@inproceedings{33508,
  abstract     = {{In this work, methods will be evaluated to numerically calculate the passive electrical parameters of planar coils. These parameters can then be used to optimize inductive applications such as wireless power transmission. The focus here will be on inductive localization, which uses high-frequency magnetic fields and the resulting induced voltage to provide localization through the coupling parameter mutual inductance. To achieve localization with high accuracy and best possible operation (resonance, signal strength, etc.), the coil parameters need to be well known. For this reason, some numerical methods for the calculation of these quantities are presented and validated. In addition, the physical effects are thereby considered in more detail, allowing the localization procedure to be better optimized compared to simulative black-box methods. The goal should be a dedicated simulation platform for planar coils to be able to develop training data for neural networks and to test and optimize localization algorithms.}},
  author       = {{Lange, Sven and Hedayat, Christian and Kuhn, Harald and Hilleringmann, Ulrich}},
  booktitle    = {{2022 Smart Systems Integration (SSI)}},
  keywords     = {{Simulation Environment, Inductive Localization, Coil Parameters, Inductive Applications, Near-Field}},
  location     = {{Grenoble, France}},
  publisher    = {{IEEE}},
  title        = {{{Modeling and Characterization of a 3D Environment for the Design of an Inductively Based Locating Method by Coil Couplings}}},
  doi          = {{10.1109/ssi56489.2022.9901416}},
  year         = {{2022}},
}

@inproceedings{33510,
  abstract     = {{In the manufacture of real wood products, defects can quickly occur during the production process. To quickly sort out these defects, a system is needed that finds damage in the irregularly structured surfaces of the product. The difficulty in this task is that each surface is visually different and no standard defects can be defined. Thus, damage detection using correlation does not work, so this paper will test different machine learning methods. To evaluate different machine learning methods, a data set is needed. For this reason, the available samples were recorded manually using a static fixed camera. Subsequently, the images were divided into sub-images, which resulted in a relatively small data set. Next, a convolutional neural network (CNN) was constructed to classify the images. However, this approach did not lead to a generalized solution, so the dataset was hashed using the a- and pHash. These hash values were then trained with a fully supervised system that will later serve as a reference model, in the semi-supervised learning procedures. To improve the supervised model and not have to label every data point, semi-supervised learning methods are used in the following. For this purpose, the CEAL method (wrapper method) is considered in the first and then the Π-Model (intrinsically semi-supervised).}},
  author       = {{Sander, Tom and Lange, Sven and Hilleringmann, Ulrich and Geneiß, Volker and Hedayat, Christian and Kuhn, Harald}},
  booktitle    = {{2022 Smart Systems Integration (SSI)}},
  keywords     = {{Machine Learning, CNN, Hashing, semi-supervised learning}},
  location     = {{Grenoble, France}},
  publisher    = {{IEEE}},
  title        = {{{Detection of Defects on Irregularly Structured Surfaces using Supervised and Semi-Supervised Learning Methods}}},
  doi          = {{10.1109/ssi56489.2022.9901433}},
  year         = {{2022}},
}

@misc{17090,
  author       = {{Itner, Dominik and Gravenkamp, Hauke and Dreiling, Dmitrij and Birk, Carolin and Henning, Bernd}},
  publisher    = {{International Association for Computational Mechanics (IACM)}},
  title        = {{{Differentiation of an SBFE model in the context of material parameter determination}}},
  year         = {{2022}},
}

@article{35128,
  abstract     = {{Here we demonstrate a new, to the best of our knowledge, type of 3-dB coupler that has an ultra-broadband operational range from 1300 to 1600 nm with low fabrication sensitivity. The overall device size is 800 µm including in/out S-bend waveguides. The coupler is an asymmetric non-uniform directional coupler that consists of two tapered waveguides. One of the coupler arms is shifted by 100 µm in the propagation direction, which results in a more wavelength-insensitive 3-dB response compared to a standard (not shifted) coupler. Moreover, compared to a long adiabatic coupler, we achieved a similar wavelength response at a 16-times-smaller device length. The couplers were fabricated using the silicon nitride platform of Lionix International. We also experimentally demonstrated an optical switch that is made by using two of these couplers in a Mach–Zehnder interferometer configuration. According to experimental results, this optical switch exhibits –10 dB of extinction ratio over the 1500–1600 nm wavelength range. Our results indicate that this new type of coupler holds great promise for various applications, including optical imaging, telecommunications, and reconfigurable photonic processors where compact, fabrication-tolerant, and wavelength-insensitive couplers are essential.}},
  author       = {{Nikbakht, Hamed and Khoshmehr, Mohammad Talebi and van Someren, Bob and Teichrib, Dieter and Hammer, Manfred and Förstner, Jens and Akca, B. Imran}},
  issn         = {{0146-9592}},
  journal      = {{Optics Letters}},
  keywords     = {{tet_topic_waveguide}},
  number       = {{2}},
  pages        = {{207}},
  publisher    = {{Optica Publishing Group}},
  title        = {{{Asymmetric, non-uniform 3-dB directional coupler with 300-nm bandwidth and a small footprint}}},
  doi          = {{10.1364/ol.476537}},
  volume       = {{48}},
  year         = {{2022}},
}

@inbook{33703,
  author       = {{Jonas-Ahrend, Gabriela and Vernholz, Mats and Temmen, Katrin}},
  booktitle    = {{Berufsausbildung zwischen Hygienemaßnahmen und Lockdown(s): Folgen für die schulische und außerschulische Berufsausbildung in Schule, im Betrieb und bei Bildungsträgern}},
  editor       = {{Heisler, Dietmar and Meier, Jörg A.}},
  pages        = {{257--276}},
  publisher    = {{wbv }},
  title        = {{{Wie bewährt sich das duale berufliche Ausbildungssystem der industriellen Metall und Elektroausbildung unter Pandemiebedingungen? Lehrkräfte und Auszubildende reflektieren}}},
  doi          = {{10.3278/9783763972579}},
  year         = {{2022}},
}

@inproceedings{35570,
  author       = {{Tjell, Katrine and Schluter, Nils and Binfet, Philipp and Schulze Darup, Moritz }},
  booktitle    = {{2021 60th IEEE Conference on Decision and Control (CDC)}},
  publisher    = {{IEEE}},
  title        = {{{Secure learning-based MPC via garbled circuit}}},
  doi          = {{10.1109/cdc45484.2021.9683540}},
  year         = {{2022}},
}

@inproceedings{35573,
  author       = {{Schluter, Nils and Neuhaus, Matthias and Schulze Darup, Moritz}},
  booktitle    = {{2021 European Control Conference (ECC)}},
  publisher    = {{IEEE}},
  title        = {{{Encrypted dynamic control with unlimited operating time via FIR filters}}},
  doi          = {{10.23919/ecc54610.2021.9655161}},
  year         = {{2022}},
}

@inproceedings{35569,
  author       = {{Teichrib, Dieter and Schulze Darup, Moritz}},
  booktitle    = {{2021 60th IEEE Conference on Decision and Control (CDC)}},
  publisher    = {{IEEE}},
  title        = {{{Tailored neural networks for learning optimal value functions in MPC}}},
  doi          = {{10.1109/cdc45484.2021.9683528}},
  year         = {{2022}},
}

@article{35586,
  author       = {{Protte, Marius and Fahr, Rene and Quevedo, Daniel E.}},
  issn         = {{1066-033X}},
  journal      = {{IEEE Control Systems}},
  keywords     = {{Electrical and Electronic Engineering, Modeling and Simulation, Control and Systems Engineering, Electrical and Electronic Engineering, Modeling and Simulation, Control and Systems Engineering}},
  number       = {{6}},
  pages        = {{57--76}},
  publisher    = {{Institute of Electrical and Electronics Engineers (IEEE)}},
  title        = {{{Behavioral Economics for Human-in-the-Loop Control Systems Design: Overconfidence and the Hot Hand Fallacy}}},
  doi          = {{10.1109/mcs.2020.3019723}},
  volume       = {{40}},
  year         = {{2022}},
}

@inbook{33466,
  abstract     = {{We review our results of numerical simulations of light scattering from different systems of densely packed irregular particles. We consider spherical clusters, thick layers and monolayers with realistic topologies and dimensions much larger than the wavelength of light. The maximum bulk packing density of clusters is 0.5. A numerically exact solution of the electromagnetic problem is obtained using the Discontinuous Galerkin Time Domain method and with application of high- performance computing. We show that high packing density causes light localization in such structures which makes an impact on the opposition phenomena: backscattering intensity surge and negative linear polarization feature. Diffuse multiple scattering is significantly reduced in the case of non-absorbing particles and near-field interaction results in a percolation-like light transport determined by the topology of the medium. With this the negative polarization feature caused by single scattering gets enhanced if compared to lower density samples. We also confirm coherent double scattering mechanism of negative polarization for light scattered from dense absorbing slabs. In this case convergent result for the scattering angle polarization dependency at backscattering can be obtained for a layer of just a few tens of particles if they are larger than the wavelength.}},
  author       = {{Grynko, Yevgen and Shkuratov, Yuriy and Alhaddad, Samer and Förstner, Jens}},
  booktitle    = {{Springer Series in Light Scattering - Volume 8: Light Polarization and Multiple Scattering in Turbid Media}},
  editor       = {{Kokhanovsky, Alexander}},
  isbn         = {{9783031102974}},
  issn         = {{2509-2790}},
  keywords     = {{tet_topic_scattering}},
  publisher    = {{Springer International Publishing}},
  title        = {{{Light Scattering by Large Densely Packed Clusters of Particles}}},
  doi          = {{10.1007/978-3-031-10298-1_4}},
  volume       = {{8}},
  year         = {{2022}},
}

@misc{36109,
  author       = {{Knorr, Lukas and Schlosser, Florian and Meschede, Henning}},
  publisher    = {{17th sdewes conference}},
  title        = {{{Assessment of Energy Efficiency and Flexibility Measures in Electrified Process Heat Generation Based on Simulations in the Animal Feed Industry}}},
  year         = {{2022}},
}

@inproceedings{34176,
  abstract     = {{Cascaded H-bridge Converters (CHBs) are a promising solution in converting power from a three-phase medium voltage of 6.6 kV...30 kV to a lower DC-voltage in the range of 100 V...1 kV to provide pure DC power to applications such as electrolyzers for hydrogen generation, data centers with a DC power distribution and DC microgrids. CHBs can be interpreted as modular multilevel converters with an isolated DC-DC output stage per module, require a large DC-link capacitor for each module to handle the second harmonic voltage ripple caused by the fluctuating input power within a fundamental grid period. Without a zero-sequence voltage injection, star-connected CHBs are operated with approximately sinusoidal arm voltages and currents. The floating star point potential enables to utilize different zero-sequence voltage injection techniques such as a third-harmonic injection with 1/6 of the grid voltage amplitude or a Min-Max voltage injection. Both well-known methods have the advantage to reduce the peak arm voltage and thereby the number of required modules by 13.4 % (to √ 3 2). This paper proves analytically that the third-harmonic injection with 1/6 of the grid voltage amplitude reduces the second harmonic voltage ripple by only 15.1 % compared to no-voltage injection for unity power factor operation and balanced grid voltages. Then it is shown, that the Min-Max injection has the often overlooked advantage of reducing the second harmonic voltage ripple by even 18.8 %. By applying the here proposed zero-sequence voltage injection in saturation modulation, the second harmonic voltage ripple of the DC-link capacitors is reduced by even 24.3 %, while still requiring the same number of modules as the Min-Max injection. For a realistic number of reserve modules, the overall energy ripple in the DC-link capacitors is reduced by 40 %.}},
  author       = {{Unruh, Roland and Schafmeister, Frank and Böcker, Joachim}},
  booktitle    = {{24th European Conference on Power Electronics and Applications (EPE'22 ECCE Europe)}},
  isbn         = {{978-9-0758-1539-9}},
  keywords     = {{Cascaded H-Bridge, Solid-State Transformer, Zero sequence voltage, Third harmonic injection, Capacitor voltage ripple}},
  location     = {{Hanover, Germany}},
  publisher    = {{IEEE}},
  title        = {{{Zero-Sequence Voltage Reduces DC-Link Capacitor Demand in Cascaded H-Bridge Converters for Large-Scale Electrolyzers by 40%}}},
  year         = {{2022}},
}

@inproceedings{33471,
  abstract     = {{The intelligibility of demodulated audio signals from analog high frequency transmissions, e.g., using single-sideband
(SSB) modulation, can be severely degraded by channel distortions and/or a mismatch between modulation and demodulation carrier frequency. In this work a neural network (NN)-based approach for carrier frequency offset (CFO) estimation from demodulated SSB signals is proposed, whereby a task specific architecture is presented. Additionally, a simulation framework for SSB signals is introduced and utilized for training the NNs. The CFO estimator is combined with a speech enhancement network to investigate its influence on the enhancement performance. The NN-based system is compared to a recently proposed pitch tracking based approach on publicly available data from real high frequency transmissions. Experiments show that the NN exhibits good CFO estimation properties and results in significant improvements in speech intelligibility, especially when combined with a noise reduction network.}},
  author       = {{Heitkämper, Jens and Schmalenstroeer, Joerg and Haeb-Umbach, Reinhold}},
  booktitle    = {{Proceedings of the 30th European Signal Processing Conference (EUSIPCO)}},
  location     = {{Belgrad}},
  title        = {{{Neural Network Based Carrier Frequency Offset Estimation From Speech Transmitted Over High Frequency Channels}}},
  year         = {{2022}},
}

@inproceedings{33806,
  author       = {{Afifi, Haitham and Karl, Holger and Gburrek, Tobias and Schmalenstroeer, Joerg}},
  booktitle    = {{2022 International Wireless Communications and Mobile Computing (IWCMC)}},
  publisher    = {{IEEE}},
  title        = {{{Data-driven Time Synchronization in Wireless Multimedia Networks}}},
  doi          = {{10.1109/iwcmc55113.2022.9824980}},
  year         = {{2022}},
}

@inproceedings{33847,
  abstract     = {{The scope of speech enhancement has changed from a monolithic view of single,
independent tasks, to a joint processing of complex conversational speech
recordings. Training and evaluation of these single tasks requires synthetic
data with access to intermediate signals that is as close as possible to the
evaluation scenario. As such data often is not available, many works instead
use specialized databases for the training of each system component, e.g
WSJ0-mix for source separation. We present a Multi-purpose Multi-Speaker
Mixture Signal Generator (MMS-MSG) for generating a variety of speech mixture
signals based on any speech corpus, ranging from classical anechoic mixtures
(e.g., WSJ0-mix) over reverberant mixtures (e.g., SMS-WSJ) to meeting-style
data. Its highly modular and flexible structure allows for the simulation of
diverse environments and dynamic mixing, while simultaneously enabling an easy
extension and modification to generate new scenarios and mixture types. These
meetings can be used for prototyping, evaluation, or training purposes. We
provide example evaluation data and baseline results for meetings based on the
WSJ corpus. Further, we demonstrate the usefulness for realistic scenarios by
using MMS-MSG to provide training data for the LibriCSS database.}},
  author       = {{Cord-Landwehr, Tobias and von Neumann, Thilo and Boeddeker, Christoph and Haeb-Umbach, Reinhold}},
  booktitle    = {{2022 International Workshop on Acoustic Signal Enhancement (IWAENC)}},
  location     = {{Bamberg}},
  title        = {{{MMS-MSG: A Multi-purpose Multi-Speaker Mixture Signal Generator}}},
  year         = {{2022}},
}

@inproceedings{33807,
  author       = {{Gburrek, Tobias and Schmalenstroeer, Joerg and Haeb-Umbach, Reinhold}},
  booktitle    = {{ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}},
  publisher    = {{IEEE}},
  title        = {{{On Synchronization of Wireless Acoustic Sensor Networks in the Presence of Time-Varying Sampling Rate Offsets and Speaker Changes}}},
  doi          = {{10.1109/icassp43922.2022.9746284}},
  year         = {{2022}},
}

@article{33451,
  abstract     = {{We present an approach to automatically generate semantic labels for real recordings of automotive range-Doppler (RD) radar spectra. Such labels are required when training a neural network for object recognition from radar data. The automatic labeling approach rests on the simultaneous recording of camera and lidar data in addition to the radar spectrum. By warping radar spectra into the camera image, state-of-the-art object recognition algorithms can be applied to label relevant objects, such as cars, in the camera image. The warping operation is designed to be fully differentiable, which allows backpropagating the gradient computed on the camera image through the warping operation to the neural network operating on the radar data. As the warping operation relies on accurate scene flow estimation, we further propose a novel scene flow estimation algorithm which exploits information from camera, lidar and radar sensors. The
proposed scene flow estimation approach is compared against a state-of-the-art scene flow algorithm, and it outperforms it by approximately 30% w.r.t. mean average error. The feasibility of the overall framework for automatic label generation for
RD spectra is verified by evaluating the performance of neural networks trained with the proposed framework for Direction-of-Arrival estimation.}},
  author       = {{Grimm, Christopher and Fei, Tai and Warsitz, Ernst and Farhoud, Ridha and Breddermann, Tobias and Haeb-Umbach, Reinhold}},
  journal      = {{IEEE Transactions on Vehicular Technology}},
  number       = {{9}},
  pages        = {{9435--9449}},
  title        = {{{Warping of Radar Data Into Camera Image for Cross-Modal Supervision in Automotive Applications}}},
  doi          = {{10.1109/TVT.2022.3182411}},
  volume       = {{71}},
  year         = {{2022}},
}

@inproceedings{33696,
  author       = {{Wiechmann, Jana and Glarner, Thomas and Rautenberg, Frederik and Wagner, Petra and Haeb-Umbach, Reinhold}},
  booktitle    = {{18. Phonetik und Phonologie im deutschsprachigen Raum (P&P)}},
  location     = {{Bielefeld}},
  title        = {{{Technically enabled explaining of voice characteristics}}},
  year         = {{2022}},
}

@inproceedings{35126,
  author       = {{Förster, Nikolas and Hölscher, Jonas and Piepenbrock, Till and Rehlaender, Philipp and Wallscheid, Oliver and Schafmeister, Frank and Böcker, Joachim}},
  booktitle    = {{2022 24th European Conference on Power Electronics and Applications (EPE’22 ECCE Europe)}},
  pages        = {{P.1--P.9}},
  title        = {{{An Open-Source FEM Magnetic Toolbox for Calculating Electric and Thermal Behavior of Power Electronic Magnetic Components}}},
  year         = {{2022}},
}

@article{30863,
  abstract     = {{<jats:title>Abstract</jats:title>
               <jats:p>In this paper a measurement procedure to identify viscoelastic material parameters of plate-like samples using broadband ultrasonic waves is presented. Ultrasonic Lamb waves are excited via the thermoelastic effect using laser radiation and detected by a piezoelectric transducer. The resulting measurement data is transformed to yield information about multiple propagating Lamb waves as well as their attenuation. These results are compared to simulation results in an inverse procedure to identify the parameters of an elastic and a viscoelastic material model.</jats:p>}},
  author       = {{Johannesmann, Sarah and Claes, Leander and Feldmann, Nadine and Zeipert, Henning and Henning, Bernd}},
  issn         = {{2196-7113}},
  journal      = {{tm - Technisches Messen}},
  keywords     = {{Electrical and Electronic Engineering, Instrumentation}},
  number       = {{7 - 8}},
  pages        = {{493 -- 506}},
  publisher    = {{Walter de Gruyter GmbH}},
  title        = {{{Lamb wave based approach to the determination of acoustic material parameters}}},
  doi          = {{10.1515/teme-2021-0134}},
  volume       = {{89}},
  year         = {{2022}},
}