Model based Integration of Human Characteristics in Production Systems: A Literature Survey - Gräßler, Iris; Roesmann, Daniel; Pottebaum, Jens (14th CIRP Conference on Intelligent Computation in Manufacturing Engineering; 15. - 17. Jul. 2020)

Generic Product Lifecycle Model: A Holistic and Adaptable Approach for Multi-Disciplinary Product-Service Systems - Gräßler, Iris; Pottebaum, Jens (Applied Sciences)

Couleur Locale - Schulze, Max (Produktive Bildstörung: Sigmar Polke und aktuelle künstlerische Positionen)
Keywords: Sigmar Polke; Bildstörung; Camouflage; Wandfarbe

Friedrich Schneider, Christus das Kind. Oratorium in drei Teilen - Werbick, Regina; Höink, Dominik; Memering, Robert

CDS Investors’ Risk Perceptions of M&A Announcements - Hippert, Benjamin; Uhde, André
Merging a sample of 492 merger and acquisition (M&A) announcements from 284 acquiring firms across Europe and North America with data from 5-year single-name credit default swaps (CDSs) written on stock-listed acquiring firms between 2005 and 2018, the paper at hand empirically analyzes the CDS investors’ risk perceptions of M&A announcements using event study methodologies. As a baseline result, we provide evidence for significantly positive cumulative average abnormal CDS spread changes for both, European and North American acquirers suggesting that CDS investors perceive an increase in the acquiring firms’ credit risk exposures due to M&A announcements. Our baseline finding holds under several robustness checks, especially when controlling for the robustness of the empirical design. Moreover, results from a large variety of sensitivity analyses reveal a number of deal and firm characteristics that may explain why CDS investors from our sample expect an increase in the acquirers’ credit risk exposures due to forthcoming M&A transactions.
Keywords: credit default swaps; risk perception of CDS investors; mergers and acquisitions; event study

Determinants of CDS Trading on Major Banks - Hippert, Benjamin; Uhde, André; Wengerek, Sascha Tobias
This paper empirically investigates determinants of the outstanding net notional amount of credit default swaps (CDSs) contracts written on banks. We extend and complement the previous literature dealing with CDS trading by analyzing a comprehensive set of CDS tradingspecific, bank-fundamental, macroeconomic and bank-institutional determinants. We find that risk hedging clearly dominates an investor’s speculation and arbitrage motive, while the latter, however, exhibits the strongest impact on the outstanding net notional amount of bank CDSs. Furthermore, being classified as a G-SIB, being a constituent of the main CDS index and the equity trading volume may significantly explain changes in the outstanding CDS net notional on banks. The analysis at hand provides important implications for both academics and practitioners, since understanding the trading motives of bank CDS investors provides a deeper insight into the opaque CDS market.
Keywords: banking; outstanding CDS net notional; determinants of bank CDS trading

Der Wunsch zu verschwinden - Schulze, Max
Das Buch stellt die drei jüngeren Serien Cool Mild Pure Warm (Streetfile), EPS und Der Wunsch zu verschwinden (Camopedia) des Künstlers Max Schulze vor. Ihm geht es um die Frage, an welchen Orten und auf welche Weise Malerei im Jahr 2021 entsteht: Wie sieht es mit den althergebrachten Kategorisierungen von Farbe und Form, Figuration und Abstraktion oder Fläche und Raum aus? Welche Wege sucht sich vor diesem Hintergrund die heutige Malerei und welche ästhetische Kraft ist ihr eigen? Die 32 Bilder der Serie Der Wunsch zu verschwinden (Camopedia) basieren auf den 32 Farbtönen des Systems «Alpina Feine», die Schulze verwendet, um unterschiedliche Camouflage-Muster zu malen. Dieses speziell kuratierte Farbsystem wird aus Marketinggründen mit Wohlfühlassoziationen verbunden. Diese Aufladung crasht mit der Verwendung des Tarnmusters im militärischen Bereich. Schulze beschäftigt die Frage, warum gerade heute, in einer Zeit, die von vielen politischen und sozialen Veränderungen bestimmt ist, Camouflage in Mode und Design allgegenwärtig ist. Für die Serie Cool Mild Pure Warm (Streetfile) greift Schulze ebenfalls auf Farbsysteme zurück, die er mit Fotos von diversen Farb-Attentaten im öffentlichen Raum kombiniert. So entsteht ein – nicht ganz humorloser – Kommentar zur kommerziellen Nutzung von Farbe in Farbsystemen, aber auch zu deren Zweckentfremdung durch politische «Attacken» im öffentlichen Raum. Der Name der Serie EPS bezieht sich auf ein Material, das unter dem Markennamen Styropor bekannt ist. Schulze klebt es auf abstrakte Malereien, doch nicht vollständig, sondern so, dass Teilbereiche der darunter liegenden Bildebene frei bleiben. Das darunter liegende Bild wird gleichsam verdeckt wie durch die Dämmung geschützt. Es entsteht ein ähnlich ambivalenter Seh-Eindruck wie bei den anderen Serien.
Keywords: Camouflage; Malerei; Wandfarbe; Wohlfühlstrategien; Farbsysteme; Farb-Attentat; öffentlicher Raum; Dämmung; Zwecketfremdung

Self-Trained Audio Tagging and Sound Event Detection in Domestic Environments - Ebbers, Janek; Haeb-Umbach, Reinhold (Proceedings of the 6th Detection and Classification of Acoustic Scenes and Events 2021 Workshop (DCASE2021))
In this paper we present our system for the Detection and Classification of Acoustic Scenes and Events (DCASE) 2021 Challenge Task 4: Sound Event Detection and Separation in Domestic Environments, where it scored the fourth rank. Our presented solution is an advancement of our system used in the previous edition of the task.We use a forward-backward convolutional recurrent neural network (FBCRNN) for tagging and pseudo labeling followed by tag-conditioned sound event detection (SED) models which are trained using strong pseudo labels provided by the FBCRNN. Our advancement over our earlier model is threefold. First, we introduce a strong label loss in the objective of the FBCRNN to take advantage of the strongly labeled synthetic data during training. Second, we perform multiple iterations of self-training for both the FBCRNN and tag-conditioned SED models. Third, while we used only tag-conditioned CNNs as our SED model in the previous edition we here explore sophisticated tag-conditioned SED model architectures, namely, bidirectional CRNNs and bidirectional convolutional transformer neural networks (CTNNs), and combine them. With metric and class specific tuning of median filter lengths for post-processing, our final SED model, consisting of 6 submodels (2 of each architecture), achieves on the public evaluation set poly-phonic sound event detection scores (PSDS) of 0.455 for scenario 1 and 0.684 for scenario as well as a collar-based F1-score of 0.596 outperforming the baselines and our model from the previous edition by far. Source code is publicly available at https://github.com/fgnt/pb_sed.

Adapting Sound Recognition to A New Environment Via Self-Training - Ebbers, Janek; Keyser, Moritz Curt; Haeb-Umbach, Reinhold (Proceedings of the 29th European Signal Processing Conference (EUSIPCO))
Recently, there has been a rising interest in sound recognition via Acoustic Sensor Networks to support applications such as ambient assisted living or environmental habitat monitoring. With state-of-the-art sound recognition being dominated by deep-learning-based approaches, there is a high demand for labeled training data. Despite the availability of large-scale data sets such as Google's AudioSet, acquiring training data matching a certain application environment is still often a problem. In this paper we are concerned with human activity monitoring in a domestic environment using an ASN consisting of multiple nodes each providing multichannel signals. We propose a self-training based domain adaptation approach, which only requires unlabeled data from the target environment. Here, a sound recognition system trained on AudioSet, the teacher, generates pseudo labels for data from the target environment on which a student network is trained. The student can furthermore glean information about the spatial arrangement of sensors and sound sources to further improve classification performance. It is shown that the student significantly improves recognition performance over the pre-trained teacher without relying on labeled data from the environment the system is deployed in.

Foreword to the special section on Computer Graphics education in the time of Covid - Santos, Beatriz Sousa; Domik, Gitta; Anderson, Eike Falk (Graph. Vis. Comput.)