This book is a review of recent artificial intelligence approaches, initiatives and applications in engineering and science fields. It features contributions that highlight the use of techniques such as machine learning, mining engineering, modeling and simulation, and fuzzy logic methods in the fields of communication, networking and information engineering.
The collection of chapters should inspire scholars involved in theoretical and applied sciences to contribute to research using computational intelligence principles and methods in their respective research communities. Professionals working on systems engineering, communications, innovative computing systems and adaptive technologies for sustainable growth, will also be able to benefit from the information provided in the book.
Author(s): Vikash Yadav, Parashu Ram Pal, Chuan-Ming Liu
Publisher: Bentham Science Publishers
Year: 2022
Language: English
Pages: 231
City: Singapore
Cover
Title
Copyright
End User License Agreement
Contents
Preface
List of Contributors
Automatic Suggestion Model for Tourist Using Efficient BST Searching
Etika Rastogi1,*, Kajal Gupta1 and Mukesh Rawat1
INTRODUCTION
Study of the Existing System
Design and Implementation of the Proposed System
Module Description
Algorithm Used
Design and Implementation of the Recommendation Model
Module Description
Algorithm Used
Execution of the Recommended Model
Performance Analysis
CONCLUSION
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENTS
REFERENCES
Internet Protocols: Transition, Security Issues and the World of IoT
Ankita Gupta1, Ankit Srivastava1 and Rohit Anand1,*
INTRODUCTION
RELATED WORK
IPV4 AND IPV6
IPv4
IPv6
Shortcomings of IPv4
NEED TO TRANSITION FROM IPV4 TO IPV6
IPv4 and IPv6 Coexistence
SECURITY THREATS
Security Threats Common to IPv4 and IPv6
Security Threats Related to IPv6
Security Threats Caused Due to Transition Mechanism
IPV6 & THE WORLD OF IOT
IPv6 over IPv4 for IoT
Why IPv6 for IoT?
Routing - IPv6 and the IoT Network
IoT Architecture Based on IPv6
CONCLUSION AND FUTURE SCOPE
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENTS
REFERENCES
Recommender Systems and their Application in Recommending Research Papers
Sonam Gupta1,*, Lipika Goel2 and Rohit Vashisht3
INTRODUCTION
Need for Recommendation System
Power of the Recommendation System
Prerequisite of Recommendation System
Natural Language Processing (NLP)
LSA Algorithm
Artificial Neural Network
LITERATURE SURVEY
STEPS OF RECOMMENDATION PROCESS
A. Data Collection
A. Training Phase
B. Recommendation Phase
FILTERING TECHNIQUES
1. Content-based Filtering
2. Collaborative Filtering
PROPOSED WORK
A. Problem Statement
B. Algorithm Used
C. Result
CONCLUSION
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENTS
REFERENCES
An Intelligent Surveillance System for Human Behavior Recognition: An Exhaustive Survey
Ruchi Jayaswal1,* and Manish Dixit1
INTRODUCTION
Classification of Human Behavior
Normal Behavior
Abnormal Behavior
Problems and Challenges
Motivation and Recent Trends
Framework for Abnormal Human Activity and Behavior Analysis
Preprocessing and Foreground Object Detection
Object Tracking
Feature Extraction and Motion Information
Classification and Activity Recognition
Some Activity Recognition Methods and Techniques
Artificial Neural Network (ANN)
Clustering
Hidden Markov Model (HMM)
Deep Learning Models
Datasets
Datasets of Abandoned Object Detection
Theft Detection Datasets
Falling Detection Dataset
Violence Detection Datasets
Fire Detection Datasets
Miscellaneous Dataset
Evaluation Metrics
Accuracy
Precision (PR), Recall (RP) and F-measure (FM)
Sensitivity and Specificity
Percent Events Detected (P.E.D.) and Percent Alarms True (P.A.T.)
Confusion Metrics
ROC Curve
CONCLUSION
Future Scope
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENTS
REFERENCES
Load Balanced Clustering in WSN using MADM Approaches
Lekhraj1,*, Alok Kumar1, Avjeet Singh1 and Anoj Kumar1
INTRODUCTION
LITERATURE SURVEY
RADIO MODEL AND UNDERTAKING
Undertaking
Radio Model
MADM APPROACHES
Topsis Approach
Promethee Approach
ATTRIBUTES USED IN SIMULATED WORK
Coverage_of_CHs
CHs_Avg_Distance
BS_AVG_DISTANCE
Avg_Eresidual
CHs_Avg_lifetime
BS_CH_Bearing
BS_Max_Distance
Eres_Con_CHS
DATA SET AND EVOLUTION METHOD
CHs Selection using TOPSIS
CHs Selection using PROMETHEE
SIMULATION RESULTS
CONCLUSION
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENTS
REFERENCES
An Overview of Energy Efficient and Data Accuracy Target Tracking Methods in WSN
Urvashi Saraswat1,* and Anita Yadav2
INTRODUCTION
Overview of Recent Target Tracking Methods in WSN
Characteristics Maintaining Energy Efficiency in Target Tracking Algorithms
Self-Organizing Network Approaches in Target Tracking
Discussion and Comparison
CONCLUSION AND FUTURE WORK
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENTS
REFERENCES
A Survey of Current Mobile Learning Technology in India
Pooja Gupta1,* and Vimal Kumar1
INTRODUCTION
M-Learning
MOBILE DEVICES
EVOLUTION OF MOBILE LEARNING
COMPONENETS OF MOBILE LEARNING
BENEFITS OF MOBILE LEARNING
CHALLENGES IN MOBILE LEARNING
APPLICATIONS OF MOBILE LEARNING
Online Learning and Blended Learning
Game-Based Learning (GBL)
Online Learning in Remote Areas
MOTIVATION
MOBILE LEARNING TOOLS
LITERATURE SURVEY
CONCLUSION AND FUTURE SCOPE
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENTS
REFERENCES
Fuzzy Systems and Applications from an Engineer’s Perspective (Fuzzy Textual Data Classification - Case Study)
Mohammed Abdul Wajeed1,*
INTRODUCTION
Probability and Fuzzy Sets
Participation Function Terminology
Gaussian Participation Function
Operations on Fuzzy Sets
Text Classification
Vocabulory_Generation
Algorithm_2 Fuzzy_Collections
CONCLUDING REMARKS
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENTS
REFERENCES
Efficient Resources Utilization of Containerized Applications Using TOPSIS
Mahendra Pratap Yadav1,*, Harishchandra A. Akarte2 and Dharmendra Kumar Yadav2
INTRODUCTION
MOTIVATION
BACKGROUND RELATED TECHNOLOGY
Load Balancing
Containers
Docker Swarm
Docker
HA Proxy
Apache HTTP Server Benchmarking Tool
RELATED WORK
PROPOSED APPROACH
EXPERIMENTAL SETUP
Build Image
Docker Compose
Create Docker Swarm
Workload Generation
Plotting Results
RESULT ANALYSIS
CONCLUSION
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENTS
REFERENCES
Increasing Performance of Boolean Retrieval Model by Data Parallelism Technique
Mukesh Rawat1,*, Preksha Pratap1, Manan Gupta1 and Hardik Sharma1
INTRODUCTION
Information Retrieval
MAJOR I.R. MODELS
Boolean Retrieval Model
Narrowing and Broadening Techniques
Smart Boolean
Extended Boolean Models
INVERTED INDEXING
Increasing Performance of Boolean Retrieval Model Using Data Parallelism Technique
Issues and Challenges of BRM
WORKING OF THE PROPOSED BOOLEAN MODEL FOR IR
Sequential Execution of this Model
Module – 1. Storing Files
Algorithm
Module – 2. Data Pre-processing
Algorithm
Module – 3. Creation of Indexes and Posting lists (String w)
Algorithm
Module - 4 Boolean Intersection
Algorithm
Parallel Execution of BRM
Algorithm
RESULT ANALYSIS
Output Screen Shots of Program
Analysis
Precision
Recall
F-measure
CONCLUSION
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENTS
REFERENCES
Subject Index
Back Cover
