Database Concepts (7th Edition)
7th Edition
ISBN: 9780133544626
Author: David M. Kroenke, David J. Auer
Publisher: PEARSON
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Chapter 4, Problem 4.28RQ
Program Plan Intro
Data model:
A data model is a logical representation of a
The data model can be divided into three types:
- Object based data model.
- Physical data model.
- Record based data model.
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Chapter 4 Solutions
Database Concepts (7th Edition)
Ch. 4 - Prob. 4.1RQCh. 4 - Prob. 4.2RQCh. 4 - Prob. 4.3RQCh. 4 - What is a use case, and what is its purpose?Ch. 4 - Give an example of a data constraint.Ch. 4 - Prob. 4.6RQCh. 4 - Define the term entity, and give an example other...Ch. 4 - Explain the difference between an entity class and...Ch. 4 - Define the term attribute, and give examples for...Ch. 4 - Define the term identifier, and indicate which...
Ch. 4 - Prob. 4.11RQCh. 4 - Prob. 4.12RQCh. 4 - Prob. 4.13RQCh. 4 - Prob. 4.14RQCh. 4 - List and give an example of the three types of...Ch. 4 - Prob. 4.16RQCh. 4 - Prob. 4.17RQCh. 4 - Prob. 4.18RQCh. 4 - Define the term weak entity, and give an example...Ch. 4 - Explain the ambiguity in the definition of the...Ch. 4 - Define the term associative entity, and give an...Ch. 4 - Define the terms supertype, subtype, and...Ch. 4 - What is an exclusive subtype relationship? Give an...Ch. 4 - What is an inclusive subtype relationship? Give an...Ch. 4 - Prob. 4.25RQCh. 4 - Prob. 4.26RQCh. 4 - Prob. 4.27RQCh. 4 - Prob. 4.28RQ
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- Please provide me with the output image of both of them . below are the diagrams code make sure to update the code and mentionned clearly each section also the digram should be clearly describe like in the attached image. please do not provide the same answer like in other question . I repost this question because it does not satisfy the requirment I need in terms of clarifty the output of both code are not very well details 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…arrow_forwardWhy 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_forward
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