TY - RPRT A1 - Dworzak, Manuel A1 - Großmann, Marcel A1 - Le, Duy Thanh T1 - Federated Learning for Service Placement in Fog and Edge Computing T2 - KuVS Fachgespräch - Würzburg Workshop on Modeling, Analysis and Simulation of Next-Generation Communication Networks 2023 (WueWoWAS’23) N2 - Service orchestration requires enormous attention and is a struggle nowadays. Of course, virtualization provides a base level of abstraction for services to be deployable on a lot of infrastructures. With container virtualization, the trend to migrate applications to a micro-services level in order to be executable in Fog and Edge Computing environments increases manageability and maintenance efforts rapidly. Similarly, network virtualization adds effort to calibrate IP flows for Software-Defined Networks and eventually route it by means of Network Function Virtualization. Nevertheless, there are concepts like MAPE-K to support micro-service distribution in next-generation cloud and network environments. We want to explore, how a service distribution can be improved by adopting machine learning concepts for infrastructure or service changes. Therefore, we show how federated machine learning is integrated into a cloud-to-fog-continuum without burdening single nodes. KW - fog computing KW - SDN KW - orchestration KW - federated learning Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-322193 ER - TY - JOUR A1 - Koopmann, Tobias A1 - Stubbemann, Maximilian A1 - Kapa, Matthias A1 - Paris, Michael A1 - Buenstorf, Guido A1 - Hanika, Tom A1 - Hotho, Andreas A1 - Jäschke, Robert A1 - Stumme, Gerd T1 - Proximity dimensions and the emergence of collaboration: a HypTrails study on German AI research JF - Scientometrics N2 - Creation and exchange of knowledge depends on collaboration. Recent work has suggested that the emergence of collaboration frequently relies on geographic proximity. However, being co-located tends to be associated with other dimensions of proximity, such as social ties or a shared organizational environment. To account for such factors, multiple dimensions of proximity have been proposed, including cognitive, institutional, organizational, social and geographical proximity. Since they strongly interrelate, disentangling these dimensions and their respective impact on collaboration is challenging. To address this issue, we propose various methods for measuring different dimensions of proximity. We then present an approach to compare and rank them with respect to the extent to which they indicate co-publications and co-inventions. We adapt the HypTrails approach, which was originally developed to explain human navigation, to co-author and co-inventor graphs. We evaluate this approach on a subset of the German research community, specifically academic authors and inventors active in research on artificial intelligence (AI). We find that social proximity and cognitive proximity are more important for the emergence of collaboration than geographic proximity. KW - collaboration KW - dimensions of proximity KW - co-authorships KW - co-inventorships KW - embedding techniques Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-269831 SN - 1588-2861 VL - 126 IS - 12 ER - TY - JOUR A1 - Fathy, Moustafa A1 - Darwish, Mostafa A. A1 - Abdelhamid, Al-Shaimaa M. A1 - Alrashedy, Gehad M. A1 - Othman, Othman Ali A1 - Naseem, Muhammad A1 - Dandekar, Thomas A1 - Othman, Eman M. T1 - Kinetin ameliorates cisplatin-induced hepatotoxicity and lymphotoxicity via attenuating oxidative damage, cell apoptosis and inflammation in rats JF - Biomedicines N2 - Though several previous studies reported the in vitro and in vivo antioxidant effect of kinetin (Kn), details on its action in cisplatin-induced toxicity are still scarce. In this study we evaluated, for the first time, the effects of kinetin in cisplatin (cp)- induced liver and lymphocyte toxicity in rats. Wistar male albino rats were divided into nine groups: (i) the control (C), (ii) groups 2,3 and 4, which received 0.25, 0.5 and 1 mg/kg kinetin for 10 days; (iii) the cisplatin (cp) group, which received a single intraperitoneal injection of CP (7.0 mg/kg); and (iv) groups 6, 7, 8 and 9, which received, for 10 days, 0.25, 0.5 and 1 mg/kg kinetin or 200 mg/kg vitamin C, respectively, and Cp on the fourth day. CP-injected rats showed a significant impairment in biochemical, oxidative stress and inflammatory parameters in hepatic tissue and lymphocytes. PCR showed a profound increase in caspase-3, and a significant decline in AKT gene expression. Intriguingly, Kn treatment restored the biochemical, redox status and inflammatory parameters. Hepatic AKT and caspase-3 expression as well as CD95 levels in lymphocytes were also restored. In conclusion, Kn mitigated oxidative imbalance, inflammation and apoptosis in CP-induced liver and lymphocyte toxicity; therefore, it can be considered as a promising therapy. KW - cisplatin KW - hepatotoxicity KW - lymphotoxicity KW - oxidative stress KW - AKT KW - CD95 KW - caspase-3 Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-281686 SN - 2227-9059 VL - 10 IS - 7 ER - TY - RPRT A1 - Martino, Luigi A1 - Deutschmann, Jörg A1 - Hielscher, Kai-Steffen A1 - German, Reinhard T1 - Towards a 5G Satellite Communication Framework for V2X T2 - KuVS Fachgespräch - Würzburg Workshop on Modeling, Analysis and Simulation of Next-Generation Communication Networks 2023 (WueWoWAS’23) N2 - In recent years, satellite communication has been expanding its field of application in the world of computer networks. This paper aims to provide an overview of how a typical scenario involving 5G Non-Terrestrial Networks (NTNs) for vehicle to everything (V2X) applications is characterized. In particular, a first implementation of a system that integrates them together will be described. Such a framework will later be used to evaluate the performance of applications such as Vehicle Monitoring (VM), Remote Driving (RD), Voice Over IP (VoIP), and others. Different configuration scenarios such as Low Earth Orbit and Geostationary Orbit will be considered. KW - 5G KW - non-terrestrial networks KW - satellite communication Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-322148 ER - TY - RPRT A1 - Rauber, Christof A. O. A1 - Brechtel, Lukas A1 - Schotten, Hans D. T1 - JCAS-Enabled Sensing as a Service in 6th-Generation Mobile Communication Networks T2 - KuVS Fachgespräch - Würzburg Workshop on Modeling, Analysis and Simulation of Next-Generation Communication Networks 2023 (WueWoWAS’23) N2 - The introduction of new types of frequency spectrum in 6G technology facilitates the convergence of conventional mobile communications and radar functions. Thus, the mobile network itself becomes a versatile sensor system. This enables mobile network operators to offer a sensing service in addition to conventional data and telephony services. The potential benefits are expected to accrue to various stakeholders, including individuals, the environment, and society in general. The paper discusses technological development, possible integration, and use cases, as well as future development areas. KW - Sensing-aaS KW - JCAS KW - 6G Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-322135 ER - TY - RPRT A1 - Loh, Frank A1 - Raffeck, Simon A1 - Geißler, Stefan A1 - Hoßfeld, Tobias T1 - Paving the Way for an Energy Efficient and Sustainable Future Internet of Things T2 - KuVS Fachgespräch - Würzburg Workshop on Modeling, Analysis and Simulation of Next-Generation Communication Networks 2023 (WueWoWAS’23) N2 - In this work, we describe the network from data collection to data processing and storage as a system based on different layers. We outline the different layers and highlight major tasks and dependencies with regard to energy consumption and energy efficiency. With this view, we can outwork challenges and questions a future system architect must answer to provide a more sustainable, green, resource friendly, and energy efficient application or system. Therefore, all system layers must be considered individually but also altogether for future IoT solutions. This requires, in particular, novel sustainability metrics in addition to current Quality of Service and Quality of Experience metrics to provide a high power, user satisfying, and sustainable network. KW - Internet of Things KW - energy efficiency KW - sustainability Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-322161 ER - TY - RPRT A1 - Funda, Christoph A1 - Konheiser, Tobias A1 - German, Reinhard A1 - Hielscher, Kai-Steffen T1 - How to Model and Predict the Scalability of a Hardware-In-The-Loop Test Bench for Data Re-Injection? T2 - KuVS Fachgespräch - Würzburg Workshop on Modeling, Analysis and Simulation of Next-Generation Communication Networks 2023 (WueWoWAS’23) N2 - This paper describes a novel application of an empirical network calculus model based on measurements of a hardware-in-the-loop (HIL) test system. The aim is to predict the performance of a HIL test bench for open-loop re-injection in the context of scalability. HIL test benches are distributed computer systems including software, hardware, and networking devices. They are used to validate complex technical systems, but have not yet been system under study themselves. Our approach is to use measurements from the HIL system to create an empirical model for arrival and service curves. We predict the performance and design the previously unknown parameters of the HIL simulator with network calculus (NC), namely the buffer sizes and the minimum needed pre-buffer time for the playback buffer. We furthermore show, that it is possible to estimate the CPU load from arrival and service-curves based on the utilization theorem, and hence estimate the scalability of the HIL system in the context of the number of sensor streams. KW - hardware-in-the-loop simulation KW - computer performance evaluation KW - network calculus KW - scalability evaluation Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-322150 ER - TY - JOUR A1 - Steininger, Michael A1 - Abel, Daniel A1 - Ziegler, Katrin A1 - Krause, Anna A1 - Paeth, Heiko A1 - Hotho, Andreas T1 - ConvMOS: climate model output statistics with deep learning JF - Data Mining and Knowledge Discovery N2 - Climate models are the tool of choice for scientists researching climate change. Like all models they suffer from errors, particularly systematic and location-specific representation errors. One way to reduce these errors is model output statistics (MOS) where the model output is fitted to observational data with machine learning. In this work, we assess the use of convolutional Deep Learning climate MOS approaches and present the ConvMOS architecture which is specifically designed based on the observation that there are systematic and location-specific errors in the precipitation estimates of climate models. We apply ConvMOS models to the simulated precipitation of the regional climate model REMO, showing that a combination of per-location model parameters for reducing location-specific errors and global model parameters for reducing systematic errors is indeed beneficial for MOS performance. We find that ConvMOS models can reduce errors considerably and perform significantly better than three commonly used MOS approaches and plain ResNet and U-Net models in most cases. Our results show that non-linear MOS models underestimate the number of extreme precipitation events, which we alleviate by training models specialized towards extreme precipitation events with the imbalanced regression method DenseLoss. While we consider climate MOS, we argue that aspects of ConvMOS may also be beneficial in other domains with geospatial data, such as air pollution modeling or weather forecasts. KW - Klima KW - Modell KW - Deep learning KW - Neuronales Netz KW - climate KW - neural networks KW - model output statistics Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-324213 SN - 1384-5810 VL - 37 IS - 1 ER - TY - JOUR A1 - Puppe, Frank T1 - Gesellschaftliche Perspektiven einer fachspezifischen KI für automatisierte Entscheidungen JF - Informatik Spektrum N2 - Die künstliche Intelligenz (KI) entwickelt sich rasant und hat bereits eindrucksvolle Erfolge zu verzeichnen, darunter übermenschliche Kompetenz in den meisten Spielen und vielen Quizshows, intelligente Suchmaschinen, individualisierte Werbung, Spracherkennung, -ausgabe und -übersetzung auf sehr hohem Niveau und hervorragende Leistungen bei der Bildverarbeitung, u. a. in der Medizin, der optischen Zeichenerkennung, beim autonomen Fahren, aber auch beim Erkennen von Menschen auf Bildern und Videos oder bei Deep Fakes für Fotos und Videos. Es ist zu erwarten, dass die KI auch in der Entscheidungsfindung Menschen übertreffen wird; ein alter Traum der Expertensysteme, der durch Lernverfahren, Big Data und Zugang zu dem gesammelten Wissen im Web in greifbare Nähe rückt. Gegenstand dieses Beitrags sind aber weniger die technischen Entwicklungen, sondern mögliche gesellschaftliche Auswirkungen einer spezialisierten, kompetenten KI für verschiedene Bereiche der autonomen, d. h. nicht nur unterstützenden Entscheidungsfindung: als Fußballschiedsrichter, in der Medizin, für richterliche Entscheidungen und sehr spekulativ auch im politischen Bereich. Dabei werden Vor- und Nachteile dieser Szenarien aus gesellschaftlicher Sicht diskutiert. KW - Künstliche Intelligenz KW - Ethik KW - Entscheidungsfindung Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-324197 SN - 0170-6012 VL - 45 IS - 2 ER - TY - JOUR A1 - Riedmann, Anna A1 - Schaper, Philipp A1 - Lugrin, Birgit T1 - Integration of a social robot and gamification in adult learning and effects on motivation, engagement and performance JF - AI & Society N2 - Learning is a central component of human life and essential for personal development. Therefore, utilizing new technologies in the learning context and exploring their combined potential are considered essential to support self-directed learning in a digital age. A learning environment can be expanded by various technical and content-related aspects. Gamification in the form of elements from video games offers a potential concept to support the learning process. This can be supplemented by technology-supported learning. While the use of tablets is already widespread in the learning context, the integration of a social robot can provide new perspectives on the learning process. However, simply adding new technologies such as social robots or gamification to existing systems may not automatically result in a better learning environment. In the present study, game elements as well as a social robot were integrated separately and conjointly into a learning environment for basic Spanish skills, with a follow-up on retained knowledge. This allowed us to investigate the respective and combined effects of both expansions on motivation, engagement and learning effect. This approach should provide insights into the integration of both additions in an adult learning context. We found that the additions of game elements and the robot did not significantly improve learning, engagement or motivation. Based on these results and a literature review, we outline relevant factors for meaningful integration of gamification and social robots in learning environments in adult learning. KW - social robot KW - gamification KW - technology-supported learning KW - adult learning Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-324208 SN - 0951-5666 ER - TY - JOUR A1 - Kempf, Sebastian A1 - Krug, Markus A1 - Puppe, Frank T1 - KIETA: Key-insight extraction from scientific tables JF - Applied Intelligence N2 - An important but very time consuming part of the research process is literature review. An already large and nevertheless growing ground set of publications as well as a steadily increasing publication rate continue to worsen the situation. Consequently, automating this task as far as possible is desirable. Experimental results of systems are key-insights of high importance during literature review and usually represented in form of tables. Our pipeline KIETA exploits these tables to contribute to the endeavor of automation by extracting them and their contained knowledge from scientific publications. The pipeline is split into multiple steps to guarantee modularity as well as analyzability, and agnosticim regarding the specific scientific domain up until the knowledge extraction step, which is based upon an ontology. Additionally, a dataset of corresponding articles has been manually annotated with information regarding table and knowledge extraction. Experiments show promising results that signal the possibility of an automated system, while also indicating limits of extracting knowledge from tables without any context. KW - table extraction KW - table understanding KW - ontology KW - key-insight extraction KW - information extraction Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-324180 SN - 0924-669X VL - 53 IS - 8 ER - TY - JOUR A1 - Maiwald, Ferdinand A1 - Bruschke, Jonas A1 - Schneider, Danilo A1 - Wacker, Markus A1 - Niebling, Florian T1 - Giving historical photographs a new perspective: introducing camera orientation parameters as new metadata in a large-scale 4D application JF - Remote Sensing N2 - The ongoing digitization of historical photographs in archives allows investigating the quality, quantity, and distribution of these images. However, the exact interior and exterior camera orientations of these photographs are usually lost during the digitization process. The proposed method uses content-based image retrieval (CBIR) to filter exterior images of single buildings in combination with metadata information. The retrieved photographs are automatically processed in an adapted structure-from-motion (SfM) pipeline to determine the camera parameters. In an interactive georeferencing process, the calculated camera positions are transferred into a global coordinate system. As all image and camera data are efficiently stored in the proposed 4D database, they can be conveniently accessed afterward to georeference newly digitized images by using photogrammetric triangulation and spatial resection. The results show that the CBIR and the subsequent SfM are robust methods for various kinds of buildings and different quantity of data. The absolute accuracy of the camera positions after georeferencing lies in the range of a few meters likely introduced by the inaccurate LOD2 models used for transformation. The proposed photogrammetric method, the database structure, and the 4D visualization interface enable adding historical urban photographs and 3D models from other locations. KW - historical images KW - 4D-GIS KW - content-based image retrieval KW - Structure-from-Motion KW - camera orientation KW - feature matching Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-311103 SN - 2072-4292 VL - 15 IS - 7 ER - TY - JOUR A1 - Fischer, Norbert A1 - Hartelt, Alexander A1 - Puppe, Frank T1 - Line-level layout recognition of historical documents with background knowledge JF - Algorithms N2 - Digitization and transcription of historic documents offer new research opportunities for humanists and are the topics of many edition projects. However, manual work is still required for the main phases of layout recognition and the subsequent optical character recognition (OCR) of early printed documents. This paper describes and evaluates how deep learning approaches recognize text lines and can be extended to layout recognition using background knowledge. The evaluation was performed on five corpora of early prints from the 15th and 16th Centuries, representing a variety of layout features. While the main text with standard layouts could be recognized in the correct reading order with a precision and recall of up to 99.9%, also complex layouts were recognized at a rate as high as 90% by using background knowledge, the full potential of which was revealed if many pages of the same source were transcribed. KW - layout recognition KW - background knowledge KW - historical document analysis KW - fully convolutional neural networks KW - baseline detection KW - text line detection Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-310938 SN - 1999-4893 VL - 16 IS - 3 ER - TY - JOUR A1 - Kirikkayis, Yusuf A1 - Gallik, Florian A1 - Winter, Michael A1 - Reichert, Manfred T1 - BPMNE4IoT: a framework for modeling, executing and monitoring IoT-driven processes JF - Future Internet N2 - The Internet of Things (IoT) enables a variety of smart applications, including smart home, smart manufacturing, and smart city. By enhancing Business Process Management Systems with IoT capabilities, the execution and monitoring of business processes can be significantly improved. Providing a holistic support for modeling, executing and monitoring IoT-driven processes, however, constitutes a challenge. Existing process modeling and process execution languages, such as BPMN 2.0, are unable to fully meet the IoT characteristics (e.g., asynchronicity and parallelism) of IoT-driven processes. In this article, we present BPMNE4IoT—A holistic framework for modeling, executing and monitoring IoT-driven processes. We introduce various artifacts and events based on the BPMN 2.0 metamodel that allow realizing the desired IoT awareness of business processes. The framework is evaluated along two real-world scenarios from two different domains. Moreover, we present a user study for comparing BPMNE4IoT and BPMN 2.0. In particular, this study has confirmed that the BPMNE4IoT framework facilitates the support of IoT-driven processes. KW - IoT KW - BPM KW - BPMN KW - IoT-driven processes Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-304097 SN - 1999-5903 VL - 15 IS - 3 ER - TY - JOUR A1 - Wienrich, Carolin A1 - Carolus, Astrid A1 - Markus, André A1 - Augustin, Yannik A1 - Pfister, Jan A1 - Hotho, Andreas T1 - Long-term effects of perceived friendship with intelligent voice assistants on usage behavior, user experience, and social perceptions JF - Computers N2 - Social patterns and roles can develop when users talk to intelligent voice assistants (IVAs) daily. The current study investigates whether users assign different roles to devices and how this affects their usage behavior, user experience, and social perceptions. Since social roles take time to establish, we equipped 106 participants with Alexa or Google assistants and some smart home devices and observed their interactions for nine months. We analyzed diverse subjective (questionnaire) and objective data (interaction data). By combining social science and data science analyses, we identified two distinct clusters—users who assigned a friendship role to IVAs over time and users who did not. Interestingly, these clusters exhibited significant differences in their usage behavior, user experience, and social perceptions of the devices. For example, participants who assigned a role to IVAs attributed more friendship to them used them more frequently, reported more enjoyment during interactions, and perceived more empathy for IVAs. In addition, these users had distinct personal requirements, for example, they reported more loneliness. This study provides valuable insights into the role-specific effects and consequences of voice assistants. Recent developments in conversational language models such as ChatGPT suggest that the findings of this study could make an important contribution to the design of dialogic human–AI interactions. KW - intelligent voice assistant KW - smart speaker KW - social relationship KW - social role KW - long-term analysis KW - social interaction KW - human–computer interaction KW - anthropomorphism Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-313552 SN - 2073-431X VL - 12 IS - 4 ER - TY - JOUR A1 - Greubel, André A1 - Andres, Daniela A1 - Hennecke, Martin T1 - Analyzing reporting on ransomware incidents: a case study JF - Social Sciences N2 - Knowledge about ransomware is important for protecting sensitive data and for participating in public debates about suitable regulation regarding its security. However, as of now, this topic has received little to no attention in most school curricula. As such, it is desirable to analyze what citizens can learn about this topic outside of formal education, e.g., from news articles. This analysis is both relevant to analyzing the public discourse about ransomware, as well as to identify what aspects of this topic should be included in the limited time available for this topic in formal education. Thus, this paper was motivated both by educational and media research. The central goal is to explore how the media reports on this topic and, additionally, to identify potential misconceptions that could stem from this reporting. To do so, we conducted an exploratory case study into the reporting of 109 media articles regarding a high-impact ransomware event: the shutdown of the Colonial Pipeline (located in the east of the USA). We analyzed how the articles introduced central terminology, what details were provided, what details were not, and what (mis-)conceptions readers might receive from them. Our results show that an introduction of the terminology and technical concepts of security is insufficient for a complete understanding of the incident. Most importantly, the articles may lead to four misconceptions about ransomware that are likely to lead to misleading conclusions about the responsibility for the incident and possible political and technical options to prevent such attacks in the future. KW - media analysis KW - informal education KW - IT security KW - ransomware KW - misconceptions Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-313746 SN - 2076-0760 VL - 12 IS - 5 ER - TY - JOUR A1 - Hossfeld, Tobias A1 - Heegaard, Poul E. A1 - Kellerer, Wolfgang T1 - Comparing the scalability of communication networks and systems JF - IEEE Access N2 - Scalability is often mentioned in literature, but a stringent definition is missing. In particular, there is no general scalability assessment which clearly indicates whether a system scales or not or whether a system scales better than another. The key contribution of this article is the definition of a scalability index (SI) which quantifies if a system scales in comparison to another system, a hypothetical system, e.g., linear system, or the theoretically optimal system. The suggested SI generalizes different metrics from literature, which are specialized cases of our SI. The primary target of our scalability framework is, however, benchmarking of two systems, which does not require any reference system. The SI is demonstrated and evaluated for different use cases, that are (1) the performance of an IoT load balancer depending on the system load, (2) the availability of a communication system depending on the size and structure of the network, (3) scalability comparison of different location selection mechanisms in fog computing with respect to delays and energy consumption; (4) comparison of time-sensitive networking (TSN) mechanisms in terms of efficiency and utilization. Finally, we discuss how to use and how not to use the SI and give recommendations and guidelines in practice. To the best of our knowledge, this is the first work which provides a general SI for the comparison and benchmarking of systems, which is the primary target of our scalability analysis. KW - communication networks KW - performance KW - availability KW - scalability Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-349403 VL - 11 ER - TY - RPRT A1 - Herrmann, Martin A1 - Rizk, Amr T1 - On Data Plane Multipath Scheduling for Connected Mobility Applications T2 - KuVS Fachgespräch - Würzburg Workshop on Modeling, Analysis and Simulation of Next-Generation Communication Networks 2023 (WueWoWAS’23) N2 - Cooperative, connected and automated mobility (CCAM) systems depend on a reliable communication to provide their service and more crucially to ensure the safety of users. One way to ensure the reliability of a data transmission is to use multiple transmission technologies in combination with redundant flows. In this paper, we describe a system requiring multipath communication in the context of CCAM. To this end, we introduce a data plane-based scheduler that uses replication and integration modules to provide redundant and transparent multipath communication. We provide an analytical model for the full replication module of the system and give an overview of how and where the data-plane scheduler components can be realized. KW - multipath scheduling KW - connected mobility applications Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-322033 N1 - Aktualisierte Version unter https://doi.org/10.25972/OPUS-35344 ER - TY - JOUR A1 - Müller, Konstantin A1 - Leppich, Robert A1 - Geiß, Christian A1 - Borst, Vanessa A1 - Pelizari, Patrick Aravena A1 - Kounev, Samuel A1 - Taubenböck, Hannes T1 - Deep neural network regression for normalized digital surface model generation with Sentinel-2 imagery JF - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing N2 - In recent history, normalized digital surface models (nDSMs) have been constantly gaining importance as a means to solve large-scale geographic problems. High-resolution surface models are precious, as they can provide detailed information for a specific area. However, measurements with a high resolution are time consuming and costly. Only a few approaches exist to create high-resolution nDSMs for extensive areas. This article explores approaches to extract high-resolution nDSMs from low-resolution Sentinel-2 data, allowing us to derive large-scale models. We thereby utilize the advantages of Sentinel 2 being open access, having global coverage, and providing steady updates through a high repetition rate. Several deep learning models are trained to overcome the gap in producing high-resolution surface maps from low-resolution input data. With U-Net as a base architecture, we extend the capabilities of our model by integrating tailored multiscale encoders with differently sized kernels in the convolution as well as conformed self-attention inside the skip connection gates. Using pixelwise regression, our U-Net base models can achieve a mean height error of approximately 2 m. Moreover, through our enhancements to the model architecture, we reduce the model error by more than 7%. KW - Deep learning KW - multiscale encoder KW - sentinel KW - surface model Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-349424 SN - 1939-1404 VL - 16 ER - TY - JOUR A1 - Liman, Leon A1 - May, Bernd A1 - Fette, Georg A1 - Krebs, Jonathan A1 - Puppe, Frank T1 - Using a clinical data warehouse to calculate and present key metrics for the radiology department: implementation and performance evaluation JF - JMIR Medical Informatics N2 - Background: Due to the importance of radiologic examinations, such as X-rays or computed tomography scans, for many clinical diagnoses, the optimal use of the radiology department is 1 of the primary goals of many hospitals. Objective: This study aims to calculate the key metrics of this use by creating a radiology data warehouse solution, where data from radiology information systems (RISs) can be imported and then queried using a query language as well as a graphical user interface (GUI). Methods: Using a simple configuration file, the developed system allowed for the processing of radiology data exported from any kind of RIS into a Microsoft Excel, comma-separated value (CSV), or JavaScript Object Notation (JSON) file. These data were then imported into a clinical data warehouse. Additional values based on the radiology data were calculated during this import process by implementing 1 of several provided interfaces. Afterward, the query language and GUI of the data warehouse were used to configure and calculate reports on these data. For the most common types of requested reports, a web interface was created to view their numbers as graphics. Results: The tool was successfully tested with the data of 4 different German hospitals from 2018 to 2021, with a total of 1,436,111 examinations. The user feedback was good, since all their queries could be answered if the available data were sufficient. The initial processing of the radiology data for using them with the clinical data warehouse took (depending on the amount of data provided by each hospital) between 7 minutes and 1 hour 11 minutes. Calculating 3 reports of different complexities on the data of each hospital was possible in 1-3 seconds for reports with up to 200 individual calculations and in up to 1.5 minutes for reports with up to 8200 individual calculations. Conclusions: A system was developed with the main advantage of being generic concerning the export of different RISs as well as concerning the configuration of queries for various reports. The queries could be configured easily using the GUI of the data warehouse, and their results could be exported into the standard formats Excel and CSV for further processing. KW - data warehouse KW - eHealth KW - hospital data KW - electronic health records KW - radiology KW - statistics and numerical data KW - medical records Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-349411 SN - 2291-9694 VL - 11 ER -