Tag: Programming

• As some of you have noted, the routers provided by many ISPs are not very good and limit your ability to harden your network. What would be some good features to consider when upgrading your home router?
  • What is 5G (not the 5.0 GHz band on your router) in networking? Should you consider switching to a 5G based provider for your home network if it were available in your area?
• Would 5G be a good option for a business? Why or why not and in what context?
• What is WISP? Would it be a good option for a home network? What about a business? What about in rural areas?
• What are some potential options for people in rural, rugged terrain, or in other areas with limited infrastructure?
• What is a network chokepoint? Are chokepoints good or bad?
• What is throttling in networking? Have you ever experienced throttling?
• What is a metered connection?
• What is torrenting?
• How can torrents reduce server load when downloading large files such as an Ubuntu iso?
• What are MANs? Are they a more secure option than individual retail public networks?
• If you were tasked with defining a personal device/BYOD security checklist to share with employees of an organization of your choice what would be the top 5 items on that checklist?
• What is 2-factor authentication?
• Is text messaging a secure form of communication? What about email? How could they be made more secure?
• What are biometrics? What are the pros and cons of using biometrics for device and network security?

r1 = Carseats$Sales

p1 = data.matrix(Carseats[, c(‘CompPrice’, ‘Income’, ‘Price’,

‘Age’, ‘ShelveLoc’)])

p11=data.frame(p1)

##now apply ridge

Y <- p1

MM <- model.matrix(p11$CompPrice ~ ., data = p11) # the predictors as a datamatrix

ridge.mod <- glmnet(MM, p11$CompPrice, alpha = 1, lambda = 14)

# Apply cross validation (to pick the best value of lambda):

cv.out <- cv.glmnet(MM,p11$CompPrice , alpha = 1)

bestlam <- cv.out$lambda.1se

print(“ridge CV best value of lambda (one standard error)”)

print(bestlam)

ridge.coef <- predict(ridge.mod, type = “coefficients”, s = bestlam)

print(ridge.coef)

Introduction

We will be developing an electrical engineering software tool for a typical residential home in Southern California.

Use MATLAB or octave-online to create a code following the instructions below. Also, comment on each line of the code (example: The following line of code ………)

Guidelines and Deliverables

As usual, create a script, include a comment at the top explaining the purpose of the script, your name, and the date it was created. The goal of this project is to estimate the daily energy production over a week of a typical residential solar panel, compare it to the energy usage of a home and determine how many solar panels are required to fulfill the energy needs of the residence.

1. For the midterm project, your computeEnergy function took in as input the number of panels and computed the amount of energy produced in a typical day. The amount of energy produced by a panel depends on the time of day and can be modeled by the mathematical formula below, where t is an array of values from 1 to 24 hours.

Update computeEnergy( ) to perform this task symbolically. Use the built in integral function, int( ) to find the kilo-Watt-hours produced in a day. Plot your integral function from 0 to 24 hours.

2. From the midterm project, you wrote code to calculate how many panels would be required to fulfill the energy needs for a home. Suppose an inverter device is needed for each panel in the array and is connected in parallel to one power source. The video below shows how to use linear algebra in MATLAB to solve for the current in each branch containing an inverter. Write a function called findCurrents( ) that takes in as input the number of panels you computed in the midterm project and returns a vector of currents in each branch. Let the source voltage, Vs, be 100V and the value of each resistance be 1500 ohms.

Video: How to solve a system of linear equations corresponding to circuit currents in MATLAB

Please no plagiarism and comment on each line of code thoroughly.

Create a program that reads in a list of CSCI classes from a file found at /public/pgm2/classes.csv. Store the list in an array of structures. Then, give the user to have a number of options to query the list of classes and get information about them. You must include the following query options:

• Quit
• Print all classes
• Print all classes by course id (e.g., CSCI 112)
• Print all classes by days of course meeting (e.g., MWF)
• Print all classes under a certain number of seats

You should also add at least one more option that is different from all the options listed above.

Sample output

You do not need to match the sample output formatting.

Choices:
a - print all available classes
n - print class given course id
d - print all classes given day of week combo
s - print all classes under certain # seats
q - quit
a
Joy and Beauty of Computing             CSCI 107    Paxton John T
62    MWF   1000-1050   
Programming with C I                    CSCI 112    Cummings Mary A
175   MWF   0900-0950   
Joy and Beauty of Data                  CSCI 127    DeFrance Daniel Louis
155   MWF   0900-0950   
Bsc Data Structures/Algorithms          CSCI 132    DeFrance Daniel Louis
156   MWF   1510-1600   
Social & Ethical Issues in CS           CSCI 215    Cummings Mary A
60    TR    1505-1555   
Data Structures and Algorithms          CSCI 232    Lloyd Hunter S
128   TR    1050-1205   
Discrete Structures                     CSCI 246    Zhu Binhai
84    MWF   0800-0850   
Concepts/Programming Languages          CSCI 305    Lloyd Hunter S
144   MWF   0800-0850   
Computer Science Theory                 CSCI 338    Zhu Binhai
140   MWF   1100-1150   
Data Mining                             CSCI 347    Neeley Veronika
75    MWF   1310-1400   
Computer Systems                        CSCI 366    Wittie Mike
60    MWF   0900-0950   
Computer Graphics                       CSCI 441    Millman David
65    TR    1630-1745   
Artificial Intelligence                 CSCI 446    Sheppard John W
63    TR    0925-1040   
Embedded Systems: Robotics              CSCI 455    Lloyd Hunter S
84    MWF   1200-1250   
Compilers                               CSCI 468    Kahanda Indika M
80    MWF   1510-1600   
Choices:
a - print all available classes
n - print class given course id
d - print all classes given day of week combo
s - print all classes under certain # seats
q - quit
n
Enter class id: CSCI 112
Programming with C I                    CSCI 112    Cummings Mary A
175   MWF   0900-0950   
Choices:
a - print all available classes
n - print class given course id
d - print all classes given day of week combo
s - print all classes under certain # seats
q - quit
n
Enter class id: CSCI 456
Choices:
a - print all available classes
n - print class given course id
d - print all classes given day of week combo
s - print all classes under certain # seats
q - quit
d
Enter day of week combo: MWF
Joy and Beauty of Computing             CSCI 107    Paxton John T
62    MWF   1000-1050   
Programming with C I                    CSCI 112    Cummings Mary A
175   MWF   0900-0950   
Joy and Beauty of Data                  CSCI 127    DeFrance Daniel Louis
155   MWF   0900-0950   
Bsc Data Structures/Algorithms          CSCI 132    DeFrance Daniel Louis
156   MWF   1510-1600   
Discrete Structures                     CSCI 246    Zhu Binhai
84    MWF   0800-0850   
Concepts/Programming Languages          CSCI 305    Lloyd Hunter S
144   MWF   0800-0850   
Computer Science Theory                 CSCI 338    Zhu Binhai
140   MWF   1100-1150   
Data Mining                             CSCI 347    Neeley Veronika
75    MWF   1310-1400   
Computer Systems                        CSCI 366    Wittie Mike
60    MWF   0900-0950   
Embedded Systems: Robotics              CSCI 455    Lloyd Hunter S
84    MWF   1200-1250   
Compilers                               CSCI 468    Kahanda Indika M
80    MWF   1510-1600   
Choices:
a - print all available classes
n - print class given course id
d - print all classes given day of week combo
s - print all classes under certain # seats
q - quit
s
Enter maximum number of seats: 200
Joy and Beauty of Computing             CSCI 107    Paxton John T
62    MWF   1000-1050   
Programming with C I                    CSCI 112    Cummings Mary A
175   MWF   0900-0950   
Joy and Beauty of Data                  CSCI 127    DeFrance Daniel Louis
155   MWF   0900-0950   
Bsc Data Structures/Algorithms          CSCI 132    DeFrance Daniel Louis
156   MWF   1510-1600   
Social & Ethical Issues in CS           CSCI 215    Cummings Mary A
60    TR    1505-1555   
Data Structures and Algorithms          CSCI 232    Lloyd Hunter S
128   TR    1050-1205   
Discrete Structures                     CSCI 246    Zhu Binhai
84    MWF   0800-0850   
Concepts/Programming Languages          CSCI 305    Lloyd Hunter S
144   MWF   0800-0850   
Computer Science Theory                 CSCI 338    Zhu Binhai
140   MWF   1100-1150   
Data Mining                             CSCI 347    Neeley Veronika
75    MWF   1310-1400   
Computer Systems                        CSCI 366    Wittie Mike
60    MWF   0900-0950   
Computer Graphics                       CSCI 441    Millman David
65    TR    1630-1745   
Artificial Intelligence                 CSCI 446    Sheppard John W
63    TR    0925-1040   
Embedded Systems: Robotics              CSCI 455    Lloyd Hunter S
84    MWF   1200-1250   
Compilers                               CSCI 468    Kahanda Indika M
80    MWF   1510-1600   
Choices:
a - print all available classes
n - print class given course id
d - print all classes given day of week combo
s - print all classes under certain # seats
q - quit
s
Enter maximum number of seats: 62
Joy and Beauty of Computing             CSCI 107    Paxton John T
62    MWF   1000-1050   
Social & Ethical Issues in CS           CSCI 215    Cummings Mary A
60    TR    1505-1555   
Computer Systems                        CSCI 366    Wittie Mike
60    MWF   0900-0950   
Choices:
a - print all available classes
n - print class given course id
d - print all classes given day of week combo
s - print all classes under certain # seats
q - quit
q
Bye!

Hints

• You can use gets to read in input with spaces without a newline character. fgets also reads input with spaces, but it keeps the newline. gets is deprecated in newer C compilers, but you can use it for this assignment.
• If gets (or fgets) is not allowing you to enter input, it may be consuming a previous newline left behind from a scanf. To fix this, you can add a getchar() before your gets.
• Remember that string assignment must be done with strcpy (unless it’s in a variable declaration/initialization).
• Use strtok to separate parts of the input strings.
• Start early!

Extras

If you want, you can include the following requirements in your program. They are ungraded, though, so ignore if you want.

• Allow your program to read files containing any number of classes, rather than hard-coding the number of lines from the file.
• Give a warning if the file doesn’t exist.
• Provide a nice output if the user enters a disallowed choice.
• Don’t use gets.
• If no class is returned by a query, print a special message.

——————————————————————————-

• comments explaining what your program does
• code is indented so that it is readable
• there are no global variables
• compiles successfully with -Wall – no warnings except for about get
• successfully reads all classes from classes.csv
• stores info for all classes in an arry of structs
• compiles and links with makefile
• there are at least four different files
• implements printing all classes correctly
• implements printing class by id correctly
• implements printing class days of week correctly
• implements printing classes under certain # seats correctly
• offers one more option to users
• extra option is implemented correctly
• your struct is in its own header file
• output is printed neatly

Our textbook (For your info).

• Robbins, J. (2012). Learning web design: A beginner’s guide to HTML, CSS, JavaScript, and web graphics (4th ed.). Sebastopol, CA: O’Reilly Media. ISBN: 978-1-449-31927-4 (print); 1449319270 (e-text).

There are 10 quiz questions related to basic Python code knowledge. Please provide the correct answer to each question.

The word document attached to the this post contains all the screenshots of ten questions.

Create a script that carries out the desired functions. Write out answers all observation/explanation questions on a separate doc. Include comments in the code in order to understand what is going on

Use the provided data set to produce the following outputs. Provide the R codes in the R-script file and an analytical report consisting of tables and written analysis in the Word file.

Note that death is a binary indicator variable that takes the value of 1 if death occurred and 0 if not.

1. Calculate the probability of death (i.e. COVID-19 infection fatality rate) and conduct t-tests of mean or proportion using a hypothesized value. Supposed the national population COVID-19 infection fatality rate during the same period was 0.042. Was the infection fatality rate in Georgia statistically different from the hypothesized national population rate during this period? Use prop.test() and binom.test() for testing the proportion in R.

Repeat the test using t.test( ), which conducts the test of means. This can be done because proportion of death is equal to the mean of a binary variable death. Do you obtain larger or smaller p-values? Which of the three t-test commands [prop.test( ), binom.test( ), and t.test( )] appear to be the most conservative?

2. Conduct multiple one-sample tests of proportion (prop.test and binom.test) for multiple groups. Note that you may need to create two vectors to isolate a group. For example, conducting a test for a male sample and another test for a female sample requires filter( ) into two vectors, and then run a test for each sample. Are they different from the hypothesized national population rate (0.042)? Make decision based on p-value. Do this in R. Provide the null and the alternative hypothesis for each test. Provide the test results in a table and several paragraphs interpreting the results.

Submit a report that examines parts 1 and 2 and your R script. Please export tables instead of screenshots from R.

export test results using broom( ), stargazer( ) or manually. Example codes to export t.test() ” I put it as Appendix”

All packages used need to be written at the beginning. You need to use “#” to mark the purpose of each step.

#install package

library(psych)

library(dplyr)

library(grid)

library(vcd)

library(gtsummary)

library(broom)

The data table should be a csv file, but the website does not allow uploading csv file. I converted the a dataset to excel file. Please convert the data set to a csv file and start working.

– C language

– using atoi

BFS or DFS bipartite graph determinor.

A graph is said to be bipartite if all its vertices can be partitioned into two

disjoint subsets X and Y so that every edge connects a vertex in X with a vertex

in Y. (One can also say that a graph is bipartite if its vertices can be colored

in two colors so that every edge has its vertices colored in different colors;

such graphs are also called 2-colorable.)

Do either A or B.

A. Design a DFS-based algorithm for checking whether a graph is bipartite. Thus,

let F be a DFS forest of a graph. It is not difficult to see that F is

2-colorable if and only if there is no back edge connecting two vertices both on

odd levels or both on even levels. It is this property that a DFS traversal

needs to verify. Note that a DFS traversal can mark vertices as even or odd when

it reaches them for the first time.

B.Design a BFS-based algorithm for checking whether a graph is bipartite. Thus,

similarly to part (A), a graph is 2-colorable if and only if its BFS forest has

no cross edge connecting.