5,573 research outputs found
Mario Sansone e gli studi di italianistica
No full textIl ruolo di Mario Sansone nella fondazione degli studi italianistici presso l'Università di Bari negli anni quaranta-settanta del Novecent
Contro la funzionalizzazione della contrattazione collettiva. Riflessioni sul pensiero di Mario Rusciano
No full textL'autore riflette sul pensiero di Mario Rusciano in punto di funzionalizzazione della contrattazione collettiva.The author reflects on the thought of Mario Rusciano in relation to the subject of the functionalisation of collective bargaining
Individual identification via electrocardiogram analysis
No full textBioMedical Engineering Online
Volume 14, Issue 1, August 14, 2015, Article number 78
Open Access
Individual identification via electrocardiogram analysis (Review)
Fratini, A.a , Sansone, M.b , Bifulco, P.b , Cesarelli, M.b
a Aston University, School of Life and Health Sciences, Aston Triangle, Birmingham, United Kingdom
b University Federico II of Naples, Department of Electronic Engineering and Information Technologies, Via Claudio, 21, Naples, Italy
View references (142)
Abstract
Background: During last decade the use of ECG recordings in biometric recognition studies has increased. ECG characteristics made it suitable for subject identification: it is unique, present in all living individuals, and hard to forge. However, in spite of the great number of approaches found in literature, no agreement exists on the most appropriate methodology. This study aimed at providing a survey of the techniques used so far in ECG-based human identification. Specifically, a pattern recognition perspective is here proposed providing a unifying framework to appreciate previous studies and, hopefully, guide future research. Methods: We searched for papers on the subject from the earliest available date using relevant electronic databases (Medline, IEEEXplore, Scopus, and Web of Knowledge). The following terms were used in different combinations: electrocardiogram, ECG, human identification, biometric, authentication and individual variability. The electronic sources were last searched on 1st March 2015. In our selection we included published research on peer-reviewed journals, books chapters and conferences proceedings. The search was performed for English language documents. Results: 100 pertinent papers were found. Number of subjects involved in the journal studies ranges from 10 to 502, age from 16 to 86, male and female subjects are generally present. Number of analysed leads varies as well as the recording conditions. Identification performance differs widely as well as verification rate. Many studies refer to publicly available databases (Physionet ECG databases repository) while others rely on proprietary recordings making difficult them to compare. As a measure of overall accuracy we computed a weighted average of the identification rate and equal error rate in authentication scenarios. Identification rate resulted equal to 94.95 % while the equal error rate equal to 0.92 %. Conclusions: Biometric recognition is a mature field of research. Nevertheless, the use of physiological signals features, such as the ECG traits, needs further improvements. ECG features have the potential to be used in daily activities such as access control and patient handling as well as in wearable electronics applications. However, some barriers still limit its growth. Further analysis should be addressed on the use of single lead recordings and the study of features which are not dependent on the recording sites (e.g. fingers, hand palms). Moreover, it is expected that new techniques will be developed using fiducials and non-fiducial based features in order to catch the best of both approaches. ECG recognition in pathological subjects is also worth of additional investigations
ECG databases for biometric systems: A systematic review
No full textComputer-based biometric systems (CBBSs) individual recognition are expert and intelligent systems that are gaining increasing interest in many areas, such as securing financial systems, telecommunications and healthcare applications. The electrocardiogram (ECG) has been used as biometric feature for its low circumvention, large acceptability and uniqueness, thus being at the basis of several CBBSs. As ECG databases collected for clinical applications are not adequate for biometric applications, we have assisted to the development of other repositories of ECG, each one different from the others and highlighting certain issues of ECG-based biometric recognition. Through a systematic framework presented here, we quantitative analyse, evaluate and compare the acquisition hardware and the acquisition protocols of ECG databases available in literature and suited to develop CBBSs. Although the most recent ones, namely CYBHI and UofTDB, result the best for the acquisition hardware and the acquisition protocols, respectively, our survey shows that none is exhaustive for developing a robust and general enough CBBSs. The analysis also highlights the current lack of standardization in this field and the difficulty of performing an effective benchmarking activity. Since a publicly available database is essential for the research community in ECG-based CBBS to correctly assess the performance of existing algorithms or even commercial expert systems, we also discuss here the main features that an “optimal” repository for the intelligent application at hand
Segmentation and classification of breast lesions using dynamic features in Dynamic Contrast Enhanced-Magnetic Resonance Imaging
No full textThe aim of this study is to propose an approach, based on
Multi Layer Perceptron classification of dynamic and textural features, for breast lesions segmentation and classification using Dynamic Contrast Enhanced-Magnetic Resonance Imaging data. We compared the performance obtainable with dynamic, textural and spatio-temporal features. In particular, 98 dynamic features, 60 textural features and 72 spatio-temporal features were considered. The
dataset included 20 breast lesions, 10 benign and 10 malignant. The performance of lesion segmentation have been
evaluated with respect to manual segmentation provided by
an expert radiologist. Results of lesion classification were
compared to histological findings. Our results indicate that
Multi Layer Perceptron can achieve better results in terms
of sensitivity, specificity and accuracy when dynamic features are considered both for lesion segmentation and classification (accuracy of 91 % and 70 %, respectively)
Friction dissipation in reciprocating internal combustion engines: cam tappet contact
No full textThe interest towards fuel consumption reduction in reciprocating internal combustion engines has achieved a key role starting from the first energy crisis during the 70’s. Even if in alternate phases, such interest had further increased during the following years assuming a fundamental role in the last years. The reason lies in the introduction of regulations that limit the emissions of carbon dioxide, as it belongs to the family of greenhouse gasses. A reduction of the friction dissipation reflects directly on consumption reduction and consequently in an improvement of emissions. The main goal of this research is to model the friction dissipation at the cam tappet interface. In this research an analytic model is proposed, it allows to estimate the dissipation due to friction with a complexity appropriate to that of the design phase and which allows to select between different design solutions in order to optimize the efficiency of the cam tappet interfaces. Model results are coherent with experimental results reported in literature
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