@inbook{17044, author = {{Leitz, Thomas and Ober-Blöbaum, Sina and Leyendecker, Sigrid}}, booktitle = {{Multibody Dynamics}}, editor = {{Terze, Zdravko}}, isbn = {{9783319072593}}, issn = {{1871-3033}}, publisher = {{Springer}}, title = {{{Variational Lie Group Formulation of Geometrically Exact Beam Dynamics: Synchronous and Asynchronous Integration}}}, doi = {{10.1007/978-3-319-07260-9}}, year = {{2014}}, } @inproceedings{17045, author = {{Gail, Tobias and Leyendecker, Sigrid and Ober-Blöbaum, Sina}}, booktitle = {{The 3rdJoint International Conference on Multibody System Dynamics}}, title = {{{On the role of quadrature rules and system dimensions in variational multirateintegrators}}}, year = {{2014}}, } @inproceedings{17046, author = {{Ober-Blöbaum, Sina and Lindhorst, Henning}}, booktitle = {{21st International Symposium on Mathematical Theory of Networks and Systems}}, title = {{{Variational formulation and structure-preserving discretization ofnonlinear electric circuits}}}, year = {{2014}}, } @article{10602, author = {{Schaefers, Lars and Platzner, Marco}}, journal = {{IEEE Transactions on Computational Intelligence and AI in Games}}, number = {{3}}, pages = {{361--374}}, title = {{{A Novel Technique and its Application to Computer Go}}}, doi = {{10.1109/TCIAIG.2014.2346997}}, volume = {{6}}, year = {{2014}}, } @article{10603, author = {{Giefers, Heiner and Platzner, Marco}}, journal = {{IEEE Transactions on Computers}}, number = {{12}}, pages = {{2919 -- 2932}}, title = {{{An FPGA-based Reconfigurable Mesh Many-Core}}}, doi = {{10.1109/TC.2013.174}}, volume = {{63}}, year = {{2014}}, } @inproceedings{10621, author = {{Anwer, Jahanzeb and Platzner, Marco and Meisner, Sebastian}}, booktitle = {{Reconfigurable Architectures Workshop (RAW)}}, title = {{{FPGA Redundancy Configurations: An Automated Design Space Exploration}}}, doi = {{10.1109/IPDPSW.2014.37}}, year = {{2014}}, } @misc{10627, author = {{Bockhorn, Arne}}, publisher = {{Paderborn University}}, title = {{{Echtzeit Klassifikation von sEMG Signalen mit einem low-cost DSP Evaluation Board}}}, year = {{2014}}, } @inproceedings{10632, author = {{Boschmann, Alexander and Platzner, Marco}}, booktitle = {{Proc. MyoElectric Controls Symposium (MEC)}}, title = {{{A computer vision-based approach to high density EMG pattern recognition using structural similarity}}}, year = {{2014}}, } @inproceedings{10633, author = {{Boschmann, Alexander and Platzner, Marco}}, booktitle = {{Proc. IEEE Int. Conf. Eng. Med. Biolog. (EMBC)}}, title = {{{Towards robust HD EMG pattern recognition: Reducing electrode displacement effect using structural similarity}}}, year = {{2014}}, } @misc{10640, author = {{Brand, Marcel}}, publisher = {{Paderborn University}}, title = {{{A Generalized Loop Accelerator Implemented as a Coarse-Grained Array}}}, year = {{2014}}, } @misc{10645, author = {{Damschen, Marvin}}, publisher = {{Paderborn University}}, title = {{{Easy-to-use-on-the-fly binary program acceleration on many-cores}}}, year = {{2014}}, } @inproceedings{10654, author = {{Glette, Kyrre and Kaufmann, Paul}}, booktitle = {{IEEE Congress on Evolutionary Computation (CEC)}}, title = {{{Lookup Table Partial Reconfiguration for an Evolvable Hardware Classifier System}}}, year = {{2014}}, } @misc{10665, author = {{Hagedorn, Christoph}}, publisher = {{Paderborn University}}, title = {{{Entwicklung einer codegrößenoptimierten Softwarebibliothek für 8-Bit Mikrocontroller in netzunabhängigen Notleuchten}}}, year = {{2014}}, } @inproceedings{10674, author = {{Ho, Nam and Kaufmann, Paul and Platzner, Marco}}, booktitle = {{24th Intl. Conf. on Field Programmable Logic and Applications (FPL)}}, keywords = {{Linux, hardware-software codesign, multiprocessing systems, parallel processing, LEON3 multicore platform, Linux kernel, PMU, hardware counters, hardware-software infrastructure, high performance embedded computing, perf_event, performance monitoring unit, Computer architecture, Hardware, Monitoring, Phasor measurement units, Radiation detectors, Registers, Software}}, pages = {{1--4}}, title = {{{A hardware/software infrastructure for performance monitoring on LEON3 multicore platforms}}}, doi = {{10.1109/FPL.2014.6927437}}, year = {{2014}}, } @inproceedings{10677, author = {{Ho, Nam and Kaufmann, Paul and Platzner, Marco}}, booktitle = {{2014 {IEEE} Intl. Conf. on Evolvable Systems (ICES)}}, keywords = {{Linux, cache storage, embedded systems, granular computing, multiprocessing systems, reconfigurable architectures, Leon3 SPARe processor, custom logic events, evolvable-self-adaptable processor cache, fine granular profiling, integer unit events, measurement infrastructure, microarchitectural events, multicore embedded system, perf_event standard Linux performance measurement interface, processor properties, run-time reconfigurable memory-to-cache address mapping engine, run-time reconfigurable multicore infrastructure, split-level caching, Field programmable gate arrays, Frequency locked loops, Irrigation, Phasor measurement units, Registers, Weaving}}, pages = {{31--37}}, title = {{{Towards self-adaptive caches: A run-time reconfigurable multi-core infrastructure}}}, doi = {{10.1109/ICES.2014.7008719}}, year = {{2014}}, } @misc{10679, author = {{König, Fabian}}, publisher = {{Paderborn University}}, title = {{{EMG-basierte simultane und proportionale Online-Steuerung einer virtuellen Prothese}}}, year = {{2014}}, } @misc{10701, author = {{Koch, Benjamin}}, publisher = {{Paderborn University}}, title = {{{Hardware Acceleration of Mechatronic Controllers on a Zynq Platform FPGA}}}, year = {{2014}}, } @misc{10715, author = {{Mittendorf, Robert}}, publisher = {{Paderborn University}}, title = {{{Advanced AES-key recovery from decayed RAM using multi-threading and FPGAs}}}, year = {{2014}}, } @misc{10732, author = {{Rüthing, Christoph}}, publisher = {{Paderborn University}}, title = {{{The Xilinx Zynq Architecture as a Platform for Reconfigurable Heterogeneous Multi-Cores}}}, year = {{2014}}, } @phdthesis{10733, abstract = {{Monte-Carlo Tree Search (MCTS) is a class of simulation-based search algorithms. It brought about great success in the past few years regarding the evaluation of deterministic two-player games such as the Asian board game Go. In this thesis, we present a parallelization of the most popular MCTS variant for large HPC compute clusters that efficiently shares a single game tree representation in a distributed memory environment and scales up to 128 compute nodes and 2048 cores. It is hereby one of the most powerful MCTS parallelizations to date. In order to measure the impact of our parallelization on the search quality and remain comparable to the most advanced MCTS implementations to date, we implemented it in a state-of-the-art Go engine Gomorra, making it competitive with the strongest Go programs in the world. We further present an empirical comparison of different Bayesian ranking systems when being used for predicting expert moves for the game of Go and introduce a novel technique for automated detection and analysis of evaluation uncertainties that show up during MCTS searches.}}, author = {{Schäfers, Lars}}, isbn = {{978-3-8325-3748-7}}, pages = {{133}}, publisher = {{Logos Verlag Berlin GmbH}}, title = {{{Parallel Monte-Carlo Tree Search for HPC Systems and its Application to Computer Go}}}, year = {{2014}}, } @inproceedings{10738, author = {{Shen, Cong and Kaufmann, Paul and Braun, Martin}}, booktitle = {{IEEE Power and Energy Society General Meeting (IEEE GM)}}, title = {{{Optimizing the Generator Start-up Sequence After a Power System Blackout}}}, year = {{2014}}, } @inproceedings{10739, author = {{Shen, Cong and Kaufmann, Paul and Braun, Martin}}, booktitle = {{Power Systems Computation Conference (PSCC)}}, publisher = {{IEEE}}, title = {{{A New Distribution Network Reconfiguration and Restoration Path Selection Algorithm}}}, year = {{2014}}, } @misc{10744, author = {{Surmund, Sebastian}}, publisher = {{Paderborn University}}, title = {{{Multithreaded Parallelization of Mechatronic Controllers on a Zynq Platform FPGA}}}, year = {{2014}}, } @book{10756, author = {{I. Esparcia-Alc{\'a}zar, Anna and Eiben, A.E. and Agapitos, Alexandros and Sim{\~o}es, Anabela and G.B. Tettamanzi, Andrea and Della Cioppa, Antonio and M. Mora, Antonio and Cotta, Carlos and Tarantino, Ernesto and Haasdijk, Evert and Divina, Federico and Fern{\'a}ndez de Vega, Francisco and Squillero, Giovanni and De Falco, Ivanoe and Ignacio Hidalgo, J. and Sim, Kevin and Glette, Kyrre and Zhang, Mengjie and Urquhart, Neil and Burelli, Paolo and Kaufmann, Paul and Po{\v s}{\'\i}k, Petr and Schaefer, Robert and Drechsler, Rolf and Antipolis, Sophia and Cagnoni, Stefano and Thanh Nguyen, Trung and S. Bush (editors), William}}, publisher = {{Springer}}, title = {{{Applications of Evolutionary Computation - 17th European Conference, EvoApplications}}}, volume = {{8602}}, year = {{2014}}, } @inproceedings{10764, author = {{Anwer, Jahanzeb and Platzner, Marco}}, booktitle = {{IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT)}}, pages = {{177--184}}, publisher = {{IEEE}}, title = {{{Analytic reliability evaluation for fault-tolerant circuit structures on FPGAs}}}, doi = {{10.1109/DFT.2014.6962108}}, year = {{2014}}, } @inproceedings{10773, author = {{Ghasemzadeh Mohammadi, Hassan and Gaillardon, Pierre-Emmanuel and Yazdani, Majid and De Micheli, Giovanni}}, booktitle = {{2014 IEEE/ACM International Symposium on Nanoscale Architectures (NANOARCH)}}, pages = {{163--168}}, publisher = {{IEEE}}, title = {{{Fast process variation analysis in nano-scaled technologies using column-wise sparse parameter selection}}}, doi = {{10.1109/NANOARCH.2014.6880479}}, year = {{2014}}, } @inproceedings{11746, abstract = {{ "A method for nonstationary noise robust automatic speech recognition (ASR) is to first estimate the changing noise statistics and second clean up the features prior to recognition accordingly. Here, the first is accomplished by noise tracking in the spectral domain, while the second relies on Bayesian enhancement in the feature domain. In this way we take advantage of our recently proposed maximum a-posteriori based (MAP-B) noise power spectral density estimation algorithm, which is able to estimate the noise statistics even in time-frequency bins dominated by speech. We show that MAP-B noise tracking leads to an improved noise model estimate in the feature domain compared to estimating noise in speech absence periods only, if the bias resulting from the nonlinear transformation from the spectral to the feature domain is accounted for. Consequently, ASR results are improved, as is shown by experiments conducted on the Aurora IV database." }}, author = {{Chinaev, Aleksej and Puels, Marc and Haeb-Umbach, Reinhold}}, booktitle = {{11. ITG Fachtagung Sprachkommunikation (ITG 2014)}}, title = {{{Spectral Noise Tracking for Improved Nonstationary Noise Robust ASR}}}, year = {{2014}}, } @inproceedings{11752, abstract = {{ "In this contribution we derive a variational EM (VEM) algorithm for model selection in complex Watson mixture models, which have been recently proposed as a model of the distribution of normalized microphone array signals in the short-time Fourier transform domain. The VEM algorithm is applied to count the number of active sources in a speech mixture by iteratively estimating the mode vectors of the Watson distributions and suppressing the signals from the corresponding directions. A key theoretical contribution is the derivation of the MMSE estimate of a quadratic form involving the mode vector of the Watson distribution. The experimental results demonstrate the effectiveness of the source counting approach at moderately low SNR. It is further shown that the VEM algorithm is more robust w.r.t. used threshold values." }}, author = {{Drude, Lukas and Chinaev, Aleksej and Tran Vu, Dang Hai and Haeb-Umbach, Reinhold}}, booktitle = {{39th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014)}}, title = {{{Source Counting in Speech Mixtures Using a Variational EM Approach for Complexwatson Mixture Models}}}, year = {{2014}}, } @inproceedings{11753, abstract = {{This contribution describes a step-wise source counting algorithm to determine the number of speakers in an offline scenario. Each speaker is identified by a variational expectation maximization (VEM) algorithm for complex Watson mixture models and therefore directly yields beamforming vectors for a subsequent speech separation process. An observation selection criterion is proposed which improves the robustness of the source counting in noise. The algorithm is compared to an alternative VEM approach with Gaussian mixture models based on directions of arrival and shown to deliver improved source counting accuracy. The article concludes by extending the offline algorithm towards a low-latency online estimation of the number of active sources from the streaming input data.}}, author = {{Drude, Lukas and Chinaev, Aleksej and Tran Vu, Dang Hai and Haeb-Umbach, Reinhold}}, booktitle = {{14th International Workshop on Acoustic Signal Enhancement (IWAENC 2014)}}, keywords = {{Accuracy, Acoustics, Estimation, Mathematical model, Soruce separation, Speech, Vectors, Bayes methods, Blind source separation, Directional statistics, Number of speakers, Speaker diarization}}, pages = {{213--217}}, title = {{{Towards Online Source Counting in Speech Mixtures Applying a Variational EM for Complex Watson Mixture Models}}}, year = {{2014}}, } @inproceedings{11814, abstract = {{ "In this paper we present an algorithm for the unsupervised segmentation of a lattice produced by a phoneme recognizer into words. Using a lattice rather than a single phoneme string accounts for the uncertainty of the recognizer about the true label sequence. An example application is the discovery of lexical units from the output of an error-prone phoneme recognizer in a zero-resource setting, where neither the lexicon nor the language model (LM) is known. We propose a computationally efficient iterative approach, which alternates between the following two steps: First, the most probable string is extracted from the lattice using a phoneme LM learned on the segmentation result of the previous iteration. Second, word segmentation is performed on the extracted string using a word and phoneme LM which is learned alongside the new segmentation. We present results on lattices produced by a phoneme recognizer on the WSJCAM0 dataset. We show that our approach delivers superior segmentation performance than an earlier approach found in the literature, in particular for higher-order language models. " }}, author = {{Heymann, Jahn and Walter, Oliver and Haeb-Umbach, Reinhold and Raj, Bhiksha}}, booktitle = {{39th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014)}}, title = {{{Iterative Bayesian Word Segmentation for Unspuervised Vocabulary Discovery from Phoneme Lattices}}}, year = {{2014}}, } @inproceedings{11831, abstract = {{ "Several self-localization algorithms have been proposed, that determine the positions of either acoustic or visual sensors autonomously. Usually these positions are given in a modality specific coordinate system, with an unknown rotation, translation and scale between the different systems. For a joint audiovisual tracking, where the different modalities support each other, the two modalities need to be mapped into a common coordinate system. In this paper we propose to estimate this mapping based on audiovisual correlates, i.e., a speaker that can be localized by both, a microphone and a camera network separately. The voice is tracked by a microphone network, which had to be calibrated by a self-localization algorithm at first, and the head is tracked by a calibrated camera network. Unlike existing Singular Value Decomposition based approaches to estimate the coordinate system mapping, we propose to perform an estimation in the shape domain, which turns out to be computationally more efficient. Simulations of the self-localization of an acoustic sensor network and a following coordinate mapping for a joint speaker localization showed a significant improvement of the localization performance, since the modalities were able to support each other." }}, author = {{Jacob, Florian and Haeb-Umbach, Reinhold}}, booktitle = {{11. ITG Fachtagung Sprachkommunikation (ITG 2014)}}, title = {{{Coordinate Mapping Between an Acoustic and Visual Sensor Network in the Shape Domain for a Joint Self-Calibrating Speaker Tracking}}}, year = {{2014}}, } @article{11861, abstract = {{In this contribution we present a theoretical and experimental investigation into the effects of reverberation and noise on features in the logarithmic mel power spectral domain, an intermediate stage in the computation of the mel frequency cepstral coefficients, prevalent in automatic speech recognition (ASR). Gaining insight into the complex interaction between clean speech, noise, and noisy reverberant speech features is essential for any ASR system to be robust against noise and reverberation present in distant microphone input signals. The findings are gathered in a probabilistic formulation of an observation model which may be used in model-based feature compensation schemes. The proposed observation model extends previous models in three major directions: First, the contribution of additive background noise to the observation error is explicitly taken into account. Second, an energy compensation constant is introduced which ensures an unbiased estimate of the reverberant speech features, and, third, a recursive variant of the observation model is developed resulting in reduced computational complexity when used in model-based feature compensation. The experimental section is used to evaluate the accuracy of the model and to describe how its parameters can be determined from test data.}}, author = {{Leutnant, Volker and Krueger, Alexander and Haeb-Umbach, Reinhold}}, issn = {{2329-9290}}, journal = {{IEEE/ACM Transactions on Audio, Speech, and Language Processing}}, keywords = {{computational complexity, reverberation, speech recognition, automatic speech recognition, background noise, clean speech, computational complexity, energy compensation, logarithmic mel power spectral domain, mel frequency cepstral coefficients, microphone input signals, model-based feature compensation schemes, noisy reverberant speech automatic recognition, noisy reverberant speech features, reverberation, Atmospheric modeling, Computational modeling, Noise, Noise measurement, Reverberation, Speech, Vectors, Model-based feature compensation, observation model for reverberant and noisy speech, recursive observation model, robust automatic speech recognition}}, number = {{1}}, pages = {{95--109}}, title = {{{A New Observation Model in the Logarithmic Mel Power Spectral Domain for the Automatic Recognition of Noisy Reverberant Speech}}}, doi = {{10.1109/TASLP.2013.2285480}}, volume = {{22}}, year = {{2014}}, } @article{11867, abstract = {{New waves of consumer-centric applications, such as voice search and voice interaction with mobile devices and home entertainment systems, increasingly require automatic speech recognition (ASR) to be robust to the full range of real-world noise and other acoustic distorting conditions. Despite its practical importance, however, the inherent links between and distinctions among the myriad of methods for noise-robust ASR have yet to be carefully studied in order to advance the field further. To this end, it is critical to establish a solid, consistent, and common mathematical foundation for noise-robust ASR, which is lacking at present. This article is intended to fill this gap and to provide a thorough overview of modern noise-robust techniques for ASR developed over the past 30 years. We emphasize methods that are proven to be successful and that are likely to sustain or expand their future applicability. We distill key insights from our comprehensive overview in this field and take a fresh look at a few old problems, which nevertheless are still highly relevant today. Specifically, we have analyzed and categorized a wide range of noise-robust techniques using five different criteria: 1) feature-domain vs. model-domain processing, 2) the use of prior knowledge about the acoustic environment distortion, 3) the use of explicit environment-distortion models, 4) deterministic vs. uncertainty processing, and 5) the use of acoustic models trained jointly with the same feature enhancement or model adaptation process used in the testing stage. With this taxonomy-oriented review, we equip the reader with the insight to choose among techniques and with the awareness of the performance-complexity tradeoffs. The pros and cons of using different noise-robust ASR techniques in practical application scenarios are provided as a guide to interested practitioners. The current challenges and future research directions in this field is also carefully analyzed.}}, author = {{Li, Jinyu and Deng, Li and Gong, Yifan and Haeb-Umbach, Reinhold}}, journal = {{IEEE Transactions on Audio, Speech and Language Processing}}, keywords = {{Speech recognition, compensation, distortion modeling, joint model training, noise, robustness, uncertainty processing}}, number = {{4}}, pages = {{745--777}}, title = {{{An Overview of Noise-Robust Automatic Speech Recognition}}}, doi = {{10.1109/TASLP.2014.2304637}}, volume = {{22}}, year = {{2014}}, } @inproceedings{11918, abstract = {{In this paper, we investigate unsupervised acoustic model training approaches for dysarthric-speech recognition. These models are first, frame-based Gaussian posteriorgrams, obtained from Vector Quantization (VQ), second, so-called Acoustic Unit Descriptors (AUDs), which are hidden Markov models of phone-like units, that are trained in an unsupervised fashion, and, third, posteriorgrams computed on the AUDs. Experiments were carried out on a database collected from a home automation task and containing nine speakers, of which seven are considered to utter dysarthric speech. All unsupervised modeling approaches delivered significantly better recognition rates than a speaker-independent phoneme recognition baseline, showing the suitability of unsupervised acoustic model training for dysarthric speech. While the AUD models led to the most compact representation of an utterance for the subsequent semantic inference stage, posteriorgram-based representations resulted in higher recognition rates, with the Gaussian posteriorgram achieving the highest slot filling F-score of 97.02%. Index Terms: unsupervised learning, acoustic unit descriptors, dysarthric speech, non-negative matrix factorization}}, author = {{Walter, Oliver and Despotovic, Vladimir and Haeb-Umbach, Reinhold and Gemmeke, Jrt and Ons, Bart and Van hamme, Hugo}}, booktitle = {{INTERSPEECH 2014}}, title = {{{An Evaluation of Unsupervised Acoustic Model Training for a Dysarthric Speech Interface}}}, year = {{2014}}, } @inproceedings{11974, author = {{Berger, Mario and Erlacher, Felix and Sommer, Christoph and Dressler, Falko}}, booktitle = {{2014 International Conference on Computing, Networking and Communications (ICNC)}}, isbn = {{9781479923588}}, title = {{{Adaptive load allocation for combining Anomaly Detectors using controlled skips}}}, doi = {{10.1109/iccnc.2014.6785438}}, year = {{2014}}, } @inproceedings{11978, author = {{Bloessl, Bastian and Segata, Michele and Sommer, Christoph and Dressler, Falko}}, booktitle = {{2013 IEEE Vehicular Networking Conference}}, isbn = {{9781479926879}}, title = {{{Towards an Open Source IEEE 802.11p stack: A full SDR-based transceiver in GNU Radio}}}, doi = {{10.1109/vnc.2013.6737601}}, year = {{2014}}, } @inproceedings{11979, author = {{Bloessl, Bastian and Puschmann, Andre and Sommer, Christoph and Dressler, Falko}}, booktitle = {{Proceedings of the 9th ACM international workshop on Wireless network testbeds, experimental evaluation and characterization - WiNTECH '14}}, isbn = {{9781450330725}}, title = {{{Timings matter}}}, doi = {{10.1145/2643230.2643240}}, year = {{2014}}, } @inproceedings{11994, author = {{Dressler, Falko and Handle, Philipp and Sommer, Christoph}}, booktitle = {{Proceedings of the 2014 ACM international workshop on Wireless and mobile technologies for smart cities - WiMobCity '14}}, isbn = {{9781450330367}}, title = {{{Towards a vehicular cloud - using parked vehicles as a temporary network and storage infrastructure}}}, doi = {{10.1145/2633661.2633671}}, year = {{2014}}, } @inproceedings{11996, author = {{Eckert, Juergen and Sommer, Christoph and Eckhoff, David}}, booktitle = {{Proceedings of the 11th ACM symposium on Performance evaluation of wireless ad hoc, sensor, & ubiquitous networks - PE-WASUN '14}}, isbn = {{9781450330251}}, title = {{{Towards a simulation framework for paraglider networks}}}, doi = {{10.1145/2653481.2655754}}, year = {{2014}}, } @inproceedings{12002, author = {{Eckhoff, David and Dressler, Falko and Sommer, Christoph}}, booktitle = {{38th Annual IEEE Conference on Local Computer Networks}}, isbn = {{9781479905379}}, title = {{{SmartRevoc: An efficient and privacy preserving revocation system using parked vehicles}}}, doi = {{10.1109/lcn.2013.6761338}}, year = {{2014}}, } @article{12003, author = {{Eckhoff, David and Sommer, Christoph}}, issn = {{1540-7993}}, journal = {{IEEE Security & Privacy}}, pages = {{77--79}}, title = {{{Driving for Big Data? Privacy Concerns in Vehicular Networking}}}, doi = {{10.1109/msp.2014.2}}, year = {{2014}}, } @inproceedings{12008, author = {{Erlacher, Felix and Klingler, Florian and Sommer, Christoph and Dressler, Falko}}, booktitle = {{2014 11th Annual Conference on Wireless On-demand Network Systems and Services (WONS)}}, isbn = {{9781479949373}}, title = {{{On the impact of street width on 5.9 GHz radio signal propagation in vehicular networks}}}, doi = {{10.1109/wons.2014.6814735}}, year = {{2014}}, } @article{12038, author = {{Malandrino, Francesco and Casetti, Claudio and Chiasserini, Carla-Fabiana and Sommer, Christoph and Dressler, Falko}}, issn = {{0018-9545}}, journal = {{IEEE Transactions on Vehicular Technology}}, pages = {{4606--4617}}, title = {{{The Role of Parked Cars in Content Downloading for Vehicular Networks}}}, doi = {{10.1109/tvt.2014.2316645}}, year = {{2014}}, } @inproceedings{12046, author = {{Segata, Michele and Bloessl, Bastian and Joerer, Stefan and Sommer, Christoph and Lo Cigno, Renato and Dressler, Falko}}, booktitle = {{2013 IEEE Vehicular Networking Conference}}, isbn = {{9781479926879}}, title = {{{Short paper: Vehicle shadowing distribution depends on vehicle type: Results of an experimental study}}}, doi = {{10.1109/vnc.2013.6737623}}, year = {{2014}}, } @inproceedings{12049, author = {{Segata, Michele and Bloessl, Bastian and Sommer, Christoph and Dressler, Falko}}, booktitle = {{2014 IEEE International Conference on Communications (ICC)}}, isbn = {{9781479920037}}, title = {{{Towards energy efficient smart phone applications: Energy models for offloading tasks into the cloud}}}, doi = {{10.1109/icc.2014.6883681}}, year = {{2014}}, } @inproceedings{12067, author = {{Sommer, Christoph and Hagenauer, Florian and Dressler, Falko}}, booktitle = {{2014 IEEE World Forum on Internet of Things (WF-IoT)}}, isbn = {{9781479934591}}, title = {{{A networking perspective on self-organizing intersection management}}}, doi = {{10.1109/wf-iot.2014.6803164}}, year = {{2014}}, } @inproceedings{12073, author = {{Tung, Lung-Chih and Mena, Jorge and Gerla, Mario and Sommer, Christoph}}, booktitle = {{2013 12th Annual Mediterranean Ad Hoc Networking Workshop (MED-HOC-NET)}}, isbn = {{9781479910045}}, title = {{{A cluster based architecture for intersection collision avoidance using heterogeneous networks}}}, doi = {{10.1109/medhocnet.2013.6767414}}, year = {{2014}}, } @inproceedings{12977, author = {{Hellebrand, Sybille and Indlekofer, Thomas and Kampmann, Matthias and A. Kochte, Michael and Liu, Chang and Wunderlich, Hans-Joachim}}, booktitle = {{IEEE International Test Conference (ITC'14)}}, publisher = {{IEEE}}, title = {{{FAST-BIST: Faster-than-at-Speed BIST Targeting Hidden Delay Defects}}}, doi = {{10.1109/test.2014.7035360}}, year = {{2014}}, } @inproceedings{15660, author = {{Busjahn, Teresa and Bednarik, Roman and Schulte, Carsten}}, booktitle = {{ETRA}}, pages = {{335--338}}, publisher = {{ACM}}, title = {{{What influences dwell time during source code reading?: analysis of element type and frequency as factors}}}, year = {{2014}}, } @inproceedings{15661, author = {{Busjahn, Teresa and Schulte, Carsten and Sharif, Bonita and Begel, Andrew and Hansen, Michael and Bednarik, Roman and Orlov, Paul and Ihantola, Petri and Shchekotova, Galina and Antropova, Maria}}, booktitle = {{ICER}}, pages = {{3--10}}, publisher = {{ACM}}, title = {{{Eye tracking in computing education}}}, year = {{2014}}, } @inproceedings{15662, author = {{Busjahn, Teresa and Schulte, Carsten and Kropp, Edna}}, booktitle = {{PPIG}}, pages = {{15}}, publisher = {{Psychology of Programming Interest Group}}, title = {{{Developing Coding Schemes for Program Comprehension using Eye Movements}}}, year = {{2014}}, } @proceedings{15663, editor = {{Schulte, Carsten and E. Caspersen, Michael and Gal-Ezer, Judith}}, publisher = {{ACM}}, title = {{{Proceedings of the 9th Workshop in Primary and Secondary Computing Education, WiPSCE 2014, Berlin, Germany, November 5-7, 2014}}}, year = {{2014}}, } @inproceedings{14874, author = {{Chen, Mei-Hua and Chen, Wei-Fan and Ku, Lun-Wei}}, booktitle = {{Proceedings of the AsiaCALL 2014}}, title = {{{RESOLVE: An Emotion Word Suggestion System Facilitates Language Learners’ Emotional Expressions}}}, year = {{2014}}, } @inproceedings{15089, author = {{Böttcher, Stefan and Hartel, Rita and Thiele, Sebastian}}, booktitle = {{Proceedings of the Second Australasian Web Conference}}, pages = {{3--12}}, publisher = {{Australian Computer Society, Inc.}}, title = {{{Difference Computation for Grammar-Compressed XML Data}}}, year = {{2014}}, } @inproceedings{15090, author = {{Böttcher, Stefan and Brandenburg, Marc and Hartel, Rita}}, booktitle = {{Proceedings of the Second Australasian Web Conference}}, pages = {{13--20}}, publisher = {{Australian Computer Society, Inc.}}, title = {{{Keyword Search on DAG-Compressed XML Data}}}, year = {{2014}}, } @inproceedings{15092, author = {{Böttcher, Stefan and Hartel, Rita and Rabe, Jonathan}}, booktitle = {{Database and Expert Systems Applications - 25th International Conference, DEXA 2014}}, isbn = {{9783319100722}}, issn = {{0302-9743}}, pages = {{122--137}}, publisher = {{Springer}}, title = {{{Efficient XML Keyword Search Based on DAG-Compression}}}, doi = {{10.1007/978-3-319-10073-9_11}}, year = {{2014}}, } @article{16046, author = {{Agarwal, M. and Fallah Tehrani, A. and Hüllermeier, Eyke}}, journal = {{Journal of Multi-Criteria Decision Analysis}}, number = {{3-4}}, title = {{{Preference-based learning of ideal solutions in TOPSIS-like decision models}}}, volume = {{22}}, year = {{2014}}, } @article{16060, author = {{Krotzky, T. and Fober, T. and Hüllermeier, Eyke and Klebe, G.}}, journal = {{IEEE/ACM Transactions of Computational Biology and Bioinformatics}}, number = {{5}}, pages = {{878--890}}, title = {{{Extended graph-based models for enhanced similarity search in Cabase}}}, volume = {{11}}, year = {{2014}}, } @article{16064, author = {{Hüllermeier, Eyke}}, journal = {{International Journal of Approximate Reasoning}}, number = {{7}}, pages = {{1519--1534}}, title = {{{Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization}}}, volume = {{55}}, year = {{2014}}, } @article{16069, author = {{Henzgen, Sascha and Strickert, M. and Hüllermeier, Eyke}}, journal = {{Evolving Systems}}, pages = {{175--191}}, title = {{{Visualization of evolving fuzzy-rule-based systems}}}, volume = {{5}}, year = {{2014}}, } @article{16077, author = {{Busa-Fekete, Robert and Szörenyi, B. and Weng, P. and Cheng, W. and Hüllermeier, Eyke}}, journal = {{Machine Learning}}, number = {{3}}, pages = {{327--351}}, title = {{{Preference-based reinforcement learning: evolutionary direct policy search using a preference-based racing algorithm.}}}, volume = {{97}}, year = {{2014}}, } @article{16078, author = {{Krempl, G. and Zliobaite, I. and Brzezinski, D. and Hüllermeier, Eyke and Last, M. and Lemaire, V. and Noack, T. and Shaker, A. and Sievi, S. and Spiliopoulou, M. and Stefanowski, J.}}, journal = {{SIGKDD Explorations}}, number = {{1}}, pages = {{1--10}}, title = {{{Open challenges for data stream mining research}}}, volume = {{16}}, year = {{2014}}, } @article{16079, author = {{Strickert, M. and Bunte, K. and Schleif, F.M. and Hüllermeier, Eyke}}, journal = {{Neurocomputing}}, pages = {{97--109}}, title = {{{Correlation-based embedding of pairwise score data}}}, volume = {{141}}, year = {{2014}}, } @article{16080, author = {{Shaker, Ammar and Hüllermeier, Eyke}}, journal = {{International Journal of Applied Mathematics and Computer Science}}, number = {{1}}, pages = {{199--212}}, title = {{{Survival analysis on data streams: Analyzing temporal events in dynamically changing environments}}}, volume = {{24}}, year = {{2014}}, } @article{16082, author = {{Senge, Robin and Bösner, S. and Dembczynski, K. and Haasenritter, J. and Hirsch, O. and Donner-Banzhoff, N. and Hüllermeier, Eyke}}, journal = {{Information Sciences}}, pages = {{16--29}}, title = {{{Reliable classification: Learning classifiers that distinguish aleatoric and epistemic uncertainty}}}, volume = {{255}}, year = {{2014}}, } @article{16083, author = {{Donner-Banzhoff, N. and Haasenritter, J. and Hüllermeier, Eyke and Viniol, A. and Bösner, S. and Becker, A.}}, journal = {{Journal of Clinical Epidemiology}}, number = {{67}}, pages = {{124--132}}, title = {{{The comprehensive diagnostic study is suggested as a design to model the diagnostic process}}}, volume = {{2}}, year = {{2014}}, } @inbook{16394, author = {{Lukovszki, Tamás and Meyer auf der Heide, Friedhelm}}, booktitle = {{Lecture Notes in Computer Science}}, isbn = {{9783319144719}}, issn = {{0302-9743}}, title = {{{Fast Collisionless Pattern Formation by Anonymous, Position-Aware Robots}}}, doi = {{10.1007/978-3-319-14472-6_17}}, year = {{2014}}, } @inbook{16395, author = {{Abshoff, Sebastian and Meyer auf der Heide, Friedhelm}}, booktitle = {{Structural Information and Communication Complexity}}, isbn = {{9783319096193}}, issn = {{0302-9743}}, title = {{{Continuous Aggregation in Dynamic Ad-Hoc Networks}}}, doi = {{10.1007/978-3-319-09620-9_16}}, year = {{2014}}, } @inproceedings{13878, author = {{Bause, Fabian and Schroder, Andreas and Rautenberg, Jens and Henning, Bernd and Gravenkamp, Hauke}}, booktitle = {{2014 IEEE International Ultrasonics Symposium}}, isbn = {{9781479970490}}, title = {{{Time-causal material modeling in the simulation of guided waves in circular viscoelastic waveguides}}}, doi = {{10.1109/ultsym.2014.0333}}, year = {{2014}}, } @inproceedings{13944, author = {{Bause, Fabian and Weber, Daniel and Rautenberg, Jens and Henning, Bernd}}, isbn = {{9783800736225}}, location = {{Nürnberg}}, publisher = {{{VDE Verlag}}}, title = {{{Unsicherheitsanalyse eines Vorwärtsmodells zur Simulation transienter Wellenausbreitung im Hohlzylinder}}}, year = {{2014}}, } @inproceedings{13945, author = {{Bause, Fabian and Brückner, Christoph and Miedl, Jens and Henning, Bernd}}, booktitle = {{Beiträge der 17. ITG/GMA-Fachtagung}}, editor = {{Gesellschaft im VDE}, Informationstechnische}}, isbn = {{9783800736225}}, publisher = {{{VDE Verlag}}}, title = {{{Model based sensitivity analysis of Leaky-Lamb wave propagation to the variation of viscous lubricant properties}}}, year = {{2014}}, } @inproceedings{13947, abstract = {{Zur schnellen und berührungslosen Materialfeuchtebestimmung wird unter anderem die Infrarotreflexionsmessung ge-nutzt. In dieser Untersuchung wird das Trocknungsverhalten von Dispersionslack auf einem rauen Substrat mit einer Multidetektoranordnung untersucht. Durch diese Anordnung ist es möglich, gerichtete und diffuse Strahlungsanteile zu detektieren, wodurch zeitvariable Glanzeffekte an der Lackoberfläche miterfasst werden. Mit Hilfe eines Raytracing-Algorithmus wird die Trocknung eines Dispersionslackes simuliert und anhand von Messdaten mit einem FTIR-Spekt-rometer verifiziert.}}, author = {{Hoof, Christian and Appelhans, Silke and Henning, Bernd}}, location = {{Nürnberg}}, title = {{{Modellgestützte Analyse des Trocknungsverhaltens von Dispersionslacken aus Daten einer NIR-Multidetektoranordnung}}}, year = {{2014}}, } @inproceedings{13948, abstract = {{Simulationen mittels der Finiten Element Methode (FEM) sind heute ein fester Bestandteil im Entwicklungsprozess von Ultraschallsystemen. Durch die simulative Ermittlung der transienten Schwingungsvorgänge können Optimierungen bezüglich gewünschter Zielkriterien vorgenommen werden. Hierdurch lassen sich die aufwendige Prototypenfertigung reduzieren und günstige Entwurfspunkte schneller ermitteln.}}, author = {{Unverzagt, Carsten and Henning, Bernd}}, pages = {{95--102}}, title = {{{Sensitivitätssteigerung im Rahmen eines inversen Ansatzes zur Materialparameterbestimmung für Piezokeramiken durch Elektrodenmodifikationen}}}, year = {{2014}}, } @article{13953, author = {{Gravenkamp, Hauke and Bause, Fabian and Chongmin, Song}}, journal = {{Computers and Structures}}, pages = {{46--55}}, title = {{{On the computation of dispersion curves for axisymmetric elastic waveguides using the Scaled Boundary Finite Element Method}}}, volume = {{131}}, year = {{2014}}, } @article{13054, author = {{Hellebrand, Sybille and Wunderlich, Hans-Joachim}}, journal = {{DeGruyter Journal on Information Technology (it)}}, number = {{4}}, pages = {{165--172}}, publisher = {{DeGruyter}}, title = {{{SAT-Based ATPG beyond Stuck-at Fault Testing}}}, volume = {{56}}, year = {{2014}}, } @article{13055, author = {{Rodriguez Gomez, Laura and Cook, Alejandro and Indlekofer, Thomas and Hellebrand, Sybille and Wunderlich, Hans-Joachim}}, journal = {{Journal of Electronic Testing - Theory and Applications (JETTA)}}, number = {{5}}, pages = {{527--540}}, publisher = {{Springer}}, title = {{{Adaptive Bayesian Diagnosis of Intermittent Faults}}}, volume = {{30}}, year = {{2014}}, } @inproceedings{13154, author = {{Graf, Tobias and Platzner, Marco}}, booktitle = {{2014 IEEE Conference on Computational Intelligence and Games}}, pages = {{1--8}}, title = {{{Common Fate Graph Patterns in Monte Carlo Tree Search for Computer Go}}}, doi = {{10.1109/CIG.2014.6932863}}, year = {{2014}}, } @misc{13213, author = {{Bause, Fabian and Webersen, Manuel and Rautenberg, Jens and Henning, Bernd}}, title = {{{Modeling and inverse identification of a high bandwidth ultrasonic measurement setup based on piezoelectric 1-3 composites}}}, year = {{2014}}, } @misc{13214, author = {{Bause, Fabian and Webersen, Manuel and Rautenberg, Jens and Henning, Bernd}}, title = {{{Modellbasierte inverse Identifikation von Ultraschall-Transducern anhand der elektrischen Eingangsimpendanz}}}, year = {{2014}}, } @inproceedings{10247, author = {{Busa-Fekete, Robert and Szörényi, B. and Hüllermeier, Eyke}}, booktitle = {{Proceedings AAAI 2014, Quebec, Canada}}, pages = {{1701--1707}}, title = {{{PAC Rank Elicitation through Adaptive Sampling of Stochastic Pairwise Preferences}}}, year = {{2014}}, } @inproceedings{10248, author = {{Busa-Fekete, Robert and Hüllermeier, Eyke}}, booktitle = {{Proceedings Int. Conf. on Algorithmic Learning Theory (ALT), Bled, Slovenia}}, pages = {{18--39}}, title = {{{A Survey of Preference-Based Online Learning with Bandit Algorithms}}}, year = {{2014}}, } @inproceedings{10249, author = {{Henzgen, Sascha and Hüllermeier, Eyke}}, booktitle = {{Proceedings Discovery Science, Bled,Slovenia }}, pages = {{123--134}}, title = {{{Mining Rank Data}}}, year = {{2014}}, } @inproceedings{10250, author = {{Fallah Tehrani, A. and Strickert, M. and Hüllermeier, Eyke}}, booktitle = {{Proceedings ESANN , Bruges, Belgium}}, title = {{{The Choquet kernel for monotone data}}}, year = {{2014}}, } @inproceedings{10251, author = {{Abdel-Aziz, A. and Strickert, M. and Hüllermeier, Eyke}}, booktitle = {{Proceedings Int. Conf. Case-Based Reasoning (ICCBR), Cork, Ireland}}, pages = {{17--31}}, title = {{{Learning Solution Similarity in Preference-Based CBR}}}, year = {{2014}}, } @inproceedings{10253, author = {{Schäfer, Dirk and Hüllermeier, Eyke}}, booktitle = {{Proceedings Lernen-Wissensentdeckung-Adaptivität (LWA), Aachen, Germany}}, pages = {{32--33}}, title = {{{Dyad Ranking Using A Bilinear Plackett-Luce Model}}}, year = {{2014}}, } @inproceedings{10254, author = {{Calders, T. and Esposito, F. and Hüllermeier, Eyke and Meo, R.}}, booktitle = {{Proceedings, Parts I-III. Lecture Notes in Computer Science}}, pages = {{8724--8726}}, publisher = {{Springer}}, title = {{{Machine Learning and Knowledge Discovery in Databases-European Conf. ECML/PKDD, Nancy, France}}}, year = {{2014}}, } @inproceedings{10295, author = {{Fürnkranz, J. and Hüllermeier, Eyke and Rudin, Cynthia and Slowinski, Roman and Sanner, Scott}}, number = {{3}}, pages = {{1--27}}, title = {{{Preference Learning (Dagstuhl Seminar 14101) Dagstuhl Reports}}}, volume = {{4}}, year = {{2014}}, } @article{10296, author = {{Shaker, Ammar and Hüllermeier, Eyke}}, journal = {{Applied Mathematics and Computer Science}}, number = {{1}}, pages = {{199--212}}, title = {{{Survival analysis on data streams: Analyzing temporal events in dynamically changing environments}}}, volume = {{24}}, year = {{2014}}, } @article{10297, author = {{Hoffmann, F. and Hüllermeier, Eyke and Kroll, A.}}, journal = {{Computational Intelligence Automatisierungstechnik}}, number = {{10}}, pages = {{685--686}}, title = {{{Ausgewählte Beiträge des GMA-Fachausschusses 5.14}}}, volume = {{62}}, year = {{2014}}, } @article{10298, author = {{Calders, T. and Esposito, F. and Hüllermeier, Eyke and Meo, R.}}, journal = {{Data Min. Knowledge Discovery}}, number = {{5-6}}, pages = {{1129--1133}}, title = {{{Guest editors`introduction:special issue of the ECML/PKDD 2014 journal track}}}, volume = {{28}}, year = {{2014}}, } @article{10299, author = {{Henzgen, Sascha and Strickert, M. and Hüllermeier, Eyke}}, journal = {{Evolving Systems}}, number = {{3}}, pages = {{175--191}}, title = {{{Visualization of evolving fuzzy rule-based systems}}}, volume = {{5}}, year = {{2014}}, } @article{10308, author = {{Hüllermeier, Eyke}}, journal = {{Int. J. Approx. Reasoning}}, number = {{7}}, pages = {{1519--1534}}, title = {{{Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization}}}, volume = {{55}}, year = {{2014}}, } @article{10309, author = {{Hüllermeier, Eyke}}, journal = {{Int. J. Approx. Reasoning}}, number = {{7}}, pages = {{1609--1613}}, title = {{{Rejoinder on "Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization}}}, volume = {{55}}, year = {{2014}}, } @article{10310, author = {{Strickert, M. and Bunte, K. and Schleif, F.- M. and Hüllermeier, Eyke}}, journal = {{Neurocomputing}}, pages = {{97--109}}, title = {{{Correlation-based embedding of pairwise score data}}}, volume = {{141}}, year = {{2014}}, } @article{10311, author = {{Senge, Robin and Bösner, S. and Dembczynski, K. and Haasenritter, J. and Hirsch, O. and Donner-Banzhoff, N. and Hüllermeier, Eyke}}, journal = {{Information Sciences}}, pages = {{16--29}}, title = {{{Reliable classification: Learning classifiers that distinguish aleatoric and epistemic uncertainty}}}, volume = {{255}}, year = {{2014}}, } @article{10312, author = {{Mernberger, M. and Moog, M. and Stork, S. and Zauner, S. and Maier, U.G. and Hüllermeier, Eyke}}, journal = {{J. Bioinformatics and Computational Biology}}, number = {{1}}, title = {{{Protein Sub-Cellular Localization Prediction for Special compartments via Optimized Time Series Distances}}}, volume = {{12}}, year = {{2014}}, } @article{10313, author = {{Calders, T. and Esposito, F. and Hüllermeier, Eyke and Meo, R.}}, journal = {{Machine Learning}}, number = {{1-2}}, pages = {{1--3}}, title = {{{Guest editors`introduction:special issue of the ECML/PKDD 2014 journal track}}}, volume = {{97}}, year = {{2014}}, } @article{10314, author = {{Busa-Fekete, Robert and Szörényi, B. and Weng, P. and Cheng, W. and Hüllermeier, Eyke}}, journal = {{Machine Learning}}, number = {{3}}, pages = {{327--351}}, title = {{{Preference-Based Reinforcement Learning: evolutionary direct policy search using a preference-based racing algorithm}}}, volume = {{97}}, year = {{2014}}, } @article{10315, author = {{Montanés, E. and Senge, Robin and Barranquero, J. and Quevedo, J.R. and Del Coz, J.J. and Hüllermeier, Eyke}}, journal = {{Pattern Recognition}}, number = {{3}}, pages = {{1494--1508}}, title = {{{Dependent binary relevance models for multi-label classification}}}, volume = {{47}}, year = {{2014}}, } @article{10316, author = {{Krempl, G. and Zliobaite, I. and Brzezinski, D. and Hüllermeier, Eyke and Last, M. and Lemaire, V. and Noack, T. and Shaker, Ammar and Sievi, S. and Spiliopoulou, M. and Stefanowski, J.}}, journal = {{SIGKDD Explorations}}, number = {{1}}, pages = {{1--10}}, title = {{{Open challenges for data stream mining research}}}, volume = {{16}}, year = {{2014}}, }