Smart Japanese listening course design based on data intelligent analysis and FPGA

摘要

Japan's lack of English communication opportunities proves to be a challenge for the learner, as there is no consistent training in listening and speaking English and will not provide significant improvement as a foreign language. A Japanese faculty teacher will launch a mobile-assisted language learning shadow application to overcome these difficulties. Students can cultivate their ears during shadow training. It is officially accepted that technology can be useful in improving speaking and listening. It then considers the change in motivation, influence, oral communication in English, English proficiency of first-year college students, and most science and engineering significant activities. Referral services based on user activities on the Internet, such as data analysis, can benefit Internet service providers and users. Although these services use a lot of statistical data that can be obtained through content and online transactions, they also face the challenge of ensuring that service providers do not infringe on their services' privacy. However, the large amount of data received by a network imposes a high predictable cost of the new implementation. This article focuses on accelerating its use in web service data anonymization and enabling data anonymization in Field Programmable Gate Teams (FPGA). Anonymizer proposes RAM and uses real network traffic to evaluate how it completes the test network usage.