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    Data and Computer Science - Statistica e Informatica

    Data and Computer Science - Statistica e Informatica

    Nome del gruppo

    : Data and Computer Science - Statistica e Informatica

    L'obiettivo del gruppo è di fornire competenze di tipo statistico e informatico per la gestione, il trattamento, l'analisi di dati complessi o di grandi dimensioni, che si presentano ad oggi in ogni ambito applicativo della conoscenza umana anche grazie all'avvento dell'Internet of things, dei flussi di informazioni non strutturate ed eterogenee provenienti dai social media, o dalla pervasività di reti di sensori, dei dispositivi mobili e delle problematiche tecnologiche ed informatiche connesse. L'aspetto informatico, in sinergia con quello statistico, risulta cruciale per la progettazione, la gestione, la modellazione e la valutazione, con tecniche probabilistiche e deterministiche, analitiche e simulative, multiformalismo e multisoluzione, di sistemi basati su calcolatore, critici per affidabilità, tempo, scala e complessità. Il tema della complessità, sia esso inteso nella descrizione e nella natura dei dati, nonché nelle procedure di produzione, memorizzazione, custodia ed elaborazione dei dati, funge da trait d’union tra le due anime del gruppo di ricerca che, anche in base alla produzione scientifica si orienta alla soluzione di problemi metodologici ed applicativi che possa rispondere in modo innovativo alle sfide che lo sviluppo tecnologico pone. Non secondari sono i problemi relativi alla corretta gestione della privacy nell’ambito della gestione dei dati.

    Di seguito sono riportate le parole chiave relative alle tematiche di competenza del gruppo:

     
    Main topics:

    - Multivariate Data Analysis

    - Regression

    - Clustering

    - Factorial Analysis

    - Classification / Discrimination

    - Data Mining

    - Symbolic Data Analysis

    - Interval data analysis

    - Distributional data analysis

    - Multicategorical data analysis

    - Statistical methods for biodiversity assessment

    - Biostatistics

    - R packages development

    - Item response theory

    - Consensus in multiperson decision making

    - Statistical indicators of equitable and sustainable well-being 

    - Statistical methods for the assessment of diversity in organizations and its impact

    - Statistical methods based on fuzzy set theory 

    - Data stream mining

    - Clustering of sensor data

    - Summarization of highly evolving data streams

    - Classification of sensor data

    - Functional Data Analysis

    - Clustering of functional data

    - Forecasting

    - Regression Methods

    - Spatial prediction

    - Outlier detection

    - Modeling and evaluation of complex systems

    - Performance and dependability modeling and evaluation of complex, dependable, safe, secure, distributed computer based systems

    - Cloud Computing and Big Data systems Performance Evaluation and prediction

    - Formal analysis of complex systems

    - Metamodeling and applications

    - Multiformalism and multisolution modeling approaches

    - Analysis and simulation of massively concurrent systems

    - Applications to ERTMS/ETCS, Service Oriented Architectures, Cloud, Big Data, e Government, Agent-based, Wireless Sensor Networks, Mobile Sensor Networks domains, Service Oriented Architecture

    - Software Engineering and Information Systems

    - Methodologies, Techniques and Tools for Model Driven Engineering and Agent-Based Systems

    - Performance prediction

    - Networked systems

    - Privacy

    - Artificial intelligence

    - Neural networks

    - Deep Neural Networks

    - Deep Learning

    - Transfer Learning

    - Security

    - Natural Language Processing

    - Text Mining

    - Text Analytics

    PROGETTI ATTIVATI NELL'AMBITO DEL GRUPPO DI RICERCA:

    Valere ANDROIDS - AutoNomous DiscoveRy Of depressIve Disorder Signs (2019-2021)

    Valere E-PASSION - Enhancing the energetic PerformAnce of Self-Sustained wIreless sensOr Networks (2019-2022)

    PON_AIM AIM1878214_2 (tema mobilità intelligente) (2019-2022)

    POR Programma Operativo FESR Campania 2014-2020. Quick&Smart, Ris3

    IT-MIUR-PRIN 2015, Complex space-time modeling and functional analysis for probabilistic forecast of seismic events. Durata 36 mesi.

    EU JU-ARTEMIS, progetto Crystal - CRitical sYSTem engineering AcceLeration (Maggio 2013-Settembre 2016); 72 partner europei.

    EU ITC COST Action IC1404 Multi Paradigm Modeling for Cyber Physical Systems (MPM4CPS); (2014 - 2018).

    EU ITC COST Action IC1406 High-Performance Modelling and Simulation for Big Data Applications (cHiPSet); (2014 - 2018).

    IT-MIUR-PRIN 2010, progetto Cloud@Home  (Marzo 2010- Settembre 2012), 5 partner italiani.

    Action 2.2 of the Research staff mobility programme under the 2011 Research Promotion Plan: "Research visits of foreign researchers to the Universitat Jaume I"

    EU COST Action IC0702 - Chair Prof. Christian Borgelt

    POR Campania FSE 2007/2013 REPOS “Reti Politiche pubbliche e sviluppo” 

    Osservatorio Regionale Sistema Universitario Campano - POR Campania FESR 2007/2013 - Asse 2 - Obiettivo Operativo 2.1

    EU FP7 - FP7-ICT-2013-5 - Progetto SPECS Secure provisioning of CLoud Services based on SLA management (2013-2016).

    IT-MIUR PON “Laboratori Pubblico-Privati”, progetto DISPLAY - Distributed hybrId Simulation PLAtform for ATM and VTS Systems (2012-2015).

    IT-MIUR-FAR, progetto LC3 - Laboratorio pubblico-privato di ricerca sul tema della Comunicazione delle Conoscenze Culturali, (2006-present), 5 partners.

    PON04a2_C - Smarthealth 2.0 project - collaboration in activity A7.5 and A7.6

    Progetto CAMPUS Ecoturismo Urbano per la Fruizione Sostenibile dei Beni Culturali - FESR Campania 2007-2013

    ALTRI PROGETTI

    FIT “Fondo speciale rotativo per l’Innovazione Tecnologica” PON 2007-13 - Programma META "Metodologie di analisi statistica, data stream mining, e analisi off-line dei risultati del data Stream mining” (resp. R. Verde)

    COLLABORAZIONI NAZIONALI E INTERNAZIONALI:

    Università degli Studi di Napoli “Federico II”

    Politecnico di Milano

    Università degli Studi di Torino

    Università “Ca' Foscari” Venezia

    Università degli Studi del Piemonte Orientale

    Università degli Studi di Firenze

    Université Sorbonne Paris Nord (France)

    Institut Supérieur d'Electronique de Paris - ISEP (France)

    University of Marrakech Cadi Ayyad (Morocco)

    University of Fez Sidi Mohamed Ben Abdellah (Morocco)

    George Mason University, USA

    Cracow University of Technology (Polonia)

    University Politehnica of Bucarest (Romania)

    Centro de Informatica - Cin - Universidade Federal de Pernambuco (Brasil)

    Universitat Jaume I E-12071 Castellon, Spain

    Universidad Complutense de Madrid

    National University of Ireland, Galway, Ireland

    Clinical Research Facility, Galway, Ireland

    The University of Defence, Brno, Czech Republic

    G. d’Annunzio University of Chieti-Pescara, Italy

    University of Almería, Spain

    “Al. I. Cuza” University, Faculty of Mathematics, Iasi, Romania

    University of Seville, Spain

    Systems Research Institute, Polish Academy of Sciences, Poland

    The Italian National Institute of Statistics, Pescara branch

    Libera Università di Bolzano

    Lancaster University

    Universidad de Zaragoza, Spain

    Universidade de Aveiro, Portugal

    Nestlè Research, Switzerland

    Segnalazione esplicita delle collaborazioni con Consorzi, Scarl, altri Enti partecipati dall’Università Vanvitelli con indicazione dei progetti in comune o svolti dai Ricercatori del gruppo nell’ambito di queste strutture.

    CIRA -.Centro Italiano Ricerche Areospaziali

    CERICT - Consorzio Interuniversitario Regionale sull’ICT

    CMCC - Centro euro-Mediterraneo sui Cambiamenti Climatici

    IT Regione Campania CAMPUS, progetto MyOpenGov (2013-2015).

    CINI - Consorzio Interuniversitario Nazionale per l’Informatica

    BENECON-Scarl - Centro di Competenza Regionale per i Beni Culturali, Ecologia e Economia

    Gruppo "ENERGIA" della SUN

     
    PRINCIPALI PUBBLICAZIONI:

    [2022] Andrea Bobbio, Lelio Campanile, Marco Gribaudo, Mauro Iacono, Fiammetta Marulli, Michele Mastroianni, A cyberwarfare perspective on risks related to health IoT devices and contact tracing. Neural Computing and Applications, Springer, ISSN: 1433-3058, DOI: 10.1007/s00521-021-06720-1

    [2021] Jacek Tchorzewski, Agnieszka Jakobik, Mauro Iacono, An ANN-based scalable hashing algorithm for computational clouds with schedulers. International Journal of Applied Mathematics and Computer Science, Num. 4, Vol. 31, Dec. 2021, De Gruyter, ISSN: 1641-876X, DOI: 10.34768/amcs-2021-0048

    [2021] Marco Gribaudo, Mauro Iacono, Daniele Manini, COVID-19 Spatial Diffusion: a Markovian Agent Based Model. Mathematics, num. 5, vol. 9, 2021, MDPI, ISSN: 2227-7390, DOI: 10.3390/math9050485

    [2021] Enrico Barbierato, Lelio Campanile, Marco Gribaudo, Mauro Iacono, Michele Mastroianni, Stefania Nacchia, Performance evaluation for the design of a hybrid cloud based distance synchronous and asynchronous learning architecture. Simulation Modelling Practice and Theory, Elsevier, 1569-190X, DOI: 10.1016/j.simpat.2021.102303

    [2021] Lelio Campanile, Mauro Iacono, Alexander H. Levis, Fiammetta Marulli, Michele Mastroianni, On privacy regulations, smart roads, blockchain and liability insurance: putting technologies at work. IEEE Security & Privacy, vol. 19, num. 1, 2021, pp. 34-43, IEEE, 1540-7993, DOI: 10.1109/MSEC.2020.3012059

    [2020] Lelio Campanile, Marco Gribaudo, Mauro Iacono, Fiammetta Marulli, Michele Mastroianni, Computer Network Simulation with ns-3: A Systematic Literature Review. Electronics, MDPI, 9(2), 272, ISSN: 2079-9292, DOI: 10.3390/electronics9020272

    [2020] Romano, E., Mateu, J. Butzbach, O. Heteroskedastic geographically weighted regression model for functional data. Spatial Statistics, Elsevier, DOI: 10.1016/j.spasta.2020.100444

    [2020] Nardone, R., Marrone, S., Gentile, U., Amato, A., Barberio, G., Benerecetti, M., De Guglielmo, R., Di Martino, B., Mazzocca, N., Peron, A., Pisani, G., Velardi, L., Vittorini, V.; An OSLC-based environment for system-level functional testing of ERTMS/ETCS controllers; (2020) Journal of Systems and Software, 161, art. no. 110478

    [2019] Drago, A., Marrone, S., Mazzocca, N., Nardone, R., Tedesco, A., Vittorini, V.: A model-driven approach for vulnerability evaluation of modern physical protection systems; (2019) Software and Systems Modeling, 18 (1), pp. 523-556.

    [2019] Romano, E., Irpino I., Mateu, J.S. Spatial functional data analysis for probability density functions: compositional functional data vs distributional data approach. Geostatistical Functional Data Analysis: Theory and Methods. John Wiley & Sons.

    [2019]  Migliori S., De Massis A., Maturo, F., Paolone F. How does family management affect innovation investment propensity? The key role of innovation impulses. Journal of Business Research. DOI: 10.1016/j.jbusres.2020.01.039. 

    [2019]  Maturo F., Ferguson J., Di Battista T., Ventre V. A fuzzy functional k-means approach for monitoring Italian regions according to health evolution over time. Soft Computing. DOI: 10.1007/s00500-019-04505-2.

    [2019] Maturo F., Balzanella A., and Di Battista T. Building Statistical Indicators of Equitable and Sustainable Well-Being in a Functional Framework. Social Indicators Research, 146(3), 449–471. DOI: 10.1007/s11205-019-02137-5

    [2019] Ferguson J., O’Leary N., Maturo F. et al. Graphical comparisons of relative disease burden across multiple risk factors. BMC Medical Research Methodology, 19(1), 186. DOI: 10.1186/s12874-019-0827-4.

    [2019] Maturo F., Fortuna F., and Di Battista T. Testing Equality of Functions Across Multiple Experimental Conditions for Different Ability Levels in the IRT Context: the Case of the IPRASE TLT 2016 Survey. Social Indicators Research, 146(1), 19-39. DOI: 10.1007/s11205-018-1893-4

    [2019] Fortuna F. and Maturo F. K-Means Clustering Item Characteristic Curves and Item Information Curves via Functional Principal Component Analysis. Quality & Quantity, 53(5), 2291-2304. DOI: 10.1007/s11135-018-0724-7

    [2019] Maturo F., Migliori S., and Paolone F. Measuring and Monitoring Diversity in Organizations through Functional Instruments with an Application to Ethnic Workforce Diversity of the U.S. Federal Agencies. Computational and Mathematical Organization Theory, 25(4), pp. 357–388. DOI: 10.1007/s10588-018-9267-7

    [2019] Balzanella, A., Irpino, A. Spatial prediction and spatial dependence monitoring on georeferenced data streams. STATISTICAL METHODS & APPLICATIONS. DOI:10.1007/s10260-019-00462-0

    [2019] Enrico Barbierato, Marco Gribaudo, Mauro Iacono, Agnieszka Jakobik, Exploiting CloudSim in a multiformalism modeling approach for cloud based systems. Simulation Modelling Practice and Theory, Elsevier, 1569-190X, DOI: 10.1016/j.simpat.2018.09.018

    [2019] Pota, M., Marulli, F., Esposito, M., De Pietro, G., Fujita, H., Multilingual POS tagging by a composite deep architecture based on character-level features and on-the-fly enriched Word Embeddings. Knowledge-Based Systems, Elsevier, 0950-7051, DOI: 10.1016/j.knosys.2018.11.003

    [2019] Antonio Balzanella, Rosanna Verde (2019). Histogram-based clustering of multiple data streams. Knowledge and Information Systems, ISSN: 0219-1377, doi: 10.1007/s10115-019-01350-5

    [2019] Antonio Balzanella, Rosanna Verde. Histogram-Based Clustering of Sensor Network Data. In: C. H. Skiadas J. R. Bozeman. Data Analysis and Applications 1. vol. 2, p. 25-36, ISTE - Wiley, ISBN: 978-1-78630-382-0, doi: 10.1002/9781119597568.ch2

    [2018] Marco Gribaudo, Mauro Iacono, Daniele Manini, Performance evaluation of replication policies in microservice based architectures. Electronic Notes on Theoretical Computer Science, Elsevier, ISSN: 1571-0661, DOI: 10.1016/j.entcs.2018.03.033

    [2018] Maturo, F. and Di Battista, T. A Functional Approach to Hill’s Numbers for Assessing Changes in Species Variety of Ecological Communities Over Time. Ecological Indicators, 84, 70 – 81. DOI: 10.1016/j.ecolind.2017.08.016

    [2018] Fortuna F., Maturo F., and Di Battista T. Clustering Functional Data Streams: Unsupervised Classification of Soccer Top Players based on Google Trends. Quality and Reliability Engineering International, 34(7). DOI: 10.1002/qre.2333

    [2018] Maturo, F. and Ventre, V.. Consensus in Multiperson Decision Making Using Fuzzy Coalitions. Soft Computing Applications for Group Decision-Making and Consensus Modeling. Series: Studies in Fuzziness and Soft Computing, 357, pp. 451–464. Springer International Publishing, Cham. DOI: 10.1007/978-3-319-60207-3_26

    [2018] Marco Gribaudo, Mauro Iacono, Mariam Kiran, A performance modeling framework for lambda architecture based applications. Future Generation Computer Systems, Elsevier, ISSN: 0167-739X, DOI: 10.1016/j.future.2017.07.033

    [2017] Marco Gribaudo, Mauro Iacono, Alexander H. Levis, An IoT based monitoring approach for cultural heritage sites: the Matera case. Concurrency and Computation: Practice and Experience, Wiley, ISSN: 1532-0634, DOI: 10.1002/cpe.4153

    [2017] Irpino A, Verde R, De Carvalho F.A.T. (2017). Fuzzy clustering of distributional data with automatic weighting of variable components. Information Sciences, vol. 406-407, p. 248-268, ISSN: 0020-0255, doi: 10.1016/j.ins.2017.04.040

    [2017] Chianese, A., Marulli, F., Piccialli, F., Benedusi, P., Jung, J.E., An associative engines based approach supporting collaborative analytics in the Internet of cultural things. Future Generation Computer Systems, Elsevier, ISSN: 0167-739X, DOI: 10.1016/j.future.2016.04.015

    [2017]  Romano, E., Balzanella A., Verde, R. Spatial variability clustering for spatially dependent functional data. STATISTICS AND COMPUTING. Vol. 27, p.645-658, DOI: 10.1007/s11222-016-9645-2

    [2017] Martinelli, Fabio, Fiammetta Marulli, and Francesco Mercaldo. Evaluating convolutional neural network for effective mobile malware detection. Procedia Computer Science 112 (2017): 2372-2381.

    [2017] Francesco Piccialli, Fiammetta Marulli, Angelo Chianese. A novel approach for automatic text analysis and generation for the cultural heritage domain. Multimedia Tools and Applications 76.8 (2017): 10389-10406.

    [2016] Angelo Chianese, Fiammetta Marulli, Francesco Piccialli. Cultural heritage and social pulse: a semantic approach for CH sensitivity discovery in social media data. 2016 IEEE Tenth International Conference on Semantic Computing (ICSC). IEEE, 2016.

    [2016] Enrico Barbierato, Marco Gribaudo, Mauro Iacono, Modeling Hybrid Systems in SIMTHESys. Electronic Notes on Theoretical Computer Science, vol. 327, pp. 5-25 (October 2016), Elsevier, ISSN: 1571-0661, DOI: 10.1016/j.entcs.2016.09.021

    [2016] Marco Gribaudo, Mauro Iacono, Daniele Manini, Improving reliability and performances in large scale distributed applications with erasure codes and replication. Future Generation Computer Systems, vol. 56, pp. 773-782 (March 2016), Elsevier, ISSN: 0167-739X, DOI: 10.1016/j.future.2015.07.006

    [2016] Davide Cerotti, Marco Gribaudo, Mauro Iacono, Pietro Piazzolla, Modeling and analysis of performances for concurrent multithread applications on multicore and GPU systems. Concurrency and Computation: Practice and Experience, vol. 28, num. 2, pp. 438-452 (February 2016), Wiley, ISSN: 1532-0634, DOI: 10.1002/cpe.3504

    [2016] Enrico Barbierato, Marco Gribaudo, Mauro Iacono, Modeling and evaluating the effects of Big Data storage resource allocation in global scale cloud architectures. International Journal of Data Warehousing and Mining, vol. 12, num. 2, pp. 1-20 (January-March 2016), IGI Global, ISSN: 1548-3924, DOI: 10.4018/IJDWM.2016040101

    [2016] Irpino A, Verde R, Balzanella A (2016). Dimension Reduction Techniques for Distributional Symbolic Data. IEEE TRANSACTIONS ON CYBERNETICS, vol. 46, p. 344-355, ISSN: 2168-2267, doi: 10.1109/TCYB.2015.2389653

    [2016] Di Battista, T., Fortuna, F., and Maturo, F. Environmental Monitoring Through Functional Biodiversity Tools. Ecological Indicators, 60, 237–247. url:http://dx.doi.org/10.1016/j.ecolind.2015.05.056

    [2016] Di Battista, T., Fortuna, F., and Maturo, F.. Parametric Functional Analysis of Variance for Fish Biodiversity Assessment. Journal of Environmental Informatics, 28, 101–109. url: http://dx.doi.org/10.3808/jei.201600348

    [2016] Balzanella A, Romano E, Verde R (2016). Modified half-region depth for spatially dependent functional data. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, p. 1-17, ISSN: 1436-3240, doi: 10.1007/s00477-016-1291-x

    [2016] Jorge Mateu, Elvira Romano (2016). Advances in spatial functional statistics. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, ISSN: 1436-3240, doi: 10.1007/s00477-016-1346-z

    [2016] Maria Dolores Ruiz-Medina, Romano E, Rosaura Fernandez-Pascual (2016). Plug-in prediction intervals for a special class of standard ARH(1) processes. JOURNAL OF MULTIVARIATE ANALYSIS, p. 138-150, ISSN: 0047-259X, doi: 10.1016/j.jmva.2015.09.001

    [2016] Rivoli L, Verde R, Irpino A (2016). The median of a set of histogram data. In: G. Alleva A. Giommi. (a cura di): G. Alleva A. Giommi, Studies in Theoretical and Applied Statistics Selected Papers of the Statistical Societies. p. 37-48, Springer International Publishing Switzerland, ISBN: 978-3-319-27272-6, doi: 10.1007/978-3-319-27274-0_4

    [2015] Marco Gribaudo, Mauro Iacono, Stefano Marrone, Exploiting Bayesian Networks for the analysis of combined Attack Trees. Electronic Notes on Theoretical Computer Science, vol. 310, pp. 91-111 (January 2015), Elsevier, ISSN: 1571-0661, DOI: 10.1016/j.entcs.2014.12.014

    [2015] Aniello Castiglione, Mauro Iacono, Marco Gribaudo, Francesco Palmieri, Modeling performances of concurrent Big Data applications. Software: Practice and Experience, vol. 45, num. 8, pp. 1127-1144 (August 2015), Wiley, ISSN: 1097-024X, DOI: 10.1002/spe.2269

    [2015] Iulian Ivlad, Jorge Mateu, Elvira Romano (2015). On some descriptive and predictive methods for the dynamics of cancer growth. STATISTICA, vol. 75, p. 247-263, ISSN: 1973-2201

    [2015] Elvira Romano, Jorge Mateu, Ramon Giraldo (2015). On the performance of two clustering methods for spatial functional data. ASTA ADVANCES IN STATISTICAL ANALYSIS, vol. 99, p. 467-492, ISSN: 1863-8171, doi: 10.1007/s10182-015-0253-9

    [2015] Irpino A, Verde R (2015). Linear regression for numeric symbolic variables: a least squares approach based on Wasserstein Distance. ADVANCES IN DATA ANALYSIS AND CLASSIFICATION, vol. 9, p. 81-106, ISSN: 1862-5347, doi: 10.1007/s11634-015-0197-7

    [2015] Verde R, Balzanella A, Irpino A (2015). Order statistics for histogram data and a box plot visualization tool. REVUE DES NOUVELLES TECHNOLOGIES DE L'INFORMATION, vol. RNTI-E-29, p. 29-48, ISSN: 1764-1667

    [2015] Casalino L, D’Ambra P, Guarracino MR, Irpino A, Maddalena L, Maiorano F, Minchiotti G, Patriarca EJ (2015). Image Analysis and Classification for High-Throughput Screening of Embryonic Stem Cells. In: Zazzu V.;Ferraro M.B.;Guarracino M.. (a cura di): Zazzu Ferraro Guarracino, Mathematical Models in Biology, Proceedings of the First Workshop on Bringing Maths To Life (BMTL 2014), p. 17-31, BERLIN: Springer, ISBN: 978-3-319-23496-0, doi: 10.1007/978-3-319-23497-7_2

    [2015] De Carvalho F., Irpino A., Verde R. (2015). Fuzzy clustering of distribution-valued data using an adaptive L2 Wasserstein distance. In: Fuzzy Systems (FUZZ-IEEE), 2015 IEEE International Conference on. p. 1-8, IEEE, Istanbul, Turkey, 2-5 Aug. 2015, doi: 10.1109/FUZZ-IEEE.2015.7337847

    [2015] Balzanella A., Romano E (2015). A depth function for geostatistical functional data. In: Morlini Isabella Minerva Tommaso Vichi Maurizio. Advances in Statistical models for Data Analysis. p. 9-16, Berlin: Springer, ISBN/ISSN: 978-3-319-17377-1, doi: 10.1007/978-3-319-17377-1

    [2015] Romano E., Balzanella A. (2015). On-Line Clustering of functional boxplots for monitoring multiple streaming time series. In: Lausen Berthold Krolak-Schwerdt Sabine Bˆhmer Matthias. Data Science, Learning by Latent Structures, and Knowledge Discovery. p. 113-225, Berlin Heidelberg: Springer-Verlag, ISBN/ISSN: 978-3-662-44982-0

    [2014] M. Iacono, S. Marrone, Model-based availability evaluation of composed web services. Journal of Telecommunications and Information Technology (JTIT), vol. 4/2014, pp. 5-13, ISSN: 1509-4553

    [2014] Francesco Flammini, Stefano Marrone, Mauro Iacono, Nicola Mazzocca, Valeria Vittorini, A Multiformalism Modular Approach to ERTMS/ETCS Failure Modelling. International Journal of Reliability, Quality and Safety Engineering, vol. 21, num. 1, pp. 1450001-1-1450001-29, World Scientific , ISSN: 0218-5393, DOI: 10.1142/S0218539314500016

    [2014] E. Barbierato, M. Gribaudo, M. Iacono, Performance Evaluation of NoSQL Big-Data applications using multi-formalism models. Future Generation Computer Systems, vol. 37, pp. 345-353 (July 2014), Elsevier, ISSN: 0167-739X, DOI: 10.1016/j.future.2013.12.036

    [2014] A. Castiglione, M. Gribaudo, M. Iacono, F. Palmieri, Exploiting mean field analysis to model performances of big data architectures. Future Generation Computer Systems, vol. 37, pp. 203-211 (July 2014), Elsevier, ISSN: 0167-739X, DOI: 10.1016/j.future.2013.07.016

    [2014] Ruiz Medina M.D., Espejo R.M., Romano E. (2014). Spatial functional normal mixed effect approach for curve classification. ADVANCES IN DATA ANALYSIS AND CLASSIFICATION, vol. 8, p. 257-285, ISSN: 1862-5347, doi: 10.1007/s11634-014-0174-6

    [2014] Irpino A, Verde R (2014). Basic statistics for distributional symbolic variables: a new metric-based approach. ADVANCES IN DATA ANALYSIS AND CLASSIFICATION, vol. 9, p. 143-175, ISSN: 1862-5347, doi: 10.1007/s11634-014-0176-4

    [2014] Irpino A, Verde R, De Carvalho F.A.T. (2014). Dynamic clustering of histogram data based on adaptive squared Wasserstein distances. EXPERT SYSTEMS WITH APPLICATIONS, vol. 41, p. 3351-3366, ISSN: 0957-4174, doi: 10.1016/j.eswa.2013.12.001

    [2014] Verde R, Irpino A, Rivoli L (2014). A Box-Plot and Outliers Detection Proposal for Histogram Data: New Tools for Data Stream Analysis. In: AA.VV.. (a cura di): Vicari Donatella; Okada Akinori; Ragozini Giancarlo; Weihs Claus, Analysis and Modeling of Complex Data in Behavioral and Social Sciences. p. 283-291, BERLIN: Springer, ISBN: 978-3-319-06691-2, doi: 10.1007/978-3-319-06692-9_30

    [2014] Verde R, Diday E (2014). Symbolic Data Analysis: A Factorial Approach Based on Fuzzy Coded Data. In: AA.VV.. (a cura di): Blasius J. Greenacre M., Visualization and Verbalization of Data. p. 254-268, LONDON:Chapmann & Hall, ISBN: 978-1-46-658980-3

    [2014] Balzanella A, IRPINO A, Verde R (2014). Monitoring spatially dependent data streams. In: 47th SIS Scientific Meeting of the Italian Statistical Society Cagliari, June 11-13, 2014. CAGLIARI: CUEC Editrice, ISBN: 9788884678744, Cagliari, 11-13 Giugno 2014

    [2014] Irpino A, Verde R, Balzanella A (2014). Spatial dependence monitoring over distributed data streams. In: Proceedings of COMPSTAT 2014. p. 483-490, The International Statistical Institute/International Association for Statistical Computing, ISBN: 978-2-8399-1347-8, Geneva (Switzerland), 19-22 Agosto 2014

    [2014] Verde R, Irpino A, Desbois D (2014). How to cope with modelling and privacy concerns? A regression model and a visualization tool for aggregated data. In: CONFERENCE OF EUROPEAN STATISTICS STAKEHOLDERS Methodologists, Producers and Users of European Statistics. ROME, Sapienza University, Dpt. of Statistical Sciences, 2014

    [2014] Balzanella A., Adelfio G., Chiodi M., D'Alessandro A. and Luzio D. (2014). Time-frequency filtering for seismic waves clustering. Analysis and Modeling of Complex Data in Behavioral and Social Sciences, pp. 1-9. BERLIN: Springer, ISBN/ISSN: 978-3-319-06691-2 ñ DOI: 10.1007/978-3-319-06692-9_1

    Categorie ISI WEB di riferimento

    Computer Science, Interdisciplinary Applications

    Computer Science, Theory & Methods

    Statistics & Probability

    SSD di riferimento

    ING-INF/05 - Sistemi di Elaborazione delle Informazioni

    SECS-S/01 - Statistica

    SECS-S/06 - Metodi matematici dell’economia e delle scienze attuariali e finanziarie

    INF/01 - Informatica

    Responsabile Scientifico/Coordinatore

    Prof.ssa Rosanna Verde

    Componenti

    Sezione Data Science (coordinatore: Prof.ssa Rosanna Verde)

    Antonio Balzanella, Professore di II fascia SECS-S/01

    Andrea Diana, dottorando

    Ferdinando Grillo, dottorando

    Antonio Irpino, Professore di II fascia SECS-S/01

    Elvira Romano, Professore di II fascia SECS-S/01

    Viviana Ventre, Ricercatore a tempo indeterminato SECS-S/06

    Rosanna Verde, Professore di I fascia SECS-S/01

    Veronica Villani, dottoranda

    Collaboratori esterni

    Fabrizio Maturo, Professore di II fascia SECS-S/01, UniCusano

    Francisco A. T. De Carvalho, Full Professor, Universidade Federal de Pernambuco (Brasil)

    Sezione Computer Science (coordinatore: Prof. Mauro Iacono)

    Luigi Piero Di Bonito, dottorando

    Mauro Iacono, Professore di II fascia ING-INF/05 

    Stefano Marrone, Professore di II fascia INF/01

    Fiammetta Marulli, Ricercatore a tempo determinato tipo B INF/01

    Collaboratori esterni

    Lelio Campanile, Professore, cultore della materia ING-INF/05

    Pasquale Cantiello, Tecnologo, Istituto Nazionale di Geofisica e Vulcanologia

    Marco Gribaudo, Professore di II fascia ING-INF/05, Politecnico di Milano

    Alexander H. Levis, Professore emerito, George Mason University

    Michele Mastroianni, Ricercatore a tempo determinato tipo A INF/01, Università degli Studi di Salerno

     
    Settore ERC

    LS2_12 - Biostatistics

    PE_13 - Probability

    PE1_14 - Statistics

    PE1_18 - Scientific computing and data processing

    PE1_21 - Application of mathematics in industry and society

    PE6_1 - Computer architecture, pervasive computing, ubiquitous computing 

    PE6_2 - Computer systems, parallel/distributed systems, sensor networks, embedded systems, cyber-physical systems

    PE6_3 - Software engineering, operating systems, computer languages

    PE6_4 - Theoretical computer science, formal methods, and quantum computing

    PE6_5 - Cryptology, security, privacy, quantum crypto

    PE6_9 - Human computer interaction and interface, visualization and natural language processing

    PE6_10 - Web and information systems, database systems, information retrieval and digital libraries, data fusion

    PE6_11 - Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video)

    PE6_12 - Scientific computing, simulation and modelling tools

    SH1_6 - Econometrics, statistical methods

    SH3_10 - Geographic information systems, spatial data analysis

    SH4_4 - Cognitive and experimental psychology: perception, action, and higher cognitive processes

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