
Proceedings of the NIELIT's International Conference on Communication, Electronics and Digital Technology
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The book presents selected papers from NIELIT's International Conference on Communication, Electronics and Digital Technology (NICEDT-2024) held during 16-17 February 2024 in Guwahati, India. The book is organized in two volumes and covers state-of-the-art research insights on artificial intelligence, machine learning, big data, data analytics, cybersecurity and forensic, network and mobile security, advance computing, cloud computing, quantum computing, VLSI and semiconductors, electronics system, Internet of Things, robotics and automations, blockchain and software technology, digital technologies for future, and assistive technology for Divyangjan (people with disabilities).
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Prof. Isaac Woungang received his M.Sc. in Mathematics from University of Aix Marseille II, France, and a Ph.D. in Computer Science from University of South, Toulon and Var, France, in 1990 and 1994 respectively. In 1999, he received a M.A.Sc. from INRS Telecommunications Research Centre, University of Quebec, Montreal, Canada. From 1999 to 2002, he worked as Software Engineer at Nortel Networks, Ottawa, Canada. Since 2002, he has been with the Department of Computer Science, Toronto Metropolitan University, where he is now Full Professor and Director of the Distributed Applications and Broadband NEtworks Lab (DABNEL). His current research interests include B5G networks design, control and management, network security, computational intelligence and machine learning applications, performance modeling, analysis, and optimization. He serves as Associate Editor of Internet of Things journal, Elsevier. He edited several books in the areas of wireless networks and computer security, published by Springer, Elsevier, Wiley. He has served in various roles in several top-notch conferences such as GLOBECOM and ICC. During 2012-2017. He served as Chair of Computer Chapter, IEEE Toronto Section.
Dr. Sanjay Kumar Dhurandher is presently serving as Executive Director, NIELIT on Deputation from Netaji Subhas University of Technology, New Delhi, where he is Professor at the Department of Information Technology. From 1995 to 2000 he worked as Scientist/Engineer at the Institute for Plasma Research, Gujarat, India, which is under the Department of Atomic Energy, India. Prof. Dhurandher has published over 250 research papers in various international journals/conferences/symposiums. He has also written/edited 8 books, published by international publishers. He is also Associate Editor of various international journals. His research interests include wireless networks, network security, underwater sensor networks, opportunistic networks, and cognitive radio networks. Prof. Dhurandher has also been actively involved in delivering keynote speeches/invited lectures at various conferences, Faculty Development Programs, Short-Term Courses, etc. held across the world/country. He is also Senior Member of IEEE and Fellow of IETE.
Prof. Yumnam Jayanta Singh is Executive Director, National Institute of Electronics and Information Technology, Govt. of India, Guwahati. He also worked with several universities in different counties, such as Don Bosco University (India), Swinburne University of Technology (Malaysia/Australia), Misurata University (Libya) with joint programs from Nottingham Trent University (England), and Skyline University (UAE) joint programs from National American University (USA). He had worked with CMM Level 5 organizations such as NTT Data (Halifax, Canada) and Tech Mahindra (Mumbai, India). Prof. Singh is Member of the Data Science Society, IASTED, EUROSIS, IETE, IEEE, etc. His research interests include Cloud Computing, Data Warehouse and Mining, Blockchain, Distributed Database Management Systems, Digital Image Processing, Software Engineering and Testing, etc. Prof. Singh has published several research papers in international and national journals and conferences. He has supervised many Ph.D. scholars and master's students. He has published 85 research publications. He is one of the founder editors of ADBU-Journal of Engineering Technology and NIELIT-International Journal of Digital Technologies. He has executed several projects of national importance and was in the team of developing the strategy plan of skilling the youths in many emerging areas.
Content
- Intro
- Preface
- Contents
- Editors and Contributors
- Artificial Intelligence, Machine Learning, Big Data, Data Analytics
- Optimization in Ensemble Model for Weather Prediction
- 1 Introduction
- 2 Materials and Methods
- 2.1 The Dataset
- 2.2 Extreme Gradient Boosting (XGBoost)
- 2.3 Optimization Techniques Used in XGBoost
- 3 Results and Discussion
- 4 Conclusion
- References
- Spectrum Efficient Resource Allocation Using Deep Neural Network in Underlay Cognitive Radios
- 1 Introduction
- 2 Related Work
- 3 System Design
- 3.1 System Model
- 3.2 Problem Formulation
- 4 Proposed Scheme
- 4.1 Motivation
- 4.2 Assumptions
- 4.3 Proposed SERA Model
- 4.4 SERA Functioning
- 5 Performance Evaluation
- 5.1 System Model Configurations
- 5.2 Results
- 6 Conclusion
- References
- Fruit and Vegetable Recognition System Using Deep Transfer Learning Approach
- 1 Introduction
- 2 Related Work
- 3 Methodology
- 3.1 Dataset Preparation
- 4 Experimental Results and Discussion
- 4.1 Experimental Setup and Data in Used
- 4.2 Comparison and Analysis of Results
- 5 Conclusion
- References
- A Comprehensive Investigation on the Performance of Traditional Machine Learning in Comparison to Deep Learning for Early Cardiovascular Disease Diagnosis
- 1 Introduction
- 2 Related Work
- 3 Approaches Used for the Study
- 4 Discussions and Analysis
- 5 Conclusion and Future Work
- References
- Hybrid-Multi-channel Deep Neural Network for Fake News Detection
- 1 Introduction
- 2 Related Work
- 3 Methodology
- 3.1 Datasets
- 3.2 Proposed Multi Channel Deep Neural Network Model
- 4 Hyper Tuning the Parameters of the Model
- 5 Results and Discussion
- 6 Conclusion and Future Scope
- References
- Integrated Gaussian-GLCM Butterfly Optimization with CNN (IGGBOCNN): A Hybrid Approach for Ovarian Cancer Classification in Medical Image Analysis
- 1 Introduction
- 2 Related Works
- 3 Proposed Methodology
- 4 Results and Discussion
- 5 Conclusion
- References
- Enhancing Brain Tumor Detection Through Deep Learning: A Comparative Study of CNN and Pre-trained VGG-16 Models
- 1 Introduction
- 2 Background and Motivation
- 3 Related Work
- 4 Standard Methodology Used
- 4.1 Dataset Description
- 4.2 Classification Model
- 4.3 Performance Evaluation Matrices
- 5 Results and Discussions
- 6 Conclusion and Future Work
- References
- Towards Development of Machine Learning Models for Fake News Detection and Sentiment Analysis
- 1 Introduction
- 2 Related Work
- 3 Methodology
- 4 Empirical Results and Analysis
- 4.1 Setting up Experiments
- 4.2 Comparison and Analysis of Results
- 5 Conclusion
- References
- A Study on Measures Based on Overlapping Area for Interval Data
- 1 Introduction
- 2 Preliminaries on Interval Data
- 2.1 Interval
- 2.2 Representations of Intervals
- 2.3 Arithmetic of Intervals
- 3 Materials and Methods
- 3.1 Measures Used for Interval Data
- 3.2 Analysis of Desirable Properties of Different Measures Used for Interval Data
- 4 Results and Discussion
- 5 Conclusion
- References
- Application of Secure Data Transmission by Integrating QR Code with Visual Cryptography
- 1 Introduction
- 1.1 QR Code
- 1.2 Motivation
- 2 Literature Review
- 3 Proposed Methodology
- 4 Experimental Result and Performance Analysis
- 4.1 Merits of Proposed Methodology
- 5 Conclusion
- References
- Event Uncertainty for Twitter Data Using Thematic Context Vector
- 1 Introduction
- 2 Related Work
- 3 Proposed Methodology
- 4 Experimentation
- 5 Results
- 6 Conclusion
- References
- A Brief Study of Prompting Techniques for Reasoning Tasks
- 1 Introduction
- 2 Related Work
- 2.1 LLM
- 2.2 Dataset
- 2.3 Basics of Prompt Principles
- 3 Prompting Techniques
- 3.1 Standard Few-Shot
- 3.2 Chain of Thought (CoT)
- 3.3 Zero Shot
- 3.4 Zero Shot CoT
- 3.5 Self-consistency
- 3.6 Least to Most
- 3.7 Active Prompt
- 3.8 Program of Thought (PoT)
- 3.9 Progressive Hint Prompting (PHP)
- 3.10 Plan and Solve (PS)
- 3.11 Tree of Thought (ToT)
- 3.12 Self-verification
- 4 Prompt- Example {Question-Solution} Task
- 5 Conclusion
- References
- Comparative Analysis of Negative Customer Review of Payment Apps: A Data Mining Approach
- 1 Introduction
- 2 Literature Review
- 3 Methodology
- 3.1 Data Pre-processing
- 3.2 Exploratory Data Analysis
- 3.3 Word Cloud Analysis
- 4 Data Analysis
- 4.1 Data Pre-processing
- 4.2 Exploratory Data Analysis (EDA)
- 4.3 Word Cloud Analysis (WCA)
- 5 Results and Discussion
- 5.1 Word Cloud Analysis Results for GPay
- 5.2 Word Cloud Analysis Results for Paytm
- 5.3 Word Cloud Analysis Results for PhonePe
- 6 Conclusion
- 6.1 Annexure
- References
- A Transformer-Based Approach for Fruit Spoilage Identification
- 1 Introduction
- 2 Literature Survey
- 3 Materials and Methods
- 3.1 Dataset Preparation
- 3.2 Proposed Transformer-Based Spoilage Diagnosis System
- 4 Results and Discussions
- 4.1 Results of ViT for 10 Epochs
- 4.2 Results of ViT for 20 Epochs
- 4.3 Comparison with Reported Work
- 5 Conclusion
- References
- A Study on Performance of Mathematics, Programming, and Practical Courses Among Female Students from Technical Education Using a Deep-Learning-Based Interpretability Framework
- 1 Introduction
- 2 Related Works
- 3 Proposed Works
- 4 Results and Discussions
- 5 Conclusion and Future Work
- References
- Efficient Handwritten English Word Detection with Neural Networks
- 1 Introduction
- 2 Literature Survey
- 3 Problem Definition
- 4 Methodology
- 4.1 Data Collection
- 4.2 Preprocessing
- 4.3 Model Design
- 4.4 Training, Testing, and Validation
- 4.5 Post-Processing
- 4.6 Evaluation Metrics
- 5 Future Work
- 6 Conclusion
- References
- MuBDA: Multimodal Biometric Data Analysis for Gender Classification Using Deep Learning Techniques
- 1 Introduction
- 2 Related Works
- 2.1 Motivation
- 2.2 Significance of the Work
- 3 Proposed Methodology
- 3.1 Transfer-Learning Architectures
- 4 Experimental Results
- 4.1 Dataset Description
- 4.2 Implementation Details
- 4.3 Results and Discussion
- 4.4 Performance Evaluation Methods
- 4.5 Evaluation Results
- 4.6 Comparative Analysis
- 5 Conclusion
- References
- Audio Data Feature Extraction for Speaker Diarization
- 1 Introduction
- 2 Results
- 3 Implementation Process
- 3.1 Implementation of MFCC
- 3.2 Implementation of Male Spectrogram
- 3.3 Implementation of Spectral Contrast
- 3.4 Implementation of Chroma Feature
- 3.5 Implementation Steps for Tonnetz Feature
- 3.6 Implementation Steps for Zero-Crossing Feature
- 3.7 Implementation of Rhythm Feature
- 4 Methodology
- 4.1 Mel-Frequency Cepstral Coefficients (MFCCs)
- 4.2 Mel-Spectrogram
- 4.3 Spectral Contrast
- 4.4 Chroma Features
- 4.5 Tonnetz
- 4.6 Zero-Crossing Rate
- 4.7 Rhythm Features
- 5 Conclusion
- References
- Cyber Security and Forensic, Network and Mobile Security
- Anomalous Network Packet Detection: A Review of Attacks, Datasets and Techniques
- 1 Introduction
- 2 Review Paper Framework
- 3 Intrusion Detection: Background Analysis
- 3.1 Categories
- 3.2 Implementation
- 3.3 Challenges
- 4 Performance Metrics
- 4.1 Detection Mechanisms
- 5 Review of Attacks
- 6 Comprehensive Review
- 6.1 Period 1: Before 2000
- 6.2 Period 2: 2001-2010
- 6.3 Period 3: 2011-2015
- 6.4 Period 4: 2016-2019
- 6.5 Period 5: 2020-2023
- 7 Review of Standard Datasets
- 8 Conclusion
- References
- Energy-Efficient Encounter, Buffer and Contact Duration-Based Routing Protocol in Opportunistic Networks
- 1 Introduction
- 2 Related Works
- 3 Proposed Energy-Efficient-EBC (E-EBC) Model
- 4 Simulation Results
- 5 Conclusion
- References
- IoT Under Attack: Designing Techniques for Mitigating Energy-Oriented DDOS Attacks on Smart Home Networks
- 1 Introduction
- 1.1 Motivation
- 1.2 Problem Statement
- 1.3 Research Objective
- 2 Background
- 2.1 Internet of Things (IoT) Network
- 2.2 Distributed Denial of Services (DDOS) Attack
- 2.3 Energy-Oriented DDoS (E-DDoS) Attack
- 3 Related Work
- 3.1 Defenses for Traditional DDoS Attacks
- 3.2 Existing Approaches for E-DDoS Attacks
- 3.3 Limitations of Current Solutions
- 3.4 Research Gaps
- 4 Proposed Smart Power Management System
- 4.1 System Design and Architecture
- 4.2 Key Components
- 4.3 Detection and Mitigation Process
- 5 Implementation and Evaluation
- 5.1 Simulation Setup
- 5.2 Attack Modeling
- 5.3 Defense Mechanism
- 5.4 Analyzing Reasons of Proposed System
- 5.5 Quantitative Results
- 6 Summary of Work
- 7 Future Directions
- 8 Conclusion
- References
- SEPA-CRT: SDN Enabled Direction Based Privacy-Preserving Authentication Scheme Using Chinese Remainder Theorem (CRT) for VANET
- 1 Introduction
- 2 Related Works
- 3 Proposed Scheme
- 3.1 System Initialization
- 3.2 Authentication
- 4 Security Analysis
- 4.1 Informal Security Analysis
- 4.2 Formal Security Analysis
- 5 Performance Analysis
- 6 Conclusion
- References
- IoT Network Intrusion Detection Using Federated Learning
- 1 Introduction
- 1.1 Motivation
- 1.2 Problem Definition
- 2 Related Work
- 3 Methodology
- 3.1 Architecture of the DNN Model
- 3.2 Conceptual Framework
- 4 Experimental Setup
- 4.1 Dataset Description
- 5 Results
- 5.1 Performance Assessment with Traditional CL Method
- 5.2 Performance Comparison With Existing Methods
- 5.3 Discussion
- 6 Conclusion and Future Work
- References
- Machine Learning, Malware Detection: SecureAI
- 1 Introduction
- 1.1 Importance of ML-Based Malware Detector Interpretability
- 2 Literature Survey
- 3 Related Work
- 4 Methodology
- 4.1 Setup
- 4.2 Models Evaluation
- 4.3 Explainability Approach
- 5 Conclusion
- 6 Limitations and Challenges
- References
- Phishing in the Inbox: A Systematic Examination of Email-Based Cyber Threats
- 1 Introduction
- 2 Background and Overview
- 2.1 Phishing Motivation
- 2.2 Types of Phishing Attacks
- 2.3 Phishing Life Cycle
- 3 Classification Strategy for Phishing
- 4 Various Features of Phishing Email
- 4.1 Basic Features
- 4.2 Dynamic Markov Chain Features
- 4.3 Latent Topic Model Features
- 5 Literature Survey
- 6 Conclusion
- References
- Advance Computing-Cloud Computing and Quantum Computing
- Efficient Mechanism for Enhanced Data Speedup in Internet of Things
- 1 Introduction
- 2 Related Work
- 3 Methodology
- 4 Results
- 5 Conclusion
- References
- Energy Harvesting in a NOMA-Based Integrated Satellite-UAV-Terrestrial Network with Amplify and Forward Relay and Imperfect CSI
- 1 Introduction
- 1.1 State of the Art
- 2 System Model and Channel Models
- 2.1 Satellite-UAV Link
- 3 UAV-User Link
- 4 Results
- 5 Conclusion
- References
- KDSR: Hybrid Machine-Learning Solution for Intrusion Detection in Fog Computing Environment
- 1 Introduction
- 2 Related Work
- 3 Proposed Methodology
- 4 Result Analysis
- 5 Conclusion
- References
- MQFURP: An Overprovision Strategy Supporting Performance Interference Management in Cloud
- 1 Introduction
- 2 Related Work
- 3 Proposed Method
- 3.1 Formulation of Traditional Framework: Single-Level QoS
- 3.2 Formulation of Proposed Method: Multi-level QoS Framework Using Resource Pooling (MQFURP)
- 4 Experiments and Results
- 4.1 Experiments
- 5 Results
- 6 Conclusion
- References
- Optimization of Computational Efficiency of GP2U-Accelerated Grid Applications on Non-dedicated Desktop Grids: A Speed-Up Factor Analysis
- 1 Introduction
- 2 Materials and Method
- 2.1 Materials
- 3 Method
- 4 Results
- 5 Conclusion
- References
- GPT Vision Meets Taxonomy: A Comprehensive Evaluation for Biological Image Classification
- 1 Introduction
- 1.1 Background on Image Classification in Biology
- 1.2 The Advent of Machine Learning and Its Implications for Biological Image Classification
- 1.3 GPT Vision's Potential in This Domain
- 1.4 Objective of the Study
- 2 Materials and Methods
- 2.1 Dataset Description
- 2.2 GPT Vision Overview
- 2.3 Analysis and Visualization Techniques
- 3 Results
- 3.1 Overall Accuracy Across Taxonomic Levels
- 3.2 Detailed Performance Metrics
- 3.3 Misclassification Analysis
- 3.4 Data Availability Statement
- 4 Discussion
- 4.1 Interpretation of the Results
- 4.2 Implications for Biological Research and Taxonomy
- 4.3 Limitations of the Study
- 5 Conclusion
- 5.1 Key Findings
- 5.2 Recommendations for Further Research
- References
- Nanostructured Sensors for Pesticide Detection in Tea
- 1 Introduction
- 2 Nanomaterials for Chemical Sensors
- 2.1 Carbon Nanotubes
- 2.2 Graphene
- 2.3 Metal Oxide Nanoparticles
- 2.4 Nanowires
- 3 Techniques of Detection Pesticides/Herbicide Using Electrochemical Sensor
- 4 Conclusion
- References
- Screening and Characterization of Aroma and Flavor-Producing Bacteria and Yeast from Traditional Fermented Food and Beverages of Northeast, India
- 1 Introduction
- 2 Objective of the Study
- 3 Work Plan
- 4 Materials and Methods
- 4.1 Sample Collection
- 4.2 Isolation and Characterization of the Flavor-Producing LAB
- 4.3 Screening of Potential Aroma and Flavor-Producing Bacteria and Yeast by Biochemical Characterization (Proteolytic Test, Lipolytic Test, Carbohydrate Fermentation Test, and Hemolytic Test)
- 4.4 Yogurt Preparation
- 4.5 Sensory Evaluation
- 5 Results
- 5.1 Isolation and Characterization of the Flavor-Producing LAB
- 5.2 Sensory Evaluation
- 6 Discussion
- 7 Conclusion
- 8 Future Work
- References
- MindWell: A Dataset Related to Mental Health
- 1 Introduction
- 2 Background
- 3 Methodology
- 4 Potential Applications and Implications
- 5 Conclusion and Future Work
- References
- Gadolinium Dilemma: Navigate Water Contamination in the Face of Indispensable Medical Advancements
- 1 Introduction
- 2 Gadolinium Ion and Its Derivatives
- 2.1 Application of Gadolinium Ion in Various Fields
- 2.2 Medical Use of Gadolinium Ion:
- 2.3 Use of Gadolinium Complexes in Nano Related Field
- 3 Toxicity of Gd
- 3.1 Effect of Gd-Based Compounds in Environment
- 3.2 Effect of Gd-Based Compounds on Human Health
- 3.3 Detection of Gd and Its Complex Forms in Different Sources of Water in the Environment
- 3.4 Removal of Toxicity Using Nanomaterials
- 4 Conclusion
- References
- Blockchain and Software Technology
- Blockchain-Based Certificate Verification System: A Decentralized Approach
- 1 Introduction
- 2 Literature Review
- 2.1 Blockchain Technology in Certificate Verification
- 2.2 Blockchain for Certificate Distribution and Security
- 2.3 Addressing Vulnerabilities with Blockchain
- 2.4 Emerging Trends and Future Prospects
- 3 Related Work
- 4 Objective of the Proposed System
- 5 Architecture Design
- 6 Proposed System
- 6.1 User Interface
- 6.2 Admin Interface
- 7 Conclusion
- References
- Examination of Broken or Non-responsive Touch Screen Display Mobile Phones
- 1 Introduction
- 2 Analytical Tool 1
- 3 Methodology 1
- 4 Analytical Tool 2
- 5 Methodology 2
- 6 Conclusion
- References
- A Review in Assamese Handwritten Character Recognition
- 1 Introduction
- 2 History of OCR
- 3 Phases of OCR
- 3.1 Image Acquisition
- 3.2 Preprocessing
- 3.3 Segmentation
- 3.4 Feature Extraction
- 3.5 Classification and Recognition
- 3.6 Post Processing
- 4 Datasets
- 5 Assamese Language and Properties of Its Script
- 6 Script-Specific Literature Review on Character Recognition
- 6.1 International
- 6.2 National
- 7 Conclusion
- References
- Inner Line Permit Using Hyperledger Fabric
- 1 Introduction
- 1.1 Objectives
- 2 Motivation and Background
- 3 Proposed System
- 4 System Workflow
- 4.1 System Architecture
- 4.2 Channel Creation
- 5 Pseudo-Code
- 6 Result
- 7 Conclusion and Future Work
- References
- Author Index
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