Confidentiality and availability issues in mobile unattended wireless sensor networks

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.

3-D Ground-Based Imaging Radar Based on C-Band Cross-MIMO Array and Tensor Compressive Sensing

We designed a ground-based radar system with a C-band 2-D cross multiple input multiple output (MIMO) array for 3-D imaging and displacement estimation purposes. For this system, we developed a far-field pseudo-polar image format algorithm using pseudo-polar spherical coordinate. The use of a tensor compressive sensing technique allows to focus under-sampled raw data and to optimize the data acquisition time and memory usage.

Accuracies of Soil Moisture Estimations Using a Semi-Empirical Model over Bare Soil Agricultural Croplands from Sentinel-1 SAR Data

This study describes a semi-empirical model developed to estimate volumetric soil moisture (<mml:semantics>theta v</mml:semantics>) in bare soils during the dry season (March-May) using C-band (5.42 GHz) synthetic aperture radar (SAR) imagery acquired from the Sentinel-1 European satellite platform at a 20 m spatial resolution. The semi-empirical model was developed using backscatter coefficient (<mml:semantics>sigma degrees dB</mml:semantics>) and in situ soil moisture collected from Siruguppa taluk (sub-district) in the Karnataka state of India.

A tight relation between series-parallel graphs and bipartite distance hereditary graphs

Bandelt and Mulder's structural characterization of bipartite distance hereditary graphs 16 asserts that such graphs can be built inductively starting from a single vertex and by re- 17 peatedly adding either pendant vertices or twins (i.e., vertices with the same neighborhood 18 as an existing one). Dirac and Duffin's structural characterization of 2-connected series- 19 parallel graphs asserts that such graphs can be built inductively starting from a single edge 20 by adding either edges in series or in parallel.

Cryptanalysis on GPUs with the Cube Attack: Design, Optimization and Performances Gains

The cube attack is a flexible cryptanalysis technique, with a simple and fascinating theoretical implant. It combines offline exhaustive searches over selected tweakable public/IV bits (the sides of the "cube"), with an online key-recovery phase. Although virtually applicable to any cipher, and generally praised by the research community, the real potential of the attack is still in question, and no implementation so far succeeded in breaking a real-world strong cipher. In this paper, we present, validate and analyze the first thorough implementation of the cube attack on a GPU cluster.

Spectral Analysis of Saddle-point Matrices from Optimization problems with Elliptic PDE Constraints

The main focus of this paper is the characterization and exploitation of the asymptotic spectrum of the saddle--point matrix sequences arising from the discretization of optimization problems constrained by elliptic partial differential equations. They uncover the existence of an hidden structure in these matrix sequences, namely, they show that these are indeed an example of Generalized Locally Toeplitz (GLT) sequences.

InSAR Meteorology: High-Resolution Geodetic Data Can Increase Atmospheric Predictability

The present study assesses the added value of high-resolution maps of precipitable water vapor, computed from synthetic aperture radar interferograms , in short-range atmospheric predictability. A large set of images, in different weather conditions, produced by Sentinel-1A in a very well monitored region near the Appalachian Mountains, are assimilated by the Weather Research and Forecast (WRF) model.