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Enabling Data-Driven Nursing Innovations: User-centered Development of a Nursing Data Module

Current Directions in Biomedical engineering 2023年第1期9卷 339-342页

作者： Warnecke, Maren Holle, Daniela Burmann, Anja Fraunhofer Institute for Software and Systems Engineering ISST Speicherstrasse 6 Dortmund Germany HS Gesundheit Bochum Bochum Germany Fraunhofer Institute for Software and Systems Engineering ISST Dortmund Germany

The documentation landscape for nursing care data in Germany is predominantly heterogeneous and unstructured. Therefore, insightful methods such as Artificial Intelligence (AI) are difficult to implement. We propose a stepwiseapproach that identifies relevant information from nursing theory and practice and maps it to a standardized nursing core data set to enable data-based improvement of nursing care. This can be used for various use-cases in care, such as risk detection and prevention in diverse care contexts. Many care processes can benefit of a cross-facility and standardized repository and associated applications. We propose an approach that enables the use of AI while leveraging consensus and evidenced-based expert knowledge from nursing science. © 2023 the author(s), published by Walter de Gruyter Berlin/Boston.

关键词： Nursing

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Towards LLM-augmented Situation Space Analysis for the Hazard and Risk Assessment of Automotive systems

Towards LLM-augmented Situation Space Analysis for the Hazar...

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2024 Lock-in or log out? Wie digitale Souveranitat gelingt, INFORMATIK 2024

作者： Hillen, Daniel Helten, Catharina Reich, Jan Fraunhofer Institute for Experimental Software Engineering Safety Engineering Fraunhofer Platz 1 Kaiserslautern67663 Germany

ISBN: (纸本)9783885797463

The hazard analysis and risk assessment (HARA) is a fundamental artifact of safety engineering that requires substantial effort from experienced engineers to conform to standards. The cost combined with today’s shortage of trained personnel demands technical solutions to reduce these efforts. Recent advances in generative AI provide new opportunities to support engineers with complex and creative tasks such as the HARA that require knowledge of the system and the environment. However, for now, the results provided by large language models are not reliable enough for safety artifacts so human engineers must review and approve them. In our study, we present a tool to create a HARA based on human-AI cooperation. Our goal is to keep human engineers involved in each decision and guide them by providing arguments, examples, and assessment proposals. In our case study, the engineers benefit from the additional reasonings and proposed assessments of the AI tool. © 2024 Gesellschaft fur Informatik (GI). All rights reserved.

关键词： Hazards

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Design Features for Data Trustee Selection in Data Spaces 13

Design Features for Data Trustee Selection in Data Spaces

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13th International Conference on Data Science, Technology and Applications, DATA 2024

作者： Steinert, Michael Tebernum, Daniel Hupperz, Marius Fraunhofer Institute for Software and Systems Engineering ISST Dortmund Germany

ISBN: (纸本)9789897587078

As the world becomes increasingly digital, data is becoming a critical resource. When used effectively, it can lead to more accurate forecasts, process optimization, and the creation of innovative business models. The necessary data is often distributed across multiple organizations, and its full value can only be realized through shared collaboration. Data spaces provide organizations with a platform for sovereign and secure data sharing. To enable legally secure data sharing and ensure compliance with regulations, data trustees play a critical role as trusted intermediaries. However, choosing a suitable data trustee that meets the needs of the participants who want to share data with each other is difficult. Our study seeks to elucidate the process by which participants of a data space can choose an appropriate data trustee. To this purpose, we have implemented a whitelist approach. We report on the results of our design science research project, which includes design features to facilitate the integration of our whitelist approach into different data space instantiations. Potential shortcomings were identified and addressed during an expert workshop. By providing verified design knowledge, we help practitioners in the data space community to incorporate the concept of how to select the most appropriate data trustee. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Data consistency

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PiVisionSort: Integrating Image Processing and Machine Learning for Material Recognition on Conveyor Belts 2

PiVisionSort: Integrating Image Processing and Machine Learn...

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2nd International Conference on Data, Information and Computing Science, CDICS 2024

作者： Kia, Shohreh Leiding, Benjamin Technische Universität Clausthal Institute for Software and System Engineering Clausthal-Zellerfeld Germany

ISBN: (纸本)9781643685762

This research aims to develop an advanced material detection system for conveyor belts, utilizing state-of-the-art image processing and machine learning techniques to automate the identification of various materials, thereby enhancing operational efficiency and accuracy in industrial settings. Current methods in material detection, such as traditional manual sorting and basic automated systems, often need more precision and adaptability in dynamic industrial environments. This paper identifies a gap in the practical and reliable detection of diverse materials under varying environmental conditions. The primary research questions addressed include: How can modern image processing and machine learning techniques improve material detection accuracy? What optimizations can be applied to ensure real-time processing efficiency? The proposed solution integrates a strategic camera setup with controlled lighting, robust image preprocessing algorithms (noise reduction, normalization, and resizing), and custom-designed detection algorithms using machine learning models. This system outperforms existing solutions by offering higher detection accuracy and adaptability to diverse industrial conditions. An interface is developed to display detection results and provide intuitive controls for system adjustments, ensuring practical use by industrial professionals. Rigorous testing and validation processes are implemented to enhance detection accuracy and processing speeds, with specific performance metrics established to measure efficacy. This paper provides a transformative impact on the manufacturing and processing industries by addressing environmental variability and material diversity. © 2025 The Authors.

关键词： Noise abatement

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Reliable and Content-specific Support for Keyword Selection through AI and Statistics Characterising Educational Content with Large Language Models & Agreement Analyses

Reliable and Content-specific Support for Keyword Selection ...

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作者： Strube, Tom Nowak, Tom Pokotylo, Mariia Kuhlenkötter, Bernd Fraunhofer Institute for Software and Systems Engineering Dortmund Germany Ruhr University Bochum Bochum Germany

Due to the recent popularity and availability of Large Language Models (LLMs), creators of educational materials can more efficiently extract keywords for use in personalised learning recommendations than ever before. However, due to the LLMs' probabalistic nature, the automation of the otherwise labour-intense keyword extraction inherits the risk of biased and non-explainable results. In this research, we present an original framework to enhance keyword selection based on content title and description through a novel, reliability-sensitive, keyword selection algorithm. For this, we collected 38 potential keywords (together with their definitions) for five topics on dementia care from previous studies, together with two contents per topic. To assess the new method's support in extracting keywords, we then prompted 5 human experts and 3 LLMs (using Retrieval Augmented Generation (RAG) for the keyword definitions) to select keywords to include and exclude for each content. Using Krippendorf's a metric, we then were able to adapt to the present agreement, and to reliably select keyword sets for inclusion and exclusion for each content individually. Last, we compared these LLM-based keyword sets with those selected by humans to assess the impact of the adaptive keyword selection algorithm. Overall, the results suggest that LLMs generally struggle with the task (66% of extraction attempts either contained hallucinated or did not return any keywords), and topic-wise internal agreement is low (a=0.59 (0.42) for model 3 (using RAG) on average;α=0.68 for human raters). Due to this, the reliable keyword selection resulted in a median set of 6|27 keywords for inclusion|exclusion per topic, with many of those keywords being within the benchmark keyword sets selected by human raters. To conclude, this approach shows effective in adapting to different levels of agreement in extracting keywords. © 2024 by Walter de Gruyter Berlin/Boston.

关键词： Reliability analysis

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USING A SMART CITY DISTRICT SIMULATOR TO TEST NEW DIGITAL SERVICES 16

USING A SMART CITY DISTRICT SIMULATOR TO TEST NEW DIGITAL SE...

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16th International Conference on ICT, Society and Human Beings, ICT 2023, the 15th International Conference on e-Health, EH 2023, the 9th International Conference on Connected Smart Cities, CSC 2023 and 8th International Conference on Big Data Analytics, Data Mining and Computational Intelligence, BigDaCI 2023

作者： Neuschwander, Philipp Elberzhager, Frank Ajdari, Arian Stüpfert, Phil Fraunhofer Institute for Experimental Software Engineering IESE Fraunhofer Platz 1 Kaiserslautern67663 Germany

ISBN: (纸本)9789898704504

Cities have become more and more digital in recent years. They have developed various digital services that they provide to their citizens. However, it is often difficult to test ideas for new services from both a technical and a user-centric perspective. Reasons for this are, among others, that existing technical infrastructures provide a complex environment where deployment is often time-consuming. Furthermore, certain qualities such as performance or data protection have to be ensured, which is something a prototypical solution might not be able to offer. We are developing digital solutions for a smart city district, and one of our main challenges is that the area is still under construction and no technical infrastructure exists yet. Therefore, we developed a mock environment for a digital ecosystem in which we can easily test new ideas and early service prototypes. In this publication, we report on how we used this environment in a hackathon event and provide experiences from the participants that used our smart city district simulator. We provide examples of the solutions and discuss how our technical solution supported the development of new digital solutions and how it might also be a solution for other cities. © ICT *** rights reserved.

关键词： Smart city

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Enabling Data-Driven Nursing Innovations: User-centered Development of a Nursing Data Module

Enabling Data-Driven Nursing Innovations: User-centered Deve...

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关键词： Nursing

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Extended Abstract of Poster: STARS: Tree-Based Classification and Testing of Feature Combinations in the Automated Robotic Domain 18

Extended Abstract of Poster: STARS: Tree-Based Classificatio...

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18th IEEE International Conference on software Testing, Verification and Validation Workshops, ICSTW 2025

作者： Schallau, Till Schmid, Dominik Pawlinorz, Nick Naujokat, Stefan Howar, Falk TU Dortmund University Dortmund44227 Germany Fraunhofer Institute for Software and Systems Engineering Dortmund44147 Germany

ISBN: (纸本)9798331534677

Testing complex systems is crucial for ensuring safety, especially in automated driving, where diverse data sources and variable environments pose challenges. Here, robust safety validation is critical but exhaustive n-way combinatorial testing is impractical due to the vast number of test cases. The STARS framework uses tree-based scenario classifiers to limit feature combinations in a given domain. © 2025 IEEE.

关键词： Automation

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Model and Algorithm for Data Distribution in the Microservice Architecture of a Web Application

Model and Algorithm for Data Distribution in the Microservic...

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2025 International Russian Smart Industry Conference, SmartIndustryCon 2025

作者： Thant Sin, Si Thu Portnov, E.M. Kokin, V.V. Institute of System and Software Engineering and Information Technologies National Research University MIET Zelenograd Moscow Russia

ISBN: (纸本)9798331511241

This paper is devoted to the study and development of a model and algorithm for data distribution in the microservice architecture of a web application, considering the possible inoperability of some services. The research focuses on enhancing the performance of load balancers by considering key parameters such as request intensity, system capacity, and reliability. A mathematical model is formulated using queuing theory and Erlang's formulas to define the optimal function for data distribution. The study proposes an improved algorithm for dynamic load balancing that actively monitors microservice performance, reducing bottlenecks and increasing processing efficiency. Simulation results demonstrate a significant improvement in the output flow of serviced data messages, increasing throughput by 15.25% compared to conventional load balancing methods. The proposed approach enables efficient utilization of system resources, enhances fault tolerance, and improves request execution speeds in microservice-based web applications. These findings highlight the importance of adaptive data distribution mechanisms in high-load environments, ensuring reliability and scalability for modern banking and financial services applications. © 2025 IEEE.

关键词： Service oriented architecture (SOA)

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Concept About Shared Digital Twin of EV Batteries to Improve the Data Exchange in the Context of Battery Transport 17

Concept About Shared Digital Twin of EV Batteries to Improve...

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17th IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2023

作者： Plotnikov, Max Schier, Arkadius Fraunhofer Institute for Material Flow & Logistics Software & Information Engineering Dortmund Germany

ISBN: (纸本)9798350396003

The present work is based on a concept to improve the information exchange during off-site transport of batteries in the context of electromobility with different actors of the value chain using descriptive research design. The challenges regarding the exchange of information with corresponding actors such as the responsible authorities or safety institutions form the main research subject of this thesis. A measure of the European Commission for the electronic provision of transport information combined with the Shared Digital Twin of a battery by means of Battery Passport makes it possible to improve the error-prone current process, especially in the B2A sector. Hereby, synergy effects arise for different actors in terms of data availability, - integrity and - sovereignty through cloud-based provision of the transport information of batteries. © 2023 IEEE.

关键词： Electronic data interchange

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