Wireless Sensor Networks (WSNs) are severely constrained in computation and communication capabilities due to the cost and size of available sensors. On the other hand, autonomic ...
In many applications of sensor networks, it is essential to ensure that messages are transmitted to their destinations as early as possible and the buffer size of each sensor node...
Huimin She, Zhonghai Lu, Axel Jantsch, Li-Rong Zhe...
— Recursive Neural Networks (RNNs) and Graph Neural Networks (GNNs) are two connectionist models that can directly process graphs. RNNs and GNNs exploit a similar processing fram...
Vincenzo Di Massa, Gabriele Monfardini, Lorenzo Sa...
We propose a statistical method for estimating a gene network based on Bayesian networks from microarray gene expression data together with biological knowledge including protein-...
The work presents a modeling and analysis framework for heterogeneous industrial networks architectures which is based on a tight integration of a network simulator with embedded ...
Franco Fummi, Stefano Martini, Marco Monguzzi, Gio...