No explanation, just need the numbers inputed
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No explanation, just need the numbers inputed
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- 3. Give an example of a random variable X that takes on values from the set of all binary strings of length 4 where the min-entropy of X and the entropy of X are very different. Explain what is causing this phenomenon.Let's consider a system where for security parametern, running for109∗n3clock cycles can break an encryption scheme with probability16∗n10∗2−n. Ifn=64, this probability is 1 (magic!) for109∗n3=109∗643clock cycles, requiring a running timeTof about three days on a1Ghzcomputer. Now a more powerful8Ghzcomputer becomes available. Butnis also doubled to 128 in the encryption scheme as well. Using the same running timeTas before on the new computer, what is the probability for this system to break this current encryption scheme? Please clearly show how you arrive at the conclusion. (Hint: First find out how much computation can be done in the given time on the new computer. Then you can see how that relates to the success probability.). Please type answer no write by hend.Suppose we use the following KB (where x,y,z are variables and r1, r2, r3, goal are constants) to determine whether a particular robot can score a) Open(x) ∧ HasBall(x) -> CanScore(x) b) Open(x) ∧ CanAssist(y,x) ∧ HasBall(y) -> CanScore(x) c) PathClear(x,y) -> CanAssist(x,y) d) PathClear(x,z) ∧ CanAssist(z,y) -> CanAssist(x,y) e) PathClear(x,goal) -> Open(x) f) PathClear(y,x) -> PathClear(x,y) g) HasBall(r3) h) PathClear(r1, goal) i) PathClear(r2, r1) j) PathClear(r3, r2) k) PathClear(r3, goal) Intuitively, CanScore(x) means x can score on goal. CanAssist(x,y) means there exists some series of passes that can get the ball from x to y. Open(x) means x can shoot on goal directly. And PathClear(x,y) means the path between x and y is clear. Provide a SLD-derivation for the query CanScore(x) in which the answer provided is r1. Provide a SLD-derivation for the query CanScore(x) in which the answer provided is r3. How many "distinct" derivations (i.e., involving different…
- You are given the following data: vocabulary V = {w1, w2, w3} and the bigram probability distribution p on V × V given by: p(w1, w1) = 1/4 p(w3, w3) = 1/8 p(w2, w2) = 0, p(w2, w1) = 1/4, p(w1, w3) = 1/4, p(w1, *) = 1/2 (that is w1 as the first of a pair), p(*, w2) = 1 /8 . Calculate p(w1, w2) and p(w2 | w3) using Markov's ruleWhat is the effect of including spelling errors, vs. automatically correcting spelling errors on Heaps’ law?Compute the vocabulary size M for this scenario: Looking at a collection of web pages, you find that there are 3000 different terms in the first 10,000 tokens and 30,000 different terms in the first 1,000,000 tokens. Assume a search engine indexes a total of 20,000,000,000 (2 × 1010) pages, containing 200 tokens on average What is the size of the vocabulary of the indexed collection as predicted by Heaps’ law?Consider a binary code to distinguish the elements of a set {a, b, c, d}, with P(a) = 0.7, P(b)=0.15, P(c)=0.1 and P(d)=0.05. On average, how many bits will be used by a sequence of 20 elements confirming to the probability distribution given above. i.e. aaaaaaaaaaaaabbbccd Group of answer choices a. 18 b. 26 c. 2 d. 40
- Computer Science A way to avoid overfitting in Deep Neural Networks is to add an additional term R to the loss function L (for example L can be the cross entropy loss) as follows: L(w) + λR(w). (1) You know that one choice for R is the L2 norm, i.e. R(w) = ||w||2 2 . One friend of yours from the School of Maths told you however that there’s no need to use squares (i.e. powers of two) and that you can achieve the same effect by using absolute values, i.e. the L1 norm: R(w) = ||w||1. Would you agree with him? i.e. is the use of the L2 norm equivalent to using the L1 norm for regularization purposes? Justify your answerAlice wants Bob (the Bank) to sign a cheque, c. She has Bob's public key e and modulus N, and chooses a random number r such that gcd(r,N) = 1. She computes re (mod N) and then multiplies the cheque, c, by this number (mod N) and sends the resulting message off to Bob to be signed. When she receives his reply, m, what should she do with it to produce the signed cheque? Select one: a. Divide the reply, m, by rd. b. Divide the reply, m, by r. c. Divide the reply, m, by re. d. Nothing - the reply is the signed chequeAlice wants Bob (the Bank) to sign a cheque, c. She has Bob's public key e and modulus N, and chooses a random number r such that gcd(r,N) = 1. She computes re (mod N) and then multiplies the cheque, c, by this number (mod N) and sends the resulting message off to Bob to be signed. When she receives his reply, m, what should she do with it to produce the signed cheque? Select one: a. Divide the reply, m, by rd. b. Divide the reply, m, by r. c. Divide the reply, m, by re. No - that won't do it. d. Nothing - the reply is the signed cheque
- Information flow metrics is used to slow down the propagation of viruses. Given that Anne: VA = 4; Bill: VB = 2, and Cathy: VC = 3. Anne creates program P containing virus. Cathy executes P that writes to Q. Can Bill execute Q (assuming Q will produce R)? Who may execute Q? Who may execute R?Consider a web-server that receives web requests at an average rate ? of 20 requestsper second that follows a Poisson distribution. Answer the following questions:(a) What's the probability that it would receive 1000 requests in a minute? (b) What's the probability that no requests will arrive for 3 seconds? (c) Consider one second and assume that 20 requests already arrived in 0.5 second, whatis the probability that 20 requests will arrive in the next 0.5 seconds? (d) If you found out that the web-server was 70% of the time busy on average, what wouldbe its average service rate?Suppose Alice computes the Secret suffix MAC (page 322: secret suffix MAC(x) = h(x || key)) for the message ”AM” with key “G” that both Alice and Bob know. The hash function that is used is h(x1x2x3)= g(g(x1 XOR x2) XOR x3 ) where each xi is a character represented as 8 bits, and g(x) is a 8-bit string that is equal to the complement of bits in x. For example, g(10110011) = 01001100. The MAC is 8 bits. (8-bit ASCII representation of the characters is given below.) What is the Secret suffix MAC computed by Alice? Show the MAC as the single character. What information is sent by Alice to Bob.
