| 1. |
- Kaiser, M., et al.
(author)
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VEDLIoT: Very Efficient Deep Learning in IoT
- 2022
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In: Proceedings of the 2022 Design, Automation and Test in Europe Conference and Exhibition, DATE 2022. - : IEEE. - 9783981926361
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Conference paper (peer-reviewed)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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| 2. |
- Salami, B., et al.
(author)
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LEGaTO: Low-Energy, Secure, and Resilient Toolset for Heterogeneous Computing
- 2020
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In: PROCEEDINGS OF THE 2020 DESIGN, AUTOMATION & TEST IN EUROPE CONFERENCE & EXHIBITION (DATE 2020). - 1530-1591. - 9783981926347 ; , s. 169-174
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Conference paper (peer-reviewed)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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| 3. |
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| 4. |
- Gundersen, Per Ole M., et al.
(author)
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Retrospective screening of new psychoactive substances (NPS) in post mortem samples from 2014 to 2021
- 2024
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In: Forensic Science International. - : ELSEVIER IRELAND LTD. - 0379-0738 .- 1872-6283. ; 361
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Journal article (peer-reviewed)abstract
- Systematic retrospective processing of previously analysed biological samples has been proven to be a valuable tool in the search for new drugs (e.g. new psychoactive substances (NPS)) and for quality assessment in clinical and forensic toxicology. In a previous study, we developed a strategy for retrospective data-analysis using a personalized library of synthetic cannabinoids, designer benzodiazepines and synthetic opioids obtained from the crowdsourced database HighResNPS (https://highresnps.com). In this study, the same strategy was employed for the compounds within the groups of NPS that were not previously included such as synthetic cathinones, phenethylamines, aminoindanes, arylalkylamines, piperazine derivates, piperidines, pyrrolidines, indolalkylamines and arylcyclohexylamines. Synthetic opioids and designer benzodiazepines, which were not part of the previous study, were also included. To enhance the effectiveness of the retrospective analysis, a predicted retention time was included for all entries. Data files from the analysis of 2186 forensic post mortem samples with an Agilent Technologies 6540 ultra-high pressure liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) performed in the laboratory from January 2014 to December 2021 were retrospectively processed with the up-to-date library. Tentative findings were classified in two groups: The findings where MS/MS data was acquired for library match (category 1) and the less certain findings where such data lacked (category 2). Five compounds of category 1 (three synthetic cathinones and two indolalkylamines) were identified in 12 samples. Only one of the findings, 4-MEAPP (4-methyl- alpha-ethylaminopentiophenone), was deemed plausible after reviewing case information. As many as 501 presumably positive category 2 findings were detected. Using the predicted retention time as an additional criterion the number was significantly reduced but still too high for a manual review. This work has demonstrated that the strategy developed in the previous study can be applied to other NPS groups. However, it is important to note the limitations such a method may have in detecting compounds at very low concentrations.
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| 5. |
- Ménétrey, J., et al.
(author)
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Attestation Mechanisms for Trusted Execution Environments Demystified
- 2022
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In: <em>Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)</em>. - Cham : Springer Science and Business Media Deutschland GmbH. - 9783031160912 ; , s. 95-113
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Conference paper (peer-reviewed)abstract
- Attestation is a fundamental building block to establish trust over software systems. When used in conjunction with trusted execution environments, it guarantees the genuineness of the code executed against powerful attackers and threats, paving the way for adoption in several sensitive application domains. This paper reviews remote attestation principles and explains how the modern and industrially well-established trusted execution environments Intel SGX, Arm TrustZone and AMD SEV, as well as emerging RISC-V solutions, leverage these mechanisms.
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