Suppose that we have n entries of computers in an electronic store. These computers are of 5 different brands. We want to sort these computer entries according to their brands. What is the trivial lower bound of this sorting problems? Is this lower bound tight? Why?
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- Computer science. Correct answer will be upvoted else downvoted. Think about a n by n chessboard. Its columns are numbered from 1 to n from the top to the base. Its sections are numbered from 1 to n from the passed on to one side. A cell on a convergence of x-th line and y-th section is indicated (x,y). The fundamental corner to corner of the chessboard is cells (x,x) for all 1≤x≤n. A stage of {1,2,3,… ,n} is composed on the fundamental slanting of the chessboard. There is actually one number composed on every one of the cells. The issue is to segment the cells under and on the principle askew (there are by and large 1+2+… +n such cells) into n associated areas fulfilling the accompanying imperatives: Each district ought to be associated. That implies that we can move from any cell of a locale to some other cell of a similar area visiting just cells of a similar district and moving from a cell to a neighboring cell. The x-th area ought to contain cell on the fundamental…Suppose that we have n entries of computers in an electronic store. These computers are of 5 different brands. We want to sort these computer entries according to their brands. What is the trivial lower bound of this sorting problems? Is this lower bound tight? Why? 13:31Suppose that we have n entries of computers in an electronic store. These computers are of 5 different brands. We want to sort these computer entries according to their brands. What is the trivial lower bound of this sorting problems? Is this lower bound tight? Why? Bir elektronik mağazada n adet bilgisayar girişimiz olduğunu varsayalım. Bu bilgisayarlar 5 farklı markaya aittir. Bu bilgisayar kayıtlarını markalarına göre sıralamak istiyoruz. Bu sıralama problemlerinin aşikar alt sınırı nedir? Bu alt sınır sıkı mıdır? Nedenini açıklayınız.
- A sorting algorithm is in O(n2) in the worst case. It takes 3 seconds to sort 10,000 records, i.e. n = 10,000. What is the predicted time for the algorithm to sort 30,000 records? Suppose that you are presented with a machine that is 100 times as fast. How many records will you be able to process on the new machine in 3 seconds?Consider a satellite moving around the earth along the equator and recording some data (air-pressure, temperature, height etc.) for scientific investigation. The data thus obtained is stored in a database where the key to each data entry is the longitude of the point. We require this data to be sorted, but each of the n data entries might have been misplaced by no more than k positions from the correct sorted order (k is a predefined constant, depending on the speed of the satellite). Design a worst-case time and space efficient algorithm for sorting such a dataset.Show that the disk moves made in the classic recursive algorithm for the Towers of Hanoi puzzle can be used for generating the binary reflected Gray code. Show how the binary reflected Gray code can be used for solving the Towers of Hanoi puzzle.
- Write a MATLAB program to solve(i) an arbitrary matrix problem A= M*N where M and N arematrices in which you need to input the numbers onyour screen. Note M and N has a size mxm.(ii) Finding an inverse of the matrixPlease answer all 4 questions in detailes. Number 3 is already answered it needs graph which I already provided. Thanks 1. What are the worst-, average-, and best-case asymptotic run times for each of the algorithms you implemented? Give intuitive arguments as to why these are the asymptotic run times. 2. Under what circumstances are these asymptotic run times achieved (i.e. for what kind of vectors, sorted, reversed, something else)? 3. Generate three graphs, one for best-, average-, and worst-case scenarios, using the data collected in your experiments and the plotData executable provided on Blackboard. plotData takes three arguments: (a) --data is the file holding the relevant data. (b) --case should be Best, Worst, or Average. (c) --save is the file where the resulting figure will be saved. For example, ./plotData --data best.csv --case Best --save best_fig generates figures for best-case run times in the file best.csv and saves the figure as best_fig.png. 4. For each of the graphs…2. For a problem we have come up with three algorithms: A, B, and C. Running time of Algorithm A is O(n¹000), Algorithm B runs in 0(2¹) and Algorithm C runs in O(n!). How do these algorithms compare in terms of speed, for large input? Explain why.
- The code shows an implementation of the Rabin-Karp algorithm in Python. What is the best and worst case of this algorithm? Explain with an example for each case, without going into mathematical detailsPlease Answer these question within 1500-2000words ... send me with pdf/docs/text file Description1. In class we covered Graham’s algorithm to find the convex hull of points in 2D. The first step is to sort the points radially around a central point so we have a simple polygon p1, p2, . . . , pn. The second step is to process this polygon in linear time, by repeatedly removing the second last point in the path if it is reflex. (Details can be found in the class slides, or on the internet.) Does the second step work to find the convex hull of any simple polygon in linear time? Prove your answer. 2. Give a polynomial time algorithm that takes a simple polygon P as input and finds, if it exists, a triangulation of P whose dual is a path. Justify correctness, and analyze the runtime of your algorithm.EXM.1.AHL.TZ0.37 IB [Maximum mark: 8] In this part, marks will only be awarded if you show the correct application of the required algorithms, and show all your working. In an offshore drilling site for a large oil company, the distances between the planned wells are given below in metres. 1 2 3 4 5 6 7 8 9 10 2 30 3 40 60 4 90 190 130 5 80 200 10 160 6 70 40 20 40 40 130 7 60 120 50 90 30 60 8 50 140 90 70 70 140 70 40 9 40 170 140 60 50 90 50 70 10 200 200 80 150 110 90 30 190 90 100 11 150 30 200 120 190 120 60 190 150 200 + It is intended to construct a network of paths to connect the different wells in a way that minimises the sum of the distances between them. Use Prim's algorithm, starting at vertex 3, to find a network of paths of minimum total length that can span the whole site. [8]