@article{StrolloParolaiBindietal.2012, author = {Strollo, Angelo and Parolai, Stefano and Bindi, Dino and Chiauzzi, Leonardo and Pagliuca, Rossella and Mucciarelli, Marco and Zschau, Jochen}, title = {Microzonation of Potenza (Southern Italy) in terms of spectral intensity ratio using joint analysis of earthquakes and ambient noise}, series = {Bulletin of earthquake engineering : official publication of the European Association for Earthquake Engineering}, volume = {10}, journal = {Bulletin of earthquake engineering : official publication of the European Association for Earthquake Engineering}, number = {2}, publisher = {Springer}, address = {Dordrecht}, issn = {1570-761X}, doi = {10.1007/s10518-011-9256-4}, pages = {493 -- 516}, year = {2012}, abstract = {A temporary seismic network composed of 11 stations was installed in the city of Potenza (Southern Italy) to record local and regional seismicity within the context of a national project funded by the Italian Department of Civil Protection (DPC). Some stations were moved after a certain time in order to increase the number of measurement points, leading to a total of 14 sites within the city by the end of the experiment. Recordings from 26 local earthquakes (M-l 2.2-3.8 ) were analyzed to compute the site responses at the 14 sites by applying both reference and non-reference site techniques. Furthermore, the Spectral Intensity (SI) for each local earthquake, as well as their ratios with respect to the values obtained at a reference site, were also calculated. In addition, a field survey of 233 single station noise measurements within the city was carried out to increase the information available at localities different from the 14 monitoring sites. By using the results of the correlation analysis between the horizontal-to-vertical spectral ratios computed from noise recordings (NHV) at the 14 selected sites and those derived by the single station noise measurements within the town as a proxy, the spectral intensity correction factors for site amplification obtained from earthquake analysis were extended to the entire city area. This procedure allowed us to provide a microzonation map of the urban area that can be directly used when calculating risk scenarios for civil defence purposes. The amplification factors estimated following this approach show values increasing along the main valley toward east where the detrital and alluvial complexes reach their maximum thickness.}, language = {en} } @article{RoschkeChengMeinel2013, author = {Roschke, Sebastian and Cheng, Feng and Meinel, Christoph}, title = {High-quality attack graph-based IDS correlation}, series = {Logic journal of the IGPL}, volume = {21}, journal = {Logic journal of the IGPL}, number = {4}, publisher = {Oxford Univ. Press}, address = {Oxford}, issn = {1367-0751}, doi = {10.1093/jigpal/jzs034}, pages = {571 -- 591}, year = {2013}, abstract = {Intrusion Detection Systems are widely deployed in computer networks. As modern attacks are getting more sophisticated and the number of sensors and network nodes grow, the problem of false positives and alert analysis becomes more difficult to solve. Alert correlation was proposed to analyse alerts and to decrease false positives. Knowledge about the target system or environment is usually necessary for efficient alert correlation. For representing the environment information as well as potential exploits, the existing vulnerabilities and their Attack Graph (AG) is used. It is useful for networks to generate an AG and to organize certain vulnerabilities in a reasonable way. In this article, a correlation algorithm based on AGs is designed that is capable of detecting multiple attack scenarios for forensic analysis. It can be parameterized to adjust the robustness and accuracy. A formal model of the algorithm is presented and an implementation is tested to analyse the different parameters on a real set of alerts from a local network. To improve the speed of the algorithm, a multi-core version is proposed and a HMM-supported version can be used to further improve the quality. The parallel implementation is tested on a multi-core correlation platform, using CPUs and GPUs.}, language = {en} } @article{KuehnScherbaum2015, author = {K{\"u}hn, Nico M. and Scherbaum, Frank}, title = {Ground-motion prediction model building: a multilevel approach}, series = {Bulletin of earthquake engineering : official publication of the European Association for Earthquake Engineering}, volume = {13}, journal = {Bulletin of earthquake engineering : official publication of the European Association for Earthquake Engineering}, number = {9}, publisher = {Springer}, address = {Dordrecht}, issn = {1570-761X}, doi = {10.1007/s10518-015-9732-3}, pages = {2481 -- 2491}, year = {2015}, abstract = {A Bayesian ground-motion model is presented that directly estimates the coefficients of the model and the correlation between different ground-motion parameters of interest. The model is developed as a multi-level model with levels for earthquake, station and record terms. This separation allows to estimate residuals for each level and thus the estimation of the associated aleatory variability. In particular, the usually estimated within-event variability is split into a between-station and between-record variability. In addition, the covariance structure between different ground-motion parameters of interest is estimated for each level, i.e. directly the between-event, between-station and between-record correlation coefficients are available. All parameters of the model are estimated via Bayesian inference, which allows to assess their epistemic uncertainty in a principled way. The model is developed using a recently compiled European strong-motion database. The target variables are peak ground velocity, peak ground acceleration and spectral acceleration at eight oscillator periods. The model performs well with respect to its residuals, and is similar to other ground-motion models using the same underlying database. The correlation coefficients are similar to those estimated for other parts of the world, with nearby periods having a high correlation. The between-station, between-event and between-record correlations follow generally a similar trend.}, language = {en} } @article{ReschkeKunzLaepple2018, author = {Reschke, Maria and Kunz, Torben and Laepple, Thomas}, title = {Comparing methods for analysing time scale dependent correlations in irregularly sampled time series data}, series = {Computers \& geosciences : an international journal devoted to the publication of papers on all aspects of geocomputation and to the distribution of computer programs and test data sets ; an official journal of the International Association for Mathematical Geology}, volume = {123}, journal = {Computers \& geosciences : an international journal devoted to the publication of papers on all aspects of geocomputation and to the distribution of computer programs and test data sets ; an official journal of the International Association for Mathematical Geology}, publisher = {Elsevier}, address = {Oxford}, issn = {0098-3004}, doi = {10.1016/j.cageo.2018.11.009}, pages = {65 -- 72}, year = {2018}, abstract = {Time series derived from paleoclimate archives are often irregularly sampled in time and thus not analysable using standard statistical methods such as correlation analyses. Although measures for the similarity between time series have been proposed for irregular time series, they do not account for the time scale dependency of the relationship. Stochastically distributed temporal sampling irregularities act qualitatively as a low-pass filter reducing the influence of fast variations from frequencies higher than about 0.5 (Delta t(max))(-1) , where Delta t(max), is the maximum time interval between observations. This may lead to overestimated correlations if the true correlation increases with time scale. Typically, correlations are underestimated due to a non-simultaneous sampling of time series. Here, we investigated different techniques to estimate time scale dependent correlations of weakly irregularly sampled time series, with a particular focus on different resampling methods and filters of varying complexity. The methods were tested on ensembles of synthetic time series that mimic the characteristics of Holocene marine sediment temperature proxy records. We found that a linear interpolation of the irregular time series onto a regular grid, followed by a simple Gaussian filter was the best approach to deal with the irregularity and account for the time scale dependence. This approach had both, minimal filter artefacts, particularly on short time scales, and a minimal loss of information due to filter length.}, language = {en} }