Chen Lanbin is China’s first ambassador to the United States, honest and upright, using evidences to safeguard the human rights of Chinese workers in the Americas, and actively negotiating the Denver anti-Chinese incident. As a subordinate of Chen Lanbin, Cai Xiyong chose to translate the US Federal Constitution, which was due to not only his personal interest but also the influence of Chen Lanbin as a patron. Based on Lefevere’s “patronage” theory, the the reasons why Cai Xiyong chose to translate the US Federal Constitution, why there existed linguistic deviations and deformations between Cai’s translation and the original text and why Cai’s translation did not catch people’s enough attention in modern China history, are examined from the three aspects of patronage: ideological, economic and status factors. On ideological factor, Both Chen Lanbin and Cai Xiyong adhered to the concept “Chinese learning as substance, western learning for application”; on economic factor, Cai Xiyong was appreciated by his leader and patron Chen Lanbin and got a salary from the Qing Dynasty government; on status factor, Cai Xiyong was recognized by his leader and patron Chen Lanbin and became an official through the Westernization Movement. Influenced by the patron Chen Lanbin, the purpose of Cai Xiyong translating the US federal Constitution is to handle the Denver anti-Chinese incident, and not to reform China’s political and legal system, transform the superstructure and overthrow the feudal rule of the Qing Dynasty government.
With the continuous expansion and deepening of international exchanges and cooperation, language differences have become the biggest obstacle to exchanges and cooperation. At present, English translation software is the translation between natural languages made by humans on the basis of computers. As an important technical means to break through language barriers, machine translation is a software that uses computers to process spoken or written language. This paper aims to study the innovative system of English translation software, using the Internet of Things and big data algorithms to analyze some loopholes and deficiencies in the innovative system, and provide some data research for the system update. This paper proposes to analyze the innovative system of translation software based on the big data of the Internet of Things (IoT). Among them, the big data of the Internet of Things chooses the dynamic frame time slot ALOHA algorithm and the lower limit estimation algorithm. Its application in system analysis is very innovative. The system consists of a translation engine and a machine dictionary, which solves the basic problem of insufficient translation database of current translations, and plays a role in helping the English translation software innovation system to improve the accuracy of translations. The experimental results of this paper show that the translation system’s translation software achieves 61.3% of the A-target fluent translations, and 22.7% of the B-targets can translate the original text. It can be seen that English translation software has important research significance.
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