Titlebook: Scalable Uncertainty Management; First International Henri Prade,V. S. Subrahmanian Conference proceedings 2007 Springer-Verlag Berlin Hei

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Meltem Öztürk,Alexis Tsoukiàse useful in simulating the technology, equipment, and practices of many different fields. In the medical field, VR can be heavily relied upon to circumvent a wide variety of tools, human resources, and other objects that may be limited or difficult to procure at any given time. As a result, the goal

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Octavian Udrea,Zoran Majkić,V. S. Subrahmaniany notations. For software-intensive systems with heterogeneous components and entailing different domain-specific aspects and different stakeholders, one editing notation is too little and voids many modelling benefits. Seamless blended modelling, which allows stakeholders to freely choose and switc

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Carlos D. Barranco,Jesús R. Campaña,Juan M. Medinaons. Nowadays, many recalls are reported for insulin infusion pump systems, motivating the usage of a formal model-based approach to improve quality. However, the usage of such approaches increases costs and development time. Thus, this study aims to assist the quality assessment of such systems cos

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Ying Wang,Weiru Liu,David Bellives. BIKE is one of them. This paper deals with several considerations around building an isochronous and constant-time implementation of the errors-vector generation (EVG) that is used by BIKE. The starting point is the Round 3 BIKE (Ver. 4.2), where a recently published timing attack motivated so

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Sergio Flesca,Filippo Furfaro,Francesco ParisiD-19 cases and social media activity on Twitter. We were particularly interested in determining if Twitter activity can be used to predict COVID-19 surges. We also were interested in exploring features of social media, such as replies, to determine their promise for understanding the views of indivi

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L. Caroprese,E. Zumpano Significant Wave Height (SWH) plays a major role in wave energy and hence this study aims to predict wave height using time series of wave characteristics as input to various machine learning approaches and analyze these approaches under several scenarios. Two different machine learning algorithms

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te Funktion” und “COTS-Komponente”. Es wird ein Systemgraf erstellt mit dem anschließend die Multiple Domain Matrix instanziiert wird und der Ablauf der Komponentenauswahl dargelegt wird. Die Komponentenauswahl bedient sich der in den Abhängigkeitsmatrizen gespeicherten Informationen. In einer exemp

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Emad Saadaben ausführen können. Ein semantisches Modell kann hierbei eine zentrale Rolle spielen. In diesem Beitrag stellen wir die Grundlage für die Ausarbeitung dieses Modells vor, mit Berücksichtigung von Qualitätsaspekten wie Standardisierung, (Wieder-) Verwendbarkeit und Integrierbarkeit. Am Ende zeigen