Titlebook: Handbuch der Laplace-Transformation; Anwendungen der Lapl Gustav Doetsch Book 1956 Springer Basel AG 1956 Anwendung.Handbuch.Laplace-Transf

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Gustav DoetschEHR data analysis has become a big data problem as data is growing rapidly. Using a nursing EHR system, we built predictive models for determining what factors influence pain in end-of-life (EOL) patients. Utilizing different modeling techniques, we developed coarse-grained and fine-grained models t

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Gustav Doetschhave proven very efficient to extract meaningful information from images. Our goal is to learn a mapping from a binary image of a 2D shape to a parametric Bézier curve representation of the medial axis of the shape using a convolutional neural network. We determine the most salient curves in the Blu

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Gustav Doetsche on specific roles. Users who manifest similar structural and connectivity patterns assume similar roles. The analysis of a network in terms of the component roles can facilitate the discovery of communities. By compressing big and complex networks, roles can also enable the discovery of important

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ing transformed approximated Heaviside functions (AHFs) for better visualization. In particular, we provide an efficient method for directly computing the scaling and shifting factors of the transformed AHFs, so that blurred edges can be improved accurately. To recover more image structures, we give

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