Browsing by Author "Velecela, E"

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    An open source SCADA system to implement advanced computer integrated manufacturing
    (IEEE COMPUTER SOCIETY, 2016-12-01) Minchala Ávila, Luis Ismael; Astudillo Salinas, Darwin Fabián; Ochoa, S; Velecela, E
    The computer integrated manufacturing (CIM) approach allows the possibility to remotely and optimally control the entire production process in a plant. The implementation of CIM architectures demands the installation of several software platforms, which most of the cases are commercial and have high licensing prices. This research presents the development of an open software architecture for advanced CIM (OSACIM) by using two open software development platforms: Java and Python. The use of open software in the development of this solution allows the creation of a low price CIM approach. The results of using the system in laboratory tests show good results in comparison with commercial softwares for developing OPC communications and SCADA systems, which perform similar functionalities as the proposed OSACIM. The main features and limitations of the system are reported.
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    CinC Challenge 2013: Comparing three algorithms to extract fetal ECG
    (SPIE, 2015-11-17) Loja, J; Astudillo Salinas, Darwin Fabián; Medina Molina, Ruben; Palacio Baus, Kenneth Samuel; Velecela, E; Wong De Balzan, Sara
    This paper reports a comparison between three fetal ECG (fECG) detectors developed during the CinC 2013 challenge for fECG detection. Algorithm A1 is based on Independent Component Analysis, A2 is based on fECG detection of RS Slope and A3 is based on Expectation-Weighted Estimation of Fiducial Points. The proposed methodology was validated using the annotated database available for the challenge. Each detector was characterized in terms of its performance by using measures of sensitivity, (Se), positive predictive value (P+) and delay time (td). Additionally, the database was contaminated with white noise for two SNR conditions. Decision fusion was tested considering the most common types of combination of detectors. Results show that the decision fusion of A1 and A2 improves fQRS detection, maintaining high Se and P+ even under low SNR conditions without a significant tdincrease.