| 1. |
- Aad, G, et al.
(författare)
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- 2015
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swepub:Mat__t
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| 2. |
- Ferrario, M., et al.
(författare)
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IRIDE : Interdisciplinary research infrastructure based on dual electron linacs and lasers
- 2014
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Ingår i: Nuclear Instruments and Methods in Physics Research Section A. - : Elsevier BV. - 0168-9002 .- 1872-9576. ; 740, s. 138-146
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Tidskriftsartikel (refereegranskat)abstract
- This paper describes the scientific aims and potentials as well as the preliminary technical design of RUDE, an innovative tool for multi-disciplinary investigations in a wide field of scientific, technological and industrial applications. IRIDE will be a high intensity "particles factory", based on a combination of high duty cycle radio-frequency superconducting electron linacs and of high energy lasers. Conceived to provide unique research possibilities for particle physics, for condensed matter physics, chemistry and material science, for structural biology and industrial applications, IRIDE will open completely new research possibilities and advance our knowledge in many branches of science and technology. [RIDE is also supposed to be realized in subsequent stages of development depending on the assigned priorities.
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| 3. |
- Sadovykh, A., et al.
(författare)
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On the Use of Hackathons to Enhance Collaboration in Large Collaborative Projects : - A Preliminary Case Study of the MegaM@Rt2 EU Project - A P
- 2019
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Ingår i: Proceedings of the 2019 Design, Automation and Test in Europe Conference and Exhibition, DATE 2019. - : Institute of Electrical and Electronics Engineers Inc.. - 9783981926323 ; , s. 498-503
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Konferensbidrag (refereegranskat)abstract
- In this paper, we present the MegaM@Rt2 ECSEL project and discuss in details our approach for fostering collaboration in this project. We choose to use an internal hackathon approach that focuses on technical collaboration between case study owners and tool/method providers. The novelty of the approach is that we organize the technical workshop at our regular project progress meetings as a challenge-based contest involving all partners in the project. Case study partners submit their challenges related to the project goals and their use cases in advance. These challenges are concise enough to be experimented within approximately 4 hours. Teams are then formed to address those challenges. The teams include tool/method providers, case study owners and researchers/developers from other consortium members. On the hackathon day, partners work together to come with results addressing the challenges that are both interesting to encourage collaboration and convincing to continue further deeper investigations. Obtained results demonstrate that the hackathon approach stimulated knowledge exchanges among project partners and triggered new collaborations, notably between tool providers and use case owners.
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| 4. |
- Ghielmetti, N., et al.
(författare)
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Real-time semantic segmentation on FPGAs for autonomous vehicles with hls4ml
- 2022
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Ingår i: Machine Learning - Science and Technology. - : IOP Publishing. - 2632-2153. ; 3:4
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we investigate how field programmable gate arrays can serve as hardware accelerators for real-time semantic segmentation tasks relevant for autonomous driving. Considering compressed versions of the ENet convolutional neural network architecture, we demonstrate a fully-on-chip deployment with a latency of 4.9 ms per image, using less than 30% of the available resources on a Xilinx ZCU102 evaluation board. The latency is reduced to 3 ms per image when increasing the batch size to ten, corresponding to the use case where the autonomous vehicle receives inputs from multiple cameras simultaneously. We show, through aggressive filter reduction and heterogeneous quantization-aware training, and an optimized implementation of convolutional layers, that the power consumption and resource utilization can be significantly reduced while maintaining accuracy on the Cityscapes dataset.
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| 5. |
- Sadovykh, A., et al.
(författare)
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A Tool-Supported Approach for Building the Architecture and Roadmap in MegaM@Rt2 Project
- 2020
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Ingår i: Adv. Intell. Sys. Comput.. - Cham : Springer Verlag. - 9783030146863 ; , s. 265-274
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Konferensbidrag (refereegranskat)abstract
- MegaM@Rt2 is a large European project dedicated to the provisioning of a model-based methodology and supporting tooling for system engineering at a wide scale. It notably targets the continuous development and runtime validation of such complex systems by developing the MegaM@Rt2 framework to address a large set of engineering processes and application domains. This collaborative project involves 27 partners from 6 different countries, 9 industrial case studies as well as over 30 different tools from project partners (and others). In the context of the project, we opted for a pragmatic model-driven approach in order to specify the case study requirements, design the high-level architecture of the MegaM@Rt2 framework, perform the gap analysis between the industrial needs and current state-of-the-art, and to plan a first framework development roadmap accordingly. The present paper concentrates on the concrete examples of the tooling approach for building the framework architecture. In particular, we discuss the collaborative modeling, requirements definition tooling, approach for components modeling, traceability and document generation. The paper also provides a brief discussion of the practical lessons we have learned from it so far.
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| 6. |
- Sadovykh, A., et al.
(författare)
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MegaM@Rt2 Project : Mega-Modelling at Runtime - Intermediate Results and Research Challenges
- 2019
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Ingår i: Lect. Notes Comput. Sci.. - Cham : Springer. - 9783030298517 ; , s. 393-405
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Konferensbidrag (refereegranskat)abstract
- MegaM@Rt2 Project is a major European effort towards the model-driven engineering of complex Cyber-Physical systems combined with runtime analysis. Both areas are dealt within the same methodology to enjoy the mutual benefits through sharing and tracking various engineering artifacts. The project involves 27 partners that contribute with diverse research and industrial practices addressing real-life case study challenges stemming from 9 application domains. These partners jointly progress towards a common framework to support those application domains with model-driven engineering, verification, and runtime analysis methods. In this paper, we present the motivation for the project, the current approach and the intermediate results in terms of tools, research work and practical evaluation on use cases from the project. We also discuss outstanding challenges and proposed approaches to address them.
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| 7. |
- Sadovykh, A., et al.
(författare)
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On a tool-supported model-based approach for building architectures and roadmaps : The MegaM@Rt2 project experience
- 2019
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Ingår i: Microprocessors and microsystems. - : Elsevier B.V.. - 0141-9331 .- 1872-9436. ; 71
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Tidskriftsartikel (refereegranskat)abstract
- MegaM@Rt2 is a large European project dedicated to the provisioning of a model-based methodology and supporting tooling for system engineering at a wide scale. It notably targets the continuous development and runtime validation of such complex systems by developing a framework addressing a large set of engineering processes and application domains. This collaborative project involves 27 partners from 6 different countries, 9 industrial case studies as well as over 30 different software tools from project partners (and others). In the context of the MegaM@Rt2 project, we elaborated on a pragmatic model-driven approach to specify the case study requirements, design the high-level architecture of a framework, perform the gap analysis between the industrial needs and current state-of-the-art, and plan a first framework development roadmap accordingly. The present paper describes the generic tool-supported approach that came out as a result. It also details its concrete application in the MegaM@Rt2 project. In particular, we discuss the collaborative modeling process, the requirement definition tooling, the approach for components modeling, as well as the traceability and document generation. In addition, we show how we used the proposed solution to specify the MegaM@Rt2 framework's conceptual tool components centered around three complementary tool sets: the MegaM@Rt2 System Engineering Tool Set, the MegaM@Rt2 Runtime Analysis Tool Set and the MegaM@Rt2 Model & Traceability Management Tool Set. The paper ends with a discussion on the practical lessons we have learned from this work so far.
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| 8. |
- Savino, G., et al.
(författare)
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Further Development of Motorcycle Autonomous Emergency Braking (MAEB), What Can In-Depth Studies Tell Us? A Multinational Study
- 2014
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Ingår i: Traffic Injury Prevention. - : Informa UK Limited. - 1538-957X .- 1538-9588. ; 15, s. S165-S172
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Tidskriftsartikel (refereegranskat)abstract
- Objective: In 2006, Motorcycle Autonomous Emergency Braking (MAEB) was developed by a European Consortium (Powered Two Wheeler Integrated Safety, PISa) as a crash severity countermeasure for riders. This system can detect an obstacle through sensors in the front of the motorcycle and brakes automatically to achieve a 0.3 g deceleration if the collision is inevitable and the rider does not react. However, if the rider does brake, full braking force is applied automatically. Previous research into the potential benefits of MAEB has shown encouraging results. However, this was based on MAEB triggering algorithms designed for motorcycle crashes involving impacts with fixed objects and rear-end crashes. To estimate the full potential benefit of MAEB, there is a need to understand the full spectrum of motorcycle crashes and further develop triggering algorithms that apply to a wider spectrum of crash scenarios. Methods: In-depth crash data from 3 different countries were used: 80 hospital admittance cases collected during 2012–2013 within a 3-h driving range of Sydney, Australia, 40 crashes with Injury Severity Score (ISS) > 15 collected in the metropolitan area of Florence, Italy, during 2009–2012, and 92 fatal crashes that occurred in Sweden during 2008–2009. In the first step, the potential applicability of MAEB among the crashes was assessed using a decision tree method. To achieve this, a new triggering algorithm for MAEB was developed to address crossing scenarios as well as crashes involving stationary objects. In the second step, the potential benefit of MAEB across the applicable crashes was examined by using numerical computer simulations. Each crash was reconstructed twice—once with and once without MAEB deployed. Results: The principal finding is that using the new triggering algorithm, MAEB is seen to apply to a broad range of multivehicle motorcycle crashes. Crash mitigation was achieved through reductions in impact speed of up to approximately 10 percent, depending on the crash scenario and the initial vehicle pre-impact speeds. Conclusions: This research is the first attempt to evaluate MAEB with simulations on a broad range of crash scenarios using in-depth data. The results give further insights into the feasibility of MAEB in different speed ranges. It is clear then that MAEB is a promising technology that warrants further attention by researchers, manufacturers, and regulators.
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