MATHEMATICS AND COMPUTER SCIENCE

Basically, I have collaborated in several works in different areas: computer vision and image processing, modelling of logistic problems related with transport in the new economy, and message dissemination on communication networks.

  1. J.A. Conejero, C. Jordán, and E. Sanabria-Codesal. An iterative algorithm for the management of an electric car-rental service. J. Appl. Math. 2014, 2014, article ID 483734, 11 pages. doi:10.1155/2014/483734
  2. J.A. Conejero, C. Jordán, E. Sanabria-Codesal. A tree-based model for setting optimal train fare zones. Math. Probl. Eng. 2014, 2014, article ID 384321, 11 pages. doi:10.1155/2014/384321
  3. J.A. Conejero, C. Jordán, and E. Sanabria-Codesal. An algorithm for self-organization of driverless vehicles of a car-rental serviceNonlinear Dyn. 84, 107-114 2016. doi:10.1007/s11071-015-2237-4
  4. C. Jordán, J.A. Gómez, and J.A. Conejero. An analysis of the influence of Graph Theory when preparing for programming contests. Mathematics, 5:1, 8, 2017. doi:10.3390/math5010008
  5. J.A. Pérez-Melián, J.A. Conejero, and C. Ferri. Zipf’s and Benford’s law in Twitter hashtags. Proceedings of the Student Research Workshop at the 15th Conference of the European Chapter of the Association for Computational Linguistics, pages 84–93, Valencia, Spain, April 3-7 2017. Link 978-1-945626-34-0
  6. C. Pérez-Benito, S. Morillas, C. Jordán, J.A. Conejero. Smoothing vs. sharpening of color images – Together or separated. Applied Mathematics Nonlinear Sciences 2:1, 299–316, 2017.  doi:10.21042/AMNS.2017.1.00025
  7. C. Pérez-Benito, C. Jordán, S. Morillas, and J.A. Conejero. A model based on local graphs for colour images and its application for Gaussian noise smoothing. J. Comp. Appl. Math. 330, 955-964, 2018. doi:10.1016/j.cam.2017.05.013
  8. C. Pérez-Benito, C. Jordán, S. Morillas, and J.A. Conejero. Graph-based methods for simultaneous smoothing and sharpening of color images. J. Comp. Appl. Math. 350, 380-395 (2019). doi:10.1016/j.cam.2018.10.031