EE104 – Fall 2020
Question 1: Modeling – Epidemic – 20 points
Applying the SIR model (or a variation of the SIDARTHE model) to the real Santa Clara County epidemic
data and explain the factors that lead to the County’s decision to move back to the most restrictive
purple tier. You must cite reliable data sources to back up your findings. Your model must be unbiased
even though you already know the outcome of the county’s tightening order.
Question 2: Modeling – World Population – 20 points
Assuming the data in the website below is credible. Using the method that you learned in EE104 to read
the tables automatically and use the historical data up to the year 2020 to predict future populations of
China and India. Are your models in agreement with the claim that “for age over 30-year, China has 40%
more people than India”? Justify your argument by EE104 methods.
Question 3: Neural Networks – Dataset – 20 points
Select a dataset (i.e. one from the Toy Datasets or the Real-World Dataset) from a sklearn.svm.SVC
methods and perform similar classification exercises as in the lecture note
Question 4: FFT/IFFT – 15 points
Create your own signal that is a mix of at least 3 signals at low, medium, and high frequencies. Use
FFT/IFFT Python method to remove one of the “unwanted” frequencies. Show both unfiltered and
filtered signals in the frequency and time domain.
Question 5: Noise Cancelling Headset Design – 20 points
Search or create the following sounds: engine noise, music, background people talking noise. Mix them
all up and show the combined waveforms in both time and frequency domains.
Your job is to design a noise cancelling headset to only yield the music with no other noise. When there
is no music, total silence is desired.
Question 6: Heart Rate Analysis – 15 points
Cite and collect 5 different baby heart rate signals from reliable sources. Use Python methods to analyze
the heart rates and suggest whether the heart rate was collected from a healthy or unhealthy baby.
Quote the source information to support your analysis. (3 points each x 5 = 15 points total)
Question 7: Data Science Relationship – 15 points
There are speculations of several factors that either positively or negatively impact the COVID-19
pandemic flatten-the-curve effort.
Research and use government data to support three of your own arguments how the curve will be
either improved or negatively impacted. Generate appropriate supporting graphs to demonstrate your
findings. (5 points fore each successful demonstrated argument, 15 points total).
Question 8: Ordinary Differential Equation – 15 points
The news has been focusing a new COVID-19 vaccination that will be available, but it will require to be
stored and transported in sub-zero Celsius temperature.
Using Python to model a portable non-electric container that will be used to transfer vaccination from
the main hospital to satellite clinics so that by the time the delivery gets to the destination, the coolant
inside temperature is still -4 degree Celsius. Specify any parameters that you will need to reach this goal,
such as limited travel distance, maximum room temperature, etc.
Hint: You can apply the Newton’s Cooling Law as one being described in this text book:
Question 9: Numerical Integration – 15 points
The Population Growth Model on page 286 of this text book suggests the curve of a population growth
with unlimited food resources.
Assuming you are hired to work for the International Food Bank organization. Your job is to analyze the
food growth prospective for each country and propose a population control plan to heads of those
nations. Select a country of your interest, obtain reliable information about the national food growth or
anything that can justify for that number, and write a Python program to produce a recommendation for
the nation leaders of that country to increase or decrease the population growth accordingly in the next
Question 10: ODE and Numerical Integration – 30 points
This problem is probably a favorite for math and physic enthusiasts.
You are working for an electric car company. The objective is to maximize the battery usage and
minimize the wear and tear of the mechanical braking system. Electric automotive industry has been
using the electrical recharging system to replace the mechanical braking where possible.
Leveraging the concepts of damped mechanical oscillations and damped electrical oscillations that you
can find in any math or physic textbook to model using Python such a combined electro-mechanical
Question 11: Matrix Algebra & GUI Interface – 30 points
Using Python to write an app to provide the following matrix operations: Matrix addition and Matrix
multiplication (15 points) .
Add a GUI interface. (15 points)
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