@inproceedings{15910, author = {{Engelbertz, Nils and Mladenov, Vladislav and Somorovsky, Juraj and Herring, David and Erinola, Nurullah and Schwenk, Jörg}}, booktitle = {{Open Identity Summit 2019}}, editor = {{Roßnagel, Heiko and Wagner, Sven and Hühnlein, Detlef}}, pages = {{ 95--106 }}, publisher = {{Gesellschaft für Informatik, Bonn}}, title = {{{Security Analysis of XAdES Validation in the CEF Digital Signature Services (DSS)}}}, year = {{2019}}, } @misc{15920, abstract = {{Secure hardware design is the most important aspect to be considered in addition to functional correctness. Achieving hardware security in today’s globalized Integrated Cir- cuit(IC) supply chain is a challenging task. One solution that is widely considered to help achieve secure hardware designs is Information Flow Tracking(IFT). It provides an ap- proach to verify that the systems adhere to security properties either by static verification during design phase or dynamic checking during runtime. Proof-Carrying Hardware(PCH) is an approach to verify a functional design prior to using it in hardware. It is a two-party verification approach, where the target party, the consumer requests new functionalities with pre-defined properties to the producer. In response, the producer designs the IP (Intellectual Property) cores with the requested functionalities that adhere to the consumer-defined properties. The producer provides the IP cores and a proof certificate combined into a proof-carrying bitstream to the consumer to verify it. If the verification is successful, the consumer can use the IP cores in his hardware. In essence, the consumer can only run verified IP cores. Correctly applied, PCH techniques can help consumers to defend against many unintentional modifications and malicious alterations of the modules they receive. There are numerous published examples of how to use PCH to detect any change in the functionality of a circuit, i.e., pairing a PCH approach with functional equivalence checking for combinational or sequential circuits. For non-functional properties, since opening new covert channels to leak secret information from secure circuits is a viable attack vector for hardware trojans, i.e., intentionally added malicious circuitry, IFT technique is employed to make sure that secret/untrusted information never reaches any unclassified/trusted outputs. This master thesis aims to explore the possibility of adapting Information Flow Tracking into a Proof-Carrying Hardware scenario. It aims to create a method that combines Infor- mation Flow Tracking(IFT) with a PCH approach at bitstream level enabling consumers to validate the trustworthiness of a module’s information flow without the computational costs of a complete flow analysis.}}, author = {{Keerthipati, Monica}}, publisher = {{Universität Paderborn}}, title = {{{A Bitstream-Level Proof-Carrying Hardware Technique for Information Flow Tracking}}}, year = {{2019}}, } @inproceedings{15921, abstract = {{Ranking plays a central role in a large number of applications driven by RDF knowledge graphs. Over the last years, many popular RDF knowledge graphs have grown so large that rankings for the facts they contain cannot be computed directly using the currently common 64-bit platforms. In this paper, we tackle two problems: Computing ranks on such large knowledge bases efficiently and incrementally. First, we present D-HARE, a distributed approach for computing ranks on very large knowledge graphs. D-HARE assumes the random surfer model and relies on data partitioning to compute matrix multiplications and transpositions on disk for matrices of arbitrary size. Moreover, the data partitioning underlying D-HARE allows the execution of most of its steps in parallel. As very large knowledge graphs are often updated periodically, we tackle the incremental computation of ranks on large knowledge bases as a second problem. We address this problem by presenting I-HARE, an approximation technique for calculating the overall ranking scores of a knowledge without the need to recalculate the ranking from scratch at each new revision. We evaluate our approaches by calculating ranks on the 3 × 10^9 and 2.4 × 10^9 triples from Wikidata resp. LinkedGeoData. Our evaluation demonstrates that D-HARE is the first holistic approach for computing ranks on very large RDF knowledge graphs. In addition, our incremental approach achieves a root mean squared error of less than 10E−7 in the best case. Both D-HARE and I-HARE are open-source and are available at: https://github.com/dice-group/incrementalHARE. }}, author = {{Desouki, Abdelmoneim Amer and Röder, Michael and Ngonga Ngomo, Axel-Cyrille}}, booktitle = {{Proceedings of the 30th ACM Conference on Hypertext and Social Media - HT '19}}, isbn = {{9781450368858}}, keywords = {{Knowledge Graphs, Ranking, RDF}}, pages = {{163--171}}, publisher = {{ACM}}, title = {{{Ranking on Very Large Knowledge Graphs}}}, doi = {{10.1145/3342220.3343660}}, year = {{2019}}, } @inproceedings{14568, author = {{Heindorf, Stefan and Scholten, Yan and Engels, Gregor and Potthast, Martin}}, booktitle = {{INFORMATIK}}, pages = {{289--290}}, title = {{{Debiasing Vandalism Detection Models at Wikidata (Extended Abstract)}}}, doi = {{10.18420/inf2019_48}}, year = {{2019}}, } @article{14817, author = {{Sommer, Christoph and Basagni, Stefano}}, issn = {{1570-8705}}, journal = {{Ad Hoc Networks}}, title = {{{Advances and novel applications of mobile wireless networking}}}, doi = {{10.1016/j.adhoc.2019.101975}}, year = {{2019}}, } @inproceedings{14819, author = {{Heinovski, Julian and Stratmann, Lukas and Buse, Dominik S. and Klingler, Florian and Franke, Mario and Oczko, Marie-Christin H. and Sommer, Christoph and Scharlau, Ingrid and Dressler, Falko}}, booktitle = {{2019 IEEE 20th International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM)}}, isbn = {{9781728102702}}, title = {{{Modeling Cycling Behavior to Improve Bicyclists' Safety at Intersections - A Networking Perspective}}}, doi = {{10.1109/wowmom.2019.8793008}}, year = {{2019}}, } @article{14821, author = {{Seipelt, Agnes Regina}}, isbn = {{978-3-96233-182-5}}, journal = {{Weberiana}}, keywords = {{Weber, Wien, Zensur}}, pages = {{107–161}}, publisher = {{Allitera}}, title = {{{Aufführungs- und zensurbedingte Veränderungen im Wiener Manuskript der Freischütz-Erstaufführung 1821 in Wien}}}, volume = {{29}}, year = {{2019}}, } @inproceedings{14822, abstract = {{Multi-talker speech and moving speakers still pose a significant challenge to automatic speech recognition systems. Assuming an enrollment utterance of the target speakeris available, the so-called SpeakerBeam concept has been recently proposed to extract the target speaker from a speech mixture. If multi-channel input is available, spatial properties of the speaker can be exploited to support the source extraction. In this contribution we investigate different approaches to exploit such spatial information. In particular, we are interested in the question, how useful this information is if the target speaker changes his/her position. To this end, we present a SpeakerBeam-based source extraction network that is adapted to work on moving speakers by recursively updating the beamformer coefficients. Experimental results are presented on two data sets, one with articially created room impulse responses, and one with real room impulse responses and noise recorded in a conference room. Interestingly, spatial features turn out to be advantageous even if the speaker position changes.}}, author = {{Heitkaemper, Jens and Feher, Thomas and Freitag, Michael and Haeb-Umbach, Reinhold}}, booktitle = {{International Conference on Statistical Language and Speech Processing 2019, Ljubljana, Slovenia}}, title = {{{A Study on Online Source Extraction in the Presence of Changing Speaker Positions}}}, year = {{2019}}, } @inproceedings{14824, abstract = {{This paper deals with multi-channel speech recognition in scenarios with multiple speakers. Recently, the spectral characteristics of a target speaker, extracted from an adaptation utterance, have been used to guide a neural network mask estimator to focus on that speaker. In this work we present two variants of speakeraware neural networks, which exploit both spectral and spatial information to allow better discrimination between target and interfering speakers. Thus, we introduce either a spatial preprocessing prior to the mask estimation or a spatial plus spectral speaker characterization block whose output is directly fed into the neural mask estimator. The target speaker’s spectral and spatial signature is extracted from an adaptation utterance recorded at the beginning of a session. We further adapt the architecture for low-latency processing by means of block-online beamforming that recursively updates the signal statistics. Experimental results show that the additional spatial information clearly improves source extraction, in particular in the same-gender case, and that our proposal achieves state-of-the-art performance in terms of distortion reduction and recognition accuracy.}}, author = {{Martin-Donas, Juan M. and Heitkaemper, Jens and Haeb-Umbach, Reinhold and Gomez, Angel M. and Peinado, Antonio M.}}, booktitle = {{INTERSPEECH 2019, Graz, Austria}}, title = {{{Multi-Channel Block-Online Source Extraction based on Utterance Adaptation}}}, year = {{2019}}, } @inproceedings{14826, abstract = {{In this paper, we present Hitachi and Paderborn University’s joint effort for automatic speech recognition (ASR) in a dinner party scenario. The main challenges of ASR systems for dinner party recordings obtained by multiple microphone arrays are (1) heavy speech overlaps, (2) severe noise and reverberation, (3) very natural onversational content, and possibly (4) insufficient training data. As an example of a dinner party scenario, we have chosen the data presented during the CHiME-5 speech recognition challenge, where the baseline ASR had a 73.3% word error rate (WER), and even the best performing system at the CHiME-5 challenge had a 46.1% WER. We extensively investigated a combination of the guided source separation-based speech enhancement technique and an already proposed strong ASR backend and found that a tight combination of these techniques provided substantial accuracy improvements. Our final system achieved WERs of 39.94% and 41.64% for the development and evaluation data, respectively, both of which are the best published results for the dataset. We also investigated with additional training data on the official small data in the CHiME-5 corpus to assess the intrinsic difficulty of this ASR task.}}, author = {{Kanda, Naoyuki and Boeddeker, Christoph and Heitkaemper, Jens and Fujita, Yusuke and Horiguchi, Shota and Haeb-Umbach, Reinhold}}, booktitle = {{INTERSPEECH 2019, Graz, Austria}}, title = {{{Guided Source Separation Meets a Strong ASR Backend: Hitachi/Paderborn University Joint Investigation for Dinner Party ASR}}}, year = {{2019}}, } @inbook{14828, author = {{Seipelt, Agnes Regina and Klugseder, Robert}}, booktitle = {{Musik im Zusammenhang: Festschrift Peter Revers zum 65. Geburtstag}}, editor = {{Aringer, Klaus and Utz, Christian and Wozonig, Thomas}}, isbn = {{978-3-99012-553-3}}, pages = {{69–87}}, publisher = {{Hollitzer}}, title = {{{Digitale Musikanalyse auf Grundlage von MEI-codierten Daten}}}, year = {{2019}}, } @proceedings{14829, editor = {{Scheideler, Christian and Berenbrink, Petra}}, isbn = {{978-1-4503-6184-2}}, publisher = {{ACM}}, title = {{{The 31st ACM Symposium on Parallelism in Algorithms and Architectures, SPAA 2019, Phoenix, AZ, USA, June 22-24, 2019}}}, doi = {{10.1145/3323165}}, year = {{2019}}, } @article{14830, author = {{Gmyr, Robert and Lefevre, Jonas and Scheideler, Christian}}, journal = {{Theory Comput. Syst.}}, number = {{2}}, pages = {{177--199}}, title = {{{Self-Stabilizing Metric Graphs}}}, doi = {{10.1007/s00224-017-9823-4}}, volume = {{63}}, year = {{2019}}, } @misc{14831, author = {{Sabu, Nithin S.}}, publisher = {{Paderborn University}}, title = {{{FPGA Acceleration of String Search Techniques in Huge Data Sets}}}, year = {{2019}}, } @phdthesis{14849, author = {{Vaz, Gavin Francis}}, publisher = {{Universität Paderborn}}, title = {{{Using Just-in-Time Code Generation to Transparently Accelerate Applications in Heterogeneous Systems}}}, year = {{2019}}, } @phdthesis{14851, author = {{Mäcker, Alexander}}, title = {{{On Scheduling with Setup Times}}}, doi = {{10.17619/UNIPB/1-828}}, year = {{2019}}, } @inproceedings{14852, abstract = {{In a variety of industrial applications, liquids are atomized to produce aerosols for further processing. Example applications are the coating of surfaces with paints, the application of ultra-thin adhesive layers and the atomization of fuels for the production of combustible dispersions. In this publication different atomizing principles (standing-wave, capillary-wave, vibrating-mesh) are examined and discussed. Using an optimized standing-wave system, tough liquids with viscosities of up to about 100 Pas could be successfully atomized.}}, author = {{Dunst, Paul and Bornmann, Peter and Hemsel, Tobias and Littmann, Walter and Sextro, Walter}}, booktitle = {{Conference Proceedings - The 4th Conference on MicroFluidic Handling Systems (MFHS2019)}}, editor = {{Lötters, Joost and Urban, Gerald}}, keywords = {{atomization, ultrasound, standing-wave, capillarywave, vibrating-mesh}}, location = {{Enschede, The Netherlands}}, pages = {{140--143}}, title = {{{Atomization of Fluids with Ultrasound}}}, year = {{2019}}, } @article{14870, author = {{Wei, Qunshuo and Sain, Basudeb and Wang, Yongtian and Reineke, Bernhard and Li, Xiaowei and Huang, Lingling and Zentgraf, Thomas}}, issn = {{1530-6984}}, journal = {{Nano Letters}}, number = {{12}}, pages = {{8964–8971}}, title = {{{Simultaneous Spectral and Spatial Modulation for Color Printing and Holography Using All-dielectric Metasurfaces}}}, doi = {{10.1021/acs.nanolett.9b03957}}, volume = {{19}}, year = {{2019}}, } @inbook{14890, author = {{Kuhlemann, Stefan and Sellmann, Meinolf and Tierney, Kevin}}, booktitle = {{Lecture Notes in Computer Science}}, isbn = {{9783030300470}}, issn = {{0302-9743}}, title = {{{Exploiting Counterfactuals for Scalable Stochastic Optimization}}}, doi = {{10.1007/978-3-030-30048-7_40}}, year = {{2019}}, } @article{14896, author = {{Dann, Andreas and Hermann, Ben and Bodden, Eric}}, issn = {{0098-5589}}, journal = {{IEEE Transactions on Software Engineering}}, pages = {{1--1}}, title = {{{ModGuard: Identifying Integrity &Confidentiality Violations in Java Modules}}}, doi = {{10.1109/tse.2019.2931331}}, year = {{2019}}, }