Tecniproject SL

Las Palmas de Gran Canaria, Spain

Tecniproject SL

Las Palmas de Gran Canaria, Spain
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Sanchez Lasheras F.,Tecniproject SL | Vilan Vilan J.A.,University of Vigo | Garcia Nieto P.J.,University of Oviedo | del Coz Diaz J.J.,University of Oviedo
Mathematical and Computer Modelling | Year: 2010

The hard chromium plating process aims at creating a coating of hard and wear-resistant chromium with a thickness of some micrometres directly on the metal part without the insertion of copper or nickel layers. Chromium plating features high levels of hardness and resistance to wear and it is due to these properties that they can be applied in a huge range of sectors. Resistance to corrosion of a hard chromium plate depends on the thickness of its coating, and its adherence and micro-fissures. This micro-fissured structure is what provides the optimal hardness of the layers. The hard chromium plating process is one of the most effective ways of protecting the base material against a hostile environment or improving the surface properties of the base material. However, in the electroplating industry, electroplaters are faced with many problems and undesirable results with chromium plated materials. Common problems faced in the electroplating industry include matt deposition, milky white chromium deposition, rough or sandy chromium deposition and insufficient thickness and hardness. This article presents an artificial neural network (ANN) model to predict the thickness of the layer in a hard chromium plating process. The optimization of the ANN was performed by means of the design of experiments theory (DOE). In the present work the purpose of using DOE is twofold: to define the optimal experiments which maximize the ratio of the model accuracy, and to minimize the number of necessary experiments (ANN models trained and validated). © 2010 Elsevier Ltd.

Alvarez Menendez L.,Hospital Materno Infantil Teresa Herrera Ch La Coruna | de Cos Juez F.J.,University of Oviedo | Sanchez Lasheras F.,Tecniproject SL
Mathematical and Computer Modelling | Year: 2010

Breast screening is a method of detecting breast cancer at a very early stage. The first step involves taking an X-ray, called a mammogram, of each breast. The mammogram can detect small changes in breast tissue which may indicate cancers which are too small to be felt either by the woman herself or by a doctor.The World Health Organisation's International Agency for Research on Cancer (IARC) concluded that mammography screening for breast cancer reduces mortality. This means that out of every 500 women screened, one life will be saved.The present research uses the information obtained from the breast screening programme carried out in the public health area of Aviles (Principality of Asturias, Spain) from 1999 to 2007. The public health area of Aviles is formed by nine municipalities with a total of 160,000 inhabitants. The selection of the public health area was based on the following criteria: ̇This is the first screening programme performed in the area.̇Almost 100% of the population in the area benefit from the public health system.̇The Aviles public health area is a well-defined area of the region that does not send patients to other public health areas, which makes the study easier and more accurate. This paper describes a neural network based approach to breast cancer diagnosis; the model developed is able to determine which women are more likely to suffer from a particular kind of tumour before they undergo a mammography. © 2010 Elsevier Ltd.

De Andres J.,University of Oviedo | Lorca P.,University of Oviedo | De Cos Juez F.J.,University of Oviedo | Sanchez-Lasheras F.,Tecniproject SL
Expert Systems with Applications | Year: 2011

During the last years, hybrid models have proven to be a promising approach for the design of classification systems for the forecasting of bankruptcy. In the present research we propose a hybrid system which combines fuzzy clustering and MARS. Both models are especially suitable for the bankruptcy prediction problem, due to their theoretical advantages when the information used for the forecasting is drawn from company financial statements. We test the accuracy of our approach in a real setting consisting of a database made up of 59,336 non-bankrupt Spanish companies and 138 distressed firms which went bankrupt during 2007. As benchmarking techniques we used discriminant analysis, MARS and a feed-forward neural network. Our results show that the hybrid model outperforms the other systems, both in terms of the percentage of correct classifications and in terms of the profit generated by the lending decisions. © 2010 Elsevier Ltd. All rights reserved.

De Cos Juez F.J.,University of Oviedo | Suarez-Suarez M.A.,University of Oviedo | Sanchez Lasheras F.,Tecniproject SL | Murcia-Mazon A.,University of Oviedo
Mathematical and Computer Modelling | Year: 2011

Osteoporosis is characterized by low bone mineral density (BMD). This illness has a high-cost impact in all developed countries. The aim of this article is the development of a mathematical method able to predict the BMD of post-menopausal women, taking into account only certain nutritional variables. This research applies neural networks for the study of the influence of diet and lifestyle on the value of bone mineral density in post-menopausal women.A questionnaire on nutritional habits and lifestyle was drawn up. The variables obtained from this, together with the BMD of the patients calculated by densitometry, were processed using genetic algorithms in order to reduce the number of input variables. Finally, a neural network model using only those variables considered important was applied.It has been proved to be possible to build a neural network model able to forecast the BMD of post-menopausal women according to their responses to the questionnaire. This model can be used to determine which women should take a densitometry in order to verify their bone quality and thus prevent some risks associated with osteoporosis. © 2010 Elsevier Ltd.

Guzman D.,University of Santiago de Chile | Guzman D.,Durham University | De Juez F.J.C.,University of Oviedo | Myers R.,Durham University | And 3 more authors.
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2010

Open-loop adaptive optics is a technique in which the turbulent wavefront is measured before it hits the deformable mirror for correction; therefore the correct control of the mirror in open-loop is key in achieving the expected level of correction. In this paper, we present non-parametric estimation techniques to model deformable mirrors working in open-loop. We have results with mirrors characterized by non-linear behavior: a Xinetics electrostrictive mirror and a Boston Micromachines MEMS mirror. The inputs for these models are the wavefront corrections to apply to the mirror and the outputs are the set of voltages to shape the mirror. We have performed experiments on both mirrors, achieving Go-To errors relative to peak-to-peak wavefront excursion in the order of 1 % RMS for the Xinetics mirror and 3 % RMS for the Boston mirror . These techniques are trained with interferometric data from the mirror under control; therefore they do not depend on the physical parameters of the device. © 2010 SPIE.

Guzman D.,University of Santiago de Chile | Guzman D.,Durham University | De Cos Juez F.J.,University of Oviedo | Myers R.,Durham University | And 2 more authors.
Optics Express | Year: 2010

Using non-parametric estimation techniques, we have modeled an area of 126 actuators of a micro-electro-mechanical deformable mirror with 1024 actuators. These techniques produce models applicable to open-loop adaptive optics, where the turbulent wavefront is measured before it hits the deformable mirror. The model's input is the wavefront correction to apply to the mirror and its output is the set of voltages to shape the mirror. Our experiments have achieved positioning errors of 3.1% rms of the peak-to-peak wavefront excursion. © 2010 Optical Society of America.

Guzman D.,Durham University | Guzman D.,Pontifical Catholic University of Chile | De Juez F.J.C.,University of Oviedo | Lasheras F.S.,TecniProject S.L | And 2 more authors.
Optics Express | Year: 2010

Open-loop adaptive optics is a technique in which the turbulent wavefront is measured before it hits the deformable mirror for correction. We present a technique to model a deformable mirror working in open-loop based on multivariate adaptive regression splines (MARS), a nonparametric regression technique. The model's input is the wavefront correction to apply to the mirror and its output is the set of voltages to shape the mirror. We performed experiments with an electrostrictive deformable mirror, achieving positioning errors of the order of 1.2% RMS of the peakto-peak wavefront excursion. The technique does not depend on the physical parameters of the device; therefore it may be included in the control scheme of any type of deformable mirror. © 2010 Optical Society of America.

Moreno F.J.,National University of Colombia | Hernandez J.A.,National University of Colombia | Sanchez F.,Tecniproject SL
AIP Conference Proceedings | Year: 2011

The recent explosion and availability of mobility based technologies such as geographic information systems, cell phones equipped with built-in GPS, among others, are a valuable source of spatio-temporal data. However, only recently there have been works focused on identifying movement patterns in groups of moving entities. We focus on a particular movement pattern: dissociation. A dissociation pattern occurs when an entity that was once associated to a population, eventually separated from it and subsequently reintegrated it again. The backwarding and forwarding patterns are a type of dissociation where an entity stays behind or ahead of another entity, respectively. Dissociation really is a diversity generator, so instead avoiding it, taking advantage could be better to prevent premature convergence in evolutionary algorithms. In this work, we present formal mathematical definitions for these patterns. A discussion of how to use dissociation patterns as a mean to preserve diversity in evolutionary algorithms is also shown. © 2011 American Institute of Physics.

Jimenez-Trevino L.,University of Oviedo | Saiz P.A.,University of Oviedo | Garcia-Portilla M.P.,University of Oviedo | Diaz-Mesa E.M.,Research Center Biomedica En Red Of Salud Mental | And 5 more authors.
Addictive Behaviors | Year: 2011

Introduction: We conducted a follow-up study to evaluate the outcome of a heroin-dependent population 25. years after their first enrollment in methadone maintenance treatment (MMT). We assessed mortality in the sample plus actual drug use, treatment, and medical factors associated with drug dependence, focusing on possible gender differences. Methods: Prospective follow-up study of 214 heroin-dependent patients consecutively admitted for MMT between 1980 and 1984 in the Asturias Public Health Service. The standardized mortality ratio (SMR) and 95% confidence interval (CI) were calculated. An ad-hoc protocol on drug misuse and treatment, drug-related morbidity and Clinical Global Impression (CGI) scores were assessed in the survivors' sample. Results: Information was received on 159 subjects, 106 of whom were deceased. Men accounted for 76.2% of the study cohort. Over the 25-year follow-up period, the SMR was 22.51 (95% CI = 22.37-22.64). In the survivors sample, 39.6% were still enrolled in MMT; human immunodeficiency virus (HIV) was diagnosed in 47.2% and hepatitis B/C in 81.1%; current heroin use was reported by 22.6%. There were no gender differences in mortality or HIV and hepatitis B/C status. None of the female survivors were using heroin at the 25-year follow-up compared with 31.1% of males. Conclusions: This study confirms the high mortality of heroin addicts even after enrollment in MMT. Severity of the addiction in terms of mortality was similar in both genders. Women who survived the 25-year follow-up were more likely to have stopped using heroin than men. © 2011 Elsevier Ltd.

Bobes J.,University of Oviedo | Iglesias Garcia C.,University of Oviedo | Garcia-Portilla Gonzalez M.P.,University of Oviedo | Bascaran M.T.,University of Oviedo | And 5 more authors.
Revista de Psiquiatria y Salud Mental | Year: 2013

Introduction: The study of administrative prevalence from cumulative psychiatric case registers allows the mental health state of the studied region and the functioning of its Health Services to be estimated. Methods: Data were extracted from the Asturias Cumulative Psychiatric Case Register (RACPAS) between January 1st 1998 and December 3th 2010. Characteristics of the population of the catchment area were studied, and their relationship with the administrative prevalence was analyzed. Results: The mean population in the studied period was 1,078,406 inhabitants. The Fritz index and the Youth and replacement indices of the active population decreased throughout the period. There was no significant increase in the prevalence of organic mental disorders, psychosis, mood disorders, and substance use in males, or behavioral disorders associated with somatic factors and physiological dysfunctions in females. There were significant gender differences in the prevalence of all disorders, except for personality disorders and organic mental disorders. Population ageing had a significant influence on the increase in the prevalence of most mental disorders in both males and females. Conclusions: A slight general increase in the administrative prevalence of mental disorders is observed during the studied period, and it was influenced by population ageing. © 2012 SEP y SEPB. Published by Elsevier España, S.L. All rights reserved.

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