Intelligent Computing and Applications: Proceedings of ICDIC 2020

Description

This book presents novel work of academicians, researchers, industry professionals, practitioners, and budding engineers to disseminate the most recent innovations, trends, and concerns along with the present-day challenges and the solving approaches for implementation in the domains of data science, intelligent computing, and computer networks and security. It is a collection of selected high-quality research papers from the International Conference on Data Science, Intelligent Computing and Cyber Security (ICDIC 2020) organized by Sree Vidyanikethan Engineering College, Tirupati, India, during 27–29 February 2020. It discusses the latest challenges and solutions in the field of data innovation, data management, data analysis, data security, and intelligent methods and applications. Conference Committee Preface Contents About the Editors 1 Prediction of Depression-Related Posts in Instagram Social Media Platform 1.1 Introduction 1.2 Literature Survey 1.3 Proposed Work 1.4 Implementation 1.5 Results and Discussions References 2 Classification of Credit Card Frauds Using Autoencoded Features 2.1 Introduction 2.2 Literature Review 2.3 Autoencoders 2.3.1 Basic Architecture 2.3.2 Mathematical Model for Autoencoder 2.4 Proposed Method 2.4.1 Feature Extraction Phase 2.4.2 Classification Phase 2.5 Results and Discussion 2.5.1 Dataset 2.5.2 Experimental Setup 2.5.3 Evaluation Metrics 2.5.4 Results and Discussion 2.6 Conclusion References 3 BIVFN: Blockchain-Enabled Intelligent Vehicular Fog Networks 3.1 Introduction 3.2 Vehicular Fog Networking 3.3 BIVFN: Blockchain-Enabled Intelligent Vehicular Fog Network for Connected Vehicles 3.3.1 Architecture 3.3.2 Phases of BIVFN 3.4 Security Requirements Attainment in BIVFN 3.5 Conclusion References 4 Deep Learning Approach for Pedestrian Detection, Tracking, and Suspicious Activity Recognition in Academic Environment 4.1 Introduction 4.2 Literature Survey 4.2.1 Pedestrian Dataset 4.2.2 Proposed Deep Learning Architecture and Academic Environment Pedestrian Dataset 4.3 Recent Deep Learning Architecture 4.4 Experimental Results 4.5 Conclusions References 5 Data-Driven Approach to Deflate Consumption in Delay Tolerant Networks 5.1 Introduction 5.2 Related Work 5.2.1 DTN Features 5.2.2 Irregular Interfacing 5.2.3 Low Speed, Inefficiency, and High Queue Interruption 5.2.4 Limited Resource 5.2.5 Node Life Time 5.2.6 Dynamic Topology 5.2.7 Performance Issues 5.3 Proposed Method 5.4 Algorithm 5.5 Conclusion References 6 Code-Level Self-adaptive Approach for Building Reusable Software Components 6.1 Introduction 6.2 Literature Survey 6.2.1 Adaptive Reuse 6.2.2 Adaptable Software System Versus Traditional Software System 6.2.3 Adaptive Methods to Improve the Software System 6.3 Proposed Work 6.3.1 Software Engineering with Reusable Components 6.3.2 Strategy Development Reuse 6.3.3 The Incorporation Process to Reuse Project 6.3.4 Process Measurement and Evolution 6.3.5 Management Reuse 6.4 Results and Discussions 6.5 Conclusion and Future Work References 7 Design of a Deep Network Model for Weed Classification 7.1 Introduction 7.2 Related Works 7.3 Methodology 7.3.1 Dataset Description 7.3.2 Dense Convolutional Neural Networks (DCNN) 7.4 Numerical Results and Discussion 7.5 Conclusion References 8 E-Voting System Using U-Net Architecture with Blockchain Technology 8.1 Introduction 8.2 Literature Survey 8.3 Methodology 8.4 Results and Discussion 8.5 Conclusion References 9 Multi-layered Architecture to Monitor and Control the Energy Management in Smart Cities 9.1 Introduction 9.1.1 Proposed Questions 9.1.2 Methodology 9.2 Literature 9.2.1 Smart Meters 9.2.2 Smart City 9.2.3 Internet of Things (IoT) 9.2.4 Cloud–Fog-IoT Environment 9.2.5 A Network Architecture 9.2.6 Drones for Smart Cities 9.2.7 Network Architectures for Smart Cities 9.2.8 Objectives of Energy Meter Monitoring Device System in 9.3 A Novel Approach to Data Acquisition for Energy Monitoring System 9.3.1 Proposed Architecture for Cloud-Fog-IoT Environment—Framework 9.3.2 The Activities in Three-Layer Network 9.3.3 Arduino-Based Energy Meter Control and Management 9.3.4 Components of IoT-Based Energy Meter Control and Management 9.3.5 Features of Proposed ‘Three-Layered Architecture’ for Smart Meter Monitoring and Management with Integration of Cloud, Fog, IoT and Wireless Sensor Network Model as Shown in Fig. 9.3 Are as Follows 9.3.6 Threat Landscape in Three Layer Architecture 9.4 Conclusions References 10 Bio-Inspired Firefly Algorithm for Polygonal Approximation on Various Shapes 10.1 Introduction 10.2 Problem Formulation 10.2.1 Basic Pre-processing 10.3 Firefly Algorithm 10.3.1 Firefly for Polygonal Approximation 10.4 Experimental Results and Discussion 10.5 Conclusion References 11 An Efficient IoT Security Solution Using Deep Learning Mechanisms 11.1 Introduction 11.2 Related Work 11.2.1 Safety in IoT Operation 11.2.2 Gaps in the Presented Security Resolutions for IoT Networks 11.2.3 Machine Learning: A Solution to Iot Security Challenges 11.3 Methodology 11.4 Results and Discussion 11.4.1 Dataset Used 11.4.2 Training and Test Data 11.5 Conclusion References 12 Intelligent Disease Analysis Using Machine Learning 12.1 Introduction 12.2 Literature Survey 12.3 Proposed Work 12.4 Results and Analysis 12.5 Conclusion References 13 Automated Detection of Skin Lesions Using Back Propagation Neural Network 13.1 Introduction 13.2 Literature Survey and Proposed Work 13.2.1 Image Segmentation 13.2.2 Morphological Image Processing 13.3 Results 13.4 Conclusion and Future Enhancement References 14 Detection of COVID-19 Using CNN and ML Algorithms 14.1 Introduction 14.2 Literature Survey 14.2.1 Pneumonia and COVID-19 Detection Using Convolution Neural Network 14.2.2 COVID-19 Detection Using Recurrent Neural Network 14.2.3 Transfer Learning to Detect COVID-19 Automatically from X-ray Images Using Convolutional Neural Networks 14.2.4 Automatic Detection of Coronavirus Disease (COVID-19) Using X-ray Images and Deep Convolutional Neural Networks 14.2.5 Use of Fuzzy Soft Set in Decision Making of COVID-19 Risks 14.2.6 CNN-LSTM Combination for COVID-19 Prediction 14.2.7 Statistical Techniques for Combating COVID-19 14.2.8 Computational Intelligence Techniques for Combating COVID-19: A Survey 14.2.9 Toward Using Recurrent Neural Networks for Predicting Influenza-Like Illness: Case Study of COVID-19 in Morocco 14.2.10 The Role of Chest Imaging in Patient Management During the COVID-19 Pandemic: A Multinational Consensus Statement from the Fleischer’s Society 14.3 Proposed Methodology 14.3.1 Detecting COVID-19 Using CNN 14.3.2 Detecting COVID-19 Using Random Forest 14.4 Experimental Results 14.5 Conclusion References 15 Prioritization of Watersheds Using GIS and Fuzzy Analytical Hierarchy (FAHP) Method 15.1 Introduction 15.2 Relevant Study 15.3 Methodology 15.3.1 Topographical Maps 15.3.2 Watershed Atlas of India (WAI) 15.3.3 Fuzzy Analytical Hierarchy Program (FAHP) 15.4 Results and Discussion 15.4.1 Morphometric Analysis 15.4.2 Watershed Prioritization Utilizing the Fuzzy Analytical Hierarchy Process (FAHP) Technique 15.5 Conclusion References 16 A Narrative Framework with Ensemble Learning for Face Emotion Recognition 16.1 Introduction 16.2 Related Work 16.3 Proposed Work 16.4 Results and Discussion 16.5 Conclusion References 17 Modified Cloud-Based Malware Identification Technique Using Machine Learning Approach 17.1 Introduction 17.2 Literature Survey 17.3 Proposed Methodology 17.4 Conclusion References 18 Design and Deployment of the Road Safety System in Vehicular Network Based on a Distance and Speed 18.1 Introduction 18.2 Literature Review 18.3 Proposed System 18.3.1 Experimental Methodology 18.3.2 Flow of Execution of an Application 18.3.3 Modules of the Application 18.4 Conclusion References 19 Diagnosis of COVID-19 Using Artificial Intelligence Techniques 19.1 Introduction 19.2 Materials and Frameworks 19.2.1 Materials and Datasets 19.2.2 Frameworks 19.3 Approach 19.4 Conclusion and Future References 20 Location Tracking via Bluetooth 20.1 Introduction 20.2 Related Work 20.3 Methodology 20.4 Implementation 20.4.1 System Components 20.4.2 Application Implementation 20.5 Conclusion References 21 Shrimp Surfacing Recognition System in the Pond Using Deep Computer Vision 21.1 Introduction 21.2 Literature Survey 21.3 Proposed Work 21.3.1 Image Data Augmentation 21.3.2 Horizontal and Vertical Shift Augmentation 21.3.3 Horizontal and Vertical Flip Augmentation 21.3.4 Random Rotation Augmentation 21.4 Results and Analysis 21.5 Conclusion References 22 Sign Language Recognition for Needy People Using Machine Learning Model 22.1 Introduction 22.2 Relevant Study 22.2.1 Pros and Cons of the Existing and Planned Models 22.3 Proposed Method 22.3.1 Data Preparation 22.4 Results and Discussion 22.5 Conclusion References 23 Efficient Usage of Spectrum by Using Joint Optimization Channel Allocation Method 23.1 Introduction 23.2 Literature Survey 23.3 Proposed Method 23.4 Experimental Results 23.5 Comparison of Results 23.6 Conclusion and Future Scope References 24 An Intelligent Energy-Efficient Routing Protocol for Wearable Body Area Networks 24.1 Introduction 24.2 Issues in Designing Routing Protocols 24.2.1 Existing Energy-Efficient Routing Protocols in WBAN 24.3 Proposed Approach 24.3.1 Intelligent Energy-Efficient Routing Protocol 24.4 Simulation Setup 24.5 Conclusion References 25 Enhanced Video Classification System with Convolutional Neural Networks Using Representative Frames as Input Data 25.1 Introduction 25.2 Related Works 25.3 Methodology 25.4 Experiments and Results 25.5 Conclusion References 26 Text Recognition from Images Using Deep Learning Techniques 26.1 Introduction 26.2 Related Work 26.2.1 Localization 26.2.2 Segmentation 26.2.3 Recognition 26.2.4 Datasets 26.3 Proposed Work 26.3.1 Image Acquisition 26.3.2 Image Processing 26.3.3 Plate Localization 26.3.4 Character Recognition 26.4 Proposed Method 26.4.1 Convolution Neural Network 26.4.2 Pooling 26.4.3 Padding 26.5 Implementation 26.5.1 Models of CNN 26.5.2 OCR using open CV and CNN 26.6 Conclusion References 27 Early Detection and Diagnosis of Oral Cancer Using Fusioned Deep Neural Network 27.1 Introduction 27.2 Literature Survey 27.3 Methodology 27.4 Result Analysis 27.5 Conclusion References 28 Fine-tuning for Transfer Learning of ResNet152 for Disease Identification in Tomato Leaves 28.1 Introduction 28.2 Literature Survey 28.3 Materials and Methods 28.3.1 Dataset 28.3.2 Transfer Learning-Based CNN Model 28.3.3 Performance Evaluation 28.4 Experimentation 28.5 Results and Discussion 28.6 Conclusion References 29 AI-Based Mental Fatigue Recognition and Responsive Recommendation System 29.1 Introduction 29.2 Related Literature on Responsive System 29.2.1 A Stress-Based Mental Fatigue—Responsive System 29.2.2 Personal Mood-Based Mental Fatigue 29.3 Methods 29.3.1 Technological Approach—IoT Devices to Acquire Data 29.3.2 Research Procedure 29.3.3 Mood 29.3.4 Stress 29.3.5 Methods—Machine Learning Models 29.4 Evaluation and Results 29.4.1 Survey Results and Clustering 29.4.2 Clustering 29.4.3 Classification Models 29.4.4 Classification Model Training 29.4.5 Results 29.5 Conclusion and Discussion References 30 Multiple Slotted Triple-Band PIFA Antenna for Wearable Medical Applications at 2.5–9 GHz 30.1 Introduction 30.2 Antenna Design 30.3 Results and Discussion 30.4 Conclusion References 31 Fish Classification System Using Customized Deep Residual Neural Networks on Small-Scale Underwater Images 31.1 Introduction 31.2 Related Works 31.3 Deep Residual Network (DRN) 31.4 Proposed Method 31.5 Results and Discussion 31.6 Conclusion References 32 Multiple Face Recognition System Using OpenFace 32.1 Introduction 32.2 Related Work 32.3 Proposed Methodology 32.4 Results 32.5 Conclusion References 33 EDAARP-Efficient and Data-Aggregative Authentic Routing Protocol for Wireless Sensor Networks 33.1 Introduction 33.2 Efficient Data-Aggregative Authentic Routing Protocol (EDAARP) 33.3 Simulation Study and Performance Analysis: 33.4 Conclusion References 34 Mobile-Based Selfie Sign Language Recognition System (SSLRS) Using Statistical Features and ANN Classifier 34.1 Introduction 34.2 Literature Review 34.3 Proposed SSLR 34.3.1 Feature Extraction 34.3.2 Classification 34.4 Result Analysis 34.4.1 Performance Evaluation: Word Matching Score (WMS) 34.5 Conclusion and Future Work References 35 An Effective Model for Malware Detection 35.1 Introduction 35.2 Literature Survey 35.3 Data Preprocessing 35.4 Model for Malware Detection (MMD) 35.4.1 Overview 35.4.2 MMD Architecture 35.5 Experimental Results 35.6 Testing MMD Model with Unknown Malware 35.7 Conclusion References 36 An Efficient Approach to Retrieve Information for Desktop Search Engine 36.1 Introduction 36.2 Related Work 36.3 Proposed Methodology 36.3.1 Clustering Probase 36.3.2 POS TAGGING and SEGMENTATION 36.3.3 Conceptualization 36.3.4 Inverted Index 36.4 Experimentation Results 36.5 Conclusion References 37 Baggage Recognition and Collection at Airports 37.1 Introduction 37.2 Methodology 37.2.1 Conventional Method 37.2.2 Proposed Solution 37.3 Implementation 37.3.1 Schematic Diagram 37.3.2 Circuit Implementation 37.4 Result and Discussion 37.5 Conclusion References 38 Computer Vision Technique to Detect Accidents 38.1 Introduction 38.2 Existing System 38.3 Proposed System 38.3.1 Faster R-CNN 38.3.2 Region Proposal Networks 38.4 System Implementation and Results 38.4.1 Anchors 38.5 Conclusion and Future Work References 39 An Efficient Machine Learning Approach for Apple Leaf Disease Detection 39.1 Introduction 39.2 Related Work 39.3 Proposed Method 39.3.1 Data Acquisition 39.3.2 Image Segmentation 39.3.3 Feature Extraction 39.3.4 Disease Detection 39.4 Results and Discussion 39.5 Conclusion References 40 Precipitation Estimation Using Deep Learning 40.1 Introduction 40.2 Related Works 40.2.1 Statistical Downscaling 40.2.2 Applications 40.3 Methodology 40.4 Discussion 40.5 Conclusion References 41 The Adaptive Strategies Improving Digital Twin Using the Internet of Things 41.1 Introduction 41.2 Relevant Work 41.3 Proposed Work 41.4 Results and Discussion 41.5 Conclusion References 42 Deep Learning for Breast Cancer Diagnosis Using Histopathological Images 42.1 Introduction 42.2 Literature Review 42.3 Proposed Method 42.4 Experimental Results 42.5 Conclusion References 43 Implementation of 12 Band Integer Filter-Bank for Digital Hearing Aid 43.1 Introduction 43.2 Integer Filter-Bank with Internal Gain Adjustment 43.2.1 Integer Filter-Bank 43.2.2 Gain Adjustment 43.3 Design Example and Performance Evaluation 43.4 Results and Discussions 43.5 Conclusion References 44 Comparative Analysis on Heart Disease Prediction Using Convolutional Neural Network with Adapted Backpropagation 44.1 Introduction 44.2 Literature Survey 44.3 Methodology 44.3.1 Data Collecting 44.3.2 Classification Modeling 44.4 Convolutional Neural Network 44.5 CNN Modified Backpropagation 44.6 Results and Discussion 44.7 Conclusion References 45 Applying Machine Learning to Enhance COVID-19 Prediction and Diagnosis of COVID-19 Treatment Using Convalescent Plasma 45.1 Introduction 45.2 Convalescent Plasma as Potentially COVID-19 Therapy 45.3 The Covid-19 Healing of Convalescent Plasma 45.3.1 Plasma Convalescent: The Principle of Action 45.3.2 Collections Steps of Convalescent Plasma 45.4 The Plasma Convalescent Dose 45.5 Conclusion References 46 Analysis of Disaster Tweets Using Natural Language Processing 46.1 Introduction 46.2 Literature Survey 46.3 Proposed Model 46.4 Algorithm 46.5 Results 46.6 Conclusion References Author Index