
IoT Based Control Networks and Intelligent Systems
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This book gathers selected papers presented at International Conference on IoT Based Control Networks and Intelligent Systems (ICICNIS 2023), organized by School of Computer Science and Engineering, REVA University, Bengaluru, India, during June 21-22, 2023. The book covers state-of-the-art research insights on Internet of things (IoT) paradigm to access, manage, and control the objects/things/people working under various information systems and deployed under wide range of applications like smart cities, healthcare, industries, and smart homes.
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Content
- Intro
- Preface
- Contents
- Editors and Contributors
- A Comparative Analysis of ISLRS Using CNN and ViT
- 1 Introduction
- 2 Literatures
- 3 Methodology
- 3.1 Dataset
- 3.2 Custom CNN Model
- 3.3 Vision Transformer
- 4 Results and Discussion
- 5 Conclusion and Scope of Future Work
- References
- Vehicle Information Management System Using Hyperledger Fabric
- 1 Introduction
- 2 Existing Vehicle Registration System
- 3 Existing Techniques for Vehicle Registration Using Blockchain
- 4 Proposed Scheme
- 4.1 New Vehicle Registration
- 4.2 Query
- 4.3 Interstate Vehicle Transfer
- 5 Implementation
- 6 Result
- 6.1 Performance Evaluation of Query Smart Contract
- 6.2 Performance Evaluation of CreateVehicle() Smart Contract
- 6.3 Performance Evaluation of Transfer(): Smart Contract
- 7 Conclusion and Future Work
- References
- S-SCRUM-Methodology for Software Securitisation at Agile Development. Application to Smart University
- 1 Introduction
- 2 Security SCRUM
- 2.1 The Role of the Security Expert
- 2.2 Security Analysis Process
- 3 S-SCRUM in Smart University
- 3.1 Sprint Securitisation-APR-Publish API Rest
- 3.2 Results of Implementing S-SCRUM at Smart University
- 4 Contributions and Lessons Learned
- 5 Conclusions
- References
- Energy-Efficient Reliable Communication Routing Using Forward Relay Selection Algorithm for IoT-Based Underwater Networks
- 1 Introduction
- 2 Underwater Sensor Network Architecture, Key Issues, and Challenges
- 2.1 Power Consumption
- 2.2 High Propagation Delay
- 2.3 Low Security
- 2.4 Navigation
- 2.5 Multipath Weakening
- 2.6 Link Budget
- 2.7 Synchronization
- 2.8 Channel Utilization
- 3 Related Works
- 4 Proposed Methodology
- 5 Results and Discussion
- 6 Conclusion
- References
- Deep Learning Approach based Plant Seedlings Classification with Xception Model
- 1 Introduction
- 2 Related Work
- 3 Proposed Approach
- 3.1 Data Preprocessing
- 4 Methods-Deep Pretrained Models
- 5 Results Analysis
- 5.1 Aarhus Dataset
- 5.2 Experimental Results
- 6 Performance Analysis on Aarhus Dataset
- 7 Conclusion
- References
- Improving Node Energy Efficiency in Wireless Sensor Networks (WSNs) Using Energy Efficiency-Based Clustering Adaptive Routing Scheme
- 1 Introduction
- 2 Related Works
- 3 Materials and Method
- 3.1 Node Initialization and Formation of Cluster
- 3.2 Influencing Cluster Routing Protocol
- 3.3 Time Energy Efficiency-Based Clustering Adaptive Routing Scheme (EECARS)
- 4 Result and Discussion
- 5 Conclusion
- References
- An Evaluation of Prediction Method for Educational Data Mining Based on Dimensionality Reduction
- 1 Introduction
- 2 Related Study
- 3 Methodology
- 3.1 Dataset Description
- 3.2 Data Preprocessing
- 3.3 Implemented Model
- 3.4 Principal Component Analysis
- 3.5 Linear Discriminant Analysis
- 3.6 Logistic Regression
- 4 Experimental Result
- 4.1 Employing Different Algorithms for Comparison
- 5 Discussion
- 6 Conclusion and Future Work
- References
- High-Performance Intelligent System for Real-Time Medical Image Using Deep Learning and Augmented Reality
- 1 Introduction
- 2 Related Works
- 3 Dataset Description
- 4 Methodology
- 4.1 Convolutional Neural Network
- 4.2 Brain Hemorrhage
- 4.3 Eye Retinopathy
- 4.4 Architectural Diagram
- 5 Experiment
- 6 Results and Discussion
- 7 Conclusion
- 8 Future Work
- References
- Diabetic Retinopathy Detection Using Machine Learning Techniques and Transfer Learning Approach
- 1 Introduction
- 2 Related Work
- 3 Proposed Work
- 3.1 Dataset
- 3.2 Preprocessing
- 3.3 Machine Learning Techniques
- 3.4 Transfer Learning Techniques
- 4 Result Analysis
- 4.1 Binary Classification
- 4.2 Multiclass Classification
- 5 Conclusion
- References
- Recommender System of Site Information Content for Optimal Display in Search Engines
- 1 Introduction
- 2 Review of Methods for Attracting New Customers Using Online Search Engines
- 3 Results and Discussion
- 4 Conclusions
- References
- Development of IoT-Based Vehicle Speed Infringement and Alcohol Consumption Detection System
- 1 Introduction
- 2 Related Work
- 3 Proposed Work
- 3.1 Working
- 4 Result Analysis
- 5 Conclusion
- References
- Phonocardiogram Identification Using Mel Frequency and Gammatone Cepstral Coefficients and an Ensemble Learning Classifier
- 1 Introduction
- 2 Materials and Method
- 2.1 Database
- 2.2 Preprocessing
- 3 Features Extraction
- 3.1 Mel Frequency Cepstral Coefficients MFCC
- 3.2 Gammatone Cepstral Coefficients GTCC
- 4 Classification
- 5 Results and Discussion
- 6 Conclusion
- References
- Automatic Conversion of Image Design into HTML and CSS
- 1 Introduction
- 2 Related Work
- 3 Tools for Creating and Converting the Design into Code
- 4 Converting Image Design into HTML/CSS
- 4.1 Step 1-Create a Graphic Design Mockup
- 4.2 Step 2-Convert a Graphic Design Mockup to HTML/CSS
- 5 Conclusion
- References
- Customizing Arduino LMiC Library Through LEAN and Scrum to Support LoRaWAN v1.1 Specification for Developing IoT Prototypes
- 1 Introduction
- 2 Methodology
- 3 Proposed Work
- 3.1 Identification
- 3.2 Planning
- 3.3 Execution
- 3.4 Review
- 4 Result Analysis
- 4.1 LoRaWAN v1.1 Class A OTAA Unconfirmed Uplinks
- 4.2 LoRaWAN v1.1 Class A ABP Confirmed Uplinks
- 4.3 LoRaWAN v1.1 Class A ABP Confirmed Downlinks
- 4.4 LoRaWAN v1.1 Key Persistence and Device Restart
- 4.5 LoRaWAN v1.0 Class A ABP Versus LoRaWAN v1.1 Class A ABP
- 5 Conclusions
- References
- Prevention of Wormhole Attack Using Mobile Secure Neighbour Discovery Protocol in Wireless Sensor Networks
- 1 Introduction
- 2 Related Works
- 3 System Model
- 3.1 Threat Model
- 3.2 Problem Formulation
- 4 Proposed Method
- 4.1 Ranging
- 5 Security Analysis
- 6 Result and Discussion
- 7 Conclusion
- References
- Comparison of Feature Extraction Methods Between MFCC, BFCC, and GFCC with SVM Classifier for Parkinson's Disease Diagnosis
- 1 Introduction
- 2 Materials and Methods
- 2.1 Database
- 2.2 Feature Extraction Techniques
- 2.3 Classification Methods
- 2.4 The Proposed Algorithm
- 2.5 Evaluation Metrics
- 3 Results and Discussion
- 4 Conclusion
- References
- A Comprehensive Study on Artificial Intelligence-Based Face Recognition Technologies
- 1 Introduction
- 2 Related Work
- 3 Techniques Used
- 3.1 Deep Convolutional Neural Networks
- 3.2 Deep Face
- 3.3 VGG-Face
- 3.4 Capsule Networks
- 3.5 3D Face Recognition
- 3.6 Principal Component Analysis
- 3.7 Linear Discriminant Analysis
- 3.8 FaceNet
- 4 Proposed Model
- 4.1 Future Scope in Proposed Model
- 5 Application
- 6 Conclusion
- References
- Design of IoT-Based Smart Wearable Device for Human Safety
- 1 Introduction
- 2 Literature Survey
- 3 Methodology
- 3.1 Working
- 4 Result
- 5 Conclusion and Future Enhancement
- References
- Detection of Artery/Vein in Retinal Images Using CNN and GCN for Diagnosis of Hypertensive Retinopathy
- 1 Introduction
- 2 Related Work
- 2.1 Segmentation of Blood Vessels
- 2.2 Classification of Artery/Vein
- 2.3 Classification of HR
- 3 Proposed Method
- 3.1 Datasets
- 3.2 Preprocessing
- 3.3 Segmentation of Blood Vessels
- 3.4 Classification of Artery/Vein Using Graph Convolutional Network (GCN)
- 4 Computation of AVR
- 5 Grading of HR
- 6 Experiments and Results
- 6.1 Determine of Parameters
- 6.2 Results and Discussion
- 7 Conclusion
- References
- An Evolutionary Optimization Based on Clustering Algorithm to Enhance VANET Communication Services
- 1 Introduction
- 1.1 VANET Overview
- 1.2 Various Optimization Techniques in VANET
- 1.3 Clustering Optimization
- 2 Related Research
- 3 Challenges
- 3.1 Clustering
- 4 Objective
- 5 Proposed Methodology of Honey Badger Algorithm in the VANET Approach
- 5.1 General Biology of the Honey Badger
- 5.2 Inspiration
- 5.3 Mathematical Framework
- 6 Performance Analysis Metrics
- 6.1 Packet Delivery Ratio (PDR)
- 6.2 End-to-End Delay
- 6.3 Network Overhead
- 6.4 Throughput
- 6.5 Energy Consumption
- 7 Result and Discussion
- 7.1 Experimental Setup
- 7.2 Performance Parameters for 1000 Iteration
- 7.3 Performance Parameters for 2000 Iterations
- 8 Conclusion
- References
- Visual Sentiment Analysis: An Analysis of Emotions in Video and Audio
- 1 Introduction
- 2 Literature Survey
- 3 Related Work
- 3.1 Facial Expression Recognition of FER-2013
- 3.2 Micro-Classification of Facial Expression
- 4 Results Analysis
- 4.1 Prediction Test of Facial Expression
- 5 Future Scope
- 6 Conclusion
- References
- Design and Functional Implementation of Green Data Center
- 1 Introduction
- 2 Literature Reviews
- 2.1 Related Work
- 3 Proposed System
- 3.1 Architecture of Our Green Data Center
- 4 Algorithm
- 4.1 Power Management Algorithms
- 4.2 Cooling Management Algorithms
- 4.3 Load Balancing Algorithms
- 5 Math Model
- 5.1 Power Usages Effectiveness
- 5.2 Carbon Usages Effectiveness
- 5.3 Energy Reuse Factor
- 5.4 Carbon Utility
- 6 Performance Evaluation
- 6.1 Power Usages Effectiveness
- 6.2 Carbon Usages Effectiveness
- 6.3 Energy Reuse Factor
- 6.4 Limitations and Challenges
- 7 Conclusion
- References
- Patient Pulse Rate and Oxygen Level Monitoring System Using IoT
- 1 Introduction
- 2 Related Works
- 3 Proposed System Design
- 4 Materials and Methods
- 4.1 Temperature Sensor
- 4.2 Pulse Rate and Oxygen Level Monitor
- 4.3 Arduino UNO
- 4.4 ESP32
- 4.5 THINGSPEAK
- 5 Results and Discussions
- 6 Conclusion
- References
- IoT-Based Solution for Monitoring Gas Emission in Sewage Treatment Plant to Prevent Human Health Hazards
- 1 Introduction
- 2 Objectives
- 2.1 Literature Review
- 2.2 Objective
- 3 Methodology
- 4 Implementation and Results
- 5 Conclusion
- References
- Evaluation of the Capabilities of LDPC Codes for Network Applications in the 802.11ax Standard
- 1 Introduction
- 2 Method for Describing the Concept in Decoding and Designing a Communication Channel Scheme
- 2.1 Approach for Building Codes
- 2.2 FPGA Implementation of LDPC Decoder
- 3 Results of Experimental Studies
- 3.1 Noise Immunity of the LDPC Basic Set
- 3.2 Limiting Possibilities of Decoding Algorithms
- 4 Conclusion
- References
- Parallel Optimization Technique to Improve the Performance of Lightweight Intrusion Detection Systems
- 1 Introduction
- 2 Related Work
- 2.1 Lightweight Intrusion Detection Systems
- 2.2 Feature Selection Techniques
- 2.3 Ensemble Learning
- 2.4 Parallel Computing Techniques
- 3 Proposed Methodology
- 3.1 Parallel Processing Framework
- 3.2 Feature Selection Techniques
- 3.3 Ensemble Learning Models
- 3.4 Hybrid Model
- 4 Experimental Evaluation
- 4.1 Experimental Setup
- 4.2 Datasets
- 4.3 Performance Metrics
- 4.4 Results and Discussion
- 5 Conclusion and Future Work
- References
- Enhancement in Securing Open Source SDN Controller Against DDoS Attack
- 1 Introduction
- 2 Literature Review
- 3 Proposed System
- 3.1 DDoS Attack Identification Architecture
- 3.2 POX Controller
- 3.3 DDoS Detection
- 3.4 DDoS Traffic Identification Using SVM
- 4 Results and Discussions
- 5 Conclusion
- References
- Proposal of a General Model for Creation of Anomaly Detection Systems in IoT Infrastructures
- 1 Introduction
- 2 Methodology for ADS Model
- 2.1 Internal Structure of the CM Process
- 2.2 Internal Structure of the Process D
- 3 Results
- 4 Conclusions and Future Work
- References
- Internet of Things (IoT) and Data Analytics for Realizing Remote Patient Monitoring
- 1 Introduction
- 2 Significance of Internet of Things
- 3 Existing Remote Patient Monitoring Approaches
- 3.1 Remote Patient Monitoring Systems
- 3.2 Remote Patient Monitoring for COVID-19 Patients
- 4 Technology Usage Dynamics
- 5 Relevance of Data Analytics for RPM as IoT Use Case
- 6 Summary of Important Findings
- 7 Research Gaps
- 8 Proposed System
- 9 Experimental Results
- 10 Conclusion and Future Work
- References
- A Brief Review of Swarm Optimization Algorithms for Electrical Engineering and Computer Science Optimization Challenges
- 1 Introduction
- 2 Research Methodology
- 2.1 Search Tactics
- 2.2 Research Database Selection
- 3 Swarm Intelligence Algorithms
- 3.1 Introduction to Swarm Intelligence Algorithms
- 3.2 Dragonfly Optimization Algorithm
- 3.3 Applications of Dragonfly Optimization Algorithm
- 3.4 Grey Wolf Optimization (GWO)
- 3.5 Applications of Grey Wolf Optimizer (GWO)
- 4 Whale Optimization Algorithm
- 4.1 Applications of Whale Optimization Algorithm
- 5 Comparison Between Algorithms Under Study for Test Functions
- 6 Our Perspective on the Research on Swarm Optimization Methods Under Study
- 7 Conclusion and Future Scope
- References
- Facilitating Secure Web Browsing by Utilizing Supervised Filtration of Malicious URLs
- 1 Introduction
- 2 Related Work
- 3 Methodology
- 3.1 Proposed Model
- 3.2 Phase1: Data set
- 3.3 Phase2: ML Models
- 3.4 Results and Descriptions
- 4 Discussion
- 5 Conclusion and Future Work
- References
- Unveiling the Impact of Outliers: An Improved Feature Engineering Technique for Heart Disease Prediction
- 1 Introduction
- 2 Review of Literatures
- 3 Feature Engineering for Outlier Detection and Removal (FEODR)
- 3.1 Data Collection
- 3.2 Feature Engineering
- 3.3 Train and Test the Model
- 3.4 Result and Discussion
- 4 Conclusion
- References
- Real-Time Road Hazard Classification Using Object Detection with Deep Learning
- 1 Introduction
- 2 Literature Review
- 3 Proposed Work
- 3.1 About YOLO v8
- 3.2 Dataset
- 3.3 Annotating the Dataset
- 3.4 Implementation
- 3.5 Limitations
- 4 Results and Future Work
- 4.1 Scores of Metrics
- 4.2 Confusion Matrix
- 4.3 F1 Curve
- 4.4 Precision Curve
- 4.5 Recall Curve
- 4.6 Output
- 4.7 Discussion of Experimental Results
- 4.8 Future Work
- 5 Conclusion
- References
- A Smart Irrigation System for Plant Health Monitoring Using Unmanned Aerial Vehicles and IoT
- 1 Introduction
- 2 Related Works
- 3 Proposed Framework
- 4 Experiments and Results
- 5 Conclusion
- References
- Green IoT-Based Automated Door Hydroponics Farming System
- 1 Introduction
- 2 Related Works
- 2.1 Literature Review
- 2.2 Gap Analysis
- 3 Proposed Approach
- 3.1 System Architecture
- 3.2 Methodology
- 3.3 Prototype Design
- 3.4 Flowchart
- 4 Hydroponics and Green Technologies
- 4.1 How Hydroponics Is Related to Green Technology
- 4.2 How Green Technology Make Difference with Automation Versus Manual System in Hydroponics Farming
- 4.3 Benefits of IoT in Hydroponics
- 4.4 How Eco-friendly Is Hydroponics?
- 4.5 Why Is Hydroponics Sustainable?
- 4.6 What Are the Positives and Negatives of Hydroponics?
- 4.7 What Are the Problems Caused by Hydroponics?
- 4.8 How to Improve the Energy Efficiency in Green IoT-Based Automated Door Hydroponics Farming System?
- 5 Conclusion
- References
- Explainable Artificial Intelligence-Based Disease Prediction with Symptoms Using Machine Learning Models
- 1 Introduction
- 2 Literature Survey
- 3 Explainable AI
- 4 Model Design
- 4.1 Dataset
- 4.2 Preprocessing
- 4.3 Model Training
- 4.4 Model Testing
- 5 Result and Analysis
- 6 Conclusion
- 6.1 Future Scope
- References
- Deep Learning Methods for Vehicle Trajectory Prediction: A Survey
- 1 Introduction
- 2 Material and Search Strategy
- 2.1 Materials and Methods
- 2.2 Research Questions
- 2.3 Search Strategy
- 2.4 Inclusion and Exclusion Criteria
- 2.5 Study Selection
- 2.6 Data Extraction Parameters
- 3 Problem Formulation
- 4 Classification of Existing Works
- 4.1 Social Awareness
- 4.2 Output Categories
- 4.3 Prediction Technique
- 5 Comparative Analysis
- 6 Performance Comparison
- 7 Conclusion
- References
- Adaptive Hybrid Optimization-Based Deep Learning for Epileptic Seizure Prediction
- 1 Introduction
- 2 Literature Survey
- 3 Proposed Adaptive Exp-SASO-DRNN for the ESP
- 3.1 Input Acquisition
- 3.2 EEG Signal Pre-processing Using Gaussian Filter
- 3.3 Feature Extraction
- 3.4 Feature Selection
- 3.5 ESP Using Deep RNN
- 4 Results and Discussion
- 4.1 Experimental Setup
- 4.2 Dataset Description
- 4.3 Performance Metrics
- 4.4 Experimental Outcome
- 4.5 Performance Analysis
- 4.6 Comparative Methods
- 4.7 Comparative Analysis
- 4.8 Comparative Discussion
- 5 Conclusion
- References
- Preeminent Sign Language System by Employing Mining Techniques
- 1 Introduction
- 2 Related Work
- 3 Methodology
- 3.1 Sign Language Used
- 3.2 Objectives
- 3.3 Databases
- 3.4 Data Acquisition Methods
- 3.5 Methods Used
- 3.6 Data Transformation
- 3.7 Principal Component Analysis (PCA) and Feature Extraction
- 3.8 Classification
- 3.9 LSTM Model
- 4 Results
- 5 Conclusion
- References
- Cyber Analyzer-A Machine Learning Approach for the Detection of Cyberbullying-A Survey
- 1 Introduction
- 2 Literature Survey
- 2.1 Introduction
- 2.2 Taxonomy
- 2.3 Related Works with the Citations of the References and Comparison
- 3 Conclusion of the Survey
- 4 Proposed Methodology
- 5 Result
- 6 Conclusion
- References
- Osteoarthritis Detection Using Deep Learning-Based Semantic GWO Threshold Segmentation
- 1 Introduction
- 2 Methodology for Knee Osteoarthritis Image Enhancement Using Deep Learning
- 3 Simulation Results
- 4 Conclusion
- References
- Federated Learning-Based Techniques for COVID-19 Detection-A Systematic Review
- 1 Introduction
- 2 Literatüre Survey
- 3 Data Privacy
- 4 Commonly Used Algorithms
- 5 Performance Evaluation for COVID-19 Detection System
- 6 Methods Used for COVID-19 Detection System
- 7 Comparative Analysis
- 8 Conclusion
- References
- Hybrid Information-Based Sign Language Recognition System
- 1 Introduction
- 2 Objectives
- 3 Methodology
- 3.1 Data Collection
- 3.2 Model Training Methodology
- 3.3 Training Model Using Gesture Image and Landmark Coordinates
- 4 Results and Discussion
- 5 Conclusion
- References
- Addressing Crop Damage from Animals with Faster R-CNN and YOLO Models
- 1 Introduction
- 2 Related Work
- 2.1 Literature Survey
- 2.2 Faster R-CNN
- 3 Proposed Method
- 3.1 Introducing YOLOv8
- 3.2 Commonly Used Algorithms
- 4 Methods Used for Animal Detection
- 5 Result Analysis
- 6 Conclusion
- References
- Cloud Computing Load Forecasting by Using Bidirectional Long Short-Term Memory Neural Network
- 1 Introduction
- 2 Background and Related Works
- 2.1 LSTM Model
- 2.2 BiLSTM Model
- 2.3 Meta-Heuristic Algorithms
- 3 Methods
- 3.1 The Original Sine Cosine Algorithm (SCA)
- 3.2 Modified Sine Cosine Algorithm (MSCA)
- 4 Experiments and Comparative Analysis
- 4.1 Utilized Data-Set and Experiment Setup
- 4.2 Experimental Outcomes
- 5 Conclusion
- References
- A Security Prototype for Improving Home Security Through LoRaWAN Technology
- 1 Introduction
- 2 Related Works
- 3 Proposed Work
- 3.1 Elements of the LPWAN Network
- 3.2 LPWAN Network Prototype Architecture
- 3.3 Implementation and Configuration
- 4 Result Analysis
- 4.1 Range
- 4.2 Response Time
- 4.3 Current Consumption
- 5 Conclusions
- References
- Design of a Privacy Taxonomy in Requirement Engineering
- 1 Introduction
- 1.1 Non Functional Requirement
- 1.2 Privacy Requirements
- 1.3 Privacy Requirements Example
- 2 Related Work
- 3 Design of Privacy Taxonomy
- 3.1 Anonymity at FR Level
- 3.2 Anonymity at System Level
- 3.3 Methods/Measures of Implementing Anonymity
- 3.4 Pseudonymity at FR Level
- 3.5 Pseudonymity at System Level
- 3.6 Unlinkability at System Level
- 3.7 Unobservability at System Level
- 3.8 Authentication at System Level
- 3.9 Authorization at FR Level
- 4 Conclusion and Future Work
- References
- Python-Based Free and Open-Source Web Framework Implements Data Privacy in Cloud Computing
- 1 Introduction
- 2 Related Work
- 2.1 Types of Cloud Computing
- 3 Methodology
- 3.1 Django
- 3.2 Python Language
- 3.3 HTML, CSS, JavaScript
- 3.4 Bootstrap
- 3.5 Amazon Web Services
- 3.6 MySQL
- 3.7 Google APIs
- 3.8 Advantages of the Proposed Approach
- 4 Experimental Results
- 5 Performance analysıs
- 6 Conclusion
- References
- Using Deep Learning and Class Imbalance Techniques to Predict Software Defects
- 1 Introduction
- 2 Objectives
- 2.1 Existing Work
- 2.2 Purpose
- 3 Methodology
- 3.1 General Overview
- 3.2 Dataset
- 3.3 Preprocessing
- 3.4 Model Development and Training
- 4 Results
- 5 Conclusion
- References
- Benefits and Challenges of Metaverse in Education
- 1 Introduction
- 2 Overview of Metaverse
- 2.1 Definition of Metaverse
- 2.2 Characteristics of the Metaverse
- 2.3 Type of Metaverse
- 3 Metaverse in Education
- 4 Limitations of Metaverse
- 5 Conclusion
- References
- Enhancing Pneumonia Detection from Chest X-ray Images Using Convolutional Neural Network and Transfer Learning Techniques
- 1 Introduction
- 2 Literature Review
- 3 Proposed Solution
- 3.1 Basic CNN
- 3.2 PVGG19 Fine Tuning Model (with and Without Data Augmentation)
- 3.3 VGG19 Model with Feature Extraction (with and Without Data Augmentation)
- 4 Results
- 4.1 CNN Basic
- 4.2 VGG19 Fine Tuning Without Data Augmentation
- 4.3 VGG19 Fine Tuning with Data Augmentation
- 4.4 VGG19 Feature Extraction Without Data Augmentation
- 4.5 VGG19 Feature Extraction with Data Augmentation
- 4.6 Overall Comparison of Training Loss, Validation Accuracy, Training Accuracy, and Validation Loss
- 5 Conclusion and Future Work
- References
- Intelligent and Real-Time Intravenous Drip Level Indication
- 1 Introduction
- 2 Related Works
- 3 Proposed Methodology
- 3.1 System Specifications
- 4 Results and Discussions
- 5 Conclusion
- References
- Author Index
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