STAD means "city" in Dutch - tribute to the founders' background acquainted at the Leiden University in the Netherlands which countryside was flat long before the globalization. STAD is an agglomeration of persons in the flat world where a new "citizen" can aggregate from almost anywhere. This city contains a lot of "buildings" tocreate and work out ideas, provide statistical science, transfer technology, analyze data with a meta-disciplinary approach, "crossing the bridge" towards other scientific communities. This city contains also "green areas" to enjoy spare time activities together, such as sport, eating and drinking, sharing innovation and enlightenment culture, dreaming the future! Founders STAD at University of Naples Federico II are Roberta Siciliano (mentore), Valerio Tutore, Massimo Aria, Antonio D'Ambrosio, whose first letters of their surnames form, amazingly, another STAD!

Publications

Publications of Methodological and Computational Statistics:

HEISER W.J., D’AMBROSIO A. (2013). Clustering and Prediction of Rankings within a Kemeny Distance Framework. In Berthold, L., Van den Poel, D, Ultsch, A. (eds). Algorithms from and for Nature and Life. pp-19-31. Springer international.

D’AMBROSIO A. (2012). Missing Data Imputation within the Statistical learning Paradigm. Proceedings of the 46th Scientific Meeting Of The Italian Statistical Society.

D’AMBROSIO A., ARIA M., SICILIANO R. (2012). Accurate Tree-based Missing Data Imputation and Data Fusion within the Statistical Learning Paradigm, Journal of Classification, vol. 29(2), pp. 227-258.


PISCITELLI A., D’AMBROSIO A. (2012). Assessing assumptions for data fusion procedures. Proceedings of the 46th Scientific Meeting Of The Italian Statistical Society.

SICILIANO, R., ARIA, M. (2011). Two-Class trees for non-parametric regression analysis. In Fichet, B., Piccolo, D., Verde, R. and Vichi, M. editors Studies in Classification, Data Analysis and Knowledge Organization, (Fichet B., Piccolo D., Verde R. e Vichi M. , eds.), in Series of Studies in Classification, Data Analysis, and Knowledge Organization, Springer-Verlag.



GIORDANO G., ARIA M. (2011). Regression trees with moderating effects. New Perspectives in Statistical Modeling and Data Analysis, eds Ingrassia S., Rocci R., Vichi M., in Studies in Classification, Data Analysis, and Knowledge Organization, Springer-Verlag, ISBN: 978-3-642-11362-8.

D'AMBROSIO A., TUTORE V.A. (2011). Conditional classification trees by weighting the Gini impurity measure, New Perspectives in Statistical Modeling and Analysis, Springer series in Studies in Classification, Data Analysis, and Knowledge Organization, 273-280.

D'AMBROSIO A., PECORARO M. (2011). Multidimensional Scaling as Visualization tool of Web Sequence Rules, in B. Fichet et al. (eds.), Classification and Multivariate Analysis for Complex Data Structures, studies in Classification, Data Analysis, and Knowledge Organization, Springer-Verlag, pp. 307-314.

SICILIANO, R., TUTORE, V., ARIA, M., D’AMBROSIO, A. (2010). Trees with leaves and without leaves in Proceedings of 45th Scientific Meeting of Italian Statistical Society (SIS2010), Padova, ISBN 978 88 6129 566 7.

D'AMBROSIO, A., TUTORE, V.A. (2009). Kemeny's axiomatic approach to find consensus ranking in tourist satisfaction, Statistica Applicata (Italian Journal of Applied Statistics), vol 20(1),  pp. 21-32

ARIA, M. (2009). Parallel Networks for Compositional Longitudinal Data, in Italian Journal of Applied Statistics, Volume 20, N.1, RCE multimedia, ISSN 1125-1964, pag. 5-20.

CONVERSANO C., SICILIANO R. (2009). Incremental Tree-Based Imputation with lexicographic ordering, Journal of Classification, vol. 26, issue 3, pp 361-379.

D'AMBROSIO, A., HEISER, W.J. (2009). Decision Trees for Preference Rankings. Invited talk: Classification and Data Analisys 2009, Book of short papers. CLEUP Padova, 133-136.

TUTORE, V.A., D'AMBROSIO A. (2009).Three-Way Data Analysis by Tree-Based Partitioning. Classification and Data Analisys 2009, Book of short papers.CLEUP Padova, 641-644.

PECORARO, M., SICILIANO, R. (2008). Statistical Methods for User Profiling in Web Usage Mining, in Handbook of Research on Text and Web Mining Technologies, edited by Min Song and Yi-Fang Brook Wu, chapter XXII, IDEA Group. Inc., Hershey, USA.



SICILIANO, R., ARIA, M., D’AMBROSIO, A. (2008). Posterior Prediction Modelling of Optimal Trees, in Proceedings in Computational Statistics (COMPSTAT 2008), 18th Symposium Held in Porto, Portugal, Brito, Paula (Ed.), Springer-Verlag, pp. 323-334. 



CONVERSANO, C., SICILIANO, R. (2008). Statistical Data Editing, in Wang J. (eds.), Encyclopedia of Data Warehousing and Data Mining,IDEA Group. Inc., Hershey, USA, volume 2, 2nd edition.

SICILIANO, R., CONVERSANO, C. (2008). Decision Tree Induction, in Wang J. (eds.), Encyclopedia of Data Warehousing and Data Mining,IDEA Group. Inc., Hershey, USA, volume 2, 2nd edition.

ARIA, M., D’AMBROSIO, A., (2008). A non parametric pre-grafting procedure for data fusion, In Proceedings of Metodi, Modelli e Tecnologie dell’Informazione a Supporto delle Decisioni, University of Salento, Lecce, 18-20 september, pag. 333-336, ISBN 978-88-8305-060-2.

D’AMBROSIO, A., PECORARO, M. (2008). Web Structure Mining through implicit behaviors via Multidimensional Scaling, in Proceedings of the First joint meeting of the Société Francophone de Classification and the Classification and Data Analysis Group of the Italian Statistical Society (SFC-CLADAG 2008), pp. 261-264.

GIORDANO, G., D’AMBROSIO, A. (2008). Multi-Class Budget Tree as weak learner for ensemble procedures,  proceedings of the XLIV scientific meeting of the Italian Statistical Society.

TUTORE, V.A., SICILIANO, R., ARIA, M. (2007). 3-Way Trees, inProceedings of the 6th Scientific Meeting of the Classification and Data Analysis Group (Macerata 12-14 september, 2007).

D'AMBROSIO, A., ARIA, M., SICILIANO, R. (2007). Robust Incremental Trees for Missing Data Imputation and Data Fusion, in Proceedings of the 6th Scientific Meeting of the Classification and Data Analysis Group(Macerata 12-14 september, 2007).

TUTORE, V.A., SICILIANO, R., ARIA, M. (2007). Conditional Classification Trees using Instrumental Variables, in Proceedings of the 7th IDA2007 Conference (Ljubljana, 6-8 September, 2007), Lecture Notes in Computer Science Series of Springer.

SICILIANO, R., ARIA, M., D'AMBROSIO, A. (2006), Boosted incremental tree-based imputation of missing data. In Proceedings in Data Analysis, Classification and the Forward Search. Springer series in Studies in Classification, Data Analysis, and Knowledge Organization. Springer-Verlag, pp 271-278.

D'AMBROSIO, A., ARIA, M., SICILIANO, R. (2006). Robust incremental imputation for data fusion, in Proceedings of the Workshop of the ERCIM WG on Matrix Computations and Statistics, Salerno, Italy, September 2-3, 2006.

TUTORE, V.A., SICILIANO, R, ARIA, M. (2006). Three Way Segmentation in Proceedings of Knowledge Extraction and Modelling (KNEMO06) IASC INTERFACE IFCS Workshop (Capri, September 4th-6th 2006).

CONVERSANO, C., SICILIANO, R. (2005). Statistical Data Editing, in Wang J. (eds.), Encyclopedia of Data Warehousing and Data Mining,IDEA Group. Inc., Hershey, USA, volume 2, pag. 359-361.

SICILIANO, R., CONVERSANO, C. (2005). Decision Tree Induction, in Wang J. (eds.), Encyclopedia of Data Warehousing and Data Mining,IDEA Group. Inc., Hershey, USA, volume 2, pag. 242-248.

PETRAKOS, G., CONVERSANO, C., FARMAKIS, G., MOLA, F., SICILIANO, R., STAVROPOULOS, P. (2004). New ways to specify data edits, Journal of Royal Statistical Society, Ser. A, 167, Part 2, 249-274.

SICILIANO, R., ARIA, M., CONVERSANO, C. (2004). Harvesting trees: methods, software and applications. In Proceedings in Computational Statistics: 16th Symposium of IASC, held Prague, August 23-27. 2004 (COMPSTAT2004), Eletronical Edition (CD) Physica-Verlag, Heidelberg.

ARIA, M., MOIJAART, A., SICILIANO, R. (2003). Neural Budget Networks of Sensorial Data, in M. Schader, W. Gaul, M. Vichi (eds.):Between Data Science and Applied Data Analysis, Studies in Classification, Data Analysis, and Knowledge Organization, Springer, Berlin (D).

ARIA, M., SICILIANO, R. (2003), Learning from Trees: Two-Stage Enhancements, CLADAG 2003, Book of Short Papers (Bologna, September 22-24, 2003), CLUEB, Bologna, 21-24.

CONVERSANO, C., DI BENEDETTO, D., SICILIANO, R. (2003), The Clockwise Trees through Visual Multivariate Splitting, CLADAG 2003, Book of Short Papers (Bologna, September 22-24, 2003), CLUEB, Bologna, 113-117.

CONVERSANO, C., MOLA, F. SICILIANO, R., (2003), How to harvest fruits from trees, Conferenza SIS: Analisi Statistica Multivariata per le scienze economiche-sociali, le scienze naturali e la tecnologia (Napoli, June 2003), RCE Edizioni, Napoli, 119-131.

ARIA, M., MOOIJAART, A., SICILIANO, R., Neural Budget NetworksProceedings of International Conference on Multiple Classifier Systems, Chia (Cagliari), June 24-26, Italy, Lecture Notes in Computer Science, Physica Verlag.

MOLA, F., SICILIANO, R. (2002). Discriminant Analysis and Factorial Multiple Splits in Recursive Partitioning for Data Mining, in Roli, F., Kittler, J. (eds.): Proceedings of International Conference on Multiple Classifier Systems, Chia (Cagliari, June 24-26, 2002), 118-126, Lecture Notes in Computer Science, Springer, Heidelberg.

CAPPELLI, C., MOLA, F., SICILIANO, R. (2002). A Statistical Approach to Growing a Reliable Honest Tree, Computational Statistics and Data Analysis, 38, 285-299, Elsevier Science.

ARIA M., MOOIJAART, A., SICILIANO, R. (2002). Multiple Neural Budget Networks for Sensorial Data Analysis, Proceedings of GFKI(Mannheim, July 22-24, 2002), Germany, Physica Verlag.

CONVERSANO, C., SICILIANO, R., MOLA, F. (2002). Generalized Additive Multi-Mixture Models for Data Mining, invited lecture at the International Workshop on Non Linear Methods and Data Mining (Roma, October 2000), Computational Statistics and Data Analysis, 38, 487-500, Elsevier Science.

ARIA, M., MOLA, F., SICILIANO, R. (2002). Growing and Visualizing Prediction Paths Trees in Market Basket Analysis, Proceedings of COMPSTAT 2002 (Berlin, August 24-28, 2002), Germany, Psysica Verlag.

CONVERSANO, C., MOLA, F., SICILIANO, R. (2001). Partitioning and Combined Model Integration for Data Mining, presented at the Symposium on Data Mining and Statistics (Augsburg, November 2000), Journal of Computational Statistics, 16, 323-339, Physica Verlag, Heidelberg (D).

CONVERSANO, C., MOLA, F., SICILIANO, R. (2001). Partitioning and Combined Model Integration for Data Mining, presented at the Symposium on Data Mining and Statistics (Augsburg, november 2000), Journal of Computational Statistics, 16, 323-339, Physica Verlag, Heidelberg (D).

CONVERSANO, C., SICILIANO, R., MOLA, F. (2000). Supervised Classifier Combination through Generalized Additive Multi-Model, in F. Roli, J. Kittler (Eds.): Proceedings of the First International Workshop on Multiple Classifier Systems, Lecture Notes in Computer Science, Physica Verlag, Heidelberg (D), 167-176.

CONVERSANO, C., MOLA, F., SICILIANO, R. (2000). Generalized Additive Multi-Model for Classification and Prediction, in H.A.L. Kiers, J.P. Rasson, P.J.F. Groen, M. Shader (Eds.): Data Analysis, Classification and Related Methods,Springer Verlag, Berlin (D), 205-210.

SICILIANO, R., MOOIJAART, A. (2000). Unconditional Latent Budget Analysis: A Neural Network Approach, in S. Borra, R. Rocci, M. Vichi, M. Schader (Eds.): Advances in Classification and Data Analysis, Berlin (D), Springer-Verlag, 127-136.

CAPPELLI, C., MOLA, F., SICILIANO, R. (2000). Selecting Regression Tree Models: a Statistical Testing Procedure, in S. Borra, R. Rocci, M. Vichi, M. Schader (Eds.): Advances in Classification and Data Analysis, Berlin (D), Springer-Verlag, 249-256.

LAURO, N.C., SICILIANO, R. (2000). Analyse non symmetrique des correspondances pour des tables de contingences, in J. Moreau, P.A. Doudin, P. Cazes (eds.): L'Analyse des Correspondances et les techniques connexes, partie III, Springer Verlag, 183-210.

SICILIANO, R., MOLA, F. (2000). Multivariate Data Analysis through Classification and Regression Trees, Computational Statistics and Data Analysis, 32, 285-301, Elsevier Science.

TAMBREA, N.C., SICILIANO, R. (1999). Exploratory Analysis of Three-Way Data by Simultaneous Latent Budget Model, Journal of Applied Stochastic Models in Business and Industry, 15, 469-484, J. Wiley & Sons.

SICILIANO, R. (1999). Latent budget trees for multiple classification, in M. Vichi, P. Optitz (Eds.): Classification and Data Analysis: Theory and Application, Springer Verlag, Heidelberg (D), 121-130.

MOLA, F., SICILIANO, R. (1998). A general splitting criterion for classification trees, Metron, 56, 3-4.

PALUMBO, F., SICILIANO, R. (1998). Factorial Discriminant Analysis and Probabilistic Models, Metron, 56, 3-4.

SICILIANO, R. (1998). Exploratory versus Decision Trees, relazione invitata a COMPSTAT '98 (Bristol, August 24-28, 1998), in R. Payne, P. Green (Eds.): Proceedings in Computational statistics: 13th Symposium of COMPSTAT, Physica Verlag, Heidelberg (D), 113-124.

CAPPELLI, C., MOLA, F., SICILIANO, R. (1998). An alternative pruning procedure based on the impurity-complexity measure, in R. Payne, P. Green (Eds.): Proceedings in Computational Statistics: 13th Symposium of COMPSTAT (Bristol, August 24-28, 1998, Physica Verlag, Heidelberg (D), ), 221-226.

KLASCHKA, J., SICILIANO, R., ANTOCH, J. (1998). Computational Enhancements in Tree-Growing Methods, invited lecture at IFCS '98 (Roma, July 21-24, 1998), in A. Rizzi, M. Vichi, H.H. Bock (Eds.): Advances in Data Science and Classification: Proceedings of the 6th Conference of the International Federation of Classification Society, Springer-Verlag, Berlin Heidelberg (D), 295-302.

SICILIANO, R., MOLA, F. (1998). Ternary Classification Trees: a Factorial Approach, in M. Greenacre, J. Blasius (Eds.): Visualization of Categorical Data, cap. 22, , Academic Press, San Diego (CA), 311-323.

SICILIANO, R., MOLA, F. (1998). On the Behaviour of Splitting Criteria in Classification Trees, in C. Hayashi, N. Ohsumi, K. Yajima, Y. Tanaka, H.-H. Bock, Y. Baba (Eds.): Data Science, Classification and Related Methods: Proceedings of the Fifth Conference of the International Federation of Classification Societies IFCS '96 (Kobe, March 27-30, 1996), Springer-Verlag, Tokyo (J), 191-198.

MOLA, F., SICILIANO, R. (1998). Visualizing Data in Tree-Structured Classification, in C. Hayashi, N. Ohsumi, K. Yajima, Y. Tanaka, H.-H. Bock, Y. Baba (Eds.): Data Science, Classification and Related Methods: Proceedings of the Fifth Conference of the International Federation of Classification Societies IFCS '96 (Kobe, March 27-30, 1996), Springer-Verlag, Tokyo (J), 223-230.

DAVINO, C., MOLA, F., SICILIANO, R., VISTOCCO, D. (1998). A Statistical Approach to Neural Networks, versione estesa della relazione invitata per NGUS '97 (Bilbao, September 10-12, 1997), in K. Fernandez-Aguirre, A. Morineau (Eds): Analyses Multidimensionnelles des Données- IV Congrés International NGUS'97, CISIA Ceresta, St. Mandé (F), 37-51.

MOLA, F., SICILIANO, R. (1997). A Fast Splitting Procedure for Classification and Regression Trees, Statistics and Computing, 7, Chapman Hall, 208-216.

SICILIANO, R., MOOIJAART, A. (1997). Three-factor association models for three-way contingency tables, Computational Statistics and Data Analysis, 24(3), Elsevier North Holland, Amsterdam (NL), 337-356.

CAPPELLI, C., SICILIANO, R. (1997). Strategies for choosing the best decision tree, versione estesa del contributo presentato a NGUS '97 (Bilbao, 10-12 settembre), in K. Fernandez-Aguirre, A. Moirneau (Ed.): Analyse Multidimensionnelles des Données - IV Congrés International NGUS '97, 101-111, CISIA Ceresta, St. Mandé, France.

MOLA, F., KLASCHKA, J., SICILIANO, R. (1996). Logistic Classification Trees, in A. Prat (Ed.): Proceedings in Computational Statistics: COMPSTAT '96 (Barcellona, August 24-28, 1996), , Physica-Verlag, Heidelberg (D), 373-378.

SICILIANO, R., MOLA (1996). Regression Trees using the Test for Total Homogeneity, in A. Prat (Ed.): Proceedings in Computational Statistics: COMPSTAT '96 (Barcellona, August 24-28, 1996), Short Communications and Posters, Physica-Verlag, Heidelberg (D), 113-114.

SICILIANO, R., MOLA, F. (1996). A Fast Regression Tree Procedure, in Forcina, A., Marchetti, G.M., Hatzinger, R., Galmacci, G. (Ed.): Statistical Modelling, Proceedings of the 11th International Workshop on Statistical Modeling (Orvieto, 15-19 luglio), 332-340, Graphos, Città di Castello.

MOLA, F., SICILIANO, R. (1996). L'analisi della stabilità nella segmentazione binARIA a due stadi, Atti della XXXVIII Riunione Scientifica della Società Italiana di Statistica, 77-84, Maggiolo, Rimini.

SICILIANO, R., VAN DER HEIJDEN, P.G.M. (1994). Simultaneous Latent Budget Analysis of a Set of Multidimensional Contingency Tables,Metron, LII, 1-2,155-180.

MOLA, F., SICILIANO, R. (1994). Alternative strategies and CATANOVA testing in two-stage binary segmentation, in E. Diday, Y. Lechevallier, M. Schader, P. Bertrand, B. Burtschy (Eds.): New Approaches in Classification and Data Analysis: Proceedings of IFCS '93, Springer Verlag, Heidelberg (D), 316-323.

SICILIANO, R., MOLA, F. (1994). Modelling for Recursive Partitioning and VARIAble Selection, in R. Dutter, W. Grossmann (Eds.): Proceedings in Computational Statistics: COMPSTAT '94 (Vienna, August 24-28, 1994), , Physica Verlag, Heidelberg (D), 172-177.

BALBI, S., SICILIANO, R. (1994). Analisi longitudinale non simmetrica di tabelle di contingenza a tre vie, Atti della XXXVII Riunione Scientifica della Società Italiana di Statistica, II, 345-356, CISU, Roma.

SICILIANO, R., MOOIJAART, A., VAN DER HEIJDEN, P.G.M. (1993). A probabilistic model for nonsymmetric correspondence analysis and prediction in contingency tables, Journal of Italian Statistical Society, 2, 1, Giardini Editori, Pisa, 85-106.

SICILIANO, R. (1992). Reduced-Rank Models for Dependence Analysis, relazione invitata a International Workshop on Multidimensional Data Analysis: Meeting of Dutch & Italian Schools, Statistica Applicata, Italian Journal of Applied Statistics, 4-4, 481-501.

MOLA, F., SICILIANO, R. (1992). A two-stage predictive splitting algorithm in binary segmentation, in Y. Dodge, J. Whittaker. (Eds.):Computational Statistics: COMPSTAT '92, 1, Physica Verlag, Heidelberg (D), 179-184.

SICILIANO, R. (1990). Asymptotic distribution of eigenvalues and statistical tests in nonsymmetric correspondence analysis, Statistica Applicata. Italian Journal of Applied Statistics, 2-3, 259-276.

SICILIANO, R., LAURO, N.C.. MOOIJAART, A. (1990). Exploratory approach and Maximum Likelihood Estimation of Models for Non Symmetrical Analysis of Two-Way Multiple Contingency Tables, in K. Momirovic, V. Mildner (Eds.): Proceedings in Computational Statistics: COMPSTAT '90 (Dubrovnik, August 30 - September 3, 1990), Physica Verlag, Heidelberg (D), 157-162.

LAURO, N.C., SICILIANO, R. (1989). Exploratory methods and modelling for contingency tables: an integrated approach, Statistica Applicata. Italian Journal of Applied Statistics, 1, 5-32.

SICILIANO, R. (1989). Non symmetrical logarithmic analysis for contingency tables, in A. Decarli, B.J. Francis, R. Gilchrist, G.U.H. Seeber (Eds.): Statistical Modelling, Proceedings of GLIM 89 and the 4th International Workshop on Statistical Modelling (Trento, July 17-21, 1989), Springer Verlag, Berlin Heidelberg (D), 278-285.


Publications of Applied Statistics:

ADAMO D., SCHIAVONE V., ARIA M., LEUCI S., RUOPPO E., DELL’AVERSANA G., MIGNOGNA M. (2013). Sleep disturbance in patients with burning mouth syndrome: a case-control study, Journal of Orofacial Pain, in press, ISI Impact Factor: 2.588.

CALDARELLI A., FIONDELLA C., MAFFEI M., SPANO R., ARIA M. (2013) CEO performance evaluation systems: empirical findings from the italian regional health services in press su Public Money and Management, Wiley, ISI Impact Factor: 0.779.

SICILIANO R., D’AMBROSIO A. (2012). Statistical monitoring of tourism in the knowledge era. In Morvillo A. (Ed.). Advances in Tourism Studies. McGrow-Hill, pp. 231-258.

FORTUNA G., LOZADA-NUR F., CHAINANI-WU N., ARIA M., CEPEDA-VALDES R., POLLIO A., MARINKOVICH M.P., MMARTINEZ-SALAZAR A.E., MIGNOGNA M., BRUCKNER A.L., SALAS-ALANIS J.C. (2012) Epidermolysis bullosa Oropharyngeal Severity score (EBOS): a multicentric development and validation in press su Journal of the American Academy of Dermatology, Elsevier, DOI: 10.1016/j.jaad.2012.04.009, ISI Impact Factor: 4.274.

ARIA, M., D’AMBROSIO, A., SICILIANO, R., TUTORE, V.A. (2011). Indagine statistica sulle aspettative e priorità per soddisfare il turista a Napoli, in Rapporto sul turismo Italiano, 2011, edizione XVII, a cura di Becheri, E., Franco Angeli, pp. 449-470.

MIGNOGNA M., FORTUNA G., POLLIO A., ARIA M., ADAMO D., LEUCI S., RUOPPO E., (2011) Multiple myeloma versus breast cancer patients with bisphosphonates-related osteonecrosis of the jaws: a comparative analysis of response to treatment and predictors of outcome, Journal of Oral Pathology and Medicine, Wiley-Blackwell, DOI: 10.1111/j.1600-0714.2011.01095.x, ISSN: 1600-0714, ISI Impact Factor: 2.075.

MONTELLA A., Aria M., D’AMBROSIO A., MAURIELLO F. (2011). Analysis of Powered Two-wheeler crashes in Italy by classification trees and rules discovery, in Accident Analysis & Prevention, Springer Elsevier, DOI: 10.1016/j.aap.2011.04.025, ISI Impact Factor: 2.350.

MONTELLA A., ARIA M., D’AMBROSIO A., MAURIELLO F. (2011). Data Mining Techniques for Exploratory Analysis of Pedestrian Crashes, Transportation Research Record – Journal of Transportation Research Board, Vol. 2237/2011, pp.107-116. DOI: 10.3141/2237-12, SCOPUS - SNIP: 0.719.

MONTELLA A., ARIA M., D’AMBROSIO A., GALANTE F., MAURIELLO F., PERNETTI M. (2011). Simulator evaluation of drivers' speed, deceleration and lateral position at rural intersections in relation to different perceptual cues, in Accident Analysis & Prevention, Springer Elsevier, DOI: 10.1016/j.aap.2011.05.030, ISI Impact Factor: 2.350.

MONTELLA, A., ARIA, M., D’AMBROSIO, A., GALANTE, F., MAURIELLO, F., PERNETTI, M. (2010). Perceptual Measures to Influence Operating Speeds and Reduce Crashes at Rural Intersections, Transportation Research Record – Journal of Transportation Research Board, vol. 2149, pp. 11-20, ISBN 9780309142809, SCOPUS - SNIP: 0.719.

GALANTE F., MAURIELLO, F., MONTELLA A., PERNETTI M., ARIA, M., D’AMBROSIO A. (2010). Traffic Calming Along Rural Highways Crossing Small Urban Communities: a Driving Simulator Experiment in Accident Analysis & Prevention, Springer Elsevier, doi:10.1016/j.aap.2010.03.017, ISI Impact Factor: 2.350.

ARIA, M., SICILIANO, R. (2009). Il metodo di campionamento, in Monitoraggio sul controllo di gestione delle PMI della provincia di Napoli, eds. Catuogno S., Coppola R., Mauriello P. e Orefice F., Centro Studi dell’Ordine dei Dottori Commercialisti di Napoli, pag. 5-10.

ARIA, M., GALLO, S., MUROLO, F., SICILIANO, R. (2008). Le leve discriminanti della soddisfazione: il caso SEPSA, in Rivista di Economia e Statistica del Territorio, Fondazione Istituto Tagliacarne, Roma, ISSN 1971-0380, N.1 gennaio-aprile 2008.

ARIA, M., SICILIANO, R., SIBILIO, R., GARGIULO, G., GIORDANO, G., D’AMBROSIO, A. (2008) Osservare la realtà per combattere l’esclusione: Focus sulla terza età. Progetto SOCIALNET, ed. DMS, University of Naples Federico II.

ARIA, M, MIGLIORE F., CASTIELLO, M. (2008) Problematica della conciliabilità tra lavoro e l’essere donna nell’area dei Centri per l’Impiego di Casarano e Tricase (Lecce). Rapporto finale della ricerca LAVORO e DONNE, POR mis. 3.17 finanziato dalla Regione Puglia.

SICILIANO, R., SIBILIO, R., ARIA, M.. (2008). Campagna d’Ascolto del Comune di Napoli: L’indagine statistica, Piano strategico della Città di Napoli, ed. DMS, Università di Napoli Federico II.

SICILIANO, R., ARIA, M., TUTORE, V. (2008). La Risorsa Turismo Parte I°. Quaderno n.5 del Centro Studi dell’Unione Industriali di Napoli, ed. Guida, Napoli, pag. 1-154.