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- Kaiser, M., et al.
(författare)
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VEDLIoT: Very Efficient Deep Learning in IoT
- 2022
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Ingår i: Proceedings of the 2022 Design, Automation and Test in Europe Conference and Exhibition, DATE 2022. - : IEEE. - 9783981926361
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Konferensbidrag (refereegranskat)abstract
- The VEDLIoT project targets the development of energy-efficient Deep Learning for distributed AIoT applications. A holistic approach is used to optimize algorithms while also dealing with safety and security challenges. The approach is based on a modular and scalable cognitive IoT hardware platform. Using modular microserver technology enables the user to configure the hardware to satisfy a wide range of applications. VEDLIoT offers a complete design flow for Next-Generation IoT devices required for collaboratively solving complex Deep Learning applications across distributed systems. The methods are tested on various use-cases ranging from Smart Home to Automotive and Industrial IoT appliances. VEDLIoT is an H2020 EU project which started in November 2020. It is currently in an intermediate stage with the first results available.
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| 3. |
- Astermark, Jan, et al.
(författare)
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Non-genetic risk factors and the development of inhibitors in haemophilia: a comprehensive review and consensus report.
- 2010
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Ingår i: Haemophilia. - : Wiley. - 1351-8216. ; May 4, s. 747-766
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Tidskriftsartikel (refereegranskat)abstract
- Summary. The development of inhibitors to the infused factor in patients with haemophilia is a serious clinical problem. Recent evidence suggests that alongside the strong genetic contribution to inhibitor formation, there are a number of non-genetic factors - perceived by the immune system as danger signals - which promote formation of inhibitors. This study provides a comprehensive review of clinical studies relating to these factors and also presents a survey of opinion concerning their importance and clinical influence, conducted among the members of the European Haemophilia Treatment Standardisation Board (EHTSB). Taken together, this information highlights the lack of robust data concerning the influence of several non-genetic risk factors on inhibitor development, and an urgent need for prospective, well-conducted studies that adhere to recommendations made by the European Medicines Agency (EMEA) for studying inhibitors. Based on current literature, the EHTSB formulated consensus recommendations. It is desirable to minimize intensive treatment wherever possible, given the clinical situation. Prophylaxis should be offered to all children, although we still need to determine optimal dosing with respect to inhibitor development, and age for starting treatment. Vaccinations should be given subcutaneously and concomitant factor concentrate infusions avoided. According to the board, there is no evidence in the literature supporting suggestions that the type of concentrate influences inhibitor risk; but all patients should be monitored during their first exposures. Furthermore, there is no evidence to support an association between pregnancy-related issues, breast feeding and treatment-related factors (e.g. route of administration, or use of blood components) and inhibitor development.
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| 5. |
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| 6. |
- Salami, B., et al.
(författare)
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LEGaTO: Low-Energy, Secure, and Resilient Toolset for Heterogeneous Computing
- 2020
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Ingår i: PROCEEDINGS OF THE 2020 DESIGN, AUTOMATION & TEST IN EUROPE CONFERENCE & EXHIBITION (DATE 2020). - 1530-1591. - 9783981926347 ; , s. 169-174
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Konferensbidrag (refereegranskat)abstract
- The LEGaTO project leverages task-based programming models to provide a software ecosystem for Made in-Europe heterogeneous hardware composed of CPUs, GPUs, FPGAs and dataflow engines. The aim is to attain one order of magnitude energy savings from the edge to the converged cloud/HPC, balanced with the security and resilience challenges. LEGaTO is an ongoing three-year EU H2020 project started in December 2017.
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