In order to develop smart cities, the demand for assessing the condition of existing
infrastructure systems in an automated manner is burgeoning rapidly. Among all the early …

The capacity to learn from examples is one of the most desirable features of neural network
models. We present a learning algorithm for the recurrent random network model (Gelenbe …

Statistical performance evaluation has assumed an increasing amount of importance as we
seek to design more and more sophisticated communication and information processing …

Analysis and Synthesis of Computer Systems presents a broad overview of methods that are
used to evaluate the performance of computer systems and networks, manufacturing …

Emergency management systems (EMS) are important and complex examples of Cyber-
Physical-Human systems that are deployed so as to optimise the outcome of an emergency …

We survey results concerning a new stochastic network we have developed [1–7], which
was initially motivated by neural network modelling [1], or—as we called it—by queueing …

In recent years a new class of queueing networks with “negative and positive” customers
was introduced by one of the authors [5], and shown to have a nonstandard product form …

We present the first type and effect system for proving authenticity properties of security
protocols based on asymmetric cryptography. The most significant new features of our type …

G-networks are queueing models in which the types of customers one usually deals with in
queues are enriched in several ways. In Gnetworks, positive customers are those that are …

Spiked recurrent neural networks with" multiple classes" of signals have been recently
introduced by Gelenbe and Fourneau (1999), as an extension of the recurrent spiked …