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Il vodafone AU WiFi Q1b In the cumultrap.m file, complete the function file to perform cumulative integration using the trapezoidal rule given two input vectors. The function should return the cumulative integrated values at the nominated independent values. You may only use the following built-in functions for your function file: zeros() and length(). Note: The integral of a set of data returns a scalar result. In contrast, the cumulative integral returns a vector, whose values represent the integral values from the start of the integration to its current point. Also, note that integral value of a single point is zero. Read the documentation for cumtrapz() for further details and use that function to verify your answers. *You should still have one figure window by the end of this task. Q1c In the Q1c.m file, integrate the following equations to obtain the longitudinal and latitudinal velocities V and displacements D of the race car: ● ● In a new figure with a 1x2 subplot arrangement, plot the following: ● ● 10:22 PM mcpl.moodlesites.com Also, determine the length of the track. You must use a for loop to complete this task. Use fprintf to print the length of the track: E.g. Track length: ???m *You should have two figure windows by the end of this task. **Use imread () to read the images Q1d A strong left turn is identified as when the race car experiences lateral G-forces greater than 0.4g. A strong right turn is identified as when the car experiences lateral G-forces less than -0.4g. VLONG = ALONG dt DLONG = f ALONG dtdt In the Q1d.m file, determine the left and right-turning corners. In a new figure with a 1x2 arrangement, plot the following: On both panels, mark the following: Satellite image (track_map.png) of the track using imshow(). [left panel] Latitude displacements against longitude displacements with the grid on and set the axes to be equal (option for axis). [right panel] ● Left-turning corners as blue dots Right-turning corners as red dots MCD4140 Assignment ● ● VLAT = | ALAT dt DLAT = ff ALAT dtdt G-force lateral acceleration against time [left panel] Latitude displacements against longitude displacements with the grid on [right panel] Dots on the left panel are sized 5, and dots on the right panel are sized 15. Remember to include a legend. *You should have three figure windows by the end of this task. Q1e Acceleration and deceleration zones are identified as follows: ● 90% ● On both panels, mark the following: Acceleration zones - where race car experiences G-forces less than -0.1g. Deceleration zones - where the race car experiences G-forces greater than 0.1g. In the Q1e.m file, create a new figure with a 1x2 subplot arrangement containing 2 subplots and plot the following: G-force due to total acceleration/deceleration against time [left panel] Latitude displacements against longitude displacements with the grid on [right panel] Accelerating zones as green dots Decelerating zones as magenta dots Page 4 of 9 Dots on the left panel are sized 5, and dots on the right panel are sized 15. Remember to include a legend. *You should have four figure windows by the end of this task.

l vodafone AU WiFi QUESTION 1 Background [3 MARKS] Accelerometers are small electronic devices that measure acceleration from moving objects. As a trainee engineer on a racing team, you have been given accelerometer data from a test run at the Watkins Glen International Racetrack. An image of the racetrack is shown in figure 1. ● Figure 1: Satellite view of the Watkins Glen International racetrack. The data you collected from the accelerometer during a test run is output to a csv file named "race_data.csv", which contains: • ● ● Note that 1g = 9.81 ms². 10:22 PM mcpl.moodlesites.com Time, t (s) Longitudinal acceleration, ALONG (ms²) Latitudinal acceleration, ALAT (ms²) G-force lateral acceleration, GLAT (g) G-force acceleration/deceleration, GAD (g) ● You have been asked to analyse the data and prepare a graphical presentation of the results by performing the following tasks: Q1a In the Q1a.m file, use the importdata() function to import values from the race_data.csv. Create variables for the time (t), longitudinal acceleration (ALONG), latitudinal acceleration (ALAT), G-force lateral acceleration (GLAT), and G-force due to total acceleration/deceleration (GAD). In a 2x2 subplot arrangement, plot the following: ● ALONG against t [top left panel] [top right panel] ● ALAT against t GLAT against t GAD against t [bottom left panel] [bottom right panel] *You should have one figure window by the end of this task. 90% MCD4140 Assignment Q1b In the cumultrap.m file, complete the function file to perform cumulative integration using the trapezoidal rule given two input vectors. The function should return the cumulative integrated values at the nominated independent values. You may only use the following built-in functions for your function file: zeros() and length(). Page 3 of 9 Note: The integral of a set of data returns a scalar result. In contrast, the cumulative integral returns a vector, whose values represent the integral values from the start of the integration to its current point. Also, note that integral value of a single point is zero. Read the documentation for cumtrapz() for further details and use that function to verify your answers. *You should still have one figure window by the end of this task. VLONG ALONG dt DLONG = ALONG dtdt Q1c In the Q1c.m file, integrate the following equations to obtain the longitudinal and latitudinal velocities V and displacements D of the race car: VLAT = ALAT dt [[ ALAT dtdt DLAT =

.vodafone AU WiFi 6 of 9 QUESTION 2 ment 8:54 PM mcpl.moodlesites.com Background Monte Carlo methods are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results. You have been asked to estimate the value of rt using the Monte Carlo method. Itz A number of randomised points is generated within the box of unit width, as shown in figure 2. Some of the points lie within the circle, while others lie outside the circle. The value of it is calculated using the following expression: 4Nc Ng Page 5 of 9 [3 MARKS] Figure 2: Randomised points generated inside a box containing a unit circle. The procedure to perform the Monte Carlo method is listed below: 1. Generate a randomised point within a square containing a circle of unit radius 2. Determine N, and N₁, and calculate the estimate of r 3. Repeat steps 1 and 2 for a specified number of points MCD4140 Assignment where Nc represents the number of points inside the unit circle, and Ns is the number of dots within the square. In figure 1, there are 17 points inside the circle and 20 points inside the square (i.e. 3 points outside the circle). Therefore, 4x17 3.4. This estimated value of should become more accurate with an increasing number of points. 20 Complete the following tasks to perform the Monte Carlo procedure described above. 2% Q2a In the Q2a.m file, generate a 2x1 subplot arrangement where the top panel contains a circle of unit radius and a square with a width of 2 units, both centred at (x,y) = (0,0) (see figure 3 for an example). Plot these shapes as black lines and set the axes to be square (option for axis). Details of the bottom panel are described in Q2b. Page 6 of 9 Q2b In the Q2b.m file, prompt the user for a specified number of points to estimate using the input() function. Generate your first randomised point by randomising its x and y-coordinates. The limits for the x and y- coordinates should be limited to the bounds of the square (i.e. from 1 to 1 in both directions). Plot this randomised point in the top panel of the figure as a red dot if it lies on or within the circle, or as a blue dot if it is outside the circle. Use a marker size of 15. After plotting your first randomised point, calculate the estimate of and plot the result as a black dot in the bottom panel of the figure (see figure 3). The current