Proceedings of International Conference on Communication and Computational Technologies

Name: Proceedings of International Conference on Communication and Computational Technologies | ICCCT 2024, Volume 1
Brand: Springer
Price: 267.49 EUR
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ICCCT 2024, Volume 1

Sandeep Kumar Saroj Hiranwal Ritu Garg S. D. Purohit(Editor)

Springer (Publisher)

1st Edition

Published on 4. December 2024

XXIV, 523 pages

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978-981-97-7423-4 (ISBN)

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Dr. Sandeep Kumar is currently a professor at CHRIST (Deemed to be University), Bangalore. He recently completed his postdoctoral research at Imam Mohammad Ibn Saud Islamic University, Riyadh, Saudi Arabia, in sentiment analysis. He is an associate editor for Springer's Human-centric Computing and Information Sciences (HCIS) journal. He has published more than eighty research papers in various international journals/conferences and attended several national and international conferences and workshops. He has authored/edited seven books in the area of computer science. Also, he has been serving as the general chair of the Congress on Intelligent Systems (CIS 2022 and 2023) and the International Conference on Communication and Computational Technologies (ICCCT 2021, 22, and 23). His research interests include nature-inspired algorithms, swarm intelligence, soft computing, and computational intelligence.

Dr. Saroj Hiranwal is an Associate Course Coordinator at BITS and Lecturer-Higher Education in the Faculty of IT at Victorian Institute of Technology, Adelaide Campus, South Australia, who has contributed to machine learning, artificial intelligence, and real-time systems. Saroj's research interests also include high performance scientific computing, cloud computing and network security. she is also working in the evolving and increasingly important field of image processing, data analytics and edge computing, which promise to pave the way for the evolution of new applications and services in the areas of healthcare, agriculture, smart cities, education, marketing and finance. Her research has appeared in numerous prestigious journals, conferences, and she has written more than 50 research papers. Saroj started her academic career in year 2006 as a Lecturer and promoted on various position including Sr. Lecturer, Reader and professor during this tenure. Saroj received a Bachelor of Engineering from the School of IT, University of Rajasthan, Jaipur, India, in 2004, a Master of Technology in IT in 2006, and a Ph.D. in Computer Science & Engineering from the Faculty of Engineering & Technology in 2014.

Dr. Ritu Garg is an assistant professor in the Department of Computer Engineering at National Institute of Technology, Kurukshetra, India, since Feb. 2008. Dr. Garg has received her Ph.D. in the area of Grid Computing from National Institute of Technology, Kurukshetra, India. Her primary area of research includes Grid Computing, Cloud Computing, Internet of Things, Fault Tolerance, Security, and Data sciences. She has published more than 70 research papers in international journals and conferences mainly in the area of energy management and reliability in grid computing, cloud computing, and IoT. She has supervised four Ph.D. thesis and 27 M.Tech. dissertations. She has acted as a TPC member of various international conferences. She is an active reviewer of many reputed journals of the IEEE, Springer, Elsevier, Wiley, InderScience, etc. She has organized many STCs, FDPs, and international conferences. She is working on MeitY, Government of India, New Delhi-sponsored project entitled "Capacity Building for Human Resource Development in Unmanned Aircraft System (Drone and related Technology)" under "Drone Applications" work theme worth Rs. 2.5 Cr.

Dr. Sunil Dutt Purohit is an associate professor of Mathematics at Rajasthan Technical University, Kota, India. He also holds a non-resident postdoctoral fellowship at the Lebanese American University's Beirut campus. He did his Master of Science (M.Sc.) in Mathematics and Ph.D. in Mathematics from Jai Narayan Vyas University, Jodhpur, India. He was awarded the University Gold Medal for being topper in M.Sc. Mathematics and awarded Junior Research Fellowship and Senior Research Fellowship of Council of Scientific and Industrial Research. His research interests include special functions, basic hypergeometric series, fractional calculus, geometric function theory, mathematical analysis, and modeling. He has credited more than 230 research articles and eight books so far. He has delivered number of talks at foreign and national institutions. He is a life member of Indian Mathematical Society (IMS), Indian Science Congress Association (ISCA), Indian Academy of Mathematics (IAM), Soft Computing Research Society, India (SCRS), and Society for Special Functions and their Applications and a member of International Association of Engineers (IAENG). He has also contributed in designing and redesigning the syllabus of engineering mathematics for UG and PG course work.

Content

Intro
Organization
Preface
Contents
Editors and Contributors
Economically Growth and Impact of Indian Regional Navigation Satellite System at International Level
1 Introduction
2 Applications of IRNSS System
3 Growth and Impact at International Level
4 Growth and Impact at Indian Economy
5 Conclusion
References
Predictive Tomato Leaf Disease Detection and Classification: A Hybrid Deep Learning Framework
1 Introduction
2 Dataset
2.1 Plant Village
2.2 Plantdoc
3 Object Detection Models
3.1 Faster R-CNN
3.2 YOLO
3.3 SSD
3.4 Mask R-CNN
4 Image Classification Models
4.1 Visual Geometry Group (VGG)
4.2 Residual Network (ResNet)
4.3 Inception (GoogLeNet)
4.4 MobileNet
4.5 Xception
5 Review on Tomato Plant Leaf Diseases Prediction
6 Proposed Methodology
7 Result and Discussion
8 Conclusion
References
Conceptual Framework for Risk Mitigation and Monitoring in Software Organizations Based on Artificial Immune System
1 Introduction
2 Background and Motivation
3 Findings
4 A New Conceptual Framework for Risk Mitigation and Monitoring Based on Immune Clonal Approach-The Design/Proposed
5 Conclusions and Future Scope
References
A Multilevel Home Fire Detection and Alert System Using Internet of Things (IoT)
1 Introduction
2 Literature Review
3 Proposed Work
3.1 System Model
3.2 System Requirements
3.3 Multilevel Fire Detection
3.4 Multilevel Fire Alerts
4 Experimental Prototype, Results, and Discussion
5 Conclusion
References
Smart Baby Warmer with Integrated Weight Sensing
1 Introduction
1.1 Internet of Things (IoT)
1.2 Global System for Mobile Communication (GSM)
2 Working Principle
2.1 Methodology
2.2 Block Diagram
2.3 Flow Chart
2.4 Working of LM35 Sensor
2.5 Working of Load Cell and HX711
2.6 Sending SMS Using GSM
2.7 Circuit Connection
3 Results and Analysis
3.1 SMS Alert
3.2 Output
3.3 Heater on
3.4 Heater off
3.5 Analysis
4 Conclusion
References
A Robust Multi-head Self-attention-Based Framework for Melanoma Detection
1 Introduction
2 Literature Review
3 Methodology
3.1 Pre-processing and Patch Embedding
3.2 Multi-head Self-attention Model
3.3 Classification
4 Experimental Results
4.1 Dataset
4.2 Data Augmentation
4.3 Simulation Results
4.4 Comparative Analysis
4.5 Discussion
5 Conclusion
References
Domain Knowledge Based Multi-CNN Approach for Dynamic and Personalized Video Summarization
1 Introduction
2 Related Works
3 Proposed Approach
3.1 Input
3.2 Domain Activity Video Segmentation
3.3 Umpire Detection and Pose Recognition
3.4 Key Segments
3.5 Personalized and Dynamic Video Summarization
4 Result Analysis
5 Conclusion
References
Efficient Information Retrieval: AWS Textract in Action
1 Introduction
2 Related Work
3 Proposed Methodology
3.1 Input Documents
3.2 Analyzing Documents
3.3 Detecting Text
3.4 Confidence Scores
3.5 Deployment
4 Results and Discussion
4.1 Image as an Input
4.2 PDF as an Input
4.3 Table as an Input
5 Conclusion and Future Work
References
Text Summarization Techniques for Kannada Language
1 Introduction
2 Literature Survey
3 Proposed Methodology
3.1 Extractive Summarization Using TF-IDF Method
3.2 Abstractive Summarization Using the LSTM Method
4 Results and Discussions
5 Conclusion
References
Parkinson's Detection From Gait Time Series Classification Using LSTM Tuned by Modified RSA Algorithm
1 Introduction
2 Related Works
2.1 Long Short-Term Memory
2.2 Metaheuristics Optimization
3 Methods
3.1 The Original RSA
3.2 Genetically Inspired RSA
4 Experiments
4.1 Dataset
4.2 Simulation Setup
4.3 Metrics
4.4 Simulation Results
5 Conclusion
References
Human Action Recognition Using Depth Motion Images and Deep Learning
1 Introduction
2 Related Work
3 Methodology
3.1 Algorithm for Displaying Depth Map Sequence
3.2 Algorithm for Depth Motion Images
3.3 Convolutional Neural Network Model
4 Results and Discussion
5 Conclusion
References
Maximizing Portfolio Returns in Stock Market Using Deep Reinforcement Techniques
1 Introduction
2 Review of Literature
3 Proposed Methodology
4 Result Analysis
5 Backtest Results
6 Conclusion
References
Detecting AI Generated Content: A Study of Methods and Applications
1 Introduction
2 Background
2.1 Watermarking
2.2 Classification
2.3 Statistical Analysis
3 Generative Models
4 Detecting AI-Generated Content
4.1 Linguistic-Based Methods
4.2 Statistical-Based Methods
4.3 Learning-Based Methods
5 Challenges in AI Content Detection
6 Applications and Scenarios
7 Conclusion
References
A Systemic Review of Machine Learning Approaches for Malicious URL Detection
1 Introduction
2 Identifying URLs with Malicious Hidden Links
2.1 Traditional Approaches to Malicious URL Detection
2.2 Heuristic Based Methods
2.3 Machine Learning Approaches
2.4 List of features extracted from the URL:
3 Malicious URL Classification with Artificial Intelligence
3.1 Random Forest Algorithm
3.2 PhishAri: Automatic Real-Time Phishing Detection on Twitter
3.3 Support Vector Machine (SVM)
4 Deep Learning Methods
4.1 Models Based on Convolutional Neural Networks
4.2 Models Based on Recurrent Neural Networks
4.3 Models Based on a Combination of CNN and RNN
4.4 Models Based on Transformers
5 Conclusion
References
Digital Image Forgery Detection Based on Convolutional Neural Networks
1 Introduction
2 Related Work
2.1 Block-Based Approach
2.2 Key Point-Based Approach
2.3 Machine Learning-Based Approach
3 The Proposed CNN Model
3.1 Image Preprocessing
3.2 Image Resizing
3.3 CNN Architecture
3.4 Classification
4 Experimental Results
4.1 Datasets
4.2 Evaluation Metrics
4.3 The Results
4.4 Discussion
4.5 Comparison with Other Works
5 Concluding Remarks
References
Banana Freshness Classification: A Deep Learning Approach with VGG16
1 Introduction
2 Literature Review
3 Methodology
3.1 Data Collection and Dataset Composition
3.2 Data Preprocessing
3.3 Data Augmentation
4 Experimental Work
4.1 Model Architecture
4.2 Model Training
5 Results and Analysis
5.1 Model Performance
5.2 Confusion Matrix
5.3 Classification Report
6 Conclusions And Future Work
References
GreenHarvest: Data-Driven Crop Yield Prediction and Eco-Friendly Fertilizer Guidance for Sustainable Agriculture
1 Introduction
2 Literature Survey
3 Problem Definition
4 Objectives
5 Methodology
6 Results and Algorithms
7 Conclusion
References
Real-Time Deep Learning Based Image Compression Techniques: Review
1 Introduction
2 Image Compression
2.1 Lossy Compression
2.2 Lossless Compression
3 Deep Learning
3.1 Auto-Encoder
3.2 Recurrent Neural Network
3.3 Convolution Neural Network
4 Literature Review
5 Discussion
6 Conclusion
References
Fog-Cloud Enabled Human Falls Prediction System Using a Hybrid Feature Selection Approach
1 Introduction
2 Related Works
3 Proposed Human Fall Prediction System
4 Hybrid Feature Selection Approach
5 Experimental Results
6 Conclusion and Future Enhancement
References
A 4-Input 8-Bit Comparator with Enhanced Binary Subtraction
1 Introduction
2 Literature Review
3 Methodology
3.1 Full Adder Logic
3.2 8-Bit Adder Logic
3.3 Comparator Logic
4 Novelty
5 Analysis
5.1 Register Transfer Level (RTL) Components Analysis
5.2 Power Analysis
5.3 Part Resource Analysis
6 Results
6.1 Input Scenario and Output
6.2 Circuit Justification
7 Conclusion and Future Scope
References
Multivalued Dependency in Neutrosophic Database System
1 Introduction
2 Basic Definitions
2.1 Neutrosophic Set
2.2 a-Equal of Neutrosophic Tuples
2.3 Neutrosophic Functional Dependency
3 A New Concept: Neutrosophic Multivalued Dependency (a-nmvd)
3.1 Multivalued Dependency
3.2 Neutrosophic Multivalued Dependency
3.3 Inference Rules for a-nmvd
4 Conclusion
References
Traffic Sign Recognition Framework Using Zero-Shot Learning
1 Introduction
2 Literature Review
3 Methodology
4 Result and Analysis
4.1 Dataset
4.2 Result
5 Conclusion
References
Machine Learning Techniques to Categorize the Sentiment Analysis of Amazon Customer Reviews
1 Introduction
2 Related Work
3 Data Preprocessing
4 Methodology
4.1 Data Source and Data Set
5 Experiment and Result
6 Conclusion
References
Alzheimer's Disease Diagnosis Using Machine Learning and Deep Learning Techniques
1 Introduction
2 Literature Survey
3 Datasets
4 Experimental Results
5 Conclusion
References
Sentinel Eyes Violence Detection System
1 Introduction
2 Literature Review
3 Methodology
3.1 Openpose
3.2 Yolov8
3.3 Cnn-Lstm
4 Result
4.1 Object Detection Models
4.2 Architectures
5 Conclusion
References
Detection of Alzheimer's Disease from Brain MRI Images Using Convolutional Neural Network
1 Introduction
2 Related Work
3 Implementation
3.1 Preprocessing
3.2 Classification Using CNN
4 Results and Discussion
4.1 Dataset Used
4.2 Evaluation Metrics
4.3 Model Performance and Training Results
4.4 Comparison of Classification Results with Existing Methods
5 Conclusions
References
Detection of Banana Plant Diseases Using Convolutional Neural Network
1 Introduction
2 Literature Review
3 Proposed Method
3.1 Prototype Drone Assembling for Collection of Crop Images
3.2 Data Collection and Dataset Creation
3.3 Image Pre-Processing Steps
3.4 Flow of the Proposed Method
3.5 Various Image Classification Models
3.6 Experimental Settings
4 Results
4.1 Performance Measures
5 Conclusion
6 Discussion
References
Insect Management in Crops Using Deep Learning
1 Introduction
1.1 Classes of Insects and Their Effects
2 Literature Survey
3 Proposed Methodology
3.1 Dataset Description
4 Results and Discussions
4.1 Metrics for Performance Evaluation
4.2 Performance Evaluation
4.3 Computation Time
5 Conclusion
References
An Intra-Slice Security Approach with Chaos-Based Stream Ciphers for 5G Networks
1 Introduction
2 Related Works
3 Methodology
3.1 Algorithms Used
3.2 Proposed Encryption Scheme
4 Results and Analysis
4.1 Performance Analysis
4.2 Security Analysis
5 Conclusion and Future Work
References
Emotion Classification Using Triple Layer CNN with ECG Signals
1 Introduction
2 Literature Survey
3 Methodology
3.1 Dataset
3.2 Preprocessing
3.3 Triple-Layered CNN Model
4 Experimental Work
5 Result Analysis
5.1 Confusion Matrix and Loss Curve
5.2 Precision, Recall & F1-Score
5.3 Comparison with Previous Work
6 Conclusion
References
Evolving Approaches in Epilepsy Management: Harnessing Internet of Things and Deep Learning
1 Introduction
1.1 Epilepsy Types
1.2 Epilepsy Diagnosis Techniques
2 Smart Technologies for Health Care
2.1 EEG Data Acquisition and IoT
2.2 IoT in Epileptic Seizure Detection
3 Discussion
4 Conclusion
5 Future Directions
References
Multipurpose Internet of Things-Based Robot for Military Use
1 Introduction
1.1 Literature Review
1.2 Proposed Method
References
A Comprehensive Review of Small Building Detection in Collapsed Images: Advancements and Applications of Machine Learning Algorithms
1 Introduction
2 Small Building Detection
3 Machine Learning in Small Structure Identification from Images
3.1 Use Cases of Artificial Neural Networks
3.2 Use Cases of Convolutional Neural Networks
3.3 Use Cases of Support Vector Machine
4 Hypothetical Statistical Representation
5 Results
6 Future Enhancement
7 Conclusion
References
Data-Based Model of PEM Fuel Cell Using Neural Network
1 Introduction
2 PEM Fuel Cell
3 Experimental Setup of PEM Fuel Cell
4 Artificial Neural Network
5 Result and Discussion
6 Conclusion
References
Ensemble Technique to Detect Intrusion in a Network Based on the UNSWB-NB15 Dataset
1 Introduction
2 Literature Review
3 Methodology
3.1 Dataset Description
3.2 Data Preprocessing
3.3 Feature Selection
3.4 Training and Testing of Classifier
4 Experimental Results and Discussion
4.1 Comparisons with Existing Intrusion Detection System
5 Conclusion
References
Enhancing Statistical Analysis with Markov Chain Models Using a Shiny R Interface
1 Introduction
2 Methods
2.1 Data Collection
2.2 Data Analysis and Processing
2.3 Construction of Prediction Models
2.4 Performance Analysis
2.5 Performance Comparison
2.6 Web Application Development
2.7 Markov Chains
2.8 Hardware Specifications: A Subsection Sample
3 Results
3.1 Interface
3.2 Predictions
4 Conclusions
References
Securing the Digital Realm: Unmasking Fraud in Online Transactions Using Supervised Machine Learning Techniques
1 Introduction
2 Related Work
3 Materials and Methods
3.1 Online Fraud Detection Dataset
3.2 Date Preprocessing
3.3 Experimental Setup
3.4 Data Exploration and Analysis
3.5 Machine Learning Models for Review Analysis
3.6 Performance Evaluation
4 Results and Discussion
5 Conclusion
References
High-Speed Parity Number Detection Algorithm in RNS Based on Akushsky Core Function
1 Introduction
2 Residue Number System
3 Parity Detection Algorithms Based on Inverse Conversion
3.1 Chinese Remainder Theorem
3.2 Approximate Method
3.3 Mixed-Radix Chinese Remainder Theorem
4 Algorithm for Parity Detection Using Akushsky Core Function
5 Performance Evaluation
6 Conclusion
References
A Review: 5G Unleashed Pioneering Leadership, Global Deployment, and Future International Policies
1 Introduction
2 Art of 5G Technology
3 International Deployment of 5G
4 EU Focus on Mobile Merger
5 Conclusion
References

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Proceedings of International Conference on Communication and Computational Technologies

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