Modern Database Management (12th Edition)
12th Edition
ISBN: 9780133544619
Author: Jeffrey A. Hoffer, Ramesh Venkataraman, Heikki Topi
Publisher: PEARSON
expand_more
expand_more
format_list_bulleted
Concept explainers
Question
Chapter 7, Problem 7.60PAE
Program Plan Intro
SQL query to provide the list of all products along with number of times they have been ordered. Venn diagram of the query.
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solution
Students have asked these similar questions
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)…
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…
Chapter 7 Solutions
Modern Database Management (12th Edition)
Ch. 7 - Prob. 7.1RQCh. 7 - Prob. 7.2RQCh. 7 - Prob. 7.3RQCh. 7 - Prob. 7.4RQCh. 7 - Prob. 7.5RQCh. 7 - Explain the relationship between EXISTS and...Ch. 7 - Prob. 7.7RQCh. 7 - Prob. 7.8RQCh. 7 - Prob. 7.9RQCh. 7 - Prob. 7.10RQ
Ch. 7 - Under what conditions can a UNION clause be used?Ch. 7 - Prob. 7.12RQCh. 7 - Prob. 7.13RQCh. 7 - List for advantages of SQL-invoked routines.Ch. 7 - Prob. 7.15RQCh. 7 - Prob. 7.16RQCh. 7 - Prob. 7.17RQCh. 7 - Prob. 7.18RQCh. 7 - Prob. 7.19RQCh. 7 - Prob. 7.20RQCh. 7 - Prob. 7.21RQCh. 7 - Prob. 7.22RQCh. 7 - Prob. 7.23RQCh. 7 - This chapter discusses the data dictionary views...Ch. 7 - Prob. 7.25PAECh. 7 - Prob. 7.26PAECh. 7 - Prob. 7.27PAECh. 7 - Are based on the class schedule 3NF relations...Ch. 7 - Prob. 7.29PAECh. 7 - Prob. 7.30PAECh. 7 - Prob. 7.31PAECh. 7 - Are based on Figure 7-17. This problem set...Ch. 7 - Prob. 7.33PAECh. 7 - Prob. 7.34PAECh. 7 - Prob. 7.35PAECh. 7 - Prob. 7.36PAECh. 7 - Prob. 7.37PAECh. 7 - Prob. 7.38PAECh. 7 - Prob. 7.39PAECh. 7 - Prob. 7.40PAECh. 7 - Prob. 7.41PAECh. 7 - Prob. 7.42PAECh. 7 - Prob. 7.43PAECh. 7 - Prob. 7.44PAECh. 7 - Write an SQL query to display the order number,...Ch. 7 - Prob. 7.46PAECh. 7 - Prob. 7.47PAECh. 7 - Prob. 7.48PAECh. 7 - Prob. 7.49PAECh. 7 - Prob. 7.50PAECh. 7 - Write an SQL query to list each customer who...Ch. 7 - Prob. 7.52PAECh. 7 - Modify Problem and Exercise 6-60 so that the list...Ch. 7 - Prob. 7.54PAECh. 7 - Prob. 7.55PAECh. 7 - Prob. 7.56PAECh. 7 - Prob. 7.57PAECh. 7 - Prob. 7.58PAECh. 7 - Prob. 7.59PAECh. 7 - Prob. 7.60PAECh. 7 - Prob. 7.61PAECh. 7 - Prob. 7.62PAECh. 7 - Prob. 7.63PAECh. 7 - Rewrite your answer to Problem and Exercise 6-71...Ch. 7 - Display the customer ID, name, and order ID for...Ch. 7 - Prob. 7.66PAECh. 7 - Prob. 7.67PAECh. 7 - Prob. 7.68PAECh. 7 - Prob. 7.69PAECh. 7 - Prob. 7.70PAECh. 7 - Prob. 7.71PAECh. 7 - Write an SQL query to list the order number,...Ch. 7 - Prob. 7.73PAECh. 7 - Prob. 7.74PAECh. 7 - Prob. 7.75PAECh. 7 - Prob. 7.76PAE
Knowledge Booster
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, computer-science and related others by exploring similar questions and additional content below.Similar questions
- 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 (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_forwardHere 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_forward
- 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…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_forwardWe 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…arrow_forward
- I want a database on MySQL to analyze blood disease analyses with a selection of all its commands, with an ER drawing, and a complete chart for normalization. I want them completely.arrow_forwardAssignment Instructions: You are tasked with developing a program to use city data from an online database and generate a city details report. 1) Create a new Project in Eclipse called "HW7". 2) Create a class "City.java" in the project and implement the UML diagram shown below and add comments to your program. 3) The logic for the method "getCityCategory" of City Class is below: a. If the population of a city is greater than 10000000, then the method returns "MEGA" b. If the population of a city is greater than 1000000 and less than 10000000, then the method returns "LARGE" c. If the population of a city is greater than 100000 and less than 1000000, then the method returns "MEDIUM" d. If the population of a city is below 100000, then the method returns "SMALL" 4) You should create another new Java program inside the project. Name the program as "xxxx_program.java”, where xxxx is your Kean username. 3) Implement the following methods inside the xxxx_program program The main method…arrow_forwardCPS 2231 - Computer Programming – Spring 2025 City Report Application - Due Date: Concepts: Classes and Objects, Reading from a file and generating report Point value: 40 points. The purpose of this project is to give students exposure to object-oriented design and programming using classes in a realistic application that involves arrays of objects and generating reports. Assignment Instructions: You are tasked with developing a program to use city data from an online database and generate a city details report. 1) Create a new Project in Eclipse called "HW7”. 2) Create a class "City.java" in the project and implement the UML diagram shown below and add comments to your program. 3) The logic for the method "getCityCategory" of City Class is below: a. If the population of a city is greater than 10000000, then the method returns "MEGA" b. If the population of a city is greater than 1000000 and less than 10000000, then the method returns "LARGE" c. If the population of a city is greater…arrow_forward
- Please calculate the average best-case IPC attainable on this code with a 2-wide, in-order, superscalar machine: ADD X1, X2, X3 SUB X3, X1, 0x100 ORR X9, X10, X11 ADD X11, X3, X2 SUB X9, X1, X3 ADD X1, X2, X3 AND X3, X1, X9 ORR X1, X11, X9 SUB X13, X14, X15 ADD X16, X13, X14arrow_forwardOutline the overall steps for configuring and securing Linux servers Consider and describe how a mixed Operating System environment will affect what you have to do to protect the company assets Describe at least three technologies that will help to protect CIA of data on Linux systemsarrow_forwardNode.js, Express, Nunjucks, MongoDB, and Mongoose There are a couple of programs similar to this assignment given in the lecture notes for the week that discusses CRUD operations. Specifically, the Admin example and the CIT301 example both have index.js code and nunjucks code similar to this assignment. You may find some of the other example programs useful as well. It would ultimately save you time if you have already studied these programs before giving this assignment a shot. Either way, hopefully you'll start early and you've kept to the schedule in terms of reading the lecture notes. You will need to create a database named travel using compass, then create a collection named trips. Use these names; your code must work with my database. The trips documents should then be imported unto the trips collection by importing the JSON file containing all the data as linked below. The file itself is named trips.json, and is available on the course website in the same folder as this…arrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
A Guide to SQLComputer ScienceISBN:9781111527273Author:Philip J. PrattPublisher:Course Technology Ptr
Database Systems: Design, Implementation, & Manag...Computer ScienceISBN:9781305627482Author:Carlos Coronel, Steven MorrisPublisher:Cengage Learning
Database Systems: Design, Implementation, & Manag...Computer ScienceISBN:9781285196145Author:Steven, Steven Morris, Carlos Coronel, Carlos, Coronel, Carlos; Morris, Carlos Coronel and Steven Morris, Carlos Coronel; Steven Morris, Steven Morris; Carlos CoronelPublisher:Cengage Learning
Np Ms Office 365/Excel 2016 I NtermedComputer ScienceISBN:9781337508841Author:CareyPublisher:Cengage
A Guide to SQL
Computer Science
ISBN:9781111527273
Author:Philip J. Pratt
Publisher:Course Technology Ptr
Database Systems: Design, Implementation, & Manag...
Computer Science
ISBN:9781305627482
Author:Carlos Coronel, Steven Morris
Publisher:Cengage Learning
Database Systems: Design, Implementation, & Manag...
Computer Science
ISBN:9781285196145
Author:Steven, Steven Morris, Carlos Coronel, Carlos, Coronel, Carlos; Morris, Carlos Coronel and Steven Morris, Carlos Coronel; Steven Morris, Steven Morris; Carlos Coronel
Publisher:Cengage Learning
Np Ms Office 365/Excel 2016 I Ntermed
Computer Science
ISBN:9781337508841
Author:Carey
Publisher:Cengage