Multi-disciplinary Trends in Artificial Intelligence: 16th International Conference, MIWAI 2023, Hyderabad, India, July 21–22, 2023, Proceedings (Lecture Notes in Computer Science, 14078)

Preface
Organization
Contents
Digital Life: An Advent of Transhumanism
	1 Introduction
	2 Digital Human
	3 Agent Theory
	4 Agent Society
	5 Diginatives
	6 Digital Life and Afterlife
	7 Digital World Making
	8 Conclusion
		8.1 Transhumanism
	References
Heuristics for K-Independent Average Traveling Salesperson Problem
	1 Introduction
	2 Formal Problem Definition
	3 Proposed Heuristics
		3.1 Constructive Heuristic No. 1 (C1)
		3.2 Constructive Heuristic No. 2 (C2)
		3.3 Constructive Heuristic No. 3 (C3)
		3.4 Constructive Heuristic No. 4 (C4)
		3.5 Constructive Heuristic No. 5 (C5)
		3.6 Constructive Heuristic No. 6 (C6)
		3.7 Constructive Heuristic No. 7 (C7)
	4 Computational Results
	5 Conclusions
	References
Book Recommendation Using Double-Stack BERT: Utilizing BERT to Extract Sentence Relation Feature for a Content-Based Filtering System
	1 Introduction
	2 Proposed Method
		2.1 Dataset
		2.2 First Stack: Feature Extraction
		2.3 Second Stack: RoBERTa
		2.4 Recommendation System
	3 Results and Discussions
		3.1 Model Testing
		3.2 Recommendation Result
	4 Conclusion
	References
Evaluating the Utility of GAN Generated Synthetic Tabular Data for Class Balancing and Low Resource Settings
	1 Introduction
	2 Literature Review
		2.1 Synthetic Data Using SMOTE and ADASYN
		2.2 Synthetic Data for Images and Text
		2.3 Synthetic Data for Tabular Data Using Generative Models
	3 Research Methodology
		3.1 Dataset Description
		3.2 Data Pre-processing
		3.3 GAN Training
		3.4 Data Modelling
	4 Results
		4.1 Assessment of GAN Synthetic Data Quality
		4.2 Results on the Utility of Synthetic Data in Class Balancing
		4.3 Low Resource Setting – Random Forest Results
	5 Conclusion
	References
How Good are Transformers in Reordering?
	1 Introduction
	2 Related Work
	3 Experiments
		3.1 Dataset and Preprocessing
		3.2 Training
		3.3 Evaluation
		3.4 Results
	4 Conclusions
	References
Automatic Differentiation Using Dual Numbers - Use Case
	1 Introduction
		1.1 Automatic Differentiation
		1.2 Dual Numbers
	2 AD with Dual Numbers
	3 DNN with Dual Numbers
	4 Sensitivities of Sensors in Thermal Power Plants
		4.1 Thermal Power Plant Parameter Sensitivity Using Dual Numbers
	5 Conclusions
	References
On Some Properties of a New PoisN Wavelet Family
	1 Introduction
	2 Continuous Wavelet Transform
	3 New Continuous Wavelet Family Generated from Poisson Kernel
	4 Properties of the Proposed New Wavelet Family
		4.1 Support, Symmetry and Regularity
		4.2 Vanishing Moments
		4.3 Frequency Decay
		4.4 Time-Frequency Bandwidth
	5 Continuous Wavelet Transform Of Gaussian Distribution with the New Wavelet
		5.1 Effect on Wavelet Coefficients of Gaussian Function
	6 Conclusion
	References
Centrality Measures Based Heuristics for Perfect Awareness Problem in Social Networks
	1 Introduction
	2 Related Work
	3 Centrality Based Heuristics
		3.1 Computing Potential Seed Set
		3.2 Pruning of Potential Seed Set
	4 Results and Discussion
	5 Conclusion
	References
Re-examining Class Selectivity in Deep Convolutional Networks
	1 Introduction
	2 Related Work
		2.1 Motivation and Contributions
	3 Role of Class Selectivity
		3.1 Layerwise Class Selectivity
		3.2 Activation Orthogonality
	4 Experiments and Results
		4.1 Class Selectivity with k and SI
		4.2 Layerwise Decomposability
		4.3 Interpreting the Results
	5 Discussion and Future Work
	References
Content Based Network Representational Learning for Movie Recommendation (CNMovieRec)
	1 Introduction
	2 Related Work
		2.1 Network Representation Learning (NRL)
	3 CNMovieRec
		3.1 Deep-CNMovieRec
	4 Experimental Results (CNMovieRec)
	5 Group Recommender System
		5.1 Experimental Results
	6 Conclusions and Future Work
	References
Parallel and Distributed Query Processing in Attributed Networks
	1 Introduction
	2 Preliminary Concepts and Related Work
	3 DSRQ_AN Approach
		3.1 Illustrations
		3.2 Query Reachability Processing
	4 MQP_PD Approach in Parallel and Distributed Environments
	5 Performance Evaluation
	6 Conclusions and Future Work
	References
Gradient Directional Predictor for Reconstructing High-Fidelity Images
	1 Introduction
	2 Gradient Based Prediction
	3 Embedding and Extraction
	4 Experimental Results
	5 Conclusion
	References
We Chased COVID-19; Did We Forget Measles? - Public Discourse and Sentiment Analysis on Spiking Measles Cases Using Natural Language Processing
	1 Introduction
	2 Methods
		2.1 Study Design
		2.2 Data Preparation and Measures
		2.3 Data Analysis
	3 Findings
	4 Discussion
		4.1 Limitations
	5 Conclusions
	References
Swarm Learning for Oncology Research
	1 Introduction
	2 Related Work
	3 Experiments, Data Availability and Split
		3.1 Data Splitting
	4 Implementation
		4.1 Neural Network Model for Prediction Using Gross Parameters from WDBC Dataset
		4.2 Neural Network Model for Recurrence Using Gross Parameters from WPBC Dataset
		4.3 Residual Network Model for Prediction Using Images from the BreakHis Dataset
	5 Results and Discussion
	6 Conclusion and Future Work
	References
A Review on Designing of Memory Computing Architecture for Image Enhancement in AI Applications
	1 Introduction
	2 Literature Review
		2.1 Problem Identification and Formulation
		2.2 Memristor-Based In-Memory Computing Architecture for RSR
		2.3 Device Physics Memristor
		2.4 Performance Assessment and Discussions
		2.5 Memory Access
	3 Conclusion
	References
Shufflenetv2: An Effective Technique for Recommendation System in E-Learning by User Preferences
	1 Introduction
	2 Literature Survey
	3 Proposed Methodology
		3.1 Data Gathering
		3.2 ResNet-152 for Feature Extraction
		3.3 ShuffleNet V2 for Classification
		3.4 Modified Butterfly Optimization Algorithm (MBOA)
	4 Results and Discussion
		4.1 Dataset Description
		4.2 Evaluation Metrics
		4.3 Performance Metrics
		4.4 Analysis of Computation Time
		4.5 Evaluation of Training Results
	5 Conclusion
	References
A Multi-modal Approach Using Game Theory for Android Forensics Tool Selection
	1 Introduction
	2 Related Work
	3 Experimental Setup
		3.1 Dataset
		3.2 Android Forensics Tools
	4 Multi-arm Bandits Problem
		4.1 ϵ-greedy Algorithm
		4.2 Upper Confidence Bound
		4.3 LinUCB
	5 Decision Tree Creation and Application of Game Theory
		5.1 Decision Tree Creation
		5.2 Game Theory Approaches
		5.3 Pay-off Calculation
		5.4 Applying Mixed Strategy Nash Equilibrium
	6 Comparisons and Results
	7 Conclusion
	References
LPCD: Incremental Approach for Dynamic Networks
	1 Introduction
	2 Related Work
	3 LPCD Incremental Approach
		3.1 Illustration of Updating the Communities
		3.2 Description of Proposed Algorithm
	4 Experimental Results
	5 Result Analysis
	6 Conclusions and Future Work
	References
Clinical Abbreviation Disambiguation Using Clinical Variants of BERT
	1 Introduction
	2 Literature Review
	3 Methodology
		3.1 Dataset
		3.2 Working of the BERT Architecture
		3.3 Why BERT Variants?
	4 Results
		4.1 Why ClinicalBERT Performed the Best?
	5 Conclusion
	References
Ontological Scene Graph Engineering and Reasoning Over YOLO Objects for Creating Panoramic VR Content
	1 Introduction
	2 Motivation
	3 Related Works
	4 Ontological Scene Graph Engineering and Reasoning for creating panoramic VR content
	5 Experimental Results and Discussion
	6 Concluding Remarks and Future Directions
	References
Incremental Classifier in the Semi Supervised Learning Environment
	1 Introduction
	2 Related Work
	3 Incremental Classifier Framework
		3.1 LC-INC Module
		3.2 Identification of New Class
		3.3 Maintain Buffer
		3.4 Clustering Approach
		3.5 Incremental Classifier Algorithm
	4 Experimental Results
	5 Conclusions and Future Work
	References
Alzheimer\'s Detection and Prediction on MRI Scans: A Comparative Study
	1 Introduction
	2 Related Work
	3 Deep Learning and MRI Classification
		3.1 Classification of Diseases Using Deep Learning
		3.2 Evaluation Criteria
		3.3 Methodology
	4 Results
		4.1 Limitations
	5 Conclusion
	References
Evaluating the Performance of Diverse Machine Learning Approaches in Stock Market Forecasting
	1 Introduction
		1.1 Fundamental Analysis
		1.2 Technical Analysis
	2 Literature Review
	3 Materials and Methods
		3.1 Data
		3.2 Exploratory Data Analysis (EDA)
		3.3 Algorithm Selection
	4 Results
		4.1 Time Series Models
		4.2 Tree-Based Models
		4.3 Deep Learning Models
		4.4 Regression Models
		4.5 Model Performance Summary
	5 Discussion
		5.1 Models Performance
	6 Future Work and Conclusions
	References
A Blockchain-Driven Framework for Issuance of NFT-Based Warranty to Customers on E-Commerce
	1 Introduction
	2 Existing System
		2.1 Deficiencies of Existing System
	3 Proposed Scheme
	4 Implementations
		4.1 Technology Stack Used
		4.2 Designing Smart Contract
		4.3 Integration
	5 Experimental Evaluation and Results
		5.1 Experimental Evaluation
		5.2 Architecture of Proposed System
		5.3 Feature Analysis
	6 Conclusion
	References
Using Machine Learning Models to Predict Corporate Credit Outlook
	1 Introduction
	2 Literature Survey
	3 Models
		3.1 Support Vector Machines (SVM) Model
		3.2 AdaBoost (Adaptive Boosting) Model
		3.3 Gradient Boosting Model
	4 Data and Variables
	5 Empirical Results
	6 Summary and Conclusions
	References
Visualization Recommendation for Incremental Data Based on Intent
	1 Introduction
	2 Related Work
	3 Incremental Visualization Recommendation (IVR)
		3.1 Introduction
		3.2 Workflow Description
		3.3 Algorithm Description
		3.4 Comparison Between Traditional and Proposed Approach
		3.5 Illustrations
	4 Discussions and Experimental Results
		4.1 Experimental Results
		4.2 Analysis of the Results
	5 Conclusions and Future Work
	References
Automating Malaria Diagnosis with XAI: Using Deep-Learning Technologies for More Accurate, Efficient, and Transparent Results
	1 Introduction
	2 Related Work
	3 Methodology
	4 Results and Discussion
	5 Conclusion
	References
Artificial Intelligence as a Service: Providing Integrity and Confidentiality
	1 Introduction
		1.1 Evolution of AI as a Service
	2 Proposed Mechanism
		2.1 Proposed Enhanced Quadratic Chaotic-Map Algorithm
		2.2 Proposed Hash-Based Homomorphism AB Encryption Model
	3 Results and Comparative Study
	4 Conclusion
	References
Live Bidding Application: Predicting Shill Bidding Using Machine Learning
	1 Introduction
	2 Literature Survey
	3 Methodology
		3.1 Problem Statement
		3.2 Methodology to Forecast Shill Bidding
	4 Algorithms Used for Modelling
		4.1 Support Vector Machine Algorithm
		4.2 Decision Tree Algorithm
	5 Results and Discussion
	6 Conclusion and Future Scope
	References
A Novel Pixel Value Predictor Using Long Short Term Memory (LSTM) Network
	1 Introduction
	2 Proposed LSTM Network Based Pixel Value Predictor
		2.1 Criterion for Considering Neighborhood
		2.2 LSTM Architecture for Pixel Value Prediction
	3 Experimental Setup and Results
	4 Conclusion
	References
Efficient Trajectory Clustering of Movements of Moving Objects
	1 Introduction
	2 Problem Definition
	3 Trajectory Data Clustering Methodology
		3.1 The Need
		3.2 The Framework
	4 Algorithm
	5 Example for Trajectory Data Clustering
	6 Conclusions
	References
Node Cooperation Enforcement Scheme for Enhancing Quality of Service in MANETs Using Machine Learning Approach
	1 Introduction
	2 Related Work
	3 Node Cooperation Enforcement Scheme
		3.1 COPRAS
		3.2 Predicting NODE’s Cooperation Degree
	4 Simulation Results and Discussion
	5 Conclusion
	References
Interpreting Chest X-Ray Classification Models: Insights and Complexity Measures in Deep Learning
	1 Introduction
	2 Insights on Different Complexity Measures
		2.1 Function-Space Complexity Measures: Norm Based Complexity Quantification
		2.2 Classical Statistical and Computational Complexity Measures
		2.3 Effective Model Complexity and Double Descent
	3 Proposed Work
		3.1 Data Modeling
		3.2 Increasing Number of Training Epochs: Setting 1
		3.3 Increasing Model Complexity: Setting 2
		3.4 Variants of Optimizer: Setting 3
		3.5 Results
		3.6 Discussions
	4 Conclusion
	References
Nuclei Segmentation Approach for Computer Aided Diagnosis
	1 Introduction
	2 Literature Survey
	3 Material and Methods
		3.1 Setup
		3.2 Exploratory Analysis
	4 Base Model and Architecture
		4.1 Binary Classification - Identifying Presence of Nuclei
		4.2 Multi Class Classification - Nuclei Cell Feature Identification
		4.3 Results and Evaluation
	5 Discussion and Conclusions
	References
Stock Market Intraday Trading Using Reinforcement Learning
	1 Introduction
	2 Literature Review
	3 Problem Statement
	4 Methodology
		4.1 Problem Definition
		4.2 Environment
		4.3 Training
		4.4 Process Flow
	5 Observations and Results
	6 Conclusion
	References
Predicting the Droughts Using Artificial Neural Networks – A Case Study
	1 Introduction
	2 Study Area
	3 Methodology
		3.1 Standardized Precipitation Index
	4 Result and Discussions
		4.1 Pre-monsoon Groundwater Gujarat, Daman, and Diu
	5 Conclusions
	References
Applying Machine Learning for Portfolio Switching Decisions
	1 Introduction
	2 Literature Survey
	3 Methodology
		3.1 Datasets and Handling Missing Values
		3.2 Feature Selection
		3.3 Training the Model
		3.4 Classifiers
		3.5 Metrics for Performance Evaluation
	4 Results
	5 Conclusion
	References
Bark Texture Classification Using Deep Transfer Learning
	1 Introduction
	2 Literature Work
	3 Materials
		3.1 Dataset
		3.2 Pre-processing and Splitting
	4 Proposed Model
	5 Experimental Results
		5.1 Results and Discussion
	6 Conclusion and Future Scope
	References
Dynamic Twitter Topic Summarization Using Speech Acts
	1 Introduction
	2 Related Work
	3 Experimental Setup
	4 Experimental Results
	5 Conclusion
	References
Generative Adversarial Network for Augmenting Low-Dose CT Images
	1 Introduction
	2 Related Work
	3 Proposed Approach
		3.1 Reconstruction
		3.2 Discriminator
		3.3 Generator
	4 Experimental Results
		4.1 Dataset Used in the Experiment
		4.2 Data Loader
	5 Performance Analysis
	6 Conclusion
	References
Improving Software Effort Estimation with Heterogeneous Stacked Ensemble Using SMOTER over ELM and SVR Base Learners
	1 Introduction
	2 Related Work
	3 Proposed Methodology
		3.1 Data Preparation
		3.2 Ensemble Learning
	4 Results and Evaluation
	5 Conclusion and Future Scope
	References
A Deep Learning Based Model to Study the Influence of Different Brain Wave Frequencies for the Disorder of Depression
	1 Introduction
	2 Related Work
	3 Methodology
		3.1 Dataset
		3.2 Pre-processing
		3.3 Experimental Design
		3.4 Hardware and Software
	4 Results and Discussion
	5 Conclusion and Future Work
	References
Planning Strategy of BDI Agents for Crowd Simulation
	1 Introduction
	2 Background
		2.1 Personality Models and Trait Theory Review
		2.2 Behavior Perception User Study Background
		2.3 Emulating Traits
		2.4 Data Analysis
	3 Our BDI Agent
	4 Experiments
		4.1 Pass-Through Scene Results
		4.2 Hallway Scenario Results
		4.3 Narrow Passage Scene Results
		4.4 Timing Results
	5 Conclusion
	References
Design and Development of Walking Monitoring System for Gait Analysis
	1 Introduction
	2 Literature Survey
	3 Phases of Gait Cycle
	4 Proposed Work
	5 Results and Analysis
	6 Conclusion
	References
Stock Market Investment Strategy Using Deep-Q-Learning Network
	1 Introduction
	2 Related Work
	3 Data
	4 Proposed Method
		4.1 Components in the Proposed Method
		4.2 External Prediction
		4.3 GRU Layers
		4.4 Stop-Loss Strategy
	5 Experimental setup/Results
		5.1 Training Process Workflow in Step by Step
		5.2 Testing Process
		5.3 Result
	6 System Overview
	7 Conclusion
	References
A Survey on Recent Text Summarization Techniques
	1 Introduction
	2 Methodologies
		2.1 Extractive Text Summarization Methodologies
		2.2 Abstractive Text Summarization Methodologies
		2.3 Reinforcement Learning Methodologies
	3 Conclusion and Future Work
	References
Conversational AI: A Study on Capabilities and Limitations of Dialogue Based System
	1 Introduction
	2 Literature Survey
	3 Materials and Methods
	4 Results
	5 Discussion
	6 Conclusion
	References
Co-clustering Based Methods and Their Significance for Recommender Systems
	1 Introduction
	2 Automated Recommender Systems
		2.1 Collaborative Filtering
		2.2 Content Based Filtering
	3 Co-clustering Approaches
		3.1 Semi-supervised Clustering
		3.2 Nonnegative Matrix Factorization
		3.3 Unsupervised Harmonic Co-clustering
		3.4 Distributed Co-clustering Framework
		3.5 Co-clustering Based on Feature Co-shrinking
		3.6 Goal Oriented Co-clustering
		3.7 Bipartite Graphs for Co-clustering
		3.8 Co-clustering of Big Data
	4 Summary of Findings
	5 Datasets
	6 Research Gaps
	7 Conclusion and Future Wor
	References
Machine Learning and Fuzzy Logic Based Intelligent Algorithm for Energy Efficient Routing in Wireless Sensor Networks
	1 Introduction
	2 Related Works
	3 Proposed Methodology
	4 Results and Discussions
	5 Conclusion
	References
Sentiment Analysis of Twitter Data on ‘The Agnipath Yojana’
	1 Introduction
		1.1 Agnipath Scheme
	2 Methodology
		2.1 Data Collection
		2.2 Sentiment Identification
		2.3 Topic Modeling
	3 Results
	4 Conclusion and Future Work
	References
Pixel Value Prediction Task: Performance Comparison of Multi-Layer Perceptron and Radial Basis Function Neural Network
	1 Introduction
	2 Pixel Prediction Task: Definition
		2.1 Considered Pixel Neighborhood
		2.2 Pixel Selection Criteria
	3 Neural Network Based Pixel Value Predictors
		3.1 Multi-Layer Perceptron (MLP) Based Pixel Value Predictor
		3.2 Radial Basis Function (RBF) Neural Network Based Pixel Value Predictor
	4 Experimental Setup and Results
		4.1 Experimental Setup
		4.2 Comparison of Pixel Prediction Performance
	5 Conclusion
	References
A Yolo-Based Deep Learning Approach for Vehicle Class Classification
	1 Introduction
	2 Literature Review
		2.1 Previous Work
	3 Architecture for Vehicle Classification
		3.1 Proposed Algorithm
	4 Results and Discussion
		4.1 Phase I: Local Platform
		4.2 Phase II: Cloud Platform
		4.3 Classification of Other Models
		4.4 Comparison with Other Models
	5 Conclusion
	References
Rescheduling Exams Within the Announced Tenure Using Reinforcement Learning
	1 Introduction
	2 Motivation
	3 Related Works
	4 Exam Timetabling Problem as a Markov Decision Process
	5 Implementation of the Examination Scheduling and Rescheduling Using Reinforcement Learning
		5.1 Learning Exam Schedule Instance as a Policy Using Bellman Equation with Temporal Difference Learning (TDL)
		5.2 Learning the Rescheduled Examination Slot as an Optimal Policy Using Bellman Equation with Temporal Difference Learning
	6 Experimental Setup with Results and Discussions
	7 Conclusion and Future Work
	References
AI Based Employee Attrition Prediction Tool
	1 Introduction
	2 Detailed Solution
	3 Conclusion and Future Directions
		3.1 USPs of Our Solution
	Appendix: COST SUMMARY TO CLIENT
	References
iSTIMULI: Prescriptive Stimulus Design for Eye Movement Analysis of Patients with Parkinson\'s Disease
	1 Introduction
	2 Related Work
	3 iSTIMULI
		3.1 Image Stimuli Design
		3.2 Eye Tracking Experiment
		3.3 Classification of PD Patients Using Machine Learning
		3.4 Visualization
	4 Results and Discussions
	5 Conclusion and Future Scope
	References
EduKrishnaa: A Career Guidance Web Application Based on Multi-intelligence Using Multiclass Classification Algorithm
	1 Introduction
	2 Literature Review
	3 Proposed Methodology
		3.1 Test Modules
		3.2 Prediction Module
		3.3 Result Module
		3.4 Recruiter Module
	4 Results
	5 Conclusion and Future Work
	References
Multi-dimensional STAQR Indexing Algorithm for Drone Applications
	1 Introduction
		1.1 Spatial Temporal Data
	2 Related Work
	3 Results and Analysis
	4 Conclusion and Future Work
	References
Low Light Image Illumination Adjustment Using Fusion of MIRNet and Deep Illumination Curves
	1 Introduction
	2 Literature
	3 Proposed Model
		3.1 MIRNet
		3.2 Deep Illumination Curves
	4 Results and Discussion
		4.1 MIRNet Model
		4.2 Deep Illumination Curve Model
		4.3 Combined Model Results
	References
A Hybrid Intelligent Cryptography Algorithm for Distributed Big Data Storage in Cloud Computing Security
	1 Introduction
	2 Literature Survey
	3 Hybrid Intelligent Cryptography
	4 Result Analysis
	5 Conclusion
	References
An Ensemble Technique to Detect Stress in Young Professional
	1 Introduction
	2 Proposed Approach
		2.1 Methodology
		2.2 Proposed Solutions
	3 Implementation and Experimental Results
		3.1 Datasets Used
		3.2 Experimental Setup
		3.3 Performance Parameters
		3.4 Discussion
	4 Conclusion
	References
iAOI: An Eye Movement Based Deep Learning Model to Identify Areas of Interest
	1 Introduction
	2 Related Work
	3 iAOI
		3.1 Recording Eye Movements
		3.2 Deep Learning Analysis
		3.3 Visualization
	4 Results and Discussions
	5 Conclusion and Future Scope
	References
Traffic Prediction in Indian Cities from Twitter Data Using Deep Learning and Word Embedding Models
	1 Introduction
	2 Literature Review
	3 System Implementation
		3.1 Dataset
		3.2 Design
		3.3 Results and Discussion
	4 Conclusion and Future Work
	References
Interpretable Chronic Kidney Disease Risk Prediction from Clinical Data Using Machine Learning
	1 Introduction
		1.1 Motivation
		1.2 Hypotheses and Limitations
		1.3 Contributions
	2 Data and Methods
	3 Experiments and Results
		3.1 Baseline Performance
		3.2 Hyperparameter Tuning
		3.3 Feature Selection and Classification
	4 Conclusion
	References
Sign Language Interpretation Using Deep Learning
	1 Introduction
	2 Literature Review
	3 Proposed Gesture Recognition System
		3.1 Gesture Recognition System Architecture
		3.2 Implementation of LAYER 1 (CNN Model)
		3.3 Implementation of Layer 2
		3.4 User Interface
		3.5 Database
		3.6 Algorithm for Gesture Recognition
	4 Results and Discussion
	5 Challenges
	6 Conclusions
	7 Future Enhancements
	References
Redefining the World of Medical Image Processing with AI – Automatic Clinical Report Generation to Support Doctors
	1 Introduction
	2 Literature Review
	3 Foundation
	4 Results
	5 Discussion and Conclusions
	6 Future Scope
	References
Statistical Analysis of the Monthly Costs of OPEC Crude Oil Using Machine Learning Models
	1 Introduction
	2 Related Work
		2.1 Objectives and Contributions
	3 Data and Methodology
	4 Results and Discussion
		4.1 Predicting the OPEC Crude Oil Prices Using Long Short-Term Memory (LSTM)
		4.2 Comparison of Linear Regression, ARIMA, ANN, SVM Linear, SVM Quadratic, Ensemble Boosted Trees, Ensemble Bagged Trees and LSTM for the Costs of OPEC Crude Oil
	5 Conclusion
	References
Conversational Artificial Intelligence in Digital Healthcare: A Bibliometric Analysis
	1 Introduction
	2 Related Studies
	3 Method
		3.1 Data Collection
		3.2 Text Preprocessing
		3.3 Bibliometric Analysis
	4 Results and Discussion
		4.1 The Future Trends in Conversational AI for Healthcare
	5 Conclusions
	References
Demand and Price Forecasting Using Deep Learning Algorithms
	1 Introduction
	2 Literature Survey
	3 Challenges in Time Series Forecasting
	4 Materials and Methods
		4.1 Dataset
		4.2 Source
		4.3 Data Preparation
		4.4 Methods
	5 Results
		5.1 Figures and Tables
	6 Discussions and Conclusions
	References
Hybrid Model Using Interacted-ARIMA and ANN Models for Efficient Forecasting
	1 Introduction
	2 Background and Review of Literature
	3 Methodology
		3.1 Autoregressive Integrated Moving Average (ARIMA) Model
		3.2 Artificial Neural Network (ANN) Model
		3.3 Interacted ARIMA (INTARIMA) Model
		3.4 Simulation Study for INTARIMA Model
		3.5 Proposed Hybrid Model
	4 Experimental Analysis
	5 Conclusion
	References
Addressing Challenges in Healthcare Big Data Analytics
	1 Introduction
	2 Background
		2.1 Handling Longitudinal Data
		2.2 Handling Heterogeneous Data
	3 Addressing Challenges Through Kernel Framework
		3.1 Mercer Kernels for Different Data Types
		3.2 Linear Combination of Mercer Kernels
		3.3 Advantages of the Kernel Framework
		3.4 Dealing with Missing Values
	4 Conclusion
	References
Assessing Reading Patterns of Learners Through Eye Tracking
	1 Introduction
		1.1 Literature Survey
	2 Methodology
		2.1 Experimental Setup
		2.2 Expert, Novice, and Partial Knowledge Behaviour from Reading Patterns
		2.3 Organized and Unorganized Reading Patterns
		2.4 Scanning, Careful Reading, and Skimming Reading Patterns
	3 Results and Analysis
	4 Conclusion
	References
Comparison of Deep Learning Algorithms for Early Detection of Melanoma Skin Cancer on Dermoscopic and Non-dermoscopic Images
	1 Introduction
	2 Literature Survey
	3 Proposed Solution
		3.1 Dataset
		3.2 Preprocessing
		3.3 Algorithms
	4 Results and Discussion
	5 Conclusion
	6 Future Scope
	References
Author Index