Recent Developments in Artificial Intelligence and Communication Technologies

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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
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