Advances in Data Science and Intelligent Data Communication Technologies for COVID-19: Innovative Solutions Against COVID-19
- Length: 321 pages
- Edition: 1
- Language: English
- Publisher: Springer
- Publication Date: 2021-08-24
- ISBN-10: 3030773019
- ISBN-13: 9783030773014
- Sales Rank: #0 (See Top 100 Books)
This book presents the emerging developments in intelligent computing, machine learning, and data mining. It also provides insights on communications, network technologies, and the Internet of things. It offers various insights on the role of the Internet of things against COVID-19 and its potential applications. It provides the latest cloud computing improvements and advanced computing and addresses data security and privacy to secure COVID-19 data.
Preface Outline placeholder Intelligent Computing, Machine Learning, and Data Mining Big Data Analysis Data Classification and Prediction Data Visualization Cloud and Edge Computing Communications and Networking Technologies Internet of Things (IoT) Data Security and Privacy Contents About the Editors Data Science Against COVID-19 1 Content-Based Retrieval of COVID-19 Affected Chest X-rays with Siamese CNN Abstract 1 Introduction 2 Related Works 3 Preliminaries 3.1 Convolutional Neural Network (CNN)—Its Advantages and Disadvantages 3.2 Siamese CNN 4 Dataset Description 5 Implementation Requirements 6 Similarity Measurement 7 Evaluation Metrics 8 Experimental Results 9 Discussion 10 Conclusion and Future Work References 2 A Machine Learning System for Awareness, Diagnosing and Predicting COVID-19 Abstract 1 Introduction 2 Literature Review 3 Stage One (Awareness Stage) 4 Stage Two (Chest X-Ray-Diagnosis) 5 Stage Three (COVID-19 Predictor Forecast Model) 6 System Deployment in Production 7 Conclusion Acknowledgements References 3 Social Distancing Model Utilizing Machine Learning Techniques Abstract 1 Introduction 2 Literature Review 3 Proposed Methodology 3.1 People Detection 3.2 People Tracking 3.3 Distance Between People Measuring 4 Implementation and Experimental Results 4.1 Implementation 4.2 Dataset 4.3 Model Evaluation 4.4 Experimental Results 5 Conclusion References 4 The Applications of Artificial Intelligence to Control COVID-19 Abstract 1 Introduction and Background 2 Successful Usability of AI Features in the Global Pandemic Situation 2.1 AI and Deep Learning Algorithms 2.2 AI Through Machine Learning and COVID-19 2.3 Visual Recognition 2.4 CCTV and Tracking Their Movement 2.5 Prediction Model of AI for COVID-19 and Its Role in Curing Coronavirus 2.6 Contributions of AI and Evolution of BlueDot 2.7 Contributions of AI Through Robotics 2.8 Contribution of AI Based Gadgets 2.9 Digital Information and Internet of Things (IOT) 2.10 AI and Saving Lives (Review of the Wearable IOT Devices Impact Our Lives) 2.11 Drone Traffic Monitoring 2.12 Facial Recognition 2.13 AI and Gadgets for Coronavirus Outbreak 2.14 Telemedicine and Coronavirus Application 2.15 Smartphone Apps for Fighting Coronavirus COVID-19 2.16 Successful Stories of AI in COVID-19 and Lesson Learned 3 Conclusion References 5 System of Systems as a Solution to Mitigate the Spread of Covid-19 Abstract 1 Introduction 2 System of Systems 3 The Architecture of the SOS 3.1 Operational Architecture 3.2 Technical Architecture 3.3 System Architecture 4 The Requirement for a System of Systems 5 Covid-19 and Its Spread 6 Economic Effects of Covid-19 7 Creating SOS for Medical Sectors 8 Challenges of Implementing SOS for Covid-19 9 Suggested Solutions 10 Conclusion References 6 Data Classification Model for COVID-19 Pandemic Abstract 1 Introduction 2 Machine Learning in Fighting COVID-19 Pandemic 3 The Applicability and Challenges of Machine Learning for Fighting COVID-19 4 Classification Task for Combating COVID-19 Pandemic 5 Taxonomy of Data Classification Models for COVID-19 5.1 Classification Techniques 5.2 Data Classification Workflow 5.3 Problem Identification and Formulation 5.3.1 Problem Formulation for Modeling 5.4 Data Classification Models 5.4.1 Support Vector Machine (SVM) 5.4.2 Artificial Neural Network (ANN) 5.4.3 Extremely Randomized Trees (Extra Trees) 5.4.4 Random Forest 5.5 Indicators to Model Performance 6 Modeling and Analysis of COVID-19 with Data Classification Model 7 Results and Discussions 7.1 Confusion Matrix 7.2 ROC Curves 7.3 Precision-Recall Curve (PRC) 8 Conclusion References 7 A Hybrid Automated Intelligent COVID-19 Classification System Based on Neutrosophic Logic and Machine Learning Techniques Using Chest X-Ray Images Abstract 1 Introduction 2 Related Work 3 The Proposed COVID-19 Diagnostic System 3.1 Pre-processing 3.2 Feature Extraction 3.3 Neutrosophic Techniques (NTS) 3.4 Machine Learning and Classification 4 Experimental Results and Discussion 4.1 Data Set Collection 4.2 Performance Measures 4.3 Results and Discussion 5 Conclusion References 8 COVID 19 Prediction Model Using Prophet Forecasting with Solution for Controlling Cases and Economy Abstract 1 Introduction 2 State of Art 3 Analysis of Random Forest Regressor and Prediction Using Prophet Time Series Model 3.1 Prophet Procedure for Time-Series Forecasting 4 Solution 5 Conclusion References 9 Artificial Intelligence for Strengthening Administrative and Support Services in Public Sector Amid COVID-19: Challenges and Opportunities in Pakistan Abstract 1 Introduction 2 Literature Review and Proposed Hypotheses 2.1 Services Governance 2.2 Facilitative Administration 2.3 Information Governance 2.4 Communication 2.5 Socializing 2.6 Decision Making 2.7 Conceptual Framework 3 Methodology and AI-Centric Approach 3.1 Instrument/Scale Development 3.2 Respondent Profile & Relevancy 3.3 Sample & Data Collection Process 3.4 Measuring and Analysis of Data 4 Results and Discussion 5 Conclusion and Future Implications 6 Annexure References 10 Artificial Intelligence in Healthcare and Medical Imaging: Role in Fighting the Spread of COVID-19 Abstract 1 Introduction 2 Literature Review 2.1 Artificial Intelligence in Healthcare 2.2 The Current State of Al in Healthcare 2.3 Point of View of Al in Healthcare 2.4 Current Researches 2.5 Implication 2.6 Expanding Care to Developing Nations 2.7 Disease Diagnostic and Prediction 2.8 Financing the Healthcare Application of Al 2.9 Sustainability 2.10 Emphasizing Diversity 2.11 Limitation of Al 2.12 The Physician–Patient Relationship 3 Artificial Intelligent in Medical Imaging 3.1 Impact on Oncology Imaging 3.2 Al Challenges in Medical Imaging 3.3 Future Perspectives 4 Role of Medical Imaging in Fighting the Coronavirus 5 Descriptive Analysis 5.1 Descriptive of Variables 6 Conclusion References Intelligent Data Communication Technologies Against COVID-19 11 An Intelligent Cloud Computing Context-Aware Model for Remote Monitoring COVID-19 Patients Using IoT Technology Abstract 1 Introduction 2 Background and Literature Review 3 The Proposed Intelligent Cloud Computing Context-Aware Architecture for Remote Monitoring COVID-19 Patients 4 Proposed HCM 4.1 The Proposed CCM 5 Case Study 5.1 Case Study Description 5.2 Initial Setup 5.3 Data Generation 5.4 Dataset Exploration 5.5 Tools 6 Results 7 Conclusion References 12 The Relationship Between the Government’s Official Facebook Pages and Healthcare Awareness During Covid-19 in Jordan Abstract 1 Introduction 2 Literature Review 2.1 Facebook and Healthcare Awareness 2.2 The Facebook Pages of Official Institutions 2.3 Facebook and Health Awareness Regarding Coronavirus in Jordan 3 The Systematic Framework of the Chapter 4 Reliability of the Measuring Instrument 5 Findings and Discussion 5.1 Most Popular Health-Awareness Content Regarding Covid-19 on the Facebook Pages of Jordanian Institutions Concerned with Fighting Covid-19 5.2 Interaction with Posts for Healthcare Awareness Through the Facebook Pages of Jordanian Institutions Involved in Fighting Covid-19 5.3 Persuasive Appeals Used in Awareness Posts About COVID-9 on the Facebook Pages of Jordanian Institutions Involved in Fighting Covid-19 5.4 Factors Containing Health-Awareness Posts on the Pages of Jordanian Institutions Concerned with Fighting Covid-19 5.5 Forms, Language and Sources (Health-Awareness Posts) on Official Facebook Pages Concerned with Confronting Covid-19 6 Conclusion and Future Research References 13 The Influence of YouTube Videos on the Learning Experience of Disabled People During the COVID-19 Outbreak Abstract 1 Introduction 1.1 Videos Impact on the Education Process 1.2 Using YouTube in the Education Process 1.3 Using YouTube in the Education Process of People with Disabilities 1.4 Guidelines for Effective Educational YouTube Videos 2 Research Model and Study Hypotheses 2.1 Video Type (VT) and Learning Experience (LE) 2.2 YouTube Text (YT) and Learning Experience (LE) 2.3 Videos Quality (VQ) and Learning Experience (LE) 2.4 YouTube Usability (YU) and Learning Experience (LE) 2.5 Perceived Usefulness (PU) and Learning Experience (LE) 3 Methodology 3.1 Discriminant Validity 3.2 Coefficient of Determination—R2 3.3 Hypotheses Testing—Path Coefficient 4 Discussion and Conclusion 5 Study Contributions, Limitations and Recommendations References 14 IoT-Based Wearable Body Sensor Network for COVID-19 Pandemic Abstract 1 Introduction 2 Internet of Things Technology in Combating COVID-19 3 The Wearable Body Sensors Network in Fighting COVID-19 Pandemic 4 IoT-Based Wearable Sensors Network Framework for Combating COVID-19 Pandemic 5 The Practical Applicability of the Proposed Framework 6 Conclusion and Future Research Directions References 15 The Dark Side of Social Media: Spreading Misleading Information During COVID-19 Crisis Abstract 1 Introduction 2 Literature Review 2.1 The Rise of Social Media 2.2 The Benefits of Social Media 2.2.1 Governments in Social Media 2.2.2 Businesses in Social Media 2.2.3 People in Social Media 2.3 The Dark Side of Social Media 2.4 Dealing with Misleading Information 2.5 Who Should Deliver Messages to Stakeholders? 2.6 Crisis Management in Literature 2.7 The Concept of Crisis Communication 2.8 Best Practices in Crisis Communication 3 Conclusion and Limitations 3.1 Conclusion 3.2 Limitations References
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