Abschreiben - ein Problem in mathematischen Lehrveranstaltungen? - Liebendörfer, Michael; Göller, Robin (Hanse-Kolloquium zur Hochschuldidaktik der Mathematik 2014 Beiträge zum gleichnamigen Symposium am 7. & 8. November 2014 an der Westfälischen Wilhelms-Universität Münster)

Eine alternative Einstiegsvorlesung in die Fachmathematik – Konzept und Auswirkungen - Göller, Robin; Liebendörfer, Michael (Beiträge zum Mathematikunterricht 2016)
Keywords: _tablet; Abschreiben

Abschreiben von Übungsaufgaben in traditionellen und innovativen Mathematikvorlesungen - Liebendörfer, Michael; Göller, Robin (Mitteilungen der Deutschen Mathematiker-Vereinigung)
Keywords: _tablet; Abschreiben

Multiobjective Model Predictive Control of an Industrial Laundry - Peitz, Sebastian; Gräler, Manuel; Henke, Christian; Molo, Mirko Hessel-von; Dellnitz, Michael; Trächtler, Ansgar (Procedia Technology)
In a wide range of applications, it is desirable to optimally control a system with respect to concurrent, potentially competing goals. This gives rise to a multiobjective optimal control problem where, instead of computing a single optimal solution, the set of optimal compromises, the so-called Pareto set, has to be approximated. When it is not possible to compute the entire control trajectory in advance, for instance due to uncertainties or unforeseeable events, model predictive control methods can be applied to control the system during operation in real time. In this article, we present an algorithm for the solution of multiobjective model predictive control problems. In an offline scenario, it can be used to compute the entire set of optimal compromises whereas in a real time scenario, one optimal compromise is computed according to an operator's preference. The results are illustrated using the example of an industrial laundry. A logistics model of the laundry is developed and then utilized in the optimization routine. Results are presented for an offline as well as an online scenario.

Monitoring and debugging using an SDK for NFV-powered telecom applications - v. Rossem, S.; Tavernier, W.; Peuster, Manuel; Colle, D.; Pickavet, M.; Demeester, P. (Proc. IEEE Conference on Network Function Virtualization and Software Defined Network (NFV-SDN), Demo Track)

Wave interaction in photonic integrated circuits: Hybrid analytical / numerical coupled mode modeling - Hammer, Manfred (Integrated Optics: Devices, Materials, and Technologies XX)
Typical optical integrated circuits combine elements, like straight and curved waveguides, or cavities, the simulation and design of which is well established through numerical eigenproblem-solvers. It remains to predict the interaction of these modes. We address this task by a ”Hybrid” variant (HCMT) of Coupled Mode Theory. Using methods from finite-element numerics, the optical properties of a circuit are approximated by superpositions of eigen-solutions for its constituents, leading to quantitative, low-dimensional, and interpretable models in the frequency domain. Spectral scans are complemented by the direct computation of supermode properties (spectral positions and linewidths, coupling-induced phase shifts). This contribution outlines the theoretical background, and discusses briefly limitations and implementational details, with the help of an example of a 2-D coupled-resonator-optical-waveguide configuration.
Keywords: tet_topic_waveguide; tet_topic_numerics

Boomerang: Demand-Driven Flow- and Context-Sensitive Pointer Analysis for Java - Späth, Johannes; Nguyen Quang Do, Lisa; Ali, Karim; Bodden, Eric (European Conference on Object-Oriented Programming (ECOOP))
Keywords: ATTRACT; ITSECWEBSITE

Parallelisierung von Algorithmen zur IR-Luftbildanalyse von Laubholzmischbeständen zur Verifizierung der Ausbreitung von Eichenkomplexschäden - Bülling, Jonas

Price-Based Allocation Games - Koepe, Jörn

Sicherheit von hybriden FPGA-Systemen in der industriellen Automatisierungstechnik -- Anforderungen und Umsetzung - Tölke, Christian

Dynamic OpenCL Task Scheduling for Energy and Performance in a Heterogeneous Environment - Wüllrich, Gunnar

Black-Box Accumulation: Collecting Incentives in a Privacy-Preserving Way - Jager, Tibor; Rupp, Andy (Proceedings on Privacy Enhancing Technologies)

Offshore Metocean Station for Energy Purposes - Balluff, Stefan; Bendfeld, Jörg (Journal of Sustainable Development of Energy, Water and Environment Systems)

Ultrasonic transmission measurements in the characterization of viscoelasticity utilizing polymeric waveguides - Bause, Fabian; Rautenberg, Jens; Feldmann, Nadine; Webersen, Manuel; Claes, Leander; Gravenkamp, Hauke; Henning, Bernd (Measurement Science and Technology)
Keywords: material characterization; material parameters; acoustic waveguide; daming; ultrasonic transducer

Determination of the material properties of polymers using laser-generated broadband ultrasound - Claes, Leander; Meyer, Thorsten; Bause, Fabian; Rautenberg, Jens; Henning, Bernd (Journal of Sensors and Sensor Systems)

Miniaturized all-optical Sound Pressure Sensor - Fischer, Balthasar; Claes, Leander (INTER-NOISE 2016)

Increasing the Sensitivity of Impedance with Respect to Material Parameters of Triple-Ring Electrode Piezoelectric Transducers using Algorithmic Differentiation - Jurgelucks, Benjamin; Claes, Leander

Optimisation of triple-ring-electrodes on piezoceramic transducers using algorithmic differentiation - Jurgelucks, Benjamin; Claes, Leander (AD2016 The 7th International Conference on Algorithmic Differentiation)

Characterization of Continuous-fiber Reinforced Thermoplastics Using Thermoacoustically Excited Ultrasonic Lamb Waves - Webersen, Manuel; Johannesmann, Sarah; Claes, Leander; Henning, Bernd (2016 IEEE IUS~Proceedings)

Vergleich zweier Verfahren der Unsicherheitsabschätzung bei linearisierten inversen Problemen mittels Bayes’scher Inferenz und Pseudoinverse am Beispiel akustischer Transmissionsmessung - Feldmann, Nadine; Bause, Fabian; Henning, Bernd (Sensoren und Messsysteme 2016)

Uncertainty estimation for linearised inverse problems comparing Bayesian inference and a pseudoinverse approach for acoustic transmission measurements - Feldmann, Nadine; Bause, Fabian; Henning, Bernd (tm - Technisches Messen)

Einbindung von Oﬀshore Windenergie durch innovative Prognosemodelle und Speichertechnologien - Bendfeld, Jörg; Balluff, Stefan; Krauter, Stefan (14. Symposium Energieinnovation 2016)

Green Energy from the Ocean An overview on costeffectiv and reliable measuring systems - Bendfeld, Jörg; Balluff, Stefan; Krauter, Stefan (2015 International Conference on Renewable Energy Research and Applications (ICRERA))

Bestimmung der relevanten klimatologischen Parameter Oﬀshore - Bendfeld, Jörg; Balluff, Stefan; Krauter, Stefan (Wissenschaftliche Verhandlungen 2016 der Deutschen Physikalischen Gesellschaft Regensburg)

Systemvergleich zur zeitlich und örtlich hochaufgelösten Einstrahlungsmessung - Bendfeld, Jörg; Balluff, Stefan; Krauter, Stefan (Wissenschaftliche Verhandlungen 2016 der Deutschen Physikalischen Gesellschaft Regensburg)

Shadowing Investigations on Thin Film Modules - Krauter, Stefan; Wendtland, S.; Weber, T.; Berghold, J.; Grunow, Paul (Proceedings of the 31st European Photovoltaic Solar Energy Conference and Exhibition, München (Deutschland), 20.–24. Juni 2016, S. 2265–2270.)

Start-Up Factory Kumasi (Ghana) – Paderborn (Germany): Smart Tropical House KNUST, Kumasi, Ghana - Klaus, Tobias; Schmitz, E.A.; Klusmann, B.; Piper, M.; Krauter, Stefan; Rongen, L.; Gruber, R.; Nkrumah, I.; Ampong, K.; Donkor, M.; Tamakloe, R. (Proceedings of the 31st European Photovoltaic Solar Energy Conference and Exhibition, München (Deutschland), 20.–24. Juni 2016, S. 3048–3049)

Deviations of results for energy yield from efficiency rankings of micro-inverters - Krauter, Stefan; Bendfeld, Jörg (Proceedings of the 31st European Photovoltaic Solar Energy Conference and Exhibition, München (Deutschland), 20.–24. Juni 2016, S. 1508–1511)

Photovoltaics and the Energy System: Adaptation of layout and load. - Kazmerski, L.; Renne, D; Kazem, H.; Sopian, D.K.; Al-Bastaki, N.; Haji, S.; Mohd, D.; Othman, Y.H.; Hoffmann, W.; Krauter, Stefan; Swift-Hook, D.T.; Book, T. (Renewable Energy in the Service of Mankind Vol II)

Experimental study of phase change materials for photovoltaic modules: Energy performance and economic yield for the EPEX spot market - Japs, Ewald; Sonnenrein, Gerrit; Krauter, Stefan; Vrabec, Jadran (Solar Energy)

Short term wind and energy prediction for offshore wind farms using neural networks - Balluff, Stefan; Bendfeld, Jörg; Krauter, Stefan (2015 International Conference on Renewable Energy Research and Applications (ICRERA))

S2CX: From relational data via SQL/XML to (Un-)Compressed XML - Böttcher, Stefan; Hartel, Rita; Wolters, Dennis (Information Systems)

Modeling Cross-Device Systems with Use Case Diagrams - Wolters, Dennis; Gerth, Christian; Engels, Gregor (Proceedings of the CAiSE'18 Forum at the 28th International Conference on Advanced Information Systems Engineering (CAiSE'16))

Towards Applying Model-based Testing in Test Case Migration - Jovanovikj, Ivan; Güldali, Baris; Grieger, Marvin (Softwaretechnik-Trends)

Reengineering of Legacy Test Cases: Problem Domain & Scenarios - Jovanovikj, Ivan; Grieger, Marvin; Güldali, Baris; Teetz, Alexander (Softwaretechnik-Trends, Proceedings of the 3rd Workshop Model-Based and Model-Driven Software Modernization (MMSM))

Friendship Processes in Network Creation Games - Kutzias, Damian

Routing Algorithms on Delayed Networks for Disaster Management Support - Schaefer, Johannes Sebastian

Asymptotically Optimal Gathering on a Grid - Cord-Landwehr, Andreas; Fischer, Matthias; Jung, Daniel; Meyer auf der Heide, Friedhelm (arXiv:1602.03303)
In this paper, we solve the local gathering problem of a swarm of $n$ indistinguishable, point-shaped robots on a two dimensional grid in asymptotically optimal time $\mathcal{O}(n)$ in the fully synchronous $\mathcal{FSYNC}$ time model. Given an arbitrarily distributed (yet connected) swarm of robots, the gathering problem on the grid is to locate all robots within a $2× 2$-sized area that is not known beforehand. Two robots are connected if they are vertical or horizontal neighbors on the grid. The locality constraint means that no global control, no compass, no global communication and only local vision is available; hence, a robot can only see its grid neighbors up to a constant $L_1$-distance, which also limits its movements. A robot can move to one of its eight neighboring grid cells and if two or more robots move to the same location they are merged to be only one robot. The locality constraint is the significant challenging issue here, since robot movements must not harm the (only globally checkable) swarm connectivity. For solving the gathering problem, we provide a synchronous algorithm -- executed by every robot -- which ensures that robots merge without breaking the swarm connectivity. In our model, robots can obtain a special state, which marks such a robot to be performing specific connectivity preserving movements in order to allow later merge operations of the swarm. Compared to the grid, for gathering in the Euclidean plane for the same robot and time model the best known upper bound is $\mathcal{O}(n^2)$.

Multiobjective Optimal Control Methods for the Development of an Intelligent Cruise Control - Dellnitz, Michael; Eckstein, Julian; Flaßkamp, Kathrin; Friedel, Patrick; Horenkamp, Christian; Köhler, Ulrich; Ober-Blöbaum, Sina; Peitz, Sebastian; Tiemeyer, Sebastian (Mathematics in Industry)

On the computation of attractors for delay differential equations - Ziessler, Adrian; Molo, Mirko Hessel-Von; Dellnitz, Michael (Journal of Computational Dynamics)

Placement of Services with Flexible Structures Specified by a YANG Data Model - Dräxler, Sevil; Karl, Holger (Proceedings of the 2nd International IEEE Conference on Network Softwarization (NetSoft))
Network function virtualization and software-defined networking allow services consisting of virtual network functions to be designed and implemented with great flexibility by facilitating automatic deployments, migrations, and reconfigurations for services and their components. For extended flexibility, we go beyond seeing services as a fixed chain of functions. We present a YANG model for describing the service structure in deployment requests in a flexible way that enables changing the order of functions in case the order of traversing them does not affect the functionality of the service. Upon receiving such requests, the network orchestration system can choose the optimal composition of service components that gives the best results for placement of services in the network. This introduces new complexities to the placement problem by greatly increasing the number of possible ways a service can be composed. In this paper, we describe a heuristic solution that selects a Pareto set of the possible compositions of a service as well as possible combinations of different services, with respect to different resource requirements of the services. Our evaluations show that the selected combinations consist of representative samples of possible structures and requirements and therefore, can result in optimal or close-to-optimal placement results.

Physical attacks on pairing-based cryptography - Günther, Peter

Patterns for Constructing Mutation Operators: Limiting the Search Space in a Software Engineering Application - Kühne, Thomas; Hamann, Heiko; Arifulina, Svetlana; Engels, Gregor (Proceedings of the 19th European Conference on Genetic Programming (EuroGP 2016))
We apply methods of genetic programming to a general problem from software engineering, namely example-based generation of specifications. In particular, we focus on model transformation by example. The definition and implementation of model transformations is a task frequently carried out by domain experts, hence, a (semi-)automatic approach is desirable. This application is challenging because the underlying search space has rich semantics, is high-dimensional, and unstructured. Hence, a computationally brute-force approach would be unscalable and potentially infeasible. To address that problem, we develop a sophisticated approach of designing complex mutation operators. We define ‘patterns’ for constructing mutation operators and report a successful case study. Furthermore, the code of the evolved model transformation is required to have high maintainability and extensibility, that is, the code should be easily readable by domain experts. We report an evaluation of this approach in a software engineering case study.

PAndA 2 : Analyzing Permission Use and Interplay in Android Apps (Tool Paper) - Jakobs, Marie-Christine; Töws, Manuel; Pauck, Felix (Workshop on Formal and Model-Driven Techniques for Developing Trustworthy Systems)
We present PAndA2, an extendable, static analysis tool for Android apps which examines permission related security threats like overprivilege, existence of permission redelegation and permission flows. PAndA2 comes along with a textual and graphical visualization of the analysis result and even supports the comparison of analysis results for different android app versions.

Sprint Diagnostic with RTK-GPS & IMU Sensor Fusion - Cedric Mertens, Jan

Implementation of Bilinear Pairings on Reconfigurable Hardware - Nassery, Abdul Sami

Acceleration of EMTP for Distribution Networks on Data Flow Machines using the Latency Insertion Method - Amin, Omair

Boolean Difference Based Reliability Evaluation of Fault Tolerant Circuit Structures on FPGAs - Anwer, Jahanzeb; Platzner, Marco (Euromicro Conference on Digital System Design (DSD))

A novel immersive augmented reality system for prosthesis training and assessment - Boschmann, Alexander; Dosen, Strahinja; Werner, Andreas; Raies, Ali; Farina, Dario (Proc. IEEE Int. Conf. Biomed. Health Informatics (BHI))

Adaptive playouts for online learning of policies during Monte Carlo Tree Search - Graf, Tobias; Platzner, Marco (Journal Theoretical Computer Science)

Beschleunigte Simulation elektrischer Stromnetze mit GPUs - Horstmann, Jens

Optimal Generation Dispatch of Distributed Generators Considering Fair Contribution to Grid Voltage Control - Ma, Chenjie; Kaufmann, Paul; Töbermann, J.-Christian; Braun, Martin (Renewable Energy)

Operating System Support for Reconfigurable Cache - Makeswaran, Vignesh

Private/Shared Data Classification and Implementation for a Multi-Softcore Platform - Ibne Ashraf, Ishraq

Thread Shadowing: On the Effectiveness of Error Detection at the Hardware Thread Level - Meisner, Sebastian; Platzner, Marco (Reconfigurable Computing and FPGAs (ReConFig), 2016 International Conference on)

Konzeption und Implementierung einer digitalen Ansteuerung für den Betrieb einer elektrischen Sendereinheit für induktive Energieübertragung - Schmidt, Marco

Applications of Evolutionary Computation - 19th European Conference, EvoApplications - Squillero, Giovanni; Burelli, Paolo; M. Mora, Antonio; Agapitos, Alexandros; S. Bush, William; Cagnoni, Stefano; Cotta, Carlos; De Falco, Ivanoe; Della Cioppa, Antonio; Divina, Federico; Eiben, A.E.; I. Esparcia-Alcázar, Anna; et al.

RCo-Design: New Visual Environment for Reconfigurable Embedded Systems - Ghribi, Ines; Ben Abdallah, Riadh; Khalgui, Mohamed; Platzner, Marco (Proceedings of the 30th European Simulation and Modelling Conference (ESM))

New Co-design Methodology for Real-time Embedded Systems - Ghribi, Ines; Ben Abdallah, Riadh; Khalgui, Mohamed; Platzner, Marco (Proceedings of the 11th International Conference on Software Engineering and Applications (ICSOFT-EA))

Efficient Statistical Parameter Selection for Nonlinear Modeling of Process/Performance Variation - Ghasemzadeh Mohammadi, Hassan; Gaillardon, Pierre-Emmanuel; De Micheli, Giovanni (IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems)

Custom Memory Controller for ReconOS - Hermansen, Sven

Preference Learning - Fürnkranz, J.; Hüllermeier, Eyke (Encyclopedia of Machine Learning and Data Mining)

Über die Rolle von Informationen in Verkehrsnetzwerken - Handirk, Tobias

A Priori SNR Estimation Using a Generalized Decision Directed Approach - Chinaev, Aleksej; Haeb-Umbach, Reinhold (INTERSPEECH 2016, San Francisco, USA)
In this contribution we investigate a priori signal-to-noise ratio (SNR) estimation, a crucial component of a single-channel speech enhancement system based on spectral subtraction. The majority of the state-of-the art a priori SNR estimators work in the power spectral domain, which is, however, not confirmed to be the optimal domain for the estimation. Motivated by the generalized spectral subtraction rule, we show how the estimation of the a priori SNR can be formulated in the so called generalized SNR domain. This formulation allows to generalize the widely used decision directed (DD) approach. An experimental investigation with different noise types reveals the superiority of the generalized DD approach over the conventional DD approach in terms of both the mean opinion score - listening quality objective measure and the output global SNR in the medium to high input SNR regime, while we show that the power spectrum is the optimal domain for low SNR. We further develop a parameterization which adjusts the domain of estimation automatically according to the estimated input global SNR. Index Terms: single-channel speech enhancement, a priori SNR estimation, generalized spectral subtraction

A Priori SNR Estimation Using Weibull Mixture Model - Chinaev, Aleksej; Heitkaemper, Jens; Haeb-Umbach, Reinhold (12. ITG Fachtagung Sprachkommunikation (ITG 2016))
This contribution introduces a novel causal a priori signal-to-noise ratio (SNR) estimator for single-channel speech enhancement. To exploit the advantages of the generalized spectral subtraction, a normalized ?-order magnitude (NAOM) domain is introduced where an a priori SNR estimation is carried out. In this domain, the NAOM coefficients of noise and clean speech signals are modeled by a Weibull distribution and aWeibullmixturemodel (WMM), respectively. While the parameters of the noise model are calculated from the noise power spectral density estimates, the speechWMM parameters are estimated from the noisy signal by applying a causal Expectation-Maximization algorithm. Further a maximum a posteriori estimate of the a priori SNR is developed. The experiments in different noisy environments show the superiority of the proposed estimator compared to the well-known decision-directed approach in terms of estimation error, estimator variance and speech quality of the enhanced signals when used for speech enhancement.

Noise-Presence-Probability-Based Noise PSD Estimation by Using DNNs - Chinaev, Aleksej; Heymann, Jahn; Drude, Lukas; Haeb-Umbach, Reinhold (12. ITG Fachtagung Sprachkommunikation (ITG 2016))
A noise power spectral density (PSD) estimation is an indispensable component of speech spectral enhancement systems. In this paper we present a noise PSD tracking algorithm, which employs a noise presence probability estimate delivered by a deep neural network (DNN). The algorithm provides a causal noise PSD estimate and can thus be used in speech enhancement systems for communication purposes. An extensive performance comparison has been carried out with ten causal state-of-the-art noise tracking algorithms taken from the literature and categorized acc. to applied techniques. The experiments showed that the proposed DNN-based noise PSD tracker outperforms all competing methods with respect to all tested performance measures, which include the noise tracking performance and the performance of a speech enhancement system employing the noise tracking component.

Blind Speech Separation based on Complex Spherical k-Mode Clustering - Drude, Lukas; Boeddeker, Christoph; Haeb-Umbach, Reinhold (Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP))

On the appropriateness of complex-valued neural networks for speech enhancement - Drude, Lukas; Raj, Bhiksha; Haeb-Umbach, Reinhold (INTERSPEECH 2016, San Francisco, USA)
Although complex-valued neural networks (CVNNs) â?? networks which can operate with complex arithmetic â?? have been around for a while, they have not been given reconsideration since the breakthrough of deep network architectures. This paper presents a critical assessment whether the novel tool set of deep neural networks (DNNs) should be extended to complex-valued arithmetic. Indeed, with DNNs making inroads in speech enhancement tasks, the use of complex-valued input data, specifically the short-time Fourier transform coefficients, is an obvious consideration. In particular when it comes to performing tasks that heavily rely on phase information, such as acoustic beamforming, complex-valued algorithms are omnipresent. In this contribution we recapitulate backpropagation in CVNNs, develop complex-valued network elements, such as the split-rectified non-linearity, and compare real- and complex-valued networks on a beamforming task. We find that CVNNs hardly provide a performance gain and conclude that the effort of developing the complex-valued counterparts of the building blocks of modern deep or recurrent neural networks can hardly be justified.

Factor Graph Decoding for Speech Presence Probability Estimation - Glarner, Thomas; Mahdi Momenzadeh, Mohammad; Drude, Lukas; Haeb-Umbach, Reinhold (12. ITG Fachtagung Sprachkommunikation (ITG 2016))
This paper is concerned with speech presence probability estimation employing an explicit model of the temporal and spectral correlations of speech. An undirected graphical model is introduced, based on a Factor Graph formulation. It is shown that this undirected model cures some of the theoretical issues of an earlier directed graphical model. Furthermore, we formulate a message passing inference scheme based on an approximate graph factorization, identify this inference scheme as a particular message passing schedule based on the turbo principle and suggest further alternative schedules. The experiments show an improved performance over speech presence probability estimation based on an IID assumption, and a slightly better performance of the turbo schedule over the alternatives.

Neural Network Based Spectral Mask Estimation for Acoustic Beamforming - Heymann, Jahn; Drude, Lukas; Haeb-Umbach, Reinhold (Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP))

On the Bias of Direction of Arrival Estimation Using Linear Microphone Arrays - Jacob, Florian; Haeb-Umbach, Reinhold (12. ITG Fachtagung Sprachkommunikation (ITG 2016))
This contribution investigates Direction of Arrival (DoA) estimation using linearly arranged microphone arrays. We are going to develop a model for the DoA estimation error in a reverberant scenario and show the existence of a bias, that is a consequence of the linear arrangement and limited field of view (FoV) bias: First, the limited FoV leading to a clipping of the measurements, and, second, the angular distribution of the signal energy of the reflections being non-uniform. Since both issues are a consequence of the linear arrangement of the sensors, the bias arises largely independent of the kind of DoA estimator. The experimental evaluation demonstrates the existence of the bias for a selected number of DoA estimation methods and proves that the prediction from the developed theoretical model matches the simulation results.

Wide Residual BLSTM Network with Discriminative Speaker Adaptation for Robust Speech Recognition - Heymann, Jahn; Drude, Lukas; Haeb-Umbach, Reinhold (Computer Speech and Language)
We present a system for the 4th CHiME challenge which significantly increases the performance for all three tracks with respect to the provided baseline system. The front-end uses a bi-directional Long Short-Term Memory (BLSTM)-based neural network to estimate signal statistics. These then steer a Generalized Eigenvalue beamformer. The back-end consists of a 22 layer deep Wide Residual Network and two extra BLSTM layers. Working on a whole utterance instead of frames allows us to refine Batch-Normalization. We also train our own BLSTM-based language model. Adding a discriminative speaker adaptation leads to further gains. The final system achieves a word error rate on the six channel real test data of 3.48%. For the two channel track we achieve 5.96% and for the one channel track 9.34%. This is the best reported performance on the challenge achieved by a single system, i.e., a configuration, which does not combine multiple systems. At the same time, our system is independent of the microphone configuration. We can thus use the same components for all three tracks.

A summary of the REVERB challenge: state-of-the-art and remaining challenges in reverberant speech processing research - Kinoshita, Keisuke; Delcroix, Marc; Gannot, Sharon; Habets, Emanuel A. P.; Haeb-Umbach, Reinhold; Kellermann, Walter; Leutnant, Volker; Maas, Roland; Nakatani, Tomohiro; Raj, Bhiksha; Sehr, Armin; Yoshioka, Takuya (EURASIP Journal on Advances in Signal Processing)

Acoustic Microphone Geometry Calibration: An overview and experimental evaluation of state-of-the-art algorithms - Plinge, Axel; Jacob, Florian; Haeb-Umbach, Reinhold; Fink, Gernot A. (IEEE Signal Processing Magazine)
Today, we are often surrounded by devices with one or more microphones, such as smartphones, laptops, and wireless microphones. If they are part of an acoustic sensor network, their distribution in the environment can be beneficially exploited for various speech processing tasks. However, applications like speaker localization, speaker tracking, and speech enhancement by beamforming avail themselves of the geometrical configuration of the sensors. Therefore, acoustic microphone geometry calibration has recently become a very active field of research. This article provides an application-oriented, comprehensive survey of existing methods for microphone position self-calibration, which will be categorized by the measurements they use and the scenarios they can calibrate. Selected methods will be evaluated comparatively with real-world recordings.
Keywords: Acoustic sensors; Microphones; Portable computers; Smart phones; Wireless communication; Wireless sensor networks

Induction-based Verification of Timed Systems - Isenberg, Tobias

The RWTH/UPB/FORTH System Combination for the 4th CHiME Challenge Evaluation - Menne, Tobias; Heymann, Jahn; Alexandridis, Anastasios; Irie, Kazuki; Zeyer, Albert; Kitza, Markus; Golik, Pavel; Kulikov, Ilia; Drude, Lukas; Schlüter, Ralf; Ney, Hermann; Haeb-Umbach, Reinhold; et al. (Computer Speech and Language)
This paper describes automatic speech recognition (ASR) systems developed jointly by RWTH, UPB and FORTH for the 1ch, 2ch and 6ch track of the 4th CHiME Challenge. In the 2ch and 6ch tracks the final system output is obtained by a Confusion Network Combination (CNC) of multiple systems. The Acoustic Model (AM) is a deep neural network based on Bidirectional Long Short-Term Memory (BLSTM) units. The systems differ by front ends and training sets used for the acoustic training. The model for the 1ch track is trained without any preprocessing. For each front end we trained and evaluated individual acoustic models. We compare the ASR performance of different beamforming approaches: a conventional superdirective beamformer [1] and an MVDR beamformer as in [2], where the steering vector is estimated based on [3]. Furthermore we evaluated a BLSTM supported Generalized Eigenvalue beamformer using NN-GEV [4]. The back end is implemented using RWTH?s open-source toolkits RASR [5], RETURNN [6] and rwthlm [7]. We rescore lattices with a Long Short-Term Memory (LSTM) based language model. The overall best results are obtained by a system combination that includes the lattices from the system of UPB?s submission [8]. Our final submission scored second in each of the three tracks of the 4th CHiME Challenge.

Unsupervised Word Discovery from Speech using Bayesian Hierarchical Models - Walter, Oliver; Haeb-Umbach, Reinhold (38th German Conference on Pattern Recognition (GCPR 2016))
In this paper we demonstrate an algorithm to learn words from speech using non-parametric Bayesian hierarchical models in an unsupervised setting. We exploit the assumption of a hierarchical structure of speech, namely the formation of spoken words as a sequence of phonemes. We employ the Nested Hierarchical Pitman-Yor Language Model, which allows an a priori unknown and possibly unlimited number of words. We assume the n-gram probabilities of words, the m-gram probabilities of phoneme sequences in words and the phoneme sequences of the words themselves as latent variables to be learned. We evaluate the algorithm on a cross language task using an existing speech recognizer trained on English speech to decode speech in the Xitsonga language supplied for the 2015 ZeroSpeech challenge. We apply the learning algorithm on the resulting phoneme graphs and achieve the highest token precision and F score compared to present systems.

Protocol options for low power sensor network MAC using wake-up receivers with duty cycling - Blobel, Johannes; Sommer, Christoph; Dressler, Falko (2016 IEEE International Conference on Communications (ICC))

On the impact of adjacent channel interference in multi-channel VANETs - Campolo, Claudia; Sommer, Christoph; Dressler, Falko; Molinaro, Antonella (2016 IEEE International Conference on Communications (ICC))

Special Issue on Multi-radio, Multi-technology, Multi-system Vehicular Communications - Campolo, Claudia; Cheng, Lin; Sommer, Christoph; (Michael) Tsai, Hsin-Mu (Computer Communications)

Cars as the base for service discovery and provision in highly dynamic networks - Hagenauer, Florian; Sommer, Christoph; Merschjohann, Simon; Higuchi, Takamasa; Dressler, Falko; Altintas, Onur (2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS))

Interconnecting smart cities by vehicles: How feasible is it? - Hagenauer, Florian; Sommer, Christoph; Onishi, Ryokichi; Wilhelm, Matthias; Dressler, Falko; Altintas, Onur (2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS))

Cars as a main ICT resource of smart cities - Hagenauer, F.; Dressler, F.; Altintas, O.; Sommer, Christoph (Smart Cities and Homes)

IEEE 802.11p unicast considered harmful - Klingler, Florian; Dressler, Falko; Sommer, Christoph (2015 IEEE Vehicular Networking Conference (VNC))

Cluster-based transmit power control in heterogeneous vehicular networks - Memedi, Agon; Hagenauer, Florian; Dressler, Falko; Sommer, Christoph (2015 IEEE Vehicular Networking Conference (VNC))

Self-aware Computing Systems: An Engineering Approach
Taking inspiration from self-awareness in humans, this book introduces the new notion of computational self-awareness as a fundamental concept for designing and operating computing systems. The basic ability of such self-aware computing systems is to collect information about their state and progress, learning and maintaining models containing knowledge that enables them to reason about their behaviour. Self-aware computing systems will have the ability to utilise this knowledge to effectively and autonomously adapt and explain their behaviour, in changing conditions. This book addresses these fundamental concepts from an engineering perspective, aiming at developing primitives for building systems and applications. It will be of value to researchers, professionals and graduate students in computer science and engineering.

X Marks the Spot: Scan-Flip-Flop Clustering for Faster-than-at-Speed Test - Kampmann, Matthias; Hellebrand, Sybille (25th IEEE Asian Test Symposium (ATS'16))

Selfish Network Creation - On Variants of Network Creation Games - Cord-Landwehr, Andreas

On the identifiability of models in multi-criteria preference learning - Labreuche, C.; Hüllermeier, Eyke; Vojtas, P.; Fallah Tehrani, A. (in Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn Germany)

Preference -based reinforcement learning using dyad ranking - Schäfer, D.; Hüllermeier, Eyke (in Proceedings DA2PL`2016 Euro Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn, Germany)

Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators - Couso, Ines; Ahmadi Fahandar, Mohsen; Hüllermeier, Eyke (in Proceedings DA2PL 2016 EURO Mini Conference From Multiple Criteria Decision Aid to Preference Learning, Paderborn Germany)

Support vector classification on noisy data using fuzzy superset losses - Lu, S.; Hüllermeier, Eyke (in Proceedings 26th Workshop Computational Intelligence, Dortmund Germany)

Plackett-Luce networks for dyad ranking - Schäfer, D.; Hüllermeier, Eyke (in Workshop LWDA "Lernen, Wissen, Daten, Analysen" Potsdam, Germany)

A data visualization course at the university of paderborn - Domik, Gitta (Pedagogy Data Visualization, IEEE VIS Workshop)

Self-stabilizing Metric Graphs - Gmyr, Robert; Lefèvre, Jonas; Scheideler, Christian (Proceedings of the 18th International Symposium on Stabilization, Safety, and Security of Distributed Systems (SSS))
We present a self-stabilizing algorithm for overlay networks that, for an arbitrary metric given by a distance oracle, constructs the graph representing that metric. The graph representing a metric is the unique minimal undirected graph such that for any pair of nodes the length of a shortest path between the nodes corresponds to the distance between the nodes according to the metric. The algorithm works under both an asynchronous and a synchronous daemon. In the synchronous case, the algorithm stablizes in time O(n) and it is almost silent in that after stabilization a node sends and receives a constant number of messages per round.

Scheduling with Interjob Communication on Parallel Processors - König, Jürgen; Mäcker, Alexander; Meyer auf der Heide, Friedhelm; Riechers, Sören (Proceedings of the 10th Annual International Conference on Combinatorial Optimization and Applications (COCOA))
Consider a scheduling problem in which a set of jobs with interjob communication, canonically represented by a weighted tree, needs to be scheduled on m parallel processors interconnected by a shared communication channel. In each time step, we may allow any processed job to use a certain capacity of the channel in order to satisfy (parts of) its communication demands to adjacent jobs processed in parallel. The goal is to find a schedule that minimizes the makespan and in which communication demands of all jobs are satisfied.We show that this problem is NP-hard in the strong sense even if the number of processors and the maximum degree of the underlying tree is constant.Consequently, we design and analyze simple approximation algorithms with asymptotic approximation ratio 2-2/m in case of paths and a ratio of 5/2 in case of arbitrary trees.

FPGA-based acceleration of high density myoelectric signal processing - Boschmann, Alexander; Agne, Andreas; Witschen, Linus Matthias; Thombansen, Georg; Kraus, Florian; Platzner, Marco (2015 International Conference on ReConFigurable Computing and FPGAs (ReConFig))
Keywords: Electromyography; Feature extraction; Delays; Hardware Pattern recognition; Prosthetics; High definition video

Routing Games With Progressive Filling - Harks, Tobias; Höfer, Martin; Schewior, Kevin; Skopalik, Alexander (IEEE/ACM Transactions on Networking)
Abstract—Max-min fairness (MMF) is a widely known approachto a fair allocation of bandwidth to each of the usersin a network. This allocation can be computed by uniformlyraising the bandwidths of all users without violating capacityconstraints. We consider an extension of these allocations byraising the bandwidth with arbitrary and not necessarily uniformtime-depending velocities (allocation rates). These allocationsare used in a game-theoretic context for routing choices, whichwe formalize in progressive filling games (PFGs). We present avariety of results for equilibria in PFGs. We show that these gamespossess pure Nash and strong equilibria. While computation ingeneral is NP-hard, there are polynomial-time algorithms forprominent classes of Max-Min-Fair Games (MMFG), includingthe case when all users have the same source-destination pair.We characterize prices of anarchy and stability for pure Nashand strong equilibria in PFGs and MMFGs when players havedifferent or the same source-destination pairs. In addition, weshow that when a designer can adjust allocation rates, it is possibleto design games with optimal strong equilibria. Some initial resultson polynomial-time algorithms in this direction are also derived.

Symmetric Anonymous Credentials with Protocols for Relations on Attributes - Hamm, Julian

UTCNN: a Deep Learning Model of Stance Classification on Social Media Text - Chen, Wei-Fan; Ku, Lun-Wei (Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics)