Decision Intelligence

Name: Decision Intelligence | Proceedings of the International Conference on Information Technology, InCITe 2023, Volume 1
Brand: Springer
Price: 341.33 EUR
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Proceedings of the International Conference on Information Technology, InCITe 2023, Volume 1

B. K. Murthy B. V. R. Reddy Nitasha Hasteer Jean-Paul Van Belle(Editor)

Springer (Publisher)

1st Edition

Published on 24. November 2023

XII, 426 pages

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978-981-99-5997-6 (ISBN)

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Dr. B. K. Murthy is CEO of the Innovation and Technology Foundation at the Indian Institute of Technology (IIT) Bhilai. He was Scientist G and Group Coordinator (R&D in IT) in the Ministry of Electronics and IT (MeitY), Government of India, where he was responsible for the promotion of R&D in the area of IT. He has been conferred the prestigious VASVIK Industrial Research Award for the year 2020 in the category of Information and Communication Technology. He spearheaded bringing out the National Strategy on Blockchain Technology from the Ministry of Electronics and IT which was released in December 2021. His research interests include artificial intelligence, software-defined networking, cloud computing, quantum computing, and blockchain technologies. He was awarded his Ph.D. degree by IIT Delhi. He has published and

presented more than 70 papers in various journals and conferences and is a regular speaker at international forums.

Dr. B. V. R. Reddy is the Director of the National Institute of Technology (NIT) Kurukshetra. Earlier he served as Professor at the University School of Information & Communication Technology (USICT), GGSIP University, India, for 22 years. He possesses an excellent academic track record both as a teacher and as a researcher besides administrative acumen in technology areas of Information and Communication Technology (ICT). He has also served in various positions as Dean of School of Engineering and Technology (USET), Dean of University School of Information and Communication Technology (USICT), Dean of University School of Architecture and Planning (USAP), Chairman and Librarian for University Information Resource Centre (UIRC), served at national institutes of repute as Faculty at NIT Kurukshetra, NIT Hamirpur and an alumnus of Andhra University, IIT Roorkee and NIT Kurukshetra.

Dr. Nitasha Hasteer is Head of the Information Technology Department and Dy. Director (Academics) at Amity School of Engineering & Technology, Amity University, India. She has 21 years of teaching, research, and administrative experience in academics and industry and is a Ph.D. in Computer Science and Engineering. Her interest areas are machine learning, cloud computing, crowdsourced software development, software project management, and process modeling through multi-criteria decision-making techniques. She has published more than 60 papers in various journals and international conferences in these areas and has guided many postgraduate students in their dissertations. She has been on the editorial board of many international conferences and obtained funding from government agencies such as the Science and Engineering Research Board, Department of Science Technology (DST), Defence Research & Development Organization (DRDO), Indian National Science Academy (INSA), and Council of Scientific & Industrial Research (CSIR) for organizing conferences in the area of Information Technology.

Dr. Jean-Paul Van Belle is a Professor in the Department of Information Systems, University of Cape Town, South Africa. He has been Director of the Centre for IT and National Development in Africa (CITANDA). His particular research focus and passion is the adoption and appropriation of emerging ICTs in a development context, i.e., development informatics, ICT4D, and Mobile for Development (M4D). He is the Prime Investigator of the Future of Work in the Global South (FOWIGS) Fairwork Network project and the Fairwork South Africa project. His other research and teaching specializations are social networking, decision support, business analytics, open government data, E- & M-commerce, E- & M-government, organizational impacts and adoption of IS, Open-Source Software, IT/IS architectures, and artificial intelligence.

Content

Intro
Preface
Contents
About the Editors
A Radio Frequency-Based Energy Harvesting Model for IoMT Device
1 Introduction
1.1 Contribution
2 Related Works
3 Proposed Model
3.1 RFEH Model
3.2 RFEH-IoMT Model
4 Performance Analysis
5 Conclusion
References
Cancer Hotspot Identification and Analysis: A Scan Statistics Approach
1 Introduction
1.1 Research Problem
1.2 Related Work
2 Relevance
3 Objective
4 Data Design and Processing
5 Methodology Adopted
5.1 Hotspot Analysis
5.2 Welch's T-test
6 Spearman's Rank Correlation Coefficient (rs)
7 Results and Discussion
7.1 Hotspot Detection
7.2 Descriptive Approach
8 Conclusion
9 Limitations
10 Scope for Future Research
References
An Artificial Voice Box that Makes Use of Unconventional Methods of Machine Learning
1 Introduction
2 Related Work
3 Materials and Methods
3.1 Neuro Decoder
3.2 Artificial Voice Box
4 Conclusion
References
State-of-Art Review on Medical Image Classification Techniques
1 Introduction
2 Image Pre-processing Techniques for Medical Images
2.1 Image Filtering
2.2 Segmentation
3 Feature Selection and Feature Extraction
4 Classification Techniques
4.1 Using Traditional Classifiers
4.2 Using Deep Learning Algorithms
5 Conclusion
References
Prediction of Loan Approval of Customers Based on Credit Score Using Machine Learning
1 Introduction
2 Motivation
3 Literature Survey
4 Methodology
4.1 Dataset
4.2 Credit Score
4.3 Pre-processing
4.4 Logistic Regression
4.5 K-Nearest Neighbour
4.6 Decision Tree
4.7 Random Forest
4.8 Linear Discriminant Analysis
5 Result Analysis
6 Conclusion and Future Scope
References
Strategies for the Adoption of AI Technologies in the South African Wine and Fruit Industries
1 Introduction
2 Literature Review
2.1 AI Technologies for the SA Agricultural Sector
2.2 Barriers and Challenges of Adopting AI Technologies in Agriculture
3 Research Design and Methodology
4 Findings and Discussion
4.1 Current AI Technologies in Agricultural Processes
4.2 Challenges of Adopting AI Technologies
4.3 Strategies to Facilitate the Adoption of AI Technologies in Agriculture
5 Conclusion
References
Real-Time Facial Mask Detection Using Deep Learning
1 Introduction
2 Related Work
3 Methodology
3.1 Data Collection
3.2 Model
3.3 Training
4 Result
5 Limitations
6 Conclusion and Future Scope
References
SSATS-Enhancement of Semantic Similarity of Abstractive Text Summarization Using Transformer
1 Introduction
2 Key Contributions
3 Literature Survey
4 Proposed Methodology
5 Experiments
5.1 Dataset
5.2 Metrics
6 Results and Discussion
7 Conclusion and Future Work
References
Semantic Segmentation of Optical Satellite Images
1 Introduction
2 Evaluation Metric
3 Related Work
4 Comparison Between State-of-the-Art Methods
5 Future Work and Challenges
6 Conclusion
References
Human Gender and Age Estimator Using Local and Global Features with Machine Learning
1 Introduction
2 Literature Survey
3 Methodology
3.1 Data Acquisition
3.2 Pre-processing
3.3 Face Detection
3.4 Adaboost Algorithm
3.5 Feature Extraction
3.6 HOG Descriptors-Histogram of Oriented Gradients
3.7 LBP-Local Binary Pattern
3.8 Feature Reduction Using PCA
3.9 Principle Component Analysis (PCA)
3.10 SVM-Support Vector Machine Classifier
4 Experimental Results
4.1 Training and Testing
5 Conclusion
References
Predictive Analysis of Neurodegenerative and Chronic Fatigue Disease
1 Introduction
1.1 Literature Review
2 Methodology
References
An Automatic Early Alert System on Detecting Dozing Driver
1 Introduction
2 Related Research Work
3 Proposed Methodology
3.1 Facial Landmark Identification
3.2 Eye Closing Detection
3.3 Yawning Detection
3.4 Alert
4 Experimental Results
5 Conclusion
References
Reversible Image Steganography to Achieve Effective PSNR
1 Introduction
2 Literature Review
3 Methodology
3.1 Reversible Image Steganography Methods for Compressed Images
3.2 Reversible Steganography Methods for Coded Images
3.3 High-Capacity Techniques for Reversible Image Steganography
3.4 Performance Study for Reversible Image Steganography
4 Experimental Results
5 Conclusion
References
EDA and Predicting Customer's Response for Cross-Sell Vehicle Insurance
1 Introduction
2 Literature Review
2.1 Why ML in Insurance
2.2 Related Work
3 Data Collection and Understanding
4 Work Flow and Framework of the Proposed Analysis
5 Data Preparation
6 Techniques Employed
7 Results and Discussion
8 Conclusion and Future Work
References
A Study of Feature-Based and Pixel-Level Image Fusion Techniques
1 Introduction
2 Pixel Fusion
3 Feature Level
4 Discrete Wavelet Transform
5 C-Mean Fuzzy Clustering
6 The Proposed Model
7 Performance Measures
7.1 Standard Deviation (SD)
7.2 Entropy (En)
7.3 Signal-to-Noise Ratio (SNR)
7.4 Deviation Index (DI)
8 Results
9 Conclusion
References
Catch Your Session, Track Your Pulse e-Health Service Using Blockchain
1 Introduction
2 Literature Survey
3 Methodology
4 Proposed System
5 Architecture System
5.1 Patient information management Module
5.2 Slot Booking Module
6 Results and Analysis
7 Conclusion
References
Ansuni Baat-A Bridge to Sign Language Communication
1 Introduction
1.1 Aim and Features
1.2 Background of the Study
2 Literature Review
3 System Analysis
3.1 Software Requirement Specification
3.2 Flow Diagram for the System
4 Methodology
4.1 Front-end
4.2 Back-end
4.3 Database
5 Result
6 Conclusion
7 Future Scope
References
A Review of Deep Learning Algorithms for Early Detection of Oral Mouth Cancer
1 Introduction
2 Research Approach
2.1 Research Question
2.2 Data Source
2.3 Paper Selection Criteria
3 Findings
4 Future Challenges
5 Conclusion
References
Malware Detection Using Deep Learning
1 Literature Review
2 Linear Regression
3 Types of Malwares
3.1 Virus
3.2 Worm
3.3 Trojan Horse
3.4 Spyware
3.5 Rootkit
4 Malware Detection
4.1 Anomaly Detection
4.2 Signature Detection
4.3 Specification-Based Detection
5 Botnet
5.1 How Botnet Attacks IoT Devices
5.2 Feature Selection
6 Algorithms Used
6.1 Logistic Regression
6.2 F1 Score
6.3 Epoch
6.4 KERAS
6.5 Standardization
7 Attributes of Datasets Used in the Project
7.1 KNN
7.2 Decision Tree
7.3 ANN
7.4 Logistic Regression
7.5 Naïve Bayes
7.6 SVM
8 Conclusion
References
Automatic Title Generation with Attention-Based LSTM
1 Introduction
1.1 Motivation and Justification of Automatic Title Generation
1.2 Contribution of the Proposed Work
2 Related Work
3 Proposed Methodology
3.1 Sequence-to-Sequence (Seq-to-Seq) Model
3.2 Seq-to-Seq Model Components
4 Experimental Setup and Result
4.1 Data Collection
4.2 Data Preprocessing
4.3 Train the Processed Data Using the Seq-to-Seq Model
5 Conclusion of the Proposed Work and Future Work
References
COVID-19 (COV-19) Spreading Diagnoses by Feature Representation Method Through Visual Learning (FVisL-CoV19)
1 Introduction
2 Related Works
3 Proposed Model
3.1 Feature Illustration of Visible-Learning-Methodology (FVisL-CoV19)
3.2 CoV19 Spreading Diagnoses Algorithm
4 Results and Discussions
4.1 Dataset Evaluation
4.2 Evaluation Metrics
4.3 Results
5 Conclusions
References
Alzheimer's Disease Classification Using Deep Learning Models
1 Introduction
2 Literature Survey
3 Proposed Work
3.1 Input
3.2 Data Pre-processing
3.3 Model Building
4 Results and Discussion
5 Conclusion
References
Brain Pathology Detection Using Convolutional Neural Network from EEG Signal
1 Introduction
2 Related Works
3 Methodology and Design
4 Implementation and Results
5 Conclusion
References
CNN-Based Adversarial Embedding for Image Steganograpy
1 Introduction
2 Literature Review
3 Methods
3.1 Existing Methods
3.2 Proposed Methods
4 Result and Discussion
5 Conclusion
References
Machine Learning Approaches for Entity Extraction from Citation Strings
1 Introduction
2 Related Work
2.1 Non-machine Learning based Approaches
2.2 Machine Learning based Approaches
2.3 Limitations of Machine Learning based Approaches
2.4 Combination of Machine Learning and non-Machine Learning methods
3 Comparative Analysis
4 Conclusion
5 Future Scope
References
A Survey on Brain Tumor Segmentation with Missing MRI Modalities
1 Introduction
2 Methodologies
2.1 Common Latent Space
2.2 Knowledge Distillation Network
2.3 Mutual Information Maximization
3 Dataset
4 Evaluation Metrices
5 Experimental Analysis
6 Conclusion and Future Work
References
Deep Learning Based Segmentation Approach for Cervical Cancer Detection Using Pap Smears
1 Introduction
2 Literature Review
3 Methodology
3.1 Dataset
3.2 Data Augmentation
3.3 Data Pre-Processing
3.4 Data Augmentation
3.5 Segmentation
3.6 Performance Measures
3.7 Proposed Method
4 Result
4.1 Segmentation of Cervical Class
5 Conclusion
References
Hybrid Sign Language Interpreter Development Using Machine Learning Approach
1 Introduction
2 Literature Review
3 Research Gaps and Queries
4 Research Methodology
4.1 Implementation of the Methodology
4.2 Threats to Validity
5 Result Outcome
6 Conclusion and Future Scope
References
Community Detection Algorithms in Social Networks: An Empirical Evaluation
1 Introduction
2 Community Detection Algorithms and Measures
2.1 Community Detection Algorithms
2.2 Evaluation Measures
3 Results and Discussion
3.1 Datasets
3.2 Experimental Setup
3.3 Results
3.4 Discussion
4 Conclusion
References
Designing Hybrid Image Fusion Algorithm Using CNN and Stationary Wavelet Transform
1 Introduction
1.1 Spatial Based
1.2 Transform Based
2 Literature Review
3 Methodology
4 Experiments and Results
5 Conclusion
References
Predict Pawpularity Score of Pets Using State of Art Algorithms
1 Introduction
2 Literature Survey
3 Methodology
3.1 Data Exploration
3.2 Model Fitting
3.3 Models Used
4 Conclusion and Future Scope
References
Comparative Analysis of Balanced Code Smell Detection Using Machine Learning
1 Introduction
2 Literature Survey
3 Research Methodology
3.1 Dataset
4 Results and Discussion
5 Conclusions
References
ETL Data Pipeline to Analyze Scraped Data
1 Introduction
2 Literature Review
3 Proposed Method
4 Data Visualization in Power BI
References
DDoS Attack Detection Using Machine Learning
1 Introduction
2 Literature Review
3 Methodology
3.1 Dataset Description
3.2 Dataset Preprocessing
4 Results
5 Conclusion
References
An Empirical Study to Investigate Class Imbalance Issue for Improving Security Bug Report Classification Prediction
1 Introduction
2 Related Work
2.1 Security Bug Report Classifications
3 Methodology
3.1 Data-Preprocessing
3.2 Class Balancing Technique
3.3 Classifier Model
3.4 Performance Measure
4 Result and Analysis
5 Threats to Validity
6 Conclusion and Future Scope
References
Factors Influencing the Use of a Soccer Team's Mobile Application by Fans in South Africa
1 Introduction
2 Literature Review
2.1 Mobile Applications in Sports
2.2 Impact of the Covid-19 Pandemic on the Sports Industry
2.3 Sport Fan Experience in Developed Versus Developing Countries
3 Research Model and Hypotheses
4 Research Design and Methodology
5 Data Analysis
5.1 Descriptive Statistics
5.2 Model Testing
6 Conclusion
References

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Decision Intelligence

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