@inproceedings{34136,
  author       = {{Grynko, Yevgen and Shkuratov, Yuriy and Alhaddad, Samer and Förstner, Jens}},
  keywords     = {{tet_topic_scattering}},
  location     = {{Granada, Spain}},
  publisher    = {{Copernicus GmbH}},
  title        = {{{Light backscattering from numerical analog of planetary regoliths}}},
  doi          = {{10.5194/epsc2022-151}},
  year         = {{2022}},
}

@inproceedings{64115,
  author       = {{Awais, Muhammad and Platzner, Marco}},
  booktitle    = {{2022 IFIP/IEEE 30th International Conference on Very Large Scale Integration (VLSI-SoC)}},
  publisher    = {{IEEE}},
  title        = {{{Automated Framework for Fast Synthesis of Approximate Hardware Accelerators}}},
  doi          = {{10.1109/vlsi-soc54400.2022.9939606}},
  year         = {{2022}},
}

@inproceedings{64260,
  author       = {{Mager, Thomas and Jürgenhake, Christoph and Dumitrescu, Roman}},
  booktitle    = {{Proceedings of the German Microwave Conference (GeMiC)}},
  location     = {{Ulm}},
  pages        = {{224--227}},
  title        = {{{Efficient method for determining substrate parameters of additive manufactured spatial circuit carriers}}},
  year         = {{2022}},
}

@misc{64268,
  author       = {{Kuit, Job}},
  title        = {{{Plancherel theory on real spherical spaces}}},
  year         = {{2022}},
}

@article{59668,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>Spin‐controlled lasers are highly interesting photonic devices and have been shown to provide ultrafast polarization dynamics in excess of 200 GHz. In contrast to conventional semiconductor lasers their temporal properties are not limited by the intensity dynamics, but are governed primarily by the interaction of the spin dynamics with the birefringent mode splitting that determines the polarization oscillation frequency. Another class of modern semiconductor lasers are high‐<jats:italic>β</jats:italic> emitters, which benefit from enhanced light–matter interaction due to strong mode confinement in low‐mode‐volume microcavities. In such structures, the emission properties can be tailored by the resonator geometry to realize for instance bimodal emission behavior in slightly elliptical micropillar cavities. This attractive feature is utilized to demonstrate and explore spin‐lasing effects in bimodal high‐<jats:italic>β</jats:italic> quantum dot micropillar lasers. The studied microlasers with a <jats:italic>β</jats:italic>‐factor of 4% show spin‐laser effects with experimental polarization oscillation frequencies up to 15 GHz and predicted frequencies up to about 100 GHz, which are controlled by the ellipticity of the resonator. These results reveal appealing prospects for very compact, ultrafast, and energy‐efficient spin‐lasers and can pave the way for future purely electrically injected spin‐lasers enabled by short injection path lengths.</jats:p>}},
  author       = {{Heermeier, Niels and Heuser, Tobias and Große, Jan and Jung, Natalie and Kaganskiy, Arsenty and Lindemann, Markus and Gerhardt, Nils Christopher and Hofmann, Martin R. and Reitzenstein, Stephan}},
  issn         = {{1863-8880}},
  journal      = {{Laser &amp; Photonics Reviews}},
  number       = {{4}},
  publisher    = {{Wiley}},
  title        = {{{Spin‐Lasing in Bimodal Quantum Dot Micropillar Cavities}}},
  doi          = {{10.1002/lpor.202100585}},
  volume       = {{16}},
  year         = {{2022}},
}

@inproceedings{46305,
  abstract     = {{Hardness of Multi-Objective (MO) continuous optimization problems results from an interplay of various problem characteristics, e. g. the degree of multi-modality. We present a benchmark study of classical and diversity focused optimizers on multi-modal MO problems based on automated algorithm configuration. We show the large effect of the latter and investigate the trade-off between convergence in objective space and diversity in decision space.}},
  author       = {{Rook, J and Trautmann, Heike and Bossek, Jakob and Grimme, C}},
  booktitle    = {{Proceedings of the Genetic and Evolutionary Computation Conference Companion}},
  editor       = {{Fieldsend, J and Wagner, M.}},
  isbn         = {{9781450392686}},
  pages        = {{356–359}},
  publisher    = {{Association for Computing Machinery}},
  title        = {{{On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems}}},
  doi          = {{10.1145/3520304.3528998}},
  year         = {{2022}},
}

@article{64264,
  abstract     = {{<jats:title>Abstract</jats:title>
               <jats:p>Künstliche Intelligenz bietet großes Potenzial im Engineering. Der Einsatz gestattet insbesondere für Wissensarbeiter eine effiziente Arbeitsteilung, in der beispielsweise fehleranfällige und repetitive Aktivitäten unterstützt werden. Eine erfolgreiche Einführung bedarf einer vorangehenden Analyse von nutzenstiftenden Einsatzpotenzialen, bei der alle Anwendenden frühzeitig einbezogen werden. Der folgende Beitrag verdeutlicht dieses Vorgehen anhand eines realen Beispiels im Sondermaschinenbau.</jats:p>}},
  author       = {{Kharatyan, Aschot and Humpert, Lynn and Anacker, Harald and Dumitrescu, Roman and Wäschle, Moritz and Albers, Albert and Horstmeyer, Sarah}},
  issn         = {{2511-0896}},
  journal      = {{Zeitschrift für wirtschaftlichen Fabrikbetrieb}},
  number       = {{6}},
  pages        = {{427--431}},
  publisher    = {{Walter de Gruyter GmbH}},
  title        = {{{Künstliche Intelligenz im Engineering}}},
  doi          = {{10.1515/zwf-2022-1074}},
  volume       = {{117}},
  year         = {{2022}},
}

@article{64263,
  abstract     = {{<jats:title>Abstract</jats:title>
               <jats:p>Künstliche Intelligenz bietet großes Potenzial im Engineering. Der Einsatz gestattet insbesondere für Wissensarbeiter eine effiziente Arbeitsteilung, in der beispielsweise fehleranfällige und repetitive Aktivitäten unterstützt werden. Eine erfolgreiche Einführung bedarf einer vorangehenden Analyse von nutzenstiftenden Einsatzpotenzialen, bei der alle Anwendenden frühzeitig einbezogen werden. Der folgende Beitrag verdeutlicht dieses Vorgehen anhand eines realen Beispiels im Sondermaschinenbau.</jats:p>}},
  author       = {{Kharatyan, Aschot and Humpert, Lynn and Anacker, Harald and Dumitrescu, Roman and Wäschle, Moritz and Albers, Albert and Horstmeyer, Sarah}},
  issn         = {{2511-0896}},
  journal      = {{Zeitschrift für wirtschaftlichen Fabrikbetrieb}},
  number       = {{6}},
  pages        = {{427--431}},
  publisher    = {{Walter de Gruyter GmbH}},
  title        = {{{Künstliche Intelligenz im Engineering}}},
  doi          = {{10.1515/zwf-2022-1074}},
  volume       = {{117}},
  year         = {{2022}},
}

@article{64570,
  author       = {{Olbrich, Martin and Palmirotta, Guendalina}},
  issn         = {{0232-704X}},
  journal      = {{Annals of Global Analysis and Geometry}},
  number       = {{1}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{Delorme’s intertwining conditions for sections of homogeneous vector bundles on two- and three-dimensional hyperbolic spaces}}},
  doi          = {{10.1007/s10455-022-09882-w}},
  volume       = {{63}},
  year         = {{2022}},
}

@article{64571,
  abstract     = {{We study the Fourier transform for compactly supported distributional sections of complex homogeneous vector bundles on symmetric spaces of non-compact type $X = G/K$. We prove a characterisation of their range. In fact, from Delorme's Paley-Wiener theorem for compactly supported smooth functions on a real reductive group of Harish-Chandra class, we deduce topological Paley-Wiener and Paley-Wiener-Schwartz theorems for sections.}},
  author       = {{Olbrich, Martin and Palmirotta, Guendalina}},
  journal      = {{Journal of Lie theory}},
  number       = {{2}},
  pages        = {{53----384}},
  publisher    = {{Heldermann Verlag}},
  title        = {{{A topological Paley-Wiener-Schwartz Theorem for sections of homogeneous vector bundles on $G/K$}}},
  volume       = {{34}},
  year         = {{2022}},
}

@inproceedings{59758,
  author       = {{Mwammenywa, Ibrahim and Kagarura, Geoffrey Mark and Petrov, Dmitry and Holle, Philip and Hilleringmann, Ulrich}},
  booktitle    = {{2021 International Conference on Electrical, Computer and Energy Technologies (ICECET)}},
  publisher    = {{IEEE}},
  title        = {{{LoRa-based Demand-side Load Monitoring and Management System for Microgrids in Africa}}},
  doi          = {{10.1109/icecet52533.2021.9698506}},
  year         = {{2022}},
}

@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}},
}

@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}},
}