This contribution addresses polymorphic uncertainty quantification within structural analysis of reinforced concrete structures composed heterogeneous and reinforcement (e.g. steel bars or carbon fibres). The macroscopic material behaviour is strongly dependent on the mesoscopic heterogeneities, which are considered by multiscale modelling. characterized representative volume elements (RVE) tra...

Todays, in many modern applications, we search for frequent and repeating patterns in the analyzed data sets. In this search, we look for patterns that frequently appear in data set and mark them as frequent patterns to enable users to make decisions based on these discoveries. Most algorithms presented in the context of data stream mining and frequent pattern detection, work either on uncertai...

Due to advances in technology, high volumes of valuable data can be collected and transmitted at high velocity in various scientific and engineering applications. Consequently, efficient data mining algorithms are in demand for analyzing these data. For instance, frequent pattern mining discovers implicit, previously unknown, and potentially useful knowledge about relationships among frequently...

With advances in technology, massive amounts of valuable data can be collected and transmitted at high velocity in various scientific, biomedical or engineering applications. Hence, scalable data analytics tools are in demand for analyzing these data. For example, scalable tools for association analysis help reveal frequently occurring patterns and their relationships, which in turn lead to int...

Probabilistic range query is an important type of query in the area of uncertain data management. A probabilistic range query returns all the objects within a specific range from the query object with a probability no less than a given threshold. In this paper we assume that each uncertain object stored in the databases is associated with a multi-dimensional Gaussian distribution, which describ...