@inproceedings{64306,
  author       = {{Heermeier, Niels and Jung, Natalie and Lindemann, Markus and Gerhardt, Nils Christopher and Hofmann, Martin R. and Heuser, Tobias and Große, Jan and Kaganskiy, Arsenty and Reitzenstein, Stephan}},
  booktitle    = {{Spintronics XV}},
  title        = {{{Spin lasing in high-beta bimodal quantum dot micropillar cavities }}},
  doi          = {{10.1117/12.2632687}},
  year         = {{2022}},
}

@article{64307,
  author       = {{Gurevich, Evgeny L. and Hofmann, Martin R. and Gerhardt, Nils Christopher and Neutsch, Krisztian}},
  journal      = {{Nanomaterials}},
  number       = {{3}},
  title        = {{{Investigation of laser-induced periodic surface structures using synthetic optical holography}}},
  doi          = {{10.3390/nano12030505}},
  volume       = {{13}},
  year         = {{2022}},
}

@article{34230,
  abstract     = {{We present the design and experimental characterization of a silicon nitride pulse interleaver based on coupled resonator optical waveguide filters. In order to achieve a targeted free spectral range of 1.44 THz, which is large given the reduced optical confinement of the silicon nitride platform, individual ring resonators are designed with tapered waveguides. Its application to time-interleaved photonically-assisted ADCs is analyzed by combining experimental characterization of the photonic integrated circuit with a comprehensive model of the entire ADC. The impact of fundamental signal distortion and noise sources affecting the converter is investigated and suitable equalization techniques at the digital signal processing level are evaluated. The novel application of a simple but powerful equalization filter in the DSP domain allows for a significant improvement of the digitized signal SNR. An ENOB of 5 over a 75 GHz bandwidth (150 GS/s) and an ENOB of 4.3 over a 100 GHz bandwidth (200 GS/s) are expected to be achievable with compact and off-the-shelf single-section semiconductor mode locked lasers, that can be further improved with lower noise light sources.}},
  author       = {{Zazzi, Andrea and Müller, Juliana and Ghannam, Ibrahim and Battermann, Moritz and Rajeswari, Gayatri Vasudevan and Weizel, Maxim and Scheytt, J. Christoph and Witzens, Jeremy}},
  issn         = {{1094-4087}},
  journal      = {{Optics Express}},
  number       = {{3}},
  publisher    = {{Optica Publishing Group}},
  title        = {{{Wideband SiN pulse interleaver for optically-enabled analog-to-digital conversion: a device-to-system analysis with cyclic equalization}}},
  doi          = {{10.1364/oe.441406}},
  volume       = {{30}},
  year         = {{2022}},
}

@article{34239,
  author       = {{Bahmanian, Meysam and Scheytt, J. Christoph}},
  issn         = {{0018-9480}},
  journal      = {{IEEE Transactions on Microwave Theory and Techniques}},
  number       = {{10}},
  pages        = {{4422--4435}},
  publisher    = {{Institute of Electrical and Electronics Engineers (IEEE)}},
  title        = {{{Noise Processes and Nonlinear Mechanisms in Optoelectronic Phase-Locked Loop Using a Balanced Optical Microwave Phase Detector}}},
  doi          = {{10.1109/tmtt.2022.3197621}},
  volume       = {{70}},
  year         = {{2022}},
}

@article{30511,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>Many critical codebases are written in C, and most of them use preprocessor directives to encode variability, effectively encoding software product lines. These preprocessor directives, however, challenge any static code analysis. SPLlift, a previously presented approach for analyzing software product lines, is limited to Java programs that use a rather simple feature encoding and to analysis problems with a finite and ideally small domain. Other approaches that allow the analysis of real-world C software product lines use special-purpose analyses, preventing the reuse of existing analysis infrastructures and ignoring the progress made by the static analysis community. This work presents <jats:sc>VarAlyzer</jats:sc>, a novel static analysis approach for software product lines. <jats:sc>VarAlyzer</jats:sc> first transforms preprocessor constructs to plain C while preserving their variability and semantics. It then solves any given distributive analysis problem on transformed product lines in a variability-aware manner. <jats:sc>VarAlyzer</jats:sc> ’s analysis results are annotated with feature constraints that encode in which configurations each result holds. Our experiments with 95 compilation units of OpenSSL show that applying <jats:sc>VarAlyzer</jats:sc> enables one to conduct inter-procedural, flow-, field- and context-sensitive data-flow analyses on entire product lines for the first time, outperforming the product-based approach for highly-configurable systems.</jats:p>}},
  author       = {{Schubert, Philipp and Gazzillo, Paul and Patterson, Zach and Braha, Julian and Schiebel, Fabian Benedikt and Hermann, Ben and Wei, Shiyi and Bodden, Eric}},
  issn         = {{0928-8910}},
  journal      = {{Automated Software Engineering}},
  keywords     = {{inter-procedural static analysis, software product lines, preprocessor, LLVM, C/C++}},
  number       = {{1}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{Static data-flow analysis for software product lines in C}}},
  doi          = {{10.1007/s10515-022-00333-1}},
  volume       = {{29}},
  year         = {{2022}},
}

@article{30210,
  abstract     = {{Lithium niobate on insulator (LNOI) has a great potential for photonic integrated circuits, providing substantial versatility in design of various integrated components. To properly use these components in the implementation of different quantum protocols, photons with different properties are required. In this paper, we theoretically demonstrate a flexible source of correlated photons built on the LNOI waveguide of a special geometry. This source is based on the parametric down-conversion (PDC) process, in which the signal and idler photons are generated at the telecom wavelength and have different spatial profiles and polarizations, but the same group velocities. Distinguishability in polarizations and spatial profiles facilitates the routing and manipulating individual photons, while the equality of their group velocities leads to the absence of temporal walk-off between photons. We show how the spectral properties of the generated photons and the number of their frequency modes can be controlled depending on the pump characteristics and the waveguide length. Finally, we discuss special regimes, in which narrowband light with strong frequency correlations and polarization-entangled Bell states are generated at the telecom wavelength.}},
  author       = {{Ebers, Lena and Ferreri, Alessandro and Hammer, Manfred and Albert, Maximilian and Meier, Cedrik and Förstner, Jens and Sharapova, Polina R.}},
  issn         = {{2515-7647}},
  journal      = {{Journal of Physics: Photonics}},
  keywords     = {{tet_topic_waveguide}},
  pages        = {{025001}},
  publisher    = {{IOP Publishing}},
  title        = {{{Flexible source of correlated photons based on LNOI rib waveguides}}},
  doi          = {{10.1088/2515-7647/ac5a5b}},
  volume       = {{4}},
  year         = {{2022}},
}

@inproceedings{40212,
  author       = {{Haucke-Korber, Barnabas and Schenke, Maximilian and Wallscheid, Oliver}},
  booktitle    = {{IKMT 2022; 13. GMM/ETG-Symposium}},
  pages        = {{1--6}},
  title        = {{{Reinforcement Learning-Based Deep Q Direct Torque Control with Adaptable Switching Frequency Towards Six-Step Operation of Permanent Magnet Synchronous Motors}}},
  year         = {{2022}},
}

@inproceedings{6553,
  author       = {{Claes, Leander and Feldmann, Nadine and Schulze, Veronika and Jurgelucks, Benjamin and Walther, Andrea and Henning, Bernd}},
  booktitle    = {{Fortschritte der Akustik - DAGA 2022}},
  location     = {{Stuttgart}},
  pages        = {{1326--1329}},
  title        = {{{Identification of piezoelectric material parameters using optimised multi-electrode specimens}}},
  year         = {{2022}},
}

@misc{6558,
  author       = {{Friesen, Olga and Claes, Leander and Feldmann, Nadine and Henning, Bernd}},
  title        = {{{Estimation of piezoelectric material parameters of ring-shaped specimens}}},
  year         = {{2022}},
}

@techreport{49113,
  abstract     = {{In this report we present our system for the Detection and Classification of Acoustic Scenes and Events (DCASE) 2022 Challenge Task 4: Sound Event Detection in Domestic Environments 1 . As in previous editions of the Challenge, we use forward-backward convolutional recurrent neural networks (FBCRNNs) [1, 2] for weakly labeled and semi-supervised sound event detection (SED) and eventually generate strong pseudo labels for weakly labeled and unlabeled data. Then, (tag-conditioned) bidirectional CRNNs (Bi-CRNNs) [1, 2] are trained in a strongly supervised manner as our final SED models. In each of the training stages we use multiple iterations of self-training. Compared to previous editions, we improved our system performance by 1) some tweaks regarding data augmentation, pseudo labeling and inference 2) using weakly labeled AudioSet data [3] for pretraining larger networks and 3) augmenting the DESED data [4] with strongly labeled AudioSet data [5] for finetuning of the networks. Source code is publicly available at https://github.com/fgnt/pb_sed.}},
  author       = {{Ebbers, Janek and Haeb-Umbach, Reinhold}},
  title        = {{{Pre-Training And Self-Training For Sound Event Detection In Domestic Environments}}},
  year         = {{2022}},
}

@misc{48628,
  author       = {{Kruse, Stephan and Scheytt, J. Christoph}},
  title        = {{{Elektrooptischer Mischer}}},
  year         = {{2022}},
}

@article{34614,
  abstract     = {{Mit steigenden Optimierungsanforderungen an das Individuum wächst auch das indivi-
duelle Bedürfnis nach Kontrolle. Dieses kann u. a. durch self tracking-Technologien erfüllt werden.
Anhand von drei Fallbeispielen – der Personenwaage, dem Wearable und dem habit tracker – zeigt
dieser Aufsatz, wie sich medienbasierte Selbsttechnologien im historischen Verlauf intensiviert und
stärker in den Alltag integriert haben. Ein besonderer Fokus liegt dabei auf der Ambivalenz dieser
Medien: Ermöglichen sie auf der einen Seite zwar eine Selbstkontrolle und stellen so potenziell sta-
bilisierende Ressourcen für das Individuum dar, schaffen sie auf der anderen Seite auch neue
Anforderungen, die es zu erfüllen gilt.}},
  author       = {{Schloots, Franziska Margarete}},
  journal      = {{ffk Journal}},
  keywords     = {{self-tracking, Selbsttechnologien, Wearable, Bullet Journal, Personenwaage, Selbstvermessung}},
  number       = {{7}},
  pages        = {{74--91}},
  title        = {{{‚Understand what’s happening within‘. Selbstkontrolle mit Personenwaage, Wearable und habit tracker}}},
  doi          = {{10.25969/MEDIAREP/18238}},
  volume       = {{6}},
  year         = {{2022}},
}

@inbook{56202,
  author       = {{Sjuts, Johann}},
  booktitle    = {{Konzepte und Studien zur Hochschuldidaktik und Lehrerbildung Mathematik}},
  isbn         = {{9783658340667}},
  issn         = {{2197-8751}},
  publisher    = {{Springer Fachmedien Wiesbaden}},
  title        = {{{Lehrerbildung als staatliche und gesellschaftliche Aufgabe angesichts gegenwärtiger und zukünftiger Herausforderungen}}},
  doi          = {{10.1007/978-3-658-34067-4_2}},
  year         = {{2022}},
}

@inproceedings{33509,
  abstract     = {{In this publication a novel method for far-field prediction from magnetic Huygens box data based on the boundary element method (BEM) is presented. Two examples are considered for the validation of this method. The first example represents an electric dipole so that the obtained calculations can be compared to an analytical solution. As a second example, a printed circuit board is considered and the calculated far-field is compared to a fullwave simulation. In both cases, the calculations for different field integral equations are under comparison, and the results indicate that the presented method performs very well with a combined field integral equation, for the specified problem, when only magnetic Huygens box data is given.}},
  author       = {{Marschalt, Christoph and Schroder, Dominik and Lange, Sven and Hilleringmann, Ulrich and Hedayat, Christian and Kuhn, Harald and Sievers, Denis and Förstner, Jens}},
  booktitle    = {{2022 Smart Systems Integration (SSI)}},
  keywords     = {{Near-Field Scanning, Huygens Box, Boundary Element Method, Method of Moments, tet_topic_hf, tet_enas}},
  location     = {{Grenoble, France}},
  publisher    = {{IEEE}},
  title        = {{{Far-field Calculation from magnetic Huygens Box Data using the Boundary Element Method}}},
  doi          = {{10.1109/ssi56489.2022.9901431}},
  year         = {{2022}},
}

@inproceedings{33848,
  abstract     = {{Impressive progress in neural network-based single-channel speech source
separation has been made in recent years. But those improvements have been
mostly reported on anechoic data, a situation that is hardly met in practice.
Taking the SepFormer as a starting point, which achieves state-of-the-art
performance on anechoic mixtures, we gradually modify it to optimize its
performance on reverberant mixtures. Although this leads to a word error rate
improvement by 7 percentage points compared to the standard SepFormer
implementation, the system ends up with only marginally better performance than
a PIT-BLSTM separation system, that is optimized with rather straightforward
means. This is surprising and at the same time sobering, challenging the
practical usefulness of many improvements reported in recent years for monaural
source separation on nonreverberant data.}},
  author       = {{Cord-Landwehr, Tobias and Boeddeker, Christoph and von Neumann, Thilo and Zorila, Catalin and Doddipatla, Rama and Haeb-Umbach, Reinhold}},
  booktitle    = {{2022 International Workshop on Acoustic Signal Enhancement (IWAENC)}},
  publisher    = {{IEEE}},
  title        = {{{Monaural source separation: From anechoic to reverberant environments}}},
  year         = {{2022}},
}

@inproceedings{33819,
  author       = {{von Neumann, Thilo and Kinoshita, Keisuke and Boeddeker, Christoph and Delcroix, Marc and Haeb-Umbach, Reinhold}},
  booktitle    = {{ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}},
  publisher    = {{IEEE}},
  title        = {{{SA-SDR: A Novel Loss Function for Separation of Meeting Style Data}}},
  doi          = {{10.1109/icassp43922.2022.9746757}},
  year         = {{2022}},
}

@misc{33816,
  author       = {{Gburrek, Tobias and Boeddeker, Christoph and von Neumann, Thilo and Cord-Landwehr, Tobias and Schmalenstroeer, Joerg and Haeb-Umbach, Reinhold}},
  publisher    = {{arXiv}},
  title        = {{{A Meeting Transcription System for an Ad-Hoc Acoustic Sensor Network}}},
  doi          = {{10.48550/ARXIV.2205.00944}},
  year         = {{2022}},
}

@inproceedings{33954,
  author       = {{Boeddeker, Christoph and Cord-Landwehr, Tobias and von Neumann, Thilo and Haeb-Umbach, Reinhold}},
  booktitle    = {{Interspeech 2022}},
  publisher    = {{ISCA}},
  title        = {{{An Initialization Scheme for Meeting Separation with Spatial Mixture Models}}},
  doi          = {{10.21437/interspeech.2022-10929}},
  year         = {{2022}},
}

@inproceedings{33958,
  abstract     = {{Recent speaker diarization studies showed that integration of end-to-end neural diarization (EEND) and clustering-based diarization is a promising approach for achieving state-of-the-art performance on various tasks. Such an approach first divides an observed signal into fixed-length segments, then performs {\it segment-level} local diarization based on an EEND module, and merges the segment-level results via clustering to form a final global diarization result. The segmentation is done to limit the number of speakers in each segment since the current EEND cannot handle a large number of speakers. In this paper, we argue that such an approach involving the segmentation has several issues; for example, it inevitably faces a dilemma that larger segment sizes increase both the context available for enhancing the performance and the number of speakers for the local EEND module to handle. To resolve such a problem, this paper proposes a novel framework that performs diarization without segmentation. However, it can still handle challenging data containing many speakers and a significant amount of overlapping speech. The proposed method can take an entire meeting for inference and perform {\it utterance-by-utterance} diarization that clusters utterance activities in terms of speakers. To this end, we leverage a neural network training scheme called Graph-PIT proposed recently for neural source separation. Experiments with simulated active-meeting-like data and CALLHOME data show the superiority of the proposed approach over the conventional methods.}},
  author       = {{Kinoshita, Keisuke and von Neumann, Thilo and Delcroix, Marc and Boeddeker, Christoph and Haeb-Umbach, Reinhold}},
  booktitle    = {{Proc. Interspeech 2022}},
  pages        = {{1486--1490}},
  publisher    = {{ISCA}},
  title        = {{{Utterance-by-utterance overlap-aware neural diarization with Graph-PIT}}},
  doi          = {{10.21437/Interspeech.2022-11408}},
  year         = {{2022}},
}

@inproceedings{32247,
  author       = {{Alshomary, Milad and Rieskamp, Jonas and Wachsmuth, Henning}},
  booktitle    = {{Proceedings of the 9th International Conference on Computational Models of Argument}},
  pages        = {{21 -- 31}},
  title        = {{{Generating Contrastive Snippets for Argument Search}}},
  doi          = {{http://dx.doi.org/10.3233/FAIA220138}},
  year         = {{2022}},
}