
Proceedings of ICRIC 2019
Description
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This book presents high-quality, original contributions (both theoretical and experimental) on software engineering, cloud computing, computer networks & internet technologies, artificial intelligence, information security, and database and distributed computing. It gathers papers presented at ICRIC 2019, the 2nd International Conference on Recent Innovations in Computing, which was held in Jammu, India, in March 2019. This conference series represents a targeted response to the growing need for research that reports on and assesses the practical implications of IoT and network technologies, AI and machine learning, cloud-based e-Learning and big data, security and privacy, image processing and computer vision, and next-generation computing technologies.
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Content
- Intro
- Preface
- Contents
- Advanced Computing
- Predictive Analysis of Absenteeism in MNCS Using Machine Learning Algorithm
- 1 Introduction
- 2 Predictive Analysis Using Machine Learning Algorithm
- 2.1 Linear Regression
- 2.2 Support Vector Regression (SVR)
- 3 Implementation of Predictive Model for Absenteeism
- 4 Conclusion and Future Work
- References
- IoT Based Healthcare Kit for Diabetic Foot Ulcer
- 1 Introduction
- 2 Related Work
- 3 Proposed System
- 3.1 Hardware
- 3.2 Sensing
- 3.3 Harvesting and Analysis
- 3.4 Alert and Reporting
- 4 Results
- 5 Conclusion
- References
- Context-Aware Smart Reliable Service Model for Intelligent Transportation System Based on Ontology
- 1 Introduction
- 2 Background Study
- 3 Ontology Based Context-Awareness in ITS
- 4 Context-Aware ITS: Use Case Scenarios
- 4.1 Use Case 1: Dynamic Traffic Signal Management (DYSM)
- 4.2 Use Case 2: Smart Parking System
- 5 Conclusion
- References
- Static, Dynamic and Intrinsic Features Based Android Malware Detection Using Machine Learning
- 1 Introduction
- 1.1 Android Malware Detection
- 1.2 Approaches to Detecting Malware
- 2 Machine Learning Classifiers
- 2.1 Support Vector Machine
- 2.2 k-Nearest Neighbor
- 2.3 Logistic Regression
- 2.4 Random Forest
- 3 Proposed Methodology
- 3.1 Data Collection
- 3.2 Feature Collection
- 3.3 Feature Extraction
- 3.4 Data Preprocessing
- 4 Experiment and Results
- 5 Conclusion and Future Scope
- References
- Machine Learning: A Review of the Algorithms and Its Applications
- 1 Introduction
- 2 Machine Learning
- 2.1 Supervised Learning
- 2.2 Unsupervised Learning
- 2.3 Deep Learning
- 2.4 Various Deep Learning Algorithms or Technologies
- 2.5 Applications
- 3 Conclusion
- References
- Deep Neural Networks for Diagnosis of Osteoporosis: A Review
- 1 Introduction
- 2 Overview of Deep Learning
- 3 Deep Learning for Diagnosis of Osteoporosis
- 3.1 Neural Networks Based on Clinical Observations
- 3.2 Deep Neural Networks Based on Image Analysis
- 4 Challenges and Future Perspectives
- 5 Conclusion
- References
- Predicting Drug Target Interactions Using Dimensionality Reduction with Ensemble Learning
- 1 Introduction
- 2 Proposed Methodology
- 2.1 Feature Encoding
- 2.2 Feature Subspacing
- 2.3 Dimensionality Reduction
- 2.4 Ensemble Learning
- 3 Experiments
- 3.1 Data
- 3.2 Experimental Results
- 4 Conclusion
- References
- Integration of Fog Computing and Internet of Things: An Useful Overview
- 1 Introduction
- 2 Related Work
- 2.1 Fog Computing-Definition
- 2.2 Similarities and Differences with Cloud Computing, Cloudlets, and Mobile Edge Computing
- 3 Interfacing Fog with Fog, Cloud, Internet of Things Devices/End-User Devices
- 4 Salient Features or Characteristics of Fog Computing
- 5 Real-Time Use Cases with Fog Computing
- 6 Challenges in Fog Computing with Internet of Things
- 7 Conclusion with Future Research Directions
- References
- Review of Machine Learning Techniques in Health Care
- 1 Introduction
- 2 Literature Survey
- 2.1 Health Care
- 2.2 Machine Learning
- 3 Applications and Current Integration of Machine Learning in Health Care
- 3.1 Medical Imaging
- 3.2 Diagnosis of Diseases
- 3.3 Behavior Modification or Treatment
- 3.4 Clinical Trial Research
- 3.5 Smart Electronic Health Records
- 3.6 Epidemic Outbreak Prediction
- 4 Conclusion
- References
- A Review of IoT Techniques and Devices: Smart Agriculture Perspective
- 1 Introduction
- 1.1 Internet of Things (IoT)
- 2 Applications of IoT in Agriculture
- 2.1 Sensor Technology
- 2.2 Soil Moister and Water-Level Sensor
- 2.3 RFID Technology
- 2.4 Radio Transmission Technology in Agriculture
- 2.5 Intelligent Irrigation Technology
- 2.6 Technical Quality Safety of Agricultural Products
- 2.7 Precision Seeding and Spraying Techniques
- 3 Benefits of IoT in Agriculture
- 3.1 Data Collected by Smart Agriculture Sensors
- 3.2 Superior Control Over the Internal Processes and, as a Result, Scarce Production Risks
- 3.3 Cost Management and Waste Shortage Felicitation to the Enhanced Control Over Production
- 3.4 Increased Business Competence Through Process Automation
- 3.5 Irrigation, Fertilizing, or Pest Control. Enhanced Product Quality and Volumes
- 4 Discussions
- 5 Conclusion
- References
- A Review of Scheduling Algorithms in Hadoop
- 1 Introduction
- 2 Hadoop
- 2.1 HDFS
- 2.2 MapReduce
- 3 Literature Review
- 4 Findings
- 5 Conclusion
- References
- Cellular Level Based Deep Learning Framework for Early Detection of Dysplasia in Oral Squamous Epithelium
- 1 Introduction
- 1.1 Dysplasia
- 1.2 Deep Learning
- 2 Literature Review
- 3 Materials and Methodology
- 4 Results and Discussion
- 5 Conclusion
- 6 Future Scope
- References
- Internet of Things-Based Hardware and Software for Smart Agriculture: A Review
- 1 Introduction
- 2 Background Study
- 3 Comparison of Current Techniques and Issues
- 4 Conclusion
- References
- Smart Approach for Real-Time Gender Prediction of European School's Principal Using Machine Learning
- 1 Introduction
- 2 Methods and Techniques
- 2.1 Dataset
- 2.2 Preprocessing
- 2.3 Testing and Validation
- 2.4 Knowledge Flow Environment
- 2.5 Performance Evaluation
- 3 Experiments Results, Analysis, and Evaluation
- 3.1 Confusion Matrices
- 3.2 Evaluation Matrices and ROC's
- 4 Web Server for Real-Time Prediction
- 5 Conclusion
- References
- GPU and CUDA in Hard Computing Approaches: Analytical Review
- 1 Introduction
- 2 GPU and CUDS
- 3 Hard Computing Applications
- 4 Comprehensive Analysis of Different Algorithms Implemented on GPU
- 4.1 Description
- 4.2 Description
- 4.3 Description
- 4.4 Description
- 4.5 Description
- 4.6 Description
- 4.7 Description
- 4.8 Description
- 4.9 Description
- 4.10 Description
- 4.11 Description
- 4.12 Description
- 4.13 Description
- 4.14 Description
- 4.15 Description
- 4.16 Description
- 4.17 Description
- 4.18 Description
- 4.19 Description
- 4.20 Description
- 4.21 Description
- 4.22 Description
- 4.23 Description
- 4.24 Description
- 4.25 Description
- 4.26 Description
- 4.27 Description
- 4.28 Description
- 4.29 Description
- 4.30 Description
- 5 Conclusion
- References
- IoT-Based Home Automation with Smart Fan and AC Using NodeMCU
- 1 Introduction
- 2 Related Work
- 3 Proposed System and Implementation
- 4 Challenges and Research Opportunities
- 4.1 Big Data
- 4.2 Distributed Computing
- 4.3 Privacy and Security
- 4.4 Edge Computing
- 5 Conclusion
- References
- Sampling Approaches for Imbalanced Data Classification Problem in Machine Learning
- 1 Introduction
- 2 Resampling Methods for Class Imbalance
- 2.1 Undersampling
- 2.2 Oversampling
- 3 Performance Evaluation
- 3.1 Datasets Used
- 3.2 Metrics
- 3.3 Machine Learning Algorithms Used
- 4 Results
- 4.1 Discussion of Results
- 5 Conclusion
- References
- Sentiment Analysis and Mood Detection on an Android Platform Using Machine Learning Integrated with Internet of Things
- 1 Introduction
- 2 Related Technologies Used
- 2.1 Twiggle
- 2.2 The North Face
- 2.3 Virtual Assistance
- 2.4 Akinator
- 2.5 Chatbots
- 3 Objectives of Moody Buddy Application
- 4 The Algorithm of Moody Buddy Application
- 4.1 Heart Rate Monitoring Device
- 4.2 Data Analysis
- 4.3 IBM Watson Questioning Answering System Proposed in Natural Language Processing
- 4.4 Once the Questionnaire Does Its Work and We Get a Calculated Result, Provisions Are Made of What to Be Done for Each and Every Emotion
- 5 Comparisons with the Related Technologies
- 6 Conclusion
- References
- Predictive Strength of Selected Classification Algorithms for Diagnosis of Liver Disease
- 1 Introduction
- 2 Data Visualization and Data Analysis
- 3 Proposed Technique
- 3.1 Cross-Validation Algorithm
- 3.2 Logistic Regression Algorithm
- 3.3 Support Vector Machine Algorithm (SVM)
- 3.4 Decision Tree Classification
- 3.5 K-Nearest Neighbors
- 3.6 Naive Bayes Algorithm
- 4 Performance Metrics and Experimental Result
- 5 Conclusion
- References
- A Review of Applications, Approaches, and Challenges in Internet of Things (IoT)
- 1 Introduction
- 2 Application Areas of Internet of Things
- 2.1 Smart Home
- 2.2 Smart City
- 2.3 Wearable
- 2.4 Smart Farming
- 2.5 Machine-to-Machine
- 3 Literature Review
- 4 Challenges
- 4.1 Privacy
- 4.2 Security
- 4.3 Energy Efficient
- 4.4 Interoperability
- 5 Conclusion and Future Work
- References
- Intellegent Networking
- Web Search Personalization Using Semantic Similarity Measure
- 1 Introduction
- 2 Related Work
- 3 Methodology
- 3.1 User Identification
- 3.2 Query Preprocessing
- 3.3 User Profile
- 3.4 Semantic Similarity
- 3.5 Query Modification
- 3.6 Ontology-Based Retrieval
- 4 Experiments and Results
- 5 Discussion and Evaluation of Experimental Results
- 6 Conclusion
- References
- Efficient Data Transmission in Wireless Sensor Networks
- 1 Hybrid Artificial Bee Colony with Salp Meta-Heuristic
- 1.1 Standard ABC
- 2 Hybrid Artificial Bee Colony with Salp Meta-Heuristic
- 2.1 Initialization Phase
- 2.2 Improved Employed Bee Phase
- 2.3 Improved Onlooker Bee Phase
- 2.4 Improved Scout Bee Phase
- 3 Efficient Data Transmission Using HABCS Meta-Heuristic
- 3.1 HABCS-Initialization Phase
- 3.2 HABCS-Route Searching Phase
- 3.3 ABCS-Data Transmission Phase
- 4 Performance Evaluation and Result Analysis
- 5 Conclusion and Future Work
- References
- Lifetime Improvement in Wireless Sensor Networks Using Hybrid Grasshopper Meta-Heuristic
- 1 Introduction
- 2 Proposed Hybrid Artificial Grasshopper Optimization Algorithm (HAGOA)
- 2.1 Artificial Grasshopper Optimization (AGOA)
- 3 Artificial Bee Colony (ABC) Variance
- 3.1 Initialization Phase
- 3.2 Improved Employed Bee Phase
- 3.3 Improved Onlooker Bee Phase
- 3.4 Improved Scout Bee Phase
- 4 Energy Optimization Using HAGOA
- 4.1 Fitness Function Notation for Node Deployment
- 4.2 Fitness Function Notation for Cluster Head Selection
- 4.3 Fitness Function Evaluation for Optimal Path Selection
- 5 HAGOA Execution
- 5.1 HAGOA Initialization Phase
- 5.2 HAGOA Cluster Phase
- 5.3 HAGOA Transmission Phase
- 6 Performance Evaluation and Result Analysis
- 7 Conclusion and Future Work
- References
- Routing Topologies and Architecture in Cognitive Radio Vehicular Ad hoc Networks
- 1 Introduction
- 2 Overview of Cognitive Radio and Its Architecture
- 3 Cognitive Radio Vehicular Ad hoc Network
- 4 Literature Review
- 5 CR-VANET for Topology and Routing Protocols
- 6 Conclusion and Future Scope
- References
- Parameter Optimization Using PSO for Neural Network-Based Short-Term PV Power Forecasting in Indian Electricity Market
- 1 Introduction
- 2 Factors Influencing the Solar PV Power Output
- 2.1 Solar Radiation Intensity
- 2.2 Temperature
- 2.3 Pearson Correlation Coefficient
- 3 Proposed Approach
- 3.1 Feed-Forward Artificial Neural Network
- 3.2 Particle Swarm Optimization
- 4 Working of Proposed Forecasting Model
- 4.1 Data Summary
- 4.2 Pre-processing Stage
- 4.3 Data Preparation
- 4.4 Training Stage
- 4.5 Forecasting Stage
- 5 Performance Evaluation Index
- 6 Result and Discussion
- 7 Conclusion
- References
- Exploring the Effects of Sybil Attack on Pure Ad Hoc Deployment of VANET
- 1 Introduction
- 2 Ad Hoc/Topology-Based Routing Protocols
- 2.1 Dynamic Source Routing (DSR) Protocol
- 3 Position-Based Routing Protocols
- 3.1 Anchor-Based Street and Traffic-Aware Routing (A-Star)
- 4 Geocast-Based Routing Protocols
- 4.1 Mobicast
- 5 Cluster-Based Routing Protocol
- 5.1 Cluster-Based Routing (CBR) Protocol
- 6 Broadcast-Based Routing Protocols
- 6.1 Density-Aware Reliable Broadcasting Protocol (DECA)
- 7 A Mechanism for Prevention of Sybil Attack in Pure Ad Hoc VANET
- 8 Conclusion
- References
- Analysis and Design of WDM Optical OFDM System with Coherent Detection Using Different Channel Spacing
- 1 Introduction
- 2 Design and Simulation
- 3 Results and Discussion
- 4 Conclusion
- References
- Design and Investigation of Multiple TX/RX FSO Systems Under Different Weather Conditions
- 1 Introduction
- 2 FSO Challenges
- 2.1 Absorption and Scattering Loss
- 2.2 Fog
- 2.3 Rain
- 2.4 Snow
- 3 Simulation and Design
- 4 Results and Discussions
- 5 Conclusion
- References
- Dynamic Distance Based Lifetime Enhancement Scheme for HWSN
- 1 Introduction
- 1.1 Motivation
- 2 Literature Review
- 3 Proposed Approach
- 3.1 Assumptions
- 3.2 Problem Formulation
- 3.3 Energy Model
- 3.4 Setup and Steady-State Phase
- 3.5 Dynamic Region Selection
- 3.6 Dynamic Hoping Selection Process
- 3.7 Algorithm of Proposed Approach
- 4 Performance Evaluation
- 4.1 Performance Metrics
- 5 Conclusion
- References
- On Security of Opportunistic Routing Protocol in Wireless Sensor Networks
- 1 Introduction
- 2 Literature Survey
- 3 Comparative Analysis of Security Methods of Opportunistic Routing in WSN
- 4 Conclusion
- References
- The Significance of Using NDN in MANET
- 1 Introduction
- 2 History and Evolution of NDN and CCN
- 2.1 CCNx
- 2.2 NDNx
- 2.3 CCNNDN-NP (NDN Next Phase)
- 3 Introduction of NDN
- 3.1 NDN Hourglass Architecture
- 3.2 NDN Network Packet Format
- 3.3 NDN Operation
- 4 NDN Advantages for MANET Solution
- 4.1 Suitable for Wireless Communication
- 4.2 Node Mobility Support
- 4.3 No Exclusive Control Mechanism Is Required
- 4.4 Better and Simpler Routing Approach
- 4.5 Better Security Support
- 4.6 Energy Efficient
- 5 Conclusion
- References
- Using NDN in Improving Energy Efficiency of MANET
- 1 Introduction
- 2 Related Work
- 3 Justification of Using NDN for MANET
- 4 Research Methodology
- 4.1 Awareness of the Problem
- 4.2 Suggestion
- 4.3 Development
- 4.4 Evaluation
- 4.5 Conclusion
- 5 Preliminary Result
- 5.1 Testbed Setup
- 5.2 Experiment Result
- 6 Conclusion and Future Work
- References
- Image Processing and Computer Vision
- Fingerprint Biometric Template Security Schemes: Attacks and Countermeasures
- 1 Introduction
- 2 Taxonomy of Template Security Schemes
- 2.1 Feature Transformation Based Schemes
- 2.2 Biometric Cryptosystem Based Schemes
- 3 Literature Review
- 4 Analysis of Template Security Schemes
- 5 Conclusion
- References
- Effect of Blurring on Identification of Aerial Images Using Convolution Neural Networks
- 1 Introduction
- 2 Background Work
- 3 CNN Architecture
- 3.1 AlexNet
- 3.2 GoogLeNet
- 4 Results and Discussion
- 4.1 Data Collection
- 4.2 Observation
- 5 Conclusion
- References
- PSO-Tuned ANN-Based Prediction Technique for Penetration of Wind Power in Grid
- 1 Introduction
- 2 Wind Forecasting Methods
- 2.1 Timescales-Based Classification [6, 7]
- 2.2 Historical Data-Based Forecasting
- 3 Artificial Neural Network (ANN)
- 4 Particle Swarm Optimization (PSO)
- 5 Error Parameters Estimation
- 6 Results and Discussion
- 7 Conclusions
- References
- A Comprehensive Review on Face Recognition Methods and Factors Affecting Facial Recognition Accuracy
- 1 Introduction
- 2 Factors Affecting Face Recognition Accuracy
- 2.1 Occlusion
- 2.2 Low Resolution
- 2.3 Noise
- 2.4 Illumination
- 2.5 Pose Variation
- 2.6 Expressions
- 2.7 Aging
- 2.8 Plastic Surgery
- 3 Classification of Face Recognition Methods
- 3.1 Appearance-Based Methods
- 3.2 Feature-Based Matching Methods
- 3.3 Hybrid Methods
- 4 A Review of Face Recognition Methods Used in Different Studies
- 4.1 Appearance-Based Approaches
- 4.2 Feature-Based Approaches
- 4.3 Hybrid Approach
- 5 Conclusion
- References
- Detection of Eye Ailments Using Segmentation of Blood Vessels from Eye Fundus Image
- 1 Introduction
- 2 Image Processing in Blood Vessel Segmentation
- 3 Literature Review
- 4 Current Gaps and Challenges
- 5 Materials and Methods
- 5.1 Dataset
- 6 Segmentation Results and Analysis
- 7 Conclusions and Future Scope
- References
- Multi-focus Image Fusion: Quantitative and Qualitative Comparative Analysis
- 1 Introduction
- 2 Materials and Methods
- 2.1 Material
- 2.2 Methods
- 3 Results and Discussion
- 4 Conclusion
- References
- Computer-Assisted Diagnosis of Thyroid Cancer Using Medical Images: A Survey
- 1 Introduction
- 2 Pre-processing
- 3 Segmentation
- 4 Classification
- 5 Discussion
- 6 Conclusion
- References
- A Novel Approach of Object Detection Using Point Feature Matching Technique for Colored Images
- 1 Introduction
- 1.1 Computer Vision
- 1.2 Prerequisite of Object Recognition
- 2 Related Work for Object Detection
- 3 Speeded-Up Robust Feature (SURF)
- 4 Feature Detection
- 5 Algorithm
- 6 Results of Proposed Method
- 7 Conclusion
- References
- E-Learning Cloud and Big Data
- Behavior Study of Bike Driver and Alert System Using IoT and Cloud
- 1 Introduction
- 2 Motivation
- 3 Related Work
- 4 eCall
- 5 Contran 245 [3]
- 6 Miroad
- 7 Proposed Model
- 7.1 Proposed Rule Set
- 8 Experimental Results
- 9 Conclusion
- References
- E-Learning Web Accessibility Framework for Deaf/Blind Kannada-Speaking Disabled People
- 1 Introduction
- 2 Literature Review
- 3 Kannada Moon Code for Disabled People
- 4 Proposed Web Accessibility Framework for Deaf/blind Kannada-Speaking Disabled People
- 5 Conclusion
- References
- Real-Time Prediction of Development and Availability of ICT and Mobile Technology in Indian and Hungarian University
- 1 Introduction and Related Work
- 2 Research Design and Methodology
- 2.1 Dataset and Preprocessing
- 2.2 Feature Extraction
- 2.3 Training, Testing, and Validation
- 2.4 Classifiers
- 2.5 Performance Metrics
- 2.6 Real Time
- 3 Experiments and Result Discussions
- 3.1 Experiment-I
- 3.2 Experiment-II
- 3.3 Experiment-III
- 3.4 Experiment-IV
- 4 Model Evaluation
- 5 Conclusion
- References
- A Web Extraction Browsing Scheme for Time-Critical Specific URLs Fetching
- 1 Introduction
- 2 Literature Survey
- 3 Problem Definition
- 4 Proposed Work
- 5 Performance Analysis and Discussion
- 6 Conclusion and Future Scope
- References
- Necessary Information to Know to Solve Class Imbalance Problem: From a User's Perspective
- 1 Introduction
- 2 Existing Analysis Techniques for Solving the Class Imbalance Problem
- 3 The Existence of Imbalanced Data Classification in the Different Application Domains
- 4 Evaluation Model for Addressing Class Imbalance Problem
- 5 Possible Research Directions
- 6 Open Discussion
- 7 Conclusions
- References
- Suicidal Ideation from the Perspective of Social and Opinion Mining
- 1 Introduction
- 2 Literature Review
- 3 Data Collection in Existing Work
- 4 Findings
- 5 Conclusion
- 6 Future Scope
- References
- Performance Analysis of Queries with Hive Optimized Data Models
- 1 Introduction
- 2 Features of Hive
- 3 Hive Optimized Data Models
- 3.1 Partitioning
- 3.2 Bucketing
- 3.3 File Formats ORC and Parquet
- 4 Related Work
- 5 Methodology
- 5.1 Datasets
- 5.2 Problem Statements
- 6 Experimental Analysis
- 7 Results
- 8 Conclusion
- References
- A Review on Scalable Learning Approches on Intrusion Detection Dataset
- 1 Introduction
- 2 Experimental Details
- 3 Results and Discussion
- 4 Conclusion
- References
- Assessing Drivers for Telecom Service Experience-Insights from Social Media
- 1 Introduction
- 2 Literature Review
- 3 Theoretical Framework
- 4 Methodology
- 5 Overview of Findings
- 5.1 Word Cloud
- 5.2 Multiple Regression Model Summary
- 6 Discussion
- 7 Conclusion
- References
- Collaborative Topic Regression-Based Recommendation Systems: A Comparative Study
- 1 Introduction
- 2 Background
- 3 Recommendation Models in CTR Family
- 4 Models in Comparison
- 5 Comparison of Recommendation Models
- 5.1 Similarities in Models
- 5.2 Dissimilarities in Models
- 6 Discussion and Future Directions
- 7 Conclusion
- References
- Automatic Extraction of Product Information from Multiple e-Commerce Web Sites
- 1 Introduction
- 2 Related Work
- 3 The Proposed Architecture
- 4 Experimental Setup and Evaluation
- 5 Conclusion
- References
- Security and Privacy
- Performance Evaluation and Modelling of the Linux Firewall Under Stress Test
- 1 Introduction
- 2 Related Work
- 3 Experiment Plan
- 3.1 Experimental Set-up
- 3.2 Experiment Plan
- 4 Observations and Results
- 4.1 Impact of Packet Rate and Rule-Set Size on the Performance of Iptables
- 4.2 Impact of Packet Rate and Time Duration on the Performance of Iptables
- 4.3 Impact of Time Duration on the Performance of Iptables
- 5 Mathematical Model
- 6 Validation of the Model
- 7 Conclusion and Future Scope
- References
- Template Security in Iris Recognition Systems: Research Challenges and Opportunities
- 1 Introduction
- 1.1 Attacks on Iris Biometric System
- 2 Iris Template Security
- 3 Review of Literature
- 4 Interpretations Appertaining to Various Iris Recognition Techniques
- 5 Research Challenges
- 6 Conclusion and Future Scope
- References
- Comprehending Code Fragment in Code Clones: A Literature-Based Perspective
- 1 Introduction
- 2 Understanding Code Fragment
- 3 Units of Measuring Clone Size
- 4 Minimum Clone Length
- 5 Impact of Clone Length
- 6 Conclusion and Future Work
- References
- Mobile Edge Computing-Enabled Blockchain Framework-A Survey
- 1 Introduction
- 2 Overview of MEC Architecture
- 2.1 Modulars in MEC
- 2.2 The MEC Architecture
- 3 Blockchain Consensus and Mining in MEC Architecture
- 3.1 Security Issues in MEC Architecture
- 3.2 Blockchain-Based Solutions
- 4 Proposed Mobile Blockchain-Enabled Edge Framework
- 5 Conclusions and Future Work
- References
- Performance Evaluation of Snort and Suricata Intrusion Detection Systems on Ubuntu Server
- 1 Introduction
- 1.1 Snort
- 1.2 Suricata
- 1.3 Snort Versus Suricata
- 2 Previous Work
- 3 Experimental SetUp
- 4 Results and Observations
- 5 Conclusion
- References
- Global Smart Card ID Using RFID: Realization of Worldwide Human Mobility for Universal Validation
- 1 Background
- 2 Introduction
- 3 A Brief Technological Overview
- 3.1 Smart Card Technology
- 3.2 RFID Technology
- 3.3 Biometric Technology
- 4 Necessity of Global Identification and Current Scenario
- 5 Major Research Approach and Validation
- 6 Challenges and Major Issues with Global Smart Card ID Using RFID
- 6.1 Registrations of Users with Multiple Identities
- 6.2 Interoperability Requirements
- 6.3 Issues of Identity Thefts and Security
- 6.4 Depleting Trust on Biometric IDs
- 6.5 Management of Associated Database System
- 6.6 Issue of Global Frequency Harmonization
- 7 Future Research Impact
- 8 Conclusion
- References
- Design of Low-Power Dual Edge-Triggered Retention Flip-Flop for IoT Devices
- 1 Introduction
- 2 Proposed Device
- 3 Results and Discussion
- 4 Conclusion
- References
- Digital India
- Development of Slot Engine for Gaming Using Java
- 1 Introduction
- 2 Flow Chart for Game Development
- 3 Flow Chart for Spirits of Zen
- 4 Features of the Game
- 4.1 Feature 1
- 4.2 Feature 2
- 4.3 Feature 3
- 5 Free Spin
- 6 Free Spin Bonus
- 7 Reels and Win Information
- 8 Payment Table
- 9 Server Testing of the Game
- 10 Conclusion
- References
- Hydroponics-An Alternative to Indian Agriculture System and Current Trends: A Review Study
- 1 Introduction
- 2 Background
- 3 Literature Review
- 4 Proposed Solution
- 5 Discussion
- 6 Conclusion
- References
- Sports Policy Implementation by the IoT Platform
- 1 Introduction
- 2 Literature Review
- 2.1 Related Work Embedded IMU
- 2.2 Wearable, Camera, and Sports Analytics
- 2.3 Localization and Motion Tracking
- 3 Purpose of the Study
- 4 Research Methodology Used in This Study
- 5 System Architecture for Smart Sports Policy
- 5.1 Implementation of Sports Policy with IoT Architecture for Play Field Games
- 6 Findings and Discussion
- 6.1 Findings from Research Work
- 7 Conclusion
- References
- Bayesian Prediction on PM Modi's Future in 2019
- 1 Introduction
- 1.1 Contributions
- 2 Research Methodology
- 2.1 External Variables
- 2.2 Influential Variables
- 2.3 Decision Variable
- 3 Experiment
- 4 Discussion
- 5 Conclusion
- References
- Design and Analysis of Thermoelectric Energy Harvesting Module for Recovery of Household Waste Heat
- 1 Introduction
- 2 Materials and Methods
- 2.1 Designing of Various Components
- 3 Results and Discussions
- 4 Conclusion
- References
- A Model of Information System Interventions for e-Learning: An Empirical Analysis of Information System Interventions in e-Learner Perceived Satisfaction
- 1 Introduction
- 2 Theoretical Framework
- 3 Research Model and Hypotheses
- 4 Research Methods
- 4.1 Instrument Development
- 4.2 Data Collection
- 5 Data Analysis and Results
- 5.1 Factor Analysis (Exploratory and Confirmatory Factor Analysis)
- 5.2 Reliability and Validity
- 5.3 Structural Model and Hypotheses Testing
- 6 Discussion and Implications
- 6.1 Limitations and Implications for Future Research
- References
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