L1={w∈{a,b}* | w starts with a} and L2={w∈{a,b}* | |w|≤ 3} then | L1 ∩ L2 | = a) 15 b) infinity c) 7 d) 1
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If L1={w∈{a,b}* | w starts with a} and L2={w∈{a,b}* | |w|≤ 3} then | L1 ∩ L2 | = a) 15 b) infinity c) 7 d) 12 e) 8 f) 4 |
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- onsider the challenge of determining whether a witness questioned by a law enforcement agency is telling the truth. An innovative questioning system pegs two individuals against each other. A reliable witness can determine whether the other individual is telling the truth. However, an unreliable witness's testimony is questionable, below is a confusion matrix of all the possible outcomes from a given scenarios, This pairwise approach could then be applied to a larger pool of witnesses. Answer the following: Assume a pool of K witnesses, in which the reliable ones are eager to help solve a case, and the unreliable ones are equally eager to hide the truth. Prove that if more than half of the witnesses are unreliable, the approach outlined above cannot help identifying the reliable witnesses.Indian cricket team Players at an winning celebration dine at a circular table on which there is a single fork between each Player. Players either eat or think, and always start dinner thinking. To eat, a Player first picks up the fork immediately to his left and, once successful, picks up the fork immediately to his right. When a required fork is not on the table, the Player waits, neither eating nor thinking, until the fork is returned to the table. After eating, a Player returns both forks to the table. No cutlery is required to think. Your task is to model the above scenario in Java. (a) Write a class called Fork with two public methods, ForkpickUp and ForkputDown. The methods should take no arguments and return no result. An instance of Fork should act as a lock to prevent concurrent access. In other words, once ForkpickUp has been called, all further calls to ForkpickUp should block until ForkputDown is called; when ForkputDown is called, one caller (if any) who is blocked should…Maximum weight = 20The above problem is a 0/1 Knapsack problem. Here there are 7 different objects labelled from A to G. The objective of this problem is to carry the different objects in your bag in such a way such that the profit is maximized. But you have to make sure that your bag does not exceed the maximum weight i.e. the maximum weight that this bag can carry is less than or equal to 15. Remember you can carry an object exactly once. Now it is your job to use Genetic Algorithm to solve this problem. 1. Encode the problem and create an initial population of 4 different chromosomes 2. Think of an appropriate fitness function to this problem and give proper justification. 3. Use the fitness function to calculate the fitness level of all the chromosomes in your population 4. Perform natural selection and select the two fittest chromosomes 5. Use the parents from (4) and perform crossover to get 2 offspring 6. Perform mutation and check the fitness of the final offspring. Comment…
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