EXPERIENCING MIS >CUSTOM<
EXPERIENCING MIS >CUSTOM<
7th Edition
ISBN: 9781323518731
Author: KROENKE
Publisher: PEARSON C
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Chapter 3, Problem 4CE
Program Plan Intro

Porter’s competitive forces model:

  • This model is mainly used to realize the competitive advantage.
  • It gives the common view of the company, its competitor, and the environment of the companies.
  • This model is developed regarding the company’s common business environment.
  • This model contains the five competitive forces. They are as follows:
    • Substitute products and services
    • New market entrants
    • Traditional competitors
    • Suppliers
    • Customers

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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…
We are doing a custom JSTL custom tag to make display page to access a tag handler.   Write two custom tags: 1) A single tag which prints a number (from 0-99) as words. Ex:    <abc:numAsWords val="32"/>   --> produces: thirty-two   2) A paired tag which puts the body in a DIV with our team colors. Ex:    <abc:teamColors school="gophers" reverse="true">     <p>Big game today</p>     <p>Bring your lucky hat</p>      <-- these will be green text on blue background   </abc:teamColors> Details: The attribute for numAsWords will be just val, from 0 to 99   - spelling, etc... isn't important here. Print "twenty-six" or "Twenty six" ... .  Attributes for teamColors are: school, a "required" string, and reversed, a non-required boolean.   - pick any four schools. I picked gophers, cyclones, hawkeyes and cornhuskers   - each school has two colors. Pick whatever seems best. For oine I picked "cyclones" and       red text on a gold body   - if…
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