statistical process control (spc) charts play a major role in quality control systems, and their correct interpretation leads to discovering probable irregularities and errors of the production system. in this regard, various artificial neural networks have been developed to identify mainly singular patterns of spc charts, while having drawbacks in handling multiple concurrent patterns. in this...

This paper presents a novel data mining technique, known as Post Sequential Patterns Mining. The technique can be used to discover structural patterns that are composed of sequential patterns, branch patterns or iterative patterns. The concurrent branch pattern is one of the main forms of structural patterns and plays an important role in event-based data modelling. To discover concurrent branc...

We present and categorize a taxonomy of concurrent bug patterns. We then use the taxonomy to create new timing heuristics for ConTest. Initial industrial experience indicates that these heuristics improve the bug finding ability of ConTest. We also show how concurrent bug patterns can be derived from concurrent design patterns. Further research is required to complete the concurrent bug taxonom...

Neural networks because of their abilities are used to patterns recognition. In statistical process control charts, a common cause variation distort expected form of unnatural patterns and so detection of assignable causes efficiently and precisely in a real-time is difficult. Therefore it would be logical to propose models based neural networks for recognition and analysis of patterns in proce...