Mining Intelligence and Knowledge Exploration: 9th International Conference, MIKE 2023, Kristiansand, Norway, June 28–30, 2023, Proceedings (Lecture Notes in Artificial Intelligence)

✍ Scribed by Seifedine Kadry (editor), Rajendra Prasath (editor)

• Publisher: Springer
• Year: 2023
• Tongue: English
• Leaves: 440
• Category: Library

✦ Synopsis

This book constitutes the refereed post-conference proceedings of the 9th International Conference on Mining Intelligence and Knowledge Exploration, MIKE 2023, held in Kristiansand, Norway, during June 28–30, 2023.

The 22 full papers and 16 short papers included in this book were carefully reviewed and selected from 87 submissions. They were grouped into various subtopics including Knowledge Exploration in IoT, Medical Informatics, Machine Learning, Text Mining, Natural Language Processing, Cryptocurrency and Blockchain, Application of Artificial Intelligence, and other areas.

✦ Table of Contents

Preface
Organization
Contents
Multimodal Body Sensor for Recognizing the Human Activity Using DMOA Based FS with DL
1 Introduction
2 Related Works
3 Proposed System
3.1 Dataset and Implementation Details
3.2 Feature Extraction
3.3 Classification Using DL Models
4 Results and Discussion
5 Conclusion
References
Detection of Chicken Disease Based on Day-Age Using Pre Trained Model of CNN
1 Introduction
2 Related Works
3 Proposed System
3.1 Dataset Analysis
3.2 Dataset Rebalancing and Recovery
3.3 Classification
4 Results and Discussion
4.1 Experimental Platform
4.2 Performance Measure
5 Conclusion
References
Image Captioning Using Xception-Long Short-Term Memory
1 Introduction
2 Related Work
3 Methodology
4 Results and Discussion
5 Limitation
6 Conclusion and Future Work
References
Performance Analysis of Different Classifiers Using HOG and LBP for Traffic Sign Detection
1 Introduction
2 Literature Review
3 Methodology
3.1 Dataset
3.2 Proposed Method
4 Feature Extraction
4.1 Gabor Filter
4.2 Canny
5 Traffic Sign Detection
5.1 MSER Algorithm
5.2 Image Pre-processing
6 Traffic Sign Classification
6.1 SVM
6.2 Random Forest
6.3 KNN
7 Experimental Results
8 Conclusion
References
Classification of the Class Imbalanced Data Using Mahalanobis Distance with Feature Filtering
1 Introduction
2 Proposed Method
3 Mahalanobis Distance
3.1 Feature Filtering
3.2 Proposed Procedure
4 Results and Discussion
5 Conclusion
References
Towards Data-Centric Approaches to Lung Cancer Classification
1 Introduction
2 Related Work
3 Methodology
3.1 Data Processing
3.2 Classification Algorithm
4 Experiments and Discussion
4.1 Dataset
4.2 Experimental Setup
4.3 Results and Discussion
5 Conclusions
References
Comparative Analysis of Machine Learning Approaches for Classifying Erythemato-Squamous Skin Diseases
1 Introduction
2 Material and Methods
2.1 Materials
2.2 Methods
3 Results and Discussions
4 Challenges and Future Scope
5 Conclusion
References
Automatic Detection of Waterbodies from Satellite Images Using DeepLabV3+
1 Introduction
2 Literature Review
3 Methodology
3.1 Database
3.2 Thresholding
3.3 DeepLabV3+
3.4 Performance Evaluation
4 Result and Discussions
5 Conclusion
References
Topic Classification of Text-Based Lesson Questions in Turkish with BERTurk
1 Introduction
2 Relatedwork
3 Architecture
4 Tests and Evaluation
5 Conclusions
References
Highest Accuracy Based Automated Depression Prediction Using Natural Language Processing
1 Introduction
2 Related Works
3 Proposed Work
3.1 Steps Followed by Decision Tree Classifier
3.2 Steps Followed in CatBoost
3.3 Step Followed in Logistic Regression
4 Conclusions
References
Crime Prediction Using Modified Capsule Network with CrissCross Optimization on the Sentiment Analysis for Cyber-Security
1 Introduction
2 Related Works
2.1 Data Collection
2.2 Proposed Crime Detection Model
2.3 Classification Using Deep Learning
3 Results and Discussion
3.1 Measuring the Performance of Model
4 Conclusion
References
Sentiment Analysis Using Lexical Approach and Fuzzy Logic
1 Introduction
2 Related Works
3 Materials and Methods
3.1 Features of Dataset
3.2 Model Creation
3.3 SentiWordNet
3.4 SentiStrength
3.5 Fuzzification
3.6 Membership Function Design
3.7 Defuzzification
4 Results and Discussion
5 Conclusion
References
HTTP, WebSocket, and SignalR: A Comparison of Real-Time Online Communication Protocols
1 Introduction
2 Literature Study
3 HTTP vs WebSocket and SignalR
3.1 Data Transfer
3.2 Connection
3.3 Scalability
3.4 Communication
3.5 Methods and Events
3.6 Error Handling
3.7 Reliability
4 Analysis and Observations
5 Conclusion
References
An IoT Based Early Alert System to Monitor and Reduce Electrical Energy Consumption at Home in Smart Cities
1 Introduction
2 System Description
2.1 Hardware Components
3 Proposed System
3.1 Methodology
4 Circuit Implementation
5 Energy Consumption Graph
6 Future Enhancements
7 Advantages
8 Limitations
9 Conclusion
References
Securing the MANET by Detecting the Flooding Attacks Using Hybrid CNN-Bi-LSTM-RF Model
1 Introduction
2 Related Works
2.1 Research Gaps
3 Proposed System
3.1 Problem Statement
3.2 Our Contribution
3.3 Proposed CNN-BiLSTM-RF Architecture
4 Results and Discussion
4.1 Simulation Environment
5 Conclusion
References
The Smart Coverage Path Planner for Autonomous Drones Using TSP and Tree Selection
1 Introduction
2 Literature Review
3 Solving TSP for Path Planning of Drones
3.1 Tree Selection Algorithms for Solving TSP
3.2 Solving TSP Using Tree Selection Algorithm
4 Experimental Results
5 Conclusion
References
UAV Smart Navigation: Combining Delaunay Triangulation and the Bat Algorithm for Enhanced Efficiency
1 Introduction
2 Literature Review
3 Solving Coverage Path Planning Problem
3.1 Area Partitioning - Delaunay Triangulation
3.2 Computation of Coverage Points
3.3 Solving TSP - Bat Optimization
4 Experimental Results
5 Conclusion
References
A Comparative Analysis of Data Backup and Network Consistency in Cluster-Base Wireless Sensor Network Protocols
1 Introduction
2 Problem Statement
3 Literature Review
4 Proposed Research Methodology
4.1 Performance Evaluation and Benchmarking
4.2 Proposed Research Methodology
5 Future Work and Conclusion
References
Development of IoT-Healthcare Model for Gastric Cancer from Pathological Images
1 Introduction
2 Related Works
3 Proposed System
3.1 Dataset
3.2 Image Preprocessing
4 Results and Discussion
4.1 Implementation Details
4.2 Validation Analysis of Proposed Model
5 Conclusion and Future Work
References
Glaucoma Detection Using the YOLO V5 Algorithm
1 Introduction
2 Literature Review
2.1 ORIGA-Light: An Online Retinal Fundus Image Database for Glaucoma Analysis and Research
2.2 Automated Glaucoma Diagnosis Using Deep Learning Approach
3 Proposed Methodology
3.1 Dataset Collection
3.2 Annotation of Images
3.3 Selection of Pre-trained Model
3.4 Method of Approach
4 Results and Discussions
5 Conclusion
References
Deep Learning Ocular Disease Detection System (ODDS)
1 Introduction
1.1 AI in Ophthalmology
2 Literature Review
3 Methodology
3.1 Dataset Curation
3.2 Preprocessing the Data
3.3 The Ocular Disease Detection System (ODDS)
4 Results
4.1 Exploratory Data Analysis
4.2 Results with CNN
4.3 Results with EfficientNet-B3
5 Conclusion
References
Efficient Chest X-Ray Investigation Using Firefly Algorithm Optimized Deep and Handcrafted Features
1 Introduction
2 Related Research
3 Methodology
3.1 Image Database
3.2 Feature Extraction
3.3 Feature Optimization with Firefly Algorithm
3.4 Performance Evaluation
4 Result and Discussion
5 Conclusion
References
Disease Detection and Risk Prediction System Based Web Application Using Machine Learning
1 Introduction
2 Literature Survey
3 Proposed System
4 Analyzing Requirement
4.1 Front-End Development
4.2 Back-End Development
4.3 Machine Learning Algorithm
4.4 Data Management
5 Methodology
6 System Architecture
7 Future Work
8 Conclusion
References
Weighted Average Ensemble Approach for Pediatric Pneumonia Diagnosis Using Channel Attention Deep CNN Architectures
1 Introduction
2 Literature Review
3 Background
3.1 ECA
3.2 Weighted Average Ensemble
4 Dataset Description and Experimental Design
4.1 Proposed Methodology
5 Results and Discussion
6 Conclusion and Future works
References
Seasonal Disease Based Demand Forecasting for Pharmaceutical Medications Using Random Forest
1 Introduction
2 Literature Review
3 Methodology
3.1 Data Acquisition and Preprocessing
3.2 Identification of Dominant Disease
3.3 Medicine Identification
3.4 Sales Forecasting
4 Result Analysis
5 Conclusion and Future Works
References
Hybrid Optimal Fine Tuning Approach in Deep Learning for Identifying Early Parkinson's Disease
1 Introduction
2 Review of the Literature
3 Computational Methodology
3.1 Hybrid Optimal Fine Tuning Technique
3.2 Preparation of Input Images
3.3 Architectural Design of HOF Tuning
3.4 Hybrid Optimal Fine Tuning Technique
3.5 Data Augmentation
3.6 Evaluation Metric
4 Results
4.1 Analysis of Hybrid Optimal Fine Tuning Technique
5 Discussions
6 Conclusion
References
Cryptocurrency Price Prediction Using Deep Learning
1 Introduction
2 Related Works
3 Proposed Work
4 Conclusion
References
Ensemble Learning Based Social Engineering Fraud Detection Module for Cryptocurrency Transactions
1 Introduction
2 Literature Survey
3 Proposed Methodology
3.1 Process Flow Overview
3.2 Design of the Fraud Detection Module
4 Implementation and Result Analysis
4.1 Dataset Description
4.2 Feature Reduction
4.3 Implementation of the Blockchain Network
4.4 Results and Performance Analysis of Fraud Detection Module
4.5 Test Cases for the Proposed System
4.6 Application User Interface
5 Conclusion and Future Work
References
Analysis and Prediction of Cryptocurrency Using Deep Learning Algorithms
1 Introduction
2 Literature Review
3 Proposed Methodology
3.1 Data Preparation
3.2 Feature Selection
3.3 Model Selection
3.4 Model Evaluation
3.5 Interpretation
4 Implementation
4.1 Analysing the Data
4.2 Predicting the Data
5 Result Analysis
6 Conclusion
References
Detecting the Attacks Using Blockchain-Based Decentralized Security Architecture in IoT Environment
1 Introduction
2 Related Works
3 Proposed System
3.1 Data Description
3.2 Data Pre Processing
3.3 Our Proposed Model
4 Results and Discussion
4.1 Performance Measure
5 Conclusion
References
Developing a System Based on Block Chain Technology for e-Voting Mechanism
1 Introduction
2 Related Works
3 Proposed System
3.1 Problem Formulation
3.2 Blockchain-Based E-Voting System
4 System Design
5 Results and Discussion
6 Conclusion
References
A Permissioned Blockchain Approach for Real-Time Embedded Control Systems
1 Introduction
1.1 Existing Works
1.2 Novelty
1.3 Article Contributions and Layout
2 The Proposed Approach
2.1 The IoT Device (Sensor Nodes) Registration Process
2.2 Data Sharing on the Web
2.3 The Hyperledger Fabric Setup
2.4 The Offloading Process Between Edge and Cloud Nodes
2.5 Algorithms and Discussion
3 Performance Analysis
4 Open Issues and Future Directions
5 Conclusion and Future Work
References
An Empirical Study of Machine Learning for Business Enterprises Management of Cloud Computing Services
1 Introduction
2 Related Works
3 Proposed System
3.1 Depolying Bid Data Analytics in the Cloud
3.2 Major Benefits for Business Organisations
3.3 Questionnaire Design and Measurement Tools
3.4 Data Collection
3.5 Data Analysis Method
3.6 XGBoost
4 Discussions and Implications
4.1 Theoretical contributions
4.2 Practical Implications
4.3 Practical Implications
5 Conclusions and Limitations
References
Prediction of Stock Market in Small-Scale Business Using Deep Learning Techniques
1 Introduction
2 Related Works
3 Proposed System
3.1 Research Data
3.2 Data Cleaning
3.3 Data Transformation
3.4 Classification Using Proposed Model
4 Results and Discussion
4.1 Evaluation Measures
5 Conclusion
References
Predictive Intelligence Based Semiconductor Substrate Fault Detection Model with User Interface
1 Introduction
2 Literature Review
3 Proposed Methodology
3.1 System Architecture
3.2 Dataset
3.3 Data Pre-Processing
3.4 Data Clustering
4 Conclusion and Future Work
References
Improving Sustainability with Deep Learning Models for Inland Water Quality Monitoring Using Satellite Imagery
1 Introduction
2 Background
2.1 VGG16 Architecture
2.2 AlexNet Architecture
2.3 GoogLeNet Architecture
3 Methodology
3.1 Dataset Description
3.2 Pre-Processing Steps for Image Classification
4 Results
5 Conclusion
References
Machine Learning Based Prediction of Student’s Performance Based on Psychological and Behavioral Data
1 Introduction
2 Literature Review
3 Proposed Methodology
3.1 System Architecture
3.2 Dataset
3.3 Data Pre-Processing
3.4 Data Visualization
3.5 Comparison of DFS and GFG
3.6 Machine Learning Algorithms
3.7 ROC Curve
4 Conclusion and Future Work
References
Task Scheduling Based Optimized Based Algorithm for Minimization of Energy Consumption in Cloud Computing Environment
1 Introduction
2 Related Works
3 Proposed System
3.1 Energy Usage Computation Module
3.2 Task Estimation Module
3.3 Task Scheduling Module
3.4 Task Allocating Module
3.5 Model of the Basic BOA
3.6 Hybrid-Flash Butterfly Optimization Algorithmx
4 Results and Discussion
4.1 Experimental Setup
4.2 Synthetic Data Set
4.3 Performance of Proposed Scheme in Terms of Makespan
5 Conclusion
References
Author Index