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Abstract: In cardiology departments supporting implantable cardioverter defibrillator (ICD) patient follow-up, patient data reside in a number of autonomous healthcare information systems that support different standard and proprietary formats, and it is up to each organization to choose electronic health record (EHR) integration solutions, underlying technologies, and standards based on their own needs, experience, and budget. However, without efficient data integration, significant gaps in the workflow will continue to hinder immediate availability of the patient data needed by healthcare professionals and their patients, and thus optimal use of clinical information and human resources. In this paper, we present the iCARDEA healthcare integration platform from the view point of ICD patient follow-up in a cardiology department, driven by the story of fictitious Mr. Schmidt, who is using the latest remote monitoring technology, manages his own personal health record (PHR), and hopes to live a long active life, supported by the latest developments in eHealth technology. […]

Im Rahmen der 15. Internationalen Motorradkonferenz in Köln wurde von der Fédération Internationale de Motocyclisme (FIM) der Award für Young Researchers verliehen. Unser Kollege Wolfgang Kremser wurde für das Paper „Towards Full-Body Motion Capture of Motorcyclists In Situ – A Validation Study and User Report“ mit dem 2. Platz ausgezeichnet. Die Körperhaltung beim Motorradfahren beeinflusst die Fahrzeugdynamik stark, was sie für Konstrukteure besonders interessant macht. Standard-Bewegungserfassungssysteme sind jedoch ungeeignet für den Außeneinsatz, da sie mehrere fest installierte Kameras benötigen. Wolfgang Kremser untersuchte daher die Realisierbarkeit einer Alternative mittels mobiler, direkt am Körper getragener Inertialsensorik. Diese Sensordaten wurden im Vergleich zu einem optischen Bewegungserfassungssystem auf einem Motorradsimulator validiert. Das untersuchte Sensorsystem zeigte eine hohe Übereinstimmung mit dem Goldstandard und scheint geeignet, um allgemeine Bewegungsmuster beim Motorradfahren aufzuzeichnen. Abstract: During motorcycle riding the driver’s posture significantly impacts the vehicle dynamics, which makes its study important to design engineers. Current gold standard motion capture systems are unfit […]

Vielen Dank, dass Sie an unserer Studie teilnehmen! Der Connected Boot wurde von Salzburg Research gemeinsam mit Atomic und der Universität Salzburg im Projekt „Digital Motion“ entwickelt. Im Rahmen der Studie 2023 soll der Algorithmus des Carving Scores für eine breitere Zielgruppe validiert und die Akzeptanz der technologischen Lösung unter den Nutzer:innen untersucht werden. Hier finden Sie alle relevanten Informationen: Umfrage Wir bitten dich, vor dem Test des Connected Boots Teil A der Umfrage auszufüllen: Zur Umfrage -Teil A Du hast den Connected Boot getestet? Bitte fülle abschließend Teil B der Umfrage aus: Zur Umfrage -Teil B Unter allen vollständig ausgefüllten Umfragen verlosen wir: 1 Paar Atomic Ski 1 Paar Atomic Skischuhe -50% oder -30% Voucher für den Atomic Online-Store Auslosung nach Studienende Mai 2023 Download der App Die App zur Studie finden Sie sowohl auf Google Play als auch im App Store: Android: Turnalizer-App iOS: Atomic Connected Für die Verwendung der App benötigen […]

Das Projekt K2_LCM ist ein Nachfolgeprojekt der derzeitigen Kooperation im Rahmen von „Gesture Aided Learning“. Das Folgeprojekt ist als ein Teil des strategischen Projektes innerhalb des K2 Zentrums konzipiert. Inhaltlich erfolgt die Anpassung und Weiterentwicklung der HMDP.

Unser Service für die Reproduzierbarkeit Ihrer Forschungsergebnisse mit einem Befehl, insbesondere für Statistik, Signalverarbeitung, Maschinelles Lernen sowie Tiefes Lernen. Reproduzierbarkeit ist eine zentrale Anforderung an wissenschaftliche Arbeit. Dennoch sind die meisten Forschungsarbeiten schwer oder gar nicht reproduzierbar. Der Code und die Daten sind kaum verfügbar und die Entwicklungsumgebungen oft nicht genau dokumentiert oder leicht nachbaubar sind. Dies stellt ein großes Problem für die wissenschaftliche Integrität und die Nachvollziehbarkeit von Ergebnissen dar. Mit unserem Service für Reproduzierbarkeit von Deep Learning unterstützen wir Universitäten und Unternehmen dabei, ihre Forschungsarbeiten so zu gestalten, dass sie einfach und nachhaltig reproduziert werden können. Unsere Lösung basiert auf containerisierten, GPU-gestützten Jupyter-Umgebungen, die eine standardisierte und reproduzierbare Experimentierplattform bieten. Unsere Leistungen Wir bieten ein umfassendes Paket für die Sicherstellung der Reproduzierbarkeit von Deep-Learning-Experimenten, darunter: Einrichtung einer reproduzierbaren Entwicklungsumgebung: Wir setzen eine standardisierte Deep-Learning-Umgebung auf, die mit nur einem Befehl exakt und versionskontrolliert reproduziert werden kann. Die Programmiersprachen/Bibliotheken Python, R, Julia, C/C++, Jupyter, PyTorch, […]

Alpine skiing is a popular sport in many countries and holds benefits in terms of health and well-being. At the same time alpine skiing is associated with a certain risk of accidents caused, among other things, by overestimating one’s own skiing skills. Self-assessment of skiing skills is not trivial. Therefore, feedback modalities can be assistive. One feasible option to provide skiers with feedback on their skiing ability are Inertial Measurement Units (IMUs). The aim of this study was to analyse the skiing quality of recreational skiers based on IMU data, collected with the Connected Boot sensor system with a living lab approach to investigate whether the skiing quality score delivers reasonable results for recreational skiers. The system has been developed with expert skiers and so far has not been validated with recreational skiers. Therefore, we aimed to investigate whether the objective skiing quality score of the Connected Boot corresponds to the self-assessed carving ability […]

This master thesis presents an approach to apply purely passive, privacy-preserving network monitoring to a performance monitoring problem. Internet service providers and network operators need to know, which services their customers are consuming on which quality level. In addition, the customer must be enabled to relate the experienced quality to the agreed service level parameters. The application of passive network monitoring for such tasks is useful: First, it can evaluate the real traffic of the customers, without injecting additional traffic to the network and second, measurement results are exactly based on the services the customers are accessing. On the other hand, passive network monitoring always includes the risk of compromising the customers’ right for privacy and therefore often raises privacy concerns from the public. Nevertheless, recent privacy-preserving monitoring frameworks allow overcoming the “privacy-versus-utility” dilemma by decoupling data capturing, filtering and data processing in separate steps, always applying the required level of privacy. This work […]

[…] individuelle Fahrverhalten wird gemessen, skirelevante Parameter wie Aufkantwinkel oder Geschwindigkeit berechnet und das Fahrkönnen mit dem eigens entwickelten „Carving Score“ beurteilt. Durch individuelles Feedback zur Bewegungsqualität bei jedem Skischwung und während des gesamten Skitages erhalten Skifahrende besseren Einblick in die eigene Leistung. Sie können an ihrer Technik feilen und so das Skierlebnis verbessern. Jetzt Tester:in werden Sie planen einen Skitag und möchten gerne wissen, ob Ihr Skischwung gecarvt oder eher gerutscht ist? Erstmals können im Winter 2022/ 23 auch Hobbyskiläufer:innen neueste Technologien ausprobieren, die mit Profis entwickelt wurden. So geht’s: Ski-Strap mit integrierter Sensortechnologie kostenlos ausleihen und am eigenen Skischuh befestigen, App installieren und ab auf die Piste. Nach jeder Abfahrt bekommen Sie unmittelbar eine Auswertung Ihrer Carving-Schwünge auf’s Handy. Hier anmelden: Anmeldung als Connected-Boot-Tester:in Wollen Sie sich auch mit Ihren Ideen in unsere Forschungsarbeit einbringen? Wir suchen Ideen, wie E-Fahrzeuge durch smartes Laden einen Beitrag zu einem stabilen Stromnetz leisten können. Mehr dazu: […]

[…] A good blog entry regarding size reduction with TopoJSON has been posted by ZevRoss. Mapbox Vector Tiles use google’s protocol buffers as binary output format which is even much smaller than TopoJSON but not human readable. Tile Map Request Protocols Besides an output format definition, the modality of requesting the tiles is important. Looking at the most popular JavaScript frameworks Mapbox GL JS and Tangrams, I discovered two protocols that are supported by both clients: Tile Map Service (TMS) Slippy Map Tiles (aka XYZ) Both standards have REST like structure. The TMS allows different clips and coordinate reference systems. Slippy Map Tiles is a special TMS restricted to the Transversal Mercator Projection with mirrored y-Axis, a defined origin and used by big players like OpenStreetMap, Google maps or Bing maps. Consequently the slippy map tiles have become to a de facto standard in serving tiles. GeoServer Extension The OpenSource GeoServer supports most of the […]

In order to study QoS and SLAs in inter-domain environment, network tomography mechanisms could be applied to inference inter-domain network characteristics from end-to-end observations. QoS estimates can be used by Internet Service Providers and corporate users to evaluate and validate the QoS as provided by the Autonomous systems. In this paper, a practical approach to inference statistical and model characteristics of inter-domain QoS based on active end-to-end QoS monitoring is discussed. The focus is a systematic approach for analysis of spatiotemporal composition of end-to-end QoS in interdomain evironment based on active QoS monitoring combined with estimation of „hidden“ unobservable inter-domain QoS impacting the end-to-end traffic. In order to validate the inter-domain tomography approach for spatial composition of end-to-end application QoS, we establish an emulation environment which models realistic topologies and utilises real network traces. We studied practical scenarios for estimating of spatial composition of emulated end-to-end VoIP traffic using the CM Toolset as active […]

Recent developments in sensor technology have made sensing units cheaper and easier to implement. These developments have made the application of “wearable technology”, or smart sporting equipment appealing to a broad audience allowing measuring metrics of motion quantity (e.g. distance, time, number of cycles) and motion quality, or how well a sport technique is performed. In the current presentation the concept of an instrumented ski boot, an instrumented alpine ski using the PyzoFlex® sensor foil technology and the determination of force components and measures of effectiveness within various cross-country skiing (XCS) techniques applying a push-off model is presented. The Atomic connected boot consists of an IMU mounted on the shaft of the boot. With this concept macroscopic metrics like turn detection, turn count (1) and jump detection (2) were developed while on a more microscopic level a skiing style detection algorithm and carving score concept (3) was established to determine the skiing/carving quality while […]

[…] der die Teilnehmenden Energie lokal erzeugen und direkt mit anderen Mitgliedern der Gemeinschaft handeln können. Ein Schwerpunkt der Architektur liegt auf der Integration modernster Technologien zur Optimierung des Netzbetriebs, der Sicherheit und des Verbrauchsmanagements. Durch Flexibilität und Skalierbarkeit kann sie auch zukünftige Anforderungen bewältigen. Handlungsempfehlungen für Energiegemeinschaften Basierend auf umfangreichen Simulationen, Stakeholder-Workshops und der Analyse von Referenzprojekten haben die Forschenden Empfehlungen formuliert, wie lokale Energiegemeinschaften in Zukunft noch effektiver gestaltet und die langfristige Stabilität und Attraktivität derartiger Energiegemeinschaften sichergestellt werden können. Das Handbuch mit Best- Practice-Beispielen und Handlungsempfehlungen richtet sich an Entscheidungsträger:innen, die Energiewirtschaft und Energiegemeinschaften. ECOSINT wurde im Klima- und Energiefonds durch das BMK und die FFG gefördert. Zum Best-Practice Handbuch & Handlungsempfehlungen: Mark Stefan, David Reihs, Florian Strebl, Jawad Kazmi, Ingrid Schürrer, Alexander Herbst, Peter Dorfinger, Stefan Linecker, Peter Stern, Stephan Cejka, Franz Zeilinger, Johannes Reichl, Rudolf Kapeller, Günther Eibl, Oliver Langthaler (2024): ECOSINT Best-Practice Handbuch & Handlungsempfehlungen. © The ECOSINT Consortium, 2020-2024.

Utilization of a mobile communication cell’s physical resources is a crucial impact factor on the data rate and quality of service available to a network user. Information about the utilization is therefore of great interest to researchers and network providers. Measurement scenarios that should be carried out independent of network providers require a measurement method that does not depend on a connection to a base station. In this work, we propose a novel estimation algorithm and introduce a measurement tool based on this algorithm, which is able to estimate the utilization of a 5G cell’s physical resources without being connected to a base station. The proposed estimation algorithm is a two-step machine learning algorithm, based on Expectation-Maximization. An off-the-shelf software-defined radio is used for the implementation of the measurement tool, making it inexpensive and widely applicable. The measurement method is entirely passive and does not depend on any connection to the network, making it […]

Classifying sleep stages is an important basis for neuroscience, health sciences, psychology and many other fields. However, the manual determination of sleep stages is tedious and time consuming. Therefore, the development of automatic sleep stage classifiers based on data collected with low-cost sensor systems is an important research area. This study aims to analyse the generalisability of different machine learning approaches for sleep stage classification. We train three different models (random forest, CNN-LSTM and seq2seq) for classifying three as well as four sleep stages, with the MESA data set. For validation, we use a fivefold cross-validation and further validate the models with one new self-recorded test data set to analyse the models’ generalisability to a completely new cohort with different characteristics with regard to age and health status. Our results show that the two deep learning approaches performed better than the random forest. Moreover, all models are generalisable and therefore suitable for sleep stage […]

[…] Historically, there have been various disjoint approaches to measuring and collecting quality metrics for mobile communications. These span from crowdsourced data collection (private and regulatory), over dedicated (drive test) measurement campaigns to monitoring within a mobile network itself (see our earlier Blogpost). The network-centered approach, however, requires full access to the communication network and is typically only feasible for the network operator. Network operators constantly monitor the state of their network to provide the targeted quality of service to the users, or to recognize network anomalies or failures. Their supervision technology is capable of monitoring the network usage and all of its parameters in full detail. This provides essential insights for network planning. The availability of such data can be an enabler for certain aspects of research, such as comprehensive user behaviour analyses or traffic type analyses. Unfortunately, due to the delicate nature of such extensive data, network operators typically do not disclose this […]

The engineering and validation of substation visualizations are still labor-intensive tasks. Most of the configuration steps are typically done manually and are thus error-prone and time consuming; they contribute to a significant degree to the overall engineering costs. The goal of this work is to decrease these costs and to increase the quality of the engineering process at the same time. The corresponding approach is based on a general concept of a model-based, automated engineering and validation framework that covers the entire engineering process of modern energy applications. First, the rationale behind this framework and its cornerstones are presented. Then, it is shown how an IEC 61850-based substation visualization can be generated and validated through automated signal tests. A prototypical implementation of the approach yields encouraging results as a high degree of automation is achieved.

The purpose of the current study was to evaluate the ecological validity of two previously developed laboratory-based random forest machine learning models and train two new ecologically valid models for the 1) prediction of foot strike angle (FSA) and 2) classification of foot strike pattern (FSP) from wearable insoles during running. The original models performed worse with track-surface running data inputs than in their original validation (prediction RMSE = 6.84° vs. 3.65°, classification accuracy = 79.5% vs. 94.1%). The new models, trained using track-surface data, improved the estimation of FSA (RMSE = 4.10°) and FSP (accuracy = 84.8%). To ensure estimation accuracy, future models should be trained with respect to the environment/conditions in which they will be implemented.

2nd International Workshop on Hypermedia & Web Engineering WORKSHOP THEME & GOALS The goal of this workshop is to bring together researchers and developers from academia and industry to exchange ideas about the problems they are facing during current Web / Hypermedia Projects, and to discuss good practices and successful case studies (concrete examples, designs and applications), as well as recent and innovative results in Web and Hypermedia Engineering. Web and Hypermedia engineering have provided several important research and practical results especially during the last decade. However, very few of them have transferred to real-life projects. Engineers are unable to study all these results, since it is a time consuming task, difficult to be accomplished in the strict timeline of a project. As a consequence, web & hypermedia research results are not used adequately (if at all) during the development of current Hypermedia / Web Information Systems. As more research results come up every […]