Meridional changes in water mass distributions off NW Africa during November 2007/2008

[EN] An optimum multiparameter analysis was applied to a data set for the eastern boundary of the North Atlantic subtropical gyre, gathered during November of two consecutive years and spanning from 16 to 36º N. This data set covers over 20º of latitude with good meridional and zonal resolution over the whole coastal transition zone. The contribution from six water types in the depth range between 100 and 2000 m is solved. In the 100 to 700 m depth range the central waters of southern and northern origin meet abruptly at the Cape Verde Frontal Zone. This front traditionally has been reported to stretch from Cape Blanc, at about 21.5º N, to the Cape Verde Islands, but in our case it penetrates as far as 24º N over the continental slope. South of 21º N latitude we actually find a less saline and more oxygenated variety of South Atlantic Central Water, which we ascribe to less diluted equatorial waters. In the 700 to 1500 m depth range the dominant water type is a diluted form of Antarctic Intermediate Water (AAIW), whose influence smoothly disappears north of the Canary Islands as it is replaced by Mediterranean Water (MW); at latitudes where both water masses coexist, we observe MW offshore while AAIW is found near-shore. North Atlantic Deep Water is the dominating water type below about 1300/1700 m depth south/north of the Canary Islands; this abrupt change in depth suggests the existence of different paths for the deep waters reaching both sides of the archipelago.

A GIS based model for solving the planar Huff problem considering different demand distributions and forbidden regions

[EN] In this paper, we have used Geographical Information Systems (GIS) to solve the planar Huff problem considering different demand distributions and forbidden regions. Most of the papers connected with the competitive location problems consider that the demand is aggregated in a finite set of points. In other few cases, the models suppose that the demand is distributed along the feasible region according to a functional form, mainly a uniform distribution. In this case, in addition to the discrete and uniform demand distributions we have considered that the demand is represented by a population surface model, that is, a raster map where each pixel has associated a value corresponding to the population living in the area that it covers...

A low complexity system based on multiple weighted decision trees for indoor localization

[EN] Indoor position estimation has become an attractive research topic due to growing interest in location-aware services. Nevertheless, satisfying solutions have not been found with the considerations of both accuracy and system complexity. From the perspective of lightweight mobile devices, they are extremely important characteristics, because both the processor power and energy availability are limited. Hence, an indoor localization system with high computational complexity can cause complete battery drain within a few hours. In our research, we use a data mining technique named boosting to develop a localization system based on multiple weighted decision trees to predict the device location, since it has high accuracy and low computational complexity.