We present a hybrid BIST approach that extracts the most frequently occurring sequences from deterministic test patterns; these extracted sequences are stored on-chip. We use clus...
The standard, ad-hoc stopping criteria used in decision tree-based context clustering are known to be sub-optimal and require parameters to be tuned. This paper proposes a new app...
The process of learning models from raw data typically requires a substantial amount of user input during the model initialization phase. We present an assistive visualization sys...
Many clustering algorithms fail when dealing with high dimensional data. Principal component analysis (PCA) is a popular dimensionality reduction algorithm. However, it assumes a ...
The evolution of complex software systems is promoted by software engineering principles and techniques like separation of concerns, encapsulation, stepwise refinement, and reusab...