Intelligent Systems, Technologies and Applications: Proceedings of Sixth ISTA 2020, India (Advances in Intelligent Systems and Computing)

Conference Organization
Organized by
Preface
Contents
About the Editors
Probability of Loan Default—Applying Data Analytics to Financial Credit Risk Prediction
	1 Introduction
	2 How Banks Assess Customers—Short Introduction
		2.1 Need of Credit Risk Assessment
	3 Related Work
		3.1 Data Analytics for Credit Risk Analysis
		3.2 Classifiers Used in Our Work
	4 Datasets Used in Experiments
		4.1 German Credit Dataset
		4.2 Give Me Some Credit Dataset
	5 Experimental Setup
		5.1 Performance Evaluation—Methodological Considerations
	6 Experimental Results
		6.1 Results for the German Credit Data
		6.2 Results for the Give Me Some Credit Dataset
		6.3 Results for the Meta-Classifiers
	7 Concluding Remarks
	References
Analytical Study on Algorithms for Content-Based Mobile Phone Recommendation System
	1 Introduction
	2 Related Works
	3 Design of Experiments
		3.1 Dataset
		3.2 Content-Based Implementation
	4 Proposed System
		4.1 Prediction Using LSI Model
		4.2 Prediction Using Cosine Similarity
	5 Results and Discussions
	6 Conclusion
	References
ShExMap and IPSM-AF—Comparison of RDF Transformation Technologies
	1 Introduction
	2 Related Work
	3 ShEx and IPSM
		3.1 Shape Expressions
		3.2 IPSM
	4 RDF transformation languages
		4.1 ShExMap
		4.2 IPSM-AF
	5 Case studies
		5.1 From IPSM-AF into ShExMap
		5.2 From ShExMap into IPSM-AF
	6 Concluding remarks
	References
AI Approaches for IoT Security Analysis
	1 Overview and Introduction
	2 Related Work
	3 Overview of IoT protocols and Security Risks
		3.1 IoT layers and protocols
		3.2 IoT Security Risks
	4 Structure of ML, DL and FL algorithms
	5 Machine Learning for Cybersecurity
		5.1 State of the Art
		5.2 General Trend Analysis
	6 Deep Learning use for Cybersecurity
		6.1 State of the Art
		6.2 General Trend Analysis
	7 Federated Learning use for IoT Cybersecurity
		7.1 State of the Art
		7.2 General Trend Analysis
	8 Discussion and Future Insights
	9 Conclusion
	References
Hybrid Deep Neural Architecture for Detection of DDoS Attacks in Cloud Computing
	1 Introduction
	2 Related Work
	3 Proposed Method
		3.1 Data Pre-processing
		3.2 Pre-processing Phase
		3.3 Pre-training Phase
		3.4 Training and Testing Phase
	4 Experimentation and Validation
	5 Results and Discussion
	6 Conclusion and Future Scope
	References
MapReduce-Driven Rough Set Fuzzy Classification Rule Generation for Big Data Processing
	1 Introduction
	2 Related Work
		2.1 Big Data and the MapReduce Programming Model
		2.2 Apache Hadoop and Apache Spark
	3 Proposed Rough Set Fuzzy Classification Rule Generation Algorithm for Big Data
		3.1 Definition of Fuzzy Rule-Based Classifier
		3.2 The Working Model of Proposed Fuzzy Rule-Based Classification Systems
	4 Experimental Study
		4.1 Dataset
		4.2 Metrics Used
		4.3 Results and Discussions
	5 Conclusion
	References
Identifying Network Intrusion Using Enhanced Whale Optimization Algorithm
	1 Introduction
	2 Related Works
	3 Experimental Setup
		3.1 Background in Framing Optimization Model
		3.2 Whale Optimization Algorithm
		3.3 Exploration and Exploitation Phase in WOA
		3.4 Maneuver in Contracting Circle and Spiral Path
		3.5 Proposed System Architecture
		3.6 Framing an Optimization Problem with Constraints
		3.7 Mathematical Formulation
	4 Empirical Study with Results
	5 Conclusion and Future Enhancement
	References
Transformed WLS-Based Data Reconciliation for a Large-Scale Process Network
	1 Introduction
	2 Data Reconciliation (DR) Techniques
		2.1 Generalized Measurement Model
		2.2 Pre-processing Techniques
	3 Simulations and Results
	4 Conclusion
	References
Data-Driven-Based Disruption Prediction in GOLEM Tokamak with Missing Values
	1 Introduction
	2 Related Work/Literature Overview
	3 GOLEM Tokamak
		3.1 Signals in GOLEM Tokamak
	4 Methodology
		4.1 Gradient Boosting
		4.2 CatBoost
	5 Results and Discussion
		5.1 CatBoost—Tuning and Training
		5.2 Optimal Threshold
	6 Conclusion and Future Works
	References
IoT-Based Home Vertical Farming
	1 Introduction
	2 Literature Review
	3 Vertical Farming System
	4 IoT Integration and Mobile Application for System
	5 Developed PCB
	6 Power Supply
	7 Crop Yield Forecasting Using Machine Learning
	8 Future Improvements
	9 Conclusion
	References
A Scalable Multi-disease Modeled CDSS Based on Bayesian Network Approach for Commonly Occurring Diseases with a NLP-Based GUI
	1 Introduction
	2 Literature Survey
	3 The Proposed System for CDSS
		3.1 Training Module
		3.2 Create Patient Module
		3.3 Symptom Checker Module
		3.4 Laboratory Test Checker Module
	4 Experimental Results and Discussion
	5 Conclusion and Future Work
	References
Analyze and Visualize the Correlation Between Heart and Cancer Diseases Using Data Mining Techniques
	1 Introduction
	2 Literature Survey
	3 Data Description
	4 Proposed Methodology
		4.1 Data Preprocessing
		4.2 K-Means Clustering
		4.3 Decision Tree
		4.4 Data Visualization
	5 Result and Analysis
	6 Conclusion
	7 Future Scope
	References
A Hybrid Deep Learning Approach for Predicting the Spread of COVID-19
	1 Introduction
	2 Contributions of This Study
	3 Literature Survey
	4 Methodology and Results
		4.1 Dataset
		4.2 Pre-processing
	5 Models
		5.1 Multi-layer Perceptron
		5.2 Convolutional Neural Network
		5.3 Long Short-Term Memory
		5.4 Autoregressive Integrated Moving Average
		5.5 CNN–LSTM Hybrid Model
		5.6 PyTorch
	6 Comparing the Models
		6.1 Metrics
	7 Conclusion and Future Scope
	References
Diabetes Prediction Using Machine Learning Techniques
	1 Introduction
	2 Literature Survey
	3 Data Description
	4 Experimental Setup
	5 Proposed Design
		5.1 Data Preprocessing
		5.2 SVM
		5.3 Decision Tree
		5.4 Ensemble Methods
		5.5 Neural Networks
		5.6 Linear Discriminant Analysis (LDA)
		5.7 Random Forest
	6 Result
	7 Future Scope
	References
Deep Neural Network Based Multi-class Arrhythmia Classification
	1 Introduction
	2 Literature Review
	3 Proposed System
		3.1 MIT–BIH Arrhythmia Dataset
		3.2 Signal Processing
		3.3 The Proposed DNN
	4 Results and Discussion
		4.1 The Dataset
		4.2 Dataset Preprocessing
		4.3 Deep Neural Network
	5 Conclusions and Future Work
	References
Lung Nodule Detection from Computed Tomography Images Using Stacked Deep Convolutional Neural Network
	1 Introduction
	2 Related Work
	3 Proposed Method
		3.1 Lung Parenchyma Segmentation
		3.2 Lung Nodule Detection
	4 Experimentation and Results
	5 Contributions
	6 Conclusion
	References
Deep Learning Classification to Improve Diagnosis of Cervical Cancer Through Swarm Intelligence-Based Feature Selection Approach
	1 Introduction
	2 Literature Survey
	3 Proposed Methodology
		3.1 Cervical Cancer Dataset
		3.2 Synthetic Minority Oversampling Technique
		3.3 Synthetic Minority Oversampling Technique Feature Selection Using Artificial Bee Colony (ABC)
		3.4 Classification Using LSTM
	4 Experimental Results and Analysis
		4.1 Accuracy Comparison With and Without Feature Selection
		4.2 Overall Classification Accuracy
		4.3 Sensitivity
		4.4 Specificity
		4.5 ROC Curve
	5 Conclusion
	References
Overview of Deep Learning in Food Image Classification for Dietary Assessment System
	1 Introduction
	2 Challenges in Food Image Recognition
		2.1 Variety of Food Items
		2.2 Obscured or Hidden Food Item
		2.3 Irregular Food Size
		2.4 Segmentation
		2.5 Liquid Food
		2.6 Non-uniform Density
		2.7 Computation Cost
		2.8 Lack of Proper Nutrition Data
	3 Overview of Deep Learning
		3.1 Deep Learning Networks
		3.2 Deep Learning Frameworks
	4 Dataset
	5 Segmentation and Classification
		5.1 Segmentation Techniques
		5.2 Image Classification Techniques
	6 Conclusion and Future Work
	References
Comparison of Face Embedding Approach Versus CNN-Based Image Classification Approach for Human Race Detection from Face
	1 Introduction
		1.1 Related Work
	2 Proposed Approach
		2.1 Embedding Extraction for Race Detection
	3 CNN-Based Networks
		3.1 Why These Networks?
		3.2 VGG-16 Network
		3.3 MobileNet Network
		3.4 Transfer Learning
	4 Dataset Details and Data Preprocessing
	5 Results and Discussion
	6 Conclusion
	References
An Effective Real-Time Approach to Automatic Number Plate Recognition (ANPR) Using YOLOv3 and OCR
	1 Introduction
	2 Proposed Methodology
		2.1 Number Plate Detection
		2.2 Interfacing
		2.3 Optical Character Recognition (OCR)
		2.4 Database Operation
		2.5 Advantages of Proposed Methodology
	3 Performance Measures
		3.1 Average Loss
		3.2 Mean Average Precision(mAP)
		3.3 Accuracy
	4 Implementation
		4.1 Implementation of YOLOv3
		4.2 Implementation of Interfacing Algorithm
		4.3 Implementation of OCR
		4.4 Implementation of Database Operation
	5 Result and Analysis
	6 Conclusion
	References
Generating Audio from Lip Movements Visual Input: A Survey
	1 Introduction
	2 Audio Model and Dataset
	3 Generating Audio from Visual Speech
	4 Speech Reconstruction from Multiview Visual Feed
	5 Visual Speech Recognition
	6 Audio Reconstruction from Video
	7 Evaluation Metrics and Comparison Table
	8 Conclusion
	References
Improving the Performance of Imbalanced Learning and Classification of a Juvenile Delinquency Data
	1 Introduction
	2 Literature Review
	3 Juvenile Delinquency Dataset
	4 Evidence of Imbalanced Effect
	5 Proposed Algorithm
	6 Experimental Results
	7 Conclusion
	References
An Experimental Stack Overflow Chatbot Architecture Using NLP Techniques
	1 Introduction
	2 Related Work
	3 Proposed Chatbot Architecture
		3.1 System Description
		3.2 Data and Pre-processing
		3.3 Classification
		3.4 Chatterbot API
		3.5 Telegram API
	4 Demonstration and Discussion
	5 Conclusion
	6 Future Scope
	References
Empirical Analysis of Performance of MT Systems and Its Metrics for English to Bengali: A Black Box-Based Approach
	1 Introduction
	2 Phases of MT Systems and Some Related Work on Evaluation Metrics
	3 Linguistic Features of English and Bengali
	4 Some Evaluation Metrics
	5 Methodology
	6 Data and Experiments
	7 Analysis and Discussion
	8 Conclusions
	References
A Spot Rainfall Prediction During Cyclones by Using Time Series Analysis Model
	1 Introduction
	2 Data Used
		2.1 Study Area
		2.2 Data Collection
		2.3 Software Used: MSEXCEL
	3 Methodology
		3.1 Scatter Plot
		3.2 Rainfall
		3.3 Cyclone
		3.4 Pre-processing Steps
	4 Results and Discussion
	5 Conclusion and Future Work
	References
Multivariate Variational Mode Decomposition based Analysis on Stock Sectors
	1 Introduction
	2 Multivariate Variational Mode Decomposition
	3 Spatio-Temporal Intrinsic Mode Decomposition
	4 Data Description
	5 Reconstruction Using STIMD
	6 Reconstruction Using Multivariate VMD
	7 Results
		7.1 Reconstruction Error for Single Modes
		7.2 Reconstruction Error for Sum of All Modes
	8 Conclusion
	References
Case-Based Expert System for Smart Air Conditioner with Adaptive Thermoregulatory Comfort
	1 Introduction
	2 Literature Survey
		2.1 Theory of Human Thermoregulation
		2.2 IoT Hardware and Software Requirements
		2.3 IoT in HVAC Systems
		2.4 Expert Systems and Case-Based Reasoning in IoT
	3 The Architecture
		3.1 IoT Architecture of Proposed Smart Air Conditioning System
		3.2 Device Management
		3.3 Challenges in the System
	4 Case-Based Expert Application for Thermoregulation Comfort
		4.1 Query Format
		4.2 Case Format
		4.3 Case Matching
		4.4 Knowledge Base
		4.5 Feedback
	5 Conclusion
	References
Prediction of Solar Power in an IoT-Enabled Solar System in an Academic Campus of India
	1 Introduction
	2 Literature Survey
	3 The Data from Installations of LNMIIT
	4 Data Prepossessing and Analysis
		4.1 Tools Used in Data Processing
		4.2 Correlation Analysis of Different Parameters
	5 The Prediction Model and the Characteristics
		5.1 Prediction Using Different Regression Models
		5.2 Evaluation of Random Forest Regressor on Various Dataset
		5.3 Prediction Model Using Neural Network
	6 Conclusion
	References
Author Index