@misc{10720, author = {{Nofen, Barbara}}, publisher = {{Paderborn University}}, title = {{{Verbesserung der Erkennungsrate eines Systems zur Klassifikation von EMG-Signalen durch den Einsatz eines hybriden Lagesensors}}}, year = {{2013}}, } @misc{10727, author = {{Pudelko, Daniel}}, publisher = {{Paderborn University}}, title = {{{Überquerung der Styx - Betriebsparametervariation und Fehlerverhalten eines Platform FPGAs}}}, year = {{2013}}, } @misc{10730, author = {{Riebler, Heinrich}}, publisher = {{Paderborn University}}, title = {{{Identifikation und Wiederherstellung von kryptographischen Schlüsseln mit FPGAs}}}, year = {{2013}}, } @misc{10741, author = {{Sprenger, Alexander}}, publisher = {{Paderborn University}}, title = {{{MiBenchHybrid : Erweiterung eines Benchmarks um Hardwarebeschleunigung}}}, year = {{2013}}, } @misc{10743, author = {{Steppeler, Philipp}}, publisher = {{Paderborn University}}, title = {{{Beschleunigung von Einzelbild-Erkennungsverfahren auf Datenfluss basierenden HPC Systemen}}}, year = {{2013}}, } @inproceedings{10745, author = {{Toebermann, Christian and Geibel, Daniel and Hau, Manuel and Brandl, Ron and Kaufmann, Paul and Ma, Chenjie and Braun, Martin and Degner, Tobias}}, booktitle = {{Real-Time Conference}}, publisher = {{OPAL RT Paris}}, title = {{{Real-Time Simulation of Distribution Grids with high Penetration of Regenerative and Distributed Generation}}}, year = {{2013}}, } @inproceedings{10774, author = {{Ghasemzadeh Mohammadi, Hassan and Gaillardon, Pierre-Emmanuel and Yazdani, Majid and De Micheli, Giovanni}}, booktitle = {{2013 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFTS)}}, pages = {{83--88}}, publisher = {{IEEE}}, title = {{{A fast TCAD-based methodology for Variation analysis of emerging nano-devices}}}, doi = {{10.1109/DFT.2013.6653587}}, year = {{2013}}, } @inproceedings{10775, author = {{Gaillardon, Pierre-Emmanuel and Ghasemzadeh Mohammadi, Hassan and De Micheli, Giovanni}}, booktitle = {{2013 14th Latin American Test Workshop-LATW}}, pages = {{1--6}}, publisher = {{IEEE}}, title = {{{Vertically-stacked silicon nanowire transistors with controllable polarity: A robustness study}}}, doi = {{10.1109/LATW.2013.6562673}}, year = {{2013}}, } @inproceedings{1093, abstract = {{Whenever huge amounts of XML data have to be transferred from a web server to multiple clients, the transferred data volumes can be reduced significantly by sending compressed XML instead of plain XML. Whenever applications require querying a compressed XML format and XML compression or decompression time is a bottleneck, parallel XML compression and parallel decompression may be of significant advantage. We choose the XML compressor XSDS as starting point for our new approach to parallel compression and parallel decompression of XML documents for the following reasons. First, XSDS generally reaches stronger compression ratios than other compressors like gzip, bzip2, and XMill. Second, in contrast to these compressors, XSDS not only supports XPath queries on compressed XML data, but also XPath queries can be evaluated on XSDS compressed data even faster than on uncompressed XML. We propose a String-search-based parsing approach to parallelize XML compression with XSDS, and we show that we can speed-up the compression of XML documents by a factor of 1.4 and that we can speed-up the decompression time even by a factor of up to 7 on a quad-core processor.}}, author = {{Böttcher, Stefan and Feldotto, Matthias and Hartel, Rita}}, booktitle = {{WEBIST 2013 - Proceedings of the 9th International Conference on Web Information Systems and Technologies, Aachen, Germany, 8-10 May, 2013}}, pages = {{77--86}}, title = {{{Schema-based Parallel Compression and Decompression of XML Data}}}, doi = {{10.5220/0004366300770086}}, year = {{2013}}, } @inproceedings{11716, abstract = {{The accuracy of automatic speech recognition systems in noisy and reverberant environments can be improved notably by exploiting the uncertainty of the estimated speech features using so-called uncertainty-of-observation techniques. In this paper, we introduce a new Bayesian decision rule that can serve as a mathematical framework from which both known and new uncertainty-of-observation techniques can be either derived or approximated. The new decision rule in its direct form leads to the new significance decoding approach for Gaussian mixture models, which results in better performance compared to standard uncertainty-of-observation techniques in different additive and convolutive noise scenarios.}}, author = {{Abdelaziz, Ahmed H. and Zeiler, Steffen and Kolossa, Dorothea and Leutnant, Volker and Haeb-Umbach, Reinhold}}, booktitle = {{Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on}}, issn = {{1520-6149}}, keywords = {{Bayes methods, Gaussian processes, convolution, decision theory, decoding, noise, reverberation, speech coding, speech recognition, Bayesian decision rule, GMM, Gaussian mixture models, additive noise scenarios, automatic speech recognition systems, convolutive noise scenarios, decoding approach, mathematical framework, reverberant environments, significance decoding, speech feature estimation, uncertainty-of-observation techniques, Hidden Markov models, Maximum likelihood decoding, Noise, Speech, Speech recognition, Uncertainty, Uncertainty-of-observation, modified imputation, noise robust speech recognition, significance decoding, uncertainty decoding}}, pages = {{6827--6831}}, title = {{{GMM-based significance decoding}}}, doi = {{10.1109/ICASSP.2013.6638984}}, year = {{2013}}, }