Statistical time lags in ac discharges

Learning Over Long Time Lags

The advantage of recurrent neural networks (RNNs) in learning dependencies between time-series data has distinguished RNNs from other deep learning models. Recently, many advances are proposed in this emerging field. However, there is a lack of comprehensive review on memory models in RNNs in the literature. This paper provides a fundamental review on RNNs and long short term memory (LSTM) mode...

Minimizing makespan in flowshop with time lags

We consider the problem of minimizing the makespan in a flowshop involving maximal and minimal time lags, denoted by Fm|θ, θ|Cmax. Time lag constraints generalize the classical precedence constraints between operations: minimal (respectively maximal) time lags indeed specify that the time elapsed between two operations must be lower(respectively upper-) bounded. We assume that such constraints ...

Time Lags: A Feasibility Study

Advective Time Lags in Box Models

We consider a box model of the thermohaline circulation with mixed boundary conditions in which advective processes are incorporated via an explicit time delay mechanism. The pipes which connect the subtropical and subpolar boxes have a nite volume and do not interact with the atmosphere or with the rest of the ocean except for channeling uxes between the subtropical and subpolar regions. The c...

Current Distribution of Ac Surface Discharges and Associated Chemistry

It is shown that ac discharges propagating at an air / dielectric interface, though of planar structure, behave, till a critical voltage Vcrit, as corona discharges in an air gap, with similar propagation fields for the filamentary discharge components and similar glow components. This leads to consider the surface discharges as gas discharges propagating above the dielectric surface. Beyond Vc...