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Assemblies were generated using the de novo assembler Velvet v1.2.10 [ 24], with optimal kmer choice for each read set refined through iterative calls to VelvetOptimiser v2.2.5 [ 48].
We will first discuss the theoretical underpinnings of this approach and then continue with an introduction to the CEGARTIX system [21] and the ArgSemSAT system [22], which both rely on iterative calls to SAT solvers for argumentation semantics of high complexity (i.e., being located on the second level of the polynomial hierarchy).
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The database of a case is completely loaded after the iterative call of IMAGMEAS for the 5 images previously acquired for that case.
It randomly reads 100 records from the data base loaded by the iterative call of IMAGMEAS, which is equivalent to the random selection of 100 fibroblast cells from the 5 original images available for the case.
In the process, the iterative shell calls a single-output model repetitively, comparing effluent concentrations from different filter setups to legislative thresholds.
Like ArgSemSAT [82], which relies on iterative SAT calls for enumerating preferred labelings, CEGARTIX can be seen as a sort of hybrid approach between direct and reduction-based methods, since only certain sub-tasks are delegated to a SAT solver.
Since PATS uses the compensation in [18], but the DC-SC method [19] has similar performance but less complexity, we also consider here an alternative iterative scheme called ES+DC-SC that combines the exhaustive search estimation of PATs called ES with the DC-SC compensation.
The derived expression enables the identification of an iterative algorithm, called IpDTFT-NR procedure, that ensures the maximum Noise Rejection on the IpDTFT frequency estimator.
The GREMLINS solver limits the amount of communication as it is based on a coarse grained iterative method called multisplitting method.
In this paper, we present an iterative framework, called WiZard to solve module selection problem under resource, latency, and power constraints.
We present an iterative algorithm, called the symmetric tensor eigen-rank-one iterative decomposition (STEROID), for decomposing a symmetric tensor into a real linear combination of symmetric rank-1 unit-norm outer factors using only eigendecompositions and least-squares fitting.
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