Agent-based simulation provides a methodology to investigate complex systems behavior, such as supply chains, while incorporating many empirical elements relative to both systems ...
In this paper, we present an abstract framework for online approximation of time-series data that yields a unified set of algorithms for several popular models: data streams, amnes...
We present a method for unsupervised discovery of abnormal occurrences of activities in multi-dimensional time series data. Unsupervised activity discovery approaches differ from ...
Time series analysis is a wide area of knowledge that studies processes in their evolution. The classical research in the area tends to find global laws underlying the behaviour o...
We explore the potential of information visualization techniques in enhancing existing methodologies for domain analysis and modeling. In this case study, we particularly focus on...