Table of Contents
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PREFACE
List of Contributors
Automatic Suggestion Model for Tourist Using Efficient BST Searching
Abstract
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
Abstract
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
Abstract
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
Data Collection
Training Phase
Recommendation Phase
FILTERING TECHNIQUES
Content-based Filtering
Collaborative Filtering
PROPOSED WORK
Problem Statement
Algorithm Used
Result
CONCLUSION
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENTS
REFERENCES
An Intelligent Surveillance System for Human Behavior Recognition: An Exhaustive Survey
Abstract
INTRODUCTION
Classification of Human Behavior
Normal Behavior
Abnormal Behavior
Suspicious Activity
Non-suspicious Activity
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
Optical Flow Features
Trajectory-based Features
Region-based Features
Classification and Activity Recognition
Some Activity Recognition Methods and Techniques
Artificial Neural Network (ANN)
Clustering
Hidden Markov Model (HMM)
Deep Learning Models
Convolutional Neural Network
Recurrent Neural Network
Vanilla Recurrent Neural Network (VRNN)
Long Short-Term Memory (LSTM)
Gated Recurrent Unit (GRU)
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
Abstract
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
Abstract
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
Abstract
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)
Abstract
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
Abstract
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
Abstract
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
Recent Developments in Artificial Intelligence and Communication Technologies
Edited by
Vikash Yadav
Government Polytechnic Bighapur Unnao
Board of Technical Education
Uttar Pradesh
India
Parashu Ram Pal
SAGE University, Bhopal
Madhya Pradesh
India
&
Chuan-Ming Liu
National Taipei University of Technology
Taiwan
BENTHAM SCIENCE PUBLISHERS LTD.
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PREFACE
Imparting intelligence has become the focus of various computational paradigms. Thanks to evolving soft computing and artificial intelligence methodologies, scientists have been able to explain and understand real-life processes and practices that formerly remained unexplored by dint of their underlying imprecision, uncertainties and redundancies, as well as the unavailability of appropriate methods for describing the inexactness, incompleteness and vagueness of information representation. Computational intelligence tries to explore and unearth intelligence embedded in the system under consideration.
This book aims to discuss computational intelligence approaches, initiatives, and applications in engineering and science fields (including Machine Intelligence, Mining Engineering, Modeling and Simulation, Computer, Communication, Networking and Information Engineering, Systems Engineering, Innovative Computing Systems, Adaptive Technologies for Sustainable Growth, and Theoretical and Applied Sciences). This collection should inspire various scholars to contribute research on intelligence principles and approaches in their respective research communities while enriching the body of research on computational intelligence.
Vikash Yadav
Department of Technical Education
Uttar Pradesh
IndiaParashu Ram Pal
SAGE University, Bhopal
Madhya Pradesh
India
&Chuan-Ming Liu
List of Contributors
Ankita GuptaG.B. Pant Engineering College, New Delhi, IndiaAnkit SrivastavaG.B. Pant Engineering College, New Delhi, IndiaAlok KumarMotilal Nehru National Institute of Technology Allahabad, Prayagraj Uttar Pradesh, IndiaAvjeet SinghMotilal Nehru National Institute of Technology Allahabad, Prayagraj Uttar Pradesh, IndiaAnoj KumarMotilal Nehru National Institute of Technology Allahabad, Prayagraj Uttar Pradesh, IndiaAnita YadavDepartment of Computer Science and Engineering, Harcourt Butler Technical University, Kanpur, Uttar Pradesh, IndiaDharmendra Kumar YadavMotilal Nehru National Institute of Technology, Prayagraj, Uttar Pradesh, IndiaEtika RastogiDepartment of Computer Science and Engineering, Meerut Institute of Engineering and Technology, Meerut, Uttar Pradesh, IndiaHarishchandra A. AkarteMotilal Nehru National Institute of Technology, Prayagraj, Uttar Pradesh, IndiaHardik SharmaDepartment of Computer Science and Engineering, Meerut Institute of Engineering & Technology, Meerut, U.P., IndiaKajal GuptaDepartment of Computer Science and Engineering, Meerut Institute of Engineering and Technology, Meerut, Uttar Pradesh, IndiaLipika GoelGokaraju Rangaraju Institute of Technology, Hyderabad, IndiaLekhrajMotilal Nehru National Institute of Technology Allahabad, Prayagraj Uttar Pradesh, IndiaMukesh RawatDepartment of Computer Science and Engineering, Meerut Institute of Engineering and Technology, Meerut, Uttar Pradesh, IndiaManish DixitDepartment of CSE & IT, Madhav Institute of Technology and Science, Gwalior, M.P., IndiaMohammed Abdul WajeedVasavi College of Engineering, Ibrahimbagh, Telangana, IndiaMahendra Pratap YadavSRMIST NCR Campus, Modinagar, Ghaziabad, UP-201204, IndiaMukesh RawatDepartment of Computer Science and Engineering, Meerut Institute of Engineering & Technology, Meerut, U.P., IndiaManan GuptaDepartment of Computer Science and Engineering, Meerut Institute of Engineering & Technology, Meerut, U.P., IndiaPooja GuptaMeerut Institute of Engineering and Technology, Meerut, Uttar Pradesh, IndiaPreksha PratapDepartment of Computer Science and Engineering, Meerut Institute of Engineering & Technology, Meerut, U.P., IndiaRohit AnandG.B. Pant Engineering College, New Delhi, IndiaRohit VashishtABES Engineering College, Ghaziabad, IndiaRuchi JayaswalDepartment of CSE & IT, Madhav Institute of Technology and Science, Gwalior, M.P., IndiaSonam GuptaAjay Kumar Garg Engineering College, Ghaziabad, IndiaUrvashi SaraswatDepartment of Computer Science and Engineering, Harcourt Butler Technical University, Kanpur, Uttar Pradesh, IndiaVimal KumarMeerut Institute of Engineering and Technology, Meerut, Uttar Pradesh, India
Automatic Suggestion Model for Tourist Using Efficient BST Searching
Etika Rastogi1,*,Kajal Gupta1,Mukesh Rawat1
1 Department of Computer Science and Engineering, Meerut Institute of Engineering and Technology, Meerut, Uttar Pradesh, India
Abstract
The traditional artificial guide service can be substituted by the advanced intelligent tourism guide system, which can help many developing tourism industries as the demand for tourism is going higher in today's world. An intelligent tourism guide system can create automatic recommendations according to the preferences [1]. With the instantaneous evolution of computer technology and electronic information technology as the basis, this chapter combines the tree-based algorithm and associated knowledge of tree theory to implement an algorithm and processing plan. The objective of our approach is to build a relationship between the user and the system. The application provides many services to the user meeting their needs and the purpose of gaining information about the places. The application mainly represents a mobile tour guide system with augmented reality. The main objective of the application is to make a system that runs on most of the mobile devices and becomes helpful to the user while visiting new places. The system should find a place using user preferences, like beaches, historical monuments, hill stations, temples, adventurous places, etc. The system should show recommendations about those places along with the description and images. This application will help the people who love to travel and want to travel to new places without having previous information about the place. This model [2-5] makes the use of efficient BST Searching as compared to the database. The information about various places is stored in the tree data structure, and it becomes easy to store a lot of data in the tree as compared to the database because it requires more memory and time to store lots of information into the database. The main advantage of using the system is to make the searching process easier and to ease the process of storing the data in the tree rather than the database. The tree-based algorithm is efficient in terms of storage and retrieval of data so that the performance of the system is enhanced. The application takes less time to fetch the data using a tree-based algorithm according to added preferences by the user as compared to the database, which takes more time to fetch the data and to display it as required.
Keywords: Algorithm, Binary search tree, Deserialization, Efficient searching, Intelligent tourism guide, Retrieval, Serialization, Traversal.
*Corresponding author Etika Rastogi: Department of Computer Science and Engineering, Meerut Institute of Engineering and Technology, Meerut, Uttar Pradesh, India; E-mail:
[email protected]CONSENT FOR PUBLICATION
Not applicable.
CONFLICT OF INTEREST
The author declares no conflict of interest, financial or otherwise.
ACKNOWLEDGEMENTS
Declared none.
References
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