To test the implementation offline, while emulating a real-time environment, several pseudo data streams were created and pushed to the detector at regular intervals mirroring the real world case.
To increase the smoothness and the accuracy of the solution obtained offline using the implementation of DP known as level-set DP, an improved version is developed, making use of adaptive grids for discretization.
In general, two design measures may be implemented offline to enhance the overall diagnostic performance, i.e., installing sensors and/or stipulating test plans for online implementations.
As a consequence, both the offline design and the online implementation are distributed and scalable.
We also propose a quasi-static synthesis strategy that determines offline a database of alternative implementations.
By and large, these MLA experiments and implementations relied on static, offline analysis of previously captured traffic.
Note that all the steps for the partial group selection can be done offline once, and hence there is no implementation complexity associated with it.
Furthermore, when integrated with our effective forward implementation, the recognition of an offline character image takes only 9.7 ms on a CPU.
The procedure is simple and multi-sequences can be offline calculated and stored, thus, the real-time implementation of the inhibitor becomes trivial.
Another implementation could create "mesh networks" for things like offline chat or ad-hoc project groups for real-time collaboration.
