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I'm developing a matlab project to give alarm when the person in the video closed eyes and yawning. I already can process video into frames and detect eyes and mouth using viola jones , but i don't know how the system can recognize that the eyes are closed and the mouth is yawning. Can you suggest the best algorithm and code to extract the feature of the eyes and mouth?

Q #1. An optical displacement sensor

has the following relationship

between the displacement (x) and

voltage (V):

Where λ has a constant value of

600mm. Using Matlab, plot the graph

of output voltage for the displacement values from 0-150mm.

Also draw a line to linearly

approximate the curve.

a) What are the input range and

span? b) What are the output range

and span?

c) Describe what is the maximum

nonlinearity value.

d) By observation, at what

displacement (x) is the sensitivity

maximum?

has the following relationship

between the displacement (x) and

voltage (V):

Where λ has a constant value of

600mm. Using Matlab, plot the graph

of output voltage for the displacement values from 0-150mm.

Also draw a line to linearly

approximate the curve.

a) What are the input range and

span? b) What are the output range

and span?

c) Describe what is the maximum

nonlinearity value.

d) By observation, at what

displacement (x) is the sensitivity

maximum?

Write a general MATLAB function for integrating experimental data using

Simpson’s 1/3 rule. Your function should check if there are an odd number of

intervals, if there are, the trapezoidal rule should be used for the last interval.

The first line of your MATLAB function should look like:

function I = Simpson(x,y)

Where the function numerically evaluates the integral of the vector of function

values ‘y’ with respect to ‘x’

Your matlab function should also include the following:

• Error check that the inputs are the same length

• Error check that the x input is equally spaced

• Warn the user (not an error, just a warning) if the trapezoidal rule has to

be used on the last interval.

Simpson’s 1/3 rule. Your function should check if there are an odd number of

intervals, if there are, the trapezoidal rule should be used for the last interval.

The first line of your MATLAB function should look like:

function I = Simpson(x,y)

Where the function numerically evaluates the integral of the vector of function

values ‘y’ with respect to ‘x’

Your matlab function should also include the following:

• Error check that the inputs are the same length

• Error check that the x input is equally spaced

• Warn the user (not an error, just a warning) if the trapezoidal rule has to

be used on the last interval.

Write a Matlab program using Matlab script le for the estimation of the projectile motion of a ball. The projectile motion equation is given below. Write a script le that prompt the user to enter the input and computes:

a) how long does the ball take before it hits the water;

b) how far is it from the base of the cliff to the point of impact.

c) Plot the impact point against the angle. For the angle (theta) that varies from

5o – 50o with the increment of 5o.

d) Plot the graph for the vertical and horizontal location of the projectile against

the time. For a xed angle of 20o and different initial speed from 5 – 10 m/s with 0.5 m/s speed increment.

Save the results obtained in the external output le containing its input entry and student particular as well.

vOx=vocosθo vOy=vosinθo x−xo=vOx t

y−yo=vO t−1gt2=(vosinθo)t−1gt2 y22

vx=vocosθo vy=vosinθo−gt v2y=(vo sinθo)2−2 g(y−yo)

a) how long does the ball take before it hits the water;

b) how far is it from the base of the cliff to the point of impact.

c) Plot the impact point against the angle. For the angle (theta) that varies from

5o – 50o with the increment of 5o.

d) Plot the graph for the vertical and horizontal location of the projectile against

the time. For a xed angle of 20o and different initial speed from 5 – 10 m/s with 0.5 m/s speed increment.

Save the results obtained in the external output le containing its input entry and student particular as well.

vOx=vocosθo vOy=vosinθo x−xo=vOx t

y−yo=vO t−1gt2=(vosinθo)t−1gt2 y22

vx=vocosθo vy=vosinθo−gt v2y=(vo sinθo)2−2 g(y−yo)

I have detected the mouth on image using the viola jones algorithm on MATLAB, I need the codings to apply different colors on the detected mouth.

I need to develop a digital makeup system using MatLAB GUI, I have already detected the face,eyes and mouth on image using the Viola Jones algorithm. I need the codings for the detection of the cheeks and apply different colors on the cheeks, can help me with the codings?

Write a matlab script to display currency conversion for US dollar, british pound, euro with singapore dollar as the base currency. your output should show the equivalent values for USD, GBP, EURO for ever singapore dollar in increments of 1 dollar until 25 dollars.

Sample Output to be as follows:

SGD USD GBP EURO

1 - - -

2 - - -

3 - - -

. .

. .

25 - - -

I don't understand how to do this.

Sample Output to be as follows:

SGD USD GBP EURO

1 - - -

2 - - -

3 - - -

. .

. .

25 - - -

I don't understand how to do this.

Diode Forward Characteristic

Write a general matlab program for growing a binary tree and use it to train a tree fully

using the data from the three categories in the table, using an entropy impurity.

(a) Use the (unpruned) tree to classify the following patterns: {A,E, I, L,N},

{D,E, J,K,N}, {B,F, J,K,M}, a nd {C,D, J, L,N}.

(b) Prune one pair of leafs, increasing the entropy impurity as little as possible.

(c) Modify your program to allow for non-binary splits, where the branching ratio

B as is determined at each node during training. Train a new tree fully using a

gain ratio impurity and then classify the points in (a).

using the data from the three categories in the table, using an entropy impurity.

(a) Use the (unpruned) tree to classify the following patterns: {A,E, I, L,N},

{D,E, J,K,N}, {B,F, J,K,M}, a nd {C,D, J, L,N}.

(b) Prune one pair of leafs, increasing the entropy impurity as little as possible.

(c) Modify your program to allow for non-binary splits, where the branching ratio

B as is determined at each node during training. Train a new tree fully using a

gain ratio impurity and then classify the points in (a).

Write a matlab program to implement the Perceptron algorithm.

(a) Starting with a = 0, apply our program to the training data from ω1 and ω2.

Note the number of iterations required for convergence.

(b) Apply our program to ω3 and ω2. Again, note the number of iterations required

for convergence.

(c) Explain the difference between the iterations required in the two cases.

(a) Starting with a = 0, apply our program to the training data from ω1 and ω2.

Note the number of iterations required for convergence.

(b) Apply our program to ω3 and ω2. Again, note the number of iterations required

for convergence.

(c) Explain the difference between the iterations required in the two cases.