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for these architectures remains a key challenge. This project will explore how reconfigurable/spatial computing devices can be integrated into large-scale heterogeneous infrastructures, which include CPUs, GPUs, DPUs, and
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data (i.e., large-scale assessments from the LKK project ) (Study 1 & 2); qualitative analysis of child data collected with the mosaic method (Study 3); a mixed-method analysis of the caregiver-child
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with the world’s highest volcanic activity, yet eruption histories, geological maps, and monitoring data are incomplete or absent. Volcanoes capable of very large magnitude eruptions (M ≥ 6), with
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. This is further hindered by a lack of diverse big data resources and matched, powerful analytical tools. As a result, progress in the field has been characteristically slow over the last 50 years
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equipment in large structure environment, it is necessary to have access to a map of its topology, which may be based on BIM data (if existent) and floor plans or must be generated from collecting and
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research group aims to use this large amount of multimodal data from both cameras and surgical devices to develop an artificial intelligence system that can assist clinicians and staff in the surgical
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and interdisciplinary projects integrated into large national and European research consortia such as the DAPHNE (DAta for PHoton and Neutron Experiments) NFDI consortium. The group offers well-equipped
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data (i.e., large-scale assessments from the LKK project ) (Study 1 & 2); qualitative analysis of child data collected with the mosaic method (Study 3); a mixed-method analysis of the caregiver-child
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offered provide access to challenging and interdisciplinary projects integrated into large national and European research consortia such as the DAPHNE (DAta for PHoton and Neutron Experiments) NFDI
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range and vast number of influencing factors makes understanding, preventing, and treating these behaviours highly challenging. This is further hindered by a lack of diverse big data resources and matched