Preface to the USTC Alumni's Series
Preface
1 Adaptive Particle Filters
1.1 Bayesian Filtering for Dynamic State Estimation
1.1.1 State and Observation Models
1.1.2 Bayesian Filtering Method
1.2 Fundamentals of Particle Filters
1.2.1 Sequential Monte Carlo Method
1.2.2 Basic Particle Filtering Algorithms
1.3 Challenging Issues in Particle Filtering
1.3.1 Unknown or Varying State Model
1.3.2 Construction of Proposal Density
1.3.3 Determination of Sample Size
1.3.4 Curse of Dimensionality
1.4 Adaptive Particle Filtering Algorithms
1.4.1 Algorithms with Adaptive Sample Size.
1.4.2 Algorithms with Adaptive Proposal:Density
1.4.3 Other Related Algorithms
1.5 Summary
References
Brief Introduction of Authors
2 Feature Localization and Shape Indexing for Content Based Image Retrieval
2.1 Introduction
2.2 Locales for Feature Localization
2.3 Search by Object Model
2.4 Shape Indexing and Recognition
2.5 Experimental Results
2.5.1 Search Using Locale-based Models
2.5.2 Video Locales
2.5.3 Shape Indexing and Recognition
2.6 Conclusion
References
Brief Introduction of Authors
3 BlueGene/L Failure Analysis and Prediction Models
3.1 Introduction
3.2 BlueGene/L Architecture, RAS Event Logs, and Job Logs
3.2.1 BlueGene/L Architecture
3.2.2 RAS Event Logs
3.2.3 Job Logs
3.3 Impact of Failures on Job Executions
3.4 Failure Prediction Based on Failure Characteristics
3.4.1 Temporal Characteristics
3.4.2 Spatial Characteristics
3.5 Predicting Failures Using the Occurrence of Non-Fatal Events
3.6 Related Work
3.7 Concluding Remarks and Future Directions
References
Brief Introduction of Authors
4 A Neuro-Fuzzy Approach towards Adaptive Intrusion Tolerant Database Systems
4.1 Overview
4.2 ITDB architecture
4.3 The Need for Adaptivity
4.4 Intelligent Techniques Solutions in Adaptive ITDB
4.5 Intelligent Techniques Solutions in Adaptive ITDB
4.6 The Design of Reconfiguration Components
4.7 Performance Metrics for Adaptive ITDB
4.8 Adaptation Criteria
4.9 The Rule-Based Adaptive Controller
4.10 The Neuro-Fuzzy Adaptive Controller
4.11 The collection of training data
4.12 Evaluation Methodology
4.12.1 Transaction Simulation
4.12.2 Evaluation Criteria
4.13 Evaluation of NFAC and RBAC Performance
4.14 Conclusion
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