@phdthesis{33265, abstract = {{This thesis deals with the investigation of dynamical properties – in particular generic synchrony breaking bifurcations – that are inherent to the structure of a semigroup network as well the numerous algebraic structures that are related to these types of networks. Most notably we investigate the interplay between network dynamics and monoid representation theory as induced by the fundamental network construction in terms of hidden symmetry as introduced by RINK and SANDERS. After providing a brief survey of the field of network dynamics in Part I, we thoroughly introduce the formalism of semigroup networks, the customized dynamical systems theory, and the necessary background from monoid representation theory in Chapters 3 and 4. The remainder of Part II investigates generic synchrony breaking bifurcations and contains three major results. The first is Theorem 5.11, which shows that generic symmetry breaking steady state bifurcations in monoid equivariant dynamics occur along absolutely indecomposable subrepresentations – a natural generalization of the corresponding statement for group equivariant dynamics. Then Theorem 7.12 relates the decomposition of a representation given by a network with high-dimensional internal phase spaces to that induced by the same network with one-dimensional internal phase spaces. This result is used to show that there is a smallest dimension of internal dynamics in which all generic l-parameter bifurcations of a fundamental network can be observed (Theorem 7.24). In Part III, we employ the machinery that was summarized and further developed in Part II to feedforward networks. We propose a general definition of this structural feature of a network and show that it can equivalently be characterized in different algebraic notions in Theorem 8.35. These are then exploited to fully classify the corresponding monoid representation for any feedforward network and to classify generic synchrony breaking steady state bifurcations with one- or highdimensional internal dynamics.}}, author = {{Schwenker, Sören}}, publisher = {{Universität Hamburg}}, title = {{{Genericity in Network Dynamics}}}, year = {{2019}}, } @article{15814, abstract = {{Once a popular theme of futuristic science fiction or far-fetched technology forecasts, digital home assistants with a spoken language interface have become a ubiquitous commodity today. This success has been made possible by major advancements in signal processing and machine learning for so-called far-field speech recognition, where the commands are spoken at a distance from the sound capturing device. The challenges encountered are quite unique and different from many other use cases of automatic speech recognition. The purpose of this tutorial article is to describe, in a way amenable to the non-specialist, the key speech processing algorithms that enable reliable fully hands-free speech interaction with digital home assistants. These technologies include multi-channel acoustic echo cancellation, microphone array processing and dereverberation techniques for signal enhancement, reliable wake-up word and end-of-interaction detection, high-quality speech synthesis, as well as sophisticated statistical models for speech and language, learned from large amounts of heterogeneous training data. In all these fields, deep learning has occupied a critical role.}}, author = {{Haeb-Umbach, Reinhold and Watanabe, Shinji and Nakatani, Tomohiro and Bacchiani, Michiel and Hoffmeister, Bjoern and Seltzer, Michael L. and Zen, Heiga and Souden, Mehrez}}, issn = {{1558-0792}}, journal = {{IEEE Signal Processing Magazine}}, number = {{6}}, pages = {{111--124}}, title = {{{Speech Processing for Digital Home Assistance: Combining Signal Processing With Deep-Learning Techniques}}}, doi = {{10.1109/MSP.2019.2918706}}, volume = {{36}}, year = {{2019}}, } @article{24958, author = {{Bauer, Anna and Lahme, Simon and Woitkowski, David and Vogelsang, Christoph and Reinhold, Peter}}, journal = {{PhyDid B – Didaktik der Physik – Beiträge zur DPG-Frühjahrstagung}}, pages = {{53--60}}, title = {{{PSΦ: Forschungsprogramm zur Studieneingangsphase im Physikstudium}}}, year = {{2019}}, } @inproceedings{13904, abstract = {{In this paper, we introduce updatable anonymous credential systems (UACS) and use them to construct a new privacy-preserving incentive system. In a UACS, a user holding a credential certifying some attributes can interact with the corresponding issuer to update his attributes. During this, the issuer knows which update function is run, but does not learn the user's previous attributes. Hence the update process preserves anonymity of the user. One example for a class of update functions are additive updates of integer attributes, where the issuer increments an unknown integer attribute value v by some known value k. This kind of update is motivated by an application of UACS to incentive systems. Users in an incentive system can anonymously accumulate points, e.g. in a shop at checkout, and spend them later, e.g. for a discount.}}, author = {{Blömer, Johannes and Bobolz, Jan and Diemert, Denis Pascal and Eidens, Fabian}}, booktitle = {{Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security - CCS '19}}, location = {{London}}, title = {{{Updatable Anonymous Credentials and Applications to Incentive Systems}}}, doi = {{10.1145/3319535.3354223}}, year = {{2019}}, } @article{35806, author = {{Stenzel, Nadja and Drumm, Sandra}}, journal = {{ProDaZ}}, title = {{{Scaffoldingelemente zur Sprachförderung im Textilunterricht.}}}, year = {{2019}}, } @article{19450, abstract = {{Wenn akustische Signalverarbeitung mit automatisiertem Lernen verknüpft wird: Nachrichtentechniker arbeiten mit mehreren Mikrofonen und tiefen neuronalen Netzen an besserer Spracherkennung unter widrigsten Bedingungen. Von solchen Sensornetzwerken könnten langfristig auch digitale Sprachassistenten profitieren.}}, author = {{Haeb-Umbach, Reinhold}}, journal = {{DFG forschung 1/2019}}, pages = {{12--15}}, title = {{{Lektionen für Alexa & Co?!}}}, doi = {{10.1002/fors.201970104}}, year = {{2019}}, } @article{36266, author = {{Weber, Jutta}}, journal = {{Gender, Technik und Politik 4.0 – Über digitalen Kapitalismus, disruptive Technologien und neue Regime der Unsicherheit, special issue of “Gender“ (Hg.: Jutta Weber/Diana Lengersdorf)}}, pages = {{7--10}}, title = {{{Vorwort: Gender, Technik und Politik 4.0 – Über digitalen Kapitalismus, disruptive Technologien und neue Regime der Unsicherheit}}}, volume = {{Vol. 11(3/19)}}, year = {{2019}}, } @article{15494, author = {{Hagengruber, Ruth}}, issn = {{09306633}}, journal = {{Konsens}}, keywords = {{Maria von Welser, Women, Media, War, Women in War, Refugees}}, number = {{2019}}, pages = {{20--22}}, publisher = {{Deutscher Akademikerinnen Bund}}, title = {{{Zur Ehrenpromotion von Maria von Welser an der Fakultät für Kulturwissenschaften der Universität Paderborn}}}, volume = {{2019}}, year = {{2019}}, } @techreport{36410, author = {{Becker, Rieke and Lauert, Markus and Otto, Arnold}}, title = {{{Tagungsbericht: Musiklandschaften zwischen Pader und Rhein. Pluralisierung und Verflechtung entlang des Hellwegs in der Frühen Neuzeit. Interdisziplinäre Tagung vom 15. bis 17. Juli 2019 in Paderborn}}}, year = {{2019}}, } @article{15444, author = {{Deppe, Michael and Henksmeier, Tobias and Gerlach, Jürgen W. and Reuter, Dirk and As, Donat J.}}, issn = {{0370-1972}}, journal = {{physica status solidi (b)}}, title = {{{Molecular Beam Epitaxy Growth and Characterization of Germanium‐Doped Cubic Al x Ga 1− x N}}}, doi = {{10.1002/pssb.201900532}}, year = {{2019}}, } @article{47951, abstract = {{Thin film lithium niobate has been of great interest recently, and an understanding of periodically poled thin films is crucial for both fundamental physics and device developments. Second-harmonic (SH) microscopy allows for the noninvasive visualization and analysis of ferroelectric domain structures and walls. While the technique is well understood in bulk lithium niobate, SH microscopy in thin films is largely influenced by interfacial reflections and resonant enhancements, which depend on film thicknesses and substrate materials. We present a comprehensive analysis of SH microscopy in x-cut lithium niobate thin films, based on a full three-dimensional focus calculation and accounting for interface reflections. We show that the dominant signal in backreflection originates from a copropagating phase-matched process observed through reflections, rather than direct detection of the counterpropagating signal as in bulk samples. We simulate the SH signatures of domain structures by a simple model of the domain wall as an extensionless transition from a −χ(2) to a +χ(2) region. This allows us to explain the main observation of domain structures in the thin-film geometry, and, in particular, we show that the SH signal from thin poled films allows to unambiguously distinguish areas, which are completely or only partly inverted in depth.}}, author = {{Rüsing, Michael and Zhao, J. and Mookherjea, S.}}, issn = {{0021-8979}}, journal = {{Journal of Applied Physics}}, keywords = {{General Physics and Astronomy}}, number = {{11}}, publisher = {{AIP Publishing}}, title = {{{Second harmonic microscopy of poled x-cut thin film lithium niobate: Understanding the contrast mechanism}}}, doi = {{10.1063/1.5113727}}, volume = {{126}}, year = {{2019}}, } @misc{48019, author = {{Meusel, Sarah and Abendroth, Sonja and Hoeft, Maike and Albers, Timm}}, title = {{{Leitfaden zur Gestaltung von Zugängen}}}, year = {{2019}}, } @inproceedings{15237, abstract = {{This paper presents an approach to voice conversion, whichdoes neither require parallel data nor speaker or phone labels fortraining. It can convert between speakers which are not in thetraining set by employing the previously proposed concept of afactorized hierarchical variational autoencoder. Here, linguisticand speaker induced variations are separated upon the notionthat content induced variations change at a much shorter timescale, i.e., at the segment level, than speaker induced variations,which vary at the longer utterance level. In this contribution wepropose to employ convolutional instead of recurrent networklayers in the encoder and decoder blocks, which is shown toachieve better phone recognition accuracy on the latent segmentvariables at frame-level due to their better temporal resolution.For voice conversion the mean of the utterance variables is re-placed with the respective estimated mean of the target speaker.The resulting log-mel spectra of the decoder output are used aslocal conditions of a WaveNet which is utilized for synthesis ofthe speech waveforms. Experiments show both good disentan-glement properties of the latent space variables, and good voiceconversion performance.}}, author = {{Gburrek, Tobias and Glarner, Thomas and Ebbers, Janek and Haeb-Umbach, Reinhold and Wagner, Petra}}, booktitle = {{Proc. 10th ISCA Speech Synthesis Workshop}}, location = {{Vienna}}, pages = {{81--86}}, title = {{{Unsupervised Learning of a Disentangled Speech Representation for Voice Conversion}}}, doi = {{10.21437/SSW.2019-15}}, year = {{2019}}, } @inproceedings{15794, abstract = {{In this paper we present our audio tagging system for the DCASE 2019 Challenge Task 2. We propose a model consisting of a convolutional front end using log-mel-energies as input features, a recurrent neural network sequence encoder and a fully connected classifier network outputting an activity probability for each of the 80 considered event classes. Due to the recurrent neural network, which encodes a whole sequence into a single vector, our model is able to process sequences of varying lengths. The model is trained with only little manually labeled training data and a larger amount of automatically labeled web data, which hence suffers from label noise. To efficiently train the model with the provided data we use various data augmentation to prevent overfitting and improve generalization. Our best submitted system achieves a label-weighted label-ranking average precision (lwlrap) of 75.5% on the private test set which is an absolute improvement of 21.7% over the baseline. This system scored the second place in the teams ranking of the DCASE 2019 Challenge Task 2 and the fifth place in the Kaggle competition “Freesound Audio Tagging 2019” with more than 400 participants. After the challenge ended we further improved performance to 76.5% lwlrap setting a new state-of-the-art on this dataset.}}, author = {{Ebbers, Janek and Haeb-Umbach, Reinhold}}, booktitle = {{DCASE2019 Workshop, New York, USA}}, title = {{{Convolutional Recurrent Neural Network and Data Augmentation for Audio Tagging with Noisy Labels and Minimal Supervision}}}, year = {{2019}}, } @inproceedings{15796, abstract = {{In this paper we consider human daily activity recognition using an acoustic sensor network (ASN) which consists of nodes distributed in a home environment. Assuming that the ASN is permanently recording, the vast majority of recordings is silence. Therefore, we propose to employ a computationally efficient two-stage sound recognition system, consisting of an initial sound activity detection (SAD) and a subsequent sound event classification (SEC), which is only activated once sound activity has been detected. We show how a low-latency activity detector with high temporal resolution can be trained from weak labels with low temporal resolution. We further demonstrate the advantage of using spatial features for the subsequent event classification task.}}, author = {{Ebbers, Janek and Drude, Lukas and Haeb-Umbach, Reinhold and Brendel, Andreas and Kellermann, Walter}}, booktitle = {{CAMSAP 2019, Guadeloupe, West Indies}}, title = {{{Weakly Supervised Sound Activity Detection and Event Classification in Acoustic Sensor Networks}}}, year = {{2019}}, } @inproceedings{15792, abstract = {{In this paper we highlight the privacy risks entailed in deep neural network feature extraction for domestic activity monitoring. We employ the baseline system proposed in the Task 5 of the DCASE 2018 challenge and simulate a feature interception attack by an eavesdropper who wants to perform speaker identification. We then propose to reduce the aforementioned privacy risks by introducing a variational information feature extraction scheme that allows for good activity monitoring performance while at the same time minimizing the information of the feature representation, thus restricting speaker identification attempts. We analyze the resulting model’s composite loss function and the budget scaling factor used to control the balance between the performance of the trusted and attacker tasks. It is empirically demonstrated that the proposed method reduces speaker identification privacy risks without significantly deprecating the performance of domestic activity monitoring tasks.}}, author = {{Nelus, Alexandru and Ebbers, Janek and Haeb-Umbach, Reinhold and Martin, Rainer}}, booktitle = {{INTERSPEECH 2019, Graz, Austria}}, title = {{{Privacy-preserving Variational Information Feature Extraction for Domestic Activity Monitoring Versus Speaker Identification}}}, year = {{2019}}, } @misc{49747, author = {{Huybrechts, Yves}}, publisher = {{BelgienNet}}, title = {{{Die Antwerpener Börse - Aufstieg, Niedergang und Wandel (VIDEO)}}}, year = {{2019}}, } @article{49878, author = {{Neiske, Iris and Vöing, Nera}}, issn = {{1860-3033}}, journal = {{Personal- und Organisationsentwicklung Forum für Führung, Moderation, Training, Programm-Organisation in Einrichtungen der Lehre und Forschung}}, number = {{3+4}}, pages = {{74--78}}, title = {{{Tätigkeitsbericht 2007-2017 der Stabsstelle Bildungsinnovationen und Hochschuldidaktik der Universität Paderborn}}}, volume = {{14}}, year = {{2019}}, } @article{49874, author = {{Neiske, Iris}}, issn = {{1434-9736}}, journal = {{Paderborner Universitätszeitschrift (puz)}}, pages = {{77}}, title = {{{Kurz berichtet. Das E-Tutoren-Programm an der UPB.}}}, year = {{2019}}, } @article{32156, abstract = {{How do ideas come into being? Our contribution takes its starting point in an observation we made in empirical data from a prior study. The data center around an instant of an academic writer’s thinking during the revision of a scientific paper. Through a detailed discourse-oriented micro-analysis, we zoom in on the writer’s thinking activity and uncover the genesis of a complex idea through a sequence of interrelated moments. These moments feature different degrees of “crystallization” of the idea; from gestures, a sketch, a short written note, oral explanations to a final spelled-out written argument. For this contribution, we re-analyze the material, asking how the idea gets formed during the thinking process and how it reaches a tangible form, which is understandable both for the thinker and for other persons. We root our analysis in a notion of language as social, embodied, and dialogical activity, drawing on concepts from Humboldt, Jakubinskij, and Vygotsky. We focus our analysis on three conceptual nodes. The first node is the ebbing and advancing of language in idea formation – observable as a trajectory through linguistically more condensed or more expanded utterance forms. The second node is the degree of objectification that the idea reaches when it is performed differently in a variety of addressivity constellations, i.e., whether and how it becomes understandable to the thinker and to others in the social sphere. Finally, the third node is the saturation of the idea through what we call intrapersonal intertextuality, i.e., its complex and dialogically related re-articulations in a sequence of formative moments. With these considerations, we articulate a clear consequence for theorizing thinking. We hold that thinking is social, embodied, and dialogically organized because it is entangled with language. Ideas come into being and become understandable and communicable to other persons only by and within their different, yet, intertextually related formations.}}, author = {{Karsten, Andrea and Bertau, Marie-Cécile}}, journal = {{Frontiers in Psychology}}, keywords = {{idea formation, language activity, objectification, intrapersonal intertextuality, articulation, Jakubinskij, Vygotsky, Humboldt}}, title = {{{How ideas come into being: Tracing intertextual moments in grades of objectification and publicness}}}, doi = {{10.3389/fpsyg.2019.02355}}, volume = {{10}}, year = {{2019}}, }