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RECENT PUBLICATIONS

2022

  • De Stefano, C., Ferrigno, L., Fontanella, F. et al. Evolutionary Computation to Implement an IoT-Based System for Water Pollution Detection. SN COMPUT. SCI. 3, 111, 2022.
  • I. Bakurov, M. Castelli, F. Fontanella, A. Scotto di Freca, L. Vanneschi, A novel binary classification approach based on geometric semantic genetic programming, Swarm and Evolutionary Computation, 69, 101028, 2022.

2021

  • Alicandro R., Lazzaroni G., Palombaro M., Derivation of linear elasticity for a general class of atomistic energies, SIAM J. Math. Anal., vol. 53 (5), 2021
  • Corbo Esposito A., Faella L., Prakash R., Piscitelli G., Tamburrino A. , Monotonicity Principle for Nonlinear Electrical Conductivity Tomography, INVERSE PROBLEMS, 37 (4), 045012, 2021
  • D. Lacitignola, F. Diele, “Using awareness to Z-control a SEIR model with overexposure: insights on Covid-19 pandemic”, Chaos Solitons & Fractals, vol. 150, 111063, 2021.
  • D. Lacitignola, I. Sgura, B.Bozzini, “Turing-Hopf patterns in a morphochemical model for electrodeposition with cross-diffusion”, Applications in Engineering Science, vol. 5, 100034, 2021.
  • D. Lacitignola, G. Saccomandi, “Managing awareness can avoid hysteresis in disease spread: an application to coronavirus Covid-19 “, Chaos, Solitons & Fractals, vol. 144, 110739, 2021.
  • D. Lacitignola, “Handling Hysteresis in a Referral Marketing Campaign with Self-information. Hints from Epidemics”. Mathematics, vol.9 (6), 680, 2021.
  • M. Molinara, A. Bria, S. De Vito, C. Marrocco, “Artificial intelligence for distributed smart systems”, Pattern Recognition Letters, Volume 142, February 2021, Pages 48-50, doi.org/10.1016/j.patrec.2020.12.006
  • N.D. Cilia, T. D’Alessandro, C. De Stefano, F. Fontanella. “Deep transfer learning algorithms applied to synthetic drawing images as a tool for supporting Alzheimer’s disease prediction”, Machine Vision and Application, in press, 2021.
  • N.D. Cilia, T. D’Alessandro, C. De Stefano, F. Fontanella, M. Molinara, “From online handwriting to synthetic images for Alzheimer’s disease detection using a deep transfer learning approach”, IEEE Journal of Biomedical and Health Informatics, August 2021, doi.org/10.1109/JBHI.2021.3101982.
  • N.D. Cilia, C. De Stefano, F. Fontanella, A. Scotto di Freca. “Feature selection as a tool to support the diagnosis of cognitive impairments through handwriting analysis”, IEEE Access 9: 78226-78240, 2021.
  • N. D. Cilia, C. De Stefano, C. Marrocco, F. Fontanella, M. Molinara and A. S. di Freca, “Deep Transfer Learning for Alzheimer’s disease detection,” 25th International Conference on Pattern Recognition (ICPR), pp. 9904-9911, doi: 10.1109/ICPR48806.2021.9412603, 2021.
  • N.D. Cilia, C. De Stefano, F. Fontanella, A. Scotto di Freca. “Handwriting-Based Classifier Combination for Cognitive Impairment Prediction”. ICPR, AIHA Workshops, Lecture notes in computer science (1): 587-599, 2021.
  • N.D. Cilia, C. De Stefano, F. Fontanella, I. Marthot-Santaniello, A. Scotto di Freca. “PapyRow: A Dataset of Row Images from Ancient Greek Papyri for Writers Identification”. ICPR Workshops (7): 223-234., 2021.
  • N.D. Cilia, C. De Stefano, F. Fontanella, A. Scotto di Freca. “Handwriting-Based Classifier Combination for Cognitive Impairment Prediction”. ICPR, 2020 Workshops, Lecture notes in computer science (1): 587-599, 2021.
  • A. Bria, C. Marrocco, F. Tortorella. “Sinc-Based Convolutional Neural Networks for EEG-BCI-Based Motor Imagery Classification”. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12661 LNCS, pp. 526-535, 2021.
  • G. Golluccio, D. Di Vito, A. Marino, A. Bria, G. Antonelli. “Task-motion planning via tree-based Q-learning approach for robotic object displacement in cluttered spaces”, in Proceedings of the 18th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2021, pp. 130-137, 2021.
  • I. Bakurov, M. Castelli, O. Gau, F. Fontanella, L. Vanneschi. “Genetic programming for stacked generalization”, Swarm and Evolutionary Computation, 65, art. no. 100913, 2021.
  • F. Fontanella, M. Molinara, A. Gallozzi, M. Cigola, L.J. Senatore, R. Florio, P. Clini, F. Celis D’amico, (2020) “HeGo, a social game as a tool for cultural heritage valorization: the case study of the Atina historical center”.Journal on Computing and Cultural Heritage, 14 (2), art. no. 3431926, 2021.

2020:

  • D. Lacitignola, “Dai pattern ai frattali, passando per il caos”, Ithaca: Viaggio nella Scienza, vol. 15, 125-134, 2020.
  • Chacouce Kaled, Faella Luisa, Carmen Perugia, Junction of Quasi-Stationary Ferromagnetic Wires, Atti Accad. Naz. Lincei Rend. Lincei Mat. Appl., 2020, 31(1), pp. 25-56, 2020
  • Faella Luisa, Khludnev, A., Corbo Esposito, “Optimal Control of Parameters for Elastic Body with Thin Inclusions”, Journal of Optimization Theory and Applications, 184(1), pp. 293-314, 2020
  • C. Marangi, F. Casella, F. Diele, D. Lacitignola, A. Martiradonna, A. Provenzale, S. Ragni, “Mathematical tools for controlling invasive species in Protected Areas” in Mathematical Approach to Climate Change and its Impacts, 211-237, Springer INdAM Series book, vol. 38, 2020.
  • C. Bourelly, A. Bria, L. Ferrigno, L. Gerevini, C. Marrocco, M. Molinara, G. Cerro, M. Cicalini, A. Ria, “A Preliminary Solution for Anomaly Detection in Water Quality Monitoring” (2020), Proceedings – 2020 IEEE International Conference on Smart Computing, SMARTCOMP 2020, 14-17 settembre 2020, DOI: 10.1109/SMARTCOMP50058.2020.00086.
  • Cilia, N.D.; De Stefano, C.; Fontanella, F.; Marrocco, C.; Molinara, M.; Freca, A.S. (2020) “An Experimental Comparison between Deep Learning and Classical Machine Learning Approaches for Writer Identification in Medieval Documents”. Journal of Imaging 2020, 6, 89, DOI: doi.org/10.3390/jimaging6090089
  • F. Fontanella, F. Colace, M. Molinara, A. Scotto Di Freca, F. Stanco (2020) “Pattern recognition and artificial intelligence techniques for cultural heritage”, Pattern Recognition Letters, Volume 138, October 2020, Pages 23-29, DOI: doi.org/10.1016/j.patrec.2020.06.018
  • A. Bria, G. Cerro, M. Ferdinandi, C. Marrocco, M. Molinara (2020). An IoT-ready solution for automated recognition of water contaminants. DOI: 10.1016/j.patrec.2020.04.019 pp 188-195. In Pattern Recognition Letters”, Volume 135, July 2020, ISSN: 0167-8655.
  • Molinara M., Ferdinandi M., Cerro G., Ferrigno L., Massera E. (2020). “An End-to-End Indoor Air Monitoring System Based on Machine Learning and SENSIPLUS Platform”. DOI: 10.1109/ACCESS.2020.2987756. ISSN: 21693536. pp 72204-72215, Volume 8, IEEE Access.
  • Savelli, B.; Bria, A.; Marrocco, C.; Tortorella, F; Molinara, M. (2020). A multi-context CNN ensemble for small lesion detection. DOI:10.1016/j.artmed.2019.101749. pp.1-13. In ARTIFICIAL INTELLIGENCE IN MEDICINE – ISSN:0933-3657 vol. 103
  • Cilia N. D., De Stefano C., Fontanella F., Marrocco C., Molinara M., Scotto Di Freca A. (2020). An end-to-end deep learning system for medieval writer identification. PATTERN RECOGNITION LETTERS, vol. 129, p. 137-143, ISSN: 0167-8655, doi: 10.1016/j.patrec.2019.11.025
  • Cilia N. D., De Stefano C., Fontanella F., Molinara M., Scotto di Freca A. (2020). “What is the minimum training data size to reliably identify writers in medieval manuscripts?” PATTERN RECOGNITION LETTERS, vol. 129, p. 198-204, ISSN: 0167-8655, doi: 10.1016/j.patrec.2019.11.030
  • . Cilia N.D., De Stefano C., Fontanella F., “Novel mutation operators of a variable-length representation for EC-based feature selection in high dimensional data”. ICIC (1): 53-63, 24, 2020.
  • Cilia N.D., De Stefano C., Fontanella F., Di Freca A.S. “Using Genetic Algorithms for the Prediction of Cognitive Impairments”. EvoApplications. Lecture Notes in Computer Science, vol 12104. Springer, Cham, pp. 479-493. 25, 2020.
  • Cilia N.D., De Stefano C., Fontanella F., Scotto di Freca A., “How words choise affect cognitive impairment detection by handwriting analysis: a preliminary study”, Communications in Computer and Information Science (CCIS), Springer, WIVACE 113- 123, 2020.

2019

  • Faella L., Perugia C., Monsurrò S. , Exact Controllability for Evolutionary Imperfect Transmission Problems. J. Math. Pures Appl. 122, 235-271, 2019
  • D. Lacitignola, I. Sgura, B. Bozzini, T. Dobrovolska, I. Krastev, “Spiral waves on the sphere for an alloy electrodeposition model”, Communications in Nonlinear Science and Numerical Simulation, vol. 79, 104930, 2019
  • C. M. Baker, F. Diele, D. Lacitignola, C. Marangi, A. Martiradonna, “Optimal control of invasive species through a dynamical systems approach”, Nonlinear Analysis: Real World Applications, vol. 49, 45-70, 2019
  • D.Lacitignola, F. Diele, “On the Z-type control of backward bifurcations in epidemic models”, Mathematical Biosciences, vol. 315, 108215, 2019
  • Betta, Giovanni, Cerro, Gianni, Ferdinandi, Marco, Ferrigno, Luigi, Molinara, Mario (2019). Contaminants detection and classification through a customized IoT-based platform: A case study. IEEE INSTRUMENTATION & MEASUREMENT MAGAZINE, vol. 22, p. 35-44, ISSN: 1094-6969, doi: 10.1109/MIM.2019.8917902
  • Cilia N.D., De Stefano C., Fontanella F., Scotto di Freca A. (2019). “A ranking-based feature selection approach for handwritten character recognition”. Pattern Recognition Letters, 121, pp. 77-86, 2019.
  • Cilia N.D., De Stefano C., Fontanella F., Molinara M., Scotto di Freca A., “A PageBased Reject Option for Writer Identification in Medieval Books”, Lecture Notes in Computer Science, 11808 LNCS, pp. 187-197. 27, 2019.
  • Cilia N.D., De Stefano C., Fontanella F., Scotto di Freca A., “Improving Handwritten Character Recognition by Using a Ranking-Based Feature Selection Approach”, Lecture Notes in Computer Science, 11401 LNCS, pp. 902-910. 28, 2019.
  • Cilia N.D., De Stefano C., Fontanella F., Molinara M., Scotto di Freca A., “Handwriting Analysis to Support Alzheimer’s Disease Diagnosis: A Preliminary Study”, Notes in Computer Science, 11679 LNCS, pp. 143-151. 29, 2019.
  • Cilia N.D., De Stefano C., Fontanella F., Molinara M. Scotto di Freca A., “Minimizing Training Data for Reliable Writer Identification in Medieval Manuscripts”, Notes in Computer Science ,11808 LNCS, pp. 198-208. 30, 2019.
  • Cilia N.D., De Stefano C., Fontanella F., Scotto di Freca A., Using handwriting features to characterize cognitive impairment, Lecture Notes in Computer Science, 11752 LNCS, pp. 683-693. 31, 2019.
  • Cilia N.D., De Stefano C., Fontanella F., Scotto di Freca A., “Variable-Length Representation for EC-Based Feature Selection in High-Dimensional Data”, Lecture Notes in Computer Science, 11454 LNCS, pp. 325-340. 32, 2019.
  • Cilia N.D., De Stefano C., Fontanella F., Molinara M. Scotto di Freca A., “A Two-Step System Based on Deep Transfer Learning for Writer Identification in Medieval Books”, Lecture Notes in Computer Science, 11679 LNCS, pp. 305-316, 2019.
  • Cilia N.D., De Stefano C., Fontanella F., Scotto di Freca A., “La spiegazione nel machine learning: un caso neuroscientifico”. ed. Gagliardi F. Cruciani M. Filosofia, Medicina e cognizione. La mente e i sistemi cognitivi. Aracne edizioni. 135-162, 2019.
  • Cilia N.D., De Stefano C., Fontanella F., Scotto di Freca A., “An Experimental Comparison of Feature-Selection and Classification Methods for Microarray Datasets”, Information, 10(3): 109. 8, 2019.
  • Cilia N.D. “L’evoluzione di un’ipotesi nell’Intelligenza Artificiale”. SYTHEZESIS, 191-214. 9, 2019.
  • Scarpato N. Cilia N.D, Romano M. “Reachability Matrix Ontology: A Cybersecurity Ontology”, Applied Artificial Intelligence, 33(7), pp. 643-655, 2019.

2018

  • Alicandro R., Dal Maso G., Lazzaroni G., Palombaro M., Derivation of a linearised elasticity model from singularly perturbed multiwell energy functionals, Arch. Rational Mech. Anal., vol. 230, p. 1–45, 2018
  • Alicandro R., Lazzaroni G., Palombaro, Derivation of a rod theory from lattice systems with interactions beyond nearest neighbours, Networks and Heterogeneous Media, vol. 13, p. 1-26, 2018
  • Faella L., Perugia C., Monsurrò S.. Homogenization of imperfect transmission problems: the case of weakly converging data. DIFFERENTIAL AND INTEGRAL EQUATIONS, vol. 31, p. 595-621, 2018
  • D. Lacitignola, “Bifurcations of equilibria in a mathematical model for metal growth”, Atti della Accademia Peloritana dei Pericolanti-Classe di Scienze Fisiche, Matematiche e Naturali, vol. 96, 2018
  • D. Lacitignola, B. Bozzini, R. Peipmann, I. Sgura, “Cross-diffusion effects on a morphochemical model for electrodeposition”, Applied Mathematical Modelling, vol. 57, 492-513, 2018
  • A.Bria, C.Marrocco, L.R.Borges, M.Molinara, A.Marchesi, J.J.Mordang, N.Karssemeijer, F.Tortorella (2018), “Improving the Automated Detection of Calcifications Using Adaptive Variance Stabilization”, IEEE Transactions on Medical Imaging, Volume 37, Issue 8, pp 1857-1864, 2018, doi: 10.1109/TMI.2018.2814058
  • G.Cerro, M.Ferdinandi, L.Ferrigno, M.Laracca, M.Molinara (2018), “Metrological characterization of a novel microsensor platform for activated carbon filters monitoring”, IEEE Transaction on Instrumentation and Measurement, vol. 67, issue 10, pp. 2504-2515, 2018, doi: 10.1109/TIM.2018.2843218
  • Cilia N.D., De Stefano C., Fontanella F., Scotto di Freca A., “Improving Evolutionary Algorithm Performance for Feature Selection in High-Dimensional Data”, Lecture Notes in Computer Science,10784 LNCS, pp. 439-454. 34, 2018.
  • Cilia N.D., De Stefano C., Fontanella F., Scotto di Freca A., “An Experimental Protocol to Support Cognitive Impairment Diagnosis by using Handwriting Analysis”, Procedia Computer Science, 141:466-471. 35, 2018.
  • A Bria, N.D. Cilia, C De Stefano, F Fontanella, C Marrocco, M Molinara, et al., “Deep Transfer Learning for writer identification in medieval books”, Metrology for Archaeology and Cultural Heritage (MetroArchaeo), 455-460, 2018.

2017

  • Alicandro R., Lazzaroni G., Palombaro M., On the effect of interactions beyond nearest neighbours on non-convex lattice systems, Calculus of Variations and PDE, vol. 56 (42), 2017
  • Alicandro R., De Luca L., Garroni A., Ponsiglione M., Minimising movements for the motion of discrete screw dislocations along glide directions, Calculus of Variations and PDE, vol. 56 (148), 2017
  • Faella L, Khludnev, A., Popova, T. Junction problem for rigid and Timoshenko elastic inclusions in elastic bodies. MATHEMATICS AND MECHANICS OF SOLIDS, vol. 22, p. 1-14, doi: 10.1177/1081286515594655, 2017
  • Faella L, Perugia C , Optimal control for a hyperbolic problem in composites with imperfect interface: A memory effect. EVOLUTION EQUATIONS AND CONTROL THEORY, vol. 6, p. 187-217, doi: 10.3934/eect.2017011, 2017
  • Faella L, Khludnev, A. M., Perugia C Optimal control of rigidity parameters of thin inclusions in composite materials. ZEITSCHRIFT FUR ANGEWANDTE MATHEMATIK UND PHYSIK, vol. 68, doi: 10.1007/s00033-017-0792-x, 2017
  • Chacouche K., Faella L, Perugia C., Quasi-stationary ferromagnetic problem for thin multi-structures. REVISTA MATEMATICA COMPLUTENSE, vol. 30, 3, p 657-685, doi: 10.1007/s13163-017-0235-4, 2017.
  • C. De Stefano, F. Fontanella, A. Scotto di Freca. “A novel mutation operator for the evolutionary learning of Bayesian networks”, 2017 IEEE Congress on Evolutionary Computation, CEC 2017 – Proceedings, art. no. 7969546, pp. 1999-2006, 2017