Given a list of millions of words, design an algorithm to create the largest possible rectangle of letters such that every row forms a word (reading left to right) and every column forms a word (reading top to bottom). The words need not be chosen consecutively from the list, but all rows must be the same length and all columns must be the same height.

In Java: When analyzing data sets, such as data for human heights or for human weights, a common step is to adjust the data. This can be done by normalizing to values between 0 and 1, or throwing away outliers. For this program, adjust the values by subtracting the smallest value from all the values. The input begins with an integer indicating the number of integers that follow. Assume that the list will always contain less than 20 integers. Ex: If the input is: 5 30 50 10 70 65 the output is: 20 40 0 60 55 For coding simplicity, follow every output value by a space, even the last one. Your program must define and call a method:public static int getMinimumInt(int[] listInts, int listSize)   import java.util.Scanner; public class LabProgram {/* Define your method here */ public static void main(String[] args) {/* Type your code here. */}}

Implement the following two sorting algorithms in a program called p3.py. Write two separate functions for these algorithms. Both functions must take a list of integers as the input parameter.1) Bogosort: first shuffle the list argument (i.e., randomize the positions of every element) and then check to see if the result is in sorted order. If it is, the algorithm terminates successfully and returns True, but if it is not then the process must be repeated.2) Bozosort: choose two elements in the list at random, swap them, and then check if the result is in sorted order. If it is, the algorithm terminates successfully and returns True, but if it is not then the process must be repeated.Write a main() function and call both sorting functions using the same list as their arguments. The list can be of any size (try a small list first). Does any of your algorithms terminate? If yes, count the number of iterations it uses to sort the list. Does it always use the same number of repetitions? If…

An ordinary ruler is a straight piece of wood where distances 0, 1, 2 . . . , N are marked, for some N ≥ 1. A sparse ruler (or simply a ruler ) is an ordinary ruler from which some of the numbers 1, . . . , N −1 may have been deleted. The number of marks on the ruler is its order and the value N is its reach. Here, we will represent a ruler as a Python list of strictly increasing integers starting with 0. For instance [0,1,3,7] is a ruler of order 4 and reach 7. A sparse ruler of reach N is complete if it is possible to measure all distances between 1 and N by taking the dierences between two marks. For instance [0,1,3] is complete because the pairs (0, 1), (1, 3), and (0, 3) yield distances of 1, 2, and 3 respectively. (Note that the pair of marks do not need to be consecutive.) On the other hand, [0,1,4] is not complete as there is no way to measure a distance of 2. could you please provide the code for this question in python , the parts in bold explain some of the concepts in this…

4. Write the pseudocode for an algorithm that takes as input a list of numbers that are sorted in nondecreasing order, and finds the location(s) of the most frequently occurring element(s) in the list. If there are more than one element that is the most frequently occurring, then return the locations of all of them. Analyze the worst-case time complexity of this algorithm and give the O() estimate. (A list is in nondecreasing order if each number in the list is greater than or equal to the number preceding it.)

solve in python

There are various sorting algorithms available to sort data of different sizes. Three of these algorithms are Bubble sort, Shell sort, and Quicksort. In Python, write a program to generate random integer numbers of multiple sizes; 10000, 30000, 40000, 50000, and 70000, and find out which of these sorting algorithms perform the fastest sorting technique. Provide data to prove and support your findings or results by plotting a graph showing the time each takes to sort data of various sizes. It should be written in a single program. Write the code in python and also show the graphical result. Also do the proper identation of the code.

LeetCode Given an array of strings words representing an English Dictionary, return the longest word in words that can be built one character at a time by other words in words. If there is more than one possible answer, return the longest word with the smallest lexicographical order. If there is no answer, return the empty string. Example 1: Input: words = ["w","wo","wor","worl","wo Output: "world" Explanation: The word "world" can be buil Example 2: Input: words = ["a", "banana", "app","appl" Output: "apple" Explanation: Both "apply" and "apple" can Constraints: • 1 <= words.length <= 1000 • 1 <= words [i]. length <= 30 words [1] consists of lowercase English letters.

ORIGINAL Q: Instead of reading in an entire list N1,N2,⋯N1​,N2,⋯​ all at once, some algorithms (depending on the task to be done) can read in only one element at a time and process that single element completely before inputting the next one. This can be a useful technique when the list is very big (e.g., billions of elements) and there might not be enough memory in the computer to store it in its entirety. Write an algorithm that reads in a sequence of values v≥0, one at a time, and computes the average of all the numbers. You should stop the computation when you input a value of V = −1. Do not include this negative value in your computations; it is not a piece of data but only a marker to identify the end of the list. PLEASE MODIFY THE FOLLOWING CODE SO THE USER INPUTS THE NUMBERS ONE BY ONE: ORIGINAL Q: Instead of reading in an entire list N1,N2,⋯N1 ,N2,⋯ all at once, some algorithms (depending on the task to be done) can read in only one element at a time and process that single…

2. Problem 2: In this problem you will test our "in class" version of Gaussian elimination against the version in numpy. Use both codes to solve some randomly chosen linear systems of size N 10, 20, 40, 80, 160, 320, 640, 1280, 2560, and 5120. Depending on your computer, the last two may or may not work. If they don't, just say so in your report. If you computer can do N- 10240 then try this as well. Note that in cach case N 10 * 2k for k = 1,..., 10. That is, each time we are doubling the size of the matrix. abone Plot the results as two curves. Our code in red and numPy in bluc. (Or whatever colors you prefer). Can you guess the function which governs the runtime? Based on this guess, how long would it take to do N 40960 using numPy? N=81920?