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Mancini, T.; Mari, F.; Melatti, I.; Salvo, I.; Tronci, E.; Gruber, J.; Hayes, B.; Prodanovic, M.; Elmegaard, L. |
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Parallel Statistical Model Checking for Safety Verification in Smart Grids |
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2018 |
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2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) |
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MCLab @ davi @ mancini-etal:2018:smartgridcomm |
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170 |
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Sinisi, S.; Alimguzhin, V.; Mancini, T.; Tronci, E.; Leeners, B. |
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Complete populations of virtual patients for in silico clinical trials |
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2021 |
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Bioinformatics |
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1-8 |
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Model-based approaches to safety and efficacy assessment of pharmacological drugs, treatment strategies, or medical devices (In Silico Clinical Trial, ISCT) aim to decrease time and cost for the needed experimentations, reduce animal and human testing, and enable precision medicine. Unfortunately, in presence of non-identifiable models (e.g., reaction networks), parameter estimation is not enough to generate complete populations of Virtual Patient (VPs), i.e., populations guaranteed to show the entire spectrum of model behaviours (phenotypes), thus ensuring representativeness of the trial.We present methods and software based on global search driven by statistical model checking that, starting from a (non-identifiable) quantitative model of the human physiology (plus drugs PK/PD) and suitable biological and medical knowledge elicited from experts, compute a population of VPs whose behaviours are representative of the whole spectrum of phenotypes entailed by the model (completeness) and pairwise distinguishable according to user-provided criteria. This enables full granularity control on the size of the population to employ in an ISCT, guaranteeing representativeness while avoiding over-representation of behaviours.We proved the effectiveness of our algorithm on a non-identifiable ODE-based model of the female Hypothalamic-Pituitary-Gonadal axis, by generating a population of 4 830 264 VPs stratified into 7 levels (at different granularity of behaviours), and assessed its representativeness against 86 retrospective health records from Pfizer, Hannover Medical School and University Hospital of Lausanne. The datasets are respectively covered by our VPs within Average Normalised Mean Absolute Error of 15%, 20%, and 35% (90% of the latter dataset is covered within 20% error). |
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1367-4803 |
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MCLab @ davi @ ref10.1093/bioinformatics/btaa1026 |
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182 |
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Melatti, I.; Mari, F.; Mancini, T.; Prodanovic, M.; Tronci, E. |
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A Two-Layer Near-Optimal Strategy for Substation Constraint Management via Home Batteries |
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2021 |
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IEEE Transactions on Industrial Electronics |
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Within electrical distribution networks, substation constraints management requires that aggregated power demand from residential users is kept within suitable bounds. Efficiency of substation constraints management can be measured as the reduction of constraints violations w.r.t. unmanaged demand. Home batteries hold the promise of enabling efficient and user-oblivious substation constraints management. Centralized control of home batteries would achieve optimal efficiency. However, it is hardly acceptable by users, since service providers (e.g., utilities or aggregators) would directly control batteries at user premises. Unfortunately, devising efficient hierarchical control strategies, thus overcoming the above problem, is far from easy. We present a novel two-layer control strategy for home batteries that avoids direct control of home devices by the service provider and at the same time yields near-optimal substation constraints management efficiency. Our simulation results on field data from 62 households in Denmark show that the substation constraints management efficiency achieved with our approach is at least 82% of the one obtained with a theoretical optimal centralized strategy. |
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MCLab @ davi @ ref9513535 |
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190 |
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Mancini, T.; Melatti, I.; Tronci, E. |
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Any-horizon uniform random sampling and enumeration of constrained scenarios for simulation-based formal verification |
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2021 |
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IEEE Transactions on Software Engineering |
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1-1 |
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Model-based approaches to the verification of non-terminating Cyber-Physical Systems (CPSs) usually rely on numerical simulation of the System Under Verification (SUV) model under input scenarios of possibly varying duration, chosen among those satisfying given constraints. Such constraints typically stem from requirements (or assumptions) on the SUV inputs and its operational environment as well as from the enforcement of additional conditions aiming at, e.g., prioritising the (often extremely long) verification activity, by, e.g., focusing on scenarios explicitly exercising selected requirements, or avoiding </i>vacuity</i> in their satisfaction. In this setting, the possibility to efficiently sample at random (with a known distribution, e.g., uniformly) within, or to efficiently enumerate (possibly in a uniformly random order) scenarios among those satisfying all the given constraints is a key enabler for the practical viability of the verification process, e.g., via simulation-based statistical model checking. Unfortunately, in case of non-trivial combinations of constraints, iterative approaches like Markovian random walks in the space of sequences of inputs in general fail in extracting scenarios according to a given distribution (e.g., uniformly), and can be very inefficient to produce at all scenarios that are both legal (with respect to SUV assumptions) and of interest (with respect to the additional constraints). For example, in our case studies, up to 91% of the scenarios generated using such iterative approaches would need to be neglected. In this article, we show how, given a set of constraints on the input scenarios succinctly defined by multiple finite memory monitors, a data structure (scenario generator) can be synthesised, from which any-horizon scenarios satisfying the input constraints can be efficiently extracted by (possibly uniform) random sampling or (randomised) enumeration. Our approach enables seamless support to virtually all simulation-based approaches to CPS verification, ranging from simple random testing to statistical model checking and formal (i.e., exhaustive) verification, when a suitable bound on the horizon or an iterative horizon enlargement strategy is defined, as in the spirit of bounded model checking. |
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1939-3520 |
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To appear |
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MCLab @ davi @ ref9527998 |
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191 |
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Bartolini, Novella; Tronci, Enrico |
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On Optimizing Service Availability of an Internet Based Architecture for Infrastructure Protection |
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2006 |
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Cnip |
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yes |
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Sapienza @ mari @ Bt06 |
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28 |
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Cecconi, Michele; Tronci, Enrico |
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Requirements Formalization and Validation for a Telecommunication Equipment Protection Switcher |
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2000 |
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IEEE Computer Society |
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0-7695-0927-4 |
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Sapienza @ mari @ CeTro00 |
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29 |
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Cesta, Amedeo; Finzi, Alberto; Fratini, Simone; Orlandini, Andrea; Tronci, Enrico |
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Merging Planning, Scheduling & Verification – A Preliminary Analysis |
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2008 |
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In Proc. of 10th ESA Workshop on Advanced Space Technologies for Robotics and Automation (ASTRA) |
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Sapienza @ mari @ Astra08 |
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24 |
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Cesta, Amedeo; Finzi, Alberto; Fratini, Simone; Orlandini, Andrea; Tronci, Enrico |
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Validation and Verification Issues in a Timeline-based Planning System |
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2008 |
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In E-Proc. of ICAPS Workshop on Knowledge Engineering for Planning and Scheduling |
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One of the key points to take into account to foster effective introduction of AI planning and scheduling systems in real world is to develop end user trust in the related technologies. Automated planning and scheduling systems often brings solutions to the users which are neither “obvious†nor immediately acceptable for them. This is due to the ability of these tools to take into account quite an amount of temporal and causal constraints and to employ resolution processes often designed to optimize the solution with respect to non trivial evaluation functions. To increase technology trust, the study of tools for verifying and validating plans and schedules produced by AI systems might be instrumental. In general, validation and verification techniques represent a needed complementary technology in developing domain independent architectures for automated problem solving. This paper presents a preliminary report of the issues concerned with the use of two software tools for formal verification of finite state systems to the validation of the solutions produced by MrSPOCK, a recent effort for building a timeline based planning tool in an ESA project. |
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Sapienza @ mari @ Keps08 |
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25 |
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Cavaliere, Federico; Mari, Federico; Melatti, Igor; Minei, Giovanni; Salvo, Ivano; Tronci, Enrico; Verzino, Giovanni; Yushtein, Yuri |
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Model Checking Satellite Operational Procedures |
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2011 |
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DAta Systems In Aerospace (DASIA), Org. EuroSpace, Canadian Space Agency, CNES, ESA, EUMETSAT. San Anton, Malta, EuroSpace. |
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We present a model checking approach for the automatic verification of satellite operational procedures (OPs). Building a model for a complex system as a satellite is a hard task. We overcome this obstruction by using a suitable simulator (SIMSAT) for the satellite. Our approach aims at improving OP quality assurance by automatic exhaustive exploration of all possible simulation scenarios. Moreover, our solution decreases OP verification costs by using a model checker (CMurphi) to automatically drive the simulator. We model OPs as user-executed programs observing the simulator telemetries and sending telecommands to the simulator. In order to assess feasibility of our approach we present experimental results on a simple meaningful scenario. Our results show that we can save up to 90% of verification time. |
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Sapienza @ mari @ Dasia11 |
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13 |
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Mazzini, Silvia; Puri, Stefano; Mari, Federico; Melatti, Igor; Tronci, Enrico |
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Formal Verification at System Level |
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2009 |
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In: DAta Systems In Aerospace (DASIA), Org. EuroSpace, Canadian Space Agency, CNES, ESA, EUMETSAT. Instanbul, Turkey, EuroSpace |
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System Level Analysis calls for a language comprehensible to experts with different background and yet precise enough to support meaningful analyses. SysML is emerging as an effective balance between such conflicting goals. In this paper we outline some the results obtained as for SysML based system level functional formal verification by an ESA/ESTEC study, with a collaboration among INTECS and La Sapienza University of Roma. The study focuses on SysML based system level functional requirements techniques. |
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Sapienza @ mari @ Dasia09 |
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