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München, Germany

Fritz W.,Leibniz Supercomputing Center | Hanka O.,Ludwig Maximilians University of Munich
9th International Conference on Networks, ICN 2010 | Year: 2010

Security is an essential business requirement towards communication networks and will play a major role in future internet concepts. Many researchers see security functionality as an integral part of a new architecture, which should be thought of as soon as the conceptional phase of any proposal. In this paper we discuss suggested security mechanisms for the so called Locator/Identifier-Split and outline problematic issues found in those concepts. Based on these observations, we propose a security architecture using smart cards, which allows for lifelong assigned identifiers and is able to handle key replacement and revocation. Furthermore, we discuss the aspect of initial bootstrap and how to integrate devices with very low computational power like sensors. © 2010 IEEE. Source


Leong S.H.,Leibniz Supercomputing Center | Frank A.,Leibniz Supercomputing Center | Kranzlmuller D.,Leibniz Supercomputing Center | Kranzlmuller D.,Ludwig Maximilians University of Munich
Procedia Computer Science | Year: 2013

Urgent computing enables responsible authorities to make educated decisions by supporting the computations of simulated predictions of time critical events. Unfortunately, most domains of science cannot afford dedicated resources for their urgent computing problems. As a solution, exploiting existing e-Infrastructures is invaluable for many problems if the wide array of available resources in today's e-Infrastructures can be utilised. In this paper, we focus on rarely occurring events that are best suited for urgent computations on existing HPC, Grid and Cloud e-Infrastructures. Since e-Infrastructures are meant to serve more than just one community of users, they have inherent characteristics that have to be modified or adapted in order to enable them effectively for urgent computing. We hope to demonstrate that there are many existing and on-going developments that can be leveraged to prepare existing e-Infrastructures for urgent computing. © 2013 The Authors. Published by Elsevier B.V. Source


Jamitzky F.,Leibniz Supercomputing Center | Stark R.W.,Ludwig Maximilians University of Munich
Ultramicroscopy | Year: 2010

From a mathematical point of view, the atomic force microscope (AFM) belongs to a special class of continuous time dynamical systems with intermittent impact collisions. Discontinuities of the velocity result from the collisions of the tip with the surface. Transition to chaos in non-linear systems can occur via the following four routes: bifurcation cascade, crisis, quasi-periodicity, and intermittency. For the AFM period doubling and period-adding cascades are well established. Other routes into chaos, however, also may play an important role. Time series data of a dynamic AFM experiment indicates a chaotic mode that is related to the intermittency route into chaos. The observed intermittency is characterized as a type III intermittency. Understanding the dynamics of the system will help improve the overall system performance by keeping the operation parameters of dynamic AFM in a range, where chaos can be avoided or at least controlled. © 2010 Elsevier B.V. Source


Bernau C.,Leibniz Supercomputing Center | Riester M.,Dana-Farber Cancer Institute | Riester M.,Harvard University | Boulesteix A.-L.,Biometry and Epidemiology | And 6 more authors.
Bioinformatics | Year: 2014

Motivation: Numerous competing algorithms for prediction in high-dimensional settings have been developed in the statistical and machine-learning literature. Learning algorithms and the prediction models they generate are typically evaluated on the basis of cross-validation error estimates in a few exemplary datasets. However, in most applications, the ultimate goal of prediction modeling is to provide accurate predictions for independent samples obtained in different settings. Cross-validation within exemplary datasets may not adequately reflect performance in the broader application context. Methods: We develop and implement a systematic approach to 'cross-study validation', to replace or supplement conventional cross-validation when evaluating high-dimensional prediction models in independent datasets. We illustrate it via simulations and in a collection of eight estrogen-receptor positive breast cancer microarray gene-expression datasets, where the objective is predicting distant metastasis-free survival (DMFS). We computed the C-index for all pairwise combinations of training and validation datasets. We evaluate several alternatives for summarizing the pairwise validation statistics, and compare these to conventional cross-validation. Results: Our data-driven simulations and our application to survival prediction with eight breast cancer microarray datasets, suggest that standard cross-validation produces inflated discrimination accuracy for all algorithms considered, when compared to cross-study validation. Furthermore, the ranking of learning algorithms differs, suggesting that algorithms performing best in cross-validation may be suboptimal when evaluated through independent validation. © 2014 The Author. Published by Oxford University Press. All rights reserved. Source


Gong J.,Ludwig Maximilians University of Munich | Wei T.,Ludwig Maximilians University of Munich | Stark R.W.,Ludwig Maximilians University of Munich | Jamitzky F.,Ludwig Maximilians University of Munich | And 6 more authors.
Journal of Structural Biology | Year: 2010

Toll-like receptors (TLRs) belong to the Toll-like receptor/interleukin-1 receptor (TLR/IL-1R) superfamily which is defined by a common cytoplasmic Toll/interleukin-1 receptor (TIR) domain. TLRs recognize pathogen-associated molecular patterns and initiate an intracellular kinase cascade to trigger an immediate defensive response. SIGIRR (single immunoglobulin interleukin-1 receptor-related molecule), another member of the TLR/IL-1R superfamily, acts as a negative regulator of MyD88-dependent TLR signaling. It attenuates the recruitment of MyD88 adaptors to the receptors with its intracellular TIR domain. Thus, SIGIRR is a highly important molecule for the therapy of autoimmune diseases caused by TLRs. So far, the structural mechanism of interactions between SIGIRR, TLRs and adaptor molecules is unclear. To develop a working hypothesis for this interaction, we constructed three-dimensional models for the TIR domains of TLR4, TLR7, MyD88 and SIGIRR based on computational modeling. Through protein-protein docking analysis, we developed models of essential complexes involved in the TLR4 and 7 signaling and the SIGIRR inhibiting processes. We suggest that SIGIRR may exert its inhibitory effect through blocking the molecular interface of TLR4, TLR7 and the MyD88 adaptor mainly via its BB-loop region. © 2009 Elsevier Inc. All rights reserved. Source

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