Publications tagged with "Model-based OPC"

1. Merging Model-Based and Data-Driven Approaches for Resilient Systems Digital Twins Design

   Campanile, L., De Biase, M. S., De Fazio, R., Di Giovanni, M., Marulli, F., & Verde, L. (2023). Merging Model-Based and Data-Driven Approaches for Resilient Systems Digital Twins Design [Conference paper]. Proceedings of the 2023 IEEE International Conference on Cyber Security and Resilience, CSR 2023, 301–306. https://doi.org/10.1109/CSR57506.2023.10224945

   Abstract

   Nowadays, the problem of system robustness, es-pecially in critical infrastructures, is a challenging open question. Some systems provide crucial services continuously failing, threatening the availability of the provided services. By designing a robust architecture, this criticality could be overcome or limited, ensuring service continuity. The definition of a resilient system involves not only its architecture but also the methodology implemented for the calculation and analysis of some indices, quantifying system performance. This study provides an innovative architecture for Digital Twins implementation based on a hybrid methodology for improving the control system in realtime. The introduced approach brings together different techniques. In particular, the work combines the point of strengths of Model-based methods and Data-driven ones, aiming to improve system performances. © 2023 IEEE.

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   {"key"=>"Campanile2023301", "type"=>"Conference paper", "bibtex"=>"@conference{Campanile2023301,\n  author = {Campanile, Lelio and De Biase, Maria Stella and De Fazio, Roberta and Di Giovanni, Michele and Marulli, Fiammetta and Verde, Laura},\n  title = {Merging Model-Based and Data-Driven Approaches for Resilient Systems Digital Twins Design},\n  year = {2023},\n  journal = {Proceedings of the 2023 IEEE International Conference on Cyber Security and Resilience, CSR 2023},\n  pages = {301 – 306},\n  doi = {10.1109/CSR57506.2023.10224945}\n}\n", "author"=>"Campanile, Lelio and De Biase, Maria Stella and De Fazio, Roberta and Di Giovanni, Michele and Marulli, Fiammetta and Verde, Laura", "author_array"=>[{"first"=>"Lelio", "last"=>"Campanile", "prefix"=>"", "suffix"=>""}, {"first"=>"Maria Stella", "last"=>"De Biase", "prefix"=>"", "suffix"=>""}, {"first"=>"Roberta", "last"=>"De Fazio", "prefix"=>"", "suffix"=>""}, {"first"=>"Michele", "last"=>"Di Giovanni", "prefix"=>"", "suffix"=>""}, {"first"=>"Fiammetta", "last"=>"Marulli", "prefix"=>"", "suffix"=>""}, {"first"=>"Laura", "last"=>"Verde", "prefix"=>"", "suffix"=>""}], "author_0_first"=>"Lelio", "author_0_last"=>"Campanile", "author_0_prefix"=>"", "author_0_suffix"=>"", "author_1_first"=>"Maria Stella", "author_1_last"=>"De Biase", "author_1_prefix"=>"", "author_1_suffix"=>"", "author_2_first"=>"Roberta", "author_2_last"=>"De Fazio", "author_2_prefix"=>"", "author_2_suffix"=>"", "author_3_first"=>"Michele", "author_3_last"=>"Di Giovanni", "author_3_prefix"=>"", "author_3_suffix"=>"", "author_4_first"=>"Fiammetta", "author_4_last"=>"Marulli", "author_4_prefix"=>"", "author_4_suffix"=>"", "author_5_first"=>"Laura", "author_5_last"=>"Verde", "author_5_prefix"=>"", "author_5_suffix"=>"", "title"=>"Merging Model-Based and Data-Driven Approaches for Resilient Systems Digital Twins Design", "year"=>"2023", "journal"=>"Proceedings of the 2023 IEEE International Conference on Cyber Security and Resilience, CSR 2023", "pages"=>"301 – 306", "doi"=>"10.1109/CSR57506.2023.10224945", "url"=>"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85171753139&doi=10.1109%2fCSR57506.2023.10224945&partnerID=40&md5=35e5eb0bfbb092e953335dd83b1b5b34", "abstract"=>"Nowadays, the problem of system robustness, es-pecially in critical infrastructures, is a challenging open question. Some systems provide crucial services continuously failing, threatening the availability of the provided services. By designing a robust architecture, this criticality could be overcome or limited, ensuring service continuity. The definition of a resilient system involves not only its architecture but also the methodology implemented for the calculation and analysis of some indices, quantifying system performance. This study provides an innovative architecture for Digital Twins implementation based on a hybrid methodology for improving the control system in realtime. The introduced approach brings together different techniques. In particular, the work combines the point of strengths of Model-based methods and Data-driven ones, aiming to improve system performances.  © 2023 IEEE.", "author_keywords"=>"Digital Twins; Process Mining; Requirement Engineering; Resilience Indices", "keywords"=>"Criticality (nuclear fission); Data-driven approach; Model-based OPC; Modeling data; Process mining; Requirement engineering; Resilience index; Resilient systems; System robustness; Systems performance; Twin design; Computer architecture", "publication_stage"=>"Final", "source"=>"Scopus", "note"=>"Cited by: 3"}
       

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2. A flexible simulation-based framework for model-based/data-driven dependability evaluation

   Abate, C., Campanile, L., & Marrone, S. (2020). A flexible simulation-based framework for model-based/data-driven dependability evaluation [Conference paper]. Proceedings - 2020 IEEE 31st International Symposium on Software Reliability Engineering Workshops, ISSREW 2020, 261–266. https://doi.org/10.1109/ISSREW51248.2020.00083

   Abstract

   Modern predictive maintenance is the convergence of several technological trends: developing new techniques and algorithms can be very costly due to the need for a physical prototype. This research has the final aim to build a simulation-based software framework for modeling and analysing complex systems and for defining predictive maintenance algorithms. By the usage of simulation, quantitative evaluation of the dependability of such systems will be possible. The ERTMS/ETCS dependability case study is presented to prove the applicability of the software. © 2020 IEEE.

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   {"key"=>"Abate2020261", "type"=>"Conference paper", "bibtex"=>"@conference{Abate2020261,\n  author = {Abate, Carlo and Campanile, Lelio and Marrone, Stefano},\n  title = {A flexible simulation-based framework for model-based/data-driven dependability evaluation},\n  year = {2020},\n  journal = {Proceedings - 2020 IEEE 31st International Symposium on Software Reliability Engineering Workshops, ISSREW 2020},\n  pages = {261 – 266},\n  doi = {10.1109/ISSREW51248.2020.00083}\n}\n", "author"=>"Abate, Carlo and Campanile, Lelio and Marrone, Stefano", "author_array"=>[{"first"=>"Carlo", "last"=>"Abate", "prefix"=>"", "suffix"=>""}, {"first"=>"Lelio", "last"=>"Campanile", "prefix"=>"", "suffix"=>""}, {"first"=>"Stefano", "last"=>"Marrone", "prefix"=>"", "suffix"=>""}], "author_0_first"=>"Carlo", "author_0_last"=>"Abate", "author_0_prefix"=>"", "author_0_suffix"=>"", "author_1_first"=>"Lelio", "author_1_last"=>"Campanile", "author_1_prefix"=>"", "author_1_suffix"=>"", "author_2_first"=>"Stefano", "author_2_last"=>"Marrone", "author_2_prefix"=>"", "author_2_suffix"=>"", "title"=>"A flexible simulation-based framework for model-based/data-driven dependability evaluation", "year"=>"2020", "journal"=>"Proceedings - 2020 IEEE 31st International Symposium on Software Reliability Engineering Workshops, ISSREW 2020", "pages"=>"261 – 266", "doi"=>"10.1109/ISSREW51248.2020.00083", "url"=>"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099830276&doi=10.1109%2fISSREW51248.2020.00083&partnerID=40&md5=8c06e5bedcaf6159251a6c79a3d7a446", "abstract"=>"Modern predictive maintenance is the convergence of several technological trends: developing new techniques and algorithms can be very costly due to the need for a physical prototype. This research has the final aim to build a simulation-based software framework for modeling and analysing complex systems and for defining predictive maintenance algorithms. By the usage of simulation, quantitative evaluation of the dependability of such systems will be possible. The ERTMS/ETCS dependability case study is presented to prove the applicability of the software.  © 2020 IEEE.", "author_keywords"=>"Data-driven methods; Dependability Evaluation; Predictive maintenance; Quantitative Formal Models", "keywords"=>"Computer programming; Maintenance; Data driven; Data-driven methods; Dependability evaluation; Flexible simulation; Formal modeling; Model-based OPC; Predictive maintenance; Quantitative formal model; Software frameworks; Technological trends; Computer software", "publication_stage"=>"Final", "source"=>"Scopus", "note"=>"Cited by: 1"}
       

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