Guido Del Vescovo

Combining Graph Seriation and Substructures Mining for Graph Recognition

Many interesting applications of Pattern Recognition techniques can take advantage in dealing with labeled graphs as input patterns. To this aim, the most important issue is the definition of a dissimilarity measure between graphs. In this paper, we outline an ensemble of methods for dealing with such data, focusing on two specific methods. The first one is simply based on a global alignment approach applied to seriated versions of the graphs. The second one is a twostages method, which applies a recurrent substructures analysis to the seriated graphs, individuating a set of frequent subsequences, employed for embedding the graphs into a real valued feature vector space. Tests have been performed by synthetically generating a set of classification problem instances with increasing problem hardness, and with a shared benchmarking database of labeled graphs.

Design and implementation of a fast recharge station for electric vehicles

In this paper it is described an innovative project born by the cooperation between Polo per la Mobilità Sostenibile (POMOS) and Citroën Italia. The project concerned the implementation of a high power fast recharge station for electric vehicles in the parking lot of the Citroën dealer. This station is free and available for all the owners of electric vehicles with no restriction on the vehicle brand. The fast recharge station is able to restore the battery pack charge to 80% of maximum value in about 20 minutes using direct current charging at 400 V. The whole project includes in addition to the fast recharge dock two traditional recharge docks driven by a vertical axis innovative mini-wind generator able to produce from 6 to 30 kW. The wind generator is allowed to exchange power with the electric grid implementing the concept of smart grid. The recharge station has been inaugurated by the Italian environment minister July 25-th 2012.

A new Granular Computing approach for sequences representation and classification

In this paper we present an innovative procedure for sequence mining and representation. It can be used as its own in Data Mining problems or as the core of a classification system based on a Granular Computing approach to represent sequences in a suited embedding space. By adopting an inexact sequence matching procedure, the algorithm is able to extract a symbols alphabet of frequent subsequences to be used as prototypes for the embedding stage. Experimental evaluation over both synthetically generated and biological datasets confirms that the modeling system is able to synthesize effective models when facing even complex and noisy problems defined by frequency-based classification rules.

Estimation of Lithium Polymer cell characteristic parameters through genetic algorithms

In this paper the possibility to characterize a Lithium Polymer (LiPo) cell, starting from a small amount of measurements only, is investigated. Experimental results achieved by a deep measurement campaign performed on one of the lithium batteries capable of the highest power on the market are partially reported and described. Part of these results together with an analytical model and a data driven procedure based on a genetic algorithm are used to deduce different quantities believed to be important for the description of the cell behavior. Finally, deduced quantities are compared with the equivalent measured ones in order to evaluate the correctness of the proposed approach.

Multi-fault diagnosis of rolling-element bearings in electric machines

This paper deals with the diagnosis of faults in roller-element bearings as the core of a dedicated Condition based Maintenance (CBM) system. Vibration signals recorded by accelerometers feed into a classification model in charge of monitoring and evaluating bearing wear. The chosen feature extraction technique is based on the computation of the Discrete Fourier Transform (DFT) and on the estimation of the normalized frequency content in each of the considered spectrum sub-bands as an indicative measure of the state of health of the roller-element bearing. Three different damage attributes have been investigated. For each attribute, both Support Vector Machines (SVM) and neurofuzzy Min-Max classifiers have been employed as the core of the diagnostic system. Test results show that it is possible to achieve high accuracy in all diagnostic problems considered. The pre-processing procedure and the classification stage, especially in the case of Min-Max fuzzy networks, do not require demanding computational hardware resources, and as a result, a simple and effective diagnostic system can be designed by feeding the synthesized Min-Max classifiers with the spectral features computed from vibration sensor outputs.

An open software system for signal routing and processing in hybrid vehicles

In the present paper a software system for onboard processing of automotive data is proposed and described. The project of a system composed by some modules interacting on the basis of a producer-consumer paradigm is discussed. The modules run as separate processes on embedded systems based on Linux operating system. Peripherals and displays are also handled by the software. The producer side is represented by the processes which are in charge of receiving and decoding information coming from data links such as CAN, RS232 or ADC chips, forming a vector of physical quantities describing the status of the vehicle. The vector is placed in a shared memory segment, where the consumer processes can read and use it for their purposes. Consumer processes include graphical displays (virtual dashboard), data logger modules recording data on persistent memory devices, and transceiver modules sending information over wired or wireless channels. In order to achieve the best flexibility and reusability over a range of vehicle types, some of the modules are fully configurable by means of a specified configuration file stored on a permanent memory device. Configuration files report the information used to decode the incoming data from the devices through the data links, as well as the directives on how to display data on screen. Partial implementation is described in detail. Future application to real vehicle prototypes is briefly discussed.