Starting Out with Java: From Control Structures through Objects (7th Edition) (What's New in Computer Science)
Starting Out with Java: From Control Structures through Objects (7th Edition) (What's New in Computer Science)
7th Edition
ISBN: 9780134802213
Author: Tony Gaddis
Publisher: PEARSON
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Chapter 6.4, Problem 6.18CP
How is a constructor named?
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Here 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 -->...
Please 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)...
Chapter 6 Solutions
Starting Out with Java: From Control Structures through Objects (7th Edition) (What's New in Computer Science)
Ch. 6.1 - What does an object use its fields for? Ch. 6.1 - Prob. 6.2CP Ch. 6.1 - How is a class like a blueprint? Ch. 6.1 - You have programs that create Scanner, Random, and... Ch. 6.1 - Prob. 6.5CP Ch. 6.1 - What values do reference variables hold? Ch. 6.1 - Prob. 6.7CP Ch. 6.2 - You hear someone make the following comment: A... Ch. 6.2 - Prob. 6.9CP Ch. 6.2 - When a variable is said to reference an object,...
Ch. 6.2 - Prob. 6.11CP Ch. 6.2 - Prob. 6.12CP Ch. 6.2 - Prob. 6.13CP Ch. 6.2 - Prob. 6.14CP Ch. 6.2 - Prob. 6.15CP Ch. 6.2 - What is a stale data item? Ch. 6.3 - Assume that r1 and r2 are variables that reference... Ch. 6.4 - How is a constructor named? Ch. 6.4 - What is a constructors return type? Ch. 6.4 - Prob. 6.20CP Ch. 6.7 - Prob. 6.21CP Ch. 6.7 - What is a methods signature? Ch. 6.7 - Look at the following class: public class... Ch. 6.7 - How many default constructors may a class have? Ch. 6.9 - Prob. 6.25CP Ch. 6.9 - When designing an object-oriented application, who... Ch. 6.9 - How do you identify the potential classes in a... Ch. 6.9 - What are a classs responsibilities? Ch. 6.9 - What two questions should you ask to determine a... Ch. 6.9 - Will all of a classs actions always be directly... Ch. 6 - This is a collection of programming statements... Ch. 6 - A class is analogous to a(n) _______. a. house b.... Ch. 6 - An object is a(n) ________. a. blueprint b.... Ch. 6 - This is a class member that holds data. a. method... Ch. 6 - This key word causes an object to be created in... Ch. 6 - This is a method that gets a value from a classs... Ch. 6 - This is a method that stores a value in a field or... Ch. 6 - When the value of an item is dependent on other... Ch. 6 - This is a method that is automatically called when... Ch. 6 - When a local variable has the same name as a... Ch. 6 - This is automatically provided for a class if you... Ch. 6 - Prob. 12MC Ch. 6 - Prob. 13MC Ch. 6 - A classs responsibilities are __________. a. the... Ch. 6 - True or False: The new operator creates an... Ch. 6 - True or False: Each instance of a class has its... Ch. 6 - True or False: When you write a constructor for a... Ch. 6 - True or False: A class may not have more than one... Ch. 6 - True or False: To find the classes needed for an... Ch. 6 - Find the error in the following class: public... Ch. 6 - Prob. 2FTE Ch. 6 - The following statement attempts to create a... Ch. 6 - Find the error in the following class: public... Ch. 6 - Find the error in the following class: public... Ch. 6 - Design a class named Pet, which should have the... Ch. 6 - Look at the following partial class definition,... Ch. 6 - Consider the following class declaration: public... Ch. 6 - Look at the following description of a problem... Ch. 6 - The bank offers the following types of accounts to... Ch. 6 - Assume that you are writing an application that... Ch. 6 - What is the difference between a class and an... Ch. 6 - A contractor uses a blueprint to build a set of... Ch. 6 - What is an accessor method? What is a mutator... Ch. 6 - is it a good idea to make fields private? Why or... Ch. 6 - If a class has a private field, what has access to... Ch. 6 - Prob. 6SA Ch. 6 - Assume a program named MailList.java is stored in... Ch. 6 - Why are constructors useful for performing... Ch. 6 - Under what circumstances does Java automatically... Ch. 6 - What do you call a constructor that accepts no... Ch. 6 - Prob. 11SA Ch. 6 - How does method overloading improve the usefulness... Ch. 6 - Employee Class Write a class named Employee that... Ch. 6 - Car Class Write a class named Car that has the... Ch. 6 - Personal Information Class Design a class that... Ch. 6 - Retail Item Class Write a class named RetailItem... Ch. 6 - Payroll Class Design a Payroll class that has... Ch. 6 - TestScores Class Design a TestScores class that... Ch. 6 - Circle Class Write a Circle class that has the... Ch. 6 - Temperature Class Write a Temperature class that... Ch. 6 - Days in a Month Write a class named MonthDays, The... Ch. 6 - A Game of Twenty-One For this assignment, you will... Ch. 6 - Freezing and Boiling Points The following table... Ch. 6 - SavingsAccount Class Design a SavingsAccount class... Ch. 6 - Deposit and Withdrawal Files Use Notepad or... Ch. 6 - Patient Charges Write a class named Patient that... Ch. 6 - Dice Game Write a program that uses the Die class... Ch. 6 - Roulette Wheel Colors On a roulette wheel, the... Ch. 6 - Coin Toss Simulator Write a class named Coin. The... Ch. 6 - Tossing Coins for a Dollar For this assignment you... Ch. 6 - Fishing Game Simulation For this assignment, you...
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- I'm reposting my question again please make sure to avoid any copy paste from the previous answer because those answer did not satisfy or responded to the need that's why I'm asking again The knowledge distillation part is not very clear in the diagram. Please create two new diagrams by separating the two student models: First Diagram (Student A - Missing Values): Clearly illustrate the student training process. Show how knowledge distillation happens between the teacher and Student A. Explain what the teacher teaches Student A (e.g., handling missing values) and how this teaching occurs (e.g., through logits, features, or attention). Second Diagram (Student B - Missing Labels): Similarly, detail the training process for Student B. Clarify how knowledge distillation works between the teacher and Student B. Specify what the teacher teaches Student B (e.g., dealing with missing labels) and how the knowledge is transferred. Since these are two distinct challenges...arrow_forwardThe knowledge distillation part is not very clear in the diagram. Please create two new diagrams by separating the two student models: First Diagram (Student A - Missing Values): Clearly illustrate the student training process. Show how knowledge distillation happens between the teacher and Student A. Explain what the teacher teaches Student A (e.g., handling missing values) and how this teaching occurs (e.g., through logits, features, or attention). Second Diagram (Student B - Missing Labels): Similarly, detail the training process for Student B. Clarify how knowledge distillation works between the teacher and Student B. Specify what the teacher teaches Student B (e.g., dealing with missing labels) and how the knowledge is transferred. Since these are two distinct challenges (missing values vs. missing labels), they should not be combined in the same diagram. Instead, create two separate diagrams for clarity. For reference, I will attach a second image...arrow_forwardNote : please avoid using AI answer the question by carefully reading it and provide a clear and concise solutionHere is a clear background and explanation of the full method, including what each part is doing and why. Background & Motivation Missing values: Some input features (sensor channels) are missing for some samples due to sensor failure or corruption. Missing labels: Not all samples have a ground-truth RUL value. For example, data collected during normal operation is often unlabeled. Most traditional deep learning models require complete data and full labels. But in our case, both are incomplete. If we try to train a model directly, it will either fail to learn properly or discard valuable data. What We Are Doing: Overview We solve this using a Teacher–Student knowledge distillation framework: We train a Teacher model on a clean and complete dataset where both inputs and labels are available. We then use that Teacher to teach two separate Student models: Student A learns...arrow_forward
- Here is a clear background and explanation of the full method, including what each part is doing and why. Background & Motivation Missing values: Some input features (sensor channels) are missing for some samples due to sensor failure or corruption. Missing labels: Not all samples have a ground-truth RUL value. For example, data collected during normal operation is often unlabeled. Most traditional deep learning models require complete data and full labels. But in our case, both are incomplete. If we try to train a model directly, it will either fail to learn properly or discard valuable data. What We Are Doing: Overview We solve this using a Teacher–Student knowledge distillation framework: We train a Teacher model on a clean and complete dataset where both inputs and labels are available. We then use that Teacher to teach two separate Student models: Student A learns from incomplete input (some sensor values missing). Student B learns from incomplete labels (RUL labels missing...arrow_forwardhere is a diagram code : graph LR subgraph Inputs [Inputs] A[Input C (Complete Data)] --> TeacherModel B[Input M (Missing Data)] --> StudentA A --> StudentB end subgraph TeacherModel [Teacher Model (Pretrained)] C[Transformer Encoder T] --> D{Teacher Prediction y_t} C --> E[Internal Features f_t] end subgraph StudentA [Student Model A (Trainable - Handles Missing Input)] F[Transformer Encoder S_A] --> G{Student A Prediction y_s^A} B --> F end subgraph StudentB [Student Model B (Trainable - Handles Missing Labels)] H[Transformer Encoder S_B] --> I{Student B Prediction y_s^B} A --> H end subgraph GroundTruth [Ground Truth RUL (Partial Labels)] J[RUL Labels] end subgraph KnowledgeDistillationA [Knowledge Distillation Block for Student A] K[Prediction Distillation Loss (y_s^A vs y_t)] L[Feature Alignment Loss (f_s^A vs f_t)] D -- Prediction Guidance --> K E -- Feature Guidance --> L G --> K F --> L J -- Supervised Guidance (if available) --> G K...arrow_forwarddetails explanation and background We solve this using a Teacher–Student knowledge distillation framework: We train a Teacher model on a clean and complete dataset where both inputs and labels are available. We then use that Teacher to teach two separate Student models: Student A learns from incomplete input (some sensor values missing). Student B learns from incomplete labels (RUL labels missing for some samples). We use knowledge distillation to guide both students, even when labels are missing. Why We Use Two Students Student A handles Missing Input Features: It receives input with some features masked out. Since it cannot see the full input, we help it by transferring internal features (feature distillation) and predictions from the teacher. Student B handles Missing RUL Labels: It receives full input but does not always have a ground-truth RUL label. We guide it using the predictions of the teacher model (prediction distillation). Using two students allows each to specialize in...arrow_forward
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