Applied Intelligence and Informatics: First International Conference, AII 2021, Nottingham, UK, July 30–31, 2021, Proceedings

Preface
Organization
Contents
Application of AI and Informatics in Disease Detection
Inference and Learning Methodology of Belief Rule Based Expert System to Assess Chikungunya
	1 Introduction
	2 Literature Review
	3 Methodology
		3.1 BRB Expert System Methodology
	4 Experimental Result
		4.1 Reliability of Trained BRBES
		4.2 ROC for Trained BRB
		4.3 Comparison of Accuracy of Trained and Non-trained BRBES Using Test Data
		4.4 Comparison among Deep learning and other Machine Learning Algorithm with BRBES
		4.5 ROC for Trained BRB
	5 Conclusion and Future Work
	References
Glaucoma Detection Using Inception Convolutional Neural Network V3
	1 Introduction
	2 Problem Statement
	3 Literature Review
	4 Method
		4.1 Data Collection
		4.2 Data Augmentation
		4.3 Inception V3
	5 Results
		5.1 Evaluation Criteria
		5.2 Comparison of Different Types of CNN Model
	6 Conclusion
	References
iConDet: An Intelligent Portable Healthcare App for the Detection of Conjunctivitis
	1 Introduction
	2 Related Work
	3 Methodology
		3.1 Proposed Pipeline
		3.2 Image Pre-processing
		3.3 Machine Learning Model
		3.4 Mobile App Development
		3.5 Evaluation Metrics
	4 Results and Discussion
		4.1 Dataset Creation
		4.2 Experimentation
		4.3 Validation
	5 Conclusion and Future Work
	References
Selecting Lung Cancer Patients from UK Primary Care Data: A Longitudinal Study of Feature Trends
	1 Introduction
	2 Methods
		2.1 Study Design and Population
		2.2 Demographic Characteristics of Cases and Controls
		2.3 Features of Interest
	3 Data Analysis
	4 Conclusion
	References
Extending Upon a Transfer Learning Approach for Brain Tumour Segmentation
	1 Introduction
	2 Background and Related Work
	3 Methodology
		3.1 BraTS2020 Dataset
		3.2 Extending the Input Channels
		3.3 Pre-processing and Data Augmentation Policies
		3.4 Training and Hyperparameters
	4 Results and Discussion
	5 Conclusion
	References
Automatic Seizure Prediction Based on Cross-Feature Fusion Stream Convolutional Neural Network
	1 Introduction
	2 Experimental Data
	3 Method
		3.1 Denoising
		3.2 Feature Extraction
		3.3 Cross-Feature Fusion Stream Convolutional Neural Network
	4 Result
	5 Conclusion
	References
Application of AI and Informatics in Healthcare
Anomaly Detection in Invasively Recorded Neuronal Signals Using Deep Neural Network: Effect of Sampling Frequency
	1 Introduction
	2 Methodology
	3 Results and Discussion
	4 Conclusion
	References
Classification of First Trimester Ultrasound Images Using Deep Convolutional Neural Network
	1 Introduction
	2 Related Works
	3 Proposed Method
		3.1 Network Construction
		3.2 Experimentation
		3.3 Parameter Selection
	4 Results and Discussion
		4.1 Model Performance
		4.2 Comparison of Model Performance
	5 Conclusion and Future Work
	References
Method to Enhance Classification of Skin Cancer Using Back Propagated Artificial Neural Network
	1 Introduction
	2 Literature Survey
		2.1 Filter and Adaptive Histogram Technique
		2.2 Gaussian Method
		2.3 Segmentation Techniques
		2.4 Artificial Neural Network Based Techniques
		2.5 Different Feature Extraction Methods
		2.6 Feature Selection Techniques
		2.7 Machine Learning Techniques
		2.8 Digital Image Utilizing Technique
		2.9 Data Mining Techniques
	3 Proposed Method
		3.1 Database Training and Testing
		3.2 Preprocessing
		3.3 Image Segmentation
		3.4 Feature Extraction
		3.5 Texture Analysis of Features
		3.6 Classifications of Cancer
	4 Results
		4.1 Evaluation Metrics
		4.2 Performance Comparison
	5 Conclusion
	References
Knowledge Discovery from Tumor Volume Using Adaptive Neuro Fuzzy Inference System Rules
	1 Introduction
	2 Literature Review
	3 Tumor Stage Identification
	4 Adaptive Neuro-Fuzzy Inference System (ANFIS) for Tumor Stage Classification
		4.1 Architecture of ANFIS
	5 NCCN Guidelines Version 2.0 Staging Nom-Small Cell Lung Cancer
	6 The Tumor, Node, and Metastasized Staging System
		6.1 Prediction of Stages in Lung Cancer
	7 ANFIS Rules
	8 Experimental Results and Discussions
		8.1 Patient Id: 002 – Slice No 63-74
	9 Conclusion
	References
Key Techniques and Challenges for Processing of Heart Sound Signals
	1 Introduction
	2 Background
		2.1 The Heart Muscle Structure
		2.2 Basic Components of PCG
	3 PCG Preprocessing
	4 PCG Segmentation
		4.1 Envelope-Based Methods
		4.2 Decomposition-Based Segmentation Methods
		4.3 Time-Frequency
		4.4 Probabilistic Models and Machine Learning-Based Methods
	5 PCG Feature Extraction
	6 Classification Models and Performance Evaluation
		6.1 SVM-Based Classifiers
		6.2 Artificial-Based Neural Network Based Classifiers
		6.3 Statistical Tests-Based Classification
		6.4 HMM-Based Classifiers
		6.5 GMM-Based Classifiers
		6.6 Deep-Learning-Based Classifiers
	7 Future Work
	8 Conclusion
	References
Enhanced Signal Processing Using Modified Cyclic Shift Tree Denoising
	1 Introduction
	2 Materials and Methods
		2.1 Wavelets Methods
		2.2 Wavelet Kalman Filter Approach
		2.3 Cyclic Shift Tree Denoising
	3 Results and Discussion
		3.1 Selection Minimum Number of Epochs
	4 Conclusion
	References
Application of AI and Informatics in Pattern Recognition
A Machine Learning Driven Android Based Mobile Application for Flower Identification
	1 Introduction
	2 Related Work
	3 System Architecture
	4 Experimentation
		4.1 Required Tools
	5 Result and Discussion
	6 Conclusion and Future Work
	References
A Generative Text Summarization Model Based on Document Structure Neural Network
	1 Introduction
	2 Related Work
		2.1 Encoder-Decoder Model Based on LSTM
		2.2 Gated Recurrent Unit (GRU) Neural Network
	3 Generative Text Summary Model Based on Document Structure Neural Network (DSNN-GSM)
		3.1 DSNN-GSM Model Structure
		3.2 Algorithm Flow Description
		3.3 Multiple Attention Mechanism
	4 Experiment
		4.1 Text Summary Evaluation Method
		4.2 Experimental Parameter Settings
		4.3 Activation Function Selection Analysis
		4.4 Comparative Analysis of Methods
	5 Conclusion
	References
Human Gender Detection from Facial Images Using Convolution Neural Network
	1 Introduction
	2 Literature Review
	3 Methodology
		3.1 Dataset
		3.2 Pre-processing
		3.3 Feature Extraction
		3.4 Classification
	4 Experimental Setup
	5 Result and Discussion
		5.1 Comparison of Result Among Different Optimizers and Activation Functions
		5.2 K-Fold Cross Validation
		5.3 Performance Metrics
	6 Conclusion and Future Work
	References
Few-Shot Learning for Tamil Handwritten Character Recognition Using Deep Siamese Convolutional Neural Network
	1 Introduction
	2 Literature Review
	3 Methodology
		3.1 Siamese-CNN Model
		3.2 Cross-entropy Loss
	4 Experimental Results
	5 Conclusion and Future Avenues
	References
A CNN Based Model for Venomous and Non-venomous Snake Classification
	1 Introduction
	2 Related Work
	3 Data Pre-processing
		3.1 About Dataset
		3.2 Data Augmentation
	4 Methodology
		4.1 Model Construction
		4.2 The Implementation Procedure
	5 Experimental Evaluation
		5.1 Tuning of the Hyper-parameters
		5.2 K-Fold Cross Validation
		5.3 Result
	6 Epilogue and Future Work
	References
Recognition of Dysfluency in Speech: A Bidirectional Long-Short Term Memory Based Approach
	1 Introduction
	2 Feature Extraction
		2.1 Speech Representation
		2.2 Mel-Frequency Cepstrum Coefficient
	3 Classification Using Recurrent Neural Networks
	4 Conclusion
	References
Application of AI and Informatics in Network, Security, and Analytics
Distributed Denial of Service Attack Detection Using Machine Learning and Class Oversampling
	1 Introduction
	2 Related Works
	3 Proposed Model
		3.1 Datasets
		3.2 Pre-processing
		3.3 Machine Learning Models
	4 Performance Evaluation
		4.1 Detection Performance
	5 Conclusion
	References
Scientific Metrological Analysis of Government Services Based on Big Data Analysis and Visualization Software Driven by Information Technology
	1 Introduction
	2 Scientometric Approach and Data
	3 Research Findings
		3.1 Annual Trends
		3.2 Major States and Institutions
		3.3 Major Publications
		3.4 Key Words Analysis of Authors
	4 Conclusion
	References
Violent Video Event Detection: A Local Optimal Oriented Pattern Based Approach
	1 Introduction
	2 Previous Works
	3 Proposed Methodology
		3.1 LOOP Feature Descriptor
		3.2 Classification Based on Support Vector Machine (SVM)
		3.3 Post-processing
	4 Experiment Results and Discussion
		4.1 Violent Datasets
		4.2 Experimental Setting
		4.3 Result
		4.4 Discussion
	5 Conclusion
	References
Human Age Estimation Using Deep Learning from Gait Data
	1 Introduction
	2 Related Work
	3 Methodology
		3.1 Dataset Description
		3.2 Model Design
	4 Result and Discussion
		4.1 System Configuration
		4.2 Tuning Hyperparameters
		4.3 Performance Evaluation Matrix
		4.4 Result
	5 Conclusion and Future Work
	References
An Error Resilient Video Transmission in Ad Hoc Network Using Error Diffusion Block Truncation Coding
	1 Introduction
	2 Proposed Work
	3 Performance Analysis
		3.1 Peak Signal to Noise Ratio
	4 Conclusion
	References
ALO: AI for Least Observed People
	1 Introduction
	2 AI for Least Observed (ALO)
	3 System Overview
		3.1 Real Time Messaging
		3.2 Bone Conduction Unit
		3.3 Object Detection
		3.4 Face Detection and Identification
	4 Conclusion
	References
Emerging Applications of AI and Informatics
COVID-Hero: Machine Learning Based COVID-19 Awareness Enhancement Mobile Game for Children
	1 Introduction
	2 Related Works
	3 Methods and Materials
		3.1 Requirement Analysis
		3.2 COVID-Hero
		3.3 Survey Works
		3.4 Machine Learning Based Analysis
	4 Experimental Result
	5 Discussion
	6 Conclusion and Future Work
	References
Literature Classification Model of Deep Learning Based on BERT-BiLSTM——Taking COVID-19 as an Example
	1 Introduction
	2 Review of Related Research
		2.1 Research on Text Classification Algorithm
		2.2 Related Research on the Application of Text Classification
	3 The Text Classification Model Based on BERT-BiLSTM
		3.1 The Description of Text Classification Problem
		3.2 Pre Training Language Model—BERT
		3.3 BiLSTM
		3.4 Support Vector Machine (SVM)
		3.5 Model Framework
	4 Experimental Setup
		4.1 Collection and Processing of Experimental Data
		4.2 Experimental Model Design
		4.3 Comparison of Experimental Results
	5 Epilogue
	References
Identifying Relevant Stakeholders in Digital Healthcare
	1 Introduction
	2 Relevant Stakeholders
	3 Method
		3.1 Narrative Synthesis Literature Review
		3.2 Adopting Bryant Model
	4 Results
	5 Discussion
	6 Conclusion
	References
COVID-19 Detection Using Chest X-Ray Images with a RegNet Structured Deep Learning Model
	1 Introduction
	2 Related Works
	3 Dataset
	4 Proposed Model Architecture
	5 Model Evaluation
	6 Result Analysis
	7 Conclusion and Future Work
	References
Mixed Bangla-English Spoken Digit Classification Using Convolutional Neural Network
	1 Introduction
	2 Literature Review
	3 Methodology
		3.1 Data Preproecessing
		3.2 Feature Extraction
		3.3 Train and Test Data
		3.4 Feature Learning and Classification Using CNN
	4 Result Analysis
	5 Conclusion
	References
Sluggish State-Based Neural Networks Provide State-of-the-art Forecasts of Covid-19 Cases
	1 Introduction
	2 Covid-19 Forecasting
	3 Methodology
		3.1 Covid-19 Dataset
		3.2 Multi-recurrent Networks
		3.3 Forecasting Methodology
	4 Results and Discussion
		4.1 Advance Monthly Predictions of Covid-19 Cases
		4.2 Advance Weekly Predictions of Covid-19 Cases
	5 Discussion
	6 Conclusion
	References
Author Index