Map matching is a widely used technology for mapping tracks to road networks. Typically, tracks are recorded using publicly available Global Navigation Satellite Systems, and road networks are derived from the publicly available OpenStreetMap project. The challenge lies in resolving the discrepancies between the spatial location of the tracks and the underlying road network of the map. Map matching is a combination of defined models, algorithms, and metrics for resolving these differences that result from measurement and map errors. The goal is to find routes within the road network that best represent the given tracks. These matches allow further analysis since they are freed from the noise of the original track, they accurately overlap with the road network, and they are corrected for impossible detours and gaps that were present in the original track. Given the ongoing need for map matching in mobility research, in this work, we present a novel map matching method based on Markov decision processes with Reinforcement Learning algorithms. We introduce the new Candidate Adoption feature, which allows our model to dynamically resolve outliers and noise clusters. We also incorporate an improved Trajectory Simplification preprocessing algorithm for further improving our performance. In addition, we introduce a new map matching metric that evaluates direction changes in the routes, which effectively reduces detours and round trips in the results. We provide our map matching implementation as Open Source Software (OSS) and compare our new approach with multiple existing OSS solutions on several public data sets. Our novel method is more robust to noise and outliers than existing methods and it outperforms them in terms of accuracy and computational speed.

Abstract
Background Triptans are effective for many migraine patients, but some do not experience adequate efficacy
and tolerability. The European Headache Federation (EHF) has proposed that patients with lack of efficacy and/or tolerability
of ≥ 2 triptans (‘triptan resistance’) could be considered eligible for treatment with the novel medications
from the ditan and gepant groups. There is little data on the frequency of ‘triptan resistance’.
Methods We used patient self-report data from the German Migraine and Headache Society (DMKG) Headache
Registry to assess triptan response and triptan efficacy and/or tolerability failure.
Results A total of 2284 adult migraine patients (females: 85.4%, age: 39.4 ± 12.8 years) were included. 42.5% (n = 970)
had failed ≥ 1 triptan, 13.1% (n = 300) had failed ≥ 2 triptans (meeting the EHF definition of ‘triptan resistance’),
and 3.9% (n = 88) had failed ≥ 3 triptans. Compared to triptan responders (current use, no failure, n = 597), triptan
non-responders had significantly more severe migraine (higher frequency (p < 0.001), intensity (p < 0.05), and disability
(p < 0.001)), that further increased with the level of triptan failure. Responders rates were highest for nasal and oral
zolmitriptan, oral eletriptan and subcutaneous sumatriptan.
Conclusion In the present setting (specialized headache care in Germany), 13.1% of the patients had failed ≥ 2
triptans. Triptan failure was associated with increased migraine severity and disability, emphasizing the importance
of establishing an effective and tolerable acute migraine medication. Acute treatment optimization might include
switching to one of the triptans with the highest responder rates and/or to a different acute medication class.
Trial registration The DMKG Headache Registry is registered with the German Clinical Trials Register (DRKS
00021081).

In personalized interaction between humans and computers, not only computers and personalization algorithms learn about the users: the users also learn about the system’s behavior and adapt their expectations accordingly. Particularly, as users expect systems to support their daily activities, this feedback loop may result in long-term changes in these daily activities and user decisions themselves. This can be observed in activities as different as autonomous driving and social media consumption. In this chapter, we investigate these effects by reviewing and analyzing a wide range of relevant literature.

Um den zunehmenden Anforderungen an die Beherrschung digitaler Techniken und an die Fähigkeit zur interdisziplinären Zusammenarbeit an Studierende aller Fach­richtungen zu begegnen wurde das interdisziplinäre Lehrformat Digitalisie­rungs­­kollegs für Studierende entwickelt. Das in vielen Fachbereichen ausbaufähige Angebot von Digitalthemen in der Hoch­schullehre wird hiermit dauerhaft erwei­tert. Ein Digitalisierungskolleg besteht aus einer Vorlesungs­reihe mit an­gren­zen­dem Seminar, in denen Studierende interdisziplinäre Lösungen für Fragen der digitalen Transformation entwickeln. Geleitet werden sie von etablierten Wissen­schaftlerinnen und Wissenschaftlern, aktiv betreut und ausge­staltet von ein bis zwei Coaches. Kernelement sowohl des Kollegs als auch der einzelnen Projekte ist die Interdisziplinarität. Eine*r der beteiligten Projekt­leiter*innen hat einen direkten Bezug zur Technik und kommt aus der Informatik, der Wirtschafts­informatik, der Elektro­technik oder vergleichbaren Disziplinen. Zielgruppe der Projekte sind Studierende verschiedener Disziplinen im Masterstudium oder in den letzten Semestern eines Bachelorstudiums. Durch die Teilnahme er­werben auch Studie­ren­de aus digitali­­sie­rungs­fernen Fächern frühzeitig umfang­reiche IT-Kenntnisse. Als Be­gleiteffekt der um­fang­reichen Vernetzung zwischen den Digi­talisierungs­kollegs (Studierende, Coaches und Projektleitende) entsteht bereits zu Beginn einer wissenschaftlichen Karriere eine große digitale Community. Alle Teil­nehmenden lernen frühzeitig die interdisziplinäre Zusammenarbeit und ver­bessern erheblich ihre Karriere­chancen inner­­halb und außer­halb der Wissenschaft.

Understanding acceleration forces and making progress in learning Skateboarding is a process of trial and error. In our paper we are describing our preliminary experiments for describing the complex interactions while pushing for speed in ramps and pump tracks. Therefore, we capture and visualize the body movement, the joint relations from hip to ankle and the resulting forces by joining iner- tial sensors on the skateboard and camera-based machine learning pose estimation of the athlete.

In our society, displays are becoming increasingly prevalent. While it is nearly inconceivable to imagine a daily life without screens, scientific research indicates that our mental well-being is nega- tively affected by the increasing use and time spent on screens. The "HomeGrid" project has been developed as a smart home concept, aiming to explore how traditional screens in private environments can be reduced while still effectively conveying information in an intuitive manner. To achieve this, two main approaches were em- ployed. Firstly, experimentation was conducted on the capture and communication of artificial light, and secondly, precise monitoring and visualization of indoor air quality were explored. These factors are fundamental indicators of both our mental and physical well- being, as high air quality, for example, enhances concentration, and light serves as a crucial regulator of our circadian rhythm.

We are entering a period of unprecedented collaboration between authors and computers, where artificial intelligence in particular seems likely to act increasingly in a co-authoring capacity. Automated or procedural storytelling represents one exciting avenue of research. By entering prompts and parameters into an AI text generator like ChatGPT, authors could leverage an enormous textual corpus to generate a “new” work that appears to have been authored by a human.

This paper proposes an alternative platform, one more reflective of the collaborative and organic creative process. Approached as a tool for augmentation, Mother showcases the potential for spatial hypertext to work alongside the author.

Two years ago the idea of International Teaching and Research in Hypertext (INTR/HT) was introduced. This paper follows up on this idea and further develops new thoughts on this topic, based on the experiences gained from three university courses taught under the umbrella of INTR/HT. We conclude we have envisioned a model for the future of international and interdisciplinary education in hypertext that has the potential to raise the next generation of hypertext researchers through efforts of collaborative teaching and learning activities.

Process mining has emerged as a powerful technique for analyzing and improving business processes. In this research paper, the application of process mining in a vertically integrated small-scale smart factory is explored. The study aims to identify challenges, analyze data issues, and explore the potential of process mining as a tool for process optimization. Employing a case study approach, data is collected from the entire process and analyzed using process mining software. The findings show how to use data to enable process mining in current scenarios. Challenges related to data synchronization and the impact of network delays on data accuracy are revealed. However, despite the challenges identified, this research demonstrates the potential of process mining to drive process optimization in smart factory environments. This paper contributes to the field of process mining and provides valuable information for academia and industry professionals seeking to optimize production processes through data-driven analysis in the era of Industry 4.0.

The paper presents SPORE, a Spatial Recommender System. As we enter a period of unprecedented collaboration between authors and computers, where artificial intelligence in particular seems likely to act increasingly in a co-authoring capacity, SPORE offers a different approach to collaboration. More organic and exploratory than other automated or procedural systems, SPORE aims to mimic the process of storybreaking that already exists in the creative industries.

Vladimir Propp (1895–1970) was a Russian folklorist, who identified what he considered the 31 fundamental actions of major characters and their consequences for a story, actions which he called functions. This paper focuses on one specific part of this principle—spheres of action—and considers how they might be explored using SPORE and its underlying infrastructure Mother, a spatial hypertext-based recommender system developed by the authors.