This book contains high-quality peer-reviewed papers of the International Conference on Big Data, Machine Learning and their Applications (ICBMA 2019) held at Motilal Nehru National Institute of Technology Allahabad, Prayagraj, India, during 29–31 May 2020.
The book provides significant contributions in a structured way so that prospective readers can understand how these techniques are used in finding solutions to complex engineering problems. The book covers the areas of big data, machine learning, bio-inspired algorithms, artificial intelligence and their applications.
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Author(s): Shailesh Tiwari; Erma Suryani; Andrew Keong Ng
Series: Lecture Notes in Networks and Systems, 150
Publisher: Springer Singapore
Year: 2020
Language: English
Pages: 670
City: Singapore
Preface
About This Book
Contents
Editors and Contributors
Analysis of Efficiency of Fractional Order Technique in a Controller for a Complex Nonlinear Control Process
1 Introduction
2 Model Description
3 Controller Design for Two-Link Robotic Manipulator
3.1 Design of the Fractional Order Fuzzy PID (FOFPID)/ Integer Order Fuzzy PID (IOFOID)
3.2 Design of the Fractional Order PID (FOPID) / Integer Order PID (IOPID)
3.3 Fractional Order Calculus
3.4 Optimization Strategy for the Controllers
4 Simulation Results
4.1 Performance Testing of the Controllers Due to Disturbance at the Controllers Output.
4.2 Performance Testing for the Parameters Uncertainties
5 Conclusion
References
NWP Models Combined with Ensemble Models for Hourly Estimation of Global Solar Irradiance
1 Introduction
1.1 Background
2 Literature Review
3 Proposed Model
3.1 Prediction Framework
3.2 Data Preprocessing and Attribute Correlation
3.3 Neural Network Machine Learning Model
4 Results and Discussions
4.1 R2Scores of Implemented Machine Learning Models
4.2 Significant Feature Extraction and Evaluation
4.3 Graphical Analysis
5 Conclusions
References
Literature Review on Agricultural Internet of Things
1 Introduction
2 Literature Survey
3 Flow Diagram
4 Challenges and Issues in Smart Agriculture
5 Approaches
6 Conclusion
7 Future Scope
References
Deep Learning Approach-Based Network Intrusion Detection System for Fog-Assisted IoT
1 Introduction
1.1 Author’s Contribution
2 Related Work
3 Overview of Deep Learning
4 Proposed Work
4.1 The Monitoring Phase
4.2 Anomaly Detection Phase
4.3 Response Generation Phase
5 Implementation and Evaluation
5.1 Datasets
5.2 Evaluation Metrics
5.3 Result Analysis
6 Conclusion
References
Improving Prediction Accuracy for Debonding Quantification in Stiffened Plate by Meta-Learning Model
1 Introduction
2 Theoretical Background
2.1 Support Vector Machine (SVM)
2.2 Random Forest (RF)
2.3 Gradient Boosting Regression (GBR)
2.4 Vote Model
2.5 Stacked Model
3 Finite Element Modelling
3.1 Stiffened Plate Modelling
3.2 Modelling of Debonding and Contact
4 Methodology Framework
5 Result and Discussions
5.1 Debonding Length Prediction
5.2 Performance Evaluation of Learning Models
6 Conclusion
References
The Need of Advanced Assisting Devices for Blind People
1 Introduction
2 Background Details and Related Work
3 Problem Statement
4 Detailed Study
5 Proposed Solution
6 Conclusions
7 Future Works
References
A Noval Fuzzy-Based Artificial Bee Colony Algorithm for Medical Records Classification
1 Introduction
2 Literature Review
3 Proposed FABC
4 Experimental Analysis
4.1 Datasets
4.2 Document Classification
4.3 Document Clustering
5 Conclusions
References
A Comparative Study: Glaucoma Detection Using Deep Neural Networks
1 Introduction
2 Detection of Glaucoma Techniques
2.1 NFL Defect Detection and Texture Analysis of NFL
2.2 Neuro Retinal Optic Cup Detection in Glaucoma Diagnosis
2.3 Computer Added Diagnoses System for Diagnosis of Glaucoma
2.4 Detection of Glaucoma by Deep Learning
3 Conclusion
References
Security Risks and Challenges in IoT-Based Applications
1 Introduction
2 Communication Technologies Used in IoT
3 Security Vulnerabilities and Threats in IoT
4 Security Implementations for IoT
5 Summary
6 Conclusion
References
An Assessment of Type-2 Diabetes Risk Prediction Using Machine Learning Techniques
1 Introduction
2 Machine Learning Techniques
2.1 Support Vector Machine
2.2 Naïve Bayes
2.3 Decision Tree (DT)
3 Objective of Study
4 Related Work
5 Conclusion
References
Comparative Study of Different Reduced Precision Techniques in Deep Neural Network
1 Introduction
2 Various Precision Formats
2.1 Fixed Point
2.2 Floating Point
3 Training Neural Network
3.1 Architecture of Neural Network
3.2 Training
4 Training in Reduced Precision
4.1 16-Bit Training
4.2 8-Bit Training
4.3 Mixed-Precision Training in 8-Bit
5 Result Analysis
6 Conclusion
References
Design of a Predictive Measure to Enhance Neural Network Architecture for Plant Disease Detection
1 Introduction
2 Convolutional Neural Network
3 Existing Architectures and Predictive Measures
3.1 Areas of Use
3.2 Data Sources
3.3 Data Pre-processing
3.4 Data Augmentation
3.5 Technical Analysis
4 Integration-Based Models
5 Overall Performance
6 ResNet
7 VGGNet
8 Support Vector Machine
9 Optimized Deep Neural Network
10 RandomForest
11 MobileNet
12 Proposed Measure
13 Comparison with Other Approaches
14 Conclusion
References
Design and Analysis of Smart Automatic Street Light System
1 Introduction
2 Proposed System Functionality
2.1 Operating Modes
3 System Implementation
4 Result and Conclusion
References
Combating DoS Attack on OpenStack Using Hypervisor Based Intrusion Detection System with the Help of Machine Learning
1 Introduction
2 OpenStack DoS Vulnerability
3 IDPs: The Solution
3.1 Recently Used IDPs on OpenStack
4 Proposed Framework
5 Implementaton
5.1 Used Setup Specifications
5.2 Steps
6 Result Analysis
7 Conclusion and Future Scope
References
Exploring Honeycomb Interconnection Networks
1 Introduction
2 Test Bed and Parameters Used
2.1 Throughput
2.2 Latency
2.3 Load Factor
2.4 Traffic Patterns
2.5 Power of Network
3 Methodology
4 Results and Discussions
4.1 Uniform Traffic
4.2 Bit Complement
4.3 Tornado Traffic
4.4 Neighbor Traffic
5 Conclusion
References
Pharmaceutical Supply Chain Management Blockchain
1 Introduction
1.1 Blockchain
1.2 Supply Chain
1.3 Smart Contracts
2 Objective
2.1 Problem Definition
2.2 Problem Formulation
2.3 Motivation
3 Related Work
4 Literature Review
5 Survey on Blockchain
5.1 Bitcoin: A Peer-To-Peer Electronic Cash System by Satoshi Nakamoto
5.2 It Increases Trust Among the Participants Because the Whole Network is Transparent in Terms of Functioning.
5.3 Blockchains Everywhere—A Use-Case of Blockchains in the Pharma Supply Chain by Thomas Bocek, Bruno B. Rodrigues, Tim Strasser, Burkhard Stiller
6 Proposed Methodology
6.1 Architecture Diagram of the Proposed System
6.2 Workflow Diagram of the Proposed System
7 Implementation
8 Results and Discussion
References
The Need of Smart Guidance Systems for Blind People in the World
1 Introduction
2 Background Details and Related Work
3 Problem Statement
4 Conclusions
References
Behavioral Cloning for Self-driving Cars Using Deep Learning
1 Introduction
2 Preprocessing
2.1 Sampling
2.2 Train-Test Split
2.3 Image Processing
3 Defining the Model
3.1 Nvidia’s Model
3.2 Hyperparameters for Nvidia’s Mode
4 Problems with the Mode
4.1 Activation Function
4.2 Overfitting
4.3 Small Dataset
5 Improvement in the Model
5.1 Activation Function
5.2 Overfitting
5.3 Data Augmentation
6 Connection to the Simulator
7 Running the Simulator
8 Experiments
9 Results
10 Discussion
11 Conclusion
References
Performance Analysis of Chatbots and Brief Study About Technical Aspects
1 Introduction
2 Design of Chatbot
3 Loebner Prize
4 Technical Working and Algorithm
4.1 Markov Chain Model
4.2 Pattern Matching
4.3 Parsing
4.4 Semantic Network
4.5 Artificial Intelligence Markup Language (AIML)
4.6 ChatScript
5 A.L.I.C.E. Chatbot Architecture
5.1 AIML Files
5.2 Types of Categories
6 Natural Language Processing (NLP)
6.1 Natural Language Text Processing Systems
6.2 Applications of Natural Language Processing
7 Conclusion
References
Evolving Evidence Gathering Process: Cloud Forensics
1 Introduction
2 Standards
3 Virtualization
3.1 Requirements of Virtualization
3.2 Issues Related to Virtualization
4 Digital Evidence in a Virtualized Environment
4.1 When to Virtualize
5 Existing Studies
6 Research Questions and Hypothesis
6.1 PHASE I
6.2 PHASE II
6.3 PHASE III
6.4 PHASE IV
6.5 Identifying Evidence for Reconstruction
7 Conclusion
References
Melanoma Detection Among Various Skin Lesions
1 Introduction
2 Related Work
3 Methodology
4 Proposed Model
5 Result
6 Conclusion
References
Emotion Detection from Audio Using SVM
1 Introduction
2 System Implementation
2.1 Features Used
2.2 Dataset
2.3 Feature Extraction
2.4 Support Vector Machine (SVM) Classifiers
3 Experimentation and Results
4 Conclusion and Future Work
References
Plant Disease Detection Using Image Classification
1 Introduction
2 Related Work
3 Type of Disease
4 Proposed Methodology
4.1 Flowchart of the Methodology
4.2 Dataset
4.3 Image Acquisition
4.4 Image Preprocessing
4.5 Image Segmentation
4.6 Binary Labeling and Augmentation
4.7 CNN Architecture
4.8 Activation Function
4.9 Learning Rate
4.10 Optimizer
4.11 Model Training
5 Result
6 Analysis
6.1 Accuracy and Loss Graph
6.2 Confusion Matrix
6.3 Comparison with Different Models
6.4 Accuracy of Individual
7 Conclusion
References
Sarcasm Detection Technique on Twitter Data with Natural Language Processing
1 Introduction
2 Related Work
3 Types of Sarcasm
4 Proposed Methodology
4.1 Dataset
4.2 Data Preprocessing
4.3 Feature Extraction
4.4 Classification
5 Result
5.1 Linear Support Vector Classifier
5.2 Naïve Bayes
5.3 Logistic Regression
5.4 Random Forest Classifier
6 Conclusion
References
CDMD: An Efficient Crop Disease Detection and Pesticide Recommendation System Using Mobile Vision and Deep Learning
1 Introduction
2 Related Work
3 CDMD:Design Architecture
3.1 Crop Health Monitoring System
3.2 Pest and Disease Recommendation System
4 Experiments and Result
4.1 Description About Data Set
4.2 Discription About Result
4.3 Practical Usage and Deployment of CDMD in Android
5 Conclusion
References
Generative Adversarial Neural Networks for Text-to-Image Synthesis of Dog Images
1 Introduction
2 Literature Survey
3 Experimental Setup
4 Results and Discussions
5 Conclusion and Futurework
References
Human Activity Recognition by Utilizing Local Ternary Pattern and Histogram of Oriented Gradients
1 Introduction
2 Literature Review
3 The Feature Descriptors and Their Properties
3.1 Local Ternary Pattern (LTP)
3.2 Histogram of Oriented Gradients (HOG)
3.3 Advantage of Combining LTP and HOG Feature
4 The Proposed Method
5 Experimental Result and Discussion
6 Conclusion
References
Study and Analysis of Various Load Balancing Techniques for Software-Defined Network (A Systematic Survey)
1 Introduction
1.1 Network Function Virtualization
1.2 Software-Defined Network
1.3 Evolution of Software-Defined Network
1.4 Load Balancing
1.5 Kinds of Load Balancing
2 Related Work
3 Comparison and Analysis
3.1 Advantages and Disadvantages of Load Balancing Techniques
3.2 Comparative Analysis of Load Balancing Techniques
4 Conclusion
References
Heterogeneous Channel Allocation in Mesh Interconnection Network Using Genetic Algorithm
1 Introduction
2 Related Work
3 Proposed Approach
4 Result Obtained
5 Conclusion
References
Detection of Human Emotion in Text
1 Introduction
1.1 Approaches
2 Background Details and Related Work
3 Computational Approaches for Emotion Detection
4 Implementation
4.1 KNN Algorithm
4.2 Hidden Markov Model
4.3 Decision Tree
4.4 Random Forest
5 Result
6 Conclusions
Reference
An Improved Hand Gesture Recognition System Based on Optimized MSVM and SIFT Feature Extraction Algorithm
1 Introduction
2 Literature Review
2.1 Gesture Using SIFT and SURF Algorithm
2.2 Template Matching
2.3 Hand Region Segmentation and Contour Extraction Method
3 Research Challenges and Methodology in HGR System
3.1 Challenges
3.2 Methodology
4 Experiment Analysis
5 Conclusion
References
An Android Application for Automatic Content Summarization of News Articles Using Multilayer Perceptron
1 Introduction
2 Related Work
3 Proposed Approach
3.1 Proposed Model
3.2 Dataset
3.3 Features
3.4 Normalization
4 Algorithms and Results
4.1 Logistic Regression
4.2 Artificial Neural Network
4.3 Naive Bayes Algorithm
5 Android Application
6 Conclusion and Future Work
References
Chronic Kidney Disease Prediction Using Artificial Neural Network
1 Introduction
2 Background Details & Related Work
3 Proposed Approach
3.1 Dataset & Data Preprocessing
3.2 Applying Artificial Neural Network
3.3 Training the Neural Network and Analyzing the Performance
4 Experimental Setup and Results
5 Conclusions
References
Vehicle Detection and Speed Tracking Based on Object Detection
1 Introduction
2 Background Details and Related Work
2.1 Speed Tracking: Physical Methods
2.2 Image Processing Method
3 Proposed Method
4 Experimental Setup and Results
5 Conclusions
References