Computational Intelligence for Engineering and Management Applications: Select Proceedings of CIEMA 2022 (Lecture Notes in Electrical Engineering, 984)

Organization Committees
Preface
Contents
About the Editors
Computational Intelligence in Energy/Logistics/Manufacturing/Power Applications
An Integrated Approach for Robot Selection Under Utopia Environment
	1 Introduction
	2 Integrated Algorithm with Extension
	3 Case Study
	4 Conclusions
	References
A Novel Soft-Computing Technique in Hydroxyapatite Coating Selection for Orthopedic Prosthesis
	1 Introduction
	2 Proposed Algorithm
	3 Numerical Example
	4 Calculation and Discussion
	5 Conclusions
	References
Remote Production Monitoring System
	1 Introduction
	2 Literature Survey
	3 System Development
		3.1 Block Diagram
		3.2 Software
		3.3 Circuit Diagram
	4 Algorithm
	5 Performance Analysis
	6 Conclusion
	References
Application of Wavelet Neural Network for Electric Field Estimation
	1 Introduction
	2 Problem Formulation
	3 Wavelet Neural Network
	4 Results and Discussions
	5 Conclusions
	References
Development of an Industrial Control Virtual Reality Module for the Application of Electrical Switchgear in Practical Applications
	1 Introduction
	2 Structure of the Virtual Module
		2.1 Problematic
		2.2 Description of the Proposal
		2.3 Analysis of Results
	3 Conclusions
	References
Coordination of Wind Turbines and Battery Energy Storage Systems in Microgrid
	1 Introduction
	2 Simulation Model
	3 Design of BESS, Wind Turbines and Microgrid
	4 Results
	5 Conclusion
	References
Weather-Aware Selection of Wireless Technologies for Neighborhood Area Network of Indian Smart Grid
	1 Introduction
	2 Related Works
	3 Methodology
	4 An Indian Case Study
	5 Results and Discussions
	6 Conclusions
	References
Computational Intelligence in Healthcare Applications
Intelligent System for Diagnosis of Pulmonary Tuberculosis Using Ensemble Method
	1 Introduction
	2 Related Work
	3 Methods
		3.1 Ensemble Methods for Prediction of Pulmonary Tuberculosis Diagnosis
		3.2 Data Source and Data Descriptions
		3.3 Feature Selection
		3.4 Missing Value Treatment Method
		3.5 Combination of Ensemble Voting Technique
		3.6 Designing Different Types of Bootstrap Samples
		3.7 Soft Voting
		3.8 Bagging
	4 Experimental Analysis and Result
		4.1 The Ensemble Classifier Performance
		4.2 Performance Analysis of Our Conceptual Meta-Ensemble Platform (Design)
		4.3 Decision Boundaries
		4.4 AdaBoost
		4.5 Machine Learning Classifiers for Stacking
		4.6 Stacking
	5 Conclusions
	References
Alcoholic Addiction Detection Based on EEG Signals Using a Deep Convolutional Neural Network
	1 Introduction
	2 Related Work
	3 Methodology
		3.1 Feature Selection Using CNN
		3.2 Performance Metrics and Evaluation
	4 CNN Architecture for EEG Classification
	5 Result
	6 Conclusion
	References
Application of Machine Learning Algorithms for Cataract Prediction
	1 Introduction
	2 Literature Review
	3 Research Methodology
		3.1 Dataset
		3.2 Preprocessing of Data
		3.3 Application of ML Algorithms
	4 Metric for Evaluation
		4.1 Precision
		4.2 Recall
		4.3 F1-Measure
	5 Results and Discussion
	6 Conclusions
	References
Strokes-Related Disease Prediction Using Machine Learning Classifiers and Deep Belief Network Model
	1 Introduction
	2 Literature Review
	3 Research Methodology
		3.1 Data Collection
		3.2 Data Parameters
		3.3 Data Pre-processing
	4 Machine Learning Algorithms
		4.1 Logistic Regression (LR)
		4.2 Random Forest (RF)
		4.3 Support Vector Machine (SVM)
		4.4 K-Nearest Neighbors (KNNs)
		4.5 Decision Tree (DT)
	5 Research Design
	6 Experiments
		6.1 Experimental Setup
		6.2 Evaluation Metrics
		6.3 Mathematical Model
	7 Results and Discussion
		7.1 Accuracy Results Based on Algorithms
		7.2 Accuracy Results Based Training Dataset
		7.3 Accuracy Results-Based Deep Belief Networks (DBN) with Symptoms
	8 Conclusion
	References
Analysis and Detection of Fraudulence Using Machine Learning Practices in Healthcare Using Digital Twin
	1 Introduction
		1.1 Literature Review
	2 Proposed System
	3 Implementation
	4 Mathematical Modeling of SDA
		4.1 Mathematical Modeling of RBM
	5 Results and Discussion
		5.1 Confusion Matrix
	6 Conclusion
	References
Prediction and Analysis of Polycystic Ovary Syndrome Using Machine Learning
	1 Introduction
	2 Methodology
		2.1 Dataset Used
		2.2 Data Pre-Processing
		2.3 Splitting into Training and Testing
		2.4 Modelling Data
	3 Data Analysis
		3.1 Using Correlation Matrix
		3.2 Using Pair Plot and KDE Plot
		3.3 Using Swarm Plot and Boxen Plot
	4 Result and Discussion
	5 Conclusion
	References
Feature Selection for Medical Diagnosis Using Machine Learning: A Review
	1 Introduction
	2 FS in the Prediction of Medical Diseases
	3 Approaches to Feature Selection
	4 Related Work
	5 Conclusions
	References
Computational Intelligence in Image/Gesture Processing
Convolutional Neural Network Architectures Comparison for X-Ray Image Classification for Disease Identification
	1 Introduction
	2 Literature Survey
	3 Methodology
		3.1 Dataset
		3.2 VGG-16 Architecture
		3.3 VGG-19 Architecture
		3.4 Inception V3 Architecture
		3.5 DenseNet201 Architecture
	4 Results and Discussions
	5 Conclusion
	References
Secure Shift-Invariant ED Mask-Based Encrypted Medical Image Watermarking
	1 Introduction
	2 Related Works
	3 Random Key Image Encryption
	4 Proposed Methodology
		4.1 Linear Shift-Invariant Edge Detector
	5 Results and Discussions
	6 Conclusions
	References
Fusion-Based Feature Extraction Technique Using Representation Learning for Content-Based Image Classification
	1 Introduction
	2 Literature Survey
	3 Proposed Techniques and Tools
		3.1 Color Histogram (CH)
		3.2 Representation Learning
	4 Datasets
	5 Results and Discussion
	6 Conclusion
	References
A Comparative Study on Challenges and Solutions on Hand Gesture Recognition
	1 Introduction
	2 Related Work
	3 Conclusion
	References
Design a Computer-Aided Diagnosis System to Find Out Tumor Portion in Mammogram Image with Classification Technique
	1 Introduction
	2 Breast Anatomy
	3 Different Forms of Breast Abnormalities
	4 Materials and Methods
	5 Work Flow
		5.1 Input Image
		5.2 Image Enhancement
		5.3 Region of Interest
		5.4 GLCM Features
		5.5 Feature Selection
		5.6 Classification
	6 Results and Discussion
	7 Conclusion
	References
Performance Analysis of Panoramic Dental X-Ray Images Using Discrete Wavelet Transform and Unbiased Risk Estimation
	1 Introduction
	2 Methodology
		2.1 Discrete Wavelet Transform
		2.2 Unbiased Risk Estimator
	3 Results and Discussion
		3.1 PSNR Comparisons
	4 Conclusion
	References
Efficient Image Retrieval Technique with Local Edge Binary Pattern Using Combined Color and Texture Features
	1 Introduction
	2 Low Level Feature Descriptors
		2.1 Color Model
		2.2 Local Binary Patterns
		2.3 Center Symmetric Local Binary Pattern (CS-LBP)
		2.4 Local Edge Patterns
	3 Proposed Method
		3.1 Similarity Measure and Query Matching
		3.2 Working Procedure of the Proposed Algorithm
		3.3 Benefits of Proposed Algorithm
	4 Analysis of Results on Different Databases
		4.1 Corel-10k Database
		4.2 MIT-Vistex Database
	5 Conclusion
	References
Texture and Deep Feature Extraction in Brain Tumor Segmentation Using Hybrid Ensemble Classifier
	1 Introduction
	2 Related Work
	3 Methodology
		3.1 Initial Processing
		3.2 Extraction of Features
		3.3 Classification
	4 Results and Discussion
		4.1 Performance Measures
		4.2 Results
		4.3 Comparison of Proposed Method with Recent Methods
	5 Conclusion
	References
Reviews in Computational Intelligence
A Systematic Review on Sentiment Analysis for the Depression Detection During COVID-19 Pandemic
	1 Introduction
	2 Literature Review
	3 Discussion and Analysis
	4 Conclusion
	References
Vehicular Adhoc Networks: A Review
	1 Introduction
		1.1 Importance of the Work to Be Carried Out
		1.2 Literature Review
	2 Research Issues
	3 Proposed Methodology
	4 Conclusion
	References
The Data Vortex Switch Architectures—A Review
	1 Introduction
	2 Data Vortex Switch Architecture and Its Various Hierarchical Models
		2.1 Original DV Switch Architecture
		2.2 Equivalent Chained (EC) Planar (MIN) Model of the Multiplexed DV Architecture
		2.3 ADV Switch Architecture
		2.4 4 × 4 Optical Data Vortex Switch Architecture
		2.5 k-ary Data Vortex Switch Architecture
		2.6 Reverse Data Vortex (RDV) Switch Architecture
		2.7 Planar Layout (PL) of Data Vortex Switch Architecture
		2.8 Modular Data Vortex Switch Architecture
	3 Comparison of Various Architectures
	4 Conclusion
	References
Survey on Genomic Prediction in Biomedical Using Artificial Intelligence
	1 Elucidation
		1.1 Phenotypic Susceptibility of Antimicrobial Substance
		1.2 Variation Mapping and Expectation of Antibiotic Resistance Method
		1.3 A Deep Learning Model to Find Antibiotics
		1.4 Antibiotic Resistance to Predict Genome
	2 Research Objective
	3 Existing Methods to Detect the Presence of Antibiotic Elements
		3.1 The Antibiotic Genomic Recognition Method
		3.2 Decision Tree-Based Model
		3.3 Whole-Cell Biosensors
	4 Algorithm and Implementation
		4.1 Algorithm to Implement the Phenotypic Susceptibility
		4.2 Algorithm to Implement Variation Mapping and Antibiotic Resistance Prediction Method
		4.3 Algorithm to Implement to Find Antibiotic Using Deep Learning Model
		4.4 Algorithm to Predict the Resistant Antibiotic Genome
	5 Research Gap
	6 Tabulation Method to Summarize the Algorithm and Implementation Techniques
	7 Conclusion
	References
A Brief Review on Right to Recall Voting System Based on Performance Using Machine Learning and Blockchain Technology
	1 Introduction
		1.1 Use of Direct Democracy
		1.2 Recall in India
		1.3 Objectives
	2 Related Works
	3 Methodology
		3.1 Merkle Root
	4 Proposed System
		4.1 Authentication and Verification of the Right to Recall Voters
		4.2 Generating Report of Voting
		4.3 Blockchain Technology
	5 Conclusions
	References
Sentiment Analysis Techniques: A Review
	1 Introduction
		1.1 Techniques of Sentiment Classification
		1.2 Applications
	2 Literature Review
	3 Conclusion
	References
Network Traffic Classification Techniques: A Review
	1 Introduction
		1.1 Description of Class Imbalance
		1.2 Existing Solutions to Class Imbalance
	2 Literature Review
		2.1 Class Imbalance for Network Traffic Classification Using Machine Learning
		2.2 Class Imbalance for Network Traffic Classification Using Deep Learning
		2.3 Class Imbalance for Network Traffic Classification Using Ensemble Technique
	3 Review Methodology
	4 Conclusion and Future Aspects
	References
Hand Gesture Identification Using Deep Learning and Artificial Neural Networks: A Review
	1 Introduction
	2 Related Work
	3 Conclusion
	References
Various Aspects of IOT, Machine Learning and Cyber-Network Security
IoT-Assisted Solutions for Monitoring Cancer Patients
	1 Introduction
	2 Related Work
	3 IoT Applied on Cancer Types
		3.1 Internet of Things and Lung Cancer
		3.2 Internet of Things and Ovarian Cancer
		3.3 Internet of Things in Thyroid Cancer
	4 IoT in Cancer Care
	5 Observations
	6 Conclusion
	References
Application of User and Entity Behavioral Analytics (UEBA) in the Detection of Cyber Threats and Vulnerabilities Management
	1 Introduction
	2 Traditional Ways of Preventing Cyber Attacks Using Artificial Intelligence
	3 User and Entity Behavioral Analysis (UEBA)
	4 UEBA—Applications of Cybersecurity
		4.1 Vectra\'s Cognito Detect
		4.2 Darktraces Enterprise Immune System
		4.3 Paladon\'s AI-Based Managed Detection and Response Service (MDR)
	5 User and Entity Behavior Analytics (UEBA) Tools of 2021
	6 Conclusion
	References
Review of Software-Defined Network-Enabled Security
	1 Introduction
		1.1 Motivation
	2 Literature Review
		2.1 Ques: How to Solve the Research Problem Through Literature Review?
	3 Technology and Research Opportunities: Future Directions
	4 Conclusion
	References
A Concise Review on Internet of Things: Architecture and Its Enabling Technologies
	1 Introduction
	2 Motivation
	3 IoT Architecture
		3.1 Three-Layer Architecture
		3.2 Four-Layer Architecture
		3.3 Five-Layer Architecture
		3.4 Six-Layer Architecture
		3.5 Seven-Layer Architecture
	4 IoT Enabling Technologies
	5 Conclusion
	References
A Solar-Powered IoT System to Monitor and Control Greenhouses-SPISMCG
	1 Introduction
	2 Related Work
	3 Hardware Requirements
		3.1 Solar Cells
		3.2 Solar Array
		3.3 Solar Panels
		3.4 Light-Dependent Resistor
		3.5 Moisture Sensor
		3.6 Humidity Sensor
		3.7 Fire Sensor
		3.8 Relay Module
		3.9 RFID RC 522
		3.10 Arduino UNO
		3.11 NodeMCU
	4 Proposed Methodology
	5 Results and Discussion
	6 Conclusion
	References
An IoT-Based Smart Band to Fight Against COVID-19 Pandemic
	1 Introduction
	2 Literature Review
	3 Process Flow of the System
	4 Working Principles with Technical Details
	5 Experimental Results
	6 Conclusion
	References
Anomaly Detection in Blockchain Using Machine Learning
	1 Introduction
	2 Literature Review
	3 Blockchain Architecture
		3.1 Blockchain 1.0
		3.2 Blockchain 2.0
		3.3 Blockchain 3.0
	4 Vulnerabilities in Blockchain
	5 Research Problem
		5.1 Research Questions
		5.2 Research Objectives
	6 Research Methodology
	7 Expected Impact
	8 Conclusion and Recommendations
	References
QoS-Aware Resource Allocation with Enhanced Uplink Transfer for U-LTE–Wi-Fi/IoT Using Cognitive Network
	1 Introduction
	2 Literature Review
	3 Proposed Methodology
		3.1 System Model
		3.2 Problem Formation for Service Rate Capacity Distribution Process
		3.3 Resource Distribution Process
	4 Simulation Results
		4.1 Spectral Efficiency
		4.2 Throughput
		4.3 Transmission Delay
		4.4 Average Transmission Number
		4.5 SINR
		4.6 Interference
	5 Conclusion
	References
A Secure Key Management on ODMRP in Mesh-Based Multicast Network
	1 Introduction
	2 On-Demand Multicast Routing Protocol (ODMRP)
		2.1 Algorithm
		2.2 Merits of ODMRP
		2.3 ODMRP\'s Drawbacks
	3 Multicast Security in MANET
		3.1 Key Management
	4 Related Work
	5 Results and Discussion
		5.1 Average Packet Delay
		5.2 Control Overhead
		5.3 Average End to End Delay
		5.4 Normalized Routing Load (NRL)
	6 Discussion
	7 Conclusion
	References
Detecting Cyber-Attacks on Internet of Things Devices: An Effective Preprocessing Method
	1 Introduction
	2 Related Works
	3 Proposed Method
		3.1 Overview
		3.2 Dataset
		3.3 Dataset Preprocessing
	4 Experiments and Evaluation
		4.1 Evaluation Criteria
		4.2 Experiment and Discussion
	5 Conclusion
	References
A Survey on Web 3.0 Security Issues and Financial Supply Chain Risk Based on Neural Networks and Blockchain
	1 Introduction
	2 Blockchain Technology and Web 3.0
	3 Literature Review
	4 Assessment of Web 3.0 Security Issues and SCF Risk
	5 Case Study of Assessment of SCF
	6 Conclusion
	References
Computational Intelligence in Special Applications
Productive Inference of Convolutional Neural Networks Using Filter Pruning Framework
	1 Introduction
	2 Related Work
	3 Methodology
	4 Experimental Results
	5 Conclusion
	6 Future Scope
	References
Gate-Enhanced Multi-domain Dialog State Tracking for Task-Oriented Dialogue Systems
	1 Introduction
	2 Related Work
	3 DSA-Gate DST Architecture
		3.1 Dialogue History Encoder
		3.2 Hierarchical Gate Predictor
		3.3 State Generator
		3.4 Loss Function
	4 MultiWoZ Dataset Analysis
		4.1 Domain Label Noise
		4.2 Over-Trivial Carryover Problem
	5 Experiments and Discussions
		5.1 Implementation Details
		5.2 Evaluation Metrics
		5.3 Experimental Results
		5.4 Open Discussion
	6 Conclusion
	References
Anomaly Based Intrusion Detection Systems in Computer Networks: Feedforward Neural Networks and Nearest Neighbor Models as Binary Classifiers
	1 Introduction
	2 Literature Review
	3 Binary Classification
		3.1 Classification Based on the Feedforward Neural Network
		3.2 The Nearest Neighbor Classifiers
	4 Results and Discussion
	5 Conclusion
	References
Flexible Reverse Engineering of Desktop and Web Applications
	1 Introduction
	2 Literature Review
	3 Methodology
	4 Result
	5 Conclusion
	6 Future Perspectives
	References
Sentence Pair Augmentation Approach for Grammatical Error Correction
	1 Introduction
	2 Related Work
		2.1 Deep Learning in Natural Language Processing
		2.2 Markov Chain
		2.3 GPT-3
		2.4 Data Augmentation for NLP
		2.5 CopyNet
	3 Proposed Method
		3.1 Overview
		3.2 Generating Pseudo Post-proofread Sentences
		3.3 Deletion of Sentences by Gated Recurrent Unit (GRU)
		3.4 Generating Pseudo Pre-proofread Sentences
	4 Experiments
		4.1 Dataset
		4.2 Experimental Settings
		4.3 Results
	5 Conclusion
	References
Hardware in the Loop of a Level Plant Embedded in Raspberry
	1 Introduction
	2 System Structure
		2.1 Problematic
		2.2 Development
		2.3 Mathematical Modelling of Level Plant
		2.4 Controller Design
		2.5 Results
	3 Conclusion
	References
Multi-label Classification Using RetinaNet Model
	1 Introduction
	2 Form of Object Detection and Classification
		2.1 Image Classification
		2.2 Object Detection
	3 Current Development
	4 Methodology
	5 RetinaNet
		5.1 Focal Loss
		5.2 Architecture
		5.3 Anchors
		5.4 Classification of Sub-net
		5.5 Box Regression Sub-net
	6 Our Need and Approach
		6.1 Multi-label Classification for Multiple Object Needs
		6.2 Customized RetinaNet Architecture for Multi-label Classification for Multi-objects
		6.3 Datasets
		6.4 Training
		6.5 Limitations and Issues
		6.6 Future Scope
	7 Conclusion
	References
Unsupervised Process Anomaly Detection Under Industry Constraints in Cyber-Physical Systems Using Convolutional Autoencoder
	1 Introduction
	2 Related Work
	3 Problem Statement
	4 A Concept for Unsupervised Process Anomaly Detection in Cyber-Physical Systems
		4.1 Overview
		4.2 AD Installation
		4.3 AD Production
		4.4 Convolutional Autoencoder
		4.5 Anomaly Detection
	5 Prototype Implementation
	6 Evaluation
		6.1 Experimental Setup
		6.2 Data Recording
		6.3 Model Configuration
		6.4 Experimental Results
	7 Conclusion and Future Work
	References
3D Virtual System of an Apple Sorting Process Using Hardware-in-the-Loop Technique
	1 Introduction
	2 System Structure
	3 Virtual Environment
		3.1 Stage 1. Process Initialization
		3.2 Stage 2. Random Creation of the Variables to Be Classified
		3.3 Stage 3. Define the Type of Variables
		3.4 Stage 4. ON/OFF Control of Actuators for Classification
		3.5 Stage 5. Result Indicator
	4 Simulation Communication
	5 Results
	6 Conclusions
	References
Application of Augmented Reality for the Monitoring of Parameters of Industrial Instruments
	1 Introduction
	2 Methodology
		2.1 Augmented Reality
		2.2 System Development
		2.3 Functionalities
		2.4 Animation and Operation
		2.5 Analysis of Results
		2.6 Preparation and Operation of the Level Module
		2.7 Data Conditioning and Acquisition
		2.8 Parameter Processing and Visualization
		2.9 Module Operation
	3 Conclusions
	References
Analysis of Spectrum Sensing Techniques in Cognitive Radio
	1 Introduction
	2 Literature Survey
	3 Motivation
	4 Overview of the Working of Cognitive Radio
		4.1 Spectrum Sensing
		4.2 Spectrum Decision
		4.3 Spectrum Sharing
		4.4 Spectrum Mobility
	5 Spectrum Sensing Techniques in Cognitive Radio
		5.1 Energy Detection
		5.2 Matched Filter Detection
		5.3 Covariance-Based Detection
		5.4 Cyclostationary Feature Detection
		5.5 Cooperative Spectrum Sensing
	6 Problem Statement
	7 Methodology
	8 Algorithms
	9 Flow Sequence
	10 Results and Analysis
	11 Conclusion
	References
Computational Intelligence in Management Applications
Monitoring of Physiological and Atmospheric Parameters of People Working in Mining Sites Using a Smart Shirt: A Review of Latest Technologies and Limitations
	1 Introduction
	2 Literature Survey
	3 Methodology
	4 Block Diagram
	5 Conclusion
	6 Future Work
	References
Phishing Site Prediction Using Machine Learning Algorithm
	1 Introduction
	2 Literature Review
	3 Research Methodology
		3.1 Data Collection
		3.2 Respondent Sampling
	4 Conclusion
	References
Rating of Movie via Movie Recommendation System Based on Apache Spark Using Big Data and Machine Learning Techniques
	1 Introduction
	2 Literature Survey
	3 Prerequisite Knowledge
		3.1 Matrix Factorization
		3.2 Alternating Least Squares
	4 Proposed Approach
		4.1 Extracting Features
		4.2 Build the Model
		4.3 Training
		4.4 Training Using Feedback Data
		4.5 Prediction
		4.6 Recommendations
		4.7 Evaluating Performance
	5 Results and Analysis
	6 Conclusion and Future Work
	References
Application of ISM in Evaluating Inter-relationships Among Software Vulnerabilities
	1 Introduction
	2 Research Methodology
		2.1 Interpretive Structure Modeling (ISM)
	3 Numerical Illustration
		3.1 Dataset Description
		3.2 Dataset Validation
		3.3 Building Model
	4 Conclusion
	References
A Decision-Making Model for Predicting the Severity of Road Traffic Accidents Based on Ensemble Learning
	1 Introduction
	2 Literature Review
	3 Methods and Materials
		3.1 Data Set Description and Data Pre-treatment
		3.2 Ensemble Learning
		3.3 Decision Tree
		3.4 Naïve Bayes
		3.5 K-Nearest Neighbor
		3.6 Performance Evaluation Metrics
	4 Result and Discussion
		4.1 Experimental System Set up
		4.2 Results of the Overall Classification Prediction
		4.3 Classification Metrics-Based Predictions
		4.4 ROC Curve-Based Prediction Results
	5 Conclusion
	References
Factor Analysis Approach to Study Mobile Applications’ Characteristics and Consumers’ Attitudes
	1 Introduction
	2 Review of Literature
		2.1 Aesthetics
		2.2 Accessibility
		2.3 Detailed Information
		2.4 Credibility
		2.5 Connect with Customer
		2.6 Consistency
	3 Research Questions and Hypothesis Development
	4 Research Methodology
		4.1 Research Design
		4.2 Sample Design
		4.3 Data Collection
		4.4 Questionnaire Design
		4.5 Statistical Tools Used
	5 Results and Discussion
		5.1 Factor Analysis Results
		5.2 Results of Stepwise Multiple Regression
	6 Conclusion
	References
Human Behavior and Emotion Detection Mechanism Using Artificial Intelligence Technology
	1 Introduction
	2 Literature Review
		2.1 Literature Survey
		2.2 Literature Survey Results and Summary of Researchers’ Contributions
		2.3 Analysis of the Deficiencies of Researchers in the Literature Survey
		2.4 Case Analysis of Artificial Intelligence Technology in Facial Emotion Detection
		2.5 Analysis of the Advantages of Wearable Technology in Emotion Detection
		2.6 Research Questions
		2.7 Research Objectives
	3 Research Methodology
	4 Expected Impact
	5 Conclusion
	References
An Enhanced Career Prospect Prediction System for Non-computer Stream Students in Software Companies
	1 Introduction
		1.1 Deep Learning
		1.2 Objective of the Research
	2 Literature Review
	3 Methodology
		3.1 Data Set Characteristics
	4 Findings and Discussions
	5 Conclusion
	References
Sentiment Analysis and Its Applications in Recommender Systems
	1 Introduction
	2 Related Works
	3 The Proposed Model
		3.1 Sentiment Analysis
		3.2 Recommender System
	4 Experiments
	5 Conclusion
	References
Two-Stage Model for Copy-Move Forgery Detection
	1 Introduction
	2 Background
	3 Proposed Methodologies
		3.1 Part-1: Copy-Move Classification
		3.2 Part-2: Forged Region Detection
	4 Result Analysis
	5 Conclusion
	References
Mathematical Model for Broccoli Growth Prediction Based on Artificial Networks
	1 Introduction
	2 Broccoli Production in Ecuador
		2.1 Broccoli
		2.2 Mathematical Models
		2.3 Neural Networks
		2.4 Learning Algorithm
		2.5 Activation Functions
	3 Development
		3.1 Mathematical Model of Broccoli Growth
		3.2 Neural Network Input Parameters
		3.3 Model Behavior
		3.4 Validation of the Model
		3.5 Mean Absolute Percentage Error—MAPE
		3.6 Scenario 3
	4 Conclusions
	References
Computational Optimization for Decision Making Applications
Overview of the Method Defining Interrelationships Between Ranked Criteria II and Its Application in Multi-criteria Decision-Making
	1 Introduction
	2 Overview of the Algorithm of the DIBR II Method
	3 Application of the DIBR II Method
	4 Conclusion
	References
Rooftop Photovoltaic Panels’ Evaluation for Houses in Prospective MADM Outline
	1 Introduction
	2 Literature Review
		2.1 Research Gap
	3 Statement Problem
	4 Methodology
	5 Numerical Example
	6 Conclusion
	References
A Proposed q-Rung Orthopair Fuzzy-Based Decision Support System for Comparing Marketing Automation Modules for Higher Education Admission
	1 Introduction
	2 Preliminaries of qROFS
	3 Materials and Methods
		3.1 Conventional Entropy Method
		3.2 Conventional PROBID Method
		3.3 Steps of the Proposed QROF-Entropy-PROBID (qEP) Framework
	4 Results
	5 Sensitivity Analysis and Validation
	6 Conclusion and Future Scope
	References
Normalization of Target-Nominal Criteria for Multi-criteria Decision-Making Problems
	1 Introduction
	2 Normalization of Target-Nominal Criteria
		2.1 Feature of Normalization of Multidimensional Data
		2.2 Goal Inversion
		2.3 Overview and Critique of the Application of Target-Based Normalization Techniques
		2.4 Generalization of Are Normalization Methods of Target-Nominal Criteria
		2.5 Comparative Analysis of Normalization of Target-Nominal Criteria Using Different Methods
	3 Conclusion
	References
Assessment of Factors Influencing Employee Retention Using AHP Technique
	1 Introduction
	2 Literature Review
	3 Research Methodology
		3.1 Analytical Hierarchy Process (AHP)
	4 Case Study
	5 Discussion and Conclusion
	References
Correction to: Factor Analysis Approach to Study Mobile Applications’ Characteristics and Consumers’ Attitudes
	Correction to:  Chapter “Factor Analysis Approach to Study Mobile Applications’ Characteristics and Consumers’ Attitudes” in: P. Chatterjee et al. (eds.), Computational Intelligence for Engineering and Management Applications, Lecture Notes in Electrical Engineering 984, https://doi.org/10.1007/978-981-19-8493-8_58