| 1. |
- Bellini, Emanuele, et al.
(författare)
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Resilience learning through self adaptation in digital twins of human-cyber-physical systems
- 2021
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Ingår i: Proceedings of the 2021 IEEE International Conference on Cyber Security and Resilience (CSR). - : IEEE. - 9781665402859 - 9781665402866 ; , s. 168-173
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Konferensbidrag (refereegranskat)abstract
- Human-Cyber-Physical-Systems (HPCS), such as critical infrastructures in modern society, are subject to several systemic threats due to their complex interconnections and interdependencies. Management of systemic threats requires a paradigm shift from static risk assessment to holistic resilience modeling and evaluation using intelligent, data-driven and run-time approaches. In fact, the complexity and criticality of HCPS requires timely decisions considering many parameters and implications, which in turn require the adoption of advanced monitoring frameworks and evaluation tools. In order to tackle such challenge, we introduce those new paradigms in a framework named RESILTRON, envisioning Digital Twins (DT) to support decision making and improve resilience in HCPS under systemic stress. In order to represent possibly complex and heterogeneous HCPS, together with their environment and stressors, we leverage on multi-simulation approaches, combining multiple formalisms, data-driven approaches and Artificial Intelligence (AI) modelling paradigms, through a structured, modular and compositional framework. DT are used to provide an adaptive abstract representation of the system in terms of multi-layered spatially-embedded dynamic networks, and to apply self-adaptation to time-warped What-If analyses, in order to find the best sequence of decisions to ensure resilience under uncertainty and continuous HPCS evolution.
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| 2. |
- Bergemann, Maria, et al.
(författare)
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The Gaia-ESO Survey : Hydrogen lines in red giants directly trace stellar mass
- 2016
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Ingår i: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 594
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Tidskriftsartikel (refereegranskat)abstract
- Red giant stars are perhaps the most important type of stars for Galactic and extra-galactic archaeology: they are luminous, occur in all stellar populations, and their surface temperatures allow precise abundance determinations for many different chemical elements. Yet, the full star formation and enrichment history of a galaxy can be traced directly only if two key observables can be determined for large stellar samples: age and chemical composition. While spectroscopy is a powerful method to analyse the detailed abundances of stars, stellar ages are the missing link in the chain, since they are not a direct observable. However, spectroscopy should be able to estimate stellar masses, which for red giants directly infer ages provided their chemical composition is known. Here we establish a new empirical relation between the shape of the hydrogen line in the observed spectra of red giants and stellar mass determined from asteroseismology. The relation allows determining stellar masses and ages with an accuracy of 10-15%. The method can be used with confidence for stars in the following range of stellar parameters: 4000 < T-eff < 5000 K, 0.5 < log g < 3.5, -2.0 < [ Fe/H] < 0.3, and luminosities log L/L-Sun < 2.5. Our analysis provides observational evidence that the H-alpha spectral characteristics of red giant stars are tightly correlated with their mass and therefore their age. We also show that the method samples well all stellar populations with ages above 1 Gyr. Targeting bright giants, the method allows obtaining simultaneous age and chemical abundance information far deeper than would be possible with asteroseismology, extending the possible survey volume to remote regions of the Milky Way and even to neighbouring galaxies such as Andromeda or the Magellanic Clouds even with current instrumentation, such as the VLT and Keck facilities.
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| 3. |
- Tagliaferri, Luca, et al.
(författare)
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ENT COBRA ONTOLOGY : the covariates classification system proposed by the Head & Neck and Skin GEC-ESTRO Working Group for interdisciplinary standardized data collection in head and neck patient cohorts treated with interventional radiotherapy (brachytherapy)
- 2018
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Ingår i: Journal of Contemporary Brachytherapy. - : Termedia Publishing. - 1689-832X .- 2081-2841. ; 10:3, s. 260-266
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Forskningsöversikt (refereegranskat)abstract
- Purpose: Clinical data collecting is expensive in terms of time and human resources. Data can be collected in different ways; therefore, performing multicentric research based on previously stored data is often difficult. The primary objective of the ENT COBRA (COnsortium for BRachytherapy data Analysis) ontology is to define a specific terminological system to standardized data collection for head and neck (H&N) cancer patients treated with interventional radiotherapy.Material and methods: ENT-COBRA is a consortium for standardized data collection for H&N patients treated with interventional radiotherapy. It is linked to H&N and Skin GEC-ESTRO Working Group and includes 11 centers from 6 countries. Its ontology was firstly defined by a multicentric working group, then evaluated by the consortium followed by a multi-professional technical commission involving a mathematician, an engineer, a physician with experience in data storage, a programmer, and a software expert.Results: Two hundred and forty variables were defined on 13 input forms. There are 3 levels, each offering a specific type of analysis: 1. Registry level (epidemiology analysis); 2. Procedures level (standard oncology analysis); 3. Research level (radiomics analysis). The ontology was approved by the consortium and technical commission; an ad-hoc software architecture ("broker") remaps the data present in already existing storage systems of the various centers according to the shared terminology system. The first data sharing was successfully performed using COBRA software and the ENT COBRA Ontology, automatically collecting data directly from 3 different hospital databases (Lubeck, Navarra, and Rome) in November 2017.Conclusions: The COBRA Ontology is a good response to the multi-dimensional criticalities of data collection, retrieval, and usability. It allows to create a software for large multicentric databases with implementation of specific remapping functions wherever necessary. This approach is well-received by all involved parties, primarily because it does not change a single center's storing technologies, procedures, and habits.
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