@inproceedings{56014, author = {{Jafarzadeh, Hanieh and Klemme, Florian and Reimer, Jan Dennis and Amrouch, Hussam and Hellebrand, Sybille and Wunderlich, Hans-Joachim}}, booktitle = {{In: IEEE International Test Conference (ITC'24), San Diego, CA, USA, November 2024}}, location = {{San Diego, CA, USA}}, publisher = {{IEEE}}, title = {{{Minimizing PVT-Variability by Exploiting the Zero Temperature Coefficient (ZTC) for Robust Delay Fault Testing}}}, year = {{2024}}, } @misc{59234, author = {{Knorr, Lukas and Schlosser, Florian and Divkovic, Denis and Buchenau, Nadja and Meschede, Henning}}, publisher = {{19th SDEWES Conference}}, title = {{{Energy Flexibility and Electrification of Industrial Process Heat: A Review}}}, year = {{2024}}, } @inproceedings{57085, abstract = {{We propose an approach for simultaneous diarization and separation of meeting data. It consists of a complex Angular Central Gaussian Mixture Model (cACGMM) for speech source separation, and a von-Mises-Fisher Mixture Model (VMFMM) for diarization in a joint statistical framework. Through the integration, both spatial and spectral information are exploited for diarization and separation. We also develop a method for counting the number of active speakers in a segment of a meeting to support block-wise processing. While the total number of speakers in a meeting may be known, it is usually not known on a per-segment level. With the proposed speaker counting, joint diarization and source separation can be done segment-by-segment, and the permutation problem across segments is solved, thus allowing for block-online processing in the future. Experimental results on the LibriCSS meeting corpus show that the integrated approach outperforms a cascaded approach of diarization and speech enhancement in terms of WER, both on a per-segment and on a per-meeting level.}}, author = {{Cord-Landwehr, Tobias and Boeddeker, Christoph and Haeb-Umbach, Reinhold}}, booktitle = {{ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}}, keywords = {{diarization, source separation, mixture model, meeting}}, location = {{Hyderabad, India}}, title = {{{Simultaneous Diarization and Separation of Meetings through the Integration of Statistical Mixture Models}}}, doi = {{10.1109/ICASSP49660.2025.10888445}}, year = {{2024}}, } @inproceedings{53659, author = {{Cord-Landwehr, Tobias and Boeddeker, Christoph and Zorilă, Cătălin and Doddipatla, Rama and Haeb-Umbach, Reinhold}}, booktitle = {{ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}}, location = {{Seoul}}, publisher = {{IEEE}}, title = {{{Geodesic Interpolation of Frame-Wise Speaker Embeddings for the Diarization of Meeting Scenarios}}}, doi = {{10.1109/icassp48485.2024.10445911}}, year = {{2024}}, } @inproceedings{57864, abstract = {{This book includes the proceedings of the 21st International Conference on Smart Technologies & Education (STE2024). The "International Conference on Smart Technologies & Education" (STE) is an annual global meeting dedicated to the fundamentals, applications, and experiences in the field of Smart Technologies, Online, Remote, and Virtual Engineering, Virtual Instrumentation, and other related new technologies. Nowadays, online and smart technologies are the core of most fields of engineering and the whole society. Consequently, the motto of this year’s STE2024 was "Smart Technologies for a Sustainable Future". The STE conference is the successor of the long-standing annual REV Conferences and the annual meeting of the International Association of Online Engineering (IAOE) together with the EduNet World Association (EWA) and the International Education Network (EduNet). In a globally connected world, the interest in online collaboration, teleworking, remote services, and other digital working environments is rapidly increasing. In response to that, the general objective of this conference is to contribute and discuss fundamentals, applications, and experiences in the field of Online and Remote Engineering, Virtual Instrumentation, and other related new technologies like Cross Reality, Open Science and Big Data, Internet of Things and Industrial Internet of Things, Industry 4.0, Cyber Security, and M2M and Smart Objects. Another objective of the conference is to discuss guidelines and new concepts for engineering education in higher and vocational education institutions, including emerging technologies in learning, MOOCs and MOOLs, and Open Resources. This year, STE2024 has been organized in Helsinki, Finland as an onsite event supporting remote presentations, from March 6 until March 8, 2024. The co-organizers of STE2024 were the Arcada University of Applied Sciences, the International Association of Online Engineering (IAOE) together with the Global Online Laboratory Consortium (GOLC), the International Education Network (EduNet), and the EduNet World Association (EWA). STE2024 has attracted 140 scientists and industrial leaders from more than 40 countries}}, author = {{Alptekin, Mesut and Temmen, Katrin}}, booktitle = {{Smart Technologies for a Sustainable Future: Proceedings of the 21st International Conference on Smart Technologies & Education. Volume 1}}, isbn = {{3-031-61891-2 978-3-031-61891-8}}, pages = {{297}}, publisher = {{Springer Nature}}, title = {{{Extended Results for Effectiveness Study of an Augmented Reality App as Preparation Tool for Electrical Engineering Laboratory Courses}}}, volume = {{1}}, year = {{2024}}, } @inbook{57863, author = {{Alptekin, Mesut and Temmen, Katrin}}, booktitle = {{Smart Technologies for a Sustainable Future}}, editor = {{Auer, Michael E. and Langmann, Reinhard and May, Dominik and Roos, Kim}}, isbn = {{978-3-031-61890-1 978-3-031-61891-8}}, pages = {{297–304}}, publisher = {{Springer Nature Switzerland}}, title = {{{Effectiveness Study of an Augmented Reality App as Preparation Tool for Electrical Engineering Laboratory Courses}}}, doi = {{10.1007/978-3-031-61891-8_29}}, volume = {{1027}}, year = {{2024}}, } @article{54459, author = {{Knorr, Lukas and Schlosser, Florian and Horstmann, Nils and Divkovic, Denis and Meschede, Henning}}, issn = {{0306-2619}}, journal = {{Applied Energy}}, publisher = {{Elsevier BV}}, title = {{{Flexible operation and integration of high-temperature heat pumps using large temperature glides}}}, doi = {{10.1016/j.apenergy.2024.123417}}, volume = {{368}}, year = {{2024}}, } @inbook{61868, author = {{Jonas-Ahrend, Gabriela}}, booktitle = {{A Pedagogical View of the COVID-19 Pandemic}}, isbn = {{9789004710139}}, publisher = {{BRILL}}, title = {{{Vocational Teacher Education in a “COVID-19 Semester”}}}, doi = {{10.1163/9789004710146_009}}, year = {{2024}}, } @inbook{57834, author = {{Vernholz, Mats}}, booktitle = {{Jahrbuch der berufs- und wirtschaftspädagogischen Forschung 2024}}, editor = {{Kögler, Kristina and Kremer, H.-Hugo and Herkner, Volkmar}}, pages = {{132--147}}, publisher = {{Verlag Barbara Budrich}}, title = {{{Gewerblich-technische Lehrkräftebildung in Deutschland - Analyse der Einflüsse auf das akademische Selbstkonzept von Lehramtsstudierenden technischer (beruflicher) Fachrichtungen}}}, doi = {{10.3224/84743054}}, year = {{2024}}, } @misc{59223, author = {{Schwabe, Tobias and Mallick, Khaleda and Singh, Karanveer and Schneider, Thomas and Scheytt, J. Christoph}}, publisher = {{Zenodo}}, title = {{{Precise optical Nyquist Pulse Synthesizer Digital- to-Analog-Converter presentation 2024 SPP 2111 }}}, doi = {{10.5281/zenodo.15114897}}, year = {{2024}}, } @misc{59224, author = {{Schwabe, Tobias and Singh, Karanveer and Schneider, Thomas and Scheytt, J. Christoph}}, publisher = {{Zenodo}}, title = {{{Precise optical Nyquist Pulse Synthesizer Digital- to-Analog-Converter (PONyDAC II) 2024 SPP 2111 }}}, doi = {{10.5281/zenodo.15114631}}, year = {{2024}}, } @inproceedings{57103, author = {{Surendranath Shroff, Vijayalakshmi and Bahmanian, Meysam and Kruse, Stephan and Scheytt, J. Christoph}}, booktitle = {{2024 IEEE BiCMOS and Compound Semiconductor Integrated Circuits and Technology Symposium (BCICTS) }}, location = {{Fort Lauderdale, Florida}}, publisher = {{IEEE}}, title = {{{Design of an Ultra-Low Phase Noise Broadband Amplifier in 130 nm SiGe BiCMOS Technology}}}, doi = {{10.1109/BCICTS59662.2024.10745663}}, year = {{2024}}, } @inproceedings{57160, abstract = {{Large audio tagging models are usually trained or pre-trained on AudioSet, a dataset that encompasses a large amount of different sound classes and acoustic environments. Knowledge distillation has emerged as a method to compress such models without compromising their effectiveness. There are many different applications for audio tagging, some of which require a specialization to a narrow domain of sounds to be classified. For these scenarios, it is beneficial to distill the large audio tagger with respect to a specific subset of sounds of interest. A method to prune a general dataset with respect to a target dataset is presented. By distilling with such a specialized pruned dataset, we obtain a compressed model with better classification accuracy in the specific target domain than with target-agnostic distillation.}}, author = {{Werning, Alexander and Haeb-Umbach, Reinhold}}, booktitle = {{32nd European Signal Processing Conference (EUSIPCO 2024)}}, keywords = {{data pruning, knowledge distillation, audio tagging}}, location = {{Lyon}}, title = {{{Target-Specific Dataset Pruning for Compression of Audio Tagging Models}}}, year = {{2024}}, } @inproceedings{53824, author = {{Koch, Kevin and Claes, Leander and Jurgelucks, Benjamin and Meihost, Lars and Henning, Bernd}}, booktitle = {{Fortschritte der Akustik - DAGA 2024}}, editor = {{Gesellschaft für Akustik e.V., Deutsche }}, pages = {{1113–1116}}, title = {{{Inverses Verfahren zur Identifikation piezoelektrischer Materialparameter unterstützt durch neuronale Netze}}}, year = {{2024}}, } @inproceedings{56834, author = {{Friesen, Olga and Claes, Leander and Scheidemann, Claus and Feldmann, Nadine and Hemsel, Tobias and Henning, Bernd}}, booktitle = {{2023 International Congress on Ultrasonics, Beijing, China}}, issn = {{1742-6596}}, pages = {{012125}}, publisher = {{IOP Publishing}}, title = {{{Estimation of temperature-dependent piezoelectric material parameters using ring-shaped specimens}}}, doi = {{10.1088/1742-6596/2822/1/012125}}, volume = {{2822}}, year = {{2024}}, } @misc{55470, author = {{Koch, Kevin and Friesen, Olga and Claes, Leander}}, publisher = {{Zenodo}}, title = {{{Randomised material parameter impedance dataset of piezoelectric rings}}}, doi = {{10.5281/zenodo.13143680}}, year = {{2024}}, } @misc{53662, author = {{Koch, Kevin and Claes, Leander}}, publisher = {{zenodo}}, title = {{{Randomised material parameter piezoelectric impedance dataset with structured electrodes}}}, doi = {{10.5281/ZENODO.11064206}}, year = {{2024}}, } @misc{55416, author = {{Claes, Leander and Koch, Kevin and Friesen, Olga and Meihost, Lars}}, title = {{{Machine learning in inverse measurement problems: An application to piezoelectric material characterisation}}}, year = {{2024}}, } @article{56777, abstract = {{The estimation of accurate piezoelectric material parameters is a fundamental prerequisite for simulation-driven design of piezoelectric actuators and sensors. Previous studies show that a full set of material parameters can be determined in an inverse procedure using a single disc-shaped specimen with an electrode structured for increased sensitivity with respect to all material parameters. However, in the case of high-power actuator applications, ring-shaped piezoelectric components are often employed, necessitating an adaptation of the previously developed method. The alteration in geometry introduces some advantages. Accordingly, there is no longer any requirement to modify the electrode structure in order to enhance sensitivity. The method to estimate the material parameters presented here consists of a total of three stages. An initial, approximate estimation of the material parameters is determined using analytical approximations for the resonance frequencies from the IEEE standard. These values are optimised in an inverse procedure that employs analytic expressions for the electrical impedance of piezoelectric rings as the forward model. Further refinement is achieved by using Finite Element (FE) simulations as the forward model again in an inverse procedure. The method is applied to electrical impedance measurement data, yielding material parameters for hard piezoelectric rings. The result shows a good agreement between the simulation and measurement results, indicating realistic material parameter values.}}, author = {{Friesen, Olga and Claes, Leander and Feldmann, Nadine and Henning, Bernd}}, issn = {{2196-7113}}, journal = {{tm - Technisches Messen}}, publisher = {{De Gruyter}}, title = {{{Estimation of piezoelectric material parameters of ring-shaped specimens}}}, doi = {{https://doi.org/10.1515/teme-2024-0107}}, year = {{2024}}, } @article{54314, author = {{Koch, Kevin and Claes, Leander and Jurgelucks, Benjamin and Meihost, Lars}}, journal = {{tm - Technisches Messen}}, publisher = {{Walter de Gruyter GmbH}}, title = {{{Neuronale Netze zur Startwertschätzung bei der Identifikation piezoelektrischer Materialparameter}}}, doi = {{10.1515/teme-2024-0099}}, year = {{2024}}, }