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2017
Conference article
Restricted
Enhanced power grid evaluation through efficient stochastic model-based analysis
Masetti G.
Electrical infrastructures provide services at the basis of a number of application sectors, several of which are critical from the perspective of human life, environment or financials. Following the increasing trend in electricity generation from renewable sources, pushed by the need to meet sustainable energy goals in many countries, more sophisticated control strategies are being adopted to regulate the operation of the electric power system, driving electrical infrastructures towards the so called Smart Grid scenario. It is therefore paramount to be assisted by technologies able to analyze the Smart Grid behavior in critical scenarios, e.g. where cyber malfunctions or grid disruptions occur. In this context, stochastic model-based analysis are well suited to assess dependability and quality of service related indicators, and continuous improvements in modeling strategies and system models design are required. Thus, my PhD work addresses this topic by contributing to study new Smart Grid scenarios, concerning the advanced interplay between ICT and electrical infrastructures in presence of cyber faults/attacks, define a new modeling approach, based on modularity and composition, and start to study how to improve the electrical grid dynamics representation. In this article these studies are briefly presented and discussed.Source: European Dependable Computing Conference, Ginevra, 4-8/09/2017
Masetti G.
Electrical infrastructures provide services at the basis of a number of application sectors, several of which are critical from the perspective of human life, environment or financials. Following the increasing trend in electricity generation from renewable sources, pushed by the need to meet sustainable energy goals in many countries, more sophisticated control strategies are being adopted to regulate the operation of the electric power system, driving electrical infrastructures towards the so called Smart Grid scenario. It is therefore paramount to be assisted by technologies able to analyze the Smart Grid behavior in critical scenarios, e.g. where cyber malfunctions or grid disruptions occur. In this context, stochastic model-based analysis are well suited to assess dependability and quality of service related indicators, and continuous improvements in modeling strategies and system models design are required. Thus, my PhD work addresses this topic by contributing to study new Smart Grid scenarios, concerning the advanced interplay between ICT and electrical infrastructures in presence of cyber faults/attacks, define a new modeling approach, based on modularity and composition, and start to study how to improve the electrical grid dynamics representation. In this article these studies are briefly presented and discussed.Source: European Dependable Computing Conference, Ginevra, 4-8/09/2017
See at:
arxiv.org 
| CNR ExploRA
2022
Conference article
Open Access
Foreseeing the impact of the proposed AI Act on the sustainability and safety of critical infrastructures
Sovrano F., Masetti G.
The AI Act has been recently proposed by the European Commission to regulate the use of AI in the EU, especially on high-risk applications, i.e. systems intended to be used as safety components in the management and operation of road traffic and the supply of water, gas, heating and electricity. On the other hand, IEC 61508, one of the most adopted international standards for safety-critical electronic components, seem to mostly forbid the use of AI in such systems. Given this conflict between IEC 61508 and the proposed AI Act, also stressed by the fact that IEC 61508 is not an harmonised European standard, with the present paper we study and analyse what is going to happen to industry after the entry into force of the AI Act. More in detail we focus on how the proposed AI Act might positively impact on the sustainability of critical infrastructures by allowing the use of AI on an industry where it was previously forbidden. To do so, we provide several examples of AI-based solutions falling under the umbrella of IEC 61508 that might have a positive impact on sustainability in alignment with the current long-term goals of the EU and the Sustainable Development Goals of the United Nations, i.e. 1) affordable and clean energy, 2) sustainable cities and communities.Source: ICEGOV 2022 - 15th International Conference on Theory and Practice of Electronic Governance, pp. 492–498, Guimarães, Portugal, 04-07/10/2022
DOI: 10.1145/3560107.3560253
Metrics:
Sovrano F., Masetti G.
The AI Act has been recently proposed by the European Commission to regulate the use of AI in the EU, especially on high-risk applications, i.e. systems intended to be used as safety components in the management and operation of road traffic and the supply of water, gas, heating and electricity. On the other hand, IEC 61508, one of the most adopted international standards for safety-critical electronic components, seem to mostly forbid the use of AI in such systems. Given this conflict between IEC 61508 and the proposed AI Act, also stressed by the fact that IEC 61508 is not an harmonised European standard, with the present paper we study and analyse what is going to happen to industry after the entry into force of the AI Act. More in detail we focus on how the proposed AI Act might positively impact on the sustainability of critical infrastructures by allowing the use of AI on an industry where it was previously forbidden. To do so, we provide several examples of AI-based solutions falling under the umbrella of IEC 61508 that might have a positive impact on sustainability in alignment with the current long-term goals of the EU and the Sustainable Development Goals of the United Nations, i.e. 1) affordable and clean energy, 2) sustainable cities and communities.Source: ICEGOV 2022 - 15th International Conference on Theory and Practice of Electronic Governance, pp. 492–498, Guimarães, Portugal, 04-07/10/2022
DOI: 10.1145/3560107.3560253
Metrics:
See at:
ISTI Repository 
| dl.acm.org | CNR ExploRA
2018
Conference article
Closed Access
Enhanced dependability evaluation through Krylov methods and matrix functions: the case of load-sharing systems
Masetti G.
Recently, the link between performance and dependability measures for Markovian models and the evaluation of bilinear forms induced by well-known matrix functions has been established. The connection can be exploited to obtain effective and efficient solution methods for allowing in particular the computation of reliability-related measures. In this paper, a reliability model for a load-sharing system is discussed and then solved through Krylov methods generated by the mentioned connection.Source: 48th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W 2018), pp. 92–95, Luxembourg City, Luxembourg, 25-28/06/2018
DOI: 10.1109/dsn-w.2018.00043
Metrics:
Masetti G.
Recently, the link between performance and dependability measures for Markovian models and the evaluation of bilinear forms induced by well-known matrix functions has been established. The connection can be exploited to obtain effective and efficient solution methods for allowing in particular the computation of reliability-related measures. In this paper, a reliability model for a load-sharing system is discussed and then solved through Krylov methods generated by the mentioned connection.Source: 48th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W 2018), pp. 92–95, Luxembourg City, Luxembourg, 25-28/06/2018
DOI: 10.1109/dsn-w.2018.00043
Metrics:
See at:
doi.org | ieeexplore.ieee.org | CNR ExploRA
2019
Doctoral thesis
Open Access
Enhanced power grid evaluation through efficient stochastic model-based analysis
Masetti G.
The electrical infrastructure can be considered nowadays as a meta-critical infrastructure: in fact it is the basis for almost all the critical infrastructures a modern nation can have, such as water, oil, gas and transportation. This implies that its correct operation is a fundamental requirement to the correct operation of the critical infrastructures that depend on it. To allow pervasive control and monitoring towards resilience and performance enhancements, the Smart Grid is emerging as a convergence of information and commu- nication technology with power system engineering. In particular, the ever increasing level of distributed energy resources penetration calls for more and more sophisticated monitoring and control facilities. So, studying the influence of distributed energy resources, of new control policies and ICT on the dependability of distribution grids offers valuable insights on how to improve the design of Smart Grids. In addition to standard dependability measures such as reliability and availability, among greatly relevant measures specifically defined for electrical distribution systems there are the voltage quality and the energy required, but not supplied, by the distribution system. A popular approach to assess electrical distribution specific measures, in presence of failures or attacks to the ICT system and/or to the electric in- frastructure, is the stochastic model-based analysis. Although several studies have been already proposed, the research in this context still faces a number of challenges, mainly due to the need: i) to consider both the ICT sub- system and the controlled electrical infrastructure, to properly account for (inter)dependencies through which operations (and failures/attacks) propa- gate; ii) to model and analyze the SG components at a sufficiently detailed level of abstraction, targeting realistic representation of their structure and behavior in view of promoting accuracy of the assessment itself. Both nomi- nal and a variety of faulty behaviors are to be investigated, since the interest is on assessing resilience and quality related attributes; iii) to tackle realistic segments of SG in terms of topology size, to make the evaluation study of real interest to stakeholders involved in the field. To cope with all these needs results in huge and complex models, to be typically defined in a modular fashion and requiring sophisticated composi- tional operators. Moreover, model solution through simulation-based eval- uation becomes unavoidable in presence of non-Markovian behavior of the involved components, thus preventing the use of analytical approaches. Given the above premises, the stochastic model-based analysis of realistic SG topologies is a research area where further investigations and enhance- ments are highly desirable. In this context, this thesis offers contributions in the direction of promoting efficient evaluation of SG in realistic scenarios from a resilience perspective.
Masetti G.
The electrical infrastructure can be considered nowadays as a meta-critical infrastructure: in fact it is the basis for almost all the critical infrastructures a modern nation can have, such as water, oil, gas and transportation. This implies that its correct operation is a fundamental requirement to the correct operation of the critical infrastructures that depend on it. To allow pervasive control and monitoring towards resilience and performance enhancements, the Smart Grid is emerging as a convergence of information and commu- nication technology with power system engineering. In particular, the ever increasing level of distributed energy resources penetration calls for more and more sophisticated monitoring and control facilities. So, studying the influence of distributed energy resources, of new control policies and ICT on the dependability of distribution grids offers valuable insights on how to improve the design of Smart Grids. In addition to standard dependability measures such as reliability and availability, among greatly relevant measures specifically defined for electrical distribution systems there are the voltage quality and the energy required, but not supplied, by the distribution system. A popular approach to assess electrical distribution specific measures, in presence of failures or attacks to the ICT system and/or to the electric in- frastructure, is the stochastic model-based analysis. Although several studies have been already proposed, the research in this context still faces a number of challenges, mainly due to the need: i) to consider both the ICT sub- system and the controlled electrical infrastructure, to properly account for (inter)dependencies through which operations (and failures/attacks) propa- gate; ii) to model and analyze the SG components at a sufficiently detailed level of abstraction, targeting realistic representation of their structure and behavior in view of promoting accuracy of the assessment itself. Both nomi- nal and a variety of faulty behaviors are to be investigated, since the interest is on assessing resilience and quality related attributes; iii) to tackle realistic segments of SG in terms of topology size, to make the evaluation study of real interest to stakeholders involved in the field. To cope with all these needs results in huge and complex models, to be typically defined in a modular fashion and requiring sophisticated composi- tional operators. Moreover, model solution through simulation-based eval- uation becomes unavoidable in presence of non-Markovian behavior of the involved components, thus preventing the use of analytical approaches. Given the above premises, the stochastic model-based analysis of realistic SG topologies is a research area where further investigations and enhance- ments are highly desirable. In this context, this thesis offers contributions in the direction of promoting efficient evaluation of SG in realistic scenarios from a resilience perspective.
See at:
ISTI Repository | CNR ExploRA
2018
Journal article
Open Access
Tartini, the third tone and the cochlea
Caselli G., Masetti G., Cecchi G.
"It is physically certain that given two simultaneous loud and prolonged tones one can hear a third tone, different from the played sounds": with these words taken from his essay Trattato di musica secondo la vera scienza dell'armonia published in 1754 Giuseppe Tartini (1692-1770), celebrated violinist, and researcher of musical theory and "physicomathematical harmonist" (Barbieri, 1990) introduces his discovery, made some years before (in 1713), of the socalled third tone. As explained by Tartini himself, if a listener stands halfway between two violin or oboe players some steps apart, he can hear another tone, in addition to the played notes (principal or primary notes), called by Tartini the "third tone"Source: Ph (Milano) (2018).
Caselli G., Masetti G., Cecchi G.
"It is physically certain that given two simultaneous loud and prolonged tones one can hear a third tone, different from the played sounds": with these words taken from his essay Trattato di musica secondo la vera scienza dell'armonia published in 1754 Giuseppe Tartini (1692-1770), celebrated violinist, and researcher of musical theory and "physicomathematical harmonist" (Barbieri, 1990) introduces his discovery, made some years before (in 1713), of the socalled third tone. As explained by Tartini himself, if a listener stands halfway between two violin or oboe players some steps apart, he can hear another tone, in addition to the played notes (principal or primary notes), called by Tartini the "third tone"Source: Ph (Milano) (2018).
See at:
ISTI Repository | www.phmagazine.it | CNR ExploRA
2020
Journal article
Open Access
Analysis of violin combination tones and their contribution to Tartini's third tone
Caselli G., Cecchi G., Malacarne M., Masetti G.
It is widely accepted that the famous Tartini's third tone, i.e., the appearance of an additional third tone of lower frequency when playing a dyad on the violin, is a subjective phenomenon generated by the listener's cochlear nonlinearity. However, the recent demonstration that additional tones of audible amplitude can also be generated by the violin itself during playing of a dyad (violin combination tones), raises the question if these tones might have influenced Tartini's third sound perception. The experiments reported here were made to ascertain this possibility. To this end, following Tartini experiments, several dyads played by either one violin or two violins playing one note of the dyad each, were recorded. The analysis of the spectra shows that violin combination tones are present in all the dyads investigated, but exclusively when the dyad is played by a single violin and not when the same dyad is played by two violins. Tartini found the third tones to be the same in both conditions, which means that violin combination tones in his experiments were either absent or too small to affect the perception of the subjective third tones arising from cochlear distortion.Source: Savart journal 1 (2020).
Caselli G., Cecchi G., Malacarne M., Masetti G.
It is widely accepted that the famous Tartini's third tone, i.e., the appearance of an additional third tone of lower frequency when playing a dyad on the violin, is a subjective phenomenon generated by the listener's cochlear nonlinearity. However, the recent demonstration that additional tones of audible amplitude can also be generated by the violin itself during playing of a dyad (violin combination tones), raises the question if these tones might have influenced Tartini's third sound perception. The experiments reported here were made to ascertain this possibility. To this end, following Tartini experiments, several dyads played by either one violin or two violins playing one note of the dyad each, were recorded. The analysis of the spectra shows that violin combination tones are present in all the dyads investigated, but exclusively when the dyad is played by a single violin and not when the same dyad is played by two violins. Tartini found the third tones to be the same in both conditions, which means that violin combination tones in his experiments were either absent or too small to affect the perception of the subjective third tones arising from cochlear distortion.Source: Savart journal 1 (2020).
See at:
ISTI Repository | www.savartjournal.org | CNR ExploRA
2018
Report
Open Access
Analyzing a security and reliability model using Krylov methods and matrix functions
Masetti G., Robol L.
It has been recently shown how the computation of performability measures for Markov models can be recasted as the evaluation of a bilinear forminduced by appropriate matrix functions. In view of these results, we show how to analyze a security model, inspired by a real world scenario. The model describes a mobile cyber-physical system of communicating nodes which are subject to security attacks. We take advantage of the properties of matrix functions of block matrices, and provide efficient evaluation methods.Moreover, we show how this new formulation can be used to retrieve interesting theoretical results, which can also rephrased in probabilistic terms.Source: ISTI Technical reports, 2018
Masetti G., Robol L.
It has been recently shown how the computation of performability measures for Markov models can be recasted as the evaluation of a bilinear forminduced by appropriate matrix functions. In view of these results, we show how to analyze a security model, inspired by a real world scenario. The model describes a mobile cyber-physical system of communicating nodes which are subject to security attacks. We take advantage of the properties of matrix functions of block matrices, and provide efficient evaluation methods.Moreover, we show how this new formulation can be used to retrieve interesting theoretical results, which can also rephrased in probabilistic terms.Source: ISTI Technical reports, 2018
See at:
ISTI Repository | CNR ExploRA
2019
Report
Open Access
Tensor methods for the computation of MTTF in large systems of loosely interconnected components
Masetti G., Robol L.
We are concerned with the computation of the mean-time-to-failure(MTTF) for a large system of loosely interconnected components, mod-eled as continuous time Markov chains. In particular, we show that split-ting the local and synchronization transitions of the smaller subsystemsallows to formulate an algorithm for the computation of the MTTF whichis proven to be linearly convergent. Then, we show how to modify themethod to make it quadratically convergent, thus overcoming the difficul-ties for problems with convergent rate close to1.In addition, it is shown that this decoupling of local and synchroniza-tion transitions allows to easily represent all the matrices and vectors in-volved in the method in the tensor-train (TT) format -- and we providenumerical evidence showing that this allows to treat large problems withup to billions of states -- which would otherwise be unfeasible.Source: ISTI Technical reports, 2019
Masetti G., Robol L.
We are concerned with the computation of the mean-time-to-failure(MTTF) for a large system of loosely interconnected components, mod-eled as continuous time Markov chains. In particular, we show that split-ting the local and synchronization transitions of the smaller subsystemsallows to formulate an algorithm for the computation of the MTTF whichis proven to be linearly convergent. Then, we show how to modify themethod to make it quadratically convergent, thus overcoming the difficul-ties for problems with convergent rate close to1.In addition, it is shown that this decoupling of local and synchroniza-tion transitions allows to easily represent all the matrices and vectors in-volved in the method in the tensor-train (TT) format -- and we providenumerical evidence showing that this allows to treat large problems withup to billions of states -- which would otherwise be unfeasible.Source: ISTI Technical reports, 2019
See at:
dcl.isti.cnr.it | ISTI Repository | CNR ExploRA
2019
Conference article
Open Access
Distinguishing Violinists and Pianists Based on Their Brain Signals
Coro G., Masetti G., Bonhoeffer P., Betcher M.
Many studies in neuropsychology have highlighted that expert musicians, who started learning music in childhood, present structural differences in their brains with respect to non-musicians. This indicates that early music learning affects the development of the brain. Also, musicians' neuronal activity is different depending on the played instrument and on the expertise. This difference can be analysed by processing electroencephalographic (EEG) signals through Artificial Intelligence models. This paper explores the feasibility to build an automatic model that distinguishes violinists from pianists based only on their brain signals. To this aim, EEG signals of violinists and pianists are recorded while they play classical music pieces and an Artificial Neural Network is trained through a cloud computing platform to build a binary classifier of segments of these signals. Our model has the best classification performance on 20 seconds EEG segments, but this performance depends on the involved musicians' expertise. Also, the brain signals of a cellist are demonstrated to be more similar to violinists' signals than to pianists' signals. In summary, this paper demonstrates that distinctive information is present in the two types of musicians' brain signals, and that this information can be detected even by an automatic model working with a basic EEG equipment.Source: ICANN 2019: Theoretical Neural Computation 28th International Conference on Artificial Neural Networks, pp. 123–137, Monaco di Baviera, 17-19/10/2019
DOI: 10.1007/978-3-030-30487-4_11
Metrics:
Coro G., Masetti G., Bonhoeffer P., Betcher M.
Many studies in neuropsychology have highlighted that expert musicians, who started learning music in childhood, present structural differences in their brains with respect to non-musicians. This indicates that early music learning affects the development of the brain. Also, musicians' neuronal activity is different depending on the played instrument and on the expertise. This difference can be analysed by processing electroencephalographic (EEG) signals through Artificial Intelligence models. This paper explores the feasibility to build an automatic model that distinguishes violinists from pianists based only on their brain signals. To this aim, EEG signals of violinists and pianists are recorded while they play classical music pieces and an Artificial Neural Network is trained through a cloud computing platform to build a binary classifier of segments of these signals. Our model has the best classification performance on 20 seconds EEG segments, but this performance depends on the involved musicians' expertise. Also, the brain signals of a cellist are demonstrated to be more similar to violinists' signals than to pianists' signals. In summary, this paper demonstrates that distinctive information is present in the two types of musicians' brain signals, and that this information can be detected even by an automatic model working with a basic EEG equipment.Source: ICANN 2019: Theoretical Neural Computation 28th International Conference on Artificial Neural Networks, pp. 123–137, Monaco di Baviera, 17-19/10/2019
DOI: 10.1007/978-3-030-30487-4_11
Metrics:
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ISTI Repository | doi.org | link.springer.com | CNR ExploRA
2020
Journal article
Open Access
Computing performability measures in Markov chains by means of matrix functions
Masetti G., Robol L.
We discuss the efficient computation of performance, reliability, and availability measures for Markov chains; these metrics - and the ones obtained by combining them, are often called performability measures. We show that this computational problem can be recasted as the evaluation of a bilinear form induced by appropriate matrix functions, and thus solved by leveraging the fast methods available for this task.Source: Journal of computational and applied mathematics 368 (2020). doi:10.1016/j.cam.2019.112534
DOI: 10.1016/j.cam.2019.112534
DOI: 10.48550/arxiv.1803.06322
Metrics:
Masetti G., Robol L.
We discuss the efficient computation of performance, reliability, and availability measures for Markov chains; these metrics - and the ones obtained by combining them, are often called performability measures. We show that this computational problem can be recasted as the evaluation of a bilinear form induced by appropriate matrix functions, and thus solved by leveraging the fast methods available for this task.Source: Journal of computational and applied mathematics 368 (2020). doi:10.1016/j.cam.2019.112534
DOI: 10.1016/j.cam.2019.112534
DOI: 10.48550/arxiv.1803.06322
Metrics:
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arXiv.org e-Print Archive | Journal of Computational and Applied Mathematics | ISTI Repository | ISTI Repository | Journal of Computational and Applied Mathematics | doi.org | www.sciencedirect.com | CNR ExploRA
2020
Conference article
Open Access
Analyzing Forward Robustness of Feedforward Deep Neural Networks with LeakyReLU Activation Function Through Symbolic Propagation
Masetti G., Di Giandomenico F.
FeedForward Deep Neural Networks (DNNs) robustness is a relevant property to study, since it allows to establish whether the classification performed by DNNs is vulnerable to small perturbations in the provided input, and several verification approaches have been developed to assess such robustness degree. Recently, an approach has been introduced to evaluate forward robustness, based on symbolic computations and designed for the ReLU activation function. In this paper, a generalization of such a symbolic approach for the widely adopted LeakyReLU activation function is developed. A preliminary numerical campaign, briefly discussed in the paper, shows interesting results.Source: Joint European Conference on Machine Learning and Knowledge Discovery in Databases, pp. 460–474, 14/09/2020
DOI: 10.1007/978-3-030-65965-3_31
Metrics:
Masetti G., Di Giandomenico F.
FeedForward Deep Neural Networks (DNNs) robustness is a relevant property to study, since it allows to establish whether the classification performed by DNNs is vulnerable to small perturbations in the provided input, and several verification approaches have been developed to assess such robustness degree. Recently, an approach has been introduced to evaluate forward robustness, based on symbolic computations and designed for the ReLU activation function. In this paper, a generalization of such a symbolic approach for the widely adopted LeakyReLU activation function is developed. A preliminary numerical campaign, briefly discussed in the paper, shows interesting results.Source: Joint European Conference on Machine Learning and Knowledge Discovery in Databases, pp. 460–474, 14/09/2020
DOI: 10.1007/978-3-030-65965-3_31
Metrics:
See at:
ISTI Repository | doi.org | link.springer.com | CNR ExploRA
2020
Conference article
Open Access
Failure management strategies for IoT-based railways systems
Righetti F., Vallati C., Anastasi G., Masetti G., Di Giandomenico F.
Railways monitoring and control are currently performed by different heterogeneous vertical systems working in isolation without or with limited cooperation among them. Such configuration, widely adopted in practical deployments today, is in contrast with the integrated vision of systems that are at the foundation of the smart-city concept. In order to overcome the current fractured ecosystem that monitors and controls railways functionalities, the adoption of a novel integrated approach is mandatory to create an all-in-one railway system. To this aim, new IoT-based communication technologies, like wireless or Power Line Communication technologies, are considered the main enablers to integrate in a very rapid and easy manner existing vertical systems. In this work, we analyse the architecture of future railways systems based on a mix of wireless and Power Line Communication technologies. In our analysis, we aim at studying possible failure management strategies on rail-road switches to improve the level of reliability, crucial requirement for systems that demand maximum resiliency as they manage a critical function of the infrastructure. In particular, we propose a set of solutions aimed at detecting and handling network and sensor failures to ensure continuity in the execution of the basic control functions. The proposed approach is evaluated by means of simulations and demonstrated to be effective in ensuring a good level of performance even when failures occur.Source: 2020 IEEE International Conference on Smart Computing, pp. 386–391, Bologna, 14-17/09/2020
DOI: 10.1109/smartcomp50058.2020.00082
Metrics:
Righetti F., Vallati C., Anastasi G., Masetti G., Di Giandomenico F.
Railways monitoring and control are currently performed by different heterogeneous vertical systems working in isolation without or with limited cooperation among them. Such configuration, widely adopted in practical deployments today, is in contrast with the integrated vision of systems that are at the foundation of the smart-city concept. In order to overcome the current fractured ecosystem that monitors and controls railways functionalities, the adoption of a novel integrated approach is mandatory to create an all-in-one railway system. To this aim, new IoT-based communication technologies, like wireless or Power Line Communication technologies, are considered the main enablers to integrate in a very rapid and easy manner existing vertical systems. In this work, we analyse the architecture of future railways systems based on a mix of wireless and Power Line Communication technologies. In our analysis, we aim at studying possible failure management strategies on rail-road switches to improve the level of reliability, crucial requirement for systems that demand maximum resiliency as they manage a critical function of the infrastructure. In particular, we propose a set of solutions aimed at detecting and handling network and sensor failures to ensure continuity in the execution of the basic control functions. The proposed approach is evaluated by means of simulations and demonstrated to be effective in ensuring a good level of performance even when failures occur.Source: 2020 IEEE International Conference on Smart Computing, pp. 386–391, Bologna, 14-17/09/2020
DOI: 10.1109/smartcomp50058.2020.00082
Metrics:
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ISTI Repository | doi.org | ieeexplore.ieee.org | CNR ExploRA
2016
Conference article
Restricted
A stochastic modelling framework to analyze smart grids control strategies
Chiaradonna S., Di Giandomenico F., Masetti G.
Smart grids provide services at the basis of a number of application sectors, several of which are critical from the perspective of human life, environment or financials. It is therefore paramount to be assisted by technologies able to analyze the smart grid behavior in critical scenarios, e.g. where cyber malfunctions or grid disruptions occur. In this paper, we present a stochastic modelling framework to quantitatively assess representative indicators of the resilience and quality of service of the distribution grid, in presence of accidental faults and malicious attacks. The results from the performed analysis can be exploited to understand the dynamics of failures and to identify potential system vulnerabilities, against which appropriate countermeasures should be developed. The features of the proposed analysis framework are discussed, pointing out the strong non-linearity of the involved physics, the developed solutions to deal with control actions and the definition of indicators under analysis. A case study based on a real-world network is also presented.Source: SEGE 2016 - 4th IEEE International Conference on Smart Energy Grid Engineering, pp. 123–130, Oshawa, Canada, 21-24 August 2016
DOI: 10.1109/sege.2016.7589512
Metrics:
Chiaradonna S., Di Giandomenico F., Masetti G.
Smart grids provide services at the basis of a number of application sectors, several of which are critical from the perspective of human life, environment or financials. It is therefore paramount to be assisted by technologies able to analyze the smart grid behavior in critical scenarios, e.g. where cyber malfunctions or grid disruptions occur. In this paper, we present a stochastic modelling framework to quantitatively assess representative indicators of the resilience and quality of service of the distribution grid, in presence of accidental faults and malicious attacks. The results from the performed analysis can be exploited to understand the dynamics of failures and to identify potential system vulnerabilities, against which appropriate countermeasures should be developed. The features of the proposed analysis framework are discussed, pointing out the strong non-linearity of the involved physics, the developed solutions to deal with control actions and the definition of indicators under analysis. A case study based on a real-world network is also presented.Source: SEGE 2016 - 4th IEEE International Conference on Smart Energy Grid Engineering, pp. 123–130, Oshawa, Canada, 21-24 August 2016
DOI: 10.1109/sege.2016.7589512
Metrics:
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doi.org | ieeexplore.ieee.org | CNR ExploRA
2016
Conference article
Restricted
Exploring equations ordering influence on variants of the Newton-Raphson method
Masetti G., Chiaradonna S., Di Giandomenico F.
Jacobian-free Newton-Raphson methods are general purpose iterative non-linear system solvers. The need to solve non-linear systems is ubiquitous throughout computational physics [1] and Jacobian-free Newton-Raphson methods can offer scalability, super-linear convergence and applicability. In fact, applications span from discretized PDEs [2] to power-flow problems [3]. The focus of this article is on Inexact-Newton-Krylov [2] and Quasi-Inverse-Newton [4] methods. For both of them, we prove analytically that the initial ordering of the equations can have a great impact on the numerical solution, as well as on the number of iterations to reach the solution. We also present numerical results obtained from a simple but representative case study, to quantify the impact of initial equations ordering on a concrete scenario.Source: 2ND International Conference "Numerical Computations: Theory and Algorithms", pp. 090053–090055, Pizzo Calabro, Italy, 19-25 June 2016
DOI: 10.1063/1.4965417
Metrics:
Masetti G., Chiaradonna S., Di Giandomenico F.
Jacobian-free Newton-Raphson methods are general purpose iterative non-linear system solvers. The need to solve non-linear systems is ubiquitous throughout computational physics [1] and Jacobian-free Newton-Raphson methods can offer scalability, super-linear convergence and applicability. In fact, applications span from discretized PDEs [2] to power-flow problems [3]. The focus of this article is on Inexact-Newton-Krylov [2] and Quasi-Inverse-Newton [4] methods. For both of them, we prove analytically that the initial ordering of the equations can have a great impact on the numerical solution, as well as on the number of iterations to reach the solution. We also present numerical results obtained from a simple but representative case study, to quantify the impact of initial equations ordering on a concrete scenario.Source: 2ND International Conference "Numerical Computations: Theory and Algorithms", pp. 090053–090055, Pizzo Calabro, Italy, 19-25 June 2016
DOI: 10.1063/1.4965417
Metrics:
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doi.org | scitation.aip.org | CNR ExploRA
2016
Conference article
Restricted
Analyzing the Impact of Failures in the Electric Power Distribution Grid
Chiaradonna S., Di Giandomenico F., Masetti G.
The electric power system is among the most critical infrastructures, being a support for many of them and for key resource sectors. In fact, the complex, digital world around us requires electric power for fundamental aspects of most business and consumer activities. Therefore, it is paramount to assure the correct power supply. Following the increasing trend in electricity generation from renewable sources, pushed by the need to meet sustainable energy goals in many countries, more sophisticated control strategies are being adopted to regulate the operation of the electric power system. Analyzing their effectiveness and ability to face operation in critical scenarios, such as in presence of failures, is certainly a relevant aspect to investigate. In this paper we focus on the medium voltage grid control and adopt a stochastic modeling framework appropriate to analyze voltage control strategies in presence of selected failure scenarios. The impact of the addressed failures on indicators of voltage stability, representative of the resilience shown by the analyzed system, is assessed in a real-world reference grid. Variability in both generation and loads is covered, to reflect realistic contexts where the addressed system is called to operate.Source: Seventh Latin-American Symposium on Dependable Computing, pp. 99–108, Calì, Colombia, 19-21 October 2016
DOI: 10.1109/ladc.2016.23
Metrics:
Chiaradonna S., Di Giandomenico F., Masetti G.
The electric power system is among the most critical infrastructures, being a support for many of them and for key resource sectors. In fact, the complex, digital world around us requires electric power for fundamental aspects of most business and consumer activities. Therefore, it is paramount to assure the correct power supply. Following the increasing trend in electricity generation from renewable sources, pushed by the need to meet sustainable energy goals in many countries, more sophisticated control strategies are being adopted to regulate the operation of the electric power system. Analyzing their effectiveness and ability to face operation in critical scenarios, such as in presence of failures, is certainly a relevant aspect to investigate. In this paper we focus on the medium voltage grid control and adopt a stochastic modeling framework appropriate to analyze voltage control strategies in presence of selected failure scenarios. The impact of the addressed failures on indicators of voltage stability, representative of the resilience shown by the analyzed system, is assessed in a real-world reference grid. Variability in both generation and loads is covered, to reflect realistic contexts where the addressed system is called to operate.Source: Seventh Latin-American Symposium on Dependable Computing, pp. 99–108, Calì, Colombia, 19-21 October 2016
DOI: 10.1109/ladc.2016.23
Metrics:
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doi.org | ieeexplore.ieee.org | CNR ExploRA
2016
Contribution to conference
Open Access
Efficient non-anonymous composition operator for modeling complex dependable systems
Chiaradonna S., Di Giandomenico F., Masetti G.
A new model composer is proposed to automatically generate non-anonymous model replicas in the context of performability and dependability evaluation. It is a state-sharing composer that extends the standard anonymous replication composer in order to share the state of a replica among a set of other specific replicas or among the replica and another external model. This new composition operator aims to improve expressiveness and performance with respect to the standard anonymous replicator, namely the one adopted by the Mobius modeling framework.Source: EDCC 2016 - 12nd European Dependable Computing Conference, Gothenburg, Sweden, 5-9 September 2016
Chiaradonna S., Di Giandomenico F., Masetti G.
A new model composer is proposed to automatically generate non-anonymous model replicas in the context of performability and dependability evaluation. It is a state-sharing composer that extends the standard anonymous replication composer in order to share the state of a replica among a set of other specific replicas or among the replica and another external model. This new composition operator aims to improve expressiveness and performance with respect to the standard anonymous replicator, namely the one adopted by the Mobius modeling framework.Source: EDCC 2016 - 12nd European Dependable Computing Conference, Gothenburg, Sweden, 5-9 September 2016
See at:
arxiv.org | CNR ExploRA
2017
Contribution to conference
Open Access
How the availability of free satellite data can improve the observation of critical infrastructures: a proposed application to landfills for municipal solid wastes
Scozzari A., Masetti G., Raco B., Battaglini R.
Landfills for Municipal Solid Wastes (MSW) produce about 20% of the total anthropogenic methane released to the atmosphere. As a consequence, these infrastructures require a systematic and efficient monitoring. Various techniques have been proposed until now for the estimation of biogas production and its release, by using more or less direct measurements, mostly characterised by a low or completely absent invasivity. During the last 13 years, observational data about a MSW disposal site located in Tuscany (Italy) have been collected on a regular basis, consisting in direct measurements of gas flux with the accumulation chamber method, combined with infrared radiometry performed in situ with portable radiometers. The availability of free Landsat imagery and the more recent availability of ASTER data (freely available since April 2016) open new monitoring possibilities, in addition to the in situ measurements described above. In particular, we present the preliminary results of a study about the usability of low resolution thermal infrared scenes to build timeseries describing the overall status of a waste disposal site. This work discusses the possibility to complement in situ measurements with satellite observations, taking benefit from the high revisit time with respect to the timings of in situ campaigns.Source: EGU 2017 - General Assemblies of the European Geosciences Union, Vienna, Austria, 23-28 April 2017
Scozzari A., Masetti G., Raco B., Battaglini R.
Landfills for Municipal Solid Wastes (MSW) produce about 20% of the total anthropogenic methane released to the atmosphere. As a consequence, these infrastructures require a systematic and efficient monitoring. Various techniques have been proposed until now for the estimation of biogas production and its release, by using more or less direct measurements, mostly characterised by a low or completely absent invasivity. During the last 13 years, observational data about a MSW disposal site located in Tuscany (Italy) have been collected on a regular basis, consisting in direct measurements of gas flux with the accumulation chamber method, combined with infrared radiometry performed in situ with portable radiometers. The availability of free Landsat imagery and the more recent availability of ASTER data (freely available since April 2016) open new monitoring possibilities, in addition to the in situ measurements described above. In particular, we present the preliminary results of a study about the usability of low resolution thermal infrared scenes to build timeseries describing the overall status of a waste disposal site. This work discusses the possibility to complement in situ measurements with satellite observations, taking benefit from the high revisit time with respect to the timings of in situ campaigns.Source: EGU 2017 - General Assemblies of the European Geosciences Union, Vienna, Austria, 23-28 April 2017
See at:
meetingorganizer.copernicus.org | ISTI Repository | CNR ExploRA
2017
Conference article
Open Access
A stochastic modeling approach for an efficient dependability evaluation of large systems with non-anonymous interconnected components
Chiaradonna S., Di Giandomenico F., Masetti G.
This paper addresses the generation of stochastic models for dependability and performability analysis of complex systems, through automatic replication of template models. The proposed solution is tailored to systems composed by large populations of similar non-anonymous components, interconnected with each other according to a variety of topologies. A new efficient replication technique is presented and its implementation is discussed. The goal is to improve the performance of simulation solvers with respect to standard approaches, when employed in the modeling of the addressed class of systems, in particular for loosely interconnected system components (as typically encountered in the electrical or transportation sectors). Effectiveness of the new technique is demonstrated by comparison with a state of the art alternative solution on a representative case study.Source: Internationa Symposium on Software Reliability Engineering, pp. 46–55, Tolosa, Francia, 23-26/10/2017
DOI: 10.1109/issre.2017.17
Metrics:
Chiaradonna S., Di Giandomenico F., Masetti G.
This paper addresses the generation of stochastic models for dependability and performability analysis of complex systems, through automatic replication of template models. The proposed solution is tailored to systems composed by large populations of similar non-anonymous components, interconnected with each other according to a variety of topologies. A new efficient replication technique is presented and its implementation is discussed. The goal is to improve the performance of simulation solvers with respect to standard approaches, when employed in the modeling of the addressed class of systems, in particular for loosely interconnected system components (as typically encountered in the electrical or transportation sectors). Effectiveness of the new technique is demonstrated by comparison with a state of the art alternative solution on a representative case study.Source: Internationa Symposium on Software Reliability Engineering, pp. 46–55, Tolosa, Francia, 23-26/10/2017
DOI: 10.1109/issre.2017.17
Metrics:
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ISTI Repository | doi.org | ieeexplore.ieee.org | CNR ExploRA
2017
Conference article
Restricted
Model-based simulation in möbius: An efficient approach targeting loosely interconnected components
Masetti G., Chiaradonna S., Di Giandomenico F.
This paper addresses the generation of stochastic models for dependability and performability analysis of complex systems, through automatic replication of template models inside the Möbius modeling framework. The proposed solution is tailored to systems composed by large populations of similar non-anonymous components, loosely interconnected with each other (as typically encountered in the electrical or transportation sectors). The approach is based on models that define channels shared among replicas, used to exchange the values of each state variable of a replica with the other replicas that need to use them. The goal is to improve the performance of simulation based solvers with respect to the existing state-sharing approach, when employed in the modeling of the addressed class of systems. Simulation results for the time overheads induced by both channel-sharing and state-sharing approaches for different system scenarios are presented and discussed. They confirm the expected gain in efficiency of the proposed channel-sharing approach in the addressed system context.Source: European Workshop on Performance Engineering, pp. 184–198, Berlino, 7-8/09/2017
DOI: 10.1007/978-3-319-66583-2_12
Metrics:
Masetti G., Chiaradonna S., Di Giandomenico F.
This paper addresses the generation of stochastic models for dependability and performability analysis of complex systems, through automatic replication of template models inside the Möbius modeling framework. The proposed solution is tailored to systems composed by large populations of similar non-anonymous components, loosely interconnected with each other (as typically encountered in the electrical or transportation sectors). The approach is based on models that define channels shared among replicas, used to exchange the values of each state variable of a replica with the other replicas that need to use them. The goal is to improve the performance of simulation based solvers with respect to the existing state-sharing approach, when employed in the modeling of the addressed class of systems. Simulation results for the time overheads induced by both channel-sharing and state-sharing approaches for different system scenarios are presented and discussed. They confirm the expected gain in efficiency of the proposed channel-sharing approach in the addressed system context.Source: European Workshop on Performance Engineering, pp. 184–198, Berlino, 7-8/09/2017
DOI: 10.1007/978-3-319-66583-2_12
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doi.org | link.springer.com | CNR ExploRA
2019
Journal article
Open Access
On Extending and Comparing Newton-Raphson Variants for Solving Power-Flow Equations
Dutto S., Masetti G., Chiaradonna S., Di Giandomenico F.
This paper focuses on power-flow equations solutions, based on the Newton-Raphson method. Two major contributions are offered. First, the definition of novel solution variants, resorting to Wirtinger calculus, is attempted. The obtained developments, although original in their formulation, led to already known variants. Despite the impaired originality of the obtained solution, there are significant lessons learned from such an effort. The second major contribution consists of a deep comparison analysis of existing solution strategies, based on complex and real variables, and the Wirtinger based ones, all properly reformulated to allow direct comparison with each other. The goal is to investigate strengths and weaknesses of the addressed techniques in terms of computational effort and convergence rate, which are the most relevant aspects to consider while choosing the approach to employ to solve power-flow equations for a specific power system under study.Source: IEEE transactions on power systems 34 (2019): 2577–2587. doi:10.1109/TPWRS.2019.2897640
DOI: 10.1109/tpwrs.2019.2897640
Metrics:
Dutto S., Masetti G., Chiaradonna S., Di Giandomenico F.
This paper focuses on power-flow equations solutions, based on the Newton-Raphson method. Two major contributions are offered. First, the definition of novel solution variants, resorting to Wirtinger calculus, is attempted. The obtained developments, although original in their formulation, led to already known variants. Despite the impaired originality of the obtained solution, there are significant lessons learned from such an effort. The second major contribution consists of a deep comparison analysis of existing solution strategies, based on complex and real variables, and the Wirtinger based ones, all properly reformulated to allow direct comparison with each other. The goal is to investigate strengths and weaknesses of the addressed techniques in terms of computational effort and convergence rate, which are the most relevant aspects to consider while choosing the approach to employ to solve power-flow equations for a specific power system under study.Source: IEEE transactions on power systems 34 (2019): 2577–2587. doi:10.1109/TPWRS.2019.2897640
DOI: 10.1109/tpwrs.2019.2897640
Metrics:
See at:
ISTI Repository | IEEE Transactions on Power Systems | ieeexplore.ieee.org | CNR ExploRA