Analyzing large amounts of ordered data is a common task in research and industry. The usual ordering domain is time: Examples for time-ordered data are sensor data, communication network data, or financial data. Besides online monitoring, it is common to investigate patterns or special events in the data after capturing it. These analysis can traditionally be performed within Data Stream Manag...

We prove the correctness of a sliding window protocol with an arbitrary finite window size n and sequence numbers modulo 2n. We show that the sliding window protocol is branching bisimilar to a queue of capacity 2n. The proof is given entirely on the basis of an axiomatic theory, and was checked with the help of PVS.

In this paper we propose an online Wavelet Discrete Transform implementation scheme. Our proposal improves the execution time compared to the traditional sliding window method. Also, we modify the definition of the data window concept given in the original scheme. The experiments we performed show that the runtime cost of the proposed algorithm is better than that of the traditional sliding win...

In many signal processing applications, such as EEG analysis, the non-stationary signal is often required to be segmented into small epochs. This is accomplished by drawing the boundaries of signal at time instances where its statistical characteristics, such as amplitude and/or frequency, change. In the proposed method, the original signal is initially decomposed into signals with different fr...

Graph coloring is one of the most famous computational problems with applications in a wide range areas such as planning and scheduling, resource allocation, pattern matching. So far are mostly studied on static graphs, which often stand contrast to practice where data inherently dynamic. A temporal graph has an edge set that changes over time. We present natural extension classical problem. Gi...