18 research outputs found
A Bayesian Network Approach for the Interpretation of Cyber Attacks to Power Systems
The focus of this paper is on the analysis of the cyber security
resilience of digital infrastructures deployed by power grids, internationally recognized as a priority since several recent cyber attacks targeted
energy systems and in particular the power service. In response to the
regulatory framework, this paper presents an analysis approach based
on the Bayesian Networks formalism and on real world threat scenarios.
Our approach enables analyses oriented to planning of security measures
and monitoring, and to forecasting of adversarial behaviours
Analisi e rilevamento intelligente di processi di attacco alle Smart-Grid
Proponiamo una metodologia basata sulle Reti Bayesiane come strumento di supporto all’analisi della sicurezza di Smart Grid, ed in particolare per la previsione di intrusioni e attività ostili
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A meta-cognitive account for the impact of implausible suggestions on estimations
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Cortical systems for local and global integration in discourse comprehension
To understand language, we integrate what we hear or read with prior context. This research investigates the neural systems underlying this integration process, in particular the integration of incoming linguistic information with local, proximal context and with global, distal context. The experiments used stories whose endings were locally consistent or locally inconsistent. In addition, the stories' global context was either relevant or irrelevant for the integration of the endings. In Experiment 1, reading latencies showed that the perceived consistency of an ending depended on its fit with the local context, but the availability of a relevant global context attenuated this effect. Experiment 2 used BOLD fMRI to study whether different neural systems are sensitive to the local consistency of the endings and the relevance of the global context. A first analysis evaluated BOLD responses during the comprehension of story endings. It identified three networks: one sensitive to consistency with local context, one sensitive to the relevance of the global context, and one sensitive to both factors. These findings suggest that some regions respond to the holistic relation of local and global contexts while others track only the global or the local contexts. A second analysis examined correlations between BOLD activity during listening of the story endings and subsequent memory for those endings. It revealed two distinct networks: Positive correlations in areas usually involved in semantic processing and memory for language, and negative correlations in sensory, motor, and visual areas, indicating that weaker activity in the latter regions is conducive to better memory for linguistic content. More widespread memory correlates were found when global context was relevant for understanding a story ending. We conclude that integration at the discourse level involves the cooperation of different networks each sensitive to separate aspects of the task, and that integration is more successfully achieved when the processing of potentially distracting information is reduced.Psycholog
Assessment of Excess Mortality in Italy in 2020–2021 as a Function of Selected Macro-Factors
Background: Excess mortality (EM) can reliably capture the impact of a pandemic, this study aims at assessing the numerous factors associated with EM during the COVID-19 pandemic in Italy. Methods: Mortality records (ISTAT 2015–2021) aggregated in the 610 Italian Labour Market Areas (LMAs) were used to obtain the EM P-scores to associate EM with socioeconomic variables. A two-step analysis was implemented: (1) Functional representation of EM and clustering. (2) Distinct functional regression by cluster. Results: The LMAs are divided into four clusters: 1 low EM; 2 moderate EM; 3 high EM; and 4 high EM-first wave. Low-Income showed a negative association with EM clusters 1 and 4. Population density and percentage of over 70 did not seem to affect EM significantly. Bed availability positively associates with EM during the first wave. The employment rate positively associates with EM during the first two waves, becoming negatively associated when the vaccination campaign began. Conclusions: The clustering shows diverse behaviours by geography and time, the impact of socioeconomic characteristics, and local governments and health services’ responses. The LMAs allow to draw a clear picture of local characteristics associated with the spread of the virus. The employment rate trend confirmed that essential workers were at risk, especially during the first wave