Distributed archive and single access system for accelerometric event data : a NERIES initiative

We developed a common access facility to homogeneously formatted accelerometric event data and to the corresponding sheet of ground motion parameters. This paper is focused on the description of the technical development of the accelerometric data server and the link with the accelerometric data explorer. The server is the third node of the 3-tier architecture of the distributed archive system for accelerometric data. The server is the link between the data users and the accelero- metric data portal. The server follows three main steps: (1) Reading and analysis of the end-user request; (2) Processing and converting data; and (3) Archiving and updating the accelerometric data explorer. This paper presents the description of the data server and the data explorer for accessing data

XSS-FP: Browser Fingerprinting using HTML Parser Quirks

There are many scenarios in which inferring the type of a client browser is desirable, for instance to fight against session stealing. This is known as browser fingerprinting. This paper presents and evaluates a novel fingerprinting technique to determine the exact nature (browser type and version, eg Firefox 15) of a web-browser, exploiting HTML parser quirks exercised through XSS. Our experiments show that the exact version of a web browser can be determined with 71% of accuracy, and that only 6 tests are sufficient to quickly determine the exact family a web browser belongs to

Data mining in bioinformatics using Weka

The Weka machine learning workbench provides a general purpose environment for automatic classification, regression, clustering and feature selection-common data mining problems in bioinformatics research. It contains an extensive collection of machine learning algorithms and data exploration and the experimental comparison of different machine learning techniques on the same problem. Weka can process data given in the form of a single relational table. Its main objectives are to (a) assist users in extracting useful information from data and (b) enable them to easily identify a suitable algorithm for generating an accurate predictive model from it

Herschel Survey of the Palomar-Green QSOs at Low Redshift

We investigate the global cold dust properties of 85 nearby (z < 0.5) QSOs, chosen from the Palomar-Green sample of optically luminous quasars. We determine their infrared spectral energy distributions and estimate their rest-frame luminosities by combining Herschel data from 70 to 500 microns with near-infrared and mid-infrared measurements from the Two Micron All Sky Survey (2MASS) and the Wide-Field Infrared Survey Explorer (WISE). In most sources the far-infrared (FIR) emission can be attributed to thermally heated dust. Single temperature modified black body fits to the FIR photometry give an average dust temperature for the sample of 33~K, with a standard deviation of 8~K, and an average dust mass of 7E6 Solar Masses with a standard deviation of 9E6 Solar Masses. Estimates of star-formation that are based on the FIR continuum emission correlate with those based on the 11.3 microns PAH feature, however, the star-formation rates estimated from the FIR continuum are higher than those estimated from the 11.3 microns PAH emission. We attribute this result to a variety of factors including the possible destruction of the PAHs and that, in some sources, a fraction of the FIR originates from dust heated by the active galactic nucleus and by old stars.Comment: accepted for publication in ApJ