Lagrangian averaging plays an important role in the analysis of wave–mean-flow interactions and other multiscale fluid phenomena. The numerical computation means, e.g. from simulation data, is, however, challenging. Typical implementations require tracking a large number particles to construct time series, which are then averaged using low-pass filter. This has drawbacks that include memory dem...

In this paper we present a new clustering method based on k-means that has been implemented on a video surveillance system. Rekmeans does not require to specify in advance the number of clusters to search for and is more precise than k-means in clustering data coming from multiple Gaussian distributions with different co-variances, while maintaining real-time performance. Experiments on real an...

The Tabu Search (TS) metaheuristic has been proposed for K-Means clustering as an alternative to Lloyd’s algorithm, which for all its ease of implementation and fast runtime, has the major drawback of being trapped at local optima. While the TS approach can yield superior performance, it involves a high computational complexity. Moreover, the difficulty in parameter selection in the existing TS...