Titlebook: Critical Infrastructures, Key Resources, Key Assets; Risk, Vulnerability, Adrian V. Gheorghe,Dan V. Vamanu,Roland Pulfer Book 2018 Springer

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Critical Infrastructures, Key Resources, and Key Assetsnition of the notions, explain their relevance and also the need to develop intelligible and robust models to diagnose and predict risks, vulnerability, resilience, fragility, and perception. This chapter reveals space, undersea, and belowground as three privileged sectors of human endeavor were cri

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Governance Vulnerability Facetsperational vulnerability, managerial vulnerability, and relational vulnerability. These notions are presented in view of . (QVA), which is a method to diagnose vulnerability in complex systems with a focus on strategies that could be undertaken for sustained system development. Theory supporting QVA

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Nuclear Reactors Vulnerability Assessment—A Generic Modelt system’s monitored parameters may be aggregated such that the control variables, . and . of the cuspidal stability model for vulnerability analysis be obtained. In addition, one ought to submit that . and . are membership functions of a fuzzy theory set of impact indicators. In this chapter, the e

反叛者

Emerging Space Treats and Satellitesndreds of thousands of readers to delve into the large world of mathematics. In one of his columns (January, 2007), he glossed over the issue of anti-satellite weaponry. In a few basic lines of Physics and a computer simulation, one is able to ‘illustrate’ the feeling that the space, while critical

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Managerial Vulnerability Assessment Modelsge of situations. Clearly, this leaves us with changes of enjoying or suffering the outcomes good or bad, respectively. At the same time, one might contend that that are means of increasing changes that the decision being make is ‘good.’ In this line of thinking, it is generally accepted that making

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Airborne Emissions and Territorial Vulnerability Assessmentscussed along with break points for chemical and radioactive release. Then the atmospheric dispersion model and its equations are discussed. The main capability of the model, as a decision support system (DSS) code, is to tell consequences of single and multiple releases of widely different duration

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System Resilience Governancecepts, and solutions to document, understand, analyze, operate, control, and transform critical infrastructure as a whole or in parts. It is not new that critical infrastructures are highly interconnected and collaborative and therefore susceptible to domino effects supported by their systemic depen

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The Case for Sihl Damk event. Note that the modeling is limited to a ‘worst case scenario’ describing a full destruction of the dam wall within a short time span and the consequent release of the whole water reservoir volume. To compare results and show the strength of the proposed model and the associated decision supp