Publications

  1. Challenges and Perspectives of Smart Grid Systems in Islands: A Real Case Study, F. Succetti, A. Rosato, R. Araneo, G. Di Lorenzo, M. Panella, Energies, 2023
  2. A randomized deep neural network for emotion recognition with landmarks detection, F. Di Luzio, A. Rosato, M. Panella, Biomedical Signal Processing and Control 81, 104418, 2023
  3. Perceptron theory can predict the accuracy of neural networks D Kleyko, A Rosato, E.P. Frady, M. Panella, F.T. Sommer, IEEE Transactions on Neural Networks and Learning Systems, 2023
  4. Systematic review of energy theft practices and autonomous detection through artificial intelligence methods E Stracqualursi, A. Rosato, G. Di Lorenzo, M. Panella, R. Araneo, Renewable and Sustainable Energy Reviews 184, 113544, 2023
  5. Multi-Damage Detection in Composite Space Structures via Deep Learning, F. Angeletti, P. Gasbarri, M. Panella, A. Rosato, Sensors 23 (17), 7515, 2023
  6. Neural Graphs: an Effective Solution for the Resource Allocation in NFV Sites interconnected by Elastic Optical Networks, V. Eramo, F.G. Lavacca, F. Valente, V. Filippetti, A. Rosato, A. Verdone, 23rd International Conference on Transparent Optical Networks (ICTON), 1-6, 2023
  7. Modular quantum circuits for secure communication, A. Ceschini, A. Rosato, M. Panella, IET Quantum Communication, 2023
  8. A Review on Quantum Approximate Optimization Algorithm and its Variants, K. Blekos, D. Brand, A. Ceschini, C.H. Chou, R.H. Li, K. Pandya, arXiv preprint arXiv:2306.09198, 2023
  9. Resource saving via ensemble techniques for quantum neural networks, M. Incudini, M. Grossi, A. Ceschini, A. Mandarino, M. Panella, S. Vallecorsa, arXiv preprint arXiv:2303.11283, 2023
  10. A Price-aware Dynamic Decision System in Energy Communities, F. Di Luzio, F. Succetti, A. Rosato, R. Araneo, M. Panella, IEEE International Conference on Environment and Electrical Engineering, 2022
  11. Quasi-Chaotic Oscillators Based on Modular Quantum Circuits, A. Ceschini, A. Rosato, M. Panella, arXiv preprint arXiv:2203.14029, 2022
  12. Analysis of Logic Schemes for the Optical Implementation of Pointwise Operations in Gated Recurrent Unit Cells, B. Alam, A. Ceschini, A. Rosato, M. Panella, R. Asquini, AISEM Annual Conference on Sensors and Microsystems, 167-173, 2022
  13. A Fast Deep Learning Technique for Wi-Fi-Based Human Activity Recognition, F. Succetti, A. Rosato, F. Di Luzio, A. Ceschini, M. Panella, Progress In Electromagnetics Research, 2022
  14. Detection of Autism Spectrum Disorder by a Fast Deep Neural Network, F. Di Luzio, F. Colonnese, A. Rosato, M. Panella, International Conference on Applied Intelligence and Informatics, 539-553, 2022
  15. Hybrid quantum-classical recurrent neural networks for time series prediction, A. Ceschini, A. Rosato, M. Panella, 2022 International Joint Conference on Neural Networks (IJCNN), 1-8, 2022
  16. Multivariate Time Series Analysis for Electrical Power Theft Detection in the Distribution Grid, A. Ceschini, A. Rosato, F. Succetti, R. Araneo, M. Panella, 2022 IEEE International Conference on Environment and Electrical Engineering, 2022
  17. All-optical AND Logic Gate Based on Semiconductor Optical Amplifiers for Implementing Deep Recurrent Neural Networks, B. Alam, A. Ceschini, A. Rosato, M. Panella, R. Asquini, 2022 International Conference on Numerical Simulation of Optoelectronic, 2022
  18. Ensembling Techniques for Quantum Neural Networks, M. Incudini, M. Grossi, A. Ceschini, A. Mandarino, M. Panella, S. Vallecorsa, et al., Proceedings of Quantum Techniques in Machine Learning (QTML 2022),               2022
  19. Multi-site Forecasting of Energy Time Series with Spatio-Temporal Graph Neural Networks, A. Verdone, S. Scardapane M. Panella, 2022 International Joint Conference on Neural Networks (IJCNN), 2022
  20. Nonexclusive Classification of Household Appliances by Fuzzy Deep Neural Networks, F. Succetti, A. Rosato, M. Panella, International Conference on Applied Intelligence and Informatics, 2022
  21. Deep learning-based Structural Health Monitoring for damage detection on a large space antenna, P. Iannelli, F. Angeletti, P. Gasbarri, M. Panella, A. Rosato, Acta Astronautica 193, 635-643, 2022
  22. Distributed LSTM-based cloud resource allocation in network function virtualization architectures, T.Catena, V. Eramo, M. Panella, A. Rosato, Computer Networks 213, 109111, 2022
  23. A Study on Structural Health Monitoring of a Large Space Antenna via Distributed Sensors and Deep Learning, F. Angeletti, P. Iannelli, P. Gasbarri, M. Panella, A. Rosato, Sensors 23 (1), 368, 2022
  24. Few-shot federated learning in randomized neural networks via hyperdimensional computing, A. Rosato, M. Panella, E. Osipov, D. Kleyko, 2022 International Joint Conference on Neural Networks (IJCNN), 1-8, 2022
  25. Time Series Prediction with Autoencoding LSTM Networks, F. Succetti, A. Ceschini, F. Di Luzio, A. Rosato, In: Advances in Computational Intelligence: 16th International Work-Conference on Artificial Neural Networks IWANN 2021, 2021
  26. Deep neural networks for electric energy theft and anomaly detection in the distribution grid, A. Ceschini, A. Rosato, F. Succetti, F. Di Luzio, M. Mitolo, R. Araneo, M. Panella, 2021 IEEE International Conference on Environment and Electrical Engineering and 2021 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe), 2021
  27. A blockwise embedding for multi-day-ahead prediction of energy time series by randomized deep neural networks, F. Di Luzio, A. Rosato, F. Succetti, M.Panella – 2021 International Joint Conference on Neural Networks (IJCNN), 2021
  28. Multivariate prediction of energy time series by autoencoded LSTM networks, F. Succetti, F. Di Luzio, A. Ceschini, A. Rosato, R. Araneo, M. Panella – 2021 IEEE International Conference on Environment and Electrical Engineering and 2021 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe) (pp. 1-5), 2021
  29. Two-stage dynamic management in energy communities using a decision system based on elastic net regularization, A. Rosato, M. Panella, A. Andreotti, O.A. Mohammed, R. Araneo, Applied Energy 291, 116852,  2021
  30. 2-D convolutional deep neural network for the multivariate prediction of photovoltaic time series, A. Rosato, R. Araneo, A. Andreotti, F. Succetti, M. Panella, Energies 14 (9), 2392, 2021
  31. Hyperdimensional computing for efficient distributed classification with randomized neural networks, A. Rosato, M. Panella, D. Kleyko, 2021 International Joint Conference on Neural Networks (IJCNN), 1-10, 2021
  32. A decentralized algorithm for distributed ensemble clustering, A. Rosato, R. Altilio, M. Panella, Information Sciences 578, 417-434, 2021
  33. Design of an LSTM Cell on a Quantum Hardware, A. Ceschini, A. Rosato, M. Panella, IEEE Transactions on Circuits and Systems II: Express Briefs 69 (3), 1822-1826, 2021
  34. On effects of compression with hyperdimensional computing in distributed randomized neural networks, A. Rosato, M. Panella, E. Osipov, D. Kleyko International Work-Conference on Artificial Neural Networks, 155-16 , 2021
  35. Perceptron theory for predicting the accuracy of neural networks, D. Kleyko, A. Rosato, E.P. Frady, M. Panella, F.T. Sommer, arXiv preprint arXiv:2012.07881, 2020
  36. ADMM consensus for deep LSTM networks, A. Rosato, F. Succetti, M. Barbirotta, M. Panella – 2020 International Joint Conference on Neural Networks (IJCNN), 2020
  37. Deep neural networks for multivariate prediction of photovoltaic power time series, F. Succetti, A. Rosato, R. Araneo, M. Panella, IEEE Access, 2020
  38. Multidimensional feeding of LSTM networks for multivariate prediction of energy time series, F. Succetti, A. Rosato, R. Araneo, M. Panella, 2020 IEEE International Conference on Environment and Electrical Engineering and 2020 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe) (pp. 1-5), 2020
  39. A Combined Deep Learning Approach for Time Series Prediction in Energy Environments, A. Rosato, F. Succetti, R. Araneo, A. Andreotti, M. Mitolo, M. Panella,  2020 IEEE/IAS 56th Industrial and Commercial Power Systems Technical Conference (I&CPS), 2020
  40. A parallel hardware implementation for 2-d hierarchical clustering based on fuzzy logic, G.C. Cardarilli, L. Di Nunzio, R. Fazzolari, M. Panella, M. Re, A. Rosato, S. Spanò, IEEE Transactions on Circuits and Systems II: Express Briefs 68 (4), 1428-1432,  2020
  41. A review of the enabling methodologies for knowledge discovery from smart grids data, F. De Caro, A. Andreotti, R. Araneo, M. Panella, A. Rosato, A. Vaccaro, D. Villacci, Energies 13 (24), 6579, 2020
  42. Time series prediction using random weights fuzzy neural networks ,A. Rosato, M. Panella, 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1-6, 2020
  43. Prediction of Photovoltaic Time Series by Recurrent Neural Networks and Genetic Embedding , A. Rosato, R. Araneo, M. Panella, 2020 IEEE Congress on Evolutionary Computation (CEC), 1-8, 2020
  44. An Energy-Aware Hardware Implementation of 2D Hierarchical Clustering, G.C. Cardarilli, R. Fazzolari, M. Matta, M. Panella, A. Rosato, S. Spanò, 2020 IEEE International Conference on Environment and Electrical Engineering and 2020 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe), 2020
  45. Deep Learning for local damage identification in large space structures via sensor-measured time responses, P. Iannelli, F. Angeletti, P. Gasbarri, M. Panella, A. Rosato, INTERNATIONAL ASTRONAUTICAL CONGRESS: IAC PROCEEDINGS 2020, 2020
  46. User centered design to improve information exchange in diabetes care through eHealth: results from a small scale exploratory study, G. Fico, A. Martinez-Millana, J.P. Leuteritz, A. Fioravanti, et al., Journal of medical systems 44, 1-12, 2020
  47. Multivariate Prediction in Photovoltaic Power Plants by a Stacked Deep Neural Network, A. Rosato, R. Araneo, M. Panella, 2019 Photonics & Electromagnetics Research Symposium-Fall (PIERS-Fall), 451-457, 2019
  48. A neural network based prediction system of distributed generation for the management of microgrids, A. Rosato, M. Panella, R. Araneo, A. Andreotti, IEEE Transactions on Industry Applications 55 (6), 7092-7102, 2019
  49. Multivariate Prediction of PM10 Concentration by LSTM Neural Networks, L. Di Antonio, A. Rosato, V. Colaiuda, A. Lombardi, B. Tomassetti, M. Panella, 2019 Photonics & Electromagnetics Research Symposium-Fall (PIERS-Fall), 423-431, 2019
  50. A training procedure for quantum random vector functional-link networks, M. Panella, A. Rosato, ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019
  51. Predictive Analysis of Photovoltaic Power Generation Using Deep Learning, A. Rosato, R. Araneo, A. Andreotti, M. Panella, 2019 IEEE International Conference on Environment and Electrical Engineering, 2019
  52. Decentralized Prediction of Electrical Time Series in Smart Grids Using Long Short-Term Memory Neural Networks, A. Rosato, R. Araneo, M. Panella, 2019 PhotonIcs & Electromagnetics Research Symposium-Spring (PIERS-Spring), 1-9, 2019
  53. A Fuzzy Neural Network Approach to Quality Assessment of Water Reservoirs, HAN Silva, A. Rosato, M. Panella, 2019 PhotonIcs & Electromagnetics Research Symposium-Spring , 2019
  54. DEEP LEARNING PER IL CONTROLLO PREDITTIVO NELLA GESTIONE DELLE RISORSE ENERGETICHE DISTRIBUITE, A. Rosato, R. Araneo, M. Panella, Memorie ET2019, 1-2, 2019
  55. A smart grid in Ponza Island: battery energy storage management by echo state neural network, A. Rosato, R. Altilio, R. Araneo, M. Panella, 2018 IEEE International Conference on Environment and Electrical Engineering, 2018
  56. Water quality prediction based on wavelet neural networks and remote sensing HAN Silva, A. Rosato, R. Altilio, M. Panella, 2018 International Joint Conference on Neural Networks (IJCNN), 1-6, 2018
  57. A sparse Bayesian model for random weight fuzzy neural networks, R. Altilio, A. Rosato, M. Panella, 2018 IEEE international conference on fuzzy systems (FUZZ-IEEE), 1-7,2018
  58. On-line learning of rvfl neural networks on finite precision hardware, A. Rosato, R. Altilio, M. Panella, m2018 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2018
  59. Neural Network Approaches to Electricity Price Forecastingly in Day-Ahead Markets, A. Rosato, R. Altilio, R. Araneo, M. Panella, 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe), 2018
  60. A distributed algorithm for the cooperative prediction of power production in PV plants, A. Rosato, M. Panella, R. Araneo, IEEE Transactions on Energy Conversion 34 (1), 497-508,  2018
  61. Apprendimento sparso di reti neurofuzzy, M. Panella, R. Altilio, A. Rosato, Memorie ET2018, 1-2, 2018
  62. Apprendimento on-line di reti neurali su architetture a precisione numerica finita, M. Panella, R. Altilio, A. Rosato, Memorie ET2018, 1-2, 2018
  63. RETI NEURALI E LOGICA FUZZY PER LA PREDIZIONE DI SERIE ENERGETICHE, A. Rosato, R. Altilio, R. Araneo, M. Panella, Memorie ET2017, 1-2, 2017
  64. Prediction in photovoltaic power by neural networks, A. Rosato, R. Altilio, R. Araneo, M. Panella, Energies 10 (7), 1003, 2017
  65. Retrieving Chlorophyll-a levels, transparency and TSS concentration from multispectral satellite data by using artificial neural networks, HAN Silva, G. Laneve, A. Rosato, M. Panella, 2017 Progress In Electromagnetics Research Symposium-Fall (PIERS-FALL), 2876, 2017
  66. A new learning approach for Takagi-Sugeno fuzzy systems applied to time series prediction, R. Altilio, A. Rosato, M. Panella, 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1-6, 2017
  67. Takagi-Sugeno fuzzy systems applied to voltage prediction of photovoltaic plants, A. Rosato, R. Altilio, R. Araneo, M. Panella, 2017 IEEE International Conference on Environment and Electrical Engineering, 2017
  68. Finite precision implementation of random vector functional-link networks, A. Rosato, R. Altilio, M. Panella, 2017 22nd International Conference on Digital Signal Processing (DSP), 1-5, 2017
  69. A nonuniform quantizer for hardware implementation of neural networks, R. Altilio, A. Rosato, M. Panella, 2017 European Conference on Circuit Theory and Design (ECCTD), 1-4, 2017
  70. A technological framework based on automatic messaging for improving adherence of diabetic patients, A. Fioravanti, Telecomunicacion, 2016
  71. MACHINE LEARNING PER L’ANALISI AMBIENTALE, A. Proietti, A. Rosato, HA Nascimento Silva, M. Panella, Memorie ET2016, 1-2, 2016
  72. Embedding of time series for the prediction in photovoltaic power plants, A. Rosato, R. Altilio, R. Araneo, M. Panella, 2016 IEEE 16th International Conference on Environment and Electrical Engineering, 2016
  73. Distributed learning of random weights fuzzy neural networks, R. Fierimonte, M. Barbato, A. Rosato, M. Panella, 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2287-2294, 2016
  74. Recent advances on distributed unsupervised learning, A. Rosato, R. Altilio, M. Panella, Advances in Neural Networks: Computational Intelligence for ICT, 77-86, 2016
  75. Comparative assessment of glucose prediction models for patients with type 1 diabetes mellitus applying sensors for glucose and physical activity monitoring, K. Zarkogianni, K. Mitsis, E. Litsa, M.T. Arredondo, G .Fico, A. Fioravanti, Medical & biological engineering & computing 53, 1333-1343, 2015
  76. Automatic messaging for improving patients engagement in diabetes management: an exploratory study, A. Fioravanti, G. Fico, D. Salvi, RI García-Betances, MT Arredondo, Medical & biological engineering & computing 53, 1285-1294, 2015
  77. Correspondence matching based on Higher Order Statistics for Multi-view plus Depth video sequences, S. Colonnese, P. Oliveira, A. Rosato, L. Ungaro, A. Beghdadi, M. Biagi, 2014 5th European Workshop on Visual Information Processing (EUVIP), 1-6, 2014
  78. Adaptive Healthcare Pathway for Diabetes Disease Management, G. Fico, A. Fioravanti, MT Arredondo, C. Diazzi, G. Arcuri, C. Conti, G. Pirini, XIII Mediterranean Conference on Medical and Biological Engineering and Computing 2013: MEDICON 2013, 2014
  79. Neuro-Fuzzy based Glucose Prediction Model for Patients with Type 1 Diabetes Mellitus, K. Zarkogianni, K. Mitsis, M.-T. Arredondo, G IEEE-EMBS International Conferences on Biomedical and Health Informatics, 2014
  80. Experience in evaluating AAL solutions in living labs, JBM Colomer, D. Salvi, MF Cabrera-Umpierrez, MT Arredondo, P. Abril, Sensors 14 (4), 7277-7311, 2014
  81. Preliminary evaluation of a personal healthcare system prototype for cognitive eRehabilitation in a living assistance domain, M. Pastorino, A. Fioravanti, MT Arredondo, JM Cogollor, J. Rojo, M. Ferre, Sensors 14 (6), 10213-10233, 2014
  82. Health‐Integrated System Paradigm: Diabetes Management, A. Fioravanti, G. Fico, AG Patón, JP Leuteritz, AG Arredondo, et al., Handbook of Biomedical Telemetry, 623-632, 2014
  83. An innovative solution based on human-computer interaction to support cognitive rehabilitation, JM Cogollor, M. Pastorino, J. Rojo, A. Fioravanti, A. Wing, MT Arredondo, Journal of accessibility and design for all 4 (3), 238-254, 2014
  84. Cogwatch: a web based platform for cognitive tele-rehabilitation and follow up of apraxia and action disorganisation syndrome patients, M. Pastorino, A. Fioravanti, MT Arredondo, JM Cogollor, J. Rojo, M. Ferre, IEEE-EMBS International Conference on Biomedical and Health Informatics, 2014
  85. Integration of personalized healthcare pathways in an ICT platform for diabetes managements: a small-scale exploratory study, G. Fico, A. Fioravanti, MT Arredondo, J. Gorman, C. Diazzi, G. Arcuri, C. Conti, IEEE Journal of Biomedical and Health Informatics 20 (1), 29-38, 2014
  86. Interactive Architecture for a Web Based Platform for Apraxia and Action Disorganisation Syndrome Rehabilitation, AMW Matteo Pastorino, Alessio Fioravanti, María Teresa Japanese Society for Medical and Biological Engine 51 (Supplement), R-324, 2013
  87. Handbook of Biomedical Telemetry (IEEE Press Series on Biomedical Engineering) – Chapter 21 JPL Alessio Fioravanti, Giuseppe Fico, Alejandro, 2013
  88. Evaluation of a Diabetes Disease Management Platform Based on an ICT Enabled Personalized Healthcare Pathway, GP Giuseppe Fico, Rebeca I. García-Betances, Member IEEE J-BHI special issue: “Biomedical ITC Convergence Engineering”, 2013
  89. A Step Forward in Human-Computer Interaction for Cognitive Rehabilitation, JH José M. Cogollor, Matteo Pastorino, Javier Rojo, V Congreso Internacional de Diseño, Redes de Investigación y Tecnología para todos, 2013
  90. Sistema de Rehabilitación Cognitiva para la Asistencia en Actividades Cotidianas de Pacientes tras Sufrir un Accidente Cerebro-Vascular, JMSZ J. Rojo, J. M. Cogollor, M. Pastorino, A 12º Workshop Robótica Cognitiva, Robocity 2030-II, 2013
  91. An iPhone-based application for promoting type 2 diabetic patients self-management towards healthy lifestyle habits, A. González, G. Fico, MT Arredondo Waldmeyer, A. Fioravanti Telecomunicacion, 2011
  92. A mobile feedback system for integrated E-health platforms to improve self-care and compliance of diabetes mellitus patients, A. Fioravanti, G. Fico, MT Arredondo, JP Leuteritz, 2011 annual international conference of the IEEE engineering in medicine and biology society, 2011
  93. A user centered design approach for patient interfaces to a diabetes IT platform, G. Fico, A. Fioravanti, MT Arredondo, JP Leuteritz, A. Guillén, D. Fernandez, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011
  94. Integration of heterogeneous biomedical sensors into an ISO/IEEE 11073 compliant application, A. Fioravanti, G. Fico, MT Arredondo, D. Salvi, JL Villalar, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology, 2010
  95. A healthy lifestyle coaching-persuasive application for patients with type 2 diabetes, G. Fico, A. Fioravanti, MT Arredondo, D. Ardigó, A. Guillén, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology, 2010
  96. Approaching personalised emergency management to Future Internet, E. Gaeta, PD Juan Luis Villalar, L. Pastor-Sanz, A. Fioravanti, Healthcare Computing, 2010            

×
Cookie
Noi e 1 terze parti selezionate utilizziamo cookie o tecnologie simili per finalità tecniche e, con il tuo consenso, anche per le finalità di funzionalità e marketing (con annunci personalizzati) come specificato nella cookie policy. Puoi liberamente prestare, rifiutare o revocare il tuo consenso, in qualsiasi momento, accedendo al pannello delle preferenze. Il rifiuto del consenso può rendere non disponibili le relative funzioni. Usa il pulsante "Accetta" per acconsentire. Usa il pulsante "Rifiuta" per continuare senza accettare. Leggi la nostra politica per i cookie
Scopri di più e personalizza Rifiuta Accetta
Cookie
Scegli quale tipo di cookie accettare. La tua scelta verrà salvata per un anno. Leggi la nostra politica per i cookie
Salva e continua Rifiuta Accetta
en_USEN
it_ITIT es_ESES fr_FRFR de_DEDE en_USEN