| Records |
| Author |
Tronci, Enrico |
Title  |
Equational Programming in Lambda-Calculus via SL-Systems. Part 1 |
Type |
Journal Article |
| Year |
1996 |
Publication |
Theoretical Computer Science |
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| Volume |
160 |
Issue |
1&2 |
Pages |
145-184 |
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Approved |
yes |
| Call Number |
Sapienza @ mari @ tcs96 |
Serial |
54 |
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| Author |
Tronci, Enrico |
| Title |
Equational Programming in lambda-calculus |
Type |
Conference Article |
| Year |
1991 |
Publication |
Sixth Annual IEEE Symposium on Logic in Computer Science (LICS) |
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Pages |
191-202 |
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IEEE Computer Society |
Place of Publication |
Amsterdam, The Netherlands |
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yes |
| Call Number |
Sapienza @ mari @ lics91 |
Serial |
58 |
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| Author |
Martinelli, Marco; Tronci, Enrico; Dipoppa, Giovanni; Balducelli, Claudio |
| Title |
Electric Power System Anomaly Detection Using Neural Networks |
Type |
Conference Article |
| Year |
2004 |
Publication |
8th International Conference on: Knowledge-Based Intelligent Information and Engineering Systems (KES) |
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Pages |
1242-1248 |
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The aim of this work is to propose an approach to monitor and protect Electric Power System by learning normal system behaviour at substations level, and raising an alarm signal when an abnormal status is detected; the problem is addressed by the use of autoassociative neural networks, reading substation measures. Experimental results show that, through the proposed approach, neural networks can be used to learn parameters underlaying system behaviour, and their output processed to detecting anomalies due to hijacking of measures, changes in the power network topology (i.e. transmission lines breaking) and unexpected power demand trend. |
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Springer |
Place of Publication |
Wellington, New Zealand |
Editor |
Negoita, M.G.; Howlett, R.J.; Jain, L.C. |
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Lecture Notes in Computer Science |
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| Series Volume |
3213 |
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3-540-23318-0 |
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yes |
| Call Number |
Sapienza @ mari @ kes04 |
Serial |
35 |
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| Author |
Brizzolari, Francesco; Melatti, Igor; Tronci, Enrico; Della Penna, Giuseppe |
| Title |
Disk Based Software Verification via Bounded Model Checking |
Type |
Conference Article |
| Year |
2007 |
Publication |
APSEC '07: Proceedings of the 14th Asia-Pacific Software Engineering Conference |
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Pages |
358-365 |
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One of the most successful approach to automatic software verification is SAT based bounded model checking (BMC). One of the main factors limiting the size of programs that can be automatically verified via BMC is the huge number of clauses that the backend SAT solver has to process. In fact, because of this, the SAT solver may easily run out of RAM. We present two disk based algorithms that can considerably decrease the number of clauses that a BMC backend SAT solver has to process in RAM. Our experimental results show that using our disk based algorithms we can automatically verify programs that are out of reach for RAM based BMC. |
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IEEE Computer Society |
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Washington, DC, USA |
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0-7695-3057-5 |
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Approved |
yes |
| Call Number |
Sapienza @ mari @ Bmtd07 |
Serial |
76 |
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| Author |
Tronci, E.; Mancini, T.; Mari, F.; Melatti, I.; Salvo, I.; Prodanovic, M.; Gruber, J. K.; Hayes, B.; Elmegaard, L. |
| Title |
Demand-Aware Price Policy Synthesis and Verification Services for Smart Grids |
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Conference Article |
| Year |
2014 |
Publication |
Proceedings of Smart Grid Communications (SmartGridComm), 2014 IEEE International Conference On |
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no |
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Sapienza @ melatti @ |
Serial |
121 |
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| Author |
Tronci, Enrico |
| Title |
Defining Data Structures via Böhm-Out |
Type |
Journal Article |
| Year |
1995 |
Publication |
J. Funct. Program. |
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5 |
Issue |
1 |
Pages |
51-64 |
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We show that any recursively enumerable subset of a data structure can be regarded as the solution set to a B??hm-out problem. |
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Approved |
yes |
| Call Number |
Sapienza @ mari @ jfp95 |
Serial |
57 |
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| Author |
Mari, Federico; Melatti, Igor; Salvo, Ivano; Tronci, Enrico |
| Title |
Control Software Visualization |
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Conference Article |
| Year |
2012 |
Publication |
Proceedings of INFOCOMP 2012, The Second International Conference on Advanced Communications and Computation |
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15-20 |
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ThinkMind |
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978-1-61208-226-4 |
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yes |
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Sapienza @ mari @ infocomp2012 |
Serial |
100 |
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| Author |
Mancini, T.; Mari, F.; Massini, A.; Melatti, I.; Salvo, I.; Sinisi, S.; Tronci, E.; Ehrig, R.; Röblitz, S.; Leeners, B. |
| Title |
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 |
Publication |
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 @ |
Serial |
175 |
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| Author |
Toni Mancini; Enrico Tronci; Ivano Salvo; Federico Mari; Annalisa Massini; Igor Melatti |
| Title |
Computing Biological Model Parameters by Parallel Statistical Model Checking |
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Journal Article |
| Year |
2015 |
Publication |
International Work Conference on Bioinformatics and Biomedical Engineering (IWBBIO 2015) |
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9044 |
Issue |
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Pages |
542-554 |
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no |
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MCLab @ davi @ |
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124 |
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Sinisi, S.; Alimguzhin, V.; Mancini, T.; Tronci, E.; Leeners, B. |
| Title |
Complete populations of virtual patients for in silico clinical trials |
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Journal Article |
| Year |
2021 |
Publication |
Bioinformatics |
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1-8 |
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| 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). |
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1367-4803 |
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no |
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MCLab @ davi @ ref10.1093/bioinformatics/btaa1026 |
Serial |
182 |
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