| Records |
| Author |
Ehrig, R.; Dierkes, T.; Schaefer, S.; Roeblitz, S.; Tronci, E.; Mancini, T.; Salvo, I.; Alimguzhin, V.; Mari, F.; Melatti, I.; Massini, A.; Leeners, B.; Krueger, T.H.C.; Egli, M.; Ille, F. |
| Title |
An integrative approach for model driven computation of treatments in reproductive medicine |
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Conference Article |
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2015 |
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Proceedings of the 15th International Symposium on Mathematical and Computational Biology (BIOMAT 2015), Rorkee, India |
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Sapienza @ preissler @ Ehrig_etal2015 |
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144 |
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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. |
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A Glimpse of SmartHG Project Test-bed and Communication Infrastructure |
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Conference Article |
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2015 |
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Digital System Design (DSD), 2015 Euromicro Conference on |
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225-232 |
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Batteries; Control systems; Databases; Production; Sensors; Servers; Smart grids; Grid State Estimation; Peak Shaving; Policy Robustness Verification; Price Policy Synthesis |
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Sapienza @ preissler @ Alimguzhin_etal2015 |
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127 |
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Mancini, Toni; Mari, Federico; Massini, Annalisa; Melatti, Igor; Tronci, Enrico |
| Title |
Simulator Semantics for System Level Formal Verification |
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Conference Article |
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2015 |
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Proceedings Sixth International Symposium on Games, Automata, Logics and Formal Verification (GandALF 2015), |
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MCLab @ davi @ |
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125 |
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Toni Mancini; Enrico Tronci; Ivano Salvo; Federico Mari; Annalisa Massini; Igor Melatti |
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Computing Biological Model Parameters by Parallel Statistical Model Checking |
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Journal Article |
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2015 |
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International Work Conference on Bioinformatics and Biomedical Engineering (IWBBIO 2015) |
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9044 |
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542-554 |
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MCLab @ davi @ |
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124 |
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Mancini, T.; Mari, F.; Massini, A.; Melatti, I.; Tronci, E. |
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SyLVaaS: System Level Formal Verification as a Service |
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Journal Article |
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2016 |
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Fundamenta Informaticae |
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149 |
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1-2 |
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101-132 |
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MCLab @ davi @ DBLP:journals/fuin/ManciniMMMT16 |
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160 |
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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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1-6 |
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MCLab @ davi @ mancini-etal:2018:smartgridcomm |
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170 |
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Mancini, T.; Mari, F.; Massini, A.; Melatti, I.; Salvo, I.; Sinisi, S.; Tronci, E.; Ehrig, R.; Röblitz, S.; Leeners, B. |
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Computing Personalised Treatments through In Silico Clinical Trials. A Case Study on Downregulation in Assisted Reproduction |
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Conference Article |
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2018 |
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25th RCRA International Workshop on “Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion” (RCRA 2018) |
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MCLab @ davi @ |
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175 |
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Mancini, T.; Mari, F.; Massini, A.; Melatti, I.; Tronci, E. |
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Anytime system level verification via parallel random exhaustive hardware in the loop simulation |
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Journal Article |
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2016 |
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Microprocessors and Microsystems |
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41 |
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12-28 |
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Model Checking of Hybrid Systems; Model checking driven simulation; Hardware in the loop simulation |
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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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0141-9331 |
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MCLab @ davi @ Mancini201612 |
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155 |
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Della Penna, Giuseppe; Intrigila, Benedetto; Melatti, Igor; Minichino, Michele; Ciancamerla, Ester; Parisse, Andrea; Tronci, Enrico; Venturini Zilli, Marisa |
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Automatic Verification of a Turbogas Control System with the Mur$\varphi$ Verifier |
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Conference Article |
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2003 |
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Hybrid Systems: Computation and Control, 6th International Workshop, HSCC 2003 Prague, Czech Republic, April 3-5, 2003, Proceedings |
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141-155 |
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Automatic analysis of Hybrid Systems poses formidable challenges both from a modeling as well as from a verification point of view. We present a case study on automatic verification of a Turbogas Control System (TCS) using an extended version of the Mur$\varphi$ verifier. TCS is the heart of ICARO, a 2MW Co-generative Electric Power Plant. For large hybrid systems, as TCS is, the modeling effort accounts for a significant part of the whole verification activity. In order to ease our modeling effort we extended the Mur$\varphi$ verifier by importing the C language long double type (finite precision real numbers) into it. We give experimental results on running our extended Mur$\varphi$ on our TCS model. For example using Mur$\varphi$ we were able to compute an admissible range of values for the variation speed of the user demand of electric power to the turbogas. |
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Springer |
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Maler, O.; Pnueli, A. |
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Lecture Notes in Computer Science |
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2623 |
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3-540-00913-2 |
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yes |
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Sapienza @ mari @ Dimmcptz03 |
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88 |
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Sinisi, S.; Alimguzhin, V.; Mancini, T.; Tronci, E.; Mari, F.; Leeners, B. |
| Title |
Optimal Personalised Treatment Computation through In Silico Clinical Trials on Patient Digital Twins |
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Journal Article |
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2020 |
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Fundamenta Informaticae |
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174 |
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283-310 |
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Artificial Intelligence; Virtual Physiological Human; In Silico Clinical Trials; Simulation; Personalised Medicine; In Silico Treatment Optimisation |
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In Silico Clinical Trials (ISCT), i.e. clinical experimental campaigns carried out by means of computer simulations, hold the promise to decrease time and cost for the safety and efficacy assessment of pharmacological treatments, reduce the need for animal and human testing, and enable precision medicine. In this paper we present methods and an algorithm that, by means of extensive computer simulation-based experimental campaigns (ISCT) guided by intelligent search, optimise a pharmacological treatment for an individual patient (precision medicine ). We show the effectiveness of our approach on a case study involving a real pharmacological treatment, namely the downregulation phase of a complex clinical protocol for assisted reproduction in humans. |
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IOS Press |
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1875-8681 |
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MCLab @ davi @ |
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187 |
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