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Author Alimguzhin, V.; Mari, F.; Melatti, I.; Tronci, E.; Ebeid, E.; Mikkelsen, S.A.; Jacobsen, R.H.; Gruber, J.K.; Hayes, B.; Huerta, F.; Prodanovic, M.
Title A Glimpse of SmartHG Project Test-bed and Communication Infrastructure Type Conference Article
Year 2015 Publication Digital System Design (DSD), 2015 Euromicro Conference on Abbreviated Journal
Volume Issue Pages 225-232
Keywords Batteries; Control systems; Databases; Production; Sensors; Servers; Smart grids; Grid State Estimation; Peak Shaving; Policy Robustness Verification; Price Policy Synthesis
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Call Number Sapienza @ preissler @ Alimguzhin_etal2015 Serial 127
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Author Mancini, T.; Mari, F.; Massini, A.; Melatti, I.; Tronci, E.
Title Anytime system level verification via parallel random exhaustive hardware in the loop simulation Type Journal Article
Year 2016 Publication Microprocessors and Microsystems Abbreviated Journal
Volume 41 Issue Pages 12-28
Keywords Model Checking of Hybrid Systems; Model checking driven simulation; Hardware in the loop simulation
Abstract Abstract System level verification of cyber-physical systems has the goal of verifying that the whole (i.e., software + hardware) system meets the given specifications. Model checkers for hybrid systems cannot handle system level verification of actual systems. Thus, Hardware In the Loop Simulation (HILS) is currently the main workhorse for system level verification. By using model checking driven exhaustive HILS, System Level Formal Verification (SLFV) can be effectively carried out for actual systems. We present a parallel random exhaustive HILS based model checker for hybrid systems that, by simulating all operational scenarios exactly once in a uniform random order, is able to provide, at any time during the verification process, an upper bound to the probability that the System Under Verification exhibits an error in a yet-to-be-simulated scenario (Omission Probability). We show effectiveness of the proposed approach by presenting experimental results on SLFV of the Inverted Pendulum on a Cart and the Fuel Control System examples in the Simulink distribution. To the best of our knowledge, no previously published model checker can exhaustively verify hybrid systems of such a size and provide at any time an upper bound to the Omission Probability.
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ISSN 0141-9331 ISBN Medium
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Call Number MCLab @ davi @ Mancini201612 Serial 155
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Author Mancini, T.
Title Now or Never: negotiating efficiently with unknown counterparts Type Journal Article
Year 2015 Publication In proceedings of the 22nd RCRA International Workshop. Ferrara, Italy. CEUR, 2015 (Co-located with the 14th Conference of the Italian Association for Artificial Intelligence (AI*IA 2015)). Abbreviated Journal
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Call Number Sapienza @ preissler @ Mancini2015 Serial 131
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Author Mancini, T.; Mari, F.; Melatti, I.; Salvo, I.; Tronci, E.
Title An Efficient Algorithm for Network Vulnerability Analysis Under Malicious Attacks Type Conference Article
Year 2018 Publication Foundations of Intelligent Systems – 24th International Symposium, ISMIS 2018, Limassol, Cyprus, October 29-31, 2018, Proceedings Abbreviated Journal
Volume Issue Pages 302-312
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Call Number MCLab @ davi @ DBLP:conf/ismis/ManciniMMST18 Serial 176
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Author Mancini, T.; Mari, F.; Melatti, I.; Salvo, I.; Tronci, E.; Gruber, J.K.; Hayes, B.; Prodanovic, M.; Elmegaard, L.
Title User Flexibility Aware Price Policy Synthesis for Smart Grids Type Conference Article
Year 2015 Publication Digital System Design (DSD), 2015 Euromicro Conference on Abbreviated Journal
Volume Issue Pages 478-485
Keywords Contracts; Current measurement; Load management; Power demand; Power measurement; State estimation; Substations; Grid State Estimation; Peak Shaving; Policy Robustness Verification; Price Policy Synthesis
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Call Number Sapienza @ preissler @ Mancini_etal2015_3 Serial 136
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Author Leeners, B.; Kruger, T.H.C.; Geraedts, K.; Tronci, E.; Mancini, T.; Ille, F.; Egli, M.; Röblitz, S.; Saleh, L.; Spanaus, K.; Schippert, C.; Zhang, Y.; Hengartner, M.P.
Title Lack of Associations between Female Hormone Levels and Visuospatial Working Memory, Divided Attention and Cognitive Bias across Two Consecutive Menstrual Cycles Type Journal Article
Year 2017 Publication Frontiers in Behavioral Neuroscience Abbreviated Journal
Volume 11 Issue Pages 120
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Abstract Background: Interpretation of observational studies on associations between prefrontal cognitive functioning and hormone levels across the female menstrual cycle is complicated due to small sample sizes and poor replicability. Methods: This observational multisite study comprised data of n=88 menstruating women from Hannover, Germany, and Zurich, Switzerland, assessed during a first cycle and n=68 re-assessed during a second cycle to rule out practice effects and false-positive chance findings. We assessed visuospatial working memory, attention, cognitive bias and hormone levels at four consecutive time-points across both cycles. In addition to inter-individual differences we examined intra-individual change over time (i.e., within-subject effects). Results: Oestrogen, progesterone and testosterone did not relate to inter-individual differences in cognitive functioning. There was a significant negative association between intra-individual change in progesterone and change in working memory from pre-ovulatory to mid-luteal phase during the first cycle, but that association did not replicate in the second cycle. Intra-individual change in testosterone related negatively to change in cognitive bias from menstrual to pre-ovulatory as well as from pre-ovulatory to mid-luteal phase in the first cycle, but these associations did not replicate in the second cycle. Conclusions: There is no consistent association between women's hormone levels, in particular oestrogen and progesterone, and attention, working memory and cognitive bias. That is, anecdotal findings observed during the first cycle did not replicate in the second cycle, suggesting that these are false-positives attributable to random variation and systematic biases such as practice effects. Due to methodological limitations, positive findings in the published literature must be interpreted with reservation.
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ISSN 1662-5153 ISBN Medium
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Call Number Sapienza @ mari @ ref10.3389/fnbeh.2017.00120 Serial 167
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Author Mancini, T. ; Mari, F.; Massini, A.; Melatti, I.; Salvo, I.; Tronci, E.
Title On minimising the maximum expected verification time Type Journal Article
Year 2017 Publication Information Processing Letters Abbreviated Journal
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Call Number Sapienza @ mari @ Serial 163
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Author Hengartner, M. P.; Kruger, T. H. C.; Geraedts, K.; Tronci, E.; Mancini, T.; Ille, F.; Egli, M.; Röblitz, S.; Ehrig, R.; Saleh, L.; Spanaus, K.; Schippert, C.; Zhang, Y.; Leeners, B.
Title Negative affect is unrelated to fluctuations in hormone levels across the menstrual cycle: Evidence from a multisite observational study across two successive cycles Type Journal Article
Year 2017 Publication Journal of Psychosomatic Research Abbreviated Journal
Volume 99 Issue Pages 21-27
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Call Number MCLab @ davi @ Serial 165
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Author Mancini, T.; Massini, A.; Tronci, E.
Title Parallelization of Cycle-Based Logic Simulation Type Journal Article
Year 2017 Publication Parallel Processing Letters Abbreviated Journal
Volume 27 Issue 02 Pages
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Call Number MCLab @ davi @ Serial 166
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Author Maggioli, F.; Mancini, T.; Tronci, E.
Title SBML2Modelica: Integrating biochemical models within open-standard simulation ecosystems Type Journal Article
Year 2019 Publication Bioinformatics Abbreviated Journal
Volume 36 Issue 7 Pages 2165â2172
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Abstract SBML is the most widespread language for the definition of biochemical models. Although dozens of SBML simulators are available, there is a general lack of support to the integration of SBML models within open-standard general-purpose simulation ecosystems. This hinders co-simulation and integration of SBML models within larger model networks, in order to, e.g., enable in-silico clinical trials of drugs, pharmacological protocols, or engineering artefacts such as biomedical devices against Virtual Physiological Human models.Modelica is one of the most popular existing open-standard general-purpose simulation languages, supported by many simulators. Modelica models are especially suited for the definition of complex networks of heterogeneous models from virtually all application domains. Models written in Modelica (and in 100+ other languages) can be readily exported into black-box Functional Mock-Up Units (FMUs), and seamlessly co-simulated and integrated into larger model networks within open-standard language-independent simulation ecosystems.In order to enable SBML model integration within heterogeneous model networks, we present SBML2Modelica, a software system translating SBML models into well-structured, user-intelligible, easily modifiable Modelica models. SBML2Modelica is SBML Level 3 Version 2 -compliant and succeeds on 96.47% of the SBML Test Suite Core (with a few rare, intricate, and easily avoidable combinations of constructs unsupported and cleanly signalled to the user). Our experimental campaign on 613 models from the BioModels database (with up to 5438 variables) shows that the major open-source (general-purpose) Modelica and FMU simulators achieve performance comparable to state-of-the-art specialised SBML simulators.SBML2Modelica is written in Java and is freely available for non-commercial use at https://bitbucket.org/mclab/sbml2modelica
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ISSN 1367-4803 ISBN Medium
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Call Number MCLab @ davi @ ref10.1093/bioinformatics/btz860 Serial 179
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