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Most recently, the federal government in Germany published new climate goals in order reach climate neutrality by 2045. This paper demonstrates a path to a cost optimal energy supply system for the German power grid until the year 2050. With special regard to regionality, the system is based on yearly myopic optimization with the required energy system transformation measures and the associated system costs. The results point out, that energy storage systems (ESS) are fundamental for renewables integration in order to have a feasible energy transition. Moreover, the investment in storage technologies increased the usage of the solar and wind technologies. Solar energy investments were highly accompanied with the installation of short-term battery storage. Longer-term storage technologies, such as H2, were accompanied with high installations of wind technologies. The results pointed out that hydrogen investments are expected to overrule short-term batteries if their cost continues to decrease sharply. Moreover, with a strong presence of ESS in the energy system, biomass energy is expected to be completely ruled out from the energy mix. With the current emission reduction strategy and without a strong presence of large scale ESS into the system, it is unlikely that the Paris agreement 2° C target by 2050 will be achieved, let alone the 1.5° C.
Elektronische Türschilder zur Darstellung von Informationen sind insbesondere in öffentlichen Gebäuden zwischenzeitlich weit verbreitet. Die Varianz dieser elektronischen Türschilder reicht vom Tablet-basierten Türschild bis hin zum PC-basierten Türschild mit externem Bildschirm. Zumeist werden die Systeme mit 230 V betrieben. Bei einer großen Summe von Türschildern in öffentlichen Gebäuden kann dies zu einem signifikanten Umsatz an Energie führen. Im Rahmen dieses Papers wird die Entwicklung eines energieautarken arbeiten Türschildes vorgestellt, bei dem ein E-Paper-Display zum Einsatz kommt. Das Türschild lässt sich per Smartphone-App und NFC-Schnittstelle konfigurieren. Es wird insbesondere auf das Low-Power-Hardware-Design der Elektronik und energetische Aspekte eingegangen.
This paper describes the authors' first experiments in creating an artificial dancer whose movements are generated through a combination of algorithmic and interactive techniques with machine learning. This approach is inspired by the time honoured practice of puppeteering. In puppeteering, an articulated but inanimate object seemingly comes to live through the combined effects of a human controlling select limbs of a puppet while the rest of the puppet's body moves according to gravity and mechanics. In the approach described here, the puppet is a machine-learning-based artificial character that has been trained on motion capture recordings of a human dancer. A single limb of this character is controlled either manually or algorithmically while the machine-learning system takes over the role of physics in controlling the remainder of the character's body. But rather than imitating physics, the machine-learning system generates body movements that are reminiscent of the particular style and technique of the dancer who was originally recorded for acquiring training data. More specifically, the machine-learning system operates by searching for body movements that are not only similar to the training material but that it also considers compatible with the externally controlled limb. As a result, the character playing the role of a puppet is no longer passively responding to the puppeteer but makes movement decisions on its own. This form of puppeteering establishes a form of dialogue between puppeteer and puppet in which both improvise together, and in which the puppet exhibits some of the creative idiosyncrasies of the original human dancer.
Strings P
(2021)
Strings is an audiovisual performance for an acoustic violin and two generative instruments, one for creating synthetic sounds and one for creating synthetic imagery. The three instruments are related to each other conceptually , technically, and aesthetically by sharing the same physical principle, that of a vibrating string. This submission continues the work the authors have previously published at xCoAx 2020. The current submission briefly summarizes the previous publication and then describes the changes that have been made to Strings. The P in the title emphasizes, that most of these changes have been informed by experiences collected during rehearsals (in German Proben). These changes have helped Strings to progress from a predominantly technical framework to a work that is ready for performance.
The transition from college to university can have a variety of psychological effects on students who need to cope with daily obligations by themselves in a new setting, which can result in loneliness and social isolation. Mobile technology, specifically mental health apps (MHapps), have been seen as promising solutions to assist university students who are facing these problems, however, there is little evidence around this topic. My research investigates how a mobile app can be designed to reduce social isolation and loneliness among university students. The Noneliness app is being developed to this end; it aims to create social opportunities through a quest-based gamified system in a secure and collaborative network of local users. Initial evaluations with the target audience provided evidence on how an app should be designed for this purpose. These results are presented and how they helped me to plan the further steps to reach my research goals. The paper is presented at MobileHCI 2020 Doctoral Consortium.
Loneliness, an emotional distress caused by the lack of meaningful social connections, has been increasingly affecting university students who need to deal with everyday situations in a new setting, especially those who have come from abroad. Currently there is little work on digital solutions to reduce loneliness. Therefore, this work describes the general design considerations for mobile apps in this context and outlines a potential solution. The mobile app Noneliness is used to this end: it aims to reduce loneliness by creating social opportunities through a quest-based gamified system in a secure and collaborative network of local users. The results of initial evaluations with the target audience are described. The results informed a user interface redesign as well as a review of the features and the gamification principles adopted.
Duplikaterkennung, -suche und -konsolidierung für Kunden- und Geschäftspartnerdaten, sog. „Identity Resolution“, ist die Voraussetzung für erfolgreiches Customer Relationship Management und Customer Experience Management, aber auch für das Risikomanagement zur Minimierung von Betrugsrisiken und Einhaltung regulatorischer Vorschriften und viele weitere Anwendungsfälle. Diese Systeme sind jedoch hochkomplex und müssen individuell an die kundenspezifischen Anforderungen angepasst werden. Der Einsatz lernbasierter Verfahren bietet großes Potenzial zur automatisierten Anpassung. In diesem Beitrag präsentieren wir für ein KMU praxisfähige, lernbasierte Verfahren zur automatischen Konfiguration von Business-Regeln in Duplikaterkennungssystemen. Dabei wurden für Fachanwender Möglichkeiten entwickelt, um beispielgetrieben das Match-System an individuelle Business-Regeln (u.a. Umzugserkennung, Sperrlistenabgleich) anzupassen und zu konfigurieren. Die entwickelten Verfahren wurden evaluiert und in einer prototypischen Lösung integriert. Wir konnten zeigen, dass unser Machine-Learning-Verfahren, die von einem Domainexperten erstellten Business-Regeln für das Duplikaterkennungssystem „identity“ verbessern konnte. Zudem konnte der hierzu erforderliche Zeitaufwand verkürzt werden.
Grey-box modelling combines physical and data-driven models to benefit from their respective advantages. Neural ordinary differential equations (NODEs) offer new possibilities for grey-box modelling, as differential equations given by physical laws and neural networks can be combined in a single modelling framework. This simplifies the simulation and optimization and allows to consider irregularly-sampled data during training and evaluation of the model. We demonstrate this approach using two levels of model complexity; first, a simple parallel resistor-capacitor circuit; and second, an equivalent circuit model of a lithium-ion battery cell, where the change of the voltage drop over the resistor-capacitor circuit including its dependence on current and State-of-Charge is implemented as NODE. After training, both models show good agreement with analytical solutions respectively with experimental data.