Consider the problem of delivering multimedia streams on the Internet. In order to decide if
the network is working correctly, one must be able to evaluate this delivered quality as …

Power loss allocation methods should be efficient enough to meet the needs of the
customers on the bus and effectively calculate the losses from generators and consumers. In …

The Random Neural Network (RNN) has received, since its inception in 1989, considerable
attention and has been successfully used in a number of applications. In this critical review …

The random neural network (RNN) is a recurrent neural network model inspired by the
spiking behaviour of biological neuronal networks. Contrary to most artificial neural network …

Understanding and modeling the wide range of influence factors that impact end user
Quality of Experience (QoE) and go beyond traditional Quality of Service (QoS) parameters …

The short latency required by IoT devices that need to access specific services have led to
the development of Fog architectures that can serve as a useful intermediary between IoT …

Random neural networks (RNN) have been efficiently used as learning tools in many
applications of different types. The learning procedure followed so far is the gradient descent …

Today's Internet does not offer any quality level beyond best effort for the majority of
applications used by a private customer. In particular, this applies for wire-line or wireless …

The idea of G-networks with negative arrivals, as well as of the relevant product form
solution including non-linear traffic equations, was first published by Erol Gelenbe in 1989 …

The conversational quality of a VoIP communication is dependent on several factors such as
the coding process used, the network conditions and the type of error correction or …