, 2011 | Abbreviated Journal | |
| Volume | Issue | Pages | 159 - 168 | ||
| Keywords | MapReduce, replication, scheduling, locality | ||||
| Abstract | Placing data as close as possible to computation is a common practice of data intensive systems, commonly referred to as the data locality problem. By analyzing existing production systems, we confirm the benefit of data locality and find that data have different popularity and varying correlation of accesses. We propose DARE, a distributed adaptive data replication algorithm that aids the scheduler to achieve better data locality. DARE solves two problems, how many replicas to allocate for each file and where to place them, using probabilistic sampling and a competitive aging algorithm independently at each node. It takes advantage of existing remote data accesses in the system and incurs no extra network usage. Using two mixed workload traces from Facebook, we show that DARE improves data locality by more than 7 times with the FIFO scheduler in Hadoop and achieves more than 85% data locality for the FAIR scheduler with delay scheduling. Turnaround time and job slowdown are reduced by 19% and 25%, respectively. | ||||
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| Language | English | Summary Language | English | Original Title | |
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| Notes | Approved  |
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| Call Number | cidis @ cidis @ | Serial | 21 | ||
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| Author | Jorge Alvarez Tello; Mireya Zapata; Dennys Paillacho | ||||
| Title | Kinematic optimization of a robot head movements for the evaluation of human-robot interaction in social robotics. | Type | Conference Article | ||
| Year | 2019 | Publication | 10th International Conference on Applied Human Factors and Ergonomics and the Affiliated Conferences (AHFE 2019), Washington D.C.; United States. Advances in Intelligent Systems and Computing | Abbreviated Journal | |
| Volume | 975 | Issue | Pages | 108-118 | |
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| Abstract | This paper presents the simplification of the head movements from the analysis of the biomechanical parameters of the head and neck at the mechanical and structural level through CAD modeling and construction with additive printing in ABS/PLA to implement non-verbal communication strategies and establish behavior patterns in the social interaction. This is using in the denominated MASHI (Multipurpose Assistant robot for Social Human-robot Interaction) experimental robotic telepresence platform, implemented by a display with a fish-eye camera along with the mechanical mechanism, which permits 4 degrees of freedom (DoF). In the development of mathematicalmechanical modeling for the kinematics codification that governs the robot and the autonomy of movement, we have the Pitch, Roll, and Yaw movements, and the combination of all of them to establish an active communication through telepresence. For the computational implementation, it will be show the rotational matrix to describe the movement. |
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| Notes | Approved |
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| Call Number | gtsi @ user @ | Serial | 108 | ||
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| Author | 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 | |
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| Corporate Author | Ph.D. Angel Sappa, Director de tesis & 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 |
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| Call Number | gtsi @ user @ | Serial | 114 | ||
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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 |
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| Call Number | cidis @ cidis @ | Serial | 122 | ||
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| Author | Dennys Paillacho; Nayeth I. Solorzano Alcivar; Jonathan S. Paillacho Corredores | ||||
| Title | LOLY 1.0: A Proposed Human-Robot-Game Platform Architecture for the Engagement of Children with Autism in the Learning Process | Type | Book Chapter | ||
| Year | 2021 | Publication | The international Conference on Systems and Information Sciences (ICCIS 2020), julio 27-29. Advances in Intelligent Systems and Computing. | Abbreviated Journal | |
| Volume | 1273 | Issue | Pages | 225-238 | |
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| ISSN | 21945357 | ISBN | 978-303059193-9 | Medium | |
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| Notes | Approved |
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| Call Number | cidis @ cidis @ | Serial | 185 | ||
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| Author | Daniela Rato, Miguel Oliviera, Victor Santos, Manuel Gomes & Angel Sappa | ||||
| Title | A Sensor-to-Pattern Calibration Framework for Multi-Modal Industrial Collaborative Cells. | Type | Journal Article | ||
| Year | 2022 | Publication | Journal of Manufacturing Systems | Abbreviated Journal | |
| Volume | Vol. 64 | Issue | Pages | pp. 497-507 | |
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| Notes | Approved |
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| Call Number | cidis @ cidis @ | Serial | 184 | ||
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| Author | Velesaca, Henry O.; Suárez, Patricia L.; Sappa, Angel D.; Carpio, Dario; Rivadeneira, Rafael E.; Sanchez, Angel | ||||
| Title | Review on Common Techniques for Urban Environment Video Analytics. | Type | Conference Article | ||
| Year | 2022 | Publication | WORKSHOP BRASILEIRO DE CIDADES INTELIGENTES (WBCI 2022) | Abbreviated Journal | |
| Volume | Issue | Porto Alegre: Sociedade Brasileira de Computação | Pages | 107-118 | |
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| Call Number | cidis @ cidis @ | Serial | 192 | ||
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| Author | Jorge L. Charco, Angel D. Sappa, Boris X. Vintimilla | ||||
| Title | Human Pose Estimation through A Novel Multi-View Scheme | Type | Conference Article | ||
| Year | 2022 | Publication | Proceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications VISIGRAPP 2022 | Abbreviated Journal | |
| Volume | 5 | Issue | Pages | 855-862 | |
| Keywords | Multi-View Scheme, Human Pose Estimation, Relative Camera Pose, Monocular Approach | ||||
| Abstract | This paper presents a multi-view scheme to tackle the challenging problem of the self-occlusion in human pose estimation problem. The proposed approach first obtains the human body joints of a set of images, which are captured from different views at the same time. Then, it enhances the obtained joints by using a multi-view scheme. Basically, the joints from a given view are used to enhance poorly estimated joints from another view, especially intended to tackle the self occlusions cases. A network architecture initially proposed for the monocular case is adapted to be used in the proposed multi-view scheme. Experimental results and comparisons with the state-of-the-art approaches on Human3.6m dataset are presented showing improvements in the accuracy of body joints estimations. |
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| Notes | Approved |
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| Call Number | cidis @ cidis @ | Serial | 169 | ||
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| Author | Xavier Soria , Gonzalo Pomboza-Junez & Angel Sappa. | ||||
| Title | LDC: Lightweight Dense CNN for Edge Detection. | Type | Journal Article | ||
| Year | 2022 | Publication | IEEE Access journal | Abbreviated Journal | |
| Volume | Vol. 10 | Issue | Pages | pp. 68281-68290 | |
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| Notes | Approved |
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| Call Number | cidis @ cidis @ | Serial | 183 | ||
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| Author | 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 | ||
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| 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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| Call Number | gtsi @ user @ | Serial | 97 | ||
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