Trace the history of American jazz from its roots to present.

Instructions: SOCIAL PHILOSOPHY and

ETHICS

— The Elite (VIPs) vs. The

Masses

Consider:

Who should a society support and champion

The Elite: the champions, the famous, the rich, the

powerful, the people who get things done, who

runs and change society (for better or worse).. In

other words: the fittest (the 1%);

OR

The Masses: the common folks, the multitude, the

profusion, the crowds, including the 51% of

people in America on some sort of social relief.

This questions colors and valuates much of

the decisions we make as a society; it is past time

to identify where we as individuals stand.

This question is the root of:

Republicans vs. Democrats

Bourgeoisie vs. Proletariat

Capitalist vs Socialist

Haves vs. Have-

Nots

“To be is to do”,

-Socrates.

“To do is to be”

‘-Jean-Paul Sartre.

“Do be do be do”.

‘_Frank Sinatra.

(Had to put that in here)

Anyhow, here is the topic you will argue:

Inquiry: Should survival of the fittest be the law

of the land?

Or should a

society support the weak?

REQUIREMENTs:

1,000-2,500 words

MLA-Format

Bulleted-abstract

Cites and works cited

Researched and supported arguments

CIS 1100: Final Exam Part B case-Timov_Family_Budget

Data File needed for the case: Timov_Family_Budget.xlsx

Instructions

Sergei and Ava Timov have asked you to create an Excel workbook for their family budget. The Timovs want to purchase a new home. They are considering two houses with different mortgages. They want the budget worksheet you create to display the impact of monthly mortgage payments on the couple’s cash flow. The couple has already designed part of the workbook and entered estimates of their take home pay and expenses for the upcoming year. They want you to set up the formulas for the remaining spreadsheet including the mortgage payments and base their decision on the Average Net Cash flow for the month for each of the two options.

Please complete the following:

1. Open the Timov_Family_Budget datafile attached to this Exam. Click Save as and save the workbook as Timov_Family_Budget_yourlastname on your own computer or on your flash drive.
2. In the Documentation sheet, enter your name in cell B3 and the date in cell B4 using the function Today().
3. In cell C6, enter a formula to calculate the sum of Serge’s monthly salary for the entire year. In cell D6, calculate Sergei’s average take-home pay each month. In cell E6, calculate Sergei’s maximum monthly take-home pay. In cell F6, calculate Sergei’s minimum monthly take home pay. (Hint: Use AutoSum and then select cells C18:N18, for Average, Max and Min, select the appropriate function in the drop down list on the AutoSum button and then select the cells C18:N18).
4. Select the range C6:F6, and then use AutoFill to complete the formula in the C7:F15 range. Use the AutoFill Options button to copy only the formulas into the selected range (radial button fill without formatting) and not both the formulas and formats. (Hint: Because you haven’t yet entered any mortgage payment values, cell D13 will show the value #DIV/0!, indicating the Excel cannot calculate the average mortgage payment because it cannot divide by zero. You’ll correct that problem shortly.) NOTE: If done correctly C6:F8 will be purple font, C9:F13 will be orange font and C14:F15 will be bold black font.
5. In the range J5:J12, enter the following loan and loan conditions of the first mortgage to compute fixed monthly payments for the loan in cell J11 using the appropriate function.

• The loan amount (or value of the principal) is $335,000.
• The annual interest rate is 5%.
• The interest rate is compounded 12 times a year (or monthly).
• The mortgage will last 30 years.

Use cell references where ever appropriate in the formula.

6. In cell J11, make the Monthly payment value positive by multiplying by -1 or inserting a minus sign between the = and the payment function.

7. In the range N5:N12, enter the following loan and loan conditions of the second mortgage to compute fixed monthly payments under Mortgage 2 (Remember to use cell references as above):

• The loan amount (or value of the principal) is $242,000.
• The annual interest rate is 4.75%.
• The interest rate is compounded 12 times a year (or monthly).
• The mortgage will last 20 years.

8. In cell N11, enter the function to calculate the monthly payment needed to pay off this loan, and then make the monthly payment value positive.
9. Sergei and Ava want to be able to view their monthly cash flow under both mortgage possibilities. The mortgage being applied to the budget will be determined by whether 1 or 2 is entered into cell C3. To switch from one mortgage to another, do the following:

• In cell C25, enter an IF function that tests whether cell C3 equals 1. If it does, display the value from cell J11; otherwise, display the value from cell N11. You will need to use absolute cell references in the formula.
• You will also need to copy the formula in cell C25 to range D25:N25 to reflect the same monthly payment for other months.
• Verify that the values in the range C25:N25 match the monthly payment for the first mortgage condition.

10. In cell C3, edit the value from 1 to 2. Verify that the monthly payment for the second mortgage appears in the range C25:N25.
11. Sergei and Ava want to maintain an average net cash flow of at least $1,000 per month. Under which mortgage is this achieved? Which cell on the sheet will help you make that decision? Please write your answer in cell A30.
12. Please save the sheet with your recommendation 1 or 2 in Cell C3. Save and close the workbook, and then upload and submit the finished file using the Final Exam link on Blackboard.

Discuss completely the process of evaluating the professional/helping relationship. What types of evaluations must be done? When should they be done? What should you do with the evaluation data?

CS559 – Computer Vision

Assignment 5

Due 1:00 pm, Dec 7, 2022

1. Suppose that the boundary of a closed region is represented by a 4-directional chain code. Write a function Area(ChainCode) in pseudo-code to compute the area of the region given its chain code representation.

2. Show that the area enclosed by the polyline  is

3. Compare Hough transform and Canny edge detection for region detection in terms of (i) robustness (insensitivity) to noise, (ii) detection of regions with irregular shape, (iii) any common technique that is used both methods.

4. (a) Compare three losses compressions techniques in terms of their suitability for natural images.

(b) Explain which lossless compression technique use variable code length. Which technique results in the optimal code length?

5, Consider the 8 by 8 subimage

Apply the JPEG compression algorithm (see lecture notes) and find and report the 1-D coefficient sequence.

1. Use the region growing function (next page) to detect:

• The red, blue, green regions in the ThreeRegions image (next page) by planting one seed in each region simultaneously. You must run the program only once to detect all three regions. This requires just a little modification to the attached function.

Extra-Credit:

• Determine the centroid, area, and circularity of the regions detected in (a)
• Find the minimum distance between the boundaries of the red and blue regions. Do not use your (human) vision and just assume that you have detected these two regions as in (a). You must come up with an efficient For example finding the distance of every pixel on the boundary of red region to every pixel in the boundary of blue region is inefficient.

ThreeRegions

Note: You must understand the code before applying it.

function J=regiongrowing(I,x,y,reg_maxdist)

% This function performs “region growing” in an image from a specified

% seedpoint (x,y)

%

% J = regiongrowing(I,x,y,t)

%

% I : input image

% J : logical output image of region

% x,y : the position of the seedpoint (if not given uses function getpts)

% t : maximum intensity distance (defaults to 0.2)

%

% The region is iteratively grown by comparing all unallocated neighbouring pixels to the region.

% The difference between a pixel’s intensity value and the region’s mean,

% is used as a measure of similarity. The pixel with the smallest difference

% measured this way is allocated to the respective region.

% This process stops when the intensity difference between region mean and

% new pixel become larger than a certain treshold (t)

%

% Example:

%

% I = im2double(imread(‘medtest.png’));

% x=198; y=359;

% J = regiongrowing(I,x,y,0.2);

% figure, imshow(I+J);

%

% Author: D. Kroon, University of Twente

if(exist(‘reg_maxdist’,’var’)==0), reg_maxdist=0.2; end

if(exist(‘y’,’var’)==0), figure, imshow(I,[]); [y,x]=getpts; y=round(y(1)); x=round(x(1)); end

J = zeros(size(I)); % Output

Isizes = size(I); % Dimensions of input image

reg_mean = I(x,y); % The mean of the segmented region

reg_size = 1; % Number of pixels in region

% Free memory to store neighbours of the (segmented) region

neg_free = 10000; neg_pos=0;

neg_list = zeros(neg_free,3);

pixdist=0; % Distance of the region newest pixel to the regio mean

% Neighbor locations (footprint)

neigb=[-1 0; 1 0; 0 -1;0 1];

% Start regiogrowing until distance between regio and posible new pixels become

% higher than a certain treshold

while(pixdist<reg_maxdist&&reg_size<numel(I))

% Add new neighbors pixels

for j=1:4,

% Calculate the neighbour coordinate

xn = x +neigb(j,1); yn = y +neigb(j,2);

% Check if neighbour is inside or outside the image

ins=(xn>=1)&&(yn>=1)&&(xn<=Isizes(1))&&(yn<=Isizes(2));

% Add neighbor if inside and not already part of the segmented area

if(ins&&(J(xn,yn)==0))

neg_pos = neg_pos+1;

neg_list(neg_pos,:) = [xn yn I(xn,yn)]; J(xn,yn)=1;

end

end

% Add a new block of free memory

if(neg_pos+10>neg_free), neg_free=neg_free+10000; neg_list((neg_pos+1):neg_free,:)=0; end

% Add pixel with intensity nearest to the mean of the region, to the region

dist = abs(neg_list(1:neg_pos,3)-reg_mean);

[pixdist, index] = min(dist);

J(x,y)=2; reg_size=reg_size+1;

% Calculate the new mean of the region

reg_mean= (reg_mean*reg_size + neg_list(index,3))/(reg_size+1);

% Save the x and y coordinates of the pixel (for the neighbour add proccess)

x = neg_list(index,1); y = neg_list(index,2);

% Remove the pixel from the neighbour (check) list

neg_list(index,:)=neg_list(neg_pos,:); neg_pos=neg_pos-1;

end

% Return the segmented area as logical matrix

J=J>1;