In Mobile Unattended Wireless Sensor Networks (MUWSNs), nodes sense the environment and store the acquired data until the arrival of a trusted data sink. MUWSNs, other than being a reference model for an increasing number of military and civilian applications, also capture a few important characteristics of emerging computing paradigms like Participatory Sensing (PS). In this paper, we start by identifying the main features and issues of MUWSNs, revising the related work in the area and highlighting their shortcomings.

We review a recently proposed approach to the computation of the E-entropy of a given signal based on the exit-time statistics, i.e., one codes the signal by looking at the instants when the fluctuations are larger than a given threshold, epsilon. Moreover, we show how the exit-times statistics, when applied to experimental turbulent data, is able to highlight the intermediate-dissipative-range of turbulent fluctuations. (C) 2000 Elsevier Science B.V. All rights reserved.

In a computer-aided system for skin cancer diagnosis, hair removal is one of the main challenges to face before applying a process of automatic skin lesion segmentation and classification. In this paper, we propose a straightforward method to detect and remove hair from dermoscopic images. Preliminarily, the regions to consider as candidate hair regions and the border/corner components located on the image frame are automatically detected. Then, the hair regions are determined using information regarding the saliency, shape and image colors.

In a typical secure communication system, messages undergo two different encodings: an error-correcting code is applied at the physical layer to ensure correct reception by the addressee (integrity), while at an upper protocol layer cryptography is leveraged to enforce secrecy with respect to eavesdroppers (confidentiality).