F. M. Frattale Mascioli

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Nonexclusive classification characterizes many real problems in which a hard decision about data labels cannot be taken. In these cases, a decision system capable of fuzzy outputs is desirable, in order to well describe problem's nature and domain. In this paper, an algorithm pursuing this approach is presented. More precisely, a nonexclusive k-class(More)
Recently there is a great interest in artificial systems able to understand and recognize human emotions. In this paper an Emotion Recognition System based on classical neural networks and neuro-fuzzy classifiers is proposed. Emotion recognition is performed in real time starting from a video stream acquired by a common webcam monitoring the user’s face.(More)
This paper describes an Automatic Vehicle Monitoring and Location System developed to be tested on the municipal fleet of electric and hybrid vehicles circulating on the small island of Ventotene in Italy. The system allows to determine the geographic position and to provide data about the vehicles, and sends the information to a remote server.
We propose a low cost prevention strategy for osteoporosis. Osteoporosis is a disease consisting in the structural deterioration of bones. This disease has a very high cost for the public health expense all over the world. Its main diagnostic tool is a radiographic analysis called computerized bone mineralometry, by which it is possible to measure the bone(More)
This paper presents a novel power flow optimization strategy in Micro Grids (MGs) connected to the main grid. When the MG includes stochastic energy sources, such as photovoltaic and micro eolic-generators, it is very useful to rely on Energy Storage Systems (ESSs) to buffer energy. In fact, an ESS can be employed to perform several functionalities, related(More)
A novel approach is proposed for overcoming the multiple minima problem, present in the learning of a supervised neural network. It allows to connect rational function approximations to neural networks and is based on the use of a truncated Fourier expansion for determining: 1) the architecture; 2) the parameters of the net, avoiding local minima in an(More)
In actual engineering a typical problem concerns the prediction (classification)of successive states of a real world system. The state is often characterized by several measures related to a multi-sensor array. We propose in the paper a clustering approach to the automatic determination of significant zones in the mulitdimensional space where data can be(More)
The use of clustering systems is very important in those real-word applications where an efficient, both accurate and economical, representation of the data to be processed is necessary. When dealing with statistical models, such a problem is usually related to the estimate of their parameters in the Maximum Likelihood context. At this regard, we propose an(More)
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