Data Structures and Algorithms in Java
6th Edition
ISBN: 9781118771334
Author: Michael T. Goodrich
Publisher: WILEY
expand_more
expand_more
format_list_bulleted
Question
Chapter 3, Problem 1R
Program Plan Intro
Pseudorandom Number generation:
In Java, there is a built-in class java.util.Random whose object as pseudorandom number to determine the sequence of numbers by randomly.
Note: Refer page number 113 to formula for next pseudorandom number in the text book.
According the formula given by the text book, the current seed “cur” value is needed to find the next pseudorandom number. But, here the only one current seed “cur” is given to find the five next pseudorandom numbers.
- Apply the given inputs for five times; get the same next pseudorandom number. So, take current seed value as “next pseudorandom number” to find the next pseudorandom numbers.
Expert Solution & Answer
Explanation of Solution
Determine the next five pseudorandom numbers:
The given inputs are,
a = 12
b = 5
n = 100
Current seed (cur) = 92
The formula for next pseudorandom number is given below:
First pseudorandom numbers:
Substitute the “a”, “b”, “n”, and “cur” in the Equation (1) to determine the first next pseudorandom number is given below:
Therefore, the first pseudorandom number for current seed (cur = 92) is 9.
Second pseudorandom numbers:
Here, let us consider the current seed “cur” as “9”. That is, result of first pseudorandom number.
Substitute the “a”, “b”, “n”, and “cur” in the Equation (1) to determine the first next pseudorandom number is given below:
Therefore, the second pseudorandom number for current seed (cur = 9) is 13.
Third pseudorandom numbers:
Here, let us consider the current seed “cur” as “13”. That is, result of second pseudorandom number.
Substitute the “a”, “b”, “n”, and “cur” in the Equation (1) to determine the first next pseudorandom number is given below:
Therefore, the third pseudorandom number for current seed (cur = 13) is 61.
Fourth pseudorandom numbers:
Here, let us consider the current seed “cur” as “61”. That is, result of second pseudorandom number.
Substitute the “a”, “b”, “n”, and “cur” in the Equation (1) to determine the first next pseudorandom number is given below:
Therefore, the fourth pseudorandom number for current seed (cur = 61) is 37.
Fifth pseudorandom numbers:
Here, let us consider the current seed “cur” as “37”. That is, result of second pseudorandom number.
Substitute the “a”, “b”, “n”, and “cur” in the Equation (1) to determine the first next pseudorandom number is given below:
Therefore, the fourth pseudorandom number for current seed (cur = 37) is 49.
Want to see more full solutions like this?
Subscribe now to access step-by-step solutions to millions of textbook problems written by subject matter experts!
schedule03:09
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 3 Solutions
Data Structures and Algorithms in Java
Ch. 3 - Prob. 1RCh. 3 - Write a Java method that repeatedly selects and...Ch. 3 - Prob. 3RCh. 3 - The TicTacToe class of Code Fragments 3.9 and 3.10...Ch. 3 - Prob. 5RCh. 3 - Prob. 6RCh. 3 - Prob. 7RCh. 3 - Prob. 8RCh. 3 - Prob. 9RCh. 3 - Prob. 10R
Ch. 3 - Prob. 11RCh. 3 - Prob. 12RCh. 3 - Prob. 13RCh. 3 - Prob. 14RCh. 3 - Prob. 15RCh. 3 - Prob. 16RCh. 3 - Prob. 17CCh. 3 - Prob. 18CCh. 3 - Prob. 19CCh. 3 - Give examples of values for a and b in the...Ch. 3 - Suppose you are given an array, A, containing 100...Ch. 3 - Write a method, shuffle(A), that rearranges the...Ch. 3 - Suppose you are designing a multiplayer game that...Ch. 3 - Write a Java method that takes two...Ch. 3 - Prob. 25CCh. 3 - Prob. 26CCh. 3 - Prob. 27CCh. 3 - Prob. 28CCh. 3 - Prob. 29CCh. 3 - Prob. 30CCh. 3 - Prob. 31CCh. 3 - Prob. 32CCh. 3 - Prob. 33CCh. 3 - Prob. 34CCh. 3 - Prob. 35CCh. 3 - Write a Java program for a matrix class that can...Ch. 3 - Write a class that maintains the top ten scores...Ch. 3 - Prob. 38PCh. 3 - Write a program that can perform the Caesar cipher...Ch. 3 - Prob. 40PCh. 3 - Prob. 41PCh. 3 - Prob. 42PCh. 3 - Prob. 43P
Knowledge Booster
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
C++ for Engineers and ScientistsComputer ScienceISBN:9781133187844Author:Bronson, Gary J.Publisher:Course Technology Ptr
C++ Programming: From Problem Analysis to Program...Computer ScienceISBN:9781337102087Author:D. S. MalikPublisher:Cengage Learning
Systems ArchitectureComputer ScienceISBN:9781305080195Author:Stephen D. BurdPublisher:Cengage Learning
Programming with Microsoft Visual Basic 2017Computer ScienceISBN:9781337102124Author:Diane ZakPublisher:Cengage Learning
New Perspectives on HTML5, CSS3, and JavaScriptComputer ScienceISBN:9781305503922Author:Patrick M. CareyPublisher:Cengage Learning
Np Ms Office 365/Excel 2016 I NtermedComputer ScienceISBN:9781337508841Author:CareyPublisher:Cengage
C++ for Engineers and Scientists
Computer Science
ISBN:9781133187844
Author:Bronson, Gary J.
Publisher:Course Technology Ptr
C++ Programming: From Problem Analysis to Program...
Computer Science
ISBN:9781337102087
Author:D. S. Malik
Publisher:Cengage Learning
Systems Architecture
Computer Science
ISBN:9781305080195
Author:Stephen D. Burd
Publisher:Cengage Learning
Programming with Microsoft Visual Basic 2017
Computer Science
ISBN:9781337102124
Author:Diane Zak
Publisher:Cengage Learning
New Perspectives on HTML5, CSS3, and JavaScript
Computer Science
ISBN:9781305503922
Author:Patrick M. Carey
Publisher:Cengage Learning
Np Ms Office 365/Excel 2016 I Ntermed
Computer Science
ISBN:9781337508841
Author:Carey
Publisher:Cengage