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Author Tronci, Enrico
Title Optimal Finite State Supervisory Control Type Conference Article
Year 1996 Publication (up) CDC '96: Proceedings of the 35th IEEE International Conference on Decision and Control Abbreviated Journal
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Abstract Supervisory Controllers are Discrete Event Dynamic Systems (DEDSs) forming the discrete core of a Hybrid Control System. We address the problem of automatic synthesis of Optimal Finite State Supervisory Controllers (OSCs). We show that Boolean First Order Logic (BFOL) and Binary Decision Diagrams (BDDs) are an effective methodological and practical framework for Optimal Finite State Supervisory Control. Using BFOL programs (i.e. systems of boolean functional equations) and BDDs we give a symbolic (i.e. BDD based) algorithm for automatic synthesis of OSCs. Our OSC synthesis algorithm can handle arbitrary sets of final states as well as plant transition relations containing loops and uncontrollable events (e.g. failures). We report on experimental results on the use of our OSC synthesis algorithm to synthesize a C program implementing a minimum fuel OSC for two autonomous vehicles moving on a 4 x 4 grid.
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Publisher IEEE Computer Society Place of Publication Washington, DC, USA Editor
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Notes Approved yes
Call Number Sapienza @ mari @ cdc96 Serial 67
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Author Driouich, Y.; Parente, M.; Tronci, E.
Title A methodology for a complete simulation of Cyber-Physical Energy Systems Type Conference Article
Year 2018 Publication (up) EESMS 2018 – Environmental, Energy, and Structural Monitoring Systems, Proceedings Abbreviated Journal
Volume Issue Pages 1-5
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Notes Approved no
Call Number MCLab @ davi @ Driouich20181 Serial 169
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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 (up) 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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Notes Best Paper Approved no
Call Number MCLab @ davi @ DBLP:conf/ismis/ManciniMMST18 Serial 176
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Author Fischer, S.; Ehrig, R.; Schaefer, S.; Tronci, E.; Mancini, T.; Egli, M.; Ille, F.; Krueger, T.H.C.; Leeners, B.; Roeblitz, S.
Title Mathematical Modeling and Simulation Provides Evidence for New Strategies of Ovarian Stimulation Type Journal Article
Year 2021 Publication (up) Frontiers in Endocrinology Abbreviated Journal
Volume 12 Issue Pages 117
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Abstract New approaches to ovarian stimulation protocols, such as luteal start, random start or double stimulation, allow for flexibility in ovarian stimulation at different phases of the menstrual cycle. It has been proposed that the success of these methods is based on the continuous growth of multiple cohorts (“waves”) of follicles throughout the menstrual cycle which leads to the availability of ovarian follicles for ovarian controlled stimulation at several time points. Though several preliminary studies have been published, their scientific evidence has not been considered as being strong enough to integrate these results into routine clinical practice. This work aims at adding further scientific evidence about the efficiency of variable-start protocols and underpinning the theory of follicular waves by using mathematical modeling and numerical simulations. For this purpose, we have modified and coupled two previously published models, one describing the time course of hormones and one describing competitive follicular growth in a normal menstrual cycle. The coupled model is used to test ovarian stimulation protocols in silico. Simulation results show the occurrence of follicles in a wave-like manner during a normal menstrual cycle and qualitatively predict the outcome of ovarian stimulation initiated at different time points of the menstrual cycle.
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ISSN 1664-2392 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number MCLab @ davi @ ref10.3389/fendo.2021.613048 Serial 189
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Author Tortora, L.; Meynen, G.; Bijlsma, J.; Tronci, E.; Ferracuti, S.
Title Neuroprediction and A.I. in Forensic Psychiatry and Criminal Justice: A Neurolaw Perspective Type Journal Article
Year 2020 Publication (up) Frontiers in Psychology Abbreviated Journal
Volume 11 Issue Pages 220
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Abstract 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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ISSN 1664-1078 ISBN Medium
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Notes Approved no
Call Number MCLab @ davi @ Neuroprediction-2020 Serial 180
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Author Leeners, B.; Krueger, T.H.C.; Geraedts, K.; Tronci, E.; Mancini, T.; Egli, M.; Roeblitz, S.; Saleh, L.; Spanaus, K.; Schippert, C.; Zhang, Y.; Ille, F.
Title Associations Between Natural Physiological and Supraphysiological Estradiol Levels and Stress Perception Type Journal Article
Year 2019 Publication (up) Frontiers in Psychology Abbreviated Journal
Volume 10 Issue Pages 1296
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Abstract Stress is a risk factor for impaired general, mental and reproductive health. The role of physiological and supraphysiological estradiol concentrations in stress perception and stress processing is less well understood. We therefore, conducted a prospective observational study to investigate the association between estradiol, stress perception and stress-related cognitive performance within serial measurements either during the natural menstrual cycle or during fertility treatment, where estradiol levels are strongly above the physiological level of a natural cycle and consequently, represent a good model to study dose-dependent effects of estradiol. Data from 44 women receiving in vitro fertilization at the Department of Reproductive Endocrinology in Zurich, Switzerland was compared to data from 88 women with measurements during their natural menstrual cycle. The german version of the Perceived Stress Questionnaire (PSQ) and the Cognitive Bias Test (CBT), in which cognitive performance is tested under time stress were used to evaluate subjective and functional aspects of stress. Estradiol levels were investigated at four different time points during the menstrual cycle and at two different time points during a fertility treatment. Cycle phase were associated with PSQ worry and cognitive bias in normally cycling women, but different phases of fertility treatment were not associated with subjectively perceived stress and stress-related cognitive bias. PSQ lack of joy and PSQ demands related to CBT in women receiving fertility treatment but not in women with a normal menstrual cycle. Only strong changes of the estradiol level during fertility treatment were weakly associated with CBT, but not with subjectively experienced stress. Our research emphasises the multidimensional character of stress and the necessity to adjust stress research to the complex nature of stress perception and processing. Infertility is associated with an increased psychological burden in patients. However, not all phases of the process to overcome infertility do significantly increase patient stress levels. Also, research on the psychological burden of infertility should consider that stress may vary during the different phases of fertility treatment.
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1664-1078 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number MCLab @ davi @ ref10.3389/fpsyg.2019.01296 Serial 178
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Author Cesta, Amedeo; Fratini, Simone; Orlandini, Andrea; Finzi, Alberto; Tronci, Enrico
Title Flexible Plan Verification: Feasibility Results Type Journal Article
Year 2011 Publication (up) Fundamenta Informaticae Abbreviated Journal
Volume 107 Issue 2 Pages 111-137
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Notes Approved yes
Call Number Sapienza @ mari @ fi11 Serial 15
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Author Leeners, B.; Krueger, T.; Geraedts, K.; Tronci, E.; Mancini, T.; Ille, F.; Egli, M.; Roeblitz, S.; Wunder, D.; Saleh, L.; Schippert, C.; Hengartner, M.P.
Title Cognitive function in association with high estradiol levels resulting from fertility treatment Type Journal Article
Year 2021 Publication (up) Hormones and Behavior Abbreviated Journal
Volume 130 Issue Pages 104951
Keywords Cognition, Estrogen, Estradiol, Fertility treatment, Attention, Cognitive bias
Abstract The putative association between hormones and cognitive performance is controversial. While there is evidence that estradiol plays a neuroprotective role, hormone treatment has not been shown to improve cognitive performance. Current research is flawed by the evaluation of combined hormonal effects throughout the menstrual cycle or in the menopausal transition. The stimulation phase of a fertility treatment offers a unique model to study the effect of estradiol on cognitive function. This quasi-experimental observational study is based on data from 44 women receiving IVF in Zurich, Switzerland. We assessed visuospatial working memory, attention, cognitive bias, and hormone levels at the beginning and at the end of the stimulation phase of ovarian superstimulation as part of a fertility treatment. In addition to inter-individual differences, we examined intra-individual change over time (within-subject effects). The substantial increases in estradiol levels resulting from fertility treatment did not relate to any considerable change in cognitive functioning. As the tests applied represent a broad variety of cognitive functions on different levels of complexity and with various brain regions involved, we can conclude that estradiol does not show a significant short-term effect on cognitive function.
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Publisher Place of Publication Editor
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ISSN 0018-506x ISBN Medium
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Notes Approved no
Call Number MCLab @ davi @ Leeners2021104951 Serial 185
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Author Alimguzhin, V.; Mari, F.; Melatti, I.; Salvo, I.; Tronci, E.
Title Linearising Discrete Time Hybrid Systems Type Journal Article
Year 2017 Publication (up) IEEE Transactions on Automatic Control Abbreviated Journal
Volume 62 Issue 10 Pages 5357-5364
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Abstract Model Based Design approaches for embedded systems aim at generating correct-by-construction control software, guaranteeing that the closed loop system (controller and plant) meets given system level formal specifications. This technical note addresses control synthesis for safety and reachability properties of possibly non-linear discrete time hybrid systems. By means of syntactical transformations that require non-linear terms to be Lipschitz continuous functions, we over-approximate non-linear dynamics with a linear system whose controllers are guaranteed to be controllers of the original system. We evaluate performance of our approach on meaningful control synthesis benchmarks, also comparing it to a state-of-the-art tool.
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ISSN 0018-9286 ISBN Medium
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Notes Approved no
Call Number Sapienza @ mari @ ref7902199 Serial 164
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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 (up) IEEE Transactions on Industrial Electronics Abbreviated Journal
Volume Issue Pages 1-1
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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.
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Notes To appear Approved no
Call Number MCLab @ davi @ ref9513535 Serial 190
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