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1. A Bayesian network is shown for the variables paper Thickness, paper Alignment and Print Quality. The conditional probabilities are provided in the tables beside the nodes. Here, Thickness = {high or low}, Alignment = {straight or angled}, and Print Quality = {good or bad}.
Calculate the following quantities from the information in the Bayesian network.
a) P(Alignment = straight)
b) P(Alignment = straight | Print Quality = good)
Is the Process before and after the swap are the same? Give reason. Process before swapping is residing in the primary memory in its original form. The regions (text, data and
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