Ecological risk assessment of hydropower dam construction based on ecological network analysis

Dam construction is regarded as one of the major factors contributing to significant modifications of the river ecosystems, and the ecological risk (ER) assessment of dam construction has received growing attention in recent years. In the present study, we explored the potential ecological risk caused by dam project based on the general principles of the ecological risk assessment. Ecological network analysis was proposed as the usable analytic method for the implement of ecological risk assessment, thus contributing to the modelling of dam-induced risk process. Applying ecological network analysis to the ecological risk assessment of river ecosystems after dam construction, this study may provide important insights into the understanding of how an affected river ecosystem reacts to the artificial perturbation on a whole-ecosystem scale

Why Risk Models should be Parameterised

Risk models using fault and event trees can be extended with explicit factors, which are states of the system, its users or its environment that influence event probabilities. The factors act as parameters in the risk model, enabling the model to be re-used and also providing a new way to estimate the overall risk of a system with many instances of the risk. A risk model with parameters can also be clearer

Application des réseaux bayésiens à la planification de la réponse à une attaque de pirates contre un champ pétrolier

International audienceCes dernières années, les attaques de pirates contre des navires ou des champs pétroliers n'ont cessé de se multiplier et de s'aggraver. Pour faire face à ce problème, le système SARGOS se présente comme une solution innovante prenant en compte toute la chaîne de traitement depuis la détection d'une menace potentielle jusqu'à la mise en oeuvre de la réaction. Pour réagir contre une attaque, il faut considérer de nombreux paramètres relatifs à la menace, la cible potentielle, les dispositifs de protection mis en place, les contraintes liées à l'environnement, etc. Pour gérer ces paramètres, les potentialités des réseaux bayésiens sont exploitées afin de définir les contre-mesures possibles ainsi que leur mode de gestion / In recent years, pirates attacks against ships or oil platforms have continued to multiply and get worse. To address this problem, the SARGOS system is as an innovative solution taking account the whole processing chain from detection of a potential threat to the implementation of the reaction. To react against an attack, we should consider many parameters of the threat, the potential target, the existing protection tools, the environment constraints, etc. To manage these parameters, the potentials of Bayesian Networks are used to identify feasible counterattacks and their managemen

Integration of a Bayesian network for response planning in a maritime piracy risk management system

International audienceThis article describes an innovative system to protect offshore oil infrastructure against maritime piracy. To detect and respond efficiently to this threat, many factors must be taken into account, including the potential target, the protection methods already in place and operational and environmental constraints, etc. To improve the handling of this complex issue, we have designed a system to manage the entire processing chain; from threat identification to implementation of the response. The system implements Bayesian networks in order to capture the multitude of parameters and their inherent uncertainties, and to identify and manage potential responses. This article describes the system architecture, the integrated Bayesian network and its contribution to response planning

Apports des réseaux bayésiens pour la sûreté et la mise en sécurité des infrastructures pétrolières offshore

National audienceCes dernières années, les attaques de pirates contre des navires ou des champs pétroliers n'ont cessé de se multiplier et de s'aggraver. Pour exemple, l'attaque contre la plate-forme pétrolière Exxon Mobil en 2010 au large du Nigeria s'est soldée par l'enlèvement de dix neuf membres d'équipage et la réduction de 45.000 barils de sa production pétrolière quotidienne ce qui a engendré une montée des prix à l'échelle internationale. Cet exemple est une parfaite illustration de la faiblesse actuelle des dispositifs anti-piraterie existants. Pour faire face à ce problème, le projet SARGOS propose un système innovant prenant en compte toute la chaine de traitement depuis la détection d'une menace potentielle jusqu'à la mise en oeuvre de la réaction. Pour réagir contre une attaque, il faut considérer de nombreux paramètres relatifs à la menace, la cible potentielle, les dispositifs de protection mis en place, les contraintes liées à l'environnement, etc. Pour gérer ces paramètres, les potentialités des réseaux bayésiens sont exploitées afin de définir les contre-mesures possibles ainsi que leur mode de gestion

Bayesian Networks in the Management of Oil Field Piracy Risk

International audienceIn recent years, pirate attacks against shipping and oil field installations have become more frequent and more serious. The SARGOS system provides an innovative solution that addresses the problem from the perspective of the entire processing chain; from the detection of a potential threat to the implementation of a response. The response to an attack must take into account multiple variables: the characteristics of the threat and the potential target, existing protection tools, environmental constraints, etc. The potential of Bayesian networks is used to manage this large number of parameters and identify appropriate counter-measures

Conception d'un réseau bayésien pour la prévention du risque de piraterie contre les champs pétroliers

International audienceCes dernières années, les attaques de pirates contre des navires ou des champs pétroliers n'ont cessé de se multiplier et de s'aggraver. Pour faire face à ce problème et réagir contre une attaque, il faut considérer de nombreux paramètres relatifs à la menace, la cible potentielle, les dispositifs de protection mis en place, les contraintes liées à l'environnement, etc. Pour gérer ces paramètres, les potentialités des réseaux bayésiens sont exploitées afin de définir les contre-mesures possibles ainsi que leur mode de gestion

Product risk assessment: a Bayesian network approach

Product risk assessment is the overall process of determining whether a product, which could be anything from a type of washing machine to a type of teddy bear, is judged safe for consumers to use. There are several methods used for product risk assessment, including RAPEX, which is the primary method used by regulators in the UK and EU. However, despite its widespread use, we identify several limitations of RAPEX including a limited approach to handling uncertainty and the inability to incorporate causal explanations for using and interpreting test data. In contrast, Bayesian Networks (BNs) are a rigorous, normative method for modelling uncertainty and causality which are already used for risk assessment in domains such as medicine and finance, as well as critical systems generally. This article proposes a BN model that provides an improved systematic method for product risk assessment that resolves the identified limitations with RAPEX. We use our proposed method to demonstrate risk assessments for a teddy bear and a new uncertified kettle for which there is no testing data and the number of product instances is unknown. We show that, while we can replicate the results of the RAPEX method, the BN approach is more powerful and flexible

A Bayesian network to manage risks of maritime piracy against offshore oil fields

International audienceIn recent years, pirate attacks against shipping and oil field installations have become more frequent and more serious. This article proposes an innovative solution to the problem of offshore piracy from the perspective of the entire processing chain: from the detection of a potential threat to the implementation of a response. The response to an attack must take into account multiple variables: the characteristics of the threat and the potential target, existing protection tools, environmental constraints, etc. The potential of Bayesian networks is used to manage this large number of parameters and identify appropriate counter-measures

Las Redes Bayesianas como herramienta para la evaluación del riesgo de reincidencia: Un estudio sobre agresores sexuales

La reincidencia, especialmente en delitos sexuales, constituye una problemática que afecta a los ámbitos político, jurídico-penal y social, con gran repercusión en los medios. Por este motivo es necesario desarrollar metodologías de análisis para su predicción, para mejorar la eficiencia de la gestión del riesgo asociado. Las Redes Bayesianas han demostrado ser una herramienta muy útil en la predicción de sucesos que dependen de muchas variables en un entorno de incertidumbre. Este trabajo introduce su uso como metodología novedosa en la evaluación del riesgo de reincidencia, a partir de un estudio sobre delincuentes sexuales basado en la información recogida en un informe previo. Se observa la coherencia de los resultados obtenidos con los del informe en cuanto a la influencia individual de las variables explicativas en el riesgo de reincidencia. El interés principal de esta metodología radica en que permite explorar la influencia simultánea de diversas variables, por lo que se podrán hacer estimaciones precisas de riesgo individualizado y estudiar las interacciones entre los factores de riesgo.Recidivism in sexual offences is a problem that affects the political, criminal justice and social context, with great media coverage. In order to improve the efficiency in managing the risk of these offences some methodologies for prediction need to be developed. Bayesian Networks have proved to be a useful tool in predicting events that depend on many variables in an uncertain environment. This paper introduces their use as a novel methodology in assessing the risk of recidivism, from a study of sex offenders based on the information in a report. Consistency of the results obtained with the report regarding the individual influence of the explanatory variables on the risk of recurrence was observed. The main interest of this methodology is to explore the simultaneous influence of several variables, so it may make accurate estimates of individual risk and study the interactions between the risk factors