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Location-aware mobile devices are becoming increasingly popular and GPS sensors are built into nearly every portable unit with computational capabilities. At the same time, the emergence of location-aware virtual services and ideas calls for new efficient spatial real-time queries. Communication latency in mobile environments interacting with high decentralization and the need of scalability in high-density systems with immense client counts leads to major challenges. In this paper we describe a decentralized architecture for continuous range queries in settings in which both, the requested and the requesting clients, are mobile. While prior works commonly use a request-response approach we provide a stream-based adaptive grid solution dealing with arbitrary high client counts and improving communication latency that meets given hard real-time constraints.
A residual neural network was adapted and applied to the Physionet/Computing data in Cardiology Challenge 2020 to detect 24 different classes of cardiac abnormalities from 12-lead. Additive Gaussian noise, signal shifting, and the classification of signal sections of different lengths were applied to prevent the network from overfitting and facilitating generalization. Due to the use of a global pooling layer after the feature extractor, the network is independent of the signal’s length. On the hidden test set of the challenge, the model achieved a validation score of 0.656 and a full test score of 0.27, placing us 15th out of 41 officially ranked teams (Team name: UC_Lab_Kn). These results show the potential of deep neural networks for ap- plication to raw data and a complex multi-class multi-label classification problem, even if the training data is from di- verse datasets and of differing lengths.
Ballistocardiography (BCG) can be used to monitor heart rate activity. Besides, the accelerometer should have high sensitivity and minimal internal noise; a low-cost approach was taken into consideration. Several measurements have been executed to determine the optimal positioning of a sensor under the mattress to obtain a signal strong enough for further analysis. A prototype for an unobtrusive accelerometer-based measurement system has been developed and tested in a conventional bed without any specific extras. The influence of the human sleep position for the output accelerometer data was tested. The obtained results indicate the potential to capture BCG signals using accelerometers. The measurement system can detect heart rate in an unobtrusive form in the home environment.
The main aim of presented in this manuscript research is to compare the results of objective and subjective measurement of sleep quality for older adults (65+) in the home environment. A total amount of 73 nights was evaluated in this study. Placing under the mattress device was used to obtain objective measurement data, and a common question on perceived sleep quality was asked to collect the subjective sleep quality level. The achieved results confirm the correlation between objective and subjective measurement of sleep quality with the average standard deviation equal to 2 of 10 possible quality points.
Forschungsfrage: Welche Rollen lassen sich in Corporate Entrepreneurship identifizieren? Wie unterscheiden sich diese anhand verschiedener Merkmale und welche Fähigkeiten scheinen besonders relevant für ihre erfolgreiche Ausführung?
Methodik: Explorative Studie mit 56 semi-strukturierten Interviews mit Corporate-Entrepreneurship-Aktivitäten im DACH-Raum
Praktische Implikationen: Ein genaues Verständnis über die jeweiligen Rollen, ihre Unterschiedlichkeiten und Anforderungen ist notwendig, um die verschiedenen Corporate-Entrepreneurship-Aktivitäten mit passendem Personal zu besetzen.
Der digitale Seilüberwacher
(2020)
In beispielhafter Zusammenarbeit zwischen Industrie (Geobrugg AG, Romanshorn/Schweiz) und Wissenschaft (WITg Institut für Werkstoffsystemtechnik Thurgau an der Hochschule Konstanz, Tägerwilen/Schweiz) wurde mit Unterstützung der Schweizer staatlichen Innovationsförderung (KTI, hee Innosuisse) ein neues Werkstoff- und Fertigungskonzept für den Bau von Fischzuchtnetzen aus hochfesten nichtrostenden Stahldrähten entwickelt.
Diese Entwicklung wurde 2019 von Swiss Inox, der Schweizer Innovationspreis Prix Inox ausgezeichnet.