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1st European Symposium on Information Systems Engineering (ESISE)
No full textAbstracts of the 1st European Symposium on Information Systems Engineering (ESISE), held from September 11 to 13, 2024, at the Kempten University of Applied Sciences in Kempten, Germany. This symposium brought together researchers and thought leaders to explore the latest advancements and challenges in the field of information systems engineering
Challenges and conditions for successfully implementing and adopting the telematics infrastructure in German outpatient healthcare: A qualitative study applying the NASSS framework
No full textBackground
Germany's healthcare system provides high-quality, universal health coverage to almost all residents. However, a major challenge lies in the strong separation of healthcare structures, which hinders efficient interprofessional and intersectoral communication and collaboration. The mandatory nationwide implementation of the telematics infrastructure may offer a solution to enhance healthcare professionals’ communication and collaboration.
Objective
Our study aims to elicit participants’ perceptions of and attitudes towards the implementation and usage of the telematics infrastructure in fostering interprofessional communication and collaboration between home-care nursing services and general practitioner practices.
Methods
We conducted interviews with seven members of general practitioner practices and 10 in home-care nursing services. Using thematic content analysis, we identified five themes, of which four along with 10 subthemes were integrated into Greenhalgh et al.'s ‘nonadoption, abandonment, scale-up, spread and sustainability’ framework.
Results
Participants recognised the potential of digital technology to enhance interprofessional communication and collaboration. However, this potential largely depended on individual healthcare actors’ willingness to seek information, invest and adapt. Attitudes towards the telematics infrastructure varied widely from hopeful confidence to outright rejection. Home-care nursing services generally viewed the telematics infrastructure with optimism, while general practitioners expressed reservations, particularly due to technological disruptions, lack of user-friendliness, and organisational structures.
Conclusion
Our findings highlight the potential of digital technology to enhance interprofessional communication. Successful implementation of technological innovations, however, goes beyond technological aspects and involves social, political and organisational processes. Future implementation strategies for such innovations in healthcare should involve users early and ensure clear communication
Trajectory Modeling for Autonomous Driving Based on Repulsive Field Method
No full textAlthough the focus of autonomous driving is on maximizing safety and efficiency, comfort and familiarity will play a key role in the adoption of autonomous driving. Therefore, it is important to develop algorithms that can mimic human driving skills and enable individualized driving styles.
The Repulsive Field Method (RFM), as proposed by H. Inoue, P. Raksincharoensak, and S. Inoue (2017) in their paper ”Intelligent Driving System for Safer Automobiles”, is a path-finding algorithm for autonomous driving that uses a repulsive potential field that models the risk potential of obstacles and road boundaries as a sum of Gaussian functions. This approach uses yaw rate candidates to predict possible trajectories for
the ego vehicle and evaluates the potential field based on these trajectories.
How well this algorithm handles moving obstacles still needs to be etermined. This method of evaluating the yaw rate candidates also opens up the possibility of predicting the future state of the potential field as well.
Another possible improvement is to spread out the points that are predicted based on the size of the ego car.
In this paper, both predictive and spatial modifications will be tested in a high-speed passing scenario that introduces moving obstacles to determine if the introduction of these modifications can be used to better replicate human behavior. To do this, a RFM module is applied to a simulation environment based on the ASAM OSI® interface standard. This will allow the resimulation of a scenario recorded with human driving to compare the algorithm with and provide future opportunities for more extensive testing
A Mobile App for Informal Care: Challenges and Opportunities in the Context of Complex Tasks and Networks
No full textInformal caregivers play a vital role in long-term care, often facing significant challenges in planning, organising, and coordinating tasks across complex care networks. While digital technologies offer substantial potential to support these activities, their adoption remains limited. This study explores the usability and acceptance of a market-ready mobile app designed to support informal caregivers inreal-life settings. Eighteen caregivers used the app without formal training over several months,followed by semi-structured qualitative interviews analysed using content analysis by Kuckartz. Results revealed that while the app's features, such as shared calendars and professional support forums, were perceived as useful, they were underutilised due to established offline routines, data privacy concerns,and limited interoperability with care services. Participants valued the app for its potential to streamline communication and coordination, particularly for geographically dispersed caregivers. However,structural barriers, including the complexity of care systems and digital mistrust, hindered broader implementation. This study highlights the need for user-centred app design and improved digital infrastructure to unlock the full potential of mobile technologies in informal care. Findings providevaluable insights into how digital solutions can bridge gaps in care networks and support the integrationof informal and professional care
Conceptual Approaches to Identify the Hazardous Scenarios in Safety Analysis for Automated Driving Systems
No full textTo ensure safety of the road users is one of the major challenges in highly automated driving. The technologies applied in semi or fully-automated vehicles that are safer than human drivers compromise functionalities and human comfort. A comprehensive understanding of the use of complex driving systems and the Operational Design Domain (ODD) is essential for the effective deployment and safe operation of Automated Driving Systems (ADSs). Hazard analysis is a foundation of various safety engineering methods, which include Functional Safety (FuSa) and Safety Of The Intended Functionality (SOTIF). The scenario-based analysis offers significant advantages in the safety analysis of automated vehicles but poses inherent difficulties in identifying unknown-hazardous scenarios. The work presented in this paper deals with the conceptual approaches of hazard scenario identification. Moreover, discusses the incorporation of Machine Learning (ML) in Hazard Analysis and Risk Assessment (HARA) for vehicles equipped with ADSs. Furthermore, this paper can serve as foundation support for research inquiries related to ADSs validation and safety assessment
Chapter 17: Mobile learners and the migration infrastructures of language learning industries
No full textLorente and Schedel provide insights into what we have come to call the global language learning industry. By comparing and contrasting the case of Malta, a language tourism destination for learning English, and the Philippines, a state that brokers its citizens as temporary labor migrants globally, the authors examine unequal human mobilities and the complex circumstances that produce them. They argue that both cases are textbook examples of a migration infrastructure that cocreates and reinforces international border regimes by reproducing certain often racialized categories of people (tourists, labor migrants) while enabling as well as impeding their mobility
Hausärztliche Versorgung im Wandel: Eine regionale Online-Befragung zu strukturellen Herausforderungen und Entwicklungsmöglichkeiten
No full textHintergrund
Die hausärztliche Versorgung steht vor wachsenden Herausforderungen, insbesondere im ländlichen Raum. Bei der zukunftsfähigen Weiterentwicklung müssen regionale Besonderheiten berücksichtigt und lokale Akteure einbezogen werden. Die Studie untersucht exemplarisch die Versorgungssituation in der Region Allgäu und identifiziert organisatorische Potenziale zur Stärkung der hausärztlichen Versorgung sowie Ansätze zur Integration neuer Praxisformen.
Methodik
Zur Erhebung der hausärztlichen Versorgungssituation wurde eine teilstrukturierte Online-Befragung mit offenen und halboffenen Fragen durchgeführt, an der 52 Personen teilnahmen. Die qualitative Auswertung der Freitextantworten erfolgte mittels qualitativer Inhaltsanalyse, die quantitative Analyse wurde deskriptiv durchgeführt.
Ergebnisse
In der Region zeigt sich eine eher kleinteilige Praxisstruktur mit bereits etablierter Delegation medizinischer Aufgaben an qualifiziertes nichtärztliches Personal. Herausforderungen bestehen in hoher Bürokratielast, personellen Engpässen und Defiziten in der digitalen Infrastruktur. Die Versorgung chronisch Kranker stellt steigende Anforderungen an die interdisziplinäre Zusammenarbeit und an das Praxismanagement. Dabei zeigt die hausarztzentrierte Versorgung positive Effekte, aber auch Optimierungspotenzial. Eine erweiterte Delegation ärztlicher Aufgaben wird begrüßt, jedoch durch fehlende Ressourcen und rechtliche Unsicherheiten eingeschränkt.
Schlussfolgerung
Um dem zukünftigen Versorgungsbedarf gerecht zu werden, bedarf es einer regionalen Versorgungssteuerung, optional ergänzt um ein integriertes Case Management. Für die koordinierte Patientenversorgung sind auf Organisationsebene Prozessanpassungen, klare Delegationsstrukturen sowie ein verbessertes Schnittstellenmanagement erforderlich
Database and Expert Systems Applications - DEXA 2025 Workshops AISys and AI4IP, Bangkok, Thailand, August 25–27, 2025, Proceedings
No full textThis volume constitutes the refereed proceedings of the 7th International Workshop on AI System Engineering: Math, Modelling and Software, AISys 2025 and the First International Workshop on Optimisation of Industrial Production with AI Algorithms, AI4IP, co-located with the 36th International Conference on Database and Expert Systems Applications, DEXA 2025, which took place in Bangkok, Thailand, during August 25-27, 2025.
The 11 full papers were thoroughly reviewed and selected from a total of 23 submissions. They are organized in topical sections as follows: AI System Engineering: Math, Modelling and Software; and Optimization of Industrial Production with AI Algorithms
Evaluating the performance of artificial intelligence in summarizing pre-coded text to support evidence synthesis: a comparison between chatbots and humans
No full textBackground
With the rise of large language models, the application of artificial intelligence in research is expanding, possibly accelerating specific stages of the research processes. This study aims to compare the accuracy, completeness and relevance of chatbot-generated responses against human responses in evidence synthesis as part of a scoping review.
Methods
We employed a structured survey-based research methodology to analyse and compare responses between two human researchers and four chatbots (ZenoChat, ChatGPT 3.5, ChatGPT 4.0, and ChatFlash) to questions based on a pre-coded sample of 407 articles. These questions were part of an evidence synthesis of a scoping review dealing with digitally supported interaction between healthcare workers.
Results
The analysis revealed no significant differences in judgments of correctness between answers by chatbots and those given by humans. However, chatbots’ answers were found to recognise the context of the original text better, and they provided more complete, albeit longer, responses. Human responses were less likely to add new content to the original text or include interpretation. Amongst the chatbots, ZenoChat provided the best-rated answers, followed by ChatFlash, with ChatGPT 3.5 and ChatGPT 4.0 tying for third. Correct contextualisation of the answer was positively correlated with completeness and correctness of the answer.
Conclusions
Chatbots powered by large language models may be a useful tool to accelerate qualitative evidence synthesis. Given the current speed of chatbot development and fine-tuning, the successful applications of chatbots to facilitate research will very likely continue to expand over the coming years
Evaluation of an Optimized Telemedicine Platform for Needs-Based Care in Outpatient Nursing
No full textDigital telemonitoring systems offer promising approaches to reducing the burden on nursing staff. In this study, the existing telemonitoring platform COMES® (COgnitive MEdical Systems) was technically further developed for use in outpatient care and tested in a study. Prior to this study, COMES® already received, stored, and displayed vital data from various mobile devices. The system was initially expanded with a Django-based middleware, integrated with the API of the company Withings, and supplemented by a new web app for data visualization designed for nursing staff. The resulting extended system, called DIP (Data Integration Platform), was then tested with various mobile devices (e.g., blood pressure monitor, scale, smartwatch) by 22 care recipients over a period of five weeks. On average, the nursing staff rated the usefulness of the DIP as neutral, primarily due to challenges in integrating it into their daily routines. In contrast, the care recipients rated the system’s user-friendliness as good to very good. The results highlight the potential of telemonitoring systems and the need for better integration of such systems into care processes