Оглавление
Группа авторов. The New Advanced Society
Table of Contents
List of Tables
List of Illustrations
Guide
Pages
The New Advanced Society. Artificial Intelligence and Industrial Internet of Things Paradigm
Dedication
Preface
Acknowledgments
1. Post Pandemic: The New Advanced Society
1.1 Introduction
1.1.1 Themes. 1.1.1.1 Theme: Areas of Management
1.1.1.2 Theme: Financial Institutions Cyber Crime
1.1.1.3 Theme: Economic Notion
1.1.1.4 Theme: Human Depression
1.1.1.5 Theme: Migrant Labor
1.1.1.6 Theme: Digital Transformation (DT) of Educational Institutions
1.1.1.7 School and College Closures
1.2 Conclusions
References
2. Distributed Ledger Technology in the Construction Industry Using Corda
2.1 Introduction
2.2 Prerequisites
2.2.1 DLT vs Blockchain
2.3 Key Points of Corda
2.3.1 Some Salient Features of Corda
2.3.2 States
2.3.3 Contract
2.3.3.1 Create and Assign Task (CAT) Contract
2.3.3.2 Request for Cash (RT) Contract
2.3.3.3 Transfer of Cash (TT) Contract
2.3.3.4 Updation of the Task (UOT) Contract
2.3.4 Flows
2.3.4.1 Flow Associated With CAT Contract
2.3.4.2 Flow Associated With RT Contract
2.3.4.3 Flow Associated With TT Contract
2.3.4.4 Flow Associated With UOT Contract
2.4 Implementation
2.4.1 System Overview
2.4.2 Working Flowchart
2.4.3 Experimental Demonstration
2.5 Future Work
2.6 Conclusion
References
3. Identity and Access Management for Internet of Things Cloud
3.1 Introduction
3.2 Internet of Things (IoT) Security
3.2.1 IoT Security Overview
3.2.2 IoT Security Requirements
3.2.3 Securing the IoT Infrastructure
3.3 IoT Cloud
3.3.1 Cloudification of IoT
3.3.2 Commercial IoT Clouds
3.3.3 IAM of IoT Clouds
3.4 IoT Cloud Related Developments
3.5 Proposed Method for IoT Cloud IAM
3.5.1 Distributed Ledger Approach for IoT Security
3.5.2 Blockchain for IoT Security Solution
3.5.3 Proposed Distributed Ledger-Based IoT Cloud IAM
3.6 Conclusion
References
4. Automated TSR Using DNN Approach for Intelligent Vehicles
4.1 Introduction
4.2 Literature Survey
4.3 Neural Network (NN)
4.4 Methodology
4.4.1 System Architecture
4.4.2 Database
4.5 Experiments and Results
4.5.1 FFNN
4.5.2 RNN
4.5.3 CNN
4.5.4 CNN
4.5.5 Pre-Trained Models
4.6 Discussion
4.7 Conclusion
References
5. Honeypot: A Trap for Attackers
5.1 Introduction
5.1.1 Research Honeypots
5.1.2 Production Honeypots
5.2 Method
5.2.1 Low-Interaction Honeypots
5.2.2 Medium-Interaction Honeypots
5.2.3 High-Interaction Honeypots
5.3 Cryptanalysis
5.3.1 System Architecture
5.3.2 Possible Attacks on Honeypot
5.3.3 Advantages of Honeypots
5.3.4 Disadvantages of Honeypots
5.4 Conclusions
References
6. Examining Security Aspects in Industrial-Based Internet of Things
6.1 Introduction
6.2 Process Frame of IoT Before Security
6.2.1 Cyber Attack
6.2.2 Security Assessment in IoT
6.2.2.1 Security in Perception and Network Frame
6.3 Attacks and Security Assessments in IIoT
6.3.1 IoT Security Techniques Analysis Based on its Merits
6.4 Conclusion
References
7. A Cooperative Navigation for Multi-Robots in Unknown Environments Using Hybrid Jaya-DE Algorithm
7.1 Introduction
7.2 Related Works
7.3 Problem Formulation
7.4 Multi-Robot Navigation Employing Hybrid Jaya-DE Algorithm. 7.4.1 Basic Jaya Algorithm
7.5 Hybrid Jaya-DE
7.5.1 Mutation
7.5.2 Crossover
7.5.3 Selection
7.6 Simulation Analysis and Performance Evaluation of Jaya-DE Algorithm
7.7 Total Navigation Path Deviation (TNPD)
7.8 Average Unexplored Goal Distance (AUGD)
7.9 Conclusion
References
8. Categorization Model for Parkinson’s Disease Occurrence and Severity Prediction
8.1 Introduction
8.2 Applications. 8.2.1 Machine Learning in PD Diagnosis
8.2.2 Challenges of PD Detection
8.2.3 Structuring of UPDRS Score
8.3 Methodology
8.3.1 Overview of Data Driven Intelligence
8.3.2 Comparison Between Deep Learning and Traditional Machine
8.3.3 Deep Learning for PD Diagnosis
8.3.4 Convolution Neural Network for PD Diagnosis
8.4 Proposed Models
8.4.1 Classification of Patient and Healthy Controls
8.4.2 Severity Score Classification
8.5 Results and Discussion
8.5.1 Performance Measures
8.5.2 Graphical Results
8.6 Conclusion
References
9. AI-Based Smart Agriculture Monitoring Using Ground-Based and Remotely Sensed Images
9.1 Introduction
9.2 Automatic Land-Cover Classification Techniques Using Remotely Sensed Images
9.3 Deep Learning-Based Agriculture Monitoring
9.4 Adaptive Approaches for Multi-Modal Classification
9.4.1 Unsupervised DA
9.4.2 Semi-Supervised DA
9.4.3 Active Learning-Based DA
9.5 System Model
9.6 IEEE 802.15.4. 9.6.1 802.15.4 MAC
9.6.2 DSME MAC
9.6.3 TSCH MAC
9.7 Analysis of IEEE 802.15.4 for Smart Agriculture
9.7.1 Effect of Device Specification
9.7.1.1 Low-Power
9.7.2 Effect of MAC Protocols
9.8 Experimental Results
9.9 Conclusion & Future Directions
References
10. Car Buying Criteria Evaluation Using Machine Learning Approach
10.1 Introduction
10.2 Literature Survey
10.3 Proposed Method
10.4 Dataset
10.5 Exploratory Data Analysis
10.6 Splitting of Data Into Training Data and Test Data
10.7 Pre-Processing
10.8 Training of Our Models
10.8.1 Gaussian Naïve Bayes
10.8.2 Decision Tree Classifier
10.8.3 Tuning the Model
10.8.4 Karnough Nearest Neighbor Classifier
10.8.5 Tuning the Model
10.8.6 Neural Network
10.8.7 Tuning the Model
10.9 Result Analysis
10.9.1 Confusion Matrix
10.9.2 Gaussian Naïve Bayes
10.9.3 Decision Tree Classifier
10.9.4 Karnough Nearest Neighbor Classifier
10.9.5 Neural Network
10.9.6 Accuracy Scores
10.10 Conclusion and Future Work
References
11. Big Data, Artificial Intelligence and Machine Learning: A Paradigm Shift in Election Campaigns
11.1 Introduction
11.2 Big Data Reveals the Voters’ Preference
11.2.1 Use of Software Applications in Election Campaigns
11.2.1.1 Team Joe App
11.2.1.2 Trump 2020
11.2.1.3 Modi App
11.3 Deep Fakes and Election Campaigns
11.3.1 Deep Fake in Delhi Elections
11.4 Social Media Bots
11.5 Future of Artificial Intelligence and Machine Learning in Election Campaigns
References
12. Impact of Optimized Segment Routing in Software Defined Networks
12.1 Introduction
12.2 Software-Defined Network
12.3 SDN Architecture
12.4 Segment Routing
12.5 Segment Routing in SDN
12.6 Traffic Engineering in SDN
12.7 Segment Routing Protocol
12.8 Simulation and Result
12.9 Conclusion and Future Work
References
13. An Investigation into COVID-19 Pandemic in India
13.1 Introduction
13.1.1 Symptoms of COVID-19
13.1.2 Precautionary Measures
13.1.3 Ways of Spreading the Coronavirus
13.2 Literature Survey
13.3 Technologies Used to Fight COVID-19. 13.3.1 Robots
13.3.2 Drone Technology
13.3.3 Crowd Surveillance
13.3.4 Spraying the Disinfectant
13.3.5 Sanitizing the Contaminated Areas
13.3.6 Monitoring Temperature Using Thermal Camera
13.3.7 Delivering Essential Things
13.3.8 Public Announcement in the Infected Areas
13.4 Impact of COVID-19 on Business
13.4.1 Impact on Financial Markets
13.4.2 Impact on Supply Side
13.4.3 Impact on Demand Side
13.4.4 Impact on International Trade
13.5 Impact of COVID-19 on Indian Economy
13.6 Data and Result Analysis
13.7 Conclusion and Future Scope
References
14. Skin Cancer Classification: Analysis of Different CNN Models via Classification Accuracy
14.1 Introduction
14.2 Literature Survey
14.3 Methodology
14.3.1 Dataset Preparation
14.3.2 Dataset Loading and Data Pre-Processing
14.3.3 Creating Models
14.4 Models Used
14.5 Simulation Results
14.5.1 Changing Size of MaxPool2D(n,n)
14.5.2 Changing Size of AveragePool2D(n,n)
14.5.3 Changing Number of con2d(32n–64n) Layers
14.5.4 Changing Number of con2d-32*n Layers
14.5.5 ROC Curves and MSE Curves
14.6 Conclusion
References
15. Route Mapping of Multiple Humanoid Robots Using Firefly-Based Artificial Potential Field Algorithm in a Cluttered Terrain
15.1 Introduction
15.2 Design of Proposed Algorithm
15.2.1 Mechanism of Artificial Potential Field
15.2.1.1 Potential Field Generated by Attractive Force of Goal
15.2.1.2 Potential Field Generated by Repulsive Force of Obstacle
15.2.2 Mechanism of Firefly Algorithm
15.2.2.1 Architecture of Optimization Problem Based on Firefly Algorithm
15.2.2.1.1 Barrier Avoidance Behavior
15.2.2.1.2 Target Finding Behavior
15.2.3 Dining Philosopher Controller
15.3 Hybridization Process of Proposed Algorithm
15.4 Execution of Proposed Algorithm in Multiple Humanoid Robots
15.5 Comparison
15.6 Conclusion
References
16. Innovative Practices in Education Systems Using Artificial Intelligence for Advanced Society
16.1 Introduction
16.2 Literature Survey
16.2.1 AI in Auto-Grading
16.2.2 AI in Smart Content
16.2.3 AI in Auto Analysis on Student’s Grade
16.2.4 AI Extends Free Intelligent Tutoring
16.2.5 AI in Predicting Student Admission and Drop-Out Rate
16.3 Proposed System
16.3.1 Data Collection Module
16.3.2 Data Pre-Processing Module
16.3.3 Clustering Module
16.3.4 Partner Selection Module
16.4 Results
16.5 Future Enhancements
16.6 Conclusion
References
17. PSO-Based Hybrid Weighted k-Nearest Neighbor Algorithm for Workload Prediction in Cloud Infrastructures
17.1 Introduction
17.2 Literature Survey
17.2.1 Machine Learning
17.3 Proposed System
17.3.1 Load Aware Cloud Computing Model
17.3.2 Wavelet Neural Network
17.3.3 Evaluation Using LOOCV Model
17.3.4 k-Nearest Neighbor (k-NN) Algorithm
17.3.5 Particle Swarm Optimization (PSO) Algorithm
17.3.6 HWkNN Optimization Algorithm Based on PSO
17.3.7 PSO-Based HWkNN (PHWkNN) Load Prediction Algorithm
17.4 Experimental Results
17.5 Conclusion
References
18. An Extensive Survey on the Prediction of Bankruptcy
18.1 Introduction
18.2 Literature Survey. 18.2.1 Data Pre-Processing
18.2.1.1 Balancing of Imbalanced Dataset
18.2.1.1.1 Oversampling
18.2.1.1.2 Undersampling
18.2.1.2 Outlier Data Handling
18.2.1.2.1 Outlier Detection
18.2.1.2.2 Outlier Handling
18.2.2 Classifiers
18.2.3 Ensemble Models
18.3 System Architecture and Simulation Results
18.4 Conclusion
References
19. Future of Indian Agriculture Using AI and Machine Learning Tools and Techniques
19.1 Introduction
19.2 Overview of AI and Machine Learning
19.3 Review of Literature
19.4 Application of AI & Machine Learning in Agriculture
19.5 Current Scenario and Emerging Trends of AI and ML in Indian Agriculture Sector
19.6 Opportunities for Agricultural Operations in India
19.7 Conclusion
References
Index
Also of Interest. Check out these published and forthcoming titles in the “Artificial Intelligence and Soft Computing for Industrial Transformation” series from Scrivener Publishing
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