How does the "slice and dice" method work for the multiple model?

Implement the transaction manager class using java Explain your code in few words. I have included other classes that have relation with the parking transaction calss

Modify the simulate() method in the Simulator class to work with the revised interface of ParkingLot and the new peek() method in Queue. In addition, implement the getIncomingQueueSize() method of Simulator using the size() method of Queue. The getIncomingQueueSize() is going to be used in the CapacityOptimizer class (next task) to determine the size of the incoming queue after a simulation run.   CODE TO MODIFY IN JAVA: public class Simulator { /** * Length of car plate numbers */ public static final int PLATE_NUM_LENGTH = 3; /** * Number of seconds in one hour */ public static final int NUM_SECONDS_IN_1H = 3600; /** * Maximum duration a car can be parked in the lot */ public static final int MAX_PARKING_DURATION = 8 * NUM_SECONDS_IN_1H; /** * Total duration of the simulation in (simulated) seconds */ public static final int SIMULATION_DURATION = 24 * NUM_SECONDS_IN_1H; /** * The probability distribution for a car leaving the lot based on the duration * that the car has been parked in…

Our client just contacted us and said that they are planning from time to time toprovide us with four integers instead of two and three.Thinking: What would be a universal/generic solution for dealing with such clients?Should we be proactive and write methods with 5, 6, 7, etc., parameters in advance?Review Multi-Way Conditional Statements, Implement the main method to invokeany of the following methods on demand, test your program with different inputs,and make sure it runs without errors. please use the bottom part of the code in purple in the first picture

Complete the Team class implementation. For the instance method get_win_percentage(), the formula is:team_wins / (team_wins + team_losses)

What is the difference in the result of returning the words in a HashSet compared with returning them in an ArrayList?

Implement the Solver class. In doing so, you are allowed to define other classes to help you (as well as use “built-in” Java classes or the book’s classes). The point of the solver class is the solve method which takes a board/puzzle configuration represented as a 2D array of booleans and returns a char array containing a minimal sequence of moves that will lead to the solved board (all the cells around the edges being filled). The board configuration is passed in as a 5-by-5 boolean array of Booleans with exactly 16 true cells (filled) and 9 false cells (empty). The solve method then returns an array of characters representing a minimal sequence of moves that solves the puzzle. In other words, if the characters from the returned array are used in order as input to the move method on the Board object representing the initial configuration, the resulting board configuration represents the solved board. Furthermore, the solution must be minimal in the sense that there are no solutions…

Write tests and implement

So how fast is the merge sort? Does it depend on the type of array? We saw with some of our previous sorts that it depended on the initial array. For example, an Insertion sort was much faster for a nearly sorted array. In this exercise, you are given the Sorter class, which contains a static mergeSort method that takes an int array and length as an input. You are also given the SortTester class which has three static methods for creating 3 different types of arrays. For this test, create one of the three arrays, then take a start time using System.currentTimeMillis(). Next, run the array through the mergeSort method in the Sorter class. Finally, record the end time and print out the results. Repeat this for the other two array types. Sample Output Random Array: ** Results Hidden ** Almost Sorted Array: ** Results Hidden ** Reverse Array: ** Results Hidden **

Implement Stratified sampling. Given training data, class labels and the fraction of validation data per class 'test_size'. Write a method to sample train data, test data, train labels and test labels such that each class has ‘test_size' fraction of data/labels for validation and 1-test_size fraction of data/labels for training.