Search

As a kind of revolutionary technology, artificial intelligence marked an explosive transformation in many fields of study. Nowadays, much of the translation work used to be done by human has been undertaken by machines. The construction of corpus is a crucial step leading to successful machine translation. The paper aims to exploring the mode of corpus construction from the perspective of information mining, information retrieval and information processing. The retrieval system uses web crawlers to collect network information and automatic tagging technology to index the collected information, then applies corresponding language processing techniques to achieve correspondence between two languages and form an index database. In the age of artificial intelligence, machines can keep a track of many users’ searches, queries, so as to record, extract as well as to feed back on different translations to build a new corpus. In this way, machine translation is improving in its scope and accuracy in translation with the goal to take up the tedious work of human translation as well as to increase the speed and reduce the cost of it.

A Molecular dynamics simulation in a converging-diverging nozzle was performed to study molecular collisions and their influence to average flow velocity according to a variety of vacuum levels. The static pressures and the dynamic pressure exerted by the molecule collision on the selected walls were compared to figure out the intensity variances of the directional flows. With pressure differences constant between the entrance and the exit of the nozzle, The numerical experiment was performed for molecular velocities and directional flows. The result shows that the velocities are increased at the nozzle exit as the vacuum level gets higher in that area because of less molecular collisions