Although the parallel corpus has an irreplaceable role in machine translation, its scale and coverage is still beyond the actual needs. Non-parallel corpus resources on the web have an inestimable potential value in machine translation and other natural language processing tasks. This article proposes a semi-supervised transductive learning method for expanding the training corpus in statistica...

Large-scale parallel corpora are indispensable to train highly accurate machine translators. However, manually constructed large-scale parallel corpora are not freely available in many language pairs. In previous studies, training data have been expanded using a pseudoparallel corpus obtained using machine translation of the monolingual corpus in the target language. However, in lowresource lan...

this paper considers identical parallel machines scheduling problem with past-sequence-dependent setup times, deteriorating jobs and learning effects, in which the actual processing time of a job on each machine is given as a function of the processing times of the jobs already processed and its scheduled position on the corresponding machine. in addition, the setup time of a job on each machin...

This paper investigates the scheduling problem of dealing with disruption caused by machine breakdown under the environment of identical parallel machines. When a machine breakdown changes the scheduling environment, the original schedule cannot be executed according to the prescribed plan. The objective after disruption is to create a recovery schedule that minimizes the original objective fun...

Data parallel simulation involves simulating the behavior of a circuit over a number of test sequences simultaneously. Compared to other parallel simulation techniques, data parallel simulation requires less overhead for synchronization and communication, and it permits higher degrees of parallelism. We have implemented two data parallel versions of the switch-level simulator COSMOS. The rst ru...