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题型:语法填空(语篇) 题类:常考题 难易度:困难

江西省南昌市第二中学2019-2020学年高一上学期英语第一次月考试卷

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    So why has English changed  time? Actually all languages change and develop  cultures meet and communicate with each other. At first the English spoken in England between about AD 450 and 1150 was very different from the English spoken today. It was based more on German  the English we speak at present. Then gradually between about 800 and 1150, English became  (little) like German because those  ruled English spoke first Danish and later French. These new comers  (rich) the English language and especially  (it) vocabulary. So by the 1600s Shakespeare was able to make use of a wider vocabulary than ever before. In 1620 some British  (settle) moved to America. Later in the 18th century some British people  (take) to Australia too. English began to be spoken in both countries. Today,  number of people learning English in the world is increasing rapidly.

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    China is leading the world in facial recognition algorithms(人脸识别算法). It is reported that its best algorithm can recognize l0 million people {#blank#}1{#/blank#} a single mistake in less than a second.

    The top five of the 39 facial recognition algorithms in the word come from China, according to a test, {#blank#}2{#/blank#} released the results for 2018 last Friday. YITU Technology, {#blank#}3{#/blank#} Shanghai-based company that claimed both the top and second spot on the list, said that its top algorithm is able {#blank#}4{#/blank#} (recognize)nearly every person in a sample base of 10 million. However, "it is very likely for a human brain to make {#blank#}5{#/blank#} (mistake) in recognizing the identities of 100 people," the company said. Algorithms from Beijing-based company Sense Time {#blank#}6{#/blank#} (win) the third and fourth spot, while the Shenzhen Institutes of Advanced Technology(SIAT)claimed {#blank#}7{#/blank#} (five) in the test. YITU said that high facial recognition accuracy(精确)means that users gain {#blank#}8{#/blank#} (good) experiences when {#blank#}9{#/blank#} (use) related products. For example, when a user uses facial ID for payment on a smartphone, it will not authorize the payment for someone else with a similar {#blank#}10{#/blank#} (appear)as the user, the company noted.

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