Sentence examples for series processed from inspiring English sources

This Italian sword-and-sandals series processed more beefcake than a drive-thru McDonald 'sin the 1960s, even if it rarely moulded its slabs of man-flesh into credible actors.

To remove the non-target signals, we model the OBP time series processed above at any given grid point as: Pleft( t right) = a + bt + ct^{2} + alpha_{1} ;{ sin }omega t + beta_{1} ;{ cos }omega t + alpha_{2} ;{ sin }2omega t + beta_{2} ;{ cos }2omega t; + ;hbox{''residual};Delta Pleft( t right)hbox.

However, sections in the series processed for BDA or HRP were also often analyzed for epifluorescence because the fluorescent labeling in these sections was similar to that in sections not processed for these tracers.

A key concept underlying time series processes is that of stationarity.

We are interested in modelling the time series process yt="σ xt)εt, where εt="φ0εt-1+vt.

Further investigations must show the extent to which this can be ensured later in the series process.

Within an extensive experiment series process-forces (i), abrasive tool-wear (ii), workpiece damages (iii) and delamination (iv) are evaluated depending on different tool geometries and fiber-orientations.

Then, for a stationary bivariate time series process (left{ {left( {X_{t},Y_{t} } right)} right}, t in {mathbb{Z}},text), we can represent formally that (left{ {X_{t } } right}) does not Granger causes (left{ {Y_{t} } right}) as left.

Given that acquisition performance is influenced by a set of other factors, we control for contextual and transactional factors as well as for the bidder and the acquisition series process.

These subjectively chosen distributions were combined with a moving average time series process for the error in the TFR or life expectancy increase.

Typically this involves two components: (i) Using time series methods to model the baseline background distribution (the time series process that is assumed to contain no outbreak signatures), (ii) Detecting outbreak signatures using filter-based time series methods.