Groundwater use in Spain: an overview in light of the EU Water Framework Directive

In semi-arid regions, aquifers provide a series of practical advantages that make them preferential sources of water supply. In Spain, groundwater meets about one-fifth of the total water demand and is used to irrigate over one-third of the total irrigated land. This article examines groundwater use in Spain from the perspective of the EU Water Framework Directive. Analysis of different sector uses suggests that core problems (and solutions) related to groundwater lie in agricultural uses and that the Directive's environmental requirements remain distant from reality on the ground, where economic, political and social reasons prevail on legal obligations set by national and supranational authorities.     

A flexible FPGA implementation for illuminance–reflectance video enhancement

Digital cameras, new generation phones, commercial TV sets and, in general, all modern devices for image acquisition and visualization can benefit from algorithms for image enhancement suitable to work in real time and preferably with limited power consumption. Among the various methods described in the scientific literature, Retinex-based approaches are able to provide very good performances, but unfortunately they typically require a high computational effort. In this article, we propose a flexible and effective architecture for the real-time enhancement of video frames, suitable to be implemented in a single FPGA device. The video enhancement algorithm is based on a modified version of the Retinex approach. This method, developed to control the dynamic range of poorly illuminated images while preserving the visual details, has been improved by the adoption of a new model to perform illuminance estimation. The video enhancement parameters are controlled in real time through an embedded microprocessor which makes the system able to modify its behavior according to the characteristics of the input images, and using information about the surrounding light conditions.     

Proportional and double imitation rules for spectrum access in cognitive radio networks

In this paper, we tackle the problem of opportunistic spectrum access in large-scale cognitive radio networks, where the unlicensed Secondary Users (SUs) access the frequency channels partially occupied by the licensed Primary Users (PUs). Each channel is characterized by an availability probability unknown to the SUs. We apply population game theory to model the spectrum access problem and develop distributed spectrum access policies based on imitation, a behavior rule widely applied in human societies consisting of imitating successful behaviors. We develop two imitation-based spectrum access policies based on the basic Proportional Imitation (PI) rule and the more advanced Double Imitation (DI) rule given that a SU can only imitate the other SUs operating on the same channel. A systematic theoretical analysis is presented for both policies on the induced imitation dynamics and the convergence properties of the proposed policies to the Nash equilibrium. Simple and natural, the proposed imitation-based spectrum access policies can be implemented distributedly based on solely local interactions and thus is especially suited in decentralized adaptive learning environments as cognitive radio networks.     

Shape from defocus via diffusion

Defocus can be modeled as a diffusion process and represented mathematically using the heat equation, where image blur corresponds to the diffusion of heat. This analogy can be extended to non-planar scenes by allowing a space-varying diffusion coefficient. The inverse problem of reconstructing 3-D structure from blurred images corresponds to an "inverse diffusion" that is notoriously ill-posed. We show how to bypass this problem by using the notion of relative blur. Given two images, within each neighborhood, the amount of diffusion necessary to transform the sharper image into the blurrier one depends on the depth of the scene. This can be used to devise a global algorithm to estimate the depth profile of the scene without recovering the deblurred image, using only forward diffusion.     

Reducing false positives in anomaly detectors through fuzzy alert aggregation

In this paper we focus on the aggregation of IDS alerts, an important component of the alert fusion process. We exploit fuzzy measures and fuzzy sets to design simple and robust alert aggregation algorithms. Exploiting fuzzy sets, we are able to robustly state whether or not two alerts are “close in time”, dealing with noisy and delayed detections. A performance metric for the evaluation of fusion systems is also proposed. Finally, we evaluate the fusion method with alert streams from anomaly-based IDS.     

Multidimensional analogs of the kendall equation for priority queueing systems: computational aspects

An analogy between celebrated Kendall equation for busy periods in the system M|GI|1 and analytical results for busy periods in the priority systemsM _r |GI _r |1 is drawn. These results can be viewed as generalizations of the functional Kendall equation. The methodology and algorithms of numerical solution of recurrent functional equations which appear in the analysis of such queueing systems are developed. The efficiency of the algorithms is achieved by acceleration of the numerical procedure of solving the classical Kendall equation. An algorithm of calculation of the system workload coefficient calculation is given.     

The anti-reflective algebra: structural and computational analysis with application to image deblurring and denoising

Anti-reflective (AR) boundary conditions (BC) have been introduced recently in connection with fast deblurring algorithms, both in the case of signals and images. Here we extend such BCs to d dimensions (d ≥ 1) and we study in detail the algebra induced by the AR-BCs, with strongly symmetric point spread functions (PSF), both from a structural and computational point of view. The use of the re-blurring idea and the computational features of the AR-algebra allow us to apply Tikhonov-like techniques within O(n ^d log(n)) arithmetic operations, where n ^d is the number of pixels of the reconstructed object. Extensive numerical experimentation concerning 2D images and strongly symmetric PSFs confirms the effectiveness of our proposal.