META-ALIGNMENT WITH CRUMBLE AND PRUNE: PARTITIONING VERY LARGE ALIGNMENT PROBLEMS FOR PERFORMANCE AND PARALLELIZATION

Meta-Alignment with Crumble and Prune: Partitioning very large alignment problems for performance and parallelization

Abstract Background Continuing research into the global multiple sequence alignment problem has resulted in more sophisticated and principled alignment methods.Unfortunately these new algorithms often require large amounts of time and memory to run, making it nearly impossible to run these algorithms on large datasets.As a solution, we present two

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A Comparison Between Two Different Approaches for a Collaborative Mixed-Virtual Environment in Industrial Maintenance

Nowadays the market is becoming increasingly competitive, factories are required not only to enhance the product quality but also to reduce manufacturing and maintenance times.In an industrial context, modern factories are composed by many automated systems, such as industrial robots, which can perform different tasks.Although industrial robots are

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