@inproceedings{11881, abstract = {{A combination of GPS (global positioning system) and INS (inertial navigation system) is known to provide high precision and highly robust vehicle localization. Notably during times when the GPS signal has a poor quality, e.g. due to the lack of a sufficiently large number of visible satellites, the INS, which may consist of a gyroscope and an odometer, will lead to improved positioning accuracy. In this paper we show how velocity information obtained from GSM (global system for mobile communications) signalling, rather than from a tachometer, can be used together with a gyroscope sensor to support localization in the presence of temporarily unavailable GPS data. We propose a sensor fusion system architecture and present simulation results that show the effectiveness of this approach.}}, author = {{Peschke, Sven and Bevermeier, Maik and Haeb-Umbach, Reinhold}}, booktitle = {{6th Workshop on Positioning Navigation and Communication (WPNC 2009)}}, keywords = {{cellular radio, distance measurement, global positioning system, Global Positioning System, global system for mobile communications, GPS positioning approach, GSM velocity, gyroscopes, gyroscope sensor, inertial navigation, inertial navigation system, odometer, sensor fusion system architecture, sensors}}, pages = {{195--202}}, title = {{{A GPS positioning approach exploiting GSM velocity estimates}}}, doi = {{10.1109/WPNC.2009.4907827}}, year = {{2009}}, } @inproceedings{11882, author = {{Peschke, Sven and Bevermeier, Maik and Haeb-Umbach, Reinhold}}, booktitle = {{DGON Navigationskonvent 2009}}, title = {{{Verbesserung von GPS-basierter Ortung durch GSM-Geschwindigkeitsschaetzungen}}}, year = {{2009}}, } @article{11937, abstract = {{In automatic speech recognition, hidden Markov models (HMMs) are commonly used for speech decoding, while switching linear dynamic models (SLDMs) can be employed for a preceding model-based speech feature enhancement. In this paper, these model types are combined in order to obtain a novel iterative speech feature enhancement and recognition architecture. It is shown that speech feature enhancement with SLDMs can be improved by feeding back information from the HMM to the enhancement stage. Two different feedback structures are derived. In the first, the posteriors of the HMM states are used to control the model probabilities of the SLDMs, while in the second they are employed to directly influence the estimate of the speech feature distribution. Both approaches lead to improvements in recognition accuracy both on the AURORA2 and AURORA4 databases compared to non-iterative speech feature enhancement with SLDMs. It is also shown that a combination with uncertainty decoding further enhances performance.}}, author = {{Windmann, Stefan and Haeb-Umbach, Reinhold}}, journal = {{IEEE Transactions on Audio, Speech, and Language Processing}}, keywords = {{AURORA2 databases, AURORA4 databases, automatic speech recognition, feedback structures, hidden Markov models, HMM, iterative methods, iterative speech feature enhancement, model probabilities, speech decoding, speech enhancement, speech feature distribution, speech recognition, switching linear dynamic models}}, number = {{5}}, pages = {{974--984}}, title = {{{Approaches to Iterative Speech Feature Enhancement and Recognition}}}, doi = {{10.1109/TASL.2009.2014894}}, volume = {{17}}, year = {{2009}}, } @article{11938, abstract = {{In this paper, parameter estimation of a state-space model of noise or noisy speech cepstra is investigated. A blockwise EM algorithm is derived for the estimation of the state and observation noise covariance from noise-only input data. It is supposed to be used during the offline training mode of a speech recognizer. Further a sequential online EM algorithm is developed to adapt the observation noise covariance on noisy speech cepstra at its input. The estimated parameters are then used in model-based speech feature enhancement for noise-robust automatic speech recognition. Experiments on the AURORA4 database lead to improved recognition results with a linear state model compared to the assumption of stationary noise.}}, author = {{Windmann, Stefan and Haeb-Umbach, Reinhold}}, journal = {{IEEE Transactions on Audio, Speech, and Language Processing}}, keywords = {{AURORA4 database, blockwise EM algorithm, covariance analysis, linear state model, noise covariance, noise-robust automatic speech recognition, noisy speech cepstra, offline training mode, parameter estimation, speech recognition, speech recognition equipment, speech recognizer, state-space methods, state-space model}}, number = {{8}}, pages = {{1577--1590}}, title = {{{Parameter Estimation of a State-Space Model of Noise for Robust Speech Recognition}}}, doi = {{10.1109/TASL.2009.2023172}}, volume = {{17}}, year = {{2009}}, } @article{12060, author = {{Sommer, Christoph and Dietrich, Isabel and Dressler, Falko}}, issn = {{1383-469X}}, journal = {{Mobile Networks and Applications}}, pages = {{786--801}}, title = {{{Simulation of Ad Hoc Routing Protocols using OMNeT++}}}, doi = {{10.1007/s11036-009-0174-5}}, year = {{2009}}, } @article{15680, author = {{Börstler, Jürgen and S. Hall, Mark and Nordström, Marie and H. Paterson, James and Sanders, Kate and Schulte, Carsten and Thomas, Lynda}}, journal = {{SIGCSE Bulletin}}, number = {{4}}, pages = {{126--143}}, title = {{{An evaluation of object oriented example programs in introductory programming textbooks}}}, volume = {{41}}, year = {{2009}}, } @inproceedings{15681, author = {{Schulte, Carsten and Tolksdorf, Robert}}, booktitle = {{DeLFI Workshops}}, pages = {{219--225}}, publisher = {{Logos Verlag}}, title = {{{Qualitätssicherung in einer interaktiven und lerneraktivierenden E-Learning-Umgebung}}}, year = {{2009}}, } @inproceedings{15682, author = {{Ehlert, Albrecht and Schulte, Carsten}}, booktitle = {{ICER}}, pages = {{15--26}}, publisher = {{ACM}}, title = {{{Empirical comparison of objects-first and objects-later}}}, year = {{2009}}, } @inproceedings{15683, author = {{Brinda, Torsten and Puhlmann, Hermann and Schulte, Carsten}}, booktitle = {{ITiCSE}}, pages = {{288--292}}, publisher = {{ACM}}, title = {{{Bridging ICT and CS: educational standards for computer science in lower secondary education}}}, year = {{2009}}, } @inproceedings{15684, author = {{Ehlert, Albrecht and Schulte, Carsten}}, booktitle = {{INFOS}}, pages = {{121--132}}, publisher = {{GI}}, title = {{{Unterschiede im Lernerfolg von Schülerinnen und Sch\üern in Abhängigkeit von der zeitlichen Reihenfolge der Themen (OOP-First bzw. OOP-Later)}}}, volume = {{P-156}}, year = {{2009}}, } @inproceedings{15685, author = {{Koubek, Jochen and Schulte, Carsten and Schulze, Peter and Witten, Helmut}}, booktitle = {{INFOS}}, pages = {{268--279}}, publisher = {{GI}}, title = {{{Informatik im Kontext (IniK) - Ein integratives Unterrichtskonzept für den Informatikunterricht}}}, volume = {{P-156}}, year = {{2009}}, } @inproceedings{15686, author = {{Schulte, Carsten}}, booktitle = {{INFOS}}, pages = {{355--366}}, publisher = {{GI}}, title = {{{Dualitätsrekonstruktion als Hilfsmittel zur Entwicklung und Planung von Informatikunterricht}}}, volume = {{P-156}}, year = {{2009}}, } @inproceedings{15773, author = {{Cheng, W. and Hüllermeier, Eyke}}, booktitle = {{In Proceedings MLD-2009 1st International Workshop on Learning from Multi-Label Data, Bled, Slovenia}}, pages = {{28--38}}, title = {{{A simple instance-based approach to multilabel classification using the Mallows model}}}, year = {{2009}}, } @inproceedings{15774, author = {{Senge, Robin and Hüllermeier, Eyke}}, booktitle = {{in Proceedings 19th Workshop Computational Intelligence, Dortmund Germany}}, editor = {{Hoffmann, F. and Hüllermeier, Eyke}}, pages = {{22--33}}, publisher = {{KIT Scientific Publishing}}, title = {{{Learning pattern tree classifiers using a co-evolutionary algorithm}}}, year = {{2009}}, } @inproceedings{15775, author = {{Fober, T. and Mernberger, M. and Moritz, R. and Hüllermeier, Eyke}}, booktitle = {{In Proceedings GCB-2009 German Conference on Bioinformatics Halle (Saale), Germany}}, editor = {{Grosse, I. and Neumann, S. and Posch, S. and Schreiber, F. and Stadler, P..}}, pages = {{21--31}}, title = {{{Graph-kernels for the comparative analysis of protein active sites}}}, year = {{2009}}, } @inproceedings{15776, author = {{Senge, Robin and Hüllermeier, Eyke}}, booktitle = {{In Proceedings Workshop LWA-2009, Lernen-Wissensentdeckung-Adaptivität, Darmstadt, Germany}}, pages = {{105--110}}, title = {{{Learning pattern tree classifiers using a co-evolutionary algorithm}}}, year = {{2009}}, } @inproceedings{15778, author = {{Fober, T. and Mernberger, M. and Melnikov, Vitaly and Moritz, R. and Hüllermeier, Eyke}}, booktitle = {{In Proceedings Workshop LWA-2009, Lernen-Wissensentdeckung-Adaptivität, Darmstadt, Germany}}, pages = {{30--36}}, title = {{{Extension and empirical comparison of graph-kernels for the analysis of protein active sites}}}, year = {{2009}}, } @article{15847, author = {{Kwong, N. H. and Schumacher, Stefan and Binder, R.}}, issn = {{0031-9007}}, journal = {{Physical Review Letters}}, title = {{{Electron-Spin Beat Susceptibility of Excitons in Semiconductor Quantum Wells}}}, doi = {{10.1103/physrevlett.103.056405}}, year = {{2009}}, } @techreport{14916, author = {{Dahle, Claudia and Bäumer, Michaela}}, title = {{{Cross-Border Group-Taxation and Loss-Offset in the EU - An Analysis for CCCTB (Common Consolidated Corporate Tax Base) and ETAS (European Tax Allocation System)}}}, volume = {{66}}, year = {{2009}}, } @article{14917, author = {{Halberstadt, Alexander and Sureth-Sloane, Caren and Voß, Armin}}, journal = {{Die Wirtschaftsprüfung}}, number = {{6}}, pages = {{373--381}}, title = {{{Der Einfluss der Abgeltungssteuer auf die Vorteilhaftigkeit von Anlagen in Genussscheine und Aktien}}}, volume = {{62}}, year = {{2009}}, }