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The scenario where the state sequence is random (rather than arbitrary) is also considered.
The mathematical formulation is based on state sequence network (SSN) representation.
A tool called Belief Scheduler is proposed for state sequence recognition in the Transferable Belief Model (TBM) framework.
The construction implicitly includes a key agreement phase (by means of the random and i.i.d. state sequence) that is crucial for the aforementioned improvement.
This model subsumes all other instances of CSI availability as special cases, and calls for an efficient utilization of the state sequence both for reliability and security purposes.
The developed MILP scheduling models are based on state sequence network representation that has proven to inherently result in smaller problems in terms of binary variables.
In the first part of the validation studies, microwave heating was applied in an agar phantom using a fast spoiled gradient recalled echo in a steady state sequence.
The resulting FSM is then able to self-configure the combinatorial logic of this FSM required to perform the compulsory state sequence.
Purpose: To present a dual-pathway multi-echo steady state sequence and reconstruction algorithm to capture T2, T2∗ and field map information.
Probability values of the optimum state sequence are collected to construct the probabilistic model which is used to compute the corresponding control limit for the specified operating condition.
The 2D-FE models have been employed in nonlinear static "pushover" analysis of isolated floor diaphragms to determine diaphragm stiffness, strength, deformation capacity, and limit state sequence.
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