On the Potential of Multi-objective Automated Algorithm Configuration on Multi-modal Multi-objective Optimisation Problems - Preuß, Oliver Ludger; Rook, Jeroen; Trautmann, Heike (Applications of Evolutionary Computation)

Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP - Seiler, Moritz; Rook, Jeroen; Heins, Jonathan; Preuß, Oliver Ludger; Bossek, Jakob; Trautmann, Heike (2023 IEEE Symposium Series on Computational Intelligence (SSCI))

Grundlagen einer Ethik des Radikalen Digitalen Humanismus - Fuchs, Christian (Digitalisierte Massenkommunikation und Verantwortung)

Critical Perspectives on Digital Capitalism: Theories and Praxis. Introduction to the Special Issue - Fuchs, Christian; Arslan, Sevda Can; Allmer, Thomas (tripleC: Communication, Capitalism & Critique)

Vincent Mosco’s Critical-Humanist Political Economy of Communication - Fuchs, Christian (tripleC: Communication, Capitalism & Critique)

Preface - Fuchs, Christian (Yuqi Na: The Chinese Internet. Political Economy and Digital Discourse)

Media, Economy and Society: A Critical Introduction. - Christian, Fuchs

Politisch? Poetisch? Persönlich? Barbara Strozzis „Il lamento“ zwischen Selbstausdruck und politischer Positionierung - Tumat, Antje (Barbara Strozzi (1619-1677). Musik und Diskurs im Venedig des Seicento)

“It’s like I got a new pair of glasses”: Reflections on sense of self, home, and belonging among transnational students in short-term study abroad programs - Müller, Mareike (Study Abroad Research in Second Language Acquisition and International Education)
This study focuses on a specific group of sojourners that has thus far remained rather unexplored in the context of study-abroad research, namely, students with extensive prior experiences of living in, traveling to, and/or familial ties with target-language mediated communities. To this end, this study examines data obtained through episodic interviews with three American students, who grew up in close contact with German-speaking communities and studied abroad in Austria for four weeks. By means of thematic analysis, the pre-study abroad sojourn motives and reflections on sense of self, home, and belonging are contrasted with these students’ immediate and delayed post-study abroad accounts. The results shed light on both the challenges young adults grapple with due to their international biographies and the transformative effects students attribute to their short-term sojourns with regard to redefining who they are and what meaning different places of home and heritage have within their individual trajectories.

Towards a computational architecture for co-constructive explainable systems - Booshehri, Meisam; Buschmeier, Hendrik; Cimiano, Philipp; Kopp, Stefan; Kornowicz, Jaroslaw; Lammert, Olesja; Matarese, Marco; Mindlin, Dimitry; Robrecht, Amelie; Vollmer, Anna-Lisa (Proceedings of the 2024 Workshop on Explainability Engineering (ExEn’24))

VACO: a Multi-perspective Development of a Therapeutic and Motivational Virtual Robotic Agent for Concentration for children with ADHD - Richter, Birte; Petras, Ira-Katharina; Vollmer, Anna-Lisa; Luong, Ayla; Siniatchkin, Michael; Wrede, Britta (arXiv:2405.03354)
In this work, we present (i) a novel approach how artificial intelligence can support in the therapy for better concentration of children with Attention Deficit Hyperactivity Disorder (ADHD) through motivational attention training with a virtual robotic agent and (ii) a development process in which different stakeholders are included with their perspectives. Therefore, we present three participative approaches to include the perspectives of different stakeholders. An online survey (Study I) was conducted with parents in Germany with the aim of ascertaining whether they would use software to promote their children's attention, what influences their attitude towards using it, and what requirements it would have to meet. About half of the parents would be willing to use software to promote attention. To develop the software as close to practice as possible, one of the developers took part in an intensive training for ADHD with the aim of testing which of the elements are technically feasible. Afterward, a first prototype was presented to clinicians (Study II) to make further adjustments. A first feasibility test (Study III) was conducted with the end users to check if the system works and if children and adolescents can use it. Attentional performance software offers multiple opportunities in the treatment of ADHD if the system is adapted to the needs of the practitioner and end user. This development process requires a lot of time and close interdisciplinary collaboration.

The Power of Combined Modalities in Interactive Robot Learning - Beierling, Helen; Vollmer, Anna-Lisa (arXiv:2405.07817)
This study contributes to the evolving field of robot learning in interaction with humans, examining the impact of diverse input modalities on learning outcomes. It introduces the concept of "meta-modalities" which encapsulate additional forms of feedback beyond the traditional preference and scalar feedback mechanisms. Unlike prior research that focused on individual meta-modalities, this work evaluates their combined effect on learning outcomes. Through a study with human participants, we explore user preferences for these modalities and their impact on robot learning performance. Our findings reveal that while individual modalities are perceived differently, their combination significantly improves learning behavior and usability. This research not only provides valuable insights into the optimization of human-robot interactive task learning but also opens new avenues for enhancing the interactive freedom and scaffolding capabilities provided to users in such settings.

An early indicator for anomalous stock market performance - Fritz, Marlon; Gries, Thomas; Wiechers, Lukas (Quantitative Finance)
We propose an indicator for detecting anomalous stock market valuation in real time such that market participants receive timely signals so as to be able to take stabilizing action. Unlike existing approaches, our anomaly indicator introduces three methodological novelties. First, we use an endogenous, purely data-driven, nonparametric trend identification method to separate long-term market movements from more short-term ones. Second, we apply SETAR models that allow for asymmetric expansions and contractions around the long-term trend and find systematic stock price cycles. Third, we implement these findings in our indicator and conduct real-time market forecasts, which have so far been neglected in the literature. Applications of our indicator using monthly S&P 500 stock data from 1970 to the end of 2022 show that short-term anomalous market movements can be identified in real time up to one year ahead. We predict all major anomalies, including the 1987 Bubble and the initial phase of the Financial Crisis that began in 2007. In total, our anomaly indicator identifies more than 80% of all – even minor – anomalous episodes. Thus, smoothing market exaggerations through early signaling seems possible.
Keywords: General Economics; Econometrics and Finance; Finance

Gramelsberger, Gabriele, “Matrices – Compensating the Loss of Anschauung”, in: M. Friedman and K. Krauthausen (eds.), Model and Mathematics. From the 19th Century to the 21st Century, Birkhäuser/Springer: Cham 2022 (Trends in the History of Science), 363–377. - Peckhaus, Volker (Mathematical Reviews, MR4485231)

Wissenstransfer zur Bewegungsförderung: Was funktioniert wie und mit wem? - Kehne, Miriam (Wissenstransfer in der Sportpädagogik. Grundlagen, Themen, Formate)

Insights and Challenges of Co-Simulation-Based Optimal Pulse Pattern Evaluation for Electric Drives - Hölsch, Lukas; Brosch, Anian; Steckel, Richard; Braun, Tristan; Wendel, Sebastian; Böcker, Joachim; Wallscheid, Oliver (IEEE Transactions on Energy Conversion)
Keywords: Electrical and Electronic Engineering; Energy Engineering and Power Technology

Model‐based analysis and specification of functional requirements and tests for complex automotive systems - Wiecher, Carsten; Mandel, Constantin; Günther, Matthias; Fischbach, Jannik; Greenyer, Joel; Greinert, Matthias; Wolff, Carsten; Dumitrescu, Roman; Mendez, Daniel; Albers, Albert (Systems Engineering)
Abstract The specification of requirements and tests are crucial activities in automotive development projects. However, due to the increasing complexity of automotive systems, practitioners fail to specify requirements and tests for distributed and evolving systems with complex interactions when following traditional development processes. To address this research gap, we propose a technique that starts with the early identification of validation concerns from a stakeholder perspective, which we use to systematically design tests that drive a scenario‐based modeling and analysis of system requirements. To ensure complete and consistent requirements and test specifications in a form that is required in automotive development projects, we develop a Model‐Based Systems Engineering (MBSE) methodology. This methodology supports system architects and test designers in the collaborative application of our technique and in maintaining a central system model, in order to automatically derive the required specifications. We evaluate our methodology by applying it at KOSTAL (Tier1 supplier) and within student projects as part of the masters program Embedded Systems Engineering. Our study corroborates that our methodology is applicable and improves existing requirements and test specification processes by supporting the integrated and stakeholder‐focused modeling of product and validation systems, where the early definition of stakeholder and validation concerns fosters a problem‐oriented, iterative and test‐driven requirements modeling.

Künstliche Intelligenz in der Produktionsplanung und -steuerung - von Enzberg, Sebastian; Weller, Julian; Pöhler, Pascal; Kühn, Arno; Römer, Michael; Dumitrescu, Roman (Zeitschrift für wirtschaftlichen Fabrikbetrieb)
Abstract Production planning and control (PPC) is a central element in the production system and represents a key element of the transformation towards Industry 4.0. Artificial intelligence (AI) is used to evaluate information and to model and optimize systems. The article gives a systematic overview of application potentials of AI in PPS and discusses the challenges on the way towards AI-based production planning and control.

Data-driven Services and Servitization in Manufacturing: Innovation, Engineering, Transformation, and Management - Koldewey, Christian; Ebel, Martin; Winter, Johannes; Dumitrescu, Roman (Proceedings of the 57th Hawaii International Conference on System Sciences | 2024)

Leveraging self-supervised learning for vibration data in industrial separators - Heuwinkel, Tim; Merkelbach, Silke; Janssen, Nils; Enzberg, Sebastian von; Dumitrescu, Roman