تحولات اخیر در هوش مصنوعی و فناوری‌های ارتباطی

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. 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