ENGIN5508-Smart Engineering Technologies
Assessment tasks
1.Sensor technology
A static calibration is performed on a pressure-measuring device called a bourdon gage with a nominal range of 0 to 100 psi. The results of this calibration are shown in the table below.
Plot the data and fit a straight line through
(a)Cycle 1
(b)Average of all the cycles
2.Computer vision
Choose your own image and use Matlab to convert it to a grayscale one and do each of the following.
a)Map the input grayscale image to its “negative image”, in which the lightest values appear dark and vice versa.
b)Map the input grayscale image to its “mirror image”, i.e., flipping it left to right.
c)Swap the red and green colour channels of the input colour image
d)Average the input grayscale image with its mirror image obtained in part b) (use im2double)
e)Add or subtract a random value between [1,255] to every pixel in a grayscale image, then clip the resulting image to have a minimum value of 0 and a maximum value of 255.
Display your input colour and grayscale images and the results obtained by the five parts above in
3.Machine learning
3.There are two groups
Use KNN with k=5 to classify which group X1 = [4.8, 3], X2 = [5.7, 3] belong to.
