Intro
Preface
Organization
Contents - Part I
Contents - Part II
Case-Based Reasoning and Machine Comprehension
On the Improvement of the Reasoning Cycle in Case-Based Reasoning
1 Introduction
2 A More Domain Knowledge Independent Approach
2.1 Case Structure
2.2 Retrieving Similar Cases
2.3 An Optimization Approach for Adaptation
3 Experimental Evaluation
3.1 Case Study
3.2 Dataset Description
3.3 Testbed Setup
3.4 Empirical Evaluation
4 Conclusion
References

Exploring Incompleteness in Case-Based Reasoning: A Strategy for Overcoming Challenge
1 Introduction
2 Background
2.1 Case-Based Reasoning and Data Completeness
2.2 Change Point Analysis
3 The Completeness Challenge: A Problem Statement
3.1 Illustrative Scenario
3.2 Problem Formulation
4 Evaluating Data Incompleteness in CBR Systems
4.1 Segmentation of the Case Base
4.2 Identification of Incompleteness Situations
5 Experimental Results
6 Conclusion
References
Leveraging both Successes and Failures in Case-Based Reasoning for Optimal Solutions

1 Introduction
2 Illustrative Example and Preliminary Concepts
2.1 Key Concepts and Notations Related to the CBR Paradigm
2.2 Collision Avoidance Navigation
3 Adaptation Through Failed and Successful Cases
3.1 Problem Statement
3.2 Principle
3.3 Local Prediction of the Target Solution
4 Evaluation
4.1 Experimental Design
4.2 Baselines and Metrics
4.3 Results
5 Conclusion
References
Transfer Learning for Abnormal Behaviors Identification in Examination Room from Surveillance Videos: A Case Study in Vietnam*-1pc
1 Introduction
2 Related Work

3 Methods
3.1 Abnormal Behaviors in the Examination Hall and Data Collection
3.2 Deep Learning Architectures for Abnormal Behavior Detection
4 Experimental Results
4.1 Environmental Settings
4.2 Abnormal Behavior Detection Using YOLO V4
4.3 Abnormal Behavior Detection with SSD MobileNet V2
4.4 Discussion
5 Conclusion
References
A Novel Question-Context Interaction Method for Machine Reading Comprehension
1 Introduction
2 Related Work
3 Methodology
3.1 Sentence Embedding
3.2 S-QCI Block
3.3 Word Fusion:
3.4 Training Process
4 Experiment

4.1 Experimental Setup
4.2 Benchmark Dataset and Baseline Models
4.3 Main Results
4.4 Ablation Study
5 Conclusion
References
Granular Computing to Forecast Alzheimer's Disease Distinctive Individual Development
1 Introduction
2 Methods
2.1 Rough Set Implementation of GrC
3 Results
3.1 Statistics
3.2 Granular Computing for Reference of Group1 Group
3.3 Granular Computing for Reference of Group2 Patients
4 Discussion
References
Computer Vision
AdVLO: Region Selection via Attention-Driven for Visual LiDAR Odometry
1 Introduction
2 Related Works