For each of the following situations, choose the sorting algorithm we studied that will perform the best. (For some questions, more than one answer might be acceptable, but you only need to list one.) We are working on an unstable system. When we try to run our sort on large arrays, sometimes the sorting algorithm will be forced to stop running in the middle of execution. (The array will be left in whatever state it was in at the time the algorithm stopped.) But we can start the algorithm over and run it again later. So we want to choose an algorithm that will make progress toward the goal even if it does not always finish executing.
(checkbox format)
Insertion sort
Selection sort
Heap sort
Merge sort

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

Using least squares fitting, you are to fit the data sets to the following models and solve for the parameters ai , where i is the index of the parameter. the input/output data for the systems are linked in the bblearn site. for each of the systems use matlab to plot the supplied data vs. the model fit on one plot. include your code in the solutions. (a) linear fit "lineardata.mat" y=a1x^3 + a2x^2 + a3x + a4 (b) plant fit "plantdata.mat g(s) = a1/(s + a2)

Singing in the rain: this first part of the film shows the early history of motion picture. how accurate do you think the portrayal of the early motion picture industry is? why? is historical accuracy important in films and theater productions? explain.