One Time User Key: a user-based secret sharing XOR-ed model for multiple user cryptography in distributed systems

The generation of encrypted channels between more than two users is complex, as it is necessary to share information about the key of each user. This problem has been partially solved through the secret sharing mechanism that makes it possible to divide a secret among several participants, so that the secret can be reconstructed by a well-defined part of them. The proposed system represents an extension of this mechanism, since it is designed to be applied systematically: each user has his/her key, through which temporary keys (One Time User Keys) are generated and are used to divide the secret, corresponding to the real encryption key. The system also overcomes the concept of numerical threshold (i.e., at least n participants are required to reconstruct the secret), allowing the definition, for each encryption, of which users can access and which specific groups of users can access. The proposed model can be applied both in distributed user-based contexts and as an extension of cryptographic functions, without impacting the overall security of the system. It addresses some requirements of the European Union Council resolution on encryption and also provides a wide possibility of applications in user-based distributed systems

Microbial risk factors of cardiovascular and cerebrovascular diseases: potential therapeutic options

Infection and inflammation may have a crucial role in the pathogenesis of atherosclerosis. This hypothesis is supported by an increasing number of reports on the interaction between chronic infection, inflammation, and atherogenesis. Assessment of serological and inflammatory markers of infection may be useful adjuncts in identifying those patients who are at a higher risk of developing vascular events, and in whom more aggressive treatments might be warranted

AUTOMATIC POINT CLOUD SEGMENTATION FOR THE DETECTION OF ALTERATIONS ON HISTORICAL BUILDINGS THROUGH AN UNSUPERVISED AND CLUSTERING-BASED MACHINE LEARNING APPROACH

Abstract. The article describes an innovative procedure for the three-dimensional analysis of decay morphologies of ancient buildings, through the application of machine learning methods for the automatic segmentation of point clouds. In the field of Cultural Heritage conservation, photogrammetric data can be exploited, for diagnostic and monitoring support, to recognize different typologies of alterations visible on the masonry surface, starting from colour information. Actually, certain stone and plaster surface pathologies (biological patina, biological colonization, chromatic alterations, spots,…) are typically characterized by chromatic variations. To this purpose, colour-based segmentation with hierarchical clustering has been implemented on colour data of point clouds, considered in the HSV colour-space. In addition, geometry-based segmentation of 3D reconstructions has been performed, in order to identify the main architectural elements (walls, vaults), and to associate them to the detected defects. The proposed workflow has been applied to some ancient buildings' environments, chosen because of their irregularity both in geometrical and colorimetric characteristics

Ensemble consensus: An unsupervised algorithm for anomaly detection in network security data

Unsupervised network traffic monitoring is of paramount importance in cyber security. It allows to detect suspicious events that are defined as non-normal and report or block them. In this work the Anomaly Consensus algorithm for unsupervised network analysis is presented. The algorithm aim is to fuse the three most important anomaly detection techniques for unsupervised detection of suspicious events. Tests are performed against the KDD Cup'99 dataset, one of the most famous supervised datasets for automatic intrusion detection created by DARPA. Accuracies reveal that Anomaly Consensus performs on-par with respect to state-of-the-art supervised learning techniques, ensuring high generalization power also in borderline tests when small amount of data (5%) is used for training and the rest is for validation and testing

Intra-scales energy transfer during the evolution of turbulence in a trapped Bose-Einstein condensate

In turbulence phenomena, including the quantum turbulence in superfluids, an energy flux flows from large to small length scales, composing a cascade of energy. A universal characteristic of turbulent flows is the existence of a range of scales where the energy flux is scale-invariant: this interval of scales is often referred to as inertial region. This property is fundamental as, for instance, in turbulence of classical fluids it characterizes the behavior of statistical features such as spectra and structure functions. Here we show that also in decaying quantum turbulence generated in trapped Bose-Einstein condensates (BECs), intervals of momentum space where the energy flux is constant can be identified. Indeed, we present a procedure to measure the energy flux using both the energy spectrum and the continuity equation. A range of scales where the flux is constant is then determined employing two distinct protocols and in the same range, the momentum distribution measured is consistent with previous work. The successful identification of a region with constant flux in turbulent BECs is a manifestation of the universal character of turbulence in these quantum systems. These measurements pave the way for studies of energy conservation and dissipation in trapped atomic superfluids, and also analogies with the related processes that take place in ordinary fluids.Comment: 7 pages, 5 figure

Using leap motion to investigate the emergence of structure in speech and language

© 2016, The Author(s). In evolutionary linguistics, experiments using artificial signal spaces are being used to investigate the emergenceof speech structure. These signal spaces need to be continuous, non-discretized spaces from which discrete unitsand patterns can emerge. They need to be dissimilar from—but comparable with—the vocal tract, in order tominimize interference from pre-existing linguistic knowledge, while informing us about language. This is a hardbalance to strike. This article outlines a new approach that uses the Leap Motion, an infrared controller that canconvert manual movement in 3d space into sound. The signal space using this approach is more flexible than signalspaces in previous attempts. Further, output data using this approach is simpler to arrange and analyze. Theexperimental interface was built using free, and mostly open- source libraries in Python. We provide our sourcecode for other researchers as open source

Evidence of Strong Quantum Turbulence in Bose Einstein Condensates

By combining experiments and numerical simulations which model precisely the dynamics of shaken atomic Bose-Einstein condensates, we reveal the surprising nature of quantum turbulence in these systems. Unlike the tangles of vortex lines described in the superfluid helium literature, we find that a turbulent atomic condensate contains a mixture of strong fragmented density fluctuations and small random vortex loops which are not homogeneously distributed. This unusual form of quantum turbulence, with its own properties and scaling behaviour, is significantly different from the turbulence which is observed in either classical or other quantum systems, thus posing a new challenge in turbulence research.Comment: 8 pages, 5 figure

Review of post-process optical form metrology for industrial-grade metal additive manufactured parts

The scope of this review is to investigate the main post-process optical form measurement technologies available in industry today and to determine whether they are applicable to industrial-grade metal additive manufactured parts. An in-depth review of the operation of optical three-dimensional form measurement technologies applicable to metal additive manufacturing is presented, with a focus on their fundamental limitations. Looking into the future, some alternative candidate measurement technologies potentially applicable to metal additive manufacturing will be discussed, which either provide higher accuracy than currently available techniques but lack measurement volume, or inversely, which operate in the appropriate measurement volume but are not currently accurate enough to be used for industrial measurement

Extramotor damage is associated with cognition in primary lateral sclerosis patients

Objectives: This is a cross-sectional study aimed at investigating cognitive performances in patients with primary lateral sclerosis (PLS) and using diffusion tensor (DT) magnetic resonance imaging (MRI) to determine the topographical distribution of microstructural white matter (WM) damage in patients with or without cognitive deficits. Methods: DT MRI scans were obtained from 21 PLS patients and 35 age- and sex-matched healthy controls. All PLS patients underwent a comprehensive neuropsychological battery. Tract-based-spatial-statistics (TBSS) was used to perform a wholebrain voxel-wise analysis of fractional anisotropy (FA), axial, radial (radD) and mean diffusivity (MD). Results: Ten PLS patients had abnormal scores in at least one neuropsychological test (PLS with cognitive deficits, PLS-cd). Compared with healthy controls and cognitively unimpaired PLS patients (PLS-cu), PLS-cd cases showed decreased FA and increased MD and radD in the corticospinal tract (CST), corpus callosum, brainstem, anterior limb of internal capsule, superior and inferior longitudinal fasciculi, fornix, thalamic radiations, and parietal lobes, bilaterally. Compared with healthy controls, PLS-cd patients showed further decreased FA and increased radD in the cerebellar WM, bilaterally. Compared with controls, PLS-cu patients showed decreased FA in the mid-body of corpus callosum. In PLS, executive and language test scores correlated with WM damage. Conclusions: This is the first study evaluating the relationship between cognitive performance and WM tract damage in PLS patients. PLS can be associated with a multi-domain cognitive impairment. WM damage to interhemispheric, limbic and major associative WM tracts seem to be the structural correlate of cognitive abnormalities in these patients