Scheduled presentations:

• Fault detection in industrial pumps based on recurrent autoencoder neural networks
  *V. Meruane (Universidad de Chile), T. Hansen (Calmly), I. Huerta (Calmly), E. Roa (Universidad de Chile), L. Quinteros (Calmly), J. Marin (Calmly)
• Damage identification of RC beams using Feed-Forward Back Propagation Neural Network Approach (FFBPN)
  *K. Oroz Farfan (Universidad Peruana de Ciencias Aplicadas), V. Ramos Cari (Universidad Peruana de Ciencias Aplicadas), J. Casas Rius (Technical University of Catalonia (BarcelonaT), R. Delgadillo Ayala (Universidad Peruana de Ciencias Aplicadas)
• Damage Classification Utilizing Autoencoders and Convolutional Neural Networks
  *F. Barbosa (Universidade Federal de Juiz de Fora), L. Resende (Universidade Federal de Juiz de Fora), R. Finotti (Universidade Federal de Juiz de Fora), A. Cury (Universidade Federal de Juiz de Fora), H. Garrido (Universidad Nacional de Cuyo), M. Domizio (Universidad Nacional de Cuyo), O. Curadelli (Universidad Nacional de Cuyo)
• Spatio-temporal damage identification through Bayesian calibration of time-varying finite element models
  *G. Parra (Universidad de los Andes), R. Astroza (Universidad de los Andes), M. Birrel (Universidad de los Andes), F. Mizón (Universidad de los Andes)
• A data driven frequency-domain virtual sensing method based on cross-spectral density matrices
  *M. Nuñez Cuji (Escuela Superior Politécnica del Litoral), R. Prieto-Galarza (Universidad Ecotec), C. Tutivén Gálvez (Escuela Superior Politécnica del Litoral), L. Avendaño Valencia (University of Southern Denmark)
• Structural Damage Identification based on the Curvature Matrix of the Accelerance
  *J. Herrera (PONTIFICIA UNIVERSIDAD JAVERIANA)