Very large time series are increasingly available from an ever wider range of IoT-enabled sensors deployed in different environments. Significant insights can be gained by mining temporal patterns these series. Unlike traditional pattern mining, (TPM) adds event intervals into extracted patterns, making them more expressive at the expense increased and space complexities. Existing TPM methods e...

background: this study attempted to investigate traffic accident fatalities during 2004-2009 and the effect of fuel rationing on traffic accident fatalities .   materials and methods: this was a cross-sectional study on available data of all traffic accident fatalities in fars province, iran, during 2004-2009. to identify and fit the best model, various instruments, including the autocorrelatio...

multiple sclerosis (ms) is one of the autoimmune diseases with an unknown cause. the aim of this study was to explore the link between air quality and ms relapses in patients who suffer from ms.this time-series study was conducted on patients registered at the iranian multiple sclerosis society in 2011-2012. they were randomly selected from patients lived in tehran in the last five years, and h...

Partial periodic patterns are an important class of regularities that exist in a time series. A key property of these patterns is that they can start, stop, and restart anywhere within a series. We classify partial periodic patterns into two types: (i) regular patterns − patterns exhibiting periodic behavior throughout a series with some exceptions and (ii) recurring patterns − patterns exhibit...