EBK SOFTWARE ENGINEERING
10th Edition
ISBN: 8220101455970
Author: SOMMERVILLE
Publisher: PEARSON
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Expert Solution & Answer
Chapter 7, Problem 7.6E
Explanation of Solution
Object-Oriented Design:
Group Diary and Time Management system:
The possible principal objects of group diary and time management system with their operations and attributes is given below. Here, there is a single diary object with different operations for group appointments and personal appointments.
| Object | Attributes | Operations |
| Diary |
Year Week_of_year Time_slot Access_permission |
Make_appointment Cancel_appointment Change_appointment Make_group_appointment Reserve_slot Book_slot Free_slot Display_diary Check_slot_status |
| Appointment |
Time Duration Place Reason Participants | |
| User | Diary | Check_time_slot |
Filling Station:
The possible principal objects of gas filling system with their operations and attributes is given below. Here, the operations and attributes are associated with each object in the fuel tank system and provided a partial desciption of the system controller...
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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…
here 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…
details 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…
Chapter 7 Solutions
EBK SOFTWARE ENGINEERING
Ch. 7 - Prob. 7.1ECh. 7 - Assume that the Mentcare system is being developed...Ch. 7 - Prob. 7.3ECh. 7 - Prob. 7.4ECh. 7 - Develop the design of the weather station to show...Ch. 7 - Prob. 7.6ECh. 7 - Draw a sequence diagram showing the interactions...Ch. 7 - Draw a UML state diagram showing the possible...Ch. 7 - Prob. 7.9ECh. 7 - Prob. 7.10E
Knowledge Booster
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