Proceedings of International Conference on Computational Intelligence and Data Engineering

Name: Proceedings of International Conference on Computational Intelligence and Data Engineering | ICCIDE 2022
Brand: Springer
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ICCIDE 2022

Nabendu Chaki Nagaraju Devarakonda Agostino Cortesi(Editor)

Springer (Publisher)

1st Edition

Published on 17. June 2023

X, 578 pages

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978-981-99-0609-3 (ISBN)

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Nabendu Chaki is a Professor in the Department Computer Science & Engineering, University of Calcutta, Kolkata, India. He is the Editor in Chief of the Springer Nature book series on Services and Business Process Reengineering. Besides editing about 40 conference proceedings with Springer, Dr. Chaki has authored 8 text and research books with CRC Press, Springer Nature, etc. He has published more than 200 Scopus Indexed research articles in Journals and International conferences. Prof. Chaki has served as a Visiting Professor in different places including US Naval Postgraduate School, California, and in different Universities in Italy and Poland. He is the founder Chair of ACM Professional Chapter in Kolkata and served in that capacity for 3 years since January 2014. He has been active during 2009-2015 towards developing several international standards in Software Engineering and Service Science as a Global (GD) member for ISO-IEC.
NagarajuDevarakonda received his B.Tech. from Sri Venkateswara University, M.Tech. from Jawaharlal Nehru University (JNU), New Delhi, and Ph.D. from Jawaharlal Nehru Technological University, Hyderabad. He has published over 90 research papers in international conferences and journals. He is the Co-Editor of Proceedings of ICCIDE 2017, 2018, 2020, and 2021. The proceedings were published in Lecture Notes on Data Engineering and Communication Technologies of SPRINGER. He published papers in ICCI*CC 2017 at OXFORD UNIVERSITY, UK, and ICCI*CC 2018 at UNIVERSITY OF CALIFORNIA, BERKELEY, USA. He is currently working as an Associate Professor in the School of Computer Science & Engineering at VIT-AP University and has 18 years of experience in teaching. His research areas are data mining, soft computing, machine learning and pattern recognition. He has supervised 25 M.Tech. students, guided 4 Ph.Ds and currently guiding 9 Ph.Ds.
Agostino Cortesi, Ph.D., is a full professor of computer science at Ca' Foscari University, Venice, Italy. He has extensive experience in the area of static analysis and software verification techniques. His main research interests concern programming languages theory, software engineering, and static analysis techniques, with particular emphasis on security applications. He coordinated the H2020 Families_Share project and the MAE Italy-India project "Formal Specification for Secured Software System". He has been the adviser of several doctoral and postdoctoral students from Italy and abroad (India, Cuba), and has published more than 150 papers in high-level international journals and proceedings of international conferences.

Editor

Nabendu Chaki

ISNI: 0000 0001 1410 9507

Nagaraju Devarakonda

Agostino Cortesi

Content

Intro
Preface
Contents
A Review of Deep Learning Methods in Automatic Facial Micro-expression Recognition
1 Introduction
2 Micro-expression Datasets
2.1 Spontaneous Micro-expression Corpus (SMIC)
2.2 Chinese Academy of Sciences Micro-expression (CASME) Dataset
2.3 Chinese Academy of Sciences Micro-expression (CASME II) Dataset
3 Micro-expression Recognition
3.1 Preprocessing
3.2 Feature Extraction
3.3 Classification
4 Performance Metrics
5 Conclusion
References
Mathematical Modeling of Diabetic Patient Model Using Intelligent Control Techniques
1 Introduction
2 Literature Survey
3 Materials and Methods
4 Conclusion
References
End-to-End Multi-dialect Malayalam Speech Recognition Using Deep-CNN, LSTM-RNN, and Machine Learning Approaches
1 Introduction
2 Related Work
3 Proposed Methodology and Design
3.1 The Proposed Methodology
3.2 Dataset
3.3 Feature Extraction
3.4 Building the Accented ASR System
4 Experimental Results
5 Conclusion and Future Scope
References
JSON Document Clustering Based on Structural Similarity and Semantic Fusion
1 Introduction
2 Literature Survey
3 JSim
3.1 Schema Extraction
3.2 Similarity Computation
3.3 Clustering
4 Experimental Evaluation
4.1 Results
4.2 Discussion
5 Conclusions
References
Solar Power Forecasting to Solve the Duck Curve Problem
1 Introduction
2 Literature Review
3 Methodology
3.1 Duck Curve
3.2 Data Acquisition and Inputs
3.3 Flowchart
3.4 Machine Learning Algorithms Tested
4 Results
4.1 Performance of Machine Learning Models
4.2 Random Forest Performance Metrics
4.3 Calculation of Generated Power for VIT Chennai
4.4 Duck Curve for VIT Chennai
4.5 Case Study
5 Conclusion
References
Dynamic Optimized Multi-metric Data Transmission over ITS
1 Introduction
2 Related Multi-cast Mobility Models
3 Proposed Implementation
3.1 Procedure for selection of Multi-cast Node
3.2 Acknowledgment (ACK) Procedure in NOSMR
3.3 Representation of Acknowledgement Data Frame
4 Experimental Results
5 Conclusion and Future Work
6 Proof of the Concept
References
Solar Energy-Based Intelligent Animal Reciprocating Device for Crop Protection Using Deep Learning Techniques
1 Introduction
2 Real-World Problems of Image Classification
3 Test System Description
4 Methodology
4.1 Convolutional Neural Networks (CNNs)
4.2 Recurrent Neural Networks (RNNs)
5 Experimental Processing
6 Conclusion
References
Toward More Robust Classifier: Negative Log-Likelihood Aware Curriculum Learning
1 Introduction
2 Literature Survey
3 Uncertainty Estimation
3.1 Mathematical Formulas for Uncertainty Quantification
4 Negative Log-Likelihood and Uncertainty
4.1 Likelihood Versus Probability
4.2 Maximum Likelihood Estimation
4.3 Negative Log-Likelihood and Its Relationship with SoftMax Activations
5 Methodology
6 Results
7 Conclusion
References
Design of Fuzzy Logic Controller-Based DPFC Device for Solar-Wind Hybrid System
1 Introduction
2 Proposed Dynamic System
2.1 Concept of Wind Energy Conversion System
2.2 Concept of Solar PV System
3 Distributed Power Flow Controller
3.1 Central Control
3.2 Series Control
3.3 Shunt Control
4 DPFC with Fuzzy Logic Controller
5 Results and Discussion
5.1 Simulation Results of PV/Wind Hybrid System Without Any Custom Device
5.2 Simulation Results of PV/Wind Hybrid System with UPFC
5.3 Simulation Results of PV/Wind Hybrid System with DPFC
5.4 Simulation Results DPFC Device with Fuzzy Logic Controller
5.5 Comparative Analysis
6 Conclusion
References
Analysis of EEG Signal with Feature and Feature Extraction Techniques for Emotion Recognition Using Deep Learning Techniques
1 Introduction
2 Related Works
3 Methodology
3.1 Datasets
3.2 Preprocessing
3.3 Extraction of Features
3.4 Feature Selection (FS)
3.5 Classifier
4 Discussion and Results
5 Conclusion
References
Innovative Generation of Transcripts and Validation Using Public Blockchain: Ethereum
1 Introduction
2 Related Work
3 Proposed Methodology
3.1 Web Server Module
3.2 Certificate Verification Module
3.3 Raft Consensus Module
3.4 Inter-planetary File System
3.5 Hyperledger Fabric Channel Module
3.6 Hyperledger Fabric Transaction
3.7 Paxos Module
3.8 Organization Inclusion and Deletion
3.9 Feedback Module
3.10 Cloud Deployment Module
4 Experimental Results
4.1 Performance Metrics
5 Conclusion and Future Work
References
Windows Malware Hunting with InceptionResNetv2 Assisted Malware Visualization Approach
1 Introduction
2 Related Works
3 Methodology
3.1 Overview
3.2 Grayscale Malware Images
3.3 InceptionResNetv2 CNN
4 Experiments
4.1 Dataset Details
4.2 Evaluation Metrics
5 Results and Analysis
6 Conclusions and Future Scope
References
Custom-Built Deep Convolutional Neural Network for Breathing Sound Classification to Detect Respiratory Diseases
1 Introduction
1.1 Significance of the Proposed Model
1.2 Research Gap and Contributions of the Paper
2 Literature Survey
3 Methodology
4 Results and Discussions
5 Conclusions and Future Scope
References
Infrastructure Resiliency in Cloud Computing
1 Introduction
2 Methodology
2.1 System Set-Up Stage
3 Experimental Results
4 Conclusion
4.1 Limitations
4.2 Recommendation
4.3 Future Research
References
Deep Learning Model With Game Theory-Based Gradient Explanations for Retinal Images
1 Introduction
2 Materials and Method
2.1 Integrated Gradients
2.2 Smooth-Grad
2.3 Shapley Values
2.4 Proposed SHAP Gradient DR Model
3 Results and Discussion
3.1 Dataset Description
3.2 Performance Evaluation of DR Classification
3.3 Analysis of the Explainability SHAP Gradient DR Model
4 Conclusion
References
A Comparative Analysis of Transformer-Based Models for Document Visual Question Answering
1 Introduction
2 Related Work
2.1 Text-Based Visual Question Answering
2.2 Transformer-Based Natural Language Processing Models
2.3 Multimodal Learning in Vision and Language Tasks
3 Methodology
3.1 Method for Text Extraction
3.2 Method for Answer Extraction Transformer-Based Models
4 Experiments and Results
4.1 DocVQA
4.2 Experimental Setup
4.3 Results Obtained by Various Models on DocVQA
4.4 Experiments
5 Conclusion and Future Work
References
Develop Hybrid Wolf Optimization with Faster RCNN to Enhance Plant Disease Detection Performance Analysis
1 Introduction
2 Related Works
3 Proposed Method
3.1 Data Collection
3.2 Feature Extraction
3.3 Predicting Diseased Spots
4 Experimental Evaluation
4.1 Prediction of Accuracy and Speed
5 Conclusion
References
An Efficient CatBoost Classifier Approach to Detect Intrusions in MQTT Protocol for Internet of Things
1 Introduction
2 Related Work
3 Message Queuing Telemetry Transport (MQTT)
4 Proposed Method for CatBoost Classifier
4.1 Research Methodology
5 Results and Discussion
5.1 Imbalanced Dataset
6 Conclusion
References
Self-regulatory Fault Forbearing and Recuperation Scheduling Model in Uncertain Cloud Context
1 Introduction
1.1 Cloud Computing
1.2 Task Scheduling
1.3 Fault Tolerance
1.4 Types of Failures in Cloud Environment
2 Literature Review
2.1 Cloud and Its Uncertainties
2.2 Resource Provisioning Strategies for Improving QoS
2.3 Fault Tolerance and Detection Techniques
2.4 Fault Tolerance and Management Techniques
2.5 Challenges Identified
3 Proposed Methodology
3.1 Experimental Setup and Dataset Description
3.2 RFDR Model
3.3 Fault Injection Mechanism
3.4 Fault Detection Mechanism
3.5 Recovery Mechanism
3.6 Failure Metrics and QoS Parameters Used
4 Experimental Evaluation and Results
4.1 Analyzing Performance of RFDR in Various Scheduling Algorithms
5 Conclusion
References
A Comprehensive Survey on Student Perceptions of Online Threat from Cyberbullying in Kosova
1 Introduction
1.1 Cyberbullying Consequences
2 Related Work
3 Methodology
3.1 Research Questions
3.2 Limitations
3.3 Data Analysis Procedures
3.4 Data Presentation
3.5 Types of Questionnaire Questions
4 Results
5 Discussion
6 Future Work
7 Conclusions
References
Addressing Localization and Hole Identification Problem in Wireless Sensor Networks
1 Introduction
2 Technological Background
3 Proposed System
3.1 Addressing Localization
3.2 Hole Identification and Healing
3.3 Implementation and Result Analysis
4 Conclusion and Future Work
References
The Impact of ICMP Attacks in Software-Defined Network Environments
1 Introduction
2 Literature Review
3 Internet Control Message Protocol (ICMP)
3.1 Operations of ICMP Protocol
3.2 ICMP Messages
3.3 ICMP Message Types
3.4 ICMP Message Format
4 ICMP Attacks in SDN Environments
4.1 Application Layer Flooding
4.2 SYN Flooding
5 Experiment and Results
5.1 CPU Utilization
5.2 Control Channel Bandwidth
5.3 Packet Delivery Ratio
5.4 Flow Request Analysis
6 Conclusion
References
An Area-Efficient Unique 4:1 Multiplexer Using Nano-electronic-Based Architecture
1 Introduction
1.1 QCA Cell
1.2 QCA Majority Gate
1.3 QCA Inverter
2 Five Input Majority Gate
3 2:1 Multiplexer
4 Proposed 4:1 Multiplexer
5 Simulation and Experimental Result Analysis
5.1 Implementation of 2:1 and Proposed 4:1 Multiplexer
5.2 Complexity of Proposed 4:1 Multiplexer
5.3 Analysis of Proposed 4:1 Multiplexer
6 Conclusion
References
Digital Realization of AdEx Neuron Model with Two-Fold Lookup Table
1 Introduction
2 AdEx Model
3 Proposed AdEx Model Using Two-Fold Lookup Table
3.1 f-LUT and e-LUT Architecture
3.2 Bit Width Requirements and Compressibility
3.3 Data Retrieval from the Two-Fold Lookup Table
4 Hardware Implementation
5 Simulation Results
6 Conclusion
References
A Novel Quantum Identity Authentication Protocol Based on Random Bell Pair Using Pre-shared Key
1 Introduction
2 Basic Ideas on EPR and Entanglement Swapping
3 Proposed Protocol
3.1 General Procedure
3.2 Quantum Procedure
3.3 Classical Procedure
4 Security of Proposed Protocols
4.1 Eve Guess on Correct Bell States Position
4.2 Eve Guess on Wrong Bell States Position
5 Conclusion
References
Analysis of Hate Tweets Using CBOW-based Optimization Word Embedding Methods Using Deep Neural Networks
1 Introduction
2 Background Study
3 System Model
3.1 Word Embedding Technique
3.2 Problem Statement
3.3 Proposed Architecture
3.4 Optimised CBOW Techniques
4 Performance Evaluation
4.1 Pre-processing
4.2 Pre-processing Steps
4.3 Techniques to Deal with Unbalanced Data
4.4 Training and Testing Data
4.5 Evaluation Metrics
4.6 Comparison with Existing Methods
5 Conclusion
References
Performance Analysis of Discrete Wavelets in Hyper Spectral Image Classification: A Deep Learning Approach
1 Introduction
2 Related Work
3 Methodology
3.1 Wavelet CNN Framework
3.2 Feature Decomposition Using Discrete Wavelets
4 Experiments and Result Analysis
4.1 Classification Results
5 Conclusion
References
Tyro: A Mobile Inventory Pod for e-Commerce Services
1 Introduction
2 Related Work
3 Methodology
3.1 Mecanum Wheels
3.2 Husky Lens Camera Module
3.3 Proposed System
3.4 Working
4 Results and Discussion
5 Conclusion
References
Segmentation and Classification of Multiple Sclerosis Using Deep Learning Networks: A Review
1 Introduction
1.1 Stages and Types of MS
2 MRI, Datasets, and Evaluation Measures
2.1 MRI
2.2 Dataset
2.3 Evaluation Measures
3 Deep Learning (DL) Networks
3.1 DL Methods for MS Lesion Segmentation
3.2 CNN
3.3 U-Net
4 Lesion Classification
5 Issues and Challenges
6 Discussion
7 Conclusion
References
Malware Detection and Classification Using Ensemble of BiLSTMs with Huffman Feature Optimization
1 Introduction
2 Related Works
3 Methodology
3.1 Overview
3.2 Feature Extraction
3.3 Huffman Feature Optimization
3.4 Training Networks
4 Experiments
4.1 Dataset Details
4.2 Evaluation Metrics
5 Results and Analysis
6 Discussion
7 Conclusions and Future Scope
References
Detection of Location of Audio-Stegware in LSB Audio Steganography
1 Introduction
2 Related Work
3 Proposed System
3.1 LSB Location Clustering
3.2 ASCII Conversion
3.3 Location Finder
4 Experimental Setup
4.1 Dataset
4.2 Simulation Setup
4.3 Evaluation Metrics
5 Experimental Results and Discussions
5.1 Effectiveness of Proposed Algorithm in Identifying Audio-Stegware Location
6 Conclusion
References
Hybrid Quantum Classical Neural Network-Based Classification of Prenatal Ventricular Septal Defect from Ultrasound Images
1 Introduction
2 Methodology
2.1 Classical Convolution Neural Network Phase
2.2 Parameterized Quantum Circuit Phase
3 Results
4 Conclusion
References
Experimental Evaluation of Reinforcement Learning Algorithms
1 Introduction
2 Related Work
3 Methodology
3.1 Data Collection
3.2 Model Evaluation Approach
3.3 Training
4 Experiments
4.1 Computation Environment
4.2 Experiments Setup
4.3 Results
5 Conclusion
6 Future Work
References
An Approach to Estimate Body Mass Index Using Facial Features
1 Introduction
2 Literature Survey
3 Methodology
4 Result and Discussion
5 Conclusion
References
An Approach to Count Palm Tress Using UAV Images
1 Introduction
2 Literature Survey
3 Proposed Method
3.1 Methodology
3.2 Flowchart
4 Architecture
5 Results
6 Conclusions and Future Work
References
Comparative Analysis on Deep Learning Algorithms for Detecting Retinal Diseases Using OCT Images
1 Introduction
2 Literature Survey
3 Methodology
3.1 Role of Deep Learning
3.2 Segmentation Approaches in Detecting Retinal Diseases
3.3 Data Preprocessing Techniques in Detecting Retinal Images
4 Performance Metrics
5 Comparative Analysis
6 Conclusion
References
PCB-LGBM: A Hybrid Feature Selection by Pearson Correlation and Boruta-LGBM for Intrusion Detection Systems
1 Introduction
2 Related Works
3 Methodology
3.1 Dataset
3.2 Preprocessing
3.3 Hybrid Feature Selection
4 Results and Analysis
5 Comparison with Existing Methods
6 Conclusion
References
Extractive Summarization Approaches for Biomedical Literature: A Comparative Analysis
1 Introduction
2 Automatic Text Summarization
3 Related Works
4 Text Summarization Algorithms
4.1 Frequency-Based Approach
4.2 Similarity-Based Approach
4.3 Luhn Approach
5 Comparative Analysis of Text Summarization Approaches
6 Conclusion
References
SMS Spam Detection Using Federated Learning
1 Introduction
1.1 Objectives
2 Background and Literature Survey
3 Federated Learning
3.1 Federated Learning Overview
3.2 Federated Learning Reference Architecture
4 Proposed System Architecture-Federative Learning
4.1 Application Development for Messaging
4.2 Backend
4.3 Working Methodology
4.4 System Details
4.5 Messaging Application
4.6 Database
5 Results
6 Conclusion and Future Scope
References
Data Extraction and Visualization of Form-Like Documents
1 Introduction
2 Previous Work
3 Methodology
3.1 Image Preprocessing and Segmentation
3.2 Text Extraction
3.3 Sentiment Analysis
4 Results and Discussion
5 Future Work
6 Conclusion
References
Author Index

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Proceedings of International Conference on Computational Intelligence and Data Engineering

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