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	Author	Sinisi, S.; Alimguzhin, V.; Mancini, T.; Tronci, E.; Leeners, B.
	Title	Complete populations of virtual patients for in silico clinical trials			Type	Journal Article
	Year	2021	Publication	Bioinformatics	Abbreviated Journal
	Volume		Issue		Pages	1-8
	Keywords
	Abstract	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).
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	1367-4803	ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	MCLab @ davi @ ref10.1093/bioinformatics/btaa1026			Serial	182
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	Author	Melatti, I.; Mari, F.; Mancini, T.; Prodanovic, M.; Tronci, E.
	Title	A Two-Layer Near-Optimal Strategy for Substation Constraint Management via Home Batteries			Type	Journal Article
	Year	2021	Publication	IEEE Transactions on Industrial Electronics	Abbreviated Journal
	Volume		Issue		Pages	1-1
	Keywords
	Abstract	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.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	To appear			Approved	no
	Call Number	MCLab @ davi @ ref9513535			Serial	190
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	Author	Mancini, T.; Melatti, I.; Tronci, E.
	Title	Any-horizon uniform random sampling and enumeration of constrained scenarios for simulation-based formal verification			Type	Journal Article
	Year	2021	Publication	IEEE Transactions on Software Engineering	Abbreviated Journal
	Volume		Issue		Pages	1-1
	Keywords
	Abstract	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.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	1939-3520	ISBN		Medium
	Area		Expedition		Conference
	Notes	To appear			Approved	no
	Call Number	MCLab @ davi @ ref9527998			Serial	191
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	Author	Della Penna, Giuseppe; Magazzeni, Daniele; Tofani, Alberto; Intrigila, Benedetto; Melatti, Igor; Tronci, Enrico
	Title	Automatic Synthesis of Robust Numerical Controllers			Type	Conference Article
	Year	2007	Publication	Icas '07	Abbreviated Journal
	Volume		Issue		Pages	4
	Keywords
	Abstract	A major problem of numerical controllers is their robustness, i.e. the state read from the plant may not be in the controller table, although it may be close to some states in the table. For continuous systems, this problem is typically handled by interpolation techniques. Unfortunately, when the plant contains both continuous and discrete variables, the interpolation approach does not work well. To cope with this kind of systems, we propose a general methodology that exploits explicit model checking in an innovative way to automatically synthesize a (time-) optimal numerical controller from a plant specification and apply an optimized strengthening algorithm only on the most significant states, in order to reach an acceptable robustness degree. We implemented all the algorithms within our CGMurphi tool, an extension of the well-known CMurphi verifier, and tested the effectiveness of our approach by applying it to the well-known truck and trailer obstacles avoidance problem.
	Address
	Corporate Author				Thesis
	Publisher	IEEE Computer Society	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0-7695-2859-5	ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	yes
	Call Number	Sapienza @ mari @ Dmtimt07			Serial	89
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	Author	Mari, Federico; Melatti, Igor; Salvo, Ivano; Tronci, Enrico
	Title	Model Based Synthesis of Control Software from System Level Formal Specifications			Type	Journal Article
	Year	2014	Publication	ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY	Abbreviated Journal	ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY
	Volume	23	Issue	1	Pages	Article 6
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher	ACM	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	1049-331X	ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	Sapienza @ melatti @			Serial	110
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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.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0141-9331	ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	MCLab @ davi @ Mancini201612			Serial	155
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	Author	Della Penna, Giuseppe; Intrigila, Benedetto; Magazzeni, Daniele; Melatti, Igor; Tronci, Enrico
	Title	CGMurphi: Automatic synthesis of numerical controllers for nonlinear hybrid systems			Type	Journal Article
	Year	2013	Publication	European Journal of Control	Abbreviated Journal	European Journal of Control
	Volume	19	Issue	1	Pages	14-36
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher	Elsevier North-Holland, Inc.	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0947-3580	ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	Sapienza @ melatti @			Serial	114
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	Author	Mari, Federico; Melatti, Igor; Salvo, Ivano; Tronci, Enrico
	Title	Control Software Visualization			Type	Conference Article
	Year	2012	Publication	Proceedings of INFOCOMP 2012, The Second International Conference on Advanced Communications and Computation	Abbreviated Journal
	Volume		Issue		Pages	15-20
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher	ThinkMind	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-61208-226-4	ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	yes
	Call Number	Sapienza @ mari @ infocomp2012			Serial	100
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	Author	Hengartner, M. P.; Kruger, T. H. C.; Geraedts, K.; Tronci, E.; Mancini, T.; Ille, F.; Egli, M.; RÃ¶blitz, 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
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	no
	Call Number	MCLab @ davi @			Serial	165
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	Author	Della Penna, Giuseppe; Magazzeni, Daniele; Tofani, Alberto; Intrigila, Benedetto; Melatti, Igor; Tronci, Enrico
	Title	Automated Generation of Optimal Controllers through Model Checking Techniques			Type	Conference Article
	Year	2006	Publication	Icinco-Icso	Abbreviated Journal
	Volume		Issue		Pages	26-33
	Keywords
	Abstract	We present a methodology for the synthesis of controllers, which exploits (explicit) model checking techniques. That is, we can cope with the systematic exploration of a very large state space. This methodology can be applied to systems where other approaches fail. In particular, we can consider systems with an highly non-linear dynamics and lacking a uniform mathematical description (model). We can also consider situations where the required control action cannot be specified as a local action, and rather a kind of planning is required. Our methodology individuates first a raw optimal controller, then extends it to obtain a more robust one. A case study is presented which considers the well known truck-trailer obstacle avoidance parking problem, in a parking lot with obstacles on it. The complex non-linear dynamics of the truck-trailer system, within the presence of obstacles, makes the parking problem extremely hard. We show how, by our methodology, we can obtain optimal controllers with different degrees of robustness.
	Address
	Corporate Author				Thesis
	Publisher	INSTICC Press	Place of Publication		Editor	Andrade-Cetto, J.; Ferrier, J.-L.; Pereira, J. M. C. D.; Filipe, J.
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	972-8865-59-7	ISBN		Medium
	Area		Expedition		Conference
	Notes				Approved	yes
	Call Number	Sapienza @ mari @ Dimmtt06			Serial	79
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