Intro
Preface
Contents
Computational Intelligence & Big Data
Construction of a Training Device in Pedagogical Engineering from the "My Scenari" Model
1 Theoretical and Conceptual Framework
1.1 Theoretical Frame
2 Results
3 Conclusion
References
Machine Learning-Based Intrusion Detection System: Review and Taxonomy
1 Introduction
2 General Concept of IDS
2.1 Intrusion Detection System (IDS)
2.2 Classification of Intrusion Detection System
3 Benchmark Datasets, Features Reduction, and Evaluation Metrics
3.1 Intrusion Detection Datasets

3.2 Feature Selection
3.3 Evaluation Metrics
4 The ML-Based NIDS
4.1 Supervised Learning Methods
5 Discussion and Conclusion
References
Retrospective Study and Evaluation of School Failure (Junior High School) in Scientific Subjects
1 Introduction
2 Context
3 The School Body in the Province of Ouezzane in Morocco
4 Theoretical Framework
4.1 School Failure
5 Methods
5.1 Traget Audience
5.2 Origin of the Data
5.3 Statistical Analysis
6 Results and Interpretation: Exploratory Approach "Comparative Analysis"

6.1 Learning Environment (Rural/urban) and Success Rate
6.2 The Effect of Learning Certain Science Subjects on Success Rates
6.3 Life and Earth Sciences
6.4 Physics Sciences
6.5 Mathematics
7 Recommendations and Proposals
8 Conclusion
References
The Use of "Mathematical Modeling" in Physics: Case of Representations and Teaching-Learning Practices
1 Introduction
2 Theoretical Framework
3 Research Methodology
4 Results and Discussions
4.1 Questionnaire 1 Addressed to Teachers
4.2 Questionnaire 2 (Addressed to Learners)
5 Conclusion
References

Towards Face-to-Face Smart Classroom that Adheres to Covid'19 Restrictions
1 Introduction
2 Related Works
3 The Proposed System
3.1 Dataset Description
3.2 Face Mask Detection Approach
3.3 Euclidean Distance
4 Experimental Results
4.1 Results of the Proposed Dataset
4.2 Results of Face Mask Detection Dataset
4.3 Comparison with Other Models
5 Conclusion
References
Supervised Machine Learning for Breast Cancer Risk Factors Analysis and Survival Prediction
1 Introduction
2 Artificial Intelligence in Epidemiology
3 Related Works
4 Methods

4.1 K-Fold Cross Validation Strategy
4.2 Logistic Regression Classification
4.3 Support Vector Machines (SVM) Classification
4.4 Decision Tree Classification
4.5 Random Forest Classification
4.6 Extremely Randomized Trees Classification
4.7 K-Nearest Neighbor Classification
4.8 Adaptive Boosting Classification
5 Results
5.1 Data Description
5.2 Performance of the Proposed Methods
6 Conclusion and Recommendation
References
Applying Process Mining in Recommender System: A Comparative Study
1 Introduction
2 Background and Foundation