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Pinar del Rio, Cuba

The University of Pinar del Río "Hermanos Saiz Montes de Oca" is a university located in Pinar del Río, Cuba. It was founded in 1972. Wikipedia.


Corres J.M.,Public University of Navarra | Garcia Y.R.,University of Pinar del Rio | Arregui F.J.,Public University of Navarra | Matias I.R.,Public University of Navarra
IEEE Sensors Journal | Year: 2011

In this paper, a new optical fiber humidity sensor based on PVdF nanowebs is presented. The electrospinning technique has been used to create a nanometric scale membrane onto the surface of a hollow core fiber (HCF). The fabricated sensor has demonstrated a repetitive response in the range from 50 to 70% of relative humidity with a rise time of 100 ms. Among other applications, this sensor is intended to be used for monitoring the human breathing. Therefore, high dynamic performances are required, especially in the higher relative humidity ranges. © 2006 IEEE.


Mena-Torres D.,University of Pinar del Rio | Aguilar-Ruiz J.S.,Pablo De Olavide University
Expert Systems with Applications | Year: 2014

Incremental learning techniques have been used extensively to address the data stream classification problem. The most important issue is to maintain a balance between accuracy and efficiency, i.e.; the algorithm should provide good classification performance with a reasonable time response. This work introduces a new technique, named Similarity-based Data Stream Classifier (SimC), which achieves good performance by introducing a novel insertion/removal policy that adapts quickly to the data tendency and maintains a representative, small set of examples and estimators that guarantees good classification rates. The methodology is also able to detect novel classes/labels, during the running phase, and to remove useless ones that do not add any value to the classification process. Statistical tests were used to evaluate the model performance, from two points of view: efficacy (classification rate) and efficiency (online response time). Five well-known techniques and sixteen data streams were compared, using the Friedman's test. Also, to find out which schemes were significantly different, the Nemenyi's, Holm's and Shaffer's tests were considered. The results show that SimC is very competitive in terms of (absolute and streaming) accuracy, and classification/updating time, in comparison to several of the most popular methods in the literature. © 2014 Elsevier Ltd. All rights reserved.


Garcia Y.R.,University of Pinar del Rio | Corres J.M.,Public University of Navarra | Goicoechea J.,Public University of Navarra
Journal of Sensors | Year: 2010

Condition monitoring of heavy electromechanical equipment is commonly accomplished in the industry using vibration analysis. Several techniques, mainly based on capacitive and piezoelectric accelerometers, have been applied for predictive maintenance. However, the negative influence of the electromagnetic interference (EMI) can be a real problem when electrical signals are used to detect and transmit physical parameters in noisy environments such as electric power generator plants with high levels of EMI. Optical fiber sensors are increasingly used because of the nonelectrical nature of signals. In this paper, the most frequently used vibration optical fiber sensors will be reviewed, classifying them by the sensing techniques and measurement principles. The main techniques, intensity modulation, fiber bragg gratings and Fabry-Pérot Interferometry, will be reviewed here. © 2010 Yoany Rodrguez Garca et al.


Castano A.,University of Pinar del Rio | Fernandez-Navarro F.,European Space Agency | Hervas-Martinez C.,University of Cordoba, Spain
Neural Processing Letters | Year: 2013

It is well-known that single-hidden-layer feedforward networks (SLFNs) with additive models are universal approximators. However the training of these models was slow until the birth of extreme learning machine (ELM) "Huang et al. Neurocomputing 70(1-3):489-501 (2006)" and its later improvements. Before ELM, the faster algorithms for efficiently training SLFNs were gradient based ones which need to be applied iteratively until a proper model is obtained. This slow convergence implies that SLFNs are not used as widely as they could be, even taking into consideration their overall good performances. The ELM allowed SLFNs to become a suitable option to classify a great number of patterns in a short time. Up to now, the hidden nodes were randomly initiated and tuned (though not in all approaches). This paper proposes a deterministic algorithm to initiate any hidden node with an additive activation function to be trained with ELM. Our algorithm uses the information retrieved from principal components analysis to fit the hidden nodes. This approach considerably decreases computational cost compared to later ELM improvements and overcomes their performance. © 2012 Springer Science+Business Media New York.


Blanco J.A.,University of British Columbia | Gonzalez E.,University of Pinar del Rio
Journal of Tropical Forest Science | Year: 2010

The ecosystem model FORECAST was used to evaluate the sustainability of current management practices in Pinus caribaea plantations in Pinar del Rio (western Cuba). Model predictions were within the range of observed field measurements of height, diameter, stem density and volume. The model performed reasonably well in capturing general growth trends (r values for dominant height, diameter and merchantable volume were 0.91, 0.77 and 0.81 respectively). In the second part of our work, model output of merchantable volume, stem biomass, soil organic matter and available N in soil were analysed in 18 different combinations of rotation length (25 vs. 50 years), thinning intensity (0, 15 and 30% stems) and fertilisation (0, 50 and 100 kg ha-1 N) in order to study the effects of different management regimes on site fertility. Our results indicated that some of the current prescriptions could produce a considerable loss of nitrogen, and in some cases, a decrease in productivity after the third 25-year rotation. However, other prescriptions can keep productivity and soil organic matter at acceptable levels. The results of our analysis illustrated the portability and utility of FORECAST as a scenario-analysis and decision-support tool in managing pine plantations in the Caribbean region and, potentially, elsewhere.

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