Data Intelligence and Cognitive Informatics

Name: Data Intelligence and Cognitive Informatics | Proceedings of ICDICI 2023
Brand: Springer
Price: 255.73 EUR
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Proceedings of ICDICI 2023

I. Jeena Jacob Selwyn Piramuthu Przemyslaw Falkowski-Gilski(Editor)

Springer (Publisher)

1st Edition

Published on 6. January 2024

XIII, 586 pages

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978-981-99-7962-2 (ISBN)

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Dr. I. Jeena Jacob is working as a Professor in Computer Science and Engineering department at GITAM University, Bangalore, India. She actively participates on the development of the research field by conducting international conferences, workshops and seminars. She has published many articles in referred journals. She has guest edited an issue for International Journal of Mobile Learning and Organisation. Her research interests include mobile learning and computing.

Dr. Selwyn Piramuthu is Professor of Information Systems at the University of Florida. He received his B.Tech, M.S., and Ph.D. respectively from IIT-Madras, University of Arizona, and University of Illinois at Urbana-Champaign. His research interests include machine learning and cryptography with applications in medical informatics, supply chain management, financial credit risk scoring, IoT, among others. His book, co-authored with Wei Zhou titled, "RFID and Sensor Network Automation in the Food Industry," was published by Wiley in 2016.

Dr. Przemyslaw Falkowski-Gilski is a graduate of the Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology. He graduated 1st degree B.Sc. studies (in Polish) and 2nd degree M.Sc. studies (in English) in 2012 and 2013, respectively. Between 2013-2017, during Ph.D. studies, he pursues his interests in the field of electronic media, particularly digital broadcasting systems and quality of networks and services. In 2018 he receives the title of Doctor of Technical Sciences with distinction, discipline Telecommunications, specialty Radio communication. Currently he works as an Assistant Professor. His field of interests is related with electronic media, particularly digital broadcasting systems, as well as quality evaluation of networks and services. His research and development interests include digital video and audio broadcasting systems, software-defined radio technology, location services and radio navigation systems, as well as quality measurements in mobile networks. Author of more than 50 scientific papers, 1 patent application, involved in approx. a dozen of both national and international conferences as a reviewer, committee member, board member.

Content

Intro
Preface
Contents
About the Editors
Automatic Sentence Classification: A Crucial Component of Sentiment Analysis
1 Introduction
2 Literature Review
3 Proposed Methodology
3.1 Data Collection
3.2 Pre-processing
3.3 Tokenization of Data
3.4 Algorithm Feeding
3.5 Best Model Selection
4 Result and Discussion
4.1 Statistical Analysis
4.2 Accuracy Graph
4.3 Confusion Matrix
4.4 Classification Report
5 Conclusion and Future Work
References
Real-Time Health Monitoring System of Patients on Utilizing Red Tacton
1 Introduction
2 Implementation
3 Proposed Methodology
4 Results
5 Conclusion
References
An Efficient Botnet Detection Using Machine Learning and Deep Learning
1 Introduction
2 Literature Review
3 Proposed Methodology
3.1 Load Dataset
3.2 Data Pre-Processing
3.3 Feature Selection
3.4 Handling Class Imbalance
3.5 Partition Dataset in Training and Testing
3.6 Apply ML/DL Models
3.7 Bot Detection
3.8 Model Evaluation
4 Experiments and Results
5 Conclusion
References
Wavelet Selection for Novel MD5-Protected DWT-Based Double Watermarking and Image Hiding Algorithm
1 Introduction
2 Related Works
3 Methodology Used
3.1 Architecture of Proposed System
3.2 Watermark Embedder
3.3 Watermark Extractor
4 Experimental Results
4.1 Pseudorandomness in Watermark Embedding
4.2 Performance Evaluation Metrics
4.3 Selection of Wavelet
4.4 Watermark Embedding and Extraction
4.5 Image Hiding
5 Conclusion and Future Work
References
Chaotic Map Based Encryption Algorithm for Secured Medical Data Analytics
1 Introduction
2 Related Work
3 Existing Techniques
3.1 Algorithm
3.2 Cryptography
3.3 Encryption
3.4 Decryption
3.5 Key
3.6 Steganography
3.7 Symmetric Encryption
4 Proposed Methodology
4.1 Secret Key Generation
4.2 Hahn's Discrete Orthogonal Moment
4.3 QR Code
4.4 Modified Logistic Map
5 Results and Discussions
References
Gold Price Forecast Using Variational Mode Decomposition-Aided Long Short-Term Model Tuned by Modified Whale Optimization Algorithm
1 Introduction
2 Background and Related Works
2.1 LSTM Overview
2.2 Variation Mode Decomposition Details
2.3 Metaheuristics Optimization
2.4 AI Applications for Gold Price Forecasting
3 Whale Optimization Algorithm
3.1 Elementary WOA
3.2 Proposed Improved WOA Algorithm Used in Time-Series Forecasting Framework
4 Experimental Setup
4.1 Results and Discussion
5 Conclusion
References
Requirements for a Career in Information Security: A Comprehensive Review
1 Introduction
2 Cybersecurity Foundation
2.1 Information Security Expertise
2.2 Duties and Tasks of an IS Professional
2.3 Job Nature and Requirements
3 Research Approach
3.1 Words Used to Search
3.2 Selection Criteria
3.3 Rejection Criteria
3.4 Data Gathering
3.5 Quality Appraisal
4 Results
5 Conclusion
References
Intrusion Detection Using Bloom and XOR Filters
1 Introduction
2 Literature Survey
3 NIDS Implementation Using Bloom Filter
4 NIDS Implementation Using XOR Filter
5 Experimental Results and Discussions
6 Conclusions and Future Work
References
A Model for Privacy-Preservation of User Query in Location-Based Services
1 Introduction
2 Related Work and Literature Survey
3 Methodology
4 Results
5 Conclusion
6 Future Work
References
A GPS Based Bus Tracking and Unreserved Ticketing System Using QR Based Verification and Validation
1 Introduction
2 Literature Survey
3 Proposed System
4 System Architecture
5 System Functionality
5.1 QR Code
5.2 Crowd Management
5.3 GPS Location
5.4 Automatic Ticket Expiry
5.5 Passenger Application
5.6 Conductor Application
6 Backend
6.1 Seat Availability
6.2 Passenger Information
6.3 Administrative Information
7 Conclusion and Future Scope
References
FileFox: A Blockchain-Based File Storage Using Ethereum and IPFS
1 Introduction
2 Background
2.1 Blockchain Storage
2.2 INFURA
2.3 Truffle
2.4 MetaMask
3 Related Work
4 Proposed System
5 Implementation
6 Result and Discussion
7 Conclusion and Future Scope
References
Minimizing Web Diversion Using Query Classification and Text Mining
1 Introduction
2 Literature Review
3 Methodology
3.1 Dataset
3.2 Feature Extraction
3.3 Semantic Matching
3.4 Web Query Classification
3.5 Machine Learning Models
3.6 Deep Learning Models
3.7 Evaluation Metrics
4 Results and Discussion
5 Future Scope
6 Conclusion
References
Connect: A Secure Approach for Collaborative Learning by Building a Social Media Platform
1 Introduction
1.1 Critical Characteristics of Social Media Are as Follows
1.2 Social Media Platforms
1.3 Need for Using Collaborative Learning
1.4 Challenges and Issues to Build Social Networking
1.5 Cloud Computing
1.6 Encryption
1.7 Importance of Social Media Platforms for Collaborative Learning
1.8 Advantages of Collaborative Learning for Faculty-To-Faculty Interaction
1.9 Security Concerns While Building a Social Media Platform
1.10 Conventional Threats
1.11 Modern Threats
1.12 Targeted Threats
1.13 Reasons Behind Online Social Media Security
2 Literature Review
2.1 Encryption Techniques Used
3 Summary of Literature Review
3.1 Importance of the Study
3.2 The Opportunities that Will Be Provided Among the Users of the System Are as Follows
4 Proposed System
4.1 Proposed Algorithmic Process
5 Discussion
6 Conclusion
References
Smart Analytics System for Digital Farming
1 Introduction
2 Need for the Study
3 Related Works
4 Proposed Work
5 Conclusion
References
Sarcasm Detection for Marathi and the role of emoticons
1 Introduction
2 Related Work
3 Dataset and Annotation
3.1 Distribution of Tweets
3.2 Emoji Analysis
4 Pre-processing of Tweets
4.1 Cleaning of Tweets
4.2 Tokenization
5 Feature Extraction and Sarcasm Detection
5.1 Sentence Embedding Using Language Model
5.2 Embeddings for Emojis in the Tweet
6 Experiments and Result Analysis
7 Conclusion
References
Fleet Management Mobile Application Using GPS Shortest Path
1 Introduction
2 Literature Survey
3 Proposed System
3.1 Modules
3.2 Algorithm Used
3.3 Database
4 Result and Discussion
5 Conclusions
References
Finger Vein Biometric System Based on Convolutional Neural Network
1 Introduction
2 Related Work
3 Proposed System
3.1 Image Enhancement
3.2 Features Extraction
3.3 AES Encryption and Decryption
3.4 Convolution Neural Network
4 Result and Discussion
4.1 Image Enhancement
4.2 Feature Extraction
4.3 AES Encryption and Decryption
5 Conclusion
References
Embedding and Extraction of Data in Speech for Covert Communication
1 Introduction
2 Literature Survey
3 Existing Methodology
4 Proposed Methodology
5 Results and Evaluation
5.1 Results
5.2 Evaluation Metrics
6 Conclusion and Future Work
References
A Machine Learning Based Model for Classification of Customer Service's Email
1 Introduction
2 Problem Statement
2.1 Shared Inboxes Fail in Managing the Emails as the Number Grows
3 Proposed Solution
3.1 Advantages of Email Multi-folder Categorization for Better Customer Support
3.2 Email with Multi-folder Categorization Works Well with a Database System
3.3 Work Together to Solve Problems at a Fast Pace
3.4 Provide Support in the 100% Context
3.5 Measure Individual Performance with Intuitive Reports
3.6 Architecture of Automatic Classification of Email
4 Research Methodology
4.1 Classification of Email Using the Technique of Machine Learning
4.2 Machine Learning Terminologies Used in Classification
4.3 Support Vector Machine
4.4 Advantages and Disadvantages for Using Support Vector Machine
4.5 Validation Tool/Dataset Used
5 Results
6 Conclusion
7 Limitations and Future Scope
References
Intelligent Identification and Multiclass Segmentation of Agricultural Crops Problem Areas by Neural Network Methods
1 Introduction
2 Methods and Materials
3 Results and Discussion
3.1 Justification of the Segmentation DNN Architecture
3.2 Learning Outcomes Developed by DNN
3.3 Discussion of the Results
4 Conclusions
References
Perishable Products: Enhancing Delivery Time Efficiency with Big Data, AI, and IoT
1 Introduction
2 Delivery Time in Our Context
2.1 Optimizing Delivery Time in Transportation: Exploring Algorithmic Approaches
2.2 Objective
2.3 Advantage
2.4 Challenger
2.5 Delivery Time Description
3 The Proposed Optimization
3.1 Model System
3.2 The Proposed Optimization for Delivery Time
3.3 Specification Parameter
4 Optımızatıon Results Analysis
4.1 Comparing CT with Integrated Recent Transportation Technologies
4.2 Evaluation and Comparison of Optimization Results
5 Conclusion
References
CNN Approach for Identification of Medicinal Plants
1 Introduction
1.1 Motivation
1.2 Scope
2 Problem Statement
3 Literature Review
4 Proposed System
4.1 Dataset
4.2 Data Preprocessing
4.3 Pretrained CNN Architecture
5 Result and Discussion
6 Conclusion
References
OBSERVO: Teaching Strategy Recommendation by Monitoring Student Behavior Patterns
1 Introduction
1.1 Problem Statement
1.2 Aims
1.3 Competitive Analysis
2 Theoretical Background
2.1 Background Technology
2.2 Face Detection and Recognition
2.3 Concept Details
3 Methodology
3.1 Thermal Image Processing Algorithm
3.2 Face Detection and Recognition Algorithm
3.3 Database Training Algorithm
3.4 Image Behavior Pattern Analysis Algorithm
3.5 Algorithm to Generate Teaching Strategy
3.6 Behavior Pattern-Teaching Strategy Mapping Using Learning Styles
4 Results and Discussions
4.1 Haar Cascading
4.2 Recognition Rates
4.3 Behavior Analysis and Teaching Strategy Generation
5 Conclusion
References
Earthquake Magnitude and Depth Prediction Based on Hybrid GRU-BiLSTM Model
1 Introduction
1.1 Motivation
1.2 Contribution
1.3 Paper Organization
2 Related Work
3 Proposed Work
3.1 Preprocessing
3.2 Gated Recurrent Units
3.3 Bidirectional Long Short-Term Memory Networks
4 Experiment
4.1 Dataset
4.2 Model Architecture
5 Results and Analysis
6 Conclusion
References
Homomorphic Encryption to Improve Pharmaceutical Data Security on the Cloud and Blockchain
1 Introduction
2 Lıterature Survey
3 Workflow of the Proposed System
3.1 Paillier Cryptosystem Algorithm
3.2 Working of Paillier Algorithm
4 Proposed System
4.1 Methodology
4.2 Manager
4.3 Employee
4.4 AES Algorithm
5 Desıgn
5.1 Manager
5.2 Employee
6 Experımentatıon and Results
7 Conclusıon
References
Medical Reimbursement Prediction Using Artificial Intelligence
1 Introduction
2 Data Summary
3 Methodology
3.1 Ground Truth
3.2 Data Preparation and Transformation
3.3 Feature Selection
3.4 Model Development
3.5 Explainability Using SHAP
4 Results
5 Strengths
6 Conclusion
References
An Intelligent System for Plant Disease Diagnosis and Analysis Based on Deep Learning and Augmented Reality
1 Introduction
2 Related Work
3 Proposed System
3.1 Data Set Description
3.2 Feature Engineering
3.3 Augmented Reality
3.4 Barracuda Package
3.5 Vuforia SDK
3.6 Cloudinary
4 Methodology
4.1 Conventional Neural Network (CNN)
4.2 K-Nearest Neighbours (KNN)
4.3 Transfer Learning (InceptionV3)
5 Result and Discussion
6 Conclusion
7 Future Work
References
Power Balancing in Four-Wheel Drive EV Using Carrier-Based PWM with Two-Level Inverter Fed Drive
1 Introduction
2 PWM Control Techniques
3 Different PWM Techniques
3.1 Sinusoidal PWM Technique
3.2 Coupled PWM Technique
3.3 Decoupled PWM Technique
3.4 Carrier-Based PWM Technique
4 Two-Level Inverter Topology
5 Block Diagram for Proposed PWM Technique
6 Simulation and Results
7 Hardware Setup and Its Result
8 Conclusion
References
Breast Cancer Detection Using B-Mode and Ultrasound Strain Imaging
1 Introduction
2 Literature Survey
3 Methodology
3.1 Ensemble Model
3.2 Loss-Accuracy Curve
4 Results and Discussions
5 Conclusion
References
Prompt Engineering in Large Language Models
1 Introduction
1.1 Overview of Large Language Models (LLMs)
1.2 Importance of Prompt Engineering for LLMs
1.3 Research Objective and Motivation
2 Prompt Engineering
2.1 The Process of Prompt Engineering
3 Prompt Engineering Techniques
3.1 Techniques for Optimizing Prompts
3.2 Advanced Techniques for Prompt Engineering
3.3 Demonstration Tasks for Prompt Engineering
4 Applications, Tools, and Trends of Prompt Engineering
4.1 Applications and Tools
4.2 Current Research and Future Trends of Prompt Engineering
4.3 Current Research and Future Trends of Large Language Models (LLMs)
5 Conclusion
References
Activity Identification and Recognition in Real-Time Video Data Using Deep Learning Techniques
1 Introduction
1.1 Baseline: Single-Frame-Human Activity Recognition
1.2 Late Fusion
1.3 Early Fusion
1.4 Slow Fusion (3D CNN)
1.5 CNN-LSTM: Long Range Convolutional Network (LRCN)
1.6 Slow Fast Network
2 Literature Survey
3 Description of Data Sets and Experimental Set-Up
3.1 Methodology of Data Set Description
3.2 Implementation and Testing
4 Results and Discussion
5 Conclusion and Future Scope
References
Article Summarization Using Deep Learning
1 Introduction
1.1 Extractive Summarization
1.2 Abstractive Summarization
2 Literature Review
3 Design and Methodologies
3.1 Text Summarization
3.2 Converting Summarized Text into Speech
3.3 Text Paraphrasing
3.4 Conversion of Text to PPT
4 Proposed Methodology
5 Performance Anaysis
6 Conclusion
7 Future Enhancement
References
Knee Osteoarthritis Severity Prediction Through Medical Image Analysis Using Deep Learning Architectures
1 Introduction
2 Literature Survey
3 Methodology
3.1 Data Collection and Pre-processing
3.2 Model Selection
4 Results and Discussion
5 Conclusion
6 Future Work
References
Prediction of Harmful Algal Blooms Severity Using Machine Learning and Deep Learning Techniques
1 Introduction
2 Literature Survey
3 Existing Methodology
4 Proposed Methodology
4.1 Dataset Description
5 Satellite Images
6 Elevation Data
6.1 Data Extraction
6.2 Feature Engineering
6.3 Image Processıng
6.4 Proposed Model Buildıng
6.5 Evaluate Model Performance
7 Experimental Results
8 Conclusion
9 Future Works
References
Comparative Analysis of Classifier Algorithms Based on Sentimental Reviews
1 Introduction
2 Related Work
3 Proposed Methodology
4 Experimental Study
4.1 Data Set and Features Description
4.2 Feature Extraction
4.3 Classifier Algorithms
5 Results and Discussion
6 Conclusions
7 Future Scope
References
Enhancing Road Safety: A System for Detecting Driver Activity Using Raspberry Pi and Computer Vision Techniques with Alcohol and Noise Sensors
1 Introduction
2 Literature Survey
3 Methodology
3.1 Driver Exhaustion Detection Architecture
3.2 Video Capture
3.3 "Haar Cascade" Algorithm
3.4 Shape Predictor
3.5 Image Processing
3.6 Calculate EAR
3.7 Calculate MAR
3.8 Fatigue Detection with Face Detection and Features Extraction
3.9 Sound Detection
4 Conclusion
References
A Decision Support System for Prediction of Air Quality Using Recurrent Neural Network
1 Introduction
2 Literature Survey
3 Problem Analysis and Proposed Strategy
3.1 Data Preprocessing
3.2 Data Visualisation
3.3 LSTM Data Presentation
3.4 Fitting the Model
3.5 Evaluating the Model
4 Experimental Results
5 Conclusion
References
Trust Aware Distributed Protocol for Malicious Node Detection in IoT-WSN
1 Introduction
2 Proposed Methodology
2.1 TADP System Model
2.2 Trust Aware Distributed and Secure Data Aggregation
2.3 Trust Protocol Optimizes the Misclassification of Node Identification
2.4 Trust Aware Protocol to Detect the Malicious Node and Remove
3 Performance Evaluation
3.1 Identification
3.2 Misidentification
3.3 Throughput
3.4 Comparative Analysis
4 Conclusion
References
A Review on YOLOv8 and Its Advancements
1 Introduction
2 Existing Object Detection Models
3 Overview of YOLOv8
4 Architecture of YOLOv8
5 Architecture Components
6 Architectural Advancements
7 Training and Inference
7.1 Downloadable Python Package via Pip
8 Command Line Interface (CLI)
9 YOLOv8 Python SDK
10 YOLOv8 Tasks and Modes
11 User Experience (UX) Enhancements
12 Performance Evaluation
12.1 Object Detection Metrics
13 Benchmark Datasets and Computational Efficiency
14 Applications and Use Cases
15 Conclusion
References
Assistance for Visually Impaired People in Identifying Multiple Scenes Using Deep Learning
1 Introduction
2 Related Works
3 Methodology
4 Process
5 Result and Discussion
6 Conclusion
References
Identification of the Best Combination of Oversampling Technique and Machine Learning Algorithm for Credit Card Fraud Detection
1 Introduction
2 Literature Survey
3 Existing Model
4 Proposed Model
5 Working Methodology
6 Results and Discussions
7 Conclusion
References
Image-To-Image Translation Using Pix2Pix GAN and Cycle GAN
1 Introduction
2 Related Work
3 Methodology
3.1 Pix2Pix GAN
3.2 Cycle GAN
4 Implementation
4.1 Steps Involved in Implementing Pix2pix GAN
4.2 Steps Involved in Implementing Cycle GAN
5 Results
6 Conclusion and Future Scope
References

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Data Intelligence and Cognitive Informatics

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