Estudio y propuestas de tratamiento de PPCP’s en aguas residuales

La reutilización de las aguas residuales es una parte esencial del uso sostenible del agua. Sin embargo, las actuales plantas de tratamiento no están preparadas para tratar determinados compuestos como los llamados “contaminantes emergentes”. Los hábitos de consumo actuales estan generando una serie de residuos o microcontaminantes que hace tan solo unos años no existian. Entre esas nuevas sustancias aparecen los PPCP’s (Pharmaceuticals & Personal Care Products) que son un amplio grupo de compuestos químicos utilizados en veterinaria, prácticas agrícolas, salut humana y cosmetología. El mayor problema que presentan estas substancias en la actualidad es el parcial desconocimiento sobre sus efectos, la ausencia de reglamentaciones que determinen las concentraciones máximas admisibles en los cauces de vertido, la reducción en procesos de depuración convencionales, así como los tratamientos específicos aplicables a su eliminación. Los objetivos del presente proyecto són: estudiar las tipologías de PPCP’s y sus influencias para la salud humana y el medio ambiente, estudiar los diferentes sistemas de tratamiento de aguas existentes en plantas depuradoras y evaluar su eficiencia en la depuración de PPCP

Microcalcification evaluation in computer assisted diagnosis for digital mammography

In order to develop applications for z;isual interpretation of medical images, the early detection and evaluation of microcalcifications in digital mammograms is verg important since their presence is often associated with a high incidence of breast cancers. Accurate classification into benign and malignant groups would help improve diagnostic sensitivity as well as reduce the number of unnecessa y biopsies. The challenge here is the selection of the useful features to distinguish benign from malignant micro calcifications. Our purpose in this work is to analyse a microcalcification evaluation method based on a set of shapebased features extracted from the digitised mammography. The segmentation of the microcalcifications is performed using a fixed-tolerance region growing method to extract boundaries of calcifications with manually selected seed pixels. Taking into account that shapes and sizes of clustered microcalcifications have been associated with a high risk of carcinoma based on digerent subjective measures, such as whether or not the calcifications are irregular, linear, vermiform, branched, rounded or ring like, our efforts were addressed to obtain a feature set related to the shape. The identification of the pammeters concerning the malignant character of the microcalcifications was performed on a set of 146 mammograms with their real diagnosis known in advance from biopsies. This allowed identifying the following shape-based parameters as the relevant ones: Number of clusters, Number of holes, Area, Feret elongation, Roughness, and Elongation. Further experiments on a set of 70 new mammogmms showed that the performance of the classification scheme is close to the mean performance of three expert radiologists, which allows to consider the proposed method for assisting the diagnosis and encourages to continue the investigation in the sense of adding new features not only related to the shape

Constraint satisfaction techniques under uncertain conditions for fault diagnosis in nonlinear dynamic systems

The speed of fault isolation is crucial for the design and reconfiguration of fault tolerant control (FTC). In this paper the fault isolation problem is stated as a constraint satisfaction problem (CSP) and solved using constraint propagation techniques. The proposed method is based on constraint satisfaction techniques and uncertainty space refining of interval parameters. In comparison with other approaches based on adaptive observers, the major advantage of the presented method is that the isolation speed is fast even taking into account uncertainty in parameters, measurements and model errors and without the monotonicity assumption. In order to illustrate the proposed approach, a case study of a nonlinear dynamic system is presented

Fault diagnosis by refining the parameter uncertainty space of nonlinear dynamic systems

This paper deals with fault detection and isolation problems for nonlinear dynamic systems. Both problems are stated as constraint satisfaction problems (CSP) and solved using consistency techniques. The main contribution is the isolation method based on consistency techniques and uncertainty space refining of interval parameters. The major advantage of this method is that the isolation speed is fast even taking into account uncertainty in parameters, measurements, and model errors. Interval calculations bring independence from the assumption of monotony considered by several approaches for fault isolation which are based on observers. An application to a well known alcoholic fermentation process model is presented