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Abstract

Human brain is “the perfect guessing machine” (James V. Stone (2012) Vision and Brain, Cambridge, Mass: The MIT Press, p. 155), trying to interpret sensory data in the light of previous biases or beliefs. Bayesian inference is carried out by three complex networks of the human brain: salience network, central executive network, and default mode network. Their function is analysed both in neurotypical person and Attention Deficit Disorder. Modern human being having predictive brain and overloaded mind must develop social identity, whose evolution went probably through three stages: social selection based on punishment, sexual selection based on reputation, and group selection based on identity.
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Abstract

The article presents a shock safety model of an indirect contact with a low-voltage electric device. This model was used for computations and analyses concerning the following: the probabilities of appearance of the particular shock protection unreliability states, electric shock states (ventricular fibrillation), contributions of the unreliability of different shock protection elements to the probability of occurrence of these states, as well as the risk of electric shock (and the shock safety), and contributions of the intensity of occurrence of damages to different shock protection elements to this risk. An example of a possibility to reduce the risk of an electric shock through changing the intensity of occurrence of damages to the selected protection elements was provided.
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Abstract

The article describes a shock safety modeling method for low-voltage electric devices, based on using a Bayesian network. This method allows for taking into account all possible combinations of the reliability and unreliability states for the shock protection elements under concern. The developed method allows for investigating electric shock incidents, analysing and assessing shock risks, as well as for determining criteria of dimensioning shock protection means, also with respect to reliability of the particular shock protection elements. Dependencies for determining and analysing the probability of appearance of reliability states of protection as well as an electric shock risk are presented in the article.
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