Find the maximum profit on an input with items of weights 3 lb., 2 lb., 1 lb., 4 lb., 5 lb. and values $25, $20, $15, $40, and $50, respectively using fractional Knapsack approach and greedy strategy-ratio. The knapsack capacity is 6 lb.
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- Construct a graph to show how the time to complete the 10th car changes as the learning curve slope parameter is varied from 75% to 95%. The Mechanical Engineering department has a student team that is designing a formula car for national competition. The time required for the team to assemble the first car is 100 hours. Their improvement (or learning rate) is 0.8, which means that as output is doubled, their time to assemble a car is reduced by 20%. Use this information to determine, Solve, (a) the time it will take the team to assemble the 10th car. (b) the total time required to assemble the first 10 cars. (c) the estimated cumulative average assembly time for the first 10 cars. Solve by hand and by spreadsheet.Hi please answer the following follow up questions as well, posted them as another question. Question 4 For the 9-tile soring problem, assume that you start from this initial state 7 2 4 5 6 8 3 1 The Goal State is: 1 2 3 4 5 6 7 8 The cost of moving any tile is 1. Let the heuristic function h(n) = number of misplaced tiles. For the shown configuration, there are four options for the next move: Move 5 to the right Move 6 to the left Move 2 down Move 3 up Each of these moves has a value f(n) = h(n) + g(n). If we choose to Move 5 to the right, then g(n) = 1. That is, it took us one step to reach this state from the initial state. h(n) = number of misplaced tiles. The misplaced tiles are {7,4,8,3,1}. So the number of misplaced tiles = h(n) = 5. If we choose to Move 6 to the left, g(n) is still = 1, but h(n) will change because the number of misplaced tiles is different. A* works by computing f(n) = h(n) + g(n) for each of these possible moves. Then it…With given mean and standard deviation we can simulate values for that normal distribution using the excel formula NORMINV(Rand(),mean,sd). This is applicable for X, Y & Z and thus the W value can also be simulated ( W = (X+Y)/Z) The simulation of 50 values are prepared and the histogram with width 3 class interval is shown in the excel sheet. Random Values around the mean and Standard deviation Y Y W Mean 1.. Y.. 0. Deviation Variance Frequency of Simulated Values Bins Frequency
- Remaining Time: 2 hours, 27 minutes, 02 seconds. Duestion Completion Status: Y=A'. B' + (AOB) b. Using Karnaugh map, simplify the following Boolean function F (show your grouping): [2 Marks] A B C F 1 1 1 1 1 1 1 1 1 0. 1 1 1 1 1 1 Click Save and Submit to save and submit. Click Save All Answers to save all answers. Save All A O Type here to search DLL FS F9 F10 F11 9 3 r 7 Y 8 W E R = G i JJ 立Information on morphine: Morphine can be administered via injection / IV. The quantity of morphine in a given dose may vary, but one guideline is to use 0.1 mg of morphine for each kg of the patient's body mass. The time taken for half the quantity of morphine to be removed from the body is 2 hours. An exponential function can be used to model the amount of morphine in the body over time: ?=?0???A=A0ekt (note that ?k will be negative). Calculate the value of ?k for morphine. Write a Python function called MorphineModel, which takes two arguments: dose amount ?0A0 and time since last dose ?t, and returns the amount of morphine in the body at this time ?t. Add to your computer code so that you have a program which is an implementation of the following flowchart. Ensure that your code is well-communicated to a user of the program (via the print statements) and well-communicated to someone reading the code (via comments).The task is to implement density estimation using the K-NN method. Obtain an iidsample of N ≥ 1 points from a univariate normal (Gaussian) distribution (let us callthe random variable X) centered at 1 and with variance 2. Now, empirically obtain anestimate of the density from the sample points using the K-NN method, for any valueof K, where 1 ≤ K ≤ N. Produce one plot for each of the following cases (each plotshould show the following three items: the N data points (instances or realizations ofX) and the true and estimated densities versus x for a large number – e.g., 1000, 10000– of discrete, linearly-spaced x values): (i) K = N = 1, (ii) K = 2, N = 10, (iii) K = 10,N = 10, (iv) K = 10, N= 1000, (v) K = 100, N= 1000, (vi) K = N = 50,000. Pleaseprovide appropriate axis labels and legends. Thus there should be a total of six figures(plots),
- So I have the following roshambo strategy function to return a random play, and tests for when one of the length of plays is less than 3 and otherwise. I have tried running it many times on a single scenario to estimate the probability for each return but the results are somehow confusing. Question: Write a series for the roshambo function below to test that it works as expected. (this could be testthat::expect_equal or testthat::expect_true or testthat::expect_error tests). Thank you. roshambo <- function(plays){ # return random play if (length(plays) < 3){ return(sample(c("R", "P", "S"), 1)) } # else find most common most_common <- names(which.max(table(plays))) if (most_common == "S"){ return("R") } else if (most_common == "R"){ return("P") } else { return("S") }}Design the optimal conical container that has (a) a cover and has walls of negligible thickness. The container is to hold 0.5 m³. Design it (determine the optimal radius and height) so that the areas of its top and sides are minimized. (b) Repeat (a) but for a conical cuntainer without a cover. You can search 'Uncle Google' or any geometry textbook to find how the surface area and volume of a conical container (as shown below) are calculated. Solve it using MATLAB's fminbnd function. LidConsider a maximization problem that is being solved by Simulated Annealing. Let the objective function value of the current state, s, be 1000. Let this state have 5 successors/neighbors: s1(950), s2(975), s3(1000), s4(1000), and s5(1050). The numbers in parentheses represent the corresponding objective function values. The current temperature is 100. The probability that the next state is: 1. s1 = [Select] 2. s2 = [Select] 3. s3 [Select] = 4. s4= [Select] [Select] 5. s5 0.778 0.121 0.156 0.2 0.606
- With Given the endpoints (21, 11) and (31, 19), using Bresenham’s Line Algorithm for abs (m) < 1,i. Calculate the slope of the lineii. Determine the initial decision parameteriii. Generate the successive decision parametersiv. Create a Scan Conversion table based on the parameters deduced in (i), (ii), and (iii)v. Plot the line and graphically re-calculate its gradientCorrect answer will be upvoted else Multiple Downvoted. Computer science. ground underneath the fence isn't level. For straightforwardness, you can imagine that the ground level under the I-th segment is equivalent to hello. You ought to adhere to a few guidelines to fabricate the fence: the successive segments ought to have a typical side of length something like 1; the first and the keep going areas should remain on the relating ground levels; the segments between might be either on the ground level or higher, yet not higher than k−1 starting from the earliest stage hello (the tallness ought to be an integer Input The principal line contains a solitary integer t (1≤t≤104) — the number of experiments. The main line of each experiment contains two integers n and k (2≤n≤2⋅105; 2≤k≤108) — the number of segments in the fence and the stature of each segment. The second line of each experiment contains n integers h1,h2,… ,hn (0≤hi≤108), where hello is the ground…There is a 100-story skyscraper there. If an egg drops from the Nth floor orIt will crack above. It won't shatter if dropped from any storey below. Two eggs are presented to you. Find N, while reducing the amount of drops for the worst scenario.