Essentials of MIS (13th Edition)
13th Edition
ISBN: 9780134802756
Author: Kenneth C. Laudon, Jane Laudon
Publisher: PEARSON
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Chapter 12.2, Problem 2CQ1
Program Plan Intro
Mobile application:
- Smart phone tend to become more important part in every person’s day to day life routine.
- Every process required to be made in a smart manner and it is considered to be more important in case of the business process.
- Every customer requires process that is made should be effective and to made on hands on, and the proper way to establish a smartest means of business is through smart phones.
- People have been evolved from the Personal computers to mobile phones.
- There is situation where every company requires a mobile application to establish their business and the requirement of the company is to development of the application to be processed in a short period of time.
- Developing a mobile application in a short period of time can be imposed with different challenges.
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Chapter 12 Solutions
Essentials of MIS (13th Edition)
Ch. 12.2 - Prob. 1CQ1Ch. 12.2 - Prob. 2CQ1Ch. 12.2 - Prob. 3CQ1Ch. 12.4 - Prob. 1CQ2Ch. 12.4 - Classify and describe the people, organization,...Ch. 12.4 - Prob. 3CQ2Ch. 12.4 - Why do you think the implementation of Snohomish...Ch. 12 - Prob. 1IQCh. 12 - Prob. 2IQCh. 12 - Prob. 3IQ
Ch. 12 - Prob. 4IQCh. 12 - Prob. 5IQCh. 12 - What are the core problem-solving steps for...Ch. 12 - Prob. 2RQCh. 12 - Prob. 3RQCh. 12 - Prob. 5DQCh. 12 - Prob. 6DQCh. 12 - Prob. 7DQCh. 12 - The Warm and Toasty Heating Oil Company used to...Ch. 12 - Prob. 9HMPCh. 12 - Prob. 11HMPCh. 12 - Prob. 12CSQCh. 12 - What problems was the Philly311 project designed...Ch. 12 - Prob. 14CSQCh. 12 - Prob. 15CSQCh. 12 - Prob. 18MLMCh. 12 - Prob. 19MLM
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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 -->…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_forwardI'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_forward
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