
MICROSOFT VISUAL C# <CUSTOM LL>
7th Edition
ISBN: 9780357093344
Author: FARRELL
Publisher: CENGAGE C
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Chapter 6, Problem 2CP
Program Plan Intro
Program Plan:
- Under the namespace MuralsRevenue and in class MuralsRevenue create a main method. Inside main method perform the following tasks.
- Create two arraysinteriorMuralCustomers and exteriorMuralCustomers of type string of dimension 2 * interiorMurals and 2*exteriorMurals respectively.
- Use for loop to read in names of customers and their talent codes for interior murals. Store each name along first row of array interiorMuralCustomers and each mural code along the second row. Use do-while loop inside this for loop to read only the valid mural codes until a right mural code is entered for each customer.
- Do same procedure for exterior mural customers as well.
- Next create variablesLcount, Scount, Acount, Ccount and Ocount to store the number of customers in each category.
- Use for loop to scan through both interiorMuralsCustomer and ExteriorMuralCustomers array and increment the values of above variables as per found category.
- Finally ask the user for a mural style category and use another for loop to list names in customer belonging to this category.
Program Description:
The main purpose of the program is to modify the MuralsRevenue program from previous chapter to get entry for names of each customer for both interior and exterior murals. Then show number of murals for each category of mural codes and also name customers as per mural codes.
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GETTING STARTED
Open the file SC_EX19_EOM2-1_FirstLastNamexlsx, available for download from the SAM website.
Save the file as SC_EX19_EOM2-1_FirstLastNamexlsx by changing the “1” to a “2”.
If you do not see the .xlsx file extension in the Save As dialog box, do not type it. The program will add the file extension for you automatically.
With the file SC_EX19_EOM2-1_FirstLastNamexlsx still open, ensure that your first and last name is displayed in cell B6 of the Documentation sheet.
If cell B6 does not display your name, delete the file and download a new copy from the SAM website.
Brad Kauffman is the senior director of projects for Rivera Engineering in Miami, Florida. The company performs engineering projects for public utilities and energy companies. Brad has started to create an Excel workbook to track estimated and actual hours and billing amounts for each project. He asks you to format the workbook to make the…
Chapter 6 Solutions
MICROSOFT VISUAL C# <CUSTOM LL>
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- Why I need ?arrow_forwardHere are two diagrams. Make them very explicit, similar to Example Diagram 3 (the Architecture of MSCTNN). graph LR subgraph Teacher_Model_B [Teacher Model (Pretrained)] Input_Teacher_B[Input C (Complete Data)] --> Teacher_Encoder_B[Transformer Encoder T] Teacher_Encoder_B --> Teacher_Prediction_B[Teacher Prediction y_T] Teacher_Encoder_B --> Teacher_Features_B[Internal Features F_T] end subgraph Student_B_Model [Student Model B (Handles Missing Labels)] Input_Student_B[Input C (Complete Data)] --> Student_B_Encoder[Transformer Encoder E_B] Student_B_Encoder --> Student_B_Prediction[Student B Prediction y_B] end subgraph Knowledge_Distillation_B [Knowledge Distillation (Student B)] Teacher_Prediction_B -- Logits Distillation Loss (L_logits_B) --> Total_Loss_B Teacher_Features_B -- Feature Alignment Loss (L_feature_B) --> Total_Loss_B Partial_Labels_B[Partial Labels y_p] -- Prediction Loss (L_pred_B) --> Total_Loss_B Total_Loss_B -- Backpropagation -->…arrow_forwardPlease provide me with the output image of both of them . below are the diagrams code I have two diagram : first diagram code graph LR subgraph Teacher Model (Pretrained) Input_Teacher[Input C (Complete Data)] --> Teacher_Encoder[Transformer Encoder T] Teacher_Encoder --> Teacher_Prediction[Teacher Prediction y_T] Teacher_Encoder --> Teacher_Features[Internal Features F_T] end subgraph Student_A_Model[Student Model A (Handles Missing Values)] Input_Student_A[Input M (Data with Missing Values)] --> Student_A_Encoder[Transformer Encoder E_A] Student_A_Encoder --> Student_A_Prediction[Student A Prediction y_A] Student_A_Encoder --> Student_A_Features[Student A Features F_A] end subgraph Knowledge_Distillation_A [Knowledge Distillation (Student A)] Teacher_Prediction -- Logits Distillation Loss (L_logits_A) --> Total_Loss_A Teacher_Features -- Feature Alignment Loss (L_feature_A) --> Total_Loss_A Ground_Truth_A[Ground Truth y_gt] -- Prediction Loss (L_pred_A)…arrow_forward
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