A statistical method is presented to determine the optima design of air quality networks detecting warning and alert levels. A simulation model is used to describe temporal and spatial variations of ...atmospheric pollutants; air quality patterns serve as the database of the procedure to design the network. Only the sites exceeding warning and alert levels, at different meteorological scenarios, are considered as potential monitoring stations. For the selection of the optima set, spatial and temporal representativity criteria are introduced; accordingly, the optima set provides a complete representativity of the space and time considered. The method is applied to the Mestre urban area, in Venice district, for the carbon monoxide pollutant.PUBLICATION ABSTRACT
Alagille syndrome is an autosomal dominant and multisystemic disease that generally manifests itself with intrahepatic bile ducts paucity, chronic cholestasis, xanthomas and with other less frequent ...clinical manifestations such as congenital heart disease, skeletal abnomalies, ophthalmic, vascular, renal and growth failure. Symptoms can be subclinical or very severe. Is caused by various genetic mutations and the majority of patients have a detectable mutation in JAG1 (90%), the remainder have mutations in NOTCH2. The diagnosis is molecular and the incidence is approximately 1 in 30,000 – 50.000. Patient management can be very complex and treatment depends on the district affected and on the symptoms. In more serious cases, with terminal liver disease, liver transplantation is used. We describe a case with main bile duct hypoplasia, intrahepatic bile ducts paucity, cholestasis and gallbladder dimorphism associated with renal malrotation and butterfly vertebrae.
Clustering of space-time series should consider: 1) the spatial nature of the objects to be clustered; 2) the characteristics of the feature space, namely the space of multivariate time trajectories; ...3) the uncertainty associated to the assignment of a spatial unit to a given cluster on the basis of the above complex features. The last aspect is dealt with by using the fuzzy C-means objective function, based on an appropriate measure of dissimilarity between time trajectories. In order to take into account the spatial nature of the statistical units, a spatial penalization term is added to the above function, depending on a suitable spatial proximity/contiguity matrix. A tuning coefficient takes care of the balance between, on one side, discriminating according to the pattern of the time trajectories and, on the other side, ensuring an approximate spatial homogeneity of the clusters. A technique for determining an optimal value of this coefficient is proposed, based on an appropriate spatial autocorrelation measure. Finally, an application is discussed.
Statistics with fuzzy random variables Colubi, Ana; Coppi, Renato; D’urso, Pierpaolo ...
Metron - International Journal of Statistics,
2007
3
Journal Article
Following the fuzzy approach, the clustering problem concerning a set of fuzzy multivariate time trajectories is addressed. The obtained clusters are characterized by observed typical LR fuzzy time ...trajectories, medoids, belonging to the data set at hand. Two different clustering models are proposed according to the cross-sectional or longitudinal aspects of the time trajectories. An application to air pollution data is carried out.
