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Driouich, Y.; Parente, M.; Tronci, E. |
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Title |
Modeling cyber-physical systems for automatic verification |
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Conference Article |
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2017 |
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14th International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design (SMACD 2017) |
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1-4 |
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cyber-physical systems;formal verification;maximum power point trackers;power engineering computing;Modelica;automatic verification;complex power electronics systems;cyber-physical systems modeling;distributed maximum power point tracking system;open standard modeling language;Computational modeling;Control systems;Integrated circuit modeling;Mathematical model;Maximum power point trackers;Object oriented modeling;Radiation effects;Automatic Formal Verification;Cyber-Physical Systems;DMPPT;Modeling;Photovoltaic systems;Simulation;System Analysis and Design |
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MCLab @ davi @ ref7981621 |
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168 |
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Pappagallo, A.; Massini, A.; Tronci, E. |
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Title |
Monte Carlo Based Statistical Model Checking of Cyber-Physical Systems: A Review |
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2020 |
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Information |
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11 |
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558 |
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MCLab @ davi @ |
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181 |
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Tortora, L.; Meynen, G.; Bijlsma, J.; Tronci, E.; Ferracuti, S. |
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Title |
Neuroprediction and A.I. in Forensic Psychiatry and Criminal Justice: A Neurolaw Perspective |
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2020 |
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Frontiers in Psychology |
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11 |
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220 |
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Advances in the use of neuroimaging in combination with A.I., and specifically the use of machine learning techniques, have led to the development of brain-reading technologies which, in the nearby future, could have many applications, such as lie detection, neuromarketing or brain-computer interfaces. Some of these could, in principle, also be used in forensic psychiatry. The application of these methods in forensic psychiatry could, for instance, be helpful to increase the accuracy of risk assessment and to identify possible interventions. This technique could be referred to as ‘A.I. neuroprediction,’ and involves identifying potential neurocognitive markers for the prediction of recidivism. However, the future implications of this technique and the role of neuroscience and A.I. in violence risk assessment remain to be established. In this paper, we review and analyze the literature concerning the use of brain-reading A.I. for neuroprediction of violence and rearrest to identify possibilities and challenges in the future use of these techniques in the fields of forensic psychiatry and criminal justice, considering legal implications and ethical issues. The analysis suggests that additional research is required on A.I. neuroprediction techniques, and there is still a great need to understand how they can be implemented in risk assessment in the field of forensic psychiatry. Besides the alluring potential of A.I. neuroprediction, we argue that its use in criminal justice and forensic psychiatry should be subjected to thorough harms/benefits analyses not only when these technologies will be fully available, but also while they are being researched and developed. |
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1664-1078 |
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MCLab @ davi @ Neuroprediction-2020 |
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180 |
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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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Title |
Computing Personalised Treatments through In Silico Clinical Trials. A Case Study on Downregulation in Assisted Reproduction |
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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.; Tronci, E.; Scialanca, A.; Lanciotti, F.; Finzi, A.; Guarneri, R.; Di Pompeo, S. |
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Title |
Optimal Fault-Tolerant Placement of Relay Nodes in a Mission Critical Wireless Network |
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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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no |
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MCLab @ davi @ |
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174 |
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Author |
Driouich, Y.; Parente, M.; Tronci, E. |
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Title |
Model Checking Cyber-Physical Energy Systems |
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2018 |
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Proceedings of 2017 International Renewable and Sustainable Energy Conference, IRSEC 2017 |
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Institute of Electrical and Electronics Engineers Inc. |
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MCLab @ davi @ Driouich2018 |
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177 |
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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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Title |
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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Driouich, Y.; Parente, M.; Tronci, E. |
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Title |
A methodology for a complete simulation of Cyber-Physical Energy Systems |
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2018 |
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EESMS 2018 – Environmental, Energy, and Structural Monitoring Systems, Proceedings |
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1-5 |
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MCLab @ davi @ Driouich20181 |
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169 |
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Author |
Tronci, Enrico |
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Introductory Paper |
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2006 |
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Sttt |
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8 |
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4-5 |
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355-358 |
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In today’s competitive market designing of digital systems (hardware as well as software) faces tremendous challenges. In fact, notwithstanding an ever decreasing project budget, time to market and product lifetime, designers are faced with an ever increasing system complexity and customer expected quality. The above situation calls for better and better formal verification techniques at all steps of the design flow. This special issue is devoted to publishing revised versions of contributions first presented at the 12th Advanced Research Working Conference on Correct Hardware Design and Verification Methods (CHARME) held 21–24 October 2003 in L’Aquila, Italy. Authors of well regarded papers from CHARME’03 were invited to submit to this special issue. All papers included here have been suitably extended and have undergone an independent round of reviewing. |
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Sapienza @ mari @ sttt06 |
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30 |
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Della Penna, Giuseppe; Magazzeni, Daniele; Tofani, Alberto; Intrigila, Benedetto; Melatti, Igor; Tronci, Enrico |
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Automated Generation Of Optimal Controllers Through Model Checking Techniques |
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2008 |
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Informatics in Control Automation and Robotics. Selected Papers from ICINCO 2006 |
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107-119 |
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Springer |
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Sapienza @ mari @ Dmtmt08 |
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26 |
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