662 citations
- Institute for Complex SystemsIT13 papers
- University of FlorenceIT8 papers
- Boston UniversityUS6 papers
- KU LeuvenBE5 papers
- London Institute for Mathematical SciencesGB5 papers
- Sapienza University of RomeIT5 papers
- European Centre for Living TechnologyIT4 papers
- University of TrentoIT4 papers
- Yeshiva UniversityUS4 papers
- Ca' Foscari University of VeniceIT3 papers
- Centre National de la Recherche ScientifiqueFR3 papers
- Centro Ricerche Enrico FermiIT3 papers
6 papers · 1 filter
A type language for message passing component-based systems
Zorica Savanović, Letterio Galletta, Hugo Torres Vieira
Component-based development is challenging in a distributed setting, for starters considering programming a task may involve the assembly of loosely-coupled remote components. In o…
Crack arrest through branching at curved weak interfaces: an experimental and numerical study
M. T. Aranda, I. G. Garcia, J. Reinoso +2
The phenomenon of arrest of an unstably-growing crack due to a curved weak interface is investigated. The weak interface can produce the deviation of the crack path, trapping the c…
Interacting non-linear reinforced stochastic processes: synchronization and no-synchronization
Irene Crimaldi, Pierre-Yves Louis, Ida Germana Minelli
'Rich get richer' rule comforts previously often chosen actions. What is happening to the evolution of individual inclinations to choose an action when agents do interact ? Interac…
Never Trust Your Victim: Weaponizing Vulnerabilities in Security Scanners
Andrea Valenza, Gabriele Costa, Alessandro Armando
The first step of every attack is reconnaissance, i.e., to acquire information about the target. A common belief is that there is almost no risk in scanning a target from a remote…
Taylor's law in innovation processes
F. Tria, I. Crimaldi, G. Aletti +1
Taylor's law quantifies the scaling properties of the fluctuations of the number of innovations occurring in open systems. Urn based modelling schemes have already proven to be eff…
Learning Queuing Networks by Recurrent Neural Networks
Giulio Garbi, Emilio Incerto, Mirco Tribastone
It is well known that building analytical performance models in practice is difficult because it requires a considerable degree of proficiency in the underlying mathematics. In thi…