Emily wants to search online for entrepreneurship opportunities in the field of business development. however, she wants to skip the topic of branding. which option will her find the most appropriate result?

Some of your friends have gotten into the burgeoning field of time-series data mining, in which one looks for patterns in sequences of events that occur over time. purchases at stock exchanges--what’s being bought-- are one source of data with a natural ordering in time. given a long sequence s of such events, your friends want an efficient way to detect certain "patterns" in them--for example, they may want to know if the four events buy yahoo, buy ebay, buy yahoo, buy oracle occur in this sequence s, in order but not necessarily consecutively. they begin with a collection of possible events (e.g., the possible’ transactions) and a sequence s of n of these events. a given event may occur multiple times in s (e.g., yahoo stock may be bought many times in a single sequence s). we will say that a sequence s’ is a subsequence of s if there is a way to delete certain of the events from s so that the remaining events, in order, are equal to the sequence s’. so, for example, the sequence of four events above is a subsequence of the sequence buy amazon, buy yahoo, buy ebay, buy yahoo, buy yahoo, buy oracle their goal is to be able to dream up short sequences and quickly detect whether they are subsequences of s. so this is the problem they pose to you: give an algorithm that takes two sequences of even~s--s’ of length m and s of length n, each possibly containing an event more than once--and decides in time o(m n) whether s’ is a subsequence of s

In a compound condition, both conditions on either side of the logical operator and must be true for the overall condition to be true. a: true b: false

Problem 1 - hashing we would like to use initials to locate an individual. for instance, mel should locate the person mark e. lehr. note: this is all upper case. generate a hash function for the above using the numbers on your telephone. you know, each letter has a number associated with it, so examine your telephone keypad. generate 512 random 3 letter initials and take statistics on a linked list array size 512 to hold this information report how many have no elements, 1 element, 2 elements, does this agree with the hashing statistics distribution?