9 citations · 15 across the 9 of their papers we have counts for
10 papers
Explanation-Based Runtime Verification for Trustworthy ML-driven Optical Networks
Omran Ayoub, Carlos Natalino, Ali Al Housseini +5
Machine learning (ML) models are increasingly integrated into optical network automation frameworks to support tasks such as failure management, performance monitoring and resource…
MuMeNet: A Network Simulator for Musical Metaverse Communications
Ali Al Housseini, Jaime Llorca, Luca Turchet +3
The Metaverse, a shared and spatially organized digital continuum, is transforming various industries, with music emerging as a leading use case. Live concerts, collaborative compo…
BinomialHash: A Constant Time, Minimal Memory Consistent Hash Algorithm
Massimo Coluzzi, Amos Brocco, Alessandro Antonucci +1
Consistent hashing is a technique for distributing data across a network of nodes in a way that minimizes reorganization when nodes join or leave the network. It is extensively app…
Liquid Neural Network-based Adaptive Learning vs. Incremental Learning for Link Load Prediction amid Concept Drift due to Network Failures
Omran Ayoub, Davide Andreoletti, Aleksandra Knapińska +6
Adapting to concept drift is a challenging task in machine learning, which is usually tackled using incremental learning techniques that periodically re-fit a learning model levera…
MementoHash: A Stateful, Minimal Memory, Best Performing Consistent Hash Algorithm
Massimo Coluzzi, Amos Brocco, Alessandro Antonucci +1
Consistent hashing is used in distributed systems and networking applications to spread data evenly and efficiently across a cluster of nodes. In this paper, we present MementoHash…
The Virtual Emotion Loop: Towards Emotion-Driven Services via Virtual Reality
Davide Andreoletti, Luca Luceri, Tiziano Leidi +2
The importance of emotions in service and in product design is well known. However, it is still not very well understood how users' emotions can be incorporated in a product or ser…
Simulation of capillary infiltration into packing structures by the Lattice-Boltzmann method for the optimization of ceramic materials
Danilo Sergi, Loris Grossi, Tiziano Leidi +1
In this work we want to simulate with the Lattice-Boltzmann method in 2D the capillary infiltration into porous structures obtained from the packing of particles. The experimental…
Lattice Boltzmann simulations on the role of channel structure for reactive capillary infiltration
Danilo Sergi, Loris Grossi, Tiziano Leidi +1
It is widely recognized that the structure of porous media is of relevance for a variety of mechanical and physical phenomena. The focus of the present work is on capillarity, a po…
Lattice Boltzmann simulation of the surface growth effects for the infiltration of molten Si in carbon preforms
Danilo Sergi, Loris Grossi, Tiziano Leidi +1
The infiltration of molten silicon into carbon preforms is a widespread technique employed in the industry in order to enhance the thermal and mechanical properties of the final ce…
Surface growth effects on reactive capillary-driven flow: Lattice Boltzmann investigation
Danilo Sergi, Loris Grossi, Tiziano Leidi +1
The Washburn law has always played a critical role for ceramics. In the microscale, surface forces take over volume forces and the phenomenon of spontaneous infiltration in narrow…