Computational Intelligence and Data Analytics: Proceedings of ICCIDA 2022 (Lecture Notes on Data Engineering and Communications Technologies, 142)

✍ Scribed by Rajkumar Buyya (editor), Susanna Munoz Hernandez (editor), Ram Mohan Rao Kovvur (editor), T. Hitendra Sarma (editor)

• Publisher: Springer
• Year: 2022
• Tongue: English
• Leaves: 616
• Category: Library

✦ Synopsis

The book presents high-quality research papers presented at the International Conference on Computational Intelligence and Data Analytics (ICCIDA 2022), organized by the Department of Information Technology, Vasavi College of Engineering, Hyderabad, India in January 2022. ICCIDA provides an excellent platform for exchanging knowledge with the global community of scientists, engineers, and educators. This volume covers cutting-edge research in two prominent areas – computational intelligence and data analytics, and allied research areas.

✦ Table of Contents

Preface
Contents
About the Editors
Container Orchestration in Edge and Fog Computing Environments for Real-Time IoT Applications
1 Introduction
1.1 Case Study: Natural Disaster Management (NDM)
1.2 Edge and Fog Computing
2 Background Technologies and Related Work
2.1 FogBus2 Framework
2.2 K3s: Lightweight Kubernetes
2.3 Related Work
3 Container Orchestration Approach
3.1 Overview of the Design
3.2 Configuration of Nodes
3.3 P2P VPN Establishment
3.4 K3s Deployment
3.5 Fogbus2 Framework Integration
4 Performance Evaluation
4.1 Experiment 1: Orchestrated FogBus2 Versus Native FogBus2
4.2 Experiment 2: Hybrid Environment Versus Cloud Environment
5 Conclusions and Future Work
References
Is Tiny Deep Learning the New Deep Learning?
1 Introduction
2 Tiny Machine Learning: An Overview
3 From Tiny Machine Learning to Tiny Deep Learning
4 Approximate Computing for Tiny Deep Learning
4.1 Precision Scaling Mechanisms
4.2 Task Dropping Mechanisms
5 Tiny Deep Learning for the Internet of Things
5.1 Early-Exit Neural Networks
5.2 Distributed Inference for TinyDL
5.3 On-Device Learning for TinyDL
5.4 Federated Learning
6 Conclusions
References
Dynamic Multi-objective Optimization Using Computational Intelligence Algorithms
1 Introduction
2 Multi-objective Optimization Concepts
2.1 Multi-objective Optimization
2.2 Dynamic Multi-objective Optimization
3 Multi-objective Algorithms
3.1 Preference-Based Approaches
3.2 Population-Based Approaches
4 Solving Dynamic Multi-objective Optimization Problems
4.1 Detecting Changes in Environment
4.2 Responding to Changes in Environment
4.3 Evaluating Algorithm Performance
5 Challenges in Dynamic Multi-objective Optimization
5.1 Decision Making
5.2 Algorithm Behavior
6 Emerging Research Areas
6.1 Many-Objective Optimization
6.2 Fitness Landscape Analysis
7 Conclusion
References
AI for Social Good—A Faustian Bargain
1 An Introduction History and Context
1.1 Knowledge Acquisition Problem for AI Systems
1.2 Machine Learning
1.3 Deep Learning and Insatiable Data Thirst
2 Smart Devices and Clouds
2.1 Networking, Processing, and Media Convergence in Smartphones
2.2 Eavesdropping and Spying in Our House
3 The Promise for Public Good
4 Standardization and Regulation of AI Technology
References
Computational Intelligence–Machine Learning
Text Summarization Approaches Under Transfer Learning and Domain Adaptation Settings—A Survey
1 Introduction
2 Transfer Learning-Based Text Summarization
2.1 Transfer Learning in Seq2Seq-Based Approaches for Text Summarization
2.2 Transfer Learning in Non-Seq2Seq-Based Approaches for Text Summarization
3 Text Summarization Using Domain Adaptation
4 Issues, Challenges and Opportunities
5 Conclusion
References
An Effective Eye-Blink-based Cyber Secure PIN Password Authentication System
1 Introduction
1.1 Our Contribution
2 Related Work
3 System Design
3.1 Algorithm
4 EBCS-PIN Implementation and Results
5 Conclusion
References
A Comparison of Algorithms for Bayesian Network Learning for Triple Word Form Theory
1 Introduction
2 Literature Review
3 Methodology
4 Structure Learning for Bayesian Network
4.1 Search and Score-Based Algorithm
4.2 Constraint-Based Approach
4.3 Hybrid Approach
5 Study Participants
6 Results
7 Discussion and Conclusion
References
Application of Machine Learning Algorithm in Identification of Anaemia Diseases
1 Introduction
1.1 Types and Detection of Anaemia
1.2 Machine Learning Algorithms
2 Methodology
2.1 Gathering Data
2.2 Data Pre-processing
2.3 Model Selection
2.4 Validation
3 Results and Discussion
3.1 Confusion Matrix
3.2 Accuracy
3.3 Sensitivity/Recall
3.4 Specificity
4 Conclusion and Future Work
References
Detection of Fruits Image Applying Decision Tree Classifier Techniques
1 Introduction
2 Related Works
3 Methodology
4 Experiment and Results
5 Conclusion
References
Disease Prediction Based on Symptoms Using Various Machine Learning Techniques
1 Introduction
2 Literature Review
3 Methodology
3.1 Input Data
3.2 Data Pre-processing
3.3 Models
3.4 Output (Diseases)
4 Implementation
4.1 Multinomial Naïve Bayes
4.2 Random Forest Classifier
4.3 K-Nearest Neighbors (KNN)
4.4 Logistic Regression
4.5 Support Vector Machines
4.6 Decision Tree
4.7 Multilayer Perceptron Classifier
5 Results and Discussion
5.1 Experimental Analysis
6 Conclusion
References
Anti-Drug Response and Drug Side Effect Prediction Methods: A Review
1 Introduction
2 Literature Survey
3 Databases and Parameters Used for Drug Adverse Reaction Prediction
3.1 Metrics for Drug Side Effect Prediction
4 Drug Side Effect Prediction Methods
4.1 Docking-Based Methods
4.2 Networks-Based Methods
4.3 Machine Learning-Based Methods
4.4 Miscellaneous Approaches
5 Conclusion and Future Work
References
Assessment of Segmentation Techniques for Irregular Border Lesion Images in Melanoma
1 Introduction
2 Related Work and Background
3 Methodology Used
3.1 Binary Otsu Segmentation
3.2 Marker-Based Watershed Segmentation
3.3 K-Means Clustering
3.4 Quality Assessment for Images
4 Results and Evaluation
5 Conclusion
References
Secure Communication and Pothole Detection for UAV Platforms
1 Introduction
2 Methodology
2.1 Secure Communication
2.2 Pothole Detection Using CNN
2.3 Pothole Detection Using Inception-V3
2.4 Pothole Detection Using YOLO
3 Results
4 Future Scope
References
An Empirical Study on Discovering Software Bugs Using Machine Learning Techniques
1 Introduction
2 Related Work
3 Methodology
4 Experimental Results
5 Conclusion and Future Work
References
Action Segmentation for RGB Video Frames Using Skeleton 3D Data of NTURGB+D
1 Introduction
2 Research Methodology
3 Dataset for Action Segmentation
4 Experimental Results
4.1 Create Datastore for Skeleton 3D Data and RGB Videos
4.2 Extraction of Color X and Color Y from Skeleton 3D Data
4.3 Dimension for Bounding Box for Action Segmentation
4.4 RGB Videos and Segmented Action Videos
5 Conclusion
References
Prediction of Rainfall Using Different Machine Learning Regression Models
1 Introduction
2 Related Work
3 Proposed Method
3.1 The Proposed Model’s Algorithm
3.2 Dataset Description
3.3 Exploratory Data Analysis
4 Results
4.1 Results of MLR
5 Conclusion
References
A Comprehensive Survey of Datasets Used for Spam and Genuineness Views Detection in Twitter
1 Introduction
2 Literature Review
3 Summary and Challenges
4 Difficulty in Extraction and Collection of Data
5 Renaming of Data
6 Lack of Standard Datasets
7 Genuineness of Data
8 Conclusion
References
Computational Intelligence–Deep Learning
Indian Classical Dance Forms Classification Using Transfer Learning
1 Introduction
2 Related Work
3 Proposed Work
3.1 ICD Architecture
3.2 VGG16 Network Architecture
3.3 ICD Classification Algorithm:
3.4 Theory
4 Experiment Results and Comparisons
4.1 Dataset
4.2 Performance Analysis
5 Conclusion and Future Enhancement
References
Skin Cancer Classification for Dermoscopy Images Using Model Based on Deep Learning and Transfer Learning
1 Introduction
2 Related Background
3 Experimental Methodology
3.1 Convolutional Neural Network
3.2 Transfer Learning
3.3 Evaluation Metrics
4 Proposed Architecture
4.1 Flow Model
4.2 Dataset Description
4.3 Experimental Setup
5 Experimental Outcomes and Observation
6 Conclusion and Future Work
References
Deep Neural Network Architecture for Face Mask Detection Against COVID-19 Pandemic Using Pre-trained Exception Network
1 Introduction
2 Background
3 Proposed Method
3.1 Load the Data Set
3.2 Model Creation
3.3 Data Set
4 Experimental Results and Discussion
5 Conclusion
References
MOOC-LSTM: The LSTM Architecture for Sentiment Analysis on MOOCs Forum Posts
1 Introduction
2 Motivation and Related Work
3 Background
3.1 Dataset
3.2 Word Embedding
3.3 Upsampling
3.4 Convolutional Neural Network
3.5 Long Short-term Memory
3.6 Adaptive Experimentation (Ax)
4 Proposed System
5 Implementation
5.1 Performance Measures
5.2 Results and Analysis
6 Conclusion and Future Work
References
License Plate Detection of Motorcyclists Without Helmets
1 Introduction
2 Related Work
3 Data
3.1 Dataset
3.2 Data Preprocessing
3.3 Architecture
4 Results
5 Conclusion
References
Object Detection and Tracking Using DeepSORT
1 Introduction
2 Related Work
3 Existing Work
3.1 Optical Flow
3.2 Mean-Shift Algorithm
4 Proposed Methodology
4.1 Dataset
4.2 Proposed Workflow
5 Results and Discussions
6 Conclusion
7 Future Work
References
Continuous Investing in Advanced Fuzzy Technologies for Smart City
1 Introduction
2 Literature Review
3 Research Objectives
4 Methods and Models
4.1 Problem Statement
4.2 Research Methodology
4.3 Game Solution and Optimal Strategies of the First Player
5 Computational Experiment
6 Computational Experiment
7 Conclusions
References
Lesion Segmentation in Skin Cancer Detection Using UNet Architecture
1 Introduction
1.1 Our Contribution
2 Preliminaries
2.1 UNet Architecture
3 Proposed Methodology
3.1 A Proposed Model of UNet
4 First Section
4.1 Dataset and Experimental Setup
4.2 Evaluation Metrics
4.3 Results and Discussions
5 Conclusion
References
Getting Around the Semantics Challenge in Hateful Memes
1 Introduction
2 Literature Review
3 Approach
3.1 A Semantic Understanding
3.2 Variational Auto-Encoders (VAE)
3.3 Helping Decode Hate in Memes
3.4 Bringing It All Together
4 Results and Discussion
5 Conclusion and Future Work
References
Classification of Brain Tumor of Magnetic Resonance Images Using Convolutional Neural Network Approach
1 Introduction
2 Related Works
3 Material and Methods
3.1 Dataset Collection and Preprocessing
3.2 Model Architecture and Learning
4 Performance Evaluation
5 Conclusion
References
Detection of COVID-19 Infection Using Convolutional Neural Network
1 Introduction
2 Literature Survey
3 Proposed Methodology
4 Experimental Results
5 Conclusions
References
Hybrid Classification Algorithm for Early Prediction of Alzheimer’s Disease
1 Introduction
2 Related Works
3 Proposed Work
3.1 Details of Dataset
3.2 Segmentation
3.3 Feature Extraction and Reduction
3.4 Classification
4 Results
4.1 Comparison of Accuracy
4.2 Comparison of Other Performance Metrics
5 Conclusion
References
Data Analytics
Evaluating Models for Better Life Expectancy Prediction
1 Introduction
1.1 Motivation and Objective
1.2 Research Questions and Contribution
2 Related Work
3 Proposed Strategy
3.1 Life Expectancy Prediction and Forecasting Model
4 Implementation Framework
4.1 Data Preparation
4.2 Feature Extraction
4.3 Life Expectancy Prediction Modeling
4.4 Life Expectancy Forecast Modeling
5 Analytics and Discussion
5.1 Forecast Modeling Results
6 Conclusion
References
Future Gold Price Prediction Using Ensemble Learning Techniques and Isolation Forest Algorithm
1 Introduction
2 Literature Study
3 Statistics and Methodology
4 Discussion and Outcomes
5 Conclusion
References
Second-Hand Car Price Prediction
1 Introduction
1.1 Motivation
1.2 Problem Addressed
1.3 Objectives
1.4 Solution/Novelty
2 Related Works
3 System Analysis
3.1 Data Set
3.2 Algorithm-Random Forest Regression
3.3 Assumptions for Random Forest Regression
4 Implementation
4.1 Pre-processing
4.2 Visualizing
4.3 Model Creation
4.4 Input
4.5 Output
5 Analysis
6 Conclusions and Future Scope
6.1 Conclusion
6.2 Future Scope
References
A Study on Air Pollution Over Hyderabad Using Factor Analysis—Kaggle Data
1 Introduction
2 Literature Survey
3 Data Details
4 Methodology
5 Results and Discussions
6 Conclusions
References
A Comparative Study of Hierarchical Risk Parity Portfolio and Eigen Portfolio on the NIFTY 50 Stocks
1 Introduction
2 Related Work
3 Data and Methodology
4 Performance Evaluation
4.1 The Auto Sector Portfolios
4.2 The Consumer Durable Sector Portfolios
4.3 The Financial Services Sector Portfolios
4.4 The Healthcare Sector Portfolios
4.5 The Information Technology Sector Portfolios
4.6 The Oil and Gas Sector Portfolios
4.7 The NIFTY 50 Portfolios
5 Conclusion
References
Collaborative Approach Toward Information Retrieval System to Get Relevant News Articles Over Web: IRS-Web
1 Introduction
2 Related Work
3 Experimental Setup
3.1 Data Acquisition and Extraction
3.2 Data Pre-processing
3.3 Cloud-Based Data Warehousing
3.4 IRS-Web
4 Results
5 Comparative Analysis
6 Conclusion
References
Patent Recommendation Engine Using Graph Database
1 Introduction
1.1 Background
1.2 Application
1.3 Limitations
1.4 Objective
2 Literature Survey
2.1 Existing Works
3 Method Proposed
3.1 Second-Degree Node Search Technique
3.2 Node Similarity Algorithm Using Jaccard Distance
3.3 Data Modeling—Nodes and Relationships
3.4 Data Preparation and Ingestion
3.5 Query Building and Execution
4 Results
5 Conclusion
References
IFF: An Intelligent Fashion Forecasting System
1 Introduction
2 Related Work
2.1 Fashion Trend Analysis
2.2 Forecasting Time Series
3 Methodology
3.1 Attribute Recognition
3.2 Dataset for Discovering the Fashion Time line
3.3 Temporal Fashion Trends
3.4 Forecasting Trends
4 Models
4.1 Grand Means Forecaster
4.2 ARIMA
4.3 Auto ARIMA
4.4 Theta Forecaster
4.5 Polynomial Trend Forecaster
4.6 Exponential Smoothing
4.7 Naive Forecaster
4.8 Lasso Least Angular Regressor
4.9 Light Gradient Boosting
5 Seq2Seq Model
6 Results
7 Application in Real-Time Forecasting of Fashion
8 Conclusion
References
SIR-M Epidemic Model: A SARS-CoV-2 Perspective
1 Introduction
2 Epidemic Model
2.1 COVID-19: A Clinical Perception
2.2 SIR-M Model
3 Experimentation and Analysis
3.1 Model Proof
3.2 Statistics Analysis
4 Conclusion
References
MultiCity: A Personalized Multi-itinerary City Recommendation Engine
1 Introduction
2 Related Work
2.1 TRS Using Orienteering Problem
2.2 Various TRS Related Works
3 Background and Problem Definition
3.1 Time-based User Interest
3.2 Traveling History
3.3 Itinerary Interest
3.4 Itinerary Popularity
3.5 Similarity Between LU and GUs
3.6 Problem Definition
3.7 Monte Carlo Tree Search Algorithm
3.8 Simulation and Back-propagation
4 Experimental Methodology
4.1 Dataset
4.2 Baseline Algorithms
4.3 Performance Metrics
4.4 Comparison of Precision, Recall and upper F Baseline 1F1-Score
5 Conclusion
References
Block Chain and Cloud Computing
A Fully Distributed Secure Approach for Database Security in Cloud Computing
1 Introduction
2 Related Work
3 Proposed Security Model
4 Implementation
5 Conclusion and Future Scope
References
Blockchain Technology Adoption for General Elections During COVID-19 Pandemic and Beyond
1 Introduction
2 Background
3 Related Work
3.1 COVID-19 Pandemic
3.2 Blockchain Technology
3.3 Conventional Voting Method
4 Implementation Approach of the Blockchain Voting Method
5 Shortcomings of Conventional Voting Method During COVID-19 Pandemic
6 Future Research Direction and Recommendations
7 Conclusion
References
Blockchain Implementation Framework for Tracing the Dairy Supply Chain
1 Introduction
2 Blockchain
3 Existing Supply Chain Process
4 Benefits of Using Blockchain in Dairy Supply Chain
5 Design and Architecture
6 Conclusion
References
Addressing Most Common Vulnerabilities in Blockchain-Based Voting Systems
1 Introduction
2 Electronic Voting Systems
2.1 David Shaum Electronic Voting System
2.2 Caltech/MIT Voting Technology Project
2.3 The E-Poll Project
2.4 The Estonian I-Voting System
2.5 South Wales iVote System
2.6 Washington DC. Electronic Voting System
2.7 Blockchain-Based Voting Systems
3 Security Concerns with Blockchain-Based Voting Systems
3.1 Mining and Conflicts in the Blockchain
3.2 Resource Drainage
3.3 Border Gateway Protocol Attack
3.4 Terminals Used for Voting
3.5 Internet Identity and Anonymous Voting
3.6 Man-In-The-Middle Attack
3.7 A 51% Attack
3.8 A D-Denial of Service Attack
4 Our Novel Proposed Solution
5 Conclusion
References
Networks and Security
Privacy Preserving Intrusion Detection System for Low Power Internet of Things
1 Introduction
2 Background
2.1 6LoWPAN-Based IoT
2.2 RPL
2.3 Security in 6LoWPAN-Based IoT
3 Related Work
4 Privacy Preserving Intrusion Detection System
4.1 Privacy Preserving Module
4.2 Attack Detection Module
5 Simulation and Results
5.1 Selective Forwarding Attack
5.2 Vampire Attack
5.3 True Positive Rate
5.4 Energy
5.5 Privacy Metric
5.6 Utility
6 Conclusion
References
Identifying Top-N Influential Nodes in Large Complex Networks Using Network Structure
1 Introduction
1.1 Motivation and Main Contributions
2 Related Work
3 Proposed Method
4 Performance
5 Conclusion and Future Directions
References
Push and Pull Factors for Successful Implementation of ERP in SMEs Within Klang Valley: A Roadmap
1 Introduction
2 Related Work
2.1 ERP Success Parameters
2.2 ERP Pull Factors
2.3 ERP Push Factors
3 Formulation
3.1 Research Phases
4 Initial Results
5 Conclusion
References
A Hybrid Social-Based Routing to Improve Performance for Delay-Tolerant Networks
1 Introduction
2 Related Work
2.1 Some of the Mostly Known Routing Protocols of DTN
2.2 Social-Based Routing Protocols of DTN
3 Proposed Methods
3.1 Routing Considerations
3.2 Censimcom Routing
3.3 Technique
3.4 Algorithm
4 Simulation and Results
4.1 Delivery Ratio
4.2 End-to-End Delay
5 Conclusions
References
Author Index