Engineering Applications of Artificial Intelligence

Preface
Introduction
Contents
Applications of Artificial Intelligence in Research
Artificial Intelligence: An Overview
1 Introduction
2 Historical Background of Artificial Intelligence
3 Literature Review
3.1 A.I. Structure
3.2 A.I. Environment
3.3 A.I. System
3.4 Natural Language Processing
3.5 Artificial Subfields
3.6 A.I. and Human
3.7 A.I. and Society
3.8 A.I. and Firms
3.9 A.I. and Management Process
4 Conclusion
5 The Implication of AI in Future Management Process
References
Application of Artificial Intelligence to Control a Nonlinear SIR Model
1 Introduction
2 A Nonlinear Control System for an SIR Epidemic Model Incorporating Vaccination
3 Optimal Control Using PMP
3.1 Optimality System
3.2 Numerical Simulation and Discussions
4 Optimal Control by a Trained ANN
4.1 Building and Training the ANN
4.2 Numerical Results and Discussions
5 Conclusion
References
Computer Vision with Deep Learning for Human Activity Recognition: Features Representation
1 Introduction
2 Review of the Literature
2.1 Convolutional Neural Network (CNN)
3 Results from Various Studied Approaches for Modeling Human Data
4 Conclusion and Outlook
References
Applications of Artificial Intelligence in Education
Streamlining Student Support: Enhancing Administrative Assistance and Interaction Through a Chatbot Solution
1 Introduction
2 Related Works
3 Limitation
4 Proposed Approach
5 Conclusions and Future Work
References
Towards a System that Predicts the Category of Educational and Vocational Guidance Questions, Utilizing Bidirectional Encoder Representations of Transformers (BERT)
1 Introduction
2 Review of Corresponding Research
2.1 The RIASEC Assessment
2.2 Deep Artificial Neural Networks
2.3 Pre-training Model
3 The Proposed Model
4 Exploring Experimental Findings and Results
4.1 The Dataset and Its Characteristics
4.2 The Steps of the Experiment
4.3 The Results
5 Conclusion
References
Artificial Intelligence in the Context of Digital Learning Environments (DLEs): Towards Adaptive Learning
1 Introduction
2 Review of Literature
2.1 Adaptive Learning: Personalized Education Through AI
2.2 Ethical Considerations in AI-Enhanced Learning
2.3 Student Perspectives on AI-Powered Adaptive Learning
3 Methodology
3.1 Data Collection
3.2 Questionnaire Design
3.3 Data Collection Procedure
3.4 Data Analysis
4 Discussion
5 Conclusion
References
A Methodology for Evaluating and Reporting the Integration of Artificial Intelligence for Sustainability in Higher Education: New Insights and Opportunities
1 Introduction
2 Assessment Tools for Sustainability in Higher Education
3 Methodology
3.1 Identify STARS Indicators
3.2 AI for ESD Areas
3.3 Mapping Process
3.4 Matrix Presentation
4 Result
5 Discussion
6 Conclusion
References
Blockchain Technology and Artificial Intelligence for Smart Education: State of Art, Challenges and Solutions
1 Introduction
2 Blockchain in Education
3 Literature Review
3.1 Methodology
3.2 Data Analysis
3.3 Discussion
4 The Proposed Solution
5 Conclusion
References
Artifical Intelligence in Nurse Education
1 Introduction
2 AI & Nurse Education
3 Roles of AI in High School and University
4 Examples of AI Tools Using in High School and University
5 AI & Curriculum of Nursing Education
5.1 Situation of Using AI in Curriculum
6 General Framework for Incorporating AI into a Nursing Curriculum
6.1 An Example of Curriculum
7 Skills for Nurses in the Education Process Related to AI
8 Preconditions for Efficient Using of AI in Nurse Education
9 Ensuring the Preconditions
10 Advantages and Disadvantages of Using AI in Nursing Education
11 Risks of Teaching About AI in Nursing Education
12 Overcoming the Risks
13 The Main Topics of Literature About AI in Nursing Education
13.1 Review of Literature
14 Sources of Information About AI in Nurse Education
15 Conclusion
References
Applications of Artificial Intelligence in Health
Artificial Intelligence Applications in Healthcare
1 Introduction
2 A Review of the Literature on AL in Healthcare
3 AI Applications in Healthcare
4 AL Challenges in Healthcare
5 Conclusions and Future Trends
6 Recommendations
References
The Use of Feature Engineering and Hyperparameter Tuning for Machine Learning Accuracy Optimization: A Case Study on Heart Disease Prediction
1 Introduction
2 Methodology
3 Process Detailing
4 Results, Discussion, and Evaluation
5 Conclusion and Recommendation
References
Plant Health—Detecting Leaf Diseases: A Systematic Review of the Literature
1 Introduction
2 Ease of Use
2.1 Search Strategy
2.2 Study Choice
3 Results and Analysis
4 Comparative Study
5 Critical Study
6 Proposed Approach
7 Conclusion and Future Work
References
Exploring the Intersection of Machine Learning and Causality in Advanced Diabetes Management: New Insight and Opportunities
1 Introduction
2 Association and Prediction
3 Causal Inference
3.1 Prediction Versus Causality
3.2 Association Versus Causality
3.3 Validity and Reliability of Real-World Evidence, and Causal Inference
4 Advancement of Machine Learning Methods in Diabetology
4.1 Biomarker Identification and Prediction of DM
4.2 Diabetic Complications
4.3 Drugs and Therapies
5 Conclusion
References
For the Nuclei Segmentation of Liver Cancer Histopathology Images, A Deep Learning Detection Approach is Used
1 Introduction
2 Related Work
3 Deep Learning Techniques for Classification and Segmentation of Histopathological Images
4 Description of the Dataset
4.1 Pre-Processing
4.2 Segmentation
4.3 Classification
5 Proposed Approach
6 Results
7 Conclusion
References
Applications of Artificial Intelligence in Recruitment and in Marketing
Metaverse for Job Search: Towards an AI-Based Virtual Recruiter in the Metaverse Era: A Systematic Literature Review
1 Introduction
2 Related Work
3 Critical Study
4 Proposed Approach
5 Limitation
6 Conclusion and Future Work
References
Metaverse for the Recruitment Process: Towards an Intelligent Virtual Recruiter
1 Introduction
2 Review of Literature
2.1 Meta-Recruitment Process
3 Methodology
3.1 Result
4 Discussion
5 Conclusion
References
Enhancing Immersive Virtual Shopping Experiences in the Retail Metaverse Through Visual Analytics, Cognitive Artificial Intelligence Techniques, Blockchain-Based Digital Assets, and Immersive Simulations: A Systematic Literature Review
1 Introduction
2 Methodology
3 The Metaverse: A New Frontier for Retails
4 Role of Visual Analytics in Comprehension of Customer Preferences
5 How AI Cognitively Enhances Retail Business in the Immersive Virtual Shopping
6 Virtual Reality and Augmented Reality Technologies Effects on the Retails Sector’s Transformation
7 Blochchain Necessary Tool for Secure Metaverse Transactions
8 Challenges of Use Blockchain
9 Challenges
10 Synthesis of the Major Results of Research
11 Limitation
12 Conclusion
References
Enhancing Customer Engagement in Loyalty Programs Through AI-Powered Market Basket Prediction Using Machine Learning Algorithms
1 Introduction
2 Related Work
3 Proposed Approach
4 Results and Discussion
4.1 Dataset
4.2 Length Feature Engineering: Identifying Key Factors for Enhancing Market Basket Prediction Accuracy
4.3 Feature Selection
5 Feature Scaling
6 Models Explored
6.1 Logistic Regression
6.2 Support Vector Machines (SVMs)
6.3 Decision Tree
6.4 Random Forest
6.5 K-nearest Neighbors Algorithm (k-NN)
7 Creating Predictive Models
7.1 Evaluating Model Performance
7.2 Evaluation of the Predictive Model
8 Discussion
9 Conclusion
References
Applications of Artificial Intelligence in Industry and in Agriculture
Application of Artificial Intelligence in the Oil and Gas Industry
1 Introduction
2 Background
2.1 Overview of the Oil and Gas Sector
2.2 Oil and Gas Sector and Its Complexity
2.3 Key Challenges
2.4 Addressing the Challenges of the Industry with AI Solutions
2.5 Overview of Artificial Intelligence
2.6 Artificial Intelligence Techniques
3 AI Applications in Upstream Operations
4 AI Applications in Midstream Operations
4.1 Pipeline Integrity Management Using AI Algorithms
5 AI Applications in Downstream Operations
5.1 Predictive Maintenance for Refining Processes
6 Safety and Environmental Applications of AI
6.1 AI-Powered Risk Assessment and Safety Monitoring
6.2 Environmental Impact Analysis and Mitigation Using AI
7 Challenges and Limitations of AI in the Oil and Gas Industry
7.1 Data Quality and Availability Challenges
7.2 Regulatory and Security Concerns
8 Future Trends and Outlook
8.1 Potential Impact of AI on the Oil and Gas Future
8.2 Opportunities for Further Research and Development
References
Duplicated Tasks Elimination for Cloud Data Center Using Modified Grey Wolf Optimization Algorithm for Energy Minimization
1 Introduction
2 Related Work
3 Grey Wolf Optimization Algorithm
3.1 Duplicated Tasks Assignment Elimination
3.2 Proposed Modified Grey Wolf Optimizer Algorithm
4 Evaluation Parameter
4.1 Experimental Setup
5 Result and Discussion
6 Conclusion
References
Enhancing Deep Learning-Based Semantic Segmentation Approaches for Smart Agriculture
1 Introduction
2 Problematic
3 Objectives
4 Technologies Used
5 Related Work
6 Results
7 Conclusion
References
Applications of Artificial Intelligence in Management, in Supply Chain, and in Finance
Role of Artificial Intelligence in Sustainable Finance
1 Introduction
2 Literature Review
2.1 Sustainable Finance
2.2 Artificial Intelligence
2.3 Sustainable Finance and Financial Performance
3 Research Method and Objectives
4 Result and Discussion
5 Findings and Suggestions
6 Implication of the Study
7 Conclusion
References
Optimizing Processes in Digital Supply Chain Management Through Artificial Intelligence: A Systematic Literature Review
1 Introduction
1.1 Rationale
2 Objectives
3 Method
3.1 Search Strategy
3.2 Study Selection
4 Results and Discussion
4.1 What’s the Role of Digitalization in Supply Chain Management?
4.2 What Are the Dimensions of Digital Technologies?
4.3 What Kinds of Limitations Exist in Research on Digital Technologies in Supply Chain Management?
5 Conclusion
References
Enhancing Hotel Services Through Sentiment Analysis
1 Introduction
2 Related Works
3 Research Methodology
3.1 Proposed Workflow
3.2 BERT
3.3 Comparison Between Traditional Machine Learning Techniques and BERT
4 Experimentation
4.1 Datasets Used
4.2 Performance Measure
4.3 Results
5 Conclusion
References