We present and apply a general-purpose, multistart algorithm for improving the performance of low-energy samplers used for solving optimization problems. The algorithm iteratively fixes the value of a large portion of the variables to values that have a high probability of being optimal. The resulting problems are smaller and less connected, and samplers tend to give better low-energy samples f...

Large-scale distributed systems used to run a long, predictable series of operations on a recurring basis (batchdriven systems) are a prime target for optimization to reduce resource usage or time consumption, since even a small improvement may yield large dividends over time. Machine learning techniques are a good way to approach this optimization problem since there are typically many variabl...

Pointer traversals pose significant overhead to the execution of object-oriented programs, since every access to an object’s state requires a pointer dereference. Eliminating redundant pointer traversals reduces both instructions executed as well as redundant memory accesses to relieve pressure on the memory subsystem. We describe an approach to elimination of redundant access expressions that ...

Background: Appropriate and timely response in urgent situations requires high knowledge, physical and mental preparedness. Since emergency medical technicians are the first professional respondents in the health system, selecting the right people among the candidates to study in this field is very important. Due to the fact that there was a no specific model in the country of Iran to propose t...

We describe a parallel model-checking algorithm for the fragment of the μ-calculus that allows one alternation of minimal and maximal fixed-point operators. This fragment is also known as Lμ. Since LTL and CTL ∗ can be encoded in this fragment, we obtain parallel model checking algorithms for practically important temporal logics. Our solution is based on a characterization of this problem in t...

Run-to-run optimization exploits the repetitive nature of batch processes to adapt the operating policy in the presence of uncertainty. For problems where terminal constraints play a dominant role in the optimization, the system can be operated close to the optimum simply by satisfying terminal constraints. The input is parameterized by using the knowledge of the shape of the optimal solution a...

In this paper, the performance of the Z-MAP algorithmis explored in the context of the turbo equalization of thefaster-than-Nyquist (FTN) signals. The complexity of the Z-MAP,in terms of the number of the surviving states at each time epoch,is studied. Finally, the performance of the Z-MAP is comparedto that of the backup M-BCJR for turbo equalizing the FTNsignals.