Editorial
Special Issue on Artificial Intelligence
a Universidad Militar Nueva Granada. Editor-in-chief, journal Ciencia e Ingenieria Neogranadina. E-mail: dora.ballesteros@unimilitar.edu.co. ORCID: https://orcid.org/0000-0003-3741-2618
Artificial intelligence (AI) is an interdisciplinary subject of science and engineering that makes it possible for machines to learn from data. AI applications include prediction, recommendation, classification and recognition, object detection, natural language processing, autonomous systems, among others. The topics of the articles in this special issue include deep learning applied to medicine [1,3], support vector machines applied to ecosystems [2], human-robot interaction [4], clustering in the identification of anomalous patterns in communication networks [5], expert systems for the simulation of natural disaster scenarios [6], real-time algorithms of artificial intelligence [7], and big data analytics for natural disasters [8].
For this special issue, the journal received manuscripts from different Colombian universities and research centers. Most of them were rejected in the preliminary round because they did not meet certain criteria (topic, typology, or anti-plagiarism). Only eight (8) of these articles were recommended for publication by peer reviewers and included in this special edition. In summary, 36.6 % of submitted manuscripts passed the pre-review round and 13 % were accepted for publication, as shown in Figure 1.
We invite readers to include these articles in their state-of-the-art research.
References
[1] O. J. Perdomo Charry and F. A. González Osorio. "A Systematic Review of Deep Learning Methods Applied to Ocular Images," Ciencia E Ingenieria Neogranadina, vol. 30, no. 1, 2019. https://doi.org/10.18359/rcin.4242
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[2] L. D. Martin, J. Medina, and E. Upegui. "Assessment of Image-Texture Improvement Applied to Unmanned Aerial Vehicle Imagery for the Identification of Biotic Stress in Espeletia. Case Study: Moorlands of Chingaza (Colombia)," Ciencia E Ingeniería Neogranadina, vol. 30, no. 1, 2019. https://doi.org/10.18359/rcin.3842
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[3] J. A. Castillo, Y. C. Granado, and C. A. Fajardo Ariza. "Patient-Specific Detection of Atrial Fibrillation in Segments of ECG Signals using Deep Neural Networks," Ciencia E Ingenieria Neogranadina, vol. 30, no. 1, 2019. https://doi.org/10.18359/rcin.4156
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[4] K. Muñoz Peña and B. Bacca Cortes. "GUI3DXBot: An Interactive Software Tool for a Tour-Guide Mobile Robot," Ciencia E Ingenieria Neogranadina, vol. 30, no. 1, 2019. https://doi.org/10.18359/rcin.3644
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[5] E. A. Leal Piedrahita. "Hierarchical Clustering for Anomalous Traffic Conditions Detection in Power Substations," Ciencia E Ingenieria Neogranadina , vol. 30, no. 1, 2019. https://doi.org/10.18359/rcin.4236
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[6] J. A. Florez Zuluaga, E. Patino Carrasco, J. D. Ortega Pabon, K. Gallego Leon, and O. L. Quintero Montoya. "A Data Fusion System for Simulation of Critical Scenarios and Decision-Making," Ciencia E Ingenieria Neogranadina , vol. 30, no. 1, 2019. https://doi.org/10.18359/rcin.4131
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[7] E. González, W. D. Villamizar Luna, and C. A. Fajardo Ariza. "A Hardware Accelerator for the Inference of a Convolutional Neural network," Ciencia E Ingenieria Neogranadina , vol. 30, no. 1, 2019. https://doi.org/10.18359/rcin.4194
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[8] D. O. Martínez Quezada, R. Ortiz Sierra, J. G. Martínez Cano, and H. Lamos Díaz. Stakeholders Identification in a Disaster Through Twitter: Study Case SINABUNG 2018," Ciencia E Ingenieria Neogranadina , vol. 30, no. 1. https://doi.org/10.18359/rcin.3938.
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