@inproceedings{11887, abstract = {{We describe an algorithm that performs regularized non-negative matrix factorization (NMF) to find independent components in non-negative data. Previous techniques proposed for this purpose require the data to be grounded, with support that goes down to 0 along each dimension. In our work, this requirement is eliminated. Based on it, we present a technique to find a low-dimensional decomposition of spectrograms by casting it as a problem of discovering independent non-negative components from it. The algorithm itself is implemented as regularized non-negative matrix factorization (NMF). Unlike other ICA algorithms, this algorithm computes the mixing matrix rather than an unmixing matrix. This algorithm provides a better decomposition than standard NMF when the underlying sources are independent. It makes better use of additional observation streams than previous non-negative ICA algorithms.}}, author = {{Raj, Bhiksha and Wilson, Kevin W. and Krueger, Alexander and Haeb-Umbach, Reinhold}}, booktitle = {{Interspeech 2010}}, title = {{{Ungrounded Independent Non-Negative Factor Analysis}}}, year = {{2010}}, } @inproceedings{11912, abstract = {{In this contribution we provide a unified treatment of blind source separation (BSS) and noise suppression, two tasks which have traditionally been considered different and for which quite different techniques have been developed. Exploiting the sparseness of the sources in the short time frequency domain and using a probabilistic model which accounts for the presence of additive noise and which captures the spatial information of the multi-channel recording, a speech enhancement system is developed which suppresses noise and simultaneously separates speakers in case multiple speakers are active. Source activity estimation and model parameter estimation form the E-step and the M-step of the Expectation Maximization algorithm, respectively. Experimental results obtained on the dataset of the Signal Separation Evaluation Campaign 2010 demonstrate the effectiveness of the proposed system.}}, author = {{Tran Vu, Dang Hai and Haeb-Umbach, Reinhold}}, booktitle = {{International Workshop on Acoustic Echo and Noise Control (IWAENC 2010)}}, title = {{{An EM Approach to Integrated Multichannel Speech Separation and Noise Suppression}}}, year = {{2010}}, } @inproceedings{11913, abstract = {{In this paper we propose to employ directional statistics in a complex vector space to approach the problem of blind speech separation in the presence of spatially correlated noise. We interpret the values of the short time Fourier transform of the microphone signals to be draws from a mixture of complex Watson distributions, a probabilistic model which naturally accounts for spatial aliasing. The parameters of the density are related to the a priori source probabilities, the power of the sources and the transfer function ratios from sources to sensors. Estimation formulas are derived for these parameters by employing the Expectation Maximization (EM) algorithm. The E-step corresponds to the estimation of the source presence probabilities for each time-frequency bin, while the M-step leads to a maximum signal-to-noise ratio (MaxSNR) beamformer in the presence of uncertainty about the source activity. Experimental results are reported for an implementation in a generalized sidelobe canceller (GSC) like spatial beamforming configuration for 3 speech sources with significant coherent noise in reverberant environments, demonstrating the usefulness of the novel modeling framework.}}, author = {{Tran Vu, Dang Hai and Haeb-Umbach, Reinhold}}, booktitle = {{IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010)}}, keywords = {{array signal processing, blind source separation, blind speech separation, complex vector space, complex Watson distribution, directional statistics, expectation-maximisation algorithm, expectation maximization algorithm, Fourier transform, Fourier transforms, generalized sidelobe canceller, interference suppression, maximum signal-to-noise ratio beamformer, microphone signal, probabilistic model, spatial aliasing, spatial beamforming configuration, speech enhancement, statistical distributions}}, pages = {{241--244}}, title = {{{Blind speech separation employing directional statistics in an Expectation Maximization framework}}}, doi = {{10.1109/ICASSP.2010.5495994}}, year = {{2010}}, } @inproceedings{11992, author = {{Dressler, Falko and Sommer, Christoph}}, booktitle = {{2010 IEEE 71st Vehicular Technology Conference}}, isbn = {{9781424425181}}, title = {{{On the Impact of Human Driver Behavior on Intelligent Transportation Systems}}}, doi = {{10.1109/vetecs.2010.5493964}}, year = {{2010}}, } @inproceedings{12057, author = {{Sommer, Christoph and Krul, Robert and German, Reinhard and Dressler, Falko}}, booktitle = {{2010 IEEE 71st Vehicular Technology Conference}}, isbn = {{9781424425181}}, title = {{{Emissions vs. Travel Time: Simulative Evaluation of the Environmental Impact of ITS}}}, doi = {{10.1109/vetecs.2010.5493943}}, year = {{2010}}, } @article{12058, author = {{Sommer, Christoph and Schmidt, Armin and Chen, Yi and German, Reinhard and Koch, Wolfgang and Dressler, Falko}}, issn = {{1570-8705}}, journal = {{Ad Hoc Networks}}, pages = {{506--517}}, title = {{{On the feasibility of UMTS-based Traffic Information Systems}}}, doi = {{10.1016/j.adhoc.2009.12.003}}, year = {{2010}}, } @article{12059, author = {{Sommer, Christoph and Eckhoff, David and Dressler, Falko}}, issn = {{0930-5157}}, journal = {{PIK - Praxis der Informationsverarbeitung und Kommunikation}}, title = {{{Improving the Accuracy of IVC Simulation Using Crowd-sourced Geodata}}}, doi = {{10.1515/piko.2010.047}}, year = {{2010}}, } @inbook{12943, author = {{Röwenstrunk, Daniel}}, booktitle = {{Digitale Edition zwischen Experiment und Standardisierung}}, editor = {{Stadler, Peter and Veit, Joachim}}, isbn = {{9783110231144}}, title = {{{Die digitale Edition von Webers Klarinettenquintett – Ein Vergleich der Edirom-Versionen 2004 und 2008}}}, doi = {{10.1515/9783110231144.61}}, year = {{2010}}, } @inproceedings{12987, author = {{Becker, Bernd and Hellebrand, Sybille and Polian, Ilia and Straube, Bernd and Vermeiren, Wolfgang and Wunderlich, Hans-Joachim}}, booktitle = {{40th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W'10)}}, publisher = {{IEEE}}, title = {{{Massive Statistical Process Variations - A Grand Challenge for Testing Nanoelectronic Circuits}}}, doi = {{10.1109/dsnw.2010.5542612}}, year = {{2010}}, } @inbook{15297, author = {{Hüllermeier, Eyke and Hühn, J.}}, booktitle = {{Advances in Machine Learning I: Dedicated to the Memory of Professor Ryszard S.Michalski}}, editor = {{Koronacki, J. and Ras, Z.W. and Wierzchon, S.T. and Kacprzyk, J.}}, pages = {{321--344}}, publisher = {{Springer}}, title = {{{An Analysis of the FURIA algorithm for fuzzy rule induction}}}, volume = {{262}}, year = {{2010}}, } @inbook{15298, author = {{Fürnkranz, J. and Hüllermeier, Eyke}}, booktitle = {{Preference Learning}}, editor = {{Fürnkranz, J. and Hüllermeier, Eyke}}, pages = {{1--18}}, publisher = {{Springer}}, title = {{{Preference Learning: An Introduction}}}, year = {{2010}}, } @article{15676, author = {{Bennedsen, Jens and Schulte, Carsten}}, journal = {{TOCE}}, number = {{2}}, pages = {{8:1--8:22}}, title = {{{BlueJ Visual Debugger for Learning the Execution of Object-Oriented Programs?}}}, volume = {{10}}, year = {{2010}}, } @inproceedings{15677, author = {{Ehlert, Albrecht and Schulte, Carsten}}, booktitle = {{ITiCSE}}, pages = {{108--112}}, publisher = {{ACM}}, title = {{{Comparison of OOP first and OOP later: first results regarding the role of comfort level}}}, year = {{2010}}, } @proceedings{15678, editor = {{Schulte, Carsten and Suhonen, Jarkko}}, publisher = {{ACM}}, title = {{{10th Koli Calling International Conference on Computing Education Research, Koli Calling '10, Koli, Finland, October 28-31, 2010}}}, year = {{2010}}, } @proceedings{15679, editor = {{Diethelm, Ira and Dörge, Christina and Hildebrandt, Claudia and Schulte, Carsten}}, publisher = {{GI}}, title = {{{Didaktik der Informatik - Möglichkeiten empirischer Forschungsmethoden und Perspektiven der Fachdidaktik. 6. Workshop der GI-Fachgruppe "Didaktik der Informatik", 16. - 17. September 2010 in Oldenburg}}}, volume = {{P-168}}, year = {{2010}}, } @inproceedings{15765, author = {{Fober, T. and Mernberger, M. and Klebe, G. and Hüllermeier, Eyke}}, booktitle = {{In Proceedings GCB-2010 German Conference on Bioinformatics Braunschweig, Germany}}, pages = {{51--60}}, title = {{{Efficient similarity retrieval for protein binding sites based on histogram comparison}}}, year = {{2010}}, } @inproceedings{15772, author = {{Dembczynski, K. and Waegeman, W. and Cheng, W. and Hüllermeier, Eyke}}, booktitle = {{In Proceedings MLD-2010, 2nd International Workshop on Learning from Multi-Label Data, Haifa, Israel}}, title = {{{On label dependence in multi-label classification}}}, year = {{2010}}, } @inproceedings{15889, author = {{Somorovsky, Juraj and Jensen, Meiko and Schwenk, Jörg}}, booktitle = {{2010 6th World Congress on Services}}, isbn = {{9781424481996}}, title = {{{Streaming-Based Verification of XML Signatures in SOAP Messages}}}, doi = {{10.1109/services.2010.57}}, year = {{2010}}, } @inproceedings{14561, abstract = {{Semi-analytical approaches for the description of dispersion in acoustic waveguides are based on root finding in a characteristic function. A mode-tracing algorithm helps to find all solutions of this problem by consecutively bracketing single roots. In this contribution we present a multistage and adaptive mode-tracing algorithm, which uses an adaptive step size for the prediction of consecutive solutions as well as an adaptive estimation of the search space around these predictions. Furthermore we present a validation stage to ensure the correlation between consecutive solutions alias waveguide modes.}}, author = {{Bause, Fabian and Rautenberg, Jens and Henning, Bernd}}, location = {{San Diego, California}}, pages = {{719--722}}, title = {{{An improved mode-tracing algorithm to compute dispersion curves of acoustic waveguides}}}, year = {{2010}}, } @inproceedings{14563, abstract = {{Die computergestützte Simulation geführter elastischer Wellen in ein- oder mehrschichtigen Wellenleitern ist in vielen Bereichen der akustischen Forschung ein essentielles Modellierungswerkzeug. Sie ermöglicht, auch in komplexen Systemen, eine Beschreibung der Wellenausbreitungsvorgänge, deren analytische Lösung zu aufwendig oder nicht durchführbar ist. Im ersten Abschnitt dieses Beitrags wird auf den halbanalytischen Solver bzw. die mathematische Formulierung des die Wellenausbreitung beschreibenden Problems eingegangen. Der zweite Abschnitt beinhaltet den mehrstufigen Aufbau eines Tracing-Algorithmus, welcher den Lösungsraum des Solvers adaptiv einschränkt, so dass Leistungsfähigkeit und Robustheit des Gesamtalgorithmus gestärkt werden.}}, author = {{Bause, Fabian and Rautenberg, Jens and Henning, Bernd}}, isbn = {{978-3-9808659-8-2}}, location = {{Berlin}}, pages = {{1027--1028}}, title = {{{Entwicklung und Parametrisierung eines Mode-Tracing Algorithmus für halbanalytische Solver}}}, year = {{2010}}, }