We present a case study that aims at quantitative assessment of the impact of requirements changes, and quantitative estimation of costs of the development activities that must be ...
A Bayesian ensemble learning method is introduced for unsupervised extraction of dynamic processes from noisy data. The data are assumed to be generated by an unknown nonlinear ma...
Least-squares estimation has always been the main approach when applying prediction error methods (PEM) in the identification of linear dynamical systems. Regardless of the estim...
Service-based IT infrastructures serve many different business processes on a shared infrastructure in parallel. The automated request execution on the interconnected software com...
This paper proposes a fast and simple unsupervised word segmentation algorithm that utilizes the local predictability of adjacent character sequences, while searching for a leaste...