Semantic models provide a formalized understanding of the contexts of datasets, facilitating a unified interpretation of data by both humans and machines. ...
In Vorbereitung
In Vorbereitung
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Comprehensive, accurately labeled sensor datasets are an essential prerequisite for training supervised machine learning models used for tasks such as ...
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Fair and secure voting is a cornerstone of democracies and, at the same time, one of the most challenging government processes. Thus, government services ...
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The digitization of manufacturing processes opens up the possibility of data-driven quality predictions based on machine learning (ML) methods, also known ...
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The number of Blockchain (BC) platforms developed since the proposal of Bitcoin in 2009 continues to increase as the price of their underlying cryptocurrencies ...
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This is my Ph.D. thesis on the area of Blockchains (BC) and their integration with Internet of things (IoT) use cases. This thesis explored many specific ...
Many real-world problems can be described by using discrete or hybrid stochastic systems. Modeling and simulation of such systems is possible, if they ...
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The monograph consists of 11 Chapters and Apendixes A, B, and C. The text begins with an introduction to the authors’ creation, where the reasons for ...
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Artificial neural networks are dominating a vast majority of application scenarios to date, and will surely extend their lead in the near future. Especially, ...
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Distributed Denial-of-Service (DDoS) attacks are one of the major causes of concerns for communication service providers. When an attack is highly sophisticated ...
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