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1. XAI-FUNGI: Dataset resulting from the user study on comprehensibility of explainable AI algorithms

2. User-centric evaluation of explainability of AI with and for humans: a comprehensive empirical study

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3. Artificial Intelligence Approaches for Predictive Maintenance in the Steel Industry: A Survey

4. Local Universal Explainer (LUX) -- a rule-based explainer with factual, counterfactual and visual explanations

5. Explainable Predictive Maintenance

6. Visual Patterns in an Interactive App for Analysis Based on Control Charts and SHAP Values

7. Improving Understandability of Explanations with a Usage of Expert Knowledge

8. Towards Explainable Deep Domain Adaptation

9. Explainable Anomaly Detection in Industrial Streams

11. Assessment of Explainable Anomaly Detection for Monitoring of Cold Rolling Process

12. Visual Explanations and Perturbation-Based Fidelity Metrics for Feature-Based Models

13. Understanding Survival Models Through Counterfactual Explanations

14. KnAC: an approach for enhancing cluster analysis with background knowledge and explanations

17. The BIRAFFE2 Experiment. Study in Bio-Reactions and Faces for Emotion-based Personalization for AI Systems

18. ML-Based Proactive Control of Industrial Processes

19. Towards Online Anomaly Detection in Steel Manufacturing Process

20. Feature Importances as a Tool for Root Cause Analysis in Time-Series Events

21. Performance of Explainable AI Methods in Asset Failure Prediction

22. Comparing Explanations from Glass-Box and Black-Box Machine-Learning Models

23. Introducing Uncertainty into Explainable AI Methods

24. Explanation-Driven Model Stacking

25. Augmenting Automatic Clustering with Expert Knowledge and Explanations

26. Towards Model-Agnostic Ensemble Explanations

30. Towards the Modeling of the Hot Rolling Industrial Process. Preliminary Results

31. Explaining Machine Learning Models of Emotion Using the BIRAFFE Dataset

32. Affective Context-Aware Systems: Architecture of a Dynamic Framework

38. Uncertain Decision Tree Classifier for Mobile Context-Aware Computing

39. Towards the Development of Sensor Platform for Processing Physiological Data from Wearable Sensors

40. On the Opportunities for Using Mobile Devices for Activity Monitoring and Understanding in Mining Applications

41. Causal Rules Detection in Streams of Unlabeled, Mixed Type Values with Finit Domains

42. Semantic Annotations for Mediation of Complex Rule Systems

43. Web-Based Editor for Structured Rule Bases

44. Framework for Benchmarking Rule-Based Inference Engines

49. Understanding Context with ContextViewer – Tool for Visualization and Initial Preprocessing of Mobile Sensors Data

50. Compact Representation of Conditional Probability for Rule-Based Mobile Context-Aware Systems